Modeling and Bayesian parameter estimation for shape memory alloy bending actuators
Crews, John H.; Smith, Ralph C.
2012-04-01
In this paper, we employ a homogenized energy model (HEM) for shape memory alloy (SMA) bending actuators. Additionally, we utilize a Bayesian method for quantifying parameter uncertainty. The system consists of a SMA wire attached to a flexible beam. As the actuator is heated, the beam bends, providing endoscopic motion. The model parameters are fit to experimental data using an ordinary least-squares approach. The uncertainty in the fit model parameters is then quantified using Markov Chain Monte Carlo (MCMC) methods. The MCMC algorithm provides bounds on the parameters, which will ultimately be used in robust control algorithms. One purpose of the paper is to test the feasibility of the Random Walk Metropolis algorithm, the MCMC method used here.
Comparison of Two Methods Used to Model Shape Parameters of Pareto Distributions
Liu, C.; Charpentier, R.R.; Su, J.
2011-01-01
Two methods are compared for estimating the shape parameters of Pareto field-size (or pool-size) distributions for petroleum resource assessment. Both methods assume mature exploration in which most of the larger fields have been discovered. Both methods use the sizes of larger discovered fields to estimate the numbers and sizes of smaller fields: (1) the tail-truncated method uses a plot of field size versus size rank, and (2) the log-geometric method uses data binned in field-size classes and the ratios of adjacent bin counts. Simulation experiments were conducted using discovered oil and gas pool-size distributions from four petroleum systems in Alberta, Canada and using Pareto distributions generated by Monte Carlo simulation. The estimates of the shape parameters of the Pareto distributions, calculated by both the tail-truncated and log-geometric methods, generally stabilize where discovered pool numbers are greater than 100. However, with fewer than 100 discoveries, these estimates can vary greatly with each new discovery. The estimated shape parameters of the tail-truncated method are more stable and larger than those of the log-geometric method where the number of discovered pools is more than 100. Both methods, however, tend to underestimate the shape parameter. Monte Carlo simulation was also used to create sequences of discovered pool sizes by sampling from a Pareto distribution with a discovery process model using a defined exploration efficiency (in order to show how biased the sampling was in favor of larger fields being discovered first). A higher (more biased) exploration efficiency gives better estimates of the Pareto shape parameters. ?? 2011 International Association for Mathematical Geosciences.
SDSS-II: Determination of shape and color parameter coefficients for SALT-II fit model
Dojcsak, L.; Marriner, J.; /Fermilab
2010-08-01
In this study we look at the SALT-II model of Type IA supernova analysis, which determines the distance moduli based on the known absolute standard candle magnitude of the Type IA supernovae. We take a look at the determination of the shape and color parameter coefficients, {alpha} and {beta} respectively, in the SALT-II model with the intrinsic error that is determined from the data. Using the SNANA software package provided for the analysis of Type IA supernovae, we use a standard Monte Carlo simulation to generate data with known parameters to use as a tool for analyzing the trends in the model based on certain assumptions about the intrinsic error. In order to find the best standard candle model, we try to minimize the residuals on the Hubble diagram by calculating the correct shape and color parameter coefficients. We can estimate the magnitude of the intrinsic errors required to obtain results with {chi}{sup 2}/degree of freedom = 1. We can use the simulation to estimate the amount of color smearing as indicated by the data for our model. We find that the color smearing model works as a general estimate of the color smearing, and that we are able to use the RMS distribution in the variables as one method of estimating the correct intrinsic errors needed by the data to obtain the correct results for {alpha} and {beta}. We then apply the resultant intrinsic error matrix to the real data and show our results.
2011-11-01
Both cases are compared to experimental data at various temperatures, and the optimized model parameters are compared to the initial estimates. 1...applications. The super-elastic effect has been utilized in orthodontic wires, eye-glass frames, stents, and annuloplasty bands [23]. Applications using...should be addressed. E-mail:jhcrews@ncsu.edu 1 Report Documentation Page Form ApprovedOMB No. 0704-0188 Public reporting burden for the collection of
Ekinci, Yunus Levent; Balkaya, Çağlayan; Göktürkler, Gökhan; Turan, Seçil
2016-06-01
An efficient approach to estimate model parameters from residual gravity data based on differential evolution (DE), a stochastic vector-based metaheuristic algorithm, has been presented. We have showed the applicability and effectiveness of this algorithm on both synthetic and field anomalies. According to our knowledge, this is a first attempt of applying DE for the parameter estimations of residual gravity anomalies due to isolated causative sources embedded in the subsurface. The model parameters dealt with here are the amplitude coefficient (A), the depth and exact origin of causative source (zo and xo, respectively) and the shape factors (q and ƞ). The error energy maps generated for some parameter pairs have successfully revealed the nature of the parameter estimation problem under consideration. Noise-free and noisy synthetic single gravity anomalies have been evaluated with success via DE/best/1/bin, which is a widely used strategy in DE. Additionally some complicated gravity anomalies caused by multiple source bodies have been considered, and the results obtained have showed the efficiency of the algorithm. Then using the strategy applied in synthetic examples some field anomalies observed for various mineral explorations such as a chromite deposit (Camaguey district, Cuba), a manganese deposit (Nagpur, India) and a base metal sulphide deposit (Quebec, Canada) have been considered to estimate the model parameters of the ore bodies. Applications have exhibited that the obtained results such as the depths and shapes of the ore bodies are quite consistent with those published in the literature. Uncertainty in the solutions obtained from DE algorithm has been also investigated by Metropolis-Hastings (M-H) sampling algorithm based on simulated annealing without cooling schedule. Based on the resulting histogram reconstructions of both synthetic and field data examples the algorithm has provided reliable parameter estimations being within the sampling limits of
Wood, Simon N; Fasiolo, Matteo
2017-12-01
We consider the optimization of smoothing parameters and variance components in models with a regular log likelihood subject to quadratic penalization of the model coefficients, via a generalization of the method of Fellner (1986) and Schall (1991). In particular: (i) we generalize the original method to the case of penalties that are linear in several smoothing parameters, thereby covering the important cases of tensor product and adaptive smoothers; (ii) we show why the method's steps increase the restricted marginal likelihood of the model, that it tends to converge faster than the EM algorithm, or obvious accelerations of this, and investigate its relation to Newton optimization; (iii) we generalize the method to any Fisher regular likelihood. The method represents a considerable simplification over existing methods of estimating smoothing parameters in the context of regular likelihoods, without sacrificing generality: for example, it is only necessary to compute with the same first and second derivatives of the log-likelihood required for coefficient estimation, and not with the third or fourth order derivatives required by alternative approaches. Examples are provided which would have been impossible or impractical with pre-existing Fellner-Schall methods, along with an example of a Tweedie location, scale and shape model which would be a challenge for alternative methods, and a sparse additive modeling example where the method facilitates computational efficiency gains of several orders of magnitude. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. © 2017, The Authors Biometrics published by Wiley Periodicals, Inc. on behalf of International Biometric Society.
Ding, Y.; Arai, K.
2007-01-01
A method for estimation of forest parameters, species, tree shape, distance between canopies by means of Monte-Carlo based radiative transfer model with forestry surface model is proposed. The model is verified through experiments with the miniature model of forest, tree array of relatively small size of trees. Two types of miniature trees, ellipse-looking and cone-looking canopy are examined in the experiments. It is found that the proposed model and experimental results show a coincidence so that the proposed method is validated. It is also found that estimation of tree shape, trunk tree distance as well as distinction between deciduous or coniferous trees can be done with the proposed model. Furthermore, influences due to multiple reflections between trees and interaction between trees and under-laying grass are clarified with the proposed method
Jia, Bing
2014-03-01
A comb-shaped chaotic region has been simulated in multiple two-dimensional parameter spaces using the Hindmarsh—Rose (HR) neuron model in many recent studies, which can interpret almost all of the previously simulated bifurcation processes with chaos in neural firing patterns. In the present paper, a comb-shaped chaotic region in a two-dimensional parameter space was reproduced, which presented different processes of period-adding bifurcations with chaos with changing one parameter and fixed the other parameter at different levels. In the biological experiments, different period-adding bifurcation scenarios with chaos by decreasing the extra-cellular calcium concentration were observed from some neural pacemakers at different levels of extra-cellular 4-aminopyridine concentration and from other pacemakers at different levels of extra-cellular caesium concentration. By using the nonlinear time series analysis method, the deterministic dynamics of the experimental chaotic firings were investigated. The period-adding bifurcations with chaos observed in the experiments resembled those simulated in the comb-shaped chaotic region using the HR model. The experimental results show that period-adding bifurcations with chaos are preserved in different two-dimensional parameter spaces, which provides evidence of the existence of the comb-shaped chaotic region and a demonstration of the simulation results in different two-dimensional parameter spaces in the HR neuron model. The results also present relationships between different firing patterns in two-dimensional parameter spaces.
Jia Bing
2014-01-01
A comb-shaped chaotic region has been simulated in multiple two-dimensional parameter spaces using the Hindmarsh—Rose (HR) neuron model in many recent studies, which can interpret almost all of the previously simulated bifurcation processes with chaos in neural firing patterns. In the present paper, a comb-shaped chaotic region in a two-dimensional parameter space was reproduced, which presented different processes of period-adding bifurcations with chaos with changing one parameter and fixed the other parameter at different levels. In the biological experiments, different period-adding bifurcation scenarios with chaos by decreasing the extra-cellular calcium concentration were observed from some neural pacemakers at different levels of extra-cellular 4-aminopyridine concentration and from other pacemakers at different levels of extra-cellular caesium concentration. By using the nonlinear time series analysis method, the deterministic dynamics of the experimental chaotic firings were investigated. The period-adding bifurcations with chaos observed in the experiments resembled those simulated in the comb-shaped chaotic region using the HR model. The experimental results show that period-adding bifurcations with chaos are preserved in different two-dimensional parameter spaces, which provides evidence of the existence of the comb-shaped chaotic region and a demonstration of the simulation results in different two-dimensional parameter spaces in the HR neuron model. The results also present relationships between different firing patterns in two-dimensional parameter spaces
Size and shape dependent lattice parameters of metallic nanoparticles
Qi, W. H.; Wang, M. P.
2005-01-01
A model is developed to account for the size and shape dependent lattice parameters of metallic nanoparticles, where the particle shape difference is considered by introducing a shape factor. It is predicted that the lattice parameters of nanoparticles in several nanometers decrease with decreasing of the particle size, which is consistent with the corresponding experimental results. Furthermore, it is found that the particle shape can lead to 10% of the total lattice variation. The model is a continuous media model and can deal with the nanoparticles larger than 1 nm. Since the shape factor approaches to infinity for nanowires and nanofilms, therefore, the model cannot be generalized to the systems of nanowires and nanofilms. For the input parameters are physical constants of bulk materials, therefore, the present model may be used to predict the lattice variation of different metallic nanoparticles with different lattice structures
Rui Xu
2013-01-01
Full Text Available Minimum description length (MDL based group-wise registration was a state-of-the-art method to determine the corresponding points of 3D shapes for the construction of statistical shape models (SSMs. However, it suffered from the problem that determined corresponding points did not uniformly spread on original shapes, since corresponding points were obtained by uniformly sampling the aligned shape on the parameterized space of unit sphere. We proposed a particle-system based method to obtain adaptive sampling positions on the unit sphere to resolve this problem. Here, a set of particles was placed on the unit sphere to construct a particle system whose energy was related to the distortions of parameterized meshes. By minimizing this energy, each particle was moved on the unit sphere. When the system became steady, particles were treated as vertices to build a spherical mesh, which was then relaxed to slightly adjust vertices to obtain optimal sampling-positions. We used 47 cases of (left and right lungs and 50 cases of livers, (left and right kidneys, and spleens for evaluations. Experiments showed that the proposed method was able to resolve the problem of the original MDL method, and the proposed method performed better in the generalization and specificity tests.
Issues in Biological Shape Modelling
Hilger, Klaus Baggesen
This talk reflects parts of the current research at informatics and Mathematical Modelling at the Technical University of Denmark within biological shape modelling. We illustrate a series of generalizations, modifications, and applications of the elements of constructing models of shape or appear......This talk reflects parts of the current research at informatics and Mathematical Modelling at the Technical University of Denmark within biological shape modelling. We illustrate a series of generalizations, modifications, and applications of the elements of constructing models of shape...
Cosmological parameters from large scale structure - geometric versus shape information
Hamann, Jan; Lesgourgues, Julien; Rampf, Cornelius; Wong, Yvonne Y Y
2010-01-01
The matter power spectrum as derived from large scale structure (LSS) surveys contains two important and distinct pieces of information: an overall smooth shape and the imprint of baryon acoustic oscillations (BAO). We investigate the separate impact of these two types of information on cosmological parameter estimation, and show that for the simplest cosmological models, the broad-band shape information currently contained in the SDSS DR7 halo power spectrum (HPS) is by far superseded by geometric information derived from the baryonic features. An immediate corollary is that contrary to popular beliefs, the upper limit on the neutrino mass m_\
Ibsen, Lars Bo; Liingaard, M.
2006-12-15
A lumped-parameter model represents the frequency dependent soil-structure interaction of a massless foundation placed on or embedded into an unbounded soil domain. In this technical report the steps of establishing a lumped-parameter model are presented. Following sections are included in this report: Static and dynamic formulation, Simple lumped-parameter models and Advanced lumped-parameter models. (au)
Liu, Jiamin; Udupa, Jayaram K
2009-04-01
Active shape models (ASM) are widely employed for recognizing anatomic structures and for delineating them in medical images. In this paper, a novel strategy called oriented active shape models (OASM) is presented in an attempt to overcome the following five limitations of ASM: 1) lower delineation accuracy, 2) the requirement of a large number of landmarks, 3) sensitivity to search range, 4) sensitivity to initialization, and 5) inability to fully exploit the specific information present in the given image to be segmented. OASM effectively combines the rich statistical shape information embodied in ASM with the boundary orientedness property and the globally optimal delineation capability of the live wire methodology of boundary segmentation. The latter characteristics allow live wire to effectively separate an object boundary from other nonobject boundaries with similar properties especially when they come very close in the image domain. The approach leads to a two-level dynamic programming method, wherein the first level corresponds to boundary recognition and the second level corresponds to boundary delineation, and to an effective automatic initialization method. The method outputs a globally optimal boundary that agrees with the shape model if the recognition step is successful in bringing the model close to the boundary in the image. Extensive evaluation experiments have been conducted by utilizing 40 image (magnetic resonance and computed tomography) data sets in each of five different application areas for segmenting breast, liver, bones of the foot, and cervical vertebrae of the spine. Comparisons are made between OASM and ASM based on precision, accuracy, and efficiency of segmentation. Accuracy is assessed using both region-based false positive and false negative measures and boundary-based distance measures. The results indicate the following: 1) The accuracy of segmentation via OASM is considerably better than that of ASM; 2) The number of landmarks
Thermomechanical macroscopic model of shape memory alloys
Volkov, A.E.; Sakharov, V.Yu.
2003-01-01
The phenomenological macroscopic model of the mechanical behaviour of the titanium nickelide-type shape memory alloys is proposed. The model contains as a parameter the average phase shear deformation accompanying the martensite formation. It makes i possible to describe correctly a number of functional properties of the shape memory alloys, in particular, the pseudoelasticity ferroplasticity, plasticity transformation and shape memory effects in the stressed and unstressed samples [ru
Shape parameters measurement of ultralight mirrors
Pech, Miroslav; Mandát, Dušan; Hrabovský, Miroslav; Palatka, Miroslav; Schovánek, Petr
2010-01-01
Roč. 121, č. 20 (2010), s. 1881-1884 ISSN 0030-4026 R&D Projects: GA MŠk(CZ) 1M06002; GA AV ČR KAN301370701 Institutional research plan: CEZ:AV0Z10100522 Keywords : Hartmann test * roughness * scattering * BRDF * mirror shape Subject RIV: BH - Optics, Masers, Lasers Impact factor: 0.454, year: 2010
El-Abiad, N.M.; Lotfi, S.A.; El Hadary, A.A.; Nagi, G.A.
2010-01-01
A study of solid tumor growth retardation by impaling the pyramid energy radiation in a pyramidal model shape was carried out. The great Pyramid of Egypt has evoked a keen interest since 1920, both for its architectural, marvel and mystical significance. Its strange thing (via shaping of razers, longer shelf life of vegetables, alerted states of consciousnesses, sleeping in hum and, wound healing). Power energy radiations are said to occur within a pyramid constructed in the exact geometric properties of Giza pyramid. The effect of housing in two different pyramidal shapes on cancer growth and some blood physiological indices in mice infected with cancer were observed. The results obtained that housing in pyramid shape cage significantly reduced the development of cancer, significant increase in liver enzymes activity and α feto proteins, however, no effect was observed in levels of thyroid hormones concentration when compared with their matched value in ordinary 2 inverted pyramid cages. It could be concluded that the radiation energy of pyramidal shapes might improve certain biochemical and physiological indices leading to tumor growth retardation
Rapid estimation of high-parameter auditory-filter shapes
Shen, Yi; Sivakumar, Rajeswari; Richards, Virginia M.
2014-01-01
A Bayesian adaptive procedure, the quick-auditory-filter (qAF) procedure, was used to estimate auditory-filter shapes that were asymmetric about their peaks. In three experiments, listeners who were naive to psychoacoustic experiments detected a fixed-level, pure-tone target presented with a spectrally notched noise masker. The qAF procedure adaptively manipulated the masker spectrum level and the position of the masker notch, which was optimized for the efficient estimation of the five parameters of an auditory-filter model. Experiment I demonstrated that the qAF procedure provided a convergent estimate of the auditory-filter shape at 2 kHz within 150 to 200 trials (approximately 15 min to complete) and, for a majority of listeners, excellent test-retest reliability. In experiment II, asymmetric auditory filters were estimated for target frequencies of 1 and 4 kHz and target levels of 30 and 50 dB sound pressure level. The estimated filter shapes were generally consistent with published norms, especially at the low target level. It is known that the auditory-filter estimates are narrower for forward masking than simultaneous masking due to peripheral suppression, a result replicated in experiment III using fewer than 200 qAF trials. PMID:25324086
Women in Shape Modeling Workshop
Tari, Sibel
2015-01-01
Presenting the latest research from the growing field of mathematical shape analysis, this volume is comprised of the collaborations of participants of the Women in Shape Modeling (WiSh) workshop, held at UCLA's Institute for Pure and Applied Mathematics in July 2013. Topics include: Simultaneous spectral and spatial analysis of shape Dimensionality reduction and visualization of data in tree-spaces, such as classes of anatomical trees like airways and blood vessels Geometric shape segmentation, exploring shape segmentation from a Gestalt perspective, using information from the Blum medial axis of edge fragments in an image Representing and editing self-similar details on 3D shapes, studying shape deformation and editing techniques Several chapters in the book directly address the problem of continuous measures of context-dependent nearness and right shape models. Medical and biological applications have been a major source of motivation in shape research, and key topics are examined here in detail. All...
Statistical models of shape optimisation and evaluation
Davies, Rhodri; Taylor, Chris
2014-01-01
Deformable shape models have wide application in computer vision and biomedical image analysis. This book addresses a key issue in shape modelling: establishment of a meaningful correspondence between a set of shapes. Full implementation details are provided.
Defect Shape Recovering by Parameter Estimation Arising in Eddy Current Testing
Kojima, Fumio
2003-01-01
This paper is concerned with a computational method for recovering a crack shape of steam generator tubes of nuclear plants. Problems on the shape identification are discussed arising in the characterization of a structural defect in a conductor using data of eddy current inspection. A surface defect on the generator tube ran be detected as a probe impedance trajectory by scanning a pancake type coil. First, a mathematical model of the inspection process is derived from the Maxwell's equation. Second, the input and output relation is given by the approximate model by virtue of the hybrid use of the finite element and boundary element method. In that model, the crack shape is characterized by the unknown coefficients of the B-spline function which approximates the crack shape geometry. Finally, a parameter estimation technique is proposed for recovering the crack shape using data from the probe coil. The computational experiments were successfully tested with the laboratory data
Characterization of plasma parameters in shaped PBX-M discharges
England, A. C.; Bell, R. E.; Hirshman, S. P.; Kaita, R.; Kugel, H. W.; LeBlanc, B. L.; Lee, D. K.; Okabayashi, M.; Sun, Y.-C.; Takahashi, H.
1997-09-01
The Princeton Beta Experiment-Modification (PBX-M) was run both with elliptical and with bean-shaped plasmas during the 1992 and 1993 operating periods. Two deuterium-fed neutral beams were used for auxiliary heating, and during 1992 the average power was 0741-3335/39/9/008/img13. This will be referred to as the lower neutral-beam power (LNBP) period. As many as four deuterium-fed neutral beams were used during 1993, and the average power was 0741-3335/39/9/008/img14. This will be referred to as the medium neutral-beam power (MNBP) period. The neutron source strength, Sn, showed a scaling with injected power 0741-3335/39/9/008/img15, 0741-3335/39/9/008/img16 for both the LMBP and MNBP periods. A much wider range of shaping parameters was studied during the MNBP as compared with the LNBP period. A weak positive dependence on bean shaping was observed for the LNBP, and a stronger positive dependence on shaping was observed for MNBP, viz 0741-3335/39/9/008/img17. High values of Sn were obtained in bean-shaped plasmas for the highest values of 0741-3335/39/9/008/img18 at 0741-3335/39/9/008/img19 for the LNBP. For the MNBP the highest values of Sn and stored energy were obtained at 0741-3335/39/9/008/img19, and the highest values of 0741-3335/39/9/008/img18 were obtained at 0741-3335/39/9/008/img22. The achievement of high Sn is aided by high neutral-beam power, high toroidal field, strong shaping, high electron temperature, and broad profiles. The achievement of high 0741-3335/39/9/008/img18 is aided by low toroidal field, high density, less shaping, broad profiles, and access to the H-mode, viz 0741-3335/39/9/008/img24. The achievement of high 0741-3335/39/9/008/img25 is aided by strong shaping, high density, broad profiles, and access to the H-mode, viz 0741-3335/39/9/008/img26. Some comparisons with the previous higher neutral-beam (HNBP) period in 1989 are also made.
Parameter assessment for virtual Stackelberg game in aerodynamic shape optimization
Wang, Jing; Xie, Fangfang; Zheng, Yao; Zhang, Jifa
2018-05-01
In this paper, parametric studies of virtual Stackelberg game (VSG) are conducted to assess the impact of critical parameters on aerodynamic shape optimization, including design cycle, split of design variables and role assignment. Typical numerical cases, including the inverse design and drag reduction design of airfoil, have been carried out. The numerical results confirm the effectiveness and efficiency of VSG. Furthermore, the most significant parameters are identified, e.g. the increase of design cycle can improve the optimization results but it will also add computational burden. These studies will maximize the productivity of the effort in aerodynamic optimization for more complicated engineering problems, such as the multi-element airfoil and wing-body configurations.
ESTIMATION OF HUMAN BODY SHAPE PARAMETERS USING MICROSOFT KINECTSENCOR
D. M. Vasilkov
2017-01-01
Full Text Available In the paper a human body shape estimation technology based on scan data acquired from sensor controller Microsoft Kinect is described. This device includes an RGB camera and a depth sensor that provides, for each pixel of the image,a distance from the camera focus to the object. A scan session produces a triangulated high-density surface noised with oscillations, isolated fragments and holes. When scanning a human, additional noise comes from garment folds and wrinkles. An algorithm of creating a sparse and regular 3D human body model (avatar free of these defects, which approximates shape, posture and basic metrics of the scanned body is proposed. This solution finds application in individual clothing industry and computer games, as well.
A statistical model for mapping morphological shape
Li Jiahan
2010-07-01
Full Text Available Abstract Background Living things come in all shapes and sizes, from bacteria, plants, and animals to humans. Knowledge about the genetic mechanisms for biological shape has far-reaching implications for a range spectrum of scientific disciplines including anthropology, agriculture, developmental biology, evolution and biomedicine. Results We derived a statistical model for mapping specific genes or quantitative trait loci (QTLs that control morphological shape. The model was formulated within the mixture framework, in which different types of shape are thought to result from genotypic discrepancies at a QTL. The EM algorithm was implemented to estimate QTL genotype-specific shapes based on a shape correspondence analysis. Computer simulation was used to investigate the statistical property of the model. Conclusion By identifying specific QTLs for morphological shape, the model developed will help to ask, disseminate and address many major integrative biological and genetic questions and challenges in the genetic control of biological shape and function.
Simple Parametric Model for Airfoil Shape Description
Ziemkiewicz, David
2017-12-01
We show a simple, analytic equation describing a class of two-dimensional shapes well suited for representation of aircraft airfoil profiles. Our goal was to create a description characterized by a small number of parameters with easily understandable meaning, providing a tool to alter the shape with optimization procedures as well as manual tweaks by the designer. The generated shapes are well suited for numerical analysis with 2D flow solving software such as XFOIL.
Shaping asteroid models using genetic evolution (SAGE)
Bartczak, P.; Dudziński, G.
2018-02-01
In this work, we present SAGE (shaping asteroid models using genetic evolution), an asteroid modelling algorithm based solely on photometric lightcurve data. It produces non-convex shapes, orientations of the rotation axes and rotational periods of asteroids. The main concept behind a genetic evolution algorithm is to produce random populations of shapes and spin-axis orientations by mutating a seed shape and iterating the process until it converges to a stable global minimum. We tested SAGE on five artificial shapes. We also modelled asteroids 433 Eros and 9 Metis, since ground truth observations for them exist, allowing us to validate the models. We compared the derived shape of Eros with the NEAR Shoemaker model and that of Metis with adaptive optics and stellar occultation observations since other models from various inversion methods were available for Metis.
Demeester, Kelly; van Wieringen, Astrid; Hendrickx, Jan-jaap; Topsakal, Vedat; Huyghe, Jeroen; Fransen, Erik; Van Laer, Lut; Van Camp, Guy; Van de Heyning, Paul
2010-06-14
This study describes the heritability of audiometric shape parameters and the familial aggregation of different types of presbycusis in a healthy, otologically screened population between 50 and 75 years old. About 342 siblings of 64 families (average family-size: 5.3) were recruited through population registries. Audiometric shape was mathematically quantified by objective parameters developed to measure size, slope, concavity, percentage of frequency-dependent and frequency-independent hearing loss and Bulge Depth. The heritability of each parameter was calculated using a variance components model. Logistic regression models were used to estimate the odds ratios (ORs). Estimates of sibling recurrence risk ratios (lambda(s)) are also provided. Heritability estimates were generally higher compared to previous studies. ORs and lambda(s) for the parameters Total Hearing Loss (size), Uniform Hearing Loss (percentage of frequency-dependent hearing loss) and Bulge Depth suggest a higher heredity for severe types of presbycusis compared to moderate or mild types. Our results suggest that the separation of the parameter 'Total Hearing Loss' into the two parameters 'Uniform Hearing Loss' and 'Non-uniform Hearing Loss' could lead to the discovery of different genetic subtypes of presbycusis. The parameter 'Bulge Depth', instead of 'Concavity', seemed to be an important parameter for classifying subjects into 'susceptible' or 'resistant' to societal or intensive environmental exposure. 2010 Elsevier B.V. All rights reserved.
Ragulina, Galina; Reitan, Trond
2016-04-01
Assessing the probability of extreme precipitation events is of great importance in civil planning. This requires understanding of how return values change with different return periods, which is essentially described by the Generalized Extreme Value distribution's shape parameter. Some works in the field have suggested a constant shape parameter, while our analysis indicates a non-universal value. We first re-analyse an older precipitation dataset (169 stations) extended by Norwegian data (71 stations). We show that while each set seems to have a constant shape parameter, it differs between the two datasets, indicating regional differences. For a more comprehensive analysis of spatial effects, we examine a global dataset (1495 stations). We provide shape parameter maps for two models. We find clear evidence for the shape parameter being dependent on elevation while the effect of latitude remains uncertain. Our results confirm an explanation in terms of dominating precipitation systems based on a proxy derived from the Köppen-Geiger climate classification.
Objective models of compressed breast shapes undergoing mammography
Feng, Steve Si Jia; Patel, Bhavika; Sechopoulos, Ioannis
2013-01-01
Purpose: To develop models of compressed breasts undergoing mammography based on objective analysis, that are capable of accurately representing breast shapes in acquired clinical images and generating new, clinically realistic shapes. Methods: An automated edge detection algorithm was used to catalogue the breast shapes of clinically acquired cranio-caudal (CC) and medio-lateral oblique (MLO) view mammograms from a large database of digital mammography images. Principal component analysis (PCA) was performed on these shapes to reduce the information contained within the shapes to a small number of linearly independent variables. The breast shape models, one of each view, were developed from the identified principal components, and their ability to reproduce the shape of breasts from an independent set of mammograms not used in the PCA, was assessed both visually and quantitatively by calculating the average distance error (ADE). Results: The PCA breast shape models of the CC and MLO mammographic views based on six principal components, in which 99.2% and 98.0%, respectively, of the total variance of the dataset is contained, were found to be able to reproduce breast shapes with strong fidelity (CC view mean ADE = 0.90 mm, MLO view mean ADE = 1.43 mm) and to generate new clinically realistic shapes. The PCA models based on fewer principal components were also successful, but to a lesser degree, as the two-component model exhibited a mean ADE = 2.99 mm for the CC view, and a mean ADE = 4.63 mm for the MLO view. The four-component models exhibited a mean ADE = 1.47 mm for the CC view and a mean ADE = 2.14 mm for the MLO view. Paired t-tests of the ADE values of each image between models showed that these differences were statistically significant (max p-value = 0.0247). Visual examination of modeled breast shapes confirmed these results. Histograms of the PCA parameters associated with the six principal components were fitted with Gaussian distributions. The six
Objective models of compressed breast shapes undergoing mammography
Feng, Steve Si Jia [Department of Biomedical Engineering, Georgia Institute of Technology and Emory University and Department of Radiology and Imaging Sciences, Emory University, 1701 Uppergate Drive Northeast, Suite 5018, Atlanta, Georgia 30322 (United States); Patel, Bhavika [Department of Radiology and Imaging Sciences, Emory University, 1701 Uppergate Drive Northeast, Suite 5018, Atlanta, Georgia 30322 (United States); Sechopoulos, Ioannis [Departments of Radiology and Imaging Sciences, Hematology and Medical Oncology and Winship Cancer Institute, Emory University, 1701 Uppergate Drive Northeast, Suite 5018, Atlanta, Georgia 30322 (United States)
2013-03-15
Purpose: To develop models of compressed breasts undergoing mammography based on objective analysis, that are capable of accurately representing breast shapes in acquired clinical images and generating new, clinically realistic shapes. Methods: An automated edge detection algorithm was used to catalogue the breast shapes of clinically acquired cranio-caudal (CC) and medio-lateral oblique (MLO) view mammograms from a large database of digital mammography images. Principal component analysis (PCA) was performed on these shapes to reduce the information contained within the shapes to a small number of linearly independent variables. The breast shape models, one of each view, were developed from the identified principal components, and their ability to reproduce the shape of breasts from an independent set of mammograms not used in the PCA, was assessed both visually and quantitatively by calculating the average distance error (ADE). Results: The PCA breast shape models of the CC and MLO mammographic views based on six principal components, in which 99.2% and 98.0%, respectively, of the total variance of the dataset is contained, were found to be able to reproduce breast shapes with strong fidelity (CC view mean ADE = 0.90 mm, MLO view mean ADE = 1.43 mm) and to generate new clinically realistic shapes. The PCA models based on fewer principal components were also successful, but to a lesser degree, as the two-component model exhibited a mean ADE = 2.99 mm for the CC view, and a mean ADE = 4.63 mm for the MLO view. The four-component models exhibited a mean ADE = 1.47 mm for the CC view and a mean ADE = 2.14 mm for the MLO view. Paired t-tests of the ADE values of each image between models showed that these differences were statistically significant (max p-value = 0.0247). Visual examination of modeled breast shapes confirmed these results. Histograms of the PCA parameters associated with the six principal components were fitted with Gaussian distributions. The six
Objective models of compressed breast shapes undergoing mammography
Feng, Steve Si Jia; Patel, Bhavika; Sechopoulos, Ioannis
2013-01-01
Purpose: To develop models of compressed breasts undergoing mammography based on objective analysis, that are capable of accurately representing breast shapes in acquired clinical images and generating new, clinically realistic shapes. Methods: An automated edge detection algorithm was used to catalogue the breast shapes of clinically acquired cranio-caudal (CC) and medio-lateral oblique (MLO) view mammograms from a large database of digital mammography images. Principal component analysis (PCA) was performed on these shapes to reduce the information contained within the shapes to a small number of linearly independent variables. The breast shape models, one of each view, were developed from the identified principal components, and their ability to reproduce the shape of breasts from an independent set of mammograms not used in the PCA, was assessed both visually and quantitatively by calculating the average distance error (ADE). Results: The PCA breast shape models of the CC and MLO mammographic views based on six principal components, in which 99.2% and 98.0%, respectively, of the total variance of the dataset is contained, were found to be able to reproduce breast shapes with strong fidelity (CC view mean ADE = 0.90 mm, MLO view mean ADE = 1.43 mm) and to generate new clinically realistic shapes. The PCA models based on fewer principal components were also successful, but to a lesser degree, as the two-component model exhibited a mean ADE = 2.99 mm for the CC view, and a mean ADE = 4.63 mm for the MLO view. The four-component models exhibited a mean ADE = 1.47 mm for the CC view and a mean ADE = 2.14 mm for the MLO view. Paired t-tests of the ADE values of each image between models showed that these differences were statistically significant (max p-value = 0.0247). Visual examination of modeled breast shapes confirmed these results. Histograms of the PCA parameters associated with the six principal components were fitted with Gaussian distributions. The six
Zhang, L.F.; Xie, M.; Tang, L.C.
2006-01-01
Estimation of the Weibull shape parameter is important in reliability engineering. However, commonly used methods such as the maximum likelihood estimation (MLE) and the least squares estimation (LSE) are known to be biased. Bias correction methods for MLE have been studied in the literature. This paper investigates the methods for bias correction when model parameters are estimated with LSE based on probability plot. Weibull probability plot is very simple and commonly used by practitioners and hence such a study is useful. The bias of the LS shape parameter estimator for multiple censored data is also examined. It is found that the bias can be modeled as the function of the sample size and the censoring level, and is mainly dependent on the latter. A simple bias function is introduced and bias correcting formulas are proposed for both complete and censored data. Simulation results are also presented. The bias correction methods proposed are very easy to use and they can typically reduce the bias of the LSE of the shape parameter to less than half percent
Influence of Welding Parameters on the Weld Pool Dimensions and Shape in a TIG Configuration
Marine Stadler
2017-04-01
Full Text Available The weld pool shape created by the plasma arc interaction on a workpiece depends on many geometrical and physical parameters and on the operating conditions. Theoretical models are developed in such a way as to predict and to characterize the material. However, these models first need to be validated. Experimental results are hence proposed with parametric studies. Nevertheless, the interaction time is often short and the weld pool shape evolution not presented. In this work, the experimental setup and the diagnostic methods characterizing the workpiece are presented. The weld pool shape was evaluated versus time according to several parameters such as the current intensity value, the distance between the two electrodes, the cathode tip angle or the plasma gas nature. The results show that the depth-to-width ratio alone is not enough to compare the impact of the parameters. The analysis points out the great influence of the current intensity on the increase of the width and depth compared to the influence of the value of the cathode tip angle. The rise of the arc length leads to an increase of the power through a higher arc voltage; nevertheless, for distances of three and five millimeters and a characteristic time of the welding process of one second, this parameter has a weak influence on the energy transferred. The use of helium leads to a bigger volume of the weld pool due to an increase of width and depth.
Quantification of parameter uncertainty for robust control of shape memory alloy bending actuators
Crews, John H; McMahan, Jerry A; Smith, Ralph C; Hannen, Jennifer C
2013-01-01
In this paper, we employ Bayesian parameter estimation techniques to derive gains for robust control of smart materials. Specifically, we demonstrate the feasibility of utilizing parameter uncertainty estimation provided by Markov chain Monte Carlo (MCMC) methods to determine controller gains for a shape memory alloy bending actuator. We treat the parameters in the equations governing the actuator’s temperature dynamics as uncertain and use the MCMC method to construct the probability densities for these parameters. The densities are then used to derive parameter bounds for robust control algorithms. For illustrative purposes, we construct a sliding mode controller based on the homogenized energy model and experimentally compare its performance to a proportional-integral controller. While sliding mode control is used here, the techniques described in this paper provide a useful starting point for many robust control algorithms. (paper)
Modelling the shape hierarchy for visually guided grasping
Omid eRezai
2014-10-01
Full Text Available The monkey anterior intraparietal area (AIP encodes visual information about three-dimensional object shape that is used to shape the hand for grasping. We modelled shape tuning in visual AIP neurons and its relationship with curvature and gradient information from the caudal intraparietal area (CIP. The main goal was to gain insight into the kinds of shape parameterizations that can account for AIP tuning and that are consistent with both the inputs to AIP and the role of AIP in grasping. We first experimented with superquadric shape parameters. We considered superquadrics because they occupy a role in robotics that is similar to AIP, in that superquadric fits are derived from visual input and used for grasp planning. We also experimented with an alternative shape parameterization that was based on an Isomap dimension reduction of spatial derivatives of depth (i.e. distance from the observer to the object surface. We considered an Isomap-based model because its parameters lacked discontinuities between similar shapes. When we matched the dimension of the Isomap to the number of superquadric parameters, the superquadric model fit the AIP data somewhat more closely. However, higher-dimensional Isomaps provided excellent fits. Also, we found that the Isomap parameters could be approximated much more accurately than superquadric parameters by feedforward neural networks with CIP-like inputs. We conclude that Isomaps, or perhaps alternative dimension reductions of visual inputs to AIP, provide a promising model of AIP electrophysiology data. However (in contrast with superquadrics further work is needed to test whether such shape parameterizations actually provide an effective basis for grasp control.
Modeling the variability of shapes of a human placenta.
Yampolsky, M; Salafia, C M; Shlakhter, O; Haas, D; Eucker, B; Thorp, J
2008-09-01
Placentas are generally round/oval in shape, but "irregular" shapes are common. In the Collaborative Perinatal Project data, irregular shapes were associated with lower birth weight for placental weight, suggesting variably shaped placentas have altered function. (I) Using a 3D one-parameter model of placental vascular growth based on Diffusion Limited Aggregation (an accepted model for generating highly branched fractals), models were run with a branching density growth parameter either fixed or perturbed at either 5-7% or 50% of model growth. (II) In a data set with detailed measures of 1207 placental perimeters, radial standard deviations of placental shapes were calculated from the umbilical cord insertion, and from the centroid of the shape (a biologically arbitrary point). These two were compared to the difference between the observed scaling exponent and the Kleiber scaling exponent (0.75), considered optimal for vascular fractal transport systems. Spearman's rank correlation considered pcentroid) was associated with differences from the Kleiber exponent (p=0.006). A dynamical DLA model recapitulates multilobate and "star" placental shapes via changing fractal branching density. We suggest that (1) irregular placental outlines reflect deformation of the underlying placental fractal vascular network, (2) such irregularities in placental outline indicate sub-optimal branching structure of the vascular tree, and (3) this accounts for the lower birth weight observed in non-round/oval placentas in the Collaborative Perinatal Project.
Photovoltaic module parameters acquisition model
Cibira, Gabriel, E-mail: cibira@lm.uniza.sk; Koščová, Marcela, E-mail: mkoscova@lm.uniza.sk
2014-09-01
Highlights: • Photovoltaic five-parameter model is proposed using Matlab{sup ®} and Simulink. • The model acquisits input sparse data matrix from stigmatic measurement. • Computer simulations lead to continuous I–V and P–V characteristics. • Extrapolated I–V and P–V characteristics are in hand. • The model allows us to predict photovoltaics exploitation in different conditions. - Abstract: This paper presents basic procedures for photovoltaic (PV) module parameters acquisition using MATLAB and Simulink modelling. In first step, MATLAB and Simulink theoretical model are set to calculate I–V and P–V characteristics for PV module based on equivalent electrical circuit. Then, limited I–V data string is obtained from examined PV module using standard measurement equipment at standard irradiation and temperature conditions and stated into MATLAB data matrix as a reference model. Next, the theoretical model is optimized to keep-up with the reference model and to learn its basic parameters relations, over sparse data matrix. Finally, PV module parameters are deliverable for acquisition at different realistic irradiation, temperature conditions as well as series resistance. Besides of output power characteristics and efficiency calculation for PV module or system, proposed model validates computing statistical deviation compared to reference model.
Photovoltaic module parameters acquisition model
Cibira, Gabriel; Koščová, Marcela
2014-01-01
Highlights: • Photovoltaic five-parameter model is proposed using Matlab ® and Simulink. • The model acquisits input sparse data matrix from stigmatic measurement. • Computer simulations lead to continuous I–V and P–V characteristics. • Extrapolated I–V and P–V characteristics are in hand. • The model allows us to predict photovoltaics exploitation in different conditions. - Abstract: This paper presents basic procedures for photovoltaic (PV) module parameters acquisition using MATLAB and Simulink modelling. In first step, MATLAB and Simulink theoretical model are set to calculate I–V and P–V characteristics for PV module based on equivalent electrical circuit. Then, limited I–V data string is obtained from examined PV module using standard measurement equipment at standard irradiation and temperature conditions and stated into MATLAB data matrix as a reference model. Next, the theoretical model is optimized to keep-up with the reference model and to learn its basic parameters relations, over sparse data matrix. Finally, PV module parameters are deliverable for acquisition at different realistic irradiation, temperature conditions as well as series resistance. Besides of output power characteristics and efficiency calculation for PV module or system, proposed model validates computing statistical deviation compared to reference model
Minimum Description Length Shape and Appearance Models
Thodberg, Hans Henrik
2003-01-01
The Minimum Description Length (MDL) approach to shape modelling is reviewed. It solves the point correspondence problem of selecting points on shapes defined as curves so that the points correspond across a data set. An efficient numerical implementation is presented and made available as open s...
Dynamics in the Parameter Space of a Neuron Model
Paulo, C. Rech
2012-06-01
Some two-dimensional parameter-space diagrams are numerically obtained by considering the largest Lyapunov exponent for a four-dimensional thirteen-parameter Hindmarsh—Rose neuron model. Several different parameter planes are considered, and it is shown that depending on the combination of parameters, a typical scenario can be preserved: for some choice of two parameters, the parameter plane presents a comb-shaped chaotic region embedded in a large periodic region. It is also shown that there exist regions close to these comb-shaped chaotic regions, separated by the comb teeth, organizing themselves in period-adding bifurcation cascades.
Statistical shape and appearance models of bones.
Sarkalkan, Nazli; Weinans, Harrie; Zadpoor, Amir A
2014-03-01
When applied to bones, statistical shape models (SSM) and statistical appearance models (SAM) respectively describe the mean shape and mean density distribution of bones within a certain population as well as the main modes of variations of shape and density distribution from their mean values. The availability of this quantitative information regarding the detailed anatomy of bones provides new opportunities for diagnosis, evaluation, and treatment of skeletal diseases. The potential of SSM and SAM has been recently recognized within the bone research community. For example, these models have been applied for studying the effects of bone shape on the etiology of osteoarthritis, improving the accuracy of clinical osteoporotic fracture prediction techniques, design of orthopedic implants, and surgery planning. This paper reviews the main concepts, methods, and applications of SSM and SAM as applied to bone. Copyright © 2013 Elsevier Inc. All rights reserved.
Shape descriptors for mode-shape recognition and model updating
Wang, W; Mottershead, J E; Mares, C
2009-01-01
The most widely used method for comparing mode shapes from finite elements and experimental measurements is the Modal Assurance Criterion (MAC), which returns a single numerical value and carries no explicit information on shape features. New techniques, based on image processing (IP) and pattern recognition (PR) are described in this paper. The Zernike moment descriptor (ZMD), Fourier descriptor (FD), and wavelet descriptor (WD), presented in this article, are the most popular shape descriptors having properties that include efficiency of expression, robustness to noise, invariance to geometric transformation and rotation, separation of local and global shape features and computational efficiency. The comparison of mode shapes is readily achieved by assembling the shape features of each mode shape into multi-dimensional shape feature vectors (SFVs) and determining the distances separating them.
Diamond-shaped electromagnetic transparent devices with homogeneous material parameters
Li Tinghua; Huang Ming; Yang Jingjing; Yu Jiang; Lan Yaozhong
2011-01-01
Based on the linear coordinate transformation method, two-dimensional and three-dimensional electromagnetic transparent devices with diamond shape composed of homogeneous and non-singular materials are proposed in this paper. The permittivity and permeability tensors of the transparent devices are derived. The performance and scattering properties of the transparent devices are confirmed by a full-wave simulation. It can physically protect electric devices such as an antenna and a radar station inside, without sacrificing their performance. This work represents important progress towards the practical realization of metamaterial-assisted transparent devices and expands the application of transformation optics.
Conditional shape models for cardiac motion estimation
Metz, Coert; Baka, Nora; Kirisli, Hortense
2010-01-01
We propose a conditional statistical shape model to predict patient specific cardiac motion from the 3D end-diastolic CTA scan. The model is built from 4D CTA sequences by combining atlas based segmentation and 4D registration. Cardiac motion estimation is, for example, relevant in the dynamic...
Parameter studies on the effect of pulse shape on the dynamic plastic deformation of a hexagon
Youngdahl, C.K.
1973-10-01
Results of a parameter study on the dynamic plastic response of a hexagonal subassembly duct subjected to an internal pressure pulse of arbitrary shape are presented. Plastic distortion of the cross section and large-deformation geometric effects that result in redistribution of the internal forces between bending and membrane stresses in the hexagon wall are included in the analytical model. Correlation procedures are established for relating permanent plastic deformation to simple properties of the pressure pulse, for both the small- and large-deformation ranges. Characteristic response times are determined, and the dynamic load factor for large-deformation plastic response is computed
Calibration of discrete element model parameters: soybeans
Ghodki, Bhupendra M.; Patel, Manish; Namdeo, Rohit; Carpenter, Gopal
2018-05-01
Discrete element method (DEM) simulations are broadly used to get an insight of flow characteristics of granular materials in complex particulate systems. DEM input parameters for a model are the critical prerequisite for an efficient simulation. Thus, the present investigation aims to determine DEM input parameters for Hertz-Mindlin model using soybeans as a granular material. To achieve this aim, widely acceptable calibration approach was used having standard box-type apparatus. Further, qualitative and quantitative findings such as particle profile, height of kernels retaining the acrylic wall, and angle of repose of experiments and numerical simulations were compared to get the parameters. The calibrated set of DEM input parameters includes the following (a) material properties: particle geometric mean diameter (6.24 mm); spherical shape; particle density (1220 kg m^{-3} ), and (b) interaction parameters such as particle-particle: coefficient of restitution (0.17); coefficient of static friction (0.26); coefficient of rolling friction (0.08), and particle-wall: coefficient of restitution (0.35); coefficient of static friction (0.30); coefficient of rolling friction (0.08). The results may adequately be used to simulate particle scale mechanics (grain commingling, flow/motion, forces, etc) of soybeans in post-harvest machinery and devices.
Photometry and shape modeling of Mars crosser asteroid (1011 Laodamia
Apostolovska G.
2014-01-01
Full Text Available An analysis of photometric observations of Mars crosser asteroid 1011 Laodamia conducted at Bulgarian National Astronomical Observatory Rozhen over a twelve year interval (2002, 2003, 2004, 2006, 2007, 2008, 2011, 2012 and 2013 is made. Based on the obtained lightcurves the spin vector, sense of rotation, and preliminary shape model of (1011 Laodamia have been determined using the lightcurve inversion method. The aim of this investigation is to increase the set of asteroids with known spin and shape parameters and to contribute in improving the model in combination with other techniques and sparse data produced by photometric asteroid surveys such as Pan-STARRS or GAIA.
Zeng, Hongtao; Lan, Tian; Chen, Qiming
2016-01-01
Two lifetime distributions derived from Perks' mortality rate function, one with 4 parameters and the other with 5 parameters, for the modeling of bathtub-shaped failure rates are proposed in this paper. The Perks' mortality/failure rate functions have historically been used for human life modeling in life insurance industry. Although this distribution is no longer used in insurance industry, considering many nice and some unique features of this function, it is necessary to revisit it and introduce it to the reliability community. The parameters of the distributions can control the scale, shape, and location of the PDF. The 4-parameter distribution can be used to model the bathtub failure rate. This model is applied to three previously published groups of lifetime data. This study shows they fit very well. The 5-parameter version can potentially model constant hazard rates of the later life of some devices in addition to the good features of 4-parameter version. Both the 4 and 5-parameter versions have closed form PDF and CDF. The truncated distributions of both versions stay within the original distribution family with simple parameter transformation. This nice feature is normally considered to be only possessed by the simple exponential distribution - Highlights: • Two new distributions are proposed to model bathtub shaped hazard rate. • Derive the close-form PDF, CDF and feature of scalability and truncatability. • Perks4 is verified to be good to model common bathtub shapes through comparison. • Perks5 has the potential to model the stabilization of hazard rate at later life.
Digital Modeling and Shaping of Design Practices
Reijonen, Satu
This paper focuses on the role of digital modeling in shaping coordinative practices between architects and energy engineers in construction design. The paper presents a case study of the use of an energy performance calculation programme, a numeric digital modeling tool, that not only enables...... coordination between the two communities but also shapes coordinative practices around the emerging building. The paper draws on two interlinked strands of literature that have engaged in the role of material artefacts in the social: the entanglement of technology in organizing and management (Orlikowski 2000......, 2010), and the socio-material constructivist studies of technology (Akrich 1992, Akrich et al. 2000, Latour 1991). The programme influences the coordinative practices in following ways: it shapes the modus of interaction between energy engineers and architects and enforces particular jurisdictional...
Effects of shape and stroke parameters on the propulsion performance of an axisymmetric swimmer.
Peng, Jifeng; Alben, Silas
2012-03-01
In nature, there exists a special group of aquatic animals which have an axisymmetric body and whose primary swimming mechanism is to use periodic body contractions to generate vortex rings in the surrounding fluid. Using jellyfish medusae as an example, this study develops a mathematical model of body kinematics of an axisymmetric swimmer and uses a computational approach to investigate the induced vortex wakes. Wake characteristics are identified for swimmers using jet propulsion and rowing, two mechanisms identified in previous studies of medusan propulsion. The parameter space of body kinematics is explored through four quantities: a measure of body shape, stroke amplitude, the ratio between body contraction duration and extension duration, and the pulsing frequency. The effects of these parameters on thrust, input power requirement and circulation production are quantified. Two metrics, cruising speed and energy cost of locomotion, are used to evaluate the propulsion performance. The study finds that a more prolate-shaped swimmer with larger stroke amplitudes is able to swim faster, but its cost of locomotion is also higher. In contrast, a more oblate-shaped swimmer with smaller stroke amplitudes uses less energy for its locomotion, but swims more slowly. Compared with symmetric strokes with equal durations of contraction and extension, faster bell contractions increase the swimming speed whereas faster bell extensions decrease it, but both require a larger energy input. This study shows that besides the well-studied correlations between medusan body shape and locomotion, stroke variables also affect the propulsion performance. It provides a framework for comparing the propulsion performance of axisymmetric swimmers based on their body kinematics when it is difficult to measure and analyze their wakes empirically. The knowledge from this study is also useful for the design of robotic swimmers that use axisymmetric body contractions for propulsion.
Effects of shape and stroke parameters on the propulsion performance of an axisymmetric swimmer
Peng Jifeng; Alben, Silas
2012-01-01
In nature, there exists a special group of aquatic animals which have an axisymmetric body and whose primary swimming mechanism is to use periodic body contractions to generate vortex rings in the surrounding fluid. Using jellyfish medusae as an example, this study develops a mathematical model of body kinematics of an axisymmetric swimmer and uses a computational approach to investigate the induced vortex wakes. Wake characteristics are identified for swimmers using jet propulsion and rowing, two mechanisms identified in previous studies of medusan propulsion. The parameter space of body kinematics is explored through four quantities: a measure of body shape, stroke amplitude, the ratio between body contraction duration and extension duration, and the pulsing frequency. The effects of these parameters on thrust, input power requirement and circulation production are quantified. Two metrics, cruising speed and energy cost of locomotion, are used to evaluate the propulsion performance. The study finds that a more prolate-shaped swimmer with larger stroke amplitudes is able to swim faster, but its cost of locomotion is also higher. In contrast, a more oblate-shaped swimmer with smaller stroke amplitudes uses less energy for its locomotion, but swims more slowly. Compared with symmetric strokes with equal durations of contraction and extension, faster bell contractions increase the swimming speed whereas faster bell extensions decrease it, but both require a larger energy input. This study shows that besides the well-studied correlations between medusan body shape and locomotion, stroke variables also affect the propulsion performance. It provides a framework for comparing the propulsion performance of axisymmetric swimmers based on their body kinematics when it is difficult to measure and analyze their wakes empirically. The knowledge from this study is also useful for the design of robotic swimmers that use axisymmetric body contractions for propulsion. (paper)
variation of some waste stabilization pond parameters with shape
solids, oxygen demand and nutrient environment. ... quality guidelines both at low cost and with ... are not the best option for less developed ... Many models by Polprasert and Others, 1983; ... quality, design and dynamic, temperature profile, .... The variance determination represents and includes all points in the curve.
Parameter optimization for surface flux transport models
Whitbread, T.; Yeates, A. R.; Muñoz-Jaramillo, A.; Petrie, G. J. D.
2017-11-01
Accurate prediction of solar activity calls for precise calibration of solar cycle models. Consequently we aim to find optimal parameters for models which describe the physical processes on the solar surface, which in turn act as proxies for what occurs in the interior and provide source terms for coronal models. We use a genetic algorithm to optimize surface flux transport models using National Solar Observatory (NSO) magnetogram data for Solar Cycle 23. This is applied to both a 1D model that inserts new magnetic flux in the form of idealized bipolar magnetic regions, and also to a 2D model that assimilates specific shapes of real active regions. The genetic algorithm searches for parameter sets (meridional flow speed and profile, supergranular diffusivity, initial magnetic field, and radial decay time) that produce the best fit between observed and simulated butterfly diagrams, weighted by a latitude-dependent error structure which reflects uncertainty in observations. Due to the easily adaptable nature of the 2D model, the optimization process is repeated for Cycles 21, 22, and 24 in order to analyse cycle-to-cycle variation of the optimal solution. We find that the ranges and optimal solutions for the various regimes are in reasonable agreement with results from the literature, both theoretical and observational. The optimal meridional flow profiles for each regime are almost entirely within observational bounds determined by magnetic feature tracking, with the 2D model being able to accommodate the mean observed profile more successfully. Differences between models appear to be important in deciding values for the diffusive and decay terms. In like fashion, differences in the behaviours of different solar cycles lead to contrasts in parameters defining the meridional flow and initial field strength.
Thermomechanical model for NiTi shape memory wires
Frost, M; Sedlák, P; Sippola, M; Šittner, P
2010-01-01
A simple one-dimensional rate-independent model is proposed. It is able to capture responses of a NiTi shape memory alloy wire element to mechanical and thermal loadings. Since the model takes into account martensitic phase transformation as well as deformation processes in the martensite, both shape memory effects and pseudoelasticity can be simulated. The model introduces non-hysteretic transformation strain. Particular attention was paid to description of partial loading cycles. By changing the input parameters the model can be adapted to various types of NiTi-based materials. The model was implemented in the finite element code Abaqus as a User routine and several simulations were performed to validate the implementation
Optimum design of forging process parameters and preform shape under uncertainties
Repalle, Jalaja; Grandhi, Ramana V.
2004-01-01
Forging is a highly complex non-linear process that is vulnerable to various uncertainties, such as variations in billet geometry, die temperature, material properties, workpiece and forging equipment positional errors and process parameters. A combination of these uncertainties could induce heavy manufacturing losses through premature die failure, final part geometric distortion and production risk. Identifying the sources of uncertainties, quantifying and controlling them will reduce risk in the manufacturing environment, which will minimize the overall cost of production. In this paper, various uncertainties that affect forging tool life and preform design are identified, and their cumulative effect on the forging process is evaluated. Since the forging process simulation is computationally intensive, the response surface approach is used to reduce time by establishing a relationship between the system performance and the critical process design parameters. Variability in system performance due to randomness in the parameters is computed by applying Monte Carlo Simulations (MCS) on generated Response Surface Models (RSM). Finally, a Robust Methodology is developed to optimize forging process parameters and preform shape. The developed method is demonstrated by applying it to an axisymmetric H-cross section disk forging to improve the product quality and robustness
Constitutive Models for Shape Memory Alloy Polycrystals
Comstock, R. J., Jr.; Somerday, M.; Wert, J. A.
1996-01-01
Shape memory alloys (SMA) exhibiting the superelastic or one-way effects can produce large recoverable strains upon application of a stress. In single crystals this stress and resulting strain are very orientation dependent. We show experimental stress/strain curves for a Ni-Al single crystal for various loading orientations. Also shown are model predictions; the open and closed circles indicate recoverable strains obtained at various stages in the transformation process. Because of the strong orientation dependence of shape memory properties, crystallographic texture can be expected to play an important role in the mechanical behavior of polycrystalline SMA. It is desirable to formulate a constitutive model to better understand and exploit the unique properties of SMA.
Jung, Uk Hee; Kim, Joon Hyung; Kim, Sung; Kim, Jin Hyuk; Choi, Young Seok
2016-01-01
Fans are representative turbo-machinery widely used for ventilation throughout the industrial world. Recently, as the importance of energy saving has been magnified with the fans, the demand for the fans with high efficiency and performance has been increasing. The representative method for enhancing the performance includes design optimization; in practice, fan performance can be improved by changing the shape parameters such as those of meridional plane, impeller, and diffuser. Before optimizing the efficient design, a process of screening to select important design parameters is essential. The present study aimed to analyze the effects of mixed-flow fans' shape parameters on fan performance (static pressure and fan static efficiency) and derive optimum models based on the results. In this study, the shape parameters considered in the impeller domain are as follows: tip clearance, number of blades, beta angle of Leading edge (LE) in the blade, and beta angle of Trailing edge (TE) in the blade. The shape parameters considered in the diffuser domain are as follows: meridional length of the Guide vane (GV), number of GV, beta angle of LE in the GV and beta angle of TE in the GV. The effects of individual shape parameters were analyzed using the CFD (Computational fluid dynamic) and DOE (Design of experiments) methods. The reliability of CFD was verified through the comparison between preliminary fan model's experiment results and CFD results, and screening processes were implemented through 24-1 fractional factorial design. From the analysis of DOE results, it could be seen that the tip clearance and the number of blades in the impeller domain greatly affected the fan performance, and the beta angle of TE at the GV in the diffuser domain greatly affected the fan performance. Finally, the optimum models with improved fan performance were created using linear regression equations derived from 24-1 fractional factorial design.
Ben-David, M.; Inberg, A.; Katzir, A.; Croitoru, N.
1999-01-01
The modification of the laser source beam quality is one of the important factors effect the delivery of laser radiation by a waveguide. In this paper the results of input radiation coupling, radius of bending, length, cross section diameter, waveguide internal wall roughness and coupling lens focal length influence on the beam shape delivered from the flexible hollow waveguides are presented. The conditions for which the beam shape is near to that of the source were found. A theoretical model for the radiation propagation gives quantitative representation of relation between attenuation, beam profile, divergence and above indicated parameters was developed. In this model was supposed that the guiding is produced by multiple incidences on a metal (silver) layer and a dielectric (silver iodine) over layer, by refraction and reflection. The propagation of the rays was calculated using the physical laws of the geometrical optics. For the scattering calculations a random distribution of roughness centers on dielectric layer surface was considered. It was also supposed that the value of the cross section internal diameter (ID=d) was much larger than the transmitted wavelength. The experimental results have shown that losses due to absorption of the propagated radiation in the guiding layers, mainly (AgI), generate satellites of the laser source delivered fundamental Gaussian beam. Increasing of the hollow waveguide internal diameter decreases the attenuation and increases the deviation of beam shape from Gaussian. Off center coupling produce decreasing of the fundamental mode height and generation of the coupled Gaussian beam satellites. The waveguide internal wall roughness produce losses of the coupled radiation and beam profile deviations from that of the laser source. A good correspondence between the theoretical and experimental results obtained
MODELING OF FUEL SPRAY CHARACTERISTICS AND DIESEL COMBUSTION CHAMBER PARAMETERS
G. M. Kukharonak
2011-01-01
Full Text Available The computer model for coordination of fuel spray characteristics with diesel combustion chamber parameters has been created in the paper. The model allows to observe fuel sprays develоpment in diesel cylinder at any moment of injection, to calculate characteristics of fuel sprays with due account of a shape and dimensions of a combustion chamber, timely to change fuel injection characteristics and supercharging parameters, shape and dimensions of a combustion chamber. Moreover the computer model permits to determine parameters of holes in an injector nozzle that provides the required fuel sprays characteristics at the stage of designing a diesel engine. Combustion chamber parameters for 4ЧН11/12.5 diesel engine have been determined in the paper.
Effects of Raindrop Shape Parameter on the Simulation of Plum Rains
Mei, H.; Zhou, L.; Li, X.; Huang, X.; Guo, W.
2017-12-01
The raindrop shape parameter of particle distribution is generally set as constant in a Double-moment Bulk Microphysics Scheme (DBMS) using Gama distribution function though which suggest huge differences in time and space according to observations. Based on Milbrandt 2-mon(MY) DBMS, four cases during Plum Rains season are simulated coupled with four empirical relationships between shape parameter (μr) and slope parameter of raindrop which have been concluded from observations of raindrop distributions. The analysis of model results suggest that μr have some influences on rainfall. Introducing the diagnostic formulas of μr may have some improvement on systematic biases of 24h accumulated rainfall and show some correction ability on local characteristics of rainfall distribution. Besides,the tendency to improve strong rainfall could be sensitive to μr. With the improvement of the diagnosis of μr using the empirically diagnostic formulas, μr increases generally in the middle- and lower-troposphere and decreases with the stronger rainfall. Its conclued that, the decline in raindrop water content and the increased raindrop mass-weighted average terminal velocity directly related to μr are the direct reasons of variations in the precipitation.On the other side, the environmental conditions including relative humidity and dynamical parameters are the key indirectly causes which has close relationships with the changes in cloud particles and rainfall distributions.Furthermore,the differences in the scale of improvement between the weak and heavy rainfall mainly come from the distinctions of response features about their variable fields respectively. The extent of variation in the features of cloud particles in warm clouds of heavy rainfall differs greatly from that of weak rainfall, though they share the same trend of variation. On the conditions of weak rainfall, the response of physical characteristics to μr performed consistent trends and some linear features
Volkov, V.I.; Kulikov, I.I.; Romanov, S.V.
1982-01-01
Signal shape registration in the JINR synchrophasotron slowly estracted beam parameter control system on-line with the ES-1010 computer is described. 32 input signals can be connected to the registrator. The maximum measurement rate of signal shape registration is about 38 kHz. The registrator consists of 32-channel analog multiplexer, 10-bit analog-to-digital converter, 1024-word buffer memory and control circuits. For information representation the colour TV monitor is used
Modeling shape selection of buckled dielectric elastomers
Langham, Jacob; Bense, Hadrien; Barkley, Dwight
2018-02-01
A dielectric elastomer whose edges are held fixed will buckle, given a sufficiently applied voltage, resulting in a nontrivial out-of-plane deformation. We study this situation numerically using a nonlinear elastic model which decouples two of the principal electrostatic stresses acting on an elastomer: normal pressure due to the mutual attraction of oppositely charged electrodes and tangential shear ("fringing") due to repulsion of like charges at the electrode edges. These enter via physically simplified boundary conditions that are applied in a fixed reference domain using a nondimensional approach. The method is valid for small to moderate strains and is straightforward to implement in a generic nonlinear elasticity code. We validate the model by directly comparing the simulated equilibrium shapes with the experiment. For circular electrodes which buckle axisymetrically, the shape of the deflection profile is captured. Annular electrodes of different widths produce azimuthal ripples with wavelengths that match our simulations. In this case, it is essential to compute multiple equilibria because the first model solution obtained by the nonlinear solver (Newton's method) is often not the energetically favored state. We address this using a numerical technique known as "deflation." Finally, we observe the large number of different solutions that may be obtained for the case of a long rectangular strip.
Safin, R. R.; Khasanshin, R. R.; Mukhametzyanov, S. R.
2018-03-01
The existing installations for heat treatment of the crushed wood are analyzed. The technology of heat treatment of the crushed wood in the devices of disk-shaped type is offered. The results of modeling for the purpose of determination of interrelation of the key design and technological parameters of the disk-shaped device are presented. It is established that the major factors, affecting duration of stay of the material in a device, are the speed of rotation of the mixer, the number of mixers and the number of rakes on the mixer.
Nasir, Ahmad Fakhri Ab; Suhaila Sabarudin, Siti; Majeed, Anwar P. P. Abdul; Ghani, Ahmad Shahrizan Abdul
2018-04-01
Chicken egg is a source of food of high demand by humans. Human operators cannot work perfectly and continuously when conducting egg grading. Instead of an egg grading system using weight measure, an automatic system for egg grading using computer vision (using egg shape parameter) can be used to improve the productivity of egg grading. However, early hypothesis has indicated that more number of egg classes will change when using egg shape parameter compared with using weight measure. This paper presents the comparison of egg classification by the two above-mentioned methods. Firstly, 120 images of chicken eggs of various grades (A–D) produced in Malaysia are captured. Then, the egg images are processed using image pre-processing techniques, such as image cropping, smoothing and segmentation. Thereafter, eight egg shape features, including area, major axis length, minor axis length, volume, diameter and perimeter, are extracted. Lastly, feature selection (information gain ratio) and feature extraction (principal component analysis) are performed using k-nearest neighbour classifier in the classification process. Two methods, namely, supervised learning (using weight measure as graded by egg supplier) and unsupervised learning (using egg shape parameters as graded by ourselves), are conducted to execute the experiment. Clustering results reveal many changes in egg classes after performing shape-based grading. On average, the best recognition results using shape-based grading label is 94.16% while using weight-based label is 44.17%. As conclusion, automated egg grading system using computer vision is better by implementing shape-based features since it uses image meanwhile the weight parameter is more suitable by using weight grading system.
Using a Shape Model in the Design of Hearing Aids
Paulsen, Rasmus Reinhold; Nielsen, Claus; Laugesen, Søren
2004-01-01
shapes by a skilled operator. These faceplate planes are aligned to the average shape from the shape model and an average faceplate plane is calculated. Given a surface representation of a new ear canal, the shape model is fitted using a combination of the iterative closest point algorithm and the active...... shape model approach. The average faceplate from the training set can now be placed on the new ear canal using the position of the fitted shape model. A leave-one-out study shows that the algorithm is able to produce results comparable to a human operator....
A nuclear radiation multi-parameter measurement system based on pulse-shape sampling
Qiu Xiaolin; Fang Guoming; Xu Peng; Di Yuming
2007-01-01
In this paper, A nuclear radiation multi-parameter measurement system based on pulse-shape sampling is introduced, including the system's characteristics, composition, operating principle, experiment data and analysis. Compared with conventional nuclear measuring apparatus, it has some remarkable advantages such as the synchronous detection using multi-parameter measurement in the same measurement platform and the general analysis of signal data by user-defined program. (authors)
EFFECT OF PLASMA CUTTING PARAMETERS UPON SHAPES OF BEARING CURVE OF C45 STEEL SURFACE
Agnieszka Skoczylas
2015-08-01
Full Text Available The article presents the results of studies on the effect of plasma cutting technological parameters upon the shape of bearing curves and the parameters of the curve. The topography of surface formed by plasma cutting were analyzed. For measuring surface roughness and determining the bearing curve the appliance T8000 RC120 – 400 by Hommel-Etamic was used together with software.
Airfoil Shape Optimization based on Surrogate Model
Mukesh, R.; Lingadurai, K.; Selvakumar, U.
2018-02-01
Engineering design problems always require enormous amount of real-time experiments and computational simulations in order to assess and ensure the design objectives of the problems subject to various constraints. In most of the cases, the computational resources and time required per simulation are large. In certain cases like sensitivity analysis, design optimisation etc where thousands and millions of simulations have to be carried out, it leads to have a life time of difficulty for designers. Nowadays approximation models, otherwise called as surrogate models (SM), are more widely employed in order to reduce the requirement of computational resources and time in analysing various engineering systems. Various approaches such as Kriging, neural networks, polynomials, Gaussian processes etc are used to construct the approximation models. The primary intention of this work is to employ the k-fold cross validation approach to study and evaluate the influence of various theoretical variogram models on the accuracy of the surrogate model construction. Ordinary Kriging and design of experiments (DOE) approaches are used to construct the SMs by approximating panel and viscous solution algorithms which are primarily used to solve the flow around airfoils and aircraft wings. The method of coupling the SMs with a suitable optimisation scheme to carryout an aerodynamic design optimisation process for airfoil shapes is also discussed.
Jang, Hwan Hak; Jeong, Seong Beom; Park, Gyung Jin
2012-01-01
A shape optimization is proposed to obtain the desired final shape of forming and forging products in the manufacturing process. The final shape of a forming product depends on the shape parameters of the initial blank shape. The final shape of a forging product depends on the shape parameters of the billet shape. Shape optimization can be used to determine the shape of the blank and billet to obtain the appropriate final forming and forging products. The equivalent static loads method for non linear static response structural optimization (ESLSO) is used to perform metal forming and forging optimization since nonlinear dynamic analysis is required. Stress equivalent static loads (stress ESLs) are newly defined using a virtual model by redefining the value of the material properties. The examples in this paper show that optimization using the stress ESLs is quite useful and the final shapes of a forming and forging products are identical to the desired shapes
Micromechanical modelling of shape memory alloy composites
Wang, Y.F.; Wang, X.M.; Yue, Z.F. [School of Mechanic, Civil Engineering and Architecture, Northwestern Polytechnical University, Xian, 710072 (China)
2004-03-01
An isothermal finite element method (FEM) model has been applied to study the behavior of two kinds of shape memory alloy (SMA) composites. For SMA-fiber reinforced normal metal composites, the FEM analysis shows that the mechanical behavior of the composites depends on the SMA volume fraction. For normal metal-fiber reinforced SMA matrix composites, the SMA phase transformation is affected by the increasing Young's modulus of the metal fiber. The phase transformation was also treated using a simple numerical analysis, which assumes that there are uniform stresses and strains distributions in the fiber and the matrix respectively. It is found that there is an obvious difference between the FEM analysis and the simple numerical assessment. Only FEM can provide reasonable predictions of phase transformations in SMA/normal metal composites. (Abstract Copyright [2004], Wiley Periodicals, Inc.)
Rock shape, restitution coefficients and rockfall trajectory modelling
Glover, James; Christen, Marc; Bühler, Yves; Bartelt, Perry
2014-05-01
Restitution coefficients are used in rockfall trajectory modelling to describe the ratio between incident and rebound velocities during ground impact. They are central to the problem of rockfall hazard analysis as they link rock mass characteristics to terrain properties. Using laboratory experiments as a guide, we first show that restitution coefficients exhibit a wide range of scatter, although the material properties of the rock and ground are constant. This leads us to the conclusion that restitution coefficients are poor descriptors of rock-ground interaction. The primary problem is that "apparent" restitution coefficients are applied at the rock's centre-of-mass and do not account for rock shape. An accurate description of the rock-ground interaction requires the contact forces to be applied at the rock surface with consideration of the momentary rock position and spin. This leads to a variety of rock motions including bouncing, sliding, skipping and rolling. Depending on the impact configuration a wide range of motions is possible. This explains the large scatter of apparent restitution coefficients. We present a rockfall model based on newly developed hard-contact algorithms which includes the effects of rock shape and therefore is able to reproduce the results of different impact configurations. We simulate the laboratory experiments to show that it is possible to reproduce run-out and dispersion of different rock shapes using parameters obtained from independent tests. Although this is a step forward in rockfall trajectory modelling, the problem of parametersing real terrain remains.
Microplane modelling of shape memory alloys
Kadkhodaei, M; Salimi, M; Rajapakse, R K N D; Mahzoon, M
2007-01-01
A three-dimensional (3D) constitutive model based on a statically constrained microplane theory with volumetric-deviatoric split is proposed for polycrystalline shape memory alloys (SMAs) under multiaxial loading paths. Microplane governing equations are 1D stress-strain relations for normal and shear stresses on each microplane, in which suitable relationships between the microscopic and macroscopic quantities are considered so that switching between elastic and inelastic local responses automatically occurs according to the macroscopic response of SMA without additional constraint. Shear stress on each microplane is expressed by the resultant shear component within the plane to overcome directional bias and to prevent the appearance of shear strain in a pure axial loading or axial strain in a pure shear loading while microplane formulations based on two shear directions may predict such impractical results. The behaviour of SMA under simple and complicated loadings has been studied. In nonproportional loading paths, the model shows interaction between stress components, as well as deviation from normality. Predicted results from the model are in good agreement with those of the existing theoretical and experimental investigations
Parameter Estimation of Partial Differential Equation Models.
Xun, Xiaolei; Cao, Jiguo; Mallick, Bani; Carroll, Raymond J; Maity, Arnab
2013-01-01
Partial differential equation (PDE) models are commonly used to model complex dynamic systems in applied sciences such as biology and finance. The forms of these PDE models are usually proposed by experts based on their prior knowledge and understanding of the dynamic system. Parameters in PDE models often have interesting scientific interpretations, but their values are often unknown, and need to be estimated from the measurements of the dynamic system in the present of measurement errors. Most PDEs used in practice have no analytic solutions, and can only be solved with numerical methods. Currently, methods for estimating PDE parameters require repeatedly solving PDEs numerically under thousands of candidate parameter values, and thus the computational load is high. In this article, we propose two methods to estimate parameters in PDE models: a parameter cascading method and a Bayesian approach. In both methods, the underlying dynamic process modeled with the PDE model is represented via basis function expansion. For the parameter cascading method, we develop two nested levels of optimization to estimate the PDE parameters. For the Bayesian method, we develop a joint model for data and the PDE, and develop a novel hierarchical model allowing us to employ Markov chain Monte Carlo (MCMC) techniques to make posterior inference. Simulation studies show that the Bayesian method and parameter cascading method are comparable, and both outperform other available methods in terms of estimation accuracy. The two methods are demonstrated by estimating parameters in a PDE model from LIDAR data.
Effect of laser pulse shaping parameters on the fidelity of quantum logic gates.
Zaari, Ryan R; Brown, Alex
2012-09-14
The effect of varying parameters specific to laser pulse shaping instruments on resulting fidelities for the ACNOT(1), NOT(2), and Hadamard(2) quantum logic gates are studied for the diatomic molecule (12)C(16)O. These parameters include varying the frequency resolution, adjusting the number of frequency components and also varying the amplitude and phase at each frequency component. A time domain analytic form of the original discretized frequency domain laser pulse function is derived, providing a useful means to infer the resulting pulse shape through variations to the aforementioned parameters. We show that amplitude variation at each frequency component is a crucial requirement for optimal laser pulse shaping, whereas phase variation provides minimal contribution. We also show that high fidelity laser pulses are dependent upon the frequency resolution and increasing the number of frequency components provides only a small incremental improvement to quantum gate fidelity. Analysis through use of the pulse area theorem confirms the resulting population dynamics for one or two frequency high fidelity laser pulses and implies similar dynamics for more complex laser pulse shapes. The ability to produce high fidelity laser pulses that provide both population control and global phase alignment is attributed greatly to the natural evolution phase alignment of the qubits involved within the quantum logic gate operation.
3D shape decomposition and comparison for gallbladder modeling
Huang, Weimin; Zhou, Jiayin; Liu, Jiang; Zhang, Jing; Yang, Tao; Su, Yi; Law, Gim Han; Chui, Chee Kong; Chang, Stephen
2011-03-01
This paper presents an approach to gallbladder shape comparison by using 3D shape modeling and decomposition. The gallbladder models can be used for shape anomaly analysis and model comparison and selection in image guided robotic surgical training, especially for laparoscopic cholecystectomy simulation. The 3D shape of a gallbladder is first represented as a surface model, reconstructed from the contours segmented in CT data by a scheme of propagation based voxel learning and classification. To better extract the shape feature, the surface mesh is further down-sampled by a decimation filter and smoothed by a Taubin algorithm, followed by applying an advancing front algorithm to further enhance the regularity of the mesh. Multi-scale curvatures are then computed on the regularized mesh for the robust saliency landmark localization on the surface. The shape decomposition is proposed based on the saliency landmarks and the concavity, measured by the distance from the surface point to the convex hull. With a given tolerance the 3D shape can be decomposed and represented as 3D ellipsoids, which reveal the shape topology and anomaly of a gallbladder. The features based on the decomposed shape model are proposed for gallbladder shape comparison, which can be used for new model selection. We have collected 19 sets of abdominal CT scan data with gallbladders, some shown in normal shape and some in abnormal shapes. The experiments have shown that the decomposed shapes reveal important topology features.
Quality assessment for radiological model parameters
Funtowicz, S.O.
1989-01-01
A prototype framework for representing uncertainties in radiological model parameters is introduced. This follows earlier development in this journal of a corresponding framework for representing uncertainties in radiological data. Refinements and extensions to the earlier framework are needed in order to take account of the additional contextual factors consequent on using data entries to quantify model parameters. The parameter coding can in turn feed in to methods for evaluating uncertainties in calculated model outputs. (author)
Establishing statistical models of manufacturing parameters
Senevat, J.; Pape, J.L.; Deshayes, J.F.
1991-01-01
This paper reports on the effect of pilgering and cold-work parameters on contractile strain ratio and mechanical properties that were investigated using a large population of Zircaloy tubes. Statistical models were established between: contractile strain ratio and tooling parameters, mechanical properties (tensile test, creep test) and cold-work parameters, and mechanical properties and stress-relieving temperature
Chandra, Shubham; Rao, Balkrishna C.
2017-06-01
The process of laser engineered net shaping (LENSTM) is an additive manufacturing technique that employs the coaxial flow of metallic powders with a high-power laser to form a melt pool and the subsequent deposition of the specimen on a substrate. Although research done over the past decade on the LENSTM processing of alloys of steel, titanium, nickel and other metallic materials typically reports superior mechanical properties in as-deposited specimens, when compared to the bulk material, there is anisotropy in the mechanical properties of the melt deposit. The current study involves the development of a numerical model of the LENSTM process, using the principles of computational fluid dynamics (CFD), and the subsequent prediction of the volume fraction of equiaxed grains to predict process parameters required for the deposition of workpieces with isotropy in their properties. The numerical simulation is carried out on ANSYS-Fluent, whose data on thermal gradient are used to determine the volume fraction of the equiaxed grains present in the deposited specimen. This study has been validated against earlier efforts on the experimental studies of LENSTM for alloys of nickel. Besides being applicable to the wider family of metals and alloys, the results of this study will also facilitate effective process design to improve both product quality and productivity.
Shape prior modeling using sparse representation and online dictionary learning.
Zhang, Shaoting; Zhan, Yiqiang; Zhou, Yan; Uzunbas, Mustafa; Metaxas, Dimitris N
2012-01-01
The recently proposed sparse shape composition (SSC) opens a new avenue for shape prior modeling. Instead of assuming any parametric model of shape statistics, SSC incorporates shape priors on-the-fly by approximating a shape instance (usually derived from appearance cues) by a sparse combination of shapes in a training repository. Theoretically, one can increase the modeling capability of SSC by including as many training shapes in the repository. However, this strategy confronts two limitations in practice. First, since SSC involves an iterative sparse optimization at run-time, the more shape instances contained in the repository, the less run-time efficiency SSC has. Therefore, a compact and informative shape dictionary is preferred to a large shape repository. Second, in medical imaging applications, training shapes seldom come in one batch. It is very time consuming and sometimes infeasible to reconstruct the shape dictionary every time new training shapes appear. In this paper, we propose an online learning method to address these two limitations. Our method starts from constructing an initial shape dictionary using the K-SVD algorithm. When new training shapes come, instead of re-constructing the dictionary from the ground up, we update the existing one using a block-coordinates descent approach. Using the dynamically updated dictionary, sparse shape composition can be gracefully scaled up to model shape priors from a large number of training shapes without sacrificing run-time efficiency. Our method is validated on lung localization in X-Ray and cardiac segmentation in MRI time series. Compared to the original SSC, it shows comparable performance while being significantly more efficient.
Robust estimation of hydrological model parameters
A. Bárdossy
2008-11-01
Full Text Available The estimation of hydrological model parameters is a challenging task. With increasing capacity of computational power several complex optimization algorithms have emerged, but none of the algorithms gives a unique and very best parameter vector. The parameters of fitted hydrological models depend upon the input data. The quality of input data cannot be assured as there may be measurement errors for both input and state variables. In this study a methodology has been developed to find a set of robust parameter vectors for a hydrological model. To see the effect of observational error on parameters, stochastically generated synthetic measurement errors were applied to observed discharge and temperature data. With this modified data, the model was calibrated and the effect of measurement errors on parameters was analysed. It was found that the measurement errors have a significant effect on the best performing parameter vector. The erroneous data led to very different optimal parameter vectors. To overcome this problem and to find a set of robust parameter vectors, a geometrical approach based on Tukey's half space depth was used. The depth of the set of N randomly generated parameters was calculated with respect to the set with the best model performance (Nash-Sutclife efficiency was used for this study for each parameter vector. Based on the depth of parameter vectors, one can find a set of robust parameter vectors. The results show that the parameters chosen according to the above criteria have low sensitivity and perform well when transfered to a different time period. The method is demonstrated on the upper Neckar catchment in Germany. The conceptual HBV model was used for this study.
Fourier Series, the DFT and Shape Modelling
Skoglund, Karl
2004-01-01
This report provides an introduction to Fourier series, the discrete Fourier transform, complex geometry and Fourier descriptors for shape analysis. The content is aimed at undergraduate and graduate students who wish to learn about Fourier analysis in general, as well as its application to shape...
A probabilistic model for component-based shape synthesis
Kalogerakis, Evangelos
2012-07-01
We present an approach to synthesizing shapes from complex domains, by identifying new plausible combinations of components from existing shapes. Our primary contribution is a new generative model of component-based shape structure. The model represents probabilistic relationships between properties of shape components, and relates them to learned underlying causes of structural variability within the domain. These causes are treated as latent variables, leading to a compact representation that can be effectively learned without supervision from a set of compatibly segmented shapes. We evaluate the model on a number of shape datasets with complex structural variability and demonstrate its application to amplification of shape databases and to interactive shape synthesis. © 2012 ACM 0730-0301/2012/08-ART55.
Model parameter updating using Bayesian networks
Treml, C.A.; Ross, Timothy J.
2004-01-01
This paper outlines a model parameter updating technique for a new method of model validation using a modified model reference adaptive control (MRAC) framework with Bayesian Networks (BNs). The model parameter updating within this method is generic in the sense that the model/simulation to be validated is treated as a black box. It must have updateable parameters to which its outputs are sensitive, and those outputs must have metrics that can be compared to that of the model reference, i.e., experimental data. Furthermore, no assumptions are made about the statistics of the model parameter uncertainty, only upper and lower bounds need to be specified. This method is designed for situations where a model is not intended to predict a complete point-by-point time domain description of the item/system behavior; rather, there are specific points, features, or events of interest that need to be predicted. These specific points are compared to the model reference derived from actual experimental data. The logic for updating the model parameters to match the model reference is formed via a BN. The nodes of this BN consist of updateable model input parameters and the specific output values or features of interest. Each time the model is executed, the input/output pairs are used to adapt the conditional probabilities of the BN. Each iteration further refines the inferred model parameters to produce the desired model output. After parameter updating is complete and model inputs are inferred, reliabilities for the model output are supplied. Finally, this method is applied to a simulation of a resonance control cooling system for a prototype coupled cavity linac. The results are compared to experimental data.
Zarepisheh, M; Li, R; Xing, L [Stanford UniversitySchool of Medicine, Stanford, CA (United States); Ye, Y [Stanford Univ, Management Science and Engineering, Stanford, Ca (United States); Boyd, S [Stanford University, Electrical Engineering, Stanford, CA (United States)
2014-06-01
Purpose: Station Parameter Optimized Radiation Therapy (SPORT) was recently proposed to fully utilize the technical capability of emerging digital LINACs, in which the station parameters of a delivery system, (such as aperture shape and weight, couch position/angle, gantry/collimator angle) are optimized altogether. SPORT promises to deliver unprecedented radiation dose distributions efficiently, yet there does not exist any optimization algorithm to implement it. The purpose of this work is to propose an optimization algorithm to simultaneously optimize the beam sampling and aperture shapes. Methods: We build a mathematical model whose variables are beam angles (including non-coplanar and/or even nonisocentric beams) and aperture shapes. To solve the resulting large scale optimization problem, we devise an exact, convergent and fast optimization algorithm by integrating three advanced optimization techniques named column generation, gradient method, and pattern search. Column generation is used to find a good set of aperture shapes as an initial solution by adding apertures sequentially. Then we apply the gradient method to iteratively improve the current solution by reshaping the aperture shapes and updating the beam angles toward the gradient. Algorithm continues by pattern search method to explore the part of the search space that cannot be reached by the gradient method. Results: The proposed technique is applied to a series of patient cases and significantly improves the plan quality. In a head-and-neck case, for example, the left parotid gland mean-dose, brainstem max-dose, spinal cord max-dose, and mandible mean-dose are reduced by 10%, 7%, 24% and 12% respectively, compared to the conventional VMAT plan while maintaining the same PTV coverage. Conclusion: Combined use of column generation, gradient search and pattern search algorithms provide an effective way to optimize simultaneously the large collection of station parameters and significantly improves
Zarepisheh, M; Li, R; Xing, L; Ye, Y; Boyd, S
2014-01-01
Purpose: Station Parameter Optimized Radiation Therapy (SPORT) was recently proposed to fully utilize the technical capability of emerging digital LINACs, in which the station parameters of a delivery system, (such as aperture shape and weight, couch position/angle, gantry/collimator angle) are optimized altogether. SPORT promises to deliver unprecedented radiation dose distributions efficiently, yet there does not exist any optimization algorithm to implement it. The purpose of this work is to propose an optimization algorithm to simultaneously optimize the beam sampling and aperture shapes. Methods: We build a mathematical model whose variables are beam angles (including non-coplanar and/or even nonisocentric beams) and aperture shapes. To solve the resulting large scale optimization problem, we devise an exact, convergent and fast optimization algorithm by integrating three advanced optimization techniques named column generation, gradient method, and pattern search. Column generation is used to find a good set of aperture shapes as an initial solution by adding apertures sequentially. Then we apply the gradient method to iteratively improve the current solution by reshaping the aperture shapes and updating the beam angles toward the gradient. Algorithm continues by pattern search method to explore the part of the search space that cannot be reached by the gradient method. Results: The proposed technique is applied to a series of patient cases and significantly improves the plan quality. In a head-and-neck case, for example, the left parotid gland mean-dose, brainstem max-dose, spinal cord max-dose, and mandible mean-dose are reduced by 10%, 7%, 24% and 12% respectively, compared to the conventional VMAT plan while maintaining the same PTV coverage. Conclusion: Combined use of column generation, gradient search and pattern search algorithms provide an effective way to optimize simultaneously the large collection of station parameters and significantly improves
On parameter estimation in deformable models
Fisker, Rune; Carstensen, Jens Michael
1998-01-01
Deformable templates have been intensively studied in image analysis through the last decade, but despite its significance the estimation of model parameters has received little attention. We present a method for supervised and unsupervised model parameter estimation using a general Bayesian form...
Modeling the shape hierarchy for visually guided grasping
Rezai, O
2014-10-01
Full Text Available The monkey anterior intraparietal area (AIP) encodes visual information about three-dimensional object shape that is used to shape the hand for grasping. We modeled shape tuning in visual AIP neurons and its relationship with curvature and gradient...
Modeling self-occlusions in dynamic shape and appearance tracking
Yang, Yanchao; Sundaramoorthi, Ganesh
2013-01-01
We present a method to track the precise shape of a dynamic object in video. Joint dynamic shape and appearance models, in which a template of the object is propagated to match the object shape and radiance in the next frame, are advantageous over
Adding Curvature to Minimum Description Length Shape Models
Thodberg, Hans Henrik; Ólafsdóttir, Hildur
2003-01-01
The Minimum Description Length (MDL) approach to shape modelling seeks a compact description of a set of shapes in terms of the coordinates of marks on the shapes. It has been shown that the mark positions resulting from this optimisation to a large extent solve the so-called point correspondence...
Shape optimization in biomimetics by homogenization modelling
Hoppe, Ronald H.W.; Petrova, Svetozara I.
2003-08-01
Optimal shape design of microstructured materials has recently attracted a great deal of attention in material science. The shape and the topology of the microstructure have a significant impact on the macroscopic properties. The present work is devoted to the shape optimization of new biomorphic microcellular ceramics produced from natural wood by biotemplating. We are interested in finding the best material-and-shape combination in order to achieve the optimal prespecified performance of the composite material. The computation of the effective material properties is carried out using the homogenization method. Adaptive mesh-refinement technique based on the computation of recovered stresses is applied in the microstructure to find the homogenized elasticity coefficients. Numerical results show the reliability of the implemented a posteriori error estimator. (author)
Schroeder, J; Reer, R; Braumann, K M
2015-02-01
As reliability of raster stereography was proved only for sagittal plane parameters with repeated measures on the same day, the present study was aiming at investigating variability and reliability of back shape reconstruction for all dimensions (sagittal, frontal, transversal) and for different intervals. For a sample of 20 healthy volunteers, intra-individual variability (SEM and CV%) and reliability (ICC ± 95% CI) were proved for sagittal (thoracic kyphosis, lumbar lordosis, pelvis tilt angle, and trunk inclination), frontal (pelvis torsion, pelvis and trunk imbalance, vertebral side deviation, and scoliosis angle), transversal (vertebral rotation), and functional (hyperextension) spine shape reconstruction parameters for different test-retest intervals (on the same day, between-day, between-week) by means of video raster stereography. Reliability was high for the sagittal plane (pelvis tilt, kyphosis and lordosis angle, and trunk inclination: ICC > 0.90), and good to high for lumbar mobility (0.86 < ICC < 0.97). Apart from sagittal plane spinal alignment, there was a lack of certainty for a high reproducibility indicated by wider ICC confidence intervals. So, reliability was fair to high for vertebral side deviation and the scoliosis angle (0.71 < ICC < 0.95), and poor to good for vertebral rotation values as well as for frontal plane upper body and pelvis position parameters (0.65 < ICC < 0.92). Coefficients for the between-day and between-week interval were a little lower than for repeated measures on the same day. Variability (SEM) was less than 1.5° or 1.5 mm, except for trunk inclination. Relative variability (CV) was greater in global trunk position and pelvis parameters (35-98%) than in scoliosis (14-20%) or sagittal sway parameters (4-8 %). Although we found a lower reproducibility for the frontal plane, raster stereography is considered to be a reliable method for the non-invasive, three-dimensional assessment of spinal alignment in normal non
Dynamic shape transitions in the sdg boson model
Kuyucak, S.
1992-01-01
The dynamic evolution of shapes in the sdg interacting boson model is investigated using the angular momentum projected mean field theory. Deformed nuclei are found to be quite stable against shape changes but transitional nuclei could exhibit dynamic shape transitions in the region L = 10-20. Conditions of existence and experimental signatures for dynamic shape transitions are discussed together with a likely candidate, 192 Os. 13 refs., 3 figs
Dynamic shape transitions in the sdg boson model
Kuyucak, S.
The dynamic evolution of shapes in the sdg interacting boson model is investigated using the angular momentum projected mean field theory. Deformed nuclei are found to be quite stable against shape changes but transitional nuclei could exhibit dynamic shape transitions in the region L = 10-20. Conditions of existence and experimental signatures for dynamic shape transitions are discussed together with a likely candidate, 192Os.
Dynamic shape transitions in the sdg boson model
Kuyucak, S. (Melbourne Univ., Parkville (Australia). School of Physics)
1992-01-01
The dynamic evolution of shapes in the sdg interacting bosun model is investigated using the angular momentum projected mean field theory. Deformed nuclei are found to be quite stable against shape changes but transitional nuclei could exhibit dynamic shape transitions in the region L = 10-20. Conditions of existence and experimental signatures for dynamic shape transitions are discussed together with a likely candidate, {sup 192}Os. (author).
Parameter identification in multinomial processing tree models
Schmittmann, V.D.; Dolan, C.V.; Raijmakers, M.E.J.; Batchelder, W.H.
2010-01-01
Multinomial processing tree models form a popular class of statistical models for categorical data that have applications in various areas of psychological research. As in all statistical models, establishing which parameters are identified is necessary for model inference and selection on the basis
Parameter Estimation of Partial Differential Equation Models
Xun, Xiaolei
2013-09-01
Partial differential equation (PDE) models are commonly used to model complex dynamic systems in applied sciences such as biology and finance. The forms of these PDE models are usually proposed by experts based on their prior knowledge and understanding of the dynamic system. Parameters in PDE models often have interesting scientific interpretations, but their values are often unknown and need to be estimated from the measurements of the dynamic system in the presence of measurement errors. Most PDEs used in practice have no analytic solutions, and can only be solved with numerical methods. Currently, methods for estimating PDE parameters require repeatedly solving PDEs numerically under thousands of candidate parameter values, and thus the computational load is high. In this article, we propose two methods to estimate parameters in PDE models: a parameter cascading method and a Bayesian approach. In both methods, the underlying dynamic process modeled with the PDE model is represented via basis function expansion. For the parameter cascading method, we develop two nested levels of optimization to estimate the PDE parameters. For the Bayesian method, we develop a joint model for data and the PDE and develop a novel hierarchical model allowing us to employ Markov chain Monte Carlo (MCMC) techniques to make posterior inference. Simulation studies show that the Bayesian method and parameter cascading method are comparable, and both outperform other available methods in terms of estimation accuracy. The two methods are demonstrated by estimating parameters in a PDE model from long-range infrared light detection and ranging data. Supplementary materials for this article are available online. © 2013 American Statistical Association.
Hysteresis behaviour of thermoelastic alloys: some shape memory alloys models
Lexcellent, C.; Torra, V.; Raniecki, B.
1993-01-01
The hysteretic behaviour of shape memory alloys (SMA) needs a more and more thin analysis because of its importance for technological applications. The comparison between different approaches allows to explicite the specifity of every model (macroscopic approach, micro-macro level, local description, phenomenological approach) and their points of convergence. On one hand, a thermodynamic treatment with a free energy expression as a mixing rule of each phase (parent or austenite phase and martensite) by adding a coupling term: the configurational energy, allowes modelling of material hysteresis loops. On the other hand, a phenomenological treatment based on a local investigation of two single crystals with a visualisation of microscopic parameters allows to perceive the phase transition mechanisms (nucleation, growth). All the obtained results show the importance of entropy production (or of the definition of the configurational energy term) for the correct description of hysteresis loops (subloops or external). (orig.)
PARAMETER ESTIMATION IN BREAD BAKING MODEL
Hadiyanto Hadiyanto
2012-05-01
Full Text Available Bread product quality is highly dependent to the baking process. A model for the development of product quality, which was obtained by using quantitative and qualitative relationships, was calibrated by experiments at a fixed baking temperature of 200°C alone and in combination with 100 W microwave powers. The model parameters were estimated in a stepwise procedure i.e. first, heat and mass transfer related parameters, then the parameters related to product transformations and finally product quality parameters. There was a fair agreement between the calibrated model results and the experimental data. The results showed that the applied simple qualitative relationships for quality performed above expectation. Furthermore, it was confirmed that the microwave input is most meaningful for the internal product properties and not for the surface properties as crispness and color. The model with adjusted parameters was applied in a quality driven food process design procedure to derive a dynamic operation pattern, which was subsequently tested experimentally to calibrate the model. Despite the limited calibration with fixed operation settings, the model predicted well on the behavior under dynamic convective operation and on combined convective and microwave operation. It was expected that the suitability between model and baking system could be improved further by performing calibration experiments at higher temperature and various microwave power levels. Abstrak PERKIRAAN PARAMETER DALAM MODEL UNTUK PROSES BAKING ROTI. Kualitas produk roti sangat tergantung pada proses baking yang digunakan. Suatu model yang telah dikembangkan dengan metode kualitatif dan kuantitaif telah dikalibrasi dengan percobaan pada temperatur 200oC dan dengan kombinasi dengan mikrowave pada 100 Watt. Parameter-parameter model diestimasi dengan prosedur bertahap yaitu pertama, parameter pada model perpindahan masa dan panas, parameter pada model transformasi, dan
Some Issues of Biological Shape Modelling with Applications
Larsen, Rasmus; Hilger, Klaus Baggesen; Skoglund, Karl
2003-01-01
This paper illustrates current research at Informatics and Mathematical Modelling at the Technical University of Denmark within biological shape modelling. We illustrate a series of generalizations to, modifications to, and applications of the elements of constructing models of shape or appearance...
Parameter identification in the logistic STAR model
Ekner, Line Elvstrøm; Nejstgaard, Emil
We propose a new and simple parametrization of the so-called speed of transition parameter of the logistic smooth transition autoregressive (LSTAR) model. The new parametrization highlights that a consequence of the well-known identification problem of the speed of transition parameter is that th...
An integrated numerical model for the prediction of Gaussian and billet shapes
Hattel, J.H.; Pryds, N.H.; Pedersen, T.B.
2004-01-01
Separate models for the atomisation and the deposition stages were recently integrated by the authors to form a unified model describing the entire spray-forming process. In the present paper, the focus is on describing the shape of the deposited material during the spray-forming process, obtained by this model. After a short review of the models and their coupling, the important factors which influence the resulting shape, i.e. Gaussian or billet, are addressed. The key parameters, which are utilized to predict the geometry and dimension of the deposited material, are the sticking efficiency and the shading effect for Gaussian and billet shape, respectively. From the obtained results, the effect of these parameters on the final shape is illustrated
Exploiting intrinsic fluctuations to identify model parameters.
Zimmer, Christoph; Sahle, Sven; Pahle, Jürgen
2015-04-01
Parameterisation of kinetic models plays a central role in computational systems biology. Besides the lack of experimental data of high enough quality, some of the biggest challenges here are identification issues. Model parameters can be structurally non-identifiable because of functional relationships. Noise in measured data is usually considered to be a nuisance for parameter estimation. However, it turns out that intrinsic fluctuations in particle numbers can make parameters identifiable that were previously non-identifiable. The authors present a method to identify model parameters that are structurally non-identifiable in a deterministic framework. The method takes time course recordings of biochemical systems in steady state or transient state as input. Often a functional relationship between parameters presents itself by a one-dimensional manifold in parameter space containing parameter sets of optimal goodness. Although the system's behaviour cannot be distinguished on this manifold in a deterministic framework it might be distinguishable in a stochastic modelling framework. Their method exploits this by using an objective function that includes a measure for fluctuations in particle numbers. They show on three example models, immigration-death, gene expression and Epo-EpoReceptor interaction, that this resolves the non-identifiability even in the case of measurement noise with known amplitude. The method is applied to partially observed recordings of biochemical systems with measurement noise. It is simple to implement and it is usually very fast to compute. This optimisation can be realised in a classical or Bayesian fashion.
Setting Parameters for Biological Models With ANIMO
Schivo, Stefano; Scholma, Jetse; Karperien, Hermanus Bernardus Johannes; Post, Janine Nicole; van de Pol, Jan Cornelis; Langerak, Romanus; André, Étienne; Frehse, Goran
2014-01-01
ANIMO (Analysis of Networks with Interactive MOdeling) is a software for modeling biological networks, such as e.g. signaling, metabolic or gene networks. An ANIMO model is essentially the sum of a network topology and a number of interaction parameters. The topology describes the interactions
Parameters and error of a theoretical model
Moeller, P.; Nix, J.R.; Swiatecki, W.
1986-09-01
We propose a definition for the error of a theoretical model of the type whose parameters are determined from adjustment to experimental data. By applying a standard statistical method, the maximum-likelihoodlmethod, we derive expressions for both the parameters of the theoretical model and its error. We investigate the derived equations by solving them for simulated experimental and theoretical quantities generated by use of random number generators. 2 refs., 4 tabs
Parameter Estimation of Nonlinear Models in Forestry.
Fekedulegn, Desta; Mac Siúrtáin, Máirtín Pádraig; Colbert, Jim J.
1999-01-01
Partial derivatives of the negative exponential, monomolecular, Mitcherlich, Gompertz, logistic, Chapman-Richards, von Bertalanffy, Weibull and the Richard’s nonlinear growth models are presented. The application of these partial derivatives in estimating the model parameters is illustrated. The parameters are estimated using the Marquardt iterative method of nonlinear regression relating top height to age of Norway spruce (Picea abies L.) from the Bowmont Norway Spruce Thinnin...
Modelling and calibration of a ring-shaped electrostatic meter
Zhang Jianyong [University of Teesside, Middlesbrough TS1 3BA (United Kingdom); Zhou Bin; Xu Chuanlong; Wang Shimin, E-mail: zhoubinde1980@gmail.co [Southeast University, Sipailou 2, Nanjing 210096 (China)
2009-02-01
Ring-shaped electrostatic flow meters can provide very useful information on pneumatically transported air-solids mixture. This type of meters are popular in measuring and controlling the pulverized coal flow distribution among conveyors leading to burners in coal-fired power stations, and they have also been used for research purposes, e.g. for the investigation of electrification mechanism of air-solids two-phase flow. In this paper, finite element method (FEM) is employed to analyze the characteristics of ring-shaped electrostatic meters, and a mathematic model has been developed to express the relationship between the meter's voltage output and the motion of charged particles in the sensing volume. The theoretical analysis and the test results using a belt rig demonstrate that the output of the meter depends upon many parameters including the characteristics of conditioning circuitry, the particle velocity vector, the amount and the rate of change of the charge carried by particles, the locations of particles and etc. This paper also introduces a method to optimize the theoretical model via calibration.
Confidence of model based shape reconstruction from sparse data
Baka, N.; de Bruijne, Marleen; Reiber, J. H. C.
2010-01-01
Statistical shape models (SSM) are commonly applied for plausible interpolation of missing data in medical imaging. However, when fitting a shape model to sparse information, many solutions may fit the available data. In this paper we derive a constrained SSM to fit noisy sparse input landmarks...
Jean Béguinot
2014-01-01
Full Text Available Specific parameters characterising shell shape may arguably have a significant role in the adaptation of bivalve molluscs to their particular environments. Yet, such functionally relevant shape parameters (shell outline elongation, dissymmetry, and ventral convexity are not those parameters that the animal may directly control. Rather than shell shape, the animal regulates shell growth. Accordingly, an alternative, growth-based description of shell-shape is best fitted to understand how the animal may control the achieved shell shape. The key point is, in practice, to bring out the link between those two alternative modes of shell-shape descriptions, that is, to derive the set of equations which connects the growth-based shell-shape parameters to the functionally relevant shell-shape parameters. Thus, a preliminary object of this note is to derive this set of equations as a tool for further investigations. A second object of this work is to provide an illustrative example of implementation of this tool. I report on an unexpected negative covariance between growth-based parameters and show how this covariance results in a severe limitation of the range of interspecific variability of the degree of ventral convexity of the shell outline within the superfamily Tellinoidea. Hypotheses are proposed regarding the constraints possibly at the origin of this limitation of interspecific variability.
Wind Farm Decentralized Dynamic Modeling With Parameters
Soltani, Mohsen; Shakeri, Sayyed Mojtaba; Grunnet, Jacob Deleuran
2010-01-01
Development of dynamic wind flow models for wind farms is part of the research in European research FP7 project AEOLUS. The objective of this report is to provide decentralized dynamic wind flow models with parameters. The report presents a structure for decentralized flow models with inputs from...... local models. The results of this report are especially useful, but not limited, to design a decentralized wind farm controller, since in centralized controller design one can also use the model and update it in a central computing node.......Development of dynamic wind flow models for wind farms is part of the research in European research FP7 project AEOLUS. The objective of this report is to provide decentralized dynamic wind flow models with parameters. The report presents a structure for decentralized flow models with inputs from...
Modeling self-occlusions in dynamic shape and appearance tracking
Yang, Yanchao
2013-12-01
We present a method to track the precise shape of a dynamic object in video. Joint dynamic shape and appearance models, in which a template of the object is propagated to match the object shape and radiance in the next frame, are advantageous over methods employing global image statistics in cases of complex object radiance and cluttered background. In cases of complex 3D object motion and relative viewpoint change, self-occlusions and disocclusions of the object are prominent, and current methods employing joint shape and appearance models are unable to accurately adapt to new shape and appearance information, leading to inaccurate shape detection. In this work, we model self-occlusions and dis-occlusions in a joint shape and appearance tracking framework. Experiments on video exhibiting occlusion/dis-occlusion, complex radiance and background show that occlusion/dis-occlusion modeling leads to superior shape accuracy compared to recent methods employing joint shape/appearance models or employing global statistics. © 2013 IEEE.
Parameter Estimation for Thurstone Choice Models
Vojnovic, Milan [London School of Economics (United Kingdom); Yun, Seyoung [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
2017-04-24
We consider the estimation accuracy of individual strength parameters of a Thurstone choice model when each input observation consists of a choice of one item from a set of two or more items (so called top-1 lists). This model accommodates the well-known choice models such as the Luce choice model for comparison sets of two or more items and the Bradley-Terry model for pair comparisons. We provide a tight characterization of the mean squared error of the maximum likelihood parameter estimator. We also provide similar characterizations for parameter estimators defined by a rank-breaking method, which amounts to deducing one or more pair comparisons from a comparison of two or more items, assuming independence of these pair comparisons, and maximizing a likelihood function derived under these assumptions. We also consider a related binary classification problem where each individual parameter takes value from a set of two possible values and the goal is to correctly classify all items within a prescribed classification error. The results of this paper shed light on how the parameter estimation accuracy depends on given Thurstone choice model and the structure of comparison sets. In particular, we found that for unbiased input comparison sets of a given cardinality, when in expectation each comparison set of given cardinality occurs the same number of times, for a broad class of Thurstone choice models, the mean squared error decreases with the cardinality of comparison sets, but only marginally according to a diminishing returns relation. On the other hand, we found that there exist Thurstone choice models for which the mean squared error of the maximum likelihood parameter estimator can decrease much faster with the cardinality of comparison sets. We report empirical evaluation of some claims and key parameters revealed by theory using both synthetic and real-world input data from some popular sport competitions and online labor platforms.
NEUTRON-PROTON EFFECTIVE RANGE PARAMETERS AND ZERO-ENERGY SHAPE DEPENDENCE.
HACKENBURG, R.W.
2005-06-01
A completely model-independent effective range theory fit to available, unpolarized, np scattering data below 3 MeV determines the zero-energy free proton cross section {sigma}{sub 0} = 20.4287 {+-} 0.0078 b, the singlet apparent effective range r{sub s} = 2.754 {+-} 0.018{sub stat} {+-} 0.056{sub syst} fm, and improves the error slightly on the parahydrogen coherent scattering length, a{sub c} = -3.7406 {+-} 0.0010 fm. The triplet and singlet scattering lengths and the triplet mixed effective range are calculated to be a{sub t} = 5.4114 {+-} 0.0015 fm, a{sub s} = -23.7153 {+-} 0.0043 fm, and {rho}{sub t}(0,-{epsilon}{sub t}) = 1.7468 {+-} 0.0019 fm. The model-independent analysis also determines the zero-energy effective ranges by treating them as separate fit parameters without the constraint from the deuteron binding energy {epsilon}{sub t}. These are determined to be {rho}{sub t}(0,0) = 1.705 {+-} 0.023 fm and {rho}{sub s}(0,0) = 2.665 {+-} 0.056 fm. This determination of {rho}{sub t}(0,0) and {rho}{sub s}(0,0) is most sensitive to the sparse data between about 20 and 600 keV, where the correlation between the determined values of {rho}{sub t}(0,0) and {rho}{sub s}(0,0) is at a minimum. This correlation is responsible for the large systematic error in r{sub s}. More precise data in this range are needed. The present data do not event determine (with confidence) that {rho}{sub t}(0,0) {ne} {rho}{sub t}(0, -{epsilon}{sub t}), referred to here as ''zero-energy shape dependence''. The widely used measurement of {sigma}{sub 0} = 20.491 {+-} 0.014 b from W. Dilg, Phys. Rev. C 11, 103 (1975), is argued to be in error.
Improved Shape Parameter Estimation in Pareto Distributed Clutter with Neural Networks
José Raúl Machado-Fernández
2016-12-01
Full Text Available The main problem faced by naval radars is the elimination of the clutter input which is a distortion signal appearing mixed with target reflections. Recently, the Pareto distribution has been related to sea clutter measurements suggesting that it may provide a better fit than other traditional distributions. The authors propose a new method for estimating the Pareto shape parameter based on artificial neural networks. The solution achieves a precise estimation of the parameter, having a low computational cost, and outperforming the classic method which uses Maximum Likelihood Estimates (MLE. The presented scheme contributes to the development of the NATE detector for Pareto clutter, which uses the knowledge of clutter statistics for improving the stability of the detection, among other applications.
Yang, Yanchao
2013-05-01
We present a method to determine the precise shape of a dynamic object from video. This problem is fundamental to computer vision, and has a number of applications, for example, 3D video/cinema post-production, activity recognition and augmented reality. Current tracking algorithms that determine precise shape can be roughly divided into two categories: 1) Global statistics partitioning methods, where the shape of the object is determined by discriminating global image statistics, and 2) Joint shape and appearance matching methods, where a template of the object from the previous frame is matched to the next image. The former is limited in cases of complex object appearance and cluttered background, where global statistics cannot distinguish between the object and background. The latter is able to cope with complex appearance and a cluttered background, but is limited in cases of camera viewpoint change and object articulation, which induce self-occlusions and self-disocclusions of the object of interest. The purpose of this thesis is to model self-occlusion/disocclusion phenomena in a joint shape and appearance tracking framework. We derive a non-linear dynamic model of the object shape and appearance taking into account occlusion phenomena, which is then used to infer self-occlusions/disocclusions, shape and appearance of the object in a variational optimization framework. To ensure robustness to other unmodeled phenomena that are present in real-video sequences, the Kalman filter is used for appearance updating. Experiments show that our method, which incorporates the modeling of self-occlusion/disocclusion, increases the accuracy of shape estimation in situations of viewpoint change and articulation, and out-performs current state-of-the-art methods for shape tracking.
Thermal expansion and lattice parameters of shaped metal deposited Ti-6Al-4V
Swarnakar, Akhilesh Kumar; Van der Biest, Omer [Katholieke Universiteit Leuven, MTM, Kasteelpark Arenberg 44, 3001 Leuven (Belgium); Baufeld, Bernd, E-mail: b.baufeld@sheffield.ac.uk [Katholieke Universiteit Leuven, MTM, Kasteelpark Arenberg 44, 3001 Leuven (Belgium)
2011-02-10
Research highlights: > Measurement of thermal expansion and of the lattice parameters of Ti-6Al-4V fabricated by shaped metal deposition up to 1100 {sup o}C. > The observation of alpha to beta transformation not reflected in the expansion but in the contraction curve is explained by non-equilibrium alpha phase of the SMD material. > Denuding of the {alpha} phase and enrichment of the {beta} phase of Vanadium due to high temperature experiments. > The unit cell volumes derived from lattice parameters measured by X-ray diffraction are at room temperature larger for the {alpha} than for the {beta} phase. With increasing temperature the unit cell volume of the {beta} phase increases stronger than the one of the {alpha} phase resulting in a similar unit cell volume at the {beta} transus temperature. - Abstract: Thermal expansion and lattice parameters are investigated up to 1100 deg. C for Ti-6Al-4V components, fabricated by shaped metal deposition. This is a novel additive layer manufacturing technique where near net-shape components are built by tungsten inert gas welding. The as-fabricated SMD Ti-6Al-4V components exhibit a constant coefficient of thermal expansion of 1.17 x 10{sup -5} K{sup -1} during heating up to 1100 {sup o}C, not reflecting the {alpha} to {beta} phase transformation. During cooling a stalling of the contraction is observed starting at the {beta} transus temperature. These high temperature experiments denude the {alpha} phase of V and enrich the {beta} phase. The development of the lattice parameters in dependence on temperature are observed with high temperature X-ray diffraction. The unit cell volumes derived from these parameters are at room temperature larger for the {alpha} than for the {beta} phase. With increasing temperature the unit cell volume of the {beta} phase increases stronger than the one of the {alpha} phase resulting in a similar unit cell volume at the {beta} transus temperature. These observations are interpreted as an
Systematic parameter inference in stochastic mesoscopic modeling
Lei, Huan; Yang, Xiu [Pacific Northwest National Laboratory, Richland, WA 99352 (United States); Li, Zhen [Division of Applied Mathematics, Brown University, Providence, RI 02912 (United States); Karniadakis, George Em, E-mail: george_karniadakis@brown.edu [Division of Applied Mathematics, Brown University, Providence, RI 02912 (United States)
2017-02-01
We propose a method to efficiently determine the optimal coarse-grained force field in mesoscopic stochastic simulations of Newtonian fluid and polymer melt systems modeled by dissipative particle dynamics (DPD) and energy conserving dissipative particle dynamics (eDPD). The response surfaces of various target properties (viscosity, diffusivity, pressure, etc.) with respect to model parameters are constructed based on the generalized polynomial chaos (gPC) expansion using simulation results on sampling points (e.g., individual parameter sets). To alleviate the computational cost to evaluate the target properties, we employ the compressive sensing method to compute the coefficients of the dominant gPC terms given the prior knowledge that the coefficients are “sparse”. The proposed method shows comparable accuracy with the standard probabilistic collocation method (PCM) while it imposes a much weaker restriction on the number of the simulation samples especially for systems with high dimensional parametric space. Fully access to the response surfaces within the confidence range enables us to infer the optimal force parameters given the desirable values of target properties at the macroscopic scale. Moreover, it enables us to investigate the intrinsic relationship between the model parameters, identify possible degeneracies in the parameter space, and optimize the model by eliminating model redundancies. The proposed method provides an efficient alternative approach for constructing mesoscopic models by inferring model parameters to recover target properties of the physics systems (e.g., from experimental measurements), where those force field parameters and formulation cannot be derived from the microscopic level in a straight forward way.
Application of lumped-parameter models
Ibsen, Lars Bo; Liingaard, Morten
This technical report concerns the lumped-parameter models for a suction caisson with a ratio between skirt length and foundation diameter equal to 1/2, embedded into an viscoelastic soil. The models are presented for three different values of the shear modulus of the subsoil (section 1.1). Subse...
Models and parameters for environmental radiological assessments
Miller, C.W.
1984-01-01
This book presents a unified compilation of models and parameters appropriate for assessing the impact of radioactive discharges to the environment. Models examined include those developed for the prediction of atmospheric and hydrologic transport and deposition, for terrestrial and aquatic food-chain bioaccumulation, and for internal and external dosimetry. Chapters have been entered separately into the data base
WINKLER'S SINGLE-PARAMETER SUBGRADE MODEL FROM ...
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Page 1 ... corresponding single-parameter Winkler model presented in this work. Keywords: Heterogeneous subgrade, Reissner's simplified continuum, Shear interaction, Simplified continuum, Winkler ... model in practical applications and its long time familiarity among practical engineers, its usage has endured to this date ...
Models and parameters for environmental radiological assessments
Miller, C W [ed.
1984-01-01
This book presents a unified compilation of models and parameters appropriate for assessing the impact of radioactive discharges to the environment. Models examined include those developed for the prediction of atmospheric and hydrologic transport and deposition, for terrestrial and aquatic food-chain bioaccumulation, and for internal and external dosimetry. Chapters have been entered separately into the data base. (ACR)
Consistent Stochastic Modelling of Meteocean Design Parameters
Sørensen, John Dalsgaard; Sterndorff, M. J.
2000-01-01
Consistent stochastic models of metocean design parameters and their directional dependencies are essential for reliability assessment of offshore structures. In this paper a stochastic model for the annual maximum values of the significant wave height, and the associated wind velocity, current...
Models and parameters for environmental radiological assessments
Miller, C.W.
1983-01-01
This article reviews the forthcoming book Models and Parameters for Environmental Radiological Assessments, which presents a unified compilation of models and parameters for assessing the impact on man of radioactive discharges, both routine and accidental, into the environment. Models presented in this book include those developed for the prediction of atmospheric and hydrologic transport and deposition, for terrestrial and aquatic food-chain bioaccumulation, and for internal and external dosimetry. Summaries are presented for each of the transport and dosimetry areas previously for each of the transport and dosimetry areas previously mentioned, and details are available in the literature cited. A chapter of example problems illustrates many of the methodologies presented throughout the text. Models and parameters presented are based on the results of extensive literature reviews and evaluations performed primarily by the staff of the Health and Safety Research Division of Oak Ridge National Laboratory
Training and two-way shape memory in NiTi alloys: influence on thermal parameters
Lahoz, R.; Puertolas, J.A.
2004-01-01
The two-way shape memory effect (TWSME) was studied in a near equiatomic commercial alloy. A training procedure based on a constant load applied in the temperature range of the parent → martensite transformation was carried out on NiTi wires. The efficiency of the method was determined from deformation-temperature measurements by MTA at different training stress and number of cycles. A maximum of two shape memory strain was obtained for a stress training of 115 MPa, independently of number of training cycles. A correlation was established between the TWSME arisen and the permanent strain generated during the training. The A s and A f transitions present a positive shift and the M s and M f a negative one with increasing training stress. All the transitions temperatures decrease with the training cycling. In the trained material, the P→M and M→P temperatures and the latent heat of these conversions undergoes a strong decrease with increasing training stress, with a strong asymmetry between the forward and the reversed transitions. The changes of these thermal parameters as a function of the training parameters were studied on a thermodynamic frame
Shell model calculations at superdeformed shapes
Nazarewicz, W.; Dobaczewski, J.; Van Isacker, P.
1991-01-01
Spectroscopy of superdeformed nuclear states opens up an exciting possibility to probe new properties of the nuclear mean field. In particular, the unusually deformed atomic nucleus can serve as a microscopic laboratory of quantum-mechanical symmetries of a three dimensional harmonic oscillator. The classifications and coupling schemes characteristic of weakly deformed systems are expected to be modified in the superdeformed world. The ''superdeformed'' symmetries lead to new quantum numbers and new effective interactions that can be employed in microscopic calculations. New classification schemes can be directly related to certain geometrical properties of the nuclear shape. 63 refs., 7 figs
General quadrupole shapes in the Interacting Boson Model
Leviatan, A.
1990-01-01
Characteristic attributes of nuclear quadrupole shapes are investigated within the algebraic framework of the Interacting Boson Model. For each shape the Hamiltonian is resolved into intrinsic and collective parts, normal modes are identified and intrinsic states are constructed and used to estimate transition matrix elements. Special emphasis is paid to new features (e.g. rigid triaxiality and coexisting deformed shapes) that emerge in the presence of the three-body interactions. 27 refs
The mobilisation model and parameter sensitivity
Blok, B.M.
1993-12-01
In the PRObabillistic Safety Assessment (PROSA) of radioactive waste in a salt repository one of the nuclide release scenario's is the subrosion scenario. A new subrosion model SUBRECN has been developed. In this model the combined effect of a depth-dependent subrosion, glass dissolution, and salt rise has been taken into account. The subrosion model SUBRECN and the implementation of this model in the German computer program EMOS4 is presented. A new computer program PANTER is derived from EMOS4. PANTER models releases of radionuclides via subrosion from a disposal site in a salt pillar into the biosphere. For uncertainty and sensitivity analyses the new subrosion model Latin Hypercube Sampling has been used for determine the different values for the uncertain parameters. The influence of the uncertainty in the parameters on the dose calculations has been investigated by the following sensitivity techniques: Spearman Rank Correlation Coefficients, Partial Rank Correlation Coefficients, Standardised Rank Regression Coefficients, and the Smirnov Test. (orig./HP)
Source term modelling parameters for Project-90
Shaw, W.; Smith, G.; Worgan, K.; Hodgkinson, D.; Andersson, K.
1992-04-01
This document summarises the input parameters for the source term modelling within Project-90. In the first place, the parameters relate to the CALIBRE near-field code which was developed for the Swedish Nuclear Power Inspectorate's (SKI) Project-90 reference repository safety assessment exercise. An attempt has been made to give best estimate values and, where appropriate, a range which is related to variations around base cases. It should be noted that the data sets contain amendments to those considered by KBS-3. In particular, a completely new set of inventory data has been incorporated. The information given here does not constitute a complete set of parameter values for all parts of the CALIBRE code. Rather, it gives the key parameter values which are used in the constituent models within CALIBRE and the associated studies. For example, the inventory data acts as an input to the calculation of the oxidant production rates, which influence the generation of a redox front. The same data is also an initial value data set for the radionuclide migration component of CALIBRE. Similarly, the geometrical parameters of the near-field are common to both sub-models. The principal common parameters are gathered here for ease of reference and avoidance of unnecessary duplication and transcription errors. (au)
A model to simulate day-to-day variations in rectum shape
Hoogeman, Mischa S.; van Herk, Marcel; Yan, Di; Boersma, Liesbeth J.; Koper, Peter C. M.; Lebesque, Joos V.
2002-01-01
PURPOSE: To develop a model that predicts possible rectum configurations that can occur during radiotherapy of prostate cancer on the basis of a planning CT scan and patient group data. MATERIALS AND METHODS: We used a stochastic shape description model with a limited number of parameters (area,
Rapid de novo shape encoding: a challenge to connectionist modeling
Greene, Ernest
2018-01-01
Neural network (connectionist) models are designed to encode image features and provide the building blocks for object and shape recognition. These models generally call for: a) initial diffuse connections from one neuron population to another, and b) training to bring about a functional change in those connections so that one or more high-tier neurons will selectively respond to a specific shape stimulus. Advanced models provide for translation, size, and rotation invariance. The present dis...
Statistical shape model with random walks for inner ear segmentation
Pujadas, Esmeralda Ruiz; Kjer, Hans Martin; Piella, Gemma
2016-01-01
is required. We propose a new framework for segmentation of micro-CT cochlear images using random walks combined with a statistical shape model (SSM). The SSM allows us to constrain the less contrasted areas and ensures valid inner ear shape outputs. Additionally, a topology preservation method is proposed...
Analysis of Modeling Parameters on Threaded Screws.
Vigil, Miquela S. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Brake, Matthew Robert [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Vangoethem, Douglas [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
2015-06-01
Assembled mechanical systems often contain a large number of bolted connections. These bolted connections (joints) are integral aspects of the load path for structural dynamics, and, consequently, are paramount for calculating a structure's stiffness and energy dissipation prop- erties. However, analysts have not found the optimal method to model appropriately these bolted joints. The complexity of the screw geometry cause issues when generating a mesh of the model. This paper will explore different approaches to model a screw-substrate connec- tion. Model parameters such as mesh continuity, node alignment, wedge angles, and thread to body element size ratios are examined. The results of this study will give analysts a better understanding of the influences of these parameters and will aide in finding the optimal method to model bolted connections.
Parameter Estimation of Spacecraft Fuel Slosh Model
Gangadharan, Sathya; Sudermann, James; Marlowe, Andrea; Njengam Charles
2004-01-01
Fuel slosh in the upper stages of a spinning spacecraft during launch has been a long standing concern for the success of a space mission. Energy loss through the movement of the liquid fuel in the fuel tank affects the gyroscopic stability of the spacecraft and leads to nutation (wobble) which can cause devastating control issues. The rate at which nutation develops (defined by Nutation Time Constant (NTC can be tedious to calculate and largely inaccurate if done during the early stages of spacecraft design. Pure analytical means of predicting the influence of onboard liquids have generally failed. A strong need exists to identify and model the conditions of resonance between nutation motion and liquid modes and to understand the general characteristics of the liquid motion that causes the problem in spinning spacecraft. A 3-D computerized model of the fuel slosh that accounts for any resonant modes found in the experimental testing will allow for increased accuracy in the overall modeling process. Development of a more accurate model of the fuel slosh currently lies in a more generalized 3-D computerized model incorporating masses, springs and dampers. Parameters describing the model include the inertia tensor of the fuel, spring constants, and damper coefficients. Refinement and understanding the effects of these parameters allow for a more accurate simulation of fuel slosh. The current research will focus on developing models of different complexity and estimating the model parameters that will ultimately provide a more realistic prediction of Nutation Time Constant obtained through simulation.
Chetan Aneja; Amit Handa
2016-01-01
In the present experimental study, dissimilar aluminum alloy AA5083 and AA6082 were friction stir welded by varying tool shape, welding speed and rotary speed of the tool in order to investigate the effect of varying tool shape and welding parameters on the mechanical properties as well as microstructure. The friction stir welding (FSW) process parameters have great influence on heat input per unit length of weld. The outcomes of experimental study prove that mechanical properties increases w...
On the effect of model parameters on forecast objects
Marzban, Caren; Jones, Corinne; Li, Ning; Sandgathe, Scott
2018-04-01
Many physics-based numerical models produce a gridded, spatial field of forecasts, e.g., a temperature map. The field for some quantities generally consists of spatially coherent and disconnected objects. Such objects arise in many problems, including precipitation forecasts in atmospheric models, eddy currents in ocean models, and models of forest fires. Certain features of these objects (e.g., location, size, intensity, and shape) are generally of interest. Here, a methodology is developed for assessing the impact of model parameters on the features of forecast objects. The main ingredients of the methodology include the use of (1) Latin hypercube sampling for varying the values of the model parameters, (2) statistical clustering algorithms for identifying objects, (3) multivariate multiple regression for assessing the impact of multiple model parameters on the distribution (across the forecast domain) of object features, and (4) methods for reducing the number of hypothesis tests and controlling the resulting errors. The final output of the methodology is a series of box plots and confidence intervals that visually display the sensitivities. The methodology is demonstrated on precipitation forecasts from a mesoscale numerical weather prediction model.
New Approaches For Asteroid Spin State and Shape Modeling From Delay-Doppler Radar Images
Raissi, Chedy; Lamee, Mehdi; Mosiane, Olorato; Vassallo, Corinne; Busch, Michael W.; Greenberg, Adam; Benner, Lance A. M.; Naidu, Shantanu P.; Duong, Nicholas
2016-10-01
Delay-Doppler radar imaging is a powerful technique to characterize the trajectories, shapes, and spin states of near-Earth asteroids; and has yielded detailed models of dozens of objects. Reconstructing objects' shapes and spins from delay-Doppler data is a computationally intensive inversion problem. Since the 1990s, delay-Doppler data has been analyzed using the SHAPE software. SHAPE performs sequential single-parameter fitting, and requires considerable computer runtime and human intervention (Hudson 1993, Magri et al. 2007). Recently, multiple-parameter fitting algorithms have been shown to more efficiently invert delay-Doppler datasets (Greenberg & Margot 2015) - decreasing runtime while improving accuracy. However, extensive human oversight of the shape modeling process is still required. We have explored two new techniques to better automate delay-Doppler shape modeling: Bayesian optimization and a machine-learning neural network.One of the most time-intensive steps of the shape modeling process is to perform a grid search to constrain the target's spin state. We have implemented a Bayesian optimization routine that uses SHAPE to autonomously search the space of spin-state parameters. To test the efficacy of this technique, we compared it to results with human-guided SHAPE for asteroids 1992 UY4, 2000 RS11, and 2008 EV5. Bayesian optimization yielded similar spin state constraints within a factor of 3 less computer runtime.The shape modeling process could be further accelerated using a deep neural network to replace iterative fitting. We have implemented a neural network with a variational autoencoder (VAE), using a subset of known asteroid shapes and a large set of synthetic radar images as inputs to train the network. Conditioning the VAE in this manner allows the user to give the network a set of radar images and get a 3D shape model as an output. Additional development will be required to train a network to reliably render shapes from delay
Model comparisons and genetic and environmental parameter ...
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Model comparisons and genetic and environmental parameter estimates of growth and the ... breeding strategies and for accurate breeding value estimation. The objectives ...... Sci. 23, 72-76. Van Wyk, J.B., Fair, M.D. & Cloete, S.W.P., 2003.
The rho-parameter in supersymmetric models
Lim, C.S.; Inami, T.; Sakai, N.
1983-10-01
The electroweak rho-parameter is examined in a general class of supersymmetric models. Formulae are given for one-loop contributions to Δrho from scalar quarks and leptons, gauge-Higgs fermions and an extra doublet of Higgs scalars. Mass differences between members of isodoublet scalar quarks and leptons are constrained to be less than about 200 GeV. (author)
A lumped parameter model of plasma focus
Gonzalez, Jose H.; Florido, Pablo C.; Bruzzone, H.; Clausse, Alejandro
1999-01-01
A lumped parameter model to estimate neutron emission of a plasma focus (PF) device is developed. The dynamic of the current sheet is calculated using a snowplow model, and the neutron production with the thermal fusion cross section for a deuterium filling gas. The results were contrasted as a function of the filling pressure with experimental measurements of a 3.68 KJ Mather-type PF. (author)
One parameter model potential for noble metals
Idrees, M.; Khwaja, F.A.; Razmi, M.S.K.
1981-08-01
A phenomenological one parameter model potential which includes s-d hybridization and core-core exchange contributions is proposed for noble metals. A number of interesting properties like liquid metal resistivities, band gaps, thermoelectric powers and ion-ion interaction potentials are calculated for Cu, Ag and Au. The results obtained are in better agreement with experiment than the ones predicted by the other model potentials in the literature. (author)
Parameters affecting profile shape of a high energy low current thin ion beam. Vol. 2
Abdel Salam, F W; Moustafa, O A; El-Khabeary, H [Accelerators Department, Nuclear Research Center, Atomic Energy Authority, Cairo, (Egypt)
1996-03-01
The shape of the profile of a high energy, low current beam of finite length has beam investigated. The beam profile shape depends on the initial beam radius, beam perveance, atomic mass number, charge state of ions, and beam length. These parameters can affect the relation between the initial beam radius and the corresponding final one. An optimum initial beam radius corresponding to minimum final beam at the target has been formulated and the relation between them is deduced taking account of the space charge effect. The minimum beam radius at the target was found to be equal to 2.3 of the optimum initial radius. It is concluded that in order to obtain a small beam radius at a target placed at a finite distance from an ion source, a beam of a low perveance, low atomic mass number and high number of electronic charge is required. This is an important detection for micro machining applications using the oscillating electron ion source which produces nearly paraxial thin beam of low perveance. 12 figs.
An integrated numerical model for the prediction of Gaussian and billet shapes
Hattel, Jesper; Pryds, Nini; Pedersen, Trine Bjerre
2004-01-01
Separate models for the atomisation and the deposition stages were recently integrated by the authors to form a unified model describing the entire spray-forming process. In the present paper, the focus is on describing the shape of the deposited material during the spray-forming process, obtained...... by this model. After a short review of the models and their coupling, the important factors which influence the resulting shape, i.e. Gaussian or billet, are addressed. The key parameters, which are utilized to predict the geometry and dimension of the deposited material, are the sticking efficiency...
Peterchev, Angel V.; DʼOstilio, Kevin; Rothwell, John C.; Murphy, David L.
2014-10-01
Objective. This work aims at flexible and practical pulse parameter control in transcranial magnetic stimulation (TMS), which is currently very limited in commercial devices. Approach. We present a third generation controllable pulse parameter device (cTMS3) that uses a novel circuit topology with two energy-storage capacitors. It incorporates several implementation and functionality advantages over conventional TMS devices and other devices with advanced pulse shape control. cTMS3 generates lower internal voltage differences and is implemented with transistors with a lower voltage rating than prior cTMS devices. Main results. cTMS3 provides more flexible pulse shaping since the circuit topology allows four coil-voltage levels during a pulse, including approximately zero voltage. The near-zero coil voltage enables snubbing of the ringing at the end of the pulse without the need for a separate active snubber circuit. cTMS3 can generate powerful rapid pulse sequences (\\lt 10 ms inter pulse interval) by increasing the width of each subsequent pulse and utilizing the large capacitor energy storage, allowing the implementation of paradigms such as paired-pulse and quadripulse TMS with a single pulse generation circuit. cTMS3 can also generate theta (50 Hz) burst stimulation with predominantly unidirectional electric field pulses. The cTMS3 device functionality and output strength are illustrated with electrical output measurements as well as a study of the effect of pulse width and polarity on the active motor threshold in ten healthy volunteers. Significance. The cTMS3 features could extend the utility of TMS as a research, diagnostic, and therapeutic tool.
Tensegrity Models and Shape Control of Vehicle Formations
Nabet, Benjamin; Leonard, Naomi Ehrich
2009-01-01
Using dynamic models of tensegrity structures, we derive provable, distributed control laws for stabilizing and changing the shape of a formation of vehicles in the plane. Tensegrity models define the desired, controlled, multi-vehicle system dynamics, where each node in the tensegrity structure maps to a vehicle and each interconnecting strut or cable in the structure maps to a virtual interconnection between vehicles. Our method provides a smooth map from any desired planar formation shape ...
Modelling the wedge shape for the virtual wedge
Chang Liyun; Ho Shengyow; Chen, Helen H W
2003-01-01
We present a method to model the virtual wedge shape in a 3D treatment planning system as a physical wedge. The virtual wedge shape was determined using the measured dose profile of the virtual wedge at a chosen reference depth. The differences between the calculated and the measured dose profiles for the virtual wedge were within 0.5% at the reference depth, and within 2.5% at other depths. This method provides a fast and accurate way to implement the virtual wedge into our planning system for any wedge angles. This method is also applicable to model the physical wedge shapes with comparable good results
Grobnic, D.; Popescu, I.M.
1993-01-01
As a result of their granular structure the conductance of ceramic high temperature superconductors depends strongly on the characteristics of the parameter distribution. To study the influence of these distributions of the magneto-resistive transition from normal to superconductive state, a mathematical model was used. This model simulates the superconductor sample, considered as large three-dimensional collection of Josephson tunnel junctions. Each individual junction, according to the values of the parameters that define it, in a given environment (temperature, magnetic field and current density) allows or not the supercurrent to flow with a given probability. The bond percolation problem was solved using a Monte Carlo procedure. To solve the random resistor network formed, a sparse matrix package was used. As parameters that defined Josephson junction which choose the resistance of the normal junction state and the critical temperature of the grain. We considered the normal junction resistance as obeying a log normal distribution and the critical temperature, a Gaussian one. The influences of the relative dispersion of the first distribution and the dispersion of the critical temperature distribution on the shape of the resistivity versus magnetic field was studied. (Author)
Cheng, Ken; Gallistel, C R
2005-04-01
In 2 recent studies on rats (J. M. Pearce, M. A. Good, P. M. Jones, & A. McGregor, see record 2004-12429-006) and chicks (L. Tommasi & C. Polli, see record 2004-15642-007), the animals were trained to search in 1 corner of a rectilinear space. When tested in transformed spaces of different shapes, the animals still showed systematic choices. Both articles rejected the global matching of shape in favor of local matching processes. The present authors show that although matching by shape congruence is unlikely, matching by the shape parameter of the 1st principal axis can explain all the data. Other shape parameters, such as symmetry axes, may do even better. Animals are likely to use some global matching to constrain and guide the use of local cues; such use keeps local matching processes from exploding in complexity.
Ng, H.P. [NUS Graduate School for Integrative Sciences and Engineering (Singapore); Biomedical Imaging Lab., Agency for Science Technology and Research (Singapore); Foong, K.W.C. [NUS Graduate School for Integrative Sciences and Engineering (Singapore); Dept. of Preventive Dentistry, National Univ. of Singapore (Singapore); Ong, S.H. [Dept. of Electrical and Computer Engineering, National Univ. of Singapore (Singapore); Div. of Bioengineering, National Univ. of Singapore (Singapore); Liu, J.; Nowinski, W.L. [Biomedical Imaging Lab., Agency for Science Technology and Research (Singapore); Goh, P.S. [Dept. of Diagnostic Radiology, National Univ. of Singapore (Singapore)
2007-06-15
The masseter plays a critical role in the mastication system. A hybrid method to shape-based interpolation is used to build the masseter model from magnetic resonance (MR) data sets. The main contribution here is the localizing of determinative slices in the data sets where clinicians are required to perform manual segmentations in order for an accurate model to be built. Shape-based criteria were used to locate the candidates for determinative slices and fuzzy-c-means (FCM) clustering technique was used to establish the determinative slices. Five masseter models were built in our work and the average overlap indices ({kappa}) achieved is 85.2%. This indicates that there is good agreement between the models and the manual contour tracings. In addition, the time taken, as compared to manually segmenting all the slices, is significantly lesser. (orig.)
Ng, H.P.; Foong, K.W.C.; Ong, S.H.; Liu, J.; Nowinski, W.L.; Goh, P.S.
2007-01-01
The masseter plays a critical role in the mastication system. A hybrid method to shape-based interpolation is used to build the masseter model from magnetic resonance (MR) data sets. The main contribution here is the localizing of determinative slices in the data sets where clinicians are required to perform manual segmentations in order for an accurate model to be built. Shape-based criteria were used to locate the candidates for determinative slices and fuzzy-c-means (FCM) clustering technique was used to establish the determinative slices. Five masseter models were built in our work and the average overlap indices (κ) achieved is 85.2%. This indicates that there is good agreement between the models and the manual contour tracings. In addition, the time taken, as compared to manually segmenting all the slices, is significantly lesser. (orig.)
Dynamics of a neuron model in different two-dimensional parameter-spaces
Rech, Paulo C.
2011-01-01
We report some two-dimensional parameter-space diagrams numerically obtained for the multi-parameter Hindmarsh-Rose neuron model. Several different parameter planes are considered, and we show that regardless of the combination of parameters, a typical scenario is preserved: for all choice of two parameters, the parameter-space presents a comb-shaped chaotic region immersed in a large periodic region. We also show that exist regions close these chaotic region, separated by the comb teeth, organized themselves in period-adding bifurcation cascades. - Research highlights: → We report parameter-spaces obtained for the Hindmarsh-Rose neuron model. → Regardless of the combination of parameters, a typical scenario is preserved. → The scenario presents a comb-shaped chaotic region immersed in a periodic region. → Periodic regions near the chaotic region are in period-adding bifurcation cascades.
Building the Nanoplasmonics Toolbox Through Shape Modeling and Single Particle Optical Studies
Ringe, Emilie
Interest in nanotechnology is driven by unprecedented properties tailorability, achievable by controlling particle structure and composition. Unlike bulk components, minute changes in size and shape affect the optical and electronic properties of nanoparticles. Characterization of such structure-function relationships and better understanding of structure control mechanisms is crucial to the development of applications such as plasmonic sensors and devices. The objective of the current research is thus twofold: to theoretically predict and understand how shape is controlled by synthesis conditions, and to experimentally unravel, through single particle studies, how shape, composition, size, and surrounding environment affect plasmonic properties in noble metal particles. Quantitative, predictive rules and fundamental knowledge obtained from this research contributes to the "nanoplasmonics toolbox", a library designed to provide scientists and engineers the tools to create and optimize novel nanotechnology applications. In this dissertation, single particle approaches are developed and used to unravel the effects of size, shape, substrate, aggregation state and surrounding environment on the optical response of metallic nanoparticles. Ag and Au nanocubes on different substrates are first presented, followed by the discussion of the concept of plasmon length, a universal parameter to describe plasmon energy for a variety of particle shapes and plasmon modes. Plasmonic sensing (both refractive index sensing and surface-enhanced Raman spectroscopy) and polarization effects are then studied at the single particle level. In the last two Chapters, analytical shape models based on the Wulff construction provide unique modeling tools for alloy and kinetically grown nanoparticles. The former reveals a size-dependence of the shape of small alloy particles (such as those used in catalysis) because of surface segregation, while the latter uniquely models the shape of many
Constant-parameter capture-recapture models
Brownie, C.; Hines, J.E.; Nichols, J.D.
1986-01-01
Jolly (1982, Biometrics 38, 301-321) presented modifications of the Jolly-Seber model for capture-recapture data, which assume constant survival and/or capture rates. Where appropriate, because of the reduced number of parameters, these models lead to more efficient estimators than the Jolly-Seber model. The tests to compare models given by Jolly do not make complete use of the data, and we present here the appropriate modifications, and also indicate how to carry out goodness-of-fit tests which utilize individual capture history information. We also describe analogous models for the case where young and adult animals are tagged. The availability of computer programs to perform the analysis is noted, and examples are given using output from these programs.
Renaud, Candice L.; Cleghorn, Kara; Hartmann, Léna; Vispoel, Bastien; Gamache, Robert R.
2018-05-01
Water can be detected throughout the universe: in comets, asteroids, dwarf planets, the inner and outer planets in our solar system, cool stars, brown dwarfs, and on many exoplanets. Here the focus is on locations rich in hydrogen gas. To properly study these environments, there is a need for the line shape parameters for H2O transitions in collision with hydrogen. This work presents calculations of the half-width and line shift, made using the Modified Complex Robert-Bonamy (MCRB) formalism, at a number of temperatures. It is shown that this collision system is strongly off-resonance. For such conditions, the atom-atom part of the intermolecular potential dominates the interaction of the radiating and perturbing molecules. The atom-atom parameters were adjusted by fitting the H2O-H2 measurements of Brown and Plymate (1996). Several techniques were used to extract lines for which there is more confidence in the quality of the data. The final potential yields results that agree with the measurements with ∼0.3% difference and a 5.9% standard deviation. Using this potential, MCRB calculations were made for all transitions in the pure rotation, ν2, ν1, and ν3 bands. The structure of the line shape parameters and the temperature dependence of the half-width, as a function of the rotational and vibrational quantum numbers, are discussed. It is shown that the power law model of the T-dependence of the half-width is inadequate over large temperature ranges.
On the importance of electrode parameters for shaping electric field patterns generated by tDCS
B. Saturnino, Guilherme; Antunes, André; Thielscher, Axel
2015-01-01
Transcranial direct current stimulation (tDCS) uses electrode pads placed on the head to deliver weak direct current to the brain and modulate neuronal excitability. The effects depend on the intensity and spatial distribution of the electric field. This in turn depends on the geometry and electric...... electrode modeling influences the calculated electric field in the brain. We take into account electrode shape, size, connector position and conductivities of different electrode materials (including saline solutions and electrode gels). These factors are systematically characterized to demonstrate...... their impact on the field distribution in the brain. The goals are to assess the effect of simplified electrode models; and to develop practical rules-of-thumb to achieve a stronger stimulation of the targeted brain regions underneath the electrode pads. We show that for standard rectangular electrode pads...
Optimal input shaping for Fisher identifiability of control-oriented lithium-ion battery models
Rothenberger, Michael J.
This dissertation examines the fundamental challenge of optimally shaping input trajectories to maximize parameter identifiability of control-oriented lithium-ion battery models. Identifiability is a property from information theory that determines the solvability of parameter estimation for mathematical models using input-output measurements. This dissertation creates a framework that exploits the Fisher information metric to quantify the level of battery parameter identifiability, optimizes this metric through input shaping, and facilitates faster and more accurate estimation. The popularity of lithium-ion batteries is growing significantly in the energy storage domain, especially for stationary and transportation applications. While these cells have excellent power and energy densities, they are plagued with safety and lifespan concerns. These concerns are often resolved in the industry through conservative current and voltage operating limits, which reduce the overall performance and still lack robustness in detecting catastrophic failure modes. New advances in automotive battery management systems mitigate these challenges through the incorporation of model-based control to increase performance, safety, and lifespan. To achieve these goals, model-based control requires accurate parameterization of the battery model. While many groups in the literature study a variety of methods to perform battery parameter estimation, a fundamental issue of poor parameter identifiability remains apparent for lithium-ion battery models. This fundamental challenge of battery identifiability is studied extensively in the literature, and some groups are even approaching the problem of improving the ability to estimate the model parameters. The first approach is to add additional sensors to the battery to gain more information that is used for estimation. The other main approach is to shape the input trajectories to increase the amount of information that can be gained from input
Modelling tourists arrival using time varying parameter
Suciptawati, P.; Sukarsa, K. G.; Kencana, Eka N.
2017-06-01
The importance of tourism and its related sectors to support economic development and poverty reduction in many countries increase researchers’ attentions to study and model tourists’ arrival. This work is aimed to demonstrate time varying parameter (TVP) technique to model the arrival of Korean’s tourists to Bali. The number of Korean tourists whom visiting Bali for period January 2010 to December 2015 were used to model the number of Korean’s tourists to Bali (KOR) as dependent variable. The predictors are the exchange rate of Won to IDR (WON), the inflation rate in Korea (INFKR), and the inflation rate in Indonesia (INFID). Observing tourists visit to Bali tend to fluctuate by their nationality, then the model was built by applying TVP and its parameters were approximated using Kalman Filter algorithm. The results showed all of predictor variables (WON, INFKR, INFID) significantly affect KOR. For in-sample and out-of-sample forecast with ARIMA’s forecasted values for the predictors, TVP model gave mean absolute percentage error (MAPE) as much as 11.24 percent and 12.86 percent, respectively.
Bruse, Jan L.; McLeod, Kristin; Biglino, Giovanni; Ntsinjana, Hopewell N.; Capelli, Claudio
2016-01-01
Medical image analysis in clinical practice is commonly carried out on 2D image data, without fully exploiting the detailed 3D anatomical information that is provided by modern non-invasive medical imaging techniques. In this paper, a statistical shape analysis method is presented, which enables the extraction of 3D anatomical shape features from cardiovascular magnetic resonance (CMR) image data, with no need for manual landmarking. The method was applied to repaired aortic coarctation arches that present complex shapes, with the aim of capturing shape features as biomarkers of potential functional relevance. The method is presented from the user-perspective and is evaluated by comparing results with traditional morphometric measurements. Steps required to set up the statistical shape modelling analyses, from pre-processing of the CMR images to parameter setting and strategies to account for size differences and outliers, are described in detail. The anatomical mean shape of 20 aortic arches post-aortic coarctation repair (CoA) was computed based on surface models reconstructed from CMR data. By analysing transformations that deform the mean shape towards each of the individual patient’s anatomy, shape patterns related to differences in body surface area (BSA) and ejection fraction (EF) were extracted. The resulting shape vectors, describing shape features in 3D, were compared with traditionally measured 2D and 3D morphometric parameters. The computed 3D mean shape was close to population mean values of geometric shape descriptors and visually integrated characteristic shape features associated with our population of CoA shapes. After removing size effects due to differences in body surface area (BSA) between patients, distinct 3D shape features of the aortic arch correlated significantly with EF (r = 0.521, p = .022) and were well in agreement with trends as shown by traditional shape descriptors. The suggested method has the potential to discover previously
Bruse, Jan L; McLeod, Kristin; Biglino, Giovanni; Ntsinjana, Hopewell N; Capelli, Claudio; Hsia, Tain-Yen; Sermesant, Maxime; Pennec, Xavier; Taylor, Andrew M; Schievano, Silvia
2016-05-31
Medical image analysis in clinical practice is commonly carried out on 2D image data, without fully exploiting the detailed 3D anatomical information that is provided by modern non-invasive medical imaging techniques. In this paper, a statistical shape analysis method is presented, which enables the extraction of 3D anatomical shape features from cardiovascular magnetic resonance (CMR) image data, with no need for manual landmarking. The method was applied to repaired aortic coarctation arches that present complex shapes, with the aim of capturing shape features as biomarkers of potential functional relevance. The method is presented from the user-perspective and is evaluated by comparing results with traditional morphometric measurements. Steps required to set up the statistical shape modelling analyses, from pre-processing of the CMR images to parameter setting and strategies to account for size differences and outliers, are described in detail. The anatomical mean shape of 20 aortic arches post-aortic coarctation repair (CoA) was computed based on surface models reconstructed from CMR data. By analysing transformations that deform the mean shape towards each of the individual patient's anatomy, shape patterns related to differences in body surface area (BSA) and ejection fraction (EF) were extracted. The resulting shape vectors, describing shape features in 3D, were compared with traditionally measured 2D and 3D morphometric parameters. The computed 3D mean shape was close to population mean values of geometric shape descriptors and visually integrated characteristic shape features associated with our population of CoA shapes. After removing size effects due to differences in body surface area (BSA) between patients, distinct 3D shape features of the aortic arch correlated significantly with EF (r = 0.521, p = .022) and were well in agreement with trends as shown by traditional shape descriptors. The suggested method has the potential to discover
Determination of edge plasma parameters by a genetic algorithm analysis of spectral line shapes
Marandet, Y.; Genesio, P.; Godbert-Mouret, L.; Koubiti, M.; Stamm, R.; Capes, H.; Guirlet, R.
2003-01-01
Comparing an experimental and a theoretical line shape can be achieved by a genetic algorithm (GA) based on an analogy to the mechanisms of natural selection. Such an algorithm is able to deal with complex non-linear models, and can avoid local minima. We have used this optimization tool in the context of edge plasma spectroscopy, for a determination of the temperatures and fractions of the various populations of neutral deuterium emitting the D α line in 2 configurations of Tore-Supra: ergodic divertor and toroidal pumped limiter. Using the GA fit, the neutral emitters are separated into up to 4 populations which can be identified as resulting from molecular dissociation reactions, charge exchange, or reflection. In all the edge plasmas studied, a significant fraction of neutrals emit in the line wings, leading to neutrals with a temperature up to a few hundreds eV if a Gaussian line shape is assumed. This conclusion could be modified if the line wing exhibits a non Gaussian behavior
Determination of edge plasma parameters by a genetic algorithm analysis of spectral line shapes
Marandet, Y.; Genesio, P.; Godbert-Mouret, L.; Koubiti, M.; Stamm, R. [Universite de Provence (PIIM), Centre de Saint-Jerome, 13 - Marseille (France); Capes, H.; Guirlet, R. [Association Euratom-CEA Cadarache, 13 - Saint-Paul-lez-Durance (France). Dept. de Recherches sur la Fusion Controlee
2003-07-01
Comparing an experimental and a theoretical line shape can be achieved by a genetic algorithm (GA) based on an analogy to the mechanisms of natural selection. Such an algorithm is able to deal with complex non-linear models, and can avoid local minima. We have used this optimization tool in the context of edge plasma spectroscopy, for a determination of the temperatures and fractions of the various populations of neutral deuterium emitting the D{sub {alpha}} line in 2 configurations of Tore-Supra: ergodic divertor and toroidal pumped limiter. Using the GA fit, the neutral emitters are separated into up to 4 populations which can be identified as resulting from molecular dissociation reactions, charge exchange, or reflection. In all the edge plasmas studied, a significant fraction of neutrals emit in the line wings, leading to neutrals with a temperature up to a few hundreds eV if a Gaussian line shape is assumed. This conclusion could be modified if the line wing exhibits a non Gaussian behavior.
Ideal Coulomb Plasma Approximation in Line Shape Models: Problematic Issues
Joel Rosato
2014-06-01
Full Text Available In weakly coupled plasmas, it is common to describe the microfield using a Debye model. We examine here an “artificial” ideal one-component plasma with an infinite Debye length, which has been used for the test of line shape codes. We show that the infinite Debye length assumption can lead to a misinterpretation of numerical simulations results, in particular regarding the convergence of calculations. Our discussion is done within an analytical collision operator model developed for hydrogen line shapes in near-impact regimes. When properly employed, this model can serve as a reference for testing the convergence of simulations.
Shape Modeling of a Concentric-tube Continuum Robot
Bai, Shaoping; Xing, Charles Chuhao
2012-01-01
Concentric-tube continuum robots feature with simple and compact structures and have a great potential in medical applications. The paper is concerned with the shape modeling of a type of concentric-tube continuum robot built with a collection of super-elastic NiTiNol tubes. The mechanics...... is modeled on the basis of energy approach for both the in-plane and out-plane cases. The torsional influences on the shape of the concentric-tube robots are considered. An experimental device was build for the model validation. The results of simulation and experiments are included and analyzed....
Shape Modelling Using Markov Random Field Restoration of Point Correspondences
Paulsen, Rasmus Reinhold; Hilger, Klaus Baggesen
2003-01-01
A method for building statistical point distribution models is proposed. The novelty in this paper is the adaption of Markov random field regularization of the correspondence field over the set of shapes. The new approach leads to a generative model that produces highly homogeneous polygonized sh...
Gallbladder shape extraction from ultrasound images using active contour models.
Ciecholewski, Marcin; Chochołowicz, Jakub
2013-12-01
Gallbladder function is routinely assessed using ultrasonographic (USG) examinations. In clinical practice, doctors very often analyse the gallbladder shape when diagnosing selected disorders, e.g. if there are turns or folds of the gallbladder, so extracting its shape from USG images using supporting software can simplify a diagnosis that is often difficult to make. The paper describes two active contour models: the edge-based model and the region-based model making use of a morphological approach, both designed for extracting the gallbladder shape from USG images. The active contour models were applied to USG images without lesions and to those showing specific disease units, namely, anatomical changes like folds and turns of the gallbladder as well as polyps and gallstones. This paper also presents modifications of the edge-based model, such as the method for removing self-crossings and loops or the method of dampening the inflation force which moves nodes if they approach the edge being determined. The user is also able to add a fragment of the approximated edge beyond which neither active contour model will move if this edge is incomplete in the USG image. The modifications of the edge-based model presented here allow more precise results to be obtained when extracting the shape of the gallbladder from USG images than if the morphological model is used. © 2013 Elsevier Ltd. Published by Elsevier Ltd. All rights reserved.
Schmitt, Oliver; Steinmann, Paul
2017-09-01
We introduce a manufacturing constraint for controlling the minimum member size in structural shape optimization problems, which is for example of interest for components fabricated in a molding process. In a parameter-free approach, whereby the coordinates of the FE boundary nodes are used as design variables, the challenging task is to find a generally valid definition for the thickness of non-parametric geometries in terms of their boundary nodes. Therefore we use the medial axis, which is the union of all points with at least two closest points on the boundary of the domain. Since the effort for the exact computation of the medial axis of geometries given by their FE discretization highly increases with the number of surface elements we use the distance function instead to approximate the medial axis by a cloud of points. The approximation is demonstrated on three 2D examples. Moreover, the formulation of a minimum thickness constraint is applied to a sensitivity-based shape optimization problem of one 2D and one 3D model.
Research on shape parameters of circular arc disc teeth for three-cone bit
Qin Hu
2018-03-01
Full Text Available Through the single row drilling experiment, this paper studied the regularity of the tooth shape parameter's influence to the disc teeth's rock-breaking effect, which provided some basis for the composite teeth type roller bit's combined experimental study and the structure design of the tooth type. This experimental research is only for the circular arc disc teeth which is arranged on the composite teeth type roller bit's main tooth. The experiments were designed using the method of orthogonal design and the results were analyzed by the fuzzy optimization method. The results show that the disc tooth's drilling effect is the best when the tip diameter is 2 mm, taper angle is 30° and the groove number is 8, and the disc tooth's drilling effect is the second best when the tip diameter is 3 mm, taper angle is 30° and the groove number is 7. The above two combined ways of drilling effect's difference is very small (the difference of the degree of the membership is 0.003.
Shape, size, and robustness: feasible regions in the parameter space of biochemical networks.
Adel Dayarian
2009-01-01
Full Text Available The concept of robustness of regulatory networks has received much attention in the last decade. One measure of robustness has been associated with the volume of the feasible region, namely, the region in the parameter space in which the system is functional. In this paper, we show that, in addition to volume, the geometry of this region has important consequences for the robustness and the fragility of a network. We develop an approximation within which we could algebraically specify the feasible region. We analyze the segment polarity gene network to illustrate our approach. The study of random walks in the parameter space and how they exit the feasible region provide us with a rich perspective on the different modes of failure of this network model. In particular, we found that, between two alternative ways of activating Wingless, one is more robust than the other. Our method provides a more complete measure of robustness to parameter variation. As a general modeling strategy, our approach is an interesting alternative to Boolean representation of biochemical networks.
The lumped parameter model for fuel pins
Liu, W S [Ontario Hydro, Toronto, ON (Canada)
1996-12-31
The use of a lumped fuel-pin model in a thermal-hydraulic code is advantageous because of computational simplicity and efficiency. The model uses an averaging approach over the fuel cross section and makes some simplifying assumptions to describe the transient equations for the averaged fuel, fuel centerline and sheath temperatures. It is shown that by introducing a factor in the effective fuel conductivity, the analytical solution of the mean fuel temperature can be modified to simulate the effects of the flux depression in the heat generation rate and the variation in fuel thermal conductivity. The simplified analytical method used in the transient equation is presented. The accuracy of the lumped parameter model has been compared with the results from the finite difference method. (author). 4 refs., 2 tabs., 4 figs.
Modelling human hard palate shape with Bézier curves.
Rick Janssen
Full Text Available People vary at most levels, from the molecular to the cognitive, and the shape of the hard palate (the bony roof of the mouth is no exception. The patterns of variation in the hard palate are important for the forensic sciences and (palaeoanthropology, and might also play a role in speech production, both in pathological cases and normal variation. Here we describe a method based on Bézier curves, whose main aim is to generate possible shapes of the hard palate in humans for use in computer simulations of speech production and language evolution. Moreover, our method can also capture existing patterns of variation using few and easy-to-interpret parameters, and fits actual data obtained from MRI traces very well with as little as two or three free parameters. When compared to the widely-used Principal Component Analysis (PCA, our method fits actual data slightly worse for the same number of degrees of freedom. However, it is much better at generating new shapes without requiring a calibration sample, its parameters have clearer interpretations, and their ranges are grounded in geometrical considerations.
Modeling of Parameters of Subcritical Assembly SAD
Petrochenkov, S; Puzynin, I
2005-01-01
The accepted conceptual design of the experimental Subcritical Assembly in Dubna (SAD) is based on the MOX core with a nominal unit capacity of 25 kW (thermal). This corresponds to the multiplication coefficient $k_{\\rm eff} =0.95$ and accelerator beam power 1 kW. A subcritical assembly driven with the existing 660 MeV proton accelerator at the Joint Institute for Nuclear Research has been modelled in order to make choice of the optimal parameters for the future experiments. The Monte Carlo method was used to simulate neutron spectra, energy deposition and doses calculations. Some of the calculation results are presented in the paper.
Parameter estimation in fractional diffusion models
Kubilius, Kęstutis; Ralchenko, Kostiantyn
2017-01-01
This book is devoted to parameter estimation in diffusion models involving fractional Brownian motion and related processes. For many years now, standard Brownian motion has been (and still remains) a popular model of randomness used to investigate processes in the natural sciences, financial markets, and the economy. The substantial limitation in the use of stochastic diffusion models with Brownian motion is due to the fact that the motion has independent increments, and, therefore, the random noise it generates is “white,” i.e., uncorrelated. However, many processes in the natural sciences, computer networks and financial markets have long-term or short-term dependences, i.e., the correlations of random noise in these processes are non-zero, and slowly or rapidly decrease with time. In particular, models of financial markets demonstrate various kinds of memory and usually this memory is modeled by fractional Brownian diffusion. Therefore, the book constructs diffusion models with memory and provides s...
Low Complexity Models to improve Incomplete Sensitivities for Shape Optimization
Stanciu, Mugurel; Mohammadi, Bijan; Moreau, Stéphane
2003-01-01
The present global platform for simulation and design of multi-model configurations treat shape optimization problems in aerodynamics. Flow solvers are coupled with optimization algorithms based on CAD-free and CAD-connected frameworks. Newton methods together with incomplete expressions of gradients are used. Such incomplete sensitivities are improved using reduced models based on physical assumptions. The validity and the application of this approach in real-life problems are presented. The numerical examples concern shape optimization for an airfoil, a business jet and a car engine cooling axial fan.
Dynamics of a neuron model in different two-dimensional parameter-spaces
Rech, Paulo C.
2011-03-01
We report some two-dimensional parameter-space diagrams numerically obtained for the multi-parameter Hindmarsh-Rose neuron model. Several different parameter planes are considered, and we show that regardless of the combination of parameters, a typical scenario is preserved: for all choice of two parameters, the parameter-space presents a comb-shaped chaotic region immersed in a large periodic region. We also show that exist regions close these chaotic region, separated by the comb teeth, organized themselves in period-adding bifurcation cascades.
Modeling the modified drug release from curved shape drug delivery systems - Dome Matrix®.
Caccavo, D; Barba, A A; d'Amore, M; De Piano, R; Lamberti, G; Rossi, A; Colombo, P
2017-12-01
The controlled drug release from hydrogel-based drug delivery systems is a topic of large interest for research in pharmacology. The mathematical modeling of the behavior of these systems is a tool of emerging relevance, since the simulations can be of use in the design of novel systems, in particular for complex shaped tablets. In this work a model, previously developed, was applied to complex-shaped oral drug delivery systems based on hydrogels (Dome Matrix®). Furthermore, the model was successfully adopted in the description of drug release from partially accessible Dome Matrix® systems (systems with some surfaces coated). In these simulations, the erosion rate was used asa fitting parameter, and its dependence upon the surface area/volume ratio and upon the local fluid dynamics was discussed. The model parameters were determined by comparison with the drug release profile from a cylindrical tablet, then the model was successfully used for the prediction of the drug release from a Dome Matrix® system, for simple module configuration and for module assembled (void and piled) configurations. It was also demonstrated that, given the same initial S/V ratio, the drug release is independent upon the shape of the tablets but it is only influenced by the S/V evolution. The model reveals itself able to describe the observed phenomena, and thus it can be of use for the design of oral drug delivery systems, even if complex shaped. Copyright © 2017 Elsevier B.V. All rights reserved.
Moose models with vanishing S parameter
Casalbuoni, R.; De Curtis, S.; Dominici, D.
2004-01-01
In the linear moose framework, which naturally emerges in deconstruction models, we show that there is a unique solution for the vanishing of the S parameter at the lowest order in the weak interactions. We consider an effective gauge theory based on K SU(2) gauge groups, K+1 chiral fields, and electroweak groups SU(2) L and U(1) Y at the ends of the chain of the moose. S vanishes when a link in the moose chain is cut. As a consequence one has to introduce a dynamical nonlocal field connecting the two ends of the moose. Then the model acquires an additional custodial symmetry which protects this result. We examine also the possibility of a strong suppression of S through an exponential behavior of the link couplings as suggested by the Randall Sundrum metric
Detecting hippocampal shape changes in Alzheimer's disease using statistical shape models
Shen, Kaikai; Bourgeat, Pierrick; Fripp, Jurgen; Meriaudeau, Fabrice; Salvado, Olivier
2011-03-01
The hippocampus is affected at an early stage in the development of Alzheimer's disease (AD). Using brain Magnetic Resonance (MR) images, we can investigate the effect of AD on the morphology of the hippocampus. Statistical shape models (SSM) are usually used to describe and model the hippocampal shape variations among the population. We use the shape variation from SSM as features to classify AD from normal control cases (NC). Conventional SSM uses principal component analysis (PCA) to compute the modes of variations among the population. Although these modes are representative of variations within the training data, they are not necessarily discriminant on labelled data. In this study, a Hotelling's T 2 test is used to qualify the landmarks which can be used for PCA. The resulting variation modes are used as predictors of AD from NC. The discrimination ability of these predictors is evaluated in terms of their classification performances using support vector machines (SVM). Using only landmarks statistically discriminant between AD and NC in SSM showed a better separation between AD and NC. These predictors also showed better correlation to the cognitive scores such as mini-mental state examination (MMSE) and Alzheimer's disease assessment scale (ADAS).
3D Shape Modeling Using High Level Descriptors
Andersen, Vedrana
features like thorns, bark and scales. Presented here is a simple method for easy modeling, transferring and editing that kind of texture. The method is an extension of the height-field texture, but incorporates an additional tilt of the height field. Related to modeling non-heightfield textures, a part...... of my work involved developing feature-aware resizing of models with complex surfaces consisting of underlying shape and a distinctive texture detail. The aim was to deform an object while preserving the shape and size of the features.......The goal of this Ph.D. project is to investigate and improve the methods for describing the surface of 3D objects, with focus on modeling geometric texture on surfaces. Surface modeling being a large field of research, the work done during this project concentrated around a few smaller areas...
van Zyl, J. Martin
2012-01-01
Random variables of the generalized Pareto distribution, can be transformed to that of the Pareto distribution. Explicit expressions exist for the maximum likelihood estimators of the parameters of the Pareto distribution. The performance of the estimation of the shape parameter of generalized Pareto distributed using transformed observations, based on the probability weighted method is tested. It was found to improve the performance of the probability weighted estimator and performs good wit...
Liu, Yang; Shibutan, Yoji [Osaka University, Osaka (Japan); Shimoda, Masatoshi [Toyota Technological Institute, Nagoya (Japan)
2015-04-15
This paper presents a parameter-free shape optimization method for the strength design of stiffeners on thin-walled structures. The maximum von Mises stress is minimized and subjected to the volume constraint. The optimum design problem is formulated as a distributed-parameter shape optimization problem under the assumptions that a stiffener is varied in the in-plane direction and that the thickness is constant. The issue of nondifferentiability, which is inherent in this min-max problem, is avoided by transforming the local measure to a smooth differentiable integral functional by using the Kreisselmeier-Steinhauser function. The shape gradient functions are derived by using the material derivative method and adjoint variable method and are applied to the H{sup 1} gradient method for shells to determine the optimal free-boundary shapes. By using this method, the smooth optimal stiffener shape can be obtained without any shape design parameterization while minimizing the maximum stress. The validity of this method is verified through two practical design examples.
Thermodynamic modelling of shape memory behaviour: some examples
Stalmans, R.; Humbeeck, J. van; Delaey, L.
1995-01-01
This paper gives a general view of a recently developed thermodynamic model of the thermoelastic martensitic transformation. Unlike existing empirical, mathematical or thermodynamic models, this generalised thermodynamic model can be used to understand and describe quantitatively the overall thermomechanical behaviour of polycrystalline shape memory alloys. Important points of difference between this and previous thermodynamic models are that the contributions of the stored elastic energy and of the crystal defects are also included. In addition, the mathematical approach and the assumptions in this model are selected in such a way that the calculations yield close approximations of the real behaviour and that the final mathematical equations are relatively simple. Several illustrations indicate that this model, in contrast to other models, can be used to understand the shape memory behaviour of complex cases. As an example of quantitative calculations, it is shown that this modelling can be an effective tool in the ''design'' of multifunctional materials consisting of shape memory elements embedded in matrix materials. (orig.)
Guo, Ning; Yang, Zhichun; Wang, Le; Ouyang, Yan; Zhang, Xinping
2018-05-01
Aiming at providing a precise dynamic structural finite element (FE) model for dynamic strength evaluation in addition to dynamic analysis. A dynamic FE model updating method is presented to correct the uncertain parameters of the FE model of a structure using strain mode shapes and natural frequencies. The strain mode shape, which is sensitive to local changes in structure, is used instead of the displacement mode for enhancing model updating. The coordinate strain modal assurance criterion is developed to evaluate the correlation level at each coordinate over the experimental and the analytical strain mode shapes. Moreover, the natural frequencies which provide the global information of the structure are used to guarantee the accuracy of modal properties of the global model. Then, the weighted summation of the natural frequency residual and the coordinate strain modal assurance criterion residual is used as the objective function in the proposed dynamic FE model updating procedure. The hybrid genetic/pattern-search optimization algorithm is adopted to perform the dynamic FE model updating procedure. Numerical simulation and model updating experiment for a clamped-clamped beam are performed to validate the feasibility and effectiveness of the present method. The results show that the proposed method can be used to update the uncertain parameters with good robustness. And the updated dynamic FE model of the beam structure, which can correctly predict both the natural frequencies and the local dynamic strains, is reliable for the following dynamic analysis and dynamic strength evaluation.
A three-dimensional constitutive model for shape memory alloy
Zhou, Bo; Yoon, Sung-Ho; Leng, Jin-Song
2009-01-01
Shape memory alloy (SMA) has a wide variety of practical applications due to its unique super-elasticity and shape memory effect. It is of practical interest to establish a constitutive model which predicts its phase transformation and mechanical behaviors. In this paper, a new three-dimensional phase transformation equation, which predicts the phase transformation behaviors of SMA, is developed based on the results of a differential scanning calorimetry (DSC) test. It overcomes both limitations: that Zhou's phase transformation equations fail to describe the phase transformation from twinned martensite to detwinned martensite of SMA and Brinson's phase transformation equation fails to express the influences of phase transformation peak temperatures on the phase transformation behaviors of SMA. A new three-dimensional constitutive equation, which predicts the mechanical behaviors associated with the super-elasticity and shape memory effect of SMA, is developed on the basis of thermodynamics and solid mechanics. Results of numerical simulations show that the new constitutive model, which includes the new phase transformation equation and constitutive equation, can predict the phase transformation and mechanical behaviors associated with the super-elasticity and shape memory effect of SMA precisely and comprehensively. It is proved that Brinson's constitutive model of SMA can be considered as one special case of the new constitutive model
Polynomial constitutive model for shape memory and pseudo elasticity
Savi, M.A.; Kouzak, Z.
1995-01-01
This paper reports an one-dimensional phenomenological constitutive model for shape memory and pseudo elasticity using a polynomial expression for the free energy which is based on the classical Devonshire theory. This study identifies the main characteristics of the classical theory and introduces a simple modification to obtain better results. (author). 9 refs., 6 figs
Irregular Shaped Building Design Optimization with Building Information Modelling
Lee Xia Sheng
2016-01-01
Full Text Available This research is to recognise the function of Building Information Modelling (BIM in design optimization for irregular shaped buildings. The study focuses on a conceptual irregular shaped “twisted” building design similar to some existing sculpture-like architectures. Form and function are the two most important aspects of new buildings, which are becoming more sophisticated as parts of equally sophisticated “systems” that we are living in. Nowadays, it is common to have irregular shaped or sculpture-like buildings which are very different when compared to regular buildings. Construction industry stakeholders are facing stiff challenges in many aspects such as buildability, cost effectiveness, delivery time and facility management when dealing with irregular shaped building projects. Building Information Modelling (BIM is being utilized to enable architects, engineers and constructors to gain improved visualization for irregular shaped buildings; this has a purpose of identifying critical issues before initiating physical construction work. In this study, three variations of design options differing in rotating angle: 30 degrees, 60 degrees and 90 degrees are created to conduct quantifiable comparisons. Discussions are focused on three major aspects including structural planning, usable building space, and structural constructability. This research concludes that Building Information Modelling is instrumental in facilitating design optimization for irregular shaped building. In the process of comparing different design variations, instead of just giving “yes or no” type of response, stakeholders can now easily visualize, evaluate and decide to achieve the right balance based on their own criteria. Therefore, construction project stakeholders are empowered with superior evaluation and decision making capability.
Eight equation model for arbitrary shaped pipe conveying fluid
Gale, J.; Tiselj, I.
2006-01-01
Linear eight-equation system for two-way coupling of single-phase fluid transient and arbitrary shaped one-dimensional pipeline movement is described and discussed. The governing phenomenon described with this system is also known as Fluid-Structure Interaction. Standard Skalak's four-equation model for axial coupling was improved with additional four Timoshenko's beam equations for description of flexural displacements and rotations. In addition to the conventional eight-equation system that enables coupling of straight sections, the applied mathematical model was improved for description of the arbitrary shaped pipeline located in two-dimensional plane. The applied model was solved with second-order accurate numerical method that is based on Godounov's characteristic upwind schemes. The model was successfully used for simulation of the rod impact induced transient and conventional instantaneous valve closure induced transient in the tank-pipe-valve system. (author)
A Minimal Path Searching Approach for Active Shape Model (ASM)-based Segmentation of the Lung.
Guo, Shengwen; Fei, Baowei
2009-03-27
We are developing a minimal path searching method for active shape model (ASM)-based segmentation for detection of lung boundaries on digital radiographs. With the conventional ASM method, the position and shape parameters of the model points are iteratively refined and the target points are updated by the least Mahalanobis distance criterion. We propose an improved searching strategy that extends the searching points in a fan-shape region instead of along the normal direction. A minimal path (MP) deformable model is applied to drive the searching procedure. A statistical shape prior model is incorporated into the segmentation. In order to keep the smoothness of the shape, a smooth constraint is employed to the deformable model. To quantitatively assess the ASM-MP segmentation, we compare the automatic segmentation with manual segmentation for 72 lung digitized radiographs. The distance error between the ASM-MP and manual segmentation is 1.75 ± 0.33 pixels, while the error is 1.99 ± 0.45 pixels for the ASM. Our results demonstrate that our ASM-MP method can accurately segment the lung on digital radiographs.
A minimal path searching approach for active shape model (ASM)-based segmentation of the lung
Guo, Shengwen; Fei, Baowei
2009-02-01
We are developing a minimal path searching method for active shape model (ASM)-based segmentation for detection of lung boundaries on digital radiographs. With the conventional ASM method, the position and shape parameters of the model points are iteratively refined and the target points are updated by the least Mahalanobis distance criterion. We propose an improved searching strategy that extends the searching points in a fan-shape region instead of along the normal direction. A minimal path (MP) deformable model is applied to drive the searching procedure. A statistical shape prior model is incorporated into the segmentation. In order to keep the smoothness of the shape, a smooth constraint is employed to the deformable model. To quantitatively assess the ASM-MP segmentation, we compare the automatic segmentation with manual segmentation for 72 lung digitized radiographs. The distance error between the ASM-MP and manual segmentation is 1.75 +/- 0.33 pixels, while the error is 1.99 +/- 0.45 pixels for the ASM. Our results demonstrate that our ASM-MP method can accurately segment the lung on digital radiographs.
Models for setting ATM parameter values
Blaabjerg, Søren; Gravey, A.; Romæuf, L.
1996-01-01
essential to set traffic characteristic values that are relevant to the considered cell stream, and that ensure that the amount of non-conforming traffic is small. Using a queueing model representation for the GCRA formalism, several methods are available for choosing the traffic characteristics. This paper......In ATM networks, a user should negotiate at connection set-up a traffic contract which includes traffic characteristics and requested QoS. The traffic characteristics currently considered are the Peak Cell Rate, the Sustainable Cell Rate, the Intrinsic Burst Tolerance and the Cell Delay Variation...... (CDV) tolerance(s). The values taken by these traffic parameters characterize the so-called ''Worst Case Traffic'' that is used by CAC procedures for accepting a new connection and allocating resources to it. Conformance to the negotiated traffic characteristics is defined, at the ingress User...
Orthodontic applications of a superelastic shape-memory alloy model
Glendenning, R.W.; Enlow, R.L.
2000-01-01
During orthodontic treatment, dental appliances (braces) made of shape memory alloys have the potential to provide nearly uniform low level stresses to dentitions during tooth movement over a large range of tooth displacement. In this paper we model superelastic behaviour of dental appliances using the finite element method and constitutive equations developed by F. Auricchio et al. Results of the mathematical model for 3-point bending and several promising 'closing loop' designs are compared with laboratory results for the same configurations. (orig.)
Modeling the behaviour of shape memory materials under large deformations
Rogovoy, A. A.; Stolbova, O. S.
2017-06-01
In this study, the models describing the behavior of shape memory alloys, ferromagnetic materials and polymers have been constructed, using a formalized approach to develop the constitutive equations for complex media under large deformations. The kinematic and constitutive equations, satisfying the principles of thermodynamics and objectivity, have been derived. The application of the Galerkin procedure to the systems of equations of solid mechanics allowed us to obtain the Lagrange variational equation and variational formulation of the magnetostatics problems. These relations have been tested in the context of the problems of finite deformation in shape memory alloys and ferromagnetic materials during forward and reverse martensitic transformations and in shape memory polymers during forward and reverse relaxation transitions from a highly elastic to a glassy state.
First Principles Modelling of Shape Memory Alloys Molecular Dynamics Simulations
Kastner, Oliver
2012-01-01
Materials sciences relate the macroscopic properties of materials to their microscopic structure and postulate the need for holistic multiscale research. The investigation of shape memory alloys is a prime example in this regard. This particular class of materials exhibits strong coupling of temperature, strain and stress, determined by solid state phase transformations of their metallic lattices. The present book presents a collection of simulation studies of this behaviour. Employing conceptually simple but comprehensive models, the fundamental material properties of shape memory alloys are qualitatively explained from first principles. Using contemporary methods of molecular dynamics simulation experiments, it is shown how microscale dynamics may produce characteristic macroscopic material properties. The work is rooted in the materials sciences of shape memory alloys and covers thermodynamical, micro-mechanical and crystallographical aspects. It addresses scientists in these research fields and thei...
Development of an engineering model for ferromagnetic shape memory alloys
Tani, Yoshiaki; Todaka, Takashi; Enokizono, Masato
2008-01-01
This paper presents a relationship among stress, temperature and magnetic properties of a ferromagnetic shape memory alloy. In order to derive an engineering model of ferromagnetic shape memory alloys, we have developed a measuring system of the relationship among stress, temperature and magnetic properties. The samples used in this measurement are Fe68-Ni10-Cr9-Mn7-Si6 wt% ferromagnetic shape memory alloy. They are thin ribbons made by rapid cooling in air. In the measurement, the ribbon sample is inserted into a sample holder winding consisting of the B-coil and compensation coils, and magnetized in an open solenoid coil. The ribbon is stressed with attachment weights and heated with a heating wire. The specific susceptibility was increased by applying tension, and slightly increased by heating below the Curie temperature
Radar observations and shape model of asteroid 16 Psyche
Shepard, Michael K.; Richardson, James; Taylor, Patrick A.; Rodriguez-Ford, Linda A.; Conrad, Al; de Pater, Imke; Adamkovics, Mate; de Kleer, Katherine; Males, Jared R.; Morzinski, Katie M.; Close, Laird M.; Kaasalainen, Mikko; Viikinkoski, Matti; Timerson, Bradley; Reddy, Vishnu; Magri, Christopher; Nolan, Michael C.; Howell, Ellen S.; Benner, Lance A. M.; Giorgini, Jon D.; Warner, Brian D.; Harris, Alan W.
2017-01-01
Using the S-band radar at Arecibo Observatory, we observed 16 Psyche, the largest M-class asteroid in the main belt. We obtained 18 radar imaging and 6 continuous wave runs in November and December 2015, and combined these with 16 continuous wave runs from 2005 and 6 recent adaptive-optics (AO) images (Drummond et al., 2016) to generate a three-dimensional shape model of Psyche. Our model is consistent with a previously published AO image (Hanus et al., 2013) and three multi-chord occultations. Our shape model has dimensions 279 × 232 × 189 km (± 10%), Deff = 226 ± 23 km, and is 6% larger than, but within the uncertainties of, the most recently published size and shape model generated from the inversion of lightcurves (Hanus et al., 2013). Psyche is roughly ellipsoidal but displays a mass-deficit over a region spanning 90° of longitude. There is also evidence for two ∼50-70 km wide depressions near its south pole. Our size and published masses lead to an overall bulk density estimate of 4500 ± 1400 kgm-3. Psyche's mean radar albedo of 0.37 ± 0.09 is consistent with a near-surface regolith composed largely of iron-nickel and ∼40% porosity. Its radar reflectivity varies by a factor of 1.6 as the asteroid rotates, suggesting global variations in metal abundance or bulk density in the near surface. The variations in radar albedo appear to correlate with large and small-scale shape features. Our size and Psyche's published absolute magnitude lead to an optical albedo of pv = 0.15 ± 0.03, and there is evidence for albedo variegations that correlate with shape features.
Asteroid 16 Psyche: Radar Observations and Shape Model
Shepard, Michael K.; Richardson, James E.; Taylor, Patrick A.; Rodriguez-Ford, Linda A.; Conrad, Al; de Pater, Imke; Adamkovics, Mate; de Kleer, Katherine R.; Males, Jared; Morzinski, Kathleen M.; Miller Close, Laird; Kaasalainen, Mikko; Viikinkoski, Matti; Timerson, Bradley; Reddy, Vishnu; Magri, Christopher; Nolan, Michael C.; Howell, Ellen S.; Warner, Brian D.; Harris, Alan W.
2016-10-01
We observed 16 Psyche, the largest M-class asteroid in the main belt, using the S-band radar at Arecibo Observatory. We obtained 18 radar imaging and 6 continuous wave runs in November and December 2015, and combined these with 16 continuous wave runs from 2005 and 6 recent adaptive-optics (AO) images to generate a three-dimensional shape model of Psyche. Our model is consistent with a previously published AO image [Hanus et al. Icarus 226, 1045-1057, 2013] and three multi-chord occultations. Our shape model has dimensions 279 x 232 x 189 km (±10%), Deff = 226 ± 23 km, and is 6% larger than, but within the uncertainties of, the most recently published size and shape model generated from the inversion of lightcurves [Hanus et al., 2013]. Psyche is roughly ellipsoidal but displays a mass-deficit over a region spanning 90° of longitude. There is also evidence for two ~50-70 km wide depressions near its south pole. Our size and published masses lead to an overall bulk density estimate of 4500 ± 1400 kg m-3. Psyche's mean radar albedo of 0.37 ± 0.09 is consistent with a near-surface regolith composed largely of iron-nickel and ~40% porosity. Its radar reflectivity varies by a factor of 1.6 as the asteroid rotates, suggesting global variations in metal abundance or bulk density in the near surface. The variations in radar albedo appear to correlate with large and small-scale shape features. Our size and Psyche's published absolute magnitude lead to an optical albedo of pv = 0.15 ± 0.03, and there is evidence for albedo variegations that correlate with shape features.
3D active shape modeling for cardiac MR and CT image segmentation
Assen, Hans Christiaan van
2006-01-01
3D Active Shape Modeling is a technique to capture shape information from a training set containing characteristic shapes of, e.g., a heart. The description contains a mean shape, and shape variations (e.g. eigen deformations and eigen values). Many models based on these statistics, and used for
Parameter Estimation of Partial Differential Equation Models
Xun, Xiaolei; Cao, Jiguo; Mallick, Bani; Maity, Arnab; Carroll, Raymond J.
2013-01-01
PDEs used in practice have no analytic solutions, and can only be solved with numerical methods. Currently, methods for estimating PDE parameters require repeatedly solving PDEs numerically under thousands of candidate parameter values, and thus
Baka, N.; Kaptein, B. L.; de Bruijne, Marleen
2011-01-01
Three-dimensional patient specific bone models are required in a range of medical applications, such as pre-operative surgery planning and improved guidance during surgery, modeling and simulation, and in vivo bone motion tracking. Shape reconstruction from a small number of X-ray images is desired...... as it lowers both the acquisition costs and the radiation dose compared to CT. We propose a method for pose estimation and shape reconstruction of 3D bone surfaces from two (or more) calibrated X-ray images using a statistical shape model (SSM). User interaction is limited to manual initialization of the mean...... pose estimation of ground truth shapes as well as 3D shape estimation using a SSM of the whole femur, from stereo cadaver X-rays, in vivo biplane fluoroscopy image-pairs, and an in vivo biplane fluoroscopic sequence. Ground truth shapes for all experiments were available in the form of CT segmentations...
A simple shape-free model for pore-size estimation with positron annihilation lifetime spectroscopy
Wada, Ken; Hyodo, Toshio
2013-01-01
Positron annihilation lifetime spectroscopy is one of the methods for estimating pore size in insulating materials. We present a shape-free model to be used conveniently for such analysis. A basic model in classical picture is modified by introducing a parameter corresponding to an effective size of the positronium (Ps). This parameter is adjusted so that its Ps-lifetime to pore-size relation merges smoothly with that of the well-established Tao-Eldrup model (with modification involving the intrinsic Ps annihilation rate) applicable to very small pores. The combined model, i.e., modified Tao-Eldrup model for smaller pores and the modified classical model for larger pores, agrees surprisingly well with the quantum-mechanics based extended Tao-Eldrup model, which deals with Ps trapped in and thermally equilibrium with a rectangular pore.
A simple shape-free model for pore-size estimation with positron annihilation lifetime spectroscopy
Wada, Ken; Hyodo, Toshio
2013-06-01
Positron annihilation lifetime spectroscopy is one of the methods for estimating pore size in insulating materials. We present a shape-free model to be used conveniently for such analysis. A basic model in classical picture is modified by introducing a parameter corresponding to an effective size of the positronium (Ps). This parameter is adjusted so that its Ps-lifetime to pore-size relation merges smoothly with that of the well-established Tao-Eldrup model (with modification involving the intrinsic Ps annihilation rate) applicable to very small pores. The combined model, i.e., modified Tao-Eldrup model for smaller pores and the modified classical model for larger pores, agrees surprisingly well with the quantum-mechanics based extended Tao-Eldrup model, which deals with Ps trapped in and thermally equilibrium with a rectangular pore.
Bian, X. X.; Gu, Y. Z.; Sun, J.; Li, M.; Liu, W. P.; Zhang, Z. G.
2013-10-01
In this study, the effects of processing temperature and vacuum applying rate on the forming quality of C-shaped carbon fiber reinforced epoxy resin matrix composite laminates during hot diaphragm forming process were investigated. C-shaped prepreg preforms were produced using a home-made hot diaphragm forming equipment. The thickness variations of the preforms and the manufacturing defects after diaphragm forming process, including fiber wrinkling and voids, were evaluated to understand the forming mechanism. Furthermore, both interlaminar slipping friction and compaction behavior of the prepreg stacks were experimentally analyzed for showing the importance of the processing parameters. In addition, autoclave processing was used to cure the C-shaped preforms to investigate the changes of the defects before and after cure process. The results show that the C-shaped prepreg preforms with good forming quality can be achieved through increasing processing temperature and reducing vacuum applying rate, which obviously promote prepreg interlaminar slipping process. The process temperature and forming rate in hot diaphragm forming process strongly influence prepreg interply frictional force, and the maximum interlaminar frictional force can be taken as a key parameter for processing parameter optimization. Autoclave process is effective in eliminating voids in the preforms and can alleviate fiber wrinkles to a certain extent.
Bohr model description of the critical point for the first order shape phase transition
Budaca, R.; Buganu, P.; Budaca, A. I.
2018-01-01
The critical point of the shape phase transition between spherical and axially deformed nuclei is described by a collective Bohr Hamiltonian with a sextic potential having simultaneous spherical and deformed minima of the same depth. The particular choice of the potential as well as the scaled and decoupled nature of the total Hamiltonian leads to a model with a single free parameter connected to the height of the barrier which separates the two minima. The solutions are found through the diagonalization in a basis of Bessel functions. The basis is optimized for each value of the free parameter by means of a boundary deformation which assures the convergence of the solutions for a fixed basis dimension. Analyzing the spectral properties of the model, as a function of the barrier height, revealed instances with shape coexisting features which are considered for detailed numerical applications.
Bohr model description of the critical point for the first order shape phase transition
R. Budaca
2018-01-01
Full Text Available The critical point of the shape phase transition between spherical and axially deformed nuclei is described by a collective Bohr Hamiltonian with a sextic potential having simultaneous spherical and deformed minima of the same depth. The particular choice of the potential as well as the scaled and decoupled nature of the total Hamiltonian leads to a model with a single free parameter connected to the height of the barrier which separates the two minima. The solutions are found through the diagonalization in a basis of Bessel functions. The basis is optimized for each value of the free parameter by means of a boundary deformation which assures the convergence of the solutions for a fixed basis dimension. Analyzing the spectral properties of the model, as a function of the barrier height, revealed instances with shape coexisting features which are considered for detailed numerical applications.
Patch-based generative shape model and MDL model selection for statistical analysis of archipelagos
Ganz, Melanie; Nielsen, Mads; Brandt, Sami
2010-01-01
We propose a statistical generative shape model for archipelago-like structures. These kind of structures occur, for instance, in medical images, where our intention is to model the appearance and shapes of calcifications in x-ray radio graphs. The generative model is constructed by (1) learning ...
Wavefront control performance modeling with WFIRST shaped pupil coronagraph testbed
Zhou, Hanying; Nemati, Bijian; Krist, John; Cady, Eric; Kern, Brian; Poberezhskiy, Ilya
2017-09-01
NASA's WFIRST mission includes a coronagraph instrument (CGI) for direct imaging of exoplanets. Significant improvement in CGI model fidelity has been made recently, alongside a testbed high contrast demonstration in a simulated dynamic environment at JPL. We present our modeling method and results of comparisons to testbed's high order wavefront correction performance for the shaped pupil coronagraph. Agreement between model prediction and testbed result at better than a factor of 2 has been consistently achieved in raw contrast (contrast floor, chromaticity, and convergence), and with that comes good agreement in contrast sensitivity to wavefront perturbations and mask lateral shear.
SHERMAN - A shape-based thermophysical model II. Application to 8567 (1996 HW1)
Howell, E. S.; Magri, C.; Vervack, R. J.; Nolan, M. C.; Taylor, P. A.; Fernández, Y. R.; Hicks, M. D.; Somers, J. M.; Lawrence, K. J.; Rivkin, A. S.; Marshall, S. E.; Crowell, J. L.
2018-03-01
We apply a new shape-based thermophysical model, SHERMAN, to the near-Earth asteroid (NEA) 8567 (1996 HW1) to derive surface properties. We use the detailed shape model of Magri et al. (2011) for this contact binary NEA to analyze spectral observations (2-4.1 microns) obtained at the NASA IRTF on several different dates to find thermal parameters that match all the data. Visible and near-infrared (0.8-2.5 microns) spectral observations are also utilized in a self-consistent way. We find that an average visible albedo of 0.33, thermal inertia of 70 (SI units) and surface roughness of 50% closely match the observations. The shape and orientation of the asteroid is very important to constrain the thermal parameters to be consistent with all the observations. Multiple viewing geometries are equally important to achieve a robust solution for small, non-spherical NEAs. We separate the infrared beaming effects of shape, viewing geometry and surface roughness for this asteroid and show how their effects combine. We compare the diameter and albedo that would be derived from the thermal observations assuming a spherical shape with those from the shape-based model. We also discuss how observations from limited viewing geometries compare to the solution from multiple observations. The size that would be derived from the individual observation dates varies by 20% from the best-fit solution, and can be either larger or smaller. If the surface properties are not homogeneous, many solutions are possible, but the average properties derived here are very tightly constrained by the multiple observations, and give important insights into the nature of small NEAs.
A macroscopic model for magnetic shape-memory single crystals
Bessoud, A. L.; Kružík, Martin; Stefanelli, U.
2013-01-01
Roč. 64, č. 2 (2013), s. 343-359 ISSN 0044-2275 R&D Projects: GA AV ČR IAA100750802; GA ČR GAP201/10/0357 Institutional support: RVO:67985556 Keywords : magnetostriction * evolution Subject RIV: BA - General Mathematics Impact factor: 1.214, year: 2013 http://library.utia.cas.cz/separaty/2012/MTR/kruzik-a macroscopic model for magnetic shape- memory single crystals.pdf
Feng, Ssj; Sechopoulos, I
2012-06-01
To develop an objective model of the shape of the compressed breast undergoing mammographic or tomosynthesis acquisition. Automated thresholding and edge detection was performed on 984 anonymized digital mammograms (492 craniocaudal (CC) view mammograms and 492 medial lateral oblique (MLO) view mammograms), to extract the edge of each breast. Principal Component Analysis (PCA) was performed on these edge vectors to identify a limited set of parameters and eigenvectors that. These parameters and eigenvectors comprise a model that can be used to describe the breast shapes present in acquired mammograms and to generate realistic models of breasts undergoing acquisition. Sample breast shapes were then generated from this model and evaluated. The mammograms in the database were previously acquired for a separate study and authorized for use in further research. The PCA successfully identified two principal components and their corresponding eigenvectors, forming the basis for the breast shape model. The simulated breast shapes generated from the model are reasonable approximations of clinically acquired mammograms. Using PCA, we have obtained models of the compressed breast undergoing mammographic or tomosynthesis acquisition based on objective analysis of a large image database. Up to now, the breast in the CC view has been approximated as a semi-circular tube, while there has been no objectively-obtained model for the MLO view breast shape. Such models can be used for various breast imaging research applications, such as x-ray scatter estimation and correction, dosimetry estimates, and computer-aided detection and diagnosis. © 2012 American Association of Physicists in Medicine.
Mohammad Sirousazar
2017-07-01
Full Text Available Water loss kinetics in osmotic dehydration of cone-shaped fruits and vegetables was modeled on the basis of diffusion mechanism, using the Fick’s second law. The model was developed by taking into account the influences of the fruit geometrical characteristics, initial water content of fruit, water diffusion coefficient in fruit, and the water concentration in hypertonic solution. Based on the obtained model, it was shown that the water diffusion coefficient and the initial water concentration of fruit have direct effects on the dehydration rate and also inverse influence on the dehydration duration. The geometrical parameters of fruit and water concentration in hypertonic solution showed direct effect on the dehydration duration as well as inverse effect on the dehydration rate. The presented model seems to be useful tool to predict the dehydration kinetics of cone-shaped fruit during osmotic dehydration process and to optimize the process prior to perform the experiments.
Modelling stochastic chances in curve shape, with an application to cancer diagnostics
Hobolth, A; Jensen, Eva B. Vedel
2000-01-01
Often, the statistical analysis of the shape of a random planar curve is based on a model for a polygonal approximation to the curve. In the present paper, we instead describe the curve as a continuous stochastic deformation of a template curve. The advantage of this continuous approach is that t......Often, the statistical analysis of the shape of a random planar curve is based on a model for a polygonal approximation to the curve. In the present paper, we instead describe the curve as a continuous stochastic deformation of a template curve. The advantage of this continuous approach...... is that the parameters in the model do not relate to a particular polygonal approximation. A somewhat similar approach has been used by Kent et al. (1996), who describe the limiting behaviour of a model with a first-order Markov property as the landmarks on the curve become closely spaced; see also Grenander(1993...
Strickler, D.J.; Peng, Y-K.M.; Jardin, S.C.; Pomphrey, N.
1990-01-01
The plasma shaping flexibility of the Compact Ignition Tokamak (CIT) poloidal field (PF) coil set is demonstrated through MHD equilibrium calculations of optimal PF coil current distributions and their variation with poloidal beta, internal inductance, plasma 95% elongation, and 95% triangularity. Calculations of the magnetic stored energy are used to compare solutions associated with various plasma parameters. The Control Matrix (CM) equilibrium code, together with the nonlinear equation and numerical optimization software packages HYBRD, and VMCON, respectively, are used to find equilibrium coil current distributions for fixed divertor geometry, volt-seconds, and plasma profiles in order to isolate the dependence on individual parameters. A reference equilibrium and coil current distribution are chosen, and correction currents dI are determined using the CM equilibrium method to obtain other specified plasma shapes. The reference equilibrium is the κ = 2 divertor at beginning of flattop (BOFT) with a minimum stored energy solution for the coil current distribution. The pressure profile function is fixed
Chetan Aneja
2016-07-01
Full Text Available In the present experimental study, dissimilar aluminum alloy AA5083 and AA6082 were friction stir welded by varying tool shape, welding speed and rotary speed of the tool in order to investigate the effect of varying tool shape and welding parameters on the mechanical properties as well as microstructure. The friction stir welding (FSW process parameters have great influence on heat input per unit length of weld. The outcomes of experimental study prove that mechanical properties increases with decreasing welding speed. Furthermore mechanical properties were also found to improve as the rotary speed increases and the same phenomenon was found to happen while using straight cylindrical threaded pin profile tool. The microstructure of the dissimilar joints revealed that at low welding speeds, the improved material mixing was observed. The similar phenomenon was found to happen at higher rotational speeds using straight cylindrical threaded tool.
Automated robust generation of compact 3D statistical shape models
Vrtovec, Tomaz; Likar, Bostjan; Tomazevic, Dejan; Pernus, Franjo
2004-05-01
Ascertaining the detailed shape and spatial arrangement of anatomical structures is important not only within diagnostic settings but also in the areas of planning, simulation, intraoperative navigation, and tracking of pathology. Robust, accurate and efficient automated segmentation of anatomical structures is difficult because of their complexity and inter-patient variability. Furthermore, the position of the patient during image acquisition, the imaging device and protocol, image resolution, and other factors induce additional variations in shape and appearance. Statistical shape models (SSMs) have proven quite successful in capturing structural variability. A possible approach to obtain a 3D SSM is to extract reference voxels by precisely segmenting the structure in one, reference image. The corresponding voxels in other images are determined by registering the reference image to each other image. The SSM obtained in this way describes statistically plausible shape variations over the given population as well as variations due to imperfect registration. In this paper, we present a completely automated method that significantly reduces shape variations induced by imperfect registration, thus allowing a more accurate description of variations. At each iteration, the derived SSM is used for coarse registration, which is further improved by describing finer variations of the structure. The method was tested on 64 lumbar spinal column CT scans, from which 23, 38, 45, 46 and 42 volumes of interest containing vertebra L1, L2, L3, L4 and L5, respectively, were extracted. Separate SSMs were generated for each vertebra. The results show that the method is capable of reducing the variations induced by registration errors.
Visualization of the variability of 3D statistical shape models by animation.
Lamecker, Hans; Seebass, Martin; Lange, Thomas; Hege, Hans-Christian; Deuflhard, Peter
2004-01-01
Models of the 3D shape of anatomical objects and the knowledge about their statistical variability are of great benefit in many computer assisted medical applications like images analysis, therapy or surgery planning. Statistical model of shapes have successfully been applied to automate the task of image segmentation. The generation of 3D statistical shape models requires the identification of corresponding points on two shapes. This remains a difficult problem, especially for shapes of complicated topology. In order to interpret and validate variations encoded in a statistical shape model, visual inspection is of great importance. This work describes the generation and interpretation of statistical shape models of the liver and the pelvic bone.
Orthodontic applications of a superelastic shape-memory alloy model
Glendenning, R.W.; Enlow, R.L. [Otago Univ., Dunedin (New Zealand). Dept. of Math. and Stat.; Hood, J.A.A. [Dept. of Oral Sciences and Orthodontics, Univ. of Otago, Dunedin (New Zealand)
2000-07-01
During orthodontic treatment, dental appliances (braces) made of shape memory alloys have the potential to provide nearly uniform low level stresses to dentitions during tooth movement over a large range of tooth displacement. In this paper we model superelastic behaviour of dental appliances using the finite element method and constitutive equations developed by F. Auricchio et al. Results of the mathematical model for 3-point bending and several promising 'closing loop' designs are compared with laboratory results for the same configurations. (orig.)
Electropolishing on single-cell: (TESLA, Reentrant and Low Loss shapes) Comsol modelling
Bruchon, M.
2007-01-01
In the framework of improvement of cavity electropolishing, modelling permits to evaluate some parameters not easily accessible by experiments and can also help us to guide them. Different laboratories (DESY, Fermilab) work on electro or chemical polishing modelling with different approaches and softwares. At CEA Saclay, COMSOL software is used to model horizontal electropolishing of cavity in two dimensions. The goal of this study has been motivated by improvement of our electropolishing setup by modifying the arrival of the acid. The influence of a protuberant cathode has been evaluated and compared for different shapes of single cell cavities: TESLA, ILC Low Loss (LL ILC ), and ILC Reentrant (RE ILC ). (author)
Batmanov, Kirill; Wang, Junbai
2017-09-18
DNA shape readout is an important mechanism of transcription factor target site recognition, in addition to the sequence readout. Several machine learning-based models of transcription factor-DNA interactions, considering DNA shape features, have been developed in recent years. Here, we present a new biophysical model of protein-DNA interactions by integrating the DNA shape properties. It is based on the neighbor dinucleotide dependency model BayesPI2, where new parameters are restricted to a subspace spanned by the dinucleotide form of DNA shape features. This allows a biophysical interpretation of the new parameters as a position-dependent preference towards specific DNA shape features. Using the new model, we explore the variation of DNA shape preferences in several transcription factors across various cancer cell lines and cellular conditions. The results reveal that there are DNA shape variations at FOXA1 (Forkhead Box Protein A1) binding sites in steroid-treated MCF7 cells. The new biophysical model is useful for elucidating the finer details of transcription factor-DNA interaction, as well as for predicting cancer mutation effects in the future.
Diabatic models with transferrable parameters for generalized chemical reactions
Reimers, Jeffrey R; McKemmish, Laura K; McKenzie, Ross H; Hush, Noel S
2017-01-01
Diabatic models applied to adiabatic electron-transfer theory yield many equations involving just a few parameters that connect ground-state geometries and vibration frequencies to excited-state transition energies and vibration frequencies to the rate constants for electron-transfer reactions, utilizing properties of the conical-intersection seam linking the ground and excited states through the Pseudo Jahn-Teller effect. We review how such simplicity in basic understanding can also be obtained for general chemical reactions. The key feature that must be recognized is that electron-transfer (or hole transfer) processes typically involve one electron (hole) moving between two orbitals, whereas general reactions typically involve two electrons or even four electrons for processes in aromatic molecules. Each additional moving electron leads to new high-energy but interrelated conical-intersection seams that distort the shape of the critical lowest-energy seam. Recognizing this feature shows how conical-intersection descriptors can be transferred between systems, and how general chemical reactions can be compared using the same set of simple parameters. Mathematical relationships are presented depicting how different conical-intersection seams relate to each other, showing that complex problems can be reduced into an effective interaction between the ground-state and a critical excited state to provide the first semi-quantitative implementation of Shaik’s “twin state” concept. Applications are made (i) demonstrating why the chemistry of the first-row elements is qualitatively so different to that of the second and later rows, (ii) deducing the bond-length alternation in hypothetical cyclohexatriene from the observed UV spectroscopy of benzene, (iii) demonstrating that commonly used procedures for modelling surface hopping based on inclusion of only the first-derivative correction to the Born-Oppenheimer approximation are valid in no region of the chemical
Modeling Macroscopic Shape Distortions during Sintering of Multi-layers
Tadesse Molla, Tesfaye
as to help achieve defect free multi-layer components. The initial thickness ratio between the layers making the multi-layer has also significant effect on the extent of camber evolution depending on the material systems. During sintering of tubular bi-layer structures, tangential (hoop) stresses are very...... large compared to radial stresses. The maximum value of hoop stress, which can generate processing defects such as cracks and coating peel-offs, occurs at the beginning of the sintering cycle. Unlike most of the models defining material properties based on porosity and grain size only, the multi...... (firing). However, unintended features like shape instabilities of samples, cracks or delamination of layers may arise during sintering of multi-layer composites. Among these defects, macroscopic shape distortions in the samples can cause problems in the assembly or performance of the final component...
A stress-induced phase transition model for semi-crystallize shape memory polymer
Guo, Xiaogang; Zhou, Bo; Liu, Liwu; Liu, Yanju; Leng, Jinsong
2014-03-01
The developments of constitutive models for shape memory polymer (SMP) have been motivated by its increasing applications. During cooling or heating process, the phase transition which is a continuous time-dependent process happens in semi-crystallize SMP and the various individual phases form at different temperature and in different configuration. Then, the transformation between these phases occurred and shape memory effect will emerge. In addition, stress applied on SMP is an important factor for crystal melting during phase transition. In this theory, an ideal phase transition model considering stress or pre-strain is the key to describe the behaviors of shape memory effect. So a normal distributed model was established in this research to characterize the volume fraction of each phase in SMP during phase transition. Generally, the experiment results are partly backward (in heating process) or forward (in cooling process) compared with the ideal situation considering delay effect during phase transition. So, a correction on the normal distributed model is needed. Furthermore, a nonlinear relationship between stress and phase transition temperature Tg is also taken into account for establishing an accurately normal distributed phase transition model. Finally, the constitutive model which taking the stress as an influence factor on phase transition was also established. Compared with the other expressions, this new-type model possesses less parameter and is more accurate. For the sake of verifying the rationality and accuracy of new phase transition and constitutive model, the comparisons between the simulated and experimental results were carried out.
Analysis and Assessment of Parameters Shaping Methane Hazard in Longwall Areas
Eugeniusz Krause
2013-01-01
Full Text Available Increasing coal production concentration and mining in coal seams of high methane content contribute to its growing emission to longwall areas. In this paper, analysis of survey data concerning the assessment of parameters that influence the level of methane hazard in mining areas is presented. The survey was conducted with experts on ventilation and methane hazard in coal mines. The parameters which influence methane hazard in longwall areas were assigned specific weights (numerical values. The summary will show which of the assessed parameters have a strong, or weak, influence on methane hazard in longwall areas close to coal seams of high methane content.
Ignition-and-Growth Modeling of NASA Standard Detonator and a Linear Shaped Charge
Oguz, Sirri
2010-01-01
The main objective of this study is to quantitatively investigate the ignition and shock sensitivity of NASA Standard Detonator (NSD) and the shock wave propagation of a linear shaped charge (LSC) after being shocked by NSD flyer plate. This combined explosive train was modeled as a coupled Arbitrary Lagrangian-Eulerian (ALE) model with LS-DYNA hydro code. An ignition-and-growth (I&G) reactive model based on unreacted and reacted Jones-Wilkins-Lee (JWL) equations of state was used to simulate the shock initiation. Various NSD-to-LSC stand-off distances were analyzed to calculate the shock initiation (or failure to initiate) and detonation wave propagation along the shaped charge. Simulation results were verified by experimental data which included VISAR tests for NSD flyer plate velocity measurement and an aluminum target severance test for LSC performance verification. Parameters used for the analysis were obtained from various published data or by using CHEETAH thermo-chemical code.
Models for estimating photosynthesis parameters from in situ production profiles
Kovač, Žarko; Platt, Trevor; Sathyendranath, Shubha; Antunović, Suzana
2017-12-01
The rate of carbon assimilation in phytoplankton primary production models is mathematically prescribed with photosynthesis irradiance functions, which convert a light flux (energy) into a material flux (carbon). Information on this rate is contained in photosynthesis parameters: the initial slope and the assimilation number. The exactness of parameter values is crucial for precise calculation of primary production. Here we use a model of the daily production profile based on a suite of photosynthesis irradiance functions and extract photosynthesis parameters from in situ measured daily production profiles at the Hawaii Ocean Time-series station Aloha. For each function we recover parameter values, establish parameter distributions and quantify model skill. We observe that the choice of the photosynthesis irradiance function to estimate the photosynthesis parameters affects the magnitudes of parameter values as recovered from in situ profiles. We also tackle the problem of parameter exchange amongst the models and the effect it has on model performance. All models displayed little or no bias prior to parameter exchange, but significant bias following parameter exchange. The best model performance resulted from using optimal parameter values. Model formulation was extended further by accounting for spectral effects and deriving a spectral analytical solution for the daily production profile. The daily production profile was also formulated with time dependent growing biomass governed by a growth equation. The work on parameter recovery was further extended by exploring how to extract photosynthesis parameters from information on watercolumn production. It was demonstrated how to estimate parameter values based on a linearization of the full analytical solution for normalized watercolumn production and from the solution itself, without linearization. The paper complements previous works on photosynthesis irradiance models by analysing the skill and consistency of
A Dynamic Mesh-Based Approach to Model Melting and Shape of an ESR Electrode
Karimi-Sibaki, E.; Kharicha, A.; Bohacek, J.; Wu, M.; Ludwig, A.
2015-10-01
This paper presents a numerical method to investigate the shape of tip and melt rate of an electrode during electroslag remelting process. The interactions between flow, temperature, and electromagnetic fields are taken into account. A dynamic mesh-based approach is employed to model the dynamic formation of the shape of electrode tip. The effect of slag properties such as thermal and electrical conductivities on the melt rate and electrode immersion depth is discussed. The thermal conductivity of slag has a dominant influence on the heat transfer in the system, hence on melt rate of electrode. The melt rate decreases with increasing thermal conductivity of slag. The electrical conductivity of slag governs the electric current path that in turn influences flow and temperature fields. The melting of electrode is a quite unstable process due to the complex interaction between the melt rate, immersion depth, and shape of electrode tip. Therefore, a numerical adaptation of electrode position in the slag has been implemented in order to achieve steady state melting. In fact, the melt rate, immersion depth, and shape of electrode tip are interdependent parameters of process. The generated power in the system is found to be dependent on both immersion depth and shape of electrode tip. In other words, the same amount of power was generated for the systems where the shapes of tip and immersion depth were different. Furthermore, it was observed that the shape of electrode tip is very similar for the systems running with the same ratio of power generation to melt rate. Comparison between simulations and experimental results was made to verify the numerical model.
Zhou, Miaolei; Wang, Shoubin; Gao, Wei
2013-01-01
As a new type of intelligent material, magnetically shape memory alloy (MSMA) has a good performance in its applications in the actuator manufacturing. Compared with traditional actuators, MSMA actuator has the advantages as fast response and large deformation; however, the hysteresis nonlinearity of the MSMA actuator restricts its further improving of control precision. In this paper, an improved Krasnosel'skii-Pokrovskii (KP) model is used to establish the hysteresis model of MSMA actuator. To identify the weighting parameters of the KP operators, an improved gradient correction algorithm and a variable step-size recursive least square estimation algorithm are proposed in this paper. In order to demonstrate the validity of the proposed modeling approach, simulation experiments are performed, simulations with improved gradient correction algorithm and variable step-size recursive least square estimation algorithm are studied, respectively. Simulation results of both identification algorithms demonstrate that the proposed modeling approach in this paper can establish an effective and accurate hysteresis model for MSMA actuator, and it provides a foundation for improving the control precision of MSMA actuator.
Hysteresis Modeling of Magnetic Shape Memory Alloy Actuator Based on Krasnosel'skii-Pokrovskii Model
Miaolei Zhou
2013-01-01
Full Text Available As a new type of intelligent material, magnetically shape memory alloy (MSMA has a good performance in its applications in the actuator manufacturing. Compared with traditional actuators, MSMA actuator has the advantages as fast response and large deformation; however, the hysteresis nonlinearity of the MSMA actuator restricts its further improving of control precision. In this paper, an improved Krasnosel'skii-Pokrovskii (KP model is used to establish the hysteresis model of MSMA actuator. To identify the weighting parameters of the KP operators, an improved gradient correction algorithm and a variable step-size recursive least square estimation algorithm are proposed in this paper. In order to demonstrate the validity of the proposed modeling approach, simulation experiments are performed, simulations with improved gradient correction algorithm and variable step-size recursive least square estimation algorithm are studied, respectively. Simulation results of both identification algorithms demonstrate that the proposed modeling approach in this paper can establish an effective and accurate hysteresis model for MSMA actuator, and it provides a foundation for improving the control precision of MSMA actuator.
A Solvable Model for Nuclear Shape Phase Transitions
Levai, G.; Arias, J. M.
2009-01-01
There has been considerable interest recently in phase transitions that occur between some well-defined nuclear shapes, e.g. the spherical vibrator, the axially deformed rotor and the γ-unstable rotor, which are assigned to the U(5), SU(3) and 0(6) symmetries. These shape phase transitions occur through critical points of the IBM phase diagram and correspond to rapid structural changes. The first transition of this type describes transition form the spherical to the γ-unstable phase and has been associated with an E(5) symmetry. Later further critical point symmetries e.g. X(5) and Y(5) have also been proposed for transitions between other nuclear shape phases. In another application the chain of even Ru isotopes was considered from A 98 to 112 [2]. The parameters were extracted from a fit to the low-lying energy spectrum of each nucleus and were used to plot the corresponding potential. It was found that up to A =102 the potential is essentially an harmonic oscillator, while at A =104 a rather flat potential was seen, in accordance with the expected phase transition and E(5) symmetry there. With increasing A then the minimum got increasingly deeper and moved away from β = 0. We discuss the possibility of generalizing the formalism in two ways: first by including dependence on the 7 variable allowing for the approximate description of nuclei close to the X(5) symmetry, and second, including higher-lying energy levels in the quasi-exactly solvable formalism
Shapes of nuclear configurations in a cranked harmonic oscillator model
Troudet, T.; Arvieu, R.
1980-05-01
The shapes of nuclear configurations are calculated using Slater determinants built with cranked harmonic oscillator single particle states. The nuclear forces role is played by a volume conservation condition (of the potential or of the density) in a first part. In a second part, we have used the finite range, density dependent interaction of Cogny. A very simple classification of configurations emerges in the first part, the relevant parameter being the equatorial eccentricity of the nuclear density. A critical equatorial eccentricity is obtained which governs the accession to the case for which the nucleus is oblate and symmetric around its axis of rotation. Nuclear configurations calculated in the second part observe remarkably well these behaviors
Nguyen, Nhan; James Urnes, Sr.
2012-01-01
Lightweight aircraft design has received a considerable attention in recent years as a means for improving cruise efficiency. Reducing aircraft weight results in lower lift requirements which directly translate into lower drag, hence reduced engine thrust requirements during cruise. The use of lightweight materials such as advanced composite materials has been adopted by airframe manufacturers in current and future aircraft. Modern lightweight materials can provide less structural rigidity while maintaining load-carrying capacity. As structural flexibility increases, aeroelastic interactions with aerodynamic forces and moments become an increasingly important consideration in aircraft design and aerodynamic performance. Furthermore, aeroelastic interactions with flight dynamics can result in issues with vehicle stability and control. Abstract This paper describes a recent aeroelastic modeling effort for an elastically shaped aircraft concept (ESAC). The aircraft model is based on the rigid-body generic transport model (GTM) originally developed at NASA Langley Research Center. The ESAC distinguishes itself from the GTM in that it is equipped with highly flexible wing structures as a weight reduction design feature. More significantly, the wings are outfitted with a novel control effector concept called variable camber continuous trailing edge (VCCTE) flap system for active control of wing aeroelastic deflections to optimize the local angle of attack of wing sections for improved aerodynamic efficiency through cruise drag reduction and lift enhancement during take-off and landing. The VCCTE flap is a multi-functional and aerodynamically efficient device capable of achieving high lift-to-drag ratios. The flap system is comprised of three chordwise segments that form the variable camber feature of the flap and multiple spanwise segments that form a piecewise continuous trailing edge. By configuring the flap camber and trailing edge shape, drag reduction could be
Experimental Modeling of the Formation of Saucer-Shaped sills
Galland, O.; Planke, S.; Malthe-Sorenssen, A.
2007-12-01
Many magma intrusions in sedimentary basins are sills, and especially saucer-shaped sills. These features are observed in many places (i.e. South Africa; the Norwegian and North Sea; Siberia; Argentina). Sand injectites exhibit similar geometries. The occurrence of such features in so various settings suggests that their emplacement results from fundamental processes in sedimentary basins. To understand such processes, we performed experimental modeling of saucer-shaped sill emplacement. The experiments consist of injecting a molten low viscosity vegetable oil (model magma) at a constant flow rate into a fine-grained Coulomb silica flour (model rock). When the oil starts intruding, the initially flat surface of the model inflates and forms a smooth dome. At the end of the experiment, the oil erupts at the edge of the dome. After the experiment, the oil cools and solidifies, the resulting solid intrusion is unburied and exposed, and its upper surface digitalized. For our purpose, we did our experiments without external deformation. We performed two series of experiments with varying depth of injection. The first series consisted of injection into a homogeneous medium. The resulting intrusions were cone-sheets and dykes. The second series consisted of heterogeneous models where the heterogeneity was a weak layer made of a flexible net. The resulting intrusions were made of (1) a horizontal basal sill emplaced along the weakness, and (2) inclined sheets nucleating at the edges of the basal sill and propagating upward and outward. The inclined sheets exhibited a convex shape, i.e. a decreasing slope outward. In addition, the deeper the sills emplaced, the larger they were. Our experimental results are consistent with saucer-shaped features in nature. We infer from our results that the transition between the basal sills and the inclined sheets results from a transition of emplacement processes. We suggest that the basal sill emplace by open (mode I) fracturing, whereas
Quantitative model for the generic 3D shape of ICMEs at 1 AU
Démoulin, P.; Janvier, M.; Masías-Meza, J. J.; Dasso, S.
2016-10-01
Context. Interplanetary imagers provide 2D projected views of the densest plasma parts of interplanetary coronal mass ejections (ICMEs), while in situ measurements provide magnetic field and plasma parameter measurements along the spacecraft trajectory, that is, along a 1D cut. The data therefore only give a partial view of the 3D structures of ICMEs. Aims: By studying a large number of ICMEs, crossed at different distances from their apex, we develop statistical methods to obtain a quantitative generic 3D shape of ICMEs. Methods: In a first approach we theoretically obtained the expected statistical distribution of the shock-normal orientation from assuming simple models of 3D shock shapes, including distorted profiles, and compared their compatibility with observed distributions. In a second approach we used the shock normal and the flux rope axis orientations together with the impact parameter to provide statistical information across the spacecraft trajectory. Results: The study of different 3D shock models shows that the observations are compatible with a shock that is symmetric around the Sun-apex line as well as with an asymmetry up to an aspect ratio of around 3. Moreover, flat or dipped shock surfaces near their apex can only be rare cases. Next, the sheath thickness and the ICME velocity have no global trend along the ICME front. Finally, regrouping all these new results and those of our previous articles, we provide a quantitative ICME generic 3D shape, including the global shape of the shock, the sheath, and the flux rope. Conclusions: The obtained quantitative generic ICME shape will have implications for several aims. For example, it constrains the output of typical ICME numerical simulations. It is also a base for studying the transport of high-energy solar and cosmic particles during an ICME propagation as well as for modeling and forecasting space weather conditions near Earth.
Shape: A 3D Modeling Tool for Astrophysics.
Steffen, Wolfgang; Koning, Nicholas; Wenger, Stephan; Morisset, Christophe; Magnor, Marcus
2011-04-01
We present a flexible interactive 3D morpho-kinematical modeling application for astrophysics. Compared to other systems, our application reduces the restrictions on the physical assumptions, data type, and amount that is required for a reconstruction of an object's morphology. It is one of the first publicly available tools to apply interactive graphics to astrophysical modeling. The tool allows astrophysicists to provide a priori knowledge about the object by interactively defining 3D structural elements. By direct comparison of model prediction with observational data, model parameters can then be automatically optimized to fit the observation. The tool has already been successfully used in a number of astrophysical research projects.
T. Pacyniak
2012-04-01
Full Text Available This work presents the technology of making foam plastics patterns used in casting as well as the final shaping stand. The analysis of the sintering process was carried out aiming at determining the influence of the pressure and the time of sintering on the flexural strength properties. The analysis of the research results confirmed that when the sintering pressure grows to the value of Pa =1,7 bar the flexural strength also increases, when the pressure value is higher than that, the degradation of the material takes place and the strength properties decrease.
Optimizing incomplete sample designs for item response model parameters
van der Linden, Willem J.
Several models for optimizing incomplete sample designs with respect to information on the item parameters are presented. The following cases are considered: (1) known ability parameters; (2) unknown ability parameters; (3) item sets with multiple ability scales; and (4) response models with
Parameter Estimates in Differential Equation Models for Chemical Kinetics
Winkel, Brian
2011-01-01
We discuss the need for devoting time in differential equations courses to modelling and the completion of the modelling process with efforts to estimate the parameters in the models using data. We estimate the parameters present in several differential equation models of chemical reactions of order n, where n = 0, 1, 2, and apply more general…
Khawaja, Z; Mazeran, P-E; Bigerelle, M; Guillemot, G; Mansori, M El
2011-01-01
This article presents a multi-scale theory based on wavelet decomposition to characterize the evolution of roughness in relation with a finishing process or an observed surface property. To verify this approach in production conditions, analyses were developed for the finishing process of the hardened steel by abrasive belts. These conditions are described by seven parameters considered in the Tagushi experimental design. The main objective of this work is to identify the most relevant roughness parameter and characteristic length allowing to assess the influence of finishing process, and to test the relevance of the measurement scale. Results show that wavelet approach allows finding this scale.
Rodríguez-Ruiz, Alejandro; Feng, Steve Si Jia; van Zelst, Jan; Vreemann, Suzan; Mann, Jessica Rice; D'Orsi, Carl Joseph; Sechopoulos, Ioannis
2017-06-01
To develop a set of accurate 2D models of compressed breasts undergoing mammography or breast tomosynthesis, based on objective analysis, to accurately characterize mammograms with few linearly independent parameters, and to generate novel clinically realistic paired cranio-caudal (CC) and medio-lateral oblique (MLO) views of the breast. We seek to improve on an existing model of compressed breasts by overcoming detector size bias, removing the nipple and non-mammary tissue, pairing the CC and MLO views from a single breast, and incorporating the pectoralis major muscle contour into the model. The outer breast shapes in 931 paired CC and MLO mammograms were automatically detected with an in-house developed segmentation algorithm. From these shapes three generic models (CC-only, MLO-only, and joint CC/MLO) with linearly independent components were constructed via principal component analysis (PCA). The ability of the models to represent mammograms not used for PCA was tested via leave-one-out cross-validation, by measuring the average distance error (ADE). The individual models based on six components were found to depict breast shapes with accuracy (mean ADE-CC = 0.81 mm, ADE-MLO = 1.64 mm, ADE-Pectoralis = 1.61 mm), outperforming the joint CC/MLO model (P ≤ 0.001). The joint model based on 12 principal components contains 99.5% of the total variance of the data, and can be used to generate new clinically realistic paired CC and MLO breast shapes. This is achieved by generating random sets of 12 principal components, following the Gaussian distributions of the histograms of each component, which were obtained from the component values determined from the images in the mammography database used. Our joint CC/MLO model can successfully generate paired CC and MLO view shapes of the same simulated breast, while the individual models can be used to represent with high accuracy clinical acquired mammograms with a small set of parameters. This is the first
Natalya Pya
2016-02-01
Full Text Available Background: Measurements of tree heights and diameters are essential in forest assessment and modelling. Tree heights are used for estimating timber volume, site index and other important variables related to forest growth and yield, succession and carbon budget models. However, the diameter at breast height (dbh can be more accurately obtained and at lower cost, than total tree height. Hence, generalized height-diameter (h-d models that predict tree height from dbh, age and other covariates are needed. For a more flexible but biologically plausible estimation of covariate effects we use shape constrained generalized additive models as an extension of existing h-d model approaches. We use causal site parameters such as index of aridity to enhance the generality and causality of the models and to enable predictions under projected changeable climatic conditions. Methods: We develop unconstrained generalized additive models (GAM and shape constrained generalized additive models (SCAM for investigating the possible effects of tree-specific parameters such as tree age, relative diameter at breast height, and site-specific parameters such as index of aridity and sum of daily mean temperature during vegetation period, on the h-d relationship of forests in Lower Saxony, Germany. Results: Some of the derived effects, e.g. effects of age, index of aridity and sum of daily mean temperature have significantly non-linear pattern. The need for using SCAM results from the fact that some of the model effects show partially implausible patterns especially at the boundaries of data ranges. The derived model predicts monotonically increasing levels of tree height with increasing age and temperature sum and decreasing aridity and social rank of a tree within a stand. The definition of constraints leads only to marginal or minor decline in the model statistics like AIC. An observed structured spatial trend in tree height is modelled via 2-dimensional surface
Study on Parameters Modeling of Wind Turbines Using SCADA Data
Yonglong YAN
2014-08-01
Full Text Available Taking the advantage of the current massive monitoring data from Supervisory Control and Data Acquisition (SCADA system of wind farm, it is of important significance for anomaly detection, early warning and fault diagnosis to build the data model of state parameters of wind turbines (WTs. The operational conditions and the relationships between the state parameters of wind turbines are complex. It is difficult to establish the model of state parameter accurately, and the modeling method of state parameters of wind turbines considering parameter selection is proposed. Firstly, by analyzing the characteristic of SCADA data, a reasonable range of data and monitoring parameters are chosen. Secondly, neural network algorithm is adapted, and the selection method of input parameters in the model is presented. Generator bearing temperature and cooling air temperature are regarded as target parameters, and the two models are built and input parameters of the models are selected, respectively. Finally, the parameter selection method in this paper and the method using genetic algorithm-partial least square (GA-PLS are analyzed comparatively, and the results show that the proposed methods are correct and effective. Furthermore, the modeling of two parameters illustrate that the method in this paper can applied to other state parameters of wind turbines.
The Influence of the Basic Styrofoam Patterns Final Shaping Parameters on the Resistance Properties
T. Pacyniak
2012-12-01
Full Text Available This work presents the analysis of the final shaping process of the patterns aimed at determining the influence of the pressure and the time of sintering on the resistance to bending. The analysis of the research results proved that when the pressure of the sintering rises and reaches Ps=2.1 bar the resistance to bending increases, above this level of the pressure the resistance value starts decreasing. The time of styrofoam sintering at which the highest bending resistance values were obtained is ts=90 s. When the sintering pressure is less than 2 bar prolongation of the time of sintering over 90 s causes a slight increase in the resistance, however, at higher pressures prolongation of the time of sintering causes submelting of the styrofoam pattern.
The Influence of the Basic Styrofoam Patterns Final Shaping Parameters on the Resistance Properties
Pacyniak T.
2012-12-01
Full Text Available This work presents the analysis of the final shaping process of the patterns aimed at determining the influence of the pressure and the time of sintering on the resistance to bending. The analysis of the research results proved that when the pressure of the sintering rises and reaches Ps=2.1 bar the resistance to bending increases, above this level of the pressure the resistance value starts decreasing. The time of styrofoam sintering at which the highest bending resistance values were obtained is ts=90s. When the sintering pressure is less than 2 bar prolongation of the time of sintering over 90 s causes a slight increase in the resistance, however, at higher pressures prolongation of the time of sintering causes submelting of the styrofoam pattern.
Shaping surface of palladium nanospheres through the control of reaction parameters
Wang Lianmeng; Tan Enzhong; Guo Lin; Wang Lihua; Han Xiaodong
2011-01-01
Solid, cracked, and flower-shaped surfaces of palladium nanospheres with high yields and good uniformity were successfully prepared by a wet chemical method. On the basis of the experimental data, the same size of palladium nanosphere with different surface morphologies can be regulated only by changing the amount of ammonium hydroxide and reductant in one experimental system. The as-prepared products were studied by transmission electron microscopy (TEM), scanning electron microscopy (SEM) and x-ray diffraction (XRD). In addition, surface-enhanced Raman scattering (SERS) spectra on the as-prepared different surface of palladium nanospheres exhibit high activity towards p-aminothiophenol (PATP) detection, and the result further reveals that the predominance of the a1 vibration mode in the SERS spectra via an electromagnetic (EM) mechanism is significant.
Abdomen and spinal cord segmentation with augmented active shape models.
Xu, Zhoubing; Conrad, Benjamin N; Baucom, Rebeccah B; Smith, Seth A; Poulose, Benjamin K; Landman, Bennett A
2016-07-01
Active shape models (ASMs) have been widely used for extracting human anatomies in medical images given their capability for shape regularization of topology preservation. However, sensitivity to model initialization and local correspondence search often undermines their performances, especially around highly variable contexts in computed-tomography (CT) and magnetic resonance (MR) images. In this study, we propose an augmented ASM (AASM) by integrating the multiatlas label fusion (MALF) and level set (LS) techniques into the traditional ASM framework. Using AASM, landmark updates are optimized globally via a region-based LS evolution applied on the probability map generated from MALF. This augmentation effectively extends the searching range of correspondent landmarks while reducing sensitivity to the image contexts and improves the segmentation robustness. We propose the AASM framework as a two-dimensional segmentation technique targeting structures with one axis of regularity. We apply AASM approach to abdomen CT and spinal cord (SC) MR segmentation challenges. On 20 CT scans, the AASM segmentation of the whole abdominal wall enables the subcutaneous/visceral fat measurement, with high correlation to the measurement derived from manual segmentation. On 28 3T MR scans, AASM yields better performances than other state-of-the-art approaches in segmenting white/gray matter in SC.
Tavakoli, A.; Naeini, H. Moslemi; Roohi, Amir H.; Gollo, M. Hoseinpour; Shahabad, Sh. Imani
2018-01-01
In the 3D laser forming process, developing an appropriate laser scan pattern for producing specimens with high quality and uniformity is critical. This study presents certain principles for developing scan paths. Seven scan path parameters are considered, including: (1) combined linear or curved path; (2) type of combined linear path; (3) order of scan sequences; (4) the position of the start point in each scan; (5) continuous or discontinuous scan path; (6) direction of scan path; and (7) angular arrangement of combined linear scan paths. Regarding these path parameters, ten combined linear scan patterns are presented. Numerical simulations show continuous hexagonal, scan pattern, scanning from outer to inner path, is the optimized. In addition, it is observed the position of the start point and the angular arrangement of scan paths is the most effective path parameters. Also, further experimentations show four sequences due to creat symmetric condition enhance the height of the bowl-shaped products and uniformity. Finally, the optimized hexagonal pattern was compared with the similar circular one. In the hexagonal scan path, distortion value and standard deviation rather to edge height of formed specimen is very low, and the edge height despite of decreasing length of scan path increases significantly compared to the circular scan path. As a result, four-sequence hexagonal scan pattern is proposed as the optimized perimeter scan path to produce bowl-shaped product.
Statistical Shape Modelling and Markov Random Field Restoration (invited tutorial and exercise)
Hilger, Klaus Baggesen
This tutorial focuses on statistical shape analysis using point distribution models (PDM) which is widely used in modelling biological shape variability over a set of annotated training data. Furthermore, Active Shape Models (ASM) and Active Appearance Models (AAM) are based on PDMs and have proven...... deformation field between shapes. The tutorial demonstrates both generative active shape and appearance models, and MRF restoration on 3D polygonized surfaces. ''Exercise: Spectral-Spatial classification of multivariate images'' From annotated training data this exercise applies spatial image restoration...... using Markov random field relaxation of a spectral classifier. Keywords: the Ising model, the Potts model, stochastic sampling, discriminant analysis, expectation maximization....
Bisaria, Himanshu; Shandilya, Pragya
2018-03-01
Nowadays NiTi SMAs are gaining more prominence due to their unique properties such as superelasticity, shape memory effect, high fatigue strength and many other enriched physical and mechanical properties. The current studies explore the effect of machining parameters namely, peak current (Ip), pulse off time (TOFF), and pulse on time (TON) on wire wear ratio (WWR), and dimensional deviation (DD) in WEDM. It was found that high discharge energy was mainly ascribed to high WWR and DD. The WWR and DD increased with the increase in pulse on time and peak current whereas high pulse off time was favourable for low WWR and DD.
Parameter Optimisation for the Behaviour of Elastic Models over Time
Mosegaard, Jesper
2004-01-01
Optimisation of parameters for elastic models is essential for comparison or finding equivalent behaviour of elastic models when parameters cannot simply be transferred or converted. This is the case with a large range of commonly used elastic models. In this paper we present a general method tha...
An automatic and effective parameter optimization method for model tuning
T. Zhang
2015-11-01
simulation results show that the optimum combination of these parameters determined using this method is able to improve the model's overall performance by 9 %. The proposed methodology and software framework can be easily applied to other GCMs to speed up the model development process, especially regarding unavoidable comprehensive parameter tuning during the model development stage.
Karimi, Davood; Samei, Golnoosh; Kesch, Claudia; Nir, Guy; Salcudean, Septimiu E
2018-05-15
Most of the existing convolutional neural network (CNN)-based medical image segmentation methods are based on methods that have originally been developed for segmentation of natural images. Therefore, they largely ignore the differences between the two domains, such as the smaller degree of variability in the shape and appearance of the target volume and the smaller amounts of training data in medical applications. We propose a CNN-based method for prostate segmentation in MRI that employs statistical shape models to address these issues. Our CNN predicts the location of the prostate center and the parameters of the shape model, which determine the position of prostate surface keypoints. To train such a large model for segmentation of 3D images using small data (1) we adopt a stage-wise training strategy by first training the network to predict the prostate center and subsequently adding modules for predicting the parameters of the shape model and prostate rotation, (2) we propose a data augmentation method whereby the training images and their prostate surface keypoints are deformed according to the displacements computed based on the shape model, and (3) we employ various regularization techniques. Our proposed method achieves a Dice score of 0.88, which is obtained by using both elastic-net and spectral dropout for regularization. Compared with a standard CNN-based method, our method shows significantly better segmentation performance on the prostate base and apex. Our experiments also show that data augmentation using the shape model significantly improves the segmentation results. Prior knowledge about the shape of the target organ can improve the performance of CNN-based segmentation methods, especially where image features are not sufficient for a precise segmentation. Statistical shape models can also be employed to synthesize additional training data that can ease the training of large CNNs.
Villarrubia, J.S., E-mail: john.villarrubia@nist.gov [Semiconductor and Dimensional Metrology Division, National Institute of Standards and Technology, Gaithersburg, MD 20899 (United States); Vladár, A.E.; Ming, B. [Semiconductor and Dimensional Metrology Division, National Institute of Standards and Technology, Gaithersburg, MD 20899 (United States); Kline, R.J.; Sunday, D.F. [Materials Science and Engineering Division, National Institute of Standards and Technology, Gaithersburg, MD 20899 (United States); Chawla, J.S.; List, S. [Intel Corporation, RA3-252, 5200 NE Elam Young Pkwy, Hillsboro, OR 97124 (United States)
2015-07-15
The width and shape of 10 nm to 12 nm wide lithographically patterned SiO{sub 2} lines were measured in the scanning electron microscope by fitting the measured intensity vs. position to a physics-based model in which the lines' widths and shapes are parameters. The approximately 32 nm pitch sample was patterned at Intel using a state-of-the-art pitch quartering process. Their narrow widths and asymmetrical shapes are representative of near-future generation transistor gates. These pose a challenge: the narrowness because electrons landing near one edge may scatter out of the other, so that the intensity profile at each edge becomes width-dependent, and the asymmetry because the shape requires more parameters to describe and measure. Modeling was performed by JMONSEL (Java Monte Carlo Simulation of Secondary Electrons), which produces a predicted yield vs. position for a given sample shape and composition. The simulator produces a library of predicted profiles for varying sample geometry. Shape parameter values are adjusted until interpolation of the library with those values best matches the measured image. Profiles thereby determined agreed with those determined by transmission electron microscopy and critical dimension small-angle x-ray scattering to better than 1 nm.
Villarrubia, J S; Vladár, A E; Ming, B; Kline, R J; Sunday, D F; Chawla, J S; List, S
2015-07-01
The width and shape of 10nm to 12 nm wide lithographically patterned SiO2 lines were measured in the scanning electron microscope by fitting the measured intensity vs. position to a physics-based model in which the lines' widths and shapes are parameters. The approximately 32 nm pitch sample was patterned at Intel using a state-of-the-art pitch quartering process. Their narrow widths and asymmetrical shapes are representative of near-future generation transistor gates. These pose a challenge: the narrowness because electrons landing near one edge may scatter out of the other, so that the intensity profile at each edge becomes width-dependent, and the asymmetry because the shape requires more parameters to describe and measure. Modeling was performed by JMONSEL (Java Monte Carlo Simulation of Secondary Electrons), which produces a predicted yield vs. position for a given sample shape and composition. The simulator produces a library of predicted profiles for varying sample geometry. Shape parameter values are adjusted until interpolation of the library with those values best matches the measured image. Profiles thereby determined agreed with those determined by transmission electron microscopy and critical dimension small-angle x-ray scattering to better than 1 nm. Published by Elsevier B.V.
Identifying the connective strength between model parameters and performance criteria
B. Guse
2017-11-01
Full Text Available In hydrological models, parameters are used to represent the time-invariant characteristics of catchments and to capture different aspects of hydrological response. Hence, model parameters need to be identified based on their role in controlling the hydrological behaviour. For the identification of meaningful parameter values, multiple and complementary performance criteria are used that compare modelled and measured discharge time series. The reliability of the identification of hydrologically meaningful model parameter values depends on how distinctly a model parameter can be assigned to one of the performance criteria. To investigate this, we introduce the new concept of connective strength between model parameters and performance criteria. The connective strength assesses the intensity in the interrelationship between model parameters and performance criteria in a bijective way. In our analysis of connective strength, model simulations are carried out based on a latin hypercube sampling. Ten performance criteria including Nash–Sutcliffe efficiency (NSE, Kling–Gupta efficiency (KGE and its three components (alpha, beta and r as well as RSR (the ratio of the root mean square error to the standard deviation for different segments of the flow duration curve (FDC are calculated. With a joint analysis of two regression tree (RT approaches, we derive how a model parameter is connected to different performance criteria. At first, RTs are constructed using each performance criterion as the target variable to detect the most relevant model parameters for each performance criterion. Secondly, RTs are constructed using each parameter as the target variable to detect which performance criteria are impacted by changes in the values of one distinct model parameter. Based on this, appropriate performance criteria are identified for each model parameter. In this study, a high bijective connective strength between model parameters and performance criteria
Resuspension parameters for TRAC dispersion model
Langer, G.
1987-01-01
Resuspension factors for the wind erosion of soil contaminated with plutonium are necessary to run the Rocky Flats Plant Terrain Responsive Atmospheric Code (TRAC). The model predicts the dispersion and resulting population dose due to accidental plutonium releases
Jonathan R Karr
2015-05-01
Full Text Available Whole-cell models that explicitly represent all cellular components at the molecular level have the potential to predict phenotype from genotype. However, even for simple bacteria, whole-cell models will contain thousands of parameters, many of which are poorly characterized or unknown. New algorithms are needed to estimate these parameters and enable researchers to build increasingly comprehensive models. We organized the Dialogue for Reverse Engineering Assessments and Methods (DREAM 8 Whole-Cell Parameter Estimation Challenge to develop new parameter estimation algorithms for whole-cell models. We asked participants to identify a subset of parameters of a whole-cell model given the model's structure and in silico "experimental" data. Here we describe the challenge, the best performing methods, and new insights into the identifiability of whole-cell models. We also describe several valuable lessons we learned toward improving future challenges. Going forward, we believe that collaborative efforts supported by inexpensive cloud computing have the potential to solve whole-cell model parameter estimation.
Circular blurred shape model for multiclass symbol recognition.
Escalera, Sergio; Fornés, Alicia; Pujol, Oriol; Lladós, Josep; Radeva, Petia
2011-04-01
In this paper, we propose a circular blurred shape model descriptor to deal with the problem of symbol detection and classification as a particular case of object recognition. The feature extraction is performed by capturing the spatial arrangement of significant object characteristics in a correlogram structure. The shape information from objects is shared among correlogram regions, where a prior blurring degree defines the level of distortion allowed in the symbol, making the descriptor tolerant to irregular deformations. Moreover, the descriptor is rotation invariant by definition. We validate the effectiveness of the proposed descriptor in both the multiclass symbol recognition and symbol detection domains. In order to perform the symbol detection, the descriptors are learned using a cascade of classifiers. In the case of multiclass categorization, the new feature space is learned using a set of binary classifiers which are embedded in an error-correcting output code design. The results over four symbol data sets show the significant improvements of the proposed descriptor compared to the state-of-the-art descriptors. In particular, the results are even more significant in those cases where the symbols suffer from elastic deformations.
Modeling Influenza Transmission Using Environmental Parameters
Soebiyanto, Radina P.; Kiang, Richard K.
2010-01-01
Influenza is an acute viral respiratory disease that has significant mortality, morbidity and economic burden worldwide. It infects approximately 5-15% of the world population, and causes 250,000 500,000 deaths each year. The role of environments on influenza is often drawn upon the latitude variability of influenza seasonality pattern. In regions with temperate climate, influenza epidemics exhibit clear seasonal pattern that peak during winter months, but it is not as evident in the tropics. Toward this end, we developed mathematical model and forecasting capabilities for influenza in regions characterized by warm climate Hong Kong (China) and Maricopa County (Arizona, USA). The best model for Hong Kong uses Land Surface Temperature (LST), precipitation and relative humidity as its covariates. Whereas for Maricopa County, we found that weekly influenza cases can be best modelled using mean air temperature as its covariates. Our forecasts can further guides public health organizations in targeting influenza prevention and control measures such as vaccination.
Automatic shape model building based on principal geodesic analysis bootstrapping
Dam, Erik B; Fletcher, P Thomas; Pizer, Stephen M
2008-01-01
iteration are used. Thereby, we gradually capture the shape variation in the training collection better and better. Convergence of the method is explicitly enforced. The method is evaluated on collections of artificial training shapes where the expected shape mean and modes of variation are known by design...
Edge Modeling by Two Blur Parameters in Varying Contrasts.
Seo, Suyoung
2018-06-01
This paper presents a method of modeling edge profiles with two blur parameters, and estimating and predicting those edge parameters with varying brightness combinations and camera-to-object distances (COD). First, the validity of the edge model is proven mathematically. Then, it is proven experimentally with edges from a set of images captured for specifically designed target sheets and with edges from natural images. Estimation of the two blur parameters for each observed edge profile is performed with a brute-force method to find parameters that produce global minimum errors. Then, using the estimated blur parameters, actual blur parameters of edges with arbitrary brightness combinations are predicted using a surface interpolation method (i.e., kriging). The predicted surfaces show that the two blur parameters of the proposed edge model depend on both dark-side edge brightness and light-side edge brightness following a certain global trend. This is similar across varying CODs. The proposed edge model is compared with a one-blur parameter edge model using experiments of the root mean squared error for fitting the edge models to each observed edge profile. The comparison results suggest that the proposed edge model has superiority over the one-blur parameter edge model in most cases where edges have varying brightness combinations.
A phenomenological two-phase constitutive model for porous shape memory alloys
El Sayed, Tamer S.
2012-07-01
We present a two-phase constitutive model for pseudoelastoplastic behavior of porous shape memory alloys (SMAs). The model consists of a dense SMA phase and a porous plasticity phase. The overall response of the porous SMA is obtained by a weighted average of responses of individual phases. Based on the chosen constitutive model parameters, the model incorporates the pseudoelastic and pseudoplastic behavior simultaneously (commonly reported for porous SMAs) as well as sequentially (i.e. dense SMAs; pseudoelastic deformation followed by the pseudoplastic deformation until failure). The presented model also incorporates failure due to the deviatoric (shear band formation) and volumetric (void growth and coalescence) plastic deformation. The model is calibrated by representative volume elements (RVEs) with different sizes of spherical voids that are solved by unit cell finite element calculations. The overall response of the model is tested against experimental results from literature. Finally, application of the presented constitutive model has been presented by performing finite element simulations of the deformation and failure in unaixial dog-bone shaped specimen and compact tension (CT) test specimen. Results show a good agreement with the experimental data reported in the literature. © 2012 Elsevier B.V. All rights reserved.
Advances in Modelling, System Identification and Parameter ...
Authors show, using numerical simulation for two system functions, the improvement in percentage normalized ... of nonlinear systems. The approach is to use multiple linearizing models fitted along the operating trajectories. ... over emphasized in the light of present day high level of research activity in the field of aerospace ...
Saint-Cyr, B.
2011-01-01
We model in this work granular materials composed of non-convex and cohesive aggregates, in view of application to the rheology of UO 2 powders. The effect of non convexity is analyzed in terms of bulk quantities (Coulomb internal friction and cohesion) and micromechanical parameters such as texture anisotropy and force transmission. In particular, we find that the packing fraction evolves in a complex manner with the shape non convexity and the shear strength increases but saturates due to interlocking between the aggregates. We introduce simple models to describe these features in terms of micro-mechanical parameters. Furthermore, a systematic investigation of shearing, uniaxial compaction and simple compression of cohesive packings show that bulk cohesion increases with non-convexity but is strongly influenced by the boundary conditions and shear bands or stress concentration. (author) [fr
Thermomechanical model for NiTi shape memory wires
Frost, Miroslav; Sedlák, Petr; Sippola, M.; Šittner, Petr
2010-01-01
Roč. 19, č. 9 (2010), s. 1-10 ISSN 0964-1726 R&D Projects: GA MŠk(CZ) 1M06031; GA ČR(CZ) GA106/09/1573; GA ČR(CZ) GP106/09/P302; GA ČR GAP108/10/1296 Institutional research plan: CEZ:AV0Z20760514; CEZ:AV0Z10100520 Keywords : shape memory alloys * modeling * proportional loading Subject RIV: BM - Solid Matter Physics ; Magnetism Impact factor: 2.094, year: 2010 http://apps.isiknowledge.com/full_record.do?product=WOS&search_mode=GeneralSearch&qid=3&SID=U2fe5mHN9p3gHClCdF1&page=1&doc=1
Talaghat, Mohammad Reza; Jokar, Seyyed Mohammad
2017-12-01
This article offers a study on estimation of heat transfer parameters (coefficient and thermal diffusivity) using analytical solutions and experimental data for regular geometric shapes (such as infinite slab, infinite cylinder, and sphere). Analytical solutions have a broad use in experimentally determining these parameters. Here, the method of Finite Integral Transform (FIT) was used for solutions of governing differential equations. The temperature change at centerline location of regular shapes was recorded to determine both the thermal diffusivity and heat transfer coefficient. Aluminum and brass were used for testing. Experiments were performed for different conditions such as in a highly agitated water medium ( T = 52 °C) and in air medium ( T = 25 °C). Then, with the known slope of the temperature ratio vs. time curve and thickness of slab or radius of the cylindrical or spherical materials, thermal diffusivity value and heat transfer coefficient may be determined. According to the method presented in this study, the estimated of thermal diffusivity of aluminum and brass is 8.395 × 10-5 and 3.42 × 10-5 for a slab, 8.367 × 10-5 and 3.41 × 10-5 for a cylindrical rod and 8.385 × 10-5 and 3.40 × 10-5 m2/s for a spherical shape, respectively. The results showed there is close agreement between the values estimated here and those already published in the literature. The TAAD% is 0.42 and 0.39 for thermal diffusivity of aluminum and brass, respectively.
First line shape analysis and spectroscopic parameters for the ν11 band of 12C2H4
Es-sebbar, Et-touhami
2016-08-11
An accurate knowledge of line intensities, collisional broadening coefficients and narrowing parameters is necessary for the interpretation of high-resolution infrared spectra of the Earth and other planetary atmospheres. One of the most promising spectral domains for (C2H4)-C-12 monitoring in such environments is located near the 336 gm window, through its v(11) C-H stretching mode. In this paper, we report an extensive study in which we precisely determine spectroscopic parameters of (C2H4)-C-12 v(11) band at 297 +/- 1 K, using a narrow Difference-Frequency-Generation (DFG) laser with 10(-4) cm(-1) resolution. Absorption measurements were performed in the 2975-2980 cm(-1) spectral window to investigate 32 lines corresponding to where, J\\'ka\\',kc\\'<- Jka,kc, 5 <= J <= 7; 0.5 <= K-a <= 6 and 1 <= K-c <= 14. Spectroscopic parameters are retrieved using either Voigt or appropriate Galatry profile to simulate the measured (C2H4)-C-12 line shape. Line intensities along with self-broadening coefficients are reported for all lines. Narrowing coefficients for each isolated line are also derived. To our knowledge, the current study reports the first extensive spectroscopic parameter measurements of the (C2H4)-C-12 v(11) band in the 2975-2980 cm(-1) range. (C) 2016 Elsevier Ltd. All rights reserved.
First line shape analysis and spectroscopic parameters for the ν11 band of 12C2H4
Es-sebbar, Et-touhami; Mantzaras, John; Benilan, Yves; Farooq, Aamir
2016-01-01
An accurate knowledge of line intensities, collisional broadening coefficients and narrowing parameters is necessary for the interpretation of high-resolution infrared spectra of the Earth and other planetary atmospheres. One of the most promising spectral domains for (C2H4)-C-12 monitoring in such environments is located near the 336 gm window, through its v(11) C-H stretching mode. In this paper, we report an extensive study in which we precisely determine spectroscopic parameters of (C2H4)-C-12 v(11) band at 297 +/- 1 K, using a narrow Difference-Frequency-Generation (DFG) laser with 10(-4) cm(-1) resolution. Absorption measurements were performed in the 2975-2980 cm(-1) spectral window to investigate 32 lines corresponding to where, J'ka',kc'<- Jka,kc, 5 <= J <= 7; 0.5 <= K-a <= 6 and 1 <= K-c <= 14. Spectroscopic parameters are retrieved using either Voigt or appropriate Galatry profile to simulate the measured (C2H4)-C-12 line shape. Line intensities along with self-broadening coefficients are reported for all lines. Narrowing coefficients for each isolated line are also derived. To our knowledge, the current study reports the first extensive spectroscopic parameter measurements of the (C2H4)-C-12 v(11) band in the 2975-2980 cm(-1) range. (C) 2016 Elsevier Ltd. All rights reserved.
Smooth extrapolation of unknown anatomy via statistical shape models
Grupp, R. B.; Chiang, H.; Otake, Y.; Murphy, R. J.; Gordon, C. R.; Armand, M.; Taylor, R. H.
2015-03-01
Several methods to perform extrapolation of unknown anatomy were evaluated. The primary application is to enhance surgical procedures that may use partial medical images or medical images of incomplete anatomy. Le Fort-based, face-jaw-teeth transplant is one such procedure. From CT data of 36 skulls and 21 mandibles separate Statistical Shape Models of the anatomical surfaces were created. Using the Statistical Shape Models, incomplete surfaces were projected to obtain complete surface estimates. The surface estimates exhibit non-zero error in regions where the true surface is known; it is desirable to keep the true surface and seamlessly merge the estimated unknown surface. Existing extrapolation techniques produce non-smooth transitions from the true surface to the estimated surface, resulting in additional error and a less aesthetically pleasing result. The three extrapolation techniques evaluated were: copying and pasting of the surface estimate (non-smooth baseline), a feathering between the patient surface and surface estimate, and an estimate generated via a Thin Plate Spline trained from displacements between the surface estimate and corresponding vertices of the known patient surface. Feathering and Thin Plate Spline approaches both yielded smooth transitions. However, feathering corrupted known vertex values. Leave-one-out analyses were conducted, with 5% to 50% of known anatomy removed from the left-out patient and estimated via the proposed approaches. The Thin Plate Spline approach yielded smaller errors than the other two approaches, with an average vertex error improvement of 1.46 mm and 1.38 mm for the skull and mandible respectively, over the baseline approach.
Statistical shape modeling based renal volume measurement using tracked ultrasound
Pai Raikar, Vipul; Kwartowitz, David M.
2017-03-01
Autosomal dominant polycystic kidney disease (ADPKD) is the fourth most common cause of kidney transplant worldwide accounting for 7-10% of all cases. Although ADPKD usually progresses over many decades, accurate risk prediction is an important task.1 Identifying patients with progressive disease is vital to providing new treatments being developed and enable them to enter clinical trials for new therapy. Among other factors, total kidney volume (TKV) is a major biomarker predicting the progression of ADPKD. Consortium for Radiologic Imaging Studies in Polycystic Kidney Disease (CRISP)2 have shown that TKV is an early, and accurate measure of cystic burden and likely growth rate. It is strongly associated with loss of renal function.3 While ultrasound (US) has proven as an excellent tool for diagnosing the disease; monitoring short-term changes using ultrasound has been shown to not be accurate. This is attributed to high operator variability and reproducibility as compared to tomographic modalities such as CT and MR (Gold standard). Ultrasound has emerged as one of the standout modality for intra-procedural imaging and with methods for spatial localization has afforded us the ability to track 2D ultrasound in physical space which it is being used. In addition to this, the vast amount of recorded tomographic data can be used to generate statistical shape models that allow us to extract clinical value from archived image sets. In this work, we aim at improving the prognostic value of US in managing ADPKD by assessing the accuracy of using statistical shape model augmented US data, to predict TKV, with the end goal of monitoring short-term changes.
Agricultural and Environmental Input Parameters for the Biosphere Model
Kaylie Rasmuson; Kurt Rautenstrauch
2003-01-01
This analysis is one of nine technical reports that support the Environmental Radiation Model for Yucca Mountain Nevada (ERMYN) biosphere model. It documents input parameters for the biosphere model, and supports the use of the model to develop Biosphere Dose Conversion Factors (BDCF). The biosphere model is one of a series of process models supporting the Total System Performance Assessment (TSPA) for the repository at Yucca Mountain. The ERMYN provides the TSPA with the capability to perform dose assessments. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows the interrelationships between the major activities and their products (the analysis and model reports) that were planned in the biosphere Technical Work Plan (TWP, BSC 2003a). It should be noted that some documents identified in Figure 1-1 may be under development and therefore not available at the time this document is issued. The ''Biosphere Model Report'' (BSC 2003b) describes the ERMYN and its input parameters. This analysis report, ANL-MGR-MD-000006, ''Agricultural and Environmental Input Parameters for the Biosphere Model'', is one of the five reports that develop input parameters for the biosphere model. This report defines and justifies values for twelve parameters required in the biosphere model. These parameters are related to use of contaminated groundwater to grow crops. The parameter values recommended in this report are used in the soil, plant, and carbon-14 submodels of the ERMYN
Checking the new IRI model: The bottomside B parameters
Mosert, M.; Buresova, D.; Miro, G.; Lazo, B.; Ezquer, R.
2003-01-01
Electron density profiles obtained at Pruhonice (50.0, 15.0), El Arenosillo (37.1, 353.2) and Havana (23, 278) were used to check the bottom-side B parameters BO (thickness parameter) and B1 (shape parameter) predicted by the new IRI - 2000 version. The electron density profiles were derived from ionograms using the ARP technique. The data base includes daytime and nighttime ionograms recorded under different seasonal and solar activity conditions. Comparisons with IRI predictions were also done. The analysis shows that: a) The parameter B1 given by IRI 2000 reproduces better the observed ARP values than the IRI-90 version and b) The observed BO values are in general well reproduced by both IRI versions: IRI-90 and IRI-2000. (author)
Checking the new IRI model The bottomside B parameters
Mosert, M; Ezquer, R; Lazo, B; Miro, G
2002-01-01
Electron density profiles obtained at Pruhonice (50.0, 15.0), El Arenosillo (37.1, 353.2) and Havana (23, 278) were used to check the bottom-side B parameters BO (thickness parameter) and B1 (shape parameter) predicted by the new IRI - 2000 version. The electron density profiles were derived from ionograms using the ARP technique. The data base includes daytime and nighttime ionograms recorded under different seasonal and solar activity conditions. Comparisons with IRI predictions were also done. The analysis shows that: a) The parameter B1 given by IRI 2000 reproduces better the observed ARP values than the IRI-90 version and b) The observed BO values are in general well reproduced by both IRI versions: IRI-90 and IRI-2000.
A simulation of water pollution model parameter estimation
Kibler, J. F.
1976-01-01
A parameter estimation procedure for a water pollution transport model is elaborated. A two-dimensional instantaneous-release shear-diffusion model serves as representative of a simple transport process. Pollution concentration levels are arrived at via modeling of a remote-sensing system. The remote-sensed data are simulated by adding Gaussian noise to the concentration level values generated via the transport model. Model parameters are estimated from the simulated data using a least-squares batch processor. Resolution, sensor array size, and number and location of sensor readings can be found from the accuracies of the parameter estimates.
Lumped parameter models for the interpretation of environmental tracer data
Maloszewski, P.; Zuber, A.
1996-01-01
Principles of the lumped-parameter approach to the interpretation of environmental tracer data are given. The following models are considered: the piston flow model (PFM), exponential flow model (EM), linear model (LM), combined piston flow and exponential flow model (EPM), combined linear flow and piston flow model (LPM), and dispersion model (DM). The applicability of these models for the interpretation of different tracer data is discussed for a steady state flow approximation. Case studies are given to exemplify the applicability of the lumped-parameter approach. Description of a user-friendly computer program is given. (author). 68 refs, 25 figs, 4 tabs
Lumped parameter models for the interpretation of environmental tracer data
Maloszewski, P [GSF-Inst. for Hydrology, Oberschleissheim (Germany); Zuber, A [Institute of Nuclear Physics, Cracow (Poland)
1996-10-01
Principles of the lumped-parameter approach to the interpretation of environmental tracer data are given. The following models are considered: the piston flow model (PFM), exponential flow model (EM), linear model (LM), combined piston flow and exponential flow model (EPM), combined linear flow and piston flow model (LPM), and dispersion model (DM). The applicability of these models for the interpretation of different tracer data is discussed for a steady state flow approximation. Case studies are given to exemplify the applicability of the lumped-parameter approach. Description of a user-friendly computer program is given. (author). 68 refs, 25 figs, 4 tabs.
Parameters modelling of amaranth grain processing technology
Derkanosova, N. M.; Shelamova, S. A.; Ponomareva, I. N.; Shurshikova, G. V.; Vasilenko, O. A.
2018-03-01
The article presents a technique that allows calculating the structure of a multicomponent bakery mixture for the production of enriched products, taking into account the instability of nutrient content, and ensuring the fulfilment of technological requirements and, at the same time considering consumer preferences. The results of modelling and analysis of optimal solutions are given by the example of calculating the structure of a three-component mixture of wheat and rye flour with an enriching component, that is, whole-hulled amaranth flour applied to the technology of bread from a mixture of rye and wheat flour on a liquid leaven.
WATGIS: A GIS-Based Lumped Parameter Water Quality Model
Glenn P. Fernandez; George M. Chescheir; R. Wayne Skaggs; Devendra M. Amatya
2002-01-01
A Geographic Information System (GIS)Âbased, lumped parameter water quality model was developed to estimate the spatial and temporal nitrogenÂloading patterns for lower coastal plain watersheds in eastern North Carolina. The model uses a spatially distributed delivery ratio (DR) parameter to account for nitrogen retention or loss along a drainage network. Delivery...
A test for the parameters of multiple linear regression models ...
A test for the parameters of multiple linear regression models is developed for conducting tests simultaneously on all the parameters of multiple linear regression models. The test is robust relative to the assumptions of homogeneity of variances and absence of serial correlation of the classical F-test. Under certain null and ...
The influence of model parameters on catchment-response
Shah, S.M.S.; Gabriel, H.F.; Khan, A.A.
2002-01-01
This paper deals with the study of influence of influence of conceptual rainfall-runoff model parameters on catchment response (runoff). A conceptual modified watershed yield model is employed to study the effects of model-parameters on catchment-response, i.e. runoff. The model is calibrated, using manual parameter-fitting approach, also known as trial and error parameter-fitting. In all, there are twenty one (21) parameters that control the functioning of the model. A lumped parametric approach is used. The detailed analysis was performed on Ling River near Kahuta, having catchment area of 56 sq. miles. The model includes physical parameters like GWSM, PETS, PGWRO, etc. fitting coefficients like CINF, CGWS, etc. and initial estimates of the surface-water and groundwater storages i.e. srosp and gwsp. Sensitivity analysis offers a good way, without repetititious computations, the proper weight and consideration that must be taken when each of the influencing factor is evaluated. Sensitivity-analysis was performed to evaluate the influence of model-parameters on runoff. The sensitivity and relative contributions of model parameters influencing catchment-response are studied. (author)
Kumar, K.
1979-01-01
It has been shown that the gross features of the collective spectra of even-even nuclei ranging from 12 C to 240 Pu are reproduced by the dynamic deformation model without any fitting parameters. We apply another test to be same model in the present study. Can this single model explain three seemingly different types of shape co-existence proposed previously: spherical op-oh and deformed 2p-2h shapes in 16 O, spherical and prolate-deformed minima in the potential energy surface of 72 Se, ground state shape and fission isomer shape of 240 Pu. Of these three nuclei, only the nucleus 72 Se is off the line of beta-stability. The calculated potential energy surfaces and collective spectra of 16 O, 72 Se, and 240 Pu are discussed and compared with experiments. The three different kinds of shape coexistence proposed previously for 16 O, 72 Se, and 240 Pu are all reproduced by the present version of the dynamic deformation model within the same model and without any fitting parameters. We conclude that the combination of the dynamics of the nine-dimensional quadrupole and pairing motions with a large space microscopic calculation provides a rather powerful tool for studying practically all even-even nuclei
Identification of ecosystem parameters by SDE-modelling
Stochastic differential equations (SDEs) for ecosystem modelling have attracted increasing attention during recent years. The modelling has mostly been through simulation experiments in order to analyse how system noise propagates through the ordinary differential equation formulation of ecosystem...... models. Estimation of parameters in SDEs is, however, possible by combining Kalman filter techniques and likelihood estimation. By modelling parameters as random walks it is possible to identify linear as well as non-linear interactions between ecosystem components. By formulating a simple linear SDE...
Modelling foot height and foot shape-related dimensions.
Xiong, Shuping; Goonetilleke, Ravindra S; Witana, Channa P; Lee Au, Emily Yim
2008-08-01
The application of foot anthropometry to design good-fitting footwear has been difficult due to the lack of generalised models. This study seeks to model foot dimensions so that the characteristic shapes of feet, especially in the midfoot region, can be understood. Fifty Hong Kong Chinese adults (26 males and 24 females) participated in this study. Their foot lengths, foot widths, ball girths and foot heights were measured and then evaluated using mathematical models. The results showed that there were no significant allometry (p > 0.05) effects of foot length on ball girth and foot width. Foot height showed no direct relationship with foot length. However, a normalisation with respect to foot length and foot height resulted in a significant relationship for both males and females with R(2) greater than 0.97. Due to the lack of a direct relationship between foot height and foot length, the current practice of grading shoes with a constant increase in height or proportionate scaling in response to foot length is less than ideal. The results when validated with other populations can be a significant way forward in the design of footwear that has an improved fit in the height dimension.
Accurate SHAPE-directed RNA secondary structure modeling, including pseudoknots.
Hajdin, Christine E; Bellaousov, Stanislav; Huggins, Wayne; Leonard, Christopher W; Mathews, David H; Weeks, Kevin M
2013-04-02
A pseudoknot forms in an RNA when nucleotides in a loop pair with a region outside the helices that close the loop. Pseudoknots occur relatively rarely in RNA but are highly overrepresented in functionally critical motifs in large catalytic RNAs, in riboswitches, and in regulatory elements of viruses. Pseudoknots are usually excluded from RNA structure prediction algorithms. When included, these pairings are difficult to model accurately, especially in large RNAs, because allowing this structure dramatically increases the number of possible incorrect folds and because it is difficult to search the fold space for an optimal structure. We have developed a concise secondary structure modeling approach that combines SHAPE (selective 2'-hydroxyl acylation analyzed by primer extension) experimental chemical probing information and a simple, but robust, energy model for the entropic cost of single pseudoknot formation. Structures are predicted with iterative refinement, using a dynamic programming algorithm. This melded experimental and thermodynamic energy function predicted the secondary structures and the pseudoknots for a set of 21 challenging RNAs of known structure ranging in size from 34 to 530 nt. On average, 93% of known base pairs were predicted, and all pseudoknots in well-folded RNAs were identified.
Investigations of the sensitivity of a coronal mass ejection model (ENLIL) to solar input parameters
Falkenberg, Thea Vilstrup; Vršnak, B.; Taktakishvili, A.
2010-01-01
Understanding space weather is not only important for satellite operations and human exploration of the solar system but also to phenomena here on Earth that may potentially disturb and disrupt electrical signals. Some of the most violent space weather effects are caused by coronal mass ejections...... (CMEs), but in order to predict the caused effects, we need to be able to model their propagation from their origin in the solar corona to the point of interest, e.g., Earth. Many such models exist, but to understand the models in detail we must understand the primary input parameters. Here we...... investigate the parameter space of the ENLILv2.5b model using the CME event of 25 July 2004. ENLIL is a time‐dependent 3‐D MHD model that can simulate the propagation of cone‐shaped interplanetary coronal mass ejections (ICMEs) through the solar system. Excepting the cone parameters (radius, position...
Regionalization of SWAT Model Parameters for Use in Ungauged Watersheds
Indrajeet Chaubey
2010-11-01
Full Text Available There has been a steady shift towards modeling and model-based approaches as primary methods of assessing watershed response to hydrologic inputs and land management, and of quantifying watershed-wide best management practice (BMP effectiveness. Watershed models often require some degree of calibration and validation to achieve adequate watershed and therefore BMP representation. This is, however, only possible for gauged watersheds. There are many watersheds for which there are very little or no monitoring data available, thus the question as to whether it would be possible to extend and/or generalize model parameters obtained through calibration of gauged watersheds to ungauged watersheds within the same region. This study explored the possibility of developing regionalized model parameter sets for use in ungauged watersheds. The study evaluated two regionalization methods: global averaging, and regression-based parameters, on the SWAT model using data from priority watersheds in Arkansas. Resulting parameters were tested and model performance determined on three gauged watersheds. Nash-Sutcliffe efficiencies (NS for stream flow obtained using regression-based parameters (0.53–0.83 compared well with corresponding values obtained through model calibration (0.45–0.90. Model performance obtained using global averaged parameter values was also generally acceptable (0.4 ≤ NS ≤ 0.75. Results from this study indicate that regionalized parameter sets for the SWAT model can be obtained and used for making satisfactory hydrologic response predictions in ungauged watersheds.
Babenko, V. A.; Petrov, N. M.
2010-01-01
On the basis of the total cross sections for neutron-proton scattering in the region of laboratory energies below 150 keV, the value of σ 0 = 20.4288(146) b was obtained for the total cross sections for neutron-proton scattering at zero energy. This value is in very good agreement with the experimental cross sections obtained by Houke and Hurst, but it is at odds with Dilg's experimental cross section. By using the value that we found for σ 0 and the experimental values of the neutron-proton coherent scattering length f, the deuteron binding energy ε t , the deuteron effective radius ρ t (-ε t , -ε t ), and the total cross section in the region of energies below 5 MeV, the following values were found in the shape-parameter approximation for the low-energy parameters of neutron-proton scattering in the spin-triplet and spin-singlet states: a t = 5.4114(27) fm, r 0t = 1.7606(35) fm, v 2t = 0.157 fm 3 , a s = -23.7154(80) fm, r 0s = 2.706(67) fm, and v 2s = 0.491 fm 3 .
Ozen, Murat; Guler, Murat
2014-02-01
Aggregate gradation is one of the key design parameters affecting the workability and strength properties of concrete mixtures. Estimating aggregate gradation from hardened concrete samples can offer valuable insights into the quality of mixtures in terms of the degree of segregation and the amount of deviation from the specified gradation limits. In this study, a methodology is introduced to determine the particle size distribution of aggregates from 2D cross sectional images of concrete samples. The samples used in the study were fabricated from six mix designs by varying the aggregate gradation, aggregate source and maximum aggregate size with five replicates of each design combination. Each sample was cut into three pieces using a diamond saw and then scanned to obtain the cross sectional images using a desktop flatbed scanner. An algorithm is proposed to determine the optimum threshold for the image analysis of the cross sections. A procedure was also suggested to determine a suitable particle shape parameter to be used in the analysis of aggregate size distribution within each cross section. Results of analyses indicated that the optimum threshold hence the pixel distribution functions may be different even for the cross sections of an identical concrete sample. Besides, the maximum ferret diameter is the most suitable shape parameter to estimate the size distribution of aggregates when computed based on the diagonal sieve opening. The outcome of this study can be of practical value for the practitioners to evaluate concrete in terms of the degree of segregation and the bounds of mixture's gradation achieved during manufacturing.
Yang, Yanchao
2013-01-01
We present a method to determine the precise shape of a dynamic object from video. This problem is fundamental to computer vision, and has a number of applications, for example, 3D video/cinema post-production, activity recognition and augmented
Shen, Kai-kai; Fripp, Jurgen; Mériaudeau, Fabrice; Chételat, Gaël; Salvado, Olivier; Bourgeat, Pierrick; Saradha, A.; Abdi, Hervé; Abdulkadir, Ahmed; Acharya, Deepa; Achuthan, Anusha; Adluru, Nagesh; Aghajanian, Jania; Agrusti, Antonella; Agyemang, Alex; Ahdidan, Jamila; Ahmad, Duaa; Ahmed, Shiek; Aisen, Paul; Akhondi-Asl, Alireza; Aksu, Yaman; Alberca, Roman; Alcauter, Sarael; Alexander, Daniel; Alin, Aylin; Almeida, Fabio; Alvarez-Lineara, Juan; Amlien, Inge; Anand, Shyam; Anderson, Dallas; Ang, Amma; Angersbach, Steve; Ansarian, Reza; Aoyama, Eiji; Appannah, Arti; Arfanakis, Konstantinos; Armor, Tom; Arrighi, Michael; Arumughababu, S. Vethanayaki; Arunagiri, Vidhya; Ashe-McNalley, Cody; Ashford, Wes; Le Page, Aurelie; Avants, Brian; Aviv, Richard; Awasthi, Sukrati; Ayache, Nicholas; Chen, Wei; Richard, Edo; Schmand, Ben
2012-01-01
The hippocampus is affected at an early stage in the development of Alzheimer's disease (AD). With the use of structural magnetic resonance (MR) imaging, we can investigate the effect of AD on the morphology of the hippocampus. The hippocampal shape variations among a population can be usually
Bayesian estimation of parameters in a regional hydrological model
K. Engeland
2002-01-01
Full Text Available This study evaluates the applicability of the distributed, process-oriented Ecomag model for prediction of daily streamflow in ungauged basins. The Ecomag model is applied as a regional model to nine catchments in the NOPEX area, using Bayesian statistics to estimate the posterior distribution of the model parameters conditioned on the observed streamflow. The distribution is calculated by Markov Chain Monte Carlo (MCMC analysis. The Bayesian method requires formulation of a likelihood function for the parameters and three alternative formulations are used. The first is a subjectively chosen objective function that describes the goodness of fit between the simulated and observed streamflow, as defined in the GLUE framework. The second and third formulations are more statistically correct likelihood models that describe the simulation errors. The full statistical likelihood model describes the simulation errors as an AR(1 process, whereas the simple model excludes the auto-regressive part. The statistical parameters depend on the catchments and the hydrological processes and the statistical and the hydrological parameters are estimated simultaneously. The results show that the simple likelihood model gives the most robust parameter estimates. The simulation error may be explained to a large extent by the catchment characteristics and climatic conditions, so it is possible to transfer knowledge about them to ungauged catchments. The statistical models for the simulation errors indicate that structural errors in the model are more important than parameter uncertainties. Keywords: regional hydrological model, model uncertainty, Bayesian analysis, Markov Chain Monte Carlo analysis
Brownian motion model with stochastic parameters for asset prices
Ching, Soo Huei; Hin, Pooi Ah
2013-09-01
The Brownian motion model may not be a completely realistic model for asset prices because in real asset prices the drift μ and volatility σ may change over time. Presently we consider a model in which the parameter x = (μ,σ) is such that its value x (t + Δt) at a short time Δt ahead of the present time t depends on the value of the asset price at time t + Δt as well as the present parameter value x(t) and m-1 other parameter values before time t via a conditional distribution. The Malaysian stock prices are used to compare the performance of the Brownian motion model with fixed parameter with that of the model with stochastic parameter.
Beam shaping for conformal fractionated stereotactic radiotherapy: a modeling study
Hacker, Fred L.; Kooy, Hanne M.; Bellerive, Marc R.; Killoran, Joseph H.; Leber, Zachary H.; Shrieve, Dennis C.; Tarbell, Nancy J.; Loeffler, Jay S.
1997-01-01
Purpose: The patient population treated with fractionated stereotactic radiotherapy (SRT) is significantly different than that treated with stereotactic radiosurgery (SRS). Generally, lesions treated with SRT are larger, less spherical, and located within critical regions of the central nervous system; hence, they offer new challenges to the treatment planner. Here a simple, cost effective, beam shaping system has been evaluated relative to both circular collimators and an ideal dynamically conforming system for effectiveness in providing conformal therapy for these lesions. Methods and Materials: We have modeled a simple system for conformal arc therapy using four independent jaws. The jaw positions and collimator angle are changed between arcs but held fixed for the duration of each arc. Eleven previously treated SRT cases have been replanned using this system. The rectangular jaw plans were then compared to the original treatment plans which used circular collimators. The plans were evaluated with respect to tissue sparing at 100%, 80%, 50%, and 20% of the prescription dose. A plan was also done for each tumor in which the beam aperture was continuously conformed to the beams eye view projection of the tumor. This was used as an ideal standard for conformal therapy in the absence of fluence modulation. Results: For tumors with a maximum extent of over 3.5 cm the rectangular jaw plans reduced the mean volume of healthy tissue involved at the prescription dose by 57% relative to the circular collimator plans. The ideal conformal plans offered no significant further improvement at the prescription dose. The relative advantage of the rectangular jaw plans decreased at lower isodoses so that at 20% of the prescription dose tissue involvement for the rectangular jaw plans was equivalent to that for the circular collimator plans. At these isodoses the ideal conformal plans gave substantially better tissue sparing. Conclusion: A simple and economical field shaping
Mechanisms Of Saucer-Shaped Sill Emplacement: Insight From Experimental Modeling
Galland, O.; Planke, S.; Malthe-Sørenssen, A.; Polteau, S.; Svensen, H.; Podladchikov, Y. Y.
2006-12-01
It has been recently demonstrated that magma intrusions in sedimentary basins had a strong impact on petroleum systems. Most of these intrusions are sills, and especially saucer-shaped sills. These features can be observed in many sedimentary basins (i.e. the Karoo basin, South Africa; the Norwegian and North Sea; the Tunguska basin, Siberia; the Neuquén basin in Argentina). The occurrence of such features in so various settings suggests that their emplacement results from fundamental processes. However, the mechanisms that govern their formation remain poorly constrained. Experiments were conducted to simulate the emplacement of saucer-shaped magma intrusions in sedimentary basins. The model rock and magma were fine-grained silica flour and molten vegetable oil, respectively. This modeling technique allows simultaneous simulation of magma emplacement and brittle deformation at a basin scale. For our purpose, we performed our experiments without external deformation. During the experiments, the oil was injected horizontally at constant flow rate within the silica flour. Then the oil initially emplaced in a sill, whereas the surface of the model inflated into a smooth dome. Subsequently, the oil propagated upwards along inclined sheets, finally reaching the surface at the edge of the dome. The resulting geometries of the intrusions were saucer-shaped sills. Then the oil solidified, and the model was cut in serial cross-sections through which the structures of the intrusive body and of the overburden can be observed. In order to constraint the processes governing the emplacement of such features, we performed a parametric study based on a set of experiments in which we systematically varied parameters such as the depth of emplacement and the injection flow rate of the oil. Our results showed that saucer diameters are larger at deeper level of emplacement. Opposite trend was obtained with varying injection flow rates. Based on our results, we conducted a detailed
Determination of the Corona model parameters with artificial neural networks
Ahmet, Nayir; Bekir, Karlik; Arif, Hashimov
2005-01-01
Full text : The aim of this study is to calculate new model parameters taking into account the corona of electrical transmission line wires. For this purpose, a neural network modeling proposed for the corona frequent characteristics modeling. Then this model was compared with the other model developed at the Polytechnic Institute of Saint Petersburg. The results of development of the specified corona model for calculation of its influence on the wave processes in multi-wires line and determination of its parameters are submitted. Results of obtained calculation equations are brought for electrical transmission line with allowance for superficial effect in the ground and wires with reference to developed corona model
Biological parameters for lung cancer in mathematical models of carcinogenesis
Jacob, P.; Jacob, V.
2003-01-01
Applications of the two-step model of carcinogenesis with clonal expansion (TSCE) to lung cancer data are reviewed, including those on atomic bomb survivors from Hiroshima and Nagasaki, British doctors, Colorado Plateau miners, and Chinese tin miners. Different sets of identifiable model parameters are used in the literature. The parameter set which could be determined with the lowest uncertainty consists of the net proliferation rate gamma of intermediate cells, the hazard h 55 at an intermediate age, and the hazard H? at an asymptotically large age. Also, the values of these three parameters obtained in the various studies are more consistent than other identifiable combinations of the biological parameters. Based on representative results for these three parameters, implications for the biological parameters in the TSCE model are derived. (author)
Oyster Creek cycle 10 nodal model parameter optimization study using PSMS
Dougher, J.D.
1987-01-01
The power shape monitoring system (PSMS) is an on-line core monitoring system that uses a three-dimensional nodal code (NODE-B) to perform nodal power calculations and compute thermal margins. The PSMS contains a parameter optimization function that improves the ability of NODE-B to accurately monitor core power distributions. This functions iterates on the model normalization parameters (albedos and mixing factors) to obtain the best agreement between predicted and measured traversing in-core probe (TIP) reading on a statepoint-by-statepoint basis. Following several statepoint optimization runs, an average set of optimized normalization parameters can be determined and can be implemented into the current or subsequent cycle core model for on-line core monitoring. A statistical analysis of 19 high-power steady-state state-points throughout Oyster Creek cycle 10 operation has shown a consistently poor virgin model performance. The normalization parameters used in the cycle 10 NODE-B model were based on a cycle 8 study, which evaluated only Exxon fuel types. The introduction of General Electric (GE) fuel into cycle 10 (172 assemblies) was a significant fuel/core design change that could have altered the optimum set of normalization parameters. Based on the need to evaluate a potential change in the model normalization parameters for cycle 11 and in an attempt to account for the poor cycle 10 model performance, a parameter optimization study was performed
Learning about physical parameters: the importance of model discrepancy
Brynjarsdóttir, Jenný; O'Hagan, Anthony
2014-01-01
Science-based simulation models are widely used to predict the behavior of complex physical systems. It is also common to use observations of the physical system to solve the inverse problem, that is, to learn about the values of parameters within the model, a process which is often called calibration. The main goal of calibration is usually to improve the predictive performance of the simulator but the values of the parameters in the model may also be of intrinsic scientific interest in their own right. In order to make appropriate use of observations of the physical system it is important to recognize model discrepancy, the difference between reality and the simulator output. We illustrate through a simple example that an analysis that does not account for model discrepancy may lead to biased and over-confident parameter estimates and predictions. The challenge with incorporating model discrepancy in statistical inverse problems is being confounded with calibration parameters, which will only be resolved with meaningful priors. For our simple example, we model the model-discrepancy via a Gaussian process and demonstrate that through accounting for model discrepancy our prediction within the range of data is correct. However, only with realistic priors on the model discrepancy do we uncover the true parameter values. Through theoretical arguments we show that these findings are typical of the general problem of learning about physical parameters and the underlying physical system using science-based mechanistic models. (paper)
A. A. Sukhotsky
2014-01-01
Full Text Available The paper describes development of the methodology for optimization of parameters for an additional operating force mechanism in a device for pneumo-centrifugal machining of glass balls. Specific feature in manufacturing glass balls for micro-optics in accordance with technological process for obtaining ball-shaped workpieces is grinding and polishing of spherical surface in a free state. In this case component billets of future balls are made in the form of cubes and the billets are given preliminary a form of ball with the help of rough grinding. An advanced method for obtaining ball-shaped work-pieces from brittle materials is a pneumocentrifugal machining. This method presupposes an application of two conic rings with abrasive working surfaces which are set coaxially with large diameters to each other and the billets are rolled along these rings. Rotation of the billets is conveyed by means of pressure medium.The present devices for pneumo-centrifugal machining are suitable for obtaining balls up to 6 mm. Machining of the work-pieces with full spherical surfaces and large diameter is non-productive due to impossibility to ensure a sufficient force on the billet in the working zone. For this reason the paper proposes a modified device where an additional force on the machined billet is created by upper working disc that is making a reciprocating motion along an axis of abrasive conic rings. The motion is realized with the help of a cylindrical camshaft mechanism in the form of a ring with a profile working end face and the purpose of present paper is to optimize parameters of the proposed device.The paper presents expressions for calculation of constitutive parameters of the additional operating force mechanism including parameters of loading element motion, main dimensions of the additional operating force mechanism and parameters of a profile element in the additional operating force mechanism.Investigation method is a mathematical
Serinaldi, Francesco
2011-01-01
In the context of the liberalized and deregulated electricity markets, price forecasting has become increasingly important for energy company's plans and market strategies. Within the class of the time series models that are used to perform price forecasting, the subclasses of methods based on stochastic time series and causal models commonly provide point forecasts, whereas the corresponding uncertainty is quantified by approximate or simulation-based confidence intervals. Aiming to improve the uncertainty assessment, this study introduces the Generalized Additive Models for Location, Scale and Shape (GAMLSS) to model the dynamically varying distribution of prices. The GAMLSS allow fitting a variety of distributions whose parameters change according to covariates via a number of linear and nonlinear relationships. In this way, price periodicities, trends and abrupt changes characterizing both the position parameter (linked to the expected value of prices), and the scale and shape parameters (related to price volatility, skewness, and kurtosis) can be explicitly incorporated in the model setup. Relying on the past behavior of the prices and exogenous variables, the GAMLSS enable the short-term (one-day ahead) forecast of the entire distribution of prices. The approach was tested on two datasets from the widely studied California Power Exchange (CalPX) market, and the less mature Italian Power Exchange (IPEX). CalPX data allow comparing the GAMLSS forecasting performance with published results obtained by different models. The study points out that the GAMLSS framework can be a flexible alternative to several linear and nonlinear stochastic models. - Research Highlights: ► Generalized Additive Models for Location, Scale and Shape (GAMLSS) are used to model electricity prices' time series. ► GAMLSS provide the entire dynamicaly varying distribution function of prices resorting to a suitable set of covariates that drive the instantaneous values of the parameters
Spatio-temporal modeling of nonlinear distributed parameter systems
Li, Han-Xiong
2011-01-01
The purpose of this volume is to provide a brief review of the previous work on model reduction and identifi cation of distributed parameter systems (DPS), and develop new spatio-temporal models and their relevant identifi cation approaches. In this book, a systematic overview and classifi cation on the modeling of DPS is presented fi rst, which includes model reduction, parameter estimation and system identifi cation. Next, a class of block-oriented nonlinear systems in traditional lumped parameter systems (LPS) is extended to DPS, which results in the spatio-temporal Wiener and Hammerstein s
Hufnagel, Heike; Pennec, Xavier; Ayache, Nicholas; Ehrhardt, Jan; Handels, Heinz
2008-01-01
Identification of point correspondences between shapes is required for statistical analysis of organ shapes differences. Since manual identification of landmarks is not a feasible option in 3D, several methods were developed to automatically find one-to-one correspondences on shape surfaces. For unstructured point sets, however, one-to-one correspondences do not exist but correspondence probabilities can be determined. A method was developed to compute a statistical shape model based on shapes which are represented by unstructured point sets with arbitrary point numbers. A fundamental problem when computing statistical shape models is the determination of correspondences between the points of the shape observations of the training data set. In the absence of landmarks, exact correspondences can only be determined between continuous surfaces, not between unstructured point sets. To overcome this problem, we introduce correspondence probabilities instead of exact correspondences. The correspondence probabilities are found by aligning the observation shapes with the affine expectation maximization-iterative closest points (EM-ICP) registration algorithm. In a second step, the correspondence probabilities are used as input to compute a mean shape (represented once again by an unstructured point set). Both steps are unified in a single optimization criterion which depe nds on the two parameters 'registration transformation' and 'mean shape'. In a last step, a variability model which best represents the variability in the training data set is computed. Experiments on synthetic data sets and in vivo brain structure data sets (MRI) are then designed to evaluate the performance of our algorithm. The new method was applied to brain MRI data sets, and the estimated point correspondences were compared to a statistical shape model built on exact correspondences. Based on established measures of ''generalization ability'' and ''specificity'', the estimates were very satisfactory
Sparse principal component analysis in medical shape modeling
Sjöstrand, Karl; Stegmann, Mikkel B.; Larsen, Rasmus
2006-03-01
Principal component analysis (PCA) is a widely used tool in medical image analysis for data reduction, model building, and data understanding and exploration. While PCA is a holistic approach where each new variable is a linear combination of all original variables, sparse PCA (SPCA) aims at producing easily interpreted models through sparse loadings, i.e. each new variable is a linear combination of a subset of the original variables. One of the aims of using SPCA is the possible separation of the results into isolated and easily identifiable effects. This article introduces SPCA for shape analysis in medicine. Results for three different data sets are given in relation to standard PCA and sparse PCA by simple thresholding of small loadings. Focus is on a recent algorithm for computing sparse principal components, but a review of other approaches is supplied as well. The SPCA algorithm has been implemented using Matlab and is available for download. The general behavior of the algorithm is investigated, and strengths and weaknesses are discussed. The original report on the SPCA algorithm argues that the ordering of modes is not an issue. We disagree on this point and propose several approaches to establish sensible orderings. A method that orders modes by decreasing variance and maximizes the sum of variances for all modes is presented and investigated in detail.
A Study on Stability of Limit Cycle Walking Model with Feet: Parameter Study
Yonggwon Jeon
2013-01-01
Full Text Available In this paper, two kinds of feet, namely, curved and flat feet, are added to limit cycle walking model to investigate its stability properties. Although both models are already proposed and are investigated, most previous works are focused on efficiency and gait behaviors. Only the stability properties of the simplest walking model conceived Garcia et al. are well defined. Therefore, there is still a need for a precise research on the effect of feet, especially in the view of local stability, bifurcation route to chaos, global stability, falling boundary and energy balance line. Therefore, this article revisits the stability analysis of limit cycle walking model with various foot shape. To analyze the effects of feet, we re-derive the equation of motion of modified models by adding one more parameter of foot shape than the simplest walking model. Also, the falling boundary and energy balance line of modified models are derived to get proper initial conditions for stable walking and to explain global stability. Simulation results show us that the curved feet can enlarge both stable walking range and area of basin of attraction while the case of flat feet depends on foot shape parameter.
Parameters Estimation of Geographically Weighted Ordinal Logistic Regression (GWOLR) Model
Zuhdi, Shaifudin; Retno Sari Saputro, Dewi; Widyaningsih, Purnami
2017-06-01
A regression model is the representation of relationship between independent variable and dependent variable. The dependent variable has categories used in the logistic regression model to calculate odds on. The logistic regression model for dependent variable has levels in the logistics regression model is ordinal. GWOLR model is an ordinal logistic regression model influenced the geographical location of the observation site. Parameters estimation in the model needed to determine the value of a population based on sample. The purpose of this research is to parameters estimation of GWOLR model using R software. Parameter estimation uses the data amount of dengue fever patients in Semarang City. Observation units used are 144 villages in Semarang City. The results of research get GWOLR model locally for each village and to know probability of number dengue fever patient categories.
Universally sloppy parameter sensitivities in systems biology models.
Ryan N Gutenkunst
2007-10-01
Full Text Available Quantitative computational models play an increasingly important role in modern biology. Such models typically involve many free parameters, and assigning their values is often a substantial obstacle to model development. Directly measuring in vivo biochemical parameters is difficult, and collectively fitting them to other experimental data often yields large parameter uncertainties. Nevertheless, in earlier work we showed in a growth-factor-signaling model that collective fitting could yield well-constrained predictions, even when it left individual parameters very poorly constrained. We also showed that the model had a "sloppy" spectrum of parameter sensitivities, with eigenvalues roughly evenly distributed over many decades. Here we use a collection of models from the literature to test whether such sloppy spectra are common in systems biology. Strikingly, we find that every model we examine has a sloppy spectrum of sensitivities. We also test several consequences of this sloppiness for building predictive models. In particular, sloppiness suggests that collective fits to even large amounts of ideal time-series data will often leave many parameters poorly constrained. Tests over our model collection are consistent with this suggestion. This difficulty with collective fits may seem to argue for direct parameter measurements, but sloppiness also implies that such measurements must be formidably precise and complete to usefully constrain many model predictions. We confirm this implication in our growth-factor-signaling model. Our results suggest that sloppy sensitivity spectra are universal in systems biology models. The prevalence of sloppiness highlights the power of collective fits and suggests that modelers should focus on predictions rather than on parameters.
Universally sloppy parameter sensitivities in systems biology models.
Gutenkunst, Ryan N; Waterfall, Joshua J; Casey, Fergal P; Brown, Kevin S; Myers, Christopher R; Sethna, James P
2007-10-01
Quantitative computational models play an increasingly important role in modern biology. Such models typically involve many free parameters, and assigning their values is often a substantial obstacle to model development. Directly measuring in vivo biochemical parameters is difficult, and collectively fitting them to other experimental data often yields large parameter uncertainties. Nevertheless, in earlier work we showed in a growth-factor-signaling model that collective fitting could yield well-constrained predictions, even when it left individual parameters very poorly constrained. We also showed that the model had a "sloppy" spectrum of parameter sensitivities, with eigenvalues roughly evenly distributed over many decades. Here we use a collection of models from the literature to test whether such sloppy spectra are common in systems biology. Strikingly, we find that every model we examine has a sloppy spectrum of sensitivities. We also test several consequences of this sloppiness for building predictive models. In particular, sloppiness suggests that collective fits to even large amounts of ideal time-series data will often leave many parameters poorly constrained. Tests over our model collection are consistent with this suggestion. This difficulty with collective fits may seem to argue for direct parameter measurements, but sloppiness also implies that such measurements must be formidably precise and complete to usefully constrain many model predictions. We confirm this implication in our growth-factor-signaling model. Our results suggest that sloppy sensitivity spectra are universal in systems biology models. The prevalence of sloppiness highlights the power of collective fits and suggests that modelers should focus on predictions rather than on parameters.
Improving weather predictability by including land-surface model parameter uncertainty
Orth, Rene; Dutra, Emanuel; Pappenberger, Florian
2016-04-01
The land surface forms an important component of Earth system models and interacts nonlinearly with other parts such as ocean and atmosphere. To capture the complex and heterogenous hydrology of the land surface, land surface models include a large number of parameters impacting the coupling to other components of the Earth system model. Focusing on ECMWF's land-surface model HTESSEL we present in this study a comprehensive parameter sensitivity evaluation using multiple observational datasets in Europe. We select 6 poorly constrained effective parameters (surface runoff effective depth, skin conductivity, minimum stomatal resistance, maximum interception, soil moisture stress function shape, total soil depth) and explore their sensitivity to model outputs such as soil moisture, evapotranspiration and runoff using uncoupled simulations and coupled seasonal forecasts. Additionally we investigate the possibility to construct ensembles from the multiple land surface parameters. In the uncoupled runs we find that minimum stomatal resistance and total soil depth have the most influence on model performance. Forecast skill scores are moreover sensitive to the same parameters as HTESSEL performance in the uncoupled analysis. We demonstrate the robustness of our findings by comparing multiple best performing parameter sets and multiple randomly chosen parameter sets. We find better temperature and precipitation forecast skill with the best-performing parameter perturbations demonstrating representativeness of model performance across uncoupled (and hence less computationally demanding) and coupled settings. Finally, we construct ensemble forecasts from ensemble members derived with different best-performing parameterizations of HTESSEL. This incorporation of parameter uncertainty in the ensemble generation yields an increase in forecast skill, even beyond the skill of the default system. Orth, R., E. Dutra, and F. Pappenberger, 2016: Improving weather predictability by
Parameter estimation of variable-parameter nonlinear Muskingum model using excel solver
Kang, Ling; Zhou, Liwei
2018-02-01
Abstract . The Muskingum model is an effective flood routing technology in hydrology and water resources Engineering. With the development of optimization technology, more and more variable-parameter Muskingum models were presented to improve effectiveness of the Muskingum model in recent decades. A variable-parameter nonlinear Muskingum model (NVPNLMM) was proposed in this paper. According to the results of two real and frequently-used case studies by various models, the NVPNLMM could obtain better values of evaluation criteria, which are used to describe the superiority of the estimated outflows and compare the accuracies of flood routing using various models, and the optimal estimated outflows by the NVPNLMM were closer to the observed outflows than the ones by other models.
Modeling and Parameter Estimation of a Small Wind Generation System
Carlos A. Ramírez Gómez
2013-11-01
Full Text Available The modeling and parameter estimation of a small wind generation system is presented in this paper. The system consists of a wind turbine, a permanent magnet synchronous generator, a three phase rectifier, and a direct current load. In order to estimate the parameters wind speed data are registered in a weather station located in the Fraternidad Campus at ITM. Wind speed data were applied to a reference model programed with PSIM software. From that simulation, variables were registered to estimate the parameters. The wind generation system model together with the estimated parameters is an excellent representation of the detailed model, but the estimated model offers a higher flexibility than the programed model in PSIM software.
NONLINEAR PLANT PIECEWISE-CONTINUOUS MODEL MATRIX PARAMETERS ESTIMATION
Roman L. Leibov
2017-09-01
Full Text Available This paper presents a nonlinear plant piecewise-continuous model matrix parameters estimation technique using nonlinear model time responses and random search method. One of piecewise-continuous model application areas is defined. The results of proposed approach application for aircraft turbofan engine piecewisecontinuous model formation are presented
Rong, Guan; Liu, Guang; Zhou, Chuang-bing
2013-01-01
Since rocks are aggregates of mineral particles, the effect of mineral microstructure on macroscopic mechanical behaviors of rocks is inneglectable. Rock samples of four different particle shapes are established in this study based on clumped particle model, and a sphericity index is used to quantify particle shape. Model parameters for simulation in PFC are obtained by triaxial compression test of quartz sandstone, and simulation of triaxial compression test is then conducted on four rock samples with different particle shapes. It is seen from the results that stress thresholds of rock samples such as crack initiation stress, crack damage stress, and peak stress decrease with the increasing of the sphericity index. The increase of sphericity leads to a drop of elastic modulus and a rise in Poisson ratio, while the decreasing sphericity usually results in the increase of cohesion and internal friction angle. Based on volume change of rock samples during simulation of triaxial compression test, variation of dilation angle with plastic strain is also studied. PMID:23997677
Rong, Guan; Liu, Guang; Hou, Di; Zhou, Chuang-Bing
2013-01-01
Since rocks are aggregates of mineral particles, the effect of mineral microstructure on macroscopic mechanical behaviors of rocks is inneglectable. Rock samples of four different particle shapes are established in this study based on clumped particle model, and a sphericity index is used to quantify particle shape. Model parameters for simulation in PFC are obtained by triaxial compression test of quartz sandstone, and simulation of triaxial compression test is then conducted on four rock samples with different particle shapes. It is seen from the results that stress thresholds of rock samples such as crack initiation stress, crack damage stress, and peak stress decrease with the increasing of the sphericity index. The increase of sphericity leads to a drop of elastic modulus and a rise in Poisson ratio, while the decreasing sphericity usually results in the increase of cohesion and internal friction angle. Based on volume change of rock samples during simulation of triaxial compression test, variation of dilation angle with plastic strain is also studied.
Identification of parameters of discrete-continuous models
Cekus, Dawid; Warys, Pawel
2015-01-01
In the paper, the parameters of a discrete-continuous model have been identified on the basis of experimental investigations and formulation of optimization problem. The discrete-continuous model represents a cantilever stepped Timoshenko beam. The mathematical model has been formulated and solved according to the Lagrange multiplier formalism. Optimization has been based on the genetic algorithm. The presented proceeding’s stages make the identification of any parameters of discrete-continuous systems possible
Identification of parameters of discrete-continuous models
Cekus, Dawid, E-mail: cekus@imipkm.pcz.pl; Warys, Pawel, E-mail: warys@imipkm.pcz.pl [Institute of Mechanics and Machine Design Foundations, Czestochowa University of Technology, Dabrowskiego 73, 42-201 Czestochowa (Poland)
2015-03-10
In the paper, the parameters of a discrete-continuous model have been identified on the basis of experimental investigations and formulation of optimization problem. The discrete-continuous model represents a cantilever stepped Timoshenko beam. The mathematical model has been formulated and solved according to the Lagrange multiplier formalism. Optimization has been based on the genetic algorithm. The presented proceeding’s stages make the identification of any parameters of discrete-continuous systems possible.
Parameter estimation in stochastic rainfall-runoff models
Jonsdottir, Harpa; Madsen, Henrik; Palsson, Olafur Petur
2006-01-01
A parameter estimation method for stochastic rainfall-runoff models is presented. The model considered in the paper is a conceptual stochastic model, formulated in continuous-discrete state space form. The model is small and a fully automatic optimization is, therefore, possible for estimating all...... the parameter values are optimal for simulation or prediction. The data originates from Iceland and the model is designed for Icelandic conditions, including a snow routine for mountainous areas. The model demands only two input data series, precipitation and temperature and one output data series...
Daily, Michael D. [Fundamental and Computational Sciences Directorate, Pacific Northwest National Laboratory, Richland, Washington 99352 (United States); Chun, Jaehun [Energy and Environment Directorate, Pacific Northwest National Laboratory, Richland, Washington 99352 (United States); Heredia-Langner, Alejandro [National Security Directorate, Pacific Northwest National Laboratory, Richland, Washington 99352 (United States); Wei, Guowei [Department of Mathematics, Michigan State University, East Lansing, Michigan 48824 (United States); Baker, Nathan A. [Computational and Statistical Analytics Division, Pacific Northwest National Laboratory, Richland, Washington 99352 (United States)
2013-11-28
Implicit solvent models are important tools for calculating solvation free energies for chemical and biophysical studies since they require fewer computational resources but can achieve accuracy comparable to that of explicit-solvent models. In past papers, geometric flow-based solvation models have been established for solvation analysis of small and large compounds. In the present work, the use of realistic experiment-based parameter choices for the geometric flow models is studied. We find that the experimental parameters of solvent internal pressure p = 172 MPa and surface tension γ = 72 mN/m produce solvation free energies within 1 RT of the global minimum root-mean-squared deviation from experimental data over the expanded set. Our results demonstrate that experimental values can be used for geometric flow solvent model parameters, thus eliminating the need for additional parameterization. We also examine the correlations between optimal values of p and γ which are strongly anti-correlated. Geometric analysis of the small molecule test set shows that these results are inter-connected with an approximately linear relationship between area and volume in the range of molecular sizes spanned by the data set. In spite of this considerable degeneracy between the surface tension and pressure terms in the model, both terms are important for the broader applicability of the model.
Some tests for parameter constancy in cointegrated VAR-models
Hansen, Henrik; Johansen, Søren
1999-01-01
Some methods for the evaluation of parameter constancy in vector autoregressive (VAR) models are discussed. Two different ways of re-estimating the VAR model are proposed; one in which all parameters are estimated recursively based upon the likelihood function for the first observations, and anot...... be applied to test the constancy of the long-run parameters in the cointegrated VAR-model. All results are illustrated using a model for the term structure of interest rates on US Treasury securities. ......Some methods for the evaluation of parameter constancy in vector autoregressive (VAR) models are discussed. Two different ways of re-estimating the VAR model are proposed; one in which all parameters are estimated recursively based upon the likelihood function for the first observations......, and another in which the cointegrating relations are estimated recursively from a likelihood function, where the short-run parameters have been concentrated out. We suggest graphical procedures based on recursively estimated eigenvalues to evaluate the constancy of the long-run parameters in the model...
Determination of the S-wave scattering shape parameter P from the zero-energy wave function
Kermode, M.W.; van Dijk, W.
1990-01-01
We show that for S-wave scattering at an energy k 2 by a local potential which supports no more than one bound state, the shape parameter P and coefficients of higher powers of k 2 in the effective range expansion function cotδ=-1/a+1/2 r 0 k 2 -Pr 0 3 k 3 +Qr 0 5 k 6 +..., where δ is the phase shift, may be obtained from the zero-energy wave function, u 0 (r). Thus δ itself may be determined from u 0 . We show that Pr 0 3 =∫ 0 R [β(r)u 0 2 (r)-bar β(r)bar u 0 2 (r)]dr, where r 0 is the effective range, β(r) is determined from an integral involving the wave function, and bar β(r) is a simple function of r which involves the scattering length and effective range
The fitting parameters extraction of conversion model of the low dose rate effect in bipolar devices
Bakerenkov, Alexander
2011-01-01
The Enhanced Low Dose Rate Sensitivity (ELDRS) in bipolar devices consists of in base current degradation of NPN and PNP transistors increase as the dose rate is decreased. As a result of almost 20-year studying, the some physical models of effect are developed, being described in detail. Accelerated test methods, based on these models use in standards. The conversion model of the effect, that allows to describe the inverse S-shaped excess base current dependence versus dose rate, was proposed. This paper presents the problem of conversion model fitting parameters extraction.
Incorporating model parameter uncertainty into inverse treatment planning
Lian Jun; Xing Lei
2004-01-01
Radiobiological treatment planning depends not only on the accuracy of the models describing the dose-response relation of different tumors and normal tissues but also on the accuracy of tissue specific radiobiological parameters in these models. Whereas the general formalism remains the same, different sets of model parameters lead to different solutions and thus critically determine the final plan. Here we describe an inverse planning formalism with inclusion of model parameter uncertainties. This is made possible by using a statistical analysis-based frameset developed by our group. In this formalism, the uncertainties of model parameters, such as the parameter a that describes tissue-specific effect in the equivalent uniform dose (EUD) model, are expressed by probability density function and are included in the dose optimization process. We found that the final solution strongly depends on distribution functions of the model parameters. Considering that currently available models for computing biological effects of radiation are simplistic, and the clinical data used to derive the models are sparse and of questionable quality, the proposed technique provides us with an effective tool to minimize the effect caused by the uncertainties in a statistical sense. With the incorporation of the uncertainties, the technique has potential for us to maximally utilize the available radiobiology knowledge for better IMRT treatment
Effect of Coating Parameters of the Buffer Layer on the Shape Ratio of TRISO-Coated Particles
KIm, Weon Ju; Park, Jong Hoon; Park, Ji Yeon; Lee, Young Woo; Chang, Jong Hwa
2005-01-01
Fuel for high temperature gas-cooled reactors (HTGR's) consists of TRISO-coated particles. Fluidized bed chemical vapor deposition (FBCVD) has been applied to fabricate the TRISO-coated fuel particles. The TRISO particles consist of UO 2 microspheres coated with layers of porous pyrolytic carbon (PyC), inner dense PyC (IPyC), SiC, and outer dense PyC (OPyC). The porous PyC coating layer, called the buffer layer, attenuates fission recoils and provides void volume for gaseous fission products and carbon monoxide. The buffer layer, which has the highest coating rate among the coating layers, shows the largest variation of the coating thickness within a particle and a batch. This could be the most plausible source of an asphericity in the TRISO particles. The aspherical particles are expected to have an inferior fuel performance. Miller et al. have predicted that a larger stress is developed within the coating layers and thus the failure probability increases in the particles with high aspect ratios. Therefore, the shape of the TRISO-coated particles should be controlled properly and has been one of the important inspection items for the quality control of the fabrication process. In this paper, we investigated the effect of coating parameters of the buffer layer on the shape of the TRISO particles. The flow rate of coating gas and the coating temperature were varied to control the buffer layer. The asphericity of the TRISO-coated particles was evaluated for the various coating conditions of the buffer layer, but at constant coating parameters for the IPyC/SiC/OPyC layers
A method for model identification and parameter estimation
Bambach, M; Heinkenschloss, M; Herty, M
2013-01-01
We propose and analyze a new method for the identification of a parameter-dependent model that best describes a given system. This problem arises, for example, in the mathematical modeling of material behavior where several competing constitutive equations are available to describe a given material. In this case, the models are differential equations that arise from the different constitutive equations, and the unknown parameters are coefficients in the constitutive equations. One has to determine the best-suited constitutive equations for a given material and application from experiments. We assume that the true model is one of the N possible parameter-dependent models. To identify the correct model and the corresponding parameters, we can perform experiments, where for each experiment we prescribe an input to the system and observe a part of the system state. Our approach consists of two stages. In the first stage, for each pair of models we determine the experiment, i.e. system input and observation, that best differentiates between the two models, and measure the distance between the two models. Then we conduct N(N − 1) or, depending on the approach taken, N(N − 1)/2 experiments and use the result of the experiments as well as the previously computed model distances to determine the true model. We provide sufficient conditions on the model distances and measurement errors which guarantee that our approach identifies the correct model. Given the model, we identify the corresponding model parameters in the second stage. The problem in the second stage is a standard parameter estimation problem and we use a method suitable for the given application. We illustrate our approach on three examples, including one where the models are elliptic partial differential equations with different parameterized right-hand sides and an example where we identify the constitutive equation in a problem from computational viscoplasticity. (paper)
Modelling hydrodynamic parameters to predict flow assisted corrosion
Poulson, B.; Greenwell, B.; Chexal, B.; Horowitz, J.
1992-01-01
During the past 15 years, flow assisted corrosion has been a worldwide problem in the power generating industry. The phenomena is complex and depends on environment, material composition, and hydrodynamic factors. Recently, modeling of flow assisted corrosion has become a subject of great importance. A key part of this effort is modeling the hydrodynamic aspects of this issue. This paper examines which hydrodynamic parameter should be used to correlate the occurrence and rate of flow assisted corrosion with physically meaningful parameters, discusses ways of measuring the relevant hydrodynamic parameter, and describes how the hydrodynamic data is incorporated into the predictive model
A distributed approach for parameters estimation in System Biology models
Mosca, E.; Merelli, I.; Alfieri, R.; Milanesi, L.
2009-01-01
Due to the lack of experimental measurements, biological variability and experimental errors, the value of many parameters of the systems biology mathematical models is yet unknown or uncertain. A possible computational solution is the parameter estimation, that is the identification of the parameter values that determine the best model fitting respect to experimental data. We have developed an environment to distribute each run of the parameter estimation algorithm on a different computational resource. The key feature of the implementation is a relational database that allows the user to swap the candidate solutions among the working nodes during the computations. The comparison of the distributed implementation with the parallel one showed that the presented approach enables a faster and better parameter estimation of systems biology models.
Optimal parameters for the FFA-Beddoes dynamic stall model
Bjoerck, A; Mert, M [FFA, The Aeronautical Research Institute of Sweden, Bromma (Sweden); Madsen, H A [Risoe National Lab., Roskilde (Denmark)
1999-03-01
Unsteady aerodynamic effects, like dynamic stall, must be considered in calculation of dynamic forces for wind turbines. Models incorporated in aero-elastic programs are of semi-empirical nature. Resulting aerodynamic forces therefore depend on values used for the semi-empiricial parameters. In this paper a study of finding appropriate parameters to use with the Beddoes-Leishman model is discussed. Minimisation of the `tracking error` between results from 2D wind tunnel tests and simulation with the model is used to find optimum values for the parameters. The resulting optimum parameters show a large variation from case to case. Using these different sets of optimum parameters in the calculation of blade vibrations, give rise to quite different predictions of aerodynamic damping which is discussed. (au)
P. Räisänen
2017-12-01
Full Text Available Snow consists of non-spherical grains of various shapes and sizes. Still, in radiative transfer calculations, snow grains are often treated as spherical. This also applies to the computation of snow albedo in the Snow, Ice, and Aerosol Radiation (SNICAR model and in the Los Alamos sea ice model, version 4 (CICE4, both of which are employed in the Community Earth System Model and in the Norwegian Earth System Model (NorESM. In this study, we evaluate the effect of snow grain shape on climate simulated by NorESM in a slab ocean configuration of the model. An experiment with spherical snow grains (SPH is compared with another (NONSPH in which the snow shortwave single-scattering properties are based on a combination of three non-spherical snow grain shapes optimized using measurements of angular scattering by blowing snow. The key difference between these treatments is that the asymmetry parameter is smaller in the non-spherical case (0.77–0.78 in the visible region than in the spherical case ( ≈ 0.89. Therefore, for the same effective snow grain size (or equivalently, the same specific projected area, the snow broadband albedo is higher when assuming non-spherical rather than spherical snow grains, typically by 0.02–0.03. Considering the spherical case as the baseline, this results in an instantaneous negative change in net shortwave radiation with a global-mean top-of-the-model value of ca. −0.22 W m−2. Although this global-mean radiative effect is rather modest, the impacts on the climate simulated by NorESM are substantial. The global annual-mean 2 m air temperature in NONSPH is 1.17 K lower than in SPH, with substantially larger differences at high latitudes. The climatic response is amplified by strong snow and sea ice feedbacks. It is further demonstrated that the effect of snow grain shape could be largely offset by adjusting the snow grain size. When assuming non-spherical snow grains with the parameterized grain
Räisänen, Petri; Makkonen, Risto; Kirkevåg, Alf; Debernard, Jens B.
2017-12-01
Snow consists of non-spherical grains of various shapes and sizes. Still, in radiative transfer calculations, snow grains are often treated as spherical. This also applies to the computation of snow albedo in the Snow, Ice, and Aerosol Radiation (SNICAR) model and in the Los Alamos sea ice model, version 4 (CICE4), both of which are employed in the Community Earth System Model and in the Norwegian Earth System Model (NorESM). In this study, we evaluate the effect of snow grain shape on climate simulated by NorESM in a slab ocean configuration of the model. An experiment with spherical snow grains (SPH) is compared with another (NONSPH) in which the snow shortwave single-scattering properties are based on a combination of three non-spherical snow grain shapes optimized using measurements of angular scattering by blowing snow. The key difference between these treatments is that the asymmetry parameter is smaller in the non-spherical case (0.77-0.78 in the visible region) than in the spherical case ( ≈ 0.89). Therefore, for the same effective snow grain size (or equivalently, the same specific projected area), the snow broadband albedo is higher when assuming non-spherical rather than spherical snow grains, typically by 0.02-0.03. Considering the spherical case as the baseline, this results in an instantaneous negative change in net shortwave radiation with a global-mean top-of-the-model value of ca. -0.22 W m-2. Although this global-mean radiative effect is rather modest, the impacts on the climate simulated by NorESM are substantial. The global annual-mean 2 m air temperature in NONSPH is 1.17 K lower than in SPH, with substantially larger differences at high latitudes. The climatic response is amplified by strong snow and sea ice feedbacks. It is further demonstrated that the effect of snow grain shape could be largely offset by adjusting the snow grain size. When assuming non-spherical snow grains with the parameterized grain size increased by ca. 70 %, the
Online State Space Model Parameter Estimation in Synchronous Machines
Z. Gallehdari
2014-06-01
The suggested approach is evaluated for a sample synchronous machine model. Estimated parameters are tested for different inputs at different operating conditions. The effect of noise is also considered in this study. Simulation results show that the proposed approach provides good accuracy for parameter estimation.
Modelling of loading, stress relaxation and stress recovery in a shape memory polymer.
Sweeney, J; Bonner, M; Ward, I M
2014-09-01
A multi-element constitutive model for a lactide-based shape memory polymer has been developed that represents loading to large tensile deformations, stress relaxation and stress recovery at 60, 65 and 70°C. The model consists of parallel Maxwell arms each comprising neo-Hookean and Eyring elements. Guiu-Pratt analysis of the stress relaxation curves yields Eyring parameters. When these parameters are used to define the Eyring process in a single Maxwell arm, the resulting model yields at too low a stress, but gives good predictions for longer times. Stress dip tests show a very stiff response on unloading by a small strain decrement. This would create an unrealistically high stress on loading to large strain if it were modelled by an elastic element. Instead it is modelled by an Eyring process operating via a flow rule that introduces strain hardening after yield. When this process is incorporated into a second parallel Maxwell arm, there results a model that fully represents both stress relaxation and stress dip tests at 60°C. At higher temperatures a third arm is required for valid predictions. Crown Copyright © 2014. Published by Elsevier Ltd. All rights reserved.
Bates, P. D.; Neal, J. C.; Fewtrell, T. J.
2012-12-01
In this we paper we consider two related questions. First, we address the issue of how much physical complexity is necessary in a model in order to simulate floodplain inundation to within validation data error. This is achieved through development of a single code/multiple physics hydraulic model (LISFLOOD-FP) where different degrees of complexity can be switched on or off. Different configurations of this code are applied to four benchmark test cases, and compared to the results of a number of industry standard models. Second we address the issue of how parameter sensitivity and transferability change with increasing complexity using numerical experiments with models of different physical and geometric intricacy. Hydraulic models are a good example system with which to address such generic modelling questions as: (1) they have a strong physical basis; (2) there is only one set of equations to solve; (3) they require only topography and boundary conditions as input data; and (4) they typically require only a single free parameter, namely boundary friction. In terms of complexity required we show that for the problem of sub-critical floodplain inundation a number of codes of different dimensionality and resolution can be found to fit uncertain model validation data equally well, and that in this situation Occam's razor emerges as a useful logic to guide model selection. We find also find that model skill usually improves more rapidly with increases in model spatial resolution than increases in physical complexity, and that standard approaches to testing hydraulic models against laboratory data or analytical solutions may fail to identify this important fact. Lastly, we find that in benchmark testing studies significant differences can exist between codes with identical numerical solution techniques as a result of auxiliary choices regarding the specifics of model implementation that are frequently unreported by code developers. As a consequence, making sound
Recent Progress on Modeling Slip Deformation in Shape Memory Alloys
Sehitoglu, H.; Alkan, S.
2018-03-01
This paper presents an overview of slip deformation in shape memory alloys. The performance of shape memory alloys depends on their slip resistance often quantified through the Critical Resolved Shear Stress (CRSS) or the flow stress. We highlight previous studies that identify the active slip systems and then proceed to show how non- Schmid effects can be dominant in shape memory slip behavior. The work is mostly derived from our recent studies while we highlight key earlier works on slip deformation. We finally discuss the implications of understanding the role of slip on curtailing the transformation strains and also the temperature range over which superelasticity prevails.
Recent Progress on Modeling Slip Deformation in Shape Memory Alloys
Sehitoglu, H.; Alkan, S.
2018-03-01
This paper presents an overview of slip deformation in shape memory alloys. The performance of shape memory alloys depends on their slip resistance often quantified through the Critical Resolved Shear Stress (CRSS) or the flow stress. We highlight previous studies that identify the active slip systems and then proceed to show how non-Schmid effects can be dominant in shape memory slip behavior. The work is mostly derived from our recent studies while we highlight key earlier works on slip deformation. We finally discuss the implications of understanding the role of slip on curtailing the transformation strains and also the temperature range over which superelasticity prevails.
Retrospective forecast of ETAS model with daily parameters estimate
Falcone, Giuseppe; Murru, Maura; Console, Rodolfo; Marzocchi, Warner; Zhuang, Jiancang
2016-04-01
We present a retrospective ETAS (Epidemic Type of Aftershock Sequence) model based on the daily updating of free parameters during the background, the learning and the test phase of a seismic sequence. The idea was born after the 2011 Tohoku-Oki earthquake. The CSEP (Collaboratory for the Study of Earthquake Predictability) Center in Japan provided an appropriate testing benchmark for the five 1-day submitted models. Of all the models, only one was able to successfully predict the number of events that really happened. This result was verified using both the real time and the revised catalogs. The main cause of the failure was in the underestimation of the forecasted events, due to model parameters maintained fixed during the test. Moreover, the absence in the learning catalog of an event similar to the magnitude of the mainshock (M9.0), which drastically changed the seismicity in the area, made the learning parameters not suitable to describe the real seismicity. As an example of this methodological development we show the evolution of the model parameters during the last two strong seismic sequences in Italy: the 2009 L'Aquila and the 2012 Reggio Emilia episodes. The achievement of the model with daily updated parameters is compared with that of same model where the parameters remain fixed during the test time.
Agricultural and Environmental Input Parameters for the Biosphere Model
Kaylie Rasmuson; Kurt Rautenstrauch
2003-06-20
This analysis is one of nine technical reports that support the Environmental Radiation Model for Yucca Mountain Nevada (ERMYN) biosphere model. It documents input parameters for the biosphere model, and supports the use of the model to develop Biosphere Dose Conversion Factors (BDCF). The biosphere model is one of a series of process models supporting the Total System Performance Assessment (TSPA) for the repository at Yucca Mountain. The ERMYN provides the TSPA with the capability to perform dose assessments. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows the interrelationships between the major activities and their products (the analysis and model reports) that were planned in the biosphere Technical Work Plan (TWP, BSC 2003a). It should be noted that some documents identified in Figure 1-1 may be under development and therefore not available at the time this document is issued. The ''Biosphere Model Report'' (BSC 2003b) describes the ERMYN and its input parameters. This analysis report, ANL-MGR-MD-000006, ''Agricultural and Environmental Input Parameters for the Biosphere Model'', is one of the five reports that develop input parameters for the biosphere model. This report defines and justifies values for twelve parameters required in the biosphere model. These parameters are related to use of contaminated groundwater to grow crops. The parameter values recommended in this report are used in the soil, plant, and carbon-14 submodels of the ERMYN.
Determination of HCME 3-D parameters using a full ice-cream cone model
Na, Hyeonock; Moon, Yong-Jae; Lee, Harim
2016-05-01
It is very essential to determine three dimensional parameters (e.g., radial speed, angular width, source location) of Coronal Mass Ejections (CMEs) for space weather forecast. Several cone models (e.g., an elliptical cone model, an ice-cream cone model, an asymmetric cone model) have been examined to estimate these parameters. In this study, we investigate which cone type is close to a halo CME morphology using 26 CMEs: halo CMEs by one spacecraft (SOHO or STEREO-A or B) and as limb CMEs by the other ones. From cone shape parameters of these CMEs such as their front curvature, we find that near full ice-cream cone type CMEs are much closer to observations than shallow ice-cream cone type CMEs. Thus we develop a new cone model in which a full ice-cream cone consists of many flat cones with different heights and angular widths. This model is carried out by the following steps: (1) construct a cone for given height and angular width, (2) project the cone onto the sky plane, (3) select points comprising the outer boundary, and (4) minimize the difference between the estimated projection speeds with the observed ones. By applying this model to 12 SOHO/LASCO halo CMEs, we find that 3-D parameters from our method are similar to those from other stereoscopic methods (a geometrical triangulation method and a Graduated Cylindrical Shell model) based on multi-spacecraft data. We are developing a general ice-cream cone model whose front shape is a free parameter determined by observations.
A mathematical model for smart functionally graded beam integrated with shape memory alloy actuators
Sepiani, H.; Ebrahimi, F.; Karimipour, H.
2009-01-01
This paper presents a theoretical study of the thermally driven behavior of a shape memory alloy (SMA)/FGM actuator under arbitrary loading and boundary conditions by developing an integrated mathematical model. The model studied is established on the geometric parameters of the three-dimensional laminated composite box beam as an actuator that consists of a functionally graded core integrated with SMA actuator layers with a uniform rectangular cross section. The constitutive equation and linear phase transformation kinetics relations of SMA layers based on Tanaka and Nagaki model are coupled with the governing equation of the actuator to predict the stress history and to model the thermo-mechanical behavior of the smart shape memory alloy/FGM beam. Based on the classical laminated beam theory, the explicit solution to the structural response of the structure, including axial and lateral deflections of the structure, is investigated. As an example, a cantilever box beam subjected to a transverse concentrated load is solved numerically. It is found that the changes in the actuator's responses during the phase transformation due to the strain recovery are significant
Milledge, David G; Bellugi, Dino; McKean, Jim A; Densmore, Alexander L; Dietrich, William E
2014-11-01
The size of a shallow landslide is a fundamental control on both its hazard and geomorphic importance. Existing models are either unable to predict landslide size or are computationally intensive such that they cannot practically be applied across landscapes. We derive a model appropriate for natural slopes that is capable of predicting shallow landslide size but simple enough to be applied over entire watersheds. It accounts for lateral resistance by representing the forces acting on each margin of potential landslides using earth pressure theory and by representing root reinforcement as an exponential function of soil depth. We test our model's ability to predict failure of an observed landslide where the relevant parameters are well constrained by field data. The model predicts failure for the observed scar geometry and finds that larger or smaller conformal shapes are more stable. Numerical experiments demonstrate that friction on the boundaries of a potential landslide increases considerably the magnitude of lateral reinforcement, relative to that due to root cohesion alone. We find that there is a critical depth in both cohesive and cohesionless soils, resulting in a minimum size for failure, which is consistent with observed size-frequency distributions. Furthermore, the differential resistance on the boundaries of a potential landslide is responsible for a critical landslide shape which is longer than it is wide, consistent with observed aspect ratios. Finally, our results show that minimum size increases as approximately the square of failure surface depth, consistent with observed landslide depth-area data.
Moussaoui, Ahmed; Bouziane, Touria
2016-01-01
The method LRPIM is a Meshless method with properties of simple implementation of the essential boundary conditions and less costly than the moving least squares (MLS) methods. This method is proposed to overcome the singularity associated to polynomial basis by using radial basis functions. In this paper, we will present a study of a 2D problem of an elastic homogenous rectangular plate by using the method LRPIM. Our numerical investigations will concern the influence of different shape parameters on the domain of convergence,accuracy and using the radial basis function of the thin plate spline. It also will presents a comparison between numerical results for different materials and the convergence domain by precising maximum and minimum values as a function of distribution nodes number. The analytical solution of the deflection confirms the numerical results. The essential points in the method are: •The LRPIM is derived from the local weak form of the equilibrium equations for solving a thin elastic plate.•The convergence of the LRPIM method depends on number of parameters derived from local weak form and sub-domains.•The effect of distributions nodes number by varying nature of material and the radial basis function (TPS).
Parameter Estimates in Differential Equation Models for Population Growth
Winkel, Brian J.
2011-01-01
We estimate the parameters present in several differential equation models of population growth, specifically logistic growth models and two-species competition models. We discuss student-evolved strategies and offer "Mathematica" code for a gradient search approach. We use historical (1930s) data from microbial studies of the Russian biologist,…
Uncertainty in dual permeability model parameters for structured soils
Arora, B.; Mohanty, B. P.; McGuire, J. T.
2012-01-01
Successful application of dual permeability models (DPM) to predict contaminant transport is contingent upon measured or inversely estimated soil hydraulic and solute transport parameters. The difficulty in unique identification of parameters for the additional macropore- and matrix-macropore interface regions, and knowledge about requisite experimental data for DPM has not been resolved to date. Therefore, this study quantifies uncertainty in dual permeability model parameters of experimental soil columns with different macropore distributions (single macropore, and low- and high-density multiple macropores). Uncertainty evaluation is conducted using adaptive Markov chain Monte Carlo (AMCMC) and conventional Metropolis-Hastings (MH) algorithms while assuming 10 out of 17 parameters to be uncertain or random. Results indicate that AMCMC resolves parameter correlations and exhibits fast convergence for all DPM parameters while MH displays large posterior correlations for various parameters. This study demonstrates that the choice of parameter sampling algorithms is paramount in obtaining unique DPM parameters when information on covariance structure is lacking, or else additional information on parameter correlations must be supplied to resolve the problem of equifinality of DPM parameters. This study also highlights the placement and significance of matrix-macropore interface in flow experiments of soil columns with different macropore densities. Histograms for certain soil hydraulic parameters display tri-modal characteristics implying that macropores are drained first followed by the interface region and then by pores of the matrix domain in drainage experiments. Results indicate that hydraulic properties and behavior of the matrix-macropore interface is not only a function of saturated hydraulic conductivity of the macroporematrix interface (Ksa) and macropore tortuosity (lf) but also of other parameters of the matrix and macropore domains.
A probabilistic model for component-based shape synthesis
Kalogerakis, Evangelos; Chaudhuri, Siddhartha; Koller, Daphne; Koltun, Vladlen
2012-01-01
represents probabilistic relationships between properties of shape components, and relates them to learned underlying causes of structural variability within the domain. These causes are treated as latent variables, leading to a compact representation
Modeling of hydrogen Stark line shapes with kinetic theory methods
Rosato, J.; Capes, H.; Stamm, R.
2012-12-01
The unified formalism for Stark line shapes is revisited and extended to non-binary interactions between an emitter and the surrounding perturbers. The accuracy of this theory is examined through comparisons with ab initio numerical simulations.
Luminescence model with quantum impact parameter for low energy ions
Cruz-Galindo, H S; Martínez-Davalos, A; Belmont-Moreno, E; Galindo, S
2002-01-01
We have modified an analytical model of induced light production by energetic ions interacting in scintillating materials. The original model is based on the distribution of energy deposited by secondary electrons produced along the ion's track. The range of scattered electrons, and thus the energy distribution, depends on a classical impact parameter between the electron and the ion's track. The only adjustable parameter of the model is the quenching density rho sub q. The modification here presented, consists in proposing a quantum impact parameter that leads to a better fit of the model to the experimental data at low incident ion energies. The light output response of CsI(Tl) detectors to low energy ions (<3 MeV/A) is fitted with the modified model and comparison is made to the original model.
The Effect of Sterilization on Size and Shape of Fat Globules in Model Processed Cheese Samples
B. Tremlová
2006-01-01
Full Text Available Model cheese samples from 4 independent productions were heat sterilized (117 °C, 20 minutes after the melting process and packing with an aim to prolong their durability. The objective of the study was to assess changes in the size and shape of fat globules due to heat sterilization by using image analysis methods. The study included a selection of suitable methods of preparation mounts, taking microphotographs and making overlays for automatic processing of photographs by image analyser, ascertaining parameters to determine the size and shape of fat globules and statistical analysis of results obtained. The results of the experiment suggest that changes in shape of fat globules due to heat sterilization are not unequivocal. We found that the size of fat globules was significantly increased (p < 0.01 due to heat sterilization (117 °C, 20 min, and the shares of small fat globules (up to 500 μm2, or 100 μm2 in the samples of heat sterilized processed cheese were decreased. The results imply that the image analysis method is very useful when assessing the effect of technological process on the quality of processed cheese quality.
Modeling of mechanical properties for ferrous shape memory alloy
Wada, Manabu; Ide, Yusuke; Mizote, Shinichiro; Naoi, Hisashi; Tsukimori, Kazuyuki
2002-08-01
In order to acquire technical data that are necessary for manufacture and design of the simulation test device for analyzing the core mechanics of Fast Breeder Reactor, ferrous shape memory alloy of Fe-28%Mn-6%Si-5%Cr is melted, forged and heat-treated. The microstructures are austenite. The specimens are deformed of up to 16% work-strain by tensile and compressive test, resulting in appearance of epsilon-martensite that is induced by stress. Then, heating at 673K for 10 minutes causes austenitic transformation from epsilon-martensite and shape memory strains are measured. We also investigate shape memory character of specimens, which are given, so called 'training treatment' of 5% pre-strain and recovery heat treatment. As a result, there is little difference between tensile and compressive test without training treatment and shape memory strain is 2% after being given 5% work-strain and recovery heat treatment. On the other hand, training treatment is remarkable and shape memory strain reaches to 3.7% after 5% work-strain. We analyze shape recovery character of this alloy specimen at three-point bending by using finite element method, and indicate possibility that its deformation behavior can be estimated from mechanical properties' data obtained at tensile and compressive test. (author)
Agricultural and Environmental Input Parameters for the Biosphere Model
K. Rasmuson; K. Rautenstrauch
2004-01-01
This analysis is one of 10 technical reports that support the Environmental Radiation Model for Yucca Mountain Nevada (ERMYN) (i.e., the biosphere model). It documents development of agricultural and environmental input parameters for the biosphere model, and supports the use of the model to develop biosphere dose conversion factors (BDCFs). The biosphere model is one of a series of process models supporting the total system performance assessment (TSPA) for the repository at Yucca Mountain. The ERMYN provides the TSPA with the capability to perform dose assessments. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows the interrelationships between the major activities and their products (the analysis and model reports) that were planned in ''Technical Work Plan for Biosphere Modeling and Expert Support'' (BSC 2004 [DIRS 169573]). The ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) describes the ERMYN and its input parameters
Determining extreme parameter correlation in ground water models
Hill, Mary Cole; Østerby, Ole
2003-01-01
can go undetected even by experienced modelers. Extreme parameter correlation can be detected using parameter correlation coefficients, but their utility depends on the presence of sufficient, but not excessive, numerical imprecision of the sensitivities, such as round-off error. This work...... investigates the information that can be obtained from parameter correlation coefficients in the presence of different levels of numerical imprecision, and compares it to the information provided by an alternative method called the singular value decomposition (SVD). Results suggest that (1) calculated...... correlation coefficients with absolute values that round to 1.00 were good indicators of extreme parameter correlation, but smaller values were not necessarily good indicators of lack of correlation and resulting unique parameter estimates; (2) the SVD may be more difficult to interpret than parameter...
Uncertainty of Modal Parameters Estimated by ARMA Models
Jensen, Jacob Laigaard; Brincker, Rune; Rytter, Anders
1990-01-01
In this paper the uncertainties of identified modal parameters such as eidenfrequencies and damping ratios are assed. From the measured response of dynamic excited structures the modal parameters may be identified and provide important structural knowledge. However the uncertainty of the parameters...... by simulation study of a lightly damped single degree of freedom system. Identification by ARMA models has been choosen as system identification method. It is concluded that both the sampling interval and number of sampled points may play a significant role with respect to the statistical errors. Furthermore......, it is shown that the model errors may also contribute significantly to the uncertainty....
Iqtait, M.; Mohamad, F. S.; Mamat, M.
2018-03-01
Biometric is a pattern recognition system which is used for automatic recognition of persons based on characteristics and features of an individual. Face recognition with high recognition rate is still a challenging task and usually accomplished in three phases consisting of face detection, feature extraction, and expression classification. Precise and strong location of trait point is a complicated and difficult issue in face recognition. Cootes proposed a Multi Resolution Active Shape Models (ASM) algorithm, which could extract specified shape accurately and efficiently. Furthermore, as the improvement of ASM, Active Appearance Models algorithm (AAM) is proposed to extracts both shape and texture of specified object simultaneously. In this paper we give more details about the two algorithms and give the results of experiments, testing their performance on one dataset of faces. We found that the ASM is faster and gains more accurate trait point location than the AAM, but the AAM gains a better match to the texture.
SPOTting Model Parameters Using a Ready-Made Python Package.
Tobias Houska
Full Text Available The choice for specific parameter estimation methods is often more dependent on its availability than its performance. We developed SPOTPY (Statistical Parameter Optimization Tool, an open source python package containing a comprehensive set of methods typically used to calibrate, analyze and optimize parameters for a wide range of ecological models. SPOTPY currently contains eight widely used algorithms, 11 objective functions, and can sample from eight parameter distributions. SPOTPY has a model-independent structure and can be run in parallel from the workstation to large computation clusters using the Message Passing Interface (MPI. We tested SPOTPY in five different case studies to parameterize the Rosenbrock, Griewank and Ackley functions, a one-dimensional physically based soil moisture routine, where we searched for parameters of the van Genuchten-Mualem function and a calibration of a biogeochemistry model with different objective functions. The case studies reveal that the implemented SPOTPY methods can be used for any model with just a minimal amount of code for maximal power of parameter optimization. They further show the benefit of having one package at hand that includes number of well performing parameter search methods, since not every case study can be solved sufficiently with every algorithm or every objective function.
Parameter resolution in two models for cell survival after radiation
Di Cera, E.; Andreasi Bassi, F.; Arcovito, G.
1989-01-01
The resolvability of model parameters for the linear-quadratic and the repair-misrepair models for cell survival after radiation has been studied by Monte Carlo simulations as a function of the number of experimental data points collected in a given dose range and the experimental error. Statistical analysis of the results reveals the range of experimental conditions under which the model parameters can be resolved with sufficient accuracy, and points out some differences in the operational aspects of the two models. (orig.)
Simultaneous inference for model averaging of derived parameters
Jensen, Signe Marie; Ritz, Christian
2015-01-01
Model averaging is a useful approach for capturing uncertainty due to model selection. Currently, this uncertainty is often quantified by means of approximations that do not easily extend to simultaneous inference. Moreover, in practice there is a need for both model averaging and simultaneous...... inference for derived parameters calculated in an after-fitting step. We propose a method for obtaining asymptotically correct standard errors for one or several model-averaged estimates of derived parameters and for obtaining simultaneous confidence intervals that asymptotically control the family...
Updating parameters of the chicken processing line model
Kurowicka, Dorota; Nauta, Maarten; Jozwiak, Katarzyna
2010-01-01
A mathematical model of chicken processing that quantitatively describes the transmission of Campylobacter on chicken carcasses from slaughter to chicken meat product has been developed in Nauta et al. (2005). This model was quantified with expert judgment. Recent availability of data allows...... updating parameters of the model to better describe processes observed in slaughterhouses. We propose Bayesian updating as a suitable technique to update expert judgment with microbiological data. Berrang and Dickens’s data are used to demonstrate performance of this method in updating parameters...... of the chicken processing line model....
Lumped-parameter Model of a Bucket Foundation
Andersen, Lars; Ibsen, Lars Bo; Liingaard, Morten
2009-01-01
efficient model that can be applied in aero-elastic codes for fast evaluation of the dynamic structural response of wind turbines. The target solutions, utilised for calibration of the lumped-parameter models, are obtained by a coupled finite-element/boundaryelement scheme in the frequency domain......, and the quality of the models are tested in the time and frequency domains. It is found that precise results are achieved by lumped-parameter models with two to four internal degrees of freedom per displacement or rotation of the foundation. Further, coupling between the horizontal sliding and rocking cannot...
Lumped-Parameter Models for Windturbine Footings on Layered Ground
Andersen, Lars
The design of modern wind turbines is typically based on lifetime analyses using aeroelastic codes. In this regard, the impedance of the foundations must be described accurately without increasing the overall size of the computationalmodel significantly. This may be obtained by the fitting...... of a lumped-parameter model to the results of a rigorous model or experimental results. In this paper, guidelines are given for the formulation of such lumped-parameter models and examples are given in which the models are utilised for the analysis of a wind turbine supported by a surface footing on a layered...
Ultrasound Common Carotid Artery Segmentation Based on Active Shape Model
Yang, Xin; Jin, Jiaoying; Xu, Mengling; Wu, Huihui; He, Wanji; Yuchi, Ming; Ding, Mingyue
2013-01-01
Carotid atherosclerosis is a major reason of stroke, a leading cause of death and disability. In this paper, a segmentation method based on Active Shape Model (ASM) is developed and evaluated to outline common carotid artery (CCA) for carotid atherosclerosis computer-aided evaluation and diagnosis. The proposed method is used to segment both media-adventitia-boundary (MAB) and lumen-intima-boundary (LIB) on transverse views slices from three-dimensional ultrasound (3D US) images. The data set consists of sixty-eight, 17 × 2 × 2, 3D US volume data acquired from the left and right carotid arteries of seventeen patients (eight treated with 80 mg atorvastatin and nine with placebo), who had carotid stenosis of 60% or more, at baseline and after three months of treatment. Manually outlined boundaries by expert are adopted as the ground truth for evaluation. For the MAB and LIB segmentations, respectively, the algorithm yielded Dice Similarity Coefficient (DSC) of 94.4% ± 3.2% and 92.8% ± 3.3%, mean absolute distances (MAD) of 0.26 ± 0.18 mm and 0.33 ± 0.21 mm, and maximum absolute distances (MAXD) of 0.75 ± 0.46 mm and 0.84 ± 0.39 mm. It took 4.3 ± 0.5 mins to segment single 3D US images, while it took 11.7 ± 1.2 mins for manual segmentation. The method would promote the translation of carotid 3D US to clinical care for the monitoring of the atherosclerotic disease progression and regression. PMID:23533535
Ultrasound Common Carotid Artery Segmentation Based on Active Shape Model
Xin Yang
2013-01-01
Full Text Available Carotid atherosclerosis is a major reason of stroke, a leading cause of death and disability. In this paper, a segmentation method based on Active Shape Model (ASM is developed and evaluated to outline common carotid artery (CCA for carotid atherosclerosis computer-aided evaluation and diagnosis. The proposed method is used to segment both media-adventitia-boundary (MAB and lumen-intima-boundary (LIB on transverse views slices from three-dimensional ultrasound (3D US images. The data set consists of sixty-eight, 17 × 2 × 2, 3D US volume data acquired from the left and right carotid arteries of seventeen patients (eight treated with 80 mg atorvastatin and nine with placebo, who had carotid stenosis of 60% or more, at baseline and after three months of treatment. Manually outlined boundaries by expert are adopted as the ground truth for evaluation. For the MAB and LIB segmentations, respectively, the algorithm yielded Dice Similarity Coefficient (DSC of 94.4% ± 3.2% and 92.8% ± 3.3%, mean absolute distances (MAD of 0.26 ± 0.18 mm and 0.33 ± 0.21 mm, and maximum absolute distances (MAXD of 0.75 ± 0.46 mm and 0.84 ± 0.39 mm. It took 4.3 ± 0.5 mins to segment single 3D US images, while it took 11.7 ± 1.2 mins for manual segmentation. The method would promote the translation of carotid 3D US to clinical care for the monitoring of the atherosclerotic disease progression and regression.
Modelling of a bridge-shaped nonlinear piezoelectric energy harvester
Gafforelli, G; Corigliano, A; Xu, R; Kim, S G
2013-01-01
Piezoelectric MicroElectroMechanical Systems (MEMS) energy harvesting is an attractive technology for harvesting small magnitudes of energy from ambient vibrations. Increasing the operating frequency bandwidth of such devices is one of the major issues for real world applications. A MEMS-scale doubly clamped nonlinear beam resonator is designed and developed to demonstrate very wide bandwidth and high power density. In this paper a first complete theoretical discussion of nonlinear resonating piezoelectric energy harvesting is provided. The sectional behaviour of the beam is studied through the Classical Lamination Theory (CLT) specifically modified to introduce the piezoelectric coupling and nonlinear Green-Lagrange strain tensor. A lumped parameter model is built through Rayleigh-Ritz Method and the resulting nonlinear coupled equations are solved in the frequency domain through the Harmonic Balance Method (HBM). Finally, the influence of external load resistance on the dynamic behaviour is studied. The theoretical model shows that nonlinear resonant harvesters have much wider power bandwidth than that of linear resonators but their maximum power is still bounded by the mechanical damping as is the case for linear resonating harvesters
Belyaev, Fedor S.; Evard, Margarita E.; Volkov, Aleksandr E.
2018-05-01
A microstructural model of shape memory alloys (SMA) describing their deformation and fatigue fracture is presented. A new criterion of fracture has been developed which takes into account the effect of hydrostatic pressure, deformation defects and material damage. It is shown that the model can describe the fatigue fracture of SMA under various thermomechanical cycling regimes. Results of calculating the number of cycles to failure at thermocycling under a constant stress, at symmetric two-sided cyclic deformation, at straining-unloading cycles, at cycling in the regime of the thermodynamic cycles of a SMA working body in the hard (strain controlled) and soft (stress controlled) working cycles, is studied. Results of calculating the number of cycles to failure are presented for different parameters of these cycles.
Woods, Christopher; Fernee, Christianne; Browne, Martin; Zakrzewski, Sonia; Dickinson, Alexander
2017-01-01
This paper introduces statistical shape modelling (SSM) for use in osteoarchaeology research. SSM is a full field, multi-material analytical technique, and is presented as a supplementary geometric morphometric (GM) tool. Lower mandibular canines from two archaeological populations and one modern population were sampled, digitised using micro-CT, aligned, registered to a baseline and statistically modelled using principal component analysis (PCA). Sample material properties were incorporated as a binary enamel/dentin parameter. Results were assessed qualitatively and quantitatively using anatomical landmarks. Finally, the technique's application was demonstrated for inter-sample comparison through analysis of the principal component (PC) weights. It was found that SSM could provide high detail qualitative and quantitative insight with respect to archaeological inter- and intra-sample variability. This technique has value for archaeological, biomechanical and forensic applications including identification, finite element analysis (FEA) and reconstruction from partial datasets.
Christopher Woods
Full Text Available This paper introduces statistical shape modelling (SSM for use in osteoarchaeology research. SSM is a full field, multi-material analytical technique, and is presented as a supplementary geometric morphometric (GM tool. Lower mandibular canines from two archaeological populations and one modern population were sampled, digitised using micro-CT, aligned, registered to a baseline and statistically modelled using principal component analysis (PCA. Sample material properties were incorporated as a binary enamel/dentin parameter. Results were assessed qualitatively and quantitatively using anatomical landmarks. Finally, the technique's application was demonstrated for inter-sample comparison through analysis of the principal component (PC weights. It was found that SSM could provide high detail qualitative and quantitative insight with respect to archaeological inter- and intra-sample variability. This technique has value for archaeological, biomechanical and forensic applications including identification, finite element analysis (FEA and reconstruction from partial datasets.
Optimization of ultrasonic array inspections using an efficient hybrid model and real crack shapes
Felice, Maria V., E-mail: maria.felice@bristol.ac.uk [Department of Mechanical Engineering, University of Bristol, Bristol, U.K. and NDE Laboratory, Rolls-Royce plc., Bristol (United Kingdom); Velichko, Alexander, E-mail: p.wilcox@bristol.ac.uk; Wilcox, Paul D., E-mail: p.wilcox@bristol.ac.uk [Department of Mechanical Engineering, University of Bristol, Bristol (United Kingdom); Barden, Tim; Dunhill, Tony [NDE Laboratory, Rolls-Royce plc., Bristol (United Kingdom)
2015-03-31
Models which simulate the interaction of ultrasound with cracks can be used to optimize ultrasonic array inspections, but this approach can be time-consuming. To overcome this issue an efficient hybrid model is implemented which includes a finite element method that requires only a single layer of elements around the crack shape. Scattering Matrices are used to capture the scattering behavior of the individual cracks and a discussion on the angular degrees of freedom of elastodynamic scatterers is included. Real crack shapes are obtained from X-ray Computed Tomography images of cracked parts and these shapes are inputted into the hybrid model. The effect of using real crack shapes instead of straight notch shapes is demonstrated. An array optimization methodology which incorporates the hybrid model, an approximate single-scattering relative noise model and the real crack shapes is then described.
Seasonal and spatial variation in broadleaf forest model parameters
Groenendijk, M.; van der Molen, M. K.; Dolman, A. J.
2009-04-01
Process based, coupled ecosystem carbon, energy and water cycle models are used with the ultimate goal to project the effect of future climate change on the terrestrial carbon cycle. A typical dilemma in such exercises is how much detail the model must be given to describe the observations reasonably realistic while also be general. We use a simple vegetation model (5PM) with five model parameters to study the variability of the parameters. These parameters are derived from the observed carbon and water fluxes from the FLUXNET database. For 15 broadleaf forests the model parameters were derived for different time resolutions. It appears that in general for all forests, the correlation coefficient between observed and simulated carbon and water fluxes improves with a higher parameter time resolution. The quality of the simulations is thus always better when a higher time resolution is used. These results show that annual parameters are not capable of properly describing weather effects on ecosystem fluxes, and that two day time resolution yields the best results. A first indication of the climate constraints can be found by the seasonal variation of the covariance between Jm, which describes the maximum electron transport for photosynthesis, and climate variables. A general seasonality we found is that during winter the covariance with all climate variables is zero. Jm increases rapidly after initial spring warming, resulting in a large covariance with air temperature and global radiation. During summer Jm is less variable, but co-varies negatively with air temperature and vapour pressure deficit and positively with soil water content. A temperature response appears during spring and autumn for broadleaf forests. This shows that an annual model parameter cannot be representative for the entire year. And relations with mean annual temperature are not possible. During summer the photosynthesis parameters are constrained by water availability, soil water content and
Comparison of parameter estimation algorithms in hydrological modelling
Blasone, Roberta-Serena; Madsen, Henrik; Rosbjerg, Dan
2006-01-01
Local search methods have been applied successfully in calibration of simple groundwater models, but might fail in locating the optimum for models of increased complexity, due to the more complex shape of the response surface. Global search algorithms have been demonstrated to perform well......-Marquardt-Levenberg algorithm (implemented in the PEST software), when applied to a steady-state and a transient groundwater model. The results show that PEST can have severe problems in locating the global optimum and in being trapped in local regions of attractions. The global SCE procedure is, in general, more effective...... and provides a better coverage of the Pareto optimal solutions at a lower computational cost....
Lu, Haibao; Wang, Xiaodong; Yao, Yongtao; Qing Fu, Yong
2018-06-01
Phenomenological models based on frozen volume parameters could well predict shape recovery behavior of shape memory polymers (SMPs), but the physical meaning of using the frozen volume parameters to describe thermomechanical properties has not been well-established. In this study, the fundamental working mechanisms of the shape memory effect (SME) in amorphous SMPs, whose temperature-dependent viscoelastic behavior follows the Eyring equation, have been established with the considerations of both internal stress and its resulted frozen volume. The stress-strain constitutive relation was initially modeled to quantitatively describe effects of internal stresses at the macromolecular scale based on the transient network theory. A phenomenological ‘frozen volume’ model was then established to characterize the macromolecule structure and SME of amorphous SMPs based on a two-site stress-relaxation model. Effects of the internal stress, frozen volume and strain rate on shape memory behavior and thermomechanical properties of the SMP were investigated. Finally, the simulation results were compared with the experimental results reported in the literature, and good agreements between the theoretical and experimental results were achieved. The novelty and key differences of our newly proposed model with respect to the previous reports are (1). The ‘frozen volume’ in our study is caused by the internal stress and governed by the two-site model theory, thus has a good physical meaning. (2). The model can be applied to characterize and predict both the thermal and thermomechanical behaviors of SMPs based on the constitutive relationship with internal stress parameters. It is expected to provide a power tool to investigate the thermomechanical behavior of the SMPs, of which both the macromolecular structure characteristics and SME could be predicted using this ‘frozen volume’ model.
Environmental Transport Input Parameters for the Biosphere Model
M. Wasiolek
2004-09-10
This analysis report is one of the technical reports documenting the Environmental Radiation Model for Yucca Mountain, Nevada (ERMYN), a biosphere model supporting the total system performance assessment for the license application (TSPA-LA) for the geologic repository at Yucca Mountain. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows relationships among the reports developed for biosphere modeling and biosphere abstraction products for the TSPA-LA, as identified in the ''Technical Work Plan for Biosphere Modeling and Expert Support'' (BSC 2004 [DIRS 169573]) (TWP). This figure provides an understanding of how this report contributes to biosphere modeling in support of the license application (LA). This report is one of the five reports that develop input parameter values for the biosphere model. The ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) describes the conceptual model and the mathematical model. The input parameter reports, shown to the right of the Biosphere Model Report in Figure 1-1, contain detailed description of the model input parameters. The output of this report is used as direct input in the ''Nominal Performance Biosphere Dose Conversion Factor Analysis'' and in the ''Disruptive Event Biosphere Dose Conversion Factor Analysis'' that calculate the values of biosphere dose conversion factors (BDCFs) for the groundwater and volcanic ash exposure scenarios, respectively. The purpose of this analysis was to develop biosphere model parameter values related to radionuclide transport and accumulation in the environment. These parameters support calculations of radionuclide concentrations in the environmental media (e.g., soil, crops, animal products, and air) resulting from a given radionuclide concentration at the source of contamination (i.e., either in groundwater or in volcanic ash). The analysis
Environmental Transport Input Parameters for the Biosphere Model
M. Wasiolek
2004-01-01
This analysis report is one of the technical reports documenting the Environmental Radiation Model for Yucca Mountain, Nevada (ERMYN), a biosphere model supporting the total system performance assessment for the license application (TSPA-LA) for the geologic repository at Yucca Mountain. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows relationships among the reports developed for biosphere modeling and biosphere abstraction products for the TSPA-LA, as identified in the ''Technical Work Plan for Biosphere Modeling and Expert Support'' (BSC 2004 [DIRS 169573]) (TWP). This figure provides an understanding of how this report contributes to biosphere modeling in support of the license application (LA). This report is one of the five reports that develop input parameter values for the biosphere model. The ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) describes the conceptual model and the mathematical model. The input parameter reports, shown to the right of the Biosphere Model Report in Figure 1-1, contain detailed description of the model input parameters. The output of this report is used as direct input in the ''Nominal Performance Biosphere Dose Conversion Factor Analysis'' and in the ''Disruptive Event Biosphere Dose Conversion Factor Analysis'' that calculate the values of biosphere dose conversion factors (BDCFs) for the groundwater and volcanic ash exposure scenarios, respectively. The purpose of this analysis was to develop biosphere model parameter values related to radionuclide transport and accumulation in the environment. These parameters support calculations of radionuclide concentrations in the environmental media (e.g., soil, crops, animal products, and air) resulting from a given radionuclide concentration at the source of contamination (i.e., either in groundwater or in volcanic ash). The analysis was performed in accordance with the TWP (BSC 2004 [DIRS 169573])
Inhalation Exposure Input Parameters for the Biosphere Model
K. Rautenstrauch
2004-09-10
This analysis is one of 10 reports that support the Environmental Radiation Model for Yucca Mountain, Nevada (ERMYN) biosphere model. The ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) describes in detail the conceptual model as well as the mathematical model and its input parameters. This report documents development of input parameters for the biosphere model that are related to atmospheric mass loading and supports the use of the model to develop biosphere dose conversion factors (BDCFs). The biosphere model is one of a series of process models supporting the total system performance assessment (TSPA) for a Yucca Mountain repository. Inhalation Exposure Input Parameters for the Biosphere Model is one of five reports that develop input parameters for the biosphere model. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows the interrelationships among the products (i.e., analysis and model reports) developed for biosphere modeling, and the plan for development of the biosphere abstraction products for TSPA, as identified in the Technical Work Plan for Biosphere Modeling and Expert Support (BSC 2004 [DIRS 169573]). This analysis report defines and justifies values of mass loading for the biosphere model. Mass loading is the total mass concentration of resuspended particles (e.g., dust, ash) in a volume of air. Mass loading values are used in the air submodel of ERMYN to calculate concentrations of radionuclides in air inhaled by a receptor and concentrations in air surrounding crops. Concentrations in air to which the receptor is exposed are then used in the inhalation submodel to calculate the dose contribution to the receptor from inhalation of contaminated airborne particles. Concentrations in air surrounding plants are used in the plant submodel to calculate the concentrations of radionuclides in foodstuffs contributed from uptake by foliar interception.
Inhalation Exposure Input Parameters for the Biosphere Model
K. Rautenstrauch
2004-01-01
This analysis is one of 10 reports that support the Environmental Radiation Model for Yucca Mountain, Nevada (ERMYN) biosphere model. The ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) describes in detail the conceptual model as well as the mathematical model and its input parameters. This report documents development of input parameters for the biosphere model that are related to atmospheric mass loading and supports the use of the model to develop biosphere dose conversion factors (BDCFs). The biosphere model is one of a series of process models supporting the total system performance assessment (TSPA) for a Yucca Mountain repository. Inhalation Exposure Input Parameters for the Biosphere Model is one of five reports that develop input parameters for the biosphere model. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows the interrelationships among the products (i.e., analysis and model reports) developed for biosphere modeling, and the plan for development of the biosphere abstraction products for TSPA, as identified in the Technical Work Plan for Biosphere Modeling and Expert Support (BSC 2004 [DIRS 169573]). This analysis report defines and justifies values of mass loading for the biosphere model. Mass loading is the total mass concentration of resuspended particles (e.g., dust, ash) in a volume of air. Mass loading values are used in the air submodel of ERMYN to calculate concentrations of radionuclides in air inhaled by a receptor and concentrations in air surrounding crops. Concentrations in air to which the receptor is exposed are then used in the inhalation submodel to calculate the dose contribution to the receptor from inhalation of contaminated airborne particles. Concentrations in air surrounding plants are used in the plant submodel to calculate the concentrations of radionuclides in foodstuffs contributed from uptake by foliar interception
Environmental Transport Input Parameters for the Biosphere Model
Wasiolek, M. A.
2003-01-01
This analysis report is one of the technical reports documenting the Environmental Radiation Model for Yucca Mountain Nevada (ERMYN), a biosphere model supporting the total system performance assessment (TSPA) for the geologic repository at Yucca Mountain. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows relationships among the reports developed for biosphere modeling and biosphere abstraction products for the TSPA, as identified in the ''Technical Work Plan: for Biosphere Modeling and Expert Support'' (TWP) (BSC 2003 [163602]). Some documents in Figure 1-1 may be under development and not available when this report is issued. This figure provides an understanding of how this report contributes to biosphere modeling in support of the license application (LA), but access to the listed documents is not required to understand the contents of this report. This report is one of the reports that develops input parameter values for the biosphere model. The ''Biosphere Model Report'' (BSC 2003 [160699]) describes the conceptual model, the mathematical model, and the input parameters. The purpose of this analysis is to develop biosphere model parameter values related to radionuclide transport and accumulation in the environment. These parameters support calculations of radionuclide concentrations in the environmental media (e.g., soil, crops, animal products, and air) resulting from a given radionuclide concentration at the source of contamination (i.e., either in groundwater or volcanic ash). The analysis was performed in accordance with the TWP (BSC 2003 [163602]). This analysis develops values of parameters associated with many features, events, and processes (FEPs) applicable to the reference biosphere (DTN: M00303SEPFEPS2.000 [162452]), which are addressed in the biosphere model (BSC 2003 [160699]). The treatment of these FEPs is described in BSC (2003 [160699], Section 6.2). Parameter values
Environmental Transport Input Parameters for the Biosphere Model
M. A. Wasiolek
2003-06-27
This analysis report is one of the technical reports documenting the Environmental Radiation Model for Yucca Mountain Nevada (ERMYN), a biosphere model supporting the total system performance assessment (TSPA) for the geologic repository at Yucca Mountain. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows relationships among the reports developed for biosphere modeling and biosphere abstraction products for the TSPA, as identified in the ''Technical Work Plan: for Biosphere Modeling and Expert Support'' (TWP) (BSC 2003 [163602]). Some documents in Figure 1-1 may be under development and not available when this report is issued. This figure provides an understanding of how this report contributes to biosphere modeling in support of the license application (LA), but access to the listed documents is not required to understand the contents of this report. This report is one of the reports that develops input parameter values for the biosphere model. The ''Biosphere Model Report'' (BSC 2003 [160699]) describes the conceptual model, the mathematical model, and the input parameters. The purpose of this analysis is to develop biosphere model parameter values related to radionuclide transport and accumulation in the environment. These parameters support calculations of radionuclide concentrations in the environmental media (e.g., soil, crops, animal products, and air) resulting from a given radionuclide concentration at the source of contamination (i.e., either in groundwater or volcanic ash). The analysis was performed in accordance with the TWP (BSC 2003 [163602]). This analysis develops values of parameters associated with many features, events, and processes (FEPs) applicable to the reference biosphere (DTN: M00303SEPFEPS2.000 [162452]), which are addressed in the biosphere model (BSC 2003 [160699]). The treatment of these FEPs is described in BSC (2003 [160699
Eck, Simon; Wörz, Stefan; Müller-Ott, Katharina; Hahn, Matthias; Biesdorf, Andreas; Schotta, Gunnar; Rippe, Karsten; Rohr, Karl
2016-08-01
The genome is partitioned into regions of euchromatin and heterochromatin. The organization of heterochromatin is important for the regulation of cellular processes such as chromosome segregation and gene silencing, and their misregulation is linked to cancer and other diseases. We present a model-based approach for automatic 3D segmentation and 3D shape analysis of heterochromatin foci from 3D confocal light microscopy images. Our approach employs a novel 3D intensity model based on spherical harmonics, which analytically describes the shape and intensities of the foci. The model parameters are determined by fitting the model to the image intensities using least-squares minimization. To characterize the 3D shape of the foci, we exploit the computed spherical harmonics coefficients and determine a shape descriptor. We applied our approach to 3D synthetic image data as well as real 3D static and real 3D time-lapse microscopy images, and compared the performance with that of previous approaches. It turned out that our approach yields accurate 3D segmentation results and performs better than previous approaches. We also show that our approach can be used for quantifying 3D shape differences of heterochromatin foci. Copyright © 2016 Elsevier B.V. All rights reserved.
Reflector modelization for neutronic diffusion and parameters identification
Argaud, J.P.
1993-04-01
Physical parameters of neutronic diffusion equations can be adjusted to decrease calculations-measurements errors. The reflector being always difficult to modelize, we choose to elaborate a new reflector model and to use the parameters of this model as adjustment coefficients in the identification procedure. Using theoretical results, and also the physical behaviour of neutronic flux solutions, the reflector model consists then in its replacement by boundary conditions for the diffusion equations on the core only. This theoretical result of non-local operator relations leads then to some discrete approximations by taking into account the multiscaled behaviour, on the core-reflector interface, of neutronic diffusion solutions. The resulting model of this approach is then compared with previous reflector modelizations, and first results indicate that this new model gives the same representation of reflector for the core than previous. (author). 12 refs
Slezak, Thomas Joseph; Radebaugh, Jani; Christiansen, Eric
2017-10-01
The shapes of craterform morphology on planetary surfaces provides rich information about their origins and evolution. While morphologic information provides rich visual clues to geologic processes and properties, the ability to quantitatively communicate this information is less easily accomplished. This study examines the morphology of craterforms using the quantitative outline-based shape methods of geometric morphometrics, commonly used in biology and paleontology. We examine and compare landforms on planetary surfaces using shape, a property of morphology that is invariant to translation, rotation, and size. We quantify the shapes of paterae on Io, martian calderas, terrestrial basaltic shield calderas, terrestrial ash-flow calderas, and lunar impact craters using elliptic Fourier analysis (EFA) and the Zahn and Roskies (Z-R) shape function, or tangent angle approach to produce multivariate shape descriptors. These shape descriptors are subjected to multivariate statistical analysis including canonical variate analysis (CVA), a multiple-comparison variant of discriminant analysis, to investigate the link between craterform shape and classification. Paterae on Io are most similar in shape to terrestrial ash-flow calderas and the shapes of terrestrial basaltic shield volcanoes are most similar to martian calderas. The shapes of lunar impact craters, including simple, transitional, and complex morphology, are classified with a 100% rate of success in all models. Multiple CVA models effectively predict and classify different craterforms using shape-based identification and demonstrate significant potential for use in the analysis of planetary surfaces.
Regionalising Parameters of a Conceptual Rainfall-Runoff Model for ...
IHACRES, a lumped conceptual rainfall-runoff model, was calibrated to six catchments ranging in size from 49km2 to 600 km2 within the upper Tana River basin to obtain a set of model parameters that characterise the hydrological behaviour within the region. Physical catchment attributes indexing topography, soil and ...
Constraint on Parameters of Inverse Compton Scattering Model for ...
B2319+60, two parameters of inverse Compton scattering model, the initial Lorentz factor and the factor of energy loss of relativistic particles are constrained. Key words. Pulsar—inverse Compton scattering—emission mechanism. 1. Introduction. Among various kinds of models for pulsar radio emission, the inverse ...
Geometry parameters for musculoskeletal modelling of the shoulder system
Van der Helm, F C; Veeger, DirkJan (H. E. J.); Pronk, G M; Van der Woude, L H; Rozendal, R H
A dynamical finite-element model of the shoulder mechanism consisting of thorax, clavicula, scapula and humerus is outlined. The parameters needed for the model are obtained in a cadaver experiment consisting of both shoulders of seven cadavers. In this paper, in particular, the derivation of
Rain storm models and the relationship between their parameters
Stol, P.T.
1977-01-01
Rainfall interstation correlation functions can be obtained with the aid of analytic rainfall or storm models. Since alternative storm models have different mathematical formulas, comparison should be based on equallity of parameters like storm diameter, mean rainfall amount, storm maximum or total
Lumped-parameters equivalent circuit for condenser microphones modeling.
Esteves, Josué; Rufer, Libor; Ekeom, Didace; Basrour, Skandar
2017-10-01
This work presents a lumped parameters equivalent model of condenser microphone based on analogies between acoustic, mechanical, fluidic, and electrical domains. Parameters of the model were determined mainly through analytical relations and/or finite element method (FEM) simulations. Special attention was paid to the air gap modeling and to the use of proper boundary condition. Corresponding lumped-parameters were obtained as results of FEM simulations. Because of its simplicity, the model allows a fast simulation and is readily usable for microphone design. This work shows the validation of the equivalent circuit on three real cases of capacitive microphones, including both traditional and Micro-Electro-Mechanical Systems structures. In all cases, it has been demonstrated that the sensitivity and other related data obtained from the equivalent circuit are in very good agreement with available measurement data.
Non-linear scaling of a musculoskeletal model of the lower limb using statistical shape models.
Nolte, Daniel; Tsang, Chui Kit; Zhang, Kai Yu; Ding, Ziyun; Kedgley, Angela E; Bull, Anthony M J
2016-10-03
Accurate muscle geometry for musculoskeletal models is important to enable accurate subject-specific simulations. Commonly, linear scaling is used to obtain individualised muscle geometry. More advanced methods include non-linear scaling using segmented bone surfaces and manual or semi-automatic digitisation of muscle paths from medical images. In this study, a new scaling method combining non-linear scaling with reconstructions of bone surfaces using statistical shape modelling is presented. Statistical Shape Models (SSMs) of femur and tibia/fibula were used to reconstruct bone surfaces of nine subjects. Reference models were created by morphing manually digitised muscle paths to mean shapes of the SSMs using non-linear transformations and inter-subject variability was calculated. Subject-specific models of muscle attachment and via points were created from three reference models. The accuracy was evaluated by calculating the differences between the scaled and manually digitised models. The points defining the muscle paths showed large inter-subject variability at the thigh and shank - up to 26mm; this was found to limit the accuracy of all studied scaling methods. Errors for the subject-specific muscle point reconstructions of the thigh could be decreased by 9% to 20% by using the non-linear scaling compared to a typical linear scaling method. We conclude that the proposed non-linear scaling method is more accurate than linear scaling methods. Thus, when combined with the ability to reconstruct bone surfaces from incomplete or scattered geometry data using statistical shape models our proposed method is an alternative to linear scaling methods. Copyright © 2016 The Author. Published by Elsevier Ltd.. All rights reserved.
A software for parameter estimation in dynamic models
M. Yuceer
2008-12-01
Full Text Available A common problem in dynamic systems is to determine parameters in an equation used to represent experimental data. The goal is to determine the values of model parameters that provide the best fit to measured data, generally based on some type of least squares or maximum likelihood criterion. In the most general case, this requires the solution of a nonlinear and frequently non-convex optimization problem. Some of the available software lack in generality, while others do not provide ease of use. A user-interactive parameter estimation software was needed for identifying kinetic parameters. In this work we developed an integration based optimization approach to provide a solution to such problems. For easy implementation of the technique, a parameter estimation software (PARES has been developed in MATLAB environment. When tested with extensive example problems from literature, the suggested approach is proven to provide good agreement between predicted and observed data within relatively less computing time and iterations.
Determination of appropriate models and parameters for premixing calculations
Park, Ik-Kyu; Kim, Jong-Hwan; Min, Beong-Tae; Hong, Seong-Wan
2008-03-15
The purpose of the present work is to use experiments that have been performed at Forschungszentrum Karlsruhe during about the last ten years for determining the most appropriate models and parameters for premixing calculations. The results of a QUEOS experiment are used to fix the parameters concerning heat transfer. The QUEOS experiments are especially suited for this purpose as they have been performed with small hot solid spheres. Therefore the area of heat exchange is known. With the heat transfer parameters fixed in this way, a PREMIX experiment is recalculated. These experiments have been performed with molten alumina (Al{sub 2}O{sub 3}) as a simulant of corium. Its initial temperature is 2600 K. With these experiments the models and parameters for jet and drop break-up are tested.
Parameter identification in a nonlinear nuclear reactor model using quasilinearization
Barreto, J.M.; Martins Neto, A.F.; Tanomaru, N.
1980-09-01
Parameter identification in a nonlinear, lumped parameter, nuclear reactor model is carried out using discrete output power measurements during the transient caused by an external reactivity change. In order to minimize the difference between the model and the reactor power responses, the parameter promt neutron generation time and a parameter in fuel temperature reactivity coefficient equation are adjusted using quasilinearization. The influences of the external reactivity disturbance, the number and frequency of measurements and the measurement noise level on the method accuracy and rate of convergence are analysed through simulation. Procedures for the design of the identification experiments are suggested. The method proved to be very effective for low level noise measurements. (Author) [pt
Determination of appropriate models and parameters for premixing calculations
Park, Ik-Kyu; Kim, Jong-Hwan; Min, Beong-Tae; Hong, Seong-Wan
2008-03-01
The purpose of the present work is to use experiments that have been performed at Forschungszentrum Karlsruhe during about the last ten years for determining the most appropriate models and parameters for premixing calculations. The results of a QUEOS experiment are used to fix the parameters concerning heat transfer. The QUEOS experiments are especially suited for this purpose as they have been performed with small hot solid spheres. Therefore the area of heat exchange is known. With the heat transfer parameters fixed in this way, a PREMIX experiment is recalculated. These experiments have been performed with molten alumina (Al 2 O 3 ) as a simulant of corium. Its initial temperature is 2600 K. With these experiments the models and parameters for jet and drop break-up are tested
Condition Parameter Modeling for Anomaly Detection in Wind Turbines
Yonglong Yan
2014-05-01
Full Text Available Data collected from the supervisory control and data acquisition (SCADA system, used widely in wind farms to obtain operational and condition information about wind turbines (WTs, is of important significance for anomaly detection in wind turbines. The paper presents a novel model for wind turbine anomaly detection mainly based on SCADA data and a back-propagation neural network (BPNN for automatic selection of the condition parameters. The SCADA data sets are determined through analysis of the cumulative probability distribution of wind speed and the relationship between output power and wind speed. The automatic BPNN-based parameter selection is for reduction of redundant parameters for anomaly detection in wind turbines. Through investigation of cases of WT faults, the validity of the automatic parameter selection-based model for WT anomaly detection is verified.
Ground level enhancement (GLE) energy spectrum parameters model
Qin, G.; Wu, S.
2017-12-01
We study the ground level enhancement (GLE) events in solar cycle 23 with the four energy spectra parameters, the normalization parameter C, low-energy power-law slope γ 1, high-energy power-law slope γ 2, and break energy E0, obtained by Mewaldt et al. 2012 who fit the observations to the double power-law equation. we divide the GLEs into two groups, one with strong acceleration by interplanetary (IP) shocks and another one without strong acceleration according to the condition of solar eruptions. We next fit the four parameters with solar event conditions to get models of the parameters for the two groups of GLEs separately. So that we would establish a model of energy spectrum for GLEs for the future space weather prediction.
Development of a Numerical Model for High-Temperature Shape Memory Alloys
DeCastro, Jonathan A.; Melcher, Kevin J.; Noebe, Ronald D.; Gaydosh, Darrell J.
2006-01-01
A thermomechanical hysteresis model for a high-temperature shape memory alloy (HTSMA) actuator material is presented. The model is capable of predicting strain output of a tensile-loaded HTSMA when excited by arbitrary temperature-stress inputs for the purpose of actuator and controls design. Common quasi-static generalized Preisach hysteresis models available in the literature require large sets of experimental data for model identification at a particular operating point, and substantially more data for multiple operating points. The novel algorithm introduced here proposes an alternate approach to Preisach methods that is better suited for research-stage alloys, such as recently-developed HTSMAs, for which a complete database is not yet available. A detailed description of the minor loop hysteresis model is presented in this paper, as well as a methodology for determination of model parameters. The model is then qualitatively evaluated with respect to well-established Preisach properties and against a set of low-temperature cycled loading data using a modified form of the one-dimensional Brinson constitutive equation. The computationally efficient algorithm demonstrates adherence to Preisach properties and excellent agreement to the validation data set.
Soil-related Input Parameters for the Biosphere Model
A. J. Smith
2003-01-01
This analysis is one of the technical reports containing documentation of the Environmental Radiation Model for Yucca Mountain Nevada (ERMYN), a biosphere model supporting the Total System Performance Assessment (TSPA) for the geologic repository at Yucca Mountain. The biosphere model is one of a series of process models supporting the Total System Performance Assessment (TSPA) for the Yucca Mountain repository. A graphical representation of the documentation hierarchy for the ERMYN biosphere model is presented in Figure 1-1. This figure shows the interrelationships among the products (i.e., analysis and model reports) developed for biosphere modeling, and the plan for development of the biosphere abstraction products for TSPA, as identified in the ''Technical Work Plan: for Biosphere Modeling and Expert Support'' (BSC 2003 [163602]). It should be noted that some documents identified in Figure 1-1 may be under development at the time this report is issued and therefore not available. This figure is included to provide an understanding of how this analysis report contributes to biosphere modeling in support of the license application, and is not intended to imply that access to the listed documents is required to understand the contents of this report. This report, ''Soil Related Input Parameters for the Biosphere Model'', is one of the five analysis reports that develop input parameters for use in the ERMYN model. This report is the source documentation for the six biosphere parameters identified in Table 1-1. ''The Biosphere Model Report'' (BSC 2003 [160699]) describes in detail the conceptual model as well as the mathematical model and its input parameters. The purpose of this analysis was to develop the biosphere model parameters needed to evaluate doses from pathways associated with the accumulation and depletion of radionuclides in the soil. These parameters support the calculation of radionuclide concentrations in soil from on-going irrigation and ash
Froehner, F.H.
1977-11-01
A least-squares shape analysis program is described which is used at the Karlsruhe Nuclear Research Center for the extraction of resonance parameters from high-resolution capture data. The FORTRAN program was written for light to medium-weight or near-magic target nuclei whose cross sections are characterized on one hand by broad s-wave levels with negligible Doppler broadening but pronounced multi-level interference, on the other hand by narrow p-, d- ... wave resonances with negligible multi-level interference but pronounced Doppler broadening. Accordingly the Reich-Moore multi-level formalism without Doppler broadening is used for s-wave levels, and a single-level description with Doppler braodening for p-, d- ... wave levels. Calculated capture yields are resolution broadened. Multiple-collision events are simulated by Monte Carlo techniques. Up to five different time-of-flight capture data sets can be fitted simultaneously for samples containing up to ten isotopes. Input and output examples are given and a FORTRAN list is appended. (orig.)
4D Shape-Preserving Modelling of Bone Growth
Andresen, Per Rønsholt; Nielsen, Mads; Kreiborg, Sven
1998-01-01
From a set of temporally separated scannings of the same anatomical structure we wish to identify and analyze the growth in terms of a metamorphosis. That is, we study the tempral change of shape which may prowide an understanding of the biological processes which govern the growth process. We...
STEREOLOGICAL ANALYSIS OF SHAPE
Asger Hobolth
2011-05-01
Full Text Available This paper concerns the problem of making stereological inference about the shape variability in a population of spatial particles. Under rotational invariance the shape variability can be estimated from central planar sections through the particles. A simple, but flexible, parametric model for rotation invariant spatial particles is suggested. It is shown how the parameters of the model can be estimated from observations on central sections. The corresponding model for planar particles is also discussed in some detail.
Parameters Optimization and Application to Glutamate Fermentation Model Using SVM
Zhang, Xiangsheng; Pan, Feng
2015-01-01
Aimed at the parameters optimization in support vector machine (SVM) for glutamate fermentation modelling, a new method is developed. It optimizes the SVM parameters via an improved particle swarm optimization (IPSO) algorithm which has better global searching ability. The algorithm includes detecting and handling the local convergence and exhibits strong ability to avoid being trapped in local minima. The material step of the method was shown. Simulation experiments demonstrate the effective...
Parameters Optimization and Application to Glutamate Fermentation Model Using SVM
Xiangsheng Zhang
2015-01-01
Full Text Available Aimed at the parameters optimization in support vector machine (SVM for glutamate fermentation modelling, a new method is developed. It optimizes the SVM parameters via an improved particle swarm optimization (IPSO algorithm which has better global searching ability. The algorithm includes detecting and handling the local convergence and exhibits strong ability to avoid being trapped in local minima. The material step of the method was shown. Simulation experiments demonstrate the effectiveness of the proposed algorithm.
A Bayesian framework for parameter estimation in dynamical models.
Flávio Codeço Coelho
Full Text Available Mathematical models in biology are powerful tools for the study and exploration of complex dynamics. Nevertheless, bringing theoretical results to an agreement with experimental observations involves acknowledging a great deal of uncertainty intrinsic to our theoretical representation of a real system. Proper handling of such uncertainties is key to the successful usage of models to predict experimental or field observations. This problem has been addressed over the years by many tools for model calibration and parameter estimation. In this article we present a general framework for uncertainty analysis and parameter estimation that is designed to handle uncertainties associated with the modeling of dynamic biological systems while remaining agnostic as to the type of model used. We apply the framework to fit an SIR-like influenza transmission model to 7 years of incidence data in three European countries: Belgium, the Netherlands and Portugal.
A lumped parameter, low dimension model of heat exchanger
Kanoh, Hideaki; Furushoo, Junji; Masubuchi, Masami
1980-01-01
This paper reports on the results of investigation of the distributed parameter model, the difference model, and the model of the method of weighted residuals for heat exchangers. By the method of weighted residuals (MWR), the opposite flow heat exchanger system is approximated by low dimension, lumped parameter model. By assuming constant specific heat, constant density, the same form of tube cross-section, the same form of the surface of heat exchange, uniform flow velocity, the linear relation of heat transfer to flow velocity, liquid heat carrier, and the thermal insulation of liquid from outside, fundamental equations are obtained. The experimental apparatus was made of acrylic resin. The response of the temperature at the exit of first liquid to the variation of the flow rate of second liquid was measured and compared with the models. The MWR model shows good approximation for the low frequency region, and as the number of division increases, good approximation spreads to higher frequency region. (Kato, T.)
Gowtham, K. N.; Vasudevan, M.; Maduraimuthu, V.; Jayakumar, T.
2011-04-01
Modified 9Cr-1Mo ferritic steel is used as a structural material for steam generator components of power plants. Generally, tungsten inert gas (TIG) welding is preferred for welding of these steels in which the depth of penetration achievable during autogenous welding is limited. Therefore, activated flux TIG (A-TIG) welding, a novel welding technique, has been developed in-house to increase the depth of penetration. In modified 9Cr-1Mo steel joints produced by the A-TIG welding process, weld bead width, depth of penetration, and heat-affected zone (HAZ) width play an important role in determining the mechanical properties as well as the performance of the weld joints during service. To obtain the desired weld bead geometry and HAZ width, it becomes important to set the welding process parameters. In this work, adaptative neuro fuzzy inference system is used to develop independent models correlating the welding process parameters like current, voltage, and torch speed with weld bead shape parameters like depth of penetration, bead width, and HAZ width. Then a genetic algorithm is employed to determine the optimum A-TIG welding process parameters to obtain the desired weld bead shape parameters and HAZ width.
Reservoir theory, groundwater transit time distributions, and lumped parameter models
Etcheverry, D.; Perrochet, P.
1999-01-01
The relation between groundwater residence times and transit times is given by the reservoir theory. It allows to calculate theoretical transit time distributions in a deterministic way, analytically, or on numerical models. Two analytical solutions validates the piston flow and the exponential model for simple conceptual flow systems. A numerical solution of a hypothetical regional groundwater flow shows that lumped parameter models could be applied in some cases to large-scale, heterogeneous aquifers. (author)
SPOTting model parameters using a ready-made Python package
Houska, Tobias; Kraft, Philipp; Breuer, Lutz
2015-04-01
The selection and parameterization of reliable process descriptions in ecological modelling is driven by several uncertainties. The procedure is highly dependent on various criteria, like the used algorithm, the likelihood function selected and the definition of the prior parameter distributions. A wide variety of tools have been developed in the past decades to optimize parameters. Some of the tools are closed source. Due to this, the choice for a specific parameter estimation method is sometimes more dependent on its availability than the performance. A toolbox with a large set of methods can support users in deciding about the most suitable method. Further, it enables to test and compare different methods. We developed the SPOT (Statistical Parameter Optimization Tool), an open source python package containing a comprehensive set of modules, to analyze and optimize parameters of (environmental) models. SPOT comes along with a selected set of algorithms for parameter optimization and uncertainty analyses (Monte Carlo, MC; Latin Hypercube Sampling, LHS; Maximum Likelihood, MLE; Markov Chain Monte Carlo, MCMC; Scuffled Complex Evolution, SCE-UA; Differential Evolution Markov Chain, DE-MCZ), together with several likelihood functions (Bias, (log-) Nash-Sutcliff model efficiency, Correlation Coefficient, Coefficient of Determination, Covariance, (Decomposed-, Relative-, Root-) Mean Squared Error, Mean Absolute Error, Agreement Index) and prior distributions (Binomial, Chi-Square, Dirichlet, Exponential, Laplace, (log-, multivariate-) Normal, Pareto, Poisson, Cauchy, Uniform, Weibull) to sample from. The model-independent structure makes it suitable to analyze a wide range of applications. We apply all algorithms of the SPOT package in three different case studies. Firstly, we investigate the response of the Rosenbrock function, where the MLE algorithm shows its strengths. Secondly, we study the Griewank function, which has a challenging response surface for
Markov Random Field Restoration of Point Correspondences for Active Shape Modelling
Hilger, Klaus Baggesen; Paulsen, Rasmus Reinhold; Larsen, Rasmus
2004-01-01
In this paper it is described how to build a statistical shape model using a training set with a sparse of landmarks. A well defined model mesh is selected and fitted to all shapes in the training set using thin plate spline warping. This is followed by a projection of the points of the warped...
Modelling of intermittent microwave convective drying: parameter sensitivity
Zhang Zhijun
2017-06-01
Full Text Available The reliability of the predictions of a mathematical model is a prerequisite to its utilization. A multiphase porous media model of intermittent microwave convective drying is developed based on the literature. The model considers the liquid water, gas and solid matrix inside of food. The model is simulated by COMSOL software. Its sensitivity parameter is analysed by changing the parameter values by ±20%, with the exception of several parameters. The sensitivity analysis of the process of the microwave power level shows that each parameter: ambient temperature, effective gas diffusivity, and evaporation rate constant, has significant effects on the process. However, the surface mass, heat transfer coefficient, relative and intrinsic permeability of the gas, and capillary diffusivity of water do not have a considerable effect. The evaporation rate constant has minimal parameter sensitivity with a ±20% value change, until it is changed 10-fold. In all results, the temperature and vapour pressure curves show the same trends as the moisture content curve. However, the water saturation at the medium surface and in the centre show different results. Vapour transfer is the major mass transfer phenomenon that affects the drying process.
Synchronous Generator Model Parameter Estimation Based on Noisy Dynamic Waveforms
Berhausen, Sebastian; Paszek, Stefan
2016-01-01
In recent years, there have occurred system failures in many power systems all over the world. They have resulted in a lack of power supply to a large number of recipients. To minimize the risk of occurrence of power failures, it is necessary to perform multivariate investigations, including simulations, of power system operating conditions. To conduct reliable simulations, the current base of parameters of the models of generating units, containing the models of synchronous generators, is necessary. In the paper, there is presented a method for parameter estimation of a synchronous generator nonlinear model based on the analysis of selected transient waveforms caused by introducing a disturbance (in the form of a pseudorandom signal) in the generator voltage regulation channel. The parameter estimation was performed by minimizing the objective function defined as a mean square error for deviations between the measurement waveforms and the waveforms calculated based on the generator mathematical model. A hybrid algorithm was used for the minimization of the objective function. In the paper, there is described a filter system used for filtering the noisy measurement waveforms. The calculation results of the model of a 44 kW synchronous generator installed on a laboratory stand of the Institute of Electrical Engineering and Computer Science of the Silesian University of Technology are also given. The presented estimation method can be successfully applied to parameter estimation of different models of high-power synchronous generators operating in a power system.
On the role of modeling parameters in IMRT plan optimization
Krause, Michael; Scherrer, Alexander; Thieke, Christian
2008-01-01
The formulation of optimization problems in intensity-modulated radiotherapy (IMRT) planning comprises the choice of various values such as function-specific parameters or constraint bounds. In current inverse planning programs that yield a single treatment plan for each optimization, it is often unclear how strongly these modeling parameters affect the resulting plan. This work investigates the mathematical concepts of elasticity and sensitivity to deal with this problem. An artificial planning case with a horse-shoe formed target with different opening angles surrounding a circular risk structure is studied. As evaluation functions the generalized equivalent uniform dose (EUD) and the average underdosage below and average overdosage beyond certain dose thresholds are used. A single IMRT plan is calculated for an exemplary parameter configuration. The elasticity and sensitivity of each parameter are then calculated without re-optimization, and the results are numerically verified. The results show the following. (1) elasticity can quantify the influence of a modeling parameter on the optimization result in terms of how strongly the objective function value varies under modifications of the parameter value. It also can describe how strongly the geometry of the involved planning structures affects the optimization result. (2) Based on the current parameter settings and corresponding treatment plan, sensitivity analysis can predict the optimization result for modified parameter values without re-optimization, and it can estimate the value intervals in which such predictions are valid. In conclusion, elasticity and sensitivity can provide helpful tools in inverse IMRT planning to identify the most critical parameters of an individual planning problem and to modify their values in an appropriate way
A compact cyclic plasticity model with parameter evolution
Krenk, Steen; Tidemann, L.
2017-01-01
The paper presents a compact model for cyclic plasticity based on energy in terms of external and internal variables, and plastic yielding described by kinematic hardening and a flow potential with an additive term controlling the nonlinear cyclic hardening. The model is basically described by five...... parameters: external and internal stiffness, a yield stress and a limiting ultimate stress, and finally a parameter controlling the gradual development of plastic deformation. Calibration against numerous experimental results indicates that typically larger plastic strains develop than predicted...
Cellular Shape Memory Alloy Structures: Experiments & Modeling (Part 1)
2012-08-01
High -‐ temperature SMAs 24 Braze Joint between two wrought pieces of a Ni24.5Pd25Ti50.5 HTSMA (HTSMA from...process can be used to join other metal alloys and high -‐ temperature SMAs 25 Cellular Shape Memory...20 30 40 50 60 910 3 4 8 5 2 T (°C) Shape memory & superelasticity 1 0 e (%) (GPa) 6 7 A NiTi wire
A sharp interface evolutionary model for shape memory alloys
Knüpfer, H.; Kružík, Martin
2016-01-01
Roč. 96, č. 11 (2016), s. 1347-1355 ISSN 0044-2267 R&D Projects: GA ČR GA14-15264S Institutional support: RVO:67985556 Keywords : Polyconvexity * shape memory materials * rate-independent problems Subject RIV: BA - General Mathematics Impact factor: 1.332, year: 2016 http://library.utia.cas.cz/separaty/2016/MTR/kruzik-0465809.pdf
Magnetic shape-memory alloys: thermomechanical modelling and analysis
Roubíček, Tomáš; Stefanelli, U.
2014-01-01
Roč. 26, č. 6 (2014), s. 783-810 ISSN 0935-1175 R&D Projects: GA ČR GAP201/10/0357 Institutional support: RVO:61388998 Keywords : magnetic shape- memory alloys * martensitic phase transformation * ferro/paramagnetic phase transformation Subject RIV: BA - General Mathematics Impact factor: 1.779, year: 2014 http://link.springer.com/article/10.1007/s00161-014-0339-8#
Climate change decision-making: Model & parameter uncertainties explored
Dowlatabadi, H.; Kandlikar, M.; Linville, C.
1995-12-31
A critical aspect of climate change decision-making is uncertainties in current understanding of the socioeconomic, climatic and biogeochemical processes involved. Decision-making processes are much better informed if these uncertainties are characterized and their implications understood. Quantitative analysis of these uncertainties serve to inform decision makers about the likely outcome of policy initiatives, and help set priorities for research so that outcome ambiguities faced by the decision-makers are reduced. A family of integrated assessment models of climate change have been developed at Carnegie Mellon. These models are distinguished from other integrated assessment efforts in that they were designed from the outset to characterize and propagate parameter, model, value, and decision-rule uncertainties. The most recent of these models is ICAM 2.1. This model includes representation of the processes of demographics, economic activity, emissions, atmospheric chemistry, climate and sea level change and impacts from these changes and policies for emissions mitigation, and adaptation to change. The model has over 800 objects of which about one half are used to represent uncertainty. In this paper we show, that when considering parameter uncertainties, the relative contribution of climatic uncertainties are most important, followed by uncertainties in damage calculations, economic uncertainties and direct aerosol forcing uncertainties. When considering model structure uncertainties we find that the choice of policy is often dominated by model structure choice, rather than parameter uncertainties.
Wind turbine model and loop shaping controller design
Gilev, Bogdan
2017-12-01
A model of a wind turbine is evaluated, consisting of: wind speed model, mechanical and electrical model of generator and tower oscillation model. Model of the whole system is linearized around of a nominal point. By using the linear model with uncertainties is synthesized a uncertain model. By using the uncertain model is developed a H∞ controller, which provide mode of stabilizing the rotor frequency and damping the tower oscillations. Finally is simulated work of nonlinear system and H∞ controller.
Miaolei Zhou
Full Text Available As a new type of smart material, magnetic shape memory alloy has the advantages of a fast response frequency and outstanding strain capability in the field of microdrive and microposition actuators. The hysteresis nonlinearity in magnetic shape memory alloy actuators, however, limits system performance and further application. Here we propose a feedforward-feedback hybrid control method to improve control precision and mitigate the effects of the hysteresis nonlinearity of magnetic shape memory alloy actuators. First, hysteresis nonlinearity compensation for the magnetic shape memory alloy actuator is implemented by establishing a feedforward controller which is an inverse hysteresis model based on Krasnosel'skii-Pokrovskii operator. Secondly, the paper employs the classical Proportion Integration Differentiation feedback control with feedforward control to comprise the hybrid control system, and for further enhancing the adaptive performance of the system and improving the control accuracy, the Radial Basis Function neural network self-tuning Proportion Integration Differentiation feedback control replaces the classical Proportion Integration Differentiation feedback control. Utilizing self-learning ability of the Radial Basis Function neural network obtains Jacobian information of magnetic shape memory alloy actuator for the on-line adjustment of parameters in Proportion Integration Differentiation controller. Finally, simulation results show that the hybrid control method proposed in this paper can greatly improve the control precision of magnetic shape memory alloy actuator and the maximum tracking error is reduced from 1.1% in the open-loop system to 0.43% in the hybrid control system.
Zhou, Miaolei; Zhang, Qi; Wang, Jingyuan
2014-01-01
As a new type of smart material, magnetic shape memory alloy has the advantages of a fast response frequency and outstanding strain capability in the field of microdrive and microposition actuators. The hysteresis nonlinearity in magnetic shape memory alloy actuators, however, limits system performance and further application. Here we propose a feedforward-feedback hybrid control method to improve control precision and mitigate the effects of the hysteresis nonlinearity of magnetic shape memory alloy actuators. First, hysteresis nonlinearity compensation for the magnetic shape memory alloy actuator is implemented by establishing a feedforward controller which is an inverse hysteresis model based on Krasnosel'skii-Pokrovskii operator. Secondly, the paper employs the classical Proportion Integration Differentiation feedback control with feedforward control to comprise the hybrid control system, and for further enhancing the adaptive performance of the system and improving the control accuracy, the Radial Basis Function neural network self-tuning Proportion Integration Differentiation feedback control replaces the classical Proportion Integration Differentiation feedback control. Utilizing self-learning ability of the Radial Basis Function neural network obtains Jacobian information of magnetic shape memory alloy actuator for the on-line adjustment of parameters in Proportion Integration Differentiation controller. Finally, simulation results show that the hybrid control method proposed in this paper can greatly improve the control precision of magnetic shape memory alloy actuator and the maximum tracking error is reduced from 1.1% in the open-loop system to 0.43% in the hybrid control system.
Parameter estimation in nonlinear models for pesticide degradation
Richter, O.; Pestemer, W.; Bunte, D.; Diekkrueger, B.
1991-01-01
A wide class of environmental transfer models is formulated as ordinary or partial differential equations. With the availability of fast computers, the numerical solution of large systems became feasible. The main difficulty in performing a realistic and convincing simulation of the fate of a substance in the biosphere is not the implementation of numerical techniques but rather the incomplete data basis for parameter estimation. Parameter estimation is a synonym for statistical and numerical procedures to derive reasonable numerical values for model parameters from data. The classical method is the familiar linear regression technique which dates back to the 18th century. Because it is easy to handle, linear regression has long been established as a convenient tool for analysing relationships. However, the wide use of linear regression has led to an overemphasis of linear relationships. In nature, most relationships are nonlinear and linearization often gives a poor approximation of reality. Furthermore, pure regression models are not capable to map the dynamics of a process. Therefore, realistic models involve the evolution in time (and space). This leads in a natural way to the formulation of differential equations. To establish the link between data and dynamical models, numerical advanced parameter identification methods have been developed in recent years. This paper demonstrates the application of these techniques to estimation problems in the field of pesticide dynamics. (7 refs., 5 figs., 2 tabs.)
Global parameter estimation for thermodynamic models of transcriptional regulation.
Suleimenov, Yerzhan; Ay, Ahmet; Samee, Md Abul Hassan; Dresch, Jacqueline M; Sinha, Saurabh; Arnosti, David N
2013-07-15
Deciphering the mechanisms involved in gene regulation holds the key to understanding the control of central biological processes, including human disease, population variation, and the evolution of morphological innovations. New experimental techniques including whole genome sequencing and transcriptome analysis have enabled comprehensive modeling approaches to study gene regulation. In many cases, it is useful to be able to assign biological significance to the inferred model parameters, but such interpretation should take into account features that affect these parameters, including model construction and sensitivity, the type of fitness calculation, and the effectiveness of parameter estimation. This last point is often neglected, as estimation methods are often selected for historical reasons or for computational ease. Here, we compare the performance of two parameter estimation techniques broadly representative of local and global approaches, namely, a quasi-Newton/Nelder-Mead simplex (QN/NMS) method and a covariance matrix adaptation-evolutionary strategy (CMA-ES) method. The estimation methods were applied to a set of thermodynamic models of gene transcription applied to regulatory elements active in the Drosophila embryo. Measuring overall fit, the global CMA-ES method performed significantly better than the local QN/NMS method on high quality data sets, but this difference was negligible on lower quality data sets with increased noise or on data sets simplified by stringent thresholding. Our results suggest that the choice of parameter estimation technique for evaluation of gene expression models depends both on quality of data, the nature of the models [again, remains to be established] and the aims of the modeling effort. Copyright © 2013 Elsevier Inc. All rights reserved.
3D active shape and appearance models in cardiac image analysis
Lelieveldt, B.P.F.; Frangi, A.F.; Mitchell, S.C.; Assen, van H.C.; Ordás, S.; Reiber, J.H.C.; Sonka, M.; Paragios, N.; Chen, Y.; Faugeras, O.
2006-01-01
This chapter introduces statistical shape- and appearance models and their biomedical applications. Three- and four-dimensional extension of these models are the main focus. Approaches leading to automated landmark definition are introduced and discussed. The applicability is underlined by
Inhalation Exposure Input Parameters for the Biosphere Model
M. Wasiolek
2006-06-05
This analysis is one of the technical reports that support the Environmental Radiation Model for Yucca Mountain, Nevada (ERMYN), referred to in this report as the biosphere model. ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) describes in detail the conceptual model as well as the mathematical model and its input parameters. This report documents development of input parameters for the biosphere model that are related to atmospheric mass loading and supports the use of the model to develop biosphere dose conversion factors (BDCFs). The biosphere model is one of a series of process models supporting the total system performance assessment (TSPA) for a Yucca Mountain repository. ''Inhalation Exposure Input Parameters for the Biosphere Model'' is one of five reports that develop input parameters for the biosphere model. A graphical representation of the documentation hierarchy for the biosphere model is presented in Figure 1-1 (based on BSC 2006 [DIRS 176938]). This figure shows the interrelationships among the products (i.e., analysis and model reports) developed for biosphere modeling and how this analysis report contributes to biosphere modeling. This analysis report defines and justifies values of atmospheric mass loading for the biosphere model. Mass loading is the total mass concentration of resuspended particles (e.g., dust, ash) in a volume of air. Mass loading values are used in the air submodel of the biosphere model to calculate concentrations of radionuclides in air inhaled by a receptor and concentrations in air surrounding crops. Concentrations in air to which the receptor is exposed are then used in the inhalation submodel to calculate the dose contribution to the receptor from inhalation of contaminated airborne particles. Concentrations in air surrounding plants are used in the plant submodel to calculate the concentrations of radionuclides in foodstuffs contributed from uptake by foliar interception. This
Inhalation Exposure Input Parameters for the Biosphere Model
M. Wasiolek
2006-01-01
This analysis is one of the technical reports that support the Environmental Radiation Model for Yucca Mountain, Nevada (ERMYN), referred to in this report as the biosphere model. ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) describes in detail the conceptual model as well as the mathematical model and its input parameters. This report documents development of input parameters for the biosphere model that are related to atmospheric mass loading and supports the use of the model to develop biosphere dose conversion factors (BDCFs). The biosphere model is one of a series of process models supporting the total system performance assessment (TSPA) for a Yucca Mountain repository. ''Inhalation Exposure Input Parameters for the Biosphere Model'' is one of five reports that develop input parameters for the biosphere model. A graphical representation of the documentation hierarchy for the biosphere model is presented in Figure 1-1 (based on BSC 2006 [DIRS 176938]). This figure shows the interrelationships among the products (i.e., analysis and model reports) developed for biosphere modeling and how this analysis report contributes to biosphere modeling. This analysis report defines and justifies values of atmospheric mass loading for the biosphere model. Mass loading is the total mass concentration of resuspended particles (e.g., dust, ash) in a volume of air. Mass loading values are used in the air submodel of the biosphere model to calculate concentrations of radionuclides in air inhaled by a receptor and concentrations in air surrounding crops. Concentrations in air to which the receptor is exposed are then used in the inhalation submodel to calculate the dose contribution to the receptor from inhalation of contaminated airborne particles. Concentrations in air surrounding plants are used in the plant submodel to calculate the concentrations of radionuclides in foodstuffs contributed from uptake by foliar interception. This report is concerned primarily with the
The level density parameters for fermi gas model
Zuang Youxiang; Wang Cuilan; Zhou Chunmei; Su Zongdi
1986-01-01
Nuclear level densities are crucial ingredient in the statistical models, for instance, in the calculations of the widths, cross sections, emitted particle spectra, etc. for various reaction channels. In this work 667 sets of more reliable and new experimental data are adopted, which include average level spacing D D , radiative capture width Γ γ 0 at neutron binding energy and cumulative level number N 0 at the low excitation energy. They are published during 1973 to 1983. Based on the parameters given by Gilbert-Cameon and Cook the physical quantities mentioned above are calculated. The calculated results have the deviation obviously from experimental values. In order to improve the fitting, the parameters in the G-C formula are adjusted and new set of level density parameters is obsained. The parameters is this work are more suitable to fit new measurements
Iterative integral parameter identification of a respiratory mechanics model.
Schranz, Christoph; Docherty, Paul D; Chiew, Yeong Shiong; Möller, Knut; Chase, J Geoffrey
2012-07-18
Patient-specific respiratory mechanics models can support the evaluation of optimal lung protective ventilator settings during ventilation therapy. Clinical application requires that the individual's model parameter values must be identified with information available at the bedside. Multiple linear regression or gradient-based parameter identification methods are highly sensitive to noise and initial parameter estimates. Thus, they are difficult to apply at the bedside to support therapeutic decisions. An iterative integral parameter identification method is applied to a second order respiratory mechanics model. The method is compared to the commonly used regression methods and error-mapping approaches using simulated and clinical data. The clinical potential of the method was evaluated on data from 13 Acute Respiratory Distress Syndrome (ARDS) patients. The iterative integral method converged to error minima 350 times faster than the Simplex Search Method using simulation data sets and 50 times faster using clinical data sets. Established regression methods reported erroneous results due to sensitivity to noise. In contrast, the iterative integral method was effective independent of initial parameter estimations, and converged successfully in each case tested. These investigations reveal that the iterative integral method is beneficial with respect to computing time, operator independence and robustness, and thus applicable at the bedside for this clinical application.
Iterative integral parameter identification of a respiratory mechanics model
Schranz Christoph
2012-07-01
Full Text Available Abstract Background Patient-specific respiratory mechanics models can support the evaluation of optimal lung protective ventilator settings during ventilation therapy. Clinical application requires that the individual’s model parameter values must be identified with information available at the bedside. Multiple linear regression or gradient-based parameter identification methods are highly sensitive to noise and initial parameter estimates. Thus, they are difficult to apply at the bedside to support therapeutic decisions. Methods An iterative integral parameter identification method is applied to a second order respiratory mechanics model. The method is compared to the commonly used regression methods and error-mapping approaches using simulated and clinical data. The clinical potential of the method was evaluated on data from 13 Acute Respiratory Distress Syndrome (ARDS patients. Results The iterative integral method converged to error minima 350 times faster than the Simplex Search Method using simulation data sets and 50 times faster using clinical data sets. Established regression methods reported erroneous results due to sensitivity to noise. In contrast, the iterative integral method was effective independent of initial parameter estimations, and converged successfully in each case tested. Conclusion These investigations reveal that the iterative integral method is beneficial with respect to computing time, operator independence and robustness, and thus applicable at the bedside for this clinical application.
MODELLING BIOPHYSICAL PARAMETERS OF MAIZE USING LANDSAT 8 TIME SERIES
T. Dahms
2016-06-01
Full Text Available Open and free access to multi-frequent high-resolution data (e.g. Sentinel – 2 will fortify agricultural applications based on satellite data. The temporal and spatial resolution of these remote sensing datasets directly affects the applicability of remote sensing methods, for instance a robust retrieving of biophysical parameters over the entire growing season with very high geometric resolution. In this study we use machine learning methods to predict biophysical parameters, namely the fraction of absorbed photosynthetic radiation (FPAR, the leaf area index (LAI and the chlorophyll content, from high resolution remote sensing. 30 Landsat 8 OLI scenes were available in our study region in Mecklenburg-Western Pomerania, Germany. In-situ data were weekly to bi-weekly collected on 18 maize plots throughout the summer season 2015. The study aims at an optimized prediction of biophysical parameters and the identification of the best explaining spectral bands and vegetation indices. For this purpose, we used the entire in-situ dataset from 24.03.2015 to 15.10.2015. Random forest and conditional inference forests were used because of their explicit strong exploratory and predictive character. Variable importance measures allowed for analysing the relation between the biophysical parameters with respect to the spectral response, and the performance of the two approaches over the plant stock evolvement. Classical random forest regression outreached the performance of conditional inference forests, in particular when modelling the biophysical parameters over the entire growing period. For example, modelling biophysical parameters of maize for the entire vegetation period using random forests yielded: FPAR: R² = 0.85; RMSE = 0.11; LAI: R² = 0.64; RMSE = 0.9 and chlorophyll content (SPAD: R² = 0.80; RMSE=4.9. Our results demonstrate the great potential in using machine-learning methods for the interpretation of long-term multi-frequent remote sensing
Modelling Biophysical Parameters of Maize Using Landsat 8 Time Series
Dahms, Thorsten; Seissiger, Sylvia; Conrad, Christopher; Borg, Erik
2016-06-01
Open and free access to multi-frequent high-resolution data (e.g. Sentinel - 2) will fortify agricultural applications based on satellite data. The temporal and spatial resolution of these remote sensing datasets directly affects the applicability of remote sensing methods, for instance a robust retrieving of biophysical parameters over the entire growing season with very high geometric resolution. In this study we use machine learning methods to predict biophysical parameters, namely the fraction of absorbed photosynthetic radiation (FPAR), the leaf area index (LAI) and the chlorophyll content, from high resolution remote sensing. 30 Landsat 8 OLI scenes were available in our study region in Mecklenburg-Western Pomerania, Germany. In-situ data were weekly to bi-weekly collected on 18 maize plots throughout the summer season 2015. The study aims at an optimized prediction of biophysical parameters and the identification of the best explaining spectral bands and vegetation indices. For this purpose, we used the entire in-situ dataset from 24.03.2015 to 15.10.2015. Random forest and conditional inference forests were used because of their explicit strong exploratory and predictive character. Variable importance measures allowed for analysing the relation between the biophysical parameters with respect to the spectral response, and the performance of the two approaches over the plant stock evolvement. Classical random forest regression outreached the performance of conditional inference forests, in particular when modelling the biophysical parameters over the entire growing period. For example, modelling biophysical parameters of maize for the entire vegetation period using random forests yielded: FPAR: R² = 0.85; RMSE = 0.11; LAI: R² = 0.64; RMSE = 0.9 and chlorophyll content (SPAD): R² = 0.80; RMSE=4.9. Our results demonstrate the great potential in using machine-learning methods for the interpretation of long-term multi-frequent remote sensing datasets to model
Parameter sensitivity analysis of a lumped-parameter model of a chain of lymphangions in series.
Jamalian, Samira; Bertram, Christopher D; Richardson, William J; Moore, James E
2013-12-01
Any disruption of the lymphatic system due to trauma or injury can lead to edema. There is no effective cure for lymphedema, partly because predictive knowledge of lymphatic system reactions to interventions is lacking. A well-developed model of the system could greatly improve our understanding of its function. Lymphangions, defined as the vessel segment between two valves, are the individual pumping units. Based on our previous lumped-parameter model of a chain of lymphangions, this study aimed to identify the parameters that affect the system output the most using a sensitivity analysis. The system was highly sensitive to minimum valve resistance, such that variations in this parameter caused an order-of-magnitude change in time-average flow rate for certain values of imposed pressure difference. Average flow rate doubled when contraction frequency was increased within its physiological range. Optimum lymphangion length was found to be some 13-14.5 diameters. A peak of time-average flow rate occurred when transmural pressure was such that the pressure-diameter loop for active contractions was centered near maximum passive vessel compliance. Increasing the number of lymphangions in the chain improved the pumping in the presence of larger adverse pressure differences. For a given pressure difference, the optimal number of lymphangions increased with the total vessel length. These results indicate that further experiments to estimate valve resistance more accurately are necessary. The existence of an optimal value of transmural pressure may provide additional guidelines for increasing pumping in areas affected by edema.
X-Parameter Based Modelling of Polar Modulated Power Amplifiers
Wang, Yelin; Nielsen, Troels Studsgaard; Sira, Daniel
2013-01-01
X-parameters are developed as an extension of S-parameters capable of modelling non-linear devices driven by large signals. They are suitable for devices having only radio frequency (RF) and DC ports. In a polar power amplifier (PA), phase and envelope of the input modulated signal are applied...... at separate ports and the envelope port is neither an RF nor a DC port. As a result, X-parameters may fail to characterise the effect of the envelope port excitation and consequently the polar PA. This study introduces a solution to the problem for a commercial polar PA. In this solution, the RF-phase path...... PA for simulations. The simulated error vector magnitude (EVM) and adjacent channel power ratio (ACPR) were compared with the measured data to validate the model. The maximum differences between the simulated and measured EVM and ACPR are less than 2% point and 3 dB, respectively....
Identifiability and error minimization of receptor model parameters with PET
Delforge, J.; Syrota, A.; Mazoyer, B.M.
1989-01-01
The identifiability problem and the general framework for experimental design optimization are presented. The methodology is applied to the problem of the receptor-ligand model parameter estimation with dynamic positron emission tomography data. The first attempts to identify the model parameters from data obtained with a single tracer injection led to disappointing numerical results. The possibility of improving parameter estimation using a new experimental design combining an injection of the labelled ligand and an injection of the cold ligand (displacement experiment) has been investigated. However, this second protocol led to two very different numerical solutions and it was necessary to demonstrate which solution was biologically valid. This has been possible by using a third protocol including both a displacement and a co-injection experiment. (authors). 16 refs.; 14 figs
An analytical model of a curved beam with a T shaped cross section
Hull, Andrew J.; Perez, Daniel; Cox, Donald L.
2018-03-01
This paper derives a comprehensive analytical dynamic model of a closed circular beam that has a T shaped cross section. The new model includes in-plane and out-of-plane vibrations derived using continuous media expressions which produces results that have a valid frequency range above those available from traditional lumped parameter models. The web is modeled using two-dimensional elasticity equations for in-plane motion and the classical flexural plate equation for out-of-plane motion. The flange is modeled using two sets of Donnell shell equations: one for the left side of the flange and one for the right side of the flange. The governing differential equations are solved with unknown wave propagation coefficients multiplied by spatial domain and time domain functions which are inserted into equilibrium and continuity equations at the intersection of the web and flange and into boundary conditions at the edges of the system resulting in 24 algebraic equations. These equations are solved to yield the wave propagation coefficients and this produces a solution to the displacement field in all three dimensions. An example problem is formulated and compared to results from finite element analysis.
Prediction of interest rate using CKLS model with stochastic parameters
Ying, Khor Chia; Hin, Pooi Ah
2014-01-01
The Chan, Karolyi, Longstaff and Sanders (CKLS) model is a popular one-factor model for describing the spot interest rates. In this paper, the four parameters in the CKLS model are regarded as stochastic. The parameter vector φ (j) of four parameters at the (J+n)-th time point is estimated by the j-th window which is defined as the set consisting of the observed interest rates at the j′-th time point where j≤j′≤j+n. To model the variation of φ (j) , we assume that φ (j) depends on φ (j−m) , φ (j−m+1) ,…, φ (j−1) and the interest rate r j+n at the (j+n)-th time point via a four-dimensional conditional distribution which is derived from a [4(m+1)+1]-dimensional power-normal distribution. Treating the (j+n)-th time point as the present time point, we find a prediction interval for the future value r j+n+1 of the interest rate at the next time point when the value r j+n of the interest rate is given. From the above four-dimensional conditional distribution, we also find a prediction interval for the future interest rate r j+n+d at the next d-th (d≥2) time point. The prediction intervals based on the CKLS model with stochastic parameters are found to have better ability of covering the observed future interest rates when compared with those based on the model with fixed parameters
Model parameters estimation and sensitivity by genetic algorithms
Marseguerra, Marzio; Zio, Enrico; Podofillini, Luca
2003-01-01
In this paper we illustrate the possibility of extracting qualitative information on the importance of the parameters of a model in the course of a Genetic Algorithms (GAs) optimization procedure for the estimation of such parameters. The Genetic Algorithms' search of the optimal solution is performed according to procedures that resemble those of natural selection and genetics: an initial population of alternative solutions evolves within the search space through the four fundamental operations of parent selection, crossover, replacement, and mutation. During the search, the algorithm examines a large amount of solution points which possibly carries relevant information on the underlying model characteristics. A possible utilization of this information amounts to create and update an archive with the set of best solutions found at each generation and then to analyze the evolution of the statistics of the archive along the successive generations. From this analysis one can retrieve information regarding the speed of convergence and stabilization of the different control (decision) variables of the optimization problem. In this work we analyze the evolution strategy followed by a GA in its search for the optimal solution with the aim of extracting information on the importance of the control (decision) variables of the optimization with respect to the sensitivity of the objective function. The study refers to a GA search for optimal estimates of the effective parameters in a lumped nuclear reactor model of literature. The supporting observation is that, as most optimization procedures do, the GA search evolves towards convergence in such a way to stabilize first the most important parameters of the model and later those which influence little the model outputs. In this sense, besides estimating efficiently the parameters values, the optimization approach also allows us to provide a qualitative ranking of their importance in contributing to the model output. The
Prediction of interest rate using CKLS model with stochastic parameters
Ying, Khor Chia [Faculty of Computing and Informatics, Multimedia University, Jalan Multimedia, 63100 Cyberjaya, Selangor (Malaysia); Hin, Pooi Ah [Sunway University Business School, No. 5, Jalan Universiti, Bandar Sunway, 47500 Subang Jaya, Selangor (Malaysia)
2014-06-19
The Chan, Karolyi, Longstaff and Sanders (CKLS) model is a popular one-factor model for describing the spot interest rates. In this paper, the four parameters in the CKLS model are regarded as stochastic. The parameter vector φ{sup (j)} of four parameters at the (J+n)-th time point is estimated by the j-th window which is defined as the set consisting of the observed interest rates at the j′-th time point where j≤j′≤j+n. To model the variation of φ{sup (j)}, we assume that φ{sup (j)} depends on φ{sup (j−m)}, φ{sup (j−m+1)},…, φ{sup (j−1)} and the interest rate r{sub j+n} at the (j+n)-th time point via a four-dimensional conditional distribution which is derived from a [4(m+1)+1]-dimensional power-normal distribution. Treating the (j+n)-th time point as the present time point, we find a prediction interval for the future value r{sub j+n+1} of the interest rate at the next time point when the value r{sub j+n} of the interest rate is given. From the above four-dimensional conditional distribution, we also find a prediction interval for the future interest rate r{sub j+n+d} at the next d-th (d≥2) time point. The prediction intervals based on the CKLS model with stochastic parameters are found to have better ability of covering the observed future interest rates when compared with those based on the model with fixed parameters.
Mathematical models to predict rheological parameters of lateritic hydromixtures
Gabriel Hernández-Ramírez
2017-10-01
Full Text Available The present work had as objective to establish mathematical models that allow the prognosis of the rheological parameters of the lateritic pulp at concentrations of solids from 35% to 48%, temperature of the preheated hydromixture superior to 82 ° C and number of mineral between 3 and 16. Four samples of lateritic pulp were used in the study at different process locations. The results allowed defining that the plastic properties of the lateritic pulp in the conditions of this study conform to the Herschel-Bulkley model for real plastics. In addition, they show that for current operating conditions, even for new situations, UPD mathematical models have a greater ability to predict rheological parameters than least squares mathematical models.
Averaging models: parameters estimation with the R-Average procedure
S. Noventa
2010-01-01
Full Text Available The Functional Measurement approach, proposed within the theoretical framework of Information Integration Theory (Anderson, 1981, 1982, can be a useful multi-attribute analysis tool. Compared to the majority of statistical models, the averaging model can account for interaction effects without adding complexity. The R-Average method (Vidotto & Vicentini, 2007 can be used to estimate the parameters of these models. By the use of multiple information criteria in the model selection procedure, R-Average allows for the identification of the best subset of parameters that account for the data. After a review of the general method, we present an implementation of the procedure in the framework of R-project, followed by some experiments using a Monte Carlo method.
Revised Parameters for the AMOEBA Polarizable Atomic Multipole Water Model
Pande, Vijay S.; Head-Gordon, Teresa; Ponder, Jay W.
2016-01-01
A set of improved parameters for the AMOEBA polarizable atomic multipole water model is developed. The protocol uses an automated procedure, ForceBalance, to adjust model parameters to enforce agreement with ab initio-derived results for water clusters and experimentally obtained data for a variety of liquid phase properties across a broad temperature range. The values reported here for the new AMOEBA14 water model represent a substantial improvement over the previous AMOEBA03 model. The new AMOEBA14 water model accurately predicts the temperature of maximum density and qualitatively matches the experimental density curve across temperatures ranging from 249 K to 373 K. Excellent agreement is observed for the AMOEBA14 model in comparison to a variety of experimental properties as a function of temperature, including the 2nd virial coefficient, enthalpy of vaporization, isothermal compressibility, thermal expansion coefficient and dielectric constant. The viscosity, self-diffusion constant and surface tension are also well reproduced. In comparison to high-level ab initio results for clusters of 2 to 20 water molecules, the AMOEBA14 model yields results similar to the AMOEBA03 and the direct polarization iAMOEBA models. With advances in computing power, calibration data, and optimization techniques, we recommend the use of the AMOEBA14 water model for future studies employing a polarizable water model. PMID:25683601
Comparisons of criteria in the assessment model parameter optimizations
Liu Xinhe; Zhang Yongxing
1993-01-01
Three criteria (chi square, relative chi square and correlation coefficient) used in model parameter optimization (MPO) process that aims at significant reduction of prediction uncertainties were discussed and compared to each other with the aid of a well-controlled tracer experiment
Revised models and genetic parameter estimates for production and ...
Genetic parameters for production and reproduction traits in the Elsenburg Dormer sheep stud were estimated using records of 11743 lambs born between 1943 and 2002. An animal model with direct and maternal additive, maternal permanent and temporary environmental effects was fitted for traits considered traits of the ...
Determination of parameters in elasto-plastic models of aluminium.
Meuwissen, M.H.H.; Oomens, C.W.J.; Baaijens, F.P.T.; Petterson, R.; Janssen, J.D.; Sol, H.; Oomens, C.W.J.
1997-01-01
A mixed numerical-experimental method is used to determine parameters in elasto-plastic constitutive models. An aluminium plate of non-standard geometry is mounted in a uniaxial tensile testing machine at which some adjustments are made to carry out shear tests. The sample is loaded and the total
Parameter Estimation for a Computable General Equilibrium Model
Arndt, Channing; Robinson, Sherman; Tarp, Finn
2002-01-01
We introduce a maximum entropy approach to parameter estimation for computable general equilibrium (CGE) models. The approach applies information theory to estimating a system of non-linear simultaneous equations. It has a number of advantages. First, it imposes all general equilibrium constraints...
Parameter Estimation for a Computable General Equilibrium Model
Arndt, Channing; Robinson, Sherman; Tarp, Finn
We introduce a maximum entropy approach to parameter estimation for computable general equilibrium (CGE) models. The approach applies information theory to estimating a system of nonlinear simultaneous equations. It has a number of advantages. First, it imposes all general equilibrium constraints...
Do Lumped-Parameter Models Provide the Correct Geometrical Damping?
Andersen, Lars
response during excitation and the geometrical damping related to free vibrations of a hexagonal footing. The optimal order of a lumped-parameter model is determined for each degree of freedom, i.e. horizontal and vertical translation as well as torsion and rocking. In particular, the necessity of coupling...... between horizontal sliding and rocking is discussed....
Key processes and input parameters for environmental tritium models
Bunnenberg, C.; Taschner, M.; Ogram, G.L.
1994-01-01
The primary objective of the work reported here is to define key processes and input parameters for mathematical models of environmental tritium behaviour adequate for use in safety analysis and licensing of fusion devices like NET and associated tritium handling facilities. (author). 45 refs., 3 figs
Key processes and input parameters for environmental tritium models
Bunnenberg, C; Taschner, M [Niedersaechsisches Inst. fuer Radiooekologie, Hannover (Germany); Ogram, G L [Ontario Hydro, Toronto, ON (Canada)
1994-12-31
The primary objective of the work reported here is to define key processes and input parameters for mathematical models of environmental tritium behaviour adequate for use in safety analysis and licensing of fusion devices like NET and associated tritium handling facilities. (author). 45 refs., 3 figs.
Genetic Fuzzy Modelling of User Perception of 3D Shapes
Achiche, Sofiane; Ahmed-Kristensen, Saeema
2011-01-01
Defining the aesthetic and emotional value of a product is an important consideration for its design. Furthermore, if several designers are faced with the task of creating an object that describe a certain emotion/perception (aggressive, soft, heavy, etc.), each is most likely to interpret...... the emotion/perception with different shapes composed of a set of different geometric features. In this paper, the authors propose an automatic approach to formalize the relationships between geometric information of 3D objects and the intended emotional content using fuzzy logic. In addition...
Inhalation Exposure Input Parameters for the Biosphere Model
M. A. Wasiolek
2003-09-24
This analysis is one of the nine reports that support the Environmental Radiation Model for Yucca Mountain Nevada (ERMYN) biosphere model. The ''Biosphere Model Report'' (BSC 2003a) describes in detail the conceptual model as well as the mathematical model and its input parameters. This report documents a set of input parameters for the biosphere model, and supports the use of the model to develop biosphere dose conversion factors (BDCFs). The biosphere model is one of a series of process models supporting the Total System Performance Assessment (TSPA) for a Yucca Mountain repository. This report, ''Inhalation Exposure Input Parameters for the Biosphere Model'', is one of the five reports that develop input parameters for the biosphere model. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows the interrelationships among the products (i.e., analysis and model reports) developed for biosphere modeling, and the plan for development of the biosphere abstraction products for TSPA, as identified in the ''Technical Work Plan: for Biosphere Modeling and Expert Support'' (BSC 2003b). It should be noted that some documents identified in Figure 1-1 may be under development at the time this report is issued and therefore not available at that time. This figure is included to provide an understanding of how this analysis report contributes to biosphere modeling in support of the license application, and is not intended to imply that access to the listed documents is required to understand the contents of this analysis report. This analysis report defines and justifies values of mass loading, which is the total mass concentration of resuspended particles (e.g., dust, ash) in a volume of air. Measurements of mass loading are used in the air submodel of ERMYN to calculate concentrations of radionuclides in air surrounding crops and concentrations in air
Integrating microbial diversity in soil carbon dynamic models parameters
Louis, Benjamin; Menasseri-Aubry, Safya; Leterme, Philippe; Maron, Pierre-Alain; Viaud, Valérie
2015-04-01
Faced with the numerous concerns about soil carbon dynamic, a large quantity of carbon dynamic models has been developed during the last century. These models are mainly in the form of deterministic compartment models with carbon fluxes between compartments represented by ordinary differential equations. Nowadays, lots of them consider the microbial biomass as a compartment of the soil organic matter (carbon quantity). But the amount of microbial carbon is rarely used in the differential equations of the models as a limiting factor. Additionally, microbial diversity and community composition are mostly missing, although last advances in soil microbial analytical methods during the two past decades have shown that these characteristics play also a significant role in soil carbon dynamic. As soil microorganisms are essential drivers of soil carbon dynamic, the question about explicitly integrating their role have become a key issue in soil carbon dynamic models development. Some interesting attempts can be found and are dominated by the incorporation of several compartments of different groups of microbial biomass in terms of functional traits and/or biogeochemical compositions to integrate microbial diversity. However, these models are basically heuristic models in the sense that they are used to test hypotheses through simulations. They have rarely been confronted to real data and thus cannot be used to predict realistic situations. The objective of this work was to empirically integrate microbial diversity in a simple model of carbon dynamic through statistical modelling of the model parameters. This work is based on available experimental results coming from a French National Research Agency program called DIMIMOS. Briefly, 13C-labelled wheat residue has been incorporated into soils with different pedological characteristics and land use history. Then, the soils have been incubated during 104 days and labelled and non-labelled CO2 fluxes have been measured at ten
Inhalation Exposure Input Parameters for the Biosphere Model
M. A. Wasiolek
2003-01-01
This analysis is one of the nine reports that support the Environmental Radiation Model for Yucca Mountain Nevada (ERMYN) biosphere model. The ''Biosphere Model Report'' (BSC 2003a) describes in detail the conceptual model as well as the mathematical model and its input parameters. This report documents a set of input parameters for the biosphere model, and supports the use of the model to develop biosphere dose conversion factors (BDCFs). The biosphere model is one of a series of process models supporting the Total System Performance Assessment (TSPA) for a Yucca Mountain repository. This report, ''Inhalation Exposure Input Parameters for the Biosphere Model'', is one of the five reports that develop input parameters for the biosphere model. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows the interrelationships among the products (i.e., analysis and model reports) developed for biosphere modeling, and the plan for development of the biosphere abstraction products for TSPA, as identified in the ''Technical Work Plan: for Biosphere Modeling and Expert Support'' (BSC 2003b). It should be noted that some documents identified in Figure 1-1 may be under development at the time this report is issued and therefore not available at that time. This figure is included to provide an understanding of how this analysis report contributes to biosphere modeling in support of the license application, and is not intended to imply that access to the listed documents is required to understand the contents of this analysis report. This analysis report defines and justifies values of mass loading, which is the total mass concentration of resuspended particles (e.g., dust, ash) in a volume of air. Measurements of mass loading are used in the air submodel of ERMYN to calculate concentrations of radionuclides in air surrounding crops and concentrations in air inhaled by a receptor. Concentrations in air to which the
Y. M. Parulekar
2012-01-01
Full Text Available Recently, there has been increasing interest in using superelastic shape memory alloys for applications in seismic resistant-design. Shape memory alloys (SMAs have a unique property by which they can recover their original shape after experiencing large strains up to 8% either by heating (shape memory effect or removing stress (pseudoelastic effect. Many simplified shape memory alloy models are suggested in the past literature for capturing the pseudoelastic response of SMAs in passive vibration control of structures. Most of these models do not consider the cyclic effects of SMA's and resulting residual martensite deformation. Therefore, a suitable constitutive model of shape memory alloy damper which represents the nonlinear hysterical dynamic system appropriately is essential. In this paper a multilinear hysteretic model incorporating residual martensite strain effect of pseudoelastic shape memory alloy damper is developed and experimentally validated using SMA wire, based damper device. A sensitivity analysis is done using the proposed model along with three other simplified SMA models. The models are implemented on a steel frame representing an SDOF system and the comparison of seismic response of structure with all the models is made in the numerical study.
Application of Parameter Estimation for Diffusions and Mixture Models
Nolsøe, Kim
The first part of this thesis proposes a method to determine the preferred number of structures, their proportions and the corresponding geometrical shapes of an m-membered ring molecule. This is obtained by formulating a statistical model for the data and constructing an algorithm which samples...... with the posterior score function. From an application point of view this methology is easy to apply, since the optimal estimating function G(;Xt1 ; : : : ;Xtn ) is equal to the classical optimal estimating function, plus a correction term which takes into account the prior information. The methology is particularly...
Agricultural and Environmental Input Parameters for the Biosphere Model
K. Rasmuson; K. Rautenstrauch
2004-09-14
This analysis is one of 10 technical reports that support the Environmental Radiation Model for Yucca Mountain Nevada (ERMYN) (i.e., the biosphere model). It documents development of agricultural and environmental input parameters for the biosphere model, and supports the use of the model to develop biosphere dose conversion factors (BDCFs). The biosphere model is one of a series of process models supporting the total system performance assessment (TSPA) for the repository at Yucca Mountain. The ERMYN provides the TSPA with the capability to perform dose assessments. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows the interrelationships between the major activities and their products (the analysis and model reports) that were planned in ''Technical Work Plan for Biosphere Modeling and Expert Support'' (BSC 2004 [DIRS 169573]). The ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) describes the ERMYN and its input parameters.
Evaluation of some infiltration models and hydraulic parameters
Haghighi, F.; Gorji, M.; Shorafa, M.; Sarmadian, F.; Mohammadi, M. H.
2010-01-01
The evaluation of infiltration characteristics and some parameters of infiltration models such as sorptivity and final steady infiltration rate in soils are important in agriculture. The aim of this study was to evaluate some of the most common models used to estimate final soil infiltration rate. The equality of final infiltration rate with saturated hydraulic conductivity (Ks) was also tested. Moreover, values of the estimated sorptivity from the Philips model were compared to estimates by selected pedotransfer functions (PTFs). The infiltration experiments used the doublering method on soils with two different land uses in the Taleghan watershed of Tehran province, Iran, from September to October, 2007. The infiltration models of Kostiakov-Lewis, Philip two-term and Horton were fitted to observed infiltration data. Some parameters of the models and the coefficient of determination goodness of fit were estimated using MATLAB software. The results showed that, based on comparing measured and model-estimated infiltration rate using root mean squared error (RMSE), Hortons model gave the best prediction of final infiltration rate in the experimental area. Laboratory measured Ks values gave significant differences and higher values than estimated final infiltration rates from the selected models. The estimated final infiltration rate was not equal to laboratory measured Ks values in the study area. Moreover, the estimated sorptivity factor by Philips model was significantly different to those estimated by selected PTFs. It is suggested that the applicability of PTFs is limited to specific, similar conditions. (Author) 37 refs.
Electro-optical parameters of bond polarizability model for aluminosilicates.
Smirnov, Konstantin S; Bougeard, Daniel; Tandon, Poonam
2006-04-06
Electro-optical parameters (EOPs) of bond polarizability model (BPM) for aluminosilicate structures were derived from quantum-chemical DFT calculations of molecular models. The tensor of molecular polarizability and the derivatives of the tensor with respect to the bond length are well reproduced with the BPM, and the EOPs obtained are in a fair agreement with available experimental data. The parameters derived were found to be transferable to larger molecules. This finding suggests that the procedure used can be applied to systems with partially ionic chemical bonds. The transferability of the parameters to periodic systems was tested in molecular dynamics simulation of the polarized Raman spectra of alpha-quartz. It appeared that the molecular Si-O bond EOPs failed to reproduce the intensity of peaks in the spectra. This limitation is due to large values of the longitudinal components of the bond polarizability and its derivative found in the molecular calculations as compared to those obtained from periodic DFT calculations of crystalline silica polymorphs by Umari et al. (Phys. Rev. B 2001, 63, 094305). It is supposed that the electric field of the solid is responsible for the difference of the parameters. Nevertheless, the EOPs obtained can be used as an initial set of parameters for calculations of polarizability related characteristics of relevant systems in the framework of BPM.
Zhang, Hao; Chen, Diyi; Wu, Changzhi; Wang, Xiangyu; Lee, Jae-Myung; Jung, Kwang-Hyo
2017-01-01
Highlights: • Novel dynamic model of a pump-turbine in S-shaped regions is proposed. • A stability criterion of runaway point is given. • Global dynamic characteristics of the pump-turbine are investigated. • Effects of the slopes of the characteristic curve on the stability are studied. - Abstract: There is a region of pump-turbine operation, often called the S-shaped region, in which one unit rotational speed corresponds to three unit flows or torques. In this paper, the dynamic model of the pump-turbine in S-shaped regions is established by introducing the nonlinear piecewise function of relative parameters. Then, the global bifurcation diagrams of the pump-turbine are presented to analyze its dynamic characteristics in the S-shaped regions. Meanwhile, a stability criterion of runaway point is given based on the established theoretical model. The numerical experiments are conducted on the model and the results are in good agreement with the theoretical analysis. Furthermore, the effects of the characteristic curve slopes on the stability of the pump-turbine are studied by an innovative use of the three-dimensional bifurcation diagrams. Finally, the factors influencing the runaway stability of pump-turbines are also discussed, based on the dynamic analysis.
Estimating model parameters in nonautonomous chaotic systems using synchronization
Yang, Xiaoli; Xu, Wei; Sun, Zhongkui
2007-01-01
In this Letter, a technique is addressed for estimating unknown model parameters of multivariate, in particular, nonautonomous chaotic systems from time series of state variables. This technique uses an adaptive strategy for tracking unknown parameters in addition to a linear feedback coupling for synchronizing systems, and then some general conditions, by means of the periodic version of the LaSalle invariance principle for differential equations, are analytically derived to ensure precise evaluation of unknown parameters and identical synchronization between the concerned experimental system and its corresponding receiver one. Exemplifies are presented by employing a parametrically excited 4D new oscillator and an additionally excited Ueda oscillator. The results of computer simulations reveal that the technique not only can quickly track the desired parameter values but also can rapidly respond to changes in operating parameters. In addition, the technique can be favorably robust against the effect of noise when the experimental system is corrupted by bounded disturbance and the normalized absolute error of parameter estimation grows almost linearly with the cutoff value of noise strength in simulation
Soil-Related Input Parameters for the Biosphere Model
Smith, A. J.
2004-01-01
This report presents one of the analyses that support the Environmental Radiation Model for Yucca Mountain Nevada (ERMYN). The ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) describes the details of the conceptual model as well as the mathematical model and the required input parameters. The biosphere model is one of a series of process models supporting the postclosure Total System Performance Assessment (TSPA) for the Yucca Mountain repository. A schematic representation of the documentation flow for the Biosphere input to TSPA is presented in Figure 1-1. This figure shows the evolutionary relationships among the products (i.e., analysis and model reports) developed for biosphere modeling, and the biosphere abstraction products for TSPA, as identified in the ''Technical Work Plan for Biosphere Modeling and Expert Support'' (TWP) (BSC 2004 [DIRS 169573]). This figure is included to provide an understanding of how this analysis report contributes to biosphere modeling in support of the license application, and is not intended to imply that access to the listed documents is required to understand the contents of this report. This report, ''Soil-Related Input Parameters for the Biosphere Model'', is one of the five analysis reports that develop input parameters for use in the ERMYN model. This report is the source documentation for the six biosphere parameters identified in Table 1-1. The purpose of this analysis was to develop the biosphere model parameters associated with the accumulation and depletion of radionuclides in the soil. These parameters support the calculation of radionuclide concentrations in soil from on-going irrigation or ash deposition and, as a direct consequence, radionuclide concentration in other environmental media that are affected by radionuclide concentrations in soil. The analysis was performed in accordance with the TWP (BSC 2004 [DIRS 169573]) where the governing procedure was defined as AP-SIII.9Q, ''Scientific Analyses''. This
Soil-Related Input Parameters for the Biosphere Model
A. J. Smith
2004-09-09
This report presents one of the analyses that support the Environmental Radiation Model for Yucca Mountain Nevada (ERMYN). The ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) describes the details of the conceptual model as well as the mathematical model and the required input parameters. The biosphere model is one of a series of process models supporting the postclosure Total System Performance Assessment (TSPA) for the Yucca Mountain repository. A schematic representation of the documentation flow for the Biosphere input to TSPA is presented in Figure 1-1. This figure shows the evolutionary relationships among the products (i.e., analysis and model reports) developed for biosphere modeling, and the biosphere abstraction products for TSPA, as identified in the ''Technical Work Plan for Biosphere Modeling and Expert Support'' (TWP) (BSC 2004 [DIRS 169573]). This figure is included to provide an understanding of how this analysis report contributes to biosphere modeling in support of the license application, and is not intended to imply that access to the listed documents is required to understand the contents of this report. This report, ''Soil-Related Input Parameters for the Biosphere Model'', is one of the five analysis reports that develop input parameters for use in the ERMYN model. This report is the source documentation for the six biosphere parameters identified in Table 1-1. The purpose of this analysis was to develop the biosphere model parameters associated with the accumulation and depletion of radionuclides in the soil. These parameters support the calculation of radionuclide concentrations in soil from on-going irrigation or ash deposition and, as a direct consequence, radionuclide concentration in other environmental media that are affected by radionuclide concentrations in soil. The analysis was performed in accordance with the TWP (BSC 2004 [DIRS 169573]) where the governing procedure
Mass balance model parameter transferability on a tropical glacier
Gurgiser, Wolfgang; Mölg, Thomas; Nicholson, Lindsey; Kaser, Georg
2013-04-01
The mass balance and melt water production of glaciers is of particular interest in the Peruvian Andes where glacier melt water has markedly increased water supply during the pronounced dry seasons in recent decades. However, the melt water contribution from glaciers is projected to decrease with appreciable negative impacts on the local society within the coming decades. Understanding mass balance processes on tropical glaciers is a prerequisite for modeling present and future glacier runoff. As a first step towards this aim we applied a process-based surface mass balance model in order to calculate observed ablation at two stakes in the ablation zone of Shallap Glacier (4800 m a.s.l., 9°S) in the Cordillera Blanca, Peru. Under the tropical climate, the snow line migrates very frequently across most of the ablation zone all year round causing large temporal and spatial variations of glacier surface conditions and related ablation. Consequently, pronounced differences between the two chosen stakes and the two years were observed. Hourly records of temperature, humidity, wind speed, short wave incoming radiation, and precipitation are available from an automatic weather station (AWS) on the moraine near the glacier for the hydrological years 2006/07 and 2007/08 while stake readings are available at intervals of between 14 to 64 days. To optimize model parameters, we used 1000 model simulations in which the most sensitive model parameters were varied randomly within their physically meaningful ranges. The modeled surface height change was evaluated against the two stake locations in the lower ablation zone (SH11, 4760m) and in the upper ablation zone (SH22, 4816m), respectively. The optimal parameter set for each point achieved good model skill but if we transfer the best parameter combination from one stake site to the other stake site model errors increases significantly. The same happens if we optimize the model parameters for each year individually and transfer
Development of a statistical shape model of multi-organ and its performance evaluation
Nakada, Misaki; Shimizu, Akinobu; Kobatake, Hidefumi; Nawano, Shigeru
2010-01-01
Existing statistical shape modeling methods for an organ can not take into account the correlation between neighboring organs. This study focuses on a level set distribution model and proposes two modeling methods for multiple organs that can take into account the correlation between neighboring organs. The first method combines level set functions of multiple organs into a vector. Subsequently it analyses the distribution of the vectors of a training dataset by a principal component analysis and builds a multiple statistical shape model. Second method constructs a statistical shape model for each organ independently and assembles component scores of different organs in a training dataset so as to generate a vector. It analyses the distribution of the vectors of to build a statistical shape model of multiple organs. This paper shows results of applying the proposed methods trained by 15 abdominal CT volumes to unknown 8 CT volumes. (author)
Constraining statistical-model parameters using fusion and spallation reactions
Charity Robert J.
2011-10-01
Full Text Available The de-excitation of compound nuclei has been successfully described for several decades by means of statistical models. However, such models involve a large number of free parameters and ingredients that are often underconstrained by experimental data. We show how the degeneracy of the model ingredients can be partially lifted by studying different entrance channels for de-excitation, which populate different regions of the parameter space of the compound nucleus. Fusion reactions, in particular, play an important role in this strategy because they ﬁx three out of four of the compound-nucleus parameters (mass, charge and total excitation energy. The present work focuses on ﬁssion and intermediate-mass-fragment emission cross sections. We prove how equivalent parameter sets for fusion-ﬁssion reactions can be resolved using another entrance channel, namely spallation reactions. Intermediate-mass-fragment emission can be constrained in a similar way. An interpretation of the best-ﬁt IMF barriers in terms of the Wigner energies of the nascent fragments is discussed.
Investigation of RADTRAN Stop Model input parameters for truck stops
Griego, N.R.; Smith, J.D.; Neuhauser, K.S.
1996-01-01
RADTRAN is a computer code for estimating the risks and consequences as transport of radioactive materials (RAM). RADTRAN was developed and is maintained by Sandia National Laboratories for the US Department of Energy (DOE). For incident-free transportation, the dose to persons exposed while the shipment is stopped is frequently a major percentage of the overall dose. This dose is referred to as Stop Dose and is calculated by the Stop Model. Because stop dose is a significant portion of the overall dose associated with RAM transport, the values used as input for the Stop Model are important. Therefore, an investigation of typical values for RADTRAN Stop Parameters for truck stops was performed. The resulting data from these investigations were analyzed to provide mean values, standard deviations, and histograms. Hence, the mean values can be used when an analyst does not have a basis for selecting other input values for the Stop Model. In addition, the histograms and their characteristics can be used to guide statistical sampling techniques to measure sensitivity of the RADTRAN calculated Stop Dose to the uncertainties in the stop model input parameters. This paper discusses the details and presents the results of the investigation of stop model input parameters at truck stops
Improved radiograph measurement inter-observer reliability by use of statistical shape models
Pegg, E.C., E-mail: elise.pegg@ndorms.ox.ac.uk [University of Oxford, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, Nuffield Orthopaedic Centre, Windmill Road, Oxford OX3 7LD (United Kingdom); Mellon, S.J., E-mail: stephen.mellon@ndorms.ox.ac.uk [University of Oxford, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, Nuffield Orthopaedic Centre, Windmill Road, Oxford OX3 7LD (United Kingdom); Salmon, G. [University of Oxford, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, Nuffield Orthopaedic Centre, Windmill Road, Oxford OX3 7LD (United Kingdom); Alvand, A., E-mail: abtin.alvand@ndorms.ox.ac.uk [University of Oxford, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, Nuffield Orthopaedic Centre, Windmill Road, Oxford OX3 7LD (United Kingdom); Pandit, H., E-mail: hemant.pandit@ndorms.ox.ac.uk [University of Oxford, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, Nuffield Orthopaedic Centre, Windmill Road, Oxford OX3 7LD (United Kingdom); Murray, D.W., E-mail: david.murray@ndorms.ox.ac.uk [University of Oxford, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, Nuffield Orthopaedic Centre, Windmill Road, Oxford OX3 7LD (United Kingdom); Gill, H.S., E-mail: richie.gill@ndorms.ox.ac.uk [University of Oxford, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, Nuffield Orthopaedic Centre, Windmill Road, Oxford OX3 7LD (United Kingdom)
2012-10-15
Pre- and post-operative radiographs of patients undergoing joint arthroplasty are often examined for a variety of purposes including preoperative planning and patient assessment. This work examines the feasibility of using active shape models (ASM) to semi-automate measurements from post-operative radiographs for the specific case of the Oxford™ Unicompartmental Knee. Measurements of the proximal tibia and the position of the tibial tray were made using the ASM model and manually. Data were obtained by four observers and one observer took four sets of measurements to allow assessment of the inter- and intra-observer reliability, respectively. The parameters measured were the tibial tray angle, the tray overhang, the tray size, the sagittal cut position, the resection level and the tibial width. Results demonstrated improved reliability (average of 27% and 11.2% increase for intra- and inter-reliability, respectively) and equivalent accuracy (p > 0.05 for compared data values) for all of the measurements using the ASM model, with the exception of the tray overhang (p = 0.0001). Less time (15 s) was required to take measurements using the ASM model compared with manual measurements, which was significant. These encouraging results indicate that semi-automated measurement techniques could improve the reliability of radiographic measurements.
Improved radiograph measurement inter-observer reliability by use of statistical shape models
Pegg, E.C.; Mellon, S.J.; Salmon, G.; Alvand, A.; Pandit, H.; Murray, D.W.; Gill, H.S.
2012-01-01
Pre- and post-operative radiographs of patients undergoing joint arthroplasty are often examined for a variety of purposes including preoperative planning and patient assessment. This work examines the feasibility of using active shape models (ASM) to semi-automate measurements from post-operative radiographs for the specific case of the Oxford™ Unicompartmental Knee. Measurements of the proximal tibia and the position of the tibial tray were made using the ASM model and manually. Data were obtained by four observers and one observer took four sets of measurements to allow assessment of the inter- and intra-observer reliability, respectively. The parameters measured were the tibial tray angle, the tray overhang, the tray size, the sagittal cut position, the resection level and the tibial width. Results demonstrated improved reliability (average of 27% and 11.2% increase for intra- and inter-reliability, respectively) and equivalent accuracy (p > 0.05 for compared data values) for all of the measurements using the ASM model, with the exception of the tray overhang (p = 0.0001). Less time (15 s) was required to take measurements using the ASM model compared with manual measurements, which was significant. These encouraging results indicate that semi-automated measurement techniques could improve the reliability of radiographic measurements
Updated climatological model predictions of ionospheric and HF propagation parameters
Reilly, M.H.; Rhoads, F.J.; Goodman, J.M.; Singh, M.
1991-01-01
The prediction performances of several climatological models, including the ionospheric conductivity and electron density model, RADAR C, and Ionospheric Communications Analysis and Predictions Program, are evaluated for different regions and sunspot number inputs. Particular attention is given to the near-real-time (NRT) predictions associated with single-station updates. It is shown that a dramatic improvement can be obtained by using single-station ionospheric data to update the driving parameters for an ionospheric model for NRT predictions of f(0)F2 and other ionospheric and HF circuit parameters. For middle latitudes, the improvement extends out thousands of kilometers from the update point to points of comparable corrected geomagnetic latitude. 10 refs
Statistical approach for uncertainty quantification of experimental modal model parameters
Luczak, M.; Peeters, B.; Kahsin, M.
2014-01-01
Composite materials are widely used in manufacture of aerospace and wind energy structural components. These load carrying structures are subjected to dynamic time-varying loading conditions. Robust structural dynamics identification procedure impose tight constraints on the quality of modal models...... represent different complexity levels ranging from coupon, through sub-component up to fully assembled aerospace and wind energy structural components made of composite materials. The proposed method is demonstrated on two application cases of a small and large wind turbine blade........ This paper aims at a systematic approach for uncertainty quantification of the parameters of the modal models estimated from experimentally obtained data. Statistical analysis of modal parameters is implemented to derive an assessment of the entire modal model uncertainty measure. Investigated structures...
Influential input parameters for reflood model of MARS code
Oh, Deog Yeon; Bang, Young Seok [Korea Institute of Nuclear Safety, Daejeon (Korea, Republic of)
2012-10-15
Best Estimate (BE) calculation has been more broadly used in nuclear industries and regulations to reduce the significant conservatism for evaluating Loss of Coolant Accident (LOCA). Reflood model has been identified as one of the problems in BE calculation. The objective of the Post BEMUSE Reflood Model Input Uncertainty Methods (PREMIUM) program of OECD/NEA is to make progress the issue of the quantification of the uncertainty of the physical models in system thermal hydraulic codes, by considering an experimental result especially for reflood. It is important to establish a methodology to identify and select the parameters influential to the response of reflood phenomena following Large Break LOCA. For this aspect, a reference calculation and sensitivity analysis to select the dominant influential parameters for FEBA experiment are performed.
Four-parameter analytical local model potential for atoms
Fei, Yu; Jiu-Xun, Sun; Rong-Gang, Tian; Wei, Yang
2009-01-01
Analytical local model potential for modeling the interaction in an atom reduces the computational effort in electronic structure calculations significantly. A new four-parameter analytical local model potential is proposed for atoms Li through Lr, and the values of four parameters are shell-independent and obtained by fitting the results of X a method. At the same time, the energy eigenvalues, the radial wave functions and the total energies of electrons are obtained by solving the radial Schrödinger equation with a new form of potential function by Numerov's numerical method. The results show that our new form of potential function is suitable for high, medium and low Z atoms. A comparison among the new potential function and other analytical potential functions shows the greater flexibility and greater accuracy of the present new potential function. (atomic and molecular physics)
Adapting Active Shape Models for 3D segmentation of tubular structures in medical images.
de Bruijne, Marleen; van Ginneken, Bram; Viergever, Max A; Niessen, Wiro J
2003-07-01
Active Shape Models (ASM) have proven to be an effective approach for image segmentation. In some applications, however, the linear model of gray level appearance around a contour that is used in ASM is not sufficient for accurate boundary localization. Furthermore, the statistical shape model may be too restricted if the training set is limited. This paper describes modifications to both the shape and the appearance model of the original ASM formulation. Shape model flexibility is increased, for tubular objects, by modeling the axis deformation independent of the cross-sectional deformation, and by adding supplementary cylindrical deformation modes. Furthermore, a novel appearance modeling scheme that effectively deals with a highly varying background is developed. In contrast with the conventional ASM approach, the new appearance model is trained on both boundary and non-boundary points, and the probability that a given point belongs to the boundary is estimated non-parametrically. The methods are evaluated on the complex task of segmenting thrombus in abdominal aortic aneurysms (AAA). Shape approximation errors were successfully reduced using the two shape model extensions. Segmentation using the new appearance model significantly outperformed the original ASM scheme; average volume errors are 5.1% and 45% respectively.
Application of parameters space analysis tools for empirical model validation
Paloma del Barrio, E. [LEPT-ENSAM UMR 8508, Talence (France); Guyon, G. [Electricite de France, Moret-sur-Loing (France)
2004-01-01
A new methodology for empirical model validation has been proposed in the framework of the Task 22 (Building Energy Analysis Tools) of the International Energy Agency. It involves two main steps: checking model validity and diagnosis. Both steps, as well as the underlying methods, have been presented in the first part of the paper. In this part, they are applied for testing modelling hypothesis in the framework of the thermal analysis of an actual building. Sensitivity analysis tools have been first used to identify the parts of the model that can be really tested on the available data. A preliminary diagnosis is then supplied by principal components analysis. Useful information for model behaviour improvement has been finally obtained by optimisation techniques. This example of application shows how model parameters space analysis is a powerful tool for empirical validation. In particular, diagnosis possibilities are largely increased in comparison with residuals analysis techniques. (author)
Wang, C.
2005-01-01
Lack of facilities in supporting design reuse is a serious problem in product shape modeling, especially in computer-aided design systems. This becomes a bottleneck of fast shape conceptualization and creation in consumer product design, which consequently prohibits creativity and innovation. In the
ShapeSelectForest: a new r package for modeling landsat time series
Mary Meyer; Xiyue Liao; Gretchen Moisen; Elizabeth Freeman
2015-01-01
We present a new R package called ShapeSelectForest recently posted to the Comprehensive R Archival Network. The package was developed to fit nonparametric shape-restricted regression splines to time series of Landsat imagery for the purpose of modeling, mapping, and monitoring annual forest disturbance dynamics over nearly three decades. For each pixel and spectral...
COMPUTATIONAL MODELING OF AIRFLOW IN NONREGULAR SHAPED CHANNELS
A. A. Voronin
2013-05-01
Full Text Available The basic approaches to computational modeling of airflow in the human nasal cavity are analyzed. Different models of turbulent flow which may be used in order to calculate air velocity and pressure are discussed. Experimental measurement results of airflow temperature are illustrated. Geometrical model of human nasal cavity reconstructed from computer-aided tomography scans and numerical simulation results of airflow inside this model are also given. Spatial distributions of velocity and temperature for inhaled and exhaled air are shown.
Test models for improving filtering with model errors through stochastic parameter estimation
Gershgorin, B.; Harlim, J.; Majda, A.J.
2010-01-01
The filtering skill for turbulent signals from nature is often limited by model errors created by utilizing an imperfect model for filtering. Updating the parameters in the imperfect model through stochastic parameter estimation is one way to increase filtering skill and model performance. Here a suite of stringent test models for filtering with stochastic parameter estimation is developed based on the Stochastic Parameterization Extended Kalman Filter (SPEKF). These new SPEKF-algorithms systematically correct both multiplicative and additive biases and involve exact formulas for propagating the mean and covariance including the parameters in the test model. A comprehensive study is presented of robust parameter regimes for increasing filtering skill through stochastic parameter estimation for turbulent signals as the observation time and observation noise are varied and even when the forcing is incorrectly specified. The results here provide useful guidelines for filtering turbulent signals in more complex systems with significant model errors.
Comparison of ionospheric profile parameters with IRI-2012 model over Jicamarca
Bello, S A; Abdullah, M; Hamid, N S A; Reinisch, B W
2017-01-01
We used the hourly ionogram data obtained from Jicamarca station (12° S, 76.9° W, dip latitude: 1.0° N) an equatorial region to study the variation of the electron density profile parameters: maximum height of F2-layer ( hm F2), bottomside thickness ( B0 ) and shape ( B1 ) parameter of F-layer. The period of study is for the year 2010 (solar minimum period).The diurnal monthly averages of these parameters are compared with the updated IRI-2012 model. The results show that hm F2 is highest during the daytime than nighttime. The variation in hmF2 was observed to modulate the thickness of the bottomside F2-layer. The observed hm F2 and B0 post-sunset peak is as result of the upward drift velocity of ionospheric plasma. We found a close agreement between IRI-CCIR hm F2 model and observed hm F2 during 0000-0700 LT while outside this period the model predictions deviate significantly with the observational values. Significant discrepancies are observed between the IRI model options for B0 and the observed B0 values. Specifically, the modeled values do not show B0 post-sunset peak. A fairly good agreement was observed between the observed B1 and IRI model options (ABT-2009 and Bill 2000) for B1 . (paper)
Comparison of ionospheric profile parameters with IRI-2012 model over Jicamarca
Bello, S. A.; Abdullah, M.; Hamid, N. S. A.; Reinisch, B. W.
2017-05-01
We used the hourly ionogram data obtained from Jicamarca station (12° S, 76.9° W, dip latitude: 1.0° N) an equatorial region to study the variation of the electron density profile parameters: maximum height of F2-layer (hmF2), bottomside thickness (B0) and shape (B1) parameter of F-layer. The period of study is for the year 2010 (solar minimum period).The diurnal monthly averages of these parameters are compared with the updated IRI-2012 model. The results show that hmF2 is highest during the daytime than nighttime. The variation in hmF2 was observed to modulate the thickness of the bottomside F2-layer. The observed hmF2 and B0 post-sunset peak is as result of the upward drift velocity of ionospheric plasma. We found a close agreement between IRI-CCIR hmF2 model and observed hmF2 during 0000-0700 LT while outside this period the model predictions deviate significantly with the observational values. Significant discrepancies are observed between the IRI model options for B0 and the observed B0 values. Specifically, the modeled values do not show B0 post-sunset peak. A fairly good agreement was observed between the observed B1 and IRI model options (ABT-2009 and Bill 2000) for B1.
Modeling size effects on the transformation behavior of shape memory alloy micropillars
Hernandez, Edwin A Peraza; Lagoudas, Dimitris C
2015-01-01
The size dependence of the thermomechanical response of shape memory alloys (SMAs) at the micro and nano-scales has gained increasing attention in the engineering community due to existing and potential uses of SMAs as solid-state actuators and components for energy dissipation in small scale devices. Particularly, their recent uses in microelectromechanical systems (MEMS) have made SMAs attractive options as active materials in small scale devices. One factor limiting further application, however, is the inability to effectively and efficiently model the observed size dependence of the SMA behavior for engineering applications. Therefore, in this work, a constitutive model for the size-dependent behavior of SMAs is proposed. Experimental observations are used to motivate the extension of an existing thermomechanical constitutive model for SMAs to account for the scale effects. It is proposed that such effects can be captured via characteristic length dependent material parameters in a power-law manner. The size dependence of the transformation behavior of NiFeGa micropillars is investigated in detail and used as model prediction cases. The constitutive model is implemented in a finite element framework and used to simulate and predict the response of SMA micropillars with different sizes. The results show a good agreement with experimental data. A parametric study performed using the calibrated model shows that the influence of micropillar aspect ratio and taper angle on the compression response is significantly smaller than that of the micropillar average diameter. It is concluded that the model is able to capture the size dependent transformation response of the SMA micropillars. In addition, the simplicity of the calibration and implementation of the proposed model make it practical for the design and numerical analysis of small scale SMA components that exhibit size dependent responses. (paper)
Model parameter learning using Kullback-Leibler divergence
Lin, Chungwei; Marks, Tim K.; Pajovic, Milutin; Watanabe, Shinji; Tung, Chih-kuan
2018-02-01
In this paper, we address the following problem: For a given set of spin configurations whose probability distribution is of the Boltzmann type, how do we determine the model coupling parameters? We demonstrate that directly minimizing the Kullback-Leibler divergence is an efficient method. We test this method against the Ising and XY models on the one-dimensional (1D) and two-dimensional (2D) lattices, and provide two estimators to quantify the model quality. We apply this method to two types of problems. First, we apply it to the real-space renormalization group (RG). We find that the obtained RG flow is sufficiently good for determining the phase boundary (within 1% of the exact result) and the critical point, but not accurate enough for critical exponents. The proposed method provides a simple way to numerically estimate amplitudes of the interactions typically truncated in the real-space RG procedure. Second, we apply this method to the dynamical system composed of self-propelled particles, where we extract the parameter of a statistical model (a generalized XY model) from a dynamical system described by the Viscek model. We are able to obtain reasonable coupling values corresponding to different noise strengths of the Viscek model. Our method is thus able to provide quantitative analysis of dynamical systems composed of self-propelled particles.
Petrillo, Antonella; Fusco, Roberta; Petrillo, Mario; Granata, Vincenza [Istituto Nazionale Tumori Fondazione Giovanni Pascale - IRCCS, Naples (Italy). Div. of Radiology; Sansone, Mario [Naples Univ. ' ' Federico II' ' (Italy). Dept. of Biomedical, Electronics and Telecommunications Engineering; Avallone, Antonio [Istituto Nazionale Tumori Fondazione Giovanni Pascale - IRCCS, Naples (Italy). Div. of Gastrointestinal Medical Oncology; Delrio, Paolo [Istituto Nazionale Tumori Fondazione Giovanni Pascale - IRCCS, Naples (Italy). Div. of Gastrointestinal surgical Oncology; Pecori, Biagio [Istituto Nazionale Tumori Fondazione Giovanni Pascale - IRCCS, Naples (Italy). Div. of Radiotherapy; Tatangelo, Fabiana [Istituto Nazionale Tumori Fondazione Giovanni Pascale - IRCCS, Naples (Italy). Div. of Diagnostic Pathology; Ciliberto, Gennaro [Istituto Nazionale Tumori Fondazione Giovanni Pascale - IRCCS, Naples (Italy)
2015-07-15
To investigate the potential of DCE-MRI to discriminate responders from non-responders after neoadjuvant chemo-radiotherapy (CRT) for locally advanced rectal cancer (LARC). We investigated several shape parameters for the time-intensity curve (TIC) in order to identify the best combination of parameters between two linear parameter classifiers. Seventy-four consecutive patients with LARC were enrolled in a prospective study approved by our ethics committee. Each patient gave written informed consent. After surgery, pathological TNM and tumour regression grade (TRG) were estimated. DCE-MRI semi-quantitative analysis (sqMRI) was performed to identify the best parameter or parameter combination to discriminate responders from non-responders in response monitoring to CRT. Percentage changes of TIC shape descriptors from the baseline to the presurgical scan were assessed and correlated with TRG. Receiver operating characteristic analysis and linear classifier were applied. Forty-six patients (62.2 %) were classified as responders, while 28 subjects (37.8 %) were considered as non-responders. sqMRI reached a sensitivity of 93.5 % and a specificity of 82.1 % combining the percentage change in Maximum Signal Difference (ΔMSD) and Wash-out Slope (ΔWOS), the Standardized Index of Shape (SIS). SIS obtains the best result in discriminating responders from non-responders after CRT in LARC, with a cut-off value of -3.0 %. (orig.)
Miller, Tom E X
2007-07-01
1. It is widely accepted that density-dependent processes play an important role in most natural populations. However, persistent challenges in our understanding of density-dependent population dynamics include evaluating the shape of the relationship between density and demographic rates (linear, concave, convex), and identifying extrinsic factors that can mediate this relationship. 2. I studied the population dynamics of the cactus bug Narnia pallidicornis on host plants (Opuntia imbricata) that varied naturally in relative reproductive effort (RRE, the proportion of meristems allocated to reproduction), an important plant quality trait. I manipulated per-plant cactus bug densities, quantified subsequent dynamics, and fit stage-structured models to the experimental data to ask if and how density influences demographic parameters. 3. In the field experiment, I found that populations with variable starting densities quickly converged upon similar growth trajectories. In the model-fitting analyses, the data strongly supported a model that defined the juvenile cactus bug retention parameter (joint probability of surviving and not dispersing) as a nonlinear decreasing function of density. The estimated shape of this relationship shifted from concave to convex with increasing host-plant RRE. 4. The results demonstrate that host-plant traits are critical sources of variation in the strength and shape of density dependence in insects, and highlight the utility of integrated experimental-theoretical approaches for identifying processes underlying patterns of change in natural populations.
Biosphere modelling for a HLW repository - scenario and parameter variations
Grogan, H.
1985-03-01
In Switzerland high-level radioactive wastes have been considered for disposal in deep-lying crystalline formations. The individual doses to man resulting from radionuclides entering the biosphere via groundwater transport are calculated. The main recipient area modelled, which constitutes the base case, is a broad gravel terrace sited along the south bank of the river Rhine. An alternative recipient region, a small valley with a well, is also modelled. A number of parameter variations are performed in order to ascertain their impact on the doses. Finally two scenario changes are modelled somewhat simplistically, these consider different prevailing climates, namely tundra and a warmer climate than present. In the base case negligibly low doses to man in the long term, resulting from the existence of a HLW repository have been calculated. Cs-135 results in the largest dose (8.4E-7 mrem/y at 6.1E+6 y) while Np-237 gives the largest dose from the actinides (3.6E-8 mrem/y). The response of the model to parameter variations cannot be easily predicted due to non-linear coupling of many of the parameters. However, the calculated doses were negligibly low in all cases as were those resulting from the two scenario variations. (author)
Contaminant transport in aquifers: improving the determination of model parameters
Sabino, C.V.S.; Moreira, R.M.; Lula, Z.L.; Chausson, Y.; Magalhaes, W.F.; Vianna, M.N.
1998-01-01
Parameters conditioning the migration behavior of cesium and mercury are measured with their tracers 137 Cs and 203 Hg in the laboratory, using both batch and column experiments. Batch tests were used to define the sorption isotherm characteristics. Also investigated were the influences of some test parameters, in particular those due to the volume of water to mass of soil ratio (V/m). A provisional relationship between V/m and the distribution coefficient, K d , has been advanced, and a procedure to estimate K d 's valid for environmental values of the ratio V/m has been suggested. Column tests provided the parameters for a transport model. A major problem to be dealt with in such tests is the collimation of the radioactivity probe. Besides mechanically optimizing the collimator, a deconvolution procedure has been suggested and tested, with statistical criteria, to filter off both noise and spurious tracer signals. Correction procedures for the integrating effect introduced by sampling at the exit of columns have also been developed. These techniques may be helpful in increasing the accuracy required in the measurement of parameters conditioning contaminant migration in soils, thus allowing more reliable predictions based on mathematical model applications. (author)
Knecht, Damian; Jankowska-Mąkosa, Anna; Duziński, Kamil
2017-08-01
The aim of this study was a detailed analysis of the boar genotypes used in AI stations with an indication of their production capacity, including age and a precise analysis of their culling time and reason. The study included 334 boars: 81 Polish Large White (PLW), 108 Polish Landrace (PL), 49 Pietrain (P), 56 Duroc × Pietrain (D × P) and 40 Hampshire × Pietrain (H × P). Semen volume, spermatozoa concentration, total number of spermatozoa, number of motile spermatozoa, and number of insemination doses were analyzed. Quadratic regression was used to illustrate the selected sperm parameters at specific ages. Among all the studied boars the lowest motilities of spermatozoa were identified in white breeds PLW and PL, and the difference between motility extremes was 3.53% (P ≤ 0.01). The highest number of insemination doses were produced from D × P crossbreed boars: about 0.7 portions more compared to PL, 1.13 to PLW, 1.18 to H × P and 1.8 to P (all differences P ≤ 0.01). It has been shown in the case of ejaculate volume that for PLW and H × P boars the culling moment was far too early in terms of production capacity and differences were, respectively, 16.35 ml for PLW and 12.61 ml for H × P. Based on the developed regression equations, the earliest maximum number of motile sperm (73.82 × 10 9 ) was obtained by H × P crossbreed boars as early as at age 24 months. The highest values for this parameter were achieved, however, by other D × P crossbreed boars: 74.30 × 10 9 at the later age of 32 months. A consequence of the high number of motile sperm in young H × P boars was that the theoretical maximum value of the number of AI doses was produced as early as the 14th month (25.59 portions). Curves of similar shape were obtained for PL and D × P boars; the difference in maximal values was 0.54 portions in favor of crossbreeds, at a later age of 7 months. It was noted that for PLW and D × P boars the highest number
Progressive Learning of Topic Modeling Parameters: A Visual Analytics Framework.
El-Assady, Mennatallah; Sevastjanova, Rita; Sperrle, Fabian; Keim, Daniel; Collins, Christopher
2018-01-01
Topic modeling algorithms are widely used to analyze the thematic composition of text corpora but remain difficult to interpret and adjust. Addressing these limitations, we present a modular visual analytics framework, tackling the understandability and adaptability of topic models through a user-driven reinforcement learning process which does not require a deep understanding of the underlying topic modeling algorithms. Given a document corpus, our approach initializes two algorithm configurations based on a parameter space analysis that enhances document separability. We abstract the model complexity in an interactive visual workspace for exploring the automatic matching results of two models, investigating topic summaries, analyzing parameter distributions, and reviewing documents. The main contribution of our work is an iterative decision-making technique in which users provide a document-based relevance feedback that allows the framework to converge to a user-endorsed topic distribution. We also report feedback from a two-stage study which shows that our technique results in topic model quality improvements on two independent measures.
Propagation channel characterization, parameter estimation, and modeling for wireless communications
Yin, Xuefeng
2016-01-01
Thoroughly covering channel characteristics and parameters, this book provides the knowledge needed to design various wireless systems, such as cellular communication systems, RFID and ad hoc wireless communication systems. It gives a detailed introduction to aspects of channels before presenting the novel estimation and modelling techniques which can be used to achieve accurate models. To systematically guide readers through the topic, the book is organised in three distinct parts. The first part covers the fundamentals of the characterization of propagation channels, including the conventional single-input single-output (SISO) propagation channel characterization as well as its extension to multiple-input multiple-output (MIMO) cases. Part two focuses on channel measurements and channel data post-processing. Wideband channel measurements are introduced, including the equipment, technology and advantages and disadvantages of different data acquisition schemes. The channel parameter estimation methods are ...
Empirical flow parameters : a tool for hydraulic model validity
Asquith, William H.; Burley, Thomas E.; Cleveland, Theodore G.
2013-01-01
The objectives of this project were (1) To determine and present from existing data in Texas, relations between observed stream flow, topographic slope, mean section velocity, and other hydraulic factors, to produce charts such as Figure 1 and to produce empirical distributions of the various flow parameters to provide a methodology to "check if model results are way off!"; (2) To produce a statistical regional tool to estimate mean velocity or other selected parameters for storm flows or other conditional discharges at ungauged locations (most bridge crossings) in Texas to provide a secondary way to compare such values to a conventional hydraulic modeling approach. (3.) To present ancillary values such as Froude number, stream power, Rosgen channel classification, sinuosity, and other selected characteristics (readily determinable from existing data) to provide additional information to engineers concerned with the hydraulic-soil-foundation component of transportation infrastructure.
Characterisation and modelling of vacancy dynamics in Ni–Mn–Ga ferromagnetic shape memory alloys
Merida, D., E-mail: david.merida@ehu.es [Fisika Aplikatua II Saila, Euskal Herriko Unibertsitatea UPV/EHU, p.k. 644, 48080 Bilbao (Spain); Elektrizitate eta Elektronika Saila, Euskal Herriko Unibertsitatea UPV/EHU, p.k. 644, 48080 Bilbao (Spain); García, J.A. [Fisika Aplikatua II Saila, Euskal Herriko Unibertsitatea UPV/EHU, p.k. 644, 48080 Bilbao (Spain); BC Materials (Basque Centre for Materials, Application and Nanostructures), 48040 Leioa (Spain); Sánchez-Alarcos, V. [Departamento de Física, Universidad Pública de Navarra, Campus de Arrosadia, 31006 Pamplona (Spain); Pérez-Landazábal, J.I.; Recarte, V. [Departamento de Física, Universidad Pública de Navarra, Campus de Arrosadia, 31006 Pamplona (Spain); Institute for Advanced Materials (INAMAT), Universidad Pública de Navarra, Campus de Arrosadía, 31006 Pamplona (Spain); Plazaola, F. [Elektrizitate eta Elektronika Saila, Euskal Herriko Unibertsitatea UPV/EHU, p.k. 644, 48080 Bilbao (Spain)
2015-08-05
Highlights: • We study the dynamics of vacancies for three different Ni–Mn–Ga alloy samples. • The formation and migration energies have been obtained experimentally. • The entropic factor and the distance a vacancy has to reach a sink are measured. • We present a theoretical model to explain the dynamics of vacancies. • Results are applicable for any thermal treatment and extensible to other alloys. - Abstract: The dynamics of vacancies in Ni–Mn–Ga shape memory alloys has been studied by positron annihilation lifetime spectroscopy. The temperature evolution of the vacancy concentration for three different Ni–Mn–Ga samples, two polycrystalline and one monocrystalline, have been determined. The formation and migration energies and the entropic factors are quite similar in all cases, but vary slightly according to composition. However, the number of jumps a vacancy has to overtake to reach a sink is five times higher in the single crystal. This is an expected result, due to the role that surfaces and grain boundaries should play in balancing the vacancy concentration. In all cases, the initial vacancy concentration for the samples quenched from 1173 K lies between 1000 ppm and 2000 ppm. A phenomenological model able to explain the dynamics of vacancies has been developed in terms of the previous parameters. The model can reproduce the vacancy dynamics for any different kind of thermal history and can be easily extended to other alloys.
Numerical evidence of liquid crystalline mesophases of a lollipop shaped model in two dimensions
Pérez-Lemus, G. R.; Armas-Pérez, J. C.; Chapela, G. A.; Quintana-H., J.
2017-12-01
Small alterations in the molecular details may produce noticeable changes in the symmetry of the resulting phase behavior. It is possible to produce morphologies having different n-fold symmetries by manipulating molecular features such as chirality, polarity or anisotropy. In this paper, a two dimensional hard molecular model is introduced to study the formation of liquid crystalline phases in low dimensionality. The model is similar to that reported by Julio C. Armas-Pérez and Jacqueline Quintana-H., Phys. Rev. E 83, 051709 (2011). The main difference is the lack of chirality in the model proposed, although they share some characteristics like the geometrical polarity. Our model is called a lollipop model, because its shape is constructed by a rounded section attached to the end of a stick. Contrary to what happens in three dimensions where chiral nematogens produce interesting and complex phases such as blue phases, the lack of molecular chirality of our model generates a richer phase diagram compared to the chiral system. We show numerical and some geometrical evidences that the lack of laterality of the non chiral model seems to provide more routes of molecular self-assembly, producing triatic, a random cluster and possibly a tetratic phase behavior which were not presented in the previous work. We support our conclusions using results obtained from isobaric and isochoric Monte Carlo simulations. Properties as the n-fold order parameters such as the nematic, tetratic and triatic as well as their correlation functions were used to characterize the phases. We also provide the Fourier transform of equilibrium configurations to analyze the n-fold symmetry characteristic of each phase.
Hussain, Faraz; Jha, Sumit K; Jha, Susmit; Langmead, Christopher J
2014-01-01
Stochastic models are increasingly used to study the behaviour of biochemical systems. While the structure of such models is often readily available from first principles, unknown quantitative features of the model are incorporated into the model as parameters. Algorithmic discovery of parameter values from experimentally observed facts remains a challenge for the computational systems biology community. We present a new parameter discovery algorithm that uses simulated annealing, sequential hypothesis testing, and statistical model checking to learn the parameters in a stochastic model. We apply our technique to a model of glucose and insulin metabolism used for in-silico validation of artificial pancreata and demonstrate its effectiveness by developing parallel CUDA-based implementation for parameter synthesis in this model.
Estimation of Kinetic Parameters in an Automotive SCR Catalyst Model
Åberg, Andreas; Widd, Anders; Abildskov, Jens
2016-01-01
be used directly for accurate full-scale transient simulations. The model was validated against full-scale data with an engine following the European Transient Cycle. The validation showed that the predictive capability for nitrogen oxides (NOx) was satisfactory. After re-estimation of the adsorption...... and desorption parameters with full-scale transient data, the fit for both NOx and NH3-slip was satisfactory....
Mathematical models to predict rheological parameters of lateritic hydromixtures
Gabriel Hernández-Ramírez; Arístides A. Legrá-Lobaina; Beatriz Ramírez-Serrano; Liudmila Pérez-García
2017-01-01
The present work had as objective to establish mathematical models that allow the prognosis of the rheological parameters of the lateritic pulp at concentrations of solids from 35% to 48%, temperature of the preheated hydromixture superior to 82 ° C and number of mineral between 3 and 16. Four samples of lateritic pulp were used in the study at different process locations. The results allowed defining that the plastic properties of the lateritic pulp in the conditions of this study conform to...
Chou, H.-M.
2003-01-01
The heat transfer characteristics for an insulated regular polygonal (or circular) pipe are investigated by using a wedge thermal resistance model as well as the interior area thermal resistance model R th =t/K s /[(1-α)A 2 +αA 3 ] with a surface area weighting factor α. The errors of the results generated by an interior area model can be obtained by comparing with the exact results generated by a wedge model. Accurate heat transfer rates can be obtained without error at the optimum α opt with the related t/R 2 . The relation between α opt and t/R 2 is α opt =1/ln(1+t/R 2 )-1/(t/R 2 ). The value of α opt is greater than zero and less than 0.5 and is independent of pipe size R 2 /R cr but strongly dependent on the insulation thickness t/R 2 . The interior area model using the optimum value α opt with the related t/R 2 should also be applied to an insulated pipe with arbitrary shape within a very small amount of error for the results of heat transfer rates. The parameter R 2 conservatively corresponds to the outside radius of the maximum inside tangent circular pipe within the arbitrary shaped pipes. The approximate dimensionless critical thickness t cr /R 2 and neutral thickness t e /R 2 of an insulated pipe with arbitrary shape are also obtained. The accuracies of the value of t cr /R 2 as well as t e /R 2 are strongly dependent on the shape of the insulated small pipe. The closer the shape of an insulated pipe is to a regular polygonal or circular pipe, the more reliable will the values of t cr /R 2 as well as t e /R 2 be
Correction tool for Active Shape Model based lumbar muscle segmentation.
Valenzuela, Waldo; Ferguson, Stephen J; Ignasiak, Dominika; Diserens, Gaelle; Vermathen, Peter; Boesch, Chris; Reyes, Mauricio
2015-08-01
In the clinical environment, accuracy and speed of the image segmentation process plays a key role in the analysis of pathological regions. Despite advances in anatomic image segmentation, time-effective correction tools are commonly needed to improve segmentation results. Therefore, these tools must provide faster corrections with a low number of interactions, and a user-independent solution. In this work we present a new interactive correction method for correcting the image segmentation. Given an initial segmentation and the original image, our tool provides a 2D/3D environment, that enables 3D shape correction through simple 2D interactions. Our scheme is based on direct manipulation of free form deformation adapted to a 2D environment. This approach enables an intuitive and natural correction of 3D segmentation results. The developed method has been implemented into a software tool and has been evaluated for the task of lumbar muscle segmentation from Magnetic Resonance Images. Experimental results show that full segmentation correction could be performed within an average correction time of 6±4 minutes and an average of 68±37 number of interactions, while maintaining the quality of the final segmentation result within an average Dice coefficient of 0.92±0.03.
Mathematical properties and parameter estimation for transit compartment pharmacodynamic models.
Yates, James W T
2008-07-03
One feature of recent research in pharmacodynamic modelling has been the move towards more mechanistically based model structures. However, in all of these models there are common sub-systems, such as feedback loops and time-delays, whose properties and contribution to the model behaviour merit some mathematical analysis. In this paper a common pharmacodynamic model sub-structure is considered: the linear transit compartment. These models have a number of interesting properties as the length of the cascade chain is increased. In the limiting case a pure time-delay is achieved [Milsum, J.H., 1966. Biological Control Systems Analysis. McGraw-Hill Book Company, New York] and the initial behaviour becoming increasingly sensitive to parameter value perturbation. It is also shown that the modelled drug effect is attenuated, though the duration of action is longer. Through this analysis the range of behaviours that such models are capable of reproducing are characterised. The properties of these models and the experimental requirements are discussed in order to highlight how mathematical analysis prior to experimentation can enhance the utility of mathematical modelling.
Buryi, E V; Kosygin, A A
2004-01-01
It is shown that, when the angular resolution of a receiving optical system is insufficient, the angular dimensions of a located object can be estimated and its shape can be reconstructed by estimating the parameters of the fourth-order correlation function (CF) of scattered coherent radiation. The reliability of the estimates of CF counts obtained by the method of a discrete spatial convolution of the intensity-field counts, the possibility of estimating the CF profile counts by the method of one-dimensional convolution of intensity counts, and the applicability of the method for reconstructing the object shape are confirmed experimentally. (laser applications and other topics in quantum electronics)
Mathematical modelling of the viable epidermis: impact of cell shape and vertical arrangement
Wittum, Rebecca; Naegel, Arne; Heisig, Michael; Wittum, Gabriel
2017-01-01
In-silico methods are valuable tools for understanding the barrier function of the skin. The key benefit is that mathematical modelling allows the interplay between cell shape and function to be elucidated. This study focuses on the viable (living
A phenomenological two-phase constitutive model for porous shape memory alloys
El Sayed, Tamer S.; Gurses, Ercan; Siddiq, Amir Mohammed
2012-01-01
, application of the presented constitutive model has been presented by performing finite element simulations of the deformation and failure in unaixial dog-bone shaped specimen and compact tension (CT) test specimen. Results show a good agreement
A Preisach type model for temperature driven hysteresis memory erasure in shape memory materials
Kopfová, J.; Krejčí, P. (Pavel)
2011-01-01
We establish the well-posedness and thermodynamic consistency of a variational inequality modeling temperature-induced memory erasure in shape memory materials. It is shown that the input-output operator is continuous with respect to uniform convergence.
James, P.
2011-12-01
With a growing need for housing in the U.K., the government has proposed increased development of brownfield sites. However, old mine workings and natural cavities represent a potential hazard before, during and after construction on such sites, and add further complication to subsurface parameters. Cavities are hence a limitation to certain redevelopment and their detection is an ever important consideration. The current standard technique for cavity detection is a borehole grid, which is intrusive, non-continuous, slow and expensive. A new robust investigation standard in the detection of cavities is sought and geophysical techniques offer an attractive alternative. Geophysical techniques have previously been utilised successfully in the detection of cavities in various geologies, but still has an uncertain reputation in the engineering industry. Engineers are unsure of the techniques and are inclined to rely on well known techniques than utilise new technologies. Bad experiences with geophysics are commonly due to the indiscriminate choice of particular techniques. It is imperative that a geophysical survey is designed with the specific site and target in mind at all times, and the ability and judgement to rule out some, or all, techniques. To this author's knowledge no comparative software exists to aid technique choice. Also, previous modelling software limit the shapes of bodies and hence typical cavity shapes are not represented. Here, we introduce 3D modelling software (Matlab) which computes and compares the response to various cavity targets from a range of techniques (gravity, gravity gradient, magnetic, magnetic gradient and GPR). Typical near surface cavity shapes are modelled including shafts, bellpits, various lining and capping materials, and migrating voids. The probability of cavity detection is assessed in typical subsurface and noise conditions across a range of survey parameters. Techniques can be compared and the limits of detection distance
Cui, J; Kratz, K; Lendlein, A
2010-01-01
Various composites have been prepared to improve the mechanical properties of shape-memory polymers (SMPs) or to incorporate new functionalities (e.g. magneto-sensitivity) in polymer matrices. In this paper, we systematically investigated the influence of the programming temperature T prog and the applied strain ε m as parameters of the shape-memory creation procedure (SMCP) on the shape-memory properties of an amorphous polyether urethane and radio-opaque composites thereof. Recovery under stress-free conditions was quantified by the shape recovery rate R r and the switching temperature T sw , while the maximum recovery stress σ max was determined at the characteristic temperature T σ,max under constant strain conditions. Excellent shape-memory properties were achieved in all experiments with R r values in between 80 and 98%. σ max could be tailored from 0.4 to 3.7 MPa. T sw and T σ,max could be systematically adjusted from 33 to 71 °C by variation of T prog for each investigated sample. The investigated radio-opaque shape-memory composites will form the material basis for mechanically active scaffolds, which could serve as an intelligent substitute for the extracellular matrix to study the influence of mechanical stimulation of tissue development
Guo, Yiting; Dong, Bin; Wang, Bing; Xie, Hongzhi; Zhang, Shuyang; Gu, Lixu
2014-01-01
Purpose: Effective and accurate segmentation of the aortic valve (AV) from sequenced ultrasound (US) images remains a technical challenge because of intrinsic factors of ultrasound images that impact the quality and the continuous changes of shape and position of segmented objects. In this paper, a novel shape-constraint gradient Chan-Vese (GCV) model is proposed for segmenting the AV from time serial echocardiography. Methods: The GCV model is derived by incorporating the energy of the gradient vector flow into a CV model framework, where the gradient vector energy term is introduced by calculating the deviation angle between the inward normal force of the evolution contour and the gradient vector force. The flow force enlarges the capture range and enhances the blurred boundaries of objects. This is achieved by adding a circle-like contour (constructed using the AV structure region as a constraint shape) as an energy item to the GCV model through the shape comparison function. This shape-constrained energy can enhance the image constraint force by effectively connecting separate gaps of the object edge as well as driving the evolution contour to quickly approach the ideal object. Because of the slight movement of the AV in adjacent frames, the initial constraint shape is defined by users, with the other constraint shapes being derived from the segmentation results of adjacent sequence frames after morphological filtering. The AV is segmented from the US images by minimizing the proposed energy function. Results: To evaluate the performance of the proposed method, five assessment parameters were used to compare it with manual delineations performed by radiologists (gold standards). Three hundred and fifteen images acquired from nine groups were analyzed in the experiment. The area-metric overlap error rate was 6.89% ± 2.88%, the relative area difference rate 3.94% ± 2.63%, the average symmetric contour distance 1.08 ± 0.43 mm, the root mean square symmetric
Guo, Yiting [Multi-disciplinary Research Center, Hebei University, Baoding 071000 (China); Dong, Bin [Hebei University Affiliated Hospital, Hebei Baoding 071000 (China); Wang, Bing [College of Mathematics and Computer Science, Hebei University, Baoding 071000 (China); Xie, Hongzhi, E-mail: xiehongzhi@medmail.com.cn, E-mail: gulixu@sjtu.edu.cn; Zhang, Shuyang [Department of Cardiovascular, Peking Union Medical College Hospital, Beijing 100005 (China); Gu, Lixu, E-mail: xiehongzhi@medmail.com.cn, E-mail: gulixu@sjtu.edu.cn [Multi-disciplinary Research Center, Hebei University, Baoding 071000, China and School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai 200030 (China)
2014-07-15
Purpose: Effective and accurate segmentation of the aortic valve (AV) from sequenced ultrasound (US) images remains a technical challenge because of intrinsic factors of ultrasound images that impact the quality and the continuous changes of shape and position of segmented objects. In this paper, a novel shape-constraint gradient Chan-Vese (GCV) model is proposed for segmenting the AV from time serial echocardiography. Methods: The GCV model is derived by incorporating the energy of the gradient vector flow into a CV model framework, where the gradient vector energy term is introduced by calculating the deviation angle between the inward normal force of the evolution contour and the gradient vector force. The flow force enlarges the capture range and enhances the blurred boundaries of objects. This is achieved by adding a circle-like contour (constructed using the AV structure region as a constraint shape) as an energy item to the GCV model through the shape comparison function. This shape-constrained energy can enhance the image constraint force by effectively connecting separate gaps of the object edge as well as driving the evolution contour to quickly approach the ideal object. Because of the slight movement of the AV in adjacent frames, the initial constraint shape is defined by users, with the other constraint shapes being derived from the segmentation results of adjacent sequence frames after morphological filtering. The AV is segmented from the US images by minimizing the proposed energy function. Results: To evaluate the performance of the proposed method, five assessment parameters were used to compare it with manual delineations performed by radiologists (gold standards). Three hundred and fifteen images acquired from nine groups were analyzed in the experiment. The area-metric overlap error rate was 6.89% ± 2.88%, the relative area difference rate 3.94% ± 2.63%, the average symmetric contour distance 1.08 ± 0.43 mm, the root mean square symmetric
Estimation Parameters And Modelling Zero Inflated Negative Binomial
Cindy Cahyaning Astuti
2016-11-01
Full Text Available Regression analysis is used to determine relationship between one or several response variable (Y with one or several predictor variables (X. Regression model between predictor variables and the Poisson distributed response variable is called Poisson Regression Model. Since, Poisson Regression requires an equality between mean and variance, it is not appropriate to apply this model on overdispersion (variance is higher than mean. Poisson regression model is commonly used to analyze the count data. On the count data type, it is often to encounteredd some observations that have zero value with large proportion of zero value on the response variable (zero Inflation. Poisson regression can be used to analyze count data but it has not been able to solve problem of excess zero value on the response variable. An alternative model which is more suitable for overdispersion data and can solve the problem of excess zero value on the response variable is Zero Inflated Negative Binomial (ZINB. In this research, ZINB is applied on the case of Tetanus Neonatorum in East Java. The aim of this research is to examine the likelihood function and to form an algorithm to estimate the parameter of ZINB and also applying ZINB model in the case of Tetanus Neonatorum in East Java. Maximum Likelihood Estimation (MLE method is used to estimate the parameter on ZINB and the likelihood function is maximized using Expectation Maximization (EM algorithm. Test results of ZINB regression model showed that the predictor variable have a partial significant effect at negative binomial model is the percentage of pregnant women visits and the percentage of maternal health personnel assisted, while the predictor variables that have a partial significant effect at zero inflation model is the percentage of neonatus visits.
COMPREHENSIVE CHECK MEASUREMENT OF KEY PARAMETERS ON MODEL BELT CONVEYOR
Vlastimil MONI
2013-07-01
Full Text Available Complex measurements of characteristic parameters realised on a long distance model belt conveyor are described. The main objective was to complete and combine the regular measurements of electric power on drives of belt conveyors operated in Czech opencast mines with measurements of other physical quantities and to gain by this way an image of their mutual relations and relations of quantities derived from them. The paper includes a short description and results of the measurements on an experimental model conveyor with a closed material transport way.
Information Theoretic Tools for Parameter Fitting in Coarse Grained Models
Kalligiannaki, Evangelia
2015-01-07
We study the application of information theoretic tools for model reduction in the case of systems driven by stochastic dynamics out of equilibrium. The model/dimension reduction is considered by proposing parametrized coarse grained dynamics and finding the optimal parameter set for which the relative entropy rate with respect to the atomistic dynamics is minimized. The minimization problem leads to a generalization of the force matching methods to non equilibrium systems. A multiplicative noise example reveals the importance of the diffusion coefficient in the optimization problem.
Surrogate based approaches to parameter inference in ocean models
Knio, Omar
2016-01-06
This talk discusses the inference of physical parameters using model surrogates. Attention is focused on the use of sampling schemes to build suitable representations of the dependence of the model response on uncertain input data. Non-intrusive spectral projections and regularized regressions are used for this purpose. A Bayesian inference formalism is then applied to update the uncertain inputs based on available measurements or observations. To perform the update, we consider two alternative approaches, based on the application of Markov Chain Monte Carlo methods or of adjoint-based optimization techniques. We outline the implementation of these techniques to infer dependence of wind drag, bottom drag, and internal mixing coefficients.
Surrogate based approaches to parameter inference in ocean models
Knio, Omar
2016-01-01
This talk discusses the inference of physical parameters using model surrogates. Attention is focused on the use of sampling schemes to build suitable representations of the dependence of the model response on uncertain input data. Non-intrusive spectral projections and regularized regressions are used for this purpose. A Bayesian inference formalism is then applied to update the uncertain inputs based on available measurements or observations. To perform the update, we consider two alternative approaches, based on the application of Markov Chain Monte Carlo methods or of adjoint-based optimization techniques. We outline the implementation of these techniques to infer dependence of wind drag, bottom drag, and internal mixing coefficients.
Cheimariotis, Grigorios-Aris; Al-Mashat, Mariam; Haris, Kostas; Aletras, Anthony H; Jögi, Jonas; Bajc, Marika; Maglaveras, Nicolaos; Heiberg, Einar
2018-02-01
Image segmentation is an essential step in quantifying the extent of reduced or absent lung function. The aim of this study is to develop and validate a new tool for automatic segmentation of lungs in ventilation and perfusion SPECT images and compare automatic and manual SPECT lung segmentations with reference computed tomography (CT) volumes. A total of 77 subjects (69 patients with obstructive lung disease, and 8 subjects without apparent perfusion of ventilation loss) performed low-dose CT followed by ventilation/perfusion (V/P) SPECT examination in a hybrid gamma camera system. In the training phase, lung shapes from the 57 anatomical low-dose CT images were used to construct two active shape models (right lung and left lung) which were then used for image segmentation. The algorithm was validated in 20 patients, comparing its results to reference delineation of corresponding CT images, and by comparing automatic segmentation to manual delineations in SPECT images. The Dice coefficient between automatic SPECT delineations and manual SPECT delineations were 0.83 ± 0.04% for the right and 0.82 ± 0.05% for the left lung. There was statistically significant difference between reference volumes from CT and automatic delineations for the right (R = 0.53, p = 0.02) and left lung (R = 0.69, p automatic quantification of wide range of measurements.
Kim, Kyung Yong; Lee, Won-Chan
2017-01-01
This article provides a detailed description of three factors (specification of the ability distribution, numerical integration, and frame of reference for the item parameter estimates) that might affect the item parameter estimation of the three-parameter logistic model, and compares five item calibration methods, which are combinations of the…