WorldWideScience

Sample records for based multiscale analysis

  1. Image quality assessment based on multiscale geometric analysis.

    Science.gov (United States)

    Gao, Xinbo; Lu, Wen; Tao, Dacheng; Li, Xuelong

    2009-07-01

    Reduced-reference (RR) image quality assessment (IQA) has been recognized as an effective and efficient way to predict the visual quality of distorted images. The current standard is the wavelet-domain natural image statistics model (WNISM), which applies the Kullback-Leibler divergence between the marginal distributions of wavelet coefficients of the reference and distorted images to measure the image distortion. However, WNISM fails to consider the statistical correlations of wavelet coefficients in different subbands and the visual response characteristics of the mammalian cortical simple cells. In addition, wavelet transforms are optimal greedy approximations to extract singularity structures, so they fail to explicitly extract the image geometric information, e.g., lines and curves. Finally, wavelet coefficients are dense for smooth image edge contours. In this paper, to target the aforementioned problems in IQA, we develop a novel framework for IQA to mimic the human visual system (HVS) by incorporating the merits from multiscale geometric analysis (MGA), contrast sensitivity function (CSF), and the Weber's law of just noticeable difference (JND). In the proposed framework, MGA is utilized to decompose images and then extract features to mimic the multichannel structure of HVS. Additionally, MGA offers a series of transforms including wavelet, curvelet, bandelet, contourlet, wavelet-based contourlet transform (WBCT), and hybrid wavelets and directional filter banks (HWD), and different transforms capture different types of image geometric information. CSF is applied to weight coefficients obtained by MGA to simulate the appearance of images to observers by taking into account many of the nonlinearities inherent in HVS. JND is finally introduced to produce a noticeable variation in sensory experience. Thorough empirical studies are carried out upon the LIVE database against subjective mean opinion score (MOS) and demonstrate that 1) the proposed framework has

  2. Development of a Sampling-Based Global Sensitivity Analysis Workflow for Multiscale Computational Cancer Models

    Science.gov (United States)

    Wang, Zhihui; Deisboeck, Thomas S.; Cristini, Vittorio

    2014-01-01

    There are two challenges that researchers face when performing global sensitivity analysis (GSA) on multiscale in silico cancer models. The first is increased computational intensity, since a multiscale cancer model generally takes longer to run than does a scale-specific model. The second problem is the lack of a best GSA method that fits all types of models, which implies that multiple methods and their sequence need to be taken into account. In this article, we therefore propose a sampling-based GSA workflow consisting of three phases – pre-analysis, analysis, and post-analysis – by integrating Monte Carlo and resampling methods with the repeated use of analysis of variance (ANOVA); we then exemplify this workflow using a two-dimensional multiscale lung cancer model. By accounting for all parameter rankings produced by multiple GSA methods, a summarized ranking is created at the end of the workflow based on the weighted mean of the rankings for each input parameter. For the cancer model investigated here, this analysis reveals that ERK, a downstream molecule of the EGFR signaling pathway, has the most important impact on regulating both the tumor volume and expansion rate in the algorithm used. PMID:25257020

  3. Multiscale principal component analysis

    International Nuclear Information System (INIS)

    Akinduko, A A; Gorban, A N

    2014-01-01

    Principal component analysis (PCA) is an important tool in exploring data. The conventional approach to PCA leads to a solution which favours the structures with large variances. This is sensitive to outliers and could obfuscate interesting underlying structures. One of the equivalent definitions of PCA is that it seeks the subspaces that maximize the sum of squared pairwise distances between data projections. This definition opens up more flexibility in the analysis of principal components which is useful in enhancing PCA. In this paper we introduce scales into PCA by maximizing only the sum of pairwise distances between projections for pairs of datapoints with distances within a chosen interval of values [l,u]. The resulting principal component decompositions in Multiscale PCA depend on point (l,u) on the plane and for each point we define projectors onto principal components. Cluster analysis of these projectors reveals the structures in the data at various scales. Each structure is described by the eigenvectors at the medoid point of the cluster which represent the structure. We also use the distortion of projections as a criterion for choosing an appropriate scale especially for data with outliers. This method was tested on both artificial distribution of data and real data. For data with multiscale structures, the method was able to reveal the different structures of the data and also to reduce the effect of outliers in the principal component analysis

  4. Adjoint Based A Posteriori Analysis of Multiscale Mortar Discretizations with Multinumerics

    KAUST Repository

    Tavener, Simon; Wildey, Tim

    2013-01-01

    In this paper we derive a posteriori error estimates for linear functionals of the solution to an elliptic problem discretized using a multiscale nonoverlapping domain decomposition method. The error estimates are based on the solution

  5. Micromechanics-Based Structural Analysis (FEAMAC) and Multiscale Visualization within Abaqus/CAE Environment

    Science.gov (United States)

    Arnold, Steven M.; Bednarcyk, Brett A.; Hussain, Aquila; Katiyar, Vivek

    2010-01-01

    A unified framework is presented that enables coupled multiscale analysis of composite structures and associated graphical pre- and postprocessing within the Abaqus/CAE environment. The recently developed, free, Finite Element Analysis--Micromechanics Analysis Code (FEAMAC) software couples NASA's Micromechanics Analysis Code with Generalized Method of Cells (MAC/GMC) with Abaqus/Standard and Abaqus/Explicit to perform micromechanics based FEA such that the nonlinear composite material response at each integration point is modeled at each increment by MAC/GMC. The Graphical User Interfaces (FEAMAC-Pre and FEAMAC-Post), developed through collaboration between SIMULIA Erie and the NASA Glenn Research Center, enable users to employ a new FEAMAC module within Abaqus/CAE that provides access to the composite microscale. FEA IAC-Pre is used to define and store constituent material properties, set-up and store composite repeating unit cells, and assign composite materials as sections with all data being stored within the CAE database. Likewise FEAMAC-Post enables multiscale field quantity visualization (contour plots, X-Y plots), with point and click access to the microscale i.e., fiber and matrix fields).

  6. Multivariate refined composite multiscale entropy analysis

    International Nuclear Information System (INIS)

    Humeau-Heurtier, Anne

    2016-01-01

    Multiscale entropy (MSE) has become a prevailing method to quantify signals complexity. MSE relies on sample entropy. However, MSE may yield imprecise complexity estimation at large scales, because sample entropy does not give precise estimation of entropy when short signals are processed. A refined composite multiscale entropy (RCMSE) has therefore recently been proposed. Nevertheless, RCMSE is for univariate signals only. The simultaneous analysis of multi-channel (multivariate) data often over-performs studies based on univariate signals. We therefore introduce an extension of RCMSE to multivariate data. Applications of multivariate RCMSE to simulated processes reveal its better performances over the standard multivariate MSE. - Highlights: • Multiscale entropy quantifies data complexity but may be inaccurate at large scale. • A refined composite multiscale entropy (RCMSE) has therefore recently been proposed. • Nevertheless, RCMSE is adapted to univariate time series only. • We herein introduce an extension of RCMSE to multivariate data. • It shows better performances than the standard multivariate multiscale entropy.

  7. A REGION-BASED MULTI-SCALE APPROACH FOR OBJECT-BASED IMAGE ANALYSIS

    Directory of Open Access Journals (Sweden)

    T. Kavzoglu

    2016-06-01

    Full Text Available Within the last two decades, object-based image analysis (OBIA considering objects (i.e. groups of pixels instead of pixels has gained popularity and attracted increasing interest. The most important stage of the OBIA is image segmentation that groups spectrally similar adjacent pixels considering not only the spectral features but also spatial and textural features. Although there are several parameters (scale, shape, compactness and band weights to be set by the analyst, scale parameter stands out the most important parameter in segmentation process. Estimating optimal scale parameter is crucially important to increase the classification accuracy that depends on image resolution, image object size and characteristics of the study area. In this study, two scale-selection strategies were implemented in the image segmentation process using pan-sharped Qickbird-2 image. The first strategy estimates optimal scale parameters for the eight sub-regions. For this purpose, the local variance/rate of change (LV-RoC graphs produced by the ESP-2 tool were analysed to determine fine, moderate and coarse scales for each region. In the second strategy, the image was segmented using the three candidate scale values (fine, moderate, coarse determined from the LV-RoC graph calculated for whole image. The nearest neighbour classifier was applied in all segmentation experiments and equal number of pixels was randomly selected to calculate accuracy metrics (overall accuracy and kappa coefficient. Comparison of region-based and image-based segmentation was carried out on the classified images and found that region-based multi-scale OBIA produced significantly more accurate results than image-based single-scale OBIA. The difference in classification accuracy reached to 10% in terms of overall accuracy.

  8. Multiscale Signal Analysis and Modeling

    CERN Document Server

    Zayed, Ahmed

    2013-01-01

    Multiscale Signal Analysis and Modeling presents recent advances in multiscale analysis and modeling using wavelets and other systems. This book also presents applications in digital signal processing using sampling theory and techniques from various function spaces, filter design, feature extraction and classification, signal and image representation/transmission, coding, nonparametric statistical signal processing, and statistical learning theory. This book also: Discusses recently developed signal modeling techniques, such as the multiscale method for complex time series modeling, multiscale positive density estimations, Bayesian Shrinkage Strategies, and algorithms for data adaptive statistics Introduces new sampling algorithms for multidimensional signal processing Provides comprehensive coverage of wavelets with presentations on waveform design and modeling, wavelet analysis of ECG signals and wavelet filters Reviews features extraction and classification algorithms for multiscale signal and image proce...

  9. Differential Geometry Based Multiscale Models

    Science.gov (United States)

    Wei, Guo-Wei

    2010-01-01

    Large chemical and biological systems such as fuel cells, ion channels, molecular motors, and viruses are of great importance to the scientific community and public health. Typically, these complex systems in conjunction with their aquatic environment pose a fabulous challenge to theoretical description, simulation, and prediction. In this work, we propose a differential geometry based multiscale paradigm to model complex macromolecular systems, and to put macroscopic and microscopic descriptions on an equal footing. In our approach, the differential geometry theory of surfaces and geometric measure theory are employed as a natural means to couple the macroscopic continuum mechanical description of the aquatic environment with the microscopic discrete atom-istic description of the macromolecule. Multiscale free energy functionals, or multiscale action functionals are constructed as a unified framework to derive the governing equations for the dynamics of different scales and different descriptions. Two types of aqueous macromolecular complexes, ones that are near equilibrium and others that are far from equilibrium, are considered in our formulations. We show that generalized Navier–Stokes equations for the fluid dynamics, generalized Poisson equations or generalized Poisson–Boltzmann equations for electrostatic interactions, and Newton's equation for the molecular dynamics can be derived by the least action principle. These equations are coupled through the continuum-discrete interface whose dynamics is governed by potential driven geometric flows. Comparison is given to classical descriptions of the fluid and electrostatic interactions without geometric flow based micro-macro interfaces. The detailed balance of forces is emphasized in the present work. We further extend the proposed multiscale paradigm to micro-macro analysis of electrohydrodynamics, electrophoresis, fuel cells, and ion channels. We derive generalized Poisson–Nernst–Planck equations that

  10. Differential geometry based multiscale models.

    Science.gov (United States)

    Wei, Guo-Wei

    2010-08-01

    Large chemical and biological systems such as fuel cells, ion channels, molecular motors, and viruses are of great importance to the scientific community and public health. Typically, these complex systems in conjunction with their aquatic environment pose a fabulous challenge to theoretical description, simulation, and prediction. In this work, we propose a differential geometry based multiscale paradigm to model complex macromolecular systems, and to put macroscopic and microscopic descriptions on an equal footing. In our approach, the differential geometry theory of surfaces and geometric measure theory are employed as a natural means to couple the macroscopic continuum mechanical description of the aquatic environment with the microscopic discrete atomistic description of the macromolecule. Multiscale free energy functionals, or multiscale action functionals are constructed as a unified framework to derive the governing equations for the dynamics of different scales and different descriptions. Two types of aqueous macromolecular complexes, ones that are near equilibrium and others that are far from equilibrium, are considered in our formulations. We show that generalized Navier-Stokes equations for the fluid dynamics, generalized Poisson equations or generalized Poisson-Boltzmann equations for electrostatic interactions, and Newton's equation for the molecular dynamics can be derived by the least action principle. These equations are coupled through the continuum-discrete interface whose dynamics is governed by potential driven geometric flows. Comparison is given to classical descriptions of the fluid and electrostatic interactions without geometric flow based micro-macro interfaces. The detailed balance of forces is emphasized in the present work. We further extend the proposed multiscale paradigm to micro-macro analysis of electrohydrodynamics, electrophoresis, fuel cells, and ion channels. We derive generalized Poisson-Nernst-Planck equations that are

  11. Multiscale deep drawing analysis of dual-phase steels using grain cluster-based RGC scheme

    International Nuclear Information System (INIS)

    Tjahjanto, D D; Eisenlohr, P; Roters, F

    2015-01-01

    Multiscale modelling and simulation play an important role in sheet metal forming analysis, since the overall material responses at macroscopic engineering scales, e.g. formability and anisotropy, are strongly influenced by microstructural properties, such as grain size and crystal orientations (texture). In the present report, multiscale analysis on deep drawing of dual-phase steels is performed using an efficient grain cluster-based homogenization scheme.The homogenization scheme, called relaxed grain cluster (RGC), is based on a generalization of the grain cluster concept, where a (representative) volume element consists of p  ×  q  ×  r (hexahedral) grains. In this scheme, variation of the strain or deformation of individual grains is taken into account through the, so-called, interface relaxation, which is formulated within an energy minimization framework. An interfacial penalty term is introduced into the energy minimization framework in order to account for the effects of grain boundaries.The grain cluster-based homogenization scheme has been implemented and incorporated into the advanced material simulation platform DAMASK, which purposes to bridge the macroscale boundary value problems associated with deep drawing analysis to the micromechanical constitutive law, e.g. crystal plasticity model. Standard Lankford anisotropy tests are performed to validate the model parameters prior to the deep drawing analysis. Model predictions for the deep drawing simulations are analyzed and compared to the corresponding experimental data. The result shows that the predictions of the model are in a very good agreement with the experimental measurement. (paper)

  12. A discrimination technique for extensive air showers based on multiscale, lacunarity and neural network analysis

    International Nuclear Information System (INIS)

    Pagliaro, Antonio; D'Ali Staiti, G.; D'Anna, F.

    2011-01-01

    We present a new method for the identification of extensive air showers initiated by different primaries. The method uses the multiscale concept and is based on the analysis of multifractal behaviour and lacunarity of secondary particle distributions together with a properly designed and trained artificial neural network. In the present work the method is discussed and applied to a set of fully simulated vertical showers, in the experimental framework of ARGO-YBJ, to obtain hadron to gamma primary separation. We show that the presented approach gives very good results, leading, in the 1-10 TeV energy range, to a clear improvement of the discrimination power with respect to the existing figures for extended shower detectors.

  13. Is WTI crude oil market becoming weakly efficient over time? New evidence from multiscale analysis based on detrended fluctuation analysis

    International Nuclear Information System (INIS)

    Wang, Yudong; Liu, Li

    2010-01-01

    This paper extends the work in Tabak and Cajueiro (Are the crude oil markets becoming weakly efficient over time, Energy Economics 29 (2007) 28-36) and Alvarez-Ramirez et al. (Short-term predictability of crude oil markets: a detrended fluctuation analysis approach, Energy Economics 30 (2008) 2645-2656). In this paper, we test for the efficiency of WTI crude oil market through observing the dynamic of local Hurst exponents employing the method of rolling window based on multiscale detrended fluctuation analysis. Empirical results show that short-term, medium-term and long-term behaviors were generally turning into efficient behavior over time. However, in this way, the results also show that the market did not evolve along stable conditions for long times. Multiscale analysis is also implemented based on multifractal detrended fluctuation analysis. We found that the small fluctuations of WTI crude oil market were persistent; however, the large fluctuations had high instability, both in the short- and long-terms. Our discussion is also extended by incorporating arguments from the crude oil market structure for explaining the different correlation dynamics. (author)

  14. Wavelet-based multiscale window transform and energy and vorticity analysis

    Science.gov (United States)

    Liang, Xiang San

    A new methodology, Multiscale Energy and Vorticity Analysis (MS-EVA), is developed to investigate sub-mesoscale, meso-scale, and large-scale dynamical interactions in geophysical fluid flows which are intermittent in space and time. The development begins with the construction of a wavelet-based functional analysis tool, the multiscale window transform (MWT), which is local, orthonormal, self-similar, and windowed on scale. The MWT is first built over the real line then modified onto a finite domain. Properties are explored, the most important one being the property of marginalization which brings together a quadratic quantity in physical space with its phase space representation. Based on MWT the MS-EVA is developed. Energy and enstrophy equations for the large-, meso-, and sub-meso-scale windows are derived and their terms interpreted. The processes thus represented are classified into four categories: transport; transfer, conversion, and dissipation/diffusion. The separation of transport from transfer is made possible with the introduction of the concept of perfect transfer. By the property of marginalization, the classical energetic analysis proves to be a particular case of the MS-EVA. The MS-EVA developed is validated with classical instability problems. The validation is carried out through two steps. First, it is established that the barotropic and baroclinic instabilities are indicated by the spatial averages of certain transfer term interaction analyses. Then calculations of these indicators are made with an Eady model and a Kuo model. The results agree precisely with what is expected from their analytical solutions, and the energetics reproduced reveal a consistent and important aspect of the unknown dynamic structures of instability processes. As an application, the MS-EVA is used to investigate the Iceland-Faeroe frontal (IFF) variability. A MS-EVA-ready dataset is first generated, through a forecasting study with the Harvard Ocean Prediction System

  15. Landslide mapping with multi-scale object-based image analysis – a case study in the Baichi watershed, Taiwan

    Directory of Open Access Journals (Sweden)

    T. Lahousse

    2011-10-01

    Full Text Available We developed a multi-scale OBIA (object-based image analysis landslide detection technique to map shallow landslides in the Baichi watershed, Taiwan, after the 2004 Typhoon Aere event. Our semi-automated detection method selected multiple scales through landslide size statistics analysis for successive classification rounds. The detection performance achieved a modified success rate (MSR of 86.5% with the training dataset and 86% with the validation dataset. This performance level was due to the multi-scale aspect of our methodology, as the MSR for single scale classification was substantially lower, even after spectral difference segmentation, with a maximum of 74%. Our multi-scale technique was capable of detecting landslides of varying sizes, including very small landslides, up to 95 m2. The method presented certain limitations: the thresholds we established for classification were specific to the study area, to the landslide type in the study area, and to the spectral characteristics of the satellite image. Because updating site-specific and image-specific classification thresholds is easy with OBIA software, our multi-scale technique is expected to be useful for mapping shallow landslides at watershed level.

  16. Multiscale analysis and computation for flows in heterogeneous media

    Energy Technology Data Exchange (ETDEWEB)

    Efendiev, Yalchin [Texas A & M Univ., College Station, TX (United States); Hou, T. Y. [California Inst. of Technology (CalTech), Pasadena, CA (United States); Durlofsky, L. J. [Stanford Univ., CA (United States); Tchelepi, H. [Stanford Univ., CA (United States)

    2016-08-04

    Our work in this project is aimed at making fundamental advances in multiscale methods for flow and transport in highly heterogeneous porous media. The main thrust of this research is to develop a systematic multiscale analysis and efficient coarse-scale models that can capture global effects and extend existing multiscale approaches to problems with additional physics and uncertainties. A key emphasis is on problems without an apparent scale separation. Multiscale solution methods are currently under active investigation for the simulation of subsurface flow in heterogeneous formations. These procedures capture the effects of fine-scale permeability variations through the calculation of specialized coarse-scale basis functions. Most of the multiscale techniques presented to date employ localization approximations in the calculation of these basis functions. For some highly correlated (e.g., channelized) formations, however, global effects are important and these may need to be incorporated into the multiscale basis functions. Other challenging issues facing multiscale simulations are the extension of existing multiscale techniques to problems with additional physics, such as compressibility, capillary effects, etc. In our project, we explore the improvement of multiscale methods through the incorporation of additional (single-phase flow) information and the development of a general multiscale framework for flows in the presence of uncertainties, compressible flow and heterogeneous transport, and geomechanics. We have considered (1) adaptive local-global multiscale methods, (2) multiscale methods for the transport equation, (3) operator-based multiscale methods and solvers, (4) multiscale methods in the presence of uncertainties and applications, (5) multiscale finite element methods for high contrast porous media and their generalizations, and (6) multiscale methods for geomechanics. Below, we present a brief overview of each of these contributions.

  17. Multiscale multifractal multiproperty analysis of financial time series based on Rényi entropy

    Science.gov (United States)

    Yujun, Yang; Jianping, Li; Yimei, Yang

    This paper introduces a multiscale multifractal multiproperty analysis based on Rényi entropy (3MPAR) method to analyze short-range and long-range characteristics of financial time series, and then applies this method to the five time series of five properties in four stock indices. Combining the two analysis techniques of Rényi entropy and multifractal detrended fluctuation analysis (MFDFA), the 3MPAR method focuses on the curves of Rényi entropy and generalized Hurst exponent of five properties of four stock time series, which allows us to study more universal and subtle fluctuation characteristics of financial time series. By analyzing the curves of the Rényi entropy and the profiles of the logarithm distribution of MFDFA of five properties of four stock indices, the 3MPAR method shows some fluctuation characteristics of the financial time series and the stock markets. Then, it also shows a richer information of the financial time series by comparing the profile of five properties of four stock indices. In this paper, we not only focus on the multifractality of time series but also the fluctuation characteristics of the financial time series and subtle differences in the time series of different properties. We find that financial time series is far more complex than reported in some research works using one property of time series.

  18. VELOCITY FIELD COMPUTATION IN VIBRATED GRANULAR MEDIA USING AN OPTICAL FLOW BASED MULTISCALE IMAGE ANALYSIS METHOD

    Directory of Open Access Journals (Sweden)

    Johan Debayle

    2011-05-01

    Full Text Available An image analysis method has been developed in order to compute the velocity field of a granular medium (sand grains, mean diameter 600 μm submitted to different kinds of mechanical stresses. The differential method based on optical flow conservation consists in describing a dense motion field with vectors associated to each pixel. A multiscale, coarse-to-fine, analytical approach through tailor sized windows yields the best compromise between accuracy and robustness of the results, while enabling an acceptable computation time. The corresponding algorithmis presented and its validation discussed through different tests. The results of the validation tests of the proposed approach show that the method is satisfactory when attributing specific values to parameters in association with the size of the image analysis window. An application in the case of vibrated sand has been studied. An instrumented laboratory device provides sinusoidal vibrations and enables external optical observations of sand motion in 3D transparent boxes. At 50 Hz, by increasing the relative acceleration G, the onset and development of two convective rolls can be observed. An ultra fast camera records the grain avalanches, and several pairs of images are analysed by the proposed method. The vertical velocity profiles are deduced and allow to precisely quantify the dimensions of the fluidized region as a function of G.

  19. Refined multiscale fuzzy entropy based on standard deviation for biomedical signal analysis.

    Science.gov (United States)

    Azami, Hamed; Fernández, Alberto; Escudero, Javier

    2017-11-01

    Multiscale entropy (MSE) has been a prevalent algorithm to quantify the complexity of biomedical time series. Recent developments in the field have tried to alleviate the problem of undefined MSE values for short signals. Moreover, there has been a recent interest in using other statistical moments than the mean, i.e., variance, in the coarse-graining step of the MSE. Building on these trends, here we introduce the so-called refined composite multiscale fuzzy entropy based on the standard deviation (RCMFE σ ) and mean (RCMFE μ ) to quantify the dynamical properties of spread and mean, respectively, over multiple time scales. We demonstrate the dependency of the RCMFE σ and RCMFE μ , in comparison with other multiscale approaches, on several straightforward signal processing concepts using a set of synthetic signals. The results evidenced that the RCMFE σ and RCMFE μ values are more stable and reliable than the classical multiscale entropy ones. We also inspect the ability of using the standard deviation as well as the mean in the coarse-graining process using magnetoencephalograms in Alzheimer's disease and publicly available electroencephalograms recorded from focal and non-focal areas in epilepsy. Our results indicated that when the RCMFE μ cannot distinguish different types of dynamics of a particular time series at some scale factors, the RCMFE σ may do so, and vice versa. The results showed that RCMFE σ -based features lead to higher classification accuracies in comparison with the RCMFE μ -based ones. We also made freely available all the Matlab codes used in this study at http://dx.doi.org/10.7488/ds/1477 .

  20. Wavelet-based multiscale analysis of minimum toe clearance variability in the young and elderly during walking.

    Science.gov (United States)

    Khandoker, Ahsan H; Karmakar, Chandan K; Begg, Rezaul K; Palaniswami, Marimuthu

    2007-01-01

    As humans age or are influenced by pathology of the neuromuscular system, gait patterns are known to adjust, accommodating for reduced function in the balance control system. The aim of this study was to investigate the effectiveness of a wavelet based multiscale analysis of a gait variable [minimum toe clearance (MTC)] in deriving indexes for understanding age-related declines in gait performance and screening of balance impairments in the elderly. MTC during walking on a treadmill for 30 healthy young, 27 healthy elderly and 10 falls risk elderly subjects with a history of tripping falls were analyzed. The MTC signal from each subject was decomposed to eight detailed signals at different wavelet scales by using the discrete wavelet transform. The variances of detailed signals at scales 8 to 1 were calculated. The multiscale exponent (beta) was then estimated from the slope of the variance progression at successive scales. The variance at scale 5 was significantly (ppathological conditions. Early detection of gait pattern changes due to ageing and balance impairments using wavelet-based multiscale analysis might provide the opportunity to initiate preemptive measures to be undertaken to avoid injurious falls.

  1. Multiscale virtual particle based elastic network model (MVP-ENM) for normal mode analysis of large-sized biomolecules.

    Science.gov (United States)

    Xia, Kelin

    2017-12-20

    In this paper, a multiscale virtual particle based elastic network model (MVP-ENM) is proposed for the normal mode analysis of large-sized biomolecules. The multiscale virtual particle (MVP) model is proposed for the discretization of biomolecular density data. With this model, large-sized biomolecular structures can be coarse-grained into virtual particles such that a balance between model accuracy and computational cost can be achieved. An elastic network is constructed by assuming "connections" between virtual particles. The connection is described by a special harmonic potential function, which considers the influence from both the mass distributions and distance relations of the virtual particles. Two independent models, i.e., the multiscale virtual particle based Gaussian network model (MVP-GNM) and the multiscale virtual particle based anisotropic network model (MVP-ANM), are proposed. It has been found that in the Debye-Waller factor (B-factor) prediction, the results from our MVP-GNM with a high resolution are as good as the ones from GNM. Even with low resolutions, our MVP-GNM can still capture the global behavior of the B-factor very well with mismatches predominantly from the regions with large B-factor values. Further, it has been demonstrated that the low-frequency eigenmodes from our MVP-ANM are highly consistent with the ones from ANM even with very low resolutions and a coarse grid. Finally, the great advantage of MVP-ANM model for large-sized biomolecules has been demonstrated by using two poliovirus virus structures. The paper ends with a conclusion.

  2. Feature and Contrast Enhancement of Mammographic Image Based on Multiscale Analysis and Morphology

    Directory of Open Access Journals (Sweden)

    Shibin Wu

    2013-01-01

    Full Text Available A new algorithm for feature and contrast enhancement of mammographic images is proposed in this paper. The approach bases on multiscale transform and mathematical morphology. First of all, the Laplacian Gaussian pyramid operator is applied to transform the mammography into different scale subband images. In addition, the detail or high frequency subimages are equalized by contrast limited adaptive histogram equalization (CLAHE and low-pass subimages are processed by mathematical morphology. Finally, the enhanced image of feature and contrast is reconstructed from the Laplacian Gaussian pyramid coefficients modified at one or more levels by contrast limited adaptive histogram equalization and mathematical morphology, respectively. The enhanced image is processed by global nonlinear operator. The experimental results show that the presented algorithm is effective for feature and contrast enhancement of mammogram. The performance evaluation of the proposed algorithm is measured by contrast evaluation criterion for image, signal-noise-ratio (SNR, and contrast improvement index (CII.

  3. Adjoint Based A Posteriori Analysis of Multiscale Mortar Discretizations with Multinumerics

    KAUST Repository

    Tavener, Simon

    2013-01-01

    In this paper we derive a posteriori error estimates for linear functionals of the solution to an elliptic problem discretized using a multiscale nonoverlapping domain decomposition method. The error estimates are based on the solution of an appropriately defined adjoint problem. We present a general framework that allows us to consider both primal and mixed formulations of the forward and adjoint problems within each subdomain. The primal subdomains are discretized using either an interior penalty discontinuous Galerkin method or a continuous Galerkin method with weakly imposed Dirichlet conditions. The mixed subdomains are discretized using Raviart- Thomas mixed finite elements. The a posteriori error estimate also accounts for the errors due to adjoint-inconsistent subdomain discretizations. The coupling between the subdomain discretizations is achieved via a mortar space. We show that the numerical discretization error can be broken down into subdomain and mortar components which may be used to drive adaptive refinement.Copyright © by SIAM.

  4. A novel fruit shape classification method based on multi-scale analysis

    Science.gov (United States)

    Gui, Jiangsheng; Ying, Yibin; Rao, Xiuqin

    2005-11-01

    Shape is one of the major concerns and which is still a difficult problem in automated inspection and sorting of fruits. In this research, we proposed the multi-scale energy distribution (MSED) for object shape description, the relationship between objects shape and its boundary energy distribution at multi-scale was explored for shape extraction. MSED offers not only the mainly energy which represent primary shape information at the lower scales, but also subordinate energy which represent local shape information at higher differential scales. Thus, it provides a natural tool for multi resolution representation and can be used as a feature for shape classification. We addressed the three main processing steps in the MSED-based shape classification. They are namely, 1) image preprocessing and citrus shape extraction, 2) shape resample and shape feature normalization, 3) energy decomposition by wavelet and classification by BP neural network. Hereinto, shape resample is resample 256 boundary pixel from a curve which is approximated original boundary by using cubic spline in order to get uniform raw data. A probability function was defined and an effective method to select a start point was given through maximal expectation, which overcame the inconvenience of traditional methods in order to have a property of rotation invariants. The experiment result is relatively well normal citrus and serious abnormality, with a classification rate superior to 91.2%. The global correct classification rate is 89.77%, and our method is more effective than traditional method. The global result can meet the request of fruit grading.

  5. Multivariate Multiscale Analysis

    Science.gov (United States)

    1990-11-08

    The conditions on k in the second half of the statement of the proposition can be somewhat relaxed. In the cases n = 2 and n = 3 the details are given...of Mathematical Func- lions, Dover, New York, N.Y., 1965. [2] Bray and D. C. Solmon, The horocycle transform and harmonic analysis on the Poincare disk...H. Izen, Inversion of the k- plane transform by orthogonal function series expansions, Inverse Problems, 5 (1989), 181-202. [20] J. V. Leahy, K. T

  6. Analysis of multi-scale chaotic characteristics of wind power based on Hilbert–Huang transform and Hurst analysis

    International Nuclear Information System (INIS)

    Liang, Zhengtang; Liang, Jun; Zhang, Li; Wang, Chengfu; Yun, Zhihao; Zhang, Xu

    2015-01-01

    Highlights: • A scale division method of wind power based on HHT and Hurst analysis is proposed. • The time–frequency components of wind power show different fractal structures. • These components are superposed and reconstructed into three scale subsequences. • Each subsequence has a chaotic characteristic and shows its own properties. • The EMD-LSSVM + ELM method improves the short-term wind power forecasting accuracy. - Abstract: The causes of uncertainty in wind farm power generation are not yet fully understood. A method for the scale division of wind power based on the Hilbert–Huang transform (HHT) and Hurst analysis is proposed in this paper, which allows the various multi-scale chaotic characteristics of wind power to be investigated to reveal further information about the dynamic behavior of wind power. First, the time–frequency characteristics of wind power are analyzed using the HHT, and then Hurst analysis is applied to analyze the stochastic/persistent characteristics of the different time–frequency components. Second, based on their fractal structures, the components are superposed and reconstructed into three series, which are defined as the Micro-, Meso- and Macro-scale subsequences. Finally, indices related to the statistical and behavioral characteristics of the subsequences are calculated and used to analyze their nonlinear dynamic behavior. The data collected from a wind farm of Hebei Province, China, are selected for case studies. The simulation results reveal that (1) although the time–frequency components can be decomposed, the different fractal structures of the signal are also derived from the original series; (2) the three scale subsequences all present chaotic characteristics and each of them exhibits its own unique properties. The Micro-scale subsequence shows strong randomness and contributes the least to the overall fluctuations; the Macro-scale subsequence is the steadiest and exhibits the most significant tendency

  7. MRI-Based Multiscale Model for Electromagnetic Analysis in the Human Head with Implanted DBS

    Directory of Open Access Journals (Sweden)

    Maria Ida Iacono

    2013-01-01

    Full Text Available Deep brain stimulation (DBS is an established procedure for the treatment of movement and affective disorders. Patients with DBS may benefit from magnetic resonance imaging (MRI to evaluate injuries or comorbidities. However, the MRI radio-frequency (RF energy may cause excessive tissue heating particularly near the electrode. This paper studies how the accuracy of numerical modeling of the RF field inside a DBS patient varies with spatial resolution and corresponding anatomical detail of the volume surrounding the electrodes. A multiscale model (MS was created by an atlas-based segmentation using a 1 mm3 head model (mRes refined in the basal ganglia by a 200 μm2 ex-vivo dataset. Four DBS electrodes targeting the left globus pallidus internus were modeled. Electromagnetic simulations at 128 MHz showed that the peak of the electric field of the MS doubled (18.7 kV/m versus 9.33 kV/m and shifted 6.4 mm compared to the mRes model. Additionally, the MS had a sixfold increase over the mRes model in peak-specific absorption rate (SAR of 43.9 kW/kg versus 7 kW/kg. The results suggest that submillimetric resolution and improved anatomical detail in the model may increase the accuracy of computed electric field and local SAR around the tip of the implant.

  8. Analysis of financial time series using multiscale entropy based on skewness and kurtosis

    Science.gov (United States)

    Xu, Meng; Shang, Pengjian

    2018-01-01

    There is a great interest in studying dynamic characteristics of the financial time series of the daily stock closing price in different regions. Multi-scale entropy (MSE) is effective, mainly in quantifying the complexity of time series on different time scales. This paper applies a new method for financial stability from the perspective of MSE based on skewness and kurtosis. To better understand the superior coarse-graining method for the different kinds of stock indexes, we take into account the developmental characteristics of the three continents of Asia, North America and European stock markets. We study the volatility of different financial time series in addition to analyze the similarities and differences of coarsening time series from the perspective of skewness and kurtosis. A kind of corresponding relationship between the entropy value of stock sequences and the degree of stability of financial markets, were observed. The three stocks which have particular characteristics in the eight piece of stock sequences were discussed, finding the fact that it matches the result of applying the MSE method to showing results on a graph. A comparative study is conducted to simulate over synthetic and real world data. Results show that the modified method is more effective to the change of dynamics and has more valuable information. The result is obtained at the same time, finding the results of skewness and kurtosis discrimination is obvious, but also more stable.

  9. Multiscale Analysis of Time Irreversibility Based on Phase-Space Reconstruction and Horizontal Visibility Graph Approach

    Science.gov (United States)

    Zhang, Yongping; Shang, Pengjian; Xiong, Hui; Xia, Jianan

    Time irreversibility is an important property of nonequilibrium dynamic systems. A visibility graph approach was recently proposed, and this approach is generally effective to measure time irreversibility of time series. However, its result may be unreliable when dealing with high-dimensional systems. In this work, we consider the joint concept of time irreversibility and adopt the phase-space reconstruction technique to improve this visibility graph approach. Compared with the previous approach, the improved approach gives a more accurate estimate for the irreversibility of time series, and is more effective to distinguish irreversible and reversible stochastic processes. We also use this approach to extract the multiscale irreversibility to account for the multiple inherent dynamics of time series. Finally, we apply the approach to detect the multiscale irreversibility of financial time series, and succeed to distinguish the time of financial crisis and the plateau. In addition, Asian stock indexes away from other indexes are clearly visible in higher time scales. Simulations and real data support the effectiveness of the improved approach when detecting time irreversibility.

  10. Mammographic feature enhancement by multiscale analysis

    International Nuclear Information System (INIS)

    Laine, A.F.; Schuler, S.; Fan, J.; Huda, W.

    1994-01-01

    This paper introduces a novel approach for accomplishing mammographic feature analysis by overcomplete multiresolution representations. The authors show that efficient representations may be identified within a continuum of scale-space and used to enhance features of importance to mammography. Methods of contrast enhancement are described based on three overcomplete multiscale representations: (1) the dyadic wavelet transform (separable), (2) the var-phi-transform (nonseparable, nonorthogonal), and (3) the hexagonal wavelet transform (nonseparable). Multiscale edges identified within distinct levels of transform space provide local support for image enhancement. Mammograms are reconstructed from wavelet coefficients modified at one or more levels by local and global nonlinear operators. In each case, edges and gain parameters are identified adaptively by a measure of energy within each level of scale-space. The authors show quantitatively that transform coefficients, modified by adaptive nonlinear operators, can make more obvious unseen or barely seen features of mammography without requiring additional radiation. The results are compared with traditional image enhancement techniques by measuring the local contrast of known mammographic features. The authors demonstrate that features extracted from multiresolution representations can provide an adaptive mechanism for accomplishing local contrast enhancement. By improving the visualization of breast pathology, they can improve chances of early detection while requiring less time to evaluate mammograms for most patients

  11. Multivariate Generalized Multiscale Entropy Analysis

    Directory of Open Access Journals (Sweden)

    Anne Humeau-Heurtier

    2016-11-01

    Full Text Available Multiscale entropy (MSE was introduced in the 2000s to quantify systems’ complexity. MSE relies on (i a coarse-graining procedure to derive a set of time series representing the system dynamics on different time scales; (ii the computation of the sample entropy for each coarse-grained time series. A refined composite MSE (rcMSE—based on the same steps as MSE—also exists. Compared to MSE, rcMSE increases the accuracy of entropy estimation and reduces the probability of inducing undefined entropy for short time series. The multivariate versions of MSE (MMSE and rcMSE (MrcMSE have also been introduced. In the coarse-graining step used in MSE, rcMSE, MMSE, and MrcMSE, the mean value is used to derive representations of the original data at different resolutions. A generalization of MSE was recently published, using the computation of different moments in the coarse-graining procedure. However, so far, this generalization only exists for univariate signals. We therefore herein propose an extension of this generalized MSE to multivariate data. The multivariate generalized algorithms of MMSE and MrcMSE presented herein (MGMSE and MGrcMSE, respectively are first analyzed through the processing of synthetic signals. We reveal that MGrcMSE shows better performance than MGMSE for short multivariate data. We then study the performance of MGrcMSE on two sets of short multivariate electroencephalograms (EEG available in the public domain. We report that MGrcMSE may show better performance than MrcMSE in distinguishing different types of multivariate EEG data. MGrcMSE could therefore supplement MMSE or MrcMSE in the processing of multivariate datasets.

  12. Numerical Analysis of Multiscale Computations

    CERN Document Server

    Engquist, Björn; Tsai, Yen-Hsi R

    2012-01-01

    This book is a snapshot of current research in multiscale modeling, computations and applications. It covers fundamental mathematical theory, numerical algorithms as well as practical computational advice for analysing single and multiphysics models containing a variety of scales in time and space. Complex fluids, porous media flow and oscillatory dynamical systems are treated in some extra depth, as well as tools like analytical and numerical homogenization, and fast multipole method.

  13. Homogenization-based interval analysis for structural-acoustic problem involving periodical composites and multi-scale uncertain-but-bounded parameters.

    Science.gov (United States)

    Chen, Ning; Yu, Dejie; Xia, Baizhan; Liu, Jian; Ma, Zhengdong

    2017-04-01

    This paper presents a homogenization-based interval analysis method for the prediction of coupled structural-acoustic systems involving periodical composites and multi-scale uncertain-but-bounded parameters. In the structural-acoustic system, the macro plate structure is assumed to be composed of a periodically uniform microstructure. The equivalent macro material properties of the microstructure are computed using the homogenization method. By integrating the first-order Taylor expansion interval analysis method with the homogenization-based finite element method, a homogenization-based interval finite element method (HIFEM) is developed to solve a periodical composite structural-acoustic system with multi-scale uncertain-but-bounded parameters. The corresponding formulations of the HIFEM are deduced. A subinterval technique is also introduced into the HIFEM for higher accuracy. Numerical examples of a hexahedral box and an automobile passenger compartment are given to demonstrate the efficiency of the presented method for a periodical composite structural-acoustic system with multi-scale uncertain-but-bounded parameters.

  14. Fusion of multiscale wavelet-based fractal analysis on retina image for stroke prediction.

    Science.gov (United States)

    Che Azemin, M Z; Kumar, Dinesh K; Wong, T Y; Wang, J J; Kawasaki, R; Mitchell, P; Arjunan, Sridhar P

    2010-01-01

    In this paper, we present a novel method of analyzing retinal vasculature using Fourier Fractal Dimension to extract the complexity of the retinal vasculature enhanced at different wavelet scales. Logistic regression was used as a fusion method to model the classifier for 5-year stroke prediction. The efficacy of this technique has been tested using standard pattern recognition performance evaluation, Receivers Operating Characteristics (ROC) analysis and medical prediction statistics, odds ratio. Stroke prediction model was developed using the proposed system.

  15. Analysis of effective diffusivity of cement based materials by multi-scale modelling

    International Nuclear Information System (INIS)

    Dridi, Wissem

    2013-01-01

    This paper presents a simplified composite model, which considers the contribution of each phase participating to the transport within OPC pastes and concretes. At the micrometer scale, the phases considered hereafter are capillary porosity (macro-porosity) and the Low Density and the High Density C-S-H both containing gel pores (nano-porosity). Predicted values of tritiated water (HTO) diffusivity in OPC pastes with various (w/c) ratios are confronted to experimental results with a good agreement. The approach is then extended to mortars and concretes scale where microstructure is described by a three phase composite sphere assemblage. Here, elementary phase distribution is assumed to change as a function of distance from aggregate surface. Model results about HTO diffusivities of mortars and concretes are presented with some experimental values. The competition between the more diffusing ITZ zone and the less diffusing bulk matrix is investigated from a sensitive analysis. The dominance of the ITZ control is confirmed. (authors)

  16. Multi-Scale Analysis of Regional Inequality based on Spatial Field Model: A Case Study of China from 2000 to 2012

    Directory of Open Access Journals (Sweden)

    Shasha Lu

    2015-10-01

    Full Text Available A large body of recent studies—from both inside and outside of China—are devoted to the understanding of China’s regional inequality. The current study introduces “the spatial field model” to achieve comprehensive evaluation and multi-scale analysis of regional inequality. The model is based on the growth pole theory, regional interaction theory, and energy space theory. The spatial field is an abstract concept that defines the potential energy difference that is formed in the process of a regional growth pole driving the economic development of peripheral areas through transportation and communication corridors. The model is able to provide potentially more precise regional inequality estimates and generates isarithmic maps that will provide highly intuitive and visualized presentations. The model is applied to evaluate the spatiotemporal pattern of economic inequality in China from 2000 to 2012 amongst internal eastern-central-western regions as well as north-south regions at three geographical scales—i.e., inter-province, inter-city, and inter-county. The results indicate that the spatial field model could comprehensively evaluate regional inequality, provide aesthetically pleasing and highly adaptable presentations based on a pixel-based raster, and realise the multi-scale analyses of the regional inequality. The paper also investigates the limitations and extensions of the spatial field model in future application.

  17. Global sensitivity analysis of multiscale properties of porous materials

    Science.gov (United States)

    Um, Kimoon; Zhang, Xuan; Katsoulakis, Markos; Plechac, Petr; Tartakovsky, Daniel M.

    2018-02-01

    Ubiquitous uncertainty about pore geometry inevitably undermines the veracity of pore- and multi-scale simulations of transport phenomena in porous media. It raises two fundamental issues: sensitivity of effective material properties to pore-scale parameters and statistical parameterization of Darcy-scale models that accounts for pore-scale uncertainty. Homogenization-based maps of pore-scale parameters onto their Darcy-scale counterparts facilitate both sensitivity analysis (SA) and uncertainty quantification. We treat uncertain geometric characteristics of a hierarchical porous medium as random variables to conduct global SA and to derive probabilistic descriptors of effective diffusion coefficients and effective sorption rate. Our analysis is formulated in terms of solute transport diffusing through a fluid-filled pore space, while sorbing to the solid matrix. Yet it is sufficiently general to be applied to other multiscale porous media phenomena that are amenable to homogenization.

  18. Multiscale agent-based cancer modeling.

    Science.gov (United States)

    Zhang, Le; Wang, Zhihui; Sagotsky, Jonathan A; Deisboeck, Thomas S

    2009-04-01

    Agent-based modeling (ABM) is an in silico technique that is being used in a variety of research areas such as in social sciences, economics and increasingly in biomedicine as an interdisciplinary tool to study the dynamics of complex systems. Here, we describe its applicability to integrative tumor biology research by introducing a multi-scale tumor modeling platform that understands brain cancer as a complex dynamic biosystem. We summarize significant findings of this work, and discuss both challenges and future directions for ABM in the field of cancer research.

  19. Towards practical multiscale approach for analysis of reinforced concrete structures

    Science.gov (United States)

    Moyeda, Arturo; Fish, Jacob

    2017-12-01

    We present a novel multiscale approach for analysis of reinforced concrete structural elements that overcomes two major hurdles in utilization of multiscale technologies in practice: (1) coupling between material and structural scales due to consideration of large representative volume elements (RVE), and (2) computational complexity of solving complex nonlinear multiscale problems. The former is accomplished using a variant of computational continua framework that accounts for sizeable reinforced concrete RVEs by adjusting the location of quadrature points. The latter is accomplished by means of reduced order homogenization customized for structural elements. The proposed multiscale approach has been verified against direct numerical simulations and validated against experimental results.

  20. Multiscale permutation entropy analysis of electrocardiogram

    Science.gov (United States)

    Liu, Tiebing; Yao, Wenpo; Wu, Min; Shi, Zhaorong; Wang, Jun; Ning, Xinbao

    2017-04-01

    To make a comprehensive nonlinear analysis to ECG, multiscale permutation entropy (MPE) was applied to ECG characteristics extraction to make a comprehensive nonlinear analysis of ECG. Three kinds of ECG from PhysioNet database, congestive heart failure (CHF) patients, healthy young and elderly subjects, are applied in this paper. We set embedding dimension to 4 and adjust scale factor from 2 to 100 with a step size of 2, and compare MPE with multiscale entropy (MSE). As increase of scale factor, MPE complexity of the three ECG signals are showing first-decrease and last-increase trends. When scale factor is between 10 and 32, complexities of the three ECG had biggest difference, entropy of the elderly is 0.146 less than the CHF patients and 0.025 larger than the healthy young in average, in line with normal physiological characteristics. Test results showed that MPE can effectively apply in ECG nonlinear analysis, and can effectively distinguish different ECG signals.

  1. Multiscale analysis of surface morphologies by curvelet and contourlet transforms

    International Nuclear Information System (INIS)

    Li, Linfu; Zhang, Xiangchao; Zhang, Hao; He, Xiaoying; Xu, Min

    2015-01-01

    The surface topographies of precision components are critical to their functionalities. However, it is challenging to characterize the topographies of complex surfaces, especially for structured surfaces. The wavelet families are promising for the multiscale geometry analysis of nonstochastic surfaces. The second-generation curvelet transform provides a sparse representation and good multiscale decomposition for curve singularities. However, the contourlet expansion, composed of bases oriented along various directions in multiple scales with smaller redundancy rates, has a remarkable capability of representing borderlines. In this paper they are both adopted for the characterization of surface topographies. Different components can be extracted according to their scales and morphological characteristics; as a result, the corresponding manufacturing processes and functionalities can be analyzed specifically. Numerical experiments are given to demonstrate the capabilities of these methods in sparse representation and effective extraction of geometry features of different nonstochastic surfaces. (paper)

  2. Multiscale analysis of heart rate dynamics: entropy and time irreversibility measures.

    Science.gov (United States)

    Costa, Madalena D; Peng, Chung-Kang; Goldberger, Ary L

    2008-06-01

    Cardiovascular signals are largely analyzed using traditional time and frequency domain measures. However, such measures fail to account for important properties related to multiscale organization and non-equilibrium dynamics. The complementary role of conventional signal analysis methods and emerging multiscale techniques, is, therefore, an important frontier area of investigation. The key finding of this presentation is that two recently developed multiscale computational tools--multiscale entropy and multiscale time irreversibility--are able to extract information from cardiac interbeat interval time series not contained in traditional methods based on mean, variance or Fourier spectrum (two-point correlation) techniques. These new methods, with careful attention to their limitations, may be useful in diagnostics, risk stratification and detection of toxicity of cardiac drugs.

  3. Neural network based multiscale image restoration approach

    Science.gov (United States)

    de Castro, Ana Paula A.; da Silva, José D. S.

    2007-02-01

    This paper describes a neural network based multiscale image restoration approach. Multilayer perceptrons are trained with artificial images of degraded gray level circles, in an attempt to make the neural network learn inherent space relations of the degraded pixels. The present approach simulates the degradation by a low pass Gaussian filter blurring operation and the addition of noise to the pixels at pre-established rates. The training process considers the degraded image as input and the non-degraded image as output for the supervised learning process. The neural network thus performs an inverse operation by recovering a quasi non-degraded image in terms of least squared. The main difference of the approach to existing ones relies on the fact that the space relations are taken from different scales, thus providing relational space data to the neural network. The approach is an attempt to come up with a simple method that leads to an optimum solution to the problem. Considering different window sizes around a pixel simulates the multiscale operation. In the generalization phase the neural network is exposed to indoor, outdoor, and satellite degraded images following the same steps use for the artificial circle image.

  4. Numerical methods and analysis of multiscale problems

    CERN Document Server

    Madureira, Alexandre L

    2017-01-01

    This book is about numerical modeling of multiscale problems, and introduces several asymptotic analysis and numerical techniques which are necessary for a proper approximation of equations that depend on different physical scales. Aimed at advanced undergraduate and graduate students in mathematics, engineering and physics – or researchers seeking a no-nonsense approach –, it discusses examples in their simplest possible settings, removing mathematical hurdles that might hinder a clear understanding of the methods. The problems considered are given by singular perturbed reaction advection diffusion equations in one and two-dimensional domains, partial differential equations in domains with rough boundaries, and equations with oscillatory coefficients. This work shows how asymptotic analysis can be used to develop and analyze models and numerical methods that are robust and work well for a wide range of parameters.

  5. Lifetime statistics of quantum chaos studied by a multiscale analysis

    KAUST Repository

    Di Falco, A.; Krauss, T. F.; Fratalocchi, Andrea

    2012-01-01

    on a silicon-on-insulator substrate. We calculate resonances through a multiscale procedure that combines energy landscape analysis and wavelet transforms. Experimental data is found to follow the universal predictions arising from random matrix theory

  6. Multiscale wavelet representations for mammographic feature analysis

    Science.gov (United States)

    Laine, Andrew F.; Song, Shuwu

    1992-12-01

    This paper introduces a novel approach for accomplishing mammographic feature analysis through multiresolution representations. We show that efficient (nonredundant) representations may be identified from digital mammography and used to enhance specific mammographic features within a continuum of scale space. The multiresolution decomposition of wavelet transforms provides a natural hierarchy in which to embed an interactive paradigm for accomplishing scale space feature analysis. Choosing wavelets (or analyzing functions) that are simultaneously localized in both space and frequency, results in a powerful methodology for image analysis. Multiresolution and orientation selectivity, known biological mechanisms in primate vision, are ingrained in wavelet representations and inspire the techniques presented in this paper. Our approach includes local analysis of complete multiscale representations. Mammograms are reconstructed from wavelet coefficients, enhanced by linear, exponential and constant weight functions localized in scale space. By improving the visualization of breast pathology we can improve the changes of early detection of breast cancers (improve quality) while requiring less time to evaluate mammograms for most patients (lower costs).

  7. Multiscale deep neural network based analysis of FDG-PET images for the early diagnosis of Alzheimer's disease.

    Science.gov (United States)

    Lu, Donghuan; Popuri, Karteek; Ding, Gavin Weiguang; Balachandar, Rakesh; Beg, Mirza Faisal

    2018-05-01

    Alzheimer's disease (AD) is one of the most common neurodegenerative diseases with a commonly seen prodromal mild cognitive impairment (MCI) phase where memory loss is the main complaint progressively worsening with behavior issues and poor self-care. However, not all individuals clinically diagnosed with MCI progress to AD. A fraction of subjects with MCI either progress to non-AD dementia or remain stable at the MCI stage without progressing to dementia. Although a curative treatment of AD is currently unavailable, it is extremely important to correctly identify the individuals in the MCI phase that will go on to develop AD so that they may benefit from a curative treatment when one becomes available in the near future. At the same time, it would be highly desirable to also correctly identify those in the MCI phase that do not have AD pathology so they may be spared from unnecessary pharmocologic interventions that, at best, may provide them no benefit, and at worse, could further harm them with adverse side-effects. Additionally, it may be easier and simpler to identify the cause of the cognitive impairment in these non-AD cases, and hence proper identification of prodromal AD will be of benefit to these individuals as well. Fluorodeoxy glucose positron emission tomography (FDG-PET) captures the metabolic activity of the brain, and this imaging modality has been reported to identify changes related to AD prior to the onset of structural changes. Prior work on designing classifier using FDG-PET imaging has been promising. Since deep-learning has recently emerged as a powerful tool to mine features and use them for accurate labeling of the group membership of given images, we propose a novel deep-learning framework using FDG-PET metabolism imaging to identify subjects at the MCI stage with presymptomatic AD and discriminate them from other subjects with MCI (non-AD / non-progressive). Our multiscale deep neural network obtained 82.51% accuracy of classification

  8. Implementation of Grid-computing Framework for Simulation in Multi-scale Structural Analysis

    Directory of Open Access Journals (Sweden)

    Data Iranata

    2010-05-01

    Full Text Available A new grid-computing framework for simulation in multi-scale structural analysis is presented. Two levels of parallel processing will be involved in this framework: multiple local distributed computing environments connected by local network to form a grid-based cluster-to-cluster distributed computing environment. To successfully perform the simulation, a large-scale structural system task is decomposed into the simulations of a simplified global model and several detailed component models using various scales. These correlated multi-scale structural system tasks are distributed among clusters and connected together in a multi-level hierarchy and then coordinated over the internet. The software framework for supporting the multi-scale structural simulation approach is also presented. The program architecture design allows the integration of several multi-scale models as clients and servers under a single platform. To check its feasibility, a prototype software system has been designed and implemented to perform the proposed concept. The simulation results show that the software framework can increase the speedup performance of the structural analysis. Based on this result, the proposed grid-computing framework is suitable to perform the simulation of the multi-scale structural analysis.

  9. Big data-enabled multiscale serviceability analysis for aging bridges☆

    Directory of Open Access Journals (Sweden)

    Yu Liang

    2016-08-01

    Full Text Available This work is dedicated to constructing a multi-scale structural health monitoring system to monitor and evaluate the serviceability of bridges based on the Hadoop Ecosystem (MS-SHM-Hadoop. By taking the advantages of the fault-tolerant distributed file system called the Hadoop Distributed File System (HDFS and high-performance parallel data processing engine called MapReduce programming paradigm, MS-SHM-Hadoop features include high scalability and robustness in data ingestion, fusion, processing, retrieval, and analytics. MS-SHM-Hadoop is a multi-scale reliability analysis framework, which ranges from nationwide bridge-surveys, global structural integrity analysis, and structural component reliability analysis. This Nationwide bridge survey uses deep-learning techniques to evaluate the bridge serviceability according to real-time sensory data or archived bridge-related data such as traffic status, weather conditions and bridge structural configuration. The global structural integrity analysis of a targeted bridge is made by processing and analyzing the measured vibration signals incurred by external loads such as wind and traffic flow. Component-wise reliability analysis is also enabled by the deep learning technique, where the input data is derived from the measured structural load effects, hyper-spectral images, and moisture measurement of the structural components. As one of its major contributions, this work employs a Bayesian network to formulate the integral serviceability of a bridge according to its components serviceability and inter-component correlations. Here the inter-component correlations are jointly specified using a statistics-oriented machine learning method (e.g., association rule learning or structural mechanics modeling and simulation.

  10. HAM-Based Adaptive Multiscale Meshless Method for Burgers Equation

    Directory of Open Access Journals (Sweden)

    Shu-Li Mei

    2013-01-01

    Full Text Available Based on the multilevel interpolation theory, we constructed a meshless adaptive multiscale interpolation operator (MAMIO with the radial basis function. Using this operator, any nonlinear partial differential equations such as Burgers equation can be discretized adaptively in physical spaces as a nonlinear matrix ordinary differential equation. In order to obtain the analytical solution of the system of ODEs, the homotopy analysis method (HAM proposed by Shijun Liao was developed to solve the system of ODEs by combining the precise integration method (PIM which can be employed to get the analytical solution of linear system of ODEs. The numerical experiences show that HAM is not sensitive to the time step, and so the arithmetic error is mainly derived from the discrete in physical space.

  11. Multiscale Path Metrics for the Analysis of Discrete Geometric Structures

    Science.gov (United States)

    2017-11-30

    Report: Multiscale Path Metrics for the Analysis of Discrete Geometric Structures The views, opinions and/or findings contained in this report are those...Analysis of Discrete Geometric Structures Report Term: 0-Other Email: tomasi@cs.duke.edu Distribution Statement: 1-Approved for public release

  12. Conformal-Based Surface Morphing and Multi-Scale Representation

    Directory of Open Access Journals (Sweden)

    Ka Chun Lam

    2014-05-01

    Full Text Available This paper presents two algorithms, based on conformal geometry, for the multi-scale representations of geometric shapes and surface morphing. A multi-scale surface representation aims to describe a 3D shape at different levels of geometric detail, which allows analyzing or editing surfaces at the global or local scales effectively. Surface morphing refers to the process of interpolating between two geometric shapes, which has been widely applied to estimate or analyze deformations in computer graphics, computer vision and medical imaging. In this work, we propose two geometric models for surface morphing and multi-scale representation for 3D surfaces. The basic idea is to represent a 3D surface by its mean curvature function, H, and conformal factor function λ, which uniquely determine the geometry of the surface according to Riemann surface theory. Once we have the (λ, H parameterization of the surface, post-processing of the surface can be done directly on the conformal parameter domain. In particular, the problem of multi-scale representations of shapes can be reduced to the signal filtering on the λ and H parameters. On the other hand, the surface morphing problem can be transformed to an interpolation process of two sets of (λ, H parameters. We test the proposed algorithms on 3D human face data and MRI-derived brain surfaces. Experimental results show that our proposed methods can effectively obtain multi-scale surface representations and give natural surface morphing results.

  13. Multiscale analysis of structure development in expanded starch snacks

    Science.gov (United States)

    van der Sman, R. G. M.; Broeze, J.

    2014-11-01

    In this paper we perform a multiscale analysis of the food structuring process of the expansion of starchy snack foods like keropok, which obtains a solid foam structure. In particular, we want to investigate the validity of the hypothesis of Kokini and coworkers, that expansion is optimal at the moisture content, where the glass transition and the boiling line intersect. In our analysis we make use of several tools, (1) time scale analysis from the field of physical transport phenomena, (2) the scale separation map (SSM) developed within a multiscale simulation framework of complex automata, (3) the supplemented state diagram (SSD), depicting phase transition and glass transition lines, and (4) a multiscale simulation model for the bubble expansion. Results of the time scale analysis are plotted in the SSD, and give insight into the dominant physical processes involved in expansion. Furthermore, the results of the time scale analysis are used to construct the SSM, which has aided us in the construction of the multiscale simulation model. Simulation results are plotted in the SSD. This clearly shows that the hypothesis of Kokini is qualitatively true, but has to be refined. Our results show that bubble expansion is optimal for moisture content, where the boiling line for gas pressure of 4 bars intersects the isoviscosity line of the critical viscosity 106 Pa.s, which runs parallel to the glass transition line.

  14. Multi-scale entropy analysis of VR-based analog-digital system of the operator mental workload

    International Nuclear Information System (INIS)

    Lee Chunyi; Hung Tamin; Sun Tienlung; Yang Chihwei; Cheng Tsungchieh; Yang Lichen

    2011-01-01

    In the past, serious accidents of nuclear power plant usually had relation with the negligence, error handling and wrong decisions of operators. Therefore, to understand and be able to measure mental workload levels of operators are significant for safety issues in the nuclear power plant, especially when operators face emergency conditions. Therefore, this study is to determine the physiological indicators to measure the operator in the task of mental workload. This paper was to use electrocardiogram (ECG) measurements, to collect the RR-Interval data; heart rate variability (HRV) to analysis the complexity of the operator. After importing the data to calculate heart rate variability of complexity analysis, it can help us to understand the operator for the analog-digital platform adaptation. The virtual analog-digital nuclear plant control room is built using a 3D game development tool called Unity3D. (author)

  15. Introduction and application of the multiscale coefficient of variation analysis.

    Science.gov (United States)

    Abney, Drew H; Kello, Christopher T; Balasubramaniam, Ramesh

    2017-10-01

    Quantifying how patterns of behavior relate across multiple levels of measurement typically requires long time series for reliable parameter estimation. We describe a novel analysis that estimates patterns of variability across multiple scales of analysis suitable for time series of short duration. The multiscale coefficient of variation (MSCV) measures the distance between local coefficient of variation estimates within particular time windows and the overall coefficient of variation across all time samples. We first describe the MSCV analysis and provide an example analytical protocol with corresponding MATLAB implementation and code. Next, we present a simulation study testing the new analysis using time series generated by ARFIMA models that span white noise, short-term and long-term correlations. The MSCV analysis was observed to be sensitive to specific parameters of ARFIMA models varying in the type of temporal structure and time series length. We then apply the MSCV analysis to short time series of speech phrases and musical themes to show commonalities in multiscale structure. The simulation and application studies provide evidence that the MSCV analysis can discriminate between time series varying in multiscale structure and length.

  16. Versatile Micromechanics Model for Multiscale Analysis of Composite Structures

    Science.gov (United States)

    Kwon, Y. W.; Park, M. S.

    2013-08-01

    A general-purpose micromechanics model was developed so that the model could be applied to various composite materials such as reinforced by particles, long fibers and short fibers as well as those containing micro voids. Additionally, the model can be used with hierarchical composite materials. The micromechanics model can be used to compute effective material properties like elastic moduli, shear moduli, Poisson's ratios, and coefficients of thermal expansion for the various composite materials. The model can also calculate the strains and stresses at the constituent material level such as fibers, particles, and whiskers from the composite level stresses and strains. The model was implemented into ABAQUS using the UMAT option for multiscale analysis. An extensive set of examples are presented to demonstrate the reliability and accuracy of the developed micromechanics model for different kinds of composite materials. Another set of examples is provided to study the multiscale analysis of composite structures.

  17. Multiscale Permutation Entropy Based Rolling Bearing Fault Diagnosis

    Directory of Open Access Journals (Sweden)

    Jinde Zheng

    2014-01-01

    Full Text Available A new rolling bearing fault diagnosis approach based on multiscale permutation entropy (MPE, Laplacian score (LS, and support vector machines (SVMs is proposed in this paper. Permutation entropy (PE was recently proposed and defined to measure the randomicity and detect dynamical changes of time series. However, for the complexity of mechanical systems, the randomicity and dynamic changes of the vibration signal will exist in different scales. Thus, the definition of MPE is introduced and employed to extract the nonlinear fault characteristics from the bearing vibration signal in different scales. Besides, the SVM is utilized to accomplish the fault feature classification to fulfill diagnostic procedure automatically. Meanwhile, in order to avoid a high dimension of features, the Laplacian score (LS is used to refine the feature vector by ranking the features according to their importance and correlations with the main fault information. Finally, the rolling bearing fault diagnosis method based on MPE, LS, and SVM is proposed and applied to the experimental data. The experimental data analysis results indicate that the proposed method could identify the fault categories effectively.

  18. Lifetime statistics of quantum chaos studied by a multiscale analysis

    KAUST Repository

    Di Falco, A.

    2012-04-30

    In a series of pump and probe experiments, we study the lifetime statistics of a quantum chaotic resonator when the number of open channels is greater than one. Our design embeds a stadium billiard into a two dimensional photonic crystal realized on a silicon-on-insulator substrate. We calculate resonances through a multiscale procedure that combines energy landscape analysis and wavelet transforms. Experimental data is found to follow the universal predictions arising from random matrix theory with an excellent level of agreement.

  19. Multiscale weighted colored graphs for protein flexibility and rigidity analysis

    Science.gov (United States)

    Bramer, David; Wei, Guo-Wei

    2018-02-01

    Protein structural fluctuation, measured by Debye-Waller factors or B-factors, is known to correlate to protein flexibility and function. A variety of methods has been developed for protein Debye-Waller factor prediction and related applications to domain separation, docking pose ranking, entropy calculation, hinge detection, stability analysis, etc. Nevertheless, none of the current methodologies are able to deliver an accuracy of 0.7 in terms of the Pearson correlation coefficients averaged over a large set of proteins. In this work, we introduce a paradigm-shifting geometric graph model, multiscale weighted colored graph (MWCG), to provide a new generation of computational algorithms to significantly change the current status of protein structural fluctuation analysis. Our MWCG model divides a protein graph into multiple subgraphs based on interaction types between graph nodes and represents the protein rigidity by generalized centralities of subgraphs. MWCGs not only predict the B-factors of protein residues but also accurately analyze the flexibility of all atoms in a protein. The MWCG model is validated over a number of protein test sets and compared with many standard methods. An extensive numerical study indicates that the proposed MWCG offers an accuracy of over 0.8 and thus provides perhaps the first reliable method for estimating protein flexibility and B-factors. It also simultaneously predicts all-atom flexibility in a molecule.

  20. EEMD-based multiscale ICA method for slewing bearing fault detection and diagnosis

    Science.gov (United States)

    Žvokelj, Matej; Zupan, Samo; Prebil, Ivan

    2016-05-01

    A novel multivariate and multiscale statistical process monitoring method is proposed with the aim of detecting incipient failures in large slewing bearings, where subjective influence plays a minor role. The proposed method integrates the strengths of the Independent Component Analysis (ICA) multivariate monitoring approach with the benefits of Ensemble Empirical Mode Decomposition (EEMD), which adaptively decomposes signals into different time scales and can thus cope with multiscale system dynamics. The method, which was named EEMD-based multiscale ICA (EEMD-MSICA), not only enables bearing fault detection but also offers a mechanism of multivariate signal denoising and, in combination with the Envelope Analysis (EA), a diagnostic tool. The multiscale nature of the proposed approach makes the method convenient to cope with data which emanate from bearings in complex real-world rotating machinery and frequently represent the cumulative effect of many underlying phenomena occupying different regions in the time-frequency plane. The efficiency of the proposed method was tested on simulated as well as real vibration and Acoustic Emission (AE) signals obtained through conducting an accelerated run-to-failure lifetime experiment on a purpose-built laboratory slewing bearing test stand. The ability to detect and locate the early-stage rolling-sliding contact fatigue failure of the bearing indicates that AE and vibration signals carry sufficient information on the bearing condition and that the developed EEMD-MSICA method is able to effectively extract it, thereby representing a reliable bearing fault detection and diagnosis strategy.

  1. Formalizing Knowledge in Multi-Scale Agent-Based Simulations.

    Science.gov (United States)

    Somogyi, Endre; Sluka, James P; Glazier, James A

    2016-10-01

    Multi-scale, agent-based simulations of cellular and tissue biology are increasingly common. These simulations combine and integrate a range of components from different domains. Simulations continuously create, destroy and reorganize constituent elements causing their interactions to dynamically change. For example, the multi-cellular tissue development process coordinates molecular, cellular and tissue scale objects with biochemical, biomechanical, spatial and behavioral processes to form a dynamic network. Different domain specific languages can describe these components in isolation, but cannot describe their interactions. No current programming language is designed to represent in human readable and reusable form the domain specific knowledge contained in these components and interactions. We present a new hybrid programming language paradigm that naturally expresses the complex multi-scale objects and dynamic interactions in a unified way and allows domain knowledge to be captured, searched, formalized, extracted and reused.

  2. Multi-scale symbolic transfer entropy analysis of EEG

    Science.gov (United States)

    Yao, Wenpo; Wang, Jun

    2017-10-01

    From both global and local perspectives, we symbolize two kinds of EEG and analyze their dynamic and asymmetrical information using multi-scale transfer entropy. Multi-scale process with scale factor from 1 to 199 and step size of 2 is applied to EEG of healthy people and epileptic patients, and then the permutation with embedding dimension of 3 and global approach are used to symbolize the sequences. The forward and reverse symbol sequences are taken as the inputs of transfer entropy. Scale factor intervals of permutation and global way are (37, 57) and (65, 85) where the two kinds of EEG have satisfied entropy distinctions. When scale factor is 67, transfer entropy of the healthy and epileptic subjects of permutation, 0.1137 and 0.1028, have biggest difference. And the corresponding values of the global symbolization is 0.0641 and 0.0601 which lies in the scale factor of 165. Research results show that permutation which takes contribution of local information has better distinction and is more effectively applied to our multi-scale transfer entropy analysis of EEG.

  3. A posteriori error analysis of multiscale operator decomposition methods for multiphysics models

    International Nuclear Information System (INIS)

    Estep, D; Carey, V; Tavener, S; Ginting, V; Wildey, T

    2008-01-01

    Multiphysics, multiscale models present significant challenges in computing accurate solutions and for estimating the error in information computed from numerical solutions. In this paper, we describe recent advances in extending the techniques of a posteriori error analysis to multiscale operator decomposition solution methods. While the particulars of the analysis vary considerably with the problem, several key ideas underlie a general approach being developed to treat operator decomposition multiscale methods. We explain these ideas in the context of three specific examples

  4. Multivariate Multi-Scale Permutation Entropy for Complexity Analysis of Alzheimer’s Disease EEG

    Directory of Open Access Journals (Sweden)

    Isabella Palamara

    2012-07-01

    Full Text Available An original multivariate multi-scale methodology for assessing the complexity of physiological signals is proposed. The technique is able to incorporate the simultaneous analysis of multi-channel data as a unique block within a multi-scale framework. The basic complexity measure is done by using Permutation Entropy, a methodology for time series processing based on ordinal analysis. Permutation Entropy is conceptually simple, structurally robust to noise and artifacts, computationally very fast, which is relevant for designing portable diagnostics. Since time series derived from biological systems show structures on multiple spatial-temporal scales, the proposed technique can be useful for other types of biomedical signal analysis. In this work, the possibility of distinguish among the brain states related to Alzheimer’s disease patients and Mild Cognitive Impaired subjects from normal healthy elderly is checked on a real, although quite limited, experimental database.

  5. Low-carbon building assessment and multi-scale input-output analysis

    Science.gov (United States)

    Chen, G. Q.; Chen, H.; Chen, Z. M.; Zhang, Bo; Shao, L.; Guo, S.; Zhou, S. Y.; Jiang, M. M.

    2011-01-01

    Presented as a low-carbon building evaluation framework in this paper are detailed carbon emission account procedures for the life cycle of buildings in terms of nine stages as building construction, fitment, outdoor facility construction, transportation, operation, waste treatment, property management, demolition, and disposal for buildings, supported by integrated carbon intensity databases based on multi-scale input-output analysis, essential for low-carbon planning, procurement and supply chain design, and logistics management.

  6. Hourly forecasting of global solar radiation based on multiscale decomposition methods: A hybrid approach

    International Nuclear Information System (INIS)

    Monjoly, Stéphanie; André, Maïna; Calif, Rudy; Soubdhan, Ted

    2017-01-01

    This paper introduces a new approach for the forecasting of solar radiation series at 1 h ahead. We investigated on several techniques of multiscale decomposition of clear sky index K_c data such as Empirical Mode Decomposition (EMD), Ensemble Empirical Mode Decomposition (EEMD) and Wavelet Decomposition. From these differents methods, we built 11 decomposition components and 1 residu signal presenting different time scales. We performed classic forecasting models based on linear method (Autoregressive process AR) and a non linear method (Neural Network model). The choice of forecasting method is adaptative on the characteristic of each component. Hence, we proposed a modeling process which is built from a hybrid structure according to the defined flowchart. An analysis of predictive performances for solar forecasting from the different multiscale decompositions and forecast models is presented. From multiscale decomposition, the solar forecast accuracy is significantly improved, particularly using the wavelet decomposition method. Moreover, multistep forecasting with the proposed hybrid method resulted in additional improvement. For example, in terms of RMSE error, the obtained forecasting with the classical NN model is about 25.86%, this error decrease to 16.91% with the EMD-Hybrid Model, 14.06% with the EEMD-Hybid model and to 7.86% with the WD-Hybrid Model. - Highlights: • Hourly forecasting of GHI in tropical climate with many cloud formation processes. • Clear sky Index decomposition using three multiscale decomposition methods. • Combination of multiscale decomposition methods with AR-NN models to predict GHI. • Comparison of the proposed hybrid model with the classical models (AR, NN). • Best results using Wavelet-Hybrid model in comparison with classical models.

  7. Multiscale Detrended Cross-Correlation Analysis of STOCK Markets

    Science.gov (United States)

    Yin, Yi; Shang, Pengjian

    2014-06-01

    In this paper, we employ the detrended cross-correlation analysis (DCCA) to investigate the cross-correlations between different stock markets. We report the results of cross-correlated behaviors in US, Chinese and European stock markets in period 1997-2012 by using DCCA method. The DCCA shows the cross-correlated behaviors of intra-regional and inter-regional stock markets in the short and long term which display the similarities and differences of cross-correlated behaviors simply and roughly and the persistence of cross-correlated behaviors of fluctuations. Then, because of the limitation and inapplicability of DCCA method, we propose multiscale detrended cross-correlation analysis (MSDCCA) method to avoid "a priori" selecting the ranges of scales over which two coefficients of the classical DCCA method are identified, and employ MSDCCA to reanalyze these cross-correlations to exhibit some important details such as the existence and position of minimum, maximum and bimodal distribution which are lost if the scale structure is described by two coefficients only and essential differences and similarities in the scale structures of cross-correlation of intra-regional and inter-regional markets. More statistical characteristics of cross-correlation obtained by MSDCCA method help us to understand how two different stock markets influence each other and to analyze the influence from thus two inter-regional markets on the cross-correlation in detail, thus we get a richer and more detailed knowledge of the complex evolutions of dynamics of the cross-correlations between stock markets. The application of MSDCCA is important to promote our understanding of the internal mechanisms and structures of financial markets and helps to forecast the stock indices based on our current results demonstrated the cross-correlations between stock indices. We also discuss the MSDCCA methods of secant rolling window with different sizes and, lastly, provide some relevant implications and

  8. Multiscale Embedded Gene Co-expression Network Analysis.

    Directory of Open Access Journals (Sweden)

    Won-Min Song

    2015-11-01

    Full Text Available Gene co-expression network analysis has been shown effective in identifying functional co-expressed gene modules associated with complex human diseases. However, existing techniques to construct co-expression networks require some critical prior information such as predefined number of clusters, numerical thresholds for defining co-expression/interaction, or do not naturally reproduce the hallmarks of complex systems such as the scale-free degree distribution of small-worldness. Previously, a graph filtering technique called Planar Maximally Filtered Graph (PMFG has been applied to many real-world data sets such as financial stock prices and gene expression to extract meaningful and relevant interactions. However, PMFG is not suitable for large-scale genomic data due to several drawbacks, such as the high computation complexity O(|V|3, the presence of false-positives due to the maximal planarity constraint, and the inadequacy of the clustering framework. Here, we developed a new co-expression network analysis framework called Multiscale Embedded Gene Co-expression Network Analysis (MEGENA by: i introducing quality control of co-expression similarities, ii parallelizing embedded network construction, and iii developing a novel clustering technique to identify multi-scale clustering structures in Planar Filtered Networks (PFNs. We applied MEGENA to a series of simulated data and the gene expression data in breast carcinoma and lung adenocarcinoma from The Cancer Genome Atlas (TCGA. MEGENA showed improved performance over well-established clustering methods and co-expression network construction approaches. MEGENA revealed not only meaningful multi-scale organizations of co-expressed gene clusters but also novel targets in breast carcinoma and lung adenocarcinoma.

  9. Multiscale Embedded Gene Co-expression Network Analysis.

    Science.gov (United States)

    Song, Won-Min; Zhang, Bin

    2015-11-01

    Gene co-expression network analysis has been shown effective in identifying functional co-expressed gene modules associated with complex human diseases. However, existing techniques to construct co-expression networks require some critical prior information such as predefined number of clusters, numerical thresholds for defining co-expression/interaction, or do not naturally reproduce the hallmarks of complex systems such as the scale-free degree distribution of small-worldness. Previously, a graph filtering technique called Planar Maximally Filtered Graph (PMFG) has been applied to many real-world data sets such as financial stock prices and gene expression to extract meaningful and relevant interactions. However, PMFG is not suitable for large-scale genomic data due to several drawbacks, such as the high computation complexity O(|V|3), the presence of false-positives due to the maximal planarity constraint, and the inadequacy of the clustering framework. Here, we developed a new co-expression network analysis framework called Multiscale Embedded Gene Co-expression Network Analysis (MEGENA) by: i) introducing quality control of co-expression similarities, ii) parallelizing embedded network construction, and iii) developing a novel clustering technique to identify multi-scale clustering structures in Planar Filtered Networks (PFNs). We applied MEGENA to a series of simulated data and the gene expression data in breast carcinoma and lung adenocarcinoma from The Cancer Genome Atlas (TCGA). MEGENA showed improved performance over well-established clustering methods and co-expression network construction approaches. MEGENA revealed not only meaningful multi-scale organizations of co-expressed gene clusters but also novel targets in breast carcinoma and lung adenocarcinoma.

  10. Multiscale analysis for ill-posed problems with semi-discrete Tikhonov regularization

    International Nuclear Information System (INIS)

    Zhong, Min; Lu, Shuai; Cheng, Jin

    2012-01-01

    Using compactly supported radial basis functions of varying radii, Wendland has shown how a multiscale analysis can be applied to the approximation of Sobolev functions on a bounded domain, when the available data are discrete and noisy. Here, we examine the application of this analysis to the solution of linear moderately ill-posed problems using semi-discrete Tikhonov–Phillips regularization. As in Wendland’s work, the actual multiscale approximation is constructed by a sequence of residual corrections, where different support radii are employed to accommodate different scales. The convergence of the algorithm for noise-free data is given. Based on the Morozov discrepancy principle, a posteriori parameter choice rule and error estimates for the noisy data are derived. Two numerical examples are presented to illustrate the appropriateness of the proposed method. (paper)

  11. Multiscale recurrence analysis of spatio-temporal data

    Science.gov (United States)

    Riedl, M.; Marwan, N.; Kurths, J.

    2015-12-01

    The description and analysis of spatio-temporal dynamics is a crucial task in many scientific disciplines. In this work, we propose a method which uses the mapogram as a similarity measure between spatially distributed data instances at different time points. The resulting similarity values of the pairwise comparison are used to construct a recurrence plot in order to benefit from established tools of recurrence quantification analysis and recurrence network analysis. In contrast to other recurrence tools for this purpose, the mapogram approach allows the specific focus on different spatial scales that can be used in a multi-scale analysis of spatio-temporal dynamics. We illustrate this approach by application on mixed dynamics, such as traveling parallel wave fronts with additive noise, as well as more complicate examples, pseudo-random numbers and coupled map lattices with a semi-logistic mapping rule. Especially the complicate examples show the usefulness of the multi-scale consideration in order to take spatial pattern of different scales and with different rhythms into account. So, this mapogram approach promises new insights in problems of climatology, ecology, or medicine.

  12. Fatigue of multiscale composites with secondary nanoplatelet reinforcement: 3D computational analysis

    DEFF Research Database (Denmark)

    Dai, Gaoming; Mishnaevsky, Leon, Jr.

    2014-01-01

    3D numerical simulations of fatigue damage of multiscale fiber reinforced polymer composites with secondary nanoclay reinforcement are carried out. Macro–micro FE models of the multiscale composites are generated automatically using Python based software. The effect of the nanoclay reinforcement....... Multiscale composites with exfoliated nanoreinforcement and aligned nanoplatelets ensure the better fatigue resistance than those with intercalated/clustered and randomly oriented nanoreinforcement....

  13. Front-end vision and multi-scale image analysis multi-scale computer vision theory and applications, written in Mathematica

    CERN Document Server

    Romeny, Bart M Haar

    2008-01-01

    Front-End Vision and Multi-Scale Image Analysis is a tutorial in multi-scale methods for computer vision and image processing. It builds on the cross fertilization between human visual perception and multi-scale computer vision (`scale-space') theory and applications. The multi-scale strategies recognized in the first stages of the human visual system are carefully examined, and taken as inspiration for the many geometric methods discussed. All chapters are written in Mathematica, a spectacular high-level language for symbolic and numerical manipulations. The book presents a new and effective

  14. Refined generalized multiscale entropy analysis for physiological signals

    Science.gov (United States)

    Liu, Yunxiao; Lin, Youfang; Wang, Jing; Shang, Pengjian

    2018-01-01

    Multiscale entropy analysis has become a prevalent complexity measurement and been successfully applied in various fields. However, it only takes into account the information of mean values (first moment) in coarse-graining procedure. Then generalized multiscale entropy (MSEn) considering higher moments to coarse-grain a time series was proposed and MSEσ2 has been implemented. However, the MSEσ2 sometimes may yield an imprecise estimation of entropy or undefined entropy, and reduce statistical reliability of sample entropy estimation as scale factor increases. For this purpose, we developed the refined model, RMSEσ2, to improve MSEσ2. Simulations on both white noise and 1 / f noise show that RMSEσ2 provides higher entropy reliability and reduces the occurrence of undefined entropy, especially suitable for short time series. Besides, we discuss the effect on RMSEσ2 analysis from outliers, data loss and other concepts in signal processing. We apply the proposed model to evaluate the complexity of heartbeat interval time series derived from healthy young and elderly subjects, patients with congestive heart failure and patients with atrial fibrillation respectively, compared to several popular complexity metrics. The results demonstrate that RMSEσ2 measured complexity (a) decreases with aging and diseases, and (b) gives significant discrimination between different physiological/pathological states, which may facilitate clinical application.

  15. Multiscale analysis of the CMB temperature derivatives

    Energy Technology Data Exchange (ETDEWEB)

    Marcos-Caballero, A.; Martínez-González, E.; Vielva, P., E-mail: marcos@ifca.unican.es, E-mail: martinez@ifca.unican.es, E-mail: vielva@ifca.unican.es [Instituto de Física de Cantabria, CSIC-Universidad de Cantabria, Avda. de los Castros s/n, 39005 Santander, Spain. (Spain)

    2017-02-01

    We study the Planck CMB temperature at different scales through its derivatives up to second order, which allows one to characterize the local shape and isotropy of the field. The problem of having an incomplete sky in the calculation and statistical characterization of the derivatives is addressed in the paper. The analysis confirms the existence of a low variance in the CMB at large scales, which is also noticeable in the derivatives. Moreover, deviations from the standard model in the gradient, curvature and the eccentricity tensor are studied in terms of extreme values on the data. As it is expected, the Cold Spot is detected as one of the most prominent peaks in terms of curvature, but additionally, when the information of the temperature and its Laplacian are combined, another feature with similar probability at the scale of 10{sup o} is also observed. However, the p -value of these two deviations increase above the 6% when they are referred to the variance calculated from the theoretical fiducial model, indicating that these deviations can be associated to the low variance anomaly. Finally, an estimator of the directional anisotropy for spinorial quantities is introduced, which is applied to the spinors derived from the field derivatives. An anisotropic direction whose probability is <1% is detected in the eccentricity tensor.

  16. Multiscale analysis of damage using dual and primal domain decomposition techniques

    NARCIS (Netherlands)

    Lloberas-Valls, O.; Everdij, F.P.X.; Rixen, D.J.; Simone, A.; Sluys, L.J.

    2014-01-01

    In this contribution, dual and primal domain decomposition techniques are studied for the multiscale analysis of failure in quasi-brittle materials. The multiscale strategy essentially consists in decomposing the structure into a number of nonoverlapping domains and considering a refined spatial

  17. Lagrangian analysis of multiscale particulate flows with the particle finite element method

    Science.gov (United States)

    Oñate, Eugenio; Celigueta, Miguel Angel; Latorre, Salvador; Casas, Guillermo; Rossi, Riccardo; Rojek, Jerzy

    2014-05-01

    We present a Lagrangian numerical technique for the analysis of flows incorporating physical particles of different sizes. The numerical approach is based on the particle finite element method (PFEM) which blends concepts from particle-based techniques and the FEM. The basis of the Lagrangian formulation for particulate flows and the procedure for modelling the motion of small and large particles that are submerged in the fluid are described in detail. The numerical technique for analysis of this type of multiscale particulate flows using a stabilized mixed velocity-pressure formulation and the PFEM is also presented. Examples of application of the PFEM to several particulate flows problems are given.

  18. Predictive Multiscale Modeling of Nanocellulose Based Materials and Systems

    International Nuclear Information System (INIS)

    Kovalenko, Andriy

    2014-01-01

    Cellulose Nanocrysals (CNC) is a renewable biodegradable biopolymer with outstanding mechanical properties made from highly abundant natural source, and therefore is very attractive as reinforcing additive to replace petroleum-based plastics in biocomposite materials, foams, and gels. Large-scale applications of CNC are currently limited due to its low solubility in non-polar organic solvents used in existing polymerization technologies. The solvation properties of CNC can be improved by chemical modification of its surface. Development of effective surface modifications has been rather slow because extensive chemical modifications destabilize the hydrogen bonding network of cellulose and deteriorate the mechanical properties of CNC. We employ predictive multiscale theory, modeling, and simulation to gain a fundamental insight into the effect of CNC surface modifications on hydrogen bonding, CNC crystallinity, solvation thermodynamics, and CNC compatibilization with the existing polymerization technologies, so as to rationally design green nanomaterials with improved solubility in non-polar solvents, controlled liquid crystal ordering and optimized extrusion properties. An essential part of this multiscale modeling approach is the statistical- mechanical 3D-RISM-KH molecular theory of solvation, coupled with quantum mechanics, molecular mechanics, and multistep molecular dynamics simulation. The 3D-RISM-KH theory provides predictive modeling of both polar and non-polar solvents, solvent mixtures, and electrolyte solutions in a wide range of concentrations and thermodynamic states. It properly accounts for effective interactions in solution such as steric effects, hydrophobicity and hydrophilicity, hydrogen bonding, salt bridges, buffer, co-solvent, and successfully predicts solvation effects and processes in bulk liquids, solvation layers at solid surface, and in pockets and other inner spaces of macromolecules and supramolecular assemblies. This methodology

  19. Predictive Multiscale Modeling of Nanocellulose Based Materials and Systems

    Science.gov (United States)

    Kovalenko, Andriy

    2014-08-01

    Cellulose Nanocrysals (CNC) is a renewable biodegradable biopolymer with outstanding mechanical properties made from highly abundant natural source, and therefore is very attractive as reinforcing additive to replace petroleum-based plastics in biocomposite materials, foams, and gels. Large-scale applications of CNC are currently limited due to its low solubility in non-polar organic solvents used in existing polymerization technologies. The solvation properties of CNC can be improved by chemical modification of its surface. Development of effective surface modifications has been rather slow because extensive chemical modifications destabilize the hydrogen bonding network of cellulose and deteriorate the mechanical properties of CNC. We employ predictive multiscale theory, modeling, and simulation to gain a fundamental insight into the effect of CNC surface modifications on hydrogen bonding, CNC crystallinity, solvation thermodynamics, and CNC compatibilization with the existing polymerization technologies, so as to rationally design green nanomaterials with improved solubility in non-polar solvents, controlled liquid crystal ordering and optimized extrusion properties. An essential part of this multiscale modeling approach is the statistical- mechanical 3D-RISM-KH molecular theory of solvation, coupled with quantum mechanics, molecular mechanics, and multistep molecular dynamics simulation. The 3D-RISM-KH theory provides predictive modeling of both polar and non-polar solvents, solvent mixtures, and electrolyte solutions in a wide range of concentrations and thermodynamic states. It properly accounts for effective interactions in solution such as steric effects, hydrophobicity and hydrophilicity, hydrogen bonding, salt bridges, buffer, co-solvent, and successfully predicts solvation effects and processes in bulk liquids, solvation layers at solid surface, and in pockets and other inner spaces of macromolecules and supramolecular assemblies. This methodology

  20. Multiscale analysis of replication technique efficiency for 3D roughness characterization of manufactured surfaces

    Science.gov (United States)

    Jolivet, S.; Mezghani, S.; El Mansori, M.

    2016-09-01

    The replication of topography has been generally restricted to optimizing material processing technologies in terms of statistical and single-scale features such as roughness. By contrast, manufactured surface topography is highly complex, irregular, and multiscale. In this work, we have demonstrated the use of multiscale analysis on replicates of surface finish to assess the precise control of the finished replica. Five commercial resins used for surface replication were compared. The topography of five standard surfaces representative of common finishing processes were acquired both directly and by a replication technique. Then, they were characterized using the ISO 25178 standard and multiscale decomposition based on a continuous wavelet transform, to compare the roughness transfer quality at different scales. Additionally, atomic force microscope force modulation mode was used in order to compare the resins’ stiffness properties. The results showed that less stiff resins are able to replicate the surface finish along a larger wavelength band. The method was then tested for non-destructive quality control of automotive gear tooth surfaces.

  1. A Multiscale, Nonlinear, Modeling Framework Enabling the Design and Analysis of Composite Materials and Structures

    Science.gov (United States)

    Bednarcyk, Brett A.; Arnold, Steven M.

    2012-01-01

    A framework for the multiscale design and analysis of composite materials and structures is presented. The ImMAC software suite, developed at NASA Glenn Research Center, embeds efficient, nonlinear micromechanics capabilities within higher scale structural analysis methods such as finite element analysis. The result is an integrated, multiscale tool that relates global loading to the constituent scale, captures nonlinearities at this scale, and homogenizes local nonlinearities to predict their effects at the structural scale. Example applications of the multiscale framework are presented for the stochastic progressive failure of a SiC/Ti composite tensile specimen and the effects of microstructural variations on the nonlinear response of woven polymer matrix composites.

  2. Analysis of global multiscale finite element methods for wave equations with continuum spatial scales

    KAUST Repository

    Jiang, Lijian; Efendiev, Yalchin; Ginting, Victor

    2010-01-01

    In this paper, we discuss a numerical multiscale approach for solving wave equations with heterogeneous coefficients. Our interest comes from geophysics applications and we assume that there is no scale separation with respect to spatial variables. To obtain the solution of these multiscale problems on a coarse grid, we compute global fields such that the solution smoothly depends on these fields. We present a Galerkin multiscale finite element method using the global information and provide a convergence analysis when applied to solve the wave equations. We investigate the relation between the smoothness of the global fields and convergence rates of the global Galerkin multiscale finite element method for the wave equations. Numerical examples demonstrate that the use of global information renders better accuracy for wave equations with heterogeneous coefficients than the local multiscale finite element method. © 2010 IMACS.

  3. Analysis of global multiscale finite element methods for wave equations with continuum spatial scales

    KAUST Repository

    Jiang, Lijian

    2010-08-01

    In this paper, we discuss a numerical multiscale approach for solving wave equations with heterogeneous coefficients. Our interest comes from geophysics applications and we assume that there is no scale separation with respect to spatial variables. To obtain the solution of these multiscale problems on a coarse grid, we compute global fields such that the solution smoothly depends on these fields. We present a Galerkin multiscale finite element method using the global information and provide a convergence analysis when applied to solve the wave equations. We investigate the relation between the smoothness of the global fields and convergence rates of the global Galerkin multiscale finite element method for the wave equations. Numerical examples demonstrate that the use of global information renders better accuracy for wave equations with heterogeneous coefficients than the local multiscale finite element method. © 2010 IMACS.

  4. A Multi-Scale Settlement Matching Algorithm Based on ARG

    Science.gov (United States)

    Yue, Han; Zhu, Xinyan; Chen, Di; Liu, Lingjia

    2016-06-01

    Homonymous entity matching is an important part of multi-source spatial data integration, automatic updating and change detection. Considering the low accuracy of existing matching methods in dealing with matching multi-scale settlement data, an algorithm based on Attributed Relational Graph (ARG) is proposed. The algorithm firstly divides two settlement scenes at different scales into blocks by small-scale road network and constructs local ARGs in each block. Then, ascertains candidate sets by merging procedures and obtains the optimal matching pairs by comparing the similarity of ARGs iteratively. Finally, the corresponding relations between settlements at large and small scales are identified. At the end of this article, a demonstration is presented and the results indicate that the proposed algorithm is capable of handling sophisticated cases.

  5. A Multi-Scale Settlement Matching Algorithm Based on ARG

    Directory of Open Access Journals (Sweden)

    H. Yue

    2016-06-01

    Full Text Available Homonymous entity matching is an important part of multi-source spatial data integration, automatic updating and change detection. Considering the low accuracy of existing matching methods in dealing with matching multi-scale settlement data, an algorithm based on Attributed Relational Graph (ARG is proposed. The algorithm firstly divides two settlement scenes at different scales into blocks by small-scale road network and constructs local ARGs in each block. Then, ascertains candidate sets by merging procedures and obtains the optimal matching pairs by comparing the similarity of ARGs iteratively. Finally, the corresponding relations between settlements at large and small scales are identified. At the end of this article, a demonstration is presented and the results indicate that the proposed algorithm is capable of handling sophisticated cases.

  6. Multiscale experimental mechanics of hierarchical carbon-based materials.

    Science.gov (United States)

    Espinosa, Horacio D; Filleter, Tobin; Naraghi, Mohammad

    2012-06-05

    Investigation of the mechanics of natural materials, such as spider silk, abalone shells, and bone, has provided great insight into the design of materials that can simultaneously achieve high specific strength and toughness. Research has shown that their emergent mechanical properties are owed in part to their specific self-organization in hierarchical molecular structures, from nanoscale to macroscale, as well as their mixing and bonding. To apply these findings to manmade materials, researchers have devoted significant efforts in developing a fundamental understanding of multiscale mechanics of materials and its application to the design of novel materials with superior mechanical performance. These efforts included the utilization of some of the most promising carbon-based nanomaterials, such as carbon nanotubes, carbon nanofibers, and graphene, together with a variety of matrix materials. At the core of these efforts lies the need to characterize material mechanical behavior across multiple length scales starting from nanoscale characterization of constituents and their interactions to emerging micro- and macroscale properties. In this report, progress made in experimental tools and methods currently used for material characterization across multiple length scales is reviewed, as well as a discussion of how they have impacted our current understanding of the mechanics of hierarchical carbon-based materials. In addition, insight is provided into strategies for bridging experiments across length scales, which are essential in establishing a multiscale characterization approach. While the focus of this progress report is in experimental methods, their concerted use with theoretical-computational approaches towards the establishment of a robust material by design methodology is also discussed, which can pave the way for the development of novel materials possessing unprecedented mechanical properties. Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  7. Analysis of individual brain activation maps using hierarchical description and multiscale detection

    International Nuclear Information System (INIS)

    Poline, J.B.; Mazoyer, B.M.

    1994-01-01

    The authors propose a new method for the analysis of brain activation images that aims at detecting activated volumes rather than pixels. The method is based on Poisson process modeling, hierarchical description, and multiscale detection (MSD). Its performances have been assessed using both Monte Carlo simulated images and experimental PET brain activation data. As compared to other methods, the MSD approach shows enhanced sensitivity with a controlled overall type I error, and has the ability to provide an estimate of the spatial limits of the detected signals. It is applicable to any kind of difference image for which the spatial autocorrelation function can be approximated by a stationary Gaussian function

  8. Analysis of complex time series using refined composite multiscale entropy

    International Nuclear Information System (INIS)

    Wu, Shuen-De; Wu, Chiu-Wen; Lin, Shiou-Gwo; Lee, Kung-Yen; Peng, Chung-Kang

    2014-01-01

    Multiscale entropy (MSE) is an effective algorithm for measuring the complexity of a time series that has been applied in many fields successfully. However, MSE may yield an inaccurate estimation of entropy or induce undefined entropy because the coarse-graining procedure reduces the length of a time series considerably at large scales. Composite multiscale entropy (CMSE) was recently proposed to improve the accuracy of MSE, but it does not resolve undefined entropy. Here we propose a refined composite multiscale entropy (RCMSE) to improve CMSE. For short time series analyses, we demonstrate that RCMSE increases the accuracy of entropy estimation and reduces the probability of inducing undefined entropy.

  9. Distributed Multiscale Data Analysis and Processing for Sensor Networks

    National Research Council Canada - National Science Library

    Wagner, Raymond; Sarvotham, Shriram; Choi, Hyeokho; Baraniuk, Richard

    2005-01-01

    .... Second, the communication overhead of multiscale algorithms can become prohibitive. In this paper, we take a first step in addressing both shortcomings by introducing two new distributed multiresolution transforms...

  10. Dynamical glucometry: Use of multiscale entropy analysis in diabetes

    Science.gov (United States)

    Costa, Madalena D.; Henriques, Teresa; Munshi, Medha N.; Segal, Alissa R.; Goldberger, Ary L.

    2014-09-01

    Diabetes mellitus (DM) is one of the world's most prevalent medical conditions. Contemporary management focuses on lowering mean blood glucose values toward a normal range, but largely ignores the dynamics of glucose fluctuations. We probed analyte time series obtained from continuous glucose monitor (CGM) sensors. We show that the fluctuations in CGM values sampled every 5 min are not uncorrelated noise. Next, using multiscale entropy analysis, we quantified the complexity of the temporal structure of the CGM time series from a group of elderly subjects with type 2 DM and age-matched controls. We further probed the structure of these CGM time series using detrended fluctuation analysis. Our findings indicate that the dynamics of glucose fluctuations from control subjects are more complex than those of subjects with type 2 DM over time scales ranging from about 5 min to 5 h. These findings support consideration of a new framework, dynamical glucometry, to guide mechanistic research and to help assess and compare therapeutic interventions, which should enhance complexity of glucose fluctuations and not just lower mean and variance of blood glucose levels.

  11. Wavelet-based multiscale adjoint waveform-difference tomography using body and surface waves

    Science.gov (United States)

    Yuan, Y. O.; Simons, F. J.; Bozdag, E.

    2014-12-01

    We present a multi-scale scheme for full elastic waveform-difference inversion. Using a wavelet transform proves to be a key factor to mitigate cycle-skipping effects. We start with coarse representations of the seismogram to correct a large-scale background model, and subsequently explain the residuals in the fine scales of the seismogram to map the heterogeneities with great complexity. We have previously applied the multi-scale approach successfully to body waves generated in a standard model from the exploration industry: a modified two-dimensional elastic Marmousi model. With this model we explored the optimal choice of wavelet family, number of vanishing moments and decomposition depth. For this presentation we explore the sensitivity of surface waves in waveform-difference tomography. The incorporation of surface waves is rife with cycle-skipping problems compared to the inversions considering body waves only. We implemented an envelope-based objective function probed via a multi-scale wavelet analysis to measure the distance between predicted and target surface-wave waveforms in a synthetic model of heterogeneous near-surface structure. Our proposed method successfully purges the local minima present in the waveform-difference misfit surface. An elastic shallow model with 100~m in depth is used to test the surface-wave inversion scheme. We also analyzed the sensitivities of surface waves and body waves in full waveform inversions, as well as the effects of incorrect density information on elastic parameter inversions. Based on those numerical experiments, we ultimately formalized a flexible scheme to consider both body and surface waves in adjoint tomography. While our early examples are constructed from exploration-style settings, our procedure will be very valuable for the study of global network data.

  12. Fast spot-based multiscale simulations of granular drainage

    Energy Technology Data Exchange (ETDEWEB)

    Rycroft, Chris H.; Wong, Yee Lok; Bazant, Martin Z.

    2009-05-22

    We develop a multiscale simulation method for dense granular drainage, based on the recently proposed spot model, where the particle packing flows by local collective displacements in response to diffusing"spots'" of interstitial free volume. By comparing with discrete-element method (DEM) simulations of 55,000 spheres in a rectangular silo, we show that the spot simulation is able to approximately capture many features of drainage, such as packing statistics, particle mixing, and flow profiles. The spot simulation runs two to three orders of magnitude faster than DEM, making it an appropriate method for real-time control or optimization. We demonstrateextensions for modeling particle heaping and avalanching at the free surface, and for simulating the boundary layers of slower flow near walls. We show that the spot simulations are robust and flexible, by demonstrating that they can be used in both event-driven and fixed timestep approaches, and showing that the elastic relaxation step used in the model can be applied much less frequently and still create good results.

  13. Multi-Scale Factor Analysis of High-Dimensional Brain Signals

    KAUST Repository

    Ting, Chee-Ming

    2017-05-18

    In this paper, we develop an approach to modeling high-dimensional networks with a large number of nodes arranged in a hierarchical and modular structure. We propose a novel multi-scale factor analysis (MSFA) model which partitions the massive spatio-temporal data defined over the complex networks into a finite set of regional clusters. To achieve further dimension reduction, we represent the signals in each cluster by a small number of latent factors. The correlation matrix for all nodes in the network are approximated by lower-dimensional sub-structures derived from the cluster-specific factors. To estimate regional connectivity between numerous nodes (within each cluster), we apply principal components analysis (PCA) to produce factors which are derived as the optimal reconstruction of the observed signals under the squared loss. Then, we estimate global connectivity (between clusters or sub-networks) based on the factors across regions using the RV-coefficient as the cross-dependence measure. This gives a reliable and computationally efficient multi-scale analysis of both regional and global dependencies of the large networks. The proposed novel approach is applied to estimate brain connectivity networks using functional magnetic resonance imaging (fMRI) data. Results on resting-state fMRI reveal interesting modular and hierarchical organization of human brain networks during rest.

  14. Global Appearance Applied to Visual Map Building and Path Estimation Using Multiscale Analysis

    Directory of Open Access Journals (Sweden)

    Francisco Amorós

    2014-01-01

    Full Text Available In this work we present a topological map building and localization system for mobile robots based on global appearance of visual information. We include a comparison and analysis of global-appearance techniques applied to wide-angle scenes in retrieval tasks. Next, we define multiscale analysis, which permits improving the association between images and extracting topological distances. Then, a topological map-building algorithm is proposed. At first, the algorithm has information only of some isolated positions of the navigation area in the form of nodes. Each node is composed of a collection of images that covers the complete field of view from a certain position. The algorithm solves the node retrieval and estimates their spatial arrangement. With these aims, it uses the visual information captured along some routes that cover the navigation area. As a result, the algorithm builds a graph that reflects the distribution and adjacency relations between nodes (map. After the map building, we also propose a route path estimation system. This algorithm takes advantage of the multiscale analysis. The accuracy in the pose estimation is not reduced to the nodes locations but also to intermediate positions between them. The algorithms have been tested using two different databases captured in real indoor environments under dynamic conditions.

  15. Multiscale Analysis of the Predictability of Stock Returns

    Directory of Open Access Journals (Sweden)

    Paweł Fiedor

    2015-06-01

    Full Text Available Due to the strong complexity of financial markets, economics does not have a unified theory of price formation in financial markets. The most common assumption is the Efficient-Market Hypothesis, which has been attacked by a number of researchers, using different tools. There were varying degrees to which these tools complied with the formal definitions of efficiency and predictability. In our earlier work, we analysed the predictability of stock returns at two time scales using the entropy rate, which can be directly linked to the mathematical definition of predictability. Nonetheless, none of the above-mentioned studies allow any general understanding of how the financial markets work, beyond disproving the Efficient-Market Hypothesis. In our previous study, we proposed the Maximum Entropy Production Principle, which uses the entropy rate to create a general principle underlying the price formation processes. Both of these studies show that the predictability of price changes is higher at the transaction level intraday scale than the scale of daily returns, but ignore all scales in between. In this study we extend these ideas using the multiscale entropy analysis framework to enhance our understanding of the predictability of price formation processes at various time scales.

  16. Multiscale Analysis of Head Impacts in Contact Sports

    Science.gov (United States)

    Guttag, Mark; Sett, Subham; Franck, Jennifer; McNamara, Kyle; Bar-Kochba, Eyal; Crisco, Joseph; Blume, Janet; Franck, Christian

    2012-02-01

    Traumatic brain injury (TBI) is one of the world's major causes of death and disability. To aid companies in designing safer and improved protective gear and to aid the medical community in producing improved quantitative TBI diagnosis and assessment tools, a multiscale finite element model of the human brain, head and neck is being developed. Recorded impact data from football and hockey helmets instrumented with accelerometers are compared to simulated impact data in the laboratory. Using data from these carefully constructed laboratory experiments, we can quantify impact location, magnitude, and linear and angular accelerations of the head. The resultant forces and accelerations are applied to a fully meshed head-form created from MRI data by Simpleware. With appropriate material properties for each region of the head-form, the Abaqus finite element model can determine the stresses, strains, and deformations in the brain. Simultaneously, an in-vitro cellular TBI criterion is being developed to be incorporated into Abaqus models for the brain. The cell-based injury criterion functions the same way that damage criteria for metals and other materials are used to predict failure in structural materials.

  17. Physics-based hybrid method for multiscale transport in porous media

    Science.gov (United States)

    Yousefzadeh, Mehrdad; Battiato, Ilenia

    2017-09-01

    Despite advancements in the development of multiscale models for flow and reactive transport in porous media, the accurate, efficient and physics-based coupling of multiple scales in hybrid models remains a major theoretical and computational challenge. Improving the predictivity of macroscale predictions by means of multiscale algorithms relative to classical at-scale models is the primary motivation for the development of multiscale simulators. Yet, very few are the quantitative studies that explicitly address the predictive capability of multiscale coupling algorithms as it is still generally not possible to have a priori estimates of the errors that are present when complex flow processes are modeled. We develop a nonintrusive pore-/continuum-scale hybrid model whose coupling error is bounded by the upscaling error, i.e. we build a predictive tightly coupled multiscale scheme. This is accomplished by slightly enlarging the subdomain where continuum-scale equations are locally invalid and analytically defining physics-based coupling conditions at the interfaces separating the two computational sub-domains, while enforcing state variable and flux continuity. The proposed multiscale coupling approach retains the advantages of domain decomposition approaches, including the use of existing solvers for each subdomain, while it gains flexibility in the choice of the numerical discretization method and maintains the coupling errors bounded by the upscaling error. We implement the coupling in finite volumes and test the proposed method by modeling flow and transport through a reactive channel and past an array of heterogeneously reactive cylinders.

  18. Generalized composite multiscale permutation entropy and Laplacian score based rolling bearing fault diagnosis

    Science.gov (United States)

    Zheng, Jinde; Pan, Haiyang; Yang, Shubao; Cheng, Junsheng

    2018-01-01

    Multiscale permutation entropy (MPE) is a recently proposed nonlinear dynamic method for measuring the randomness and detecting the nonlinear dynamic change of time series and can be used effectively to extract the nonlinear dynamic fault feature from vibration signals of rolling bearing. To solve the drawback of coarse graining process in MPE, an improved MPE method called generalized composite multiscale permutation entropy (GCMPE) was proposed in this paper. Also the influence of parameters on GCMPE and its comparison with the MPE are studied by analyzing simulation data. GCMPE was applied to the fault feature extraction from vibration signal of rolling bearing and then based on the GCMPE, Laplacian score for feature selection and the Particle swarm optimization based support vector machine, a new fault diagnosis method for rolling bearing was put forward in this paper. Finally, the proposed method was applied to analyze the experimental data of rolling bearing. The analysis results show that the proposed method can effectively realize the fault diagnosis of rolling bearing and has a higher fault recognition rate than the existing methods.

  19. Multiscale entropy based study of the pathological time series

    International Nuclear Information System (INIS)

    Wang Jun; Ma Qianli

    2008-01-01

    This paper studies the multiscale entropy (MSE) of electrocardiogram's ST segment and compares the MSE results of ST segment with that of electrocardiogram in the first time. Electrocardiogram complexity changing characteristics has important clinical significance for early diagnosis. Study shows that the average MSE values and the varying scope fluctuation could be more effective to reveal the heart health status. Particularly the multiscale values varying scope fluctuation is a more sensitive parameter for early heart disease detection and has a clinical diagnostic significance. (general)

  20. Multi-scale analysis of lung computed tomography images

    CERN Document Server

    Gori, I; Fantacci, M E; Preite Martinez, A; Retico, A; De Mitri, I; Donadio, S; Fulcheri, C

    2007-01-01

    A computer-aided detection (CAD) system for the identification of lung internal nodules in low-dose multi-detector helical Computed Tomography (CT) images was developed in the framework of the MAGIC-5 project. The three modules of our lung CAD system, a segmentation algorithm for lung internal region identification, a multi-scale dot-enhancement filter for nodule candidate selection and a multi-scale neural technique for false positive finding reduction, are described. The results obtained on a dataset of low-dose and thin-slice CT scans are shown in terms of free response receiver operating characteristic (FROC) curves and discussed.

  1. Multiscale analysis of spreading in a large communication network

    International Nuclear Information System (INIS)

    Kivelä, Mikko; Pan, Raj Kumar; Kaski, Kimmo; Kertész, János; Saramäki, Jari; Karsai, Márton

    2012-01-01

    In temporal networks, both the topology of the underlying network and the timings of interaction events can be crucial in determining how a dynamic process mediated by the network unfolds. We have explored the limiting case of the speed of spreading in the SI model, set up such that an event between an infectious and a susceptible individual always transmits the infection. The speed of this process sets an upper bound for the speed of any dynamic process that is mediated through the interaction events of the network. With the help of temporal networks derived from large-scale time-stamped data on mobile phone calls, we extend earlier results that indicate the slowing-down effects of burstiness and temporal inhomogeneities. In such networks, links are not permanently active, but dynamic processes are mediated by recurrent events taking place on the links at specific points in time. We perform a multiscale analysis and pinpoint the importance of the timings of event sequences on individual links, their correlations with neighboring sequences, and the temporal pathways taken by the network-scale spreading process. This is achieved by studying empirically and analytically different characteristic relay times of links, relevant to the respective scales, and a set of temporal reference models that allow for removing selected time-domain correlations one by one. Our analysis shows that for the spreading velocity, time-domain inhomogeneities are as important as the network topology, which indicates the need to take time-domain information into account when studying spreading dynamics. In particular, results for the different characteristic relay times underline the importance of the burstiness of individual links

  2. Multi-scale and multi-orientation medical image analysis

    NARCIS (Netherlands)

    Haar Romenij, ter B.M.; Deserno, T.M.

    2011-01-01

    Inspired by multi-scale and multi-orientation mechanisms recognized in the first stages of our visual system, this chapter gives a tutorial overview of the basic principles. Images are discrete, measured data. The optimal aperture for an observation with as little artefacts as possible, is derived

  3. Multiscale Simulation Framework for Coupled Fluid Flow and Mechanical Deformation

    Energy Technology Data Exchange (ETDEWEB)

    Hou, Thomas [California Inst. of Technology (CalTech), Pasadena, CA (United States); Efendiev, Yalchin [Stanford Univ., CA (United States); Tchelepi, Hamdi [Texas A & M Univ., College Station, TX (United States); Durlofsky, Louis [Stanford Univ., CA (United States)

    2016-05-24

    Our work in this project is aimed at making fundamental advances in multiscale methods for flow and transport in highly heterogeneous porous media. The main thrust of this research is to develop a systematic multiscale analysis and efficient coarse-scale models that can capture global effects and extend existing multiscale approaches to problems with additional physics and uncertainties. A key emphasis is on problems without an apparent scale separation. Multiscale solution methods are currently under active investigation for the simulation of subsurface flow in heterogeneous formations. These procedures capture the effects of fine-scale permeability variations through the calculation of specialized coarse-scale basis functions. Most of the multiscale techniques presented to date employ localization approximations in the calculation of these basis functions. For some highly correlated (e.g., channelized) formations, however, global effects are important and these may need to be incorporated into the multiscale basis functions. Other challenging issues facing multiscale simulations are the extension of existing multiscale techniques to problems with additional physics, such as compressibility, capillary effects, etc. In our project, we explore the improvement of multiscale methods through the incorporation of additional (single-phase flow) information and the development of a general multiscale framework for flows in the presence of uncertainties, compressible flow and heterogeneous transport, and geomechanics. We have considered (1) adaptive local-global multiscale methods, (2) multiscale methods for the transport equation, (3) operator-based multiscale methods and solvers, (4) multiscale methods in the presence of uncertainties and applications, (5) multiscale finite element methods for high contrast porous media and their generalizations, and (6) multiscale methods for geomechanics.

  4. Multi codes and multi-scale analysis for void fraction prediction in hot channel for VVER-1000/V392

    International Nuclear Information System (INIS)

    Hoang Minh Giang; Hoang Tan Hung; Nguyen Huu Tiep

    2015-01-01

    Recently, an approach of multi codes and multi-scale analysis is widely applied to study core thermal hydraulic behavior such as void fraction prediction. Better results are achieved by using multi codes or coupling codes such as PARCS and RELAP5. The advantage of multi-scale analysis is zooming of the interested part in the simulated domain for detail investigation. Therefore, in this study, the multi codes between MCNP5, RELAP5, CTF and also the multi-scale analysis based RELAP5 and CTF are applied to investigate void fraction in hot channel of VVER-1000/V392 reactor. Since VVER-1000/V392 reactor is a typical advanced reactor that can be considered as the base to develop later VVER-1200 reactor, then understanding core behavior in transient conditions is necessary in order to investigate VVER technology. It is shown that the item of near wall boiling, Γ w in RELAP5 proposed by Lahey mechanistic method may not give enough accuracy of void fraction prediction as smaller scale code as CTF. (author)

  5. A case study on the influence of multiscale modelling in design and structural analysis

    DEFF Research Database (Denmark)

    Nicholas, Paul; Zwierzycki, Mateusz; La Magna, Riccardo

    2017-01-01

    . To illustrate the concept of multi-scale modelling, the prototype of a bridge structure that was realised making use of this information transfer between models will be presented. The prototype primarily takes advantage of the geometric and material stiffening effect of incremental metal forming. The local......The current paper discusses the role of multi-scale modelling within the context of design and structural analysis. Depending on the level of detail, a design model may retain, lose or enhance key information. The term multi-scale refers to the break-down of a design and analysis task into multiple...... levels of detail and the transfer of this information between models. Focusing on the influence that different models have on the analysed performance of the structure, the paper will discuss the advantages and trade-offs of coupling multiple levels of abstraction in terms of design and structure...

  6. A Posteriori Analysis of Adaptive Multiscale Operator Decomposition Methods for Multiphysics Problems

    Energy Technology Data Exchange (ETDEWEB)

    Donald Estep; Michael Holst; Simon Tavener

    2010-02-08

    This project was concerned with the accurate computational error estimation for numerical solutions of multiphysics, multiscale systems that couple different physical processes acting across a large range of scales relevant to the interests of the DOE. Multiscale, multiphysics models are characterized by intimate interactions between different physics across a wide range of scales. This poses significant computational challenges addressed by the proposal, including: (1) Accurate and efficient computation; (2) Complex stability; and (3) Linking different physics. The research in this project focused on Multiscale Operator Decomposition methods for solving multiphysics problems. The general approach is to decompose a multiphysics problem into components involving simpler physics over a relatively limited range of scales, and then to seek the solution of the entire system through some sort of iterative procedure involving solutions of the individual components. MOD is a very widely used technique for solving multiphysics, multiscale problems; it is heavily used throughout the DOE computational landscape. This project made a major advance in the analysis of the solution of multiscale, multiphysics problems.

  7. Multiscale Static Analysis of Notched and Unnotched Laminates Using the Generalized Method of Cells

    Science.gov (United States)

    Naghipour Ghezeljeh, Paria; Arnold, Steven M.; Pineda, Evan J.; Stier, Bertram; Hansen, Lucas; Bednarcyk, Brett A.; Waas, Anthony M.

    2016-01-01

    The generalized method of cells (GMC) is demonstrated to be a viable micromechanics tool for predicting the deformation and failure response of laminated composites, with and without notches, subjected to tensile and compressive static loading. Given the axial [0], transverse [90], and shear [+45/-45] response of a carbon/epoxy (IM7/977-3) system, the unnotched and notched behavior of three multidirectional layups (Layup 1: [0,45,90,-45](sub 2S), Layup 2: [0,60,0](sub 3S), and Layup 3: [30,60,90,-30, -60](sub 2S)) are predicted under both tensile and compressive static loading. Matrix nonlinearity is modeled in two ways. The first assumes all nonlinearity is due to anisotropic progressive damage of the matrix only, which is modeled, using the multiaxial mixed-mode continuum damage model (MMCDM) within GMC. The second utilizes matrix plasticity coupled with brittle final failure based on the maximum principle strain criteria to account for matrix nonlinearity and failure within the Finite Element Analysis--Micromechanics Analysis Code (FEAMAC) software multiscale framework. Both MMCDM and plasticity models incorporate brittle strain- and stress-based failure criteria for the fiber. Upon satisfaction of these criteria, the fiber properties are immediately reduced to a nominal value. The constitutive response for each constituent (fiber and matrix) is characterized using a combination of vendor data and the axial, transverse, and shear responses of unnotched laminates. Then, the capability of the multiscale methodology is assessed by performing blind predictions of the mentioned notched and unnotched composite laminates response under tensile and compressive loading. Tabulated data along with the detailed results (i.e., stress-strain curves as well as damage evolution states at various ratios of strain to failure) for all laminates are presented.

  8. Color Image Enhancement Using Multiscale Retinex Based on Particle Swarm Optimization Method

    Science.gov (United States)

    Matin, F.; Jeong, Y.; Kim, K.; Park, K.

    2018-01-01

    This paper introduces, a novel method for the image enhancement using multiscale retinex and practical swarm optimization. Multiscale retinex is widely used image enhancement technique which intemperately pertains on parameters such as Gaussian scales, gain and offset, etc. To achieve the privileged effect, the parameters need to be tuned manually according to the image. In order to handle this matter, a developed retinex algorithm based on PSO has been used. The PSO method adjusted the parameters for multiscale retinex with chromaticity preservation (MSRCP) attains better outcome to compare with other existing methods. The experimental result indicates that the proposed algorithm is an efficient one and not only provides true color loyalty in low light conditions but also avoid color distortion at the same time.

  9. Image classification using multiscale information fusion based on saliency driven nonlinear diffusion filtering.

    Science.gov (United States)

    Hu, Weiming; Hu, Ruiguang; Xie, Nianhua; Ling, Haibin; Maybank, Stephen

    2014-04-01

    In this paper, we propose saliency driven image multiscale nonlinear diffusion filtering. The resulting scale space in general preserves or even enhances semantically important structures such as edges, lines, or flow-like structures in the foreground, and inhibits and smoothes clutter in the background. The image is classified using multiscale information fusion based on the original image, the image at the final scale at which the diffusion process converges, and the image at a midscale. Our algorithm emphasizes the foreground features, which are important for image classification. The background image regions, whether considered as contexts of the foreground or noise to the foreground, can be globally handled by fusing information from different scales. Experimental tests of the effectiveness of the multiscale space for the image classification are conducted on the following publicly available datasets: 1) the PASCAL 2005 dataset; 2) the Oxford 102 flowers dataset; and 3) the Oxford 17 flowers dataset, with high classification rates.

  10. From the direct numerical simulation to system codes-perspective for the multi-scale analysis of LWR thermal hydraulics

    International Nuclear Information System (INIS)

    Bestion, D.

    2010-01-01

    A multi-scale analysis of water-cooled reactor thermal hydraulics can be used to take advantage of increased computer power and improved simulation tools, including Direct Numerical Simulation (DNS), Computational Fluid Dynamics (CFD) (in both open and porous mediums), and system thermalhydraulic codes. This paper presents a general strategy for this procedure for various thermalhydraulic scales. A short state of the art is given for each scale, and the role of the scale in the overall multi-scale analysis process is defined. System thermalhydraulic codes will remain a privileged tool for many investigations related to safety. CFD in porous medium is already being frequently used for core thermal hydraulics, either in 3D modules of system codes or in component codes. CFD in open medium allows zooming on some reactor components in specific situations, and may be coupled to the system and component scales. Various modeling approaches exist in the domain from DNS to CFD which may be used to improve the understanding of flow processes, and as a basis for developing more physically based models for macroscopic tools. A few examples are given to illustrate the multi-scale approach. Perspectives for the future are drawn from the present state of the art and directions for future research and development are given

  11. Multi-scale calculation based on dual domain material point method combined with molecular dynamics

    Energy Technology Data Exchange (ETDEWEB)

    Dhakal, Tilak Raj [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2017-02-27

    This dissertation combines the dual domain material point method (DDMP) with molecular dynamics (MD) in an attempt to create a multi-scale numerical method to simulate materials undergoing large deformations with high strain rates. In these types of problems, the material is often in a thermodynamically non-equilibrium state, and conventional constitutive relations are often not available. In this method, the closure quantities, such as stress, at each material point are calculated from a MD simulation of a group of atoms surrounding the material point. Rather than restricting the multi-scale simulation in a small spatial region, such as phase interfaces, or crack tips, this multi-scale method can be used to consider non-equilibrium thermodynamic e ects in a macroscopic domain. This method takes advantage that the material points only communicate with mesh nodes, not among themselves; therefore MD simulations for material points can be performed independently in parallel. First, using a one-dimensional shock problem as an example, the numerical properties of the original material point method (MPM), the generalized interpolation material point (GIMP) method, the convected particle domain interpolation (CPDI) method, and the DDMP method are investigated. Among these methods, only the DDMP method converges as the number of particles increases, but the large number of particles needed for convergence makes the method very expensive especially in our multi-scale method where we calculate stress in each material point using MD simulation. To improve DDMP, the sub-point method is introduced in this dissertation, which provides high quality numerical solutions with a very small number of particles. The multi-scale method based on DDMP with sub-points is successfully implemented for a one dimensional problem of shock wave propagation in a cerium crystal. The MD simulation to calculate stress in each material point is performed in GPU using CUDA to accelerate the

  12. Asymptotic Expansion Homogenization for Multiscale Nuclear Fuel Analysis

    International Nuclear Information System (INIS)

    2015-01-01

    Engineering scale nuclear fuel performance simulations can benefit by utilizing high-fidelity models running at a lower length scale. Lower length-scale models provide a detailed view of the material behavior that is used to determine the average material response at the macroscale. These lower length-scale calculations may provide insight into material behavior where experimental data is sparse or nonexistent. This multiscale approach is especially useful in the nuclear field, since irradiation experiments are difficult and expensive to conduct. The lower length-scale models complement the experiments by influencing the types of experiments required and by reducing the total number of experiments needed. This multiscale modeling approach is a central motivation in the development of the BISON-MARMOT fuel performance codes at Idaho National Laboratory. These codes seek to provide more accurate and predictive solutions for nuclear fuel behavior. One critical aspect of multiscale modeling is the ability to extract the relevant information from the lower length-scale sim- ulations. One approach, the asymptotic expansion homogenization (AEH) technique, has proven to be an effective method for determining homogenized material parameters. The AEH technique prescribes a system of equations to solve at the microscale that are used to compute homogenized material constants for use at the engineering scale. In this work, we employ AEH to explore the effect of evolving microstructural thermal conductivity and elastic constants on nuclear fuel performance. We show that the AEH approach fits cleanly into the BISON and MARMOT codes and provides a natural, multidimensional homogenization capability.

  13. Delineation of Urban Active Faults Using Multi-scale Gravity Analysis in Shenzhen, South China

    Science.gov (United States)

    Xu, C.; Liu, X.

    2015-12-01

    In fact, many cities in the world are established on the active faults. As the rapid urban development, thousands of large facilities, such as ultrahigh buildings, supersized bridges, railway, and so on, are built near or on the faults, which may change the balance of faults and induce urban earthquake. Therefore, it is significant to delineate effectively the faults for urban planning construction and social sustainable development. Due to dense buildings in urban area, the ordinary approaches to identify active faults, like geological survey, artificial seismic exploration and electromagnetic exploration, are not convenient to be carried out. Gravity, reflecting the mass distribution of the Earth's interior, provides a more efficient and convenient method to delineate urban faults. The present study is an attempt to propose a novel gravity method, multi-scale gravity analysis, for identifying urban active faults and determining their stability. Firstly, the gravity anomalies are decomposed by wavelet multi-scale analysis. Secondly, based on the decomposed gravity anomalies, the crust is layered and the multilayer horizontal tectonic stress is inverted. Lastly, the decomposed anomalies and the inverted horizontal tectonic stress are used to infer the distribution and stability of main active faults. For validating our method, a case study on active faults in Shenzhen City is processed. The results show that the distribution of decomposed gravity anomalies and multilayer horizontal tectonic stress are controlled significantly by the strike of the main faults and can be used to infer depths of the faults. The main faults in Shenzhen may range from 4km to 20km in the depth. Each layer of the crust is nearly equipressure since the horizontal tectonic stress has small amplitude. It indicates that the main faults in Shenzhen are relatively stable and have no serious impact on planning and construction of the city.

  14. Multi-Scale Factor Analysis of High-Dimensional Brain Signals

    KAUST Repository

    Ting, Chee-Ming; Ombao, Hernando; Salleh, Sh-Hussain

    2017-01-01

    In this paper, we develop an approach to modeling high-dimensional networks with a large number of nodes arranged in a hierarchical and modular structure. We propose a novel multi-scale factor analysis (MSFA) model which partitions the massive

  15. The set of prime numbers: Multiscale analysis and numeric accelerators

    International Nuclear Information System (INIS)

    Iovane, Gerardo

    2009-01-01

    In this work, we show that the prime numbers follow a multiscale distribution. Indeed they can be classified thanks to tree structures, which are expressed in terms of two maximal subsets of N and using multilayer selection rules, acting on these sets of prime candidates. Consequently, the prime numbers follow a specific deterministic rules. Indeed, a numeric accelerator for generating primes can be realized in terms of the above mentioned specific rules. From the comparison with the Fibonacci numbers a beautiful harmony comes in terms of the Golden Mean which is relevant to high energy physics and E-Infinity theory too.

  16. Sustainable Manufacturing via Multi-Scale, Physics-Based Process Modeling and Manufacturing-Informed Design

    Energy Technology Data Exchange (ETDEWEB)

    None

    2017-04-01

    This factsheet describes a project that developed and demonstrated a new manufacturing-informed design framework that utilizes advanced multi-scale, physics-based process modeling to dramatically improve manufacturing productivity and quality in machining operations while reducing the cost of machined components.

  17. Strain analysis of nanowire interfaces in multiscale composites

    Science.gov (United States)

    Malakooti, Mohammad H.; Zhou, Zhi; Spears, John H.; Shankwitz, Timothy J.; Sodano, Henry A.

    2016-04-01

    Recently, the reinforcement-matrix interface of fiber reinforced polymers has been modified through grafting nanostructures - particularly carbon nanotubes and ZnO nanowires - on to the fiber surface. This type of interface engineering has made a great impact on the development of multiscale composites that have high stiffness, interfacial strength, toughness, and vibrational damping - qualities that are mutually exclusive to a degree in most raw materials. Although the efficacy of such nanostructured interfaces has been established, the reinforcement mechanisms of these multiscale composites have not been explored. Here, strain transfer across a nanowire interphase is studied in order to gain a heightened understanding of the working principles of physical interface modification and the formation of a functional gradient. This problem is studied using a functionally graded piezoelectric interface composed of vertically aligned lead zirconate titanate nanowires, as their piezoelectric properties can be utilized to precisely control the strain on one side of the interface. The displacement and strain across the nanowire interface is captured using digital image correlation. It is demonstrated that the material gradient created through nanowires cause a smooth strain transfer from reinforcement phase into matrix phase that eliminates the stress concentration between these phases, which have highly mismatched elasticity.

  18. Revisiting of Multiscale Static Analysis of Notched Laminates Using the Generalized Method of Cells

    Science.gov (United States)

    Naghipour Ghezeljeh, Paria; Arnold, Steven M.; Pineda, Evan J.

    2016-01-01

    Composite material systems generally exhibit a range of behavior on different length scales (from constituent level to macro); therefore, a multiscale framework is beneficial for the design and engineering of these material systems. The complex nature of the observed composite failure during experiments suggests the need for a three-dimensional (3D) multiscale model to attain a reliable prediction. However, the size of a multiscale three-dimensional finite element model can become prohibitively large and computationally costly. Two-dimensional (2D) models are preferred due to computational efficiency, especially if many different configurations have to be analyzed for an in-depth damage tolerance and durability design study. In this study, various 2D and 3D multiscale analyses will be employed to conduct a detailed investigation into the tensile failure of a given multidirectional, notched carbon fiber reinforced polymer laminate. Threedimensional finite element analysis is typically considered more accurate than a 2D finite element model, as compared with experiments. Nevertheless, in the absence of adequate mesh refinement, large differences may be observed between a 2D and 3D analysis, especially for a shear-dominated layup. This observed difference has not been widely addressed in previous literature and is the main focus of this paper.

  19. Framework for adaptive multiscale analysis of nonhomogeneous point processes.

    Science.gov (United States)

    Helgason, Hannes; Bartroff, Jay; Abry, Patrice

    2011-01-01

    We develop the methodology for hypothesis testing and model selection in nonhomogeneous Poisson processes, with an eye toward the application of modeling and variability detection in heart beat data. Modeling the process' non-constant rate function using templates of simple basis functions, we develop the generalized likelihood ratio statistic for a given template and a multiple testing scheme to model-select from a family of templates. A dynamic programming algorithm inspired by network flows is used to compute the maximum likelihood template in a multiscale manner. In a numerical example, the proposed procedure is nearly as powerful as the super-optimal procedures that know the true template size and true partition, respectively. Extensions to general history-dependent point processes is discussed.

  20. ANALYSIS/MODEL COVER SHEET, MULTISCALE THERMOHYDROLOGIC MODEL

    International Nuclear Information System (INIS)

    Buscheck, T.A.

    2001-01-01

    The purpose of the Multiscale Thermohydrologic Model (MSTHM) is to describe the thermohydrologic evolution of the near-field environment (NFE) and engineered barrier system (EBS) throughout the potential high-level nuclear waste repository at Yucca Mountain for a particular engineering design (CRWMS M andO 2000c). The process-level model will provide thermohydrologic (TH) information and data (such as in-drift temperature, relative humidity, liquid saturation, etc.) for use in other technical products. This data is provided throughout the entire repository area as a function of time. The MSTHM couples the Smeared-heat-source Drift-scale Thermal-conduction (SDT), Line-average-heat-source Drift-scale Thermohydrologic (LDTH), Discrete-heat-source Drift-scale Thermal-conduction (DDT), and Smeared-heat-source Mountain-scale Thermal-conduction (SMT) submodels such that the flow of water and water vapor through partially-saturated fractured rock is considered. The MSTHM accounts for 3-D drift-scale and mountain-scale heat flow, repository-scale variability of stratigraphy and infiltration flux, and waste package (WP)-to-WP variability in heat output from WPs. All submodels use the nonisothermal unsaturated-saturated flow and transport (NUFT) simulation code. The MSTHM is implemented in several data-processing steps. The four major steps are: (1) submodel input-file preparation, (2) execution of the four submodel families with the use of the NUFT code, (3) execution of the multiscale thermohydrologic abstraction code (MSTHAC), and (4) binning and post-processing (i.e., graphics preparation) of the output from MSTHAC. Section 6 describes the MSTHM in detail. The objectives of this Analyses and Model Report (AMR) are to investigate near field (NF) and EBS thermohydrologic environments throughout the repository area at various evolution periods, and to provide TH data that may be used in other process model reports

  1. 3D deblending of simultaneous source data based on 3D multi-scale shaping operator

    Science.gov (United States)

    Zu, Shaohuan; Zhou, Hui; Mao, Weijian; Gong, Fei; Huang, Weilin

    2018-04-01

    We propose an iterative three-dimensional (3D) deblending scheme using 3D multi-scale shaping operator to separate 3D simultaneous source data. The proposed scheme is based on the property that signal is coherent, whereas interference is incoherent in some domains, e.g., common receiver domain and common midpoint domain. In two-dimensional (2D) blended record, the coherency difference of signal and interference is in only one spatial direction. Compared with 2D deblending, the 3D deblending can take more sparse constraints into consideration to obtain better performance, e.g., in 3D common receiver gather, the coherency difference is in two spatial directions. Furthermore, with different levels of coherency, signal and interference distribute in different scale curvelet domains. In both 2D and 3D blended records, most coherent signal locates in coarse scale curvelet domain, while most incoherent interference distributes in fine scale curvelet domain. The scale difference is larger in 3D deblending, thus, we apply the multi-scale shaping scheme to further improve the 3D deblending performance. We evaluate the performance of 3D and 2D deblending with the multi-scale and global shaping operators, respectively. One synthetic and one field data examples demonstrate the advantage of the 3D deblending with 3D multi-scale shaping operator.

  2. Scale-specific effects: A report on multiscale analysis of acupunctured EEG in entropy and power

    Science.gov (United States)

    Song, Zhenxi; Deng, Bin; Wei, Xile; Cai, Lihui; Yu, Haitao; Wang, Jiang; Wang, Ruofan; Chen, Yingyuan

    2018-02-01

    Investigating acupuncture effects contributes to improving clinical application and understanding neuronal dynamics under external stimulation. In this report, we recorded electroencephalography (EEG) signals evoked by acupuncture at ST36 acupoint with three stimulus frequencies of 50, 100 and 200 times per minutes, and selected non-acupuncture EEGs as the control group. Multiscale analyses were introduced to investigate the possible acupuncture effects on complexity and power in multiscale level. Using multiscale weighted-permutation entropy, we found the significant effects on increased complexity degree in EEG signals induced by acupuncture. The comparison of three stimulation manipulations showed that 100 times/min generated most obvious effects, and affected most cortical regions. By estimating average power spectral density, we found decreased power induced by acupuncture. The joint distribution of entropy and power indicated an inverse correlation, and this relationship was weakened by acupuncture effects, especially under the manipulation of 100 times/min frequency. Above findings are more evident and stable in large scales than small scales, which suggests that multiscale analysis allows evaluating significant effects in specific scale and enables to probe the inherent characteristics underlying physiological signals.

  3. Multiscale Retinex

    Directory of Open Access Journals (Sweden)

    Ana Belén Petro

    2014-04-01

    Full Text Available While the retinex theory aimed at explaining human color perception, its derivations have led to efficient algorithms enhancing local image contrast, thus permitting among other features, to "see in the shadows". Among these derived algorithms, Multiscale Retinex is probably the most successful center-surround image filter. In this paper, we offer an analysis and implementation of Multiscale Retinex. We point out and resolve some ambiguities of the method. In particular, we show that the important color correction final step of the method can be seriously improved. This analysis permits to come up with an automatic implementation of Multiscale Retinex which is as faithful as possible to the one described in the original paper. Overall, this implementation delivers excellent results and confirms the validity of Multiscale Retinex for image color restoration and contrast enhancement. Nevertheless, while the method parameters can be fixed, we show that a crucial choice must be left to the user, depending on the lightning condition of the image: the method must either be applied to each color independently if a color balance is required, or to the luminance only if the goal is to achieve local contrast enhancement. Thus, we propose two slightly different algorithms to deal with both cases.

  4. Network analysis reveals multiscale controls on streamwater chemistry

    Science.gov (United States)

    Kevin J. McGuire; Christian E. Torgersen; Gene E. Likens; Donald C. Buso; Winsor H. Lowe; Scott W. Bailey

    2014-01-01

    By coupling synoptic data from a basin-wide assessment of streamwater chemistry with network-based geostatistical analysis, we show that spatial processes differentially affect biogeochemical condition and pattern across a headwater stream network. We analyzed a high-resolution dataset consisting of 664 water samples collected every 100 m throughout 32 tributaries in...

  5. Validating Remotely Sensed Land Surface Evapotranspiration Based on Multi-scale Field Measurements

    Science.gov (United States)

    Jia, Z.; Liu, S.; Ziwei, X.; Liang, S.

    2012-12-01

    The land surface evapotranspiration plays an important role in the surface energy balance and the water cycle. There have been significant technical and theoretical advances in our knowledge of evapotranspiration over the past two decades. Acquisition of the temporally and spatially continuous distribution of evapotranspiration using remote sensing technology has attracted the widespread attention of researchers and managers. However, remote sensing technology still has many uncertainties coming from model mechanism, model inputs, parameterization schemes, and scaling issue in the regional estimation. Achieving remotely sensed evapotranspiration (RS_ET) with confident certainty is required but difficult. As a result, it is indispensable to develop the validation methods to quantitatively assess the accuracy and error sources of the regional RS_ET estimations. This study proposes an innovative validation method based on multi-scale evapotranspiration acquired from field measurements, with the validation results including the accuracy assessment, error source analysis, and uncertainty analysis of the validation process. It is a potentially useful approach to evaluate the accuracy and analyze the spatio-temporal properties of RS_ET at both the basin and local scales, and is appropriate to validate RS_ET in diverse resolutions at different time-scales. An independent RS_ET validation using this method was presented over the Hai River Basin, China in 2002-2009 as a case study. Validation at the basin scale showed good agreements between the 1 km annual RS_ET and the validation data such as the water balanced evapotranspiration, MODIS evapotranspiration products, precipitation, and landuse types. Validation at the local scale also had good results for monthly, daily RS_ET at 30 m and 1 km resolutions, comparing to the multi-scale evapotranspiration measurements from the EC and LAS, respectively, with the footprint model over three typical landscapes. Although some

  6. Multiscale analysis of restoration priorities for marine shoreline planning.

    Science.gov (United States)

    Diefenderfer, Heida L; Sobocinski, Kathryn L; Thom, Ronald M; May, Christopher W; Borde, Amy B; Southard, Susan L; Vavrinec, John; Sather, Nichole K

    2009-10-01

    Planners are being called on to prioritize marine shorelines for conservation status and restoration action. This study documents an approach to determining the management strategy most likely to succeed based on current conditions at local and landscape scales. The conceptual framework based in restoration ecology pairs appropriate restoration strategies with sites based on the likelihood of producing long-term resilience given the condition of ecosystem structures and processes at three scales: the shorezone unit (site), the drift cell reach (nearshore marine landscape), and the watershed (terrestrial landscape). The analysis is structured by a conceptual ecosystem model that identifies anthropogenic impacts on targeted ecosystem functions. A scoring system, weighted by geomorphic class, is applied to available spatial data for indicators of stress and function using geographic information systems. This planning tool augments other approaches to prioritizing restoration, including historical conditions and change analysis and ecosystem valuation.

  7. Multiscale image analysis reveals structural heterogeneity of the cell microenvironment in homotypic spheroids.

    Science.gov (United States)

    Schmitz, Alexander; Fischer, Sabine C; Mattheyer, Christian; Pampaloni, Francesco; Stelzer, Ernst H K

    2017-03-03

    Three-dimensional multicellular aggregates such as spheroids provide reliable in vitro substitutes for tissues. Quantitative characterization of spheroids at the cellular level is fundamental. We present the first pipeline that provides three-dimensional, high-quality images of intact spheroids at cellular resolution and a comprehensive image analysis that completes traditional image segmentation by algorithms from other fields. The pipeline combines light sheet-based fluorescence microscopy of optically cleared spheroids with automated nuclei segmentation (F score: 0.88) and concepts from graph analysis and computational topology. Incorporating cell graphs and alpha shapes provided more than 30 features of individual nuclei, the cellular neighborhood and the spheroid morphology. The application of our pipeline to a set of breast carcinoma spheroids revealed two concentric layers of different cell density for more than 30,000 cells. The thickness of the outer cell layer depends on a spheroid's size and varies between 50% and 75% of its radius. In differently-sized spheroids, we detected patches of different cell densities ranging from 5 × 10 5 to 1 × 10 6  cells/mm 3 . Since cell density affects cell behavior in tissues, structural heterogeneities need to be incorporated into existing models. Our image analysis pipeline provides a multiscale approach to obtain the relevant data for a system-level understanding of tissue architecture.

  8. How next-generation sequencing and multiscale data analysis will transform infectious disease management.

    Science.gov (United States)

    Pak, Theodore R; Kasarskis, Andrew

    2015-12-01

    Recent reviews have examined the extent to which routine next-generation sequencing (NGS) on clinical specimens will improve the capabilities of clinical microbiology laboratories in the short term, but do not explore integrating NGS with clinical data from electronic medical records (EMRs), immune profiling data, and other rich datasets to create multiscale predictive models. This review introduces a range of "omics" and patient data sources relevant to managing infections and proposes 3 potentially disruptive applications for these data in the clinical workflow. The combined threats of healthcare-associated infections and multidrug-resistant organisms may be addressed by multiscale analysis of NGS and EMR data that is ideally updated and refined over time within each healthcare organization. Such data and analysis should form the cornerstone of future learning health systems for infectious disease. © The Author 2015. Published by Oxford University Press on behalf of the Infectious Diseases Society of America.

  9. Changes in the Complexity of Heart Rate Variability with Exercise Training Measured by Multiscale Entropy-Based Measurements

    Directory of Open Access Journals (Sweden)

    Frederico Sassoli Fazan

    2018-01-01

    Full Text Available Quantifying complexity from heart rate variability (HRV series is a challenging task, and multiscale entropy (MSE, along with its variants, has been demonstrated to be one of the most robust approaches to achieve this goal. Although physical training is known to be beneficial, there is little information about the long-term complexity changes induced by the physical conditioning. The present study aimed to quantify the changes in physiological complexity elicited by physical training through multiscale entropy-based complexity measurements. Rats were subject to a protocol of medium intensity training ( n = 13 or a sedentary protocol ( n = 12 . One-hour HRV series were obtained from all conscious rats five days after the experimental protocol. We estimated MSE, multiscale dispersion entropy (MDE and multiscale SDiff q from HRV series. Multiscale SDiff q is a recent approach that accounts for entropy differences between a given time series and its shuffled dynamics. From SDiff q , three attributes (q-attributes were derived, namely SDiff q m a x , q m a x and q z e r o . MSE, MDE and multiscale q-attributes presented similar profiles, except for SDiff q m a x . q m a x showed significant differences between trained and sedentary groups on Time Scales 6 to 20. Results suggest that physical training increases the system complexity and that multiscale q-attributes provide valuable information about the physiological complexity.

  10. Classification of high resolution imagery based on fusion of multiscale texture features

    International Nuclear Information System (INIS)

    Liu, Jinxiu; Liu, Huiping; Lv, Ying; Xue, Xiaojuan

    2014-01-01

    In high resolution data classification process, combining texture features with spectral bands can effectively improve the classification accuracy. However, the window size which is difficult to choose is regarded as an important factor influencing overall classification accuracy in textural classification and current approaches to image texture analysis only depend on a single moving window which ignores different scale features of various land cover types. In this paper, we propose a new method based on the fusion of multiscale texture features to overcome these problems. The main steps in new method include the classification of fixed window size spectral/textural images from 3×3 to 15×15 and comparison of all the posterior possibility values for every pixel, as a result the biggest probability value is given to the pixel and the pixel belongs to a certain land cover type automatically. The proposed approach is tested on University of Pavia ROSIS data. The results indicate that the new method improve the classification accuracy compared to results of methods based on fixed window size textural classification

  11. Multi-scale dynamical analysis (MSDA) of sea level records versus PDO, AMO, and NAO indexes

    OpenAIRE

    Scafetta, Nicola

    2013-01-01

    Herein I propose a multi-scale dynamical analysis to facilitate the physical interpretation of tide gauge records. The technique uses graphical diagrams. It is applied to six secular-long tide gauge records representative of the world oceans: Sydney, Pacific coast of Australia; Fremantle, Indian Ocean coast of Australia; New York City, Atlantic coast of USA; Honolulu, U.S. state of Hawaii; San Diego, U.S. state of California; and Venice, Mediterranean Sea, Italy. For comparison, an equivalent...

  12. Multiscale methods coupling atomistic and continuum mechanics: analysis of a simple case

    OpenAIRE

    Blanc , Xavier; Le Bris , Claude; Legoll , Frédéric

    2007-01-01

    International audience; The description and computation of fine scale localized phenomena arising in a material (during nanoindentation, for instance) is a challenging problem that has given birth to many multiscale methods. In this work, we propose an analysis of a simple one-dimensional method that couples two scales, the atomistic one and the continuum mechanics one. The method includes an adaptive criterion in order to split the computational domain into two subdomains, that are described...

  13. Multiscale Distance Coherence Vector Algorithm for Content-Based Image Retrieval

    Science.gov (United States)

    Jiexian, Zeng; Xiupeng, Liu

    2014-01-01

    Multiscale distance coherence vector algorithm for content-based image retrieval (CBIR) is proposed due to the same descriptor with different shapes and the shortcomings of antinoise performance of the distance coherence vector algorithm. By this algorithm, the image contour curve is evolved by Gaussian function first, and then the distance coherence vector is, respectively, extracted from the contour of the original image and evolved images. Multiscale distance coherence vector was obtained by reasonable weight distribution of the distance coherence vectors of evolved images contour. This algorithm not only is invariable to translation, rotation, and scaling transformation but also has good performance of antinoise. The experiment results show us that the algorithm has a higher recall rate and precision rate for the retrieval of images polluted by noise. PMID:24883416

  14. An infrared small target detection method based on multiscale local homogeneity measure

    Science.gov (United States)

    Nie, Jinyan; Qu, Shaocheng; Wei, Yantao; Zhang, Liming; Deng, Lizhen

    2018-05-01

    Infrared (IR) small target detection plays an important role in the field of image detection area owing to its intrinsic characteristics. This paper presents a multiscale local homogeneity measure (MLHM) for infrared small target detection, which can enhance the performance of IR small target detection system. Firstly, intra-patch homogeneity of the target itself and the inter-patch heterogeneity between target and the local background regions are integrated to enhance the significant of small target. Secondly, a multiscale measure based on local regions is proposed to obtain the most appropriate response. Finally, an adaptive threshold method is applied to small target segmentation. Experimental results on three different scenarios indicate that the MLHM has good performance under the interference of strong noise.

  15. Multi-Scale Pixel-Based Image Fusion Using Multivariate Empirical Mode Decomposition

    Directory of Open Access Journals (Sweden)

    Naveed ur Rehman

    2015-05-01

    Full Text Available A novel scheme to perform the fusion of multiple images using the multivariate empirical mode decomposition (MEMD algorithm is proposed. Standard multi-scale fusion techniques make a priori assumptions regarding input data, whereas standard univariate empirical mode decomposition (EMD-based fusion techniques suffer from inherent mode mixing and mode misalignment issues, characterized respectively by either a single intrinsic mode function (IMF containing multiple scales or the same indexed IMFs corresponding to multiple input images carrying different frequency information. We show that MEMD overcomes these problems by being fully data adaptive and by aligning common frequency scales from multiple channels, thus enabling their comparison at a pixel level and subsequent fusion at multiple data scales. We then demonstrate the potential of the proposed scheme on a large dataset of real-world multi-exposure and multi-focus images and compare the results against those obtained from standard fusion algorithms, including the principal component analysis (PCA, discrete wavelet transform (DWT and non-subsampled contourlet transform (NCT. A variety of image fusion quality measures are employed for the objective evaluation of the proposed method. We also report the results of a hypothesis testing approach on our large image dataset to identify statistically-significant performance differences.

  16. Multiscale analysis of the correlation of processing parameters on viscidity of composites fabricated by automated fiber placement

    Science.gov (United States)

    Han, Zhenyu; Sun, Shouzheng; Fu, Yunzhong; Fu, Hongya

    2017-10-01

    Viscidity is an important physical indicator for assessing fluidity of resin that is beneficial to contact resin with the fibers effectively and reduce manufacturing defects during automated fiber placement (AFP) process. However, the effect of processing parameters on viscidity evolution is rarely studied during AFP process. In this paper, viscidities under different scales are analyzed based on multi-scale analysis method. Firstly, viscous dissipation energy (VDE) within meso-unit under different processing parameters is assessed by using finite element method (FEM). According to multi-scale energy transfer model, meso-unit energy is used as the boundary condition for microscopic analysis. Furthermore, molecular structure of micro-system is built by molecular dynamics (MD) method. And viscosity curves are then obtained by integrating stress autocorrelation function (SACF) with time. Finally, the correlation characteristics of processing parameters to viscosity are revealed by using gray relational analysis method (GRAM). A group of processing parameters is found out to achieve the stability of viscosity and better fluidity of resin.

  17. Multi-scale analysis of deformation behavior at SCC crack tip (2). (Contract research)

    International Nuclear Information System (INIS)

    Kaji, Yoshiyuki; Miwa, Yukio; Tsukada, Takashi; Hayakawa, Masao; Nagashima, Nobuo

    2007-03-01

    This report describes a result of the research conducted by the Japan Atomic Energy Agency and the National Institute for Materials Science under contract with Japan Nuclear Energy Safety Organization (JNES) that was concerned with a multi-scale analysis of plastic deformation behavior at the crack tip of stress corrosion cracking (SCC). The research was carried out to evaluate the validity of the SCC growth data acquired in the intergranular SCC (IGSCC) project based on a mechanistic understanding of SCC. For the purpose, in this research, analyses of the plastic deformation behavior and microstructure around the crack tip were performed in a nano-order scale. The hardness measured in nano, meso and macro scales was employed as a common index of the strength, and the essential data necessary to understand the SCC propagation behavior were acquired and analyzed that are mainly a size of plastic deformation region and a microstructural information in the region, e.g. data of crystallografy, microscopic deformation and dislocations at the inside of grains and grain boundaries. In this year, we analyzed the state of plastic deformation region at the crack tip of IGSCC under various conditions and investigated relationship between crack growth behavior and stress intensity factor. Especially, we investigated in detail about two different hardened specimens used in the SCC growth tests in the IGSCC project. (J.P.N.)

  18. An automated multi-scale network-based scheme for detection and location of seismic sources

    Science.gov (United States)

    Poiata, N.; Aden-Antoniow, F.; Satriano, C.; Bernard, P.; Vilotte, J. P.; Obara, K.

    2017-12-01

    We present a recently developed method - BackTrackBB (Poiata et al. 2016) - allowing to image energy radiation from different seismic sources (e.g., earthquakes, LFEs, tremors) in different tectonic environments using continuous seismic records. The method exploits multi-scale frequency-selective coherence in the wave field, recorded by regional seismic networks or local arrays. The detection and location scheme is based on space-time reconstruction of the seismic sources through an imaging function built from the sum of station-pair time-delay likelihood functions, projected onto theoretical 3D time-delay grids. This imaging function is interpreted as the location likelihood of the seismic source. A signal pre-processing step constructs a multi-band statistical representation of the non stationary signal, i.e. time series, by means of higher-order statistics or energy envelope characteristic functions. Such signal-processing is designed to detect in time signal transients - of different scales and a priori unknown predominant frequency - potentially associated with a variety of sources (e.g., earthquakes, LFE, tremors), and to improve the performance and the robustness of the detection-and-location location step. The initial detection-location, based on a single phase analysis with the P- or S-phase only, can then be improved recursively in a station selection scheme. This scheme - exploiting the 3-component records - makes use of P- and S-phase characteristic functions, extracted after a polarization analysis of the event waveforms, and combines the single phase imaging functions with the S-P differential imaging functions. The performance of the method is demonstrated here in different tectonic environments: (1) analysis of the one year long precursory phase of 2014 Iquique earthquake in Chile; (2) detection and location of tectonic tremor sources and low-frequency earthquakes during the multiple episodes of tectonic tremor activity in southwestern Japan.

  19. Multi-scale sustainability assessments for biomass-based and coal-based fuels in China.

    Science.gov (United States)

    Man, Yi; Xiao, Honghua; Cai, Wei; Yang, Siyu

    2017-12-01

    Transportation liquid fuels production is heavily depend on oil. In recent years, developing biomass based and coal based fuels are regarded as promising alternatives for non-petroleum based fuels in China. With the rapid growth of constructing and planning b biomass based and coal based fuels production projects, sustainability assessments are needed to simultaneously consider the resource, the economic, and the environmental factors. This paper performs multi-scale analyses on the biomass based and coal based fuels in China. The production cost, life cycle cost, and ecological life cycle cost (ELCC) of these synfuels are investigated to compare their pros to cons and reveal the sustainability. The results show that BTL fuels has high production cost. It lacks of economic attractiveness. However, insignificant resource cost and environmental cost lead to a substantially lower ELCC, which may indicate better ecological sustainability. CTL fuels, on the contrary, is lower in production cost and reliable for economic benefit. But its coal consumption and pollutant emissions are both serious, leading to overwhelming resource cost and environmental cost. A shifting from petroleum to CTL fuels could double the ELCC, posing great threat to the sustainability of the entire fuels industry. Copyright © 2017 Elsevier B.V. All rights reserved.

  20. Intelligent Fault Diagnosis of Rotary Machinery Based on Unsupervised Multiscale Representation Learning

    Science.gov (United States)

    Jiang, Guo-Qian; Xie, Ping; Wang, Xiao; Chen, Meng; He, Qun

    2017-11-01

    The performance of traditional vibration based fault diagnosis methods greatly depends on those handcrafted features extracted using signal processing algorithms, which require significant amounts of domain knowledge and human labor, and do not generalize well to new diagnosis domains. Recently, unsupervised representation learning provides an alternative promising solution to feature extraction in traditional fault diagnosis due to its superior learning ability from unlabeled data. Given that vibration signals usually contain multiple temporal structures, this paper proposes a multiscale representation learning (MSRL) framework to learn useful features directly from raw vibration signals, with the aim to capture rich and complementary fault pattern information at different scales. In our proposed approach, a coarse-grained procedure is first employed to obtain multiple scale signals from an original vibration signal. Then, sparse filtering, a newly developed unsupervised learning algorithm, is applied to automatically learn useful features from each scale signal, respectively, and then the learned features at each scale to be concatenated one by one to obtain multiscale representations. Finally, the multiscale representations are fed into a supervised classifier to achieve diagnosis results. Our proposed approach is evaluated using two different case studies: motor bearing and wind turbine gearbox fault diagnosis. Experimental results show that the proposed MSRL approach can take full advantages of the availability of unlabeled data to learn discriminative features and achieved better performance with higher accuracy and stability compared to the traditional approaches.

  1. A Comprehensive Analysis of Multiscale Field-Aligned Currents: Characteristics, Controlling Parameters, and Relationships

    Science.gov (United States)

    McGranaghan, Ryan M.; Mannucci, Anthony J.; Forsyth, Colin

    2017-12-01

    We explore the characteristics, controlling parameters, and relationships of multiscale field-aligned currents (FACs) using a rigorous, comprehensive, and cross-platform analysis. Our unique approach combines FAC data from the Swarm satellites and the Advanced Magnetosphere and Planetary Electrodynamics Response Experiment (AMPERE) to create a database of small-scale (˜10-150 km, 250 km) FACs. We examine these data for the repeatable behavior of FACs across scales (i.e., the characteristics), the dependence on the interplanetary magnetic field orientation, and the degree to which each scale "departs" from nominal large-scale specification. We retrieve new information by utilizing magnetic latitude and local time dependence, correlation analyses, and quantification of the departure of smaller from larger scales. We find that (1) FACs characteristics and dependence on controlling parameters do not map between scales in a straight forward manner, (2) relationships between FAC scales exhibit local time dependence, and (3) the dayside high-latitude region is characterized by remarkably distinct FAC behavior when analyzed at different scales, and the locations of distinction correspond to "anomalous" ionosphere-thermosphere behavior. Comparing with nominal large-scale FACs, we find that differences are characterized by a horseshoe shape, maximizing across dayside local times, and that difference magnitudes increase when smaller-scale observed FACs are considered. We suggest that both new physics and increased resolution of models are required to address the multiscale complexities. We include a summary table of our findings to provide a quick reference for differences between multiscale FACs.

  2. Non-linear multivariate and multiscale monitoring and signal denoising strategy using Kernel Principal Component Analysis combined with Ensemble Empirical Mode Decomposition method

    Science.gov (United States)

    Žvokelj, Matej; Zupan, Samo; Prebil, Ivan

    2011-10-01

    The article presents a novel non-linear multivariate and multiscale statistical process monitoring and signal denoising method which combines the strengths of the Kernel Principal Component Analysis (KPCA) non-linear multivariate monitoring approach with the benefits of Ensemble Empirical Mode Decomposition (EEMD) to handle multiscale system dynamics. The proposed method which enables us to cope with complex even severe non-linear systems with a wide dynamic range was named the EEMD-based multiscale KPCA (EEMD-MSKPCA). The method is quite general in nature and could be used in different areas for various tasks even without any really deep understanding of the nature of the system under consideration. Its efficiency was first demonstrated by an illustrative example, after which the applicability for the task of bearing fault detection, diagnosis and signal denosing was tested on simulated as well as actual vibration and acoustic emission (AE) signals measured on purpose-built large-size low-speed bearing test stand. The positive results obtained indicate that the proposed EEMD-MSKPCA method provides a promising tool for tackling non-linear multiscale data which present a convolved picture of many events occupying different regions in the time-frequency plane.

  3. Multiscale Computing with the Multiscale Modeling Library and Runtime Environment

    NARCIS (Netherlands)

    Borgdorff, J.; Mamonski, M.; Bosak, B.; Groen, D.; Ben Belgacem, M.; Kurowski, K.; Hoekstra, A.G.

    2013-01-01

    We introduce a software tool to simulate multiscale models: the Multiscale Coupling Library and Environment 2 (MUSCLE 2). MUSCLE 2 is a component-based modeling tool inspired by the multiscale modeling and simulation framework, with an easy-to-use API which supports Java, C++, C, and Fortran. We

  4. Self-consistent clustering analysis: an efficient multiscale scheme for inelastic heterogeneous materials

    Energy Technology Data Exchange (ETDEWEB)

    Liu, Z.; Bessa, M. A.; Liu, W.K.

    2017-10-25

    A predictive computational theory is shown for modeling complex, hierarchical materials ranging from metal alloys to polymer nanocomposites. The theory can capture complex mechanisms such as plasticity and failure that span across multiple length scales. This general multiscale material modeling theory relies on sound principles of mathematics and mechanics, and a cutting-edge reduced order modeling method named self-consistent clustering analysis (SCA) [Zeliang Liu, M.A. Bessa, Wing Kam Liu, “Self-consistent clustering analysis: An efficient multi-scale scheme for inelastic heterogeneous materials,” Comput. Methods Appl. Mech. Engrg. 306 (2016) 319–341]. SCA reduces by several orders of magnitude the computational cost of micromechanical and concurrent multiscale simulations, while retaining the microstructure information. This remarkable increase in efficiency is achieved with a data-driven clustering method. Computationally expensive operations are performed in the so-called offline stage, where degrees of freedom (DOFs) are agglomerated into clusters. The interaction tensor of these clusters is computed. In the online or predictive stage, the Lippmann-Schwinger integral equation is solved cluster-wise using a self-consistent scheme to ensure solution accuracy and avoid path dependence. To construct a concurrent multiscale model, this scheme is applied at each material point in a macroscale structure, replacing a conventional constitutive model with the average response computed from the microscale model using just the SCA online stage. A regularized damage theory is incorporated in the microscale that avoids the mesh and RVE size dependence that commonly plagues microscale damage calculations. The SCA method is illustrated with two cases: a carbon fiber reinforced polymer (CFRP) structure with the concurrent multiscale model and an application to fatigue prediction for additively manufactured metals. For the CFRP problem, a speed up estimated to be about

  5. A fully-automated multiscale kernel graph cuts based particle localization scheme for temporal focusing two-photon microscopy

    Science.gov (United States)

    Huang, Xia; Li, Chunqiang; Xiao, Chuan; Sun, Wenqing; Qian, Wei

    2017-03-01

    The temporal focusing two-photon microscope (TFM) is developed to perform depth resolved wide field fluorescence imaging by capturing frames sequentially. However, due to strong nonignorable noises and diffraction rings surrounding particles, further researches are extremely formidable without a precise particle localization technique. In this paper, we developed a fully-automated scheme to locate particles positions with high noise tolerance. Our scheme includes the following procedures: noise reduction using a hybrid Kalman filter method, particle segmentation based on a multiscale kernel graph cuts global and local segmentation algorithm, and a kinematic estimation based particle tracking method. Both isolated and partial-overlapped particles can be accurately identified with removal of unrelated pixels. Based on our quantitative analysis, 96.22% isolated particles and 84.19% partial-overlapped particles were successfully detected.

  6. Network analysis reveals multiscale controls on streamwater chemistry

    Science.gov (United States)

    McGuire, Kevin J.; Torgersen, Christian E.; Likens, Gene E.; Buso, Donald C.; Lowe, Winsor H.; Bailey, Scott W.

    2014-01-01

    By coupling synoptic data from a basin-wide assessment of streamwater chemistry with network-based geostatistical analysis, we show that spatial processes differentially affect biogeochemical condition and pattern across a headwater stream network. We analyzed a high-resolution dataset consisting of 664 water samples collected every 100 m throughout 32 tributaries in an entire fifth-order stream network. These samples were analyzed for an exhaustive suite of chemical constituents. The fine grain and broad extent of this study design allowed us to quantify spatial patterns over a range of scales by using empirical semivariograms that explicitly incorporated network topology. Here, we show that spatial structure, as determined by the characteristic shape of the semivariograms, differed both among chemical constituents and by spatial relationship (flow-connected, flow-unconnected, or Euclidean). Spatial structure was apparent at either a single scale or at multiple nested scales, suggesting separate processes operating simultaneously within the stream network and surrounding terrestrial landscape. Expected patterns of spatial dependence for flow-connected relationships (e.g., increasing homogeneity with downstream distance) occurred for some chemical constituents (e.g., dissolved organic carbon, sulfate, and aluminum) but not for others (e.g., nitrate, sodium). By comparing semivariograms for the different chemical constituents and spatial relationships, we were able to separate effects on streamwater chemistry of (i) fine-scale versus broad-scale processes and (ii) in-stream processes versus landscape controls. These findings provide insight on the hierarchical scaling of local, longitudinal, and landscape processes that drive biogeochemical patterns in stream networks.

  7. Network analysis reveals multiscale controls on streamwater chemistry.

    Science.gov (United States)

    McGuire, Kevin J; Torgersen, Christian E; Likens, Gene E; Buso, Donald C; Lowe, Winsor H; Bailey, Scott W

    2014-05-13

    By coupling synoptic data from a basin-wide assessment of streamwater chemistry with network-based geostatistical analysis, we show that spatial processes differentially affect biogeochemical condition and pattern across a headwater stream network. We analyzed a high-resolution dataset consisting of 664 water samples collected every 100 m throughout 32 tributaries in an entire fifth-order stream network. These samples were analyzed for an exhaustive suite of chemical constituents. The fine grain and broad extent of this study design allowed us to quantify spatial patterns over a range of scales by using empirical semivariograms that explicitly incorporated network topology. Here, we show that spatial structure, as determined by the characteristic shape of the semivariograms, differed both among chemical constituents and by spatial relationship (flow-connected, flow-unconnected, or Euclidean). Spatial structure was apparent at either a single scale or at multiple nested scales, suggesting separate processes operating simultaneously within the stream network and surrounding terrestrial landscape. Expected patterns of spatial dependence for flow-connected relationships (e.g., increasing homogeneity with downstream distance) occurred for some chemical constituents (e.g., dissolved organic carbon, sulfate, and aluminum) but not for others (e.g., nitrate, sodium). By comparing semivariograms for the different chemical constituents and spatial relationships, we were able to separate effects on streamwater chemistry of (i) fine-scale versus broad-scale processes and (ii) in-stream processes versus landscape controls. These findings provide insight on the hierarchical scaling of local, longitudinal, and landscape processes that drive biogeochemical patterns in stream networks.

  8. Multi-scale Gaussian representation and outline-learning based cell image segmentation

    Science.gov (United States)

    2013-01-01

    Background High-throughput genome-wide screening to study gene-specific functions, e.g. for drug discovery, demands fast automated image analysis methods to assist in unraveling the full potential of such studies. Image segmentation is typically at the forefront of such analysis as the performance of the subsequent steps, for example, cell classification, cell tracking etc., often relies on the results of segmentation. Methods We present a cell cytoplasm segmentation framework which first separates cell cytoplasm from image background using novel approach of image enhancement and coefficient of variation of multi-scale Gaussian scale-space representation. A novel outline-learning based classification method is developed using regularized logistic regression with embedded feature selection which classifies image pixels as outline/non-outline to give cytoplasm outlines. Refinement of the detected outlines to separate cells from each other is performed in a post-processing step where the nuclei segmentation is used as contextual information. Results and conclusions We evaluate the proposed segmentation methodology using two challenging test cases, presenting images with completely different characteristics, with cells of varying size, shape, texture and degrees of overlap. The feature selection and classification framework for outline detection produces very simple sparse models which use only a small subset of the large, generic feature set, that is, only 7 and 5 features for the two cases. Quantitative comparison of the results for the two test cases against state-of-the-art methods show that our methodology outperforms them with an increase of 4-9% in segmentation accuracy with maximum accuracy of 93%. Finally, the results obtained for diverse datasets demonstrate that our framework not only produces accurate segmentation but also generalizes well to different segmentation tasks. PMID:24267488

  9. Protein multi-scale organization through graph partitioning and robustness analysis: application to the myosin–myosin light chain interaction

    International Nuclear Information System (INIS)

    Delmotte, A; Barahona, M; Tate, E W; Yaliraki, S N

    2011-01-01

    Despite the recognized importance of the multi-scale spatio-temporal organization of proteins, most computational tools can only access a limited spectrum of time and spatial scales, thereby ignoring the effects on protein behavior of the intricate coupling between the different scales. Starting from a physico-chemical atomistic network of interactions that encodes the structure of the protein, we introduce a methodology based on multi-scale graph partitioning that can uncover partitions and levels of organization of proteins that span the whole range of scales, revealing biological features occurring at different levels of organization and tracking their effect across scales. Additionally, we introduce a measure of robustness to quantify the relevance of the partitions through the generation of biochemically-motivated surrogate random graph models. We apply the method to four distinct conformations of myosin tail interacting protein, a protein from the molecular motor of the malaria parasite, and study properties that have been experimentally addressed such as the closing mechanism, the presence of conserved clusters, and the identification through computational mutational analysis of key residues for binding

  10. Multiscale analysis of nonlinear systems using computational homology

    Energy Technology Data Exchange (ETDEWEB)

    Konstantin Mischaikow; Michael Schatz; William Kalies; Thomas Wanner

    2010-05-24

    This is a collaborative project between the principal investigators. However, as is to be expected, different PIs have greater focus on different aspects of the project. This report lists these major directions of research which were pursued during the funding period: (1) Computational Homology in Fluids - For the computational homology effort in thermal convection, the focus of the work during the first two years of the funding period included: (1) A clear demonstration that homology can sensitively detect the presence or absence of an important flow symmetry, (2) An investigation of homology as a probe for flow dynamics, and (3) The construction of a new convection apparatus for probing the effects of large-aspect-ratio. (2) Computational Homology in Cardiac Dynamics - We have initiated an effort to test the use of homology in characterizing data from both laboratory experiments and numerical simulations of arrhythmia in the heart. Recently, the use of high speed, high sensitivity digital imaging in conjunction with voltage sensitive fluorescent dyes has enabled researchers to visualize electrical activity on the surface of cardiac tissue, both in vitro and in vivo. (3) Magnetohydrodynamics - A new research direction is to use computational homology to analyze results of large scale simulations of 2D turbulence in the presence of magnetic fields. Such simulations are relevant to the dynamics of black hole accretion disks. The complex flow patterns from simulations exhibit strong qualitative changes as a function of magnetic field strength. Efforts to characterize the pattern changes using Fourier methods and wavelet analysis have been unsuccessful. (4) Granular Flow - two experts in the area of granular media are studying 2D model experiments of earthquake dynamics where the stress fields can be measured; these stress fields from complex patterns of 'force chains' that may be amenable to analysis using computational homology. (5) Microstructure

  11. Multiscale analysis of nonlinear systems using computational homology

    Energy Technology Data Exchange (ETDEWEB)

    Konstantin Mischaikow, Rutgers University/Georgia Institute of Technology, Michael Schatz, Georgia Institute of Technology, William Kalies, Florida Atlantic University, Thomas Wanner,George Mason University

    2010-05-19

    This is a collaborative project between the principal investigators. However, as is to be expected, different PIs have greater focus on different aspects of the project. This report lists these major directions of research which were pursued during the funding period: (1) Computational Homology in Fluids - For the computational homology effort in thermal convection, the focus of the work during the first two years of the funding period included: (1) A clear demonstration that homology can sensitively detect the presence or absence of an important flow symmetry, (2) An investigation of homology as a probe for flow dynamics, and (3) The construction of a new convection apparatus for probing the effects of large-aspect-ratio. (2) Computational Homology in Cardiac Dynamics - We have initiated an effort to test the use of homology in characterizing data from both laboratory experiments and numerical simulations of arrhythmia in the heart. Recently, the use of high speed, high sensitivity digital imaging in conjunction with voltage sensitive fluorescent dyes has enabled researchers to visualize electrical activity on the surface of cardiac tissue, both in vitro and in vivo. (3) Magnetohydrodynamics - A new research direction is to use computational homology to analyze results of large scale simulations of 2D turbulence in the presence of magnetic fields. Such simulations are relevant to the dynamics of black hole accretion disks. The complex flow patterns from simulations exhibit strong qualitative changes as a function of magnetic field strength. Efforts to characterize the pattern changes using Fourier methods and wavelet analysis have been unsuccessful. (4) Granular Flow - two experts in the area of granular media are studying 2D model experiments of earthquake dynamics where the stress fields can be measured; these stress fields from complex patterns of 'force chains' that may be amenable to analysis using computational homology. (5) Microstructure

  12. Multi-Scale Computational Modeling of Ni-Base Superalloy Brazed Joints for Gas Turbine Applications

    Science.gov (United States)

    Riggs, Bryan

    Brazed joints are commonly used in the manufacture and repair of aerospace components including high temperature gas turbine components made of Ni-base superalloys. For such critical applications, it is becoming increasingly important to account for the mechanical strength and reliability of the brazed joint. However, material properties of brazed joints are not readily available and methods for evaluating joint strength such as those listed in AWS C3.2 have inherent challenges compared with testing bulk materials. In addition, joint strength can be strongly influenced by the degree of interaction between the filler metal (FM) and the base metal (BM), the joint design, and presence of flaws or defects. As a result, there is interest in the development of a multi-scale computational model to predict the overall mechanical behavior and fitness-for-service of brazed joints. Therefore, the aim of this investigation was to generate data and methodology to support such a model for Ni-base superalloy brazed joints with conventional Ni-Cr-B based FMs. Based on a review of the technical literature a multi-scale modeling approach was proposed to predict the overall performance of brazed joints by relating mechanical properties to the brazed joint microstructure. This approach incorporates metallurgical characterization, thermodynamic/kinetic simulations, mechanical testing, fracture mechanics and finite element analysis (FEA) modeling to estimate joint properties based on the initial BM/FM composition and brazing process parameters. Experimental work was carried out in each of these areas to validate the multi-scale approach and develop improved techniques for quantifying brazed joint properties. Two Ni-base superalloys often used in gas turbine applications, Inconel 718 and CMSX-4, were selected for study and vacuum furnace brazed using two common FMs, BNi-2 and BNi-9. Metallurgical characterization of these brazed joints showed two primary microstructural regions; a soft

  13. Multi-scale analysis of teleconnection indices: climate noise and nonlinear trend analysis

    Directory of Open Access Journals (Sweden)

    C. Franzke

    2009-02-01

    Full Text Available The multi-scale nature and climate noise properties of teleconnection indices are examined by using the Empirical Mode Decomposition (EMD procedure. The EMD procedure allows for the analysis of non-stationary time series to extract physically meaningful intrinsic mode functions (IMF and nonlinear trends. The climatologically relevant monthly mean teleconnection indices of the North Atlantic Oscillation (NAO, the North Pacific index (NP and the Southern Annular Mode (SAM are analyzed.

    The significance of IMFs and trends are tested against the null hypothesis of climate noise. The analysis of surrogate monthly mean time series from a red noise process shows that the EMD procedure is effectively a dyadic filter bank and the IMFs (except the first IMF are nearly Gaussian distributed. The distribution of the variance contained in IMFs of an ensemble of AR(1 simulations is nearly χ2 distributed. To test the statistical significance of the IMFs of the teleconnection indices and their nonlinear trends we utilize an ensemble of corresponding monthly averaged AR(1 processes, which we refer to as climate noise. Our results indicate that most of the interannual and decadal variability of the analysed teleconnection indices cannot be distinguished from climate noise. The NP and SAM indices have significant nonlinear trends, while the NAO has no significant trend when tested against a climate noise hypothesis.

  14. Robust Face Recognition via Multi-Scale Patch-Based Matrix Regression.

    Directory of Open Access Journals (Sweden)

    Guangwei Gao

    Full Text Available In many real-world applications such as smart card solutions, law enforcement, surveillance and access control, the limited training sample size is the most fundamental problem. By making use of the low-rank structural information of the reconstructed error image, the so-called nuclear norm-based matrix regression has been demonstrated to be effective for robust face recognition with continuous occlusions. However, the recognition performance of nuclear norm-based matrix regression degrades greatly in the face of the small sample size problem. An alternative solution to tackle this problem is performing matrix regression on each patch and then integrating the outputs from all patches. However, it is difficult to set an optimal patch size across different databases. To fully utilize the complementary information from different patch scales for the final decision, we propose a multi-scale patch-based matrix regression scheme based on which the ensemble of multi-scale outputs can be achieved optimally. Extensive experiments on benchmark face databases validate the effectiveness and robustness of our method, which outperforms several state-of-the-art patch-based face recognition algorithms.

  15. A Comprehensive Database and Analysis Framework To Incorporate Multiscale Data Types and Enable Integrated Analysis of Bioactive Polyphenols.

    Science.gov (United States)

    Ho, Lap; Cheng, Haoxiang; Wang, Jun; Simon, James E; Wu, Qingli; Zhao, Danyue; Carry, Eileen; Ferruzzi, Mario G; Faith, Jeremiah; Valcarcel, Breanna; Hao, Ke; Pasinetti, Giulio M

    2018-03-05

    The development of a given botanical preparation for eventual clinical application requires extensive, detailed characterizations of the chemical composition, as well as the biological availability, biological activity, and safety profiles of the botanical. These issues are typically addressed using diverse experimental protocols and model systems. Based on this consideration, in this study we established a comprehensive database and analysis framework for the collection, collation, and integrative analysis of diverse, multiscale data sets. Using this framework, we conducted an integrative analysis of heterogeneous data from in vivo and in vitro investigation of a complex bioactive dietary polyphenol-rich preparation (BDPP) and built an integrated network linking data sets generated from this multitude of diverse experimental paradigms. We established a comprehensive database and analysis framework as well as a systematic and logical means to catalogue and collate the diverse array of information gathered, which is securely stored and added to in a standardized manner to enable fast query. We demonstrated the utility of the database in (1) a statistical ranking scheme to prioritize response to treatments and (2) in depth reconstruction of functionality studies. By examination of these data sets, the system allows analytical querying of heterogeneous data and the access of information related to interactions, mechanism of actions, functions, etc., which ultimately provide a global overview of complex biological responses. Collectively, we present an integrative analysis framework that leads to novel insights on the biological activities of a complex botanical such as BDPP that is based on data-driven characterizations of interactions between BDPP-derived phenolic metabolites and their mechanisms of action, as well as synergism and/or potential cancellation of biological functions. Out integrative analytical approach provides novel means for a systematic integrative

  16. Multi-scale learning based segmentation of glands in digital colonrectal pathology images.

    Science.gov (United States)

    Gao, Yi; Liu, William; Arjun, Shipra; Zhu, Liangjia; Ratner, Vadim; Kurc, Tahsin; Saltz, Joel; Tannenbaum, Allen

    2016-02-01

    Digital histopathological images provide detailed spatial information of the tissue at micrometer resolution. Among the available contents in the pathology images, meso-scale information, such as the gland morphology, texture, and distribution, are useful diagnostic features. In this work, focusing on the colon-rectal cancer tissue samples, we propose a multi-scale learning based segmentation scheme for the glands in the colon-rectal digital pathology slides. The algorithm learns the gland and non-gland textures from a set of training images in various scales through a sparse dictionary representation. After the learning step, the dictionaries are used collectively to perform the classification and segmentation for the new image.

  17. Multiscale Thermo-Mechanical Design and Analysis of High Frequency and High Power Vacuum Electron Devices

    Science.gov (United States)

    Gamzina, Diana

    Diana Gamzina March 2016 Mechanical and Aerospace Engineering Multiscale Thermo-Mechanical Design and Analysis of High Frequency and High Power Vacuum Electron Devices Abstract A methodology for performing thermo-mechanical design and analysis of high frequency and high average power vacuum electron devices is presented. This methodology results in a "first-pass" engineering design directly ready for manufacturing. The methodology includes establishment of thermal and mechanical boundary conditions, evaluation of convective film heat transfer coefficients, identification of material options, evaluation of temperature and stress field distributions, assessment of microscale effects on the stress state of the material, and fatigue analysis. The feature size of vacuum electron devices operating in the high frequency regime of 100 GHz to 1 THz is comparable to the microstructure of the materials employed for their fabrication. As a result, the thermo-mechanical performance of a device is affected by the local material microstructure. Such multiscale effects on the stress state are considered in the range of scales from about 10 microns up to a few millimeters. The design and analysis methodology is demonstrated on three separate microwave devices: a 95 GHz 10 kW cw sheet beam klystron, a 263 GHz 50 W long pulse wide-bandwidth sheet beam travelling wave tube, and a 346 GHz 1 W cw backward wave oscillator.

  18. Multiscale science for science-based stockpile stewardship

    Energy Technology Data Exchange (ETDEWEB)

    Margolin, L.; Sharp, D.

    2000-12-01

    This is the final report of a three-year, Laboratory-Directed Research and Development (LDRD) project at the Los Alamos National Laboratory (LANL). The goal of this project has been to develop and apply the methods of multi scale science to the problems of fluid and material mixing due to instability and turbulence, and of materials characterization. Our specific focus has been on the SBSS (science-based stockpile stewardship) issue of assessing the performance of a weapons with off-design, aged, or remanufactured components in the absence of full-scale testing. Our products are physics models, based on microphysical principles and parameters, and suitable for implementation in the large scale design and assessment codes used in the nuclear weapons program.

  19. Use of multiscale zirconium alloy deformation models in nuclear fuel behavior analysis

    Energy Technology Data Exchange (ETDEWEB)

    Montgomery, Robert, E-mail: robert.montgomery@pnnl.gov [Pacific Northwest National Laboratory (United States); Tomé, Carlos, E-mail: tome@lanl.gov [Los Alamos National Laboratory (United States); Liu, Wenfeng, E-mail: wenfeng.liu@anatech.com [ANATECH Corporation (United States); Alankar, Alankar, E-mail: alankar.alankar@iitb.ac.in [Indian Institute of Technology Bombay (India); Subramanian, Gopinath, E-mail: gopinath.subramanian@usm.edu [University of Southern Mississippi (United States); Stanek, Christopher, E-mail: stanek@lanl.gov [Los Alamos National Laboratory (United States)

    2017-01-01

    Accurate prediction of cladding mechanical behavior is a key aspect of modeling nuclear fuel behavior, especially for conditions of pellet-cladding interaction (PCI), reactivity-initiated accidents (RIA), and loss of coolant accidents (LOCA). Current approaches to fuel performance modeling rely on empirical constitutive models for cladding creep, growth and plastic deformation, which are limited to the materials and conditions for which the models were developed. To improve upon this approach, a microstructurally-based zirconium alloy mechanical deformation analysis capability is being developed within the United States Department of Energy Consortium for Advanced Simulation of Light Water Reactors (CASL). Specifically, the viscoplastic self-consistent (VPSC) polycrystal plasticity modeling approach, developed by Lebensohn and Tomé [1], has been coupled with the BISON engineering scale fuel performance code to represent the mechanistic material processes controlling the deformation behavior of light water reactor (LWR) cladding. A critical component of VPSC is the representation of the crystallographic nature (defect and dislocation movement) and orientation of the grains within the matrix material and the ability to account for the role of texture on deformation. A future goal is for VPSC to obtain information on reaction rate kinetics from atomistic calculations to inform the defect and dislocation behavior models described in VPSC. The multiscale modeling of cladding deformation mechanisms allowed by VPSC far exceed the functionality of typical semi-empirical constitutive models employed in nuclear fuel behavior codes to model irradiation growth and creep, thermal creep, or plasticity. This paper describes the implementation of an interface between VPSC and BISON and provides initial results utilizing the coupled functionality.

  20. Extracting sensitive spectrum bands of rapeseed using multiscale multifractal detrended fluctuation analysis

    Science.gov (United States)

    Jiang, Shan; Wang, Fang; Shen, Luming; Liao, Guiping; Wang, Lin

    2017-03-01

    Spectrum technology has been widely used in crop non-destructive testing diagnosis for crop information acquisition. Since spectrum covers a wide range of bands, it is of critical importance to extract the sensitive bands. In this paper, we propose a methodology to extract the sensitive spectrum bands of rapeseed using multiscale multifractal detrended fluctuation analysis. Our obtained sensitive bands are relatively robust in the range of 534 nm-574 nm. Further, by using the multifractal parameter (Hurst exponent) of the extracted sensitive bands, we propose a prediction model to forecast the Soil and plant analyzer development values ((SPAD), often used as a parameter to indicate the chlorophyll content) and an identification model to distinguish the different planting patterns. Three vegetation indices (VIs) based on previous work are used for comparison. Three evaluation indicators, namely, the root mean square error, the correlation coefficient, and the relative error employed in the SPAD values prediction model all demonstrate that our Hurst exponent has the best performance. Four rapeseed compound planting factors, namely, seeding method, planting density, fertilizer type, and weed control method are considered in the identification model. The Youden indices calculated by the random decision forest method and the K-nearest neighbor method show that our Hurst exponent is superior to other three Vis, and their combination for the factor of seeding method. In addition, there is no significant difference among the five features for other three planting factors. This interesting finding suggests that the transplanting and the direct seeding would make a big difference in the growth of rapeseed.

  1. A Multiscale Finite Element Model Validation Method of Composite Cable-Stayed Bridge Based on Structural Health Monitoring System

    Directory of Open Access Journals (Sweden)

    Rumian Zhong

    2015-01-01

    Full Text Available A two-step response surface method for multiscale finite element model (FEM updating and validation is presented with respect to Guanhe Bridge, a composite cable-stayed bridge in the National Highway number G15, in China. Firstly, the state equations of both multiscale and single-scale FEM are established based on the basic equation in structural dynamic mechanics to update the multiscale coupling parameters and structural parameters. Secondly, based on the measured data from the structural health monitoring (SHM system, a Monte Carlo simulation is employed to analyze the uncertainty quantification and transmission, where the uncertainties of the multiscale FEM and measured data were considered. The results indicate that the relative errors between the calculated and measured frequencies are less than 2%, and the overlap ratio indexes of each modal frequency are larger than 80% without the average absolute value of relative errors. These demonstrate that the proposed method can be applied to validate the multiscale FEM, and the validated FEM can reflect the current conditions of the real bridge; thus it can be used as the basis for bridge health monitoring, damage prognosis (DP, and safety prognosis (SP.

  2. Multi-scale carbon micro/nanofibers-based adsorbents for protein immobilization

    Energy Technology Data Exchange (ETDEWEB)

    Singh, Shiv; Singh, Abhinav [Department of Chemical Engineering, Indian Institute of Technology Kanpur, Kanpur 208016 (India); Bais, Vaibhav Sushil Singh; Prakash, Balaji [Department of Biological Science and Bioengineering, Indian Institute of Technology Kanpur, Kanpur 208016 (India); Verma, Nishith, E-mail: nishith@iitk.ac.in [Department of Chemical Engineering, Indian Institute of Technology Kanpur, Kanpur 208016 (India); Center for Environmental Science and Engineering, Indian Institute of Technology Kanpur, Kanpur 208016 (India)

    2014-05-01

    In the present study, different proteins, namely, bovine serum albumin (BSA), glucose oxidase (GOx) and the laboratory purified YqeH were immobilized in the phenolic resin precursor-based multi-scale web of activated carbon microfibers (ACFs) and carbon nanofibers (CNFs). These biomolecules are characteristically different from each other, having different structure, number of parent amino acid molecules and isoelectric point. CNF was grown on ACF substrate by chemical vapor deposition, using Ni nanoparticles (Nps) as the catalyst. The ultra-sonication of the CNFs was carried out in acidic medium to remove Ni Nps from the tip of the CNFs to provide additional active sites for adsorption. The prepared material was directly used as an adsorbent for proteins, without requiring any additional treatment. Several analytical techniques were used to characterize the prepared materials, including scanning electron microscopy, Fourier transform infrared spectroscopy, BET surface area, pore-size distribution, and UV–vis spectroscopy. The adsorption capacities of prepared ACFs/CNFs in this study were determined to be approximately 191, 39 and 70 mg/g for BSA, GOx and YqeH, respectively, revealing that the carbon micro-nanofibers forming synthesized multi-scale web are efficient materials for the immobilization of protein molecules. - Highlights: • Ni metal Np-dispersed carbon micro-nanofibers (ACFs/CNFs) are prepared. • ACFs/CNFs are mesoporous. • Significant adsorption of BSA, GOx and YqeH is observed on ACFs/CNFs. • Multi-scale web of ACFs/CNFs is effective for protein immobilization.

  3. Mixed multiscale finite element methods using approximate global information based on partial upscaling

    KAUST Repository

    Jiang, Lijian

    2009-10-02

    The use of limited global information in multiscale simulations is needed when there is no scale separation. Previous approaches entail fine-scale simulations in the computation of the global information. The computation of the global information is expensive. In this paper, we propose the use of approximate global information based on partial upscaling. A requirement for partial homogenization is to capture long-range (non-local) effects present in the fine-scale solution, while homogenizing some of the smallest scales. The local information at these smallest scales is captured in the computation of basis functions. Thus, the proposed approach allows us to avoid the computations at the scales that can be homogenized. This results in coarser problems for the computation of global fields. We analyze the convergence of the proposed method. Mathematical formalism is introduced, which allows estimating the errors due to small scales that are homogenized. The proposed method is applied to simulate two-phase flows in heterogeneous porous media. Numerical results are presented for various permeability fields, including those generated using two-point correlation functions and channelized permeability fields from the SPE Comparative Project (Christie and Blunt, SPE Reserv Evalu Eng 4:308-317, 2001). We consider simple cases where one can identify the scales that can be homogenized. For more general cases, we suggest the use of upscaling on the coarse grid with the size smaller than the target coarse grid where multiscale basis functions are constructed. This intermediate coarse grid renders a partially upscaled solution that contains essential non-local information. Numerical examples demonstrate that the use of approximate global information provides better accuracy than purely local multiscale methods. © 2009 Springer Science+Business Media B.V.

  4. Improved convergence of gradient-based reconstruction using multi-scale models

    International Nuclear Information System (INIS)

    Cunningham, G.S.; Hanson, K.M.; Koyfman, I.

    1996-01-01

    Geometric models have received increasing attention in medical imaging for tasks such as segmentation, reconstruction, restoration, and registration. In order to determine the best configuration of the geometric model in the context of any of these tasks, one needs to perform a difficult global optimization of an energy function that may have many local minima. Explicit models of geometry, also called deformable models, snakes, or active contours, have been used extensively to solve image segmentation problems in a non-Bayesian framework. Researchers have seen empirically that multi-scale analysis is useful for convergence to a configuration that is near the global minimum. In this type of analysis, the image data are convolved with blur functions of increasing resolution, and an optimal configuration of the snake is found for each blurred image. The configuration obtained using the highest resolution blur is used as the solution to the global optimization problem. In this article, the authors use explicit models of geometry for a variety of Bayesian estimation problems, including image segmentation, reconstruction and restoration. The authors introduce a multi-scale approach that blurs the geometric model, rather than the image data, and show that this approach turns a global, highly nonquadratic optimization into a sequence of local, approximately quadratic problems that converge to the global minimum. The result is a deterministic, robust, and efficient optimization strategy applicable to a wide variety of Bayesian estimation problems in which geometric models of images are an important component

  5. Analysis of Multi-Scale Phenomena in Heterogeneous Materials

    Science.gov (United States)

    2011-02-22

    requires the use of properties of the Catalan numbers to show that the series coefficients are exponentially bounded in the H1 Sobolev norm. This is joint...the use of a small number of optimal local basis functions. The local bases are supported on sub domains of fixed diameter within the computa- tional...not display a currently valid OMB control number . 1. REPORT DATE 22 FEB 2011 2. REPORT TYPE FINAL REPORT 3. DATES COVERED 03-01-2008 to 03-03

  6. A finite element framework for multiscale/multiphysics analysis of structures with complex microstructures

    Science.gov (United States)

    Varghese, Julian

    This research work has contributed in various ways to help develop a better understanding of textile composites and materials with complex microstructures in general. An instrumental part of this work was the development of an object-oriented framework that made it convenient to perform multiscale/multiphysics analyses of advanced materials with complex microstructures such as textile composites. In addition to the studies conducted in this work, this framework lays the groundwork for continued research of these materials. This framework enabled a detailed multiscale stress analysis of a woven DCB specimen that revealed the effect of the complex microstructure on the stress and strain energy release rate distribution along the crack front. In addition to implementing an oxidation model, the framework was also used to implement strategies that expedited the simulation of oxidation in textile composites so that it would take only a few hours. The simulation showed that the tow architecture played a significant role in the oxidation behavior in textile composites. Finally, a coupled diffusion/oxidation and damage progression analysis was implemented that was used to study the mechanical behavior of textile composites under mechanical loading as well as oxidation. A parametric study was performed to determine the effect of material properties and the number of plies in the laminate on its mechanical behavior. The analyses indicated a significant effect of the tow architecture and other parameters on the damage progression in the laminates.

  7. Numerical Analysis of Electromagnetic Fields in Multiscale Model

    International Nuclear Information System (INIS)

    Ma Ji; Fang Guang-You; Ji Yi-Cai

    2015-01-01

    Modeling technique for electromagnetic fields excited by antennas is an important topic in computational electromagnetics, which is concerned with the numerical solution of Maxwell's equations. In this paper, a novel hybrid technique that combines method of moments (MoM) with finite-difference time-domain (FDTD) method is presented to handle the problem. This approach employed Huygen's principle to realize the hybridization of the two classical numerical algorithms. For wideband electromagnetic data, the interpolation scheme is used in the MoM based on the dyadic Green's function. On the other hand, with the help of equivalence principle, the scattered electric and magnetic fields on the Huygen's surface calculated by MoM are taken as the sources for FDTD. Therefore, the electromagnetic fields in the environment can be obtained by employing finite-difference time-domain method. Finally, numerical results show the validity of the proposed technique by analyzing two canonical samples. (paper)

  8. Advances in Modal Analysis Using a Robust and Multiscale Method

    Science.gov (United States)

    Picard, Cécile; Frisson, Christian; Faure, François; Drettakis, George; Kry, Paul G.

    2010-12-01

    This paper presents a new approach to modal synthesis for rendering sounds of virtual objects. We propose a generic method that preserves sound variety across the surface of an object at different scales of resolution and for a variety of complex geometries. The technique performs automatic voxelization of a surface model and automatic tuning of the parameters of hexahedral finite elements, based on the distribution of material in each cell. The voxelization is performed using a sparse regular grid embedding of the object, which permits the construction of plausible lower resolution approximations of the modal model. We can compute the audible impulse response of a variety of objects. Our solution is robust and can handle nonmanifold geometries that include both volumetric and surface parts. We present a system which allows us to manipulate and tune sounding objects in an appropriate way for games, training simulations, and other interactive virtual environments.

  9. Advances in Modal Analysis Using a Robust and Multiscale Method

    Directory of Open Access Journals (Sweden)

    Frisson Christian

    2010-01-01

    Full Text Available Abstract This paper presents a new approach to modal synthesis for rendering sounds of virtual objects. We propose a generic method that preserves sound variety across the surface of an object at different scales of resolution and for a variety of complex geometries. The technique performs automatic voxelization of a surface model and automatic tuning of the parameters of hexahedral finite elements, based on the distribution of material in each cell. The voxelization is performed using a sparse regular grid embedding of the object, which permits the construction of plausible lower resolution approximations of the modal model. We can compute the audible impulse response of a variety of objects. Our solution is robust and can handle nonmanifold geometries that include both volumetric and surface parts. We present a system which allows us to manipulate and tune sounding objects in an appropriate way for games, training simulations, and other interactive virtual environments.

  10. Stochastic multi-scale analysis of homogenised properties considering uncertainties in cellular solid microstructures using a first-order perturbation

    Directory of Open Access Journals (Sweden)

    Khairul Salleh Basaruddin

    Full Text Available Randomness in the microstructure due to variations in microscopic properties and geometrical information is used to predict the stochastically homogenised properties of cellular media. Two stochastic problems at the micro-scale level that commonly occur due to fabrication inaccuracies, degradation mechanisms or natural heterogeneity were analysed using a stochastic homogenisation method based on a first-order perturbation. First, the influence of Young's modulus variation in an adhesive on the macroscopic properties of an aluminium-adhesive honeycomb structure was investigated. The fluctuations in the microscopic properties were then combined by varying the microstructure periodicity in a corrugated-core sandwich plate to obtain the variation of the homogenised property. The numerical results show that the uncertainties in the microstructure affect the dispersion of the homogenised property. These results indicate the importance of the presented stochastic multi-scale analysis for the design and fabrication of cellular solids when considering microscopic random variation.

  11. Multi-scale sensitivity analysis of pile installation using DEM

    Science.gov (United States)

    Esposito, Ricardo Gurevitz; Velloso, Raquel Quadros; , Eurípedes do Amaral Vargas, Jr.; Danziger, Bernadete Ragoni

    2017-12-01

    The disturbances experienced by the soil due to the pile installation and dynamic soil-structure interaction still present major challenges to foundation engineers. These phenomena exhibit complex behaviors, difficult to measure in physical tests and to reproduce in numerical models. Due to the simplified approach used by the discrete element method (DEM) to simulate large deformations and nonlinear stress-dilatancy behavior of granular soils, the DEM consists of an excellent tool to investigate these processes. This study presents a sensitivity analysis of the effects of introducing a single pile using the PFC2D software developed by Itasca Co. The different scales investigated in these simulations include point and shaft resistance, alterations in porosity and stress fields and particles displacement. Several simulations were conducted in order to investigate the effects of different numerical approaches showing indications that the method of installation and particle rotation could influence greatly in the conditions around the numerical pile. Minor effects were also noted due to change in penetration velocity and pile-soil friction. The difference in behavior of a moving and a stationary pile shows good qualitative agreement with previous experimental results indicating the necessity of realizing a force equilibrium process prior to any load-test to be simulated.

  12. Multi-scale structural analysis of gas diffusion layers

    Science.gov (United States)

    Göbel, Martin; Godehardt, Michael; Schladitz, Katja

    2017-07-01

    The macroscopic properties of materials are strongly determined by their micro structure. Here, transport properties of gas diffusion layers (GDL) for fuel cells are considered. In order to simulate flow and thermal properties, detailed micro structural information is essential. 3D images obtained by high-resolution computed tomography using synchrotron radiation and scanning electron microscopy (SEM) combined with focused ion beam (FIB) serial slicing were used. A recent method for reconstruction of porous structures from FIB-SEM images and sophisticated morphological image transformations were applied to segment the solid structural components. The essential algorithmic steps for segmenting the different components in the tomographic data-sets are described and discussed. In this paper, two types of GDL, based on a non-woven substrate layer and a paper substrate layer were considered, respectively. More than three components are separated within the synchrotron radiation computed tomography data. That is, fiber system, polytetrafluoroethylene (PTFE) binder/impregnation, micro porous layer (MPL), inclusions within the latter, and pore space are segmented. The usage of the thus derived 3D structure data in different simulation applications can be demonstrated. Simulations of macroscopic properties such as thermal conductivity, depending on the flooding state of the GDL are possible.

  13. Multiscale Representations Phase II

    National Research Council Canada - National Science Library

    Bar-Yam, Yaneer

    2004-01-01

    .... Multiscale analysis provides an analytic tool that can be applied to evaluating force capabilities as well as the relevance of designs for technological innovations to support force structures and their modernization...

  14. Sea-land segmentation for infrared remote sensing images based on superpixels and multi-scale features

    Science.gov (United States)

    Lei, Sen; Zou, Zhengxia; Liu, Dunge; Xia, Zhenghuan; Shi, Zhenwei

    2018-06-01

    Sea-land segmentation is a key step for the information processing of ocean remote sensing images. Traditional sea-land segmentation algorithms ignore the local similarity prior of sea and land, and thus fail in complex scenarios. In this paper, we propose a new sea-land segmentation method for infrared remote sensing images to tackle the problem based on superpixels and multi-scale features. Considering the connectivity and local similarity of sea or land, we interpret the sea-land segmentation task in view of superpixels rather than pixels, where similar pixels are clustered and the local similarity are explored. Moreover, the multi-scale features are elaborately designed, comprising of gray histogram and multi-scale total variation. Experimental results on infrared bands of Landsat-8 satellite images demonstrate that the proposed method can obtain more accurate and more robust sea-land segmentation results than the traditional algorithms.

  15. Fusing Multiscale Charts into 3D ENC Systems Based on Underwater Topography and Remote Sensing Image

    Directory of Open Access Journals (Sweden)

    Tao Liu

    2015-01-01

    Full Text Available The purpose of this study is to propose an approach to fuse multiscale charts into three-dimensional (3D electronic navigational chart (ENC systems based on underwater topography and remote sensing image. This is the first time that the fusion of multiscale standard ENCs in the 3D ENC system has been studied. First, a view-dependent visualization technology is presented for the determination of the display condition of a chart. Second, a map sheet processing method is described for dealing with the map sheet splice problem. A process order called “3D order” is designed to adapt to the characteristics of the chart. A map sheet clipping process is described to deal with the overlap between the adjacent map sheets. And our strategy for map sheet splice is proposed. Third, the rendering method for ENC objects in the 3D ENC system is introduced. Fourth, our picking-up method for ENC objects is proposed. Finally, we implement the above methods in our system: automotive intelligent chart (AIC 3D electronic chart display and information systems (ECDIS. And our method can handle the fusion problem well.

  16. Multiscale crystal defect dynamics: A coarse-grained lattice defect model based on crystal microstructure

    Science.gov (United States)

    Lyu, Dandan; Li, Shaofan

    2017-10-01

    Crystal defects have microstructure, and this microstructure should be related to the microstructure of the original crystal. Hence each type of crystals may have similar defects due to the same failure mechanism originated from the same microstructure, if they are under the same loading conditions. In this work, we propose a multiscale crystal defect dynamics (MCDD) model that models defects by considering its intrinsic microstructure derived from the microstructure or material genome of the original perfect crystal. The main novelties of present work are: (1) the discrete exterior calculus and algebraic topology theory are used to construct a scale-up (coarse-grained) dual lattice model for crystal defects, which may represent all possible defect modes inside a crystal; (2) a higher order Cauchy-Born rule (up to the fourth order) is adopted to construct atomistic-informed constitutive relations for various defect process zones, and (3) an hierarchical strain gradient theory based finite element formulation is developed to support an hierarchical multiscale cohesive (process) zone model for various defects in a unified formulation. The efficiency of MCDD computational algorithm allows us to simulate dynamic defect evolution at large scale while taking into account atomistic interaction. The MCDD model has been validated by comparing of the results of MCDD simulations with that of molecular dynamics (MD) in the cases of nanoindentation and uniaxial tension. Numerical simulations have shown that MCDD model can predict dislocation nucleation induced instability and inelastic deformation, and thus it may provide an alternative solution to study crystal plasticity.

  17. A numerical homogenization method for heterogeneous, anisotropic elastic media based on multiscale theory

    KAUST Repository

    Gao, Kai

    2015-06-05

    The development of reliable methods for upscaling fine-scale models of elastic media has long been an important topic for rock physics and applied seismology. Several effective medium theories have been developed to provide elastic parameters for materials such as finely layered media or randomly oriented or aligned fractures. In such cases, the analytic solutions for upscaled properties can be used for accurate prediction of wave propagation. However, such theories cannot be applied directly to homogenize elastic media with more complex, arbitrary spatial heterogeneity. Therefore, we have proposed a numerical homogenization algorithm based on multiscale finite-element methods for simulating elastic wave propagation in heterogeneous, anisotropic elastic media. Specifically, our method used multiscale basis functions obtained from a local linear elasticity problem with appropriately defined boundary conditions. Homogenized, effective medium parameters were then computed using these basis functions, and the approach applied a numerical discretization that was similar to the rotated staggered-grid finite-difference scheme. Comparisons of the results from our method and from conventional, analytical approaches for finely layered media showed that the homogenization reliably estimated elastic parameters for this simple geometry. Additional tests examined anisotropic models with arbitrary spatial heterogeneity in which the average size of the heterogeneities ranged from several centimeters to several meters, and the ratio between the dominant wavelength and the average size of the arbitrary heterogeneities ranged from 10 to 100. Comparisons to finite-difference simulations proved that the numerical homogenization was equally accurate for these complex cases.

  18. Integrated multiscale simulation of combined heat and power based district heating system

    International Nuclear Information System (INIS)

    Li, Peifeng; Nord, Natasa; Ertesvåg, Ivar Ståle; Ge, Zhihua; Yang, Zhiping; Yang, Yongping

    2015-01-01

    Highlights: • Simulation of power plant, district heating network and heat users in detail and integrated. • Coupled calculation and analysis of the heat and pressure losses of the district heating network. • District heating is not preferable for very low heat load due to relatively high heat loss. • Lower design supply temperatures of the district heating network give higher system efficiency. - Abstract: Many studies have been carried out separately on combined heat and power and district heating. However, little work has been done considering the heat source, the district heating network and the heat users simultaneously, especially when it comes to the heating system with large-scale combined heat and power plant. For the purpose of energy conservation, it is very important to know well the system performance of the integrated heating system from the very primary fuel input to the terminal heat users. This paper set up a model of 300 MW electric power rated air-cooled combined heat and power plant using Ebsilon software, which was validated according to the design data from the turbine manufacturer. Then, the model of heating network and heat users were developed based on the fundamental theories of fluid mechanics and heat transfer. Finally the combined heat and power based district heating system was obtained and the system performances within multiscale scope of the system were analyzed using the developed Ebsilon model. Topics with regard to the heat loss, the pressure drop, the pump power consumption and the supply temperatures of the district heating network were discussed. Besides, the operational issues of the integrated system were also researched. Several useful conclusions were drawn. It was found that a lower design primary supply temperature of the district heating network would give a higher seasonal energy efficiency of the integrated system throughout the whole heating season. Moreover, it was not always right to relate low design

  19. Multiscale analysis of potential fields by a ridge consistency criterion: the reconstruction of the Bishop basement

    Science.gov (United States)

    Fedi, M.; Florio, G.; Cascone, L.

    2012-01-01

    We use a multiscale approach as a semi-automated interpreting tool of potential fields. The depth to the source and the structural index are estimated in two steps: first the depth to the source, as the intersection of the field ridges (lines built joining the extrema of the field at various altitudes) and secondly, the structural index by the scale function. We introduce a new criterion, called 'ridge consistency' in this strategy. The criterion is based on the principle that the structural index estimations on all the ridges converging towards the same source should be consistent. If these estimates are significantly different, field differentiation is used to lessen the interference effects from nearby sources or regional fields, to obtain a consistent set of estimates. In our multiscale framework, vertical differentiation is naturally joint to the low-pass filtering properties of the upward continuation, so is a stable process. Before applying our criterion, we studied carefully the errors on upward continuation caused by the finite size of the survey area. To this end, we analysed the complex magnetic synthetic case, known as Bishop model, and evaluated the best extrapolation algorithm and the optimal width of the area extension, needed to obtain accurate upward continuation. Afterwards, we applied the method to the depth estimation of the whole Bishop basement bathymetry. The result is a good reconstruction of the complex basement and of the shape properties of the source at the estimated points.

  20. Development of Multi-Scale Finite Element Analysis Codes for High Formability Sheet Metal Generation

    International Nuclear Information System (INIS)

    Nnakamachi, Eiji; Kuramae, Hiroyuki; Ngoc Tam, Nguyen; Nakamura, Yasunori; Sakamoto, Hidetoshi; Morimoto, Hideo

    2007-01-01

    In this study, the dynamic- and static-explicit multi-scale finite element (F.E.) codes are developed by employing the homogenization method, the crystalplasticity constitutive equation and SEM-EBSD measurement based polycrystal model. These can predict the crystal morphological change and the hardening evolution at the micro level, and the macroscopic plastic anisotropy evolution. These codes are applied to analyze the asymmetrical rolling process, which is introduced to control the crystal texture of the sheet metal for generating a high formability sheet metal. These codes can predict the yield surface and the sheet formability by analyzing the strain path dependent yield, the simple sheet forming process, such as the limit dome height test and the cylindrical deep drawing problems. It shows that the shear dominant rolling process, such as the asymmetric rolling, generates ''high formability'' textures and eventually the high formability sheet. The texture evolution and the high formability of the newly generated sheet metal experimentally were confirmed by the SEM-EBSD measurement and LDH test. It is concluded that these explicit type crystallographic homogenized multi-scale F.E. code could be a comprehensive tool to predict the plastic induced texture evolution, anisotropy and formability by the rolling process and the limit dome height test analyses

  1. Developing Flexible, Integrated Hydrologic Modeling Systems for Multiscale Analysis in the Midwest and Great Lakes Region

    Science.gov (United States)

    Hamlet, A. F.; Chiu, C. M.; Sharma, A.; Byun, K.; Hanson, Z.

    2016-12-01

    Physically based hydrologic modeling of surface and groundwater resources that can be flexibly and efficiently applied to support water resources policy/planning/management decisions at a wide range of spatial and temporal scales are greatly needed in the Midwest, where stakeholder access to such tools is currently a fundamental barrier to basic climate change assessment and adaptation efforts, and also the co-production of useful products to support detailed decision making. Based on earlier pilot studies in the Pacific Northwest Region, we are currently assembling a suite of end-to-end tools and resources to support various kinds of water resources planning and management applications across the region. One of the key aspects of these integrated tools is that the user community can access gridded products at any point along the end-to-end chain of models, looking backwards in time about 100 years (1915-2015), and forwards in time about 85 years using CMIP5 climate model projections. The integrated model is composed of historical and projected future meteorological data based on station observations and statistical and dynamically downscaled climate model output respectively. These gridded meteorological data sets serve as forcing data for the macro-scale VIC hydrologic model implemented over the Midwest at 1/16 degree resolution. High-resolution climate model (4km WRF) output provides inputs for the analyses of urban impacts, hydrologic extremes, agricultural impacts, and impacts to the Great Lakes. Groundwater recharge estimated by the surface water model provides input data for fine-scale and macro-scale groundwater models needed for specific applications. To highlight the multi-scale use of the integrated models in support of co-production of scientific information for decision making, we briefly describe three current case studies addressing different spatial scales of analysis: 1) Effects of climate change on the water balance of the Great Lakes, 2) Future

  2. A New Feature Extraction Method Based on EEMD and Multi-Scale Fuzzy Entropy for Motor Bearing

    Directory of Open Access Journals (Sweden)

    Huimin Zhao

    2016-12-01

    Full Text Available Feature extraction is one of the most important, pivotal, and difficult problems in mechanical fault diagnosis, which directly relates to the accuracy of fault diagnosis and the reliability of early fault prediction. Therefore, a new fault feature extraction method, called the EDOMFE method based on integrating ensemble empirical mode decomposition (EEMD, mode selection, and multi-scale fuzzy entropy is proposed to accurately diagnose fault in this paper. The EEMD method is used to decompose the vibration signal into a series of intrinsic mode functions (IMFs with a different physical significance. The correlation coefficient analysis method is used to calculate and determine three improved IMFs, which are close to the original signal. The multi-scale fuzzy entropy with the ability of effective distinguishing the complexity of different signals is used to calculate the entropy values of the selected three IMFs in order to form a feature vector with the complexity measure, which is regarded as the inputs of the support vector machine (SVM model for training and constructing a SVM classifier (EOMSMFD based on EDOMFE and SVM for fulfilling fault pattern recognition. Finally, the effectiveness of the proposed method is validated by real bearing vibration signals of the motor with different loads and fault severities. The experiment results show that the proposed EDOMFE method can effectively extract fault features from the vibration signal and that the proposed EOMSMFD method can accurately diagnose the fault types and fault severities for the inner race fault, the outer race fault, and rolling element fault of the motor bearing. Therefore, the proposed method provides a new fault diagnosis technology for rotating machinery.

  3. A semi-analytical approach towards plane wave analysis of local resonance metamaterials using a multiscale enriched continuum description

    NARCIS (Netherlands)

    Sridhar, A.; Kouznetsova, V.; Geers, M.G.D.

    2017-01-01

    This work presents a novel multiscale semi-analytical technique for the acoustic plane wave analysis of (negative) dynamic mass density type local resonance metamaterials with complex micro-structural geometry. A two step solution strategy is adopted, in which the unit cell problem at the

  4. OBJECT-ORIENTED CHANGE DETECTION BASED ON MULTI-SCALE APPROACH

    Directory of Open Access Journals (Sweden)

    Y. Jia

    2016-06-01

    Full Text Available The change detection of remote sensing images means analysing the change information quantitatively and recognizing the change types of the surface coverage data in different time phases. With the appearance of high resolution remote sensing image, object-oriented change detection method arises at this historic moment. In this paper, we research multi-scale approach for high resolution images, which includes multi-scale segmentation, multi-scale feature selection and multi-scale classification. Experimental results show that this method has a stronger advantage than the traditional single-scale method of high resolution remote sensing image change detection.

  5. Multiscale Characterization of PM2.5 in Southern Taiwan based on Noise-assisted Multivariate Empirical Mode Decomposition and Time-dependent Intrinsic Correlation

    Science.gov (United States)

    Hsiao, Y. R.; Tsai, C.

    2017-12-01

    As the WHO Air Quality Guideline indicates, ambient air pollution exposes world populations under threat of fatal symptoms (e.g. heart disease, lung cancer, asthma etc.), raising concerns of air pollution sources and relative factors. This study presents a novel approach to investigating the multiscale variations of PM2.5 in southern Taiwan over the past decade, with four meteorological influencing factors (Temperature, relative humidity, precipitation and wind speed),based on Noise-assisted Multivariate Empirical Mode Decomposition(NAMEMD) algorithm, Hilbert Spectral Analysis(HSA) and Time-dependent Intrinsic Correlation(TDIC) method. NAMEMD algorithm is a fully data-driven approach designed for nonlinear and nonstationary multivariate signals, and is performed to decompose multivariate signals into a collection of channels of Intrinsic Mode Functions (IMFs). TDIC method is an EMD-based method using a set of sliding window sizes to quantify localized correlation coefficients for multiscale signals. With the alignment property and quasi-dyadic filter bank of NAMEMD algorithm, one is able to produce same number of IMFs for all variables and estimates the cross correlation in a more accurate way. The performance of spectral representation of NAMEMD-HSA method is compared with Complementary Empirical Mode Decomposition/ Hilbert Spectral Analysis (CEEMD-HSA) and Wavelet Analysis. The nature of NAMAMD-based TDICC analysis is then compared with CEEMD-based TDIC analysis and the traditional correlation analysis.

  6. Multiscale design and life-cycle based sustainability assessment of polymer nanocomposite coatings

    Science.gov (United States)

    Uttarwar, Rohan G.

    simulations are performed using molecular dynamics methodology to study several structural and morphological features such as effect of polymer molecular weight, polydispersity, rheology, nanoparticle volume fraction, size, shape and chemical nature on the bulk mechanical and self-cleaning properties of the coating film. At macro-scale, a paint spray system which is used for automotive coating application is studied by using CFD-based simulation methodology to generate crucial information about the effects of nanocoating technology on environmental emissions and coating film quality. The cradle-to-grave life-cycle based sustainability assessment study address all the critical issues related to economic benefits, environmental implications and societal effects of nanocoating technology through case studies of automotive coating systems. It is accomplished by identifying crucial correlations among measurable parameters at different stages and developing sustainability indicator matrices for analysis of each stage of life-cycle. The findings from the research can have great potential to draft useful conclusions in favor of future development of coating systems with novel functionalities and improved sustainability.

  7. A multi-scale integrated analysis of the energy use in Romania, Bulgaria, Poland and Hungary

    International Nuclear Information System (INIS)

    Iorgulescu, Raluca I.; Polimeni, John M.

    2009-01-01

    This paper discusses energy use in the case of four countries, Bulgaria, Poland, Hungary, and Romania, which changed the economic system from command economy to open-market. The analysis provided uses the multi-scale integrated analysis of societal metabolism (MSIASM) approach and contrasts it with the use of the traditional indicators approach (GDP growth rates and energy intensity). These traditional indicators have been widely criticized for being inadequate reflections of how energy policies work. Furthermore, the one-size-fits-all policies that result from analyzing these indicators are inaccurate, particularly for transitional economies. The alternative indicators, economic labor productivity, saturation index of human activity, and exosomatic metabolic rates are used to investigate the four case studies considering the complexity of the transition process

  8. A Physiologically Based, Multi-Scale Model of Skeletal Muscle Structure and Function

    Science.gov (United States)

    Röhrle, O.; Davidson, J. B.; Pullan, A. J.

    2012-01-01

    Models of skeletal muscle can be classified as phenomenological or biophysical. Phenomenological models predict the muscle’s response to a specified input based on experimental measurements. Prominent phenomenological models are the Hill-type muscle models, which have been incorporated into rigid-body modeling frameworks, and three-dimensional continuum-mechanical models. Biophysically based models attempt to predict the muscle’s response as emerging from the underlying physiology of the system. In this contribution, the conventional biophysically based modeling methodology is extended to include several structural and functional characteristics of skeletal muscle. The result is a physiologically based, multi-scale skeletal muscle finite element model that is capable of representing detailed, geometrical descriptions of skeletal muscle fibers and their grouping. Together with a well-established model of motor-unit recruitment, the electro-physiological behavior of single muscle fibers within motor units is computed and linked to a continuum-mechanical constitutive law. The bridging between the cellular level and the organ level has been achieved via a multi-scale constitutive law and homogenization. The effect of homogenization has been investigated by varying the number of embedded skeletal muscle fibers and/or motor units and computing the resulting exerted muscle forces while applying the same excitatory input. All simulations were conducted using an anatomically realistic finite element model of the tibialis anterior muscle. Given the fact that the underlying electro-physiological cellular muscle model is capable of modeling metabolic fatigue effects such as potassium accumulation in the T-tubular space and inorganic phosphate build-up, the proposed framework provides a novel simulation-based way to investigate muscle behavior ranging from motor-unit recruitment to force generation and fatigue. PMID:22993509

  9. A physiologically based, multi-scale model of skeletal muscle structure and function

    Directory of Open Access Journals (Sweden)

    Oliver eRöhrle

    2012-09-01

    Full Text Available Models of skeletal muscle can be classified as phenomenological or biophysical. Phenomenological models predict the muscle's response to a specified input based on experimental measurements. Prominent phenomenological models are the Hill-type muscle models, which have been incorporated into rigid-body modelling frameworks, and three-dimensional continuum-mechanical models. Biophysically based models attempt to predict the muscle's response as emerging from the underlying physiology of the system. In this contribution, the conventional biophysically based modelling methodology is extended to include several structural and functional characteristics of skeletal muscle. The result is a physiologically based, multi-scale skeletal muscle finite element model that is capable of representing detailed, geometrical descriptions of skeletal muscle fibres and their grouping. Together with a well-established model of motor unit recruitment, the electro-physiological behaviour of single muscle fibres within motor units is computed and linked to a continuum-mechanical constitutive law. The bridging between the cellular level and the organ level has been achieved via a multi-scale constitutive law and homogenisation. The effect of homogenisation has been investigated by varying the number of embedded skeletal muscle fibres and/or motor units and computing the resulting exerted muscle forces while applying the same excitatory input. All simulations were conducted using an anatomically realistic finite element model of the Tibialis Anterior muscle. Given the fact that the underlying electro-physiological cellular muscle model is capable of modelling metabolic fatigue effects such as potassium accumulation in the T-tubular space and inorganic phosphate build-up, the proposed framework provides a novel simulation-based way to investigate muscle behaviour ranging from motor unit recruitment to force generation and fatigue.

  10. SU-F-18C-15: Model-Based Multiscale Noise Reduction On Low Dose Cone Beam Projection

    International Nuclear Information System (INIS)

    Yao, W; Farr, J

    2014-01-01

    Purpose: To improve image quality of low dose cone beam CT for patient positioning in radiation therapy. Methods: In low dose cone beam CT (CBCT) imaging systems, Poisson process governs the randomness of photon fluence at x-ray source and the detector because of the independent binomial process of photon absorption in medium. On a CBCT projection, the variance of fluence consists of the variance of noiseless imaging structure and that of Poisson noise, which is proportional to the mean (noiseless) of the fluence at the detector. This requires multiscale filters to smoothen noise while keeping the structure information of the imaged object. We used a mathematical model of Poisson process to design multiscale filters and established the balance of noise correction and structure blurring. The algorithm was checked with low dose kilo-voltage CBCT projections acquired from a Varian OBI system. Results: From the investigation of low dose CBCT of a Catphan phantom and patients, it showed that our model-based multiscale technique could efficiently reduce noise and meanwhile keep the fine structure of the imaged object. After the image processing, the number of visible line pairs in Catphan phantom scanned with 4 ms pulse time was similar to that scanned with 32 ms, and soft tissue structure from simulated 4 ms patient head-and-neck images was also comparable with scanned 20 ms ones. Compared with fixed-scale technique, the image quality from multiscale one was improved. Conclusion: Use of projection-specific multiscale filters can reach better balance on noise reduction and structure information loss. The image quality of low dose CBCT can be improved by using multiscale filters

  11. Multi-scale analysis of deformation behavior at SCC crack tip (3) (Contract research)

    International Nuclear Information System (INIS)

    Kaji, Yoshiyuki; Miwa, Yukio; Tsukada, Takashi; Hayakawa, Masao; Nagashima, Nobuo

    2008-08-01

    In recent years, incidents of the stress corrosion cracking (SCC) were frequently reported that occurred to the various components of domestic boiling water reactors (BWR), and the cause investigation and measure become the present important issue. By the Japan nuclear energy safety organization (JNES), a research project on the intergranular SCC (IGSCC) in nuclear grade stainless steels (henceforth, IGSCC project) is under enforcement from a point of view to secure safety and reliability of BWR, and SCC growth data of low carbon stainless steels are being accumulated for the weld part or the work-hardened region adjacent to the weld metal. In the project, it has been an important subject to guarantee the validity of accumulated SCC data. At a crack tip of SCC in compact tension (CT) type specimen used for the SCC propagation test, a macroscopic plastic region is formed where heterogeneity of microstructure developed by microscopic sliding and dislocations is observed. However, there is little quantitative information on the plastic region, and therefore, to assess the data of macroscopic SCC growth rate and the validity of propagation test method, it is essentially required to investigate the plastic region at the crack tip in detail from a microscopic viewpoint. This report describes a result of the research conducted by the Japan Atomic Energy Agency and the National Institute for Materials Science under contract with JNES that was concerned with a multi-scale analysis of plastic deformation behavior at the crack tip of SCC. The research was carried out to evaluate the validity of the SCC growth data acquired in the IGSCC project based on a mechanistic understanding of SCC. For the purpose, in this research, analyses of the plastic deformation behavior and microstructure around the crack tip were performed in a nano-order scale. The hardness measured in nano, meso and macro scales was employed as a common index of the strength, and the essential data necessary

  12. Geo-spatial Cognition on Human's Social Activity Space Based on Multi-scale Grids

    Directory of Open Access Journals (Sweden)

    ZHAI Weixin

    2016-12-01

    Full Text Available Widely applied location aware devices, including mobile phones and GPS receivers, have provided great convenience for collecting large volume individuals' geographical information. The researches on the human's society behavior space has attracts an increasingly number of researchers. In our research, based on location-based Flickr data From 2004 to May, 2014 in China, we choose five levels of spatial grids to form the multi-scale frame for investigate the correlation between the scale and the geo-spatial cognition on human's social activity space. The HT-index is selected as the fractal inspired by Alexander to estimate the maturity of the society activity on different scales. The results indicate that that the scale characteristics are related to the spatial cognition to a certain extent. It is favorable to use the spatial grid as a tool to control scales for geo-spatial cognition on human's social activity space.

  13. Tuple image multi-scale optical flow for detailed cardiac motion extraction: Application to left ventricle rotation analysis

    NARCIS (Netherlands)

    Assen, van H.C.; Florack, L.M.J.; Westenberg, J.J.M.; Haar Romenij, ter B.M.; Hamarneh, G.; Abugharbieh, R.

    2008-01-01

    We present a new method for detailed tracking of cardiac motion based on MR-tagging imaging, multi-scale optical flow, and HARP-like image filtering.In earlier work, we showed that the results obtained with our method correlate very well with Phase Contrast MRI. In this paper we combine the

  14. Multi-Scale Entropy Analysis as a Method for Time-Series Analysis of Climate Data

    Directory of Open Access Journals (Sweden)

    Heiko Balzter

    2015-03-01

    Full Text Available Evidence is mounting that the temporal dynamics of the climate system are changing at the same time as the average global temperature is increasing due to multiple climate forcings. A large number of extreme weather events such as prolonged cold spells, heatwaves, droughts and floods have been recorded around the world in the past 10 years. Such changes in the temporal scaling behaviour of climate time-series data can be difficult to detect. While there are easy and direct ways of analysing climate data by calculating the means and variances for different levels of temporal aggregation, these methods can miss more subtle changes in their dynamics. This paper describes multi-scale entropy (MSE analysis as a tool to study climate time-series data and to identify temporal scales of variability and their change over time in climate time-series. MSE estimates the sample entropy of the time-series after coarse-graining at different temporal scales. An application of MSE to Central European, variance-adjusted, mean monthly air temperature anomalies (CRUTEM4v is provided. The results show that the temporal scales of the current climate (1960–2014 are different from the long-term average (1850–1960. For temporal scale factors longer than 12 months, the sample entropy increased markedly compared to the long-term record. Such an increase can be explained by systems theory with greater complexity in the regional temperature data. From 1961 the patterns of monthly air temperatures are less regular at time-scales greater than 12 months than in the earlier time period. This finding suggests that, at these inter-annual time scales, the temperature variability has become less predictable than in the past. It is possible that climate system feedbacks are expressed in altered temporal scales of the European temperature time-series data. A comparison with the variance and Shannon entropy shows that MSE analysis can provide additional information on the

  15. Alzheimer's Disease Detection in Brain Magnetic Resonance Images Using Multiscale Fractal Analysis

    International Nuclear Information System (INIS)

    Lahmiri, Salim; Boukadoum, Mounir

    2013-01-01

    We present a new automated system for the detection of brain magnetic resonance images (MRI) affected by Alzheimer's disease (AD). The MRI is analyzed by means of multiscale analysis (MSA) to obtain its fractals at six different scales. The extracted fractals are used as features to differentiate healthy brain MRI from those of AD by a support vector machine (SVM) classifier. The result of classifying 93 brain MRIs consisting of 51 images of healthy brains and 42 of brains affected by AD, using leave-one-out cross-validation method, yielded 99.18% ± 0.01 classification accuracy, 100% sensitivity, and 98.20% ± 0.02 specificity. These results and a processing time of 5.64 seconds indicate that the proposed approach may be an efficient diagnostic aid for radiologists in the screening for AD

  16. Microstructure-based multiscale modeling of elevated temperature deformation in aluminum alloys

    International Nuclear Information System (INIS)

    Krajewski, Paul E.; Hector, Louis G.; Du Ningning; Bower, Allan F.

    2010-01-01

    A multiscale model for predicting elevated temperature deformation in Al-Mg alloys is presented. Constitutive models are generated from a theoretical methodology and used to investigate the effects of grain size on formability. Flow data are computed with a polycrystalline, microstructure-based model which accounts for grain boundary sliding, stress-induced diffusion, and dislocation creep. Favorable agreement is found between the computed flow data and elevated temperature tensile measurements. A creep constitutive model is then fit to the computed flow data and used in finite-element simulations of two simple gas pressure forming processes, where favorable results are observed. These results are fully consistent with gas pressure forming experiments, and suggest a greater role for constitutive models, derived largely from theoretical methodologies, in the design of Al alloys with enhanced elevated temperature formability. The methodology detailed herein provides a framework for incorporation of results from atomistic-scale models of dislocation creep and diffusion.

  17. Vision-Based Bicycle Detection Using Multiscale Block Local Binary Pattern

    Directory of Open Access Journals (Sweden)

    Hongyu Hu

    2014-01-01

    Full Text Available Bicycle traffic has heavy proportion among all travel modes in some developing countries, which is crucial for urban traffic control and management as well as facility design. This paper proposes a real-time multiple bicycle detection algorithm based on video. At first, an effective feature called multiscale block local binary pattern (MBLBP is extracted for representing the moving object, which is a well-classified feature to distinguish between bicycles and nonbicycles; then, a cascaded bicycle classifier trained by AdaBoost algorithm is proposed, which has a good computation efficiency. Finally, the method is tested with video sequence captured from the real-world traffic scenario. The bicycles in the test scenario are successfully detected.

  18. Exploring the effects of climatic variables on monthly precipitation variation using a continuous wavelet-based multiscale entropy approach.

    Science.gov (United States)

    Roushangar, Kiyoumars; Alizadeh, Farhad; Adamowski, Jan

    2018-08-01

    Understanding precipitation on a regional basis is an important component of water resources planning and management. The present study outlines a methodology based on continuous wavelet transform (CWT) and multiscale entropy (CWME), combined with self-organizing map (SOM) and k-means clustering techniques, to measure and analyze the complexity of precipitation. Historical monthly precipitation data from 1960 to 2010 at 31 rain gauges across Iran were preprocessed by CWT. The multi-resolution CWT approach segregated the major features of the original precipitation series by unfolding the structure of the time series which was often ambiguous. The entropy concept was then applied to components obtained from CWT to measure dispersion, uncertainty, disorder, and diversification of subcomponents. Based on different validity indices, k-means clustering captured homogenous areas more accurately, and additional analysis was performed based on the outcome of this approach. The 31 rain gauges in this study were clustered into 6 groups, each one having a unique CWME pattern across different time scales. The results of clustering showed that hydrologic similarity (multiscale variation of precipitation) was not based on geographic contiguity. According to the pattern of entropy across the scales, each cluster was assigned an entropy signature that provided an estimation of the entropy pattern of precipitation data in each cluster. Based on the pattern of mean CWME for each cluster, a characteristic signature was assigned, which provided an estimation of the CWME of a cluster across scales of 1-2, 3-8, and 9-13 months relative to other stations. The validity of the homogeneous clusters demonstrated the usefulness of the proposed approach to regionalize precipitation. Further analysis based on wavelet coherence (WTC) was performed by selecting central rain gauges in each cluster and analyzing against temperature, wind, Multivariate ENSO index (MEI), and East Atlantic (EA) and

  19. A multiscale asymptotic analysis of time evolution equations on the complex plane

    Energy Technology Data Exchange (ETDEWEB)

    Braga, Gastão A., E-mail: gbraga@mat.ufmg.br [Departamento de Matemática, Universidade Federal de Minas Gerais, Caixa Postal 702, 30161-970 Belo Horizonte, MG (Brazil); Conti, William R. P., E-mail: wrpconti@gmail.com [Departamento de Ciências do Mar, Universidade Federal de São Paulo, Rua Dr. Carvalho de Mendonça 144, 11070-100 Santos, SP (Brazil)

    2016-07-15

    Using an appropriate norm on the space of entire functions, we extend to the complex plane the renormalization group method as developed by Bricmont et al. The method is based upon a multiscale approach that allows for a detailed description of the long time asymptotics of solutions to initial value problems. The time evolution equation considered here arises in the study of iterations of the block spin renormalization group transformation for the hierarchical N-vector model. We show that, for initial conditions belonging to a certain Fréchet space of entire functions of exponential type, the asymptotics is universal in the sense that it is dictated by the fixed point of a certain operator acting on the space of initial conditions.

  20. Complexity Analysis of Carbon Market Using the Modified Multi-Scale Entropy

    Directory of Open Access Journals (Sweden)

    Jiuli Yin

    2018-06-01

    Full Text Available Carbon markets provide a market-based way to reduce climate pollution. Subject to general market regulations, the major existing emission trading markets present complex characteristics. This paper analyzes the complexity of carbon market by using the multi-scale entropy. Pilot carbon markets in China are taken as the example. Moving average is adopted to extract the scales due to the short length of the data set. Results show a low-level complexity inferring that China’s pilot carbon markets are quite immature in lack of market efficiency. However, the complexity varies in different time scales. China’s carbon markets (except for the Chongqing pilot are more complex in the short period than in the long term. Furthermore, complexity level in most pilot markets increases as the markets developed, showing an improvement in market efficiency. All these results demonstrate that an effective carbon market is required for the full function of emission trading.

  1. Modelling concrete behaviour at early-age: multi-scale analysis and simulation of a massive disposal structure

    International Nuclear Information System (INIS)

    Honorio-De-Faria, Tulio

    2015-01-01

    The accurate prediction of the long and short-term behaviour of concrete structures in the nuclear domain is essential to ensure optimal performances (integrity, containment properties) during their service life. In the particular case of massive concrete structures, at early age the heat produced by hydration reactions cannot be evacuated fast enough so that high temperatures may be reached and the resulting gradients of temperature might lead to cracking according to the external and internal restraints to which the structures are subjected. The goals of this study are (1) to perform numerical simulations in order to describe and predict the thermo-chemo-mechanical behaviour at early-age of a massive concrete structure devoted to nuclear waste disposal on surface, and (2) to develop and apply up-scaling tools to estimate rigorously the key properties of concrete needed in an early-age analysis from the composition of the material. Firstly, a chemo-thermal analysis aims at determining the influence of convection, solar radiation, re-radiation and hydration heat on the thermal response of the structure. Practical recommendations regarding concreting temperatures are provided in order to limit the maximum temperature reached within the structure. Then, by means of a mechanical analysis, simplified and more complex (i.e. accounting for coupled creep and damage) modelling strategies are used to assess scenarios involving different boundary conditions defined from the previous chemo-thermal analysis. Secondly, a study accounting for the multi-scale character of concrete is performed. A simplified model of cement hydration kinetics is proposed. The evolution of the different phases at the cement paste level can be estimated. Then, analytical and numerical tools to upscale the ageing properties are presented and applied to estimate the mechanical and thermal properties of cement based materials. Finally, the input data used in the structural analysis are compared with

  2. Multi-scale salient feature extraction on mesh models

    KAUST Repository

    Yang, Yongliang; Shen, ChaoHui

    2012-01-01

    We present a new method of extracting multi-scale salient features on meshes. It is based on robust estimation of curvature on multiple scales. The coincidence between salient feature and the scale of interest can be established straightforwardly, where detailed feature appears on small scale and feature with more global shape information shows up on large scale. We demonstrate this multi-scale description of features accords with human perception and can be further used for several applications as feature classification and viewpoint selection. Experiments exhibit that our method as a multi-scale analysis tool is very helpful for studying 3D shapes. © 2012 Springer-Verlag.

  3. Multi-scale modeling of the thermo-mechanical behavior of particle-based composites

    International Nuclear Information System (INIS)

    Di Paola, F.

    2010-01-01

    The aim of this work was to perform numerical simulations of the thermal and mechanical behavior of a particle-based nuclear fuel. This is a refractory composite material made of UO 2 spherical particles which are coated with two layers of pyrocarbon and embedded in a graphite matrix at a high volume fraction (45%). The objective was to develop a multi-scale modeling of this composite material which can estimate its mean behavior as well as the heterogeneity of the local mechanical variables. The first part of this work was dedicated to the modeling of the microstructure in 3D. To do this, we developed tools to generate random distributions of spheres, meshes and to characterize the morphology of the microstructure towards the finite element code Cast3M. A hundred of numerical samples of the composite were created. The second part was devoted to the characterization of the thermo-elastic behavior by the finite element modeling of the samples. We studied the influence of different modeling parameters, one of them is the boundary conditions. We proposed a method to vanish the boundary conditions effects from the computed solution by analyzing it on an internal sub-volume of the sample obtained by erosion. Then, we determined the effective properties (elastic moduli, thermal conductivity and thermal expansion) and the stress distribution within the matrix. Finally, in the third part we proposed a multi-scale modeling to determine the mean values and the variance and covariance of the local mechanical variables for any macroscopic load. This statistical approach have been used to estimate the intra-phase distribution of these variables in the composite material. (author) [fr

  4. Multi-scale modeling of the thermo-mechanical behavior of particle-based composites

    International Nuclear Information System (INIS)

    Di Paola, F.

    2010-11-01

    The aim of this work was to perform numerical simulations of the thermal and mechanical behavior of a particle-based nuclear fuel. This is a refractory composite material made of UO 2 spherical particles which are coated with two layers of pyrocarbon and embedded in a graphite matrix at a high volume fraction (45 %). The objective was to develop a multi-scale modeling of this composite material which can estimate its mean behavior as well as the heterogeneity of the local mechanical variables. The first part of this work was dedicated to the modeling of the microstructure in 3D. To do this, we developed tools to generate random distributions of spheres, meshes and to characterize the morphology of the microstructure towards the finite element code Cast3M. A hundred of numerical samples of the composite were created. The second part was devoted to the characterization of the thermo-elastic behavior by the finite element modeling of the samples. We studied the influence of different modeling parameters, one of them is the boundary conditions. We proposed a method to vanish the boundary conditions effects from the computed solution by analyzing it on an internal sub-volume of the sample obtained by erosion. Then, we determined the effective properties (elastic moduli, thermal conductivity and thermal expansion) and the stress distribution within the matrix. Finally, in the third part we proposed a multi-scale modeling to determine the mean values and the variance and covariance of the local mechanical variables for any macroscopic load. This statistical approach have been used to estimate the intra-phase distribution of these variables in the composite material. (author)

  5. Investigation of geometrical effects in the carbon allotropes manipulation based on AFM: multiscale approach

    Energy Technology Data Exchange (ETDEWEB)

    Korayem, M. H., E-mail: hkorayem@iust.ac.ir; Hefzabad, R. N.; Homayooni, A.; Aslani, H. [Iran University of Science and Technology, Robotic Research Laboratory, Center of Excellence in Experimental Solid Mechanics and Dynamics, School of Mechanical Engineering (Iran, Islamic Republic of)

    2017-01-15

    Carbon allotropes are used as nanocarriers for drug and cell delivery. To obtain an accurate result in the nanoscale, it is important to use a precise model. In this paper, a multiscale approach is presented to investigate the manipulation process of carbon allotropes based on atomic force microscopy (AFM). For this purpose, the AFM setup is separated into two parts with different sizes as macro field (MF) and nano field (NF). Using Kirchhoff’s plate model, the cantilever (the main part of MF) is modeled. The molecular dynamics method is applied to model the NF part, and then the MF and NF are coupled with the multiscale algorithm. With this model, by considering the effect of size and shape, the manipulation of carbon allotropes is carried out. The manipulations of armchair CNTs and fullerenes are performed to study the diameter changing effects. The result shows that the manipulation and friction force increases by increasing the diameter. The result of the indentation depth for the armchair CNTs indicates that decreasing the diameter causes the indentation depth to reduce. Moreover, the manipulations of four kinds of carbon allotropes with the same number of atoms have been studied to investigate the geometrical effects. The shapes of these nanoparticles change from sphere to cylinder. The results illustrate that the manipulation and the friction force decrease as the nanoparticle shape varies from sphere to cylinder. The Von-Mises results demonstrate that by changing the nanoparticle shape from the spherical to the cylindrical form, the stress increases, although the manipulation force reduces.

  6. Investigation of geometrical effects in the carbon allotropes manipulation based on AFM: multiscale approach

    International Nuclear Information System (INIS)

    Korayem, M. H.; Hefzabad, R. N.; Homayooni, A.; Aslani, H.

    2017-01-01

    Carbon allotropes are used as nanocarriers for drug and cell delivery. To obtain an accurate result in the nanoscale, it is important to use a precise model. In this paper, a multiscale approach is presented to investigate the manipulation process of carbon allotropes based on atomic force microscopy (AFM). For this purpose, the AFM setup is separated into two parts with different sizes as macro field (MF) and nano field (NF). Using Kirchhoff’s plate model, the cantilever (the main part of MF) is modeled. The molecular dynamics method is applied to model the NF part, and then the MF and NF are coupled with the multiscale algorithm. With this model, by considering the effect of size and shape, the manipulation of carbon allotropes is carried out. The manipulations of armchair CNTs and fullerenes are performed to study the diameter changing effects. The result shows that the manipulation and friction force increases by increasing the diameter. The result of the indentation depth for the armchair CNTs indicates that decreasing the diameter causes the indentation depth to reduce. Moreover, the manipulations of four kinds of carbon allotropes with the same number of atoms have been studied to investigate the geometrical effects. The shapes of these nanoparticles change from sphere to cylinder. The results illustrate that the manipulation and the friction force decrease as the nanoparticle shape varies from sphere to cylinder. The Von-Mises results demonstrate that by changing the nanoparticle shape from the spherical to the cylindrical form, the stress increases, although the manipulation force reduces.

  7. Multiscale Cancer Modeling

    Science.gov (United States)

    Macklin, Paul; Cristini, Vittorio

    2013-01-01

    Simulating cancer behavior across multiple biological scales in space and time, i.e., multiscale cancer modeling, is increasingly being recognized as a powerful tool to refine hypotheses, focus experiments, and enable more accurate predictions. A growing number of examples illustrate the value of this approach in providing quantitative insight on the initiation, progression, and treatment of cancer. In this review, we introduce the most recent and important multiscale cancer modeling works that have successfully established a mechanistic link between different biological scales. Biophysical, biochemical, and biomechanical factors are considered in these models. We also discuss innovative, cutting-edge modeling methods that are moving predictive multiscale cancer modeling toward clinical application. Furthermore, because the development of multiscale cancer models requires a new level of collaboration among scientists from a variety of fields such as biology, medicine, physics, mathematics, engineering, and computer science, an innovative Web-based infrastructure is needed to support this growing community. PMID:21529163

  8. Multi-scale Analysis of High Resolution Topography: Feature Extraction and Identification of Landscape Characteristic Scales

    Science.gov (United States)

    Passalacqua, P.; Sangireddy, H.; Stark, C. P.

    2015-12-01

    With the advent of digital terrain data, detailed information on terrain characteristics and on scale and location of geomorphic features is available over extended areas. Our ability to observe landscapes and quantify topographic patterns has greatly improved, including the estimation of fluxes of mass and energy across landscapes. Challenges still remain in the analysis of high resolution topography data; the presence of features such as roads, for example, challenges classic methods for feature extraction and large data volumes require computationally efficient extraction and analysis methods. Moreover, opportunities exist to define new robust metrics of landscape characterization for landscape comparison and model validation. In this presentation we cover recent research in multi-scale and objective analysis of high resolution topography data. We show how the analysis of the probability density function of topographic attributes such as slope, curvature, and topographic index contains useful information for feature localization and extraction. The analysis of how the distributions change across scales, quantified by the behavior of modal values and interquartile range, allows the identification of landscape characteristic scales, such as terrain roughness. The methods are introduced on synthetic signals in one and two dimensions and then applied to a variety of landscapes of different characteristics. Validation of the methods includes the analysis of modeled landscapes where the noise distribution is known and features of interest easily measured.

  9. Interacting price model and fluctuation behavior analysis from Lempel–Ziv complexity and multi-scale weighted-permutation entropy

    International Nuclear Information System (INIS)

    Li, Rui; Wang, Jun

    2016-01-01

    A financial price model is developed based on the voter interacting system in this work. The Lempel–Ziv complexity is introduced to analyze the complex behaviors of the stock market. Some stock market stylized facts including fat tails, absence of autocorrelation and volatility clustering are investigated for the proposed price model firstly. Then the complexity of fluctuation behaviors of the real stock markets and the proposed price model are mainly explored by Lempel–Ziv complexity (LZC) analysis and multi-scale weighted-permutation entropy (MWPE) analysis. A series of LZC analyses of the returns and the absolute returns of daily closing prices and moving average prices are performed. Moreover, the complexity of the returns, the absolute returns and their corresponding intrinsic mode functions (IMFs) derived from the empirical mode decomposition (EMD) with MWPE is also investigated. The numerical empirical study shows similar statistical and complex behaviors between the proposed price model and the real stock markets, which exhibits that the proposed model is feasible to some extent. - Highlights: • A financial price dynamical model is developed based on the voter interacting system. • Lempel–Ziv complexity is the firstly applied to investigate the stock market dynamics system. • MWPE is employed to explore the complexity fluctuation behaviors of the stock market. • Empirical results show the feasibility of the proposed financial model.

  10. Interacting price model and fluctuation behavior analysis from Lempel–Ziv complexity and multi-scale weighted-permutation entropy

    Energy Technology Data Exchange (ETDEWEB)

    Li, Rui, E-mail: lirui1401@bjtu.edu.cn; Wang, Jun

    2016-01-08

    A financial price model is developed based on the voter interacting system in this work. The Lempel–Ziv complexity is introduced to analyze the complex behaviors of the stock market. Some stock market stylized facts including fat tails, absence of autocorrelation and volatility clustering are investigated for the proposed price model firstly. Then the complexity of fluctuation behaviors of the real stock markets and the proposed price model are mainly explored by Lempel–Ziv complexity (LZC) analysis and multi-scale weighted-permutation entropy (MWPE) analysis. A series of LZC analyses of the returns and the absolute returns of daily closing prices and moving average prices are performed. Moreover, the complexity of the returns, the absolute returns and their corresponding intrinsic mode functions (IMFs) derived from the empirical mode decomposition (EMD) with MWPE is also investigated. The numerical empirical study shows similar statistical and complex behaviors between the proposed price model and the real stock markets, which exhibits that the proposed model is feasible to some extent. - Highlights: • A financial price dynamical model is developed based on the voter interacting system. • Lempel–Ziv complexity is the firstly applied to investigate the stock market dynamics system. • MWPE is employed to explore the complexity fluctuation behaviors of the stock market. • Empirical results show the feasibility of the proposed financial model.

  11. Automatic facial pore analysis system using multi-scale pore detection.

    Science.gov (United States)

    Sun, J Y; Kim, S W; Lee, S H; Choi, J E; Ko, S J

    2017-08-01

    As facial pore widening and its treatments have become common concerns in the beauty care field, the necessity for an objective pore-analyzing system has been increased. Conventional apparatuses lack in usability requiring strong light sources and a cumbersome photographing process, and they often yield unsatisfactory analysis results. This study was conducted to develop an image processing technique for automatic facial pore analysis. The proposed method detects facial pores using multi-scale detection and optimal scale selection scheme and then extracts pore-related features such as total area, average size, depth, and the number of pores. Facial photographs of 50 subjects were graded by two expert dermatologists, and correlation analyses between the features and clinical grading were conducted. We also compared our analysis result with those of conventional pore-analyzing devices. The number of large pores and the average pore size were highly correlated with the severity of pore enlargement. In comparison with the conventional devices, the proposed analysis system achieved better performance showing stronger correlation with the clinical grading. The proposed system is highly accurate and reliable for measuring the severity of skin pore enlargement. It can be suitably used for objective assessment of the pore tightening treatments. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  12. Study on GPS Common-view Observation Data with Multiscale Kalman Filter Based on Correlation Structure of the Discrete Wavelet Coefficients

    National Research Council Canada - National Science Library

    Xiaojuan, Ou; Wei, Zhou; Jianguo, Yu

    2005-01-01

    In this paper, we pay our attention to the multiscale kalman algorithm based on correlation structure of the discrete wavelet coefficients for the restoration of the GPS common-view observation data...

  13. Localized multi-scale energy and vorticity analysis. II. Finite-amplitude instability theory and validation

    Science.gov (United States)

    San Liang, X.; Robinson, Allan R.

    2007-12-01

    A novel localized finite-amplitude hydrodynamic stability analysis is established in a unified treatment for the study of real oceanic and atmospheric processes, which are in general highly nonlinear, and intermittent in space and time. We first re-state the classical definition using the multi-scale energy and vorticity analysis (MS-EVA) developed in Liang and Robinson [Liang, X.S., Robinson, A.R., 2005. Localized multiscale energy and vorticity analysis. I. Fundamentals. Dyn. Atmos. Oceans 38, 195-230], and then manipulate certain global operators to achieve the temporal and spatial localization. The key of the spatial localization is transfer-transport separation, which is made precise with the concept of perfect transfer, while relaxation of marginalization leads to the localization of time. In doing so the information of transfer lost in the averages is retrieved and an easy-to-use instability metric is obtained. The resulting metric is field-like (Eulerian), conceptually generalizing the classical formalism, a bulk notion over the whole system. In this framework, an instability has a structure, which is of particular use for open flow processes. We check the structure of baroclinic instability with the benchmark Eady model solution, and the Iceland-Faeroe Frontal (IFF) intrusion, a highly localized and nonlinear process occurring frequently in the region between Iceland and Faeroe Islands. A clear isolated baroclinic instability is identified around the intrusion, which is further found to be characterized by the transition from a spatially growing mode to a temporally growing mode. We also check the consistency of the MS-EVA dynamics with the barotropic Kuo model. An observation is that a local perturbation burst does not necessarily imply an instability: the perturbation energy could be transported from other processes occurring elsewhere. We find that our analysis yields a Kuo theorem-consistent mean-eddy interaction, which is not seen in a conventional

  14. Mixed multiscale finite element methods using approximate global information based on partial upscaling

    KAUST Repository

    Jiang, Lijian; Efendiev, Yalchin; Mishev, IIya

    2009-01-01

    The use of limited global information in multiscale simulations is needed when there is no scale separation. Previous approaches entail fine-scale simulations in the computation of the global information. The computation of the global information

  15. Single Image Super-Resolution Based on Multi-Scale Competitive Convolutional Neural Network.

    Science.gov (United States)

    Du, Xiaofeng; Qu, Xiaobo; He, Yifan; Guo, Di

    2018-03-06

    Deep convolutional neural networks (CNNs) are successful in single-image super-resolution. Traditional CNNs are limited to exploit multi-scale contextual information for image reconstruction due to the fixed convolutional kernel in their building modules. To restore various scales of image details, we enhance the multi-scale inference capability of CNNs by introducing competition among multi-scale convolutional filters, and build up a shallow network under limited computational resources. The proposed network has the following two advantages: (1) the multi-scale convolutional kernel provides the multi-context for image super-resolution, and (2) the maximum competitive strategy adaptively chooses the optimal scale of information for image reconstruction. Our experimental results on image super-resolution show that the performance of the proposed network outperforms the state-of-the-art methods.

  16. A voxel-based multiscale model to simulate the radiation response of hypoxic tumors.

    Science.gov (United States)

    Espinoza, I; Peschke, P; Karger, C P

    2015-01-01

    In radiotherapy, it is important to predict the response of tumors to irradiation prior to the treatment. This is especially important for hypoxic tumors, which are known to be highly radioresistant. Mathematical modeling based on the dose distribution, biological parameters, and medical images may help to improve this prediction and to optimize the treatment plan. A voxel-based multiscale tumor response model for simulating the radiation response of hypoxic tumors was developed. It considers viable and dead tumor cells, capillary and normal cells, as well as the most relevant biological processes such as (i) proliferation of tumor cells, (ii) hypoxia-induced angiogenesis, (iii) spatial exchange of cells leading to tumor growth, (iv) oxygen-dependent cell survival after irradiation, (v) resorption of dead cells, and (vi) spatial exchange of cells leading to tumor shrinkage. Oxygenation is described on a microscopic scale using a previously published tumor oxygenation model, which calculates the oxygen distribution for each voxel using the vascular fraction as the most important input parameter. To demonstrate the capabilities of the model, the dependence of the oxygen distribution on tumor growth and radiation-induced shrinkage is investigated. In addition, the impact of three different reoxygenation processes is compared and tumor control probability (TCP) curves for a squamous cells carcinoma of the head and neck (HNSSC) are simulated under normoxic and hypoxic conditions. The model describes the spatiotemporal behavior of the tumor on three different scales: (i) on the macroscopic scale, it describes tumor growth and shrinkage during radiation treatment, (ii) on a mesoscopic scale, it provides the cell density and vascular fraction for each voxel, and (iii) on the microscopic scale, the oxygen distribution may be obtained in terms of oxygen histograms. With increasing tumor size, the simulated tumors develop a hypoxic core. Within the model, tumor shrinkage was

  17. A voxel-based multiscale model to simulate the radiation response of hypoxic tumors

    International Nuclear Information System (INIS)

    Espinoza, I.; Peschke, P.; Karger, C. P.

    2015-01-01

    Purpose: In radiotherapy, it is important to predict the response of tumors to irradiation prior to the treatment. This is especially important for hypoxic tumors, which are known to be highly radioresistant. Mathematical modeling based on the dose distribution, biological parameters, and medical images may help to improve this prediction and to optimize the treatment plan. Methods: A voxel-based multiscale tumor response model for simulating the radiation response of hypoxic tumors was developed. It considers viable and dead tumor cells, capillary and normal cells, as well as the most relevant biological processes such as (i) proliferation of tumor cells, (ii) hypoxia-induced angiogenesis, (iii) spatial exchange of cells leading to tumor growth, (iv) oxygen-dependent cell survival after irradiation, (v) resorption of dead cells, and (vi) spatial exchange of cells leading to tumor shrinkage. Oxygenation is described on a microscopic scale using a previously published tumor oxygenation model, which calculates the oxygen distribution for each voxel using the vascular fraction as the most important input parameter. To demonstrate the capabilities of the model, the dependence of the oxygen distribution on tumor growth and radiation-induced shrinkage is investigated. In addition, the impact of three different reoxygenation processes is compared and tumor control probability (TCP) curves for a squamous cells carcinoma of the head and neck (HNSSC) are simulated under normoxic and hypoxic conditions. Results: The model describes the spatiotemporal behavior of the tumor on three different scales: (i) on the macroscopic scale, it describes tumor growth and shrinkage during radiation treatment, (ii) on a mesoscopic scale, it provides the cell density and vascular fraction for each voxel, and (iii) on the microscopic scale, the oxygen distribution may be obtained in terms of oxygen histograms. With increasing tumor size, the simulated tumors develop a hypoxic core. Within the

  18. A hybrid model for dissolved oxygen prediction in aquaculture based on multi-scale features

    Directory of Open Access Journals (Sweden)

    Chen Li

    2018-03-01

    Full Text Available To increase prediction accuracy of dissolved oxygen (DO in aquaculture, a hybrid model based on multi-scale features using ensemble empirical mode decomposition (EEMD is proposed. Firstly, original DO datasets are decomposed by EEMD and we get several components. Secondly, these components are used to reconstruct four terms including high frequency term, intermediate frequency term, low frequency term and trend term. Thirdly, according to the characteristics of high and intermediate frequency terms, which fluctuate violently, the least squares support vector machine (LSSVR is used to predict the two terms. The fluctuation of low frequency term is gentle and periodic, so it can be modeled by BP neural network with an optimal mind evolutionary computation (MEC-BP. Then, the trend term is predicted using grey model (GM because it is nearly linear. Finally, the prediction values of DO datasets are calculated by the sum of the forecasting values of all terms. The experimental results demonstrate that our hybrid model outperforms EEMD-ELM (extreme learning machine based on EEMD, EEMD-BP and MEC-BP models based on the mean absolute error (MAE, mean absolute percentage error (MAPE, mean square error (MSE and root mean square error (RMSE. Our hybrid model is proven to be an effective approach to predict aquaculture DO.

  19. Multiscale Hybrid Micro-Nanocomposites Based on Carbon Nanotubes and Carbon Fibers

    Directory of Open Access Journals (Sweden)

    Fawad Inam

    2010-01-01

    Full Text Available Amino-modified double wall carbon nanotube (DWCNT-NH2/carbon fiber (CF/epoxy hybrid micro-nanocomposite laminates were prepared by a resin infusion technique. DWCNT-NH2/epoxy nanocomposites and carbon fiber/epoxy microcomposites were made for comparison. Morphological analysis of the hybrid composites was performed using field emission scanning electron microscope. A good dispersion at low loadings of carbon nanotubes (CNTs in epoxy matrix was achieved by a bath ultrasonication method. Mechanical characterization of the hybrid micro-nanocomposites manufactured by a resin infusion process included three-point bending, mode I interlaminar toughness, dynamic mechanical analysis, and drop-weight impact testing. The addition of small amounts of CNTs (0.025, 0.05, and 0.1 wt% to epoxy resins for the fabrication of multiscale carbon fiber composites resulted in a maximum enhancement in flexural modulus by 35%, a 5% improvement in flexural strength, a 6% improvement in absorbed impact energy, and 23% decrease in the mode I interlaminar toughness. Hybridization of carbon fiber-reinforced epoxy using CNTs resulted in a reduction in and dampening characteristics, presumably as a result of the presence of micron-sized agglomerates.

  20. Distributed multiscale computing

    NARCIS (Netherlands)

    Borgdorff, J.

    2014-01-01

    Multiscale models combine knowledge, data, and hypotheses from different scales. Simulating a multiscale model often requires extensive computation. This thesis evaluates distributing these computations, an approach termed distributed multiscale computing (DMC). First, the process of multiscale

  1. Multiscale Entropy Analysis of Heart Rate Variability for Assessing the Severity of Sleep Disordered Breathing

    Directory of Open Access Journals (Sweden)

    Wen-Yao Pan

    2015-01-01

    Full Text Available Obstructive sleep apnea (OSA is an independent cardiovascular risk factor to which autonomic nervous dysfunction has been reported to be an important contributor. Ninety subjects recruited from the sleep center of a single medical center were divided into four groups: normal snoring subjects without OSA (apnea hypopnea index, AHI < 5, n = 11, mild OSA (5 ≤ AHI < 15, n = 10, moderate OSA (15 ≤ AHI < 30, n = 24, and severe OSA (AHI ≥ 30, n = 45. Demographic (i.e., age, gender, anthropometric (i.e., body mass index, neck circumference, and polysomnographic (PSG data were recorded and compared among the different groups. For each subject, R-R intervals (RRI from 10 segments of 10-minute electrocardiogram recordings during non-rapid eye movement sleep at stage N2 were acquired and analyzed for heart rate variability (HRV and sample entropy using multiscale entropy index (MEI that was divided into small scale (MEISS, scale 1–5 and large scale (MEILS, scale 6–10. Our results not only demonstrated that MEISS could successfully distinguish normal snoring subjects and those with mild OSA from those with moderate and severe disease, but also revealed good correlation between MEISS and AHI with Spearman correlation analysis (r = −0.684, p < 0.001. Therefore, using the two parameters of EEG and ECG, MEISS may serve as a simple preliminary screening tool for assessing the severity of OSA before proceeding to PSG analysis.

  2. Non-classic multiscale modeling of manipulation based on AFM, in aqueous and humid ambient

    Science.gov (United States)

    Korayem, M. H.; Homayooni, A.; Hefzabad, R. N.

    2018-05-01

    To achieve a precise manipulation, it is important that an accurate model consisting the size effect and environmental conditions be employed. In this paper, the non-classical multiscale modeling is developed to investigate the manipulation in a vacuum, aqueous and humid ambient. The manipulation structure is considered into two parts as a macro-field (MF) and a nano-field (NF). The governing equations of the AFM components (consist of the cantilever and tip) in the MF are derived based on the modified couple stress theory. The material length scale parameter is used to study the size effect. The fluid flow in the MF is assumed as the Couette and Creeping flows. Moreover, the NF is modeled using the molecular dynamics. The Electro-Based (ELBA) model is considered to model the ambient condition in the NF. The nanoparticle in the different conditions is taken into account to study the manipulation. The results of the manipulation indicate that the predicted deflection of the non-classical model is less than the classical one. Comparison of the nanoparticle travelled distance on substrate shows that the manipulation in the submerged condition is close to the ideal manipulation. The results of humid condition illustrate that by increasing the relative humidity (RH) the manipulation force decreases. Furthermore, Root Mean Square (RMS) as a criterion of damage demonstrates that the submerged nanoparticle has the minimum damage, however, the minimum manipulation force occurs in superlative humid ambient.

  3. Multiscale modeling of graphene- and nanotube-based reinforced polymer nanocomposites

    Energy Technology Data Exchange (ETDEWEB)

    Montazeri, A. [Computational Physical Sciences Research Laboratory, School of Nano-Science, Institute for Research in Fundamental Sciences (IPM), Tehran (Iran, Islamic Republic of); Rafii-Tabar, H., E-mail: rafii-tabar@nano.ipm.ac.ir [Computational Physical Sciences Research Laboratory, School of Nano-Science, Institute for Research in Fundamental Sciences (IPM), Tehran (Iran, Islamic Republic of); Department of Medical Physics and Biomedical Engineering, and Research Centre for Medical Nanotechnology and Tissue Engineering, Shahid Beheshti University of Medical Sciences, Evin, Tehran (Iran, Islamic Republic of)

    2011-10-31

    A combination of molecular dynamics, molecular structural mechanics, and finite element method is employed to compute the elastic constants of a polymeric nanocomposite embedded with graphene sheets, and carbon nanotubes. The model is first applied to study the effect of inclusion of graphene sheets on the Young modulus of the composite. To explore the significance of the nanofiller geometry, the elastic constants of nanotube-based and graphene-based polymer composites are computed under identical conditions. The reinforcement role of these nanofillers is also investigated in transverse directions. Moreover, the dependence of the nanocomposite's axial Young modulus on the presence of ripples on the surface of the embedded graphene sheets, due to thermal fluctuations, is examined via MD simulations. Finally, we have also studied the effect of sliding motion of graphene layers on the elastic constants of the nanocomposite. -- Highlights: → A hierarchical MD/FEM multiscale model of nanocomposites is developed. → At low nanofiller content, graphene layers perform significantly better than CNTs. → Ripples in the graphene layers reduce the Young modulus of nanocomposites. → The elastic moduli is considerably affected by the shear of graphene layers.

  4. Multiscale modeling of graphene- and nanotube-based reinforced polymer nanocomposites

    International Nuclear Information System (INIS)

    Montazeri, A.; Rafii-Tabar, H.

    2011-01-01

    A combination of molecular dynamics, molecular structural mechanics, and finite element method is employed to compute the elastic constants of a polymeric nanocomposite embedded with graphene sheets, and carbon nanotubes. The model is first applied to study the effect of inclusion of graphene sheets on the Young modulus of the composite. To explore the significance of the nanofiller geometry, the elastic constants of nanotube-based and graphene-based polymer composites are computed under identical conditions. The reinforcement role of these nanofillers is also investigated in transverse directions. Moreover, the dependence of the nanocomposite's axial Young modulus on the presence of ripples on the surface of the embedded graphene sheets, due to thermal fluctuations, is examined via MD simulations. Finally, we have also studied the effect of sliding motion of graphene layers on the elastic constants of the nanocomposite. -- Highlights: → A hierarchical MD/FEM multiscale model of nanocomposites is developed. → At low nanofiller content, graphene layers perform significantly better than CNTs. → Ripples in the graphene layers reduce the Young modulus of nanocomposites. → The elastic moduli is considerably affected by the shear of graphene layers.

  5. Multiscale sample entropy and cross-sample entropy based on symbolic representation and similarity of stock markets

    Science.gov (United States)

    Wu, Yue; Shang, Pengjian; Li, Yilong

    2018-03-01

    A modified multiscale sample entropy measure based on symbolic representation and similarity (MSEBSS) is proposed in this paper to research the complexity of stock markets. The modified algorithm reduces the probability of inducing undefined entropies and is confirmed to be robust to strong noise. Considering the validity and accuracy, MSEBSS is more reliable than Multiscale entropy (MSE) for time series mingled with much noise like financial time series. We apply MSEBSS to financial markets and results show American stock markets have the lowest complexity compared with European and Asian markets. There are exceptions to the regularity that stock markets show a decreasing complexity over the time scale, indicating a periodicity at certain scales. Based on MSEBSS, we introduce the modified multiscale cross-sample entropy measure based on symbolic representation and similarity (MCSEBSS) to consider the degree of the asynchrony between distinct time series. Stock markets from the same area have higher synchrony than those from different areas. And for stock markets having relative high synchrony, the entropy values will decrease with the increasing scale factor. While for stock markets having high asynchrony, the entropy values will not decrease with the increasing scale factor sometimes they tend to increase. So both MSEBSS and MCSEBSS are able to distinguish stock markets of different areas, and they are more helpful if used together for studying other features of financial time series.

  6. Unsupervised DInSAR processing chain for multi-scale displacement analysis

    Science.gov (United States)

    Casu, Francesco; Manunta, Michele

    2016-04-01

    , thus leading to the generation of Interferometric products for both global and local scale displacement analysis. Among several examples, we will show a wide displacement SBAS processing, carried out over the southern California, during which the whole ascending ENVISAT data set of more than 740 images has been fully processed on a Cloud Computing environment in less than 9 hours, leading to the generation of a displacement map of about 150,000 square kilometres. The P-SBAS characteristics allowed also us to integrate the algorithm within the ESA Geohazard Exploitation Platform (GEP), which is based on the use of GRID and Cloud Computing facilities, thus making freely available to the EO community a web tool for massive and systematic interferometric displacement time series generation. This work has been partially supported by: the Italian MIUR under the RITMARE project; the CNR-DPC agreement and the ESA GEP project.

  7. Analysis of Fiber Clustering in Composite Materials Using High-Fidelity Multiscale Micromechanics

    Science.gov (United States)

    Bednarcyk, Brett A.; Aboudi, Jacob; Arnold, Steven M.

    2015-01-01

    A new multiscale micromechanical approach is developed for the prediction of the behavior of fiber reinforced composites in presence of fiber clustering. The developed method is based on a coupled two-scale implementation of the High-Fidelity Generalized Method of Cells theory, wherein both the local and global scales are represented using this micromechanical method. Concentration tensors and effective constitutive equations are established on both scales and linked to establish the required coupling, thus providing the local fields throughout the composite as well as the global properties and effective nonlinear response. Two nondimensional parameters, in conjunction with actual composite micrographs, are used to characterize the clustering of fibers in the composite. Based on the predicted local fields, initial yield and damage envelopes are generated for various clustering parameters for a polymer matrix composite with both carbon and glass fibers. Nonlinear epoxy matrix behavior is also considered, with results in the form of effective nonlinear response curves, with varying fiber clustering and for two sets of nonlinear matrix parameters.

  8. Representation of Block-Based Image Features in a Multi-Scale Framework for Built-Up Area Detection

    Directory of Open Access Journals (Sweden)

    Zhongwen Hu

    2016-02-01

    Full Text Available The accurate extraction and mapping of built-up areas play an important role in many social, economic, and environmental studies. In this paper, we propose a novel approach for built-up area detection from high spatial resolution remote sensing images, using a block-based multi-scale feature representation framework. First, an image is divided into small blocks, in which the spectral, textural, and structural features are extracted and represented using a multi-scale framework; a set of refined Harris corner points is then used to select blocks as training samples; finally, a built-up index image is obtained by minimizing the normalized spectral, textural, and structural distances to the training samples, and a built-up area map is obtained by thresholding the index image. Experiments confirm that the proposed approach is effective for high-resolution optical and synthetic aperture radar images, with different scenes and different spatial resolutions.

  9. Multiple-Fault Diagnosis Method Based on Multiscale Feature Extraction and MSVM_PPA

    Directory of Open Access Journals (Sweden)

    Min Zhang

    2018-01-01

    Full Text Available Identification of rolling bearing fault patterns, especially for the compound faults, has attracted notable attention and is still a challenge in fault diagnosis. In this paper, a novel method called multiscale feature extraction (MFE and multiclass support vector machine (MSVM with particle parameter adaptive (PPA is proposed. MFE is used to preprocess the process signals, which decomposes the data into intrinsic mode function by empirical mode decomposition method, and instantaneous frequency of decomposed components was obtained by Hilbert transformation. Then, statistical features and principal component analysis are utilized to extract significant information from the features, to get effective data from multiple faults. MSVM method with PPA parameters optimization will classify the fault patterns. The results of a case study of the rolling bearings faults data from Case Western Reserve University show that (1 the proposed intelligent method (MFE_PPA_MSVM improves the classification recognition rate; (2 the accuracy will decline when the number of fault patterns increases; (3 prediction accuracy can be the best when the training set size is increased to 70% of the total sample set. It verifies the method is feasible and efficient for fault diagnosis.

  10. Numerical Simulation of Early Age Cracking of Reinforced Concrete Bridge Decks with a Full-3D Multiscale and Multi-Chemo-Physical Integrated Analysis

    Directory of Open Access Journals (Sweden)

    Tetsuya Ishida

    2018-03-01

    Full Text Available In November 2011, the Japanese government resolved to build “Revival Roads” in the Tohoku region to accelerate the recovery from the Great East Japan Earthquake of March 2011. Because the Tohoku region experiences such cold and snowy weather in winter, complex degradation from a combination of frost damage, chloride attack from de-icing agents, alkali–silica reaction, cracking and fatigue is anticipated. Thus, to enhance the durability performance of road structures, particularly reinforced concrete (RC bridge decks, multiple countermeasures are proposed: a low water-to-cement ratio in the mix, mineral admixtures such as ground granulated blast furnace slag and/or fly ash to mitigate the risks of chloride attack and alkali–silica reaction, anticorrosion rebar and 6% entrained air for frost damage. It should be noted here that such high durability specifications may conversely increase the risk of early age cracking caused by temperature and shrinkage due to the large amounts of cement and the use of mineral admixtures. Against this background, this paper presents a numerical simulation of early age deformation and cracking of RC bridge decks with full 3D multiscale and multi-chemo-physical integrated analysis. First, a multiscale constitutive model of solidifying cementitious materials is briefly introduced based on systematic knowledge coupling microscopic thermodynamic phenomena and microscopic structural mechanics. With the aim to assess the early age thermal and shrinkage-induced cracks on real bridge deck, the study began with extensive model validations by applying the multiscale and multi-physical integrated analysis system to small specimens and mock-up RC bridge deck specimens. Then, through the application of the current computational system, factors that affect the generation and propagation of early age thermal and shrinkage-induced cracks are identified via experimental validation and full-scale numerical simulation on real

  11. BSDWormer; an Open Source Implementation of a Poisson Wavelet Multiscale Analysis for Potential Fields

    Science.gov (United States)

    Horowitz, F. G.; Gaede, O.

    2014-12-01

    Wavelet multiscale edge analysis of potential fields (a.k.a. "worms") has been known since Moreau et al. (1997) and was independently derived by Hornby et al. (1999). The technique is useful for producing a scale-explicit overview of the structures beneath a gravity or magnetic survey, including establishing the location and estimating the attitude of surface features, as well as incorporating information about the geometric class (point, line, surface, volume, fractal) of the underlying sources — in a fashion much like traditional structural indices from Euler solutions albeit with better areal coverage. Hornby et al. (2002) show that worms form the locally highest concentration of horizontal edges of a given strike — which in conjunction with the results from Mallat and Zhong (1992) induces a (non-unique!) inversion where the worms are physically interpretable as lateral boundaries in a source distribution that produces a close approximation of the observed potential field. The technique has enjoyed widespread adoption and success in the Australian mineral exploration community — including "ground truth" via successfully drilling structures indicated by the worms. Unfortunately, to our knowledge, all implementations of the code to calculate the worms/multiscale edges (including Horowitz' original research code) are either part of commercial software packages, or have copyright restrictions that impede the use of the technique by the wider community. The technique is completely described mathematically in Hornby et al. (1999) along with some later publications. This enables us to re-implement from scratch the code required to calculate and visualize the worms. We are freely releasing the results under an (open source) BSD two-clause software license. A git repository is available at . We will give an overview of the technique, show code snippets using the codebase, and present visualization results for example datasets (including the Surat basin of Australia

  12. A multiscale MD-FE model of diffusion in composite media with internal surface interaction based on numerical homogenization procedure.

    Science.gov (United States)

    Kojic, M; Milosevic, M; Kojic, N; Kim, K; Ferrari, M; Ziemys, A

    2014-02-01

    Mass transport by diffusion within composite materials may depend not only on internal microstructural geometry, but also on the chemical interactions between the transported substance and the material of the microstructure. Retrospectively, there is a gap in methods and theory to connect material microstructure properties with macroscale continuum diffusion characteristics. Here we present a new hierarchical multiscale model for diffusion within composite materials that couples material microstructural geometry and interactions between diffusing particles and the material matrix. This model, which bridges molecular dynamics (MD) and the finite element (FE) method, is employed to construct a continuum diffusion model based on a novel numerical homogenization procedure. The procedure is general and robust for evaluating constitutive material parameters of the continuum model. These parameters include the traditional bulk diffusion coefficients and, additionally, the distances from the solid surface accounting for surface interaction effects. We implemented our models to glucose diffusion through the following two geometrical/material configurations: tightly packed silica nanospheres, and a complex fibrous structure surrounding nanospheres. Then, rhodamine 6G diffusion analysis through an aga-rose gel network was performed, followed by a model validation using our experimental results. The microstructural model, numerical homogenization and continuum model offer a new platform for modeling and predicting mass diffusion through complex biological environment and within composite materials that are used in a wide range of applications, like drug delivery and nanoporous catalysts.

  13. A multiscale MD–FE model of diffusion in composite media with internal surface interaction based on numerical homogenization procedure

    Science.gov (United States)

    Kojic, M.; Milosevic, M.; Kojic, N.; Kim, K.; Ferrari, M.; Ziemys, A.

    2014-01-01

    Mass transport by diffusion within composite materials may depend not only on internal microstructural geometry, but also on the chemical interactions between the transported substance and the material of the microstructure. Retrospectively, there is a gap in methods and theory to connect material microstructure properties with macroscale continuum diffusion characteristics. Here we present a new hierarchical multiscale model for diffusion within composite materials that couples material microstructural geometry and interactions between diffusing particles and the material matrix. This model, which bridges molecular dynamics (MD) and the finite element (FE) method, is employed to construct a continuum diffusion model based on a novel numerical homogenization procedure. The procedure is general and robust for evaluating constitutive material parameters of the continuum model. These parameters include the traditional bulk diffusion coefficients and, additionally, the distances from the solid surface accounting for surface interaction effects. We implemented our models to glucose diffusion through the following two geometrical/material configurations: tightly packed silica nanospheres, and a complex fibrous structure surrounding nanospheres. Then, rhodamine 6G diffusion analysis through an aga-rose gel network was performed, followed by a model validation using our experimental results. The microstructural model, numerical homogenization and continuum model offer a new platform for modeling and predicting mass diffusion through complex biological environment and within composite materials that are used in a wide range of applications, like drug delivery and nanoporous catalysts. PMID:24578582

  14. Multiscale Simulation of Porous Ceramics Based on Movable Cellular Automaton Method

    Science.gov (United States)

    Smolin, A.; Smolin, I.; Eremina, G.; Smolina, I.

    2017-10-01

    The paper presents a model for simulating mechanical behaviour of multiscale porous ceramics based on movable cellular automaton method, which is a novel particle method in computational mechanics of solid. The initial scale of the proposed approach corresponds to the characteristic size of the smallest pores in the ceramics. At this scale, we model uniaxial compression of several representative samples with an explicit account of pores of the same size but with the random unique position in space. As a result, we get the average values of Young’s modulus and strength, as well as the parameters of the Weibull distribution of these properties at the current scale level. These data allow us to describe the material behaviour at the next scale level were only the larger pores are considered explicitly, while the influence of small pores is included via the effective properties determined at the previous scale level. If the pore size distribution function of the material has N maxima we need to perform computations for N - 1 levels in order to get the properties from the lowest scale up to the macroscale step by step. The proposed approach was applied to modelling zirconia ceramics with bimodal pore size distribution. The obtained results show correct behaviour of the model sample at the macroscale.

  15. Multiscale Feature Model for Terrain Data Based on Adaptive Spatial Neighborhood

    Directory of Open Access Journals (Sweden)

    Huijie Zhang

    2013-01-01

    Full Text Available Multiresolution hierarchy based on features (FMRH has been applied in the field of terrain modeling and obtained significant results in real engineering. However, it is difficult to schedule multiresolution data in FMRH from external memory. This paper proposed new multiscale feature model and related strategies to cluster spatial data blocks and solve the scheduling problems of FMRH using spatial neighborhood. In the model, the nodes with similar error in the different layers should be in one cluster. On this basis, a space index algorithm for each cluster guided by Hilbert curve is proposed. It ensures that multi-resolution terrain data can be loaded without traversing the whole FMRH; therefore, the efficiency of data scheduling is improved. Moreover, a spatial closeness theorem of cluster is put forward and is also proved. It guarantees that the union of data blocks composites a whole terrain without any data loss. Finally, experiments have been carried out on many different large scale data sets, and the results demonstrate that the schedule time is shortened and the efficiency of I/O operation is apparently improved, which is important in real engineering.

  16. An adjustable multi-scale single beam acoustic tweezers based on ultrahigh frequency ultrasonic transducer.

    Science.gov (United States)

    Chen, Xiaoyang; Lam, Kwok Ho; Chen, Ruimin; Chen, Zeyu; Yu, Ping; Chen, Zhongping; Shung, K Kirk; Zhou, Qifa

    2017-11-01

    This paper reports the fabrication, characterization, and microparticle manipulation capability of an adjustable multi-scale single beam acoustic tweezers (SBAT) that is capable of flexibly changing the size of "tweezers" like ordinary metal tweezers with a single-element ultrahigh frequency (UHF) ultrasonic transducer. The measured resonant frequency of the developed transducer at 526 MHz is the highest frequency of piezoelectric single crystal based ultrasonic transducers ever reported. This focused UHF ultrasonic transducer exhibits a wide bandwidth (95.5% at -10 dB) due to high attenuation of high-frequency ultrasound wave, which allows the SBAT effectively excite with a wide range of excitation frequency from 150 to 400 MHz by using the "piezoelectric actuator" model. Through controlling the excitation frequency, the wavelength of ultrasound emitted from the SBAT can be changed to selectively manipulate a single microparticle of different sizes (3-100 μm) by using only one transducer. This concept of flexibly changing "tweezers" size is firstly introduced into the study of SBAT. At the same time, it was found that this incident ultrasound wavelength play an important role in lateral trapping and manipulation for microparticle of different sizes. Biotechnol. Bioeng. 2017;114: 2637-2647. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

  17. SUBTYPE COASTLINE DETERMINATION IN URBAN COAST BASED ON MULTISCALE FEATURES: A CASE STUDY IN TIANJIN, CHINA

    Directory of Open Access Journals (Sweden)

    Y. Song

    2018-04-01

    Full Text Available In urban coast, coastline is a direct factor to reflect human activities. It is of crucial importance to the understanding of urban growth, resource development and ecological environment. Due to complexity and uncertainty in this type of coast, it is difficult to detect accurate coastline position and determine the subtypes of the coastline. In this paper, we present a multiscale feature-based subtype coastline determination (MFBSCD method to extract coastline and determine the subtypes. In this method, uncertainty-considering coastline detection (UCCD method is proposed to separate water and land for more accurate coastline position. The MFBSCD method can well integrate scale-invariant features of coastline in geometry and spatial structure to determine coastline in subtype scale, and can make subtypes verify with each other during processing to ensure the accuracy of final results. It was applied to Landsat Thematic Mapper (TM and Operational Land Imager (OLI images of Tianjin, China, and the accuracy of the extracted coastlines was assessed with the manually delineated coastline. The mean ME (misclassification error and mean LM (Line Matching are 0.0012 and 24.54 m respectively. The method provides an inexpensive and automated means of coastline mapping with subtype scale in coastal city sectors with intense human interference, which can be significant for coast resource management and evaluation of urban development.

  18. Subtype Coastline Determination in Urban Coast Based on Multiscale Features: a Case Study in Tianjin, China

    Science.gov (United States)

    Song, Y.; Ai, Y.; Zhu, H.

    2018-04-01

    In urban coast, coastline is a direct factor to reflect human activities. It is of crucial importance to the understanding of urban growth, resource development and ecological environment. Due to complexity and uncertainty in this type of coast, it is difficult to detect accurate coastline position and determine the subtypes of the coastline. In this paper, we present a multiscale feature-based subtype coastline determination (MFBSCD) method to extract coastline and determine the subtypes. In this method, uncertainty-considering coastline detection (UCCD) method is proposed to separate water and land for more accurate coastline position. The MFBSCD method can well integrate scale-invariant features of coastline in geometry and spatial structure to determine coastline in subtype scale, and can make subtypes verify with each other during processing to ensure the accuracy of final results. It was applied to Landsat Thematic Mapper (TM) and Operational Land Imager (OLI) images of Tianjin, China, and the accuracy of the extracted coastlines was assessed with the manually delineated coastline. The mean ME (misclassification error) and mean LM (Line Matching) are 0.0012 and 24.54 m respectively. The method provides an inexpensive and automated means of coastline mapping with subtype scale in coastal city sectors with intense human interference, which can be significant for coast resource management and evaluation of urban development.

  19. Fault Diagnosis of Rotating Machinery Based on the Multiscale Local Projection Method and Diagonal Slice Spectrum

    Directory of Open Access Journals (Sweden)

    Yong Lv

    2018-04-01

    Full Text Available The vibration signals of bearings and gears measured from rotating machinery usually have nonlinear, nonstationary characteristics. The local projection algorithm cannot only reduce the noise of the nonlinear system, but can also preserve the nonlinear deterministic structure of the signal. The influence of centroid selection on the performance of noise reduction methods is analyzed, and the multiscale local projection method of centroid was proposed in this paper. This method considers both the geometrical shape and statistical error of the signal in high dimensional phase space, which can effectively eliminate the noise and preserve the complete geometric structure of the attractors. The diagonal slice spectrum can identify the frequency components of quadratic phase coupling and enlarge the coupled frequency component in the nonlinear signal. Therefore, the proposed method based on the above two algorithms can achieve more accurate results of fault diagnosis of gears and rolling bearings. The simulated signal is used to verify its effectiveness in a numerical simulation. Then, the proposed method is conducted for fault diagnosis of gears and rolling bearings in application researches. The fault characteristics of faulty bearings and gears can be extracted successfully in the researches. The experimental results indicate the effectiveness of the novel proposed method.

  20. Multi-scale individual-based model of microbial and bioconversion dynamics in aerobic granular sludge.

    Science.gov (United States)

    Xavier, Joao B; De Kreuk, Merle K; Picioreanu, Cristian; Van Loosdrecht, Mark C M

    2007-09-15

    Aerobic granular sludge is a novel compact biological wastewater treatment technology for integrated removal of COD (chemical oxygen demand), nitrogen, and phosphate charges. We present here a multiscale model of aerobic granular sludge sequencing batch reactors (GSBR) describing the complex dynamics of populations and nutrient removal. The macro scale describes bulk concentrations and effluent composition in six solutes (oxygen, acetate, ammonium, nitrite, nitrate, and phosphate). A finer scale, the scale of one granule (1.1 mm of diameter), describes the two-dimensional spatial arrangement of four bacterial groups--heterotrophs, ammonium oxidizers, nitrite oxidizers, and phosphate accumulating organisms (PAO)--using individual based modeling (IbM) with species-specific kinetic models. The model for PAO includes three internal storage compounds: polyhydroxyalkanoates (PHA), poly phosphate, and glycogen. Simulations of long-term reactor operation show how the microbial population and activity depends on the operating conditions. Short-term dynamics of solute bulk concentrations are also generated with results comparable to experimental data from lab scale reactors. Our results suggest that N-removal in GSBR occurs mostly via alternating nitrification/denitrification rather than simultaneous nitrification/denitrification, supporting an alternative strategy to improve N-removal in this promising wastewater treatment process.

  1. Multi-scale Analysis of MEMS Sensors Subject to Drop Impacts

    Directory of Open Access Journals (Sweden)

    Sarah Zerbini

    2007-09-01

    Full Text Available The effect of accidental drops on MEMS sensors are examined within the frame-work of a multi-scale finite element approach. With specific reference to a polysilicon MEMSaccelerometer supported by a naked die, the analysis is decoupled into macro-scale (at dielength-scale and meso-scale (at MEMS length-scale simulations, accounting for the verysmall inertial contribution of the sensor to the overall dynamics of the device. Macro-scaleanalyses are adopted to get insights into the link between shock waves caused by the impactagainst a target surface and propagating inside the die, and the displacement/acceleration his-tories at the MEMS anchor points. Meso-scale analyses are adopted to detect the most stresseddetails of the sensor and to assess whether the impact can lead to possible localized failures.Numerical results show that the acceleration at sensor anchors cannot be considered an ob-jective indicator for drop severity. Instead, accurate analyses at sensor level are necessary toestablish how MEMS can fail because of drops.

  2. Computation of complexity measures of morphologically significant zones decomposed from binary fractal sets via multiscale convexity analysis

    International Nuclear Information System (INIS)

    Lim, Sin Liang; Koo, Voon Chet; Daya Sagar, B.S.

    2009-01-01

    Multiscale convexity analysis of certain fractal binary objects-like 8-segment Koch quadric, Koch triadic, and random Koch quadric and triadic islands-is performed via (i) morphologic openings with respect to recursively changing the size of a template, and (ii) construction of convex hulls through half-plane closings. Based on scale vs convexity measure relationship, transition levels between the morphologic regimes are determined as crossover scales. These crossover scales are taken as the basis to segment binary fractal objects into various morphologically prominent zones. Each segmented zone is characterized through normalized morphologic complexity measures. Despite the fact that there is no notably significant relationship between the zone-wise complexity measures and fractal dimensions computed by conventional box counting method, fractal objects-whether they are generated deterministically or by introducing randomness-possess morphologically significant sub-zones with varied degrees of spatial complexities. Classification of realistic fractal sets and/or fields according to sub-zones possessing varied degrees of spatial complexities provides insight to explore links with the physical processes involved in the formation of fractal-like phenomena.

  3. Multi-scale textural feature extraction and particle swarm optimization based model selection for false positive reduction in mammography.

    Science.gov (United States)

    Zyout, Imad; Czajkowska, Joanna; Grzegorzek, Marcin

    2015-12-01

    The high number of false positives and the resulting number of avoidable breast biopsies are the major problems faced by current mammography Computer Aided Detection (CAD) systems. False positive reduction is not only a requirement for mass but also for calcification CAD systems which are currently deployed for clinical use. This paper tackles two problems related to reducing the number of false positives in the detection of all lesions and masses, respectively. Firstly, textural patterns of breast tissue have been analyzed using several multi-scale textural descriptors based on wavelet and gray level co-occurrence matrix. The second problem addressed in this paper is the parameter selection and performance optimization. For this, we adopt a model selection procedure based on Particle Swarm Optimization (PSO) for selecting the most discriminative textural features and for strengthening the generalization capacity of the supervised learning stage based on a Support Vector Machine (SVM) classifier. For evaluating the proposed methods, two sets of suspicious mammogram regions have been used. The first one, obtained from Digital Database for Screening Mammography (DDSM), contains 1494 regions (1000 normal and 494 abnormal samples). The second set of suspicious regions was obtained from database of Mammographic Image Analysis Society (mini-MIAS) and contains 315 (207 normal and 108 abnormal) samples. Results from both datasets demonstrate the efficiency of using PSO based model selection for optimizing both classifier hyper-parameters and parameters, respectively. Furthermore, the obtained results indicate the promising performance of the proposed textural features and more specifically, those based on co-occurrence matrix of wavelet image representation technique. Copyright © 2015 Elsevier Ltd. All rights reserved.

  4. Fiber orientation interpolation for the multiscale analysis of short fiber reinforced composite parts

    Science.gov (United States)

    Köbler, Jonathan; Schneider, Matti; Ospald, Felix; Andrä, Heiko; Müller, Ralf

    2018-06-01

    For short fiber reinforced plastic parts the local fiber orientation has a strong influence on the mechanical properties. To enable multiscale computations using surrogate models we advocate a two-step identification strategy. Firstly, for a number of sample orientations an effective model is derived by numerical methods available in the literature. Secondly, to cover a general orientation state, these effective models are interpolated. In this article we develop a novel and effective strategy to carry out this interpolation. Firstly, taking into account symmetry arguments, we reduce the fiber orientation phase space to a triangle in R^2 . For an associated triangulation of this triangle we furnish each node with an surrogate model. Then, we use linear interpolation on the fiber orientation triangle to equip each fiber orientation state with an effective stress. The proposed approach is quite general, and works for any physically nonlinear constitutive law on the micro-scale, as long as surrogate models for single fiber orientation states can be extracted. To demonstrate the capabilities of our scheme we study the viscoelastic creep behavior of short glass fiber reinforced PA66, and use Schapery's collocation method together with FFT-based computational homogenization to derive single orientation state effective models. We discuss the efficient implementation of our method, and present results of a component scale computation on a benchmark component by using ABAQUS ®.

  5. Fiber orientation interpolation for the multiscale analysis of short fiber reinforced composite parts

    Science.gov (United States)

    Köbler, Jonathan; Schneider, Matti; Ospald, Felix; Andrä, Heiko; Müller, Ralf

    2018-04-01

    For short fiber reinforced plastic parts the local fiber orientation has a strong influence on the mechanical properties. To enable multiscale computations using surrogate models we advocate a two-step identification strategy. Firstly, for a number of sample orientations an effective model is derived by numerical methods available in the literature. Secondly, to cover a general orientation state, these effective models are interpolated. In this article we develop a novel and effective strategy to carry out this interpolation. Firstly, taking into account symmetry arguments, we reduce the fiber orientation phase space to a triangle in R^2 . For an associated triangulation of this triangle we furnish each node with an surrogate model. Then, we use linear interpolation on the fiber orientation triangle to equip each fiber orientation state with an effective stress. The proposed approach is quite general, and works for any physically nonlinear constitutive law on the micro-scale, as long as surrogate models for single fiber orientation states can be extracted. To demonstrate the capabilities of our scheme we study the viscoelastic creep behavior of short glass fiber reinforced PA66, and use Schapery's collocation method together with FFT-based computational homogenization to derive single orientation state effective models. We discuss the efficient implementation of our method, and present results of a component scale computation on a benchmark component by using ABAQUS ®.

  6. Based on a multi-agent system for multi-scale simulation and application of household's LUCC: a case study for Mengcha village, Mizhi county, Shaanxi province.

    Science.gov (United States)

    Chen, Hai; Liang, Xiaoying; Li, Rui

    2013-01-01

    Multi-Agent Systems (MAS) offer a conceptual approach to include multi-actor decision making into models of land use change. Through the simulation based on the MAS, this paper tries to show the application of MAS in the micro scale LUCC, and reveal the transformation mechanism of difference scale. This paper starts with a description of the context of MAS research. Then, it adopts the Nested Spatial Choice (NSC) method to construct the multi-scale LUCC decision-making model. And a case study for Mengcha village, Mizhi County, Shaanxi Province is reported. Finally, the potentials and drawbacks of the following approach is discussed and concluded. From our design and implementation of the MAS in multi-scale model, a number of observations and conclusions can be drawn on the implementation and future research directions. (1) The use of the LUCC decision-making and multi-scale transformation framework provides, according to us, a more realistic modeling of multi-scale decision making process. (2) By using continuous function, rather than discrete function, to construct the decision-making of the households is more realistic to reflect the effect. (3) In this paper, attempts have been made to give a quantitative analysis to research the household interaction. And it provides the premise and foundation for researching the communication and learning among the households. (4) The scale transformation architecture constructed in this paper helps to accumulate theory and experience for the interaction research between the micro land use decision-making and the macro land use landscape pattern. Our future research work will focus on: (1) how to rational use risk aversion principle, and put the rule on rotation between household parcels into model. (2) Exploring the methods aiming at researching the household decision-making over a long period, it allows us to find the bridge between the long-term LUCC data and the short-term household decision-making. (3) Researching the

  7. Multi-scale complexity analysis of muscle coactivation during gait in children with cerebral palsy

    Directory of Open Access Journals (Sweden)

    Wen eTao

    2015-07-01

    Full Text Available The objective of this study is to characterize complexity of lower-extremity muscle coactivation and coordination during gait in children with cerebral palsy (CP, children with typical development (TD and healthy adults, by applying recently developed multivariate multi-scale entropy (MMSE analysis to surface EMG signals. Eleven CP children (CP group, eight TD children and seven healthy adults (consider as an entire control group were asked to walk while surface EMG signals were collected from 5 thigh muscles and 3 lower leg muscles on each leg (16 EMG channels in total. The 16-channel surface EMG data, recorded during a series of consecutive gait cycles, were simultaneously processed by multivariate empirical mode decomposition (MEMD, to generate fully aligned data scales for subsequent MMSE analysis. In order to conduct extensive examination of muscle coactivation complexity using the MEMD-enhanced MMSE, 14 data analysis schemes were designed by varying partial muscle combinations and time durations of data segments. Both TD children and healthy adults showed almost consistent MMSE curves over multiple scales for all the 14 schemes, without any significant difference (p > 0.09. However, quite diversity in MMSE curve was observed in the CP group when compared with those in the control group. There appears to be diverse neuropathological processes in CP that may affect dynamical complexity of muscle coactivation and coordination during gait. The abnormal complexity patterns emerging in CP group can be attributed to different factors such as motor control impairments, loss of muscle couplings, and spasticity or paralysis in individual muscles. All these findings expand our knowledge of neuropathology of CP from a novel point of view of muscle co-activation complexity, also indicating the potential to derive a quantitative index for assessing muscle activation characteristics as well as motor function in CP.

  8. A Multi-scale Approach for CO2 Accounting and Risk Analysis in CO2 Enhanced Oil Recovery Sites

    Science.gov (United States)

    Dai, Z.; Viswanathan, H. S.; Middleton, R. S.; Pan, F.; Ampomah, W.; Yang, C.; Jia, W.; Lee, S. Y.; McPherson, B. J. O. L.; Grigg, R.; White, M. D.

    2015-12-01

    Using carbon dioxide in enhanced oil recovery (CO2-EOR) is a promising technology for emissions management because CO2-EOR can dramatically reduce carbon sequestration costs in the absence of greenhouse gas emissions policies that include incentives for carbon capture and storage. This study develops a multi-scale approach to perform CO2 accounting and risk analysis for understanding CO2 storage potential within an EOR environment at the Farnsworth Unit of the Anadarko Basin in northern Texas. A set of geostatistical-based Monte Carlo simulations of CO2-oil-water flow and transport in the Marrow formation are conducted for global sensitivity and statistical analysis of the major risk metrics: CO2 injection rate, CO2 first breakthrough time, CO2 production rate, cumulative net CO2 storage, cumulative oil and CH4 production, and water injection and production rates. A global sensitivity analysis indicates that reservoir permeability, porosity, and thickness are the major intrinsic reservoir parameters that control net CO2 injection/storage and oil/CH4 recovery rates. The well spacing (the distance between the injection and production wells) and the sequence of alternating CO2 and water injection are the major operational parameters for designing an effective five-spot CO2-EOR pattern. The response surface analysis shows that net CO2 injection rate increases with the increasing reservoir thickness, permeability, and porosity. The oil/CH4 production rates are positively correlated to reservoir permeability, porosity and thickness, but negatively correlated to the initial water saturation. The mean and confidence intervals are estimated for quantifying the uncertainty ranges of the risk metrics. The results from this study provide useful insights for understanding the CO2 storage potential and the corresponding risks of commercial-scale CO2-EOR fields.

  9. Multi-scale multi-physics computational chemistry simulation based on ultra-accelerated quantum chemical molecular dynamics method for structural materials in boiling water reactor

    International Nuclear Information System (INIS)

    Miyamoto, Akira; Sato, Etsuko; Sato, Ryo; Inaba, Kenji; Hatakeyama, Nozomu

    2014-01-01

    In collaboration with experimental experts we have reported in the present conference (Hatakeyama, N. et al., “Experiment-integrated multi-scale, multi-physics computational chemistry simulation applied to corrosion behaviour of BWR structural materials”) the results of multi-scale multi-physics computational chemistry simulations applied to the corrosion behaviour of BWR structural materials. In macro-scale, a macroscopic simulator of anode polarization curve was developed to solve the spatially one-dimensional electrochemical equations on the material surface in continuum level in order to understand the corrosion behaviour of typical BWR structural material, SUS304. The experimental anode polarization behaviours of each pure metal were reproduced by fitting all the rates of electrochemical reactions and then the anode polarization curve of SUS304 was calculated by using the same parameters and found to reproduce the experimental behaviour successfully. In meso-scale, a kinetic Monte Carlo (KMC) simulator was applied to an actual-time simulation of the morphological corrosion behaviour under the influence of an applied voltage. In micro-scale, an ultra-accelerated quantum chemical molecular dynamics (UA-QCMD) code was applied to various metallic oxide surfaces of Fe 2 O 3 , Fe 3 O 4 , Cr 2 O 3 modelled as same as water molecules and dissolved metallic ions on the surfaces, then the dissolution and segregation behaviours were successfully simulated dynamically by using UA-QCMD. In this paper we describe details of the multi-scale, multi-physics computational chemistry method especially the UA-QCMD method. This method is approximately 10,000,000 times faster than conventional first-principles molecular dynamics methods based on density-functional theory (DFT), and the accuracy was also validated for various metals and metal oxides compared with DFT results. To assure multi-scale multi-physics computational chemistry simulation based on the UA-QCMD method for

  10. Knickzone Extraction Tool (KET – A new ArcGIS toolset for automatic extraction of knickzones from a DEM based on multi-scale stream gradients

    Directory of Open Access Journals (Sweden)

    Zahra Tuba

    2017-04-01

    Full Text Available Extraction of knickpoints or knickzones from a Digital Elevation Model (DEM has gained immense significance owing to the increasing implications of knickzones on landform development. However, existing methods for knickzone extraction tend to be subjective or require time-intensive data processing. This paper describes the proposed Knickzone Extraction Tool (KET, a new raster-based Python script deployed in the form of an ArcGIS toolset that automates the process of knickzone extraction and is both fast and more user-friendly. The KET is based on multi-scale analysis of slope gradients along a river course, where any locally steep segment (knickzone can be extracted as an anomalously high local gradient. We also conducted a comparative analysis of the KET and other contemporary knickzone identification techniques. The relationship between knickzone distribution and its morphometric characteristics are also examined through a case study of a mountainous watershed in Japan.

  11. MRI-based multiscale models for the hemodynamic and structural evaluation of surgically reconstructed aortic arches

    DEFF Research Database (Denmark)

    Pittaccio, S; Migliavacca, F; Balossino, R

    2007-01-01

    ) geometries of a porcine aortic arch were derived from magnetic resonance imaging (MRI) images. Inlet conditions were derived from MRI velocimetry. A multiscale approach was used for the imposition of outlet conditions, wherein a lumped parameter net provided an active afterload. Evidence was found that ring...

  12. An approach to multiscale modelling with graph grammars.

    Science.gov (United States)

    Ong, Yongzhi; Streit, Katarína; Henke, Michael; Kurth, Winfried

    2014-09-01

    Functional-structural plant models (FSPMs) simulate biological processes at different spatial scales. Methods exist for multiscale data representation and modification, but the advantages of using multiple scales in the dynamic aspects of FSPMs remain unclear. Results from multiscale models in various other areas of science that share fundamental modelling issues with FSPMs suggest that potential advantages do exist, and this study therefore aims to introduce an approach to multiscale modelling in FSPMs. A three-part graph data structure and grammar is revisited, and presented with a conceptual framework for multiscale modelling. The framework is used for identifying roles, categorizing and describing scale-to-scale interactions, thus allowing alternative approaches to model development as opposed to correlation-based modelling at a single scale. Reverse information flow (from macro- to micro-scale) is catered for in the framework. The methods are implemented within the programming language XL. Three example models are implemented using the proposed multiscale graph model and framework. The first illustrates the fundamental usage of the graph data structure and grammar, the second uses probabilistic modelling for organs at the fine scale in order to derive crown growth, and the third combines multiscale plant topology with ozone trends and metabolic network simulations in order to model juvenile beech stands under exposure to a toxic trace gas. The graph data structure supports data representation and grammar operations at multiple scales. The results demonstrate that multiscale modelling is a viable method in FSPM and an alternative to correlation-based modelling. Advantages and disadvantages of multiscale modelling are illustrated by comparisons with single-scale implementations, leading to motivations for further research in sensitivity analysis and run-time efficiency for these models.

  13. A Multiscale Agent-Based in silico Model of Liver Fibrosis Progression

    Energy Technology Data Exchange (ETDEWEB)

    Dutta-Moscato, Joyeeta [Department of Biomedical Informatics, University of Pittsburgh, Pittsburgh, PA (United States); Department of Surgery, University of Pittsburgh, Pittsburgh, PA (United States); Center for Inflammation and Regenerative Modeling, McGowan Institute for Regenerative Medicine, University of Pittsburgh, Pittsburgh, PA (United States); Solovyev, Alexey [Center for Inflammation and Regenerative Modeling, McGowan Institute for Regenerative Medicine, University of Pittsburgh, Pittsburgh, PA (United States); Department of Mathematics, University of Pittsburgh, Pittsburgh, PA (United States); Mi, Qi [Center for Inflammation and Regenerative Modeling, McGowan Institute for Regenerative Medicine, University of Pittsburgh, Pittsburgh, PA (United States); Department of Sports Medicine and Nutrition, University of Pittsburgh, Pittsburgh, PA (United States); Nishikawa, Taichiro [McGowan Institute for Regenerative Medicine, University of Pittsburgh, Pittsburgh, PA (United States); Department of Surgery, Children’s Hospital of Pittsburgh, Pittsburgh, PA (United States); Soto-Gutierrez, Alejandro [McGowan Institute for Regenerative Medicine, University of Pittsburgh, Pittsburgh, PA (United States); Department of Pathology, University of Pittsburgh, Pittsburgh, PA (United States); Thomas E. Starzl Transplantation Institute, University of Pittsburgh, Pittsburgh, PA (United States); Fox, Ira J. [McGowan Institute for Regenerative Medicine, University of Pittsburgh, Pittsburgh, PA (United States); Department of Surgery, Children’s Hospital of Pittsburgh, Pittsburgh, PA (United States); Thomas E. Starzl Transplantation Institute, University of Pittsburgh, Pittsburgh, PA (United States); Vodovotz, Yoram, E-mail: vodovotzy@upmc.edu [Department of Surgery, University of Pittsburgh, Pittsburgh, PA (United States); Center for Inflammation and Regenerative Modeling, McGowan Institute for Regenerative Medicine, University of Pittsburgh, Pittsburgh, PA (United States)

    2014-05-30

    Chronic hepatic inflammation involves a complex interplay of inflammatory and mechanical influences, ultimately manifesting in a characteristic histopathology of liver fibrosis. We created an agent-based model (ABM) of liver tissue in order to computationally examine the consequence of liver inflammation. Our liver fibrosis ABM (LFABM) is comprised of literature-derived rules describing molecular and histopathological aspects of inflammation and fibrosis in a section of chemically injured liver. Hepatocytes are modeled as agents within hexagonal lobules. Injury triggers an inflammatory reaction, which leads to activation of local Kupffer cells and recruitment of monocytes from circulation. Portal fibroblasts and hepatic stellate cells are activated locally by the products of inflammation. The various agents in the simulation are regulated by above-threshold concentrations of pro- and anti-inflammatory cytokines and damage-associated molecular pattern molecules. The simulation progresses from chronic inflammation to collagen deposition, exhibiting periportal fibrosis followed by bridging fibrosis, and culminating in disruption of the regular lobular structure. The ABM exhibited key histopathological features observed in liver sections from rats treated with carbon tetrachloride (CCl{sub 4}). An in silico “tension test” for the hepatic lobules predicted an overall increase in tissue stiffness, in line with clinical elastography literature and published studies in CCl{sub 4}-treated rats. Therapy simulations suggested differential anti-fibrotic effects of neutralizing tumor necrosis factor alpha vs. enhancing M2 Kupffer cells. We conclude that a computational model of liver inflammation on a structural skeleton of physical forces can recapitulate key histopathological and macroscopic properties of CCl{sub 4}-injured liver. This multiscale approach linking molecular and chemomechanical stimuli enables a model that could be used to gain translationally relevant

  14. A Multiscale Agent-Based in silico Model of Liver Fibrosis Progression

    International Nuclear Information System (INIS)

    Dutta-Moscato, Joyeeta; Solovyev, Alexey; Mi, Qi; Nishikawa, Taichiro; Soto-Gutierrez, Alejandro; Fox, Ira J.; Vodovotz, Yoram

    2014-01-01

    Chronic hepatic inflammation involves a complex interplay of inflammatory and mechanical influences, ultimately manifesting in a characteristic histopathology of liver fibrosis. We created an agent-based model (ABM) of liver tissue in order to computationally examine the consequence of liver inflammation. Our liver fibrosis ABM (LFABM) is comprised of literature-derived rules describing molecular and histopathological aspects of inflammation and fibrosis in a section of chemically injured liver. Hepatocytes are modeled as agents within hexagonal lobules. Injury triggers an inflammatory reaction, which leads to activation of local Kupffer cells and recruitment of monocytes from circulation. Portal fibroblasts and hepatic stellate cells are activated locally by the products of inflammation. The various agents in the simulation are regulated by above-threshold concentrations of pro- and anti-inflammatory cytokines and damage-associated molecular pattern molecules. The simulation progresses from chronic inflammation to collagen deposition, exhibiting periportal fibrosis followed by bridging fibrosis, and culminating in disruption of the regular lobular structure. The ABM exhibited key histopathological features observed in liver sections from rats treated with carbon tetrachloride (CCl 4 ). An in silico “tension test” for the hepatic lobules predicted an overall increase in tissue stiffness, in line with clinical elastography literature and published studies in CCl 4 -treated rats. Therapy simulations suggested differential anti-fibrotic effects of neutralizing tumor necrosis factor alpha vs. enhancing M2 Kupffer cells. We conclude that a computational model of liver inflammation on a structural skeleton of physical forces can recapitulate key histopathological and macroscopic properties of CCl 4 -injured liver. This multiscale approach linking molecular and chemomechanical stimuli enables a model that could be used to gain translationally relevant insights into

  15. Multiscale Analysis of Nanocomposites and Their Use in Structural Level Applications

    Science.gov (United States)

    Hasan, Zeaid

    This research focuses on the benefits of using nanocomposites in aerospace structural components to prevent or delay the onset of unique composite failure modes, such as delamination. Analytical, numerical, and experimental analyses were conducted to provide a comprehensive understanding of how carbon nanotubes (CNTs) can provide additional structural integrity when they are used in specific hot spots within a structure. A multiscale approach was implemented to determine the mechanical and thermal properties of the nanocomposites, which were used in detailed finite element models (FEMs) to analyze interlaminar failures in T and Hat section stringers. The delamination that first occurs between the tow filler and the bondline between the stringer and skin was of particular interest. Both locations are considered to be hot spots in such structural components, and failures tend to initiate from these areas. In this research, nanocomposite use was investigated as an alternative to traditional methods of suppressing delamination. The stringer was analyzed under different loading conditions and assuming different structural defects. Initial damage, defined as the first drop in the load displacement curve was considered to be a useful variable to compare the different behaviors in this study and was detected via the virtual crack closure technique (VCCT) implemented in the FE analysis. Experiments were conducted to test T section skin/stringer specimens under pull-off loading, replicating those used in composite panels as stiffeners. Two types of designs were considered: one using pure epoxy to fill the tow region and another that used nanocomposite with 5 wt. % CNTs. The response variable in the tests was the initial damage. Detailed analyses were conducted using FEMs to correlate with the experimental data. The correlation between both the experiment and model was satisfactory. Finally, the effects of thermal cure and temperature variation on nanocomposite structure

  16. Three-dimensional Crustal Structure beneath the Tibetan Plateau Revealed by Multi-scale Gravity Analysis

    Science.gov (United States)

    Xu, C.; Luo, Z.; Sun, R.; Li, Q.

    2017-12-01

    The Tibetan Plateau, the largest and highest plateau on Earth, was uplifted, shorten and thicken by the collision and continuous convergence of the Indian and Eurasian plates since 50 million years ago, the Eocene epoch. Fine three-dimensional crustal structure of the Tibetan Plateau is helpful in understanding the tectonic development. At present, the ordinary method used for revealing crustal structure is seismic method, which is inhibited by poor seismic station coverage, especially in the central and western plateau primarily due to the rugged terrain. Fortunately, with the implementation of satellite gravity missions, gravity field models have demonstrated unprecedented global-scale accuracy and spatial resolution, which can subsequently be employed to study the crustal structure of the entire Tibetan Plateau. This study inverts three-dimensional crustal density and Moho topography of the Tibetan Plateau from gravity data using multi-scale gravity analysis. The inverted results are in agreement with those provided by the previous works. Besides, they can reveal rich tectonic development of the Tibetan Plateau: (1) The low-density channel flow can be observed from the inverted crustal density; (2) The Moho depth in the west is deeper than that in the east, and the deepest Moho, which is approximately 77 km, is located beneath the western Qiangtang Block; (3) The Moho fold, the directions of which are in agreement with the results of surface movement velocities estimated from Global Positioning System, exists clearly on the Moho topography.This study is supported by the National Natural Science Foundation of China (Grant No. 41504015), the China Postdoctoral Science Foundation (Grant No. 2015M572146), and the Surveying and Mapping Basic Research Programme of the National Administration of Surveying, Mapping and Geoinformation (Grant No. 15-01-08).

  17. Multi-scale analysis of nuclear reactor thermal-hydraulics-first applications using the NEPTUNE platform

    International Nuclear Information System (INIS)

    Guelfi, A.; Boucker, M.; Mimouni, S.; Bestion, D.; Boudier, P.

    2005-01-01

    The NEPTUNE project aims at building a new two-phase flow thermal-hydraulics platform for nuclear reactor simulation. EDF (Electricite de France) and CEA (Commissariat a l'Energie Atomique) with the co-sponsorship of IRSN (Institut de Radioprotection et Surete Nucleaire) and FRAMATOME-ANP, are jointly developing the NEPTUNE multi-scale platform that includes new physical models and numerical methods for each of the computing scales. One usually distinguishes three different scales for industrial simulations: the 'system' scale, the 'component' scale (subchannel analysis) and CFD (Computational Fluid Dynamics). In addition DNS (Direct Numerical Simulation) can provide information at a smaller scale that can be useful for the development of the averaged scales. The NEPTUNE project also includes work on software architecture and research on new numerical methods for coupling codes since both are required to improve industrial calculations. All these R and D challenges have been defined in order to meet industrial needs and the underlying stakes (mainly the competitiveness and the safety of Nuclear Power Plants). This paper focuses on three high priority needs: DNB (Departure from Nucleate Boiling) prediction, directly linked to fuel performance; PTS (Pressurized Thermal Shock), a key issue when studying the lifespan of critical components and LBLOCA (Large Break Loss of Coolant Accident), a reference accident for safety studies. For each of these industrial applications, we provide a review of the last developments within the NEPTUNE platform and we present the first results. A particular attention is also given to physical validation and the needs for further experimental data. (authors)

  18. Multiscale entropy analysis of resting-state magnetoencephalogram with tensor factorisations in Alzheimer's disease

    DEFF Research Database (Denmark)

    Escudero, Javier; Evrim, Acar Ataman; Fernández, Alberto

    2015-01-01

    dynamics. We consider the "refined composite multiscale entropy" (rcMSE), which computes entropy "profiles" showing levels of physiological complexity over temporal scales for individual signals. We compute the rcMSE of resting-state magnetoencephalogram (MEG) recordings from 36 patients with Alzheimer...

  19. Spatio-Temporal Super-Resolution Reconstruction of Remote-Sensing Images Based on Adaptive Multi-Scale Detail Enhancement.

    Science.gov (United States)

    Zhu, Hong; Tang, Xinming; Xie, Junfeng; Song, Weidong; Mo, Fan; Gao, Xiaoming

    2018-02-07

    There are many problems in existing reconstruction-based super-resolution algorithms, such as the lack of texture-feature representation and of high-frequency details. Multi-scale detail enhancement can produce more texture information and high-frequency information. Therefore, super-resolution reconstruction of remote-sensing images based on adaptive multi-scale detail enhancement (AMDE-SR) is proposed in this paper. First, the information entropy of each remote-sensing image is calculated, and the image with the maximum entropy value is regarded as the reference image. Subsequently, spatio-temporal remote-sensing images are processed using phase normalization, which is to reduce the time phase difference of image data and enhance the complementarity of information. The multi-scale image information is then decomposed using the L ₀ gradient minimization model, and the non-redundant information is processed by difference calculation and expanding non-redundant layers and the redundant layer by the iterative back-projection (IBP) technique. The different-scale non-redundant information is adaptive-weighted and fused using cross-entropy. Finally, a nonlinear texture-detail-enhancement function is built to improve the scope of small details, and the peak signal-to-noise ratio (PSNR) is used as an iterative constraint. Ultimately, high-resolution remote-sensing images with abundant texture information are obtained by iterative optimization. Real results show an average gain in entropy of up to 0.42 dB for an up-scaling of 2 and a significant promotion gain in enhancement measure evaluation for an up-scaling of 2. The experimental results show that the performance of the AMED-SR method is better than existing super-resolution reconstruction methods in terms of visual and accuracy improvements.

  20. Spatio-Temporal Super-Resolution Reconstruction of Remote-Sensing Images Based on Adaptive Multi-Scale Detail Enhancement

    Science.gov (United States)

    Zhu, Hong; Tang, Xinming; Xie, Junfeng; Song, Weidong; Mo, Fan; Gao, Xiaoming

    2018-01-01

    There are many problems in existing reconstruction-based super-resolution algorithms, such as the lack of texture-feature representation and of high-frequency details. Multi-scale detail enhancement can produce more texture information and high-frequency information. Therefore, super-resolution reconstruction of remote-sensing images based on adaptive multi-scale detail enhancement (AMDE-SR) is proposed in this paper. First, the information entropy of each remote-sensing image is calculated, and the image with the maximum entropy value is regarded as the reference image. Subsequently, spatio-temporal remote-sensing images are processed using phase normalization, which is to reduce the time phase difference of image data and enhance the complementarity of information. The multi-scale image information is then decomposed using the L0 gradient minimization model, and the non-redundant information is processed by difference calculation and expanding non-redundant layers and the redundant layer by the iterative back-projection (IBP) technique. The different-scale non-redundant information is adaptive-weighted and fused using cross-entropy. Finally, a nonlinear texture-detail-enhancement function is built to improve the scope of small details, and the peak signal-to-noise ratio (PSNR) is used as an iterative constraint. Ultimately, high-resolution remote-sensing images with abundant texture information are obtained by iterative optimization. Real results show an average gain in entropy of up to 0.42 dB for an up-scaling of 2 and a significant promotion gain in enhancement measure evaluation for an up-scaling of 2. The experimental results show that the performance of the AMED-SR method is better than existing super-resolution reconstruction methods in terms of visual and accuracy improvements. PMID:29414893

  1. Multiscale modeling of radiation damage in Fe-based alloys in the fusion environment

    International Nuclear Information System (INIS)

    Wirth, B.D.; Odette, G.R.; Marian, J.; Ventelon, L.; Young-Vandersall, J.A.; Zepeda-Ruiz, L.A.

    2004-01-01

    Ferritic alloys represent a technologically important class of candidate materials for fusion first wall and blanket structures. A detailed understanding of the mechanisms of defect accumulation and microstructure evolution, and the corresponding effects on mechanical properties is required to predict their in-service structural performance limits. The physical processes involved in radiation damage, and its effects on mechanical properties, are inherently multiscale and hierarchical, spanning length and time scales from the atomic nucleus to meters and picosecond to decades. In this paper, we present a multiscale modeling methodology to describe radiation effects within the fusion energy environment. Selected results from atomic scale investigation are presented, focusing on (i) the mechanisms of self-interstitial dislocation loop formation with Burgers vector of a in iron relative to vanadium, (ii) helium transport and (iii) the interaction between helium and small self-interstitial clusters in iron, and (iv) dislocation-helium bubble interactions in fcc aluminum

  2. Multi-scale model analysis of boundary layer ozone over East Asia

    Directory of Open Access Journals (Sweden)

    M. Lin

    2009-05-01

    Full Text Available This study employs the regional Community Multiscale Air Quality (CMAQ model to examine seasonal and diurnal variations of boundary layer ozone (O3 over East Asia. We evaluate the response of model simulations of boundary layer O3 to the choice of chemical mechanisms, meteorological fields, boundary conditions, and model resolutions. Data obtained from surface stations, aircraft measurements, and satellites are used to advance understanding of O3 chemistry and mechanisms over East Asia and evaluate how well the model represents the observed features. Satellite measurements and model simulations of summertime rainfall are used to assess the impact of the Asian monsoon on O3 production. Our results suggest that summertime O3 over Central Eastern China is highly sensitive to cloud cover and monsoonal rainfall over this region. Thus, accurate simulation of the East Asia summer monsoon is critical to model analysis of atmospheric chemistry over China. Examination of hourly summertime O3 mixing ratios from sites in Japan confirms the important role of diurnal boundary layer fluctuations in controlling ground-level O3. By comparing five different model configurations with observations at six sites, the specific mechanisms responsible for model behavior are identified and discussed. In particular, vertical mixing, urban chemistry, and dry deposition depending on boundary layer height strongly affect model ability to capture observed behavior. Central Eastern China appears to be the most sensitive region in our study to the choice of chemical mechanisms. Evaluation with TRACE-P aircraft measurements reveals that neither the CB4 nor the SAPRC99 mechanisms consistently capture observed behavior of key photochemical oxidants in springtime. However, our analysis finds that SAPRC99 performs somewhat better in simulating mixing ratios of H2O2 (hydrogen peroxide

  3. Classification of high-resolution remote sensing images based on multi-scale superposition

    Science.gov (United States)

    Wang, Jinliang; Gao, Wenjie; Liu, Guangjie

    2017-07-01

    Landscape structures and process on different scale show different characteristics. In the study of specific target landmarks, the most appropriate scale for images can be attained by scale conversion, which improves the accuracy and efficiency of feature identification and classification. In this paper, the authors carried out experiments on multi-scale classification by taking the Shangri-la area in the north-western Yunnan province as the research area and the images from SPOT5 HRG and GF-1 Satellite as date sources. Firstly, the authors upscaled the two images by cubic convolution, and calculated the optimal scale for different objects on the earth shown in images by variation functions. Then the authors conducted multi-scale superposition classification on it by Maximum Likelyhood, and evaluated the classification accuracy. The results indicates that: (1) for most of the object on the earth, the optimal scale appears in the bigger scale instead of the original one. To be specific, water has the biggest optimal scale, i.e. around 25-30m; farmland, grassland, brushwood, roads, settlement places and woodland follows with 20-24m. The optimal scale for shades and flood land is basically as the same as the original one, i.e. 8m and 10m respectively. (2) Regarding the classification of the multi-scale superposed images, the overall accuracy of the ones from SPOT5 HRG and GF-1 Satellite is 12.84% and 14.76% higher than that of the original multi-spectral images, respectively, and Kappa coefficient is 0.1306 and 0.1419 higher, respectively. Hence, the multi-scale superposition classification which was applied in the research area can enhance the classification accuracy of remote sensing images .

  4. Experimentally-based multiscale model of the elastic moduli of bovine trabecular bone and its constituents

    Energy Technology Data Exchange (ETDEWEB)

    Hamed, Elham [University of Illinois at Urbana-Champaign, Department of Mechanical Science and Engineering, 1206 West Green Street, Urbana, IL 61801 (United States); Novitskaya, Ekaterina, E-mail: eevdokim@ucsd.edu [University of California, San Diego, Department of Mechanical and Aerospace Engineering, Materials Science and Engineering Program, 9500 Gilman Dr., La Jolla, CA 92093 (United States); Li, Jun; Jasiuk, Iwona [University of Illinois at Urbana-Champaign, Department of Mechanical Science and Engineering, 1206 West Green Street, Urbana, IL 61801 (United States); McKittrick, Joanna [University of California, San Diego, Department of Mechanical and Aerospace Engineering, Materials Science and Engineering Program, 9500 Gilman Dr., La Jolla, CA 92093 (United States)

    2015-09-01

    The elastic moduli of trabecular bone were modeled using an analytical multiscale approach. Trabecular bone was represented as a porous nanocomposite material with a hierarchical structure spanning from the collagen–mineral level to the trabecular architecture level. In parallel, compression testing was done on bovine femoral trabecular bone samples in two anatomical directions, parallel to the femoral neck axis and perpendicular to it, and the measured elastic moduli were compared with the corresponding theoretical results. To gain insights on the interaction of collagen and minerals at the nanoscale, bone samples were deproteinized or demineralized. After such processing, the treated samples remained as self-standing structures and were tested in compression. Micro-computed tomography was used to characterize the hierarchical structure of these three bone types and to quantify the amount of bone porosity. The obtained experimental data served as inputs to the multiscale model and guided us to represent bone as an interpenetrating composite material. Good agreement was found between the theory and experiments for the elastic moduli of the untreated, deproteinized, and demineralized trabecular bone. - Highlights: • A multiscale model was used to predict the elastic moduli of trabecular bone. • Samples included demineralized, deproteinized and untreated bone. • The model portrays bone as a porous, interpenetrating two phase composite. • The experimental elastic moduli for trabecular bone fell between theoretical bounds.

  5. Experimentally-based multiscale model of the elastic moduli of bovine trabecular bone and its constituents

    International Nuclear Information System (INIS)

    Hamed, Elham; Novitskaya, Ekaterina; Li, Jun; Jasiuk, Iwona; McKittrick, Joanna

    2015-01-01

    The elastic moduli of trabecular bone were modeled using an analytical multiscale approach. Trabecular bone was represented as a porous nanocomposite material with a hierarchical structure spanning from the collagen–mineral level to the trabecular architecture level. In parallel, compression testing was done on bovine femoral trabecular bone samples in two anatomical directions, parallel to the femoral neck axis and perpendicular to it, and the measured elastic moduli were compared with the corresponding theoretical results. To gain insights on the interaction of collagen and minerals at the nanoscale, bone samples were deproteinized or demineralized. After such processing, the treated samples remained as self-standing structures and were tested in compression. Micro-computed tomography was used to characterize the hierarchical structure of these three bone types and to quantify the amount of bone porosity. The obtained experimental data served as inputs to the multiscale model and guided us to represent bone as an interpenetrating composite material. Good agreement was found between the theory and experiments for the elastic moduli of the untreated, deproteinized, and demineralized trabecular bone. - Highlights: • A multiscale model was used to predict the elastic moduli of trabecular bone. • Samples included demineralized, deproteinized and untreated bone. • The model portrays bone as a porous, interpenetrating two phase composite. • The experimental elastic moduli for trabecular bone fell between theoretical bounds

  6. Multiscale approach including microfibril scale to assess elastic constants of cortical bone based on neural network computation and homogenization method.

    Science.gov (United States)

    Barkaoui, Abdelwahed; Chamekh, Abdessalem; Merzouki, Tarek; Hambli, Ridha; Mkaddem, Ali

    2014-03-01

    The complexity and heterogeneity of bone tissue require a multiscale modeling to understand its mechanical behavior and its remodeling mechanisms. In this paper, a novel multiscale hierarchical approach including microfibril scale based on hybrid neural network (NN) computation and homogenization equations was developed to link nanoscopic and macroscopic scales to estimate the elastic properties of human cortical bone. The multiscale model is divided into three main phases: (i) in step 0, the elastic constants of collagen-water and mineral-water composites are calculated by averaging the upper and lower Hill bounds; (ii) in step 1, the elastic properties of the collagen microfibril are computed using a trained NN simulation. Finite element calculation is performed at nanoscopic levels to provide a database to train an in-house NN program; and (iii) in steps 2-10 from fibril to continuum cortical bone tissue, homogenization equations are used to perform the computation at the higher scales. The NN outputs (elastic properties of the microfibril) are used as inputs for the homogenization computation to determine the properties of mineralized collagen fibril. The mechanical and geometrical properties of bone constituents (mineral, collagen, and cross-links) as well as the porosity were taken in consideration. This paper aims to predict analytically the effective elastic constants of cortical bone by modeling its elastic response at these different scales, ranging from the nanostructural to mesostructural levels. Our findings of the lowest scale's output were well integrated with the other higher levels and serve as inputs for the next higher scale modeling. Good agreement was obtained between our predicted results and literature data. Copyright © 2013 John Wiley & Sons, Ltd.

  7. Multiscale Analysis of Foreign Exchange Order Flows and Technical Trading Profitability

    OpenAIRE

    Nikola Gradojevic; Camillo Lento

    2012-01-01

    This paper investigates the multiscale (frequency-dependent) relationship between technical trading profitability and feedback trading effects in the Canada/U.S. dollar foreign exchange market. The results suggest weak evidence that technical trading activities of financial and non-financial customers drive frequent violations of the FX market microstructure assumption that exchange rate movements are driven by order flow. After controlling for transaction costs, we find that the contribution...

  8. Physically based multiscale-viscoplastic model for metals and steel alloys: Theory and computation

    Science.gov (United States)

    Abed, Farid H.

    The main requirement of large deformation problems such as high-speed machining, impact, and various primarily metal forming, is to develop constitutive relations which are widely applicable and capable of accounting for complex paths of deformation. Achieving such desirable goals for material like metals and steel alloys involves a comprehensive study of their microstructures and experimental observations under different loading conditions. In general, metal structures display a strong rate- and temperature-dependence when deformed non-uniformly into the inelastic range. This effect has important implications for an increasing number of applications in structural and engineering mechanics. The mechanical behavior of these applications cannot be characterized by classical (rate-independent) continuum theories because they incorporate no 'material length scales'. It is therefore necessary to develop a rate-dependent (viscoplasticity) continuum theory bridging the gap between the classical continuum theories and the microstructure simulations. Physically based vicoplasticity models for different types of metals (body centered cubic, face centered cubic and hexagonal close-packed) and steel alloys are derived in this work for this purpose. We adopt a multi-scale, hierarchical thermodynamic consistent framework to construct the material constitutive relations for the rate-dependent behavior. The concept of thermal activation energy, dislocations interactions mechanisms and the role of dislocations dynamics in crystals are used in the derivation process taking into consideration the contribution of the plastic strain evolution of dislocation density to the flow stress of polycrystalline metals. Material length scales are implicitly introduced into the governing equations through material rate-dependency (viscosity). The proposed framework is implemented into the commercially well-known finite element software ABAQUS. The finite element simulations of material

  9. Development of a hybrid multi-scale phantom for Monte-Carlo based internal dosimetry

    International Nuclear Information System (INIS)

    Marcatili, S.; Villoing, D.; Bardies, M.

    2015-01-01

    Full text of publication follows. Aim: in recent years several phantoms were developed for radiopharmaceutical dosimetry in clinical and preclinical settings. Voxel-based models (Zubal, Max/Fax, ICRP110) were developed to reach a level of realism that could not be achieved by mathematical models. In turn, 'hybrid' models (XCAT, MOBY/ROBY, Mash/Fash) allow a further degree of versatility by offering the possibility to finely tune each model according to various parameters. However, even 'hybrid' models require the generation of a voxel version for Monte-Carlo modeling of radiation transport. Since absorbed dose simulation time is strictly related to geometry spatial sampling, a compromise should be made between phantom realism and simulation speed. This trade-off leads on one side in an overestimation of the size of small radiosensitive structures such as the skin or hollow organs' walls, and on the other hand to unnecessarily detailed voxellization of large, homogeneous structures. The Aim of this work is to develop a hybrid multi-resolution phantom model for Geant4 and Gate, to better characterize energy deposition in small structures while preserving reasonable computation times. Materials and Methods: we have developed a pipeline for the conversion of preexisting phantoms into a multi-scale Geant4 model. Meshes of each organ are created from raw binary images of a phantom and then voxellized to the smallest spatial sampling required by the user. The user can then decide to re-sample the internal part of each organ, while leaving a layer of smallest voxels at the edge of the organ. In this way, the realistic shape of the organ is maintained while reducing the voxel number in the inner part. For hollow organs, the wall is always modeled using the smallest voxel sampling. This approach allows choosing different voxel resolutions for each organ according to a specific application. Results: preliminary results show that it is possible to

  10. Analysis of crude oil markets with improved multiscale weighted permutation entropy

    Science.gov (United States)

    Niu, Hongli; Wang, Jun; Liu, Cheng

    2018-03-01

    Entropy measures are recently extensively used to study the complexity property in nonlinear systems. Weighted permutation entropy (WPE) can overcome the ignorance of the amplitude information of time series compared with PE and shows a distinctive ability to extract complexity information from data having abrupt changes in magnitude. Improved (or sometimes called composite) multi-scale (MS) method possesses the advantage of reducing errors and improving the accuracy when applied to evaluate multiscale entropy values of not enough long time series. In this paper, we combine the merits of WPE and improved MS to propose the improved multiscale weighted permutation entropy (IMWPE) method for complexity investigation of a time series. Then it is validated effective through artificial data: white noise and 1 / f noise, and real market data of Brent and Daqing crude oil. Meanwhile, the complexity properties of crude oil markets are explored respectively of return series, volatility series with multiple exponents and EEMD-produced intrinsic mode functions (IMFs) which represent different frequency components of return series. Moreover, the instantaneous amplitude and frequency of Brent and Daqing crude oil are analyzed by the Hilbert transform utilized to each IMF.

  11. Correlations between the signal complexity of cerebral and cardiac electrical activity: a multiscale entropy analysis.

    Directory of Open Access Journals (Sweden)

    Pei-Feng Lin

    Full Text Available The heart begins to beat before the brain is formed. Whether conventional hierarchical central commands sent by the brain to the heart alone explain all the interplay between these two organs should be reconsidered. Here, we demonstrate correlations between the signal complexity of brain and cardiac activity. Eighty-seven geriatric outpatients with healthy hearts and varied cognitive abilities each provided a 24-hour electrocardiography (ECG and a 19-channel eye-closed routine electroencephalography (EEG. Multiscale entropy (MSE analysis was applied to three epochs (resting-awake state, photic stimulation of fast frequencies (fast-PS, and photic stimulation of slow frequencies (slow-PS of EEG in the 1-58 Hz frequency range, and three RR interval (RRI time series (awake-state, sleep and that concomitant with the EEG for each subject. The low-to-high frequency power (LF/HF ratio of RRI was calculated to represent sympatho-vagal balance. With statistics after Bonferroni corrections, we found that: (a the summed MSE value on coarse scales of the awake RRI (scales 11-20, RRI-MSE-coarse were inversely correlated with the summed MSE value on coarse scales of the resting-awake EEG (scales 6-20, EEG-MSE-coarse at Fp2, C4, T6 and T4; (b the awake RRI-MSE-coarse was inversely correlated with the fast-PS EEG-MSE-coarse at O1, O2 and C4; (c the sleep RRI-MSE-coarse was inversely correlated with the slow-PS EEG-MSE-coarse at Fp2; (d the RRI-MSE-coarse and LF/HF ratio of the awake RRI were correlated positively to each other; (e the EEG-MSE-coarse at F8 was proportional to the cognitive test score; (f the results conform to the cholinergic hypothesis which states that cognitive impairment causes reduction in vagal cardiac modulation; (g fast-PS significantly lowered the EEG-MSE-coarse globally. Whether these heart-brain correlations could be fully explained by the central autonomic network is unknown and needs further exploration.

  12. A discrete linearizability test based on multiscale analysis

    International Nuclear Information System (INIS)

    Heredero, R Hernandez; Levi, D; Scimiterna, C

    2010-01-01

    In this paper we consider the classification of dispersive linearizable partial difference equations defined on a quad-graph by the multiple scale reduction around their harmonic solution. We show that the A 1 , A 2 and A 3 linearizability conditions restrain the number of the parameters which enter into the equation. A subclass of the equations which pass the A 3 C-integrability conditions can be linearized by a Moebius transformation. (fast track communication)

  13. Wavelets and multiscale signal processing

    CERN Document Server

    Cohen, Albert

    1995-01-01

    Since their appearance in mid-1980s, wavelets and, more generally, multiscale methods have become powerful tools in mathematical analysis and in applications to numerical analysis and signal processing. This book is based on "Ondelettes et Traitement Numerique du Signal" by Albert Cohen. It has been translated from French by Robert D. Ryan and extensively updated by both Cohen and Ryan. It studies the existing relations between filter banks and wavelet decompositions and shows how these relations can be exploited in the context of digital signal processing. Throughout, the book concentrates on the fundamentals. It begins with a chapter on the concept of multiresolution analysis, which contains complete proofs of the basic results. The description of filter banks that are related to wavelet bases is elaborated in both the orthogonal case (Chapter 2), and in the biorthogonal case (Chapter 4). The regularity of wavelets, how this is related to the properties of the filters and the importance of regularity for t...

  14. Quantitative multi-scale analysis of mineral distributions and fractal pore structures for a heterogeneous Junger Basin shale

    International Nuclear Information System (INIS)

    Wang, Y.D.; Ren, Y.Q.; Hu, T.; Deng, B.; Xiao, T.Q.; Liu, K.Y.; Yang, Y.S.

    2016-01-01

    Three dimensional (3D) characterization of shales has recently attracted wide attentions in relation to the growing importance of shale oil and gas. Obtaining a complete 3D compositional distribution of shale has proven to be challenging due to its multi-scale characteristics. A combined multi-energy X-ray micro-CT technique and data-constrained modelling (DCM) approach has been used to quantitatively investigate the multi-scale mineral and porosity distributions of a heterogeneous shale from the Junger Basin, northwestern China by sub-sampling. The 3D sub-resolution structures of minerals and pores in the samples are quantitatively obtained as the partial volume fraction distributions, with colours representing compositions. The shale sub-samples from two areas have different physical structures for minerals and pores, with the dominant minerals being feldspar and dolomite, respectively. Significant heterogeneities have been observed in the analysis. The sub-voxel sized pores form large interconnected clusters with fractal structures. The fractal dimensions of the largest clusters for both sub-samples were quantitatively calculated and found to be 2.34 and 2.86, respectively. The results are relevant in quantitative modelling of gas transport in shale reservoirs

  15. Multi-Scale Particle Size Distributions of Mars, Moon and Itokawa based on a time-maturation dependent fragmentation model

    Science.gov (United States)

    Charalambous, C. A.; Pike, W. T.

    2013-12-01

    We present the development of a soil evolution framework and multiscale modelling of the surface of Mars, Moon and Itokawa thus providing an atlas of extra-terrestrial Particle Size Distributions (PSD). These PSDs are profoundly based on a tailoring method which interconnects several datasets from different sites captured by the various missions. The final integrated product is then fully justified through a soil evolution analysis model mathematically constructed via fundamental physical principles (Charalambous, 2013). The construction of the PSD takes into account the macroscale fresh primary impacts and their products, the mesoscale distributions obtained by the in-situ data of surface missions (Golombek et al., 1997, 2012) and finally the microscopic scale distributions provided by Curiosity and Phoenix Lander (Pike, 2011). The distribution naturally extends at the magnitudinal scales at which current data does not exist due to the lack of scientific instruments capturing the populations at these data absent scales. The extension is based on the model distribution (Charalambous, 2013) which takes as parameters known values of material specific probabilities of fragmentation and grinding limits. Additionally, the establishment of a closed-form statistical distribution provides a quantitative description of the soil's structure. Consequently, reverse engineering of the model distribution allows the synthesis of soil that faithfully represents the particle population at the studied sites (Charalambous, 2011). Such representation essentially delivers a virtual soil environment to work with for numerous applications. A specific application demonstrated here will be the information that can directly be extracted for the successful drilling probability as a function of distance in an effort to aid the HP3 instrument of the 2016 Insight Mission to Mars. Pike, W. T., et al. "Quantification of the dry history of the Martian soil inferred from in situ microscopy

  16. Development of a coupled neutronic/thermal-hydraulic tool with multi-scale capabilities and applications to HPLWR core analysis

    International Nuclear Information System (INIS)

    Monti, Lanfranco; Starflinger, Joerg; Schulenberg, Thomas

    2011-01-01

    Highlights: → Advanced analysis and design techniques for innovative reactors are addressed. → Detailed investigation of a 3 pass core design with a multi-physics-scales tool. → Coupled 40-group neutron transport/equivalent channels TH core analyses methods. → Multi-scale capabilities: from equivalent channels to sub-channel pin-by-pin study. → High fidelity approach: reduction of conservatism involved in core simulations. - Abstract: The High Performance Light Water Reactor (HPLWR) is a thermal spectrum nuclear reactor cooled and moderated with light water operated at supercritical pressure. It is an innovative reactor concept, which requires developing and applying advanced analysis tools as described in the paper. The relevant water density reduction associated with the heat-up, together with the multi-pass core design, results in a pronounced coupling between neutronic and thermal-hydraulic analyses, which takes into account the strong natural influence of the in-core distribution of power generation and water properties. The neutron flux gradients within the multi-pass core, together with the pronounced dependence of water properties on the temperature, require to consider a fine spatial resolution in which the individual fuel pins are resolved to provide precise evaluation of the clad temperature, currently considered as one of the crucial design criteria. These goals have been achieved considering an advanced analysis method based on the usage of existing codes which have been coupled with developed interfaces. Initially neutronic and thermal-hydraulic full core calculations have been iterated until a consistent solution is found to determine the steady state full power condition of the HPLWR core. Results of few group neutronic analyses might be less reliable in case of HPLWR 3-pass core than for conventional LWRs because of considerable changes of the neutron spectrum within the core, hence 40 groups transport theory has been preferred to the

  17. Assessing multiscale complexity of short heart rate variability series through a model-based linear approach

    Science.gov (United States)

    Porta, Alberto; Bari, Vlasta; Ranuzzi, Giovanni; De Maria, Beatrice; Baselli, Giuseppe

    2017-09-01

    We propose a multiscale complexity (MSC) method assessing irregularity in assigned frequency bands and being appropriate for analyzing the short time series. It is grounded on the identification of the coefficients of an autoregressive model, on the computation of the mean position of the poles generating the components of the power spectral density in an assigned frequency band, and on the assessment of its distance from the unit circle in the complex plane. The MSC method was tested on simulations and applied to the short heart period (HP) variability series recorded during graded head-up tilt in 17 subjects (age from 21 to 54 years, median = 28 years, 7 females) and during paced breathing protocols in 19 subjects (age from 27 to 35 years, median = 31 years, 11 females) to assess the contribution of time scales typical of the cardiac autonomic control, namely in low frequency (LF, from 0.04 to 0.15 Hz) and high frequency (HF, from 0.15 to 0.5 Hz) bands to the complexity of the cardiac regulation. The proposed MSC technique was compared to a traditional model-free multiscale method grounded on information theory, i.e., multiscale entropy (MSE). The approach suggests that the reduction of HP variability complexity observed during graded head-up tilt is due to a regularization of the HP fluctuations in LF band via a possible intervention of sympathetic control and the decrement of HP variability complexity observed during slow breathing is the result of the regularization of the HP variations in both LF and HF bands, thus implying the action of physiological mechanisms working at time scales even different from that of respiration. MSE did not distinguish experimental conditions at time scales larger than 1. Over a short time series MSC allows a more insightful association between cardiac control complexity and physiological mechanisms modulating cardiac rhythm compared to a more traditional tool such as MSE.

  18. Morphology Dependent Flow Stress in Nickel-Based Superalloys in the Multi-Scale Crystal Plasticity Framework

    Directory of Open Access Journals (Sweden)

    Shahriyar Keshavarz

    2017-11-01

    Full Text Available This paper develops a framework to obtain the flow stress of nickel-based superalloys as a function of γ-γ’ morphology. The yield strength is a major factor in the design of these alloys. This work provides additional effects of γ’ morphology in the design scope that has been adopted for the model developed by authors. In general, the two-phase γ-γ’ morphology in nickel-based superalloys can be divided into three variables including γ’ shape, γ’ volume fraction and γ’ size in the sub-grain microstructure. In order to obtain the flow stress, non-Schmid crystal plasticity constitutive models at two length scales are employed and bridged through a homogenized multi-scale framework. The multi-scale framework includes two sub-grain and homogenized grain scales. For the sub-grain scale, a size-dependent, dislocation-density-based finite element model (FEM of the representative volume element (RVE with explicit depiction of the γ-γ’ morphology is developed as a building block for the homogenization. For the next scale, an activation-energy-based crystal plasticity model is developed for the homogenized single crystal of Ni-based superalloys. The constitutive models address the thermo-mechanical behavior of nickel-based superalloys for a large temperature range and include orientation dependencies and tension-compression asymmetry. This homogenized model is used to obtain the morphology dependence on the flow stress in nickel-based superalloys and can significantly expedite crystal plasticity FE simulations in polycrystalline microstructures, as well as higher scale FE models in order to cast and design superalloys.

  19. A multiscale model to evaluate the efficacy of anticancer therapies based on chimeric polypeptide nanoparticles

    Science.gov (United States)

    Paiva, L. R.; Martins, M. L.

    2011-01-01

    A multiscale model for tumor growth and its chemotherapy using conjugate nanoparticles is presented, and the corresponding therapeutic outcomes are evaluated. It is found that doxorubicin assembled into chimeric polypeptide nanoparticles cannot eradicate either vascularized primary tumors or avascular micrometastasis even administrated at loads close to their maximum tolerated doses. Furthermore, an effective and safety treatment demands for conjugate nanoparticles targeted to the malignant cells with much higher specificity and affinity than those currently observed in order to leave most of the normal tissues unaffected and to ensure a fast intracellular drug accumulation.

  20. Regularization of EIT reconstruction based on multi-scales wavelet transforms

    Directory of Open Access Journals (Sweden)

    Gong Bo

    2016-09-01

    Full Text Available Electrical Impedance Tomography (EIT intends to obtain the conductivity distribution of a domain from the electrical boundary conditions. This is an ill-posed inverse problem usually solved on finite element meshes. Wavelet transforms are widely used for medical image reconstruction. However, because of the irregular form of the finite element meshes, the canonical wavelet transforms is impossible to perform on meshes. In this article, we present a framework that combines multi-scales wavelet transforms and finite element meshes by viewing meshes as undirected graphs and applying spectral graph wavelet transform on the meshes.

  1. Multi-scale exploration of the technical, economic, and environmental dimensions of bio-based chemical production

    DEFF Research Database (Denmark)

    Zhuang, Kai; Herrgard, Markus

    2015-01-01

    factories. To address this issue, we have developed a comprehensive Multi-scale framework for modeling Sustainable Industrial Chemicals production (MuSIC), which integrates modeling approaches for cellular metabolism, bioreactor design, upstream/downstream processes and economic impact assessment. We...... investment in a new bio-based chemical industry, there is a need for assessing the technological, economic, and environmental potentials of combinations of biomass feedstocks, biochemical products, bioprocess technologies, and metabolic engineering approaches in the early phase of development of cell...... demonstrate the use of the MuSIC framework in a case study where two major polymer precursors (1,3-propanediol and 3-hydroxypropionic acid) are produced from two biomass feedstocks (corn-based glucose and soy-based glycerol) through 66 proposed biosynthetic pathways in two host organisms (Escherichia coli...

  2. Towards a physically-based multi-scale ecohydrological simulator for semi-arid regions

    Science.gov (United States)

    Caviedes-Voullième, Daniel; Josefik, Zoltan; Hinz, Christoph

    2017-04-01

    The use of numerical models as tools for describing and understanding complex ecohydrological systems has enabled to test hypothesis and propose fundamental, process-based explanations of the system system behaviour as a whole as well as its internal dynamics. Reaction-diffusion equations have been used to describe and generate organized pattern such as bands, spots, and labyrinths using simple feedback mechanisms and boundary conditions. Alternatively, pattern-matching cellular automaton models have been used to generate vegetation self-organization in arid and semi-arid regions also using simple description of surface hydrological processes. A key question is: How much physical realism is needed in order to adequately capture the pattern formation processes in semi-arid regions while reliably representing the water balance dynamics at the relevant time scales? In fact, redistribution of water by surface runoff at the hillslope scale occurs at temporal resolution of minutes while the vegetation development requires much lower temporal resolution and longer times spans. This generates a fundamental spatio-temporal multi-scale problem to be solved, for which high resolution rainfall and surface topography are required. Accordingly, the objective of this contribution is to provide proof-of-concept that governing processes can be described numerically at those multiple scales. The requirements for a simulating ecohydrological processes and pattern formation with increased physical realism are, amongst others: i. high resolution rainfall that adequately captures the triggers of growth as vegetation dynamics of arid regions respond as pulsed systems. ii. complex, natural topography in order to accurately model drainage patterns, as surface water redistribution is highly sensitive to topographic features. iii. microtopography and hydraulic roughness, as small scale variations do impact on large scale hillslope behaviour iv. moisture dependent infiltration as temporal

  3. Multi-scale MHD analysis of heliotron plasma in change of background field

    International Nuclear Information System (INIS)

    Ichiguchi, K.; Sakakibara, S.; Ohdachi, S.; Carreras, B.A.

    2012-11-01

    A partial collapse observed in the Large Helical Device (LHD) experiments shifting the magnetic axis inwardly with a real time control of the background field is analyzed with a magnetohydrodynamics (MHD) numerical simulation. The simulation is carried out with a multi-scale simulation scheme. In the simulation, the equilibrium also evolves including the change of the pressure and the rotational transform due to the perturbation dynamics. The simulation result agrees with the experiments qualitatively, which shows that the mechanism is attributed to the destabilization of an infernal-like mode. The destabilization is caused by the change of the background field through the enhancement of the magnetic hill. (author)

  4. Characterizing Co-movements between Indian and Emerging Asian Equity Markets through Wavelet Multi-Scale Analysis

    Directory of Open Access Journals (Sweden)

    Aasif Shah

    2015-06-01

    Full Text Available Multi-scale representations are effective in characterising the time-frequency characteristics of financial return series. They have the capability to reveal the properties not evident with typical time domain analysis. Given the aforesaid, this study derives crucial insights from multi scale analysis to investigate the co- movements between Indian and emerging Asian equity markets using wavelet correlation and wavelet coherence measures. It is reported that the Indian equity market is strongly integrated with Asian equity markets at lower frequency scales and relatively less blended at higher frequencies. On the other hand the results from cross correlations suggest that the lead-lag relationship becomes substantial as we turn to lower frequency scales and finally, wavelet coherence demonstrates that this correlation eventually grows strong in the interim of the crises period at lower frequency scales. Overall the findings are relevant and have strong policy and practical implications.

  5. Unified implicit kinetic scheme for steady multiscale heat transfer based on the phonon Boltzmann transport equation

    Science.gov (United States)

    Zhang, Chuang; Guo, Zhaoli; Chen, Songze

    2017-12-01

    An implicit kinetic scheme is proposed to solve the stationary phonon Boltzmann transport equation (BTE) for multiscale heat transfer problem. Compared to the conventional discrete ordinate method, the present method employs a macroscopic equation to accelerate the convergence in the diffusive regime. The macroscopic equation can be taken as a moment equation for phonon BTE. The heat flux in the macroscopic equation is evaluated from the nonequilibrium distribution function in the BTE, while the equilibrium state in BTE is determined by the macroscopic equation. These two processes exchange information from different scales, such that the method is applicable to the problems with a wide range of Knudsen numbers. Implicit discretization is implemented to solve both the macroscopic equation and the BTE. In addition, a memory reduction technique, which is originally developed for the stationary kinetic equation, is also extended to phonon BTE. Numerical comparisons show that the present scheme can predict reasonable results both in ballistic and diffusive regimes with high efficiency, while the memory requirement is on the same order as solving the Fourier law of heat conduction. The excellent agreement with benchmark and the rapid converging history prove that the proposed macro-micro coupling is a feasible solution to multiscale heat transfer problems.

  6. Multiscale registration of medical images based on edge preserving scale space with application in image-guided radiation therapy

    Science.gov (United States)

    Li, Dengwang; Li, Hongsheng; Wan, Honglin; Chen, Jinhu; Gong, Guanzhong; Wang, Hongjun; Wang, Liming; Yin, Yong

    2012-08-01

    Mutual information (MI) is a well-accepted similarity measure for image registration in medical systems. However, MI-based registration faces the challenges of high computational complexity and a high likelihood of being trapped into local optima due to an absence of spatial information. In order to solve these problems, multi-scale frameworks can be used to accelerate registration and improve robustness. Traditional Gaussian pyramid representation is one such technique but it suffers from contour diffusion at coarse levels which may lead to unsatisfactory registration results. In this work, a new multi-scale registration framework called edge preserving multiscale registration (EPMR) was proposed based upon an edge preserving total variation L1 norm (TV-L1) scale space representation. TV-L1 scale space is constructed by selecting edges and contours of images according to their size rather than the intensity values of the image features. This ensures more meaningful spatial information with an EPMR framework for MI-based registration. Furthermore, we design an optimal estimation of the TV-L1 parameter in the EPMR framework by training and minimizing the transformation offset between the registered pairs for automated registration in medical systems. We validated our EPMR method on both simulated mono- and multi-modal medical datasets with ground truth and clinical studies from a combined positron emission tomography/computed tomography (PET/CT) scanner. We compared our registration framework with other traditional registration approaches. Our experimental results demonstrated that our method outperformed other methods in terms of the accuracy and robustness for medical images. EPMR can always achieve a small offset value, which is closer to the ground truth both for mono-modality and multi-modality, and the speed can be increased 5-8% for mono-modality and 10-14% for multi-modality registration under the same condition. Furthermore, clinical application by adaptive

  7. Multiscale registration of medical images based on edge preserving scale space with application in image-guided radiation therapy

    International Nuclear Information System (INIS)

    Li Dengwang; Wan Honglin; Li Hongsheng; Chen Jinhu; Gong Guanzhong; Yin Yong; Wang Hongjun; Wang Liming

    2012-01-01

    Mutual information (MI) is a well-accepted similarity measure for image registration in medical systems. However, MI-based registration faces the challenges of high computational complexity and a high likelihood of being trapped into local optima due to an absence of spatial information. In order to solve these problems, multi-scale frameworks can be used to accelerate registration and improve robustness. Traditional Gaussian pyramid representation is one such technique but it suffers from contour diffusion at coarse levels which may lead to unsatisfactory registration results. In this work, a new multi-scale registration framework called edge preserving multiscale registration (EPMR) was proposed based upon an edge preserving total variation L1 norm (TV-L1) scale space representation. TV-L1 scale space is constructed by selecting edges and contours of images according to their size rather than the intensity values of the image features. This ensures more meaningful spatial information with an EPMR framework for MI-based registration. Furthermore, we design an optimal estimation of the TV-L1 parameter in the EPMR framework by training and minimizing the transformation offset between the registered pairs for automated registration in medical systems. We validated our EPMR method on both simulated mono- and multi-modal medical datasets with ground truth and clinical studies from a combined positron emission tomography/computed tomography (PET/CT) scanner. We compared our registration framework with other traditional registration approaches. Our experimental results demonstrated that our method outperformed other methods in terms of the accuracy and robustness for medical images. EPMR can always achieve a small offset value, which is closer to the ground truth both for mono-modality and multi-modality, and the speed can be increased 5–8% for mono-modality and 10–14% for multi-modality registration under the same condition. Furthermore, clinical application by

  8. Multiscale vision model for event detection and reconstruction in two-photon imaging data

    DEFF Research Database (Denmark)

    Brazhe, Alexey; Mathiesen, Claus; Lind, Barbara Lykke

    2014-01-01

    on a modified multiscale vision model, an object detection framework based on the thresholding of wavelet coefficients and hierarchical trees of significant coefficients followed by nonlinear iterative partial object reconstruction, for the analysis of two-photon calcium imaging data. The framework is discussed...... of the multiscale vision model is similar in the denoising, but provides a better segmenation of the image into meaningful objects, whereas other methods need to be combined with dedicated thresholding and segmentation utilities....

  9. Novel Multiscale Modeling Tool Applied to Pseudomonas aeruginosa Biofilm Formation

    OpenAIRE

    Biggs, Matthew B.; Papin, Jason A.

    2013-01-01

    Multiscale modeling is used to represent biological systems with increasing frequency and success. Multiscale models are often hybrids of different modeling frameworks and programming languages. We present the MATLAB-NetLogo extension (MatNet) as a novel tool for multiscale modeling. We demonstrate the utility of the tool with a multiscale model of Pseudomonas aeruginosa biofilm formation that incorporates both an agent-based model (ABM) and constraint-based metabolic modeling. The hybrid mod...

  10. Multiscale singularity trees

    DEFF Research Database (Denmark)

    Somchaipeng, Kerawit; Sporring, Jon; Johansen, Peter

    2007-01-01

    We propose MultiScale Singularity Trees (MSSTs) as a structure to represent images, and we propose an algorithm for image comparison based on comparing MSSTs. The algorithm is tested on 3 public image databases and compared to 2 state-of-theart methods. We conclude that the computational complexity...... of our algorithm only allows for the comparison of small trees, and that the results of our method are comparable with state-of-the-art using much fewer parameters for image representation....

  11. Energy analysis for a sustainable future multi-scale integrated analysis of societal and ecosystem metabolism

    CERN Document Server

    Giampietro, Mario; Sorman, Alevgül H

    2013-01-01

    The vast majority of the countries of the world are now facing an imminent energy crisis, particularly the USA, China, India, Japan and EU countries, but also developing countries having to boost their economic growth precisely when more powerful economies will prevent them from using the limited supply of fossil energy. Despite this crisis, current protocols of energy accounting have been developed for dealing with fossil energy exclusively and are therefore not useful for the analysis of alternative energy sources. The first part of the book illustrates the weakness of existing analyses of energy problems: the science of energy was born and developed neglecting the issue of scale. The authors argue that it is necessary to adopt more complex protocols of accounting and analysis in order to generate robust energy scenarios and effective assessments of the quality of alternative energy sources. The second part of the book introduces the concept of energetic metabolism of modern societies and uses empirical res...

  12. Multi-scale Exploration of the Technical, Economic, and Environmental Dimensions of Bio-based Chemical Production

    DEFF Research Database (Denmark)

    Zhuang, Kai; Herrgard, Markus

    2014-01-01

    of a variety of policies and practices (e.g. land-usage, energy source mixture, CO2 emission cap), as well as trade offs between different objectives (e.g. profits for different sectors, emission minimization) for key stakeholders involved in the biochemical value chain (agriculture, energy, and biotechnology......In recent years, bio-based chemicals have gained traction as a sustainable alternative topetrochemicals. In order to maximize the impacts of researches and investments, there is a need to focus on the most promising combinations of feedstocks, biochemical products, and bioprocesses. To address...... this issue, we developed a multiscale framework that integrates modeling approaches across scales of cellular metabolism, bioreactor, bioprocess, and economy/ecosystem, and is able to simultaneously assess biological, technological, economic and environmental feasibility of different production scenarios...

  13. Concrete Image Segmentation Based on Multiscale Mathematic Morphology Operators and Otsu Method

    Directory of Open Access Journals (Sweden)

    Sheng-Bo Zhou

    2015-01-01

    Full Text Available The aim of the current study lies in the development of a reformative technique of image segmentation for Computed Tomography (CT concrete images with the strength grades of C30 and C40. The results, through the comparison of the traditional threshold algorithms, indicate that three threshold algorithms and five edge detectors fail to meet the demand of segmentation for Computed Tomography concrete images. The paper proposes a new segmentation method, by combining multiscale noise suppression morphology edge detector with Otsu method, which is more appropriate for the segmentation of Computed Tomography concrete images with low contrast. This method cannot only locate the boundaries between objects and background with high accuracy, but also obtain a complete edge and eliminate noise.

  14. Coherent multiscale image processing using dual-tree quaternion wavelets.

    Science.gov (United States)

    Chan, Wai Lam; Choi, Hyeokho; Baraniuk, Richard G

    2008-07-01

    The dual-tree quaternion wavelet transform (QWT) is a new multiscale analysis tool for geometric image features. The QWT is a near shift-invariant tight frame representation whose coefficients sport a magnitude and three phases: two phases encode local image shifts while the third contains image texture information. The QWT is based on an alternative theory for the 2-D Hilbert transform and can be computed using a dual-tree filter bank with linear computational complexity. To demonstrate the properties of the QWT's coherent magnitude/phase representation, we develop an efficient and accurate procedure for estimating the local geometrical structure of an image. We also develop a new multiscale algorithm for estimating the disparity between a pair of images that is promising for image registration and flow estimation applications. The algorithm features multiscale phase unwrapping, linear complexity, and sub-pixel estimation accuracy.

  15. Multi-scale analysis of the European airspace using network community detection.

    Directory of Open Access Journals (Sweden)

    Gérald Gurtner

    Full Text Available We show that the European airspace can be represented as a multi-scale traffic network whose nodes are airports, sectors, or navigation points and links are defined and weighted according to the traffic of flights between the nodes. By using a unique database of the air traffic in the European airspace, we investigate the architecture of these networks with a special emphasis on their community structure. We propose that unsupervised network community detection algorithms can be used to monitor the current use of the airspace and improve it by guiding the design of new ones. Specifically, we compare the performance of several community detection algorithms, both with fixed and variable resolution, and also by using a null model which takes into account the spatial distance between nodes, and we discuss their ability to find communities that could be used to define new control units of the airspace.

  16. Multi-scale analysis to uncover habitat use of red-crowned cranes: Implications for conservation

    Directory of Open Access Journals (Sweden)

    Chunyue LIU, Hongxing JIANG, Shuqing ZHANG, Chunrong LI,Yunqiu HOU, Fawen QIAN

    2013-10-01

    Full Text Available A multi-scale approach is essential to assess the factors that limit avian habitat use. Numerous studies have examined habitat use by the red-crowned crane, but integrated multi-scale habitat use information is lacking. We evaluated the effects of several habitat variables quantified across many spatial scales on crane use and abundance in two periods (2000 and 2009 at Yancheng National Nature Reserve, China. The natural wetlands decreased in area by 30,601 ha (-6.9% from 2000 to 2009, predominantly as a result of conversion to aquaculture ponds and farmland, and the remaining was under degradation due to expansion of the exotic smooth cordgrass. The cranes are focusing in on either larger patches or those that are in close proximity to each other in both years, but occupied patches had smaller size, less proximity and more regular boundaries in 2009. At landscape scales, the area percentage of common seepweed, reed ponds and paddy fields had a greater positive impact on crane presence than the area percentage of aquaculture ponds. The cranes were more abundant in patches that had a greater percent area of common seepweed and reed ponds, while the percent area of paddy fields was inversely related to crane abundance in 2009 due to changing agricultural practices. In 2009, cranes tended to use less fragmented plots in natural wetlands and more fragmented plots in anthropogenic paddy fields, which were largely associated with the huge loss and degradation of natural habitats between the two years. Management should focus on restoration of large patches of natural wetlands, and formation of a relatively stable area of large paddy field and reed pond to mitigate the loss of natural wetlands [Current Zoology 59 (5: 604–617, 2013].

  17. Multiscale remote sensing analysis to monitor riparian and upland semiarid vegetation

    Science.gov (United States)

    Nguyen, Uyen

    The health of natural vegetation communities is of concern due to observed changes in the climatic-hydrological regime and land cover changes particularly in arid and semiarid regions. Monitoring vegetation at multi temporal and spatial scales can be the most informative approach for detecting change and inferring causal agents of change and remediation strategies. Riparian communities are tightly linked to annual stream hydrology, ground water elevations and sediment transport. These processes are subject to varying magnitudes of disturbance overtime and are candidates for multi-scale monitoring. My first research objective focused on the response of vegetation in the Upper San Pedro River, Arizona, to reduced base flows and climate change. I addressed the correlation between riparian vegetation and hydro-climate variables during the last three decades in one of the remaining undammed rivers in the southwestern U.S. Its riparian forest is threatened by the diminishing base flows, attributed by different studies either to increases in evapotranspiration (ET) due to conversion of grasslands to mesquite shrublands in the adjacent uplands, or to increased regional groundwater pumping to serve growing populations in surrounding urban areas and or to some interactions of those causes. Landsat 5 imagery was acquired for pre- monsoon period, when riparian trees had leafed out but before the arrival of summer monsoon rains in July. The result has showed Normalized Difference Vegetation Index (NDVI) values from both Landsat and Moderate Resolution Imaging Spectrometer (MODIS) had significant decreases which positively correlated to river flows, which decreased over the study period, and negatively correlated with air temperatures, which have increased by about 1.4°C from 1904 to the present. The predictions from other studies that decreased river flows could negatively impact the riparian forest were supported by this study. The pre-monsoon Normalized Different Vegetation

  18. Multi-scale modeling and analysis of convective boiling: towards the prediction of CHF in rod bundles

    International Nuclear Information System (INIS)

    Niceno, B.; Sato, Y.; Badillo, A.; Andreani, M.

    2010-01-01

    In this paper we describe current activities on the project Multi-Scale Modeling and Analysis of convective boiling (MSMA), conducted jointly by the Paul Scherrer Institute (PSI) and the Swiss Nuclear Utilities (Swissnuclear). The long-term aim of the MSMA project is to formulate improved closure laws for Computational Fluid Dynamics (CFD) simulations for prediction of convective boiling and eventually of the Critical Heat Flux (CHF). As boiling is controlled by the competition of numerous phenomena at various length and time scales, a multi-scale approach is employed to tackle the problem at different scales. In the MSMA project, the scales on which we focus range from the CFD scale (macro-scale), bubble size scale (meso-scale), liquid micro-layer and triple interline scale (micro-scale), and molecular scale (nano-scale). The current focus of the project is on micro- and meso- scales modeling. The numerical framework comprises a highly efficient, parallel DNS solver, the PSI-BOIL code. The code has incorporated an Immersed Boundary Method (IBM) to tackle complex geometries. For simulation of meso-scales (bubbles), we use the Constrained Interpolation Profile method: Conservative Semi-Lagrangian 2nd order (CIP-CSL2). The phase change is described either by applying conventional jump conditions at the interface, or by using the Phase Field (PF) approach. In this work, we present selected results for flows in complex geometry using the IBM, selected bubbly flow simulations using the CIP-CSL2 method and results for phase change using the PF approach. In the subsequent stage of the project, the importance of effects of nano-scale processes on the global boiling heat transfer will be evaluated. To validate the models, more experimental information will be needed in the future, so it is expected that the MSMA project will become the seed for a long-term, combined theoretical and experimental program

  19. Adaptive multiscale processing for contrast enhancement

    Science.gov (United States)

    Laine, Andrew F.; Song, Shuwu; Fan, Jian; Huda, Walter; Honeyman, Janice C.; Steinbach, Barbara G.

    1993-07-01

    This paper introduces a novel approach for accomplishing mammographic feature analysis through overcomplete multiresolution representations. We show that efficient representations may be identified from digital mammograms within a continuum of scale space and used to enhance features of importance to mammography. Choosing analyzing functions that are well localized in both space and frequency, results in a powerful methodology for image analysis. We describe methods of contrast enhancement based on two overcomplete (redundant) multiscale representations: (1) Dyadic wavelet transform (2) (phi) -transform. Mammograms are reconstructed from transform coefficients modified at one or more levels by non-linear, logarithmic and constant scale-space weight functions. Multiscale edges identified within distinct levels of transform space provide a local support for enhancement throughout each decomposition. We demonstrate that features extracted from wavelet spaces can provide an adaptive mechanism for accomplishing local contrast enhancement. We suggest that multiscale detection and local enhancement of singularities may be effectively employed for the visualization of breast pathology without excessive noise amplification.

  20. A multi-scale, multi-disciplinary approach for assessing the technological, economic and environmental performance of bio-based chemicals.

    Science.gov (United States)

    Herrgård, Markus; Sukumara, Sumesh; Campodonico, Miguel; Zhuang, Kai

    2015-12-01

    In recent years, bio-based chemicals have gained interest as a renewable alternative to petrochemicals. However, there is a significant need to assess the technological, biological, economic and environmental feasibility of bio-based chemicals, particularly during the early research phase. Recently, the Multi-scale framework for Sustainable Industrial Chemicals (MuSIC) was introduced to address this issue by integrating modelling approaches at different scales ranging from cellular to ecological scales. This framework can be further extended by incorporating modelling of the petrochemical value chain and the de novo prediction of metabolic pathways connecting existing host metabolism to desirable chemical products. This multi-scale, multi-disciplinary framework for quantitative assessment of bio-based chemicals will play a vital role in supporting engineering, strategy and policy decisions as we progress towards a sustainable chemical industry. © 2015 Authors; published by Portland Press Limited.

  1. Multi-scale modeling in morphogenesis: a critical analysis of the cellular Potts model.

    Directory of Open Access Journals (Sweden)

    Anja Voss-Böhme

    Full Text Available Cellular Potts models (CPMs are used as a modeling framework to elucidate mechanisms of biological development. They allow a spatial resolution below the cellular scale and are applied particularly when problems are studied where multiple spatial and temporal scales are involved. Despite the increasing usage of CPMs in theoretical biology, this model class has received little attention from mathematical theory. To narrow this gap, the CPMs are subjected to a theoretical study here. It is asked to which extent the updating rules establish an appropriate dynamical model of intercellular interactions and what the principal behavior at different time scales characterizes. It is shown that the longtime behavior of a CPM is degenerate in the sense that the cells consecutively die out, independent of the specific interdependence structure that characterizes the model. While CPMs are naturally defined on finite, spatially bounded lattices, possible extensions to spatially unbounded systems are explored to assess to which extent spatio-temporal limit procedures can be applied to describe the emergent behavior at the tissue scale. To elucidate the mechanistic structure of CPMs, the model class is integrated into a general multiscale framework. It is shown that the central role of the surface fluctuations, which subsume several cellular and intercellular factors, entails substantial limitations for a CPM's exploitation both as a mechanistic and as a phenomenological model.

  2. Multi-Scale Visualization Analysis of Bus Flow Average Travel Speed in Qingdao

    Science.gov (United States)

    Yong, HAN; Man, GAO; Xiao-Lei, ZHANG; Jie, LI; Ge, CHEN

    2016-11-01

    Public transportation is a kind of complex spatiotemporal behaviour. The traffic congestion and environmental pollution caused by the increase in private cars is becoming more and more serious in our city. Spatiotemporal data visualization is an effective tool for studying traffic, transforming non-visual data into recognizable images, which can reveal where/when congestion is formed, developed and disappeared in space and time simultaneously. This paper develops a multi-scale visualization of average travel speed derived from floating bus data, to enable congestion on urban bus networks to be shown and analyzed. The techniques of R language, Echarts, WebGL are used to draw statistical pictures and 3D wall map, which show the congestion in Qingdao from the view of space and time. The results are as follows:(1) There is a more severely delay in Shibei and Shinan areas than Licun and Laoshan areas; (2) The high congestion usually occurs on Hong Kong Middle Road, Shandong Road, Nanjing Road, Liaoyang West Road and Taiping Road;(3) There is a similar law from Monday to Sunday that the congestion is severer in the morning and evening rush hours than other hours; (4) On Monday morning the severity of congestion is higher than on Friday morning, and on Friday evening the severity is higher than on Monday evening. The research results will help to improve the public transportation of Qingdao.

  3. Time-Varying, Multi-Scale Adaptive System Reliability Analysis of Lifeline Infrastructure Networks

    Energy Technology Data Exchange (ETDEWEB)

    Gearhart, Jared Lee [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Kurtz, Nolan Scot [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

    2014-09-01

    The majority of current societal and economic needs world-wide are met by the existing networked, civil infrastructure. Because the cost of managing such infrastructure is high and increases with time, risk-informed decision making is essential for those with management responsibilities for these systems. To address such concerns, a methodology that accounts for new information, deterioration, component models, component importance, group importance, network reliability, hierarchical structure organization, and efficiency concerns has been developed. This methodology analyzes the use of new information through the lens of adaptive Importance Sampling for structural reliability problems. Deterioration, multi-scale bridge models, and time-variant component importance are investigated for a specific network. Furthermore, both bridge and pipeline networks are studied for group and component importance, as well as for hierarchical structures in the context of specific networks. Efficiency is the primary driver throughout this study. With this risk-informed approach, those responsible for management can address deteriorating infrastructure networks in an organized manner.

  4. Infrared Harvesting Colloidal Quantum Dot Solar Cell Based on Multi-scale Disordered Electrodes

    KAUST Repository

    Tian, Yi

    2015-06-23

    Colloidal quantum dot photovoltaics (CQDPV) offer a big potential to be a renewable energy source due to low cost and tunable band-gap. Currently, the certified power conversion efficiency of CQDPV has reached 9.2%. Compared to the 31% theoretical efficiency limit of single junction solar cells, device performances have still have a large potential to be improved. For photovoltaic devices, a classical way to enhance absorption is to increase the thickness of the active layers. Although this approach can improve absorption, it reduces the charge carriers extraction efficiency. Photo-generated carriers, in fact, are prone to recombine within the defects inside CQD active layers. In an effort to solve this problem, we proposed to increase light absorption from a given thickness of colloidal quantum dot layers with the assistance of disorder. Our approach is to develop new types of electrodes with multi-scale disordered features, which localize energy into the active layer through plasmonic effects. We fabricated nanostructured gold substrates by electrochemical methods, which allow to control surface disorder as a function of deposition conditions. We demonstrated that the light absorption from 600 nm to 800 nm is impressively enhanced, when the disorder of the nanostructured surface increases. Compared to the planar case, the most disorder case increased 65% light absorption at the wavelength of λ = 700nm in the 100 nm PbS film. The average absorption enhancement across visible and infrared region in 100 nm PbS film is 49.94%. By developing a photovoltaic module, we measured a dramatic 34% improvement in the short-circuit current density of the device. The power conversion efficiency of the tested device in top-illumination configuration showed 25% enhancement.

  5. Microstructural analysis of TRISO particles using multi-scale X-ray computed tomography

    Energy Technology Data Exchange (ETDEWEB)

    Lowe, T., E-mail: tristan.lowe@manchester.ac.uk [Manchester X-ray Imaging Facility, School of Materials, University of Manchester, M13 9PL (United Kingdom); Bradley, R.S. [Manchester X-ray Imaging Facility, School of Materials, University of Manchester, M13 9PL (United Kingdom); Yue, S. [Manchester X-ray Imaging Facility, School of Materials, University of Manchester, M13 9PL (United Kingdom); The Research Complex at Harwell, Rutherford Appleton Laboratory, Didcot, Oxfordshire OX11 0FA (United Kingdom); Barii, K. [School of Mechanical Engineering, University of Manchester, M13 9PL (United Kingdom); Gelb, J. [Zeiss Xradia Inc., Pleasanton, CA (United States); Rohbeck, N. [Manchester X-ray Imaging Facility, School of Materials, University of Manchester, M13 9PL (United Kingdom); Turner, J. [School of Mechanical Engineering, University of Manchester, M13 9PL (United Kingdom); Withers, P.J. [Manchester X-ray Imaging Facility, School of Materials, University of Manchester, M13 9PL (United Kingdom); The Research Complex at Harwell, Rutherford Appleton Laboratory, Didcot, Oxfordshire OX11 0FA (United Kingdom)

    2015-06-15

    TRISO particles, a composite nuclear fuel built up by ceramic and graphitic layers, have outstanding high temperature resistance. TRISO fuel is the key technology for High Temperature Reactors (HTRs) and the Generation IV Very High Temperature Reactor (VHTR) variant. TRISO offers unparalleled containment of fission products and is extremely robust during accident conditions. An understanding of the thermal performance and mechanical properties of TRISO fuel requires a detailed knowledge of pore sizes, their distribution and interconnectivity. Here 50 nm, nano-, and 1 μm resolution, micro-computed tomography (CT), have been used to quantify non-destructively porosity of a surrogate TRISO particle at the 0.3–10 μm and 3–100 μm scales respectively. This indicates that pore distributions can reliably be measured down to a size approximately 3 times the pixel size which is consistent with the segmentation process. Direct comparison with Scanning Electron Microscopy (SEM) sections indicates that destructive sectioning can introduce significant levels of coarse damage, especially in the pyrolytic carbon layers. Further comparative work is required to identify means of minimizing such damage for SEM studies. Finally since it is non-destructive, multi-scale time-lapse X-ray CT opens the possibility of intermittently tracking the degradation of TRISO structure under thermal cycles or radiation conditions in order to validate models of degradation such as kernel movement. X-ray CT in-situ experimentation of TRISO particles under load and temperature could also be used to understand the internal changes that occur in the particles under accident conditions.

  6. Multiscale Computational Analysis of Nitrogen and Oxygen Gas-Phase Thermochemistry in Hypersonic Flows

    Science.gov (United States)

    Bender, Jason D.

    Understanding hypersonic aerodynamics is important for the design of next-generation aerospace vehicles for space exploration, national security, and other applications. Ground-level experimental studies of hypersonic flows are difficult and expensive; thus, computational science plays a crucial role in this field. Computational fluid dynamics (CFD) simulations of extremely high-speed flows require models of chemical and thermal nonequilibrium processes, such as dissociation of diatomic molecules and vibrational energy relaxation. Current models are outdated and inadequate for advanced applications. We describe a multiscale computational study of gas-phase thermochemical processes in hypersonic flows, starting at the atomic scale and building systematically up to the continuum scale. The project was part of a larger effort centered on collaborations between aerospace scientists and computational chemists. We discuss the construction of potential energy surfaces for the N4, N2O2, and O4 systems, focusing especially on the multi-dimensional fitting problem. A new local fitting method named L-IMLS-G2 is presented and compared with a global fitting method. Then, we describe the theory of the quasiclassical trajectory (QCT) approach for modeling molecular collisions. We explain how we implemented the approach in a new parallel code for high-performance computing platforms. Results from billions of QCT simulations of high-energy N2 + N2, N2 + N, and N2 + O2 collisions are reported and analyzed. Reaction rate constants are calculated and sets of reactive trajectories are characterized at both thermal equilibrium and nonequilibrium conditions. The data shed light on fundamental mechanisms of dissociation and exchange reactions -- and their coupling to internal energy transfer processes -- in thermal environments typical of hypersonic flows. We discuss how the outcomes of this investigation and other related studies lay a rigorous foundation for new macroscopic models for

  7. Multiscale approach for the construction of equilibrated all-atom models of a poly(ethylene glycol)-based hydrogel

    Science.gov (United States)

    Li, Xianfeng; Murthy, N. Sanjeeva; Becker, Matthew L.; Latour, Robert A.

    2016-01-01

    A multiscale modeling approach is presented for the efficient construction of an equilibrated all-atom model of a cross-linked poly(ethylene glycol) (PEG)-based hydrogel using the all-atom polymer consistent force field (PCFF). The final equilibrated all-atom model was built with a systematic simulation toolset consisting of three consecutive parts: (1) building a global cross-linked PEG-chain network at experimentally determined cross-link density using an on-lattice Monte Carlo method based on the bond fluctuation model, (2) recovering the local molecular structure of the network by transitioning from the lattice model to an off-lattice coarse-grained (CG) model parameterized from PCFF, followed by equilibration using high performance molecular dynamics methods, and (3) recovering the atomistic structure of the network by reverse mapping from the equilibrated CG structure, hydrating the structure with explicitly represented water, followed by final equilibration using PCFF parameterization. The developed three-stage modeling approach has application to a wide range of other complex macromolecular hydrogel systems, including the integration of peptide, protein, and/or drug molecules as side-chains within the hydrogel network for the incorporation of bioactivity for tissue engineering, regenerative medicine, and drug delivery applications. PMID:27013229

  8. Multiscale modeling of the effect of carbon nanotube orientation on the shear deformation properties of reinforced polymer-based composites

    Energy Technology Data Exchange (ETDEWEB)

    Montazeri, A. [Institute for Nano-Science and Technology, Sharif University of Technology, Tehran (Iran, Islamic Republic of); Computational Physical Sciences Research Laboratory, School of Nano-Science, Institute for Research in Fundamental Sciences (IPM), Tehran (Iran, Islamic Republic of); Sadeghi, M. [Institute for Nano-Science and Technology, Sharif University of Technology, Tehran (Iran, Islamic Republic of); Naghdabadi, R., E-mail: naghdabd@sharif.ed [Institute for Nano-Science and Technology, Sharif University of Technology, Tehran (Iran, Islamic Republic of); Department of Mechanical Engineering, Sharif University of Technology, Tehran (Iran, Islamic Republic of); Rafii-Tabar, H. [Computational Physical Sciences Research Laboratory, School of Nano-Science, Institute for Research in Fundamental Sciences (IPM), Tehran (Iran, Islamic Republic of); Department of Medical Physics and Biomedical Engineering, and Research Centre for Medical Nanotechnology and Tissue Engineering, Shahid Beheshti University of Medical Sciences, Evin, Tehran (Iran, Islamic Republic of)

    2011-04-04

    A combination of molecular dynamics (MD), continuum elasticity and FEM is used to predict the effect of CNT orientation on the shear modulus of SWCNT-polymer nanocomposites. We first develop a transverse-isotropic elastic model of SWCNTs based on the continuum elasticity and MD to compute the transverse-isotropic elastic constants of SWCNTs. These constants are then used in an FEM-based simulation to investigate the effect of SWCNT alignment on the shear modulus of nanocomposites. Furthermore, shear stress distributions along the nanotube axis and over its cross-sectional area are investigated to study the effect of CNT orientation on the shear load transfer. - Highlights: A transverse-isotropic elastic model of SWCNTs is presented. A hierarchical MD/FEM multiscale model of SWCNT-polymer composites is developed. Behavior of these nanocomposites under shear deformation is studied. A symmetric shear stress distribution occurs only in SWCNTs with 45{sup o} orientation. The total shear load sustained is greatest in the case of 45{sup o} orientation.

  9. Multiscale modeling of the effect of carbon nanotube orientation on the shear deformation properties of reinforced polymer-based composites

    International Nuclear Information System (INIS)

    Montazeri, A.; Sadeghi, M.; Naghdabadi, R.; Rafii-Tabar, H.

    2011-01-01

    A combination of molecular dynamics (MD), continuum elasticity and FEM is used to predict the effect of CNT orientation on the shear modulus of SWCNT-polymer nanocomposites. We first develop a transverse-isotropic elastic model of SWCNTs based on the continuum elasticity and MD to compute the transverse-isotropic elastic constants of SWCNTs. These constants are then used in an FEM-based simulation to investigate the effect of SWCNT alignment on the shear modulus of nanocomposites. Furthermore, shear stress distributions along the nanotube axis and over its cross-sectional area are investigated to study the effect of CNT orientation on the shear load transfer. - Highlights: → A transverse-isotropic elastic model of SWCNTs is presented. → A hierarchical MD/FEM multiscale model of SWCNT-polymer composites is developed. → Behavior of these nanocomposites under shear deformation is studied. → A symmetric shear stress distribution occurs only in SWCNTs with 45 o orientation. → The total shear load sustained is greatest in the case of 45 o orientation.

  10. On a morphological approach of the meso-structure for the multi-scale analysis of the thermo-hydro-mechanical behaviour of cementitious materials

    International Nuclear Information System (INIS)

    Le, T.T.H.

    2011-01-01

    The investigation of the behavior of heated concrete is a major research topic which concerns the assessment of safety level of structures when exposed to high temperatures, for instance during a fire. For this purpose, several modeling approaches were developed within thermo-hydro-mechanical (THM) frameworks in order to take into account the involved physic-chemical and mechanical processes that affect stability of heated concrete. However, existing models often do note account explicitly for the heterogeneity of the material: concrete is composite material that may be schematized as an assembly of inclusions (aggregates) embedded in a cementitious matrix (cement paste). This latter may be described as a partially saturated open porous medium. The aggregates are characterized by their mineralogical nature together with their morphology and size distribution. The material heterogeneity bring an additional complexity: the need to take into account the microstructure in order to quantify the effect of matrix-inclusion thermal, hygral and mechanical incompatibilities on the THM behavior of concrete. This work is a first step in this direction. For this purpose, a three-dimensional (3D) multi-scale finite element model is developed. It allows affecting specific behaviors to matrix and inclusions. For the former, where mass transports occur within the connected porous network, a three-fluids approach (liquid water, vapor and dry air) is adopted and is coupled to a poro-mechanical damage based approach. For inclusions (aggregates) no hygral component arises a pure thermo-mechanical model is considered. The developed model is then used to investigate, either by 2D or 3D numerical simulations, effects of mineralogical nature, morphology and distribution of aggregates. Studied effects have mainly concerned the influence of these parameters on local fluctuations of simulated temperature, gas pressure and damage fields with regard to experimentally observed dispersion. The

  11. Multiscale Persistent Functions for Biomolecular Structure Characterization

    Energy Technology Data Exchange (ETDEWEB)

    Xia, Kelin [Nanyang Technological University (Singapore). Division of Mathematical Sciences, School of Physical, Mathematical Sciences and School of Biological Sciences; Li, Zhiming [Central China Normal University, Wuhan (China). Key Laboratory of Quark and Lepton Physics (MOE) and Institute of Particle Physics; Mu, Lin [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Computer Science and Mathematics Division

    2017-11-02

    Here in this paper, we introduce multiscale persistent functions for biomolecular structure characterization. The essential idea is to combine our multiscale rigidity functions (MRFs) with persistent homology analysis, so as to construct a series of multiscale persistent functions, particularly multiscale persistent entropies, for structure characterization. To clarify the fundamental idea of our method, the multiscale persistent entropy (MPE) model is discussed in great detail. Mathematically, unlike the previous persistent entropy (Chintakunta et al. in Pattern Recognit 48(2):391–401, 2015; Merelli et al. in Entropy 17(10):6872–6892, 2015; Rucco et al. in: Proceedings of ECCS 2014, Springer, pp 117–128, 2016), a special resolution parameter is incorporated into our model. Various scales can be achieved by tuning its value. Physically, our MPE can be used in conformational entropy evaluation. More specifically, it is found that our method incorporates in it a natural classification scheme. This is achieved through a density filtration of an MRF built from angular distributions. To further validate our model, a systematical comparison with the traditional entropy evaluation model is done. Additionally, it is found that our model is able to preserve the intrinsic topological features of biomolecular data much better than traditional approaches, particularly for resolutions in the intermediate range. Moreover, by comparing with traditional entropies from various grid sizes, bond angle-based methods and a persistent homology-based support vector machine method (Cang et al. in Mol Based Math Biol 3:140–162, 2015), we find that our MPE method gives the best results in terms of average true positive rate in a classic protein structure classification test. More interestingly, all-alpha and all-beta protein classes can be clearly separated from each other with zero error only in our model. Finally, a special protein structure index (PSI) is proposed, for the first

  12. A distributed multiscale computation of a tightly coupled model using the Multiscale Modeling Language

    NARCIS (Netherlands)

    Borgdorff, J.; Bona-Casas, C.; Mamonski, M.; Kurowski, K.; Piontek, T.; Bosak, B.; Rycerz, K.; Ciepiela, E.; Gubala, T.; Harezlak, D.; Bubak, M.; Lorenz, E.; Hoekstra, A.G.

    2012-01-01

    Nature is observed at all scales; with multiscale modeling, scientists bring together several scales for a holistic analysis of a phenomenon. The models on these different scales may require significant but also heterogeneous computational resources, creating the need for distributed multiscale

  13. Introduction of an agent-based multi-scale modular architecture for dynamic knowledge representation of acute inflammation

    Directory of Open Access Journals (Sweden)

    An Gary

    2008-05-01

    Full Text Available Abstract Background One of the greatest challenges facing biomedical research is the integration and sharing of vast amounts of information, not only for individual researchers, but also for the community at large. Agent Based Modeling (ABM can provide a means of addressing this challenge via a unifying translational architecture for dynamic knowledge representation. This paper presents a series of linked ABMs representing multiple levels of biological organization. They are intended to translate the knowledge derived from in vitro models of acute inflammation to clinically relevant phenomenon such as multiple organ failure. Results and Discussion ABM development followed a sequence starting with relatively direct translation from in-vitro derived rules into a cell-as-agent level ABM, leading on to concatenated ABMs into multi-tissue models, eventually resulting in topologically linked aggregate multi-tissue ABMs modeling organ-organ crosstalk. As an underlying design principle organs were considered to be functionally composed of an epithelial surface, which determined organ integrity, and an endothelial/blood interface, representing the reaction surface for the initiation and propagation of inflammation. The development of the epithelial ABM derived from an in-vitro model of gut epithelial permeability is described. Next, the epithelial ABM was concatenated with the endothelial/inflammatory cell ABM to produce an organ model of the gut. This model was validated against in-vivo models of the inflammatory response of the gut to ischemia. Finally, the gut ABM was linked to a similarly constructed pulmonary ABM to simulate the gut-pulmonary axis in the pathogenesis of multiple organ failure. The behavior of this model was validated against in-vivo and clinical observations on the cross-talk between these two organ systems Conclusion A series of ABMs are presented extending from the level of intracellular mechanism to clinically observed behavior

  14. Introduction of an agent-based multi-scale modular architecture for dynamic knowledge representation of acute inflammation.

    Science.gov (United States)

    An, Gary

    2008-05-27

    One of the greatest challenges facing biomedical research is the integration and sharing of vast amounts of information, not only for individual researchers, but also for the community at large. Agent Based Modeling (ABM) can provide a means of addressing this challenge via a unifying translational architecture for dynamic knowledge representation. This paper presents a series of linked ABMs representing multiple levels of biological organization. They are intended to translate the knowledge derived from in vitro models of acute inflammation to clinically relevant phenomenon such as multiple organ failure. ABM development followed a sequence starting with relatively direct translation from in-vitro derived rules into a cell-as-agent level ABM, leading on to concatenated ABMs into multi-tissue models, eventually resulting in topologically linked aggregate multi-tissue ABMs modeling organ-organ crosstalk. As an underlying design principle organs were considered to be functionally composed of an epithelial surface, which determined organ integrity, and an endothelial/blood interface, representing the reaction surface for the initiation and propagation of inflammation. The development of the epithelial ABM derived from an in-vitro model of gut epithelial permeability is described. Next, the epithelial ABM was concatenated with the endothelial/inflammatory cell ABM to produce an organ model of the gut. This model was validated against in-vivo models of the inflammatory response of the gut to ischemia. Finally, the gut ABM was linked to a similarly constructed pulmonary ABM to simulate the gut-pulmonary axis in the pathogenesis of multiple organ failure. The behavior of this model was validated against in-vivo and clinical observations on the cross-talk between these two organ systems. A series of ABMs are presented extending from the level of intracellular mechanism to clinically observed behavior in the intensive care setting. The ABMs all utilize cell-level agents

  15. Study of lattice strain evolution during biaxial deformation of stainless steel using a finite element and fast Fourier transform based multi-scale approach

    International Nuclear Information System (INIS)

    Upadhyay, M.V.; Van Petegem, S.; Panzner, T.; Lebensohn, R.A.; Van Swygenhoven, H.

    2016-01-01

    A multi-scale elastic-plastic finite element and fast Fourier transform based approach is proposed to study lattice strain evolution during uniaxial and biaxial loading of stainless steel cruciform shaped samples. At the macroscale, finite element simulations capture the complex coupling between applied forces in the arms and gauge stresses induced by the cruciform geometry. The predicted gauge stresses are used as macroscopic boundary conditions to drive a mesoscale elasto-viscoplastic fast Fourier transform model, from which lattice strains are calculated for particular grain families. The calculated lattice strain evolution matches well with experimental values from in-situ neutron diffraction measurements and demonstrates that the spread in lattice strain evolution between different grain families decreases with increasing biaxial stress ratio. During equibiaxial loading, the model reveals that the lattice strain evolution in all grain families, and not just the 311 grain family, is representative of the polycrystalline response. A detailed quantitative analysis of the 200 and 220 grain family reveals that the contribution of elastic and plastic anisotropy to the lattice strain evolution significantly depends on the applied stress ratio.

  16. Mechanical integrity of a carbon nanotube/copper-based through-silicon via for 3D integrated circuits: a multi-scale modeling approach.

    Science.gov (United States)

    Awad, Ibrahim; Ladani, Leila

    2015-12-04

    Carbon nanotube (CNT)/copper (Cu) composite material is proposed to replace Cu-based through-silicon vias (TSVs) in micro-electronic packages. The proposed material is believed to offer extraordinary mechanical and electrical properties and the presence of CNTs in Cu is believed to overcome issues associated with miniaturization of Cu interconnects, such as electromigration. This study introduces a multi-scale modeling of the proposed TSV in order to evaluate its mechanical integrity under mechanical and thermo-mechanical loading conditions. Molecular dynamics (MD) simulation was used to determine CNT/Cu interface adhesion properties. A cohesive zone model (CZM) was found to be most appropriate to model the interface adhesion, and CZM parameters at the nanoscale were determined using MD simulation. CZM parameters were then used in the finite element analysis in order to understand the mechanical and thermo-mechanical behavior of composite TSV at micro-scale. From the results, CNT/Cu separation does not take place prior to plastic deformation of Cu in bending, and separation does not take place when standard thermal cycling is applied. Further investigation is recommended in order to alleviate the increased plastic deformation in Cu at the CNT/Cu interface in both loading conditions.

  17. Multiscale characterization of pore spaces using multifractals analysis of scanning electronic microscopy images of carbonates

    Directory of Open Access Journals (Sweden)

    M. S. Jouini

    2011-12-01

    Full Text Available Pore spaces heterogeneity in carbonates rocks has long been identified as an important factor impacting reservoir productivity. In this paper, we study the heterogeneity of carbonate rocks pore spaces based on the image analysis of scanning electron microscopy (SEM data acquired at various magnifications. Sixty images of twelve carbonate samples from a reservoir in the Middle East were analyzed. First, pore spaces were extracted from SEM images using a segmentation technique based on watershed algorithm. Pores geometries revealed a multifractal behavior at various magnifications from 800x to 12 000x. In addition, the singularity spectrum provided quantitative values that describe the degree of heterogeneity in the carbonates samples. Moreover, for the majority of the analyzed samples, we found low variations (around 5% in the multifractal dimensions for magnifications between 1700x and 12 000x. Finally, these results demonstrate that multifractal analysis could be an appropriate tool for characterizing quantitatively the heterogeneity of carbonate pore spaces geometries. However, our findings show that magnification has an impact on multifractal dimensions, revealing the limit of applicability of multifractal descriptions for these natural structures.

  18. Urban Flow and Pollutant Dispersion Simulation with Multi-scale coupling of Meteorological Model with Computational Fluid Dynamic Analysis

    Science.gov (United States)

    Liu, Yushi; Poh, Hee Joo

    2014-11-01

    The Computational Fluid Dynamics analysis has become increasingly important in modern urban planning in order to create highly livable city. This paper presents a multi-scale modeling methodology which couples Weather Research and Forecasting (WRF) Model with open source CFD simulation tool, OpenFOAM. This coupling enables the simulation of the wind flow and pollutant dispersion in urban built-up area with high resolution mesh. In this methodology meso-scale model WRF provides the boundary condition for the micro-scale CFD model OpenFOAM. The advantage is that the realistic weather condition is taken into account in the CFD simulation and complexity of building layout can be handled with ease by meshing utility of OpenFOAM. The result is validated against the Joint Urban 2003 Tracer Field Tests in Oklahoma City and there is reasonably good agreement between the CFD simulation and field observation. The coupling of WRF- OpenFOAM provide urban planners with reliable environmental modeling tool in actual urban built-up area; and it can be further extended with consideration of future weather conditions for the scenario studies on climate change impact.

  19. Assessment of Heart Rate Variability during an Endurance Mountain Trail Race by Multi-Scale Entropy Analysis

    Directory of Open Access Journals (Sweden)

    Montserrat Vallverdú

    2017-12-01

    Full Text Available The aim of the study was to analyze heart rate variability (HRV response to high-intensity exercise during a 35-km mountain trail race and to ascertain whether fitness level could influence autonomic nervous system (ANS modulation. Time-domain, frequency-domain, and multi-scale entropy (MSE indexes were calculated for eleven mountain-trail runners who completed the race. Many changes were observed, mostly related to exercise load and fatigue. These changes were characterized by increased mean values and standard deviations of the normal-to-normal intervals associated with sympathetic activity, and by decreased differences between successive intervals related to parasympathetic activity. Normalized low frequency (LF power suggested that ANS modulation varied greatly during the race and between individuals. Normalized high frequency (HF power, associated with parasympathetic activity, varied considerably over the race, and tended to decrease at the final stages, whereas changes in the LF/HF ratio corresponded to intervals with varying exercise load. MSE indexes, related to system complexity, indicated the existence of many interactions between the heart and its neurological control mechanism. The time-domain, frequency-domain, and MSE indexes were also able to discriminate faster from slower runners, mainly in the more difficult and in the final stages of the race. These findings suggest the use of HRV analysis to study cardiac function mechanisms in endurance sports.

  20. Modeling the effects of light and sucrose on in vitro propagated plants: a multiscale system analysis using artificial intelligence technology.

    Science.gov (United States)

    Gago, Jorge; Martínez-Núñez, Lourdes; Landín, Mariana; Flexas, Jaume; Gallego, Pedro P

    2014-01-01

    Plant acclimation is a highly complex process, which cannot be fully understood by analysis at any one specific level (i.e. subcellular, cellular or whole plant scale). Various soft-computing techniques, such as neural networks or fuzzy logic, were designed to analyze complex multivariate data sets and might be used to model large such multiscale data sets in plant biology. In this study we assessed the effectiveness of applying neuro-fuzzy logic to modeling the effects of light intensities and sucrose content/concentration in the in vitro culture of kiwifruit on plant acclimation, by modeling multivariate data from 14 parameters at different biological scales of organization. The model provides insights through application of 14 sets of straightforward rules and indicates that plants with lower stomatal aperture areas and higher photoinhibition and photoprotective status score best for acclimation. The model suggests the best condition for obtaining higher quality acclimatized plantlets is the combination of 2.3% sucrose and photonflux of 122-130 µmol m(-2) s(-1). Our results demonstrate that artificial intelligence models are not only successful in identifying complex non-linear interactions among variables, by integrating large-scale data sets from different levels of biological organization in a holistic plant systems-biology approach, but can also be used successfully for inferring new results without further experimental work.

  1. Near scale-free dynamics in neural population activity of waking/sleeping rats revealed by multiscale analysis.

    Directory of Open Access Journals (Sweden)

    Leonid A Safonov

    Full Text Available A neuron embedded in an intact brain, unlike an isolated neuron, participates in network activity at various spatial resolutions. Such multiple scale spatial dynamics is potentially reflected in multiple time scales of temporal dynamics. We identify such multiple dynamical time scales of the inter-spike interval (ISI fluctuations of neurons of waking/sleeping rats by means of multiscale analysis. The time scale of large non-Gaussianity in the ISI fluctuations, measured with the Castaing method, ranges up to several minutes, markedly escaping the low-pass filtering characteristics of neurons. A comparison between neural activity during waking and sleeping reveals that non-Gaussianity is stronger during waking than sleeping throughout the entire range of scales observed. We find a remarkable property of near scale independence of the magnitude correlations as the primary cause of persistent non-Gaussianity. Such scale-invariance of correlations is characteristic of multiplicative cascade processes and raises the possibility of the existence of a scale independent memory preserving mechanism.

  2. Adaptive Multiscale Noise Control Enhanced Stochastic Resonance Method Based on Modified EEMD with Its Application in Bearing Fault Diagnosis

    Directory of Open Access Journals (Sweden)

    Jimeng Li

    2016-01-01

    Full Text Available The structure of mechanical equipment becomes increasingly complex, and tough environments under which it works often make bearings and gears subject to failure. However, effective extraction of useful feature information submerged in strong noise that is indicative of structural defects has remained a major challenge. Therefore, an adaptive multiscale noise control enhanced stochastic resonance (SR method based on modified ensemble empirical mode decomposition (EEMD for mechanical fault diagnosis is proposed in the paper. According to the oscillation characteristics of signal itself, the algorithm of modified EEMD can adaptively decompose the fault signals into different scales and it reduces the decomposition levels to improve calculation efficiency of the proposed method. Through filter processing with the constructed filters, the orthogonality of adjacent intrinsic mode functions (IMFs can be improved, which is conducive to enhancing the extraction of weak features from strong noise. The constructed signal obtained by using IMFs is inputted into the SR system, and the noise control parameter of different scales is optimized and selected with the help of the genetic algorithm, thus achieving the enhancement extraction of weak features. Finally, simulation experiments and engineering application of bearing fault diagnosis demonstrate the effectiveness and feasibility of the proposed method.

  3. Multi-scale modelling of radiation damage in Fe-Cr based on ab initio electronic structure calculations

    International Nuclear Information System (INIS)

    Olsson, Paer

    2004-04-01

    The efficiency of fast neutron reactors, such as for fusion, breeding and transmutation, depend strongly on the neutron radiation resistance of the materials used in the reactors. The binary Fe-Cr alloy, which has many attractive properties in this regard, is the base for the best steels of today which are, however, still not up to the required standards. Therefore, substantial effort has been devoted to finding new materials that can cope with the demands better. Experimental studies must be complemented with extensive theoretical modelling in order to understand the effects that different alloying elements has on the resistance properties of materials. To this end, the first steps of multi-scale modelling has been taken, starting out with ab initio calculations of the electronic structure of the complete concentration range range of the disordered binary Fe-C alloy. The mixing enthalpy of Fe-Cr has been quantitatively predicted and has, together with data from literature, been used in order to fit two sets of interatomic potentials for the purpose of simulating defect evolution with molecular dynamics and kinetic Monte-Carlo codes. These dedicated Fe-Cr alloy potentials are new and represent important additions to the pure element potentials that can be found in literature

  4. Self-adaptive Newton-based iteration strategy for the LES of turbulent multi-scale flows

    International Nuclear Information System (INIS)

    Daude, F.; Mary, I.; Comte, P.

    2014-01-01

    An improvement of the efficiency of implicit schemes based on Newton-like methods for the simulation of turbulent flows by compressible LES or DNS is proposed. It hinges on a zonal Self-Adaptive Newton method (hereafter denoted SAN), capable of taking advantage of Newton convergence rate heterogeneities in multi-scale flow configurations due to a strong spatial variation of the mesh resolution, such as transitional or turbulent flows controlled by small actuators or passive devices. Thanks to a predictor of the local Newton convergence rate, SAN provides computational savings by allocating resources in regions where they are most needed. The consistency with explicit time integration and the efficiency of the method are checked in three test cases: - The standard test-case of 2-D linear advection of a vortex, on three different two-block grids. - Transition to 3-D turbulence on the lee-side of an airfoil at high angle of attack, which features a challenging laminar separation bubble with a turbulent reattachment. - A passively-controlled turbulent transonic cavity flow, for which the CPU time is reduced by a factor of 10 with respect to the baseline algorithm, illustrates the interest of the proposed algorithm. (authors)

  5. Multi-scale modelling of radiation damage in Fe-Cr based on ab initio electronic structure calculations

    Energy Technology Data Exchange (ETDEWEB)

    Olsson, Paer

    2004-04-01

    The efficiency of fast neutron reactors, such as for fusion, breeding and transmutation, depend strongly on the neutron radiation resistance of the materials used in the reactors. The binary Fe-Cr alloy, which has many attractive properties in this regard, is the base for the best steels of today which are, however, still not up to the required standards. Therefore, substantial effort has been devoted to finding new materials that can cope with the demands better. Experimental studies must be complemented with extensive theoretical modelling in order to understand the effects that different alloying elements has on the resistance properties of materials. To this end, the first steps of multi-scale modelling has been taken, starting out with ab initio calculations of the electronic structure of the complete concentration range range of the disordered binary Fe-C alloy. The mixing enthalpy of Fe-Cr has been quantitatively predicted and has, together with data from literature, been used in order to fit two sets of interatomic potentials for the purpose of simulating defect evolution with molecular dynamics and kinetic Monte-Carlo codes. These dedicated Fe-Cr alloy potentials are new and represent important additions to the pure element potentials that can be found in literature.

  6. Optical system design with wide field of view and high resolution based on monocentric multi-scale construction

    Science.gov (United States)

    Wang, Fang; Wang, Hu; Xiao, Nan; Shen, Yang; Xue, Yaoke

    2018-03-01

    With the development of related technology gradually mature in the field of optoelectronic information, it is a great demand to design an optical system with high resolution and wide field of view(FOV). However, as it is illustrated in conventional Applied Optics, there is a contradiction between these two characteristics. Namely, the FOV and imaging resolution are limited by each other. Here, based on the study of typical wide-FOV optical system design, we propose the monocentric multi-scale system design method to solve this problem. Consisting of a concentric spherical lens and a series of micro-lens array, this system has effective improvement on its imaging quality. As an example, we designed a typical imaging system, which has a focal length of 35mm and a instantaneous field angle of 14.7", as well as the FOV set to be 120°. By analyzing the imaging quality, we demonstrate that in different FOV, all the values of MTF at 200lp/mm are higher than 0.4 when the sampling frequency of the Nyquist is 200lp/mm, which shows a good accordance with our design.

  7. Modeling natural emissions in the Community Multiscale Air Quality (CMAQ Model–I: building an emissions data base

    Directory of Open Access Journals (Sweden)

    S. F. Mueller

    2010-05-01

    Full Text Available A natural emissions inventory for the continental United States and surrounding territories is needed in order to use the US Environmental Protection Agency Community Multiscale Air Quality (CMAQ Model for simulating natural air quality. The CMAQ air modeling system (including the Sparse Matrix Operator Kernel Emissions (SMOKE emissions processing system currently estimates non-methane volatile organic compound (NMVOC emissions from biogenic sources, nitrogen oxide (NOx emissions from soils, ammonia from animals, several types of particulate and reactive gas emissions from fires, as well as sea salt emissions. However, there are several emission categories that are not commonly treated by the standard CMAQ Model system. Most notable among these are nitrogen oxide emissions from lightning, reduced sulfur emissions from oceans, geothermal features and other continental sources, windblown dust particulate, and reactive chlorine gas emissions linked with sea salt chloride. A review of past emissions modeling work and existing global emissions data bases provides information and data necessary for preparing a more complete natural emissions data base for CMAQ applications. A model-ready natural emissions data base is developed to complement the anthropogenic emissions inventory used by the VISTAS Regional Planning Organization in its work analyzing regional haze based on the year 2002. This new data base covers a modeling domain that includes the continental United States plus large portions of Canada, Mexico and surrounding oceans. Comparing July 2002 source data reveals that natural emissions account for 16% of total gaseous sulfur (sulfur dioxide, dimethylsulfide and hydrogen sulfide, 44% of total NOx, 80% of reactive carbonaceous gases (NMVOCs and carbon monoxide, 28% of ammonia, 96% of total chlorine (hydrochloric acid, nitryl chloride and sea salt chloride, and 84% of fine particles (i.e., those smaller than 2.5 μm in size released into the

  8. Modeling natural emissions in the Community Multiscale Air Quality (CMAQ) Model-I: building an emissions data base

    Science.gov (United States)

    Smith, S. N.; Mueller, S. F.

    2010-05-01

    A natural emissions inventory for the continental United States and surrounding territories is needed in order to use the US Environmental Protection Agency Community Multiscale Air Quality (CMAQ) Model for simulating natural air quality. The CMAQ air modeling system (including the Sparse Matrix Operator Kernel Emissions (SMOKE) emissions processing system) currently estimates non-methane volatile organic compound (NMVOC) emissions from biogenic sources, nitrogen oxide (NOx) emissions from soils, ammonia from animals, several types of particulate and reactive gas emissions from fires, as well as sea salt emissions. However, there are several emission categories that are not commonly treated by the standard CMAQ Model system. Most notable among these are nitrogen oxide emissions from lightning, reduced sulfur emissions from oceans, geothermal features and other continental sources, windblown dust particulate, and reactive chlorine gas emissions linked with sea salt chloride. A review of past emissions modeling work and existing global emissions data bases provides information and data necessary for preparing a more complete natural emissions data base for CMAQ applications. A model-ready natural emissions data base is developed to complement the anthropogenic emissions inventory used by the VISTAS Regional Planning Organization in its work analyzing regional haze based on the year 2002. This new data base covers a modeling domain that includes the continental United States plus large portions of Canada, Mexico and surrounding oceans. Comparing July 2002 source data reveals that natural emissions account for 16% of total gaseous sulfur (sulfur dioxide, dimethylsulfide and hydrogen sulfide), 44% of total NOx, 80% of reactive carbonaceous gases (NMVOCs and carbon monoxide), 28% of ammonia, 96% of total chlorine (hydrochloric acid, nitryl chloride and sea salt chloride), and 84% of fine particles (i.e., those smaller than 2.5 μm in size) released into the atmosphere

  9. Modeling natural emissions in the Community Multiscale Air Quality (CMAQ) model - Part 1: Building an emissions data base

    Science.gov (United States)

    Smith, S. N.; Mueller, S. F.

    2010-01-01

    A natural emissions inventory for the continental United States and surrounding territories is needed in order to use the US Environmental Protection Agency Community Multiscale Air Quality (CMAQ) Model for simulating natural air quality. The CMAQ air modeling system (including the Sparse Matrix Operator Kernel Emissions (SMOKE) emissions processing system) currently estimates volatile organic compound (VOC) emissions from biogenic sources, nitrogen oxide (NOx) emissions from soils, ammonia from animals, several types of particulate and reactive gas emissions from fires, as well as windblown dust and sea salt emissions. However, there are several emission categories that are not commonly treated by the standard CMAQ Model system. Most notable among these are nitrogen oxide emissions from lightning, reduced sulfur emissions from oceans, geothermal features and other continental sources, and reactive chlorine gas emissions linked with sea salt chloride. A review of past emissions modeling work and existing global emissions data bases provides information and data necessary for preparing a more complete natural emissions data base for CMAQ applications. A model-ready natural emissions data base is developed to complement the anthropogenic emissions inventory used by the VISTAS Regional Planning Organization in its work analyzing regional haze based on the year 2002. This new data base covers a modeling domain that includes the continental United States plus large portions of Canada, Mexico and surrounding oceans. Comparing July 2002 source data reveals that natural emissions account for 16% of total gaseous sulfur (sulfur dioxide, dimethylsulfide and hydrogen sulfide), 44% of total NOx, 80% of reactive carbonaceous gases (VOCs and carbon monoxide), 28% of ammonia, 96% of total chlorine (hydrochloric acid, nitryl chloride and sea salt chloride), and 84% of fine particles (i.e., those smaller than 2.5 μm in size) released into the atmosphere. The seasonality and

  10. Value at risk estimation with entropy-based wavelet analysis in exchange markets

    Science.gov (United States)

    He, Kaijian; Wang, Lijun; Zou, Yingchao; Lai, Kin Keung

    2014-08-01

    In recent years, exchange markets are increasingly integrated together. Fluctuations and risks across different exchange markets exhibit co-moving and complex dynamics. In this paper we propose the entropy-based multivariate wavelet based approaches to analyze the multiscale characteristic in the multidimensional domain and improve further the Value at Risk estimation reliability. Wavelet analysis has been introduced to construct the entropy-based Multiscale Portfolio Value at Risk estimation algorithm to account for the multiscale dynamic correlation. The entropy measure has been proposed as the more effective measure with the error minimization principle to select the best basis when determining the wavelet families and the decomposition level to use. The empirical studies conducted in this paper have provided positive evidence as to the superior performance of the proposed approach, using the closely related Chinese Renminbi and European Euro exchange market.

  11. Distributed multiscale computing with MUSCLE 2, the Multiscale Coupling Library and Environment

    NARCIS (Netherlands)

    Borgdorff, J.; Mamonski, M.; Bosak, B.; Kurowski, K.; Ben Belgacem, M.; Chopard, B.; Groen, D.; Coveney, P.V.; Hoekstra, A.G.

    2014-01-01

    We present the Multiscale Coupling Library and Environment: MUSCLE 2. This multiscale component-based execution environment has a simple to use Java, C++, C, Python and Fortran API, compatible with MPI, OpenMP and threading codes. We demonstrate its local and distributed computing capabilities and

  12. Multiscale image-based modeling and simulation of gas flow and particle transport in the human lungs

    Science.gov (United States)

    Tawhai, Merryn H; Hoffman, Eric A

    2013-01-01

    Improved understanding of structure and function relationships in the human lungs in individuals and sub-populations is fundamentally important to the future of pulmonary medicine. Image-based measures of the lungs can provide sensitive indicators of localized features, however to provide a better prediction of lung response to disease, treatment and environment, it is desirable to integrate quantifiable regional features from imaging with associated value-added high-level modeling. With this objective in mind, recent advances in computational fluid dynamics (CFD) of the bronchial airways - from a single bifurcation symmetric model to a multiscale image-based subject-specific lung model - will be reviewed. The interaction of CFD models with local parenchymal tissue expansion - assessed by image registration - allows new understanding of the interplay between environment, hot spots where inhaled aerosols could accumulate, and inflammation. To bridge ventilation function with image-derived central airway structure in CFD, an airway geometrical modeling method that spans from the model ‘entrance’ to the terminal bronchioles will be introduced. Finally, the effects of turbulent flows and CFD turbulence models on aerosol transport and deposition will be discussed. CFD simulation of airflow and particle transport in the human lung has been pursued by a number of research groups, whose interest has been in studying flow physics and airways resistance, improving drug delivery, or investigating which populations are most susceptible to inhaled pollutants. The three most important factors that need to be considered in airway CFD studies are lung structure, regional lung function, and flow characteristics. Their correct treatment is important because the transport of therapeutic or pollutant particles is dependent on the characteristics of the flow by which they are transported; and the airflow in the lungs is dependent on the geometry of the airways and how ventilation

  13. Wavelet Cross-Spectrum Analysis of Multi-Scale Disturbance Instability and Transition on Sharp Cone Hypersonic Boundary Layer

    International Nuclear Information System (INIS)

    Jian, Han; Nan, Jiang

    2008-01-01

    Experimental measurement of hypersonic boundary layer stability and transition on a sharp cone with a half angle of 5° is carried out at free-coming stream Mach number 6 in a hypersonic wind tunnel. Mean and fluctuation surface-thermal-flux characteristics of the hypersonic boundary layer flow are measured by Pt-thin-film thermocouple temperature sensors installed at 28 stations on the cone surface along longitudinal direction. At hypersonic speeds, the dominant flow instabilities demonstrate that the growth rate of the second mode tends to exceed that of the low-frequency mode. Wavelet-based cross-spectrum technique is introduced to obtain the multi-scale cross-spectral characteristics of the fluctuating signals in the frequency range of the second mode. Nonlinear interactions both of the second mode disturbance and the first mode disturbance are demonstrated to be dominant instabilities in the initial stage of laminar-turbulence transition for hypersonic shear flow. (fundamental areas of phenomenology (including applications))

  14. Multi-scale radiomic analysis of sub-cortical regions in MRI related to autism, gender and age

    Science.gov (United States)

    Chaddad, Ahmad; Desrosiers, Christian; Toews, Matthew

    2017-03-01

    We propose using multi-scale image textures to investigate links between neuroanatomical regions and clinical variables in MRI. Texture features are derived at multiple scales of resolution based on the Laplacian-of-Gaussian (LoG) filter. Three quantifier functions (Average, Standard Deviation and Entropy) are used to summarize texture statistics within standard, automatically segmented neuroanatomical regions. Significance tests are performed to identify regional texture differences between ASD vs. TDC and male vs. female groups, as well as correlations with age (corrected p brain imaging data exchange (ABIDE) brain MRI dataset is used to evaluate texture features derived from 31 brain regions from 1112 subjects including 573 typically developing control (TDC, 99 females, 474 males) and 539 Autism spectrum disorder (ASD, 65 female and 474 male) subjects. Statistically significant texture differences between ASD vs. TDC groups are identified asymmetrically in the right hippocampus, left choroid-plexus and corpus callosum (CC), and symmetrically in the cerebellar white matter. Sex-related texture differences in TDC subjects are found in primarily in the left amygdala, left cerebellar white matter, and brain stem. Correlations between age and texture in TDC subjects are found in the thalamus-proper, caudate and pallidum, most exhibiting bilateral symmetry.

  15. Multi-scale exploration of the technical, economic, and environmental dimensions of bio-based chemical production.

    Science.gov (United States)

    Zhuang, Kai H; Herrgård, Markus J

    2015-09-01

    In recent years, bio-based chemicals have gained traction as a sustainable alternative to petrochemicals. However, despite rapid advances in metabolic engineering and synthetic biology, there remain significant economic and environmental challenges. In order to maximize the impact of research investment in a new bio-based chemical industry, there is a need for assessing the technological, economic, and environmental potentials of combinations of biomass feedstocks, biochemical products, bioprocess technologies, and metabolic engineering approaches in the early phase of development of cell factories. To address this issue, we have developed a comprehensive Multi-scale framework for modeling Sustainable Industrial Chemicals production (MuSIC), which integrates modeling approaches for cellular metabolism, bioreactor design, upstream/downstream processes and economic impact assessment. We demonstrate the use of the MuSIC framework in a case study where two major polymer precursors (1,3-propanediol and 3-hydroxypropionic acid) are produced from two biomass feedstocks (corn-based glucose and soy-based glycerol) through 66 proposed biosynthetic pathways in two host organisms (Escherichia coli and Saccharomyces cerevisiae). The MuSIC framework allows exploration of tradeoffs and interactions between economy-scale objectives (e.g. profit maximization, emission minimization), constraints (e.g. land-use constraints) and process- and cell-scale technology choices (e.g. strain design or oxygenation conditions). We demonstrate that economy-scale assessment can be used to guide specific strain design decisions in metabolic engineering, and that these design decisions can be affected by non-intuitive dependencies across multiple scales. Copyright © 2015 International Metabolic Engineering Society. Published by Elsevier Inc. All rights reserved.

  16. Integrating landscape analysis and planning: a multi-scale approach for oriented management of tourist recreation.

    Science.gov (United States)

    de Aranzabal, Itziar; Schmitz, María F; Pineda, Francisco D

    2009-11-01

    Tourism and landscape are interdependent concepts. Nature- and culture-based tourism are now quite well developed activities and can constitute an excellent way of exploiting the natural resources of certain areas, and should therefore be considered as key objectives in landscape planning and management in a growing number of countries. All of this calls for careful evaluation of the effects of tourism on the territory. This article focuses on an integrated spatial method for landscape analysis aimed at quantifying the relationship between preferences of visitors and landscape features. The spatial expression of the model relating types of leisure and recreational preferences to the potential capacity of the landscape to meet them involves a set of maps showing degrees of potential visitor satisfaction. The method constitutes a useful tool for the design of tourism planning and management strategies, with landscape conservation as a reference.

  17. Integrating Landscape Analysis and Planning: A Multi-Scale Approach for Oriented Management of Tourist Recreation

    Science.gov (United States)

    de Aranzabal, Itziar; Schmitz, María F.; Pineda, Francisco D.

    2009-11-01

    Tourism and landscape are interdependent concepts. Nature- and culture-based tourism are now quite well developed activities and can constitute an excellent way of exploiting the natural resources of certain areas, and should therefore be considered as key objectives in landscape planning and management in a growing number of countries. All of this calls for careful evaluation of the effects of tourism on the territory. This article focuses on an integrated spatial method for landscape analysis aimed at quantifying the relationship between preferences of visitors and landscape features. The spatial expression of the model relating types of leisure and recreational preferences to the potential capacity of the landscape to meet them involves a set of maps showing degrees of potential visitor satisfaction. The method constitutes a useful tool for the design of tourism planning and management strategies, with landscape conservation as a reference.

  18. Multi-scale cellulose based new bio-aerogel composites with thermal super-insulating and tunable mechanical properties.

    Science.gov (United States)

    Seantier, Bastien; Bendahou, Dounia; Bendahou, Abdelkader; Grohens, Yves; Kaddami, Hamid

    2016-03-15

    Bio-composite aerogels based on bleached cellulose fibers (BCF) and cellulose nanoparticles having various morphological and physico-chemical characteristics are prepared by a freeze-drying technique and characterized. The various composite aerogels obtained were compared to a BCF aerogel used as the reference. Severe changes in the material morphology were observed by SEM and AFM due to a variation of the cellulose nanoparticle properties such as the aspect ratio, the crystalline index and the surface charge density. BCF fibers form a 3D network and they are surrounded by the cellulose nanoparticle thin films inducing a significant reduction of the size of the pores in comparison with a neat BCF based aerogel. BET analyses confirm the appearance of a new organization structure with pores of nanometric sizes. As a consequence, a decrease of the thermal conductivities is observed from 28mWm(-1)K(-1) (BCF aerogel) to 23mWm(-1)K(-1) (bio-composite aerogel), which is below the air conductivity (25mWm(-1)K(-1)). This improvement of the insulation properties for composite materials is more pronounced for aerogels based on cellulose nanoparticles having a low crystalline index and high surface charge (NFC-2h). The significant improvement of their insulation properties allows the bio-composite aerogels to enter the super-insulating materials family. The characteristics of cellulose nanoparticles also influence the mechanical properties of the bio-composite aerogels. A significant improvement of the mechanical properties under compression is obtained by self-organization, yielding a multi-scale architecture of the cellulose nanoparticles in the bio-composite aerogels. In this case, the mechanical property is more dependent on the morphology of the composite aerogel rather than the intrinsic characteristics of the cellulose nanoparticles. Copyright © 2015 Elsevier Ltd. All rights reserved.

  19. Resistance Training Exercise Program for Intervention to Enhance Gait Function in Elderly Chronically Ill Patients: Multivariate Multiscale Entropy for Center of Pressure Signal Analysis

    Directory of Open Access Journals (Sweden)

    Ming-Shu Chen

    2014-01-01

    Full Text Available Falls are unpredictable accidents, and the resulting injuries can be serious in the elderly, particularly those with chronic diseases. Regular exercise is recommended to prevent and treat hypertension and other chronic diseases by reducing clinical blood pressure. The “complexity index” (CI, based on multiscale entropy (MSE algorithm, has been applied in recent studies to show a person’s adaptability to intrinsic and external perturbations and widely used measure of postural sway or stability. The multivariate multiscale entropy (MMSE was advanced algorithm used to calculate the complexity index (CI values of the center of pressure (COP data. In this study, we applied the MSE & MMSE to analyze gait function of 24 elderly, chronically ill patients (44% female; 56% male; mean age, 67.56±10.70 years with either cardiovascular disease, diabetes mellitus, or osteoporosis. After a 12-week training program, postural stability measurements showed significant improvements. Our results showed beneficial effects of resistance training, which can be used to improve postural stability in the elderly and indicated that MMSE algorithms to calculate CI of the COP data were superior to the multiscale entropy (MSE algorithm to identify the sense of balance in the elderly.

  20. Multivariate multiscale complex network analysis of vertical upward oil-water two-phase flow in a small diameter pipe.

    Science.gov (United States)

    Gao, Zhong-Ke; Yang, Yu-Xuan; Zhai, Lu-Sheng; Dang, Wei-Dong; Yu, Jia-Liang; Jin, Ning-De

    2016-02-02

    High water cut and low velocity vertical upward oil-water two-phase flow is a typical complex system with the features of multiscale, unstable and non-homogenous. We first measure local flow information by using distributed conductance sensor and then develop a multivariate multiscale complex network (MMCN) to reveal the dispersed oil-in-water local flow behavior. Specifically, we infer complex networks at different scales from multi-channel measurements for three typical vertical oil-in-water flow patterns. Then we characterize the generated multiscale complex networks in terms of network clustering measure. The results suggest that the clustering coefficient entropy from the MMCN not only allows indicating the oil-in-water flow pattern transition but also enables to probe the dynamical flow behavior governing the transitions of vertical oil-water two-phase flow.

  1. RNA-TVcurve: a Web server for RNA secondary structure comparison based on a multi-scale similarity of its triple vector curve representation.

    Science.gov (United States)

    Li, Ying; Shi, Xiaohu; Liang, Yanchun; Xie, Juan; Zhang, Yu; Ma, Qin

    2017-01-21

    RNAs have been found to carry diverse functionalities in nature. Inferring the similarity between two given RNAs is a fundamental step to understand and interpret their functional relationship. The majority of functional RNAs show conserved secondary structures, rather than sequence conservation. Those algorithms relying on sequence-based features usually have limitations in their prediction performance. Hence, integrating RNA structure features is very critical for RNA analysis. Existing algorithms mainly fall into two categories: alignment-based and alignment-free. The alignment-free algorithms of RNA comparison usually have lower time complexity than alignment-based algorithms. An alignment-free RNA comparison algorithm was proposed, in which novel numerical representations RNA-TVcurve (triple vector curve representation) of RNA sequence and corresponding secondary structure features are provided. Then a multi-scale similarity score of two given RNAs was designed based on wavelet decomposition of their numerical representation. In support of RNA mutation and phylogenetic analysis, a web server (RNA-TVcurve) was designed based on this alignment-free RNA comparison algorithm. It provides three functional modules: 1) visualization of numerical representation of RNA secondary structure; 2) detection of single-point mutation based on secondary structure; and 3) comparison of pairwise and multiple RNA secondary structures. The inputs of the web server require RNA primary sequences, while corresponding secondary structures are optional. For the primary sequences alone, the web server can compute the secondary structures using free energy minimization algorithm in terms of RNAfold tool from Vienna RNA package. RNA-TVcurve is the first integrated web server, based on an alignment-free method, to deliver a suite of RNA analysis functions, including visualization, mutation analysis and multiple RNAs structure comparison. The comparison results with two popular RNA

  2. Multiscale approach to the physics of radiation damage with ions

    International Nuclear Information System (INIS)

    Surdutovich, E.; Solov'yov, A.

    2014-01-01

    The multiscale approach to the assessment of bio-damage resulting upon irradiation of biological media with ions is reviewed, explained and compared to other approaches. The processes of ion propagation in the medium concurrent with ionization and excitation of molecules, transport of secondary products, dynamics of the medium, and biological damage take place on a number of different temporal, spatial and energy scales. The multiscale approach, a physical phenomenon-based analysis of the scenario that leads to radiation damage, has been designed to consider all relevant effects on a variety of scales and develop an approach to the quantitative assessment of biological damage as a result of irradiation with ions. Presently, physical and chemical effects are included in the scenario while the biological effects such as DNA repair are only mentioned. This paper explains the scenario of radiation damage with ions, overviews its major parts, and applies the multiscale approach to different experimental conditions. On the basis of this experience, the recipe for application of the multiscale approach is formulated. The recipe leads to the calculation of relative biological effectiveness. (authors)

  3. Towards systems biology of the gravity response of higher plants -multiscale analysis of Arabidopsis thaliana root growth

    Science.gov (United States)

    Palme, Klaus; Aubry, D.; Bensch, M.; Schmidt, T.; Ronneberger, O.; Neu, C.; Li, X.; Wang, H.; Santos, F.; Wang, B.; Paponov, I.; Ditengou, F. A.; Teale, W. T.; Volkmann, D.; Baluska, F.; Nonis, A.; Trevisan, S.; Ruperti, B.; Dovzhenko, A.

    Gravity plays a fundamental role in plant growth and development. Up to now, little is known about the molecular organisation of the signal transduction cascades and networks which co-ordinate gravity perception and response. By using an integrated systems biological approach, a systems analysis of gravity perception and the subsequent tightly-regulated growth response is planned in the model plant Arabidopsis thaliana. This approach will address questions such as: (i) what are the components of gravity signal transduction pathways? (ii) what are the dynamics of these components? (iii) what is their spatio-temporal regulation in different tis-sues? Using Arabidopsis thaliana as a model-we use root growth to obtain insights in the gravity response. New techniques enable identification of the individual genes affected by grav-ity and further integration of transcriptomics and proteomics data into interaction networks and cell communication events that operate during gravitropic curvature. Using systematic multiscale analysis we have identified regulatory networks consisting of transcription factors, the protein degradation machinery, vesicle trafficking and cellular signalling during the gravire-sponse. We developed approach allowing to incorporate key features of the root system across all relevant spatial and temporal scales to describe gene-expression patterns and correlate them with individual gene and protein functions. Combination of high-resolution microscopy and novel computational tools resulted in development of the root 3D model in which quantitative descriptions of cellular network properties and of multicellular interactions important in root growth and gravitropism can be integrated for the first time.

  4. Analysis of multi-scale morphodynamic behaviour of a high energy beach facing the Sea of Japan

    Directory of Open Access Journals (Sweden)

    Harshinie Urmila Karunarathna

    2015-07-01

    Full Text Available Monthly cross shore beach profiles measured at the Ogata Wave Observation pier located in Joetsu-Ogata Coast, Niigata Prefecture, Japan, was analysed to investigate multi-scale morphodynamic beach behaviour. The Ogata beach, facing the Sea of Japan, is subjected to high energy wave conditions with that has a strong winter/summer seasonal signature. The measured beach profiles at the beach show very significant variability where cross-shore movement of shoreline position and lowering of the beach at the location of measurements exceed 20 m and 4 m respectively. The shoreline position seems to follow the seasonal variability of incident wave climate where a correlation coefficient of 0.77 was found between monthly averaged incident significant wave height and the measured monthly shoreline position. During the summer months, the beach variability mostly concentrated to in the sub-tidal part of the profile, while a significant amount of upper beach change was observed during the winter months. The beach profile shape was found to rotate between three different beach states in time; (i concave reflective profile; (ii profile with sub-tidal berm; and (iii gentle, dissipative profile. Empirical Orthogonal Function (EOF analysis of the profiles show that the variability of beach profile shape is dominated by (a upper shoreface steepening; (b sub tidal berm development and dissipation; and (c variability of the overall profile slope, which have some longer than seasonal cyclic signatures. Comparison of temporal EOFs with climate indices such as Southern Oscillation Index and Pacific Decadal Oscillation index shows notable some correlations between profile change and climatic variability in the region. The analysis also shows that the morphological variability of Joetsu-Ogata Coast has similarities and some distinct spatial and temporal differences to beaches of similar kind found elsewhere.

  5. Simulating Nationwide Pandemics: Applying the Multi-scale Epidemiologic Simulation and Analysis System to Human Infectious Diseases

    Energy Technology Data Exchange (ETDEWEB)

    Dombroski, M; Melius, C; Edmunds, T; Banks, L E; Bates, T; Wheeler, R

    2008-09-24

    This study uses the Multi-scale Epidemiologic Simulation and Analysis (MESA) system developed for foreign animal diseases to assess consequences of nationwide human infectious disease outbreaks. A literature review identified the state of the art in both small-scale regional models and large-scale nationwide models and characterized key aspects of a nationwide epidemiological model. The MESA system offers computational advantages over existing epidemiological models and enables a broader array of stochastic analyses of model runs to be conducted because of those computational advantages. However, it has only been demonstrated on foreign animal diseases. This paper applied the MESA modeling methodology to human epidemiology. The methodology divided 2000 US Census data at the census tract level into school-bound children, work-bound workers, elderly, and stay at home individuals. The model simulated mixing among these groups by incorporating schools, workplaces, households, and long-distance travel via airports. A baseline scenario with fixed input parameters was run for a nationwide influenza outbreak using relatively simple social distancing countermeasures. Analysis from the baseline scenario showed one of three possible results: (1) the outbreak burned itself out before it had a chance to spread regionally, (2) the outbreak spread regionally and lasted a relatively long time, although constrained geography enabled it to eventually be contained without affecting a disproportionately large number of people, or (3) the outbreak spread through air travel and lasted a long time with unconstrained geography, becoming a nationwide pandemic. These results are consistent with empirical influenza outbreak data. The results showed that simply scaling up a regional small-scale model is unlikely to account for all the complex variables and their interactions involved in a nationwide outbreak. There are several limitations of the methodology that should be explored in future

  6. Predicting the impact of combined therapies on myeloma cell growth using a hybrid multi-scale agent-based model.

    Science.gov (United States)

    Ji, Zhiwei; Su, Jing; Wu, Dan; Peng, Huiming; Zhao, Weiling; Nlong Zhao, Brian; Zhou, Xiaobo

    2017-01-31

    Multiple myeloma is a malignant still incurable plasma cell disorder. This is due to refractory disease relapse, immune impairment, and development of multi-drug resistance. The growth of malignant plasma cells is dependent on the bone marrow (BM) microenvironment and evasion of the host's anti-tumor immune response. Hence, we hypothesized that targeting tumor-stromal cell interaction and endogenous immune system in BM will potentially improve the response of multiple myeloma (MM). Therefore, we proposed a computational simulation of the myeloma development in the complicated microenvironment which includes immune cell components and bone marrow stromal cells and predicted the effects of combined treatment with multi-drugs on myeloma cell growth. We constructed a hybrid multi-scale agent-based model (HABM) that combines an ODE system and Agent-based model (ABM). The ODEs was used for modeling the dynamic changes of intracellular signal transductions and ABM for modeling the cell-cell interactions between stromal cells, tumor, and immune components in the BM. This model simulated myeloma growth in the bone marrow microenvironment and revealed the important role of immune system in this process. The predicted outcomes were consistent with the experimental observations from previous studies. Moreover, we applied this model to predict the treatment effects of three key therapeutic drugs used for MM, and found that the combination of these three drugs potentially suppress the growth of myeloma cells and reactivate the immune response. In summary, the proposed model may serve as a novel computational platform for simulating the formation of MM and evaluating the treatment response of MM to multiple drugs.

  7. Extraction of multi-scale landslide morphological features based on local Gi* using airborne LiDAR-derived DEM

    Science.gov (United States)

    Shi, Wenzhong; Deng, Susu; Xu, Wenbing

    2018-02-01

    For automatic landslide detection, landslide morphological features should be quantitatively expressed and extracted. High-resolution Digital Elevation Models (DEMs) derived from airborne Light Detection and Ranging (LiDAR) data allow fine-scale morphological features to be extracted, but noise in DEMs influences morphological feature extraction, and the multi-scale nature of landslide features should be considered. This paper proposes a method to extract landslide morphological features characterized by homogeneous spatial patterns. Both profile and tangential curvature are utilized to quantify land surface morphology, and a local Gi* statistic is calculated for each cell to identify significant patterns of clustering of similar morphometric values. The method was tested on both synthetic surfaces simulating natural terrain and airborne LiDAR data acquired over an area dominated by shallow debris slides and flows. The test results of the synthetic data indicate that the concave and convex morphologies of the simulated terrain features at different scales and distinctness could be recognized using the proposed method, even when random noise was added to the synthetic data. In the test area, cells with large local Gi* values were extracted at a specified significance level from the profile and the tangential curvature image generated from the LiDAR-derived 1-m DEM. The morphologies of landslide main scarps, source areas and trails were clearly indicated, and the morphological features were represented by clusters of extracted cells. A comparison with the morphological feature extraction method based on curvature thresholds proved the proposed method's robustness to DEM noise. When verified against a landslide inventory, the morphological features of almost all recent (historical (> 10 years) landslides were extracted. This finding indicates that the proposed method can facilitate landslide detection, although the cell clusters extracted from curvature images should

  8. A multiscale and multiphysics numerical framework for modelling of hygrothermal ageing in laminated composites

    NARCIS (Netherlands)

    Barcelos Carneiro M Rocha, Iuri; van der Meer, F.P.; Nijssen, RPL; Sluijs, Bert

    2017-01-01

    In this work, a numerical framework for modelling of hygrothermal ageing in laminated composites is proposed. The model consists of a macroscopic diffusion analysis based on Fick's second law coupled with a multiscale FE2 stress analysis in order to take microscopic degradation

  9. Multifunctional multiscale composites: Processing, modeling and characterization

    Science.gov (United States)

    Qiu, Jingjing

    Carbon nanotubes (CNTs) demonstrate extraordinary properties and show great promise in enhancing out-of-plane properties of traditional polymer/fiber composites and enabling functionality. However, current manufacturing challenges hinder the realization of their potential. In the dissertation research, both experimental and computational efforts have been conducted to investigate effective manufacturing techniques of CNT integrated multiscale composites. The fabricated composites demonstrated significant improvements in physical properties, such as tensile strength, tensile modulus, inter-laminar shear strength, thermal dimension stability and electrical conductivity. Such multiscale composites were truly multifunctional with the addition of CNTs. Furthermore, a novel hierarchical multiscale modeling method was developed in this research. Molecular dynamic (MD) simulation offered reasonable explanation of CNTs dispersion and their motion in polymer solution. Bi-mode finite-extensible-nonlinear-elastic (FENE) dumbbell simulation was used to analyze the influence of CNT length distribution on the stress tensor and shear-rate-dependent viscosity. Based on the simulated viscosity profile and empirical equations from experiments, a macroscale flow simulation model on the finite element method (FEM) method was developed and validated to predict resin flow behavior in the processing of CNT-enhanced multiscale composites. The proposed multiscale modeling method provided a comprehensive understanding of micro/nano flow in both atomistic details and mesoscale. The simulation model can be used to optimize process design and control of the mold-filling process in multiscale composite manufacturing. This research provided systematic investigations into the CNT-based multiscale composites. The results from this study may be used to leverage the benefits of CNTs and open up new application opportunities for high-performance multifunctional multiscale composites. Keywords. Carbon

  10. Analysis of multi-scale systemic risk in Brazil's financial market

    Directory of Open Access Journals (Sweden)

    Adriana Bruscato Bortoluzzo

    2014-06-01

    Full Text Available This work analyzes whether the relationship between risk and returns predicted by the Capital Asset Pricing Model (CAPM is valid in the Brazilian stock market. The analysis is based on discrete wavelet decomposition on different time scales. This technique allows to analyze the relationship between different time horizons, since the short-term ones (2 to 4 days up to the long-term ones (64 to 128 days. The results indicate that there is a negative or null relationship between systemic risk and returns for Brazil from 2004 to 2007. As the average excess return of a market portfolio in relation to a risk-free asset during that period was positive, it would be expected this relationship to be positive. That is, higher systematic risk should result in higher excess returns, which did not occur. Therefore, during that period, appropriate compensation for systemic risk was not observed in the Brazilian market. The scales that proved to be most significant to the risk-return relation were the first three, which corresponded to short-term time horizons. When treating differently, year-by-year, and consequently separating positive and negative premiums, some relevance is found, during some years, in the risk/return relation predicted by the CAPM. However, this pattern did not persist throughout the years. Therefore, there is not any evidence strong enough confirming that the asset pricing follows the model.

  11. Multiscale modeling of interwoven Kevlar fibers based on random walk to predict yarn structural response

    Science.gov (United States)

    Recchia, Stephen

    Kevlar is the most common high-end plastic filament yarn used in body armor, tire reinforcement, and wear resistant applications. Kevlar is a trade name for an aramid fiber. These are fibers in which the chain molecules are highly oriented along the fiber axis, so the strength of the chemical bond can be exploited. The bulk material is extruded into filaments that are bound together into yarn, which may be chorded with other materials as in car tires, woven into a fabric, or layered in an epoxy to make composite panels. The high tensile strength to low weight ratio makes this material ideal for designs that decrease weight and inertia, such as automobile tires, body panels, and body armor. For designs that use Kevlar, increasing the strength, or tenacity, to weight ratio would improve performance or reduce cost of all products that are based on this material. This thesis computationally and experimentally investigates the tenacity and stiffness of Kevlar yarns with varying twist ratios. The test boundary conditions were replicated with a geometrically accurate finite element model, resulting in a customized code that can reproduce tortuous filaments in a yarn was developed. The solid model geometry capturing filament tortuosity was implemented through a random walk method of axial geometry creation. A finite element analysis successfully recreated the yarn strength and stiffness dependency observed during the tests. The physics applied in the finite element model was reproduced in an analytical equation that was able to predict the failure strength and strain dependency of twist ratio. The analytical solution can be employed to optimize yarn design for high strength applications.

  12. Multi-scale effects of nestling diet on breeding performance in a terrestrial top predator inferred from stable isotope analysis.

    Directory of Open Access Journals (Sweden)

    Jaime Resano-Mayor

    Full Text Available Inter-individual diet variation within populations is likely to have important ecological and evolutionary implications. The diet-fitness relationships at the individual level and the emerging population processes are, however, poorly understood for most avian predators inhabiting complex terrestrial ecosystems. In this study, we use an isotopic approach to assess the trophic ecology of nestlings in a long-lived raptor, the Bonelli's eagle Aquila fasciata, and investigate whether nestling dietary breath and main prey consumption can affect the species' reproductive performance at two spatial scales: territories within populations and populations over a large geographic area. At the territory level, those breeding pairs whose nestlings consumed similar diets to the overall population (i.e. moderate consumption of preferred prey, but complemented by alternative prey categories or those disproportionally consuming preferred prey were more likely to fledge two chicks. An increase in the diet diversity, however, related negatively with productivity. The age and replacements of breeding pair members had also an influence on productivity, with more fledglings associated to adult pairs with few replacements, as expected in long-lived species. At the population level, mean productivity was higher in those population-years with lower dietary breadth and higher diet similarity among territories, which was related to an overall higher consumption of preferred prey. Thus, we revealed a correspondence in diet-fitness relationships at two spatial scales: territories and populations. We suggest that stable isotope analyses may be a powerful tool to monitor the diet of terrestrial avian predators on large spatio-temporal scales, which could serve to detect potential changes in the availability of those prey on which predators depend for breeding. We encourage ecologists and evolutionary and conservation biologists concerned with the multi-scale fitness

  13. Multiscale seismicity analysis and forecasting: examples from the Western Pacific and Iceland

    International Nuclear Information System (INIS)

    Eberhard, A. J.

    2014-01-01

    Seismicity forecasting has three major challenges: (1) the development of models or algorithms to forecast of seismicity, (2) the evaluation and testing of the forecasts and (3) the need for an appropriate software package. The goal of my thesis is to improve seismicity forecasting. I do this by contributing to a solution for all of the three challenges, using data from the West Pacific and from Iceland. The thesis is split into three chapters, each focusing on one of the challenges and each chapter will be (or already is) published in a peer-reviewed scientific journal. This first chapter (chapter 2 in this thesis) is about testing of seismic forecasts. The Collaboratory for the Study of Earthquake Predictability (CSEP, www.cseptesting.org; Jordan, 2006) has been conducting an earthquake forecast experiment in the western Pacific. The data and forecasts of this experiment serve as example for this chapter. For the three participating statistical models, I analyze the first four years of this experiment. I use likelihood-based metrics to evaluate the consistency of the forecasts with the observed target earthquakes, and I apply measures based on Student’s t-test and the Wilcoxon signed-rank test to compare the forecasts. I estimate also the uncertainties of the test results resulting from uncertainties in earthquake location and seismic moment. The estimated uncertainties are relatively small and suggest that the evaluation metrics are relatively robust. In chapter 3 I focus on the forecast itself with an Operational Earthquake Forecasting (OEF) experiment–forecasting seismicity in near real-time–for Iceland. The goal is to estimate the feasibility of OEF with the state-of-the-art models. I use the period between 2007 and 2010 and a sparsely processed catalogue as basis for a retrospective forecasting experiment with next-day forecasts. To better understand the effect of updating cycle on the probability gain I also use scheme in which the forecasts are

  14. Multiscale seismicity analysis and forecasting: examples from the Western Pacific and Iceland

    Energy Technology Data Exchange (ETDEWEB)

    Eberhard, A. J.

    2014-07-01

    Seismicity forecasting has three major challenges: (1) the development of models or algorithms to forecast of seismicity, (2) the evaluation and testing of the forecasts and (3) the need for an appropriate software package. The goal of my thesis is to improve seismicity forecasting. I do this by contributing to a solution for all of the three challenges, using data from the West Pacific and from Iceland. The thesis is split into three chapters, each focusing on one of the challenges and each chapter will be (or already is) published in a peer-reviewed scientific journal. This first chapter (chapter 2 in this thesis) is about testing of seismic forecasts. The Collaboratory for the Study of Earthquake Predictability (CSEP, www.cseptesting.org; Jordan, 2006) has been conducting an earthquake forecast experiment in the western Pacific. The data and forecasts of this experiment serve as example for this chapter. For the three participating statistical models, I analyze the first four years of this experiment. I use likelihood-based metrics to evaluate the consistency of the forecasts with the observed target earthquakes, and I apply measures based on Student’s t-test and the Wilcoxon signed-rank test to compare the forecasts. I estimate also the uncertainties of the test results resulting from uncertainties in earthquake location and seismic moment. The estimated uncertainties are relatively small and suggest that the evaluation metrics are relatively robust. In chapter 3 I focus on the forecast itself with an Operational Earthquake Forecasting (OEF) experiment–forecasting seismicity in near real-time–for Iceland. The goal is to estimate the feasibility of OEF with the state-of-the-art models. I use the period between 2007 and 2010 and a sparsely processed catalogue as basis for a retrospective forecasting experiment with next-day forecasts. To better understand the effect of updating cycle on the probability gain I also use scheme in which the forecasts are

  15. Efficient multiscale magnetic-domain analysis of iron-core material under mechanical stress

    Science.gov (United States)

    Nishikubo, Atsushi; Ito, Shumpei; Mifune, Takeshi; Matsuo, Tetsuji; Kaido, Chikara; Takahashi, Yasuhito; Fujiwara, Koji

    2018-05-01

    For an efficient analysis of magnetization, a partial-implicit solution method is improved using an assembled domain structure model with six-domain mesoscopic particles exhibiting pinning-type hysteresis. The quantitative analysis of non-oriented silicon steel succeeds in predicting the stress dependence of hysteresis loss with computation times greatly reduced by using the improved partial-implicit method. The effect of cell division along the thickness direction is also evaluated.

  16. Multi-scale trends analysis of landscape stressors in an urbanizing coastal watershed

    Science.gov (United States)

    Anthropogenic land based stressors within a watershed can deliver major impacts to downstream and adjacent coastal waterways affecting water quality and estuarine habitats. Our research focused on a subset of non-point sources of watershed stressors specifically, human population...

  17. The research of selection model based on LOD in multi-scale display of electronic map

    Science.gov (United States)

    Zhang, Jinming; You, Xiong; Liu, Yingzhen

    2008-10-01

    This paper proposes a selection model based on LOD to aid the display of electronic map. The ratio of display scale to map scale is regarded as a LOD operator. The categorization rule, classification rule, elementary rule and spatial geometry character rule of LOD operator setting are also concluded.

  18. Multiscale change-point analysis of inhomogeneous Poisson processes using unbalanced wavelet decompositions

    NARCIS (Netherlands)

    Jansen, M.H.; Di Bucchianico, A.; Mattheij, R.M.M.; Peletier, M.A.

    2006-01-01

    We present a continuous wavelet analysis of count data with timevarying intensities. The objective is to extract intervals with significant intensities from background intervals. This includes the precise starting point of the significant interval, its exact duration and the (average) level of

  19. Multi-scale modeling of the thermo-hydro- mechanical behaviour of heterogeneous materials. Application to cement-based materials under severe loads

    International Nuclear Information System (INIS)

    Grondin, Frederic Alain

    2005-01-01

    The work of modeling presented here relates to the study of the thermo-hydro- mechanical behaviour of porous materials based on hydraulic binder such as concrete, High Performance Concrete or more generally cement-based materials. This work is based on the exploitation of the Digital Concrete model, of the finite element code Symphonie developed in the Scientific and Technical Centre for Building (CSTB), in coupling with the homogenization methods to obtain macroscopic behaviour laws drawn from the Micro-Macro relations. Scales of investigation, macroscopic and microscopic, has been exploited by simulation in order to allow the comprehension fine of the behaviour of cement-based materials according to thermal, hydrous and mechanical loads. It appears necessary to take into account various scales of modeling. In order to study the behaviour of the structure, we are brought to reduce the scale of investigation to study the material more particularly. The research tasks presented suggest a new approach for the identification of the multi-physic behaviour of materials by simulation. In complement of the purely experimental approach, based on observations on the sample with measurements of the apparent parameters on the macroscopic scale, this new approach allows to obtain the fine analysis of elementary mechanisms in acting within the material. These elementary mechanisms are at the origin of the evolution of the macroscopic parameters measured in experimental tests. In this work, coefficients of the thermo-hydro-mechanical behaviour law of porous materials and the equivalent hydraulic conductivity were obtained by a multi-scales approach. Applications has been carried out on the study of the damaged behaviour of cement-based materials, in the objective to determine the elasticity tensor and the permeability tensor of a High Performance Concrete at high temperatures under a mechanical load. Also, the study of the strain evolution of cement-based materials at low

  20. A multiscale MDCT image-based breathing lung model with time-varying regional ventilation

    Energy Technology Data Exchange (ETDEWEB)

    Yin, Youbing, E-mail: youbing-yin@uiowa.edu [Department of Mechanical and Industrial Engineering, The University of Iowa, Iowa City, IA 52242 (United States); IIHR-Hydroscience and Engineering, The University of Iowa, Iowa City, IA 52242 (United States); Department of Radiology, The University of Iowa, Iowa City, IA 52242 (United States); Choi, Jiwoong, E-mail: jiwoong-choi@uiowa.edu [Department of Mechanical and Industrial Engineering, The University of Iowa, Iowa City, IA 52242 (United States); IIHR-Hydroscience and Engineering, The University of Iowa, Iowa City, IA 52242 (United States); Hoffman, Eric A., E-mail: eric-hoffman@uiowa.edu [Department of Radiology, The University of Iowa, Iowa City, IA 52242 (United States); Department of Biomedical Engineering, The University of Iowa, Iowa City, IA 52242 (United States); Department of Internal Medicine, The University of Iowa, Iowa City, IA 52242 (United States); Tawhai, Merryn H., E-mail: m.tawhai@auckland.ac.nz [Auckland Bioengineering Institute, The University of Auckland, Auckland (New Zealand); Lin, Ching-Long, E-mail: ching-long-lin@uiowa.edu [Department of Mechanical and Industrial Engineering, The University of Iowa, Iowa City, IA 52242 (United States); IIHR-Hydroscience and Engineering, The University of Iowa, Iowa City, IA 52242 (United States)

    2013-07-01

    A novel algorithm is presented that links local structural variables (regional ventilation and deforming central airways) to global function (total lung volume) in the lung over three imaged lung volumes, to derive a breathing lung model for computational fluid dynamics simulation. The algorithm constitutes the core of an integrative, image-based computational framework for subject-specific simulation of the breathing lung. For the first time, the algorithm is applied to three multi-detector row computed tomography (MDCT) volumetric lung images of the same individual. A key technique in linking global and local variables over multiple images is an in-house mass-preserving image registration method. Throughout breathing cycles, cubic interpolation is employed to ensure C{sub 1} continuity in constructing time-varying regional ventilation at the whole lung level, flow rate fractions exiting the terminal airways, and airway deformation. The imaged exit airway flow rate fractions are derived from regional ventilation with the aid of a three-dimensional (3D) and one-dimensional (1D) coupled airway tree that connects the airways to the alveolar tissue. An in-house parallel large-eddy simulation (LES) technique is adopted to capture turbulent-transitional-laminar flows in both normal and deep breathing conditions. The results obtained by the proposed algorithm when using three lung volume images are compared with those using only one or two volume images. The three-volume-based lung model produces physiologically-consistent time-varying pressure and ventilation distribution. The one-volume-based lung model under-predicts pressure drop and yields un-physiological lobar ventilation. The two-volume-based model can account for airway deformation and non-uniform regional ventilation to some extent, but does not capture the non-linear features of the lung.

  1. A multiscale MDCT image-based breathing lung model with time-varying regional ventilation

    Science.gov (United States)

    Yin, Youbing; Choi, Jiwoong; Hoffman, Eric A.; Tawhai, Merryn H.; Lin, Ching-Long

    2012-01-01

    A novel algorithm is presented that links local structural variables (regional ventilation and deforming central airways) to global function (total lung volume) in the lung over three imaged lung volumes, to derive a breathing lung model for computational fluid dynamics simulation. The algorithm constitutes the core of an integrative, image-based computational framework for subject-specific simulation of the breathing lung. For the first time, the algorithm is applied to three multi-detector row computed tomography (MDCT) volumetric lung images of the same individual. A key technique in linking global and local variables over multiple images is an in-house mass-preserving image registration method. Throughout breathing cycles, cubic interpolation is employed to ensure C1 continuity in constructing time-varying regional ventilation at the whole lung level, flow rate fractions exiting the terminal airways, and airway deformation. The imaged exit airway flow rate fractions are derived from regional ventilation with the aid of a three-dimensional (3D) and one-dimensional (1D) coupled airway tree that connects the airways to the alveolar tissue. An in-house parallel large-eddy simulation (LES) technique is adopted to capture turbulent-transitional-laminar flows in both normal and deep breathing conditions. The results obtained by the proposed algorithm when using three lung volume images are compared with those using only one or two volume images. The three-volume-based lung model produces physiologically-consistent time-varying pressure and ventilation distribution. The one-volume-based lung model under-predicts pressure drop and yields un-physiological lobar ventilation. The two-volume-based model can account for airway deformation and non-uniform regional ventilation to some extent, but does not capture the non-linear features of the lung. PMID:23794749

  2. Nonlocal multi-scale traffic flow models: analysis beyond vector spaces

    Directory of Open Access Journals (Sweden)

    Peter E. Kloeden

    2016-08-01

    Full Text Available Abstract Realistic models of traffic flow are nonlinear and involve nonlocal effects in balance laws. Flow characteristics of different types of vehicles, such as cars and trucks, need to be described differently. Two alternatives are used here, $$L^p$$ L p -valued Lebesgue measurable density functions and signed Radon measures. The resulting solution spaces are metric spaces that do not have a linear structure, so the usual convenient methods of functional analysis are no longer applicable. Instead ideas from mutational analysis will be used, in particular the method of Euler compactness will be applied to establish the well-posedness of the nonlocal balance laws. This involves the concatenation of solutions of piecewise linear systems on successive time subintervals obtained by freezing the nonlinear nonlocal coefficients to their values at the start of each subinterval. Various compactness criteria lead to a convergent subsequence. Careful estimates of the linear systems are needed to implement this program.

  3. Text Stream Trend Analysis using Multiscale Visual Analytics with Applications to Social Media Systems

    Energy Technology Data Exchange (ETDEWEB)

    Steed, Chad A [ORNL; Beaver, Justin M [ORNL; BogenII, Paul L. [Google Inc.; Drouhard, Margaret MEG G [ORNL; Pyle, Joshua M [ORNL

    2015-01-01

    In this paper, we introduce a new visual analytics system, called Matisse, that allows exploration of global trends in textual information streams with specific application to social media platforms. Despite the potential for real-time situational awareness using these services, interactive analysis of such semi-structured textual information is a challenge due to the high-throughput and high-velocity properties. Matisse addresses these challenges through the following contributions: (1) robust stream data management, (2) automated sen- timent/emotion analytics, (3) inferential temporal, geospatial, and term-frequency visualizations, and (4) a flexible drill-down interaction scheme that progresses from macroscale to microscale views. In addition to describing these contributions, our work-in-progress paper concludes with a practical case study focused on the analysis of Twitter 1% sample stream information captured during the week of the Boston Marathon bombings.

  4. Methods for High-Order Multi-Scale and Stochastic Problems Analysis, Algorithms, and Applications

    Science.gov (United States)

    2016-10-17

    the good performance of these schemes. In [4], we study spectral collocation methods for functions which are analytic in the open interval but have...the detailed detonation struc- ture. The efficient parallel AMR-WENO method provides a good tool for these detonation simulations. In [10], a...with his students a few years ago. This method has now found a wide usage in applications. In [11], we give a stability analysis, using both the GKS

  5. Multi-scale location analysis of vulnerabilities and their link to disturbances within digital ecosystems

    OpenAIRE

    Jackson, Jennifer

    2017-01-01

    As computer networks evolve, so too does the techniques used by attackers to exploit new vulnerabilities. Natural ecosystems already have resistant and resilient properties that help protect them from unwanted disturbances despite the existence of different vulnerabilities. Computer networks and their environments can be considered as digital ecosystems with different vulnerabilities, and security attacks can be considered as unwanted disturbances. Analysis of vulnerabilities and attacks from...

  6. Multi-scale Analysis of Topographic Surface Roughness in the Midland Valley, Scotland

    OpenAIRE

    Grohmann, Carlos

    2017-01-01

    Surface roughness is an important geomorphological variable which has been used in the earth and planetary sciences to infer material properties, current/past processes and the time elapsed since formation. No single definition exists, however within the context of geomorphometry we use surface roughness as a expression of the variability of a topographic surface at a given scale, where the scale of analysis is determined by the size of the landforms or geomorphic features of interest. Six te...

  7. A Posteriori Error Analysis and Uncertainty Quantification for Adaptive Multiscale Operator Decomposition Methods for Multiphysics Problems

    Science.gov (United States)

    2014-04-01

    Integral Role in Soft Tissue Mechanics, K. Troyer, D. Estep, and C. Puttlitz, Acta Biomaterialia 8 (201 2), 234-244 • A posteriori analysis of multi rate...2013, submitted • A posteriori error estimation for the Lax -Wendroff finite difference scheme, J. B. Collins, D. Estep, and S. Tavener, Journal of...oped over neArly six decades of activity and the major developments form a highly inter- connected web. We do not. ətternpt to review the history of

  8. Multidisciplinary approach and multi-scale elemental analysis and separation chemistry

    International Nuclear Information System (INIS)

    Mariet, Clarisse

    2014-01-01

    The development of methods for the analysis of trace elements is an important component of my research activities either for a radiometric measure or mass spectrometric detection. Many studies raise the question of the chemical signature of a sample or a process: eruptive behavior of a volcano, indicator of pollution, ion exchange in vectors vesicles of active principles,... Each time, highly sensitive analytical procedures, accurate and multi-elementary as well as the development of specific protocols were needed. Neutron activation analysis has often been used as reference procedure and allowed to validate the chemical lixiviation and the measurement by ICP-MS. Analysis of radioactive samples requires skills in analysis of trace but also separation chemistry. Two separation methods occupy an important place in the separation chemistry of radionuclides: chromatography and liquid-liquid extraction. The study of extraction of Lanthanide (III) by the oxide octyl (phenyl)-n, N-diisobutyl-carbamoylmethyl phosphine (CMPO) and a calixarene-CMPO led to better understand and quantify the influence of operating conditions on their performance of extraction and selectivity. The high concentration of salts in aqueous solutions required to reason in terms of thermodynamic activities in relying on a comprehensive approach to quantification of deviations from ideality. In order to reduce the amount of waste generated and costs, alternatives to the hydrometallurgical extraction processes were considered using ionic liquids at low temperatures as alternative solvents in biphasic processes. Remaining in this logic of effluent reduction, miniaturization of the liquid-liquid extraction is also study so as to exploit the characteristics of microscopic scale (very large specific surface, short diffusion distances). The miniaturization of chromatographic separations carries the same ambitions of gain of volumes of wastes and reagents. The miniaturization of the separation Uranium

  9. An Improved Algorithm Based on Minimum Spanning Tree for Multi-scale Segmentation of Remote Sensing Imagery

    Directory of Open Access Journals (Sweden)

    LI Hui

    2015-07-01

    Full Text Available As the basis of object-oriented information extraction from remote sensing imagery,image segmentation using multiple image features,exploiting spatial context information, and by a multi-scale approach are currently the research focuses. Using an optimization approach of the graph theory, an improved multi-scale image segmentation method is proposed. In this method, the image is applied with a coherent enhancement anisotropic diffusion filter followed by a minimum spanning tree segmentation approach, and the resulting segments are merged with reference to a minimum heterogeneity criterion.The heterogeneity criterion is defined as a function of the spectral characteristics and shape parameters of segments. The purpose of the merging step is to realize the multi-scale image segmentation. Tested on two images, the proposed method was visually and quantitatively compared with the segmentation method employed in the eCognition software. The results show that the proposed method is effective and outperforms the latter on areas with subtle spectral differences.

  10. Efficient Computation of Multiscale Entropy over Short Biomedical Time Series Based on Linear State-Space Models

    Directory of Open Access Journals (Sweden)

    Luca Faes

    2017-01-01

    Full Text Available The most common approach to assess the dynamical complexity of a time series across multiple temporal scales makes use of the multiscale entropy (MSE and refined MSE (RMSE measures. In spite of their popularity, MSE and RMSE lack an analytical framework allowing their calculation for known dynamic processes and cannot be reliably computed over short time series. To overcome these limitations, we propose a method to assess RMSE for autoregressive (AR stochastic processes. The method makes use of linear state-space (SS models to provide the multiscale parametric representation of an AR process observed at different time scales and exploits the SS parameters to quantify analytically the complexity of the process. The resulting linear MSE (LMSE measure is first tested in simulations, both theoretically to relate the multiscale complexity of AR processes to their dynamical properties and over short process realizations to assess its computational reliability in comparison with RMSE. Then, it is applied to the time series of heart period, arterial pressure, and respiration measured for healthy subjects monitored in resting conditions and during physiological stress. This application to short-term cardiovascular variability documents that LMSE can describe better than RMSE the activity of physiological mechanisms producing biological oscillations at different temporal scales.

  11. Hierarchical multiscale modeling for flows in fractured media using generalized multiscale finite element method

    KAUST Repository

    Efendiev, Yalchin R.

    2015-06-05

    In this paper, we develop a multiscale finite element method for solving flows in fractured media. Our approach is based on generalized multiscale finite element method (GMsFEM), where we represent the fracture effects on a coarse grid via multiscale basis functions. These multiscale basis functions are constructed in the offline stage via local spectral problems following GMsFEM. To represent the fractures on the fine grid, we consider two approaches (1) discrete fracture model (DFM) (2) embedded fracture model (EFM) and their combination. In DFM, the fractures are resolved via the fine grid, while in EFM the fracture and the fine grid block interaction is represented as a source term. In the proposed multiscale method, additional multiscale basis functions are used to represent the long fractures, while short-size fractures are collectively represented by a single basis functions. The procedure is automatically done via local spectral problems. In this regard, our approach shares common concepts with several approaches proposed in the literature as we discuss. We would like to emphasize that our goal is not to compare DFM with EFM, but rather to develop GMsFEM framework which uses these (DFM or EFM) fine-grid discretization techniques. Numerical results are presented, where we demonstrate how one can adaptively add basis functions in the regions of interest based on error indicators. We also discuss the use of randomized snapshots (Calo et al. Randomized oversampling for generalized multiscale finite element methods, 2014), which reduces the offline computational cost.

  12. Multiscale visual quality assessment for cluster analysis with self-organizing maps

    Science.gov (United States)

    Bernard, Jürgen; von Landesberger, Tatiana; Bremm, Sebastian; Schreck, Tobias

    2011-01-01

    Cluster analysis is an important data mining technique for analyzing large amounts of data, reducing many objects to a limited number of clusters. Cluster visualization techniques aim at supporting the user in better understanding the characteristics and relationships among the found clusters. While promising approaches to visual cluster analysis already exist, these usually fall short of incorporating the quality of the obtained clustering results. However, due to the nature of the clustering process, quality plays an important aspect, as for most practical data sets, typically many different clusterings are possible. Being aware of clustering quality is important to judge the expressiveness of a given cluster visualization, or to adjust the clustering process with refined parameters, among others. In this work, we present an encompassing suite of visual tools for quality assessment of an important visual cluster algorithm, namely, the Self-Organizing Map (SOM) technique. We define, measure, and visualize the notion of SOM cluster quality along a hierarchy of cluster abstractions. The quality abstractions range from simple scalar-valued quality scores up to the structural comparison of a given SOM clustering with output of additional supportive clustering methods. The suite of methods allows the user to assess the SOM quality on the appropriate abstraction level, and arrive at improved clustering results. We implement our tools in an integrated system, apply it on experimental data sets, and show its applicability.

  13. Multi-scale AM-FM motion analysis of ultrasound videos of carotid artery plaques

    Science.gov (United States)

    Murillo, Sergio; Murray, Victor; Loizou, C. P.; Pattichis, C. S.; Pattichis, Marios; Barriga, E. Simon

    2012-03-01

    An estimated 82 million American adults have one or more type of cardiovascular diseases (CVD). CVD is the leading cause of death (1 of every 3 deaths) in the United States. When considered separately from other CVDs, stroke ranks third among all causes of death behind diseases of the heart and cancer. Stroke accounts for 1 out of every 18 deaths and is the leading cause of serious long-term disability in the United States. Motion estimation of ultrasound videos (US) of carotid artery (CA) plaques provides important information regarding plaque deformation that should be considered for distinguishing between symptomatic and asymptomatic plaques. In this paper, we present the development of verifiable methods for the estimation of plaque motion. Our methodology is tested on a set of 34 (5 symptomatic and 29 asymptomatic) ultrasound videos of carotid artery plaques. Plaque and wall motion analysis provides information about plaque instability and is used in an attempt to differentiate between symptomatic and asymptomatic cases. The final goal for motion estimation and analysis is to identify pathological conditions that can be detected from motion changes due to changes in tissue stiffness.

  14. Multiscale Trend Analysis for Pampa Grasslands Using Ground Data and Vegetation Sensor Imagery

    Directory of Open Access Journals (Sweden)

    Fernando C. Scottá

    2015-07-01

    Full Text Available This study aimed to evaluate changes in the aboveground net primary productivity (ANPP of grasslands in the Pampa biome by using experimental plots and changes in the spectral responses of similar vegetation communities obtained by remote sensing and to compare both datasets with meteorological variations to validate the transition scales of the datasets. Two different geographic scales were considered in this study. At the local scale, an analysis of the climate and its direct influences on grassland ANPP was performed using data from a long-term experiment. At the regional scale, the influences of climate on the grassland reflectance patterns were determined using vegetation sensor imagery data. Overall, the monthly variations of vegetation canopy growth analysed using environmental changes (air temperature, total rainfall and total evapotranspiration were similar. The results from the ANPP data and the NDVI data showed the that variations in grassland growth were similar and independent of the analysis scale, which indicated that local data and the relationships of local data with climate can be considered at the regional scale in the Pampa biome by using remote sensing.

  15. Multiscale Convolutional Neural Networks for Hand Detection

    Directory of Open Access Journals (Sweden)

    Shiyang Yan

    2017-01-01

    Full Text Available Unconstrained hand detection in still images plays an important role in many hand-related vision problems, for example, hand tracking, gesture analysis, human action recognition and human-machine interaction, and sign language recognition. Although hand detection has been extensively studied for decades, it is still a challenging task with many problems to be tackled. The contributing factors for this complexity include heavy occlusion, low resolution, varying illumination conditions, different hand gestures, and the complex interactions between hands and objects or other hands. In this paper, we propose a multiscale deep learning model for unconstrained hand detection in still images. Deep learning models, and deep convolutional neural networks (CNNs in particular, have achieved state-of-the-art performances in many vision benchmarks. Developed from the region-based CNN (R-CNN model, we propose a hand detection scheme based on candidate regions generated by a generic region proposal algorithm, followed by multiscale information fusion from the popular VGG16 model. Two benchmark datasets were applied to validate the proposed method, namely, the Oxford Hand Detection Dataset and the VIVA Hand Detection Challenge. We achieved state-of-the-art results on the Oxford Hand Detection Dataset and had satisfactory performance in the VIVA Hand Detection Challenge.

  16. Multiscale Analysis of Effects of Additive and Multiplicative Noise on Delay Differential Equations near a Bifurcation Point

    International Nuclear Information System (INIS)

    Klosek, M.M.

    2004-01-01

    We study effects of noisy and deterministic perturbations on oscillatory solutions to delay differential equations. We develop the multiscale technique and derive amplitude equations for noisy oscillations near a critical delay. We investigate effects of additive and multiplicative noise. We show that if the magnitudes of noise and deterministic perturbations are balanced, then the oscillatory behavior persists for long times being sustained by the noise. We illustrate the technique and its results on linear and logistic delay equations. (author)

  17. TOWARDS A MULTI-SCALE AGENT-BASED PROGRAMMING LANGUAGE METHODOLOGY.

    Science.gov (United States)

    Somogyi, Endre; Hagar, Amit; Glazier, James A

    2016-12-01

    Living tissues are dynamic, heterogeneous compositions of objects , including molecules, cells and extra-cellular materials, which interact via chemical, mechanical and electrical process and reorganize via transformation, birth, death and migration processes . Current programming language have difficulty describing the dynamics of tissues because: 1: Dynamic sets of objects participate simultaneously in multiple processes, 2: Processes may be either continuous or discrete, and their activity may be conditional, 3: Objects and processes form complex, heterogeneous relationships and structures, 4: Objects and processes may be hierarchically composed, 5: Processes may create, destroy and transform objects and processes. Some modeling languages support these concepts, but most cannot translate models into executable simulations. We present a new hybrid executable modeling language paradigm, the Continuous Concurrent Object Process Methodology ( CCOPM ) which naturally expresses tissue models, enabling users to visually create agent-based models of tissues, and also allows computer simulation of these models.

  18. Lower bound multiscale element for in situ cast joints in triaxial stress

    DEFF Research Database (Denmark)

    Herfelt, Morten Andersen; Poulsen, Peter Noe; Hoang, Linh Cao

    2018-01-01

    of design are therefore needed, and a framework based on finite element limit analysis is being developed. In this paper, a one-dimensional multiscale joint element is presented, and a mechanical model is proposed as the yield function of the macro element. The scope of the model is to capture the behaviour...

  19. Intercomparison of the community multiscale air quality model and CALGRID using process analysis.

    Science.gov (United States)

    O'Neill, Susan M; Lamb, Brian K

    2005-08-01

    This study was designed to examine the similarities and differences between two advanced photochemical air quality modeling systems: EPA Models-3/CMAQ and CALGRID/CALMET. Both modeling systems were applied to an ozone episode that occurred along the I-5 urban corridor in western Washington and Oregon during July 11-14, 1996. Both models employed the same modeling domain and used the same detailed gridded emission inventory. The CMAQ model was run using both the CB-IV and RADM2 chemical mechanisms, while CALGRID was used with the SAPRC-97 chemical mechanism. Outputfrom the Mesoscale Meteorological Model (MM5) employed with observational nudging was used in both models. The two modeling systems, representing three chemical mechanisms and two sets of meteorological inputs, were evaluated in terms of statistical performance measures for both 1- and 8-h average observed ozone concentrations. The results showed that the different versions of the systems were more similar than different, and all versions performed well in the Portland region and downwind of Seattle but performed poorly in the more rural region north of Seattle. Improving the meteorological input into the CALGRID/CALMET system with planetary boundary layer (PBL) parameters from the Models-3/CMAQ meteorology preprocessor (MCIP) improved the performance of the CALGRID/CALMET system. The 8-h ensemble case was often the best performer of all the cases indicating that the models perform better over longer analysis periods. The 1-h ensemble case, derived from all runs, was not necessarily an improvement over the five individual cases, but the standard deviation about the mean provided a measure of overall modeling uncertainty. Process analysis was applied to examine the contribution of the individual processes to the species conservation equation. The process analysis results indicated that the two modeling systems arrive at similar solutions by very different means. Transport rates are faster and exhibit

  20. Multiscale analysis: a way to investigate laser damage precursors in materials for high power applications at nanosecond pulse duration

    Science.gov (United States)

    Natoli, J. Y.; Wagner, F.; Ciapponi, A.; Capoulade, J.; Gallais, L.; Commandré, M.

    2010-11-01

    The mechanism of laser induced damage in optical materials under high power nanosecond laser irradiation is commonly attributed to the presence of precursor centers. Depending on material and laser source, the precursors could have different origins. Some of them are clearly extrinsic, such as impurities or structural defects linked to the fabrication conditions. In most cases the center size ranging from sub-micrometer to nanometer scale does not permit an easy detection by optical techniques before irradiation. Most often, only a post mortem observation of optics permits to proof the local origin of breakdown. Multi-scale analyzes by changing irradiation beam size have been performed to investigate the density, size and nature of laser damage precursors. Destructive methods such as raster scan, laser damage probability plot and morphology studies permit to deduce the precursor densities. Another experimental way to get information on nature of precursors is to use non destructive methods such as photoluminescence and absorption measurements. The destructive and non destructive multiscale studies are also motivated for practical reasons. Indeed LIDT studies of large optics as those used in LMJ or NIF projects are commonly performed on small samples and with table top lasers whose characteristics change from one to another. In these conditions, it is necessary to know exactly the influence of the different experimental parameters and overall the spot size effect on the final data. In this paper, we present recent developments in multiscale characterization and results obtained on optical coatings (surface case) and KDP crystal (bulk case).

  1. Multiscale analysis of depth-dependent soil penetration resistance in a tropical soil

    Science.gov (United States)

    Paiva De Lima, Renato; Santos, Djail; Medeiros Bezerra, Joel; Machado Siqueira, Glécio; Paz González, Antonio

    2013-04-01

    Soil penetration resistance (PR) is widely used because it is linked to basic soil properties; it is correlated to root growth and plant production and is also used as a practical tool for assessing soil compaction and to evaluate the effects of soil management. This study investigates how results from multifractal analysis can quantify key elements of depth-dependent PR profiles and how this information can be used at the field scale. We analyzed multifractality of 50 PR vertical profiles, measured from 0 to 40 cm depth and randomly located on a 6.5 ha sugar cane field in north-eastern Brazil. According to the Soil Taxonomy, the studied soil was classified as an Orthic Podsol The scaling property of each profile was typified by singularity and Rényi spectra estimated by the method of moments. The Hurst exponent was used to parameterize the autocorrelation of the vertical PR data sets. Singularity and Rènyi spectra showed the vertical PR data sets exhibited a well-defined multifractal structure. Hurst exponent values were close to one indicating strong persistence in PR variation with soil depth. Also Hurst exponent was negatively and significantly correlated to coefficient of variation (CV) and skewness of the depth-dependent PR. Multifractal analysis added valuable information to describe the spatial arrangement of depth-dependent penetrometer data sets, which was not taken into account by classical statistical indices. Multifractal parameters were mapped over the experimental field and compared with mean, maximum and minimum values of PR; these maps showed the multifractal approach also may complete information provided by descriptive statistics at the field scale.

  2. Multi-scale hippocampal parcellation improves atlas-based segmentation accuracy

    Science.gov (United States)

    Plassard, Andrew J.; McHugo, Maureen; Heckers, Stephan; Landman, Bennett A.

    2017-02-01

    Known for its distinct role in memory, the hippocampus is one of the most studied regions of the brain. Recent advances in magnetic resonance imaging have allowed for high-contrast, reproducible imaging of the hippocampus. Typically, a trained rater takes 45 minutes to manually trace the hippocampus and delineate the anterior from the posterior segment at millimeter resolution. As a result, there has been a significant desire for automated and robust segmentation of the hippocampus. In this work we use a population of 195 atlases based on T1-weighted MR images with the left and right hippocampus delineated into the head and body. We initialize the multi-atlas segmentation to a region directly around each lateralized hippocampus to both speed up and improve the accuracy of registration. This initialization allows for incorporation of nearly 200 atlases, an accomplishment which would typically involve hundreds of hours of computation per target image. The proposed segmentation results in a Dice similiarity coefficient over 0.9 for the full hippocampus. This result outperforms a multi-atlas segmentation using the BrainCOLOR atlases (Dice 0.85) and FreeSurfer (Dice 0.75). Furthermore, the head and body delineation resulted in a Dice coefficient over 0.87 for both structures. The head and body volume measurements also show high reproducibility on the Kirby 21 reproducibility population (R2 greater than 0.95, p develop a robust tool for measurement of the hippocampus and other temporal lobe structures.

  3. Multi-scale thermal stability of a hard thermoplastic protein-based material

    Science.gov (United States)

    Latza, Victoria; Guerette, Paul A.; Ding, Dawei; Amini, Shahrouz; Kumar, Akshita; Schmidt, Ingo; Keating, Steven; Oxman, Neri; Weaver, James C.; Fratzl, Peter; Miserez, Ali; Masic, Admir

    2015-09-01

    Although thermoplastic materials are mostly derived from petro-chemicals, it would be highly desirable, from a sustainability perspective, to produce them instead from renewable biopolymers. Unfortunately, biopolymers exhibiting thermoplastic behaviour and which preserve their mechanical properties post processing are essentially non-existent. The robust sucker ring teeth (SRT) from squid and cuttlefish are one notable exception of thermoplastic biopolymers. Here we describe thermoplastic processing of squid SRT via hot extrusion of fibres, demonstrating the potential suitability of these materials for large-scale thermal forming. Using high-resolution in situ X-ray diffraction and vibrational spectroscopy, we elucidate the molecular and nanoscale features responsible for this behaviour and show that SRT consist of semi-crystalline polymers, whereby heat-resistant, nanocrystalline β-sheets embedded within an amorphous matrix are organized into a hexagonally packed nanofibrillar lattice. This study provides key insights for the molecular design of biomimetic protein- and peptide-based thermoplastic structural biopolymers with potential biomedical and 3D printing applications.

  4. Multiscale modelling and analysis of collective decision making in swarm robotics.

    Science.gov (United States)

    Vigelius, Matthias; Meyer, Bernd; Pascoe, Geoffrey

    2014-01-01

    We present a unified approach to describing certain types of collective decision making in swarm robotics that bridges from a microscopic individual-based description to aggregate properties. Our approach encompasses robot swarm experiments, microscopic and probabilistic macroscopic-discrete simulations as well as an analytic mathematical model. Following up on previous work, we identify the symmetry parameter, a measure of the progress of the swarm towards a decision, as a fundamental integrated swarm property and formulate its time evolution as a continuous-time Markov process. Contrary to previous work, which justified this approach only empirically and a posteriori, we justify it from first principles and derive hard limits on the parameter regime in which it is applicable.

  5. Multiscale Modelling and Analysis of Collective Decision Making in Swarm Robotics

    Science.gov (United States)

    Vigelius, Matthias; Meyer, Bernd; Pascoe, Geoffrey

    2014-01-01

    We present a unified approach to describing certain types of collective decision making in swarm robotics that bridges from a microscopic individual-based description to aggregate properties. Our approach encompasses robot swarm experiments, microscopic and probabilistic macroscopic-discrete simulations as well as an analytic mathematical model. Following up on previous work, we identify the symmetry parameter, a measure of the progress of the swarm towards a decision, as a fundamental integrated swarm property and formulate its time evolution as a continuous-time Markov process. Contrary to previous work, which justified this approach only empirically and a posteriori, we justify it from first principles and derive hard limits on the parameter regime in which it is applicable. PMID:25369026

  6. Bayesian Multiscale Analysis of X-Ray Jet Features in High Redshift Quasars

    Science.gov (United States)

    McKeough, Kathryn; Siemiginowska, A.; Kashyap, V.; Stein, N.

    2014-01-01

    X-ray emission of powerful quasar jets may be a result of the inverse Compton (IC) process in which the Cosmic Microwave Background (CMB) photons gain energy by interactions with the jet’s relativistic electrons. However, there is no definite evidence that IC/CMB process is responsible for the observed X-ray emission of large scale jets. A step toward understanding the X-ray emission process is to study the Radio and X-ray morphologies of the jet. We implement a sophisticated Bayesian image analysis program, Low-count Image Reconstruction and Analysis (LIRA) (Esch et al. 2004; Conners & van Dyk 2007), to analyze jet features in 11 Chandra images of high redshift quasars (z ~ 2 - 4.8). Out of the 36 regions where knots are visible in the radio jets, nine showed detectable X-ray emission. We measured the ratios of the X-ray and radio luminosities of the detected features and found that they are consistent with the CMB radiation relationship. We derived a range of the bulk lorentz factor (Γ) for detected jet features under the CMB jet emission model. There is no discernible trend of Γ with redshift within the sample. The efficiency of the X-ray emission between the detected jet feature and the corresponding quasar also shows no correlation with redshift. This work is supported in part by the National Science Foundation REU and the Department of Defense ASSURE programs under NSF Grant no.1262851 and by the Smithsonian Institution, and by NASA Contract NAS8-39073 to the Chandra X-ray Center (CXC). This research has made use of data obtained from the Chandra Data Archive and Chandra Source Catalog, and software provided by the CXC in the application packages CIAO, ChIPS, and Sherpa. We thank Teddy Cheung for providing the VLA radio images. Connors, A., & van Dyk, D. A. 2007, Statistical Challenges in Modern Astronomy IV, 371, 101 Esch, D. N., Connors, A., Karovska, M., & van Dyk, D. A. 2004, ApJ, 610, 1213

  7. Multiscale analysis of the invariants of the velocity gradient tensor in isotropic turbulence

    Science.gov (United States)

    Danish, Mohammad; Meneveau, Charles

    2018-04-01

    Knowledge of local flow-topology, the patterns of streamlines around a moving fluid element as described by the velocity-gradient tensor, is useful for developing insights into turbulence processes, such as energy cascade, material element deformation, or scalar mixing. Much has been learned in the recent past about flow topology at the smallest (viscous) scales of turbulence. However, less is known at larger scales, for instance, at the inertial scales of turbulence. In this work, we present a detailed study on the scale dependence of various quantities of interest, such as the population fraction of different types of flow-topologies, the joint probability distribution of the second and third invariants of the velocity gradient tensor, and the geometrical alignment of vorticity with strain-rate eigenvectors. We perform the analysis on a simulation dataset of isotropic turbulence at Reλ=433 . While quantities appear close to scale invariant in the inertial range, we observe a "bump" in several quantities at length scales between the inertial and viscous ranges. For instance, the population fraction of unstable node-saddle-saddle flow topology shows an increase when reducing the scale from the inertial entering the viscous range. A similar bump is observed for the vorticity-strain-rate alignment. In order to document possible dynamical causes for the different trends in the viscous and inertial ranges, we examine the probability fluxes appearing in the Fokker-Plank equation governing the velocity gradient invariants. Specifically, we aim to understand whether the differences observed between the viscous and inertial range statistics are due to effects caused by pressure, subgrid-scale, or viscous stresses or various combinations of these terms. To decompose the flow into small and large scales, we mainly use a spectrally compact non-negative filter with good spatial localization properties (Eyink-Aluie filter). The analysis shows that when going from the inertial

  8. Multi-scale analysis of hermatypic coral assemblages at Mexican Central Pacific

    Directory of Open Access Journals (Sweden)

    Joicye Hernández-Zulueta

    2017-03-01

    Full Text Available The Mexican Central Pacific is located in a zone of oceanographic transition between two biogeographic provinces with particular conditions that affect the associated fauna. The objective of this study was to evaluate the variation of hermatypic coral assemblages in this region and to determine their relationship with the heterogeneity of the benthonic habitat and spatial variables. A total of 156 transects were carried out at 41 sites in the years 2010 and 2011. The sampling effort returned 96.7% of the coral richness expected for the area, with a total of 15 species recorded. The results showed that richness, diversity and cover of corals varied only at the site and state scales. However, the composition and coverage of all coral species, as well as the benthonic habitat structure, differed significantly across the study scales (i.e. sites, zones and states. Canonical redundancy analysis showed that variation in the richness, diversity and assemblages of corals was explained by the cover of live corals, articulated calcareous algae, sandy substrate, sponges and fleshy macroalgae. This study suggests that local scale (i.e. site variation in the coral assemblages of the Mexican Central Pacific is the result of the heterogeneity of the benthonic habitat, while geomorphological and oceanographic characteristics play a greater role at regional scale.

  9. Multi-scale Modelling of bcc-Fe Based Alloys for Nuclear Applications

    International Nuclear Information System (INIS)

    Malerba, Lorenzo

    2008-01-01

    , advanced techniques to fit interatomic potentials consistent with thermodynamics are proposed and the results of their application to the mentioned alloys are presented. Next, the development of advanced methods, based on the use of artificial intelligence, to improve both the physical reliability and the computational efficiency of kinetic Monte Carlo codes for the study of point-defect clustering and phase changes beyond the scale of MD, is reported. These recent progresses bear the promise of being able, in the near future, of producing reliable tools for the description of the microstructure evolution of realistic model alloys under irradiation. (author)

  10. Multiscale study of metal nanoparticles

    Science.gov (United States)

    Lee, Byeongchan

    Extremely small structures with reduced dimensionality have emerged as a scientific motif for their interesting properties. In particular, metal nanoparticles have been identified as a fundamental material in many catalytic activities; as a consequence, a better understanding of structure-function relationship of nanoparticles has become crucial. The functional analysis of nanoparticles, reactivity for example, requires an accurate method at the electronic structure level, whereas the structural analysis to find energetically stable local minima is beyond the scope of quantum mechanical methods as the computational cost becomes prohibitingly high. The challenge is that the inherent length scale and accuracy associated with any single method hardly covers the broad scale range spanned by both structural and functional analyses. In order to address this, and effectively explore the energetics and reactivity of metal nanoparticles, a hierarchical multiscale modeling is developed, where methodologies of different length scales, i.e. first principles density functional theory, atomistic calculations, and continuum modeling, are utilized in a sequential fashion. This work has focused on identifying the essential information that bridges two different methods so that a successive use of different methods is seamless. The bond characteristics of low coordination systems have been obtained with first principles calculations, and incorporated into the atomistic simulation. This also rectifies the deficiency of conventional interatomic potentials fitted to bulk properties, and improves the accuracy of atomistic calculations for nanoparticles. For the systematic shape selection of nanoparticles, we have improved the Wulff-type construction using a semi-continuum approach, in which atomistic surface energetics and crystallinity of materials are added on to the continuum framework. The developed multiscale modeling scheme is applied to the rational design of platinum

  11. Automatic Ship Detection in Remote Sensing Images from Google Earth of Complex Scenes Based on Multiscale Rotation Dense Feature Pyramid Networks

    Directory of Open Access Journals (Sweden)

    Xue Yang

    2018-01-01

    Full Text Available Ship detection has been playing a significant role in the field of remote sensing for a long time, but it is still full of challenges. The main limitations of traditional ship detection methods usually lie in the complexity of application scenarios, the difficulty of intensive object detection, and the redundancy of the detection region. In order to solve these problems above, we propose a framework called Rotation Dense Feature Pyramid Networks (R-DFPN which can effectively detect ships in different scenes including ocean and port. Specifically, we put forward the Dense Feature Pyramid Network (DFPN, which is aimed at solving problems resulting from the narrow width of the ship. Compared with previous multiscale detectors such as Feature Pyramid Network (FPN, DFPN builds high-level semantic feature-maps for all scales by means of dense connections, through which feature propagation is enhanced and feature reuse is encouraged. Additionally, in the case of ship rotation and dense arrangement, we design a rotation anchor strategy to predict the minimum circumscribed rectangle of the object so as to reduce the redundant detection region and improve the recall. Furthermore, we also propose multiscale region of interest (ROI Align for the purpose of maintaining the completeness of the semantic and spatial information. Experiments based on remote sensing images from Google Earth for ship detection show that our detection method based on R-DFPN representation has state-of-the-art performance.

  12. A concurrent multiscale micromorphic molecular dynamics

    International Nuclear Information System (INIS)

    Li, Shaofan; Tong, Qi

    2015-01-01

    In this work, we have derived a multiscale micromorphic molecular dynamics (MMMD) from first principle to extend the (Andersen)-Parrinello-Rahman molecular dynamics to mesoscale and continuum scale. The multiscale micromorphic molecular dynamics is a con-current three-scale dynamics that couples a fine scale molecular dynamics, a mesoscale micromorphic dynamics, and a macroscale nonlocal particle dynamics together. By choosing proper statistical closure conditions, we have shown that the original Andersen-Parrinello-Rahman molecular dynamics is the homogeneous and equilibrium case of the proposed multiscale micromorphic molecular dynamics. In specific, we have shown that the Andersen-Parrinello-Rahman molecular dynamics can be rigorously formulated and justified from first principle, and its general inhomogeneous case, i.e., the three scale con-current multiscale micromorphic molecular dynamics can take into account of macroscale continuum mechanics boundary condition without the limitation of atomistic boundary condition or periodic boundary conditions. The discovered multiscale scale structure and the corresponding multiscale dynamics reveal a seamless transition from atomistic scale to continuum scale and the intrinsic coupling mechanism among them based on first principle formulation

  13. Heteroprotein Complex Formation of Bovine Lactoferrin and Pea Protein Isolate: A Multiscale Structural Analysis.

    Science.gov (United States)

    Adal, Eda; Sadeghpour, Amin; Connell, Simon; Rappolt, Michael; Ibanoglu, Esra; Sarkar, Anwesha

    2017-02-13

    Associative electrostatic interactions between two oppositely charged globular proteins, lactoferrin (LF) and pea protein isolate (PPI), the latter being a mixture of vicilin, legumin, and convicilin, was studied with a specific PPI/LF molar ratio at room temperature. Structural aspects of the electrostatic complexes probed at different length scales were investigated as a function of pH by means of different complementary techniques, namely, with dynamic light scattering, small-angle X-ray scattering (SAXS), turbidity measurements, and atomic force microscopy (AFM). Irrespective of the applied techniques, the results consistently displayed that complexation between LF and PPI did occur. In an optimum narrow range of pH 5.0-5.8, a viscous liquid phase of complex coacervate was obtained upon mild centrifugation of the turbid LF-PPI mixture with a maximum R h , turbidity and the ζ-potential being close to zero observed at pH 5.4. In particular, the SAXS data demonstrated that the coacervates were densely assembled with a roughly spherical size distribution exhibiting a maximum extension of ∼80 nm at pH 5.4. Equally, AFM image analysis showed size distributions containing most frequent cluster sizes around 40-80 nm with spherical to elliptical shapes (axis aspect ratio ≤ 2) as well as less frequent elongated to chainlike structures. The most frequently observed compact complexes, we identify as mainly leading to LF-PPI coacervation, whereas for the less frequent chain-like aggregates, we hypothesize that additionally PPI-PPI facilitated complexes exist.

  14. The U.S. Shale Oil and Gas Resource - a Multi-Scale Analysis of Productivity

    Science.gov (United States)

    O'sullivan, F.

    2014-12-01

    Over the past decade, the large-scale production of natural gas, and more recently oil, from U.S. shale formations has had a transformative impact on the energy industry. The emergence of shale oil and gas as recoverable resources has altered perceptions regarding both the future abundance and cost of hydrocarbons, and has shifted the balance of global energy geopolitics. However, despite the excitement, shale is a resource in its nascency, and many challenges surrounding its exploitation remain. One of the most significant of these is the dramatic variation in resource productivity across multiple length scales, which is a feature of all of today's shale plays. This paper will describe the results of work that has looked to characterize the spatial and temporal variations in the productivity of the contemporary shale resource. Analysis will be presented that shows there is a strong stochastic element to observed shale well productivity in all the major plays. It will be shown that the nature of this stochasticity is consistent regardless of specific play being considered. A characterization of this stochasticity will be proposed. As a parallel to the discussion of productivity, the paper will also address the issue of "learning" in shale development. It will be shown that "creaming" trends are observable and that although "absolute" well productivity levels have increased, "specific" productivity levels (i.e. considering well and stimulation size) have actually falling markedly in many plays. The paper will also show that among individual operators' well ensembles, normalized well-to-well performance distributions are almost identical, and have remained consistent year-to-year. This result suggests little if any systematic learning regarding the effective management of well-to-well performance variability has taken place. The paper will conclude with an articulation of how the productivity characteristics of the shale resource are impacting on the resources

  15. Semi-convection in the ocean and in stars: A multi-scale analysis

    Directory of Open Access Journals (Sweden)

    Friedrich Kupka

    2015-04-01

    Full Text Available Fluid stratified by gravitation can be subject to a number of instabilities which eventually lead to a flow that causes enhanced mixing and transport of heat. The special case where a destabilizing temperature gradient counteracts the action of a stabilizing gradient in molecular weight is of interest to astrophysics (inside stars and giant planets and geophysics (lakes, oceans as well as to some engineering applications. The detailed dynamics of such a system depend on the molecular diffusivities of heat, momentum, and solute as well as system parameters including the ratio of the two gradients to each other. Further important properties are the formation and merging of well-defined layers in the fluid which cannot be derived from linear stability analysis. Moreover, the physical processes operate on a vast range of length and time scales. This has made the case of semi-convection, where a mean temperature gradient destabilizes the stratification while at the same time the mean molecular gradient tends to stabilize it, a challenge to physical modelling and to numerical hydrodynamical simulation. During the MetStröm project the simulation codes ANTARES and MITgcm have been extended such that they can be used for the simulations of such flows. We present a comparison of effective diffusivities derived from direct numerical simulations. For both stars and the oceanic regimes, the Nusselt numbers (scaled diffusivities follow similar relationships. Semi-convection quickly becomes inefficient, because the formation of layers limits vertical mixing. In contrast to the complementary saltfingering, these layers tend to damp instabilities so that effective diffusivities of salinity (concentration are up to two orders of magnitudes smaller than in the former case.

  16. Temperature multiscale entropy analysis: a promising marker for early prediction of mortality in septic patients

    International Nuclear Information System (INIS)

    Papaioannou, V E; Pneumatikos, I A; Chouvarda, I G; Maglaveras, N K; Baltopoulos, G I

    2013-01-01

    A few studies estimating temperature complexity have found decreased Shannon entropy, during severe stress. In this study, we measured both Shannon and Tsallis entropy of temperature signals in a cohort of critically ill patients and compared these measures with the sequential organ failure assessment (SOFA) score, in terms of intensive care unit (ICU) mortality. Skin temperature was recorded in 21 mechanically ventilated patients, who developed sepsis and septic shock during the first 24 h of an ICU-acquired infection. Shannon and Tsallis entropies were calculated in wavelet-based decompositions of the temperature signal. Statistically significant differences of entropy features were tested between survivors and non-survivors and classification models were built, for predicting final outcome. Significantly reduced Tsallis and Shannon entropies were found in non-survivors (seven patients, 33%) as compared to survivors. Wavelet measurements of both entropy metrics were found to predict ICU mortality better than SOFA, according to a combination of area under the curve, sensitivity and specificity values. Both entropies exhibited similar prognostic accuracy. Combination of SOFA and entropy presented improved the outcome of univariate models. We suggest that reduced wavelet Shannon and Tsallis entropies of temperature signals may complement SOFA in mortality prediction, during the first 24 h of an ICU-acquired infection. (paper)

  17. Analysis of Decadal Vegetation Dynamics Using Multi-Scale Satellite Images

    Science.gov (United States)

    Chiang, Y.; Chen, K.

    2013-12-01

    This study aims at quantifying vegetation fractional cover (VFC) by incorporating multi-resolution satellite images, including Formosat-2(RSI), SPOT(HRV/HRG), Landsat (MSS/TM) and Terra/Aqua(MODIS), to investigate long-term and seasonal vegetation dynamics in Taiwan. We used 40-year NDVI records for derivation of VFC, with field campaigns routinely conducted to calibrate the critical NDVI threshold. Given different sensor capabilities in terms of their spatial and spectral properties, translation and infusion of NDVIs was used to assure NDVI coherence and to determine the fraction of vegetation cover at different spatio-temporal scales. Based on the proposed method, a bimodal sequence of intra-annual VFC which corresponds to the dual-cropping agriculture pattern was observed. Compared to seasonal VFC variation (78~90%), decadal VFC reveals moderate oscillations (81~86%), which were strongly linked with landuse changes and several major disturbances. This time-series mapping of VFC can be used to examine vegetation dynamics and its response associated with short-term and long-term anthropogenic/natural events.

  18. Multi-scales analysis of the global change impact on the diversity of the aphid communities

    International Nuclear Information System (INIS)

    Hulle, M.

    2007-01-01

    The primary objective of this project is to investigate the effects of global change on the biodiversity of aphid communities in Western Europe. Biodiversity has been examined at 3 levels: total number of species, phenology and reproductive strategy. Data were provided by EXAMINE, the European suction traps network which has been now operating for 35 years. 392 different species have been identified. At each location, total number of species has been regularly increasing, one additional species being caught every 1 or 2 years depending on location. This is due to introduced species but also to warming which favours rare species. No general trend of increasing density has been detected, but phenological earliness of almost all species (annual date of first appearance in suction traps) is strongly correlated with temperature and especially with mean daily temperature (during more or less long periods of time lying principally in February and March) or number of days below 0 C. Strong relationships between aphid phenology and environmental variables have been found and there is strong discrimination between species with different life cycle strategies, and between species feeding on herbs and trees, suggesting the possible value of trait-based groupings in predicting responses to environmental changes. These preliminary results suggest that 1) biodiversity has increased during the last decades; 2) there is a pool of species among which some of them reach a detectable density only during years where temperatures are high enough; 3) a set of newly introduced species succeed in settling being favoured by warming and 4) phenology of aphids is expected to advance and their abundance to increase with temperature, and the possible role of natural enemies to regulate abundant species is discussed. (author)

  19. MULTISCALE TENSOR ANISOTROPIC FILTERING OF FLUORESCENCE MICROSCOPY FOR DENOISING MICROVASCULATURE.

    Science.gov (United States)

    Prasath, V B S; Pelapur, R; Glinskii, O V; Glinsky, V V; Huxley, V H; Palaniappan, K

    2015-04-01

    Fluorescence microscopy images are contaminated by noise and improving image quality without blurring vascular structures by filtering is an important step in automatic image analysis. The application of interest here is to automatically extract the structural components of the microvascular system with accuracy from images acquired by fluorescence microscopy. A robust denoising process is necessary in order to extract accurate vascular morphology information. For this purpose, we propose a multiscale tensor with anisotropic diffusion model which progressively and adaptively updates the amount of smoothing while preserving vessel boundaries accurately. Based on a coherency enhancing flow with planar confidence measure and fused 3D structure information, our method integrates multiple scales for microvasculature preservation and noise removal membrane structures. Experimental results on simulated synthetic images and epifluorescence images show the advantage of our improvement over other related diffusion filters. We further show that the proposed multiscale integration approach improves denoising accuracy of different tensor diffusion methods to obtain better microvasculature segmentation.

  20. Multi-scale Drivers of Variations in Atmospheric Evaporative Demand Based on Observations and Physically-based Modeling

    Science.gov (United States)

    Peng, L.; Sheffield, J.; Li, D.

    2015-12-01

    Evapotranspiration (ET) is a key link between the availability of water resources and climate change and climate variability. Variability of ET has important environmental and socioeconomic implications for managing hydrological hazards, food and energy production. Although there have been many observational and modeling studies of ET, how ET has varied and the drivers of the variations at different temporal scales remain elusive. Much of the uncertainty comes from the atmospheric evaporative demand (AED), which is the combined effect of radiative and aerodynamic controls. The inconsistencies among modeled AED estimates and the limited observational data may originate from multiple sources including the limited time span and uncertainties in the data. To fully investigate and untangle the intertwined drivers of AED, we present a spectrum analysis to identify key controls of AED across multiple temporal scales. We use long-term records of observed pan evaporation for 1961-2006 from 317 weather stations across China and physically-based model estimates of potential evapotranspiration (PET). The model estimates are based on surface meteorology and radiation derived from reanalysis, satellite retrievals and station data. Our analyses show that temperature plays a dominant role in regulating variability of AED at the inter-annual scale. At the monthly and seasonal scales, the primary control of AED shifts from radiation in humid regions to humidity in dry regions. Unlike many studies focusing on the spatial pattern of ET drivers based on a traditional supply and demand framework, this study underlines the importance of temporal scales when discussing controls of ET variations.

  1. An Online Generalized Multiscale Discontinuous Galerkin Method (GMsDGM) for Flows in Heterogeneous Media

    KAUST Repository

    Chung, Eric T.

    2017-02-07

    Offline computation is an essential component in most multiscale model reduction techniques. However, there are multiscale problems in which offline procedure is insufficient to give accurate representations of solutions, due to the fact that offline computations are typically performed locally and global information is missing in these offline information. To tackle this difficulty, we develop an online local adaptivity technique for local multiscale model reduction problems. We design new online basis functions within Discontinuous Galerkin method based on local residuals and some optimally estimates. The resulting basis functions are able to capture the solution efficiently and accurately, and are added to the approximation iteratively. Moreover, we show that the iterative procedure is convergent with a rate independent of physical scales if the initial space is chosen carefully. Our analysis also gives a guideline on how to choose the initial space. We present some numerical examples to show the performance of the proposed method.

  2. Generalization of mixed multiscale finite element methods with applications

    Energy Technology Data Exchange (ETDEWEB)

    Lee, C S [Texas A & M Univ., College Station, TX (United States)

    2016-08-01

    Many science and engineering problems exhibit scale disparity and high contrast. The small scale features cannot be omitted in the physical models because they can affect the macroscopic behavior of the problems. However, resolving all the scales in these problems can be prohibitively expensive. As a consequence, some types of model reduction techniques are required to design efficient solution algorithms. For practical purpose, we are interested in mixed finite element problems as they produce solutions with certain conservative properties. Existing multiscale methods for such problems include the mixed multiscale finite element methods. We show that for complicated problems, the mixed multiscale finite element methods may not be able to produce reliable approximations. This motivates the need of enrichment for coarse spaces. Two enrichment approaches are proposed, one is based on generalized multiscale finte element metthods (GMsFEM), while the other is based on spectral element-based algebraic multigrid (rAMGe). The former one, which is called mixed GMsFEM, is developed for both Darcy’s flow and linear elasticity. Application of the algorithm in two-phase flow simulations are demonstrated. For linear elasticity, the algorithm is subtly modified due to the symmetry requirement of the stress tensor. The latter enrichment approach is based on rAMGe. The algorithm differs from GMsFEM in that both of the velocity and pressure spaces are coarsened. Due the multigrid nature of the algorithm, recursive application is available, which results in an efficient multilevel construction of the coarse spaces. Stability, convergence analysis, and exhaustive numerical experiments are carried out to validate the proposed enrichment approaches. iii

  3. A method to generate fully multi-scale optimal interpolation by combining efficient single process analyses, illustrated by a DINEOF analysis spiced with a local optimal interpolation

    Directory of Open Access Journals (Sweden)

    J.-M. Beckers

    2014-10-01

    Full Text Available We present a method in which the optimal interpolation of multi-scale processes can be expanded into a succession of simpler interpolations. First, we prove how the optimal analysis of a superposition of two processes can be obtained by different mathematical formulations involving iterations and analysis focusing on a single process. From the different mathematical equivalent formulations, we then select the most efficient ones by analyzing the behavior of the different possibilities in a simple and well-controlled test case. The clear guidelines deduced from this experiment are then applied to a real situation in which we combine large-scale analysis of hourly Spinning Enhanced Visible and Infrared Imager (SEVIRI satellite images using data interpolating empirical orthogonal functions (DINEOF with a local optimal interpolation using a Gaussian covariance. It is shown that the optimal combination indeed provides the best reconstruction and can therefore be exploited to extract the maximum amount of useful information from the original data.

  4. Low-wave number analysis of observations and ensemble forecasts to develop metrics for the selection of most realistic members to study multi-scale interactions between the environment and the convective organization of hurricanes: Focus on Rapid Intensification

    Science.gov (United States)

    Hristova-Veleva, S. M.; Chen, H.; Gopalakrishnan, S.; Haddad, Z. S.

    2017-12-01

    Tropical cyclones (TCs) are the product of complex multi-scale processes and interactions. The role of the environment has long been recognized. However, recent research has shown that convective-scale processes in the hurricane core might also play a crucial role in determining TCs intensity and size. Several studies have linked Rapid Intensification to the characteristics of the convective clouds (shallow versus deep), their organization (isolated versus wide-spread) and their location with respect to dynamical controls (the vertical shear, the radius of maximum wind). Yet a third set of controls signifies the interaction between the storm-scale and large-scale processes. Our goal is to use observations and models to advance the still-lacking understanding of these processes. Recently, hurricane models have improved significantly. However, deterministic forecasts have limitations due to the uncertainty in the representation of the physical processes and initial conditions. A crucial step forward is the use of high-resolution ensembles. We adopt the following approach: i) generate a high resolution ensemble forecast using HWRF; ii) produce synthetic data (e.g. brightness temperature) from the model fields for direct comparison to satellite observations; iii) develop metrics to allow us to sub-select the realistic members of the ensemble, based on objective measures of the similarity between observed and forecasted structures; iv) for these most-realistic members, determine the skill in forecasting TCs to provide"guidance on guidance"; v) use the members with the best predictive skill to untangle the complex multi-scale interactions. We will report on the first three goals of our research, using forecasts and observations of hurricane Edouard (2014), focusing on RI. We will focus on describing the metrics for the selection of the most appropriate ensemble members, based on applying low-wave number analysis (WNA - Hristova-Veleva et al., 2016) to the observed and

  5. SU-E-I-100: Heterogeneity Studying for Primary and Lymphoma Tumors by Using Multi-Scale Image Texture Analysis with PET-CT Images

    Energy Technology Data Exchange (ETDEWEB)

    Li, Dengwang [Shandong Normal University, Jinan, Shandong Province (China); Wang, Qinfen [Shandong Normal University, Jinan, Shandong (China); Li, H; Chen, J [Shandong Cancer Hospital and Institute, Jinan, Shandong (China)

    2014-06-01

    Purpose: The purpose of this research is studying tumor heterogeneity of the primary and lymphoma by using multi-scale texture analysis with PET-CT images, where the tumor heterogeneity is expressed by texture features. Methods: Datasets were collected from 12 lung cancer patients, and both of primary and lymphoma tumors were detected with all these patients. All patients underwent whole-body 18F-FDG PET/CT scan before treatment.The regions of interest (ROI) of primary and lymphoma tumor were contoured by experienced clinical doctors. Then the ROI of primary and lymphoma tumor is extracted automatically by using Matlab software. According to the geometry size of contour structure, the images of tumor are decomposed by multi-scale method.Wavelet transform was performed on ROI structures within images by L layers sampling, and then wavelet sub-bands which have the same size of the original image are obtained. The number of sub-bands is 3L+1.The gray level co-occurrence matrix (GLCM) is calculated within different sub-bands, thenenergy, inertia, correlation and gray in-homogeneity were extracted from GLCM.Finally, heterogeneity statistical analysis was studied for primary and lymphoma tumor using the texture features. Results: Energy, inertia, correlation and gray in-homogeneity are calculated with our experiments for heterogeneity statistical analysis.Energy for primary and lymphomatumor is equal with the same patient, while gray in-homogeneity and inertia of primaryare 2.59595±0.00855, 0.6439±0.0007 respectively. Gray in-homogeneity and inertia of lymphoma are 2.60115±0.00635, 0.64435±0.00055 respectively. The experiments showed that the volume of lymphoma is smaller than primary tumor, but thegray in-homogeneity and inertia were higher than primary tumor with the same patient, and the correlation with lymphoma tumors is zero, while the correlation with primary tumor isslightly strong. Conclusion: This studying showed that there were effective heterogeneity

  6. MULTISCALE THERMOHYDROLOGIC MODEL

    International Nuclear Information System (INIS)

    T. Buscheck

    2005-01-01

    The intended purpose of the multiscale thermohydrologic model (MSTHM) is to predict the possible range of thermal-hydrologic conditions, resulting from uncertainty and variability, in the repository emplacement drifts, including the invert, and in the adjoining host rock for the repository at Yucca Mountain. The goal of the MSTHM is to predict a reasonable range of possible thermal-hydrologic conditions within the emplacement drift. To be reasonable, this range includes the influence of waste-package-to-waste-package heat output variability relevant to the license application design, as well as the influence of uncertainty and variability in the geologic and hydrologic conditions relevant to predicting the thermal-hydrologic response in emplacement drifts. This goal is quite different from the goal of a model to predict a single expected thermal-hydrologic response. As a result, the development and validation of the MSTHM and the associated analyses using this model are focused on the goal of predicting a reasonable range of thermal-hydrologic conditions resulting from parametric uncertainty and waste-package-to-waste-package heat-output variability. Thermal-hydrologic conditions within emplacement drifts depend primarily on thermal-hydrologic conditions in the host rock at the drift wall and on the temperature difference between the drift wall and the drip-shield and waste-package surfaces. Thus, the ability to predict a reasonable range of relevant in-drift MSTHM output parameters (e.g., temperature and relative humidity) is based on valid predictions of thermal-hydrologic processes in the host rock, as well as valid predictions of heat-transfer processes between the drift wall and the drip-shield and waste-package surfaces. Because the invert contains crushed gravel derived from the host rock, the invert is, in effect, an extension of the host rock, with thermal and hydrologic properties that have been modified by virtue of the crushing (and the resulting

  7. MULTISCALE THERMOHYDROLOGIC MODEL

    Energy Technology Data Exchange (ETDEWEB)

    T. Buscheck

    2005-07-07

    The intended purpose of the multiscale thermohydrologic model (MSTHM) is to predict the possible range of thermal-hydrologic conditions, resulting from uncertainty and variability, in the repository emplacement drifts, including the invert, and in the adjoining host rock for the repository at Yucca Mountain. The goal of the MSTHM is to predict a reasonable range of possible thermal-hydrologic conditions within the emplacement drift. To be reasonable, this range includes the influence of waste-package-to-waste-package heat output variability relevant to the license application design, as well as the influence of uncertainty and variability in the geologic and hydrologic conditions relevant to predicting the thermal-hydrologic response in emplacement drifts. This goal is quite different from the goal of a model to predict a single expected thermal-hydrologic response. As a result, the development and validation of the MSTHM and the associated analyses using this model are focused on the goal of predicting a reasonable range of thermal-hydrologic conditions resulting from parametric uncertainty and waste-package-to-waste-package heat-output variability. Thermal-hydrologic conditions within emplacement drifts depend primarily on thermal-hydrologic conditions in the host rock at the drift wall and on the temperature difference between the drift wall and the drip-shield and waste-package surfaces. Thus, the ability to predict a reasonable range of relevant in-drift MSTHM output parameters (e.g., temperature and relative humidity) is based on valid predictions of thermal-hydrologic processes in the host rock, as well as valid predictions of heat-transfer processes between the drift wall and the drip-shield and waste-package surfaces. Because the invert contains crushed gravel derived from the host rock, the invert is, in effect, an extension of the host rock, with thermal and hydrologic properties that have been modified by virtue of the crushing (and the resulting

  8. Multiscale System Theory

    Science.gov (United States)

    1990-02-21

    LIDS-P-1953 Multiscale System Theory Albert Benveniste IRISA-INRIA, Campus de Beaulieu 35042 RENNES CEDEX, FRANCE Ramine Nikoukhah INRIA...TITLE AND SUBTITLE Multiscale System Theory 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d. PROJECT NUMBER 5e...the development of a corresponding system theory and a theory of stochastic processes and their estimation. The research presented in this and several

  9. Multiscale Simulations Using Particles

    DEFF Research Database (Denmark)

    Walther, Jens Honore

    vortex methods for problems in continuum fluid dynamics, dissipative particle dynamics for flow at the meso scale, and atomistic molecular dynamics simulations of nanofluidic systems. We employ multiscale techniques to breach the atomistic and continuum scales to study fundamental problems in fluid...... dynamics. Recent work on the thermophoretic motion of water nanodroplets confined inside carbon nanotubes, and multiscale techniques for polar liquids will be discussed in detail at the symposium....

  10. Finding Multi-scale Connectivity in Our Geospace Observational System: A New Perspective for Total Electron Content Data Through Network Analysis

    Science.gov (United States)

    McGranaghan, R. M.; Mannucci, A. J.; Verkhoglyadova, O. P.; Malik, N.

    2017-12-01

    How do we evolve beyond current traditional methods in order to innovate into the future? In what disruptive innovations will the next frontier of space physics and aeronomy (SPA) be grounded? We believe the answer to these compelling, yet equally challenging, questions lies in a shift of focus: from a narrow, field-specific view to a radically inclusive, interdisciplinary new modus operandi at the intersection of SPA and the information and data sciences. Concretely addressing these broader themes, we present results from a novel technique for knowledge discovery in the magnetosphere-ionosphere-thermosphere (MIT) system: complex network analysis (NA). We share findings from the first NA of ionospheric total electron content (TEC) data, including hemispheric and interplanetary magnetic field clock angle dependencies [1]. Our work shows that NA complements more traditional approaches for the investigation of TEC structure and dynamics, by both reaffirming well-established understanding, giving credence to the method, and identifying new connections, illustrating the exciting potential. We contextualize these new results through a discussion of the potential of data-driven discovery in the MIT system when innovative data science techniques are embraced. We address implications and potentially disruptive data analysis approaches for SPA in terms of: 1) the future of the geospace observational system; 2) understanding multi-scale phenomena; and 3) machine learning. [1] McGranaghan, R. M., A. J. Mannucci, O. Verkhoglyadova, and N. Malik (2017), Finding multiscale connectivity in our geospace observational system: Network analysis of total electron content, J. Geophys. Res. Space Physics, 122, doi:10.1002/2017JA024202.

  11. Multiscale geometric modeling of macromolecules I: Cartesian representation

    Science.gov (United States)

    Xia, Kelin; Feng, Xin; Chen, Zhan; Tong, Yiying; Wei, Guo-Wei

    2014-01-01

    This paper focuses on the geometric modeling and computational algorithm development of biomolecular structures from two data sources: Protein Data Bank (PDB) and Electron Microscopy Data Bank (EMDB) in the Eulerian (or Cartesian) representation. Molecular surface (MS) contains non-smooth geometric singularities, such as cusps, tips and self-intersecting facets, which often lead to computational instabilities in molecular simulations, and violate the physical principle of surface free energy minimization. Variational multiscale surface definitions are proposed based on geometric flows and solvation analysis of biomolecular systems. Our approach leads to geometric and potential driven Laplace-Beltrami flows for biomolecular surface evolution and formation. The resulting surfaces are free of geometric singularities and minimize the total free energy of the biomolecular system. High order partial differential equation (PDE)-based nonlinear filters are employed for EMDB data processing. We show the efficacy of this approach in feature-preserving noise reduction. After the construction of protein multiresolution surfaces, we explore the analysis and characterization of surface morphology by using a variety of curvature definitions. Apart from the classical Gaussian curvature and mean curvature, maximum curvature, minimum curvature, shape index, and curvedness are also applied to macromolecular surface analysis for the first time. Our curvature analysis is uniquely coupled to the analysis of electrostatic surface potential, which is a by-product of our variational multiscale solvation models. As an expository investigation, we particularly emphasize the numerical algorithms and computational protocols for practical applications of the above multiscale geometric models. Such information may otherwise be scattered over the vast literature on this topic. Based on the curvature and electrostatic analysis from our multiresolution surfaces, we introduce a new concept, the

  12. Multiscale geometric modeling of macromolecules I: Cartesian representation

    Energy Technology Data Exchange (ETDEWEB)

    Xia, Kelin [Department of Mathematics, Michigan State University, MI 48824 (United States); Feng, Xin [Department of Computer Science and Engineering, Michigan State University, MI 48824 (United States); Chen, Zhan [Department of Mathematics, Michigan State University, MI 48824 (United States); Tong, Yiying [Department of Computer Science and Engineering, Michigan State University, MI 48824 (United States); Wei, Guo-Wei, E-mail: wei@math.msu.edu [Department of Mathematics, Michigan State University, MI 48824 (United States); Department of Biochemistry and Molecular Biology, Michigan State University, MI 48824 (United States)

    2014-01-15

    This paper focuses on the geometric modeling and computational algorithm development of biomolecular structures from two data sources: Protein Data Bank (PDB) and Electron Microscopy Data Bank (EMDB) in the Eulerian (or Cartesian) representation. Molecular surface (MS) contains non-smooth geometric singularities, such as cusps, tips and self-intersecting facets, which often lead to computational instabilities in molecular simulations, and violate the physical principle of surface free energy minimization. Variational multiscale surface definitions are proposed based on geometric flows and solvation analysis of biomolecular systems. Our approach leads to geometric and potential driven Laplace–Beltrami flows for biomolecular surface evolution and formation. The resulting surfaces are free of geometric singularities and minimize the total free energy of the biomolecular system. High order partial differential equation (PDE)-based nonlinear filters are employed for EMDB data processing. We show the efficacy of this approach in feature-preserving noise reduction. After the construction of protein multiresolution surfaces, we explore the analysis and characterization of surface morphology by using a variety of curvature definitions. Apart from the classical Gaussian curvature and mean curvature, maximum curvature, minimum curvature, shape index, and curvedness are also applied to macromolecular surface analysis for the first time. Our curvature analysis is uniquely coupled to the analysis of electrostatic surface potential, which is a by-product of our variational multiscale solvation models. As an expository investigation, we particularly emphasize the numerical algorithms and computational protocols for practical applications of the above multiscale geometric models. Such information may otherwise be scattered over the vast literature on this topic. Based on the curvature and electrostatic analysis from our multiresolution surfaces, we introduce a new concept, the

  13. Metropolitanization and Forest Recovery in Southern Brazil: a Multiscale Analysis of the Florianópolis City-Region, Santa Catarina State, 1970 to 2005

    Directory of Open Access Journals (Sweden)

    Sandra R. Baptista

    2008-12-01

    Full Text Available Within the contexts of globalization and the Atlantic Forest ecoregion, I present a multiscale analysis of anthropogenic landscape dynamics in the Florianópolis city-region, Santa Catarina, southern Brazil. Drawing on field research conducted between 2000 and 2004 and a review of the literature, I examined Brazilian demographic and agricultural census data for the period of 1970 to 1995-1996. I hypothesized that economic restructuring, new institutional arrangements, and the valuation of environmental amenities and ecosystem services have contributed to forest recovery trends and thus a forest transition in the city-region. My results indicate that along with rapid urbanization, in-migration, socioeconomic polarization, and segregation, the city-region has experienced the contraction of private agricultural land area, expansion of protected areas, recovery of forests, and conversion of coastal plain ecosystems to built environments. Future analyses of forest transition dynamics should consider the spatial configurations of socioeconomic inequality in city-regions.

  14. Generalized multiscale finite element method for elasticity equations

    KAUST Repository

    Chung, Eric T.

    2014-10-05

    In this paper, we discuss the application of generalized multiscale finite element method (GMsFEM) to elasticity equation in heterogeneous media. We consider steady state elasticity equations though some of our applications are motivated by elastic wave propagation in subsurface where the subsurface properties can be highly heterogeneous and have high contrast. We present the construction of main ingredients for GMsFEM such as the snapshot space and offline spaces. The latter is constructed using local spectral decomposition in the snapshot space. The spectral decomposition is based on the analysis which is provided in the paper. We consider both continuous Galerkin and discontinuous Galerkin coupling of basis functions. Both approaches have their cons and pros. Continuous Galerkin methods allow avoiding penalty parameters though they involve partition of unity functions which can alter the properties of multiscale basis functions. On the other hand, discontinuous Galerkin techniques allow gluing multiscale basis functions without any modifications. Because basis functions are constructed independently from each other, this approach provides an advantage. We discuss the use of oversampling techniques that use snapshots in larger regions to construct the offline space. We provide numerical results to show that one can accurately approximate the solution using reduced number of degrees of freedom.

  15. An automated vessel segmentation of retinal images using multiscale vesselness

    International Nuclear Information System (INIS)

    Ben Abdallah, M.; Malek, J.; Tourki, R.; Krissian, K.

    2011-01-01

    The ocular fundus image can provide information on pathological changes caused by local ocular diseases and early signs of certain systemic diseases, such as diabetes and hypertension. Automated analysis and interpretation of fundus images has become a necessary and important diagnostic procedure in ophthalmology. The extraction of blood vessels from retinal images is an important and challenging task in medical analysis and diagnosis. In this paper, we introduce an implementation of the anisotropic diffusion which allows reducing the noise and better preserving small structures like vessels in 2D images. A vessel detection filter, based on a multi-scale vesselness function, is then applied to enhance vascular structures.

  16. Multiscale modelling and experimentation of hydrogen embrittlement in aerospace materials

    Science.gov (United States)

    Jothi, Sathiskumar

    Pulse plated nickel and nickel based superalloys have been used extensively in the Ariane 5 space launcher engines. Large structural Ariane 5 space launcher engine components such as combustion chambers with complex microstructures have usually been manufactured using electrodeposited nickel with advanced pulse plating techniques with smaller parts made of nickel based superalloys joined or welded to the structure to fabricate Ariane 5 space launcher engines. One of the major challenges in manufacturing these space launcher components using newly developed materials is a fundamental understanding of how different materials and microstructures react with hydrogen during welding which can lead to hydrogen induced cracking. The main objective of this research has been to examine and interpret the effects of microstructure on hydrogen diffusion and hydrogen embrittlement in (i) nickel based superalloy 718, (ii) established and (iii) newly developed grades of pulse plated nickel used in the Ariane 5 space launcher engine combustion chamber. Also, the effect of microstructures on hydrogen induced hot and cold cracking and weldability of three different grades of pulse plated nickel were investigated. Multiscale modelling and experimental methods have been used throughout. The effect of microstructure on hydrogen embrittlement was explored using an original multiscale numerical model (exploiting synthetic and real microstructures) and a wide range of material characterization techniques including scanning electron microscopy, 2D and 3D electron back scattering diffraction, in-situ and ex-situ hydrogen charged slow strain rate tests, thermal spectroscopy analysis and the Varestraint weldability test. This research shows that combined multiscale modelling and experimentation is required for a fundamental understanding of microstructural effects in hydrogen embrittlement in these materials. Methods to control the susceptibility to hydrogen induced hot and cold cracking and

  17. Quantifying multiscale inefficiency in electricity markets

    Energy Technology Data Exchange (ETDEWEB)

    Uritskaya, Olga Y. [Department of Economics, University of Calgary, Calgary, Alberta T2N 1N4, and Department of Economics and Management, St. Petersburg Polytechnic University, St. Petersburg (Russian Federation); Serletis, Apostolos [Department of Economics, University of Calgary, Calgary, Alberta (Canada)

    2008-11-15

    One of the basic features of efficient markets is the absence of correlations between price increments over any time scale leading to random walk-type behavior of prices. In this paper, we propose a new approach for measuring deviations from the efficient market state based on an analysis of scale-dependent fractal exponent characterizing correlations at different time scales. The approach is applied to two electricity markets, Alberta and Mid Columbia (Mid-C), as well as to the AECO Alberta natural gas market (for purposes of providing a comparison between storable and non-storable commodities). We show that price fluctuations in all studied markets are not efficient, with electricity prices exhibiting complex multiscale correlated behavior not captured by monofractal methods used in previous studies. (author)

  18. Quantifying multiscale inefficiency in electricity markets

    International Nuclear Information System (INIS)

    Uritskaya, Olga Y.; Serletis, Apostolos

    2008-01-01

    One of the basic features of efficient markets is the absence of correlations between price increments over any time scale leading to random walk-type behavior of prices. In this paper, we propose a new approach for measuring deviations from the efficient market state based on an analysis of scale-dependent fractal exponent characterizing correlations at different time scales. The approach is applied to two electricity markets, Alberta and Mid Columbia (Mid-C), as well as to the AECO Alberta natural gas market (for purposes of providing a comparison between storable and non-storable commodities). We show that price fluctuations in all studied markets are not efficient, with electricity prices exhibiting complex multiscale correlated behavior not captured by monofractal methods used in previous studies. (author)

  19. Image-based multiscale mechanical modeling shows the importance of structural heterogeneity in the human lumbar facet capsular ligament.

    Science.gov (United States)

    Zarei, Vahhab; Liu, Chao J; Claeson, Amy A; Akkin, Taner; Barocas, Victor H

    2017-08-01

    The lumbar facet capsular ligament (FCL) primarily consists of aligned type I collagen fibers that are mainly oriented across the joint. The aim of this study was to characterize and incorporate in-plane local fiber structure into a multiscale finite element model to predict the mechanical response of the FCL during in vitro mechanical tests, accounting for the heterogeneity in different scales. Characterization was accomplished by using entire-domain polarization-sensitive optical coherence tomography to measure the fiber structure of cadaveric lumbar FCLs ([Formula: see text]). Our imaging results showed that fibers in the lumbar FCL have a highly heterogeneous distribution and are neither isotropic nor completely aligned. The averaged fiber orientation was [Formula: see text] ([Formula: see text] in the inferior region and [Formula: see text] in the middle and superior regions), with respect to lateral-medial direction (superior-medial to inferior-lateral). These imaging data were used to construct heterogeneous structural models, which were then used to predict experimental gross force-strain behavior and the strain distribution during equibiaxial and strip biaxial tests. For equibiaxial loading, the structural model fit the experimental data well but underestimated the lateral-medial forces by [Formula: see text]16% on average. We also observed pronounced heterogeneity in the strain field, with stretch ratios for different elements along the lateral-medial axis of sample typically ranging from about 0.95 to 1.25 during a 12% strip biaxial stretch in the lateral-medial direction. This work highlights the multiscale structural and mechanical heterogeneity of the lumbar FCL, which is significant both in terms of injury prediction and microstructural constituents' (e.g., neurons) behavior.

  20. Final Technical Report "Multiscale Simulation Algorithms for Biochemical Systems"

    Energy Technology Data Exchange (ETDEWEB)

    Petzold, Linda R.

    2012-10-25

    Biochemical systems are inherently multiscale and stochastic. In microscopic systems formed by living cells, the small numbers of reactant molecules can result in dynamical behavior that is discrete and stochastic rather than continuous and deterministic. An analysis tool that respects these dynamical characteristics is the stochastic simulation algorithm (SSA, Gillespie, 1976), a numerical simulation procedure that is essentially exact for chemical systems that are spatially homogeneous or well stirred. Despite recent improvements, as a procedure that simulates every reaction event, the SSA is necessarily inefficient for most realistic problems. There are two main reasons for this, both arising from the multiscale nature of the underlying problem: (1) stiffness, i.e. the presence of multiple timescales, the fastest of which are stable; and (2) the need to include in the simulation both species that are present in relatively small quantities and should be modeled by a discrete stochastic process, and species that are present in larger quantities and are more efficiently modeled by a deterministic differential equation (or at some scale in between). This project has focused on the development of fast and adaptive algorithms, and the fun- damental theory upon which they must be based, for the multiscale simulation of biochemical systems. Areas addressed by this project include: (1) Theoretical and practical foundations for ac- celerated discrete stochastic simulation (tau-leaping); (2) Dealing with stiffness (fast reactions) in an efficient and well-justified manner in discrete stochastic simulation; (3) Development of adaptive multiscale algorithms for spatially homogeneous discrete stochastic simulation; (4) Development of high-performance SSA algorithms.

  1. Influences of the land use pattern on water quality in low-order streams of the Dongjiang River basin, China: A multi-scale analysis.

    Science.gov (United States)

    Ding, Jiao; Jiang, Yuan; Liu, Qi; Hou, Zhaojiang; Liao, Jianyu; Fu, Lan; Peng, Qiuzhi

    2016-05-01

    Understanding the relationships between land use patterns and water quality in low-order streams is useful for effective landscape planning to protect downstream water quality. A clear understanding of these relationships remains elusive due to the heterogeneity of land use patterns and scale effects. To better assess land use influences, we developed empirical models relating land use patterns to the water quality of low-order streams at different geomorphic regions across multi-scales in the Dongjiang River basin using multivariate statistical analyses. The land use pattern was quantified in terms of the composition, configuration and hydrological distance of land use types at the reach buffer, riparian corridor and catchment scales. Water was sampled under summer base flow at 56 low-order catchments, which were classified into two homogenous geomorphic groups. The results indicated that the water quality of low-order streams was most strongly affected by the configuration metrics of land use. Poorer water quality was associated with higher patch densities of cropland, orchards and grassland in the mountain catchments, whereas it was associated with a higher value for the largest patch index of urban land use in the plain catchments. The overall water quality variation was explained better by catchment scale than by riparian- or reach-scale land use, whereas the spatial scale over which land use influenced water quality also varied across specific water parameters and the geomorphic basis. Our study suggests that watershed management should adopt better landscape planning and multi-scale measures to improve water quality. Copyright © 2016 Elsevier B.V. All rights reserved.

  2. Multiscale Lyapunov exponent for 2-microlocal functions

    International Nuclear Information System (INIS)

    Dhifaoui, Zouhaier; Kortas, Hedi; Ammou, Samir Ben

    2009-01-01

    The Lyapunov exponent is an important indicator of chaotic dynamics. Using wavelet analysis, we define a multiscale representation of this exponent which we demonstrate the scale-wise dependence for functions belonging to C x 0 s,s ' spaces. An empirical study involving simulated processes and financial time series corroborates the theoretical findings.

  3. Wavelet-based analysis of gastric microcirculation in rats with ulcer bleedings

    Science.gov (United States)

    Pavlov, A. N.; Rodionov, M. A.; Pavlova, O. N.; Semyachkina-Glushkovskaya, O. V.; Berdnikova, V. A.; Kuznetsova, Ya. V.; Semyachkin-Glushkovskij, I. A.

    2012-03-01

    Studying of nitric oxide (NO) dependent mechanisms of regulation of microcirculation in a stomach can provide important diagnostic markers of the development of stress-induced ulcer bleedings. In this work we use a multiscale analysis based on the discrete wavelet-transform to characterize a latent stage of illness formation in rats. A higher sensitivity of stomach vessels to the NO-level in ill rats is discussed.

  4. Peridynamic Multiscale Finite Element Methods

    Energy Technology Data Exchange (ETDEWEB)

    Costa, Timothy [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Bond, Stephen D. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Littlewood, David John [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Moore, Stan Gerald [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

    2015-12-01

    art of local models with the flexibility and accuracy of the nonlocal peridynamic model. In the mixed locality method this coupling occurs across scales, so that the nonlocal model can be used to communicate material heterogeneity at scales inappropriate to local partial differential equation models. Additionally, the computational burden of the weak form of the peridynamic model is reduced dramatically by only requiring that the model be solved on local patches of the simulation domain which may be computed in parallel, taking advantage of the heterogeneous nature of next generation computing platforms. Addition- ally, we present a novel Galerkin framework, the 'Ambulant Galerkin Method', which represents a first step towards a unified mathematical analysis of local and nonlocal multiscale finite element methods, and whose future extension will allow the analysis of multiscale finite element methods that mix models across scales under certain assumptions of the consistency of those models.

  5. Genetic divergence among cupuaçu accessions by multiscale bootstrap resampling

    Directory of Open Access Journals (Sweden)

    Vinicius Silva dos Santos

    2015-06-01

    Full Text Available This study aimed at investigating the genetic divergence of eighteen accessions of cupuaçu trees based on fruit morphometric traits and comparing usual methods of cluster analysis with the proposed multiscale bootstrap resampling methodology. The data were obtained from an experiment conducted in Tomé-Açu city (PA, Brazil, arranged in a completely randomized design with eighteen cupuaçu accessions and 10 repetitions, from 2004 to 2011. Genetic parameters were estimated by restricted maximum likelihood/best linear unbiased prediction (REML/BLUP methodology. The predicted breeding values were used in the study on genetic divergence through Unweighted Pair Cluster Method with Arithmetic Mean (UPGMA hierarchical clustering and Tocher’s optimization method based on standardized Euclidean distance. Clustering consistency and optimal number of clusters in the UPGMA method were verified by the cophenetic correlation coefficient (CCC and Mojena’s criterion, respectively, besides the multiscale bootstrap resampling technique. The use of the clustering UPGMA method in situations with and without multiscale bootstrap resulted in four and five clusters, respectively, while the Tocher’s method resulted in seven clusters. The multiscale bootstrap resampling technique proves to be efficient to assess the consistency of clustering in hierarchical methods and, consequently, the optimal number of clusters.

  6. Improved Multiscale Entropy Technique with Nearest-Neighbor Moving-Average Kernel for Nonlinear and Nonstationary Short-Time Biomedical Signal Analysis

    Directory of Open Access Journals (Sweden)

    S. P. Arunachalam

    2018-01-01

    Full Text Available Analysis of biomedical signals can yield invaluable information for prognosis, diagnosis, therapy evaluation, risk assessment, and disease prevention which is often recorded as short time series data that challenges existing complexity classification algorithms such as Shannon entropy (SE and other techniques. The purpose of this study was to improve previously developed multiscale entropy (MSE technique by incorporating nearest-neighbor moving-average kernel, which can be used for analysis of nonlinear and non-stationary short time series physiological data. The approach was tested for robustness with respect to noise analysis using simulated sinusoidal and ECG waveforms. Feasibility of MSE to discriminate between normal sinus rhythm (NSR and atrial fibrillation (AF was tested on a single-lead ECG. In addition, the MSE algorithm was applied to identify pivot points of rotors that were induced in ex vivo isolated rabbit hearts. The improved MSE technique robustly estimated the complexity of the signal compared to that of SE with various noises, discriminated NSR and AF on single-lead ECG, and precisely identified the pivot points of ex vivo rotors by providing better contrast between the rotor core and the peripheral region. The improved MSE technique can provide efficient complexity analysis of variety of nonlinear and nonstationary short-time biomedical signals.

  7. A multiscale approach to mutual information matching

    NARCIS (Netherlands)

    Pluim, J.P.W.; Maintz, J.B.A.; Viergever, M.A.; Hanson, K.M.

    1998-01-01

    Methods based on mutual information have shown promising results for matching of multimodal brain images. This paper discusses a multiscale approach to mutual information matching, aiming for an acceleration of the matching process while considering the accuracy and robustness of the method. Scaling

  8. Multiscale optimization of saturated poroelastic actuators

    DEFF Research Database (Denmark)

    Andreasen, Casper Schousboe; Sigmund, Ole

    A multiscale method for optimizing the material micro structure in a macroscopically heterogeneous saturated poroelastic media with respect to macro properties is presented. The method is based on topology optimization using the homogenization technique, here applied to the optimization of a bi...

  9. Determining the multi-scale hedge ratios of stock index futures using the lower partial moments method

    Science.gov (United States)

    Dai, Jun; Zhou, Haigang; Zhao, Shaoquan

    2017-01-01

    This paper considers a multi-scale future hedge strategy that minimizes lower partial moments (LPM). To do this, wavelet analysis is adopted to decompose time series data into different components. Next, different parametric estimation methods with known distributions are applied to calculate the LPM of hedged portfolios, which is the key to determining multi-scale hedge ratios over different time scales. Then these parametric methods are compared with the prevailing nonparametric kernel metric method. Empirical results indicate that in the China Securities Index 300 (CSI 300) index futures and spot markets, hedge ratios and hedge efficiency estimated by the nonparametric kernel metric method are inferior to those estimated by parametric hedging model based on the features of sequence distributions. In addition, if minimum-LPM is selected as a hedge target, the hedging periods, degree of risk aversion, and target returns can affect the multi-scale hedge ratios and hedge efficiency, respectively.

  10. The Abridgment and Relaxation Time for a Linear Multi-Scale Model Based on Multiple Site Phosphorylation.

    Directory of Open Access Journals (Sweden)

    Shuo Wang

    Full Text Available Random effect in cellular systems is an important topic in systems biology and often simulated with Gillespie's stochastic simulation algorithm (SSA. Abridgment refers to model reduction that approximates a group of reactions by a smaller group with fewer species and reactions. This paper presents a theoretical analysis, based on comparison of the first exit time, for the abridgment on a linear chain reaction model motivated by systems with multiple phosphorylation sites. The analysis shows that if the relaxation time of the fast subsystem is much smaller than the mean firing time of the slow reactions, the abridgment can be applied with little error. This analysis is further verified with numerical experiments for models of bistable switch and oscillations in which linear chain system plays a critical role.

  11. Multi-scale analysis of bone chemistry, morphology and mechanics in the oim model of osteogenesis imperfecta.

    Science.gov (United States)

    Bart, Zachary R; Hammond, Max A; Wallace, Joseph M

    2014-08-01

    Osteogenesis imperfecta is a congenital disease commonly characterized by brittle bones and caused by mutations in the genes encoding Type I collagen, the single most abundant protein produced by the body. The oim model has a natural collagen mutation, converting its heterotrimeric structure (two α1 and one α2 chains) into α1 homotrimers. This mutation in collagen may impact formation of the mineral, creating a brittle bone phenotype in animals. Femurs from male wild type (WT) and homozygous (oim/oim) mice, all at 12 weeks of age, were assessed using assays at multiple length scales with minimal sample processing to ensure a near-physiological state. Atomic force microscopy (AFM) demonstrated detectable differences in the organization of collagen at the nanoscale that may partially contribute to alterations in material and structural behavior obtained through mechanical testing and reference point indentation (RPI). Changes in geometric and chemical structure obtained from µ-Computed Tomography and Raman spectroscopy indicate a smaller bone with reduced trabecular architecture and altered chemical composition. Decreased tissue material properties in oim/oim mice are likely driven by changes in collagen fibril structure, decreasing space available for mineral nucleation and growth, as supported by a reduction in mineral crystallinity. Multi-scale analyses of this nature offer much in assessing how molecular changes compound to create a degraded, brittle bone phenotype.

  12. Multiscale Biological Materials

    DEFF Research Database (Denmark)

    Frølich, Simon

    of multiscale biological systems have been investigated and new research methods for automated Rietveld refinement and diffraction scattering computed tomography developed. The composite nature of biological materials was investigated at the atomic scale by looking at the consequences of interactions between...

  13. Fast Multiscale Reservoir Simulations using POD-DEIM Model Reduction

    KAUST Repository

    Ghasemi, Mohammadreza; Yang, Yanfang; Gildin, Eduardo; Efendiev, Yalchin R.; Calo, Victor M.

    2015-01-01

    snapshots are inexpensively computed using local model reduction techniques based on Generalized Multiscale Finite Element Method (GMsFEM) which provides (1) a hierarchical approximation of snapshot vectors (2) adaptive computations by using coarse grids (3

  14. Multiscale Simulations for Coupled Flow and Transport Using the Generalized Multiscale Finite Element Method

    KAUST Repository

    Chung, Eric

    2015-12-11

    In this paper, we develop a mass conservative multiscale method for coupled flow and transport in heterogeneous porous media. We consider a coupled system consisting of a convection-dominated transport equation and a flow equation. We construct a coarse grid solver based on the Generalized Multiscale Finite Element Method (GMsFEM) for a coupled system. In particular, multiscale basis functions are constructed based on some snapshot spaces for the pressure and the concentration equations and some local spectral decompositions in the snapshot spaces. The resulting approach uses a few multiscale basis functions in each coarse block (for both the pressure and the concentration) to solve the coupled system. We use the mixed framework, which allows mass conservation. Our main contributions are: (1) the development of a mass conservative GMsFEM for the coupled flow and transport; (2) the development of a robust multiscale method for convection-dominated transport problems by choosing appropriate test and trial spaces within Petrov-Galerkin mixed formulation. We present numerical results and consider several heterogeneous permeability fields. Our numerical results show that with only a few basis functions per coarse block, we can achieve a good approximation.

  15. Multiscale Simulations for Coupled Flow and Transport Using the Generalized Multiscale Finite Element Method

    KAUST Repository

    Chung, Eric; Efendiev, Yalchin R.; Leung, Wing; Ren, Jun

    2015-01-01

    In this paper, we develop a mass conservative multiscale method for coupled flow and transport in heterogeneous porous media. We consider a coupled system consisting of a convection-dominated transport equation and a flow equation. We construct a coarse grid solver based on the Generalized Multiscale Finite Element Method (GMsFEM) for a coupled system. In particular, multiscale basis functions are constructed based on some snapshot spaces for the pressure and the concentration equations and some local spectral decompositions in the snapshot spaces. The resulting approach uses a few multiscale basis functions in each coarse block (for both the pressure and the concentration) to solve the coupled system. We use the mixed framework, which allows mass conservation. Our main contributions are: (1) the development of a mass conservative GMsFEM for the coupled flow and transport; (2) the development of a robust multiscale method for convection-dominated transport problems by choosing appropriate test and trial spaces within Petrov-Galerkin mixed formulation. We present numerical results and consider several heterogeneous permeability fields. Our numerical results show that with only a few basis functions per coarse block, we can achieve a good approximation.

  16. Multiscale Shannon's Entropy Modeling of Orientation and Distance in Steel Fiber Micro-Tomography Data.

    Science.gov (United States)

    Chiverton, John P; Ige, Olubisi; Barnett, Stephanie J; Parry, Tony

    2017-11-01

    This paper is concerned with the modeling and analysis of the orientation and distance between steel fibers in X-ray micro-tomography data. The advantage of combining both orientation and separation in a model is that it helps provide a detailed understanding of how the steel fibers are arranged, which is easy to compare. The developed models are designed to summarize the randomness of the orientation distribution of the steel fibers both locally and across an entire volume based on multiscale entropy. Theoretical modeling, simulation, and application to real imaging data are shown here. The theoretical modeling of multiscale entropy for orientation includes a proof showing the final form of the multiscale taken over a linear range of scales. A series of image processing operations are also included to overcome interslice connectivity issues to help derive the statistical descriptions of the orientation distributions of the steel fibers. The results demonstrate that multiscale entropy provides unique insights into both simulated and real imaging data of steel fiber reinforced concrete.

  17. Multi-Scale Scattering Transform in Music Similarity Measuring

    Science.gov (United States)

    Wang, Ruobai

    Scattering transform is a Mel-frequency spectrum based, time-deformation stable method, which can be used in evaluating music similarity. Compared with Dynamic time warping, it has better performance in detecting similar audio signals under local time-frequency deformation. Multi-scale scattering means to combine scattering transforms of different window lengths. This paper argues that, multi-scale scattering transform is a good alternative of dynamic time warping in music similarity measuring. We tested the performance of multi-scale scattering transform against other popular methods, with data designed to represent different conditions.

  18. Generalization Performance of Regularized Ranking With Multiscale Kernels.

    Science.gov (United States)

    Zhou, Yicong; Chen, Hong; Lan, Rushi; Pan, Zhibin

    2016-05-01

    The regularized kernel method for the ranking problem has attracted increasing attentions in machine learning. The previous regularized ranking algorithms are usually based on reproducing kernel Hilbert spaces with a single kernel. In this paper, we go beyond this framework by investigating the generalization performance of the regularized ranking with multiscale kernels. A novel ranking algorithm with multiscale kernels is proposed and its representer theorem is proved. We establish the upper bound of the generalization error in terms of the complexity of hypothesis spaces. It shows that the multiscale ranking algorithm can achieve satisfactory learning rates under mild conditions. Experiments demonstrate the effectiveness of the proposed method for drug discovery and recommendation tasks.

  19. Three-dimensional reconstruction of the human spine from bi-planar radiographs: using multiscale wavelet analysis and spline interpolators for semi-automation

    Science.gov (United States)

    Deschenes, Sylvain; Godbout, Benoit; Branchaud, Dominic; Mitton, David; Pomero, Vincent; Bleau, Andre; Skalli, Wafa; de Guise, Jacques A.

    2003-05-01

    We propose a new fast stereoradiographic 3D reconstruction method for the spine. User input is limited to few points passing through the spine on two radiographs and two line segments representing the end plates of the limiting vertebrae. A 3D spline that hints the positions of the vertebrae in space is then generated. We then use wavelet multi-scale analysis (WMSA) to automatically localize specific features in both lateral and frontal radiographs. The WMSA gives an elegant spectral investigation that leads to gradient generation and edge extraction. Analysis of the information contained at several scales leads to the detection of 1) two curves enclosing the vertebral bodies' walls and 2) inter-vertebral spaces along the spine. From this data, we extract four points per vertebra per view, corresponding to the corners of the vertebral bodies. These points delimit a hexahedron in space where we can match the vertebral body. This hexahedron is then passed through a 3D statistical database built using local and global information generated from a bank of normal and scoliotic spines. Finally, models of the vertebrae are positioned with respect to these landmarks, completing the 3D reconstruction.

  20. Towards distributed multiscale computing for the VPH

    NARCIS (Netherlands)

    Hoekstra, A.G.; Coveney, P.

    2010-01-01

    Multiscale modeling is fundamental to the Virtual Physiological Human (VPH) initiative. Most detailed three-dimensional multiscale models lead to prohibitive computational demands. As a possible solution we present MAPPER, a computational science infrastructure for Distributed Multiscale Computing

  1. Toward the multiscale nature of stress corrosion cracking

    Directory of Open Access Journals (Sweden)

    Xiaolong Liu

    2018-02-01

    Full Text Available This article reviews the multiscale nature of stress corrosion cracking (SCC observed by high-resolution characterizations in austenite stainless steels and Ni-base superalloys in light water reactors (including boiling water reactors, pressurized water reactors, and supercritical water reactors with related opinions. A new statistical summary and comparison of observed degradation phenomena at different length scales is included. The intrinsic causes of this multiscale nature of SCC are discussed based on existing evidence and related opinions, ranging from materials theory to practical processing technologies. Questions of interest are then discussed to improve bottom-up understanding of the intrinsic causes. Last, a multiscale modeling and simulation methodology is proposed as a promising interdisciplinary solution to understand the intrinsic causes of the multiscale nature of SCC in light water reactors, based on a review of related supporting application evidence.

  2. Multiscale Thermohydrologic Model

    Energy Technology Data Exchange (ETDEWEB)

    T. Buscheck

    2004-10-12

    The purpose of the multiscale thermohydrologic model (MSTHM) is to predict the possible range of thermal-hydrologic conditions, resulting from uncertainty and variability, in the repository emplacement drifts, including the invert, and in the adjoining host rock for the repository at Yucca Mountain. Thus, the goal is to predict the range of possible thermal-hydrologic conditions across the repository; this is quite different from predicting a single expected thermal-hydrologic response. The MSTHM calculates the following thermal-hydrologic parameters: temperature, relative humidity, liquid-phase saturation, evaporation rate, air-mass fraction, gas-phase pressure, capillary pressure, and liquid- and gas-phase fluxes (Table 1-1). These thermal-hydrologic parameters are required to support ''Total System Performance Assessment (TSPA) Model/Analysis for the License Application'' (BSC 2004 [DIRS 168504]). The thermal-hydrologic parameters are determined as a function of position along each of the emplacement drifts and as a function of waste package type. These parameters are determined at various reference locations within the emplacement drifts, including the waste package and drip-shield surfaces and in the invert. The parameters are also determined at various defined locations in the adjoining host rock. The MSTHM uses data obtained from the data tracking numbers (DTNs) listed in Table 4.1-1. The majority of those DTNs were generated from the following analyses and model reports: (1) ''UZ Flow Model and Submodels'' (BSC 2004 [DIRS 169861]); (2) ''Development of Numerical Grids for UZ Flow and Transport Modeling'' (BSC 2004); (3) ''Calibrated Properties Model'' (BSC 2004 [DIRS 169857]); (4) ''Thermal Conductivity of the Potential Repository Horizon'' (BSC 2004 [DIRS 169854]); (5) ''Thermal Conductivity of the Non-Repository Lithostratigraphic Layers

  3. Lime treatment of an Italian pyroclastic soil: a multi-scale analysis for the correlation of mechanical and chemo-mineralogical effects.

    Science.gov (United States)

    Guidobaldi, Giulia; Cambi, Costanza; Cecconi, Manuela; Comodi, Paola; Zucchini, Azzurra

    2017-04-01

    improvements. Direct shear tests on treated soil samples revealed a brittle and dilatant behaviour; both features are more evident with increasing lime content, curing time and stress levels. Mechanical and chemo-mineralogical observations were coupled to obtain a better comprehension of the treated soil system evolution. During the chemo-mineralogical investigation phase, the ongoing system modifications at particle level were extremely stressed mixing soil and lime in the same weight proportions. This also led to a clear identification of the reaction products and kinetics through µX-Ray Fluorescence, X-Ray Diffraction, Thermogravimetry, Fourier Transformed Infra-Red and 29Si Nuclear Magnetic Resonance spectroscopy. The performed multi-scale analysis of the treated pyroclastic soil revealed the high reactivity of the system to lime addition, and the occurrence of pozzolanic reactions since the very beginning. The availability of secondary phases, in both crystalline and gel-like state, and their structural features are the main responsible for the observed mechanical behavior of the treated soil, showing the effectiveness of the treatment and the key role of zeolites in the chemo-physical evolution of the system. The obtained results, validated and supported by a deep comprehension of the micro-scale processes induced by lime treatment might open new perspective for future fruitful applications of pyroclastic problematic soils.

  4. Effect of size and geometry of gold nanostructures in performance of laser-based hyperthermia: a multiscale- multiphysics modelling

    International Nuclear Information System (INIS)

    Samadinia, Hossein; Rafii-Tabar, Hashem; Sasanpour, Pezhman; Razaghi, Mohammad Reza; Nezhad, Mohammadreza Hormozi

    2016-01-01

    The importance of hyperthermia as a promising method in disruption and removal of cancerous cells is well understood. One of the effective options of concentration of heat within a specific tissue is using laser and exploiting absorption properties of metallic nanostructures. In this report, the geometrical effect of gold nanostructures in the performance of laser based hyperthermia has been analyzed. The analysis is based on the consideration of absorption properties of gold nanostructures, interaction of laser light with a specific tissue containing nanostructures and the effect of generated heat on elevation of temperature inside the tissue. The analysis is performed using Mie theory (for extraction of absorption/scattering properties of nanostructures), Monte Carlo (MC) (interaction of light inside the tissue) and solving the heat equation (considering the elevation of temperature inside the tissue). We have compared the effect of a laser beam on the maximum temperature inside the tissue and the results indicate that focusing the beam size of the laser to half width will culminate in a 50% elevation of maximum temperature in the tissue, while the average temperature raise inside the tissue will not be altered. (paper)

  5. Generalized Multiscale Finite Element Methods for Wave Propagation in Heterogeneous Media

    KAUST Repository

    Chung, Eric T.

    2014-11-13

    Numerical modeling of wave propagation in heterogeneous media is important in many applications. Due to their complex nature, direct numerical simulations on the fine grid are prohibitively expensive. It is therefore important to develop efficient and accurate methods that allow the use of coarse grids. In this paper, we present a multiscale finite element method for wave propagation on a coarse grid. The proposed method is based on the generalized multiscale finite element method (GMsFEM) (see [Y. Efendiev, J. Galvis, and T. Hou, J. Comput. Phys., 251 (2012), pp. 116--135]). To construct multiscale basis functions, we start with two snapshot spaces in each coarse-grid block, where one represents the degrees of freedom on the boundary and the other represents the degrees of freedom in the interior. We use local spectral problems to identify important modes in each snapshot space. These local spectral problems are different from each other and their formulations are based on the analysis. To the best of knowledge, this is the first time that multiple snapshot spaces and multiple spectral problems are used and necessary for efficient computations. Using the dominant modes from local spectral problems, multiscale basis functions are constructed to represent the solution space locally within each coarse block. These multiscale basis functions are coupled via the symmetric interior penalty discontinuous Galerkin method which provides a block diagonal mass matrix and, consequently, results in fast computations in an explicit time discretization. Our methods\\' stability and spectral convergence are rigorously analyzed. Numerical examples are presented to show our methods\\' performance. We also test oversampling strategies. In particular, we discuss how the modes from different snapshot spaces can affect the proposed methods\\' accuracy.

  6. Generalized multiscale finite element methods: Oversampling strategies

    KAUST Repository

    Efendiev, Yalchin R.; Galvis, Juan; Li, Guanglian; Presho, Michael

    2014-01-01

    In this paper, we propose oversampling strategies in the generalized multiscale finite element method (GMsFEM) framework. The GMsFEM, which has been recently introduced in Efendiev et al. (2013b) [Generalized Multiscale Finite Element Methods, J. Comput. Phys., vol. 251, pp. 116-135, 2013], allows solving multiscale parameter-dependent problems at a reduced computational cost by constructing a reduced-order representation of the solution on a coarse grid. The main idea of the method consists of (1) the construction of snapshot space, (2) the construction of the offline space, and (3) construction of the online space (the latter for parameter-dependent problems). In Efendiev et al. (2013b) [Generalized Multiscale Finite Element Methods, J. Comput. Phys., vol. 251, pp. 116-135, 2013], it was shown that the GMsFEM provides a flexible tool to solve multiscale problems with a complex input space by generating appropriate snapshot, offline, and online spaces. In this paper, we develop oversampling techniques to be used in this context (see Hou and Wu (1997) where oversampling is introduced for multiscale finite element methods). It is known (see Hou and Wu (1997)) that the oversampling can improve the accuracy of multiscale methods. In particular, the oversampling technique uses larger regions (larger than the target coarse block) in constructing local basis functions. Our motivation stems from the analysis presented in this paper, which shows that when using oversampling techniques in the construction of the snapshot space and offline space, GMsFEM will converge independent of small scales and high contrast under certain assumptions. We consider the use of a multiple eigenvalue problems to improve the convergence and discuss their relation to single spectral problems that use oversampled regions. The oversampling procedures proposed in this paper differ from those in Hou and Wu (1997). In particular, the oversampling domains are partially used in constructing local

  7. Optimizing the fabrication process and interplay of device components of polymer solar cells using a field-based multiscale solar-cell algorithm

    International Nuclear Information System (INIS)

    Donets, Sergii; Pershin, Anton; Baeurle, Stephan A.

    2015-01-01

    Both the device composition and fabrication process are well-known to crucially affect the power conversion efficiency of polymer solar cells. Major advances have recently been achieved through the development of novel device materials and inkjet printing technologies, which permit to improve their durability and performance considerably. In this work, we demonstrate the usefulness of a recently developed field-based multiscale solar-cell algorithm to investigate the influence of the material characteristics, like, e.g., electrode surfaces, polymer architectures, and impurities in the active layer, as well as post-production treatments, like, e.g., electric field alignment, on the photovoltaic performance of block-copolymer solar-cell devices. Our study reveals that a short exposition time of the polymer bulk heterojunction to the action of an external electric field can lead to a low photovoltaic performance due to an incomplete alignment process, leading to undulated or disrupted nanophases. With increasing exposition time, the nanophases align in direction to the electric field lines, resulting in an increase of the number of continuous percolation paths and, ultimately, in a reduction of the number of exciton and charge-carrier losses. Moreover, we conclude by modifying the interaction strengths between the electrode surfaces and active layer components that a too low or too high affinity of an electrode surface to one of the components can lead to defective contacts, causing a deterioration of the device performance. Finally, we infer from the study of block-copolymer nanoparticle systems that particle impurities can significantly affect the nanostructure of the polymer matrix and reduce the photovoltaic performance of the active layer. For a critical volume fraction and size of the nanoparticles, we observe a complete phase transformation of the polymer nanomorphology, leading to a drop of the internal quantum efficiency. For other particle-numbers and -sizes

  8. Efficient Integration of Coupled Electrical-chemical Systems in Multiscale Neuronal Simulations

    Directory of Open Access Journals (Sweden)

    Ekaterina Brocke

    2016-09-01

    Full Text Available Multiscale modeling and simulations in neuroscience is gaining scientific attention due to its growing importance and unexplored capabilities. For instance, it can help to acquire better understanding of biological phenomena that have important features at multiple scales of time and space. This includes synaptic plasticity, memory formation and modulation, homeostasis. There are several ways to organize multiscale simulations depending on the scientific problem and the system to be modeled. One of the possibilities is to simulate different components of a multiscale system simultaneously and exchange data when required. The latter may become a challenging task for several reasons. One of them is that the components of a multiscale system usually span different spatial and temporal scales, such that rigorous analysis of possible coupling solutions is required. For certain classes of problems a number of coupling mechanisms have been proposed and successfully used. However, a strict mathematical theory is missing in many cases. Recent work in the field has not so far investigated artifacts that may arise during coupled integration of different approximation methods. Moreover, the coupling of widely used numerical fixed step size solvers may lead to unexpected inefficiency. In this paper we address the question of possible numerical artifacts that can arise during the integration of a coupled system. We develop an efficient strategy to couple the components of a multiscale test system. We introduce an efficient coupling method based on the second-order backward differentiation formula numerical approximation. The method uses an adaptive step size integration with an error estimation proposed by Skelboe (2000. The method shows a significant advantage over conventional fixed step size solvers used for similar problems. We explore different coupling strategies that define the organization of computations between system components. We study the

  9. A Novel Method of Fault Diagnosis for Rolling Bearing Based on Dual Tree Complex Wavelet Packet Transform and Improved Multiscale Permutation Entropy

    Directory of Open Access Journals (Sweden)

    Guiji Tang

    2016-01-01

    Full Text Available A novel method of fault diagnosis for rolling bearing, which combines the dual tree complex wavelet packet transform (DTCWPT, the improved multiscale permutation entropy (IMPE, and the linear local tangent space alignment (LLTSA with the extreme learning machine (ELM, is put forward in this paper. In this method, in order to effectively discover the underlying feature information, DTCWPT, which has the attractive properties as nearly shift invariance and reduced aliasing, is firstly utilized to decompose the original signal into a set of subband signals. Then, IMPE, which is designed to reduce the variability of entropy measures, is applied to characterize the properties of each obtained subband signal at different scales. Furthermore, the feature vectors are constructed by combining IMPE of each subband signal. After the feature vectors construction, LLTSA is employed to compress the high dimensional vectors of the training and the testing samples into the low dimensional vectors with better distinguishability. Finally, the ELM classifier is used to automatically accomplish the condition identification with the low dimensional feature vectors. The experimental data analysis results validate the effectiveness of the presented diagnosis method and demonstrate that this method can be applied to distinguish the different fault types and fault degrees of rolling bearings.

  10. Multiscale Modeling of Poromechanics in Geologic Media

    Science.gov (United States)

    Castelletto, N.; Hajibeygi, H.; Klevtsov, S.; Tchelepi, H.

    2017-12-01

    We describe a hybrid MultiScale Finite Element-Finite Volume (h-MSFE-FV) framework for the simulation of single-phase Darcy flow through deformable porous media that exhibit highly heterogeneous poromechanical properties over a wide range of length scales. In such systems, high resolution characterizations are a key requirement to obtain reliable modeling predictions and motivate the development of multiscale solution strategies to cope with the computational burden. A coupled two-field fine-scale mixed FE-FV discretization of the governing equations, namely conservation laws of linear momentum and mass, is first implemented based on a displacement-pressure formulation. After imposing a coarse-scale grid on the given fine-scale problem, for the MSFE displacement stage, the coarse-scale basis functions are obtained by solving local equilibrium problems within coarse elements. Such MSFE stage is then coupled with the MSFV method for flow, in which a dual-coarse grid is introduced to obtain approximate but conservative multiscale solutions. Robustness and accuracy of the proposed multiscale framework is demonstrated using a variety of challenging test problems.

  11. A Comparison of Multiscale Permutation Entropy Measures in On-Line Depth of Anesthesia Monitoring.

    Science.gov (United States)

    Su, Cui; Liang, Zhenhu; Li, Xiaoli; Li, Duan; Li, Yongwang; Ursino, Mauro

    2016-01-01

    Multiscale permutation entropy (MSPE) is becoming an interesting tool to explore neurophysiological mechanisms in recent years. In this study, six MSPE measures were proposed for on-line depth of anesthesia (DoA) monitoring to quantify the anesthetic effect on the real-time EEG recordings. The performance of these measures in describing the transient characters of simulated neural populations and clinical anesthesia EEG were evaluated and compared. Six MSPE algorithms-derived from Shannon permutation entropy (SPE), Renyi permutation entropy (RPE) and Tsallis permutation entropy (TPE) combined with the decomposition procedures of coarse-graining (CG) method and moving average (MA) analysis-were studied. A thalamo-cortical neural mass model (TCNMM) was used to generate noise-free EEG under anesthesia to quantitatively assess the robustness of each MSPE measure against noise. Then, the clinical anesthesia EEG recordings from 20 patients were analyzed with these measures. To validate their effectiveness, the ability of six measures were compared in terms of tracking the dynamical changes in EEG data and the performance in state discrimination. The Pearson correlation coefficient (R) was used to assess the relationship among MSPE measures. CG-based MSPEs failed in on-line DoA monitoring at multiscale analysis. In on-line EEG analysis, the MA-based MSPE measures at 5 decomposed scales could track the transient changes of EEG recordings and statistically distinguish the awake state, unconsciousness and recovery of consciousness (RoC) state significantly. Compared to single-scale SPE and RPE, MSPEs had better anti-noise ability and MA-RPE at scale 5 performed best in this aspect. MA-TPE outperformed other measures with faster tracking speed of the loss of unconsciousness. MA-based multiscale permutation entropies have the potential for on-line anesthesia EEG analysis with its simple computation and sensitivity to drug effect changes. CG-based multiscale permutation

  12. Residual-driven online generalized multiscale finite element methods

    KAUST Repository

    Chung, Eric T.

    2015-09-08

    The construction of local reduced-order models via multiscale basis functions has been an area of active research. In this paper, we propose online multiscale basis functions which are constructed using the offline space and the current residual. Online multiscale basis functions are constructed adaptively in some selected regions based on our error indicators. We derive an error estimator which shows that one needs to have an offline space with certain properties to guarantee that additional online multiscale basis function will decrease the error. This error decrease is independent of physical parameters, such as the contrast and multiple scales in the problem. The offline spaces are constructed using Generalized Multiscale Finite Element Methods (GMsFEM). We show that if one chooses a sufficient number of offline basis functions, one can guarantee that additional online multiscale basis functions will reduce the error independent of contrast. We note that the construction of online basis functions is motivated by the fact that the offline space construction does not take into account distant effects. Using the residual information, we can incorporate the distant information provided the offline approximation satisfies certain properties. In the paper, theoretical and numerical results are presented. Our numerical results show that if the offline space is sufficiently large (in terms of the dimension) such that the coarse space contains all multiscale spectral basis functions that correspond to small eigenvalues, then the error reduction by adding online multiscale basis function is independent of the contrast. We discuss various ways computing online multiscale basis functions which include a use of small dimensional offline spaces.

  13. Multiscale Modeling of Carbon Nanotube-Epoxy Nanocomposites

    Science.gov (United States)

    Fasanella, Nicholas A.

    Epoxy-composites are widely used in the aerospace industry. In order to improve upon stiffness and thermal conductivity; carbon nanotube additives to epoxies are being explored. This dissertation presents multiscale modeling techniques to study the engineering properties of single walled carbon nanotube (SWNT)-epoxy nanocomposites, consisting of pristine and covalently functionalized systems. Using Molecular Dynamics (MD), thermomechanical properties were calculated for a representative polymer unit cell. Finite Element (FE) and orientation distribution function (ODF) based methods were used in a multiscale framework to obtain macroscale properties. An epoxy network was built using the dendrimer growth approach. The epoxy model was verified by matching the experimental glass transition temperature, density, and dilatation. MD, via the constant valence force field (CVFF), was used to explore the mechanical and dilatometric effects of adding pristine and functionalized SWNTs to epoxy. Full stiffness matrices and linear coefficient of thermal expansion vectors were obtained. The Green-Kubo method was used to investigate the thermal conductivity as a function of temperature for the various nanocomposites. Inefficient phonon transport at the ends of nanotubes is an important factor in the thermal conductivity of the nanocomposites, and for this reason discontinuous nanotubes were modeled in addition to long nanotubes. To obtain continuum-scale elastic properties from the MD data, multiscale modeling was considered to give better control over the volume fraction of nanotubes, and investigate the effects of nanotube alignment. Two methods were considered; an FE based method, and an ODF based method. The FE method probabilistically assigned elastic properties of elements from the MD lattice results based on the desired volume fraction and alignment of the nanotubes. For the ODF method, a distribution function was generated based on the desired amount of nanotube alignment

  14. Multi-scale analysis of the effect of nano-filler particle diameter on the physical properties of CAD/CAM composite resin blocks.

    Science.gov (United States)

    Yamaguchi, Satoshi; Inoue, Sayuri; Sakai, Takahiko; Abe, Tomohiro; Kitagawa, Haruaki; Imazato, Satoshi

    2017-05-01

    The objective of this study was to assess the effect of silica nano-filler particle diameters in a computer-aided design/manufacturing (CAD/CAM) composite resin (CR) block on physical properties at the multi-scale in silico. CAD/CAM CR blocks were modeled, consisting of silica nano-filler particles (20, 40, 60, 80, and 100 nm) and matrix (Bis-GMA/TEGDMA), with filler volume contents of 55.161%. Calculation of Young's moduli and Poisson's ratios for the block at macro-scale were analyzed by homogenization. Macro-scale CAD/CAM CR blocks (3 × 3 × 3 mm) were modeled and compressive strengths were defined when the fracture loads exceeded 6075 N. MPS values of the nano-scale models were compared by localization analysis. As the filler size decreased, Young's moduli and compressive strength increased, while Poisson's ratios and MPS decreased. All parameters were significantly correlated with the diameters of the filler particles (Pearson's correlation test, r = -0.949, 0.943, -0.951, 0.976, p CAD/CAM CR blocks can be enhanced by loading silica nanofiller particles of smaller diameter. CAD/CAM CR blocks by using smaller silica nano-filler particles have a potential to increase fracture resistance.

  15. Novel multiscale modeling tool applied to Pseudomonas aeruginosa biofilm formation.

    Directory of Open Access Journals (Sweden)

    Matthew B Biggs

    Full Text Available Multiscale modeling is used to represent biological systems with increasing frequency and success. Multiscale models are often hybrids of different modeling frameworks and programming languages. We present the MATLAB-NetLogo extension (MatNet as a novel tool for multiscale modeling. We demonstrate the utility of the tool with a multiscale model of Pseudomonas aeruginosa biofilm formation that incorporates both an agent-based model (ABM and constraint-based metabolic modeling. The hybrid model correctly recapitulates oxygen-limited biofilm metabolic activity and predicts increased growth rate via anaerobic respiration with the addition of nitrate to the growth media. In addition, a genome-wide survey of metabolic mutants and biofilm formation exemplifies the powerful analyses that are enabled by this computational modeling tool.

  16. Novel multiscale modeling tool applied to Pseudomonas aeruginosa biofilm formation.

    Science.gov (United States)

    Biggs, Matthew B; Papin, Jason A

    2013-01-01

    Multiscale modeling is used to represent biological systems with increasing frequency and success. Multiscale models are often hybrids of different modeling frameworks and programming languages. We present the MATLAB-NetLogo extension (MatNet) as a novel tool for multiscale modeling. We demonstrate the utility of the tool with a multiscale model of Pseudomonas aeruginosa biofilm formation that incorporates both an agent-based model (ABM) and constraint-based metabolic modeling. The hybrid model correctly recapitulates oxygen-limited biofilm metabolic activity and predicts increased growth rate via anaerobic respiration with the addition of nitrate to the growth media. In addition, a genome-wide survey of metabolic mutants and biofilm formation exemplifies the powerful analyses that are enabled by this computational modeling tool.

  17. Multi-Scale Validation of a Nanodiamond Drug Delivery System and Multi-Scale Engineering Education

    Science.gov (United States)

    Schwalbe, Michelle Kristin

    2010-01-01

    This dissertation has two primary concerns: (i) evaluating the uncertainty and prediction capabilities of a nanodiamond drug delivery model using Bayesian calibration and bias correction, and (ii) determining conceptual difficulties of multi-scale analysis from an engineering education perspective. A Bayesian uncertainty quantification scheme…

  18. Multiscale modelling of nanostructures

    International Nuclear Information System (INIS)

    Vvedensky, Dimitri D

    2004-01-01

    Most materials phenomena are manifestations of processes that are operative over a vast range of length and time scales. A complete understanding of the behaviour of materials thereby requires theoretical and computational tools that span the atomic-scale detail of first-principles methods and the more coarse-grained description provided by continuum equations. Recent efforts have focused on combining traditional methodologies-density functional theory, molecular dynamics, Monte Carlo methods and continuum descriptions-within a unified multiscale framework. This review covers the techniques that have been developed to model various aspects of materials behaviour with the ultimate aim of systematically coupling the atomistic to the continuum descriptions. The approaches described typically have been motivated by particular applications but can often be applied in wider contexts. The self-assembly of quantum dot ensembles will be used as a case study for the issues that arise and the methods used for all nanostructures. Although quantum dots can be obtained with all the standard growth methods and for a variety of material systems, their appearance is a quite selective process, involving the competition between equilibrium and kinetic effects, and the interplay between atomistic and long-range interactions. Most theoretical models have addressed particular aspects of the ordering kinetics of quantum dot ensembles, with far fewer attempts at a comprehensive synthesis of this inherently multiscale phenomenon. We conclude with an assessment of the current status of multiscale modelling strategies and highlight the main outstanding issues. (topical review)

  19. Trajectory Based Traffic Analysis

    DEFF Research Database (Denmark)

    Krogh, Benjamin Bjerre; Andersen, Ove; Lewis-Kelham, Edwin

    2013-01-01

    We present the INTRA system for interactive path-based traffic analysis. The analyses are developed in collaboration with traffic researchers and provide novel insights into conditions such as congestion, travel-time, choice of route, and traffic-flow. INTRA supports interactive point-and-click a......We present the INTRA system for interactive path-based traffic analysis. The analyses are developed in collaboration with traffic researchers and provide novel insights into conditions such as congestion, travel-time, choice of route, and traffic-flow. INTRA supports interactive point......-and-click analysis, due to a novel and efficient indexing structure. With the web-site daisy.aau.dk/its/spqdemo/we will demonstrate several analyses, using a very large real-world data set consisting of 1.9 billion GPS records (1.5 million trajectories) recorded from more than 13000 vehicles, and touching most...

  20. Multiscale modelling of DNA mechanics

    International Nuclear Information System (INIS)

    Dršata, Tomáš; Lankaš, Filip

    2015-01-01

    Mechanical properties of DNA are important not only in a wide range of biological processes but also in the emerging field of DNA nanotechnology. We review some of the recent developments in modeling these properties, emphasizing the multiscale nature of the problem. Modern atomic resolution, explicit solvent molecular dynamics simulations have contributed to our understanding of DNA fine structure and conformational polymorphism. These simulations may serve as data sources to parameterize rigid base models which themselves have undergone major development. A consistent buildup of larger entities involving multiple rigid bases enables us to describe DNA at more global scales. Free energy methods to impose large strains on DNA, as well as bead models and other approaches, are also briefly discussed. (topical review)

  1. Drought impacts on vegetation dynamics in the Mediterranean based on remote sensing and multi-scale drought indices

    Science.gov (United States)

    Trigo, Ricardo; Gouveia, Celia M.; Beguería, Santiago; Vicente-Serrano, Sergio

    2015-04-01

    A number of recent studies have identified a significant increase in the frequency of drought events in the Mediterranean basin (e.g. Trigo et al., 2013, Vicente-Serrano et al., 2014). In the Mediterranean region, large drought episodes are responsible for the most negative impacts on the vegetation including significant losses of crop yield, increasing risk of forest fires (e.g. Gouveia et al., 2012) and even forest decline. The aim of the present work is to analyze in detail the impacts of drought episodes on vegetation in the Mediterranean basin behavior using NDVI data from (from GIMMS) for entire Mediterranean basin (1982-2006) and the multi-scale drought index (the Standardised Precipitation-Evapotranspiration Index (SPEI). Correlation maps between fields of monthly NDVI and SPEI for at different time scales (1-24 months) were computed in order to identify the regions and seasons most affected by droughts. Affected vegetation presents high spatial and seasonal variability, with a maximum in summer and a minimum in winter. During February 50% of the affected pixels corresponded to a time scale of 6 months, while in November the most frequent time scale corresponded to 3 months, representing more than 40% of the affected region. Around 20% of grid points corresponded to the longer time scales (18 and 24 months), persisting fairly constant along the year. In all seasons the wetter clusters present higher NDVI values which indicates that aridity holds a key role to explain the spatial differences in the NDVI values along the year. Despite the localization of these clusters in areas with higher values of monthly water balance, the strongest control of drought on vegetation activity are observed for the drier classes located over regions with smaller absolute values of water balance. Gouveia C.M., Bastos A., Trigo R.M., DaCamara C.C. (2012) "Drought impacts on vegetation in the pre and post-fire events over Iberian Peninsula". Natural Hazards and Earth System

  2. In Silico Oncology: Quantification of the In Vivo Antitumor Efficacy of Cisplatin-Based Doublet Therapy in Non-Small Cell Lung Cancer (NSCLC) through a Multiscale Mechanistic Model

    Science.gov (United States)

    Kolokotroni, Eleni; Dionysiou, Dimitra; Veith, Christian; Kim, Yoo-Jin; Franz, Astrid; Grgic, Aleksandar; Bohle, Rainer M.; Stamatakos, Georgios

    2016-01-01

    The 5-year survival of non-small cell lung cancer patients can be as low as 1% in advanced stages. For patients with resectable disease, the successful choice of preoperative chemotherapy is critical to eliminate micrometastasis and improve operability. In silico experimentations can suggest the optimal treatment protocol for each patient based on their own multiscale data. A determinant for reliable predictions is the a priori estimation of the drugs’ cytotoxic efficacy on cancer cells for a given treatment. In the present work a mechanistic model of cancer response to treatment is applied for the estimation of a plausible value range of the cell killing efficacy of various cisplatin-based doublet regimens. Among others, the model incorporates the cancer related mechanism of uncontrolled proliferation, population heterogeneity, hypoxia and treatment resistance. The methodology is based on the provision of tumor volumetric data at two time points, before and after or during treatment. It takes into account the effect of tumor microenvironment and cell repopulation on treatment outcome. A thorough sensitivity analysis based on one-factor-at-a-time and latin hypercube sampling/partial rank correlation coefficient approaches has established the volume growth rate and the growth fraction at diagnosis as key features for more accurate estimates. The methodology is applied on the retrospective data of thirteen patients with non-small cell lung cancer who received cisplatin in combination with gemcitabine, vinorelbine or docetaxel in the neoadjuvant context. The selection of model input values has been guided by a comprehensive literature survey on cancer-specific proliferation kinetics. The latin hypercube sampling has been recruited to compensate for patient-specific uncertainties. Concluding, the present work provides a quantitative framework for the estimation of the in-vivo cell-killing ability of various chemotherapies. Correlation studies of such estimates with

  3. In Silico Oncology: Quantification of the In Vivo Antitumor Efficacy of Cisplatin-Based Doublet Therapy in Non-Small Cell Lung Cancer (NSCLC through a Multiscale Mechanistic Model.

    Directory of Open Access Journals (Sweden)

    Eleni Kolokotroni

    2016-09-01

    Full Text Available The 5-year survival of non-small cell lung cancer patients can be as low as 1% in advanced stages. For patients with resectable disease, the successful choice of preoperative chemotherapy is critical to eliminate micrometastasis and improve operability. In silico experimentations can suggest the optimal treatment protocol for each patient based on their own multiscale data. A determinant for reliable predictions is the a priori estimation of the drugs' cytotoxic efficacy on cancer cells for a given treatment. In the present work a mechanistic model of cancer response to treatment is applied for the estimation of a plausible value range of the cell killing efficacy of various cisplatin-based doublet regimens. Among others, the model incorporates the cancer related mechanism of uncontrolled proliferation, population heterogeneity, hypoxia and treatment resistance. The methodology is based on the provision of tumor volumetric data at two time points, before and after or during treatment. It takes into account the effect of tumor microenvironment and cell repopulation on treatment outcome. A thorough sensitivity analysis based on one-factor-at-a-time and latin hypercube sampling/partial rank correlation coefficient approaches has established the volume growth rate and the growth fraction at diagnosis as key features for more accurate estimates. The methodology is applied on the retrospective data of thirteen patients with non-small cell lung cancer who received cisplatin in combination with gemcitabine, vinorelbine or docetaxel in the neoadjuvant context. The selection of model input values has been guided by a comprehensive literature survey on cancer-specific proliferation kinetics. The latin hypercube sampling has been recruited to compensate for patient-specific uncertainties. Concluding, the present work provides a quantitative framework for the estimation of the in-vivo cell-killing ability of various chemotherapies. Correlation studies of

  4. Computational design and multiscale modeling of a nanoactuator using DNA actuation

    International Nuclear Information System (INIS)

    Hamdi, Mustapha

    2009-01-01

    Developments in the field of nano-biodevices coupling nanostructures and biological components are of great interest in medical nanorobotics. As the fundamentals of bio/non-bio interaction processes are still poorly understood in the design of these devices, design tools and multiscale dynamics modeling approaches are necessary at the fabrication pre-project stage. This paper proposes a new concept of optimized carbon nanotube based servomotor design for drug delivery and biomolecular transport applications. The design of an encapsulated DNA-multi-walled carbon nanotube actuator is prototyped using multiscale modeling. The system is parametrized by using a quantum level approach and characterized by using a molecular dynamics simulation. Based on the analysis of the simulation results, a servo nanoactuator using ionic current feedback is simulated and analyzed for application as a drug delivery carrier.

  5. Multi Resolution In-Situ Testing and Multiscale Simulation for Creep Fatigue Damage Analysis of Alloy 617

    Energy Technology Data Exchange (ETDEWEB)

    Liu, Yongming [Arizona State Univ., Tempe, AZ (United States). School for Engineering of Matter, Transport and Energy; Oskay, Caglar [Vanderbilt Univ., Nashville, TN (United States). Dept. of Civil and Environmental Engineering

    2017-04-30

    This report outlines the research activities that were carried out for the integrated experimental and simulation investigation of creep-fatigue damage mechanism and life prediction of Nickel-based alloy, Inconel 617 at high temperatures (950° and 850°). First, a novel experimental design using a hybrid control technique is proposed. The newly developed experimental technique can generate different combinations of creep and fatigue damage by changing the experimental design parameters. Next, detailed imaging analysis and statistical data analysis are performed to quantify the failure mechanisms of the creep fatigue of alloy 617 at high temperatures. It is observed that the creep damage is directly associated with the internal voids at the grain boundaries and the fatigue damage is directly related to the surface cracking. It is also observed that the classical time fraction approach does not has a good correlation with the experimental observed damage features. An effective time fraction parameter is seen to have an excellent correlation with the material microstructural damage. Thus, a new empirical damage interaction diagram is proposed based on the experimental observations. Following this, a macro level viscoplastic model coupled with damage is developed to simulate the stress/strain response under creep fatigue loadings. A damage rate function based on the hysteresis energy and creep energy is proposed to capture the softening behavior of the material and a good correlation with life prediction and material hysteresis behavior is observed. The simulation work is extended to include the microstructural heterogeneity. A crystal plasticity finite element model considering isothermal and large deformation conditions at the microstructural scale has been developed for fatigue, creep-fatigue as well as creep deformation and rupture at high temperature. The model considers collective dislocation glide and climb of the grains and progressive damage accumulation of

  6. Measurement, modeling and perception of painted surfaces: A Multi-scale Analysis of the Touch-up Problem

    Science.gov (United States)

    Kalghatgi, Suparna Kishore

    Real-world surfaces typically have geometric features at a range of spatial scales. At the microscale, opaque surfaces are often characterized by bidirectional reflectance distribution functions (BRDF), which describes how a surface scatters incident light. At the mesoscale, surfaces often exhibit visible texture -- stochastic or patterned arrangements of geometric features that provide visual information about surface properties such as roughness, smoothness, softness, etc. These textures also affect how light is scattered by the surface, but the effects are at a different spatial scale than those captured by the BRDF. Through this research, we investigate how microscale and mesoscale surface properties interact to contribute to overall surface appearance. This behavior is also the cause of the well-known "touch-up problem" in the paint industry, where two regions coated with exactly the same paint, look different in color, gloss and/or texture because of differences in application methods. At first, samples were created by applying latex paint to standard wallboard surfaces. Two application methods- spraying and rolling were used. The BRDF and texture properties of the samples were measured, which revealed differences at both the microscale and mesoscale. This data was then used as input for a physically-based image synthesis algorithm, to generate realistic images of the surfaces under different viewing conditions. In order to understand the factors that govern touch-up visibility, psychophysical tests were conducted using calibrated, digital photographs of the samples as stimuli. Images were presented in pairs and a two alternative forced choice design was used for the experiments. These judgments were then used as data for a Thurstonian scaling analysis to produce psychophysical scales of visibility, which helped determine the effect of paint formulation, application methods, and viewing and illumination conditions on the touch-up problem. The results can be

  7. Multiscale Modeling of Wear Degradation

    KAUST Repository

    Moraes, Alvaro; Ruggeri, Fabrizio; Tempone, Raul; Vilanova, Pedro

    2016-01-01

    Cylinder liners of diesel engines used for marine propulsion are naturally subjected to a wear process, and may fail when their wear exceeds a specified limit. Since failures often represent high economical costs, it is utterly important to predict and avoid them. In this work [4], we model the wear process using a pure jump process. Therefore, the inference goal here is to estimate: the number of possible jumps, its sizes, the coefficients and the shapes of the jump intensities. We propose a multiscale approach for the inference problem that can be seen as an indirect inference scheme. We found that using a Gaussian approximation based on moment expansions, it is possible to accurately estimate the jump intensities and the jump amplitudes. We obtained results equivalent to the state of the art but using a simpler and less expensive approach.

  8. Multiscale Modeling of Wear Degradation

    KAUST Repository

    Moraes, Alvaro; Ruggeri, Fabrizio; Tempone, Raul; Vilanova, Pedro

    2015-01-01

    Cylinder liners of diesel engines used for marine propulsion are naturally subjected to a wear process, and may fail when their wear exceeds a specified limit. Since failures often represent high economical costs, it is utterly important to predict and avoid them. In this work [4], we model the wear process using a pure jump process. Therefore, the inference goal here is to estimate: the number of possible jumps, its sizes, the coefficients and the shapes of the jump intensities. We propose a multiscale approach for the inference problem that can be seen as an indirect inference scheme. We found that using a Gaussian approximation based on moment expansions, it is possible to accurately estimate the jump intensities and the jump amplitudes. We obtained results equivalent to the state of the art but using a simpler and less expensive approach.

  9. Multiscale Modeling of Wear Degradation

    KAUST Repository

    Moraes, Alvaro

    2015-01-07

    Cylinder liners of diesel engines used for marine propulsion are naturally subjected to a wear process, and may fail when their wear exceeds a specified limit. Since failures often represent high economical costs, it is utterly important to predict and avoid them. In this work [4], we model the wear process using a pure jump process. Therefore, the inference goal here is to estimate: the number of possible jumps, its sizes, the coefficients and the shapes of the jump intensities. We propose a multiscale approach for the inference problem that can be seen as an indirect inference scheme. We found that using a Gaussian approximation based on moment expansions, it is possible to accurately estimate the jump intensities and the jump amplitudes. We obtained results equivalent to the state of the art but using a simpler and less expensive approach.

  10. Multiscale Modeling of Wear Degradation

    KAUST Repository

    Moraes, Alvaro

    2014-01-06

    Cylinder liners of diesel engines used for marine propulsion are naturally subjected to a wear process, and may fail when their wear exceeds a specified limit. Since failures often represent high economical costs, it is utterly important to predict and avoid them. In this work [4], we model the wear process using a pure jump process. Therefore, the inference goal here is to estimate: the number of possible jumps, its sizes, the coefficients and the shapes of the jump intensities. We propose a multiscale approach for the inference problem that can be seen as an indirect inference scheme. We found that using a Gaussian approximation based on moment expansions, it is possible to accurately estimate the jump intensities and the jump amplitudes. We obtained results equivalent to the state of the art but using a simpler and less expensive approach.

  11. Multiscale Modeling of Wear Degradation

    KAUST Repository

    Moraes, Alvaro

    2016-01-06

    Cylinder liners of diesel engines used for marine propulsion are naturally subjected to a wear process, and may fail when their wear exceeds a specified limit. Since failures often represent high economical costs, it is utterly important to predict and avoid them. In this work [4], we model the wear process using a pure jump process. Therefore, the inference goal here is to estimate: the number of possible jumps, its sizes, the coefficients and the shapes of the jump intensities. We propose a multiscale