Accurate lithography simulation model based on convolutional neural networks
Watanabe, Yuki; Kimura, Taiki; Matsunawa, Tetsuaki; Nojima, Shigeki
2017-07-01
Lithography simulation is an essential technique for today's semiconductor manufacturing process. In order to calculate an entire chip in realistic time, compact resist model is commonly used. The model is established for faster calculation. To have accurate compact resist model, it is necessary to fix a complicated non-linear model function. However, it is difficult to decide an appropriate function manually because there are many options. This paper proposes a new compact resist model using CNN (Convolutional Neural Networks) which is one of deep learning techniques. CNN model makes it possible to determine an appropriate model function and achieve accurate simulation. Experimental results show CNN model can reduce CD prediction errors by 70% compared with the conventional model.
An Accurate and Dynamic Computer Graphics Muscle Model
Levine, David Asher
1997-01-01
A computer based musculo-skeletal model was developed at the University in the departments of Mechanical and Biomedical Engineering. This model accurately represents human shoulder kinematics. The result of this model is the graphical display of bones moving through an appropriate range of motion based on inputs of EMGs and external forces. The need existed to incorporate a geometric muscle model in the larger musculo-skeletal model. Previous muscle models did not accurately represent muscle geometries, nor did they account for the kinematics of tendons. This thesis covers the creation of a new muscle model for use in the above musculo-skeletal model. This muscle model was based on anatomical data from the Visible Human Project (VHP) cadaver study. Two-dimensional digital images from the VHP were analyzed and reconstructed to recreate the three-dimensional muscle geometries. The recreated geometries were smoothed, reduced, and sliced to form data files defining the surfaces of each muscle. The muscle modeling function opened these files during run-time and recreated the muscle surface. The modeling function applied constant volume limitations to the muscle and constant geometry limitations to the tendons.
Mental models accurately predict emotion transitions.
Thornton, Mark A; Tamir, Diana I
2017-06-06
Successful social interactions depend on people's ability to predict others' future actions and emotions. People possess many mechanisms for perceiving others' current emotional states, but how might they use this information to predict others' future states? We hypothesized that people might capitalize on an overlooked aspect of affective experience: current emotions predict future emotions. By attending to regularities in emotion transitions, perceivers might develop accurate mental models of others' emotional dynamics. People could then use these mental models of emotion transitions to predict others' future emotions from currently observable emotions. To test this hypothesis, studies 1-3 used data from three extant experience-sampling datasets to establish the actual rates of emotional transitions. We then collected three parallel datasets in which participants rated the transition likelihoods between the same set of emotions. Participants' ratings of emotion transitions predicted others' experienced transitional likelihoods with high accuracy. Study 4 demonstrated that four conceptual dimensions of mental state representation-valence, social impact, rationality, and human mind-inform participants' mental models. Study 5 used 2 million emotion reports on the Experience Project to replicate both of these findings: again people reported accurate models of emotion transitions, and these models were informed by the same four conceptual dimensions. Importantly, neither these conceptual dimensions nor holistic similarity could fully explain participants' accuracy, suggesting that their mental models contain accurate information about emotion dynamics above and beyond what might be predicted by static emotion knowledge alone.
Mental models accurately predict emotion transitions
Thornton, Mark A.; Tamir, Diana I.
2017-01-01
Successful social interactions depend on people’s ability to predict others’ future actions and emotions. People possess many mechanisms for perceiving others’ current emotional states, but how might they use this information to predict others’ future states? We hypothesized that people might capitalize on an overlooked aspect of affective experience: current emotions predict future emotions. By attending to regularities in emotion transitions, perceivers might develop accurate mental models of others’ emotional dynamics. People could then use these mental models of emotion transitions to predict others’ future emotions from currently observable emotions. To test this hypothesis, studies 1–3 used data from three extant experience-sampling datasets to establish the actual rates of emotional transitions. We then collected three parallel datasets in which participants rated the transition likelihoods between the same set of emotions. Participants’ ratings of emotion transitions predicted others’ experienced transitional likelihoods with high accuracy. Study 4 demonstrated that four conceptual dimensions of mental state representation—valence, social impact, rationality, and human mind—inform participants’ mental models. Study 5 used 2 million emotion reports on the Experience Project to replicate both of these findings: again people reported accurate models of emotion transitions, and these models were informed by the same four conceptual dimensions. Importantly, neither these conceptual dimensions nor holistic similarity could fully explain participants’ accuracy, suggesting that their mental models contain accurate information about emotion dynamics above and beyond what might be predicted by static emotion knowledge alone. PMID:28533373
A new, accurate predictive model for incident hypertension
DEFF Research Database (Denmark)
Völzke, Henry; Fung, Glenn; Ittermann, Till
2013-01-01
Data mining represents an alternative approach to identify new predictors of multifactorial diseases. This work aimed at building an accurate predictive model for incident hypertension using data mining procedures.......Data mining represents an alternative approach to identify new predictors of multifactorial diseases. This work aimed at building an accurate predictive model for incident hypertension using data mining procedures....
Bilinear reduced order approximate model of parabolic distributed solar collectors
Elmetennani, Shahrazed; Laleg-Kirati, Taous-Meriem
2015-01-01
This paper proposes a novel, low dimensional and accurate approximate model for the distributed parabolic solar collector, by means of a modified gaussian interpolation along the spatial domain. The proposed reduced model, taking the form of a low
Nonlinear thermal reduced model for Microwave Circuit Analysis
Chang, Christophe; Sommet, Raphael; Quéré, Raymond; Dueme, Ph.
2004-01-01
With the constant increase of transistor power density, electro thermal modeling is becoming a necessity for accurate prediction of device electrical performances. For this reason, this paper deals with a methodology to obtain a precise nonlinear thermal model based on Model Order Reduction of a three dimensional thermal Finite Element (FE) description. This reduced thermal model is based on the Ritz vector approach which ensure the steady state solution in every case. An equi...
Noyes, Ben F.; Mokaberi, Babak; Mandoy, Ram; Pate, Alex; Huijgen, Ralph; McBurney, Mike; Chen, Owen
2017-03-01
Reducing overlay error via an accurate APC feedback system is one of the main challenges in high volume production of the current and future nodes in the semiconductor industry. The overlay feedback system directly affects the number of dies meeting overlay specification and the number of layers requiring dedicated exposure tools through the fabrication flow. Increasing the former number and reducing the latter number is beneficial for the overall efficiency and yield of the fabrication process. An overlay feedback system requires accurate determination of the overlay error, or fingerprint, on exposed wafers in order to determine corrections to be automatically and dynamically applied to the exposure of future wafers. Since current and future nodes require correction per exposure (CPE), the resolution of the overlay fingerprint must be high enough to accommodate CPE in the overlay feedback system, or overlay control module (OCM). Determining a high resolution fingerprint from measured data requires extremely dense overlay sampling that takes a significant amount of measurement time. For static corrections this is acceptable, but in an automated dynamic correction system this method creates extreme bottlenecks for the throughput of said system as new lots have to wait until the previous lot is measured. One solution is using a less dense overlay sampling scheme and employing computationally up-sampled data to a dense fingerprint. That method uses a global fingerprint model over the entire wafer; measured localized overlay errors are therefore not always represented in its up-sampled output. This paper will discuss a hybrid system shown in Fig. 1 that combines a computationally up-sampled fingerprint with the measured data to more accurately capture the actual fingerprint, including local overlay errors. Such a hybrid system is shown to result in reduced modelled residuals while determining the fingerprint, and better on-product overlay performance.
Vascular stents: Coupling full 3-D with reduced-order structural models
International Nuclear Information System (INIS)
Avdeev, I; Shams, M
2010-01-01
Self-expanding nitinol stents are used to treat peripheral arterial disease. The peripheral arteries are subjected to a combination of mechanical forces such as compression, torsion, bending, and contraction. Most commercially available peripheral self-expanding stents are composed of a series of sub-millimeter V-shaped struts, which are laser-cut from a nitinol tube and surface-treated for better fatigue performance. The numerical stent models must accurately predict location and distribution of local stresses and strains caused by large arterial deformations. Full 3-D finite element non-linear analysis of an entire stent is computationally expensive to the point of being prohibitive, especially for longer stents. Reduced-order models based on beam or shell elements are fairly accurate in capturing global deformations, but are not very helpful in predicting stent failure. We propose a mixed approach that combines the full 3-D model and reduced-order models. Several global-local, full 3-D/reduced-order finite element models of a peripheral self-expanding stent were validated and compared with experimental data. The kinematic constraint method used to couple various elements together was found to be very efficient and easily applicable to commercial FEA codes. The proposed mixed models can be used to accurately predict stent failure based on realistic (patient-specific), non-linear kinematic behavior of peripheral arteries.
Anatomically accurate, finite model eye for optical modeling.
Liou, H L; Brennan, N A
1997-08-01
There is a need for a schematic eye that models vision accurately under various conditions such as refractive surgical procedures, contact lens and spectacle wear, and near vision. Here we propose a new model eye close to anatomical, biometric, and optical realities. This is a finite model with four aspheric refracting surfaces and a gradient-index lens. It has an equivalent power of 60.35 D and an axial length of 23.95 mm. The new model eye provides spherical aberration values within the limits of empirical results and predicts chromatic aberration for wavelengths between 380 and 750 nm. It provides a model for calculating optical transfer functions and predicting optical performance of the eye.
HIGHLY-ACCURATE MODEL ORDER REDUCTION TECHNIQUE ON A DISCRETE DOMAIN
Directory of Open Access Journals (Sweden)
L. D. Ribeiro
2015-09-01
Full Text Available AbstractIn this work, we present a highly-accurate technique of model order reduction applied to staged processes. The proposed method reduces the dimension of the original system based on null values of moment-weighted sums of heat and mass balance residuals on real stages. To compute these sums of weighted residuals, a discrete form of Gauss-Lobatto quadrature was developed, allowing a high degree of accuracy in these calculations. The locations where the residuals are cancelled vary with time and operating conditions, characterizing a desirable adaptive nature of this technique. Balances related to upstream and downstream devices (such as condenser, reboiler, and feed tray of a distillation column are considered as boundary conditions of the corresponding difference-differential equations system. The chosen number of moments is the dimension of the reduced model being much lower than the dimension of the complete model and does not depend on the size of the original model. Scaling of the discrete independent variable related with the stages was crucial for the computational implementation of the proposed method, avoiding accumulation of round-off errors present even in low-degree polynomial approximations in the original discrete variable. Dynamical simulations of distillation columns were carried out to check the performance of the proposed model order reduction technique. The obtained results show the superiority of the proposed procedure in comparison with the orthogonal collocation method.
Reduced-Order Modeling for Flutter/LCO Using Recurrent Artificial Neural Network
Yao, Weigang; Liou, Meng-Sing
2012-01-01
The present study demonstrates the efficacy of a recurrent artificial neural network to provide a high fidelity time-dependent nonlinear reduced-order model (ROM) for flutter/limit-cycle oscillation (LCO) modeling. An artificial neural network is a relatively straightforward nonlinear method for modeling an input-output relationship from a set of known data, for which we use the radial basis function (RBF) with its parameters determined through a training process. The resulting RBF neural network, however, is only static and is not yet adequate for an application to problems of dynamic nature. The recurrent neural network method [1] is applied to construct a reduced order model resulting from a series of high-fidelity time-dependent data of aero-elastic simulations. Once the RBF neural network ROM is constructed properly, an accurate approximate solution can be obtained at a fraction of the cost of a full-order computation. The method derived during the study has been validated for predicting nonlinear aerodynamic forces in transonic flow and is capable of accurate flutter/LCO simulations. The obtained results indicate that the present recurrent RBF neural network is accurate and efficient for nonlinear aero-elastic system analysis
Reducing dose calculation time for accurate iterative IMRT planning
International Nuclear Information System (INIS)
Siebers, Jeffrey V.; Lauterbach, Marc; Tong, Shidong; Wu Qiuwen; Mohan, Radhe
2002-01-01
A time-consuming component of IMRT optimization is the dose computation required in each iteration for the evaluation of the objective function. Accurate superposition/convolution (SC) and Monte Carlo (MC) dose calculations are currently considered too time-consuming for iterative IMRT dose calculation. Thus, fast, but less accurate algorithms such as pencil beam (PB) algorithms are typically used in most current IMRT systems. This paper describes two hybrid methods that utilize the speed of fast PB algorithms yet achieve the accuracy of optimizing based upon SC algorithms via the application of dose correction matrices. In one method, the ratio method, an infrequently computed voxel-by-voxel dose ratio matrix (R=D SC /D PB ) is applied for each beam to the dose distributions calculated with the PB method during the optimization. That is, D PB xR is used for the dose calculation during the optimization. The optimization proceeds until both the IMRT beam intensities and the dose correction ratio matrix converge. In the second method, the correction method, a periodically computed voxel-by-voxel correction matrix for each beam, defined to be the difference between the SC and PB dose computations, is used to correct PB dose distributions. To validate the methods, IMRT treatment plans developed with the hybrid methods are compared with those obtained when the SC algorithm is used for all optimization iterations and with those obtained when PB-based optimization is followed by SC-based optimization. In the 12 patient cases studied, no clinically significant differences exist in the final treatment plans developed with each of the dose computation methodologies. However, the number of time-consuming SC iterations is reduced from 6-32 for pure SC optimization to four or less for the ratio matrix method and five or less for the correction method. Because the PB algorithm is faster at computing dose, this reduces the inverse planning optimization time for our implementation
A Reduced Order Model to Predict Transient Flows around Straight Bladed Vertical Axis Wind Turbines
Directory of Open Access Journals (Sweden)
Soledad Le Clainche
2018-03-01
Full Text Available We develop a reduced order model to represent the complex flow behaviour around vertical axis wind turbines. First, we simulate vertical axis turbines using an accurate high order discontinuous Galerkin–Fourier Navier–Stokes Large Eddy Simulation solver with sliding meshes and extract flow snapshots in time. Subsequently, we construct a reduced order model based on a high order dynamic mode decomposition approach that selects modes based on flow frequency. We show that only a few modes are necessary to reconstruct the flow behaviour of the original simulation, even for blades rotating in turbulent regimes. Furthermore, we prove that an accurate reduced order model can be constructed using snapshots that do not sample one entire turbine rotation (but only a fraction of it, which reduces the cost of generating the reduced order model. Additionally, we compare the reduced order model based on the high order Navier–Stokes solver to fast 2D simulations (using a Reynolds Averaged Navier–Stokes turbulent model to illustrate the good performance of the proposed methodology.
On nonlinear reduced order modeling
International Nuclear Information System (INIS)
Abdel-Khalik, Hany S.
2011-01-01
When applied to a model that receives n input parameters and predicts m output responses, a reduced order model estimates the variations in the m outputs of the original model resulting from variations in its n inputs. While direct execution of the forward model could provide these variations, reduced order modeling plays an indispensable role for most real-world complex models. This follows because the solutions of complex models are expensive in terms of required computational overhead, thus rendering their repeated execution computationally infeasible. To overcome this problem, reduced order modeling determines a relationship (often referred to as a surrogate model) between the input and output variations that is much cheaper to evaluate than the original model. While it is desirable to seek highly accurate surrogates, the computational overhead becomes quickly intractable especially for high dimensional model, n ≫ 10. In this manuscript, we demonstrate a novel reduced order modeling method for building a surrogate model that employs only 'local first-order' derivatives and a new tensor-free expansion to efficiently identify all the important features of the original model to reach a predetermined level of accuracy. This is achieved via a hybrid approach in which local first-order derivatives (i.e., gradient) of a pseudo response (a pseudo response represents a random linear combination of original model’s responses) are randomly sampled utilizing a tensor-free expansion around some reference point, with the resulting gradient information aggregated in a subspace (denoted by the active subspace) of dimension much less than the dimension of the input parameters space. The active subspace is then sampled employing the state-of-the-art techniques for global sampling methods. The proposed method hybridizes the use of global sampling methods for uncertainty quantification and local variational methods for sensitivity analysis. In a similar manner to
BWR stability using a reducing dynamical model
International Nuclear Information System (INIS)
Ballestrin Bolea, J. M.; Blazquez Martinez, J. B.
1990-01-01
BWR stability can be treated with reduced order dynamical models. When the parameters of the model came from dynamical models. When the parameters of the model came from experimental data, the predictions are accurate. In this work an alternative derivation for the void fraction equation is made, but remarking the physical structure of the parameters. As the poles of power/reactivity transfer function are related with the parameters, the measurement of the poles by other techniques such as noise analysis will lead to the parameters, but the system of equations is non-linear. Simple parametric calculation of decay ratio are performed, showing why BWRs become unstable when they are operated at low flow and high power. (Author)
Accurate modeling and maximum power point detection of ...
African Journals Online (AJOL)
Accurate modeling and maximum power point detection of photovoltaic ... Determination of MPP enables the PV system to deliver maximum available power. ..... adaptive artificial neural network: Proposition for a new sizing procedure.
Accurate Modeling Method for Cu Interconnect
Yamada, Kenta; Kitahara, Hiroshi; Asai, Yoshihiko; Sakamoto, Hideo; Okada, Norio; Yasuda, Makoto; Oda, Noriaki; Sakurai, Michio; Hiroi, Masayuki; Takewaki, Toshiyuki; Ohnishi, Sadayuki; Iguchi, Manabu; Minda, Hiroyasu; Suzuki, Mieko
This paper proposes an accurate modeling method of the copper interconnect cross-section in which the width and thickness dependence on layout patterns and density caused by processes (CMP, etching, sputtering, lithography, and so on) are fully, incorporated and universally expressed. In addition, we have developed specific test patterns for the model parameters extraction, and an efficient extraction flow. We have extracted the model parameters for 0.15μm CMOS using this method and confirmed that 10%τpd error normally observed with conventional LPE (Layout Parameters Extraction) was completely dissolved. Moreover, it is verified that the model can be applied to more advanced technologies (90nm, 65nm and 55nm CMOS). Since the interconnect delay variations due to the processes constitute a significant part of what have conventionally been treated as random variations, use of the proposed model could enable one to greatly narrow the guardbands required to guarantee a desired yield, thereby facilitating design closure.
BWR stability using a reduced dynamical model
International Nuclear Information System (INIS)
Ballestrin Bolea, J.M.; Blazquez, J.B.
1990-01-01
BWR stability can be treated with reduced order dynamical models. When the parameters of the model came from experimental data, the predictions are accurate. In this work an alternative derivation for the void fraction equation is made, but remarking the physical struct-ure of the parameters. As the poles of power/reactivity transfer function are related with the parameters, the measurement of the poles by other techniques such as noise analysis will lead to the parameters, but the system of equations in non-linear. Simple parametric calculat-ion of decay ratio are performed, showing why BWRs become unstable when they are operated at low flow and high power. (Author). 7 refs
Uncertainty Aware Structural Topology Optimization Via a Stochastic Reduced Order Model Approach
Aguilo, Miguel A.; Warner, James E.
2017-01-01
This work presents a stochastic reduced order modeling strategy for the quantification and propagation of uncertainties in topology optimization. Uncertainty aware optimization problems can be computationally complex due to the substantial number of model evaluations that are necessary to accurately quantify and propagate uncertainties. This computational complexity is greatly magnified if a high-fidelity, physics-based numerical model is used for the topology optimization calculations. Stochastic reduced order model (SROM) methods are applied here to effectively 1) alleviate the prohibitive computational cost associated with an uncertainty aware topology optimization problem; and 2) quantify and propagate the inherent uncertainties due to design imperfections. A generic SROM framework that transforms the uncertainty aware, stochastic topology optimization problem into a deterministic optimization problem that relies only on independent calls to a deterministic numerical model is presented. This approach facilitates the use of existing optimization and modeling tools to accurately solve the uncertainty aware topology optimization problems in a fraction of the computational demand required by Monte Carlo methods. Finally, an example in structural topology optimization is presented to demonstrate the effectiveness of the proposed uncertainty aware structural topology optimization approach.
Can phenological models predict tree phenology accurately under climate change conditions?
Chuine, Isabelle; Bonhomme, Marc; Legave, Jean Michel; García de Cortázar-Atauri, Inaki; Charrier, Guillaume; Lacointe, André; Améglio, Thierry
2014-05-01
The onset of the growing season of trees has been globally earlier by 2.3 days/decade during the last 50 years because of global warming and this trend is predicted to continue according to climate forecast. The effect of temperature on plant phenology is however not linear because temperature has a dual effect on bud development. On one hand, low temperatures are necessary to break bud dormancy, and on the other hand higher temperatures are necessary to promote bud cells growth afterwards. Increasing phenological changes in temperate woody species have strong impacts on forest trees distribution and productivity, as well as crops cultivation areas. Accurate predictions of trees phenology are therefore a prerequisite to understand and foresee the impacts of climate change on forests and agrosystems. Different process-based models have been developed in the last two decades to predict the date of budburst or flowering of woody species. They are two main families: (1) one-phase models which consider only the ecodormancy phase and make the assumption that endodormancy is always broken before adequate climatic conditions for cell growth occur; and (2) two-phase models which consider both the endodormancy and ecodormancy phases and predict a date of dormancy break which varies from year to year. So far, one-phase models have been able to predict accurately tree bud break and flowering under historical climate. However, because they do not consider what happens prior to ecodormancy, and especially the possible negative effect of winter temperature warming on dormancy break, it seems unlikely that they can provide accurate predictions in future climate conditions. It is indeed well known that a lack of low temperature results in abnormal pattern of bud break and development in temperate fruit trees. An accurate modelling of the dormancy break date has thus become a major issue in phenology modelling. Two-phases phenological models predict that global warming should delay
Identification of reduced-order model for an aeroelastic system from flutter test data
Directory of Open Access Journals (Sweden)
Wei Tang
2017-02-01
Full Text Available Recently, flutter active control using linear parameter varying (LPV framework has attracted a lot of attention. LPV control synthesis usually generates controllers that are at least of the same order as the aeroelastic models. Therefore, the reduced-order model is required by synthesis for avoidance of large computation cost and high-order controller. This paper proposes a new procedure for generation of accurate reduced-order linear time-invariant (LTI models by using system identification from flutter testing data. The proposed approach is in two steps. The well-known poly-reference least squares complex frequency (p-LSCF algorithm is firstly employed for modal parameter identification from frequency response measurement. After parameter identification, the dominant physical modes are determined by clear stabilization diagrams and clustering technique. In the second step, with prior knowledge of physical poles, the improved frequency-domain maximum likelihood (ML estimator is presented for building accurate reduced-order model. Before ML estimation, an improved subspace identification considering the poles constraint is also proposed for initializing the iterative procedure. Finally, the performance of the proposed procedure is validated by real flight flutter test data.
Directory of Open Access Journals (Sweden)
J. Wohlfeil
2012-07-01
Full Text Available Modern pixel-wise image matching algorithms like Semi-Global Matching (SGM are able to compute high resolution digital surface models from airborne and spaceborne stereo imagery. Although image matching itself can be performed automatically, there are prerequisites, like high geometric accuracy, which are essential for ensuring the high quality of resulting surface models. Especially for line cameras, these prerequisites currently require laborious manual interaction using standard tools, which is a growing problem due to continually increasing demand for such surface models. The tedious work includes partly or fully manual selection of tie- and/or ground control points for ensuring the required accuracy of the relative orientation of images for stereo matching. It also includes masking of large water areas that seriously reduce the quality of the results. Furthermore, a good estimate of the depth range is required, since accurate estimates can seriously reduce the processing time for stereo matching. In this paper an approach is presented that allows performing all these steps fully automated. It includes very robust and precise tie point selection, enabling the accurate calculation of the images’ relative orientation via bundle adjustment. It is also shown how water masking and elevation range estimation can be performed automatically on the base of freely available SRTM data. Extensive tests with a large number of different satellite images from QuickBird and WorldView are presented as proof of the robustness and reliability of the proposed method.
Simple, fast and accurate two-diode model for photovoltaic modules
Energy Technology Data Exchange (ETDEWEB)
Ishaque, Kashif; Salam, Zainal; Taheri, Hamed [Faculty of Electrical Engineering, Universiti Teknologi Malaysia, UTM 81310, Skudai, Johor Bahru (Malaysia)
2011-02-15
This paper proposes an improved modeling approach for the two-diode model of photovoltaic (PV) module. The main contribution of this work is the simplification of the current equation, in which only four parameters are required, compared to six or more in the previously developed two-diode models. Furthermore the values of the series and parallel resistances are computed using a simple and fast iterative method. To validate the accuracy of the proposed model, six PV modules of different types (multi-crystalline, mono-crystalline and thin-film) from various manufacturers are tested. The performance of the model is evaluated against the popular single diode models. It is found that the proposed model is superior when subjected to irradiance and temperature variations. In particular the model matches very accurately for all important points of the I-V curves, i.e. the peak power, short-circuit current and open circuit voltage. The modeling method is useful for PV power converter designers and circuit simulator developers who require simple, fast yet accurate model for the PV module. (author)
Energy Technology Data Exchange (ETDEWEB)
Huang, P-C; Hsu, C-H [Department of Biomedical Engineering and Environmental Sciences, National Tsing Hua University, Hsinchu, Taiwan (China); Hsiao, I-T [Department Medical Imaging and Radiological Sciences, Chang Gung University, Tao-Yuan, Taiwan (China); Lin, K M [Medical Engineering Research Division, National Health Research Institutes, Zhunan Town, Miaoli County, Taiwan (China)], E-mail: cghsu@mx.nthu.edu.tw
2009-06-15
Accurate modeling of the photon acquisition process in pinhole SPECT is essential for optimizing resolution. In this work, the authors develop an accurate system model in which pinhole finite aperture and depth-dependent geometric sensitivity are explicitly included. To achieve high-resolution pinhole SPECT, the voxel size is usually set in the range of sub-millimeter so that the total number of image voxels increase accordingly. It is inevitably that a system matrix that models a variety of favorable physical factors will become extremely sophisticated. An efficient implementation for such an accurate system model is proposed in this research. We first use the geometric symmetries to reduce redundant entries in the matrix. Due to the sparseness of the matrix, only non-zero terms are stored. A novel center-to-radius recording rule is also developed to effectively describe the relation between a voxel and its related detectors at every projection angle. The proposed system matrix is also suitable for multi-threaded computing. Finally, the accuracy and effectiveness of the proposed system model is evaluated in a workstation equipped with two Quad-Core Intel X eon processors.
Bilinear reduced order approximate model of parabolic distributed solar collectors
Elmetennani, Shahrazed
2015-07-01
This paper proposes a novel, low dimensional and accurate approximate model for the distributed parabolic solar collector, by means of a modified gaussian interpolation along the spatial domain. The proposed reduced model, taking the form of a low dimensional bilinear state representation, enables the reproduction of the heat transfer dynamics along the collector tube for system analysis. Moreover, presented as a reduced order bilinear state space model, the well established control theory for this class of systems can be applied. The approximation efficiency has been proven by several simulation tests, which have been performed considering parameters of the Acurex field with real external working conditions. Model accuracy has been evaluated by comparison to the analytical solution of the hyperbolic distributed model and its semi discretized approximation highlighting the benefits of using the proposed numerical scheme. Furthermore, model sensitivity to the different parameters of the gaussian interpolation has been studied.
Reduced Order Models for Dynamic Behavior of Elastomer Damping Devices
Morin, B.; Legay, A.; Deü, J.-F.
2016-09-01
In the context of passive damping, various mechanical systems from the space industry use elastomer components (shock absorbers, silent blocks, flexible joints...). The material of these devices has frequency, temperature and amplitude dependent characteristics. The associated numerical models, using viscoelastic and hyperelastic constitutive behaviour, may become computationally too expensive during a design process. The aim of this work is to propose efficient reduced viscoelastic models of rubber devices. The first step is to choose an accurate material model that represent the viscoelasticity. The second step is to reduce the rubber device finite element model to a super-element that keeps the frequency dependence. This reduced model is first built by taking into account the fact that the device's interfaces are much more rigid than the rubber core. To make use of this difference, kinematical constraints enforce the rigid body motion of these interfaces reducing the rubber device model to twelve dofs only on the interfaces (three rotations and three translations per face). Then, the superelement is built by using a component mode synthesis method. As an application, the dynamic behavior of a structure supported by four hourglass shaped rubber devices under harmonic loads is analysed to show the efficiency of the proposed approach.
Reduced Multivariate Polynomial Model for Manufacturing Costs Estimation of Piping Elements
Directory of Open Access Journals (Sweden)
Nibaldo Rodriguez
2013-01-01
Full Text Available This paper discusses the development and evaluation of an estimation model of manufacturing costs of piping elements through the application of a Reduced Multivariate Polynomial (RMP. The model allows obtaining accurate estimations, even when enough and adequate information is not available. This situation typically occurs in the early stages of the design process of industrial products. The experimental evaluations show that the approach is capable, with a low complexity, of reducing uncertainties and to predict costs with significant precision. Comparisons with a neural network showed also that the RMP performs better considering a set of classical performance measures with the corresponding lower complexity and higher accuracy.
Aeroelastic simulation using CFD based reduced order models
International Nuclear Information System (INIS)
Zhang, W.; Ye, Z.; Li, H.; Yang, Q.
2005-01-01
This paper aims at providing an accurate and efficient method for aeroelastic simulation. System identification is used to get the reduced order models of unsteady aerodynamics. Unsteady Euler codes are used to compute the output signals while 3211 multistep input signals are utilized. LS(Least Squares) method is used to estimate the coefficients of the input-output difference model. The reduced order models are then used in place of the unsteady CFD code for aeroelastic simulation. The aeroelastic equations are marched by an improved 4th order Runge-Kutta method that only needs to compute the aerodynamic loads one time at every time step. The computed results agree well with that of the direct coupling CFD/CSD methods. The computational efficiency is improved 1∼2 orders while still retaining the high accuracy. A standard aeroelastic computing example (isogai wing) with S type flutter boundary is computed and analyzed. It is due to the system has more than one neutral points at the Mach range of 0.875∼0.9. (author)
Accurate laser skin perforation technique aimed at promoting bleeding and reducing pain
Directory of Open Access Journals (Sweden)
Han-Chao Chang
2015-11-01
Full Text Available Laser skin perforation is an effective and promising technique for use in blood collection. In this study, the relation between the perforation profile of skin and laser irradiation at various energies is discussed. Increasing laser energy does not uniformly expand the size and depth of a hole because the shallow depth of field (DOF of the focused light primarily concentrates energy on the skin surface. In practice, the hole gradually transforms from a semielliptical shape to an upside-down avocado shape as the laser energy increases. This phenomenon can increase the amount of bleeding and reduce pain. The findings support the feasibility of developing an accurate laser skin perforation method.
Accurate Modeling of Ionospheric Electromagnetic Fields Generated by a Low Altitude VLF Transmitter
2009-03-31
AFRL-RV-HA-TR-2009-1055 Accurate Modeling of Ionospheric Electromagnetic Fields Generated by a Low Altitude VLF Transmitter ...m (or even 500 m) at mid to high latitudes . At low latitudes , the FDTD model exhibits variations that make it difficult to determine a reliable...Scientific, Final 3. DATES COVERED (From - To) 02-08-2006 – 31-12-2008 4. TITLE AND SUBTITLE Accurate Modeling of Ionospheric Electromagnetic Fields
Accurate anisotropic material modelling using only tensile tests for hot and cold forming
Abspoel, M.; Scholting, M. E.; Lansbergen, M.; Neelis, B. M.
2017-09-01
Accurate material data for simulations require a lot of effort. Advanced yield loci require many different kinds of tests and a Forming Limit Curve (FLC) needs a large amount of samples. Many people use simple material models to reduce the effort of testing, however some models are either not accurate enough (i.e. Hill’48), or do not describe new types of materials (i.e. Keeler). Advanced yield loci describe the anisotropic materials behaviour accurately, but are not widely adopted because of the specialized tests, and data post-processing is a hurdle for many. To overcome these issues, correlations between the advanced yield locus points (biaxial, plane strain and shear) and mechanical properties have been investigated. This resulted in accurate prediction of the advanced stress points using only Rm, Ag and r-values in three directions from which a Vegter yield locus can be constructed with low effort. FLC’s can be predicted with the equations of Abspoel & Scholting depending on total elongation A80, r-value and thickness. Both predictive methods are initially developed for steel, aluminium and stainless steel (BCC and FCC materials). The validity of the predicted Vegter yield locus is investigated with simulation and measurements on both hot and cold formed parts and compared with Hill’48. An adapted specimen geometry, to ensure a homogeneous temperature distribution in the Gleeble hot tensile test, was used to measure the mechanical properties needed to predict a hot Vegter yield locus. Since for hot material, testing of stress states other than uniaxial is really challenging, the prediction for the yield locus adds a lot of value. For the hot FLC an A80 sample with a homogeneous temperature distribution is needed which is due to size limitations not possible in the Gleeble tensile tester. Heating the sample in an industrial type furnace and tensile testing it in a dedicated device is a good alternative to determine the necessary parameters for the FLC
Fast and accurate calculation of dilute quantum gas using Uehling–Uhlenbeck model equation
Energy Technology Data Exchange (ETDEWEB)
Yano, Ryosuke, E-mail: ryosuke.yano@tokiorisk.co.jp
2017-02-01
The Uehling–Uhlenbeck (U–U) model equation is studied for the fast and accurate calculation of a dilute quantum gas. In particular, the direct simulation Monte Carlo (DSMC) method is used to solve the U–U model equation. DSMC analysis based on the U–U model equation is expected to enable the thermalization to be accurately obtained using a small number of sample particles and the dilute quantum gas dynamics to be calculated in a practical time. Finally, the applicability of DSMC analysis based on the U–U model equation to the fast and accurate calculation of a dilute quantum gas is confirmed by calculating the viscosity coefficient of a Bose gas on the basis of the Green–Kubo expression and the shock layer of a dilute Bose gas around a cylinder.
Raghupathy, Arun; Ghia, Karman; Ghia, Urmila
2008-11-01
Compact Thermal Models (CTM) to represent IC packages has been traditionally developed using the DELPHI-based (DEvelopment of Libraries of PHysical models for an Integrated design) methodology. The drawbacks of this method are presented, and an alternative method is proposed. A reduced-order model that provides the complete thermal information accurately with less computational resources can be effectively used in system level simulations. Proper Orthogonal Decomposition (POD), a statistical method, can be used to reduce the order of the degree of freedom or variables of the computations for such a problem. POD along with the Galerkin projection allows us to create reduced-order models that reproduce the characteristics of the system with a considerable reduction in computational resources while maintaining a high level of accuracy. The goal of this work is to show that this method can be applied to obtain a boundary condition independent reduced-order thermal model for complex components. The methodology is applied to the 1D transient heat equation.
Accurate Holdup Calculations with Predictive Modeling & Data Integration
Energy Technology Data Exchange (ETDEWEB)
Azmy, Yousry [North Carolina State Univ., Raleigh, NC (United States). Dept. of Nuclear Engineering; Cacuci, Dan [Univ. of South Carolina, Columbia, SC (United States). Dept. of Mechanical Engineering
2017-04-03
In facilities that process special nuclear material (SNM) it is important to account accurately for the fissile material that enters and leaves the plant. Although there are many stages and processes through which materials must be traced and measured, the focus of this project is material that is “held-up” in equipment, pipes, and ducts during normal operation and that can accumulate over time into significant quantities. Accurately estimating the holdup is essential for proper SNM accounting (vis-à-vis nuclear non-proliferation), criticality and radiation safety, waste management, and efficient plant operation. Usually it is not possible to directly measure the holdup quantity and location, so these must be inferred from measured radiation fields, primarily gamma and less frequently neutrons. Current methods to quantify holdup, i.e. Generalized Geometry Holdup (GGH), primarily rely on simple source configurations and crude radiation transport models aided by ad hoc correction factors. This project seeks an alternate method of performing measurement-based holdup calculations using a predictive model that employs state-of-the-art radiation transport codes capable of accurately simulating such situations. Inverse and data assimilation methods use the forward transport model to search for a source configuration that best matches the measured data and simultaneously provide an estimate of the level of confidence in the correctness of such configuration. In this work the holdup problem is re-interpreted as an inverse problem that is under-determined, hence may permit multiple solutions. A probabilistic approach is applied to solving the resulting inverse problem. This approach rates possible solutions according to their plausibility given the measurements and initial information. This is accomplished through the use of Bayes’ Theorem that resolves the issue of multiple solutions by giving an estimate of the probability of observing each possible solution. To use
Allele-sharing models: LOD scores and accurate linkage tests.
Kong, A; Cox, N J
1997-11-01
Starting with a test statistic for linkage analysis based on allele sharing, we propose an associated one-parameter model. Under general missing-data patterns, this model allows exact calculation of likelihood ratios and LOD scores and has been implemented by a simple modification of existing software. Most important, accurate linkage tests can be performed. Using an example, we show that some previously suggested approaches to handling less than perfectly informative data can be unacceptably conservative. Situations in which this model may not perform well are discussed, and an alternative model that requires additional computations is suggested.
Reduced-Order Modeling of Unsteady Aerodynamics Across Multiple Mach Regimes
2013-01-01
elastic deformation, has been the subject of intensive study and has been treated in a number of textbooks , including Refs. 9–11, as well as review...simulations, which can be quite computationally-intensive. Reduced-order models (ROMs) o er a solution to these competing demands of accuracy and e ciency...regimes, from subsonic to hypersonic ight. The correction factor term allows the ROM to be accurate over a range of vehicle elastic modal deformation
Simple and Accurate Analytical Solutions of the Electrostatically Actuated Curled Beam Problem
Younis, Mohammad I.
2014-08-17
We present analytical solutions of the electrostatically actuated initially deformed cantilever beam problem. We use a continuous Euler-Bernoulli beam model combined with a single-mode Galerkin approximation. We derive simple analytical expressions for two commonly observed deformed beams configurations: the curled and tilted configurations. The derived analytical formulas are validated by comparing their results to experimental data in the literature and numerical results of a multi-mode reduced order model. The derived expressions do not involve any complicated integrals or complex terms and can be conveniently used by designers for quick, yet accurate, estimations. The formulas are found to yield accurate results for most commonly encountered microbeams of initial tip deflections of few microns. For largely deformed beams, we found that these formulas yield less accurate results due to the limitations of the single-mode approximations they are based on. In such cases, multi-mode reduced order models need to be utilized.
Accurate path integration in continuous attractor network models of grid cells.
Burak, Yoram; Fiete, Ila R
2009-02-01
Grid cells in the rat entorhinal cortex display strikingly regular firing responses to the animal's position in 2-D space and have been hypothesized to form the neural substrate for dead-reckoning. However, errors accumulate rapidly when velocity inputs are integrated in existing models of grid cell activity. To produce grid-cell-like responses, these models would require frequent resets triggered by external sensory cues. Such inadequacies, shared by various models, cast doubt on the dead-reckoning potential of the grid cell system. Here we focus on the question of accurate path integration, specifically in continuous attractor models of grid cell activity. We show, in contrast to previous models, that continuous attractor models can generate regular triangular grid responses, based on inputs that encode only the rat's velocity and heading direction. We consider the role of the network boundary in the integration performance of the network and show that both periodic and aperiodic networks are capable of accurate path integration, despite important differences in their attractor manifolds. We quantify the rate at which errors in the velocity integration accumulate as a function of network size and intrinsic noise within the network. With a plausible range of parameters and the inclusion of spike variability, our model networks can accurately integrate velocity inputs over a maximum of approximately 10-100 meters and approximately 1-10 minutes. These findings form a proof-of-concept that continuous attractor dynamics may underlie velocity integration in the dorsolateral medial entorhinal cortex. The simulations also generate pertinent upper bounds on the accuracy of integration that may be achieved by continuous attractor dynamics in the grid cell network. We suggest experiments to test the continuous attractor model and differentiate it from models in which single cells establish their responses independently of each other.
Accurate protein structure modeling using sparse NMR data and homologous structure information.
Thompson, James M; Sgourakis, Nikolaos G; Liu, Gaohua; Rossi, Paolo; Tang, Yuefeng; Mills, Jeffrey L; Szyperski, Thomas; Montelione, Gaetano T; Baker, David
2012-06-19
While information from homologous structures plays a central role in X-ray structure determination by molecular replacement, such information is rarely used in NMR structure determination because it can be incorrect, both locally and globally, when evolutionary relationships are inferred incorrectly or there has been considerable evolutionary structural divergence. Here we describe a method that allows robust modeling of protein structures of up to 225 residues by combining (1)H(N), (13)C, and (15)N backbone and (13)Cβ chemical shift data, distance restraints derived from homologous structures, and a physically realistic all-atom energy function. Accurate models are distinguished from inaccurate models generated using incorrect sequence alignments by requiring that (i) the all-atom energies of models generated using the restraints are lower than models generated in unrestrained calculations and (ii) the low-energy structures converge to within 2.0 Å backbone rmsd over 75% of the protein. Benchmark calculations on known structures and blind targets show that the method can accurately model protein structures, even with very remote homology information, to a backbone rmsd of 1.2-1.9 Å relative to the conventional determined NMR ensembles and of 0.9-1.6 Å relative to X-ray structures for well-defined regions of the protein structures. This approach facilitates the accurate modeling of protein structures using backbone chemical shift data without need for side-chain resonance assignments and extensive analysis of NOESY cross-peak assignments.
Performance of a reduced-order FSI model for flow-induced vocal fold vibration
Luo, Haoxiang; Chang, Siyuan; Chen, Ye; Rousseau, Bernard; PhonoSim Team
2017-11-01
Vocal fold vibration during speech production involves a three-dimensional unsteady glottal jet flow and three-dimensional nonlinear tissue mechanics. A full 3D fluid-structure interaction (FSI) model is computationally expensive even though it provides most accurate information about the system. On the other hand, an efficient reduced-order FSI model is useful for fast simulation and analysis of the vocal fold dynamics, which can be applied in procedures such as optimization and parameter estimation. In this work, we study performance of a reduced-order model as compared with the corresponding full 3D model in terms of its accuracy in predicting the vibration frequency and deformation mode. In the reduced-order model, we use a 1D flow model coupled with a 3D tissue model that is the same as in the full 3D model. Two different hyperelastic tissue behaviors are assumed. In addition, the vocal fold thickness and subglottal pressure are varied for systematic comparison. The result shows that the reduced-order model provides consistent predictions as the full 3D model across different tissue material assumptions and subglottal pressures. However, the vocal fold thickness has most effect on the model accuracy, especially when the vocal fold is thin.
Blackman, Jonathan; Field, Scott E; Galley, Chad R; Szilágyi, Béla; Scheel, Mark A; Tiglio, Manuel; Hemberger, Daniel A
2015-09-18
Simulating a binary black hole coalescence by solving Einstein's equations is computationally expensive, requiring days to months of supercomputing time. Using reduced order modeling techniques, we construct an accurate surrogate model, which is evaluated in a millisecond to a second, for numerical relativity (NR) waveforms from nonspinning binary black hole coalescences with mass ratios in [1, 10] and durations corresponding to about 15 orbits before merger. We assess the model's uncertainty and show that our modeling strategy predicts NR waveforms not used for the surrogate's training with errors nearly as small as the numerical error of the NR code. Our model includes all spherical-harmonic _{-2}Y_{ℓm} waveform modes resolved by the NR code up to ℓ=8. We compare our surrogate model to effective one body waveforms from 50M_{⊙} to 300M_{⊙} for advanced LIGO detectors and find that the surrogate is always more faithful (by at least an order of magnitude in most cases).
Accurate modeling of the hose instability in plasma wakefield accelerators
Mehrling, T. J.; Benedetti, C.; Schroeder, C. B.; Martinez de la Ossa, A.; Osterhoff, J.; Esarey, E.; Leemans, W. P.
2018-05-01
Hosing is a major challenge for the applicability of plasma wakefield accelerators and its modeling is therefore of fundamental importance to facilitate future stable and compact plasma-based particle accelerators. In this contribution, we present a new model for the evolution of the plasma centroid, which enables the accurate investigation of the hose instability in the nonlinear blowout regime. It paves the road for more precise and comprehensive studies of hosing, e.g., with drive and witness beams, which were not possible with previous models.
A reduced fidelity model for the rotary chemical looping combustion reactor
International Nuclear Information System (INIS)
Iloeje, Chukwunwike O.; Zhao, Zhenlong; Ghoniem, Ahmed F.
2017-01-01
Highlights: • Methodology for developing a reduced fidelity rotary CLC reactor model is presented. • The reduced model determines optimal reactor configuration that meets design and operating requirements. • A 4-order of magnitude reduction in computational cost is achieved with good prediction accuracy. • Sensitivity studies demonstrate importance of accurate kinetic parameters for reactor optimization. - Abstract: The rotary chemical looping combustion reactor has great potential for efficient integration with CO_2 capture-enabled energy conversion systems. In earlier studies, we described a one-dimensional rotary reactor model, and used it to demonstrate the feasibility of continuous reactor operation. Though this detailed model provides a high resolution representation of the rotary reactor performance, it is too computationally expensive for studies that require multiple model evaluations. Specifically, it is not ideal for system-level studies where the reactor is a single component in an energy conversion system. In this study, we present a reduced fidelity model (RFM) of the rotary reactor that reduces computational cost and determines an optimal combination of variables that satisfy reactor design requirements. Simulation results for copper, nickel and iron-based oxygen carriers show a four-order of magnitude reduction in simulation time, and reasonable prediction accuracy. Deviations from the detailed reference model predictions range from 3% to 20%, depending on oxygen carrier type and operating conditions. This study also demonstrates how the reduced model can be modified to deal with both optimization and design oriented problems. A parametric study using the reduced model is then applied to analyze the sensitivity of the optimal reactor design to changes in selected operating and kinetic parameters. These studies show that temperature and activation energy have a greater impact on optimal geometry than parameters like pressure or feed fuel
Robust simulation of buckled structures using reduced order modeling
International Nuclear Information System (INIS)
Wiebe, R.; Perez, R.A.; Spottswood, S.M.
2016-01-01
Lightweight metallic structures are a mainstay in aerospace engineering. For these structures, stability, rather than strength, is often the critical limit state in design. For example, buckling of panels and stiffeners may occur during emergency high-g maneuvers, while in supersonic and hypersonic aircraft, it may be induced by thermal stresses. The longstanding solution to such challenges was to increase the sizing of the structural members, which is counter to the ever present need to minimize weight for reasons of efficiency and performance. In this work we present some recent results in the area of reduced order modeling of post- buckled thin beams. A thorough parametric study of the response of a beam to changing harmonic loading parameters, which is useful in exposing complex phenomena and exercising numerical models, is presented. Two error metrics that use but require no time stepping of a (computationally expensive) truth model are also introduced. The error metrics are applied to several interesting forcing parameter cases identified from the parametric study and are shown to yield useful information about the quality of a candidate reduced order model. Parametric studies, especially when considering forcing and structural geometry parameters, coupled environments, and uncertainties would be computationally intractable with finite element models. The goal is to make rapid simulation of complex nonlinear dynamic behavior possible for distributed systems via fast and accurate reduced order models. This ability is crucial in allowing designers to rigorously probe the robustness of their designs to account for variations in loading, structural imperfections, and other uncertainties. (paper)
Robust simulation of buckled structures using reduced order modeling
Wiebe, R.; Perez, R. A.; Spottswood, S. M.
2016-09-01
Lightweight metallic structures are a mainstay in aerospace engineering. For these structures, stability, rather than strength, is often the critical limit state in design. For example, buckling of panels and stiffeners may occur during emergency high-g maneuvers, while in supersonic and hypersonic aircraft, it may be induced by thermal stresses. The longstanding solution to such challenges was to increase the sizing of the structural members, which is counter to the ever present need to minimize weight for reasons of efficiency and performance. In this work we present some recent results in the area of reduced order modeling of post- buckled thin beams. A thorough parametric study of the response of a beam to changing harmonic loading parameters, which is useful in exposing complex phenomena and exercising numerical models, is presented. Two error metrics that use but require no time stepping of a (computationally expensive) truth model are also introduced. The error metrics are applied to several interesting forcing parameter cases identified from the parametric study and are shown to yield useful information about the quality of a candidate reduced order model. Parametric studies, especially when considering forcing and structural geometry parameters, coupled environments, and uncertainties would be computationally intractable with finite element models. The goal is to make rapid simulation of complex nonlinear dynamic behavior possible for distributed systems via fast and accurate reduced order models. This ability is crucial in allowing designers to rigorously probe the robustness of their designs to account for variations in loading, structural imperfections, and other uncertainties.
Bayesian calibration of power plant models for accurate performance prediction
International Nuclear Information System (INIS)
Boksteen, Sowande Z.; Buijtenen, Jos P. van; Pecnik, Rene; Vecht, Dick van der
2014-01-01
Highlights: • Bayesian calibration is applied to power plant performance prediction. • Measurements from a plant in operation are used for model calibration. • A gas turbine performance model and steam cycle model are calibrated. • An integrated plant model is derived. • Part load efficiency is accurately predicted as a function of ambient conditions. - Abstract: Gas turbine combined cycles are expected to play an increasingly important role in the balancing of supply and demand in future energy markets. Thermodynamic modeling of these energy systems is frequently applied to assist in decision making processes related to the management of plant operation and maintenance. In most cases, model inputs, parameters and outputs are treated as deterministic quantities and plant operators make decisions with limited or no regard of uncertainties. As the steady integration of wind and solar energy into the energy market induces extra uncertainties, part load operation and reliability are becoming increasingly important. In the current study, methods are proposed to not only quantify various types of uncertainties in measurements and plant model parameters using measured data, but to also assess their effect on various aspects of performance prediction. The authors aim to account for model parameter and measurement uncertainty, and for systematic discrepancy of models with respect to reality. For this purpose, the Bayesian calibration framework of Kennedy and O’Hagan is used, which is especially suitable for high-dimensional industrial problems. The article derives a calibrated model of the plant efficiency as a function of ambient conditions and operational parameters, which is also accurate in part load. The article shows that complete statistical modeling of power plants not only enhances process models, but can also increases confidence in operational decisions
A reduced low-temperature electro-thermal coupled model for lithium-ion batteries
International Nuclear Information System (INIS)
Jiang, Jiuchun; Ruan, Haijun; Sun, Bingxiang; Zhang, Weige; Gao, Wenzhong; Wang, Le Yi; Zhang, Linjing
2016-01-01
Highlights: • A reduced low-temperature electro-thermal coupled model is proposed. • A novel frequency-dependent equation for polarization parameters is presented. • The model is validated under different frequency and low-temperature conditions. • The reduced model exhibits a high accuracy with a low computational effort. • The adaptability of the proposed methodology for model reduction is verified. - Abstract: A low-temperature electro-thermal coupled model, which is based on the electrochemical mechanism, is developed to accurately capture both electrical and thermal behaviors of batteries. Activation energies reveal that temperature dependence of resistances is greater than that of capacitances. The influence of frequency on polarization voltage and irreversible heat is discussed, and frequency dependence of polarization resistance and capacitance is obtained. Based on the frequency-dependent equation, a reduced low-temperature electro-thermal coupled model is proposed and experimentally validated under different temperature, frequency and amplitude conditions. Simulation results exhibit good agreement with experimental data, where the maximum relative voltage error and temperature error are below 2.65% and 1.79 °C, respectively. The reduced model is demonstrated to have almost the same accuracy as the original model and require a lower computational effort. The effectiveness and adaptability of the proposed methodology for model reduction is verified using batteries with three different cathode materials from different manufacturers. The reduced model, thanks to its high accuracy and simplicity, provides a promising candidate for development of rapid internal heating and optimal charging strategies at low temperature, and for evaluation of the state of battery health in on-board battery management system.
Wu, Liejun; Chen, Maoxue; Chen, Yongli; Li, Qing X.
2013-01-01
The gas holdup time (tM) is a dominant parameter in gas chromatographic retention models. The difference equation (DE) model proposed by Wu et al. (J. Chromatogr. A 2012, http://dx.doi.org/10.1016/j.chroma.2012.07.077) excluded tM. In the present paper, we propose that the relationship between the adjusted retention time tRZ′ and carbon number z of n-alkanes follows a quadratic equation (QE) when an accurate tM is obtained. This QE model is the same as or better than the DE model for an accurate expression of the retention behavior of n-alkanes and model applications. The QE model covers a larger range of n-alkanes with better curve fittings than the linear model. The accuracy of the QE model was approximately 2–6 times better than the DE model and 18–540 times better than the LE model. Standard deviations of the QE model were approximately 2–3 times smaller than those of the DE model. PMID:22989489
Accurate monoenergetic electron parameters of laser wakefield in a bubble model
Raheli, A.; Rahmatallahpur, S. H.
2012-11-01
A reliable analytical expression for the potential of plasma waves with phase velocities near the speed of light is derived. The presented spheroid cavity model is more consistent than the previous spherical and ellipsoidal model and it explains the mono-energetic electron trajectory more accurately, especially at the relativistic region. As a result, the quasi-mono-energetic electrons output beam interacting with the laser plasma can be more appropriately described with this model.
Muñoz-Esparza, Domingo; Kosović, Branko; Jiménez, Pedro A.; Coen, Janice L.
2018-04-01
The level-set method is typically used to track and propagate the fire perimeter in wildland fire models. Herein, a high-order level-set method using fifth-order WENO scheme for the discretization of spatial derivatives and third-order explicit Runge-Kutta temporal integration is implemented within the Weather Research and Forecasting model wildland fire physics package, WRF-Fire. The algorithm includes solution of an additional partial differential equation for level-set reinitialization. The accuracy of the fire-front shape and rate of spread in uncoupled simulations is systematically analyzed. It is demonstrated that the common implementation used by level-set-based wildfire models yields to rate-of-spread errors in the range 10-35% for typical grid sizes (Δ = 12.5-100 m) and considerably underestimates fire area. Moreover, the amplitude of fire-front gradients in the presence of explicitly resolved turbulence features is systematically underestimated. In contrast, the new WRF-Fire algorithm results in rate-of-spread errors that are lower than 1% and that become nearly grid independent. Also, the underestimation of fire area at the sharp transition between the fire front and the lateral flanks is found to be reduced by a factor of ≈7. A hybrid-order level-set method with locally reduced artificial viscosity is proposed, which substantially alleviates the computational cost associated with high-order discretizations while preserving accuracy. Simulations of the Last Chance wildfire demonstrate additional benefits of high-order accurate level-set algorithms when dealing with complex fuel heterogeneities, enabling propagation across narrow fuel gaps and more accurate fire backing over the lee side of no fuel clusters.
A reduced-form intensity-based model under fuzzy environments
Wu, Liang; Zhuang, Yaming
2015-05-01
The external shocks and internal contagion are the important sources of default events. However, the external shocks and internal contagion effect on the company is not observed, we cannot get the accurate size of the shocks. The information of investors relative to the default process exhibits a certain fuzziness. Therefore, using randomness and fuzziness to study such problems as derivative pricing or default probability has practical needs. But the idea of fuzzifying credit risk models is little exploited, especially in a reduced-form model. This paper proposes a new default intensity model with fuzziness and presents a fuzzy default probability and default loss rate, and puts them into default debt and credit derivative pricing. Finally, the simulation analysis verifies the rationality of the model. Using fuzzy numbers and random analysis one can consider more uncertain sources in the default process of default and investors' subjective judgment on the financial markets in a variety of fuzzy reliability so as to broaden the scope of possible credit spreads.
Estrada, T; Zhang, B; Cicotti, P; Armen, R S; Taufer, M
2012-07-01
We present a scalable and accurate method for classifying protein-ligand binding geometries in molecular docking. Our method is a three-step process: the first step encodes the geometry of a three-dimensional (3D) ligand conformation into a single 3D point in the space; the second step builds an octree by assigning an octant identifier to every single point in the space under consideration; and the third step performs an octree-based clustering on the reduced conformation space and identifies the most dense octant. We adapt our method for MapReduce and implement it in Hadoop. The load-balancing, fault-tolerance, and scalability in MapReduce allow screening of very large conformation spaces not approachable with traditional clustering methods. We analyze results for docking trials for 23 protein-ligand complexes for HIV protease, 21 protein-ligand complexes for Trypsin, and 12 protein-ligand complexes for P38alpha kinase. We also analyze cross docking trials for 24 ligands, each docking into 24 protein conformations of the HIV protease, and receptor ensemble docking trials for 24 ligands, each docking in a pool of HIV protease receptors. Our method demonstrates significant improvement over energy-only scoring for the accurate identification of native ligand geometries in all these docking assessments. The advantages of our clustering approach make it attractive for complex applications in real-world drug design efforts. We demonstrate that our method is particularly useful for clustering docking results using a minimal ensemble of representative protein conformational states (receptor ensemble docking), which is now a common strategy to address protein flexibility in molecular docking. Copyright © 2012 Elsevier Ltd. All rights reserved.
Ichii, K.; Suzuki, T.; Kato, T.; Ito, A.; Hajima, T.; Ueyama, M.; Sasai, T.; Hirata, R.; Saigusa, N.; Ohtani, Y.; Takagi, K.
2009-08-01
Terrestrial biosphere models show large uncertainties when simulating carbon and water cycles, and reducing these uncertainties is a priority for developing more accurate estimates of both terrestrial ecosystem statuses and future climate changes. To reduce uncertainties and improve the understanding of these carbon budgets, we investigated the ability of flux datasets to improve model simulations and reduce variabilities among multi-model outputs of terrestrial biosphere models in Japan. Using 9 terrestrial biosphere models (Support Vector Machine-based regressions, TOPS, CASA, VISIT, Biome-BGC, DAYCENT, SEIB, LPJ, and TRIFFID), we conducted two simulations: (1) point simulations at four flux sites in Japan and (2) spatial simulations for Japan with a default model (based on original settings) and an improved model (based on calibration using flux observations). Generally, models using default model settings showed large deviations in model outputs from observation with large model-by-model variability. However, after we calibrated the model parameters using flux observations (GPP, RE and NEP), most models successfully simulated seasonal variations in the carbon cycle, with less variability among models. We also found that interannual variations in the carbon cycle are mostly consistent among models and observations. Spatial analysis also showed a large reduction in the variability among model outputs, and model calibration using flux observations significantly improved the model outputs. These results show that to reduce uncertainties among terrestrial biosphere models, we need to conduct careful validation and calibration with available flux observations. Flux observation data significantly improved terrestrial biosphere models, not only on a point scale but also on spatial scales.
Energy Technology Data Exchange (ETDEWEB)
Przybylski, D.; Shelyag, S.; Cally, P. S. [Monash Center for Astrophysics, School of Mathematical Sciences, Monash University, Clayton, Victoria 3800 (Australia)
2015-07-01
We present a technique to construct a spectropolarimetrically accurate magnetohydrostatic model of a large-scale solar magnetic field concentration, mimicking a sunspot. Using the constructed model we perform a simulation of acoustic wave propagation, conversion, and absorption in the solar interior and photosphere with the sunspot embedded into it. With the 6173 Å magnetically sensitive photospheric absorption line of neutral iron, we calculate observable quantities such as continuum intensities, Doppler velocities, as well as the full Stokes vector for the simulation at various positions at the solar disk, and analyze the influence of non-locality of radiative transport in the solar photosphere on helioseismic measurements. Bisector shapes were used to perform multi-height observations. The differences in acoustic power at different heights within the line formation region at different positions at the solar disk were simulated and characterized. An increase in acoustic power in the simulated observations of the sunspot umbra away from the solar disk center was confirmed as the slow magnetoacoustic wave.
International Nuclear Information System (INIS)
Przybylski, D.; Shelyag, S.; Cally, P. S.
2015-01-01
We present a technique to construct a spectropolarimetrically accurate magnetohydrostatic model of a large-scale solar magnetic field concentration, mimicking a sunspot. Using the constructed model we perform a simulation of acoustic wave propagation, conversion, and absorption in the solar interior and photosphere with the sunspot embedded into it. With the 6173 Å magnetically sensitive photospheric absorption line of neutral iron, we calculate observable quantities such as continuum intensities, Doppler velocities, as well as the full Stokes vector for the simulation at various positions at the solar disk, and analyze the influence of non-locality of radiative transport in the solar photosphere on helioseismic measurements. Bisector shapes were used to perform multi-height observations. The differences in acoustic power at different heights within the line formation region at different positions at the solar disk were simulated and characterized. An increase in acoustic power in the simulated observations of the sunspot umbra away from the solar disk center was confirmed as the slow magnetoacoustic wave
Accurate, low-cost 3D-models of gullies
Onnen, Nils; Gronz, Oliver; Ries, Johannes B.; Brings, Christine
2015-04-01
Soil erosion is a widespread problem in arid and semi-arid areas. The most severe form is the gully erosion. They often cut into agricultural farmland and can make a certain area completely unproductive. To understand the development and processes inside and around gullies, we calculated detailed 3D-models of gullies in the Souss Valley in South Morocco. Near Taroudant, we had four study areas with five gullies different in size, volume and activity. By using a Canon HF G30 Camcorder, we made varying series of Full HD videos with 25fps. Afterwards, we used the method Structure from Motion (SfM) to create the models. To generate accurate models maintaining feasible runtimes, it is necessary to select around 1500-1700 images from the video, while the overlap of neighboring images should be at least 80%. In addition, it is very important to avoid selecting photos that are blurry or out of focus. Nearby pixels of a blurry image tend to have similar color values. That is why we used a MATLAB script to compare the derivatives of the images. The higher the sum of the derivative, the sharper an image of similar objects. MATLAB subdivides the video into image intervals. From each interval, the image with the highest sum is selected. E.g.: 20min. video at 25fps equals 30.000 single images. The program now inspects the first 20 images, saves the sharpest and moves on to the next 20 images etc. Using this algorithm, we selected 1500 images for our modeling. With VisualSFM, we calculated features and the matches between all images and produced a point cloud. Then, MeshLab has been used to build a surface out of it using the Poisson surface reconstruction approach. Afterwards we are able to calculate the size and the volume of the gullies. It is also possible to determine soil erosion rates, if we compare the data with old recordings. The final step would be the combination of the terrestrial data with the data from our aerial photography. So far, the method works well and we
Shen, Jiajian; Tryggestad, Erik; Younkin, James E; Keole, Sameer R; Furutani, Keith M; Kang, Yixiu; Herman, Michael G; Bues, Martin
2017-10-01
To accurately model the beam delivery time (BDT) for a synchrotron-based proton spot scanning system using experimentally determined beam parameters. A model to simulate the proton spot delivery sequences was constructed, and BDT was calculated by summing times for layer switch, spot switch, and spot delivery. Test plans were designed to isolate and quantify the relevant beam parameters in the operation cycle of the proton beam therapy delivery system. These parameters included the layer switch time, magnet preparation and verification time, average beam scanning speeds in x- and y-directions, proton spill rate, and maximum charge and maximum extraction time for each spill. The experimentally determined parameters, as well as the nominal values initially provided by the vendor, served as inputs to the model to predict BDTs for 602 clinical proton beam deliveries. The calculated BDTs (T BDT ) were compared with the BDTs recorded in the treatment delivery log files (T Log ): ∆t = T Log -T BDT . The experimentally determined average layer switch time for all 97 energies was 1.91 s (ranging from 1.9 to 2.0 s for beam energies from 71.3 to 228.8 MeV), average magnet preparation and verification time was 1.93 ms, the average scanning speeds were 5.9 m/s in x-direction and 19.3 m/s in y-direction, the proton spill rate was 8.7 MU/s, and the maximum proton charge available for one acceleration is 2.0 ± 0.4 nC. Some of the measured parameters differed from the nominal values provided by the vendor. The calculated BDTs using experimentally determined parameters matched the recorded BDTs of 602 beam deliveries (∆t = -0.49 ± 1.44 s), which were significantly more accurate than BDTs calculated using nominal timing parameters (∆t = -7.48 ± 6.97 s). An accurate model for BDT prediction was achieved by using the experimentally determined proton beam therapy delivery parameters, which may be useful in modeling the interplay effect and patient throughput. The model may
Reduced cost mission design using surrogate models
Feldhacker, Juliana D.; Jones, Brandon A.; Doostan, Alireza; Hampton, Jerrad
2016-01-01
This paper uses surrogate models to reduce the computational cost associated with spacecraft mission design in three-body dynamical systems. Sampling-based least squares regression is used to project the system response onto a set of orthogonal bases, providing a representation of the ΔV required for rendezvous as a reduced-order surrogate model. Models are presented for mid-field rendezvous of spacecraft in orbits in the Earth-Moon circular restricted three-body problem, including a halo orbit about the Earth-Moon L2 libration point (EML-2) and a distant retrograde orbit (DRO) about the Moon. In each case, the initial position of the spacecraft, the time of flight, and the separation between the chaser and the target vehicles are all considered as design inputs. The results show that sample sizes on the order of 102 are sufficient to produce accurate surrogates, with RMS errors reaching 0.2 m/s for the halo orbit and falling below 0.01 m/s for the DRO. A single function call to the resulting surrogate is up to two orders of magnitude faster than computing the same solution using full fidelity propagators. The expansion coefficients solved for in the surrogates are then used to conduct a global sensitivity analysis of the ΔV on each of the input parameters, which identifies the separation between the spacecraft as the primary contributor to the ΔV cost. Finally, the models are demonstrated to be useful for cheap evaluation of the cost function in constrained optimization problems seeking to minimize the ΔV required for rendezvous. These surrogate models show significant advantages for mission design in three-body systems, in terms of both computational cost and capabilities, over traditional Monte Carlo methods.
Reduced order modeling in topology optimization of vibroacoustic problems
DEFF Research Database (Denmark)
Creixell Mediante, Ester; Jensen, Jakob Søndergaard; Brunskog, Jonas
2017-01-01
complex 3D parts. The optimization process can therefore become highly time consuming due to the need to solve a large system of equations at each iteration. Projection-based parametric Model Order Reduction (pMOR) methods have successfully been applied for reducing the computational cost of material......There is an interest in introducing topology optimization techniques in the design process of structural-acoustic systems. In topology optimization, the design space must be finely meshed in order to obtain an accurate design, which results in large numbers of degrees of freedom when designing...... or size optimization in large vibroacoustic models; however, new challenges are encountered when dealing with topology optimization. Since a design parameter per element is considered, the total number of design variables becomes very large; this poses a challenge to most existing pMOR techniques, which...
Sinha, Manodeep; Berlind, Andreas A.; McBride, Cameron K.; Scoccimarro, Roman; Piscionere, Jennifer A.; Wibking, Benjamin D.
2018-04-01
Interpreting the small-scale clustering of galaxies with halo models can elucidate the connection between galaxies and dark matter halos. Unfortunately, the modelling is typically not sufficiently accurate for ruling out models statistically. It is thus difficult to use the information encoded in small scales to test cosmological models or probe subtle features of the galaxy-halo connection. In this paper, we attempt to push halo modelling into the "accurate" regime with a fully numerical mock-based methodology and careful treatment of statistical and systematic errors. With our forward-modelling approach, we can incorporate clustering statistics beyond the traditional two-point statistics. We use this modelling methodology to test the standard ΛCDM + halo model against the clustering of SDSS DR7 galaxies. Specifically, we use the projected correlation function, group multiplicity function and galaxy number density as constraints. We find that while the model fits each statistic separately, it struggles to fit them simultaneously. Adding group statistics leads to a more stringent test of the model and significantly tighter constraints on model parameters. We explore the impact of varying the adopted halo definition and cosmological model and find that changing the cosmology makes a significant difference. The most successful model we tried (Planck cosmology with Mvir halos) matches the clustering of low luminosity galaxies, but exhibits a 2.3σ tension with the clustering of luminous galaxies, thus providing evidence that the "standard" halo model needs to be extended. This work opens the door to adding interesting freedom to the halo model and including additional clustering statistics as constraints.
Chowdhury, Amor; Sarjaš, Andrej
2016-09-15
The presented paper describes accurate distance measurement for a field-sensed magnetic suspension system. The proximity measurement is based on a Hall effect sensor. The proximity sensor is installed directly on the lower surface of the electro-magnet, which means that it is very sensitive to external magnetic influences and disturbances. External disturbances interfere with the information signal and reduce the usability and reliability of the proximity measurements and, consequently, the whole application operation. A sensor fusion algorithm is deployed for the aforementioned reasons. The sensor fusion algorithm is based on the Unscented Kalman Filter, where a nonlinear dynamic model was derived with the Finite Element Modelling approach. The advantage of such modelling is a more accurate dynamic model parameter estimation, especially in the case when the real structure, materials and dimensions of the real-time application are known. The novelty of the paper is the design of a compact electro-magnetic actuator with a built-in low cost proximity sensor for accurate proximity measurement of the magnetic object. The paper successively presents a modelling procedure with the finite element method, design and parameter settings of a sensor fusion algorithm with Unscented Kalman Filter and, finally, the implementation procedure and results of real-time operation.
A new model for the accurate calculation of natural gas viscosity
Xiaohong Yang; Shunxi Zhang; Weiling Zhu
2017-01-01
Viscosity of natural gas is a basic and important parameter, of theoretical and practical significance in the domain of natural gas recovery, transmission and processing. In order to obtain the accurate viscosity data efficiently at a low cost, a new model and its corresponding functional relation are derived on the basis of the relationship among viscosity, temperature and density derived from the kinetic theory of gases. After the model parameters were optimized using a lot of experimental ...
Empirical Reduced-Order Modeling for Boundary Feedback Flow Control
Directory of Open Access Journals (Sweden)
Seddik M. Djouadi
2008-01-01
Full Text Available This paper deals with the practical and theoretical implications of model reduction for aerodynamic flow-based control problems. Various aspects of model reduction are discussed that apply to partial differential equation- (PDE- based models in general. Specifically, the proper orthogonal decomposition (POD of a high dimension system as well as frequency domain identification methods are discussed for initial model construction. Projections on the POD basis give a nonlinear Galerkin model. Then, a model reduction method based on empirical balanced truncation is developed and applied to the Galerkin model. The rationale for doing so is that linear subspace approximations to exact submanifolds associated with nonlinear controllability and observability require only standard matrix manipulations utilizing simulation/experimental data. The proposed method uses a chirp signal as input to produce the output in the eigensystem realization algorithm (ERA. This method estimates the system's Markov parameters that accurately reproduce the output. Balanced truncation is used to show that model reduction is still effective on ERA produced approximated systems. The method is applied to a prototype convective flow on obstacle geometry. An H∞ feedback flow controller is designed based on the reduced model to achieve tracking and then applied to the full-order model with excellent performance.
Shah, A A; Xing, W W; Triantafyllidis, V
2017-04-01
In this paper, we develop reduced-order models for dynamic, parameter-dependent, linear and nonlinear partial differential equations using proper orthogonal decomposition (POD). The main challenges are to accurately and efficiently approximate the POD bases for new parameter values and, in the case of nonlinear problems, to efficiently handle the nonlinear terms. We use a Bayesian nonlinear regression approach to learn the snapshots of the solutions and the nonlinearities for new parameter values. Computational efficiency is ensured by using manifold learning to perform the emulation in a low-dimensional space. The accuracy of the method is demonstrated on a linear and a nonlinear example, with comparisons with a global basis approach.
Chen Xin; Liu Li; Long Teng; Yue Zhenjiang
2015-01-01
Aerothermoelasticity is one of the key technologies for hypersonic vehicles. Accurate and efficient computation of the aerothermodynamics is one of the primary challenges for hypersonic aerothermoelastic analysis. Aimed at solving the shortcomings of engineering calculation, computation fluid dynamics (CFD) and experimental investigation, a reduced order modeling (ROM) framework for aerothermodynamics based on CFD predictions using an enhanced algorithm of fast maximin Latin hypercube design ...
Hudin, Jamal Maulana; Riana, Dwiza
2016-01-01
Accurate accounting information system is one of accounting information systems used in the sixcompanies in the city of Sukabumi. DeLone and McLean information system success model is asuitable model to measure the success of the application of information systems in an organizationor company. This study will analyze factors that measure the success of DeLone & McLeaninformation systems model to the users of the Accurate accounting information systems in sixcompanies in the city of Sukabumi. ...
Accurate modeling and evaluation of microstructures in complex materials
Tahmasebi, Pejman
2018-02-01
Accurate characterization of heterogeneous materials is of great importance for different fields of science and engineering. Such a goal can be achieved through imaging. Acquiring three- or two-dimensional images under different conditions is not, however, always plausible. On the other hand, accurate characterization of complex and multiphase materials requires various digital images (I) under different conditions. An ensemble method is presented that can take one single (or a set of) I(s) and stochastically produce several similar models of the given disordered material. The method is based on a successive calculating of a conditional probability by which the initial stochastic models are produced. Then, a graph formulation is utilized for removing unrealistic structures. A distance transform function for the Is with highly connected microstructure and long-range features is considered which results in a new I that is more informative. Reproduction of the I is also considered through a histogram matching approach in an iterative framework. Such an iterative algorithm avoids reproduction of unrealistic structures. Furthermore, a multiscale approach, based on pyramid representation of the large Is, is presented that can produce materials with millions of pixels in a matter of seconds. Finally, the nonstationary systems—those for which the distribution of data varies spatially—are studied using two different methods. The method is tested on several complex and large examples of microstructures. The produced results are all in excellent agreement with the utilized Is and the similarities are quantified using various correlation functions.
Microbiome Data Accurately Predicts the Postmortem Interval Using Random Forest Regression Models
Directory of Open Access Journals (Sweden)
Aeriel Belk
2018-02-01
Full Text Available Death investigations often include an effort to establish the postmortem interval (PMI in cases in which the time of death is uncertain. The postmortem interval can lead to the identification of the deceased and the validation of witness statements and suspect alibis. Recent research has demonstrated that microbes provide an accurate clock that starts at death and relies on ecological change in the microbial communities that normally inhabit a body and its surrounding environment. Here, we explore how to build the most robust Random Forest regression models for prediction of PMI by testing models built on different sample types (gravesoil, skin of the torso, skin of the head, gene markers (16S ribosomal RNA (rRNA, 18S rRNA, internal transcribed spacer regions (ITS, and taxonomic levels (sequence variants, species, genus, etc.. We also tested whether particular suites of indicator microbes were informative across different datasets. Generally, results indicate that the most accurate models for predicting PMI were built using gravesoil and skin data using the 16S rRNA genetic marker at the taxonomic level of phyla. Additionally, several phyla consistently contributed highly to model accuracy and may be candidate indicators of PMI.
Non-intrusive reduced order modeling of nonlinear problems using neural networks
Hesthaven, J. S.; Ubbiali, S.
2018-06-01
We develop a non-intrusive reduced basis (RB) method for parametrized steady-state partial differential equations (PDEs). The method extracts a reduced basis from a collection of high-fidelity solutions via a proper orthogonal decomposition (POD) and employs artificial neural networks (ANNs), particularly multi-layer perceptrons (MLPs), to accurately approximate the coefficients of the reduced model. The search for the optimal number of neurons and the minimum amount of training samples to avoid overfitting is carried out in the offline phase through an automatic routine, relying upon a joint use of the Latin hypercube sampling (LHS) and the Levenberg-Marquardt (LM) training algorithm. This guarantees a complete offline-online decoupling, leading to an efficient RB method - referred to as POD-NN - suitable also for general nonlinear problems with a non-affine parametric dependence. Numerical studies are presented for the nonlinear Poisson equation and for driven cavity viscous flows, modeled through the steady incompressible Navier-Stokes equations. Both physical and geometrical parametrizations are considered. Several results confirm the accuracy of the POD-NN method and show the substantial speed-up enabled at the online stage as compared to a traditional RB strategy.
Modeling of Non-Gravitational Forces for Precise and Accurate Orbit Determination
Hackel, Stefan; Gisinger, Christoph; Steigenberger, Peter; Balss, Ulrich; Montenbruck, Oliver; Eineder, Michael
2014-05-01
Remote sensing satellites support a broad range of scientific and commercial applications. The two radar imaging satellites TerraSAR-X and TanDEM-X provide spaceborne Synthetic Aperture Radar (SAR) and interferometric SAR data with a very high accuracy. The precise reconstruction of the satellite's trajectory is based on the Global Positioning System (GPS) measurements from a geodetic-grade dual-frequency Integrated Geodetic and Occultation Receiver (IGOR) onboard the spacecraft. The increasing demand for precise radar products relies on validation methods, which require precise and accurate orbit products. An analysis of the orbit quality by means of internal and external validation methods on long and short timescales shows systematics, which reflect deficits in the employed force models. Following the proper analysis of this deficits, possible solution strategies are highlighted in the presentation. The employed Reduced Dynamic Orbit Determination (RDOD) approach utilizes models for gravitational and non-gravitational forces. A detailed satellite macro model is introduced to describe the geometry and the optical surface properties of the satellite. Two major non-gravitational forces are the direct and the indirect Solar Radiation Pressure (SRP). The satellite TerraSAR-X flies on a dusk-dawn orbit with an altitude of approximately 510 km above ground. Due to this constellation, the Sun almost constantly illuminates the satellite, which causes strong across-track accelerations on the plane rectangular to the solar rays. The indirect effect of the solar radiation is called Earth Radiation Pressure (ERP). This force depends on the sunlight, which is reflected by the illuminated Earth surface (visible spectra) and the emission of the Earth body in the infrared spectra. Both components of ERP require Earth models to describe the optical properties of the Earth surface. Therefore, the influence of different Earth models on the orbit quality is assessed. The scope of
Pineda, M.; Stamatakis, M.
2017-07-01
Modeling the kinetics of surface catalyzed reactions is essential for the design of reactors and chemical processes. The majority of microkinetic models employ mean-field approximations, which lead to an approximate description of catalytic kinetics by assuming spatially uncorrelated adsorbates. On the other hand, kinetic Monte Carlo (KMC) methods provide a discrete-space continuous-time stochastic formulation that enables an accurate treatment of spatial correlations in the adlayer, but at a significant computation cost. In this work, we use the so-called cluster mean-field approach to develop higher order approximations that systematically increase the accuracy of kinetic models by treating spatial correlations at a progressively higher level of detail. We further demonstrate our approach on a reduced model for NO oxidation incorporating first nearest-neighbor lateral interactions and construct a sequence of approximations of increasingly higher accuracy, which we compare with KMC and mean-field. The latter is found to perform rather poorly, overestimating the turnover frequency by several orders of magnitude for this system. On the other hand, our approximations, while more computationally intense than the traditional mean-field treatment, still achieve tremendous computational savings compared to KMC simulations, thereby opening the way for employing them in multiscale modeling frameworks.
Accurate Energy Consumption Modeling of IEEE 802.15.4e TSCH Using Dual-BandOpenMote Hardware.
Daneels, Glenn; Municio, Esteban; Van de Velde, Bruno; Ergeerts, Glenn; Weyn, Maarten; Latré, Steven; Famaey, Jeroen
2018-02-02
The Time-Slotted Channel Hopping (TSCH) mode of the IEEE 802.15.4e amendment aims to improve reliability and energy efficiency in industrial and other challenging Internet-of-Things (IoT) environments. This paper presents an accurate and up-to-date energy consumption model for devices using this IEEE 802.15.4e TSCH mode. The model identifies all network-related CPU and radio state changes, thus providing a precise representation of the device behavior and an accurate prediction of its energy consumption. Moreover, energy measurements were performed with a dual-band OpenMote device, running the OpenWSN firmware. This allows the model to be used for devices using 2.4 GHz, as well as 868 MHz. Using these measurements, several network simulations were conducted to observe the TSCH energy consumption effects in end-to-end communication for both frequency bands. Experimental verification of the model shows that it accurately models the consumption for all possible packet sizes and that the calculated consumption on average differs less than 3% from the measured consumption. This deviation includes measurement inaccuracies and the variations of the guard time. As such, the proposed model is very suitable for accurate energy consumption modeling of TSCH networks.
Simple Mathematical Models Do Not Accurately Predict Early SIV Dynamics
Directory of Open Access Journals (Sweden)
Cecilia Noecker
2015-03-01
Full Text Available Upon infection of a new host, human immunodeficiency virus (HIV replicates in the mucosal tissues and is generally undetectable in circulation for 1–2 weeks post-infection. Several interventions against HIV including vaccines and antiretroviral prophylaxis target virus replication at this earliest stage of infection. Mathematical models have been used to understand how HIV spreads from mucosal tissues systemically and what impact vaccination and/or antiretroviral prophylaxis has on viral eradication. Because predictions of such models have been rarely compared to experimental data, it remains unclear which processes included in these models are critical for predicting early HIV dynamics. Here we modified the “standard” mathematical model of HIV infection to include two populations of infected cells: cells that are actively producing the virus and cells that are transitioning into virus production mode. We evaluated the effects of several poorly known parameters on infection outcomes in this model and compared model predictions to experimental data on infection of non-human primates with variable doses of simian immunodifficiency virus (SIV. First, we found that the mode of virus production by infected cells (budding vs. bursting has a minimal impact on the early virus dynamics for a wide range of model parameters, as long as the parameters are constrained to provide the observed rate of SIV load increase in the blood of infected animals. Interestingly and in contrast with previous results, we found that the bursting mode of virus production generally results in a higher probability of viral extinction than the budding mode of virus production. Second, this mathematical model was not able to accurately describe the change in experimentally determined probability of host infection with increasing viral doses. Third and finally, the model was also unable to accurately explain the decline in the time to virus detection with increasing viral
A new, accurate predictive model for incident hypertension.
Völzke, Henry; Fung, Glenn; Ittermann, Till; Yu, Shipeng; Baumeister, Sebastian E; Dörr, Marcus; Lieb, Wolfgang; Völker, Uwe; Linneberg, Allan; Jørgensen, Torben; Felix, Stephan B; Rettig, Rainer; Rao, Bharat; Kroemer, Heyo K
2013-11-01
Data mining represents an alternative approach to identify new predictors of multifactorial diseases. This work aimed at building an accurate predictive model for incident hypertension using data mining procedures. The primary study population consisted of 1605 normotensive individuals aged 20-79 years with 5-year follow-up from the population-based study, that is the Study of Health in Pomerania (SHIP). The initial set was randomly split into a training and a testing set. We used a probabilistic graphical model applying a Bayesian network to create a predictive model for incident hypertension and compared the predictive performance with the established Framingham risk score for hypertension. Finally, the model was validated in 2887 participants from INTER99, a Danish community-based intervention study. In the training set of SHIP data, the Bayesian network used a small subset of relevant baseline features including age, mean arterial pressure, rs16998073, serum glucose and urinary albumin concentrations. Furthermore, we detected relevant interactions between age and serum glucose as well as between rs16998073 and urinary albumin concentrations [area under the receiver operating characteristic (AUC 0.76)]. The model was confirmed in the SHIP validation set (AUC 0.78) and externally replicated in INTER99 (AUC 0.77). Compared to the established Framingham risk score for hypertension, the predictive performance of the new model was similar in the SHIP validation set and moderately better in INTER99. Data mining procedures identified a predictive model for incident hypertension, which included innovative and easy-to-measure variables. The findings promise great applicability in screening settings and clinical practice.
Generating Facial Expressions Using an Anatomically Accurate Biomechanical Model.
Wu, Tim; Hung, Alice; Mithraratne, Kumar
2014-11-01
This paper presents a computational framework for modelling the biomechanics of human facial expressions. A detailed high-order (Cubic-Hermite) finite element model of the human head was constructed using anatomical data segmented from magnetic resonance images. The model includes a superficial soft-tissue continuum consisting of skin, the subcutaneous layer and the superficial Musculo-Aponeurotic system. Embedded within this continuum mesh, are 20 pairs of facial muscles which drive facial expressions. These muscles were treated as transversely-isotropic and their anatomical geometries and fibre orientations were accurately depicted. In order to capture the relative composition of muscles and fat, material heterogeneity was also introduced into the model. Complex contact interactions between the lips, eyelids, and between superficial soft tissue continuum and deep rigid skeletal bones were also computed. In addition, this paper investigates the impact of incorporating material heterogeneity and contact interactions, which are often neglected in similar studies. Four facial expressions were simulated using the developed model and the results were compared with surface data obtained from a 3D structured-light scanner. Predicted expressions showed good agreement with the experimental data.
Frequency-domain reduced order models for gravitational waves from aligned-spin compact binaries
International Nuclear Information System (INIS)
Pürrer, Michael
2014-01-01
Black-hole binary coalescences are one of the most promising sources for the first detection of gravitational waves. Fast and accurate theoretical models of the gravitational radiation emitted from these coalescences are highly important for the detection and extraction of physical parameters. Spinning effective-one-body models for binaries with aligned-spins have been shown to be highly faithful, but are slow to generate and thus have not yet been used for parameter estimation (PE) studies. I provide a frequency-domain singular value decomposition-based surrogate reduced order model that is thousands of times faster for typical system masses and has a faithfulness mismatch of better than ∼0.1% with the original SEOBNRv1 model for advanced LIGO detectors. This model enables PE studies up to signal-to-noise ratios (SNRs) of 20 and even up to 50 for total masses below 50 M ⊙ . This paper discusses various choices for approximations and interpolation over the parameter space that can be made for reduced order models of spinning compact binaries, provides a detailed discussion of errors arising in the construction and assesses the fidelity of such models. (paper)
Corazza, Stefano; Gambaretto, Emiliano; Mündermann, Lars; Andriacchi, Thomas P
2010-04-01
A novel approach for the automatic generation of a subject-specific model consisting of morphological and joint location information is described. The aim is to address the need for efficient and accurate model generation for markerless motion capture (MMC) and biomechanical studies. The algorithm applied and expanded on previous work on human shapes space by embedding location information for ten joint centers in a subject-specific free-form surface. The optimal locations of joint centers in the 3-D mesh were learned through linear regression over a set of nine subjects whose joint centers were known. The model was shown to be sufficiently accurate for both kinematic (joint centers) and morphological (shape of the body) information to allow accurate tracking with MMC systems. The automatic model generation algorithm was applied to 3-D meshes of different quality and resolution such as laser scans and visual hulls. The complete method was tested using nine subjects of different gender, body mass index (BMI), age, and ethnicity. Experimental training error and cross-validation errors were 19 and 25 mm, respectively, on average over the joints of the ten subjects analyzed in the study.
Fast prediction and evaluation of eccentric inspirals using reduced-order models
Barta, Dániel; Vasúth, Mátyás
2018-06-01
A large number of theoretically predicted waveforms are required by matched-filtering searches for the gravitational-wave signals produced by compact binary coalescence. In order to substantially alleviate the computational burden in gravitational-wave searches and parameter estimation without degrading the signal detectability, we propose a novel reduced-order-model (ROM) approach with applications to adiabatic 3PN-accurate inspiral waveforms of nonspinning sources that evolve on either highly or slightly eccentric orbits. We provide a singular-value decomposition-based reduced-basis method in the frequency domain to generate reduced-order approximations of any gravitational waves with acceptable accuracy and precision within the parameter range of the model. We construct efficient reduced bases comprised of a relatively small number of the most relevant waveforms over three-dimensional parameter-space covered by the template bank (total mass 2.15 M⊙≤M ≤215 M⊙ , mass ratio 0.01 ≤q ≤1 , and initial orbital eccentricity 0 ≤e0≤0.95 ). The ROM is designed to predict signals in the frequency band from 10 Hz to 2 kHz for aLIGO and aVirgo design sensitivity. Beside moderating the data reduction, finer sampling of fiducial templates improves the accuracy of surrogates. Considerable increase in the speedup from several hundreds to thousands can be achieved by evaluating surrogates for low-mass systems especially when combined with high-eccentricity.
An Accurate Gaussian Process-Based Early Warning System for Dengue Fever
Albinati, Julio; Meira Jr, Wagner; Pappa, Gisele Lobo
2016-01-01
Dengue fever is a mosquito-borne disease present in all Brazilian territory. Brazilian government, however, lacks an accurate early warning system to quickly predict future dengue outbreaks. Such system would help health authorities to plan their actions and to reduce the impact of the disease in the country. However, most attempts to model dengue fever use parametric models which enforce a specific expected behaviour and fail to capture the inherent complexity of dengue dynamics. Therefore, ...
Lin, L.; Luo, X.; Qin, F.; Yang, J.
2018-03-01
As one of the combustion products of hydrocarbon fuels in a combustion-heated wind tunnel, water vapor may condense during the rapid expansion process, which will lead to a complex two-phase flow inside the wind tunnel and even change the design flow conditions at the nozzle exit. The coupling of the phase transition and the compressible flow makes the estimation of the condensation effects in such wind tunnels very difficult and time-consuming. In this work, a reduced theoretical model is developed to approximately compute the nozzle-exit conditions of a flow including real-gas and homogeneous condensation effects. Specifically, the conservation equations of the axisymmetric flow are first approximated in the quasi-one-dimensional way. Then, the complex process is split into two steps, i.e., a real-gas nozzle flow but excluding condensation, resulting in supersaturated nozzle-exit conditions, and a discontinuous jump at the end of the nozzle from the supersaturated state to a saturated state. Compared with two-dimensional numerical simulations implemented with a detailed condensation model, the reduced model predicts the flow parameters with good accuracy except for some deviations caused by the two-dimensional effect. Therefore, this reduced theoretical model can provide a fast, simple but also accurate estimation of the condensation effect in combustion-heated hypersonic tunnels.
Missif, Lial Raja; Kadhum, Mohammad M.
2017-09-01
Wireless Sensor Network (WSN) has been widely used for monitoring where sensors are deployed to operate independently to sense abnormal phenomena. Most of the proposed environmental monitoring systems are designed based on a predetermined sensing range which does not reflect the sensor reliability, event characteristics, and the environment conditions. Measuring of the capability of a sensor node to accurately detect an event within a sensing field is of great important for monitoring applications. This paper presents an efficient mechanism for even detection based on probabilistic sensing model. Different models have been presented theoretically in this paper to examine their adaptability and applicability to the real environment applications. The numerical results of the experimental evaluation have showed that the probabilistic sensing model provides accurate observation and delectability of an event, and it can be utilized for different environment scenarios.
Bagheri, Shahriar; Wu, Nan; Filizadeh, Shaahin
2018-06-01
This paper presents an iterative numerical method that accurately models an energy harvesting system charging a capacitor with piezoelectric patches. The constitutive relations of piezoelectric materials connected with an external charging circuit with a diode bridge and capacitors lead to the electromechanical coupling effect and the difficulty of deriving accurate transient mechanical response, as well as the charging progress. The proposed model is built upon the Euler-Bernoulli beam theory and takes into account the electromechanical coupling effects as well as the dynamic process of charging an external storage capacitor. The model is validated through experimental tests on a cantilever beam coated with piezoelectric patches. Several parametric studies are performed and the functionality of the model is verified. The efficiency of power harvesting system can be predicted and tuned considering variations in different design parameters. Such a model can be utilized to design robust and optimal energy harvesting system.
Fast and accurate exercise policies for Bermudan swaptions in the LIBOR market model
P.K. Karlsson (Patrik); S. Jain (Shashi); C.W. Oosterlee (Kees)
2016-01-01
htmlabstractThis paper describes an American Monte Carlo approach for obtaining fast and accurate exercise policies for pricing of callable LIBOR Exotics (e.g., Bermudan swaptions) in the LIBOR market model using the Stochastic Grid Bundling Method (SGBM). SGBM is a bundling and regression based
International Nuclear Information System (INIS)
Amini, Y; Emdad, H; Farid, M
2014-01-01
Piezoelectric energy harvesting (PEH) from ambient energy sources, particularly vibrations, has attracted considerable interest throughout the last decade. Since fluid flow has a high energy density, it is one of the best candidates for PEH. Indeed, a piezoelectric energy harvesting process from the fluid flow takes the form of natural three-way coupling of the turbulent fluid flow, the electromechanical effect of the piezoelectric material and the electrical circuit. There are some experimental and numerical studies about piezoelectric energy harvesting from fluid flow in literatures. Nevertheless, accurate modeling for predicting characteristics of this three-way coupling has not yet been developed. In the present study, accurate modeling for this triple coupling is developed and validated by experimental results. A new code based on this modeling in an openFOAM platform is developed. (paper)
Accurate Modelling of Surface Currents and Internal Tides in a Semi-enclosed Coastal Sea
Allen, S. E.; Soontiens, N. K.; Dunn, M. B. H.; Liu, J.; Olson, E.; Halverson, M. J.; Pawlowicz, R.
2016-02-01
The Strait of Georgia is a deep (400 m), strongly stratified, semi-enclosed coastal sea on the west coast of North America. We have configured a baroclinic model of the Strait of Georgia and surrounding coastal waters using the NEMO ocean community model. We run daily nowcasts and forecasts and publish our sea-surface results (including storm surge warnings) to the web (salishsea.eos.ubc.ca/storm-surge). Tides in the Strait of Georgia are mixed and large. The baroclinic model and previous barotropic models accurately represent tidal sea-level variations and depth mean currents. The baroclinic model reproduces accurately the diurnal but not the semi-diurnal baroclinic tidal currents. In the Southern Strait of Georgia, strong internal tidal currents at the semi-diurnal frequency are observed. Strong semi-diurnal tides are also produced in the model, but are almost 180 degrees out of phase with the observations. In the model, in the surface, the barotropic and baroclinic tides reinforce, whereas the observations show that at the surface the baroclinic tides oppose the barotropic. As such the surface currents are very poorly modelled. Here we will present evidence of the internal tidal field from observations. We will discuss the generation regions of the tides, the necessary modifications to the model required to correct the phase, the resulting baroclinic tides and the improvements in the surface currents.
The i-V curve characteristics of burner-stabilized premixed flames: detailed and reduced models
Han, Jie
2016-07-17
The i-V curve describes the current drawn from a flame as a function of the voltage difference applied across the reaction zone. Since combustion diagnostics and flame control strategies based on electric fields depend on the amount of current drawn from flames, there is significant interest in modeling and understanding i-V curves. We implement and apply a detailed model for the simulation of the production and transport of ions and electrons in one-dimensional premixed flames. An analytical reduced model is developed based on the detailed one, and analytical expressions are used to gain insight into the characteristics of the i-Vcurve for various flame configurations. In order for the reduced model to capture the spatial distribution of the electric field accurately, the concept of a dead zone region, where voltage is constant, is introduced, and a suitable closure for the spatial extent of the dead zone is proposed and validated. The results from the reduced modeling framework are found to be in good agreement with those from the detailed simulations. The saturation voltage is found to depend significantly on the flame location relative to the electrodes, and on the sign of the voltage difference applied. Furthermore, at sub-saturation conditions, the current is shown to increase linearly or quadratically with the applied voltage, depending on the flame location. These limiting behaviors exhibited by the reduced model elucidate the features of i-V curves observed experimentally. The reduced model relies on the existence of a thin layer where charges are produced, corresponding to the reaction zone of a flame. Consequently, the analytical model we propose is not limited to the study of premixed flames, and may be applied easily to others configurations, e.g.~nonpremixed counterflow flames.
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.
Fast and accurate calculation of the properties of water and steam for simulation
International Nuclear Information System (INIS)
Szegi, Zs.; Gacs, A.
1990-01-01
A basic principle simulator was developed at the CRIP, Budapest, for real time simulation of the transients of WWER-440 type nuclear power plants. Its integral part is the fast and accurate calculation of the thermodynamic properties of water and steam. To eliminate successive approximations, the model system of the secondary coolant circuit requires binary forms which are known as inverse functions, countinuous when crossing the saturation line, accurate and coherent for all argument combinations. A solution which reduces the computer memory and execution time demand is reported. (author) 36 refs.; 5 figs.; 3 tabs
Turney, Benjamin W
2014-03-01
Obtaining renal access is one of the most important and complex steps in learning percutaneous nephrolithotomy (PCNL). Ideally, this skill should be practiced outside the operating room. There is a need for anatomically accurate and cheap models for simulated training. The objective was to develop a cost-effective, anatomically accurate, nonbiologic training model for simulated PCNL access under fluoroscopic guidance. Collecting systems from routine computed tomography urograms were extracted and reformatted using specialized software. These images were printed in a water-soluble plastic on a three-dimensional (3D) printer to create biomodels. These models were embedded in silicone and then the models were dissolved in water to leave a hollow collecting system within a silicone model. These PCNL models were filled with contrast medium and sealed. A layer of dense foam acted as a spacer to replicate the tissues between skin and kidney. 3D printed models of human collecting systems are a useful adjunct in planning PCNL access. The PCNL access training model is relatively low cost and reproduces the anatomy of the renal collecting system faithfully. A range of models reflecting the variety and complexity of human collecting systems can be reproduced. The fluoroscopic triangulation process needed to target the calix of choice can be practiced successfully in this model. This silicone PCNL training model accurately replicates the anatomic architecture and orientation of the human renal collecting system. It provides a safe, clean, and effective model for training in accurate fluoroscopy-guided PCNL access.
In-situ measurements of material thermal parameters for accurate LED lamp thermal modelling
Vellvehi, M.; Perpina, X.; Jorda, X.; Werkhoven, R.J.; Kunen, J.M.G.; Jakovenko, J.; Bancken, P.; Bolt, P.J.
2013-01-01
This work deals with the extraction of key thermal parameters for accurate thermal modelling of LED lamps: air exchange coefficient around the lamp, emissivity and thermal conductivity of all lamp parts. As a case study, an 8W retrofit lamp is presented. To assess simulation results, temperature is
BEYOND ELLIPSE(S): ACCURATELY MODELING THE ISOPHOTAL STRUCTURE OF GALAXIES WITH ISOFIT AND CMODEL
International Nuclear Information System (INIS)
Ciambur, B. C.
2015-01-01
This work introduces a new fitting formalism for isophotes that enables more accurate modeling of galaxies with non-elliptical shapes, such as disk galaxies viewed edge-on or galaxies with X-shaped/peanut bulges. Within this scheme, the angular parameter that defines quasi-elliptical isophotes is transformed from the commonly used, but inappropriate, polar coordinate to the “eccentric anomaly.” This provides a superior description of deviations from ellipticity, better capturing the true isophotal shape. Furthermore, this makes it possible to accurately recover both the surface brightness profile, using the correct azimuthally averaged isophote, and the two-dimensional model of any galaxy: the hitherto ubiquitous, but artificial, cross-like features in residual images are completely removed. The formalism has been implemented into the Image Reduction and Analysis Facility tasks Ellipse and Bmodel to create the new tasks “Isofit,” and “Cmodel.” The new tools are demonstrated here with application to five galaxies, chosen to be representative case-studies for several areas where this technique makes it possible to gain new scientific insight. Specifically: properly quantifying boxy/disky isophotes via the fourth harmonic order in edge-on galaxies, quantifying X-shaped/peanut bulges, higher-order Fourier moments for modeling bars in disks, and complex isophote shapes. Higher order (n > 4) harmonics now become meaningful and may correlate with structural properties, as boxyness/diskyness is known to do. This work also illustrates how the accurate construction, and subtraction, of a model from a galaxy image facilitates the identification and recovery of over-lapping sources such as globular clusters and the optical counterparts of X-ray sources
Li, Fangzheng; Liu, Chunying; Song, Xuexiong; Huan, Yanjun; Gao, Shansong; Jiang, Zhongling
2018-01-01
Access to adequate anatomical specimens can be an important aspect in learning the anatomy of domestic animals. In this study, the authors utilized a structured light scanner and fused deposition modeling (FDM) printer to produce highly accurate animal skeletal models. First, various components of the bovine skeleton, including the femur, the…
Fast and accurate Bayesian model criticism and conflict diagnostics using R-INLA
Ferkingstad, Egil
2017-10-16
Bayesian hierarchical models are increasingly popular for realistic modelling and analysis of complex data. This trend is accompanied by the need for flexible, general and computationally efficient methods for model criticism and conflict detection. Usually, a Bayesian hierarchical model incorporates a grouping of the individual data points, as, for example, with individuals in repeated measurement data. In such cases, the following question arises: Are any of the groups “outliers,” or in conflict with the remaining groups? Existing general approaches aiming to answer such questions tend to be extremely computationally demanding when model fitting is based on Markov chain Monte Carlo. We show how group-level model criticism and conflict detection can be carried out quickly and accurately through integrated nested Laplace approximations (INLA). The new method is implemented as a part of the open-source R-INLA package for Bayesian computing (http://r-inla.org).
Energy Technology Data Exchange (ETDEWEB)
Ballestrin Bolea, J M; Blazquez Martinez, J B
1990-07-01
BWR stability can be treated with reduced order dynamical models. When the parameters of the model came from dynamical models. When the parameters of the model came from experimental data, the predictions are accurate. In this work an alternative derivation for the void fraction equation is made, but remarking the physical structure of the parameters. As the poles of power/reactivity transfer function are related with the parameters, the measurement of the poles by other techniques such as noise analysis will lead to the parameters, but the system of equations is non-linear. Simple parametric calculation of decay ratio are performed, showing why BWRs become unstable when they are operated at low flow and high power. (Author)
García-Diéguez, Carlos; Bernard, Olivier; Roca, Enrique
2013-03-01
The Anaerobic Digestion Model No. 1 (ADM1) is a complex model which is widely accepted as a common platform for anaerobic process modeling and simulation. However, it has a large number of parameters and states that hinder its calibration and use in control applications. A principal component analysis (PCA) technique was extended and applied to simplify the ADM1 using data of an industrial wastewater treatment plant processing winery effluent. The method shows that the main model features could be obtained with a minimum of two reactions. A reduced stoichiometric matrix was identified and the kinetic parameters were estimated on the basis of representative known biochemical kinetics (Monod and Haldane). The obtained reduced model takes into account the measured states in the anaerobic wastewater treatment (AWT) plant and reproduces the dynamics of the process fairly accurately. The reduced model can support on-line control, optimization and supervision strategies for AWT plants. Copyright © 2013 Elsevier Ltd. All rights reserved.
Accurate calibration of the velocity-dependent one-scale model for domain walls
International Nuclear Information System (INIS)
Leite, A.M.M.; Martins, C.J.A.P.; Shellard, E.P.S.
2013-01-01
We study the asymptotic scaling properties of standard domain wall networks in several cosmological epochs. We carry out the largest field theory simulations achieved to date, with simulation boxes of size 2048 3 , and confirm that a scale-invariant evolution of the network is indeed the attractor solution. The simulations are also used to obtain an accurate calibration for the velocity-dependent one-scale model for domain walls: we numerically determine the two free model parameters to have the values c w =0.34±0.16 and k w =0.98±0.07, which are of higher precision than (but in agreement with) earlier estimates.
Accurate calibration of the velocity-dependent one-scale model for domain walls
Energy Technology Data Exchange (ETDEWEB)
Leite, A.M.M., E-mail: up080322016@alunos.fc.up.pt [Centro de Astrofisica, Universidade do Porto, Rua das Estrelas, 4150-762 Porto (Portugal); Ecole Polytechnique, 91128 Palaiseau Cedex (France); Martins, C.J.A.P., E-mail: Carlos.Martins@astro.up.pt [Centro de Astrofisica, Universidade do Porto, Rua das Estrelas, 4150-762 Porto (Portugal); Shellard, E.P.S., E-mail: E.P.S.Shellard@damtp.cam.ac.uk [Department of Applied Mathematics and Theoretical Physics, Centre for Mathematical Sciences, University of Cambridge, Wilberforce Road, Cambridge CB3 0WA (United Kingdom)
2013-01-08
We study the asymptotic scaling properties of standard domain wall networks in several cosmological epochs. We carry out the largest field theory simulations achieved to date, with simulation boxes of size 2048{sup 3}, and confirm that a scale-invariant evolution of the network is indeed the attractor solution. The simulations are also used to obtain an accurate calibration for the velocity-dependent one-scale model for domain walls: we numerically determine the two free model parameters to have the values c{sub w}=0.34{+-}0.16 and k{sub w}=0.98{+-}0.07, which are of higher precision than (but in agreement with) earlier estimates.
An accurate behavioral model for single-photon avalanche diode statistical performance simulation
Xu, Yue; Zhao, Tingchen; Li, Ding
2018-01-01
An accurate behavioral model is presented to simulate important statistical performance of single-photon avalanche diodes (SPADs), such as dark count and after-pulsing noise. The derived simulation model takes into account all important generation mechanisms of the two kinds of noise. For the first time, thermal agitation, trap-assisted tunneling and band-to-band tunneling mechanisms are simultaneously incorporated in the simulation model to evaluate dark count behavior of SPADs fabricated in deep sub-micron CMOS technology. Meanwhile, a complete carrier trapping and de-trapping process is considered in afterpulsing model and a simple analytical expression is derived to estimate after-pulsing probability. In particular, the key model parameters of avalanche triggering probability and electric field dependence of excess bias voltage are extracted from Geiger-mode TCAD simulation and this behavioral simulation model doesn't include any empirical parameters. The developed SPAD model is implemented in Verilog-A behavioral hardware description language and successfully operated on commercial Cadence Spectre simulator, showing good universality and compatibility. The model simulation results are in a good accordance with the test data, validating high simulation accuracy.
Reduced Moment-Based Models for Oxygen Precipitates and Dislocation Loops in Silicon
Trzynadlowski, Bart
The demand for ever smaller, higher-performance integrated circuits and more efficient, cost-effective solar cells continues to push the frontiers of process technology. Fabrication of silicon devices requires extremely precise control of impurities and crystallographic defects. Failure to do so not only reduces performance, efficiency, and yield, it threatens the very survival of commercial enterprises in today's fiercely competitive and price-sensitive global market. The presence of oxygen in silicon is an unavoidable consequence of the Czochralski process, which remains the most popular method for large-scale production of single-crystal silicon. Oxygen precipitates that form during thermal processing cause distortion of the surrounding silicon lattice and can lead to the formation of dislocation loops. Localized deformation caused by both of these defects introduces potential wells that trap diffusing impurities such as metal atoms, which is highly desirable if done far away from sensitive device regions. Unfortunately, dislocations also reduce the mechanical strength of silicon, which can cause wafer warpage and breakage. Engineers must negotiate this and other complex tradeoffs when designing fabrication processes. Accomplishing this in a complex, modern process involving a large number of thermal steps is impossible without the aid of computational models. In this dissertation, new models for oxygen precipitation and dislocation loop evolution are described. An oxygen model using kinetic rate equations to evolve the complete precipitate size distribution was developed first. This was then used to create a reduced model tracking only the moments of the size distribution. The moment-based model was found to run significantly faster than its full counterpart while accurately capturing the evolution of oxygen precipitates. The reduced model was fitted to experimental data and a sensitivity analysis was performed to assess the robustness of the results. Source
A Two-Scale Reduced Model for Darcy Flow in Fractured Porous Media
Chen, Huangxin
2016-06-01
In this paper, we develop a two-scale reduced model for simulating the Darcy flow in two-dimensional porous media with conductive fractures. We apply the approach motivated by the embedded fracture model (EFM) to simulate the flow on the coarse scale, and the effect of fractures on each coarse scale grid cell intersecting with fractures is represented by the discrete fracture model (DFM) on the fine scale. In the DFM used on the fine scale, the matrix-fracture system are resolved on unstructured grid which represents the fractures accurately, while in the EFM used on the coarse scale, the flux interaction between fractures and matrix are dealt with as a source term, and the matrix-fracture system can be resolved on structured grid. The Raviart-Thomas mixed finite element methods are used for the solution of the coupled flows in the matrix and the fractures on both fine and coarse scales. Numerical results are presented to demonstrate the efficiency of the proposed model for simulation of flow in fractured porous media.
Accurate, model-based tuning of synthetic gene expression using introns in S. cerevisiae.
Directory of Open Access Journals (Sweden)
Ido Yofe
2014-06-01
Full Text Available Introns are key regulators of eukaryotic gene expression and present a potentially powerful tool for the design of synthetic eukaryotic gene expression systems. However, intronic control over gene expression is governed by a multitude of complex, incompletely understood, regulatory mechanisms. Despite this lack of detailed mechanistic understanding, here we show how a relatively simple model enables accurate and predictable tuning of synthetic gene expression system in yeast using several predictive intron features such as transcript folding and sequence motifs. Using only natural Saccharomyces cerevisiae introns as regulators, we demonstrate fine and accurate control over gene expression spanning a 100 fold expression range. These results broaden the engineering toolbox of synthetic gene expression systems and provide a framework in which precise and robust tuning of gene expression is accomplished.
Mohammed, F.
2016-12-01
Landslide hazards such as fast-moving debris flows, slow-moving landslides, and other mass flows cause numerous fatalities, injuries, and damage. Landslide occurrences in fjords, bays, and lakes can additionally generate tsunamis with locally extremely high wave heights and runups. Two-dimensional depth-averaged models can successfully simulate the entire lifecycle of the three-dimensional landslide dynamics and tsunami propagation efficiently and accurately with the appropriate assumptions. Landslide rheology is defined using viscous fluids, visco-plastic fluids, and granular material to account for the possible landslide source materials. Saturated and unsaturated rheologies are further included to simulate debris flow, debris avalanches, mudflows, and rockslides respectively. The models are obtained by reducing the fully three-dimensional Navier-Stokes equations with the internal rheological definition of the landslide material, the water body, and appropriate scaling assumptions to obtain the depth-averaged two-dimensional models. The landslide and tsunami models are coupled to include the interaction between the landslide and the water body for tsunami generation. The reduced models are solved numerically with a fast semi-implicit finite-volume, shock-capturing based algorithm. The well-balanced, positivity preserving algorithm accurately accounts for wet-dry interface transition for the landslide runout, landslide-water body interface, and the tsunami wave flooding on land. The models are implemented as a General-Purpose computing on Graphics Processing Unit-based (GPGPU) suite of models, either coupled or run independently within the suite. The GPGPU implementation provides up to 1000 times speedup over a CPU-based serial computation. This enables simulations of multiple scenarios of hazard realizations that provides a basis for a probabilistic hazard assessment. The models have been successfully validated against experiments, past studies, and field data
A simple but accurate procedure for solving the five-parameter model
International Nuclear Information System (INIS)
Mares, Oana; Paulescu, Marius; Badescu, Viorel
2015-01-01
Highlights: • A new procedure for extracting the parameters of the one-diode model is proposed. • Only the basic information listed in the datasheet of PV modules are required. • Results demonstrate a simple, robust and accurate procedure. - Abstract: The current–voltage characteristic of a photovoltaic module is typically evaluated by using a model based on the solar cell equivalent circuit. The complexity of the procedure applied for extracting the model parameters depends on data available in manufacture’s datasheet. Since the datasheet is not detailed enough, simplified models have to be used in many cases. This paper proposes a new procedure for extracting the parameters of the one-diode model in standard test conditions, using only the basic data listed by all manufactures in datasheet (short circuit current, open circuit voltage and maximum power point). The procedure is validated by using manufacturers’ data for six commercially crystalline silicon photovoltaic modules. Comparing the computed and measured current–voltage characteristics the determination coefficient is in the range 0.976–0.998. Thus, the proposed procedure represents a feasible tool for solving the five-parameter model applied to crystalline silicon photovoltaic modules. The procedure is described in detail, to guide potential users to derive similar models for other types of photovoltaic modules.
Zhao, Xiao-mei; Xie, Dong-fan; Li, Qi
2015-02-01
With the development of intelligent transport system, advanced information feedback strategies have been developed to reduce traffic congestion and enhance the capacity. However, previous strategies provide accurate information to travelers and our simulation results show that accurate information brings negative effects, especially in delay case. Because travelers prefer to the best condition route with accurate information, and delayed information cannot reflect current traffic condition but past. Then travelers make wrong routing decisions, causing the decrease of the capacity and the increase of oscillations and the system deviating from the equilibrium. To avoid the negative effect, bounded rationality is taken into account by introducing a boundedly rational threshold BR. When difference between two routes is less than the BR, routes have equal probability to be chosen. The bounded rationality is helpful to improve the efficiency in terms of capacity, oscillation and the gap deviating from the system equilibrium.
Model's sparse representation based on reduced mixed GMsFE basis methods
Energy Technology Data Exchange (ETDEWEB)
Jiang, Lijian, E-mail: ljjiang@hnu.edu.cn [Institute of Mathematics, Hunan University, Changsha 410082 (China); Li, Qiuqi, E-mail: qiuqili@hnu.edu.cn [College of Mathematics and Econometrics, Hunan University, Changsha 410082 (China)
2017-06-01
In this paper, we propose a model's sparse representation based on reduced mixed generalized multiscale finite element (GMsFE) basis methods for elliptic PDEs with random inputs. A typical application for the elliptic PDEs is the flow in heterogeneous random porous media. Mixed generalized multiscale finite element method (GMsFEM) is one of the accurate and efficient approaches to solve the flow problem in a coarse grid and obtain the velocity with local mass conservation. When the inputs of the PDEs are parameterized by the random variables, the GMsFE basis functions usually depend on the random parameters. This leads to a large number degree of freedoms for the mixed GMsFEM and substantially impacts on the computation efficiency. In order to overcome the difficulty, we develop reduced mixed GMsFE basis methods such that the multiscale basis functions are independent of the random parameters and span a low-dimensional space. To this end, a greedy algorithm is used to find a set of optimal samples from a training set scattered in the parameter space. Reduced mixed GMsFE basis functions are constructed based on the optimal samples using two optimal sampling strategies: basis-oriented cross-validation and proper orthogonal decomposition. Although the dimension of the space spanned by the reduced mixed GMsFE basis functions is much smaller than the dimension of the original full order model, the online computation still depends on the number of coarse degree of freedoms. To significantly improve the online computation, we integrate the reduced mixed GMsFE basis methods with sparse tensor approximation and obtain a sparse representation for the model's outputs. The sparse representation is very efficient for evaluating the model's outputs for many instances of parameters. To illustrate the efficacy of the proposed methods, we present a few numerical examples for elliptic PDEs with multiscale and random inputs. In particular, a two-phase flow model in
A hamster model for Marburg virus infection accurately recapitulates Marburg hemorrhagic fever.
Marzi, Andrea; Banadyga, Logan; Haddock, Elaine; Thomas, Tina; Shen, Kui; Horne, Eva J; Scott, Dana P; Feldmann, Heinz; Ebihara, Hideki
2016-12-15
Marburg virus (MARV), a close relative of Ebola virus, is the causative agent of a severe human disease known as Marburg hemorrhagic fever (MHF). No licensed vaccine or therapeutic exists to treat MHF, and MARV is therefore classified as a Tier 1 select agent and a category A bioterrorism agent. In order to develop countermeasures against this severe disease, animal models that accurately recapitulate human disease are required. Here we describe the development of a novel, uniformly lethal Syrian golden hamster model of MHF using a hamster-adapted MARV variant Angola. Remarkably, this model displayed almost all of the clinical features of MHF seen in humans and non-human primates, including coagulation abnormalities, hemorrhagic manifestations, petechial rash, and a severely dysregulated immune response. This MHF hamster model represents a powerful tool for further dissecting MARV pathogenesis and accelerating the development of effective medical countermeasures against human MHF.
Qi, Di
Turbulent dynamical systems are ubiquitous in science and engineering. Uncertainty quantification (UQ) in turbulent dynamical systems is a grand challenge where the goal is to obtain statistical estimates for key physical quantities. In the development of a proper UQ scheme for systems characterized by both a high-dimensional phase space and a large number of instabilities, significant model errors compared with the true natural signal are always unavoidable due to both the imperfect understanding of the underlying physical processes and the limited computational resources available. One central issue in contemporary research is the development of a systematic methodology for reduced order models that can recover the crucial features both with model fidelity in statistical equilibrium and with model sensitivity in response to perturbations. In the first part, we discuss a general mathematical framework to construct statistically accurate reduced-order models that have skill in capturing the statistical variability in the principal directions of a general class of complex systems with quadratic nonlinearity. A systematic hierarchy of simple statistical closure schemes, which are built through new global statistical energy conservation principles combined with statistical equilibrium fidelity, are designed and tested for UQ of these problems. Second, the capacity of imperfect low-order stochastic approximations to model extreme events in a passive scalar field advected by turbulent flows is investigated. The effects in complicated flow systems are considered including strong nonlinear and non-Gaussian interactions, and much simpler and cheaper imperfect models with model error are constructed to capture the crucial statistical features in the stationary tracer field. Several mathematical ideas are introduced to improve the prediction skill of the imperfect reduced-order models. Most importantly, empirical information theory and statistical linear response theory are
Energy Technology Data Exchange (ETDEWEB)
McDaniel, Dwayne [Florida International Univ., Miami, FL (United States); Dulikravich, George [Florida International Univ., Miami, FL (United States); Cizmas, Paul [Florida International Univ., Miami, FL (United States)
2017-11-27
This report summarizes the objectives, tasks and accomplishments made during the three year duration of this research project. The report presents the results obtained by applying advanced computational techniques to develop reduced-order models (ROMs) in the case of reacting multiphase flows based on high fidelity numerical simulation of gas-solids flow structures in risers and vertical columns obtained by the Multiphase Flow with Interphase eXchanges (MFIX) software. The research includes a numerical investigation of reacting and non-reacting gas-solids flow systems and computational analysis that will involve model development to accelerate the scale-up process for the design of fluidization systems by providing accurate solutions that match the full-scale models. The computational work contributes to the development of a methodology for obtaining ROMs that is applicable to the system of gas-solid flows. Finally, the validity of the developed ROMs is evaluated by comparing the results against those obtained using the MFIX code. Additionally, the robustness of existing POD-based ROMs for multiphase flows is improved by avoiding non-physical solutions of the gas void fraction and ensuring that the reduced kinetics models used for reactive flows in fluidized beds are thermodynamically consistent.
Fast and accurate focusing analysis of large photon sieve using pinhole ring diffraction model.
Liu, Tao; Zhang, Xin; Wang, Lingjie; Wu, Yanxiong; Zhang, Jizhen; Qu, Hemeng
2015-06-10
In this paper, we developed a pinhole ring diffraction model for the focusing analysis of a large photon sieve. Instead of analyzing individual pinholes, we discuss the focusing of all of the pinholes in a single ring. An explicit equation for the diffracted field of individual pinhole ring has been proposed. We investigated the validity range of this generalized model and analytically describe the sufficient conditions for the validity of this pinhole ring diffraction model. A practical example and investigation reveals the high accuracy of the pinhole ring diffraction model. This simulation method could be used for fast and accurate focusing analysis of a large photon sieve.
Rapcsak, Steven Z.; Henry, Maya L.; Teague, Sommer L.; Carnahan, Susan D.; Beeson, Pélagie M.
2007-01-01
Coltheart and colleagues (Coltheart, Rastle, Perry, Langdon, & Ziegler, 2001; Castles, Bates, & Coltheart, 2006) have demonstrated that an equation derived from dual-route theory accurately predicts reading performance in young normal readers and in children with reading impairment due to developmental dyslexia or stroke. In this paper we present evidence that the dual-route equation and a related multiple regression model also accurately predict both reading and spelling performance in adult...
International Nuclear Information System (INIS)
Saito, Toki; Nakajima, Yoshikazu; Sugita, Naohiko; Mitsuishi, Mamoru; Hashizume, Hiroyuki; Kuramoto, Kouichi; Nakashima, Yosio
2011-01-01
Statistical deformable model based two-dimensional/three-dimensional (2-D/3-D) registration is a promising method for estimating the position and shape of patient bone in the surgical space. Since its accuracy depends on the statistical model capacity, we propose a method for accurately generating a statistical bone model from a CT volume. Our method employs the Sphere-Attribute-Image (SAI) and has improved the accuracy of corresponding point search in statistical model generation. At first, target bone surfaces are extracted as SAIs from the CT volume. Then the textures of SAIs are classified to some regions using Maximally-stable-extremal-regions methods. Next, corresponding regions are determined using Normalized cross-correlation (NCC). Finally, corresponding points in each corresponding region are determined using NCC. The application of our method to femur bone models was performed, and worked well in the experiments. (author)
Accurate Modeling of Advanced Reflectarrays
DEFF Research Database (Denmark)
Zhou, Min
to the conventional phase-only optimization technique (POT), the geometrical parameters of the array elements are directly optimized to fulfill the far-field requirements, thus maintaining a direct relation between optimization goals and optimization variables. As a result, better designs can be obtained compared...... of the incident field, the choice of basis functions, and the technique to calculate the far-field. Based on accurate reference measurements of two offset reflectarrays carried out at the DTU-ESA Spherical NearField Antenna Test Facility, it was concluded that the three latter factors are particularly important...... using the GDOT to demonstrate its capabilities. To verify the accuracy of the GDOT, two offset contoured beam reflectarrays that radiate a high-gain beam on a European coverage have been designed and manufactured, and subsequently measured at the DTU-ESA Spherical Near-Field Antenna Test Facility...
An accurate fatigue damage model for welded joints subjected to variable amplitude loading
Aeran, A.; Siriwardane, S. C.; Mikkelsen, O.; Langen, I.
2017-12-01
Researchers in the past have proposed several fatigue damage models to overcome the shortcomings of the commonly used Miner’s rule. However, requirements of material parameters or S-N curve modifications restricts their practical applications. Also, application of most of these models under variable amplitude loading conditions have not been found. To overcome these restrictions, a new fatigue damage model is proposed in this paper. The proposed model can be applied by practicing engineers using only the S-N curve given in the standard codes of practice. The model is verified with experimentally derived damage evolution curves for C 45 and 16 Mn and gives better agreement compared to previous models. The model predicted fatigue lives are also in better correlation with experimental results compared to previous models as shown in earlier published work by the authors. The proposed model is applied to welded joints subjected to variable amplitude loadings in this paper. The model given around 8% shorter fatigue lives compared to Eurocode given Miner’s rule. This shows the importance of applying accurate fatigue damage models for welded joints.
Xu, Xuemiao; Zhang, Huaidong; Han, Guoqiang; Kwan, Kin Chung; Pang, Wai-Man; Fang, Jiaming; Zhao, Gansen
2016-04-11
Exterior orientation parameters' (EOP) estimation using space resection plays an important role in topographic reconstruction for push broom scanners. However, existing models of space resection are highly sensitive to errors in data. Unfortunately, for lunar imagery, the altitude data at the ground control points (GCPs) for space resection are error-prone. Thus, existing models fail to produce reliable EOPs. Motivated by a finding that for push broom scanners, angular rotations of EOPs can be estimated independent of the altitude data and only involving the geographic data at the GCPs, which are already provided, hence, we divide the modeling of space resection into two phases. Firstly, we estimate the angular rotations based on the reliable geographic data using our proposed mathematical model. Then, with the accurate angular rotations, the collinear equations for space resection are simplified into a linear problem, and the global optimal solution for the spatial position of EOPs can always be achieved. Moreover, a certainty term is integrated to penalize the unreliable altitude data for increasing the error tolerance. Experimental results evidence that our model can obtain more accurate EOPs and topographic maps not only for the simulated data, but also for the real data from Chang'E-1, compared to the existing space resection model.
Directory of Open Access Journals (Sweden)
Xuemiao Xu
2016-04-01
Full Text Available Exterior orientation parameters’ (EOP estimation using space resection plays an important role in topographic reconstruction for push broom scanners. However, existing models of space resection are highly sensitive to errors in data. Unfortunately, for lunar imagery, the altitude data at the ground control points (GCPs for space resection are error-prone. Thus, existing models fail to produce reliable EOPs. Motivated by a finding that for push broom scanners, angular rotations of EOPs can be estimated independent of the altitude data and only involving the geographic data at the GCPs, which are already provided, hence, we divide the modeling of space resection into two phases. Firstly, we estimate the angular rotations based on the reliable geographic data using our proposed mathematical model. Then, with the accurate angular rotations, the collinear equations for space resection are simplified into a linear problem, and the global optimal solution for the spatial position of EOPs can always be achieved. Moreover, a certainty term is integrated to penalize the unreliable altitude data for increasing the error tolerance. Experimental results evidence that our model can obtain more accurate EOPs and topographic maps not only for the simulated data, but also for the real data from Chang’E-1, compared to the existing space resection model.
Wang, Shiyao; Deng, Zhidong; Yin, Gang
2016-02-24
A high-performance differential global positioning system (GPS) receiver with real time kinematics provides absolute localization for driverless cars. However, it is not only susceptible to multipath effect but also unable to effectively fulfill precise error correction in a wide range of driving areas. This paper proposes an accurate GPS-inertial measurement unit (IMU)/dead reckoning (DR) data fusion method based on a set of predictive models and occupancy grid constraints. First, we employ a set of autoregressive and moving average (ARMA) equations that have different structural parameters to build maximum likelihood models of raw navigation. Second, both grid constraints and spatial consensus checks on all predictive results and current measurements are required to have removal of outliers. Navigation data that satisfy stationary stochastic process are further fused to achieve accurate localization results. Third, the standard deviation of multimodal data fusion can be pre-specified by grid size. Finally, we perform a lot of field tests on a diversity of real urban scenarios. The experimental results demonstrate that the method can significantly smooth small jumps in bias and considerably reduce accumulated position errors due to DR. With low computational complexity, the position accuracy of our method surpasses existing state-of-the-arts on the same dataset and the new data fusion method is practically applied in our driverless car.
Directory of Open Access Journals (Sweden)
Shiyao Wang
2016-02-01
Full Text Available A high-performance differential global positioning system (GPS receiver with real time kinematics provides absolute localization for driverless cars. However, it is not only susceptible to multipath effect but also unable to effectively fulfill precise error correction in a wide range of driving areas. This paper proposes an accurate GPS–inertial measurement unit (IMU/dead reckoning (DR data fusion method based on a set of predictive models and occupancy grid constraints. First, we employ a set of autoregressive and moving average (ARMA equations that have different structural parameters to build maximum likelihood models of raw navigation. Second, both grid constraints and spatial consensus checks on all predictive results and current measurements are required to have removal of outliers. Navigation data that satisfy stationary stochastic process are further fused to achieve accurate localization results. Third, the standard deviation of multimodal data fusion can be pre-specified by grid size. Finally, we perform a lot of field tests on a diversity of real urban scenarios. The experimental results demonstrate that the method can significantly smooth small jumps in bias and considerably reduce accumulated position errors due to DR. With low computational complexity, the position accuracy of our method surpasses existing state-of-the-arts on the same dataset and the new data fusion method is practically applied in our driverless car.
International Nuclear Information System (INIS)
Pino, Francisco; Roé, Nuria; Aguiar, Pablo; Falcon, Carles; Ros, Domènec; Pavía, Javier
2015-01-01
Purpose: Single photon emission computed tomography (SPECT) has become an important noninvasive imaging technique in small-animal research. Due to the high resolution required in small-animal SPECT systems, the spatially variant system response needs to be included in the reconstruction algorithm. Accurate modeling of the system response should result in a major improvement in the quality of reconstructed images. The aim of this study was to quantitatively assess the impact that an accurate modeling of spatially variant collimator/detector response has on image-quality parameters, using a low magnification SPECT system equipped with a pinhole collimator and a small gamma camera. Methods: Three methods were used to model the point spread function (PSF). For the first, only the geometrical pinhole aperture was included in the PSF. For the second, the septal penetration through the pinhole collimator was added. In the third method, the measured intrinsic detector response was incorporated. Tomographic spatial resolution was evaluated and contrast, recovery coefficients, contrast-to-noise ratio, and noise were quantified using a custom-built NEMA NU 4–2008 image-quality phantom. Results: A high correlation was found between the experimental data corresponding to intrinsic detector response and the fitted values obtained by means of an asymmetric Gaussian distribution. For all PSF models, resolution improved as the distance from the point source to the center of the field of view increased and when the acquisition radius diminished. An improvement of resolution was observed after a minimum of five iterations when the PSF modeling included more corrections. Contrast, recovery coefficients, and contrast-to-noise ratio were better for the same level of noise in the image when more accurate models were included. Ring-type artifacts were observed when the number of iterations exceeded 12. Conclusions: Accurate modeling of the PSF improves resolution, contrast, and recovery
Energy Technology Data Exchange (ETDEWEB)
Pino, Francisco [Unitat de Biofísica, Facultat de Medicina, Universitat de Barcelona, Barcelona 08036, Spain and Servei de Física Mèdica i Protecció Radiològica, Institut Català d’Oncologia, L’Hospitalet de Llobregat 08907 (Spain); Roé, Nuria [Unitat de Biofísica, Facultat de Medicina, Universitat de Barcelona, Barcelona 08036 (Spain); Aguiar, Pablo, E-mail: pablo.aguiar.fernandez@sergas.es [Fundación Ramón Domínguez, Complexo Hospitalario Universitario de Santiago de Compostela 15706, Spain and Grupo de Imagen Molecular, Instituto de Investigacións Sanitarias de Santiago de Compostela (IDIS), Galicia 15782 (Spain); Falcon, Carles; Ros, Domènec [Institut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona 08036, Spain and CIBER en Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Barcelona 08036 (Spain); Pavía, Javier [Institut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona 080836 (Spain); CIBER en Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Barcelona 08036 (Spain); and Servei de Medicina Nuclear, Hospital Clínic, Barcelona 08036 (Spain)
2015-02-15
Purpose: Single photon emission computed tomography (SPECT) has become an important noninvasive imaging technique in small-animal research. Due to the high resolution required in small-animal SPECT systems, the spatially variant system response needs to be included in the reconstruction algorithm. Accurate modeling of the system response should result in a major improvement in the quality of reconstructed images. The aim of this study was to quantitatively assess the impact that an accurate modeling of spatially variant collimator/detector response has on image-quality parameters, using a low magnification SPECT system equipped with a pinhole collimator and a small gamma camera. Methods: Three methods were used to model the point spread function (PSF). For the first, only the geometrical pinhole aperture was included in the PSF. For the second, the septal penetration through the pinhole collimator was added. In the third method, the measured intrinsic detector response was incorporated. Tomographic spatial resolution was evaluated and contrast, recovery coefficients, contrast-to-noise ratio, and noise were quantified using a custom-built NEMA NU 4–2008 image-quality phantom. Results: A high correlation was found between the experimental data corresponding to intrinsic detector response and the fitted values obtained by means of an asymmetric Gaussian distribution. For all PSF models, resolution improved as the distance from the point source to the center of the field of view increased and when the acquisition radius diminished. An improvement of resolution was observed after a minimum of five iterations when the PSF modeling included more corrections. Contrast, recovery coefficients, and contrast-to-noise ratio were better for the same level of noise in the image when more accurate models were included. Ring-type artifacts were observed when the number of iterations exceeded 12. Conclusions: Accurate modeling of the PSF improves resolution, contrast, and recovery
Reduced-Order Modeling of 3D Rayleigh-Benard Turbulent Convection
Hassanzadeh, Pedram; Grover, Piyush; Nabi, Saleh
2017-11-01
Accurate Reduced-Order Models (ROMs) of turbulent geophysical flows have broad applications in science and engineering; for example, to study the climate system or to perform real-time flow control/optimization in energy systems. Here we focus on 3D Rayleigh-Benard turbulent convection at the Rayleigh number of 106 as a prototype for turbulent geophysical flows, which are dominantly buoyancy driven. The purpose of the study is to evaluate and improve the performance of different model reduction techniques using this setting. One-dimensional ROMs for horizontally averaged temperature are calculated using several methods. Specifically, the Linear Response Function (LRF) of the system is calculated from a large DNS dataset using Dynamic Mode Decomposition (DMD) and Fluctuation-Dissipation Theorem (FDT). The LRF is also calculated using the Green's function method of Hassanzadeh and Kuang (2016, J. Atmos. Sci.), which is based on using numerous forced DNS runs. The performance of these LRFs in estimating the system's response to weak external forcings or controlling the time-mean flow are compared and contrasted. The spectral properties of the LRFs and the scaling of the accuracy with the length of the dataset (for the data-driven methods) are also discussed.
Can crop-climate models be accurate and precise? A case study for wheat production in Denmark
DEFF Research Database (Denmark)
Montesino San Martin, Manuel; Olesen, Jørgen E.; Porter, John Roy
2015-01-01
Crop models, used to make projections of climate change impacts, differ greatly in structural detail. Complexity of model structure has generic effects on uncertainty and error propagation in climate change impact assessments. We applied Bayesian calibration to three distinctly different empirical....... Yields predicted by the mechanistic model were generally more accurate than the empirical models for extrapolated conditions. This trend does not hold for all extrapolations; mechanistic and empirical models responded differently due to their sensitivities to distinct weather features. However, higher...... suitable for generic model ensembles for near-term agricultural impact assessments of climate change....
Directory of Open Access Journals (Sweden)
Chen Xin
2015-10-01
Full Text Available Aerothermoelasticity is one of the key technologies for hypersonic vehicles. Accurate and efficient computation of the aerothermodynamics is one of the primary challenges for hypersonic aerothermoelastic analysis. Aimed at solving the shortcomings of engineering calculation, computation fluid dynamics (CFD and experimental investigation, a reduced order modeling (ROM framework for aerothermodynamics based on CFD predictions using an enhanced algorithm of fast maximin Latin hypercube design is developed. Both proper orthogonal decomposition (POD and surrogate are considered and compared to construct ROMs. Two surrogate approaches named Kriging and optimized radial basis function (ORBF are utilized to construct ROMs. Furthermore, an enhanced algorithm of fast maximin Latin hypercube design is proposed, which proves to be helpful to improve the precisions of ROMs. Test results for the three-dimensional aerothermodynamic over a hypersonic surface indicate that: the ROMs precision based on Kriging is better than that by ORBF, ROMs based on Kriging are marginally more accurate than ROMs based on POD-Kriging. In a word, the ROM framework for hypersonic aerothermodynamics has good precision and efficiency.
Model predictive control based on reduced order models applied to belt conveyor system.
Chen, Wei; Li, Xin
2016-11-01
In the paper, a model predictive controller based on reduced order model is proposed to control belt conveyor system, which is an electro-mechanics complex system with long visco-elastic body. Firstly, in order to design low-degree controller, the balanced truncation method is used for belt conveyor model reduction. Secondly, MPC algorithm based on reduced order model for belt conveyor system is presented. Because of the error bound between the full-order model and reduced order model, two Kalman state estimators are applied in the control scheme to achieve better system performance. Finally, the simulation experiments are shown that balanced truncation method can significantly reduce the model order with high-accuracy and model predictive control based on reduced-model performs well in controlling the belt conveyor system. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.
Hackel, Stefan; Montenbruck, Oliver; Steigenberger, -Peter; Eineder, Michael; Gisinger, Christoph
Remote sensing satellites support a broad range of scientific and commercial applications. The two radar imaging satellites TerraSAR-X and TanDEM-X provide spaceborne Synthetic Aperture Radar (SAR) and interferometric SAR data with a very high accuracy. The increasing demand for precise radar products relies on sophisticated validation methods, which require precise and accurate orbit products. Basically, the precise reconstruction of the satellite’s trajectory is based on the Global Positioning System (GPS) measurements from a geodetic-grade dual-frequency receiver onboard the spacecraft. The Reduced Dynamic Orbit Determination (RDOD) approach utilizes models for the gravitational and non-gravitational forces. Following a proper analysis of the orbit quality, systematics in the orbit products have been identified, which reflect deficits in the non-gravitational force models. A detailed satellite macro model is introduced to describe the geometry and the optical surface properties of the satellite. Two major non-gravitational forces are the direct and the indirect Solar Radiation Pressure (SRP). Due to the dusk-dawn orbit configuration of TerraSAR-X, the satellite is almost constantly illuminated by the Sun. Therefore, the direct SRP has an effect on the lateral stability of the determined orbit. The indirect effect of the solar radiation principally contributes to the Earth Radiation Pressure (ERP). The resulting force depends on the sunlight, which is reflected by the illuminated Earth surface in the visible, and the emission of the Earth body in the infrared spectra. Both components of ERP require Earth models to describe the optical properties of the Earth surface. Therefore, the influence of different Earth models on the orbit quality is assessed within the presentation. The presentation highlights the influence of non-gravitational force and satellite macro models on the orbit quality of TerraSAR-X.
Calculation of accurate small angle X-ray scattering curves from coarse-grained protein models
Directory of Open Access Journals (Sweden)
Stovgaard Kasper
2010-08-01
Full Text Available Abstract Background Genome sequencing projects have expanded the gap between the amount of known protein sequences and structures. The limitations of current high resolution structure determination methods make it unlikely that this gap will disappear in the near future. Small angle X-ray scattering (SAXS is an established low resolution method for routinely determining the structure of proteins in solution. The purpose of this study is to develop a method for the efficient calculation of accurate SAXS curves from coarse-grained protein models. Such a method can for example be used to construct a likelihood function, which is paramount for structure determination based on statistical inference. Results We present a method for the efficient calculation of accurate SAXS curves based on the Debye formula and a set of scattering form factors for dummy atom representations of amino acids. Such a method avoids the computationally costly iteration over all atoms. We estimated the form factors using generated data from a set of high quality protein structures. No ad hoc scaling or correction factors are applied in the calculation of the curves. Two coarse-grained representations of protein structure were investigated; two scattering bodies per amino acid led to significantly better results than a single scattering body. Conclusion We show that the obtained point estimates allow the calculation of accurate SAXS curves from coarse-grained protein models. The resulting curves are on par with the current state-of-the-art program CRYSOL, which requires full atomic detail. Our method was also comparable to CRYSOL in recognizing native structures among native-like decoys. As a proof-of-concept, we combined the coarse-grained Debye calculation with a previously described probabilistic model of protein structure, TorusDBN. This resulted in a significant improvement in the decoy recognition performance. In conclusion, the presented method shows great promise for
Directory of Open Access Journals (Sweden)
F. Coccetti
2003-01-01
Full Text Available In this contribution we present an accurate investigation of three different techniques for the modeling of complex planar circuits. The em analysis is performed by means of different electromagnetic full-wave solvers in the timedomain and in the frequency-domain. The first one is the Transmission Line Matrix (TLM method. In the second one the TLM method is combined with the Integral Equation (IE method. The latter is based on the Generalized Transverse Resonance Diffraction (GTRD. In order to test the methods we model different structures and compare the calculated Sparameters to measured results, with good agreement.
Energy Technology Data Exchange (ETDEWEB)
Meeks, E.; Chou, C. -P.; Garratt, T.
2013-03-31
Engineering simulations of coal gasifiers are typically performed using computational fluid dynamics (CFD) software, where a 3-D representation of the gasifier equipment is used to model the fluid flow in the gasifier and source terms from the coal gasification process are captured using discrete-phase model source terms. Simulations using this approach can be very time consuming, making it difficult to imbed such models into overall system simulations for plant design and optimization. For such system-level designs, process flowsheet software is typically used, such as Aspen Plus® [1], where each component where each component is modeled using a reduced-order model. For advanced power-generation systems, such as integrated gasifier/gas-turbine combined-cycle systems (IGCC), the critical components determining overall process efficiency and emissions are usually the gasifier and combustor. Providing more accurate and more computationally efficient reduced-order models for these components, then, enables much more effective plant-level design optimization and design for control. Based on the CHEMKIN-PRO and ENERGICO software, we have developed an automated methodology for generating an advanced form of reduced-order model for gasifiers and combustors. The reducedorder model offers representation of key unit operations in flowsheet simulations, while allowing simulation that is fast enough to be used in iterative flowsheet calculations. Using high-fidelity fluiddynamics models as input, Reaction Design’s ENERGICO® [2] software can automatically extract equivalent reactor networks (ERNs) from a CFD solution. For the advanced reduced-order concept, we introduce into the ERN a much more detailed kinetics model than can be included practically in the CFD simulation. The state-of-the-art chemistry solver technology within CHEMKIN-PRO allows that to be accomplished while still maintaining a very fast model turn-around time. In this way, the ERN becomes the basis for
Hybrid reduced order modeling for assembly calculations
Energy Technology Data Exchange (ETDEWEB)
Bang, Youngsuk, E-mail: ysbang00@fnctech.com [FNC Technology, Co. Ltd., Yongin-si (Korea, Republic of); Abdel-Khalik, Hany S., E-mail: abdelkhalik@purdue.edu [Purdue University, West Lafayette, IN (United States); Jessee, Matthew A., E-mail: jesseema@ornl.gov [Oak Ridge National Laboratory, Oak Ridge, TN (United States); Mertyurek, Ugur, E-mail: mertyurek@ornl.gov [Oak Ridge National Laboratory, Oak Ridge, TN (United States)
2015-12-15
Highlights: • Reducing computational cost in engineering calculations. • Reduced order modeling algorithm for multi-physics problem like assembly calculation. • Non-intrusive algorithm with random sampling. • Pattern recognition in the components with high sensitive and large variation. - Abstract: While the accuracy of assembly calculations has considerably improved due to the increase in computer power enabling more refined description of the phase space and use of more sophisticated numerical algorithms, the computational cost continues to increase which limits the full utilization of their effectiveness for routine engineering analysis. Reduced order modeling is a mathematical vehicle that scales down the dimensionality of large-scale numerical problems to enable their repeated executions on small computing environment, often available to end users. This is done by capturing the most dominant underlying relationships between the model's inputs and outputs. Previous works demonstrated the use of the reduced order modeling for a single physics code, such as a radiation transport calculation. This manuscript extends those works to coupled code systems as currently employed in assembly calculations. Numerical tests are conducted using realistic SCALE assembly models with resonance self-shielding, neutron transport, and nuclides transmutation/depletion models representing the components of the coupled code system.
Hybrid reduced order modeling for assembly calculations
International Nuclear Information System (INIS)
Bang, Youngsuk; Abdel-Khalik, Hany S.; Jessee, Matthew A.; Mertyurek, Ugur
2015-01-01
Highlights: • Reducing computational cost in engineering calculations. • Reduced order modeling algorithm for multi-physics problem like assembly calculation. • Non-intrusive algorithm with random sampling. • Pattern recognition in the components with high sensitive and large variation. - Abstract: While the accuracy of assembly calculations has considerably improved due to the increase in computer power enabling more refined description of the phase space and use of more sophisticated numerical algorithms, the computational cost continues to increase which limits the full utilization of their effectiveness for routine engineering analysis. Reduced order modeling is a mathematical vehicle that scales down the dimensionality of large-scale numerical problems to enable their repeated executions on small computing environment, often available to end users. This is done by capturing the most dominant underlying relationships between the model's inputs and outputs. Previous works demonstrated the use of the reduced order modeling for a single physics code, such as a radiation transport calculation. This manuscript extends those works to coupled code systems as currently employed in assembly calculations. Numerical tests are conducted using realistic SCALE assembly models with resonance self-shielding, neutron transport, and nuclides transmutation/depletion models representing the components of the coupled code system.
Xiao, Suzhi; Tao, Wei; Zhao, Hui
2016-04-28
In order to acquire an accurate three-dimensional (3D) measurement, the traditional fringe projection technique applies complex and laborious procedures to compensate for the errors that exist in the vision system. However, the error sources in the vision system are very complex, such as lens distortion, lens defocus, and fringe pattern nonsinusoidality. Some errors cannot even be explained or rendered with clear expressions and are difficult to compensate directly as a result. In this paper, an approach is proposed that avoids the complex and laborious compensation procedure for error sources but still promises accurate 3D measurement. It is realized by the mathematical model extension technique. The parameters of the extended mathematical model for the 'phase to 3D coordinates transformation' are derived using the least-squares parameter estimation algorithm. In addition, a phase-coding method based on a frequency analysis is proposed for the absolute phase map retrieval to spatially isolated objects. The results demonstrate the validity and the accuracy of the proposed flexible fringe projection vision system on spatially continuous and discontinuous objects for 3D measurement.
Rapcsak, Steven Z; Henry, Maya L; Teague, Sommer L; Carnahan, Susan D; Beeson, Pélagie M
2007-06-18
Coltheart and co-workers [Castles, A., Bates, T. C., & Coltheart, M. (2006). John Marshall and the developmental dyslexias. Aphasiology, 20, 871-892; Coltheart, M., Rastle, K., Perry, C., Langdon, R., & Ziegler, J. (2001). DRC: A dual route cascaded model of visual word recognition and reading aloud. Psychological Review, 108, 204-256] have demonstrated that an equation derived from dual-route theory accurately predicts reading performance in young normal readers and in children with reading impairment due to developmental dyslexia or stroke. In this paper, we present evidence that the dual-route equation and a related multiple regression model also accurately predict both reading and spelling performance in adult neurological patients with acquired alexia and agraphia. These findings provide empirical support for dual-route theories of written language processing.
International Nuclear Information System (INIS)
Chin, Vun Jack; Salam, Zainal; Ishaque, Kashif
2016-01-01
Highlights: • An accurate computational method for the two-diode model of PV module is proposed. • The hybrid method employs analytical equations and Differential Evolution (DE). • I PV , I o1 , and R p are computed analytically, while a 1 , a 2 , I o2 and R s are optimized. • This allows the model parameters to be computed without using costly assumptions. - Abstract: This paper proposes an accurate computational technique for the two-diode model of PV module. Unlike previous methods, it does not rely on assumptions that cause the accuracy to be compromised. The key to this improvement is the implementation of a hybrid solution, i.e. by incorporating the analytical method with the differential evolution (DE) optimization technique. Three parameters, i.e. I PV , I o1 , and R p are computed analytically, while the remaining, a 1 , a 2 , I o2 and R s are optimized using the DE. To validate its accuracy, the proposed method is tested on three PV modules of different technologies: mono-crystalline, poly-crystalline and thin film. Furthermore, its performance is evaluated against two popular computational methods for the two-diode model. The proposed method is found to exhibit superior accuracy for the variation in irradiance and temperature for all module types. In particular, the improvement in accuracy is evident at low irradiance conditions; the root-mean-square error is one order of magnitude lower than that of the other methods. In addition, the values of the model parameters are consistent with the physics of PV cell. It is envisaged that the method can be very useful for PV simulation, in which accuracy of the model is of prime concern.
Wang, Mingyu; Han, Lijuan; Liu, Shasha; Zhao, Xuebing; Yang, Jinghua; Loh, Soh Kheang; Sun, Xiaomin; Zhang, Chenxi; Fang, Xu
2015-09-01
Renewable energy from lignocellulosic biomass has been deemed an alternative to depleting fossil fuels. In order to improve this technology, we aim to develop robust mathematical models for the enzymatic lignocellulose degradation process. By analyzing 96 groups of previously published and newly obtained lignocellulose saccharification results and fitting them to Weibull distribution, we discovered Weibull statistics can accurately predict lignocellulose saccharification data, regardless of the type of substrates, enzymes and saccharification conditions. A mathematical model for enzymatic lignocellulose degradation was subsequently constructed based on Weibull statistics. Further analysis of the mathematical structure of the model and experimental saccharification data showed the significance of the two parameters in this model. In particular, the λ value, defined the characteristic time, represents the overall performance of the saccharification system. This suggestion was further supported by statistical analysis of experimental saccharification data and analysis of the glucose production levels when λ and n values change. In conclusion, the constructed Weibull statistics-based model can accurately predict lignocellulose hydrolysis behavior and we can use the λ parameter to assess the overall performance of enzymatic lignocellulose degradation. Advantages and potential applications of the model and the λ value in saccharification performance assessment were discussed. Copyright © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Learning reduced kinetic Monte Carlo models of complex chemistry from molecular dynamics.
Yang, Qian; Sing-Long, Carlos A; Reed, Evan J
2017-08-01
We propose a novel statistical learning framework for automatically and efficiently building reduced kinetic Monte Carlo (KMC) models of large-scale elementary reaction networks from data generated by a single or few molecular dynamics simulations (MD). Existing approaches for identifying species and reactions from molecular dynamics typically use bond length and duration criteria, where bond duration is a fixed parameter motivated by an understanding of bond vibrational frequencies. In contrast, we show that for highly reactive systems, bond duration should be a model parameter that is chosen to maximize the predictive power of the resulting statistical model. We demonstrate our method on a high temperature, high pressure system of reacting liquid methane, and show that the learned KMC model is able to extrapolate more than an order of magnitude in time for key molecules. Additionally, our KMC model of elementary reactions enables us to isolate the most important set of reactions governing the behavior of key molecules found in the MD simulation. We develop a new data-driven algorithm to reduce the chemical reaction network which can be solved either as an integer program or efficiently using L1 regularization, and compare our results with simple count-based reduction. For our liquid methane system, we discover that rare reactions do not play a significant role in the system, and find that less than 7% of the approximately 2000 reactions observed from molecular dynamics are necessary to reproduce the molecular concentration over time of methane. The framework described in this work paves the way towards a genomic approach to studying complex chemical systems, where expensive MD simulation data can be reused to contribute to an increasingly large and accurate genome of elementary reactions and rates.
A new model for the accurate calculation of natural gas viscosity
Directory of Open Access Journals (Sweden)
Xiaohong Yang
2017-03-01
Full Text Available Viscosity of natural gas is a basic and important parameter, of theoretical and practical significance in the domain of natural gas recovery, transmission and processing. In order to obtain the accurate viscosity data efficiently at a low cost, a new model and its corresponding functional relation are derived on the basis of the relationship among viscosity, temperature and density derived from the kinetic theory of gases. After the model parameters were optimized using a lot of experimental data, the diagram showing the variation of viscosity along with temperature and density is prepared, showing that: ① the gas viscosity increases with the increase of density as well as the increase of temperature in the low density region; ② the gas viscosity increases with the decrease of temperature in high density region. With this new model, the viscosity of 9 natural gas samples was calculated precisely. The average relative deviation between these calculated values and 1539 experimental data measured at 250–450 K and 0.10–140.0 MPa is less than 1.9%. Compared with the 793 experimental data with a measurement error less than 0.5%, the maximum relative deviation is less than 0.98%. It is concluded that this new model is more advantageous than the previous 8 models in terms of simplicity, accuracy, fast calculation, and direct applicability to the CO2 bearing gas samples.
Yang, Q.; Liu, X.; Wu, W.; Kizer, S.; Baize, R. R.
2016-12-01
Fast and accurate radiative transfer model is the key for satellite data assimilation and observation system simulation experiments for numerical weather prediction and climate study applications. We proposed and developed a dual stream PCRTM-SOLAR model which may simulate radiative transfer in the cloudy atmosphere with solar radiation quickly and accurately. Multi-scattering of multiple layers of clouds/aerosols is included in the model. The root-mean-square errors are usually less than 5x10-4 mW/cm2.sr.cm-1. The computation speed is 3 to 4 orders of magnitude faster than the medium speed correlated-k option MODTRAN5. This model will enable a vast new set of scientific calculations that were previously limited due to the computational expenses of available radiative transfer models.
Nonperturbative treatment of reduced model with fermions
International Nuclear Information System (INIS)
Gutierrez, W.R.
1983-01-01
A nonperturbative method is presented to show that the reduced model produces the correct leading large-N contribution to the fermion Green's functions. A new form of the reduced model is introduced, which avoids the quenching procedure. Also the equation for the meson bound states is discussed. The method is illustrated in the case of two-dimensional QCD
Machine learning of parameters for accurate semiempirical quantum chemical calculations
International Nuclear Information System (INIS)
Dral, Pavlo O.; Lilienfeld, O. Anatole von; Thiel, Walter
2015-01-01
We investigate possible improvements in the accuracy of semiempirical quantum chemistry (SQC) methods through the use of machine learning (ML) models for the parameters. For a given class of compounds, ML techniques require sufficiently large training sets to develop ML models that can be used for adapting SQC parameters to reflect changes in molecular composition and geometry. The ML-SQC approach allows the automatic tuning of SQC parameters for individual molecules, thereby improving the accuracy without deteriorating transferability to molecules with molecular descriptors very different from those in the training set. The performance of this approach is demonstrated for the semiempirical OM2 method using a set of 6095 constitutional isomers C 7 H 10 O 2 , for which accurate ab initio atomization enthalpies are available. The ML-OM2 results show improved average accuracy and a much reduced error range compared with those of standard OM2 results, with mean absolute errors in atomization enthalpies dropping from 6.3 to 1.7 kcal/mol. They are also found to be superior to the results from specific OM2 reparameterizations (rOM2) for the same set of isomers. The ML-SQC approach thus holds promise for fast and reasonably accurate high-throughput screening of materials and molecules
Chen, Xin; Liu, Li; Zhou, Sida; Yue, Zhenjiang
2016-09-01
Reduced order models(ROMs) based on the snapshots on the CFD high-fidelity simulations have been paid great attention recently due to their capability of capturing the features of the complex geometries and flow configurations. To improve the efficiency and precision of the ROMs, it is indispensable to add extra sampling points to the initial snapshots, since the number of sampling points to achieve an adequately accurate ROM is generally unknown in prior, but a large number of initial sampling points reduces the parsimony of the ROMs. A fuzzy-clustering-based adding-point strategy is proposed and the fuzzy clustering acts an indicator of the region in which the precision of ROMs is relatively low. The proposed method is applied to construct the ROMs for the benchmark mathematical examples and a numerical example of hypersonic aerothermodynamics prediction for a typical control surface. The proposed method can achieve a 34.5% improvement on the efficiency than the estimated mean squared error prediction algorithm and shows same-level prediction accuracy.
International Nuclear Information System (INIS)
Liu Quanwei; Luo Zhongyan; Zhu Haiqiao; Wu Jizong
2007-01-01
For high radioactivity level of dissolved solution of spent fuel and the solution of uranium product, radioactive hazard must be considered and reduced as low as possible during accurate determination of uranium. In this work automatic potentiometric titration was applied and the sample only 10 mg of uranium contained was taken in order to reduce the harm of analyzer suffered from the radioactivity. RSD<0.06%, at the same time the result can be corrected for more reliable and accurate measurement. The determination method can effectively reduce the harm of analyzer suffered from the radioactivity, and meets the requirement of reliable accurate measurement of uranium. (authors)
Towards more accurate wind and solar power prediction by improving NWP model physics
Steiner, Andrea; Köhler, Carmen; von Schumann, Jonas; Ritter, Bodo
2014-05-01
The growing importance and successive expansion of renewable energies raise new challenges for decision makers, economists, transmission system operators, scientists and many more. In this interdisciplinary field, the role of Numerical Weather Prediction (NWP) is to reduce the errors and provide an a priori estimate of remaining uncertainties associated with the large share of weather-dependent power sources. For this purpose it is essential to optimize NWP model forecasts with respect to those prognostic variables which are relevant for wind and solar power plants. An improved weather forecast serves as the basis for a sophisticated power forecasts. Consequently, a well-timed energy trading on the stock market, and electrical grid stability can be maintained. The German Weather Service (DWD) currently is involved with two projects concerning research in the field of renewable energy, namely ORKA*) and EWeLiNE**). Whereas the latter is in collaboration with the Fraunhofer Institute (IWES), the project ORKA is led by energy & meteo systems (emsys). Both cooperate with German transmission system operators. The goal of the projects is to improve wind and photovoltaic (PV) power forecasts by combining optimized NWP and enhanced power forecast models. In this context, the German Weather Service aims to improve its model system, including the ensemble forecasting system, by working on data assimilation, model physics and statistical post processing. This presentation is focused on the identification of critical weather situations and the associated errors in the German regional NWP model COSMO-DE. First steps leading to improved physical parameterization schemes within the NWP-model are presented. Wind mast measurements reaching up to 200 m height above ground are used for the estimation of the (NWP) wind forecast error at heights relevant for wind energy plants. One particular problem is the daily cycle in wind speed. The transition from stable stratification during
Directory of Open Access Journals (Sweden)
Suzhi Xiao
2016-04-01
Full Text Available In order to acquire an accurate three-dimensional (3D measurement, the traditional fringe projection technique applies complex and laborious procedures to compensate for the errors that exist in the vision system. However, the error sources in the vision system are very complex, such as lens distortion, lens defocus, and fringe pattern nonsinusoidality. Some errors cannot even be explained or rendered with clear expressions and are difficult to compensate directly as a result. In this paper, an approach is proposed that avoids the complex and laborious compensation procedure for error sources but still promises accurate 3D measurement. It is realized by the mathematical model extension technique. The parameters of the extended mathematical model for the ’phase to 3D coordinates transformation’ are derived using the least-squares parameter estimation algorithm. In addition, a phase-coding method based on a frequency analysis is proposed for the absolute phase map retrieval to spatially isolated objects. The results demonstrate the validity and the accuracy of the proposed flexible fringe projection vision system on spatially continuous and discontinuous objects for 3D measurement.
Generalized Reduced Order Model Generation, Phase I
National Aeronautics and Space Administration — M4 Engineering proposes to develop a generalized reduced order model generation method. This method will allow for creation of reduced order aeroservoelastic state...
A new algebraic turbulence model for accurate description of airfoil flows
Xiao, Meng-Juan; She, Zhen-Su
2017-11-01
We report a new algebraic turbulence model (SED-SL) based on the SED theory, a symmetry-based approach to quantifying wall turbulence. The model specifies a multi-layer profile of a stress length (SL) function in both the streamwise and wall-normal directions, which thus define the eddy viscosity in the RANS equation (e.g. a zero-equation model). After a successful simulation of flat plate flow (APS meeting, 2016), we report here further applications of the model to the flow around airfoil, with significant improvement of the prediction accuracy of the lift (CL) and drag (CD) coefficients compared to other popular models (e.g. BL, SA, etc.). Two airfoils, namely RAE2822 airfoil and NACA0012 airfoil, are computed for over 50 cases. The results are compared to experimental data from AGARD report, which shows deviations of CL bounded within 2%, and CD within 2 counts (10-4) for RAE2822 and 6 counts for NACA0012 respectively (under a systematic adjustment of the flow conditions). In all these calculations, only one parameter (proportional to the Karmen constant) shows slight variation with Mach number. The most remarkable outcome is, for the first time, the accurate prediction of the drag coefficient. The other interesting outcome is the physical interpretation of the multi-layer parameters: they specify the corresponding multi-layer structure of turbulent boundary layer; when used together with simulation data, the SED-SL enables one to extract physical information from empirical data, and to understand the variation of the turbulent boundary layer.
An accurate analytical solution of a zero-dimensional greenhouse model for global warming
International Nuclear Information System (INIS)
Foong, S K
2006-01-01
In introducing the complex subject of global warming, books and papers usually use the zero-dimensional greenhouse model. When the ratio of the infrared radiation energy of the Earth's surface that is lost to outer space to the non-reflected average solar radiation energy is small, the model admits an accurate approximate analytical solution-the resulting energy balance equation of the model is a quartic equation that can be solved analytically-and thus provides an alternative solution and instructional strategy. A search through the literature fails to find an analytical solution, suggesting that the solution may be new. In this paper, we review the model, derive the approximation and obtain its solution. The dependence of the temperature of the surface of the Earth and the temperature of the atmosphere on seven parameters is made explicit. A simple and convenient formula for global warming (or cooling) in terms of the percentage change of the parameters is derived. The dependence of the surface temperature on the parameters is illustrated by several representative graphs
Fast and accurate modeling of stray light in optical systems
Perrin, Jean-Claude
2017-11-01
The first problem to be solved in most optical designs with respect to stray light is that of internal reflections on the several surfaces of individual lenses and mirrors, and on the detector itself. The level of stray light ratio can be considerably reduced by taking into account the stray light during the optimization to determine solutions in which the irradiance due to these ghosts is kept to the minimum possible value. Unhappily, the routines available in most optical design software's, for example CODE V, do not permit all alone to make exact quantitative calculations of the stray light due to these ghosts. Therefore, the engineer in charge of the optical design is confronted to the problem of using two different software's, one for the design and optimization, for example CODE V, one for stray light analysis, for example ASAP. This makes a complete optimization very complex . Nevertheless, using special techniques and combinations of the routines available in CODE V, it is possible to have at its disposal a software macro tool to do such an analysis quickly and accurately, including Monte-Carlo ray tracing, or taking into account diffraction effects. This analysis can be done in a few minutes, to be compared to hours with other software's.
An Efficient Hybrid DSMC/MD Algorithm for Accurate Modeling of Micro Gas Flows
Liang, Tengfei
2013-01-01
Aiming at simulating micro gas flows with accurate boundary conditions, an efficient hybrid algorithmis developed by combining themolecular dynamics (MD) method with the direct simulationMonte Carlo (DSMC)method. The efficiency comes from the fact that theMD method is applied only within the gas-wall interaction layer, characterized by the cut-off distance of the gas-solid interaction potential, to resolve accurately the gas-wall interaction process, while the DSMC method is employed in the remaining portion of the flow field to efficiently simulate rarefied gas transport outside the gas-wall interaction layer. A unique feature about the present scheme is that the coupling between the two methods is realized by matching the molecular velocity distribution function at the DSMC/MD interface, hence there is no need for one-toone mapping between a MD gas molecule and a DSMC simulation particle. Further improvement in efficiency is achieved by taking advantage of gas rarefaction inside the gas-wall interaction layer and by employing the "smart-wall model" proposed by Barisik et al. The developed hybrid algorithm is validated on two classical benchmarks namely 1-D Fourier thermal problem and Couette shear flow problem. Both the accuracy and efficiency of the hybrid algorithm are discussed. As an application, the hybrid algorithm is employed to simulate thermal transpiration coefficient in the free-molecule regime for a system with atomically smooth surface. Result is utilized to validate the coefficients calculated from the pure DSMC simulation with Maxwell and Cercignani-Lampis gas-wall interaction models. ©c 2014 Global-Science Press.
Reduced modeling of signal transduction – a modular approach
Directory of Open Access Journals (Sweden)
Ederer Michael
2007-09-01
Full Text Available Abstract Background Combinatorial complexity is a challenging problem in detailed and mechanistic mathematical modeling of signal transduction. This subject has been discussed intensively and a lot of progress has been made within the last few years. A software tool (BioNetGen was developed which allows an automatic rule-based set-up of mechanistic model equations. In many cases these models can be reduced by an exact domain-oriented lumping technique. However, the resulting models can still consist of a very large number of differential equations. Results We introduce a new reduction technique, which allows building modularized and highly reduced models. Compared to existing approaches further reduction of signal transduction networks is possible. The method also provides a new modularization criterion, which allows to dissect the model into smaller modules that are called layers and can be modeled independently. Hallmarks of the approach are conservation relations within each layer and connection of layers by signal flows instead of mass flows. The reduced model can be formulated directly without previous generation of detailed model equations. It can be understood and interpreted intuitively, as model variables are macroscopic quantities that are converted by rates following simple kinetics. The proposed technique is applicable without using complex mathematical tools and even without detailed knowledge of the mathematical background. However, we provide a detailed mathematical analysis to show performance and limitations of the method. For physiologically relevant parameter domains the transient as well as the stationary errors caused by the reduction are negligible. Conclusion The new layer based reduced modeling method allows building modularized and strongly reduced models of signal transduction networks. Reduced model equations can be directly formulated and are intuitively interpretable. Additionally, the method provides very good
Multi-fidelity machine learning models for accurate bandgap predictions of solids
International Nuclear Information System (INIS)
Pilania, Ghanshyam; Gubernatis, James E.; Lookman, Turab
2016-01-01
Here, we present a multi-fidelity co-kriging statistical learning framework that combines variable-fidelity quantum mechanical calculations of bandgaps to generate a machine-learned model that enables low-cost accurate predictions of the bandgaps at the highest fidelity level. Additionally, the adopted Gaussian process regression formulation allows us to predict the underlying uncertainties as a measure of our confidence in the predictions. In using a set of 600 elpasolite compounds as an example dataset and using semi-local and hybrid exchange correlation functionals within density functional theory as two levels of fidelities, we demonstrate the excellent learning performance of the method against actual high fidelity quantum mechanical calculations of the bandgaps. The presented statistical learning method is not restricted to bandgaps or electronic structure methods and extends the utility of high throughput property predictions in a significant way.
International Nuclear Information System (INIS)
Yamacli, Serhan; Avci, Mutlu
2009-01-01
In this work, development of a voltage dependent resistance model for metallic carbon nanotubes is aimed. Firstly, the resistance of metallic carbon nanotube interconnects are obtained from ab initio simulations and then the voltage dependence of the resistance is modeled through regression. Self-consistent non-equilibrium Green's function formalism combined with density functional theory is used for calculating the voltage dependent resistance of metallic carbon nanotubes. It is shown that voltage dependent resistances of carbon nanotubes can be accurately modeled as a polynomial function which enables rapid integration of carbon nanotube interconnect models into electronic design automation tools.
Reduced Order Modeling of Combustion Instability in a Gas Turbine Model Combustor
Arnold-Medabalimi, Nicholas; Huang, Cheng; Duraisamy, Karthik
2017-11-01
Hydrocarbon fuel based propulsion systems are expected to remain relevant in aerospace vehicles for the foreseeable future. Design of these devices is complicated by combustion instabilities. The capability to model and predict these effects at reduced computational cost is a requirement for both design and control of these devices. This work focuses on computational studies on a dual swirl model gas turbine combustor in the context of reduced order model development. Full fidelity simulations are performed utilizing URANS and Hybrid RANS-LES with finite rate chemistry. Following this, data decomposition techniques are used to extract a reduced basis representation of the unsteady flow field. These bases are first used to identify sensor locations to guide experimental interrogations and controller feedback. Following this, initial results on developing a control-oriented reduced order model (ROM) will be presented. The capability of the ROM will be further assessed based on different operating conditions and geometric configurations.
High-resolution LES of the rotating stall in a reduced scale model pump-turbine
International Nuclear Information System (INIS)
Pacot, Olivier; Avellan, François; Kato, Chisachi
2014-01-01
Extending the operating range of modern pump-turbines becomes increasingly important in the course of the integration of renewable energy sources in the existing power grid. However, at partial load condition in pumping mode, the occurrence of rotating stall is critical to the operational safety of the machine and on the grid stability. The understanding of the mechanisms behind this flow phenomenon yet remains vague and incomplete. Past numerical simulations using a RANS approach often led to inconclusive results concerning the physical background. For the first time, the rotating stall is investigated by performing a large scale LES calculation on the HYDRODYNA pump-turbine scale model featuring approximately 100 million elements. The computations were performed on the PRIMEHPC FX10 of the University of Tokyo using the overset Finite Element open source code FrontFlow/blue with the dynamic Smagorinsky turbulence model and the no-slip wall condition. The internal flow computed is the one when operating the pump-turbine at 76% of the best efficiency point in pumping mode, as previous experimental research showed the presence of four rotating cells. The rotating stall phenomenon is accurately reproduced for a reduced Reynolds number using the LES approach with acceptable computing resources. The results show an excellent agreement with available experimental data from the reduced scale model testing at the EPFL Laboratory for Hydraulic Machines. The number of stall cells as well as the propagation speed corroborates the experiment
High-resolution LES of the rotating stall in a reduced scale model pump-turbine
Pacot, Olivier; Kato, Chisachi; Avellan, François
2014-03-01
Extending the operating range of modern pump-turbines becomes increasingly important in the course of the integration of renewable energy sources in the existing power grid. However, at partial load condition in pumping mode, the occurrence of rotating stall is critical to the operational safety of the machine and on the grid stability. The understanding of the mechanisms behind this flow phenomenon yet remains vague and incomplete. Past numerical simulations using a RANS approach often led to inconclusive results concerning the physical background. For the first time, the rotating stall is investigated by performing a large scale LES calculation on the HYDRODYNA pump-turbine scale model featuring approximately 100 million elements. The computations were performed on the PRIMEHPC FX10 of the University of Tokyo using the overset Finite Element open source code FrontFlow/blue with the dynamic Smagorinsky turbulence model and the no-slip wall condition. The internal flow computed is the one when operating the pump-turbine at 76% of the best efficiency point in pumping mode, as previous experimental research showed the presence of four rotating cells. The rotating stall phenomenon is accurately reproduced for a reduced Reynolds number using the LES approach with acceptable computing resources. The results show an excellent agreement with available experimental data from the reduced scale model testing at the EPFL Laboratory for Hydraulic Machines. The number of stall cells as well as the propagation speed corroborates the experiment.
Mechanisms causing reduced Arctic sea ice loss in a coupled climate model
Directory of Open Access Journals (Sweden)
A. E. West
2013-03-01
Full Text Available The fully coupled climate model HadGEM1 produces one of the most accurate simulations of the historical record of Arctic sea ice seen in the IPCC AR4 multi-model ensemble. In this study, we examine projections of sea ice decline out to 2030, produced by two ensembles of HadGEM1 with natural and anthropogenic forcings included. These ensembles project a significant slowing of the rate of ice loss to occur after 2010, with some integrations even simulating a small increase in ice area. We use an energy budget of the Arctic to examine the causes of this slowdown. A negative feedback effect by which rapid reductions in ice thickness north of Greenland reduce ice export is found to play a major role. A slight reduction in ocean-to-ice heat flux in the relevant period, caused by changes in the meridional overturning circulation (MOC and subpolar gyre in some integrations, as well as freshening of the mixed layer driven by causes other than ice melt, is also found to play a part. Finally, we assess the likelihood of a slowdown occurring in the real world due to these causes.
Directory of Open Access Journals (Sweden)
Jebur Ahmed
2018-01-01
Full Text Available 3D models delivered from digital photogrammetric techniques have massively increased and developed to meet the requirements of many applications. The reliability of these models is basically dependent on the data processing cycle and the adopted tool solution in addition to data quality. Agisoft PhotoScan is a professional image-based 3D modelling software, which seeks to create orderly, precise n 3D content from fixed images. It works with arbitrary images those qualified in both controlled and uncontrolled conditions. Following the recommendations of many users all around the globe, Agisoft PhotoScan, has become an important source to generate precise 3D data for different applications. How reliable is this data for accurate 3D modelling applications is the current question that needs an answer. Therefore; in this paper, the performance of the Agisoft PhotoScan software was assessed and analyzed to show the potential of the software for accurate 3D modelling applications. To investigate this, a study was carried out in the University of Baghdad / Al-Jaderia campus using data collected from airborne metric camera with 457m flying height. The Agisoft results show potential according to the research objective and the dataset quality following statistical and validation shape analysis.
Accurate characterisation of hole size and location by projected fringe profilometry
Wu, Yuxiang; Dantanarayana, Harshana G.; Yue, Huimin; Huntley, Jonathan M.
2018-06-01
The ability to accurately estimate the location and geometry of holes is often required in the field of quality control and automated assembly. Projected fringe profilometry is a potentially attractive technique on account of being non-contacting, of lower cost, and orders of magnitude faster than the traditional coordinate measuring machine. However, we demonstrate in this paper that fringe projection is susceptible to significant (hundreds of µm) measurement artefacts in the neighbourhood of hole edges, which give rise to errors of a similar magnitude in the estimated hole geometry. A mechanism for the phenomenon is identified based on the finite size of the imaging system’s point spread function and the resulting bias produced near to sample discontinuities in geometry and reflectivity. A mathematical model is proposed, from which a post-processing compensation algorithm is developed to suppress such errors around the holes. The algorithm includes a robust and accurate sub-pixel edge detection method based on a Fourier descriptor of the hole contour. The proposed algorithm was found to reduce significantly the measurement artefacts near the hole edges. As a result, the errors in estimated hole radius were reduced by up to one order of magnitude, to a few tens of µm for hole radii in the range 2–15 mm, compared to those from the uncompensated measurements.
A reduced order model of a quadruped walking system
International Nuclear Information System (INIS)
Sano, Akihito; Furusho, Junji; Naganuma, Nobuyuki
1990-01-01
Trot walking has recently been studied by several groups because of its stability and realizability. In the trot, diagonally opposed legs form pairs. While one pair of legs provides support, the other pair of legs swings forward in preparation for the next step. In this paper, we propose a reduced order model for the trot walking. The reduced order model is derived by using two dominant modes of the closed loop system in which the local feedback at each joint is implemented. It is shown by numerical examples that the obtained reduced order model can well approximate the original higher order model. (author)
Generalized reduced fluid model with finite ion-gyroradius effects
International Nuclear Information System (INIS)
Hsu, C.T.; Hazeltine, R.D.; Morrison, P.J.
1985-04-01
Reduced fluid models have become important tools for studying the nonlinear dynamics of plasma in a large aspect-ratio tokamak. A self-consistent nonlinear reduced fluid model, with finite ion-gyroradius effects is presented. The model is distinctive in allowing for arbitrary beta and in satisfying an exact, relatively simple energy conservation law
The APT model as reduced-rank regression
Bekker, P.A.; Dobbelstein, P.; Wansbeek, T.J.
Integrating the two steps of an arbitrage pricing theory (APT) model leads to a reduced-rank regression (RRR) model. So the results on RRR can be used to estimate APT models, making estimation very simple. We give a succinct derivation of estimation of RRR, derive the asymptotic variance of RRR
A Reduced-order NLTE Kinetic Model for Radiating Plasmas of Outer Envelopes of Stellar Atmospheres
Energy Technology Data Exchange (ETDEWEB)
Munafò, Alessandro [Aerospace Engineering Department, University of Illinois at Urbana-Champaign, 206A Talbot Lab., 104 S. Wright Street, Urbana, IL 61801 (United States); Mansour, Nagi N. [NASA Ames Research Center, Moffett Field, 94035 CA (United States); Panesi, Marco, E-mail: munafo@illinois.edu, E-mail: nagi.n.mansour@nasa.gov, E-mail: m.panesi@illinois.edu [Aerospace Engineering Department, University of Illinois at Urbana-Champaign, 306 Talbot Lab., 104 S. Wright Street, Urbana, IL 61801 (United States)
2017-04-01
The present work proposes a self-consistent reduced-order NLTE kinetic model for radiating plasmas found in the outer layers of stellar atmospheres. A detailed collisional-radiative kinetic mechanism is constructed by leveraging the most up-to-date set of ab initio and experimental data available in the literature. This constitutes the starting point for the derivation of a reduced-order model, obtained by lumping the bound energy states into groups. In order to determine the needed thermo-physical group properties, uniform and Maxwell–Boltzmann energy distributions are used to reconstruct the energy population of each group. Finally, the reduced set of governing equations for the material gas and the radiation field is obtained based on the moment method. Applications consider the steady flow across a shock wave in partially ionized hydrogen. The results clearly demonstrate that adopting a Maxwell–Boltzmann grouping allows, on the one hand, for a substantial reduction of the number of unknowns and, on the other, to maintain accuracy for both gas and radiation quantities. Also, it is observed that, when neglecting line radiation, the use of two groups already leads to a very accurate resolution of the photo-ionization precursor, internal relaxation, and radiative cooling regions. The inclusion of line radiation requires adopting just one additional group to account for optically thin losses in the α , β , and γ lines of the Balmer and Paschen series. This trend has been observed for a wide range of shock wave velocities.
Lung ultrasound accurately detects pneumothorax in a preterm newborn lamb model.
Blank, Douglas A; Hooper, Stuart B; Binder-Heschl, Corinna; Kluckow, Martin; Gill, Andrew W; LaRosa, Domenic A; Inocencio, Ishmael M; Moxham, Alison; Rodgers, Karyn; Zahra, Valerie A; Davis, Peter G; Polglase, Graeme R
2016-06-01
Pneumothorax is a common emergency affecting extremely preterm. In adult studies, lung ultrasound has performed better than chest x-ray in the diagnosis of pneumothorax. The purpose of this study was to determine the efficacy of lung ultrasound (LUS) examination to detect pneumothorax using a preterm animal model. This was a prospective, observational study using newborn Border-Leicester lambs at gestational age = 126 days (equivalent to gestational age = 26 weeks in humans) receiving mechanical ventilation from birth to 2 h of life. At the conclusion of the experiment, LUS was performed, the lambs were then euthanised and a post-mortem exam was immediately performed. We used previously published ultrasound techniques to identify pneumothorax. Test characteristics of LUS to detect pneumothorax were calculated, using the post-mortem exam as the 'gold standard' test. Nine lambs (18 lungs) were examined. Four lambs had a unilateral pneumothorax, all of which were identified by LUS with no false positives. This was the first study to use post-mortem findings to test the efficacy of LUS to detect pneumothorax in a newborn animal model. Lung ultrasound accurately detected pneumothorax, verified by post-mortem exam, in premature, newborn lambs. © 2016 Paediatrics and Child Health Division (The Royal Australasian College of Physicians).
Optimal Cluster Mill Pass Scheduling With an Accurate and Rapid New Strip Crown Model
International Nuclear Information System (INIS)
Malik, Arif S.; Grandhi, Ramana V.; Zipf, Mark E.
2007-01-01
Besides the requirement to roll coiled sheet at high levels of productivity, the optimal pass scheduling of cluster-type reversing cold mills presents the added challenge of assigning mill parameters that facilitate the best possible strip flatness. The pressures of intense global competition, and the requirements for increasingly thinner, higher quality specialty sheet products that are more difficult to roll, continue to force metal producers to commission innovative flatness-control technologies. This means that during the on-line computerized set-up of rolling mills, the mathematical model should not only determine the minimum total number of passes and maximum rolling speed, it should simultaneously optimize the pass-schedule so that desired flatness is assured, either by manual or automated means. In many cases today, however, on-line prediction of strip crown and corresponding flatness for the complex cluster-type rolling mills is typically addressed either by trial and error, by approximate deflection models for equivalent vertical roll-stacks, or by non-physical pattern recognition style models. The abundance of the aforementioned methods is largely due to the complexity of cluster-type mill configurations and the lack of deflection models with sufficient accuracy and speed for on-line use. Without adequate assignment of the pass-schedule set-up parameters, it may be difficult or impossible to achieve the required strip flatness. In this paper, we demonstrate optimization of cluster mill pass-schedules using a new accurate and rapid strip crown model. This pass-schedule optimization includes computations of the predicted strip thickness profile to validate mathematical constraints. In contrast to many of the existing methods for on-line prediction of strip crown and flatness on cluster mills, the demonstrated method requires minimal prior tuning and no extensive training with collected mill data. To rapidly and accurately solve the multi-contact problem
Improvement of a land surface model for accurate prediction of surface energy and water balances
International Nuclear Information System (INIS)
Katata, Genki
2009-02-01
In order to predict energy and water balances between the biosphere and atmosphere accurately, sophisticated schemes to calculate evaporation and adsorption processes in the soil and cloud (fog) water deposition on vegetation were implemented in the one-dimensional atmosphere-soil-vegetation model including CO 2 exchange process (SOLVEG2). Performance tests in arid areas showed that the above schemes have a significant effect on surface energy and water balances. The framework of the above schemes incorporated in the SOLVEG2 and instruction for running the model are documented. With further modifications of the model to implement the carbon exchanges between the vegetation and soil, deposition processes of materials on the land surface, vegetation stress-growth-dynamics etc., the model is suited to evaluate an effect of environmental loads to ecosystems by atmospheric pollutants and radioactive substances under climate changes such as global warming and drought. (author)
Accurate 3d Textured Models of Vessels for the Improvement of the Educational Tools of a Museum
Soile, S.; Adam, K.; Ioannidis, C.; Georgopoulos, A.
2013-02-01
Besides the demonstration of the findings, modern museums organize educational programs which aim to experience and knowledge sharing combined with entertainment rather than to pure learning. Toward that effort, 2D and 3D digital representations are gradually replacing the traditional recording of the findings through photos or drawings. The present paper refers to a project that aims to create 3D textured models of two lekythoi that are exhibited in the National Archaeological Museum of Athens in Greece; on the surfaces of these lekythoi scenes of the adventures of Odysseus are depicted. The project is expected to support the production of an educational movie and some other relevant interactive educational programs for the museum. The creation of accurate developments of the paintings and of accurate 3D models is the basis for the visualization of the adventures of the mythical hero. The data collection was made by using a structured light scanner consisting of two machine vision cameras that are used for the determination of geometry of the object, a high resolution camera for the recording of the texture, and a DLP projector. The creation of the final accurate 3D textured model is a complicated and tiring procedure which includes the collection of geometric data, the creation of the surface, the noise filtering, the merging of individual surfaces, the creation of a c-mesh, the creation of the UV map, the provision of the texture and, finally, the general processing of the 3D textured object. For a better result a combination of commercial and in-house software made for the automation of various steps of the procedure was used. The results derived from the above procedure were especially satisfactory in terms of accuracy and quality of the model. However, the procedure was proved to be time consuming while the use of various software packages presumes the services of a specialist.
Hybrid reduced order modeling for assembly calculations
Energy Technology Data Exchange (ETDEWEB)
Bang, Y.; Abdel-Khalik, H. S. [North Carolina State University, Raleigh, NC (United States); Jessee, M. A.; Mertyurek, U. [Oak Ridge National Laboratory, Oak Ridge, TN (United States)
2013-07-01
While the accuracy of assembly calculations has considerably improved due to the increase in computer power enabling more refined description of the phase space and use of more sophisticated numerical algorithms, the computational cost continues to increase which limits the full utilization of their effectiveness for routine engineering analysis. Reduced order modeling is a mathematical vehicle that scales down the dimensionality of large-scale numerical problems to enable their repeated executions on small computing environment, often available to end users. This is done by capturing the most dominant underlying relationships between the model's inputs and outputs. Previous works demonstrated the use of the reduced order modeling for a single physics code, such as a radiation transport calculation. This manuscript extends those works to coupled code systems as currently employed in assembly calculations. Numerical tests are conducted using realistic SCALE assembly models with resonance self-shielding, neutron transport, and nuclides transmutation/depletion models representing the components of the coupled code system. (authors)
Accurate Treatment of Collisions and Water-Delivery in Models of Terrestrial Planet Formation
Haghighipour, Nader; Maindl, Thomas; Schaefer, Christoph
2017-10-01
It is widely accepted that collisions among solid bodies, ignited by their interactions with planetary embryos is the key process in the formation of terrestrial planets and transport of volatiles and chemical compounds to their accretion zones. Unfortunately, due to computational complexities, these collisions are often treated in a rudimentary way. Impacts are considered to be perfectly inelastic and volatiles are considered to be fully transferred from one object to the other. This perfect-merging assumption has profound effects on the mass and composition of final planetary bodies as it grossly overestimates the masses of these objects and the amounts of volatiles and chemical elements transferred to them. It also entirely neglects collisional-loss of volatiles (e.g., water) and draws an unrealistic connection between these properties and the chemical structure of the protoplanetary disk (i.e., the location of their original carriers). We have developed a new and comprehensive methodology to simulate growth of embryos to planetary bodies where we use a combination of SPH and N-body codes to accurately model collisions as well as the transport/transfer of chemical compounds. Our methodology accounts for the loss of volatiles (e.g., ice sublimation) during the orbital evolution of their careers and accurately tracks their transfer from one body to another. Results of our simulations show that traditional N-body modeling of terrestrial planet formation overestimates the amount of the mass and water contents of the final planets by over 60% implying that not only the amount of water they suggest is far from being realistic, small planets such as Mars can also form in these simulations when collisions are treated properly. We will present details of our methodology and discuss its implications for terrestrial planet formation and water delivery to Earth.
CSIR Research Space (South Africa)
Osburn, L
2010-01-01
Full Text Available The construction industry has turned to energy modelling in order to assist them in reducing the amount of energy consumed by buildings. However, while the energy loads of buildings can be accurately modelled, energy models often under...
Reverse time migration by Krylov subspace reduced order modeling
Basir, Hadi Mahdavi; Javaherian, Abdolrahim; Shomali, Zaher Hossein; Firouz-Abadi, Roohollah Dehghani; Gholamy, Shaban Ali
2018-04-01
Imaging is a key step in seismic data processing. To date, a myriad of advanced pre-stack depth migration approaches have been developed; however, reverse time migration (RTM) is still considered as the high-end imaging algorithm. The main limitations associated with the performance cost of reverse time migration are the intensive computation of the forward and backward simulations, time consumption, and memory allocation related to imaging condition. Based on the reduced order modeling, we proposed an algorithm, which can be adapted to all the aforementioned factors. Our proposed method benefit from Krylov subspaces method to compute certain mode shapes of the velocity model computed by as an orthogonal base of reduced order modeling. Reverse time migration by reduced order modeling is helpful concerning the highly parallel computation and strongly reduces the memory requirement of reverse time migration. The synthetic model results showed that suggested method can decrease the computational costs of reverse time migration by several orders of magnitudes, compared with reverse time migration by finite element method.
Evaluating and reducing a model of radiocaesium soil-plant uptake
Energy Technology Data Exchange (ETDEWEB)
Tarsitano, D.; Young, S.D. [School of Biosciences, University of Nottingham, University Park, Nottingham, NG7 2RD (United Kingdom); Crout, N.M.J., E-mail: neil.crout@nottingham.ac.u [School of Biosciences, University of Nottingham, University Park, Nottingham, NG7 2RD (United Kingdom)
2011-03-15
An existing model of radiocaesium transfer to grasses was extended to include wheat and barley and parameterised using data from a wide range of soils and contact times. The model structure was revised and evaluated using a subset of the available data which was not used for model parameterisation. The resulting model was then used as a basis for systematic model reduction to test the utility of the model components. This analysis suggested that the use of 4 model variables (relating to radiocaesium adsorption on organic matter and the pH sensitivity of soil solution potassium concentration) and 1 model input (pH) are not required. The results of this analysis were used to develop a reduced model which was further evaluated in terms of comparisons to observations. The reduced model had an improved empirical performance and fewer adjustable parameters and soil characteristic inputs. - Research highlights: {yields} A model of plant radiocesium uptake is evaluated and re-parameterised. {yields} The representation of time dependent changes in plant uptake is improved. {yields} Model reduction is applied to evaluate the model structure. {yields} A reduced model is identified which outperforms the previously reported model. {yields} The reduced model requires fewer soil specific inputs.
Fast and accurate methods for phylogenomic analyses
Directory of Open Access Journals (Sweden)
Warnow Tandy
2011-10-01
Full Text Available Abstract Background Species phylogenies are not estimated directly, but rather through phylogenetic analyses of different gene datasets. However, true gene trees can differ from the true species tree (and hence from one another due to biological processes such as horizontal gene transfer, incomplete lineage sorting, and gene duplication and loss, so that no single gene tree is a reliable estimate of the species tree. Several methods have been developed to estimate species trees from estimated gene trees, differing according to the specific algorithmic technique used and the biological model used to explain differences between species and gene trees. Relatively little is known about the relative performance of these methods. Results We report on a study evaluating several different methods for estimating species trees from sequence datasets, simulating sequence evolution under a complex model including indels (insertions and deletions, substitutions, and incomplete lineage sorting. The most important finding of our study is that some fast and simple methods are nearly as accurate as the most accurate methods, which employ sophisticated statistical methods and are computationally quite intensive. We also observe that methods that explicitly consider errors in the estimated gene trees produce more accurate trees than methods that assume the estimated gene trees are correct. Conclusions Our study shows that highly accurate estimations of species trees are achievable, even when gene trees differ from each other and from the species tree, and that these estimations can be obtained using fairly simple and computationally tractable methods.
International Nuclear Information System (INIS)
Vu-Quoc, L.; Lesburg, L.; Zhang, X.
2004-01-01
An elasto-plastic frictional tangential force-displacement (TFD) model for spheres in contact for accurate and efficient granular-flow simulations is presented in this paper; the present TFD is consistent with the elasto-plastic normal force-displacement (NFD) model presented in [ASME Journal of Applied Mechanics 67 (2) (2000) 363; Proceedings of the Royal Society of London, Series A 455 (1991) (1999) 4013]. The proposed elasto-plastic frictional TFD model is accurate, and is validated against non-linear finite-element analyses involving plastic flows under both loading and unloading conditions. The novelty of the present TFD model lies in (i) the additive decomposition of the elasto-plastic contact area radius into an elastic part and a plastic part, (ii) the correction of the particles' radii at the contact point, and (iii) the correction of the particles' elastic moduli. The correction of the contact-area radius represents an effect of plastic deformation in colliding particles; the correction of the radius of curvature represents a permanent indentation after impact; the correction of the elastic moduli represents a softening of the material due to plastic flow. The construction of both the present elasto-plastic frictional TFD model and its consistent companion, the elasto-plastic NFD model, parallels the formalism of the continuum theory of elasto-plasticity. Both NFD and TFD models form a coherent set of force-displacement (FD) models not available hitherto for granular-flow simulations, and are consistent with the Hertz, Cattaneo, Mindlin, Deresiewicz contact mechanics theory. Together, these FD models will allow for efficient simulations of granular flows (or granular gases) involving a large number of particles
Gosses, Moritz; Nowak, Wolfgang; Wöhling, Thomas
2017-04-01
reduced model space, thereby allowing the recalculation of system matrices at every time-step necessary for non-linear models while retaining the speed of the reduced model. This makes POD-DEIM applicable for groundwater models simulating unconfined aquifers. However, in our analysis, the method struggled to reproduce variable river boundaries accurately and gave no advantage for variable Dirichlet boundaries compared to the original POD method. We have developed another extension for POD that targets to address these remaining problems by performing a second POD operation on the model matrix on the left-hand side of the equation. The method aims to at least reproduce the accuracy of the other methods where they are applicable while outperforming them for setups with changing river boundaries or variable Dirichlet boundaries. We compared the new extension with original POD and POD-DEIM for different combinations of model structures and boundary conditions. The new method shows the potential of POD extensions for applications to non-linear groundwater systems and complex boundary conditions that go beyond the current, relatively limited range of applications. References: Siade, A. J., Putti, M., and Yeh, W. W.-G. (2010). Snapshot selection for groundwater model reduction using proper orthogonal decomposition. Water Resour. Res., 46(8):W08539. Stanko, Z. P., Boyce, S. E., and Yeh, W. W.-G. (2016). Nonlinear model reduction of unconfined groundwater flow using pod and deim. Advances in Water Resources, 97:130 - 143.
Wang, Huai-Chun; Minh, Bui Quang; Susko, Edward; Roger, Andrew J
2018-03-01
Proteins have distinct structural and functional constraints at different sites that lead to site-specific preferences for particular amino acid residues as the sequences evolve. Heterogeneity in the amino acid substitution process between sites is not modeled by commonly used empirical amino acid exchange matrices. Such model misspecification can lead to artefacts in phylogenetic estimation such as long-branch attraction. Although sophisticated site-heterogeneous mixture models have been developed to address this problem in both Bayesian and maximum likelihood (ML) frameworks, their formidable computational time and memory usage severely limits their use in large phylogenomic analyses. Here we propose a posterior mean site frequency (PMSF) method as a rapid and efficient approximation to full empirical profile mixture models for ML analysis. The PMSF approach assigns a conditional mean amino acid frequency profile to each site calculated based on a mixture model fitted to the data using a preliminary guide tree. These PMSF profiles can then be used for in-depth tree-searching in place of the full mixture model. Compared with widely used empirical mixture models with $k$ classes, our implementation of PMSF in IQ-TREE (http://www.iqtree.org) speeds up the computation by approximately $k$/1.5-fold and requires a small fraction of the RAM. Furthermore, this speedup allows, for the first time, full nonparametric bootstrap analyses to be conducted under complex site-heterogeneous models on large concatenated data matrices. Our simulations and empirical data analyses demonstrate that PMSF can effectively ameliorate long-branch attraction artefacts. In some empirical and simulation settings PMSF provided more accurate estimates of phylogenies than the mixture models from which they derive.
Using electronic health records and Internet search information for accurate influenza forecasting.
Yang, Shihao; Santillana, Mauricio; Brownstein, John S; Gray, Josh; Richardson, Stewart; Kou, S C
2017-05-08
Accurate influenza activity forecasting helps public health officials prepare and allocate resources for unusual influenza activity. Traditional flu surveillance systems, such as the Centers for Disease Control and Prevention's (CDC) influenza-like illnesses reports, lag behind real-time by one to 2 weeks, whereas information contained in cloud-based electronic health records (EHR) and in Internet users' search activity is typically available in near real-time. We present a method that combines the information from these two data sources with historical flu activity to produce national flu forecasts for the United States up to 4 weeks ahead of the publication of CDC's flu reports. We extend a method originally designed to track flu using Google searches, named ARGO, to combine information from EHR and Internet searches with historical flu activities. Our regularized multivariate regression model dynamically selects the most appropriate variables for flu prediction every week. The model is assessed for the flu seasons within the time period 2013-2016 using multiple metrics including root mean squared error (RMSE). Our method reduces the RMSE of the publicly available alternative (Healthmap flutrends) method by 33, 20, 17 and 21%, for the four time horizons: real-time, one, two, and 3 weeks ahead, respectively. Such accuracy improvements are statistically significant at the 5% level. Our real-time estimates correctly identified the peak timing and magnitude of the studied flu seasons. Our method significantly reduces the prediction error when compared to historical publicly available Internet-based prediction systems, demonstrating that: (1) the method to combine data sources is as important as data quality; (2) effectively extracting information from a cloud-based EHR and Internet search activity leads to accurate forecast of flu.
International Nuclear Information System (INIS)
Brandt, J.; Ebel, A.; Elbern, H.; Jakobs, H.; Memmesheimer, M.; Mikkelsen, T.; Thykier-Nielsen, S.; Zlatev, Z.
1997-01-01
Atmospheric transport of air pollutants is, in principle, a well understood process. If information about the state of the atmosphere is given in all details (infinitely accurate information about wind speed, etc.) and infinitely fast computers are available then the advection equation could in principle be solved exactly. This is, however, not the case: discretization of the equations and input data introduces some uncertainties and errors in the results. Therefore many different issues have to be carefully studied in order to diminish these uncertainties and to develop an accurate transport model. Some of these are e.g. the numerical treatment of the transport equation, accuracy of the mean meteorological input fields and parameterizations of sub-grid scale phenomena (as e.g. parameterizations of the 2 nd and higher order turbulence terms in order to reach closure in the perturbation equation). A tracer model for studying transport and dispersion of air pollution caused by a single but strong source is under development. The model simulations from the first ETEX release illustrate the differences caused by using various analyzed fields directly in the tracer model or using a meteorological driver. Also different parameterizations of the mixing height and the vertical exchange are compared. (author)
Energy Technology Data Exchange (ETDEWEB)
Tenant, Sean; Pang, Chun Lap; Dissanayake, Prageeth [Peninsula Radiology Academy, Plymouth (United Kingdom); Vardhanabhuti, Varut [Plymouth University Peninsula Schools of Medicine and Dentistry, Plymouth (United Kingdom); University of Hong Kong, Department of Diagnostic Radiology, Li Ka Shing Faculty of Medicine, Pokfulam (China); Stuckey, Colin; Gutteridge, Catherine [Plymouth Hospitals NHS Trust, Plymouth (United Kingdom); Hyde, Christopher [University of Exeter Medical School, St Luke' s Campus, Exeter (United Kingdom); Roobottom, Carl [Plymouth University Peninsula Schools of Medicine and Dentistry, Plymouth (United Kingdom); Plymouth Hospitals NHS Trust, Plymouth (United Kingdom)
2017-10-15
To evaluate the accuracy of reduced-dose CT scans reconstructed using a new generation of model-based iterative reconstruction (MBIR) in the imaging of urinary tract stone disease, compared with a standard-dose CT using 30% adaptive statistical iterative reconstruction. This single-institution prospective study recruited 125 patients presenting either with acute renal colic or for follow-up of known urinary tract stones. They underwent two immediately consecutive scans, one at standard dose settings and one at the lowest dose (highest noise index) the scanner would allow. The reduced-dose scans were reconstructed using both ASIR 30% and MBIR algorithms and reviewed independently by two radiologists. Objective and subjective image quality measures as well as diagnostic data were obtained. The reduced-dose MBIR scan was 100% concordant with the reference standard for the assessment of ureteric stones. It was extremely accurate at identifying calculi of 3 mm and above. The algorithm allowed a dose reduction of 58% without any loss of scan quality. A reduced-dose CT scan using MBIR is accurate in acute imaging for renal colic symptoms and for urolithiasis follow-up and allows a significant reduction in dose. (orig.)
On reducibility and ergodicity of population projection matrix models
DEFF Research Database (Denmark)
Stott, Iain; Townley, Stuart; Carslake, David
2010-01-01
from all stages to all other stages) and therefore ergodic (whatever initial stage structure is used in the population projection, it will always exhibit the same stable asymptotic growth rate). 2. Evaluation of 652 PPM models for 171 species from the literature suggests that 24·7% of PPM models...... structure used in the population projection). In our sample of published PPMs, 15·6% are non-ergodic. 3. This presents a problem: reducible–ergodic models often defy biological rationale in their description of the life cycle but may or may not prove problematic for analysis as they often behave similarly...... of reducibility in published PPMs, with significant implications for the predictive power of such models in many cases. We suggest that as a general rule, reducibility of PPM models should be avoided. However, we provide a guide to the pertinent analysis of reducible matrix models, largely based upon whether...
Accurate Fuel Estimates using CAN Bus Data and 3D Maps
DEFF Research Database (Denmark)
Andersen, Ove; Torp, Kristian
2018-01-01
The focus on reducing CO 2 emissions from the transport sector is larger than ever. Increasingly stricter reductions on fuel consumption and emissions are being introduced by the EU, e.g., to reduce the air pollution in many larger cities. Large sets of high-frequent GPS data from vehicles already...... the accuracy of fuel consumption estimates with up to 40% on hilly roads. There is only very little improvement of the high-precision (H3D) map over the simple 3D map. The fuel consumption estimates are most accurate on flat terrain with average fuel estimates of up to 99% accuracy. The fuel estimates are most...... exist. However, fuel consumption data is still rarely collected even though it is possible to measure the fuel consumption with high accuracy, e.g., using an OBD-II device and a smartphone. This paper, presents a method for comparing fuel-consumption estimates using the SIDRA TRIP model with real fuel...
Ruzziconi, Laura
2013-06-10
We present a study of the dynamic behavior of a microelectromechanical systems (MEMS) device consisting of an imperfect clamped-clamped microbeam subjected to electrostatic and electrodynamic actuation. Our objective is to develop a theoretical analysis, which is able to describe and predict all the main relevant aspects of the experimental response. Extensive experimental investigation is conducted, where the main imperfections coming from microfabrication are detected, the first four experimental natural frequencies are identified and the nonlinear dynamics are explored at increasing values of electrodynamic excitation, in a neighborhood of the first symmetric resonance. Several backward and forward frequency sweeps are acquired. The nonlinear behavior is highlighted, which includes ranges of multistability, where the nonresonant and the resonant branch coexist, and intervals where superharmonic resonances are clearly visible. Numerical simulations are performed. Initially, two single mode reduced-order models are considered. One is generated via the Galerkin technique, and the other one via the combined use of the Ritz method and the Padé approximation. Both of them are able to provide a satisfactory agreement with the experimental data. This occurs not only at low values of electrodynamic excitation, but also at higher ones. Their computational efficiency is discussed in detail, since this is an essential aspect for systematic local and global simulations. Finally, the theoretical analysis is further improved and a two-degree-of-freedom reduced-order model is developed, which is also capable of capturing the measured second symmetric superharmonic resonance. Despite the apparent simplicity, it is shown that all the proposed reduced-order models are able to describe the experimental complex nonlinear dynamics of the device accurately and properly, which validates the proposed theoretical approach. © 2013 IOP Publishing Ltd.
Parametric reduced models for the nonlinear Schrödinger equation.
Harlim, John; Li, Xiantao
2015-05-01
Reduced models for the (defocusing) nonlinear Schrödinger equation are developed. In particular, we develop reduced models that only involve the low-frequency modes given noisy observations of these modes. The ansatz of the reduced parametric models are obtained by employing a rational approximation and a colored-noise approximation, respectively, on the memory terms and the random noise of a generalized Langevin equation that is derived from the standard Mori-Zwanzig formalism. The parameters in the resulting reduced models are inferred from noisy observations with a recently developed ensemble Kalman filter-based parametrization method. The forecasting skill across different temperature regimes are verified by comparing the moments up to order four, a two-time correlation function statistics, and marginal densities of the coarse-grained variables.
Moghadas, D.; André, F.; Vereecken, H.; Lambot, S.
2009-04-01
Water is a vital resource for human needs, agriculture, sanitation and industrial supply. The knowledge of soil water dynamics and solute transport is essential in agricultural and environmental engineering as it controls plant growth, hydrological processes, and the contamination of surface and subsurface water. Increased irrigation efficiency has also an important role for water conservation, reducing drainage and mitigating some of the water pollution and soil salinity. Geophysical methods are effective techniques for monitoring the vadose zone. In particular, electromagnetic induction (EMI) can provide in a non-invasive way important information about the soil electrical properties at the field scale, which are mainly correlated to important variables such as soil water content, salinity, and texture. EMI is based on the radiation of a VLF EM wave into the soil. Depending on its electrical conductivity, Foucault currents are generated and produce a secondary EM field which is then recorded by the EMI system. Advanced techniques for EMI data interpretation resort to inverse modeling. Yet, a major gap in current knowledge is the limited accuracy of the forward model used for describing the EMI-subsurface system, usually relying on strongly simplifying assumptions. We present a new low frequency EMI method based on Vector Network Analyzer (VNA) technology and advanced forward modeling using a linear system of complex transfer functions for describing the EMI loop antenna and a three-dimensional solution of Maxwell's equations for wave propagation in multilayered media. VNA permits simple, international standard calibration of the EMI system. We derived a Green's function for the zero-offset, off-ground horizontal loop antenna and also proposed an optimal integration path for faster evaluation of the spatial-domain Green's function from its spectral counterpart. This new integration path shows fewer oscillations compared with the real path and permits to avoid the
Spiral CT scanning plan to generate accurate Fe models of the human femur
International Nuclear Information System (INIS)
Zannoni, C.; Testi, D.; Capello, A.
1999-01-01
In spiral computed tomography (CT), source rotation, patient translation, and data acquisition are continuously conducted. Settings of the detector collimation and the table increment affect the image quality in terms of spatial and contrast resolution. This study assessed and measured the efficacy of spiral CT in those applications where the accurate reconstruction of bone morphology is critical: custom made prosthesis design or three dimensional modelling of the mechanical behaviour of long bones. Results show that conventional CT grants the highest accuracy. Spiral CT with D=5 mm and P=1,5 in the regions where the morphology is more regular, slightly degrades the image quality but allows to acquire at comparable cost an higher number of images increasing the longitudinal resolution of the acquired data set. (author)
Vladescu, Jason C; Carroll, Regina; Paden, Amber; Kodak, Tiffany M
2012-01-01
The present study replicates and extends previous research on the use of video modeling (VM) with voiceover instruction to train staff to implement discrete-trial instruction (DTI). After staff trainees reached the mastery criterion when teaching an adult confederate with VM, they taught a child with a developmental disability using DTI. The results showed that the staff trainees' accurate implementation of DTI remained high, and both child participants acquired new skills. These findings provide additional support that VM may be an effective method to train staff members to conduct DTI.
Sapsis, Themistoklis P; Majda, Andrew J
2013-08-20
A framework for low-order predictive statistical modeling and uncertainty quantification in turbulent dynamical systems is developed here. These reduced-order, modified quasilinear Gaussian (ROMQG) algorithms apply to turbulent dynamical systems in which there is significant linear instability or linear nonnormal dynamics in the unperturbed system and energy-conserving nonlinear interactions that transfer energy from the unstable modes to the stable modes where dissipation occurs, resulting in a statistical steady state; such turbulent dynamical systems are ubiquitous in geophysical and engineering turbulence. The ROMQG method involves constructing a low-order, nonlinear, dynamical system for the mean and covariance statistics in the reduced subspace that has the unperturbed statistics as a stable fixed point and optimally incorporates the indirect effect of non-Gaussian third-order statistics for the unperturbed system in a systematic calibration stage. This calibration procedure is achieved through information involving only the mean and covariance statistics for the unperturbed equilibrium. The performance of the ROMQG algorithm is assessed on two stringent test cases: the 40-mode Lorenz 96 model mimicking midlatitude atmospheric turbulence and two-layer baroclinic models for high-latitude ocean turbulence with over 125,000 degrees of freedom. In the Lorenz 96 model, the ROMQG algorithm with just a single mode captures the transient response to random or deterministic forcing. For the baroclinic ocean turbulence models, the inexpensive ROMQG algorithm with 252 modes, less than 0.2% of the total, captures the nonlinear response of the energy, the heat flux, and even the one-dimensional energy and heat flux spectra.
Plancade, Sandra; Rozenholc, Yves; Lund, Eiliv
2012-12-11
Illumina BeadArray technology includes non specific negative control features that allow a precise estimation of the background noise. As an alternative to the background subtraction proposed in BeadStudio which leads to an important loss of information by generating negative values, a background correction method modeling the observed intensities as the sum of the exponentially distributed signal and normally distributed noise has been developed. Nevertheless, Wang and Ye (2012) display a kernel-based estimator of the signal distribution on Illumina BeadArrays and suggest that a gamma distribution would represent a better modeling of the signal density. Hence, the normal-exponential modeling may not be appropriate for Illumina data and background corrections derived from this model may lead to wrong estimation. We propose a more flexible modeling based on a gamma distributed signal and a normal distributed background noise and develop the associated background correction, implemented in the R-package NormalGamma. Our model proves to be markedly more accurate to model Illumina BeadArrays: on the one hand, it is shown on two types of Illumina BeadChips that this model offers a more correct fit of the observed intensities. On the other hand, the comparison of the operating characteristics of several background correction procedures on spike-in and on normal-gamma simulated data shows high similarities, reinforcing the validation of the normal-gamma modeling. The performance of the background corrections based on the normal-gamma and normal-exponential models are compared on two dilution data sets, through testing procedures which represent various experimental designs. Surprisingly, we observe that the implementation of a more accurate parametrisation in the model-based background correction does not increase the sensitivity. These results may be explained by the operating characteristics of the estimators: the normal-gamma background correction offers an improvement
International Nuclear Information System (INIS)
Batou, A.; Soize, C.; Brie, N.
2013-01-01
Highlights: • A ROM of a nonlinear dynamical structure is built with a global displacements basis. • The reduced order model of fuel assemblies is accurate and of very small size. • The shocks between grids of a row of seven fuel assemblies are computed. -- Abstract: We are interested in the construction of a reduced-order computational model for nonlinear complex dynamical structures which are characterized by the presence of numerous local elastic modes in the low-frequency band. This high modal density makes the use of the classical modal analysis method not suitable. Therefore the reduced-order computational model is constructed using a basis of a space of global displacements, which is constructed a priori and which allows the nonlinear dynamical response of the structure observed on the stiff part to be predicted with a good accuracy. The methodology is applied to a complex industrial structure which is made up of a row of seven fuel assemblies with possibility of collisions between grids and which is submitted to a seismic loading
Energy Technology Data Exchange (ETDEWEB)
Batou, A., E-mail: anas.batou@univ-paris-est.fr [Université Paris-Est, Laboratoire Modélisation et Simulation Multi Echelle, MSME UMR 8208 CNRS, 5 bd Descartes, 77454 Marne-la-Vallee (France); Soize, C., E-mail: christian.soize@univ-paris-est.fr [Université Paris-Est, Laboratoire Modélisation et Simulation Multi Echelle, MSME UMR 8208 CNRS, 5 bd Descartes, 77454 Marne-la-Vallee (France); Brie, N., E-mail: nicolas.brie@edf.fr [EDF R and D, Département AMA, 1 avenue du général De Gaulle, 92140 Clamart (France)
2013-09-15
Highlights: • A ROM of a nonlinear dynamical structure is built with a global displacements basis. • The reduced order model of fuel assemblies is accurate and of very small size. • The shocks between grids of a row of seven fuel assemblies are computed. -- Abstract: We are interested in the construction of a reduced-order computational model for nonlinear complex dynamical structures which are characterized by the presence of numerous local elastic modes in the low-frequency band. This high modal density makes the use of the classical modal analysis method not suitable. Therefore the reduced-order computational model is constructed using a basis of a space of global displacements, which is constructed a priori and which allows the nonlinear dynamical response of the structure observed on the stiff part to be predicted with a good accuracy. The methodology is applied to a complex industrial structure which is made up of a row of seven fuel assemblies with possibility of collisions between grids and which is submitted to a seismic loading.
Diniz, Leonardo G.; Kirnosov, Nikita; Alijah, Alexander; Mohallem, José R.; Adamowicz, Ludwik
2016-04-01
A very accurate dipole moment curve (DMC) for the ground X1Σ+ electronic state of the 7LiH molecule is reported. It is calculated with the use of all-particle explicitly correlated Gaussian functions with shifted centers. The DMC - the most accurate to our knowledge - and the corresponding highly accurate potential energy curve are used to calculate the transition energies, the transition dipole moments, and the Einstein coefficients for the rovibrational transitions with ΔJ = - 1 and Δv ⩽ 5 . The importance of the non-adiabatic effects in determining these properties is evaluated using the model of a vibrational R-dependent effective reduced mass in the rovibrational calculations introduced earlier (Diniz et al., 2015). The results of the present calculations are used to assess the quality of the two complete linelists of 7LiH available in the literature.
A simple technique for an accurate shielding of the lungs during total body irradiation
Directory of Open Access Journals (Sweden)
Hana Mekdash
2017-09-01
Conclusion: This new technique succeeded in reducing the length of the overall treatment session of the conventional TBI procedure and hence reduced patient discomfort while ensuring accurate shielding of the lungs.
Vortex network community based reduced-order force model
Gopalakrishnan Meena, Muralikrishnan; Nair, Aditya; Taira, Kunihiko
2017-11-01
We characterize the vortical wake interactions by utilizing network theory and cluster-based approaches, and develop a data-inspired unsteady force model. In the present work, the vortical interaction network is defined by nodes representing vortical elements and the edges quantified by induced velocity measures amongst the vortices. The full vorticity field is reduced to a finite number of vortical clusters based on network community detection algorithm, which serves as a basis for a skeleton network that captures the essence of the wake dynamics. We use this reduced representation of the wake to develop a data-inspired reduced-order force model that can predict unsteady fluid forces on the body. The overall formulation is demonstrated for laminar flows around canonical bluff body wake and stalled flow over an airfoil. We also show the robustness of the present network-based model against noisy data, which motivates applications towards turbulent flows and experimental measurements. Supported by the National Science Foundation (Grant 1632003).
An accurate real-time model of maglev planar motor based on compound Simpson numerical integration
Kou, Baoquan; Xing, Feng; Zhang, Lu; Zhou, Yiheng; Liu, Jiaqi
2017-05-01
To realize the high-speed and precise control of the maglev planar motor, a more accurate real-time electromagnetic model, which considers the influence of the coil corners, is proposed in this paper. Three coordinate systems for the stator, mover and corner coil are established. The coil is divided into two segments, the straight coil segment and the corner coil segment, in order to obtain a complete electromagnetic model. When only take the first harmonic of the flux density distribution of a Halbach magnet array into account, the integration method can be carried out towards the two segments according to Lorenz force law. The force and torque analysis formula of the straight coil segment can be derived directly from Newton-Leibniz formula, however, this is not applicable to the corner coil segment. Therefore, Compound Simpson numerical integration method is proposed in this paper to solve the corner segment. With the validation of simulation and experiment, the proposed model has high accuracy and can realize practical application easily.
Accurate Online Full Charge Capacity Modeling of Smartphone Batteries
Hoque, Mohammad A.; Siekkinen, Matti; Koo, Jonghoe; Tarkoma, Sasu
2016-01-01
Full charge capacity (FCC) refers to the amount of energy a battery can hold. It is the fundamental property of smartphone batteries that diminishes as the battery ages and is charged/discharged. We investigate the behavior of smartphone batteries while charging and demonstrate that the battery voltage and charging rate information can together characterize the FCC of a battery. We propose a new method for accurately estimating FCC without exposing low-level system details or introducing new ...
A reduced covariant string model for the extrinsic string
International Nuclear Information System (INIS)
Botelho, L.C.L.
1989-01-01
It is studied a reduced covariant string model for the extrinsic string by using Polyakov's path integral formalism. On the basis of this reduced model it is suggested that the extrinsic string has its critical dimension given by 13. Additionally, it is calculated in a simple way Poliakov's renormalization group law for the string rigidity coupling constants. (A.C.A.S.) [pt
Prediction of Accurate Mixed Mode Fatigue Crack Growth Curves using the Paris' Law
Sajith, S.; Krishna Murthy, K. S. R.; Robi, P. S.
2017-12-01
Accurate information regarding crack growth times and structural strength as a function of the crack size is mandatory in damage tolerance analysis. Various equivalent stress intensity factor (SIF) models are available for prediction of mixed mode fatigue life using the Paris' law. In the present investigation these models have been compared to assess their efficacy in prediction of the life close to the experimental findings as there are no guidelines/suggestions available on selection of these models for accurate and/or conservative predictions of fatigue life. Within the limitations of availability of experimental data and currently available numerical simulation techniques, the results of present study attempts to outline models that would provide accurate and conservative life predictions.
Fast and Accurate Residential Fire Detection Using Wireless Sensor Networks
Bahrepour, Majid; Meratnia, Nirvana; Havinga, Paul J.M.
2010-01-01
Prompt and accurate residential fire detection is important for on-time fire extinguishing and consequently reducing damages and life losses. To detect fire sensors are needed to measure the environmental parameters and algorithms are required to decide about occurrence of fire. Recently, wireless
Can segmental model reductions quantify whole-body balance accurately during dynamic activities?
Jamkrajang, Parunchaya; Robinson, Mark A; Limroongreungrat, Weerawat; Vanrenterghem, Jos
2017-07-01
When investigating whole-body balance in dynamic tasks, adequately tracking the whole-body centre of mass (CoM) or derivatives such as the extrapolated centre of mass (XCoM) can be crucial but add considerable measurement efforts. The aim of this study was to investigate whether reduced kinematic models can still provide adequate CoM and XCoM representations during dynamic sporting tasks. Seventeen healthy recreationally active subjects (14 males and 3 females; age, 24.9±3.2years; height, 177.3±6.9cm; body mass 72.6±7.0kg) participated in this study. Participants completed three dynamic movements, jumping, kicking, and overarm throwing. Marker-based kinematic data were collected with 10 optoelectronic cameras at 250Hz (Oqus Qualisys, Gothenburg, Sweden). The differences between (X)CoM from a full-body model (gold standard) and (X)CoM representations based on six selected model reductions were evaluated using a Bland-Altman approach. A threshold difference was set at ±2cm to help the reader interpret which model can still provide an acceptable (X)CoM representation. Antero-posterior and medio-lateral displacement profiles of the CoM representation based on lower limbs, trunk and upper limbs showed strong agreement, slightly reduced for lower limbs and trunk only. Representations based on lower limbs only showed less strong agreement, particularly for XCoM in kicking. Overall, our results provide justification of the use of certain model reductions for specific needs, saving measurement effort whilst limiting the error of tracking (X)CoM trajectories in the context of whole-body balance investigation. Copyright © 2017 Elsevier B.V. All rights reserved.
Reduced order for nuclear reactor model in frequency and time domain
International Nuclear Information System (INIS)
Nugroho, D.H.
1997-01-01
In control system theory, a model can be represented by frequency or time domain. In frequency domain, the model was represented by transfer function. in time domain, the model was represented by state space. for the sake of simplification in computation, it is necessary to reduce the model order. the main aim of this research is to find the best in nuclear reactor model. Model order reduction in frequency domain can be done utilizing pole-zero cancellation method; while in time domain utilizing balanced aggregation method the balanced aggregation method was developed by moore (1981). In this paper, the two kinds of method were applied to reduce a nuclear reactor model which was constructed by neutron dynamics and heat transfer equations. to validate that the model characteristics were not change when model order reduction applied, the response was utilized for full and reduced order. it was shown that the nuclear reactor order model can be reduced from order 8 to 2 order 2 is the best order for nuclear reactor model
Directory of Open Access Journals (Sweden)
Qingwen Li
2015-01-01
Full Text Available In the tunnel and underground space engineering, the blasting wave will attenuate from shock wave to stress wave to elastic seismic wave in the host rock. Also, the host rock will form crushed zone, fractured zone, and elastic seismic zone under the blasting loading and waves. In this paper, an accurate mathematical dynamic loading model was built. And the crushed zone as well as fractured zone was considered as the blasting vibration source thus deducting the partial energy for cutting host rock. So this complicated dynamic problem of segmented differential blasting was regarded as an equivalent elastic boundary problem by taking advantage of Saint-Venant’s Theorem. At last, a 3D model in finite element software FLAC3D accepted the constitutive parameters, uniformly distributed mutative loading, and the cylindrical attenuation law to predict the velocity curves and effective tensile curves for calculating safety criterion formulas of surrounding rock and tunnel liner after verifying well with the in situ monitoring data.
Fast, Accurate Memory Architecture Simulation Technique Using Memory Access Characteristics
小野, 貴継; 井上, 弘士; 村上, 和彰
2007-01-01
This paper proposes a fast and accurate memory architecture simulation technique. To design memory architecture, the first steps commonly involve using trace-driven simulation. However, expanding the design space makes the evaluation time increase. A fast simulation is achieved by a trace size reduction, but it reduces the simulation accuracy. Our approach can reduce the simulation time while maintaining the accuracy of the simulation results. In order to evaluate validity of proposed techniq...
Li, Fangzheng; Liu, Chunying; Song, Xuexiong; Huan, Yanjun; Gao, Shansong; Jiang, Zhongling
2018-01-01
Access to adequate anatomical specimens can be an important aspect in learning the anatomy of domestic animals. In this study, the authors utilized a structured light scanner and fused deposition modeling (FDM) printer to produce highly accurate animal skeletal models. First, various components of the bovine skeleton, including the femur, the fifth rib, and the sixth cervical (C6) vertebra were used to produce digital models. These were then used to produce 1:1 scale physical models with the FDM printer. The anatomical features of the digital models and three-dimensional (3D) printed models were then compared with those of the original skeletal specimens. The results of this study demonstrated that both digital and physical scale models of animal skeletal components could be rapidly produced using 3D printing technology. In terms of accuracy between models and original specimens, the standard deviations of the femur and the fifth rib measurements were 0.0351 and 0.0572, respectively. All of the features except the nutrient foramina on the original bone specimens could be identified in the digital and 3D printed models. Moreover, the 3D printed models could serve as a viable alternative to original bone specimens when used in anatomy education, as determined from student surveys. This study demonstrated an important example of reproducing bone models to be used in anatomy education and veterinary clinical training. Anat Sci Educ 11: 73-80. © 2017 American Association of Anatomists. © 2017 American Association of Anatomists.
Accurate numerical simulation of reaction-diffusion processes for heavy oil recovery
Energy Technology Data Exchange (ETDEWEB)
Govind, P.A.; Srinivasan, S. [Society of Petroleum Engineers, Richardson, TX (United States)]|[Texas Univ., Austin, TX (United States)
2008-10-15
This study evaluated a reaction-diffusion simulation tool designed to analyze the displacement of carbon dioxide (CO{sub 2}) in a simultaneous injection of carbon dioxide and elemental sodium in a heavy oil reservoir. Sodium was used due to the exothermic reaction of sodium with in situ that occurs when heat is used to reduce oil viscosity. The process also results in the formation of sodium hydroxide that reduces interfacial tension at the bitumen interface. A commercial simulation tool was used to model the sodium transport mechanism to the reaction interface through diffusion as well as the reaction zone's subsequent displacement. The aim of the study was to verify if the in situ reaction was able to generate sufficient heat to reduce oil viscosity and improve the displacement of the heavy oil. The study also assessed the accuracy of the reaction front simulation tool, in which an alternate method was used to model the propagation front as a moving heat source. The sensitivity of the simulation results were then evaluated in relation to the diffusion coefficient in order to understand the scaling characteristics of the reaction-diffusion zone. A pore-scale simulation was then up-scaled to grid blocks. Results of the study showed that when sodium suspended in liquid CO{sub 2} is injected into reservoirs, it diffuses through the carrier phase and interacts with water. A random walk diffusion algorithm with reactive dissipation was implemented to more accurately characterize reaction and diffusion processes. It was concluded that the algorithm modelled physical dispersion while neglecting the effect of numerical dispersion. 10 refs., 3 tabs., 24 figs.
Multigrid time-accurate integration of Navier-Stokes equations
Arnone, Andrea; Liou, Meng-Sing; Povinelli, Louis A.
1993-01-01
Efficient acceleration techniques typical of explicit steady-state solvers are extended to time-accurate calculations. Stability restrictions are greatly reduced by means of a fully implicit time discretization. A four-stage Runge-Kutta scheme with local time stepping, residual smoothing, and multigridding is used instead of traditional time-expensive factorizations. Some applications to natural and forced unsteady viscous flows show the capability of the procedure.
Levy, David T; Huang, An-Tsun; Havumaki, Joshua S; Meza, Rafael
2016-05-01
Michigan has implemented several of the tobacco control policies recommended by the World Health Organization MPOWER goals. We consider the effect of those policies and additional policies consistent with MPOWER goals on smoking prevalence and smoking-attributable deaths (SADs). The SimSmoke tobacco control policy simulation model is used to examine the effect of past policies and a set of additional policies to meet the MPOWER goals. The model is adapted to Michigan using state population, smoking, and policy data starting in 1993. SADs are estimated using standard attribution methods. Upon validating the model, SimSmoke is used to distinguish the effect of policies implemented since 1993 against a counterfactual with policies kept at their 1993 levels. The model is then used to project the effect of implementing stronger policies beginning in 2014. SimSmoke predicts smoking prevalence accurately between 1993 and 2010. Since 1993, a relative reduction in smoking rates of 22 % by 2013 and of 30 % by 2054 can be attributed to tobacco control policies. Of the 22 % reduction, 44 % is due to taxes, 28 % to smoke-free air laws, 26 % to cessation treatment policies, and 2 % to youth access. Moreover, 234,000 SADs are projected to be averted by 2054. With additional policies consistent with MPOWER goals, the model projects that, by 2054, smoking prevalence can be further reduced by 17 % with 80,000 deaths averted relative to the absence of those policies. Michigan SimSmoke shows that tobacco control policies, including cigarette taxes, smoke-free air laws, and cessation treatment policies, have substantially reduced smoking and SADs. Higher taxes, strong mass media campaigns, and cessation treatment policies would further reduce smoking prevalence and SADs.
Accelerating transient simulation of linear reduced order models.
Energy Technology Data Exchange (ETDEWEB)
Thornquist, Heidi K.; Mei, Ting; Keiter, Eric Richard; Bond, Brad
2011-10-01
Model order reduction (MOR) techniques have been used to facilitate the analysis of dynamical systems for many years. Although existing model reduction techniques are capable of providing huge speedups in the frequency domain analysis (i.e. AC response) of linear systems, such speedups are often not obtained when performing transient analysis on the systems, particularly when coupled with other circuit components. Reduced system size, which is the ostensible goal of MOR methods, is often insufficient to improve transient simulation speed on realistic circuit problems. It can be shown that making the correct reduced order model (ROM) implementation choices is crucial to the practical application of MOR methods. In this report we investigate methods for accelerating the simulation of circuits containing ROM blocks using the circuit simulator Xyce.
Reducing Spatial Data Complexity for Classification Models
International Nuclear Information System (INIS)
Ruta, Dymitr; Gabrys, Bogdan
2007-01-01
Intelligent data analytics gradually becomes a day-to-day reality of today's businesses. However, despite rapidly increasing storage and computational power current state-of-the-art predictive models still can not handle massive and noisy corporate data warehouses. What is more adaptive and real-time operational environment requires multiple models to be frequently retrained which further hinders their use. Various data reduction techniques ranging from data sampling up to density retention models attempt to address this challenge by capturing a summarised data structure, yet they either do not account for labelled data or degrade the classification performance of the model trained on the condensed dataset. Our response is a proposition of a new general framework for reducing the complexity of labelled data by means of controlled spatial redistribution of class densities in the input space. On the example of Parzen Labelled Data Compressor (PLDC) we demonstrate a simulatory data condensation process directly inspired by the electrostatic field interaction where the data are moved and merged following the attracting and repelling interactions with the other labelled data. The process is controlled by the class density function built on the original data that acts as a class-sensitive potential field ensuring preservation of the original class density distributions, yet allowing data to rearrange and merge joining together their soft class partitions. As a result we achieved a model that reduces the labelled datasets much further than any competitive approaches yet with the maximum retention of the original class densities and hence the classification performance. PLDC leaves the reduced dataset with the soft accumulative class weights allowing for efficient online updates and as shown in a series of experiments if coupled with Parzen Density Classifier (PDC) significantly outperforms competitive data condensation methods in terms of classification performance at the
Reducing Spatial Data Complexity for Classification Models
Ruta, Dymitr; Gabrys, Bogdan
2007-11-01
Intelligent data analytics gradually becomes a day-to-day reality of today's businesses. However, despite rapidly increasing storage and computational power current state-of-the-art predictive models still can not handle massive and noisy corporate data warehouses. What is more adaptive and real-time operational environment requires multiple models to be frequently retrained which further hinders their use. Various data reduction techniques ranging from data sampling up to density retention models attempt to address this challenge by capturing a summarised data structure, yet they either do not account for labelled data or degrade the classification performance of the model trained on the condensed dataset. Our response is a proposition of a new general framework for reducing the complexity of labelled data by means of controlled spatial redistribution of class densities in the input space. On the example of Parzen Labelled Data Compressor (PLDC) we demonstrate a simulatory data condensation process directly inspired by the electrostatic field interaction where the data are moved and merged following the attracting and repelling interactions with the other labelled data. The process is controlled by the class density function built on the original data that acts as a class-sensitive potential field ensuring preservation of the original class density distributions, yet allowing data to rearrange and merge joining together their soft class partitions. As a result we achieved a model that reduces the labelled datasets much further than any competitive approaches yet with the maximum retention of the original class densities and hence the classification performance. PLDC leaves the reduced dataset with the soft accumulative class weights allowing for efficient online updates and as shown in a series of experiments if coupled with Parzen Density Classifier (PDC) significantly outperforms competitive data condensation methods in terms of classification performance at the
Accurate Multisteps Traffic Flow Prediction Based on SVM
Directory of Open Access Journals (Sweden)
Zhang Mingheng
2013-01-01
Full Text Available Accurate traffic flow prediction is prerequisite and important for realizing intelligent traffic control and guidance, and it is also the objective requirement for intelligent traffic management. Due to the strong nonlinear, stochastic, time-varying characteristics of urban transport system, artificial intelligence methods such as support vector machine (SVM are now receiving more and more attentions in this research field. Compared with the traditional single-step prediction method, the multisteps prediction has the ability that can predict the traffic state trends over a certain period in the future. From the perspective of dynamic decision, it is far important than the current traffic condition obtained. Thus, in this paper, an accurate multi-steps traffic flow prediction model based on SVM was proposed. In which, the input vectors were comprised of actual traffic volume and four different types of input vectors were compared to verify their prediction performance with each other. Finally, the model was verified with actual data in the empirical analysis phase and the test results showed that the proposed SVM model had a good ability for traffic flow prediction and the SVM-HPT model outperformed the other three models for prediction.
Accurate evaluation of exchange fields in finite element micromagnetic solvers
Chang, R.; Escobar, M. A.; Li, S.; Lubarda, M. V.; Lomakin, V.
2012-04-01
Quadratic basis functions (QBFs) are implemented for solving the Landau-Lifshitz-Gilbert equation via the finite element method. This involves the introduction of a set of special testing functions compatible with the QBFs for evaluating the Laplacian operator. The results by using QBFs are significantly more accurate than those via linear basis functions. QBF approach leads to significantly more accurate results than conventionally used approaches based on linear basis functions. Importantly QBFs allow reducing the error of computing the exchange field by increasing the mesh density for structured and unstructured meshes. Numerical examples demonstrate the feasibility of the method.
International Nuclear Information System (INIS)
Paul, Subhanker; Singh, Suneet
2015-01-01
The prime objective of the presented work is to develop a Nodalized Reduced Order Model (NROM) to carry linear stability analysis of flow instabilities in a two-phase flow system. The model is developed by dividing the single phase and two-phase region of a uniformly heated channel into N number of nodes followed by time dependent spatial linear approximations for single phase enthalpy and two-phase quality between the consecutive nodes. Moving boundary scheme has been adopted in the model, where all the node boundaries vary with time due to the variation of boiling boundary inside the heated channel. Using a state space approach, the instability thresholds are delineated by stability maps plotted in parameter planes of phase change number (N pch ) and subcooling number (N sub ). The prime feature of the present model is that, though the model equations are simpler due to presence of linear-linear approximations for single phase enthalpy and two-phase quality, yet the results are in good agreement with the existing models (Karve [33]; Dokhane [34]) where the model equations run for several pages and experimental data (Solberg [41]). Unlike the existing ROMs, different two-phase friction factor multiplier correlations have been incorporated in the model. The applicability of various two-phase friction factor multipliers and their effects on stability behaviour have been depicted by carrying a comparative study. It is also observed that the Friedel model for friction factor calculations produces the most accurate results with respect to the available experimental data. (authors)
ADAPTATION MODEL FOR REDUCING THE MANAGERIAL STRESS
Directory of Open Access Journals (Sweden)
VIOLETA GLIGOROVSKI
2017-12-01
Full Text Available Changes are an inseparable component of the company's life cycle and they can contribute to its essential growth in the future. The purpose of this paper is to explain managerial stress caused by implementation of changes and creating an adaptation model to decrease managerial stress. How much the manager will successfully lead the project for implementation of a change and how much they will manage to amortize stress among employees, mostly depends on their expertise, knowledge and skills to accurately and comprehensively inform and integrate the employees in the overall process. The adaptation model is actually a new approach and recommendation for managers for dealing with stress when the changes are implemented. Methodology. For this purpose, the data presented, in fact, were collected through a questionnaire that was submitted to 61 respondents/ managers. The data were measured using the Likert scale from 1 to 7. Namely, with the help of the Likert scale, quantification of stress was made in relation to the various variables that were identified as the most important for the researched issues. An adaption model (new approach for amortizing changes was created using the DIA Diagram application, to show the relations between manager and the relevant amortization approaches.
Sensitivity study of reduced models of the activated sludge process ...
African Journals Online (AJOL)
2009-08-07
Aug 7, 2009 ... Sensitivity study of reduced models of the activated sludge process, for the purposes of parameter estimation and process optimisation: Benchmark process with ASM1 and UCT reduced biological models. S du Plessis and R Tzoneva*. Department of Electrical Engineering, Cape Peninsula University of ...
Poulter, B.; Ciais, P.; Joetzjer, E.; Maignan, F.; Luyssaert, S.; Barichivich, J.
2015-12-01
Accurately estimating forest biomass and forest carbon dynamics requires new integrated remote sensing, forest inventory, and carbon cycle modeling approaches. Presently, there is an increasing and urgent need to reduce forest biomass uncertainty in order to meet the requirements of carbon mitigation treaties, such as Reducing Emissions from Deforestation and forest Degradation (REDD+). Here we describe a new parameterization and assimilation methodology used to estimate tropical forest biomass using the ORCHIDEE-CAN dynamic global vegetation model. ORCHIDEE-CAN simulates carbon uptake and allocation to individual trees using a mechanistic representation of photosynthesis, respiration and other first-order processes. The model is first parameterized using forest inventory data to constrain background mortality rates, i.e., self-thinning, and productivity. Satellite remote sensing data for forest structure, i.e., canopy height, is used to constrain simulated forest stand conditions using a look-up table approach to match canopy height distributions. The resulting forest biomass estimates are provided for spatial grids that match REDD+ project boundaries and aim to provide carbon estimates for the criteria described in the IPCC Good Practice Guidelines Tier 3 category. With the increasing availability of forest structure variables derived from high-resolution LIDAR, RADAR, and optical imagery, new methodologies and applications with process-based carbon cycle models are becoming more readily available to inform land management.
Directory of Open Access Journals (Sweden)
Wenrui Huang
2010-03-01
Full Text Available This paper presents an improvement of the Mellor and Yamada's 2nd order turbulence model in the Princeton Ocean Model (POM for better predictions of vertical stratifications of salinity in estuaries. The model was evaluated in the strongly stratified estuary, Apalachicola River, Florida, USA. The three-dimensional hydrodynamic model was applied to study the stratified flow and salinity intrusion in the estuary in response to tide, wind, and buoyancy forces. Model tests indicate that model predictions over estimate the stratification when using the default turbulent parameters. Analytic studies of density-induced and wind-induced flows indicate that accurate estimation of vertical eddy viscosity plays an important role in describing vertical profiles. Initial model revision experiments show that the traditional approach of modifying empirical constants in the turbulence model leads to numerical instability. In order to improve the performance of the turbulence model while maintaining numerical stability, a stratification factor was introduced to allow adjustment of the vertical turbulent eddy viscosity and diffusivity. Sensitivity studies indicate that the stratification factor, ranging from 1.0 to 1.2, does not cause numerical instability in Apalachicola River. Model simulations show that increasing the turbulent eddy viscosity by a stratification factor of 1.12 results in an optimal agreement between model predictions and observations in the case study presented in this study. Using the proposed stratification factor provides a useful way for coastal modelers to improve the turbulence model performance in predicting vertical turbulent mixing in stratified estuaries and coastal waters.
Yang, Qiguang; Liu, Xu; Wu, Wan; Kizer, Susan; Baize, Rosemary R.
2016-01-01
A hybrid stream PCRTM-SOLAR model has been proposed for fast and accurate radiative transfer simulation. It calculates the reflected solar (RS) radiances with a fast coarse way and then, with the help of a pre-saved matrix, transforms the results to obtain the desired high accurate RS spectrum. The methodology has been demonstrated with the hybrid stream discrete ordinate (HSDO) radiative transfer (RT) model. The HSDO method calculates the monochromatic radiances using a 4-stream discrete ordinate method, where only a small number of monochromatic radiances are simulated with both 4-stream and a larger N-stream (N = 16) discrete ordinate RT algorithm. The accuracy of the obtained channel radiance is comparable to the result from N-stream moderate resolution atmospheric transmission version 5 (MODTRAN5). The root-mean-square errors are usually less than 5x10(exp -4) mW/sq cm/sr/cm. The computational speed is three to four-orders of magnitude faster than the medium speed correlated-k option MODTRAN5. This method is very efficient to simulate thousands of RS spectra under multi-layer clouds/aerosols and solar radiation conditions for climate change study and numerical weather prediction applications.
The role of public policies in reducing smoking: the Minnesota SimSmoke tobacco policy model.
Levy, David T; Boyle, Raymond G; Abrams, David B
2012-11-01
Following the landmark lawsuit and settlement with the tobacco industry, Minnesota pursued the implementation of stricter tobacco control policies, including tax increases, mass media campaigns, smokefree air laws, and cessation treatment policies. Modeling is used to examine policy effects on smoking prevalence and smoking-attributable deaths. To estimate the effect of tobacco control policies in Minnesota on smoking prevalence and smoking-attributable deaths using the SimSmoke simulation model. Minnesota data starting in 1993 are applied to SimSmoke, a simulation model used to examine the effect of tobacco control policies over time on smoking initiation and cessation. Upon validating the model against smoking prevalence, SimSmoke is used to distinguish the effect of policies implemented since 1993 on smoking prevalence. Using standard attribution methods, SimSmoke also estimates deaths averted as a result of the policies. SimSmoke predicts smoking prevalence accurately between 1993 and 2011. Since 1993, a relative reduction in smoking rates of 29% by 2011 and of 41% by 2041 can be attributed to tobacco control policies, mainly tax increases, smokefree air laws, media campaigns, and cessation treatment programs. Moreover, 48,000 smoking-attributable deaths will be averted by 2041. Minnesota SimSmoke demonstrates that tobacco control policies, especially taxes, have substantially reduced smoking prevalence and smoking-attributable deaths. Taxes, smokefree air laws, mass media, cessation treatment policies, and youth-access enforcement contributed to the decline in prevalence and deaths averted, with the strongest component being taxes. With stronger policies, for example, increasing cigarette taxes to $4.00 per pack, Minnesota's smoking rate could be reduced by another 13%, and 7200 deaths could be averted by 2041. Copyright © 2012 American Journal of Preventive Medicine. Published by Elsevier Inc. All rights reserved.
A Reduced Wind Power Grid Model for Research and Education
DEFF Research Database (Denmark)
Akhmatov, Vladislav; Lund, Torsten; Hansen, Anca Daniela
2007-01-01
A reduced grid model of a transmission system with a number of central power plants, consumption centers, local wind turbines and a large offshore wind farm is developed and implemented in the simulation tool PowerFactory (DIgSILENT). The reduced grid model is given by Energinet.dk, Transmission...
Reduced order modeling of flashing two-phase jets
Energy Technology Data Exchange (ETDEWEB)
Gurecky, William, E-mail: william.gurecky@utexas.edu; Schneider, Erich, E-mail: eschneider@mail.utexas.edu; Ballew, Davis, E-mail: davisballew@utexas.edu
2015-12-01
Highlights: • Accident simulation requires ability to quickly predict two-phase flashing jet's damage potential. • A reduced order modeling methodology informed by experimental or computational data is described. • Zone of influence volumes are calculated for jets of various upstream thermodynamic conditions. - Abstract: In the event of a Loss of Coolant Accident (LOCA) in a pressurized water reactor, the escaping coolant produces a highly energetic flashing jet with the potential to damage surrounding structures. In LOCA analysis, the goal is often to evaluate many break scenarios in a Monte Carlo style simulation to evaluate the resilience of a reactor design. Therefore, in order to quickly predict the damage potential of flashing jets, it is of interest to develop a reduced order model that relates the damage potential of a jet to the pressure and temperature upstream of the break and the distance from the break to a given object upon which the jet is impinging. This work presents framework for producing a Reduced Order Model (ROM) that may be informed by measured data, Computational Fluid Dynamics (CFD) simulations, or a combination of both. The model is constructed by performing regression analysis on the pressure field data, allowing the impingement pressure to be quickly reconstructed for any given upstream thermodynamic condition within the range of input data. The model is applicable to both free and fully impinging two-phase flashing jets.
An efficient and accurate method for calculating nonlinear diffraction beam fields
Energy Technology Data Exchange (ETDEWEB)
Jeong, Hyun Jo; Cho, Sung Jong; Nam, Ki Woong; Lee, Jang Hyun [Division of Mechanical and Automotive Engineering, Wonkwang University, Iksan (Korea, Republic of)
2016-04-15
This study develops an efficient and accurate method for calculating nonlinear diffraction beam fields propagating in fluids or solids. The Westervelt equation and quasilinear theory, from which the integral solutions for the fundamental and second harmonics can be obtained, are first considered. A computationally efficient method is then developed using a multi-Gaussian beam (MGB) model that easily separates the diffraction effects from the plane wave solution. The MGB models provide accurate beam fields when compared with the integral solutions for a number of transmitter-receiver geometries. These models can also serve as fast, powerful modeling tools for many nonlinear acoustics applications, especially in making diffraction corrections for the nonlinearity parameter determination, because of their computational efficiency and accuracy.
Alligné, S.; Maruzewski, P.; Dinh, T.; Wang, B.; Fedorov, A.; Iosfin, J.; Avellan, F.
2010-08-01
The growing development of renewable energies combined with the process of privatization, lead to a change of economical energy market strategies. Instantaneous pricings of electricity as a function of demand or predictions, induces profitable peak productions which are mainly covered by hydroelectric power plants. Therefore, operators harness more hydroelectric facilities at full load operating conditions. However, the Francis Turbine features an axi-symmetric rope leaving the runner which may act under certain conditions as an internal energy source leading to instability. Undesired power and pressure fluctuations are induced which may limit the maximum available power output. BC Hydro experiences such constraints in a hydroelectric power plant consisting of four 435 MW Francis Turbine generating units, which is located in Canada's province of British Columbia. Under specific full load operating conditions, one unit experiences power and pressure fluctuations at 0.46 Hz. The aim of the paper is to present a methodology allowing prediction of this prototype's instability frequency from investigations on the reduced scale model. A new hydro acoustic vortex rope model has been developed in SIMSEN software, taking into account the energy dissipation due to the thermodynamic exchange between the gas and the surrounding liquid. A combination of measurements, CFD simulations and computation of eigenmodes of the reduced scale model installed on test rig, allows the accurate calibration of the vortex rope model parameters at the model scale. Then, transposition of parameters to the prototype according to similitude laws is applied and stability analysis of the power plant is performed. The eigenfrequency of 0.39 Hz related to the first eigenmode of the power plant is determined to be unstable. Predicted frequency of the full load power and pressure fluctuations at the unit unstable operating point is found to be in general agreement with the prototype measurements.
International Nuclear Information System (INIS)
Alligne, S; Maruzewski, P; Avellan, F; Dinh, T; Wang, B; Fedorov, A; Iosfin, J
2010-01-01
The growing development of renewable energies combined with the process of privatization, lead to a change of economical energy market strategies. Instantaneous pricings of electricity as a function of demand or predictions, induces profitable peak productions which are mainly covered by hydroelectric power plants. Therefore, operators harness more hydroelectric facilities at full load operating conditions. However, the Francis Turbine features an axi-symmetric rope leaving the runner which may act under certain conditions as an internal energy source leading to instability. Undesired power and pressure fluctuations are induced which may limit the maximum available power output. BC Hydro experiences such constraints in a hydroelectric power plant consisting of four 435 MW Francis Turbine generating units, which is located in Canada's province of British Columbia. Under specific full load operating conditions, one unit experiences power and pressure fluctuations at 0.46 Hz. The aim of the paper is to present a methodology allowing prediction of this prototype's instability frequency from investigations on the reduced scale model. A new hydro acoustic vortex rope model has been developed in SIMSEN software, taking into account the energy dissipation due to the thermodynamic exchange between the gas and the surrounding liquid. A combination of measurements, CFD simulations and computation of eigenmodes of the reduced scale model installed on test rig, allows the accurate calibration of the vortex rope model parameters at the model scale. Then, transposition of parameters to the prototype according to similitude laws is applied and stability analysis of the power plant is performed. The eigenfrequency of 0.39 Hz related to the first eigenmode of the power plant is determined to be unstable. Predicted frequency of the full load power and pressure fluctuations at the unit unstable operating point is found to be in general agreement with the prototype measurements.
An accurate real-time model of maglev planar motor based on compound Simpson numerical integration
Directory of Open Access Journals (Sweden)
Baoquan Kou
2017-05-01
Full Text Available To realize the high-speed and precise control of the maglev planar motor, a more accurate real-time electromagnetic model, which considers the influence of the coil corners, is proposed in this paper. Three coordinate systems for the stator, mover and corner coil are established. The coil is divided into two segments, the straight coil segment and the corner coil segment, in order to obtain a complete electromagnetic model. When only take the first harmonic of the flux density distribution of a Halbach magnet array into account, the integration method can be carried out towards the two segments according to Lorenz force law. The force and torque analysis formula of the straight coil segment can be derived directly from Newton-Leibniz formula, however, this is not applicable to the corner coil segment. Therefore, Compound Simpson numerical integration method is proposed in this paper to solve the corner segment. With the validation of simulation and experiment, the proposed model has high accuracy and can realize practical application easily.
Advanced Fluid Reduced Order Models for Compressible Flow.
Energy Technology Data Exchange (ETDEWEB)
Tezaur, Irina Kalashnikova [Sandia National Lab. (SNL-CA), Livermore, CA (United States); Fike, Jeffrey A. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Carlberg, Kevin Thomas [Sandia National Lab. (SNL-CA), Livermore, CA (United States); Barone, Matthew F. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Maddix, Danielle [Stanford Univ., CA (United States); Mussoni, Erin E. [Sandia National Lab. (SNL-CA), Livermore, CA (United States); Balajewicz, Maciej [Univ. of Illinois, Urbana-Champaign, IL (United States)
2017-09-01
This report summarizes fiscal year (FY) 2017 progress towards developing and implementing within the SPARC in-house finite volume flow solver advanced fluid reduced order models (ROMs) for compressible captive-carriage flow problems of interest to Sandia National Laboratories for the design and qualification of nuclear weapons components. The proposed projection-based model order reduction (MOR) approach, known as the Proper Orthogonal Decomposition (POD)/Least- Squares Petrov-Galerkin (LSPG) method, can substantially reduce the CPU-time requirement for these simulations, thereby enabling advanced analyses such as uncertainty quantification and de- sign optimization. Following a description of the project objectives and FY17 targets, we overview briefly the POD/LSPG approach to model reduction implemented within SPARC . We then study the viability of these ROMs for long-time predictive simulations in the context of a two-dimensional viscous laminar cavity problem, and describe some FY17 enhancements to the proposed model reduction methodology that led to ROMs with improved predictive capabilities. Also described in this report are some FY17 efforts pursued in parallel to the primary objective of determining whether the ROMs in SPARC are viable for the targeted application. These include the implemen- tation and verification of some higher-order finite volume discretization methods within SPARC (towards using the code to study the viability of ROMs on three-dimensional cavity problems) and a novel structure-preserving constrained POD/LSPG formulation that can improve the accuracy of projection-based reduced order models. We conclude the report by summarizing the key takeaways from our FY17 findings, and providing some perspectives for future work.
A more accurate scheme for calculating Earth's skin temperature
Tsuang, Ben-Jei; Tu, Chia-Ying; Tsai, Jeng-Lin; Dracup, John A.; Arpe, Klaus; Meyers, Tilden
2009-02-01
The theoretical framework of the vertical discretization of a ground column for calculating Earth’s skin temperature is presented. The suggested discretization is derived from the evenly heat-content discretization with the optimal effective thickness for layer-temperature simulation. For the same level number, the suggested discretization is more accurate in skin temperature as well as surface ground heat flux simulations than those used in some state-of-the-art models. A proposed scheme (“op(3,2,0)”) can reduce the normalized root-mean-square error (or RMSE/STD ratio) of the calculated surface ground heat flux of a cropland site significantly to 2% (or 0.9 W m-2), from 11% (or 5 W m-2) by a 5-layer scheme used in ECMWF, from 19% (or 8 W m-2) by a 5-layer scheme used in ECHAM, and from 74% (or 32 W m-2) by a single-layer scheme used in the UCLA GCM. Better accuracy can be achieved by including more layers to the vertical discretization. Similar improvements are expected for other locations with different land types since the numerical error is inherited into the models for all the land types. The proposed scheme can be easily implemented into state-of-the-art climate models for the temperature simulation of snow, ice and soil.
How Accurate are Government Forecast of Economic Fundamentals?
C-L. Chang (Chia-Lin); Ph.H.B.F. Franses (Philip Hans); M.J. McAleer (Michael)
2009-01-01
textabstractA government’s ability to forecast key economic fundamentals accurately can affect business confidence, consumer sentiment, and foreign direct investment, among others. A government forecast based on an econometric model is replicable, whereas one that is not fully based on an
Alter, Stephen J.; Brauckmann, Gregory J.; Kleb, Bil; Streett, Craig L; Glass, Christopher E.; Schuster, David M.
2015-01-01
Using the Fully Unstructured Three-Dimensional (FUN3D) computational fluid dynamics code, an unsteady, time-accurate flow field about a Space Launch System configuration was simulated at a transonic wind tunnel condition (Mach = 0.9). Delayed detached eddy simulation combined with Reynolds Averaged Naiver-Stokes and a Spallart-Almaras turbulence model were employed for the simulation. Second order accurate time evolution scheme was used to simulate the flow field, with a minimum of 0.2 seconds of simulated time to as much as 1.4 seconds. Data was collected at 480 pressure taps at locations, 139 of which matched a 3% wind tunnel model, tested in the Transonic Dynamic Tunnel (TDT) facility at NASA Langley Research Center. Comparisons between computation and experiment showed agreement within 5% in terms of location for peak RMS levels, and 20% for frequency and magnitude of power spectral densities. Grid resolution and time step sensitivity studies were performed to identify methods for improved accuracy comparisons to wind tunnel data. With limited computational resources, accurate trends for reduced vibratory loads on the vehicle were observed. Exploratory methods such as determining minimized computed errors based on CFL number and sub-iterations, as well as evaluating frequency content of the unsteady pressures and evaluation of oscillatory shock structures were used in this study to enhance computational efficiency and solution accuracy. These techniques enabled development of a set of best practices, for the evaluation of future flight vehicle designs in terms of vibratory loads.
Towards cycle-accurate performance predictions for real-time embedded systems
Triantafyllidis, K.; Bondarev, E.; With, de P.H.N.; Arabnia, H.R.; Deligiannidis, L.; Jandieri, G.
2013-01-01
In this paper we present a model-based performance analysis method for component-based real-time systems, featuring cycle-accurate predictions of latencies and enhanced system robustness. The method incorporates the following phases: (a) instruction-level profiling of SW components, (b) modeling the
Accurate Estimation of Target amounts Using Expanded BASS Model for Demand-Side Management
Kim, Hyun-Woong; Park, Jong-Jin; Kim, Jin-O.
2008-10-01
The electricity demand in Korea has rapidly increased along with a steady economic growth since 1970s. Therefore Korea has positively propelled not only SSM (Supply-Side Management) but also DSM (Demand-Side Management) activities to reduce investment cost of generating units and to save supply costs of electricity through the enhancement of whole national energy utilization efficiency. However study for rebate, which have influence on success or failure on DSM program, is not sufficient. This paper executed to modeling mathematically expanded Bass model considering rebates, which have influence on penetration amounts for DSM program. To reflect rebate effect more preciously, the pricing function using in expanded Bass model directly reflects response of potential participants for rebate level.
Simulation study of a rectifying bipolar ion channel: Detailed model versus reduced model
Directory of Open Access Journals (Sweden)
Z. Ható
2016-02-01
Full Text Available We study a rectifying mutant of the OmpF porin ion channel using both all-atom and reduced models. The mutant was created by Miedema et al. [Nano Lett., 2007, 7, 2886] on the basis of the NP semiconductor diode, in which an NP junction is formed. The mutant contains a pore region with positive amino acids on the left-hand side and negative amino acids on the right-hand side. Experiments show that this mutant rectifies. Although we do not know the structure of this mutant, we can build an all-atom model for it on the basis of the structure of the wild type channel. Interestingly, molecular dynamics simulations for this all-atom model do not produce rectification. A reduced model that contains only the important degrees of freedom (the positive and negative amino acids and free ions in an implicit solvent, on the other hand, exhibits rectification. Our calculations for the reduced model (using the Nernst-Planck equation coupled to Local Equilibrium Monte Carlo simulations reveal a rectification mechanism that is different from that seen for semiconductor diodes. The basic reason is that the ions are different in nature from electrons and holes (they do not recombine. We provide explanations for the failure of the all-atom model including the effect of all the other atoms in the system as a noise that inhibits the response of ions (that would be necessary for rectification to the polarizing external field.
An Efficient Reduced-Order Model for the Nonlinear Dynamics of Carbon Nanotubes
Xu, Tiantian
2014-08-17
Because of the inherent nonlinearities involving the behavior of CNTs when excited by electrostatic forces, modeling and simulating their behavior is challenging. The complicated form of the electrostatic force describing the interaction of their cylindrical shape, forming upper electrodes, to lower electrodes poises serious computational challenges. This presents an obstacle against applying and using several nonlinear dynamics tools that typically used to analyze the behavior of complicated nonlinear systems, such as shooting, continuation, and integrity analysis techniques. This works presents an attempt to resolve this issue. We present an investigation of the nonlinear dynamics of carbon nanotubes when actuated by large electrostatic forces. We study expanding the complicated form of the electrostatic force into enough number of terms of the Taylor series. We plot and compare the expanded form of the electrostatic force to the exact form and found that at least twenty terms are needed to capture accurately the strong nonlinear form of the force over the full range of motion. Then, we utilize this form along with an Euler–Bernoulli beam model to study the static and dynamic behavior of CNTs. The geometric nonlinearity and the nonlinear electrostatic force are considered. An efficient reduced-order model (ROM) based on the Galerkin method is developed and utilized to simulate the static and dynamic responses of the CNTs. We found that the use of the new expanded form of the electrostatic force enables avoiding the cumbersome evaluation of the spatial integrals involving the electrostatic force during the modal projection procedure in the Galerkin method, which needs to be done at every time step. Hence, the new method proves to be much more efficient computationally.
Application of thin plate splines for accurate regional ionosphere modeling with multi-GNSS data
Krypiak-Gregorczyk, Anna; Wielgosz, Pawel; Borkowski, Andrzej
2016-04-01
GNSS-derived regional ionosphere models are widely used in both precise positioning, ionosphere and space weather studies. However, their accuracy is often not sufficient to support precise positioning, RTK in particular. In this paper, we presented new approach that uses solely carrier phase multi-GNSS observables and thin plate splines (TPS) for accurate ionospheric TEC modeling. TPS is a closed solution of a variational problem minimizing both the sum of squared second derivatives of a smoothing function and the deviation between data points and this function. This approach is used in UWM-rt1 regional ionosphere model developed at UWM in Olsztyn. The model allows for providing ionospheric TEC maps with high spatial and temporal resolutions - 0.2x0.2 degrees and 2.5 minutes, respectively. For TEC estimation, EPN and EUPOS reference station data is used. The maps are available with delay of 15-60 minutes. In this paper we compare the performance of UWM-rt1 model with IGS global and CODE regional ionosphere maps during ionospheric storm that took place on March 17th, 2015. During this storm, the TEC level over Europe doubled comparing to earlier quiet days. The performance of the UWM-rt1 model was validated by (a) comparison to reference double-differenced ionospheric corrections over selected baselines, and (b) analysis of post-fit residuals to calibrated carrier phase geometry-free observational arcs at selected test stations. The results show a very good performance of UWM-rt1 model. The obtained post-fit residuals in case of UWM maps are lower by one order of magnitude comparing to IGS maps. The accuracy of UWM-rt1 -derived TEC maps is estimated at 0.5 TECU. This may be directly translated to the user positioning domain.
Scoring predictive models using a reduced representation of proteins: model and energy definition.
Fogolari, Federico; Pieri, Lidia; Dovier, Agostino; Bortolussi, Luca; Giugliarelli, Gilberto; Corazza, Alessandra; Esposito, Gennaro; Viglino, Paolo
2007-03-23
Reduced representations of proteins have been playing a keyrole in the study of protein folding. Many such models are available, with different representation detail. Although the usefulness of many such models for structural bioinformatics applications has been demonstrated in recent years, there are few intermediate resolution models endowed with an energy model capable, for instance, of detecting native or native-like structures among decoy sets. The aim of the present work is to provide a discrete empirical potential for a reduced protein model termed here PC2CA, because it employs a PseudoCovalent structure with only 2 Centers of interactions per Amino acid, suitable for protein model quality assessment. All protein structures in the set top500H have been converted in reduced form. The distribution of pseudobonds, pseudoangle, pseudodihedrals and distances between centers of interactions have been converted into potentials of mean force. A suitable reference distribution has been defined for non-bonded interactions which takes into account excluded volume effects and protein finite size. The correlation between adjacent main chain pseudodihedrals has been converted in an additional energetic term which is able to account for cooperative effects in secondary structure elements. Local energy surface exploration is performed in order to increase the robustness of the energy function. The model and the energy definition proposed have been tested on all the multiple decoys' sets in the Decoys'R'us database. The energetic model is able to recognize, for almost all sets, native-like structures (RMSD less than 2.0 A). These results and those obtained in the blind CASP7 quality assessment experiment suggest that the model compares well with scoring potentials with finer granularity and could be useful for fast exploration of conformational space. Parameters are available at the url: http://www.dstb.uniud.it/~ffogolari/download/.
Hartveit, Espen; Veruki, Margaret Lin
2010-03-15
Accurate measurement of the junctional conductance (G(j)) between electrically coupled cells can provide important information about the functional properties of coupling. With the development of tight-seal, whole-cell recording, it became possible to use dual, single-electrode voltage-clamp recording from pairs of small cells to measure G(j). Experiments that require reduced perturbation of the intracellular environment can be performed with high-resistance pipettes or the perforated-patch technique, but an accompanying increase in series resistance (R(s)) compromises voltage-clamp control and reduces the accuracy of G(j) measurements. Here, we present a detailed analysis of methodologies available for accurate determination of steady-state G(j) and related parameters under conditions of high R(s), using continuous or discontinuous single-electrode voltage-clamp (CSEVC or DSEVC) amplifiers to quantify the parameters of different equivalent electrical circuit model cells. Both types of amplifiers can provide accurate measurements of G(j), with errors less than 5% for a wide range of R(s) and G(j) values. However, CSEVC amplifiers need to be combined with R(s)-compensation or mathematical correction for the effects of nonzero R(s) and finite membrane resistance (R(m)). R(s)-compensation is difficult for higher values of R(s) and leads to instability that can damage the recorded cells. Mathematical correction for R(s) and R(m) yields highly accurate results, but depends on accurate estimates of R(s) throughout an experiment. DSEVC amplifiers display very accurate measurements over a larger range of R(s) values than CSEVC amplifiers and have the advantage that knowledge of R(s) is unnecessary, suggesting that they are preferable for long-duration experiments and/or recordings with high R(s). Copyright (c) 2009 Elsevier B.V. All rights reserved.
Noori, Roohollah; Safavi, Salman; Nateghi Shahrokni, Seyyed Afshin
2013-07-01
The five-day biochemical oxygen demand (BOD5) is one of the key parameters in water quality management. In this study, a novel approach, i.e., reduced-order adaptive neuro-fuzzy inference system (ROANFIS) model was developed for rapid estimation of BOD5. In addition, an uncertainty analysis of adaptive neuro-fuzzy inference system (ANFIS) and ROANFIS models was carried out based on Monte-Carlo simulation. Accuracy analysis of ANFIS and ROANFIS models based on both developed discrepancy ratio and threshold statistics revealed that the selected ROANFIS model was superior. Pearson correlation coefficient (R) and root mean square error for the best fitted ROANFIS model were 0.96 and 7.12, respectively. Furthermore, uncertainty analysis of the developed models indicated that the selected ROANFIS had less uncertainty than the ANFIS model and accurately forecasted BOD5 in the Sefidrood River Basin. Besides, the uncertainty analysis also showed that bracketed predictions by 95% confidence bound and d-factor in the testing steps for the selected ROANFIS model were 94% and 0.83, respectively.
MaMR: High-performance MapReduce programming model for material cloud applications
Jing, Weipeng; Tong, Danyu; Wang, Yangang; Wang, Jingyuan; Liu, Yaqiu; Zhao, Peng
2017-02-01
With the increasing data size in materials science, existing programming models no longer satisfy the application requirements. MapReduce is a programming model that enables the easy development of scalable parallel applications to process big data on cloud computing systems. However, this model does not directly support the processing of multiple related data, and the processing performance does not reflect the advantages of cloud computing. To enhance the capability of workflow applications in material data processing, we defined a programming model for material cloud applications that supports multiple different Map and Reduce functions running concurrently based on hybrid share-memory BSP called MaMR. An optimized data sharing strategy to supply the shared data to the different Map and Reduce stages was also designed. We added a new merge phase to MapReduce that can efficiently merge data from the map and reduce modules. Experiments showed that the model and framework present effective performance improvements compared to previous work.
Reduced Order Modeling in General Relativity
Tiglio, Manuel
2014-03-01
Reduced Order Modeling is an emerging yet fast developing filed in gravitational wave physics. The main goals are to enable fast modeling and parameter estimation of any detected signal, along with rapid matched filtering detecting. I will focus on the first two. Some accomplishments include being able to replace, with essentially no lost of physical accuracy, the original models with surrogate ones (which are not effective ones, that is, they do not simplify the physics but go on a very different track, exploiting the particulars of the waveform family under consideration and state of the art dimensional reduction techniques) which are very fast to evaluate. For example, for EOB models they are at least around 3 orders of magnitude faster than solving the original equations, with physically equivalent results. For numerical simulations the speedup is at least 11 orders of magnitude. For parameter estimation our current numbers are about bringing ~100 days for a single SPA inspiral binary neutron star Bayesian parameter estimation analysis to under a day. More recently, it has been shown that the full precessing problem for, say, 200 cycles, can be represented, through some new ideas, by a remarkably compact set of carefully chosen reduced basis waveforms (~10-100, depending on the accuracy requirements). I will highlight what I personally believe are the challenges to face next in this subarea of GW physics and where efforts should be directed. This talk will summarize work in collaboration with: Harbir Antil (GMU), Jonathan Blackman (Caltech), Priscila Canizares (IoA, Cambridge, UK), Sarah Caudill (UWM), Jonathan Gair (IoA. Cambridge. UK), Scott Field (UMD), Chad R. Galley (Caltech), Frank Herrmann (Germany), Han Hestahven (EPFL, Switzerland), Jason Kaye (Brown, Stanford & Courant). Evan Ochsner (UWM), Ricardo Nochetto (UMD), Vivien Raymond (LIGO, Caltech), Rory Smith (LIGO, Caltech) Bela Ssilagyi (Caltech) and MT (UMD & Caltech).
Harris, Charlie L; Strayhorn, Gregory; Moore, Sandra; Goldman, Brian; Martin, Michelle Y
2016-01-01
Obese African American women under-appraise their body mass index (BMI) classification and report fewer weight loss attempts than women who accurately appraise their weight status. This cross-sectional study examined whether physician-informed weight status could predict weight self-perception and weight self-regulation strategies in obese women. A convenience sample of 118 low-income women completed a survey assessing demographic characteristics, comorbidities, weight self-perception, and weight self-regulation strategies. BMI was calculated during nurse triage. Binary logistic regression models were performed to test hypotheses. The odds of obese accurate appraisers having been informed about their weight status were six times greater than those of under-appraisers. The odds of those using an "approach" self-regulation strategy having been physician-informed were four times greater compared with those using an "avoidance" strategy. Physicians are uniquely positioned to influence accurate weight self-perception and adaptive weight self-regulation strategies in underserved women, reducing their risk for obesity-related morbidity.
Approaches for Reduced Order Modeling of Electrically Actuated von Karman Microplates
Saghir, Shahid
2016-07-25
This article presents and compares different approaches to develop reduced order models for the nonlinear von Karman rectangular microplates actuated by nonlinear electrostatic forces. The reduced-order models aim to investigate the static and dynamic behavior of the plate under small and large actuation forces. A fully clamped microplate is considered. Different types of basis functions are used in conjunction with the Galerkin method to discretize the governing equations. First we investigate the convergence with the number of modes retained in the model. Then for validation purpose, a comparison of the static results is made with the results calculated by a nonlinear finite element model. The linear eigenvalue problem for the plate under the electrostatic force is solved for a wide range of voltages up to pull-in. Results among the various reduced-order modes are compared and are also validated by comparing to results of the finite-element model. Further, the reduced order models are employed to capture the forced dynamic response of the microplate under small and large vibration amplitudes. Comparison of the different approaches are made for this case. Keywords: electrically actuated microplates, static analysis, dynamics of microplates, diaphragm vibration, large amplitude vibrations, nonlinear dynamics
Reduced Complexity Volterra Models for Nonlinear System Identification
Directory of Open Access Journals (Sweden)
Hacıoğlu Rıfat
2001-01-01
Full Text Available A broad class of nonlinear systems and filters can be modeled by the Volterra series representation. However, its practical use in nonlinear system identification is sometimes limited due to the large number of parameters associated with the Volterra filter′s structure. The parametric complexity also complicates design procedures based upon such a model. This limitation for system identification is addressed in this paper using a Fixed Pole Expansion Technique (FPET within the Volterra model structure. The FPET approach employs orthonormal basis functions derived from fixed (real or complex pole locations to expand the Volterra kernels and reduce the number of estimated parameters. That the performance of FPET can considerably reduce the number of estimated parameters is demonstrated by a digital satellite channel example in which we use the proposed method to identify the channel dynamics. Furthermore, a gradient-descent procedure that adaptively selects the pole locations in the FPET structure is developed in the paper.
Directory of Open Access Journals (Sweden)
M. Zacharek
2017-05-01
Full Text Available These studies have been conductedusing non-metric digital camera and dense image matching algorithms, as non-contact methods of creating monuments documentation.In order toprocess the imagery, few open-source software and algorithms of generating adense point cloud from images have been executed. In the research, the OSM Bundler, VisualSFM software, and web application ARC3D were used. Images obtained for each of the investigated objects were processed using those applications, and then dense point clouds and textured 3D models were created. As a result of post-processing, obtained models were filtered and scaled.The research showedthat even using the open-source software it is possible toobtain accurate 3D models of structures (with an accuracy of a few centimeters, but for the purpose of documentation and conservation of cultural and historical heritage, such accuracy can be insufficient.
van Wyk, Marnus J; Bingle, Marianne; Meyer, Frans J C
2005-09-01
International bodies such as International Commission on Non-Ionizing Radiation Protection (ICNIRP) and the Institute for Electrical and Electronic Engineering (IEEE) make provision for human exposure assessment based on SAR calculations (or measurements) and basic restrictions. In the case of base station exposure this is mostly applicable to occupational exposure scenarios in the very near field of these antennas where the conservative reference level criteria could be unnecessarily restrictive. This study presents a variety of critical aspects that need to be considered when calculating SAR in a human body close to a mobile phone base station antenna. A hybrid FEM/MoM technique is proposed as a suitable numerical method to obtain accurate results. The verification of the FEM/MoM implementation has been presented in a previous publication; the focus of this study is an investigation into the detail that must be included in a numerical model of the antenna, to accurately represent the real-world scenario. This is accomplished by comparing numerical results to measurements for a generic GSM base station antenna and appropriate, representative canonical and human phantoms. The results show that it is critical to take the disturbance effect of the human phantom (a large conductive body) on the base station antenna into account when the antenna-phantom spacing is less than 300 mm. For these small spacings, the antenna structure must be modeled in detail. The conclusion is that it is feasible to calculate, using the proposed techniques and methodology, accurate occupational compliance zones around base station antennas based on a SAR profile and basic restriction guidelines. (c) 2005 Wiley-Liss, Inc.
International Nuclear Information System (INIS)
Sharp, Leah Z.; Egorova, Dassia; Domcke, Wolfgang
2010-01-01
Two-dimensional (2D) photon-echo spectra of a single subunit of the Fenna-Matthews-Olson (FMO) bacteriochlorophyll trimer of Chlorobium tepidum are simulated, employing the equation-of-motion phase-matching approach (EOM-PMA). We consider a slightly extended version of the previously proposed Frenkel exciton model, which explicitly accounts for exciton coherences in the secular approximation. The study is motivated by a recent experiment reporting long-lived coherent oscillations in 2D transients [Engel et al., Nature 446, 782 (2007)] and aims primarily at accurate simulations of the spectroscopic signals, with the focus on oscillations of 2D peak intensities with population time. The EOM-PMA accurately accounts for finite pulse durations as well as pulse-overlap effects and does not invoke approximations apart from the weak-field limit for a given material system. The population relaxation parameters of the exciton model are taken from the literature. The effects of various dephasing mechanisms on coherence lifetimes are thoroughly studied. It is found that the experimentally detected multiple frequencies in peak oscillations cannot be reproduced by the employed FMO model, which calls for the development of a more sophisticated exciton model of the FMO complex.
Application of an accurate thermal hydraulics solver in VTT's reactor dynamics codes
International Nuclear Information System (INIS)
Rajamaeki, M.; Raety, H.; Kyrki-Rajamaeki, R.; Eskola, M.
1998-01-01
VTT's reactor dynamics codes are developed further and new more detailed models are created for tasks related to increased safety requirements. For thermal hydraulics calculations an accurate general flow model based on a new solution method PLIM has been developed. It has been applied in VTT's one-dimensional TRAB and three-dimensional HEXTRAN codes. Results of a demanding international boron dilution benchmark defined by VTT are given and compared against results of other codes with original or improved boron tracking. The new PLIM method not only allows the accurate modelling of a propagating boron dilution front, but also the tracking of a temperature front, which is missed by the special boron tracking models. (orig.)
Energy Technology Data Exchange (ETDEWEB)
Bok, H.-H.; Kim, S.N.; Suh, D.W. [Graduate Institute of Ferrous Technology, POSTECH, San 31, Hyoja-dong, Nam-gu, Pohang, Gyeongsangbuk-do (Korea, Republic of); Barlat, F., E-mail: f.barlat@postech.ac.kr [Graduate Institute of Ferrous Technology, POSTECH, San 31, Hyoja-dong, Nam-gu, Pohang, Gyeongsangbuk-do (Korea, Republic of); Lee, M.-G., E-mail: myounglee@korea.ac.kr [Department of Materials Science and Engineering, Korea University, Anam-dong, Seongbuk-gu, Seoul (Korea, Republic of)
2015-02-25
A non-isothermal phase transformation kinetics model obtained by modifying the well-known JMAK approach is proposed for application to a low carbon boron steel (22MnB5) sheet. In the modified kinetics model, the parameters are functions of both temperature and cooling rate, and can be identified by a numerical optimization method. Moreover, in this approach the transformation start and finish temperatures are variable instead of the constants that depend on chemical composition. These variable reference temperatures are determined from the measured CCT diagram using dilatation experiments. The kinetics model developed in this work captures the complex transformation behavior of the boron steel sheet sample accurately. In particular, the predicted hardness and phase fractions in the specimens subjected to a wide range of cooling rates were validated by experiments.
Directory of Open Access Journals (Sweden)
Sergei L Kosakovsky Pond
2009-11-01
Full Text Available Genetically diverse pathogens (such as Human Immunodeficiency virus type 1, HIV-1 are frequently stratified into phylogenetically or immunologically defined subtypes for classification purposes. Computational identification of such subtypes is helpful in surveillance, epidemiological analysis and detection of novel variants, e.g., circulating recombinant forms in HIV-1. A number of conceptually and technically different techniques have been proposed for determining the subtype of a query sequence, but there is not a universally optimal approach. We present a model-based phylogenetic method for automatically subtyping an HIV-1 (or other viral or bacterial sequence, mapping the location of breakpoints and assigning parental sequences in recombinant strains as well as computing confidence levels for the inferred quantities. Our Subtype Classification Using Evolutionary ALgorithms (SCUEAL procedure is shown to perform very well in a variety of simulation scenarios, runs in parallel when multiple sequences are being screened, and matches or exceeds the performance of existing approaches on typical empirical cases. We applied SCUEAL to all available polymerase (pol sequences from two large databases, the Stanford Drug Resistance database and the UK HIV Drug Resistance Database. Comparing with subtypes which had previously been assigned revealed that a minor but substantial (approximately 5% fraction of pure subtype sequences may in fact be within- or inter-subtype recombinants. A free implementation of SCUEAL is provided as a module for the HyPhy package and the Datamonkey web server. Our method is especially useful when an accurate automatic classification of an unknown strain is desired, and is positioned to complement and extend faster but less accurate methods. Given the increasingly frequent use of HIV subtype information in studies focusing on the effect of subtype on treatment, clinical outcome, pathogenicity and vaccine design, the importance
How Accurately can we Calculate Thermal Systems?
International Nuclear Information System (INIS)
Cullen, D; Blomquist, R N; Dean, C; Heinrichs, D; Kalugin, M A; Lee, M; Lee, Y; MacFarlan, R; Nagaya, Y; Trkov, A
2004-01-01
I would like to determine how accurately a variety of neutron transport code packages (code and cross section libraries) can calculate simple integral parameters, such as K eff , for systems that are sensitive to thermal neutron scattering. Since we will only consider theoretical systems, we cannot really determine absolute accuracy compared to any real system. Therefore rather than accuracy, it would be more precise to say that I would like to determine the spread in answers that we obtain from a variety of code packages. This spread should serve as an excellent indicator of how accurately we can really model and calculate such systems today. Hopefully, eventually this will lead to improvements in both our codes and the thermal scattering models that they use in the future. In order to accomplish this I propose a number of extremely simple systems that involve thermal neutron scattering that can be easily modeled and calculated by a variety of neutron transport codes. These are theoretical systems designed to emphasize the effects of thermal scattering, since that is what we are interested in studying. I have attempted to keep these systems very simple, and yet at the same time they include most, if not all, of the important thermal scattering effects encountered in a large, water-moderated, uranium fueled thermal system, i.e., our typical thermal reactors
Accurate control testing for clay liner permeability
Energy Technology Data Exchange (ETDEWEB)
Mitchell, R J
1991-08-01
Two series of centrifuge tests were carried out to evaluate the use of centrifuge modelling as a method of accurate control testing of clay liner permeability. The first series used a large 3 m radius geotechnical centrifuge and the second series a small 0.5 m radius machine built specifically for research on clay liners. Two permeability cells were fabricated in order to provide direct data comparisons between the two methods of permeability testing. In both cases, the centrifuge method proved to be effective and efficient, and was found to be free of both the technical difficulties and leakage risks normally associated with laboratory permeability testing of fine grained soils. Two materials were tested, a consolidated kaolin clay having an average permeability coefficient of 1.2{times}10{sup -9} m/s and a compacted illite clay having a permeability coefficient of 2.0{times}10{sup -11} m/s. Four additional tests were carried out to demonstrate that the 0.5 m radius centrifuge could be used for linear performance modelling to evaluate factors such as volumetric water content, compaction method and density, leachate compatibility and other construction effects on liner leakage. The main advantages of centrifuge testing of clay liners are rapid and accurate evaluation of hydraulic properties and realistic stress modelling for performance evaluations. 8 refs., 12 figs., 7 tabs.
Pauwels, Steven; Boucart, Nick; Dierckx, Benoit; Van Vlierberghe, Pieter
2000-05-01
The use of a scanning laser Doppler vibrometer for vibration testing is becoming a popular instrument. The scanning laser Doppler vibrometer is a non-contacting transducer that can measure many points at a high spatial resolution in a short time. Manually aiming the laser beam at the points that need to be measured is very time consuming. In order to use it effectively, the position of the laser Doppler vibrometer needs to be determined relative to the structure. If the position of the laser Doppler vibrometer is known, any visible point on the structure can be hit and measured automatically. A new algorithm for this position determination is developed, based on a geometry model of the structure. After manually aiming the laser beam at 4 or more known points, the laser position and orientation relative to the structure is determined. Using this calculated position and orientation a list with the mirror angles for every measurement point is generated, which is used during the measurement. The algorithm is validated using 3 practical cases. In the first case a plate is used of which the points are measured very accurately, so the geometry model is assumed to be perfect. The second case is a brake disc. Here the geometry points are measured with a ruler, thus not so accurate. The final validation is done on a body in white of a car. A reduced finite element model is used as geometry model. This calibration shows that the new algorithm is very effective and practically usable.
DEFF Research Database (Denmark)
Hermannsson, Pétur Gordon; Vannahme, Christoph; Smith, Cameron L. C.
2014-01-01
and superstrate materials. The importance of accounting for material dispersion in order to obtain accurate simulation results is highlighted, and a method for doing so using an iterative approach is demonstrated. Furthermore, an application for the model is demonstrated, in which the material dispersion......In the past decade, photonic crystal resonant reflectors have been increasingly used as the basis for label-free biochemical assays in lab-on-a-chip applications. In both designing and interpreting experimental results, an accurate model describing the optical behavior of such structures...... is essential. Here, an analytical method for precisely predicting the absolute positions of resonantly reflected wavelengths is presented. The model is experimentally verified to be highly accurate using nanoreplicated, polymer-based photonic crystal grating reflectors with varying grating periods...
Parametric structural modeling of insect wings
International Nuclear Information System (INIS)
Mengesha, T E; Vallance, R R; Barraja, M; Mittal, R
2009-01-01
Insects produce thrust and lift forces via coupled fluid-structure interactions that bend and twist their compliant wings during flapping cycles. Insight into this fluid-structure interaction is achieved with numerical modeling techniques such as coupled finite element analysis and computational fluid dynamics, but these methods require accurate and validated structural models of insect wings. Structural models of insect wings depend principally on the shape, dimensions and material properties of the veins and membrane cells. This paper describes a method for parametric modeling of wing geometry using digital images and demonstrates the use of the geometric models in constructing three-dimensional finite element (FE) models and simple reduced-order models. The FE models are more complete and accurate than previously reported models since they accurately represent the topology of the vein network, as well as the shape and dimensions of the veins and membrane cells. The methods are demonstrated by developing a parametric structural model of a cicada forewing.
Estimating Gravity Biases with Wavelets in Support of a 1-cm Accurate Geoid Model
Ahlgren, K.; Li, X.
2017-12-01
Systematic errors that reside in surface gravity datasets are one of the major hurdles in constructing a high-accuracy geoid model at high resolutions. The National Oceanic and Atmospheric Administration's (NOAA) National Geodetic Survey (NGS) has an extensive historical surface gravity dataset consisting of approximately 10 million gravity points that are known to have systematic biases at the mGal level (Saleh et al. 2013). As most relevant metadata is absent, estimating and removing these errors to be consistent with a global geopotential model and airborne data in the corresponding wavelength is quite a difficult endeavor. However, this is crucial to support a 1-cm accurate geoid model for the United States. With recently available independent gravity information from GRACE/GOCE and airborne gravity from the NGS Gravity for the Redefinition of the American Vertical Datum (GRAV-D) project, several different methods of bias estimation are investigated which utilize radial basis functions and wavelet decomposition. We estimate a surface gravity value by incorporating a satellite gravity model, airborne gravity data, and forward-modeled topography at wavelet levels according to each dataset's spatial wavelength. Considering the estimated gravity values over an entire gravity survey, an estimate of the bias and/or correction for the entire survey can be found and applied. In order to assess the accuracy of each bias estimation method, two techniques are used. First, each bias estimation method is used to predict the bias for two high-quality (unbiased and high accuracy) geoid slope validation surveys (GSVS) (Smith et al. 2013 & Wang et al. 2017). Since these surveys are unbiased, the various bias estimation methods should reflect that and provide an absolute accuracy metric for each of the bias estimation methods. Secondly, the corrected gravity datasets from each of the bias estimation methods are used to build a geoid model. The accuracy of each geoid model
State reduced order models for the modelling of the thermal behavior of buildings
Energy Technology Data Exchange (ETDEWEB)
Menezo, Christophe; Bouia, Hassan; Roux, Jean-Jacques; Depecker, Patrick [Institute National de Sciences Appliquees de Lyon, Villeurbanne Cedex, (France). Centre de Thermique de Lyon (CETHIL). Equipe Thermique du Batiment]. E-mail: menezo@insa-cethil-etb.insa-lyon.fr; bouia@insa-cethil-etb.insa-lyon.fr; roux@insa-cethil-etb.insa-lyon.fr; depecker@insa-cethil-etb.insa-lyon.fr
2000-07-01
This work is devoted to the field of building physics and related to the reduction of heat conduction models. The aim is to enlarge the model libraries of heat and mass transfer codes through limiting the considerable dimensions reached by the numerical systems during the modelling process of a multizone building. We show that the balanced realization technique, specifically adapted to the coupling of reduced order models with the other thermal phenomena, turns out to be very efficient. (author)
Kroonblawd, Matthew P; Pietrucci, Fabio; Saitta, Antonino Marco; Goldman, Nir
2018-04-10
We demonstrate the capability of creating robust density functional tight binding (DFTB) models for chemical reactivity in prebiotic mixtures through force matching to short time scale quantum free energy estimates. Molecular dynamics using density functional theory (DFT) is a highly accurate approach to generate free energy surfaces for chemical reactions, but the extreme computational cost often limits the time scales and range of thermodynamic states that can feasibly be studied. In contrast, DFTB is a semiempirical quantum method that affords up to a thousandfold reduction in cost and can recover DFT-level accuracy. Here, we show that a force-matched DFTB model for aqueous glycine condensation reactions yields free energy surfaces that are consistent with experimental observations of reaction energetics. Convergence analysis reveals that multiple nanoseconds of combined trajectory are needed to reach a steady-fluctuating free energy estimate for glycine condensation. Predictive accuracy of force-matched DFTB is demonstrated by direct comparison to DFT, with the two approaches yielding surfaces with large regions that differ by only a few kcal mol -1 .
International Nuclear Information System (INIS)
Wu, Szu-Ying; Tsai, Bor-Jiun; Chen, Jien-Jong
2015-01-01
In this study, a 3-D automatic elastic-plastic finite element mesh generator is established to accurately predict the J-integral value of an arbitrary reducer with a constant-depth internal circumferential surface crack under bending and axial force. The contact pairs are used on the crack surfaces to simulate the actual contact behaviors of the crack model under loadings. In order to verify the accuracy of the proposed elastic-plastic finite element model for a reducer with a surface crack, the cracked straight pipe models are generated according to a special modeling procedure for a flawed reducer. The J-integral values along the crack front of surface crack are calculated and compared with the straight pipe models which have been verified in the previous published studies. Based on the comparison of computed results, good agreements are obtained to show the accuracy of present numerical models. More confidence on using the 3-D elastic-plastic finite element analysis for reducers with internal circumferential surface cracks can be thus established in this work
A reduced fidelity model for the rotary chemical looping combustion reactor
Iloeje, Chukwunwike O.
2017-01-11
The rotary chemical looping combustion reactor has great potential for efficient integration with CO capture-enabled energy conversion systems. In earlier studies, we described a one-dimensional rotary reactor model, and used it to demonstrate the feasibility of continuous reactor operation. Though this detailed model provides a high resolution representation of the rotary reactor performance, it is too computationally expensive for studies that require multiple model evaluations. Specifically, it is not ideal for system-level studies where the reactor is a single component in an energy conversion system. In this study, we present a reduced fidelity model (RFM) of the rotary reactor that reduces computational cost and determines an optimal combination of variables that satisfy reactor design requirements. Simulation results for copper, nickel and iron-based oxygen carriers show a four-order of magnitude reduction in simulation time, and reasonable prediction accuracy. Deviations from the detailed reference model predictions range from 3% to 20%, depending on oxygen carrier type and operating conditions. This study also demonstrates how the reduced model can be modified to deal with both optimization and design oriented problems. A parametric study using the reduced model is then applied to analyze the sensitivity of the optimal reactor design to changes in selected operating and kinetic parameters. These studies show that temperature and activation energy have a greater impact on optimal geometry than parameters like pressure or feed fuel fraction for the selected oxygen carrier materials.
Qi, D.; Majda, A.
2017-12-01
A low-dimensional reduced-order statistical closure model is developed for quantifying the uncertainty in statistical sensitivity and intermittency in principal model directions with largest variability in high-dimensional turbulent system and turbulent transport models. Imperfect model sensitivity is improved through a recent mathematical strategy for calibrating model errors in a training phase, where information theory and linear statistical response theory are combined in a systematic fashion to achieve the optimal model performance. The idea in the reduced-order method is from a self-consistent mathematical framework for general systems with quadratic nonlinearity, where crucial high-order statistics are approximated by a systematic model calibration procedure. Model efficiency is improved through additional damping and noise corrections to replace the expensive energy-conserving nonlinear interactions. Model errors due to the imperfect nonlinear approximation are corrected by tuning the model parameters using linear response theory with an information metric in a training phase before prediction. A statistical energy principle is adopted to introduce a global scaling factor in characterizing the higher-order moments in a consistent way to improve model sensitivity. Stringent models of barotropic and baroclinic turbulence are used to display the feasibility of the reduced-order methods. Principal statistical responses in mean and variance can be captured by the reduced-order models with accuracy and efficiency. Besides, the reduced-order models are also used to capture crucial passive tracer field that is advected by the baroclinic turbulent flow. It is demonstrated that crucial principal statistical quantities like the tracer spectrum and fat-tails in the tracer probability density functions in the most important large scales can be captured efficiently with accuracy using the reduced-order tracer model in various dynamical regimes of the flow field with
Reducing CQI Signalling Overhead in HSPA
Directory of Open Access Journals (Sweden)
Saied M. Abd El-atty
2008-01-01
Full Text Available The efficiency of adaptive modulation and coding (AMC procedure in high speed Downlink packet access (HSDPA depends on the frequency of the channel quality information (CQI reports transmitted by the UE to Node B. The more frequent the reports are the more accurate the link adaptation procedure is. On the other hand, the frequent CQI reports increase uplink interference, reducing thus the signal reception quality at the uplink. In this study, we propose an improved CQI reporting scheme which aims to reduce the required CQI signaling by exploiting a CQI prediction method based on a finite-state Markov chain (FSMC model of the wireless channel. The simulation results show that under a high downlink traffic load, the proposed scheme has a near-to-optimum performance while produces less interference compared to the respective periodic CQI scheme.
Towards Relaxing the Spherical Solar Radiation Pressure Model for Accurate Orbit Predictions
Lachut, M.; Bennett, J.
2016-09-01
The well-known cannonball model has been used ubiquitously to capture the effects of atmospheric drag and solar radiation pressure on satellites and/or space debris for decades. While it lends itself naturally to spherical objects, its validity in the case of non-spherical objects has been debated heavily for years throughout the space situational awareness community. One of the leading motivations to improve orbit predictions by relaxing the spherical assumption, is the ongoing demand for more robust and reliable conjunction assessments. In this study, we explore the orbit propagation of a flat plate in a near-GEO orbit under the influence of solar radiation pressure, using a Lambertian BRDF model. Consequently, this approach will account for the spin rate and orientation of the object, which is typically determined in practice using a light curve analysis. Here, simulations will be performed which systematically reduces the spin rate to demonstrate the point at which the spherical model no longer describes the orbital elements of the spinning plate. Further understanding of this threshold would provide insight into when a higher fidelity model should be used, thus resulting in improved orbit propagations. Therefore, the work presented here is of particular interest to organizations and researchers that maintain their own catalog, and/or perform conjunction analyses.
Directory of Open Access Journals (Sweden)
Claudia M. Colciago
2018-06-01
Full Text Available This paper deals with fast simulations of the hemodynamics in large arteries by considering a reduced model of the associated fluid-structure interaction problem, which in turn allows an additional reduction in terms of the numerical discretisation. The resulting method is both accurate and computationally cheap. This goal is achieved by means of two levels of reduction: first, we describe the model equations with a reduced mathematical formulation which allows to write the fluid-structure interaction problem as a Navier-Stokes system with non-standard boundary conditions; second, we employ numerical reduction techniques to further and drastically lower the computational costs. The non standard boundary condition is of a generalized Robin type, with a boundary mass and boundary stiffness terms accounting for the arterial wall compliance. The numerical reduction is obtained coupling two well-known techniques: the proper orthogonal decomposition and the reduced basis method, in particular the greedy algorithm. We start by reducing the numerical dimension of the problem at hand with a proper orthogonal decomposition and we measure the system energy with specific norms; this allows to take into account the different orders of magnitude of the state variables, the velocity and the pressure. Then, we introduce a strategy based on a greedy procedure which aims at enriching the reduced discretization space with low offline computational costs. As application, we consider a realistic hemodynamics problem with a perturbation in the boundary conditions and we show the good performances of the reduction techniques presented in the paper. The results obtained with the numerical reduction algorithm are compared with the one obtained by a standard finite element method. The gains obtained in term of CPU time are of three orders of magnitude.
Transport coefficient computation based on input/output reduced order models
Hurst, Joshua L.
The guiding purpose of this thesis is to address the optimal material design problem when the material description is a molecular dynamics model. The end goal is to obtain a simplified and fast model that captures the property of interest such that it can be used in controller design and optimization. The approach is to examine model reduction analysis and methods to capture a specific property of interest, in this case viscosity, or more generally complex modulus or complex viscosity. This property and other transport coefficients are defined by a input/output relationship and this motivates model reduction techniques that are tailored to preserve input/output behavior. In particular Singular Value Decomposition (SVD) based methods are investigated. First simulation methods are identified that are amenable to systems theory analysis. For viscosity, these models are of the Gosling and Lees-Edwards type. They are high order nonlinear Ordinary Differential Equations (ODEs) that employ Periodic Boundary Conditions. Properties can be calculated from the state trajectories of these ODEs. In this research local linear approximations are rigorously derived and special attention is given to potentials that are evaluated with Periodic Boundary Conditions (PBC). For the Gosling description LTI models are developed from state trajectories but are found to have limited success in capturing the system property, even though it is shown that full order LTI models can be well approximated by reduced order LTI models. For the Lees-Edwards SLLOD type model nonlinear ODEs will be approximated by a Linear Time Varying (LTV) model about some nominal trajectory and both balanced truncation and Proper Orthogonal Decomposition (POD) will be used to assess the plausibility of reduced order models to this system description. An immediate application of the derived LTV models is Quasilinearization or Waveform Relaxation. Quasilinearization is a Newton's method applied to the ODE operator
Accurate Medium-Term Wind Power Forecasting in a Censored Classification Framework
DEFF Research Database (Denmark)
Dahl, Christian M.; Croonenbroeck, Carsten
2014-01-01
We provide a wind power forecasting methodology that exploits many of the actual data's statistical features, in particular both-sided censoring. While other tools ignore many of the important “stylized facts” or provide forecasts for short-term horizons only, our approach focuses on medium......-term forecasts, which are especially necessary for practitioners in the forward electricity markets of many power trading places; for example, NASDAQ OMX Commodities (formerly Nord Pool OMX Commodities) in northern Europe. We show that our model produces turbine-specific forecasts that are significantly more...... accurate in comparison to established benchmark models and present an application that illustrates the financial impact of more accurate forecasts obtained using our methodology....
An optimal control model for reducing and trading of carbon emissions
Guo, Huaying; Liang, Jin
2016-03-01
A stochastic optimal control model of reducing and trading for carbon emissions is established in this paper. With considerations of reducing the carbon emission growth and the price of the allowances in the market, an optimal policy is searched to have the minimum total costs to achieve the agreement of emission reduction targets. The model turns to a two-dimension HJB equation problem. By the methods of reducing dimension and Cole-Hopf transformation, a semi-closed form solution of the corresponding HJB problem under some assumptions is obtained. For more general cases, the numerical calculations, analysis and comparisons are presented.
AN OVERVIEW OF REDUCED ORDER MODELING TECHNIQUES FOR SAFETY APPLICATIONS
Energy Technology Data Exchange (ETDEWEB)
Mandelli, D.; Alfonsi, A.; Talbot, P.; Wang, C.; Maljovec, D.; Smith, C.; Rabiti, C.; Cogliati, J.
2016-10-01
The RISMC project is developing new advanced simulation-based tools to perform Computational Risk Analysis (CRA) for the existing fleet of U.S. nuclear power plants (NPPs). These tools numerically model not only the thermal-hydraulic behavior of the reactors primary and secondary systems, but also external event temporal evolution and component/system ageing. Thus, this is not only a multi-physics problem being addressed, but also a multi-scale problem (both spatial, µm-mm-m, and temporal, seconds-hours-years). As part of the RISMC CRA approach, a large amount of computationally-expensive simulation runs may be required. An important aspect is that even though computational power is growing, the overall computational cost of a RISMC analysis using brute-force methods may be not viable for certain cases. A solution that is being evaluated to assist the computational issue is the use of reduced order modeling techniques. During the FY2015, we investigated and applied reduced order modeling techniques to decrease the RISMC analysis computational cost by decreasing the number of simulation runs; for this analysis improvement we used surrogate models instead of the actual simulation codes. This article focuses on the use of reduced order modeling techniques that can be applied to RISMC analyses in order to generate, analyze, and visualize data. In particular, we focus on surrogate models that approximate the simulation results but in a much faster time (microseconds instead of hours/days).
A Reduced-Order Model of Transport Phenomena for Power Plant Simulation
Energy Technology Data Exchange (ETDEWEB)
Paul Cizmas; Brian Richardson; Thomas Brenner; Raymond Fontenot
2009-09-30
A reduced-order model based on proper orthogonal decomposition (POD) has been developed to simulate transient two- and three-dimensional isothermal and non-isothermal flows in a fluidized bed. Reduced-order models of void fraction, gas and solids temperatures, granular energy, and z-direction gas and solids velocity have been added to the previous version of the code. These algorithms are presented and their implementation is discussed. Verification studies are presented for each algorithm. A number of methods to accelerate the computations performed by the reduced-order model are presented. The errors associated with each acceleration method are computed and discussed. Using a combination of acceleration methods, a two-dimensional isothermal simulation using the reduced-order model is shown to be 114 times faster than using the full-order model. In the pursue of achieving the objectives of the project and completing the tasks planned for this program, several unplanned and unforeseen results, methods and studies have been generated. These additional accomplishments are also presented and they include: (1) a study of the effect of snapshot sampling time on the computation of the POD basis functions, (2) an investigation of different strategies for generating the autocorrelation matrix used to find the POD basis functions, (3) the development and implementation of a bubble detection and tracking algorithm based on mathematical morphology, (4) a method for augmenting the proper orthogonal decomposition to better capture flows with discontinuities, such as bubbles, and (5) a mixed reduced-order/full-order model, called point-mode proper orthogonal decomposition, designed to avoid unphysical due to approximation errors. The limitations of the proper orthogonal decomposition method in simulating transient flows with moving discontinuities, such as bubbling flows, are discussed and several methods are proposed to adapt the method for future use.
Directory of Open Access Journals (Sweden)
Andreas Tuerk
2017-05-01
Full Text Available Accuracy of transcript quantification with RNA-Seq is negatively affected by positional fragment bias. This article introduces Mix2 (rd. "mixquare", a transcript quantification method which uses a mixture of probability distributions to model and thereby neutralize the effects of positional fragment bias. The parameters of Mix2 are trained by Expectation Maximization resulting in simultaneous transcript abundance and bias estimates. We compare Mix2 to Cufflinks, RSEM, eXpress and PennSeq; state-of-the-art quantification methods implementing some form of bias correction. On four synthetic biases we show that the accuracy of Mix2 overall exceeds the accuracy of the other methods and that its bias estimates converge to the correct solution. We further evaluate Mix2 on real RNA-Seq data from the Microarray and Sequencing Quality Control (MAQC, SEQC Consortia. On MAQC data, Mix2 achieves improved correlation to qPCR measurements with a relative increase in R2 between 4% and 50%. Mix2 also yields repeatable concentration estimates across technical replicates with a relative increase in R2 between 8% and 47% and reduced standard deviation across the full concentration range. We further observe more accurate detection of differential expression with a relative increase in true positives between 74% and 378% for 5% false positives. In addition, Mix2 reveals 5 dominant biases in MAQC data deviating from the common assumption of a uniform fragment distribution. On SEQC data, Mix2 yields higher consistency between measured and predicted concentration ratios. A relative error of 20% or less is obtained for 51% of transcripts by Mix2, 40% of transcripts by Cufflinks and RSEM and 30% by eXpress. Titration order consistency is correct for 47% of transcripts for Mix2, 41% for Cufflinks and RSEM and 34% for eXpress. We, further, observe improved repeatability across laboratory sites with a relative increase in R2 between 8% and 44% and reduced standard deviation.
Fast and accurate three-dimensional point spread function computation for fluorescence microscopy.
Li, Jizhou; Xue, Feng; Blu, Thierry
2017-06-01
The point spread function (PSF) plays a fundamental role in fluorescence microscopy. A realistic and accurately calculated PSF model can significantly improve the performance in 3D deconvolution microscopy and also the localization accuracy in single-molecule microscopy. In this work, we propose a fast and accurate approximation of the Gibson-Lanni model, which has been shown to represent the PSF suitably under a variety of imaging conditions. We express the Kirchhoff's integral in this model as a linear combination of rescaled Bessel functions, thus providing an integral-free way for the calculation. The explicit approximation error in terms of parameters is given numerically. Experiments demonstrate that the proposed approach results in a significantly smaller computational time compared with current state-of-the-art techniques to achieve the same accuracy. This approach can also be extended to other microscopy PSF models.
Development of a Fast and Accurate PCRTM Radiative Transfer Model in the Solar Spectral Region
Liu, Xu; Yang, Qiguang; Li, Hui; Jin, Zhonghai; Wu, Wan; Kizer, Susan; Zhou, Daniel K.; Yang, Ping
2016-01-01
A fast and accurate principal component-based radiative transfer model in the solar spectral region (PCRTMSOLAR) has been developed. The algorithm is capable of simulating reflected solar spectra in both clear sky and cloudy atmospheric conditions. Multiple scattering of the solar beam by the multilayer clouds and aerosols are calculated using a discrete ordinate radiative transfer scheme. The PCRTM-SOLAR model can be trained to simulate top-of-atmosphere radiance or reflectance spectra with spectral resolution ranging from 1 cm(exp -1) resolution to a few nanometers. Broadband radiances or reflectance can also be calculated if desired. The current version of the PCRTM-SOLAR covers a spectral range from 300 to 2500 nm. The model is valid for solar zenith angles ranging from 0 to 80 deg, the instrument view zenith angles ranging from 0 to 70 deg, and the relative azimuthal angles ranging from 0 to 360 deg. Depending on the number of spectral channels, the speed of the current version of PCRTM-SOLAR is a few hundred to over one thousand times faster than the medium speed correlated-k option MODTRAN5. The absolute RMS error in channel radiance is smaller than 10(exp -3) mW/cm)exp 2)/sr/cm(exp -1) and the relative error is typically less than 0.2%.
Identification of the reduced order models of a BWR reactor
International Nuclear Information System (INIS)
Hernandez S, A.
2004-01-01
The present work has as objective to analyze the relative stability of a BWR type reactor. It is analyzed that so adaptive it turns out to identify the parameters of a model of reduced order so that this it reproduces a condition of given uncertainty. This will take of a real fact happened in the La Salle plant under certain operation conditions of power and flow of coolant. The parametric identification is carried out by means of an algorithm of recursive least square and an Output Error model (Output Error), measuring the output power of the reactor when the instability is present, and considering that it is produced by a change in the reactivity of the system in the same way that a sign of type step. Also it is carried out an analytic comparison of the relative stability, analyzing two types of answers: the original answer of the uncertainty of the reactor vs. the obtained response identifying the parameters of the model of reduced order, reaching the conclusion that it is very viable to adapt a model of reduced order to study the stability of a reactor, under the only condition to consider that the dynamics of the reactivity is of step type. (Author)
Modeling and Optimization of Direct Chill Casting to Reduce Ingot Cracking
Energy Technology Data Exchange (ETDEWEB)
Das, Subodh K.
2006-01-09
reheating-cooling method (RCM), was developed and validated for measuring mechanical properties in the nonequilibrium mushy zones of alloys. The new method captures the brittle nature of aluminum alloys at temperatures close to the nonequilibrium solidus temperature, while specimens tested using the reheating method exhibit significant ductility. The RCM has been used for determining the mechanical properties of alloys at nonequilibrium mushy zone temperatures. Accurate data obtained during this project show that the metal becomes more brittle at high temperatures and high strain rates. (4) The elevated-temperature mechanical properties of the alloy were determined. Constitutive models relating the stress and strain relationship at elevated temperatures were also developed. The experimental data fit the model well. (5) An integrated 3D DC casting model has been used to simulate heat transfer, fluid flow, solidification, and thermally induced stress-strain during casting. A temperature-dependent HTC between the cooling water and the ingot surface, cooling water flow rate, and air gap were coupled in this model. An elasto-viscoplastic model based on high-temperature mechanical testing was used to calculate the stress during casting. The 3D integrated model can be used for the prediction of temperature, fluid flow, stress, and strain distribution in DC cast ingots. (6) The cracking propensity of DC cast ingots can be predicted using the 3D integrated model as well as thermodynamic models. Thus, an ingot cracking index based on the ratio of local stress to local alloy strength was established. Simulation results indicate that cracking propensity increases with increasing casting speed. The composition of the ingots also has a major effect on cracking formation. It was found that copper and zinc increase the cracking propensity of DC cast ingots. The goal of this Aluminum Industry of the Future (IOF) project was to assist the aluminum industry in reducing the incidence of stress
Seeing and Being Seen: Predictors of Accurate Perceptions about Classmates’ Relationships
Neal, Jennifer Watling; Neal, Zachary P.; Cappella, Elise
2015-01-01
This study examines predictors of observer accuracy (i.e. seeing) and target accuracy (i.e. being seen) in perceptions of classmates’ relationships in a predominantly African American sample of 420 second through fourth graders (ages 7 – 11). Girls, children in higher grades, and children in smaller classrooms were more accurate observers. Targets (i.e. pairs of children) were more accurately observed when they occurred in smaller classrooms of higher grades and involved same-sex, high-popularity, and similar-popularity children. Moreover, relationships between pairs of girls were more accurately observed than relationships between pairs of boys. As a set, these findings suggest the importance of both observer and target characteristics for children’s accurate perceptions of classroom relationships. Moreover, the substantial variation in observer accuracy and target accuracy has methodological implications for both peer-reported assessments of classroom relationships and the use of stochastic actor-based models to understand peer selection and socialization processes. PMID:26347582
Speelman, Eveline N.; Sewall, Jacob O.; Noone, David; Huber, Matthew; von der Heydt, Anna; Damsté, Jaap Sinninghe; Reichart, Gert-Jan
2010-09-01
Proxy-based climate reconstructions suggest the existence of a strongly reduced equator-to-pole temperature gradient during the Azolla interval in the Early/Middle Eocene, compared to modern. Changes in the hydrological cycle, as a consequence of a reduced temperature gradient, are expected to be reflected in the isotopic composition of precipitation (δD, δ 18O). The interpretation of water isotopic records to quantitatively reconstruct past precipitation patterns is, however, hampered by a lack of detailed information on changes in their spatial and temporal distribution. Using the isotope-enabled version of the National Center for Atmospheric Research (NCAR) atmospheric general circulation model, Community Atmosphere Model v.3 (isoCAM3), relationships between water isotopes and past climates can be simulated. Here we examine the influence of an imposed reduced meridional sea surface temperature gradient on the spatial distribution of precipitation and its isotopic composition in an Early/Middle Eocene setting. As a result of the applied forcings, the Eocene simulation predicts the occurrence of less depleted high latitude precipitation, with δD values ranging only between 0 and -140‰ (compared to Present-day 0 to -300‰). Comparison with Early/Middle Eocene-age isotopic proxy data shows that the simulation accurately captures the main features of the spatial distribution of the isotopic composition of Early/Middle Eocene precipitation over land in conjunction with the aspects of the modeled Early/Middle Eocene climate. Hence, the included stable isotope module quantitatively supports the existence of a reduced meridional temperature gradient during this interval.
Predictive models reduce talent development costs in female gymnastics.
Pion, Johan; Hohmann, Andreas; Liu, Tianbiao; Lenoir, Matthieu; Segers, Veerle
2017-04-01
This retrospective study focuses on the comparison of different predictive models based on the results of a talent identification test battery for female gymnasts. We studied to what extent these models have the potential to optimise selection procedures, and at the same time reduce talent development costs in female artistic gymnastics. The dropout rate of 243 female elite gymnasts was investigated, 5 years past talent selection, using linear (discriminant analysis) and non-linear predictive models (Kohonen feature maps and multilayer perceptron). The coaches classified 51.9% of the participants correct. Discriminant analysis improved the correct classification to 71.6% while the non-linear technique of Kohonen feature maps reached 73.7% correctness. Application of the multilayer perceptron even classified 79.8% of the gymnasts correctly. The combination of different predictive models for talent selection can avoid deselection of high-potential female gymnasts. The selection procedure based upon the different statistical analyses results in decrease of 33.3% of cost because the pool of selected athletes can be reduced to 92 instead of 138 gymnasts (as selected by the coaches). Reduction of the costs allows the limited resources to be fully invested in the high-potential athletes.
The economic value of accurate wind power forecasting to utilities
Energy Technology Data Exchange (ETDEWEB)
Watson, S J [Rutherford Appleton Lab., Oxfordshire (United Kingdom); Giebel, G; Joensen, A [Risoe National Lab., Dept. of Wind Energy and Atmospheric Physics, Roskilde (Denmark)
1999-03-01
With increasing penetrations of wind power, the need for accurate forecasting is becoming ever more important. Wind power is by its very nature intermittent. For utility schedulers this presents its own problems particularly when the penetration of wind power capacity in a grid reaches a significant level (>20%). However, using accurate forecasts of wind power at wind farm sites, schedulers are able to plan the operation of conventional power capacity to accommodate the fluctuating demands of consumers and wind farm output. The results of a study to assess the value of forecasting at several potential wind farm sites in the UK and in the US state of Iowa using the Reading University/Rutherford Appleton Laboratory National Grid Model (NGM) are presented. The results are assessed for different types of wind power forecasting, namely: persistence, optimised numerical weather prediction or perfect forecasting. In particular, it will shown how the NGM has been used to assess the value of numerical weather prediction forecasts from the Danish Meteorological Institute model, HIRLAM, and the US Nested Grid Model, which have been `site tailored` by the use of the linearized flow model WA{sup s}P and by various Model output Statistics (MOS) and autoregressive techniques. (au)
Reduced order dynamic model for polysaccharides molecule attached to an atomic force microscope
International Nuclear Information System (INIS)
Tang Deman; Li Aiqin; Attar, Peter; Dowell, Earl H.
2004-01-01
A dynamic analysis and numerical simulation has been conducted of a polysaccharides molecular structure (a ten (10) single-α-D-glucose molecule chain) connected to a moving atomic force microscope (AFM). Sinusoidal base excitation of the AFM cantilevered beam is considered. First a linearized perturbation model is constructed for the complex polysaccharides molecular structure. Then reduced order (dynamic) models based upon a proper orthogonal decomposition (POD) technique are constructed using global modes for both the linearized perturbation model and for the full nonlinear model. The agreement between the original and reduced order models (ROM/POD) is very good even when only a few global modes are included in the ROM for either the linear case or for the nonlinear case. The computational advantage of the reduced order model is clear from the results presented
A reduced model for ion temperature gradient turbulent transport in helical plasmas
International Nuclear Information System (INIS)
Nunami, M.; Watanabe, T.-H.; Sugama, H.
2013-07-01
A novel reduced model for ion temperature gradient (ITG) turbulent transport in helical plasmas is presented. The model enables one to predict nonlinear gyrokinetic simulation results from linear gyrokinetic analyses. It is shown from nonlinear gyrokinetic simulations of the ITG turbulence in helical plasmas that the transport coefficient can be expressed as a function of the turbulent fluctuation level and the averaged zonal flow amplitude. Then, the reduced model for the turbulent ion heat diffusivity is derived by representing the nonlinear turbulent fluctuations and zonal flow amplitude in terms of the linear growth rate of the ITG instability and the linear response of the zonal flow potentials. It is confirmed that the reduced transport model results are in good agreement with those from nonlinear gyrokinetic simulations for high ion temperature plasmas in the Large Helical Device. (author)
Reduced-Order Computational Model for Low-Frequency Dynamics of Automobiles
Directory of Open Access Journals (Sweden)
A. Arnoux
2013-01-01
Full Text Available A reduced-order model is constructed to predict, for the low-frequency range, the dynamical responses in the stiff parts of an automobile constituted of stiff and flexible parts. The vehicle has then many elastic modes in this range due to the presence of many flexible parts and equipment. A nonusual reduced-order model is introduced. The family of the elastic modes is not used and is replaced by an adapted vector basis of the admissible space of global displacements. Such a construction requires a decomposition of the domain of the structure in subdomains in order to control the spatial wave length of the global displacements. The fast marching method is used to carry out the subdomain decomposition. A probabilistic model of uncertainties is introduced. The parameters controlling the level of uncertainties are estimated solving a statistical inverse problem. The methodology is validated with a large computational model of an automobile.
Accurate thickness measurement of graphene
International Nuclear Information System (INIS)
Shearer, Cameron J; Slattery, Ashley D; Stapleton, Andrew J; Shapter, Joseph G; Gibson, Christopher T
2016-01-01
Graphene has emerged as a material with a vast variety of applications. The electronic, optical and mechanical properties of graphene are strongly influenced by the number of layers present in a sample. As a result, the dimensional characterization of graphene films is crucial, especially with the continued development of new synthesis methods and applications. A number of techniques exist to determine the thickness of graphene films including optical contrast, Raman scattering and scanning probe microscopy techniques. Atomic force microscopy (AFM), in particular, is used extensively since it provides three-dimensional images that enable the measurement of the lateral dimensions of graphene films as well as the thickness, and by extension the number of layers present. However, in the literature AFM has proven to be inaccurate with a wide range of measured values for single layer graphene thickness reported (between 0.4 and 1.7 nm). This discrepancy has been attributed to tip-surface interactions, image feedback settings and surface chemistry. In this work, we use standard and carbon nanotube modified AFM probes and a relatively new AFM imaging mode known as PeakForce tapping mode to establish a protocol that will allow users to accurately determine the thickness of graphene films. In particular, the error in measuring the first layer is reduced from 0.1–1.3 nm to 0.1–0.3 nm. Furthermore, in the process we establish that the graphene-substrate adsorbate layer and imaging force, in particular the pressure the tip exerts on the surface, are crucial components in the accurate measurement of graphene using AFM. These findings can be applied to other 2D materials. (paper)
International Nuclear Information System (INIS)
ZareNezhad, Bahman; Aminian, Ali
2011-01-01
This paper presents a new approach based on using an artificial neural network (ANN) model for predicting the acid dew points of the combustion gases in process and power plants. The most important acidic combustion gases namely, SO 3 , SO 2 , NO 2 , HCl and HBr are considered in this investigation. Proposed Network is trained using the Levenberg-Marquardt back propagation algorithm and the hyperbolic tangent sigmoid activation function is applied to calculate the output values of the neurons of the hidden layer. According to the network's training, validation and testing results, a three layer neural network with nine neurons in the hidden layer is selected as the best architecture for accurate prediction of the acidic combustion gases dew points over wide ranges of acid and moisture concentrations. The proposed neural network model can have significant application in predicting the condensation temperatures of different acid gases to mitigate the corrosion problems in stacks, pollution control devices and energy recovery systems.
MODELING CONTROLLED ASYNCHRONOUS ELECTRIC DRIVES WITH MATCHING REDUCERS AND TRANSFORMERS
Directory of Open Access Journals (Sweden)
V. S. Petrushin
2015-04-01
Full Text Available Purpose. Working out of mathematical models of the speed-controlled induction electric drives ensuring joint consideration of transformers, motors and loadings, and also matching reducers and transformers, both in static, and in dynamic regimes for the analysis of their operating characteristics. Methodology. At mathematical modelling are considered functional, mass, dimensional and cost indexes of reducers and transformers that allows observing engineering and economic aspects of speed-controlled induction electric drives. The mathematical models used for examination of the transitive electromagnetic and electromechanical processes, are grounded on systems of nonlinear differential equations with nonlinear coefficients (parameters of equivalent circuits of motors, varying in each operating point, including owing to appearances of saturation of magnetic system and current displacement in a winding of a rotor of an induction motor. For the purpose of raise of level of adequacy of models a magnetic circuit iron, additional and mechanical losses are considered. Results. Modelling of the several speed-controlled induction electric drives, different by components, but working on a loading equal on character, magnitude and a demanded control range is executed. At use of characteristic families including mechanical, at various parameters of regulating on which performances of the load mechanism are superimposed, the adjusting characteristics representing dependences of a modification of electrical, energy and thermal magnitudes from an angular speed of motors are gained. Originality. The offered complex models of speed-controlled induction electric drives with matching reducers and transformers, give the chance to realize well-founded sampling of components of drives. They also can be used as the design models by working out of speed-controlled induction motors. Practical value. Operating characteristics of various speed-controlled induction electric
Sensitivity study of reduced models of the activated sludge process ...
African Journals Online (AJOL)
The problem of derivation and calculation of sensitivity functions for all parameters of the mass balance reduced model of the COST benchmark activated sludge plant is formulated and solved. The sensitivity functions, equations and augmented sensitivity state space models are derived for the cases of ASM1 and UCT ...
Fast and accurate inductance and coupling calculation for a multi-layer Nb process
International Nuclear Information System (INIS)
Fourie, Coenrad J; Takahashi, Akitomo; Yoshikawa, Nobuyuki
2015-01-01
Currently, fabrication processes for superconductive integrated circuits are moving to multiple wiring and shielding layers, some of which are placed below the main ground plane (GP) and device layers. The Advanced Industrial Science and Technology advanced process (ADP2) was the first such multi-layer Nb process with planarized passive transmission line and GP layers below the junction layer, and is at the time of writing still the most developed. This process allows complex circuit designs, and accurate inductance extraction helps to push the boundaries of the layouts possible. We show that the position of ground connections between ground layers influences the inductance of structures for which these GPs act as return path, and that this needs to be accounted for in modelling. However, due to the number of wiring layers and GPs, full layout modelling of large cells causes long calculation times. In this paper we discuss methods with which to reduce model size, and calibrate InductEx calculations using these methods against measured results. We show that model reduction followed by calibration results in fast calculation times while good accuracy is maintained. We also show that InductEx correctly handles coupling between conductors in a multi-layer layout, and how to model layouts to gauge unwanted coupling between power lines and single flux quantum electronics. (paper)
The FLUKA code: An accurate simulation tool for particle therapy
Battistoni, Giuseppe; Böhlen, Till T; Cerutti, Francesco; Chin, Mary Pik Wai; Dos Santos Augusto, Ricardo M; Ferrari, Alfredo; Garcia Ortega, Pablo; Kozlowska, Wioletta S; Magro, Giuseppe; Mairani, Andrea; Parodi, Katia; Sala, Paola R; Schoofs, Philippe; Tessonnier, Thomas; Vlachoudis, Vasilis
2016-01-01
Monte Carlo (MC) codes are increasingly spreading in the hadrontherapy community due to their detailed description of radiation transport and interaction with matter. The suitability of a MC code for application to hadrontherapy demands accurate and reliable physical models capable of handling all components of the expected radiation field. This becomes extremely important for correctly performing not only physical but also biologically-based dose calculations, especially in cases where ions heavier than protons are involved. In addition, accurate prediction of emerging secondary radiation is of utmost importance in innovative areas of research aiming at in-vivo treatment verification. This contribution will address the recent developments of the FLUKA MC code and its practical applications in this field. Refinements of the FLUKA nuclear models in the therapeutic energy interval lead to an improved description of the mixed radiation field as shown in the presented benchmarks against experimental data with bot...
Directory of Open Access Journals (Sweden)
Niklas Berliner
Full Text Available Advances in sequencing have led to a rapid accumulation of mutations, some of which are associated with diseases. However, to draw mechanistic conclusions, a biochemical understanding of these mutations is necessary. For coding mutations, accurate prediction of significant changes in either the stability of proteins or their affinity to their binding partners is required. Traditional methods have used semi-empirical force fields, while newer methods employ machine learning of sequence and structural features. Here, we show how combining both of these approaches leads to a marked boost in accuracy. We introduce ELASPIC, a novel ensemble machine learning approach that is able to predict stability effects upon mutation in both, domain cores and domain-domain interfaces. We combine semi-empirical energy terms, sequence conservation, and a wide variety of molecular details with a Stochastic Gradient Boosting of Decision Trees (SGB-DT algorithm. The accuracy of our predictions surpasses existing methods by a considerable margin, achieving correlation coefficients of 0.77 for stability, and 0.75 for affinity predictions. Notably, we integrated homology modeling to enable proteome-wide prediction and show that accurate prediction on modeled structures is possible. Lastly, ELASPIC showed significant differences between various types of disease-associated mutations, as well as between disease and common neutral mutations. Unlike pure sequence-based prediction methods that try to predict phenotypic effects of mutations, our predictions unravel the molecular details governing the protein instability, and help us better understand the molecular causes of diseases.
Testing of a novel pin array guide for accurate three-dimensional glenoid component positioning.
Lewis, Gregory S; Stevens, Nicole M; Armstrong, April D
2015-12-01
A substantial challenge in total shoulder replacement is accurate positioning and alignment of the glenoid component. This challenge arises from limited intraoperative exposure and complex arthritic-driven deformity. We describe a novel pin array guide and method for patient-specific guiding of the glenoid central drill hole. We also experimentally tested the hypothesis that this method would reduce errors in version and inclination compared with 2 traditional methods. Polymer models of glenoids were created from computed tomography scans from 9 arthritic patients. Each 3-dimensional (3D) printed scapula was shrouded to simulate the operative situation. Three different methods for central drill alignment were tested, all with the target orientation of 5° retroversion and 0° inclination: no assistance, assistance by preoperative 3D imaging, and assistance by the pin array guide. Version and inclination errors of the drill line were compared. Version errors using the pin array guide (3° ± 2°) were significantly lower than version errors associated with no assistance (9° ± 7°) and preoperative 3D imaging (8° ± 6°). Inclination errors were also significantly lower using the pin array guide compared with no assistance. The new pin array guide substantially reduced errors in orientation of the central drill line. The guide method is patient specific but does not require rapid prototyping and instead uses adjustments to an array of pins based on automated software calculations. This method may ultimately provide a cost-effective solution enabling surgeons to obtain accurate orientation of the glenoid. Copyright © 2015 Journal of Shoulder and Elbow Surgery Board of Trustees. Published by Elsevier Inc. All rights reserved.
An updated prediction model of the global risk of cardiovascular disease in HIV-positive persons
DEFF Research Database (Denmark)
Friis-Møller, Nina; Ryom, Lene; Smith, Colette
2016-01-01
,663 HIV-positive persons from 20 countries in Europe and Australia, who were free of CVD at entry into the Data-collection on Adverse Effects of Anti-HIV Drugs (D:A:D) study. Cox regression models (full and reduced) were developed that predict the risk of a global CVD endpoint. The predictive performance...... significantly predicted risk more accurately than the recalibrated Framingham model (Harrell's c-statistic of 0.791, 0.783 and 0.766 for the D:A:D full, D:A:D reduced, and Framingham models respectively; p models also more accurately predicted five-year CVD-risk for key prognostic subgroups...... to quantify risk and to guide preventive care....
Advanced Models and Controls for Prediction and Extension of Battery Lifetime (Presentation)
Energy Technology Data Exchange (ETDEWEB)
Smith, K.; Wood, E.; Santhanagopalan, S.; Kim, G.; Pesaran, A.
2014-02-01
Predictive models of capacity and power fade must consider a multiplicity of degradation modes experienced by Li-ion batteries in the automotive environment. Lacking accurate models and tests, lifetime uncertainty must presently be absorbed by overdesign and excess warranty costs. To reduce these costs and extend life, degradation models are under development that predict lifetime more accurately and with less test data. The lifetime models provide engineering feedback for cell, pack and system designs and are being incorporated into real-time control strategies.
Mehra, Tarun; Koljonen, Virve; Seifert, Burkhardt; Volbracht, Jörk; Giovanoli, Pietro; Plock, Jan; Moos, Rudolf Maria
2015-01-01
Reimbursement systems have difficulties depicting the actual cost of burn treatment, leaving care providers with a significant financial burden. Our aim was to establish a simple and accurate reimbursement model compatible with prospective payment systems. A total of 370 966 electronic medical records of patients discharged in 2012 to 2013 from Swiss university hospitals were reviewed. A total of 828 cases of burns including 109 cases of severe burns were retained. Costs, revenues and earnings for severe and nonsevere burns were analysed and a linear regression model predicting total inpatient treatment costs was established. The median total costs per case for severe burns was tenfold higher than for nonsevere burns (179 949 CHF [167 353 EUR] vs 11 312 CHF [10 520 EUR], interquartile ranges 96 782-328 618 CHF vs 4 874-27 783 CHF, p <0.001). The median of earnings per case for nonsevere burns was 588 CHF (547 EUR) (interquartile range -6 720 - 5 354 CHF) whereas severe burns incurred a large financial loss to care providers, with median earnings of -33 178 CHF (30 856 EUR) (interquartile range -95 533 - 23 662 CHF). Differences were highly significant (p <0.001). Our linear regression model predicting total costs per case with length of stay (LOS) as independent variable had an adjusted R2 of 0.67 (p <0.001 for LOS). Severe burns are systematically underfunded within the Swiss reimbursement system. Flat-rate DRG-based refunds poorly reflect the actual treatment costs. In conclusion, we suggest a reimbursement model based on a per diem rate for treatment of severe burns.
Reduced Order Model Implementation in the Risk-Informed Safety Margin Characterization Toolkit
International Nuclear Information System (INIS)
Mandelli, Diego; Smith, Curtis L.; Alfonsi, Andrea; Rabiti, Cristian; Cogliati, Joshua J.; Talbot, Paul W.; Rinaldi, Ivan; Maljovec, Dan; Wang, Bei; Pascucci, Valerio; Zhao, Haihua
2015-01-01
The RISMC project aims to develop new advanced simulation-based tools to perform Probabilistic Risk Analysis (PRA) for the existing fleet of U.S. nuclear power plants (NPPs). These tools numerically model not only the thermo-hydraulic behavior of the reactor primary and secondary systems but also external events temporal evolution and components/system ageing. Thus, this is not only a multi-physics problem but also a multi-scale problem (both spatial, µm-mm-m, and temporal, ms-s-minutes-years). As part of the RISMC PRA approach, a large amount of computationally expensive simulation runs are required. An important aspect is that even though computational power is regularly growing, the overall computational cost of a RISMC analysis may be not viable for certain cases. A solution that is being evaluated is the use of reduce order modeling techniques. During the FY2015, we investigated and applied reduced order modeling techniques to decrease the RICM analysis computational cost by decreasing the number of simulations runs to perform and employ surrogate models instead of the actual simulation codes. This report focuses on the use of reduced order modeling techniques that can be applied to any RISMC analysis to generate, analyze and visualize data. In particular, we focus on surrogate models that approximate the simulation results but in a much faster time (µs instead of hours/days). We apply reduced order and surrogate modeling techniques to several RISMC types of analyses using RAVEN and RELAP-7 and show the advantages that can be gained.
Reduced Order Model Implementation in the Risk-Informed Safety Margin Characterization Toolkit
Energy Technology Data Exchange (ETDEWEB)
Mandelli, Diego [Idaho National Lab. (INL), Idaho Falls, ID (United States); Smith, Curtis L. [Idaho National Lab. (INL), Idaho Falls, ID (United States); Alfonsi, Andrea [Idaho National Lab. (INL), Idaho Falls, ID (United States); Rabiti, Cristian [Idaho National Lab. (INL), Idaho Falls, ID (United States); Cogliati, Joshua J. [Idaho National Lab. (INL), Idaho Falls, ID (United States); Talbot, Paul W. [Idaho National Lab. (INL), Idaho Falls, ID (United States); Rinaldi, Ivan [Idaho National Lab. (INL), Idaho Falls, ID (United States); Maljovec, Dan [Idaho National Lab. (INL), Idaho Falls, ID (United States); Wang, Bei [Idaho National Lab. (INL), Idaho Falls, ID (United States); Pascucci, Valerio [Idaho National Lab. (INL), Idaho Falls, ID (United States); Zhao, Haihua [Idaho National Lab. (INL), Idaho Falls, ID (United States)
2015-09-01
The RISMC project aims to develop new advanced simulation-based tools to perform Probabilistic Risk Analysis (PRA) for the existing fleet of U.S. nuclear power plants (NPPs). These tools numerically model not only the thermo-hydraulic behavior of the reactor primary and secondary systems but also external events temporal evolution and components/system ageing. Thus, this is not only a multi-physics problem but also a multi-scale problem (both spatial, µm-mm-m, and temporal, ms-s-minutes-years). As part of the RISMC PRA approach, a large amount of computationally expensive simulation runs are required. An important aspect is that even though computational power is regularly growing, the overall computational cost of a RISMC analysis may be not viable for certain cases. A solution that is being evaluated is the use of reduce order modeling techniques. During the FY2015, we investigated and applied reduced order modeling techniques to decrease the RICM analysis computational cost by decreasing the number of simulations runs to perform and employ surrogate models instead of the actual simulation codes. This report focuses on the use of reduced order modeling techniques that can be applied to any RISMC analysis to generate, analyze and visualize data. In particular, we focus on surrogate models that approximate the simulation results but in a much faster time (µs instead of hours/days). We apply reduced order and surrogate modeling techniques to several RISMC types of analyses using RAVEN and RELAP-7 and show the advantages that can be gained.
Thermosyphon Flooding in Reduced Gravity Environments Test Results
Gibson, Marc A.; Jaworske, Donald A.; Sanzi, Jim; Ljubanovic, Damir
2013-01-01
The condenser flooding phenomenon associated with gravity aided two-phase thermosyphons was studied using parabolic flights to obtain the desired reduced gravity environment (RGE). The experiment was designed and built to test a total of twelve titanium water thermosyphons in multiple gravity environments with the goal of developing a model that would accurately explain the correlation between gravitational forces and the maximum axial heat transfer limit associated with condenser flooding. Results from laboratory testing and parabolic flights are included in this report as part I of a two part series. The data analysis and correlations are included in a follow on paper.
Floden, Evan W; Tommaso, Paolo D; Chatzou, Maria; Magis, Cedrik; Notredame, Cedric; Chang, Jia-Ming
2016-07-08
The PSI/TM-Coffee web server performs multiple sequence alignment (MSA) of proteins by combining homology extension with a consistency based alignment approach. Homology extension is performed with Position Specific Iterative (PSI) BLAST searches against a choice of redundant and non-redundant databases. The main novelty of this server is to allow databases of reduced complexity to rapidly perform homology extension. This server also gives the possibility to use transmembrane proteins (TMPs) reference databases to allow even faster homology extension on this important category of proteins. Aside from an MSA, the server also outputs topological prediction of TMPs using the HMMTOP algorithm. Previous benchmarking of the method has shown this approach outperforms the most accurate alignment methods such as MSAProbs, Kalign, PROMALS, MAFFT, ProbCons and PRALINE™. The web server is available at http://tcoffee.crg.cat/tmcoffee. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.
Reduced-Order Structure-Preserving Model for Parallel-Connected Three-Phase Grid-Tied Inverters
Energy Technology Data Exchange (ETDEWEB)
Johnson, Brian B [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Purba, Victor [University of Minnesota; Jafarpour, Saber [University of California Santa-Barbara; Bullo, Francesco [University of California Santa-Barbara; Dhople, Sairaj V. [University of Minnesota
2017-08-21
Next-generation power networks will contain large numbers of grid-connected inverters satisfying a significant fraction of system load. Since each inverter model has a relatively large number of dynamic states, it is impractical to analyze complex system models where the full dynamics of each inverter are retained. To address this challenge, we derive a reduced-order structure-preserving model for parallel-connected grid-tied three-phase inverters. Here, each inverter in the system is assumed to have a full-bridge topology, LCL filter at the point of common coupling, and the control architecture for each inverter includes a current controller, a power controller, and a phase-locked loop for grid synchronization. We outline a structure-preserving reduced-order inverter model with lumped parameters for the setting where the parallel inverters are each designed such that the filter components and controller gains scale linearly with the power rating. By structure preserving, we mean that the reduced-order three-phase inverter model is also composed of an LCL filter, a power controller, current controller, and PLL. We show that the system of parallel inverters can be modeled exactly as one aggregated inverter unit and this equivalent model has the same number of dynamical states as any individual inverter in the system. Numerical simulations validate the reduced-order model.
Strassmann, Kuno M.; Joos, Fortunat
2018-05-01
The Bern Simple Climate Model (BernSCM) is a free open-source re-implementation of a reduced-form carbon cycle-climate model which has been used widely in previous scientific work and IPCC assessments. BernSCM represents the carbon cycle and climate system with a small set of equations for the heat and carbon budget, the parametrization of major nonlinearities, and the substitution of complex component systems with impulse response functions (IRFs). The IRF approach allows cost-efficient yet accurate substitution of detailed parent models of climate system components with near-linear behavior. Illustrative simulations of scenarios from previous multimodel studies show that BernSCM is broadly representative of the range of the climate-carbon cycle response simulated by more complex and detailed models. Model code (in Fortran) was written from scratch with transparency and extensibility in mind, and is provided open source. BernSCM makes scientifically sound carbon cycle-climate modeling available for many applications. Supporting up to decadal time steps with high accuracy, it is suitable for studies with high computational load and for coupling with integrated assessment models (IAMs), for example. Further applications include climate risk assessment in a business, public, or educational context and the estimation of CO2 and climate benefits of emission mitigation options.
A Reduced Wind Power Grid Model for Research and Education
Energy Technology Data Exchange (ETDEWEB)
Akhmatov, V. [Energinet.dk, Fjordvejen 1-11, DK-7000 Fredericia (Denmark); Lund, T.; Hansen, A.D.; Sorensen, P.E. [Risoe National Laboratory, DK-4000 Roskilde (Denmark); Nielsen, A.H. [Centre for Electric Technology, Technical University of Denmark, DK-2800 Kgs. Lyngby (Denmark)
2006-07-01
A reduced grid model of a transmission system with a number of central power plants, consumption centers, local wind turbines and a large offshore wind farm is developed and implemented in the simulation tool PowerFactory (DIgSILENT). The reduced grid model is given by Energinet.dk, Transmission System Operator of Denmark (TSO) for Natural Gas and Electricity, to the Danish Universities and the Risoe National Laboratory. Its intended usage is education and studying of interaction between electricity-producing wind turbines and a realistic transmission system. Focus in these studies is on voltage stability issues and on the ride-through capability of different wind turbine concepts, equipped with advanced controllers, developed by the Risoe National Laboratory.
ACCURATE UNIVERSAL MODELS FOR THE MASS ACCRETION HISTORIES AND CONCENTRATIONS OF DARK MATTER HALOS
International Nuclear Information System (INIS)
Zhao, D. H.; Jing, Y. P.; Mo, H. J.; Boerner, G.
2009-01-01
A large amount of observations have constrained cosmological parameters and the initial density fluctuation spectrum to a very high accuracy. However, cosmological parameters change with time and the power index of the power spectrum dramatically varies with mass scale in the so-called concordance ΛCDM cosmology. Thus, any successful model for its structural evolution should work well simultaneously for various cosmological models and different power spectra. We use a large set of high-resolution N-body simulations of a variety of structure formation models (scale-free, standard CDM, open CDM, and ΛCDM) to study the mass accretion histories, the mass and redshift dependence of concentrations, and the concentration evolution histories of dark matter halos. We find that there is significant disagreement between the much-used empirical models in the literature and our simulations. Based on our simulation results, we find that the mass accretion rate of a halo is tightly correlated with a simple function of its mass, the redshift, parameters of the cosmology, and of the initial density fluctuation spectrum, which correctly disentangles the effects of all these factors and halo environments. We also find that the concentration of a halo is strongly correlated with the universe age when its progenitor on the mass accretion history first reaches 4% of its current mass. According to these correlations, we develop new empirical models for both the mass accretion histories and the concentration evolution histories of dark matter halos, and the latter can also be used to predict the mass and redshift dependence of halo concentrations. These models are accurate and universal: the same set of model parameters works well for different cosmological models and for halos of different masses at different redshifts, and in the ΛCDM case the model predictions match the simulation results very well even though halo mass is traced to about 0.0005 times the final mass, when
Escitalopram reduces increased hippocampal cytogenesis in a genetic rat depression model
DEFF Research Database (Denmark)
Petersén, Asa; Wörtwein, Gitta; Gruber, Susanne H M
2008-01-01
to stressors, but, so far, not in models of depression. Here we report that the number of BrdU positive cells in hippocampus was (1) significantly higher in a rat model of depression, the Flinders Sensitive Line (FSL) compared to control FRL, (2) increased in both FSL and FRL following maternal separation, (3......) reduced by escitalopram treatment in maternally separated animals to the level found in non-separated animals. These results argue against the prevailing hypothesis that adult cytogenesis is reduced in depression and that the common mechanism underlying antidepressant treatments is to increase adult...
Rybynok, V. O.; Kyriacou, P. A.
2007-10-01
Diabetes is one of the biggest health challenges of the 21st century. The obesity epidemic, sedentary lifestyles and an ageing population mean prevalence of the condition is currently doubling every generation. Diabetes is associated with serious chronic ill health, disability and premature mortality. Long-term complications including heart disease, stroke, blindness, kidney disease and amputations, make the greatest contribution to the costs of diabetes care. Many of these long-term effects could be avoided with earlier, more effective monitoring and treatment. Currently, blood glucose can only be monitored through the use of invasive techniques. To date there is no widely accepted and readily available non-invasive monitoring technique to measure blood glucose despite the many attempts. This paper challenges one of the most difficult non-invasive monitoring techniques, that of blood glucose, and proposes a new novel approach that will enable the accurate, and calibration free estimation of glucose concentration in blood. This approach is based on spectroscopic techniques and a new adaptive modelling scheme. The theoretical implementation and the effectiveness of the adaptive modelling scheme for this application has been described and a detailed mathematical evaluation has been employed to prove that such a scheme has the capability of extracting accurately the concentration of glucose from a complex biological media.
Energy Technology Data Exchange (ETDEWEB)
Rybynok, V O; Kyriacou, P A [City University, London (United Kingdom)
2007-10-15
Diabetes is one of the biggest health challenges of the 21st century. The obesity epidemic, sedentary lifestyles and an ageing population mean prevalence of the condition is currently doubling every generation. Diabetes is associated with serious chronic ill health, disability and premature mortality. Long-term complications including heart disease, stroke, blindness, kidney disease and amputations, make the greatest contribution to the costs of diabetes care. Many of these long-term effects could be avoided with earlier, more effective monitoring and treatment. Currently, blood glucose can only be monitored through the use of invasive techniques. To date there is no widely accepted and readily available non-invasive monitoring technique to measure blood glucose despite the many attempts. This paper challenges one of the most difficult non-invasive monitoring techniques, that of blood glucose, and proposes a new novel approach that will enable the accurate, and calibration free estimation of glucose concentration in blood. This approach is based on spectroscopic techniques and a new adaptive modelling scheme. The theoretical implementation and the effectiveness of the adaptive modelling scheme for this application has been described and a detailed mathematical evaluation has been employed to prove that such a scheme has the capability of extracting accurately the concentration of glucose from a complex biological media.
International Nuclear Information System (INIS)
Rybynok, V O; Kyriacou, P A
2007-01-01
Diabetes is one of the biggest health challenges of the 21st century. The obesity epidemic, sedentary lifestyles and an ageing population mean prevalence of the condition is currently doubling every generation. Diabetes is associated with serious chronic ill health, disability and premature mortality. Long-term complications including heart disease, stroke, blindness, kidney disease and amputations, make the greatest contribution to the costs of diabetes care. Many of these long-term effects could be avoided with earlier, more effective monitoring and treatment. Currently, blood glucose can only be monitored through the use of invasive techniques. To date there is no widely accepted and readily available non-invasive monitoring technique to measure blood glucose despite the many attempts. This paper challenges one of the most difficult non-invasive monitoring techniques, that of blood glucose, and proposes a new novel approach that will enable the accurate, and calibration free estimation of glucose concentration in blood. This approach is based on spectroscopic techniques and a new adaptive modelling scheme. The theoretical implementation and the effectiveness of the adaptive modelling scheme for this application has been described and a detailed mathematical evaluation has been employed to prove that such a scheme has the capability of extracting accurately the concentration of glucose from a complex biological media
Energy Technology Data Exchange (ETDEWEB)
Myint, P. C. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Hao, Y. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Firoozabadi, A. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
2015-03-27
Thermodynamic property calculations of mixtures containing carbon dioxide (CO_{2}) and water, including brines, are essential in theoretical models of many natural and industrial processes. The properties of greatest practical interest are density, solubility, and enthalpy. Many models for density and solubility calculations have been presented in the literature, but there exists only one study, by Spycher and Pruess, that has compared theoretical molar enthalpy predictions with experimental data [1]. In this report, we recommend two different models for enthalpy calculations: the CPA equation of state by Li and Firoozabadi [2], and the CO_{2} activity coefficient model by Duan and Sun [3]. We show that the CPA equation of state, which has been demonstrated to provide good agreement with density and solubility data, also accurately calculates molar enthalpies of pure CO_{2}, pure water, and both CO_{2}-rich and aqueous (H_{2}O-rich) mixtures of the two species. It is applicable to a wider range of conditions than the Spycher and Pruess model. In aqueous sodium chloride (NaCl) mixtures, we show that Duan and Sun’s model yields accurate results for the partial molar enthalpy of CO_{2}. It can be combined with another model for the brine enthalpy to calculate the molar enthalpy of H_{2}O-CO_{2}-NaCl mixtures. We conclude by explaining how the CPA equation of state may be modified to further improve agreement with experiments. This generalized CPA is the basis of our future work on this topic.
Toward accurate tooth segmentation from computed tomography images using a hybrid level set model
Energy Technology Data Exchange (ETDEWEB)
Gan, Yangzhou; Zhao, Qunfei [Department of Automation, Shanghai Jiao Tong University, and Key Laboratory of System Control and Information Processing, Ministry of Education of China, Shanghai 200240 (China); Xia, Zeyang, E-mail: zy.xia@siat.ac.cn, E-mail: jing.xiong@siat.ac.cn; Hu, Ying [Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, and The Chinese University of Hong Kong, Shenzhen 518055 (China); Xiong, Jing, E-mail: zy.xia@siat.ac.cn, E-mail: jing.xiong@siat.ac.cn [Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 510855 (China); Zhang, Jianwei [TAMS, Department of Informatics, University of Hamburg, Hamburg 22527 (Germany)
2015-01-15
Purpose: A three-dimensional (3D) model of the teeth provides important information for orthodontic diagnosis and treatment planning. Tooth segmentation is an essential step in generating the 3D digital model from computed tomography (CT) images. The aim of this study is to develop an accurate and efficient tooth segmentation method from CT images. Methods: The 3D dental CT volumetric images are segmented slice by slice in a two-dimensional (2D) transverse plane. The 2D segmentation is composed of a manual initialization step and an automatic slice by slice segmentation step. In the manual initialization step, the user manually picks a starting slice and selects a seed point for each tooth in this slice. In the automatic slice segmentation step, a developed hybrid level set model is applied to segment tooth contours from each slice. Tooth contour propagation strategy is employed to initialize the level set function automatically. Cone beam CT (CBCT) images of two subjects were used to tune the parameters. Images of 16 additional subjects were used to validate the performance of the method. Volume overlap metrics and surface distance metrics were adopted to assess the segmentation accuracy quantitatively. The volume overlap metrics were volume difference (VD, mm{sup 3}) and Dice similarity coefficient (DSC, %). The surface distance metrics were average symmetric surface distance (ASSD, mm), RMS (root mean square) symmetric surface distance (RMSSSD, mm), and maximum symmetric surface distance (MSSD, mm). Computation time was recorded to assess the efficiency. The performance of the proposed method has been compared with two state-of-the-art methods. Results: For the tested CBCT images, the VD, DSC, ASSD, RMSSSD, and MSSD for the incisor were 38.16 ± 12.94 mm{sup 3}, 88.82 ± 2.14%, 0.29 ± 0.03 mm, 0.32 ± 0.08 mm, and 1.25 ± 0.58 mm, respectively; the VD, DSC, ASSD, RMSSSD, and MSSD for the canine were 49.12 ± 9.33 mm{sup 3}, 91.57 ± 0.82%, 0.27 ± 0.02 mm, 0
Toward accurate tooth segmentation from computed tomography images using a hybrid level set model
International Nuclear Information System (INIS)
Gan, Yangzhou; Zhao, Qunfei; Xia, Zeyang; Hu, Ying; Xiong, Jing; Zhang, Jianwei
2015-01-01
Purpose: A three-dimensional (3D) model of the teeth provides important information for orthodontic diagnosis and treatment planning. Tooth segmentation is an essential step in generating the 3D digital model from computed tomography (CT) images. The aim of this study is to develop an accurate and efficient tooth segmentation method from CT images. Methods: The 3D dental CT volumetric images are segmented slice by slice in a two-dimensional (2D) transverse plane. The 2D segmentation is composed of a manual initialization step and an automatic slice by slice segmentation step. In the manual initialization step, the user manually picks a starting slice and selects a seed point for each tooth in this slice. In the automatic slice segmentation step, a developed hybrid level set model is applied to segment tooth contours from each slice. Tooth contour propagation strategy is employed to initialize the level set function automatically. Cone beam CT (CBCT) images of two subjects were used to tune the parameters. Images of 16 additional subjects were used to validate the performance of the method. Volume overlap metrics and surface distance metrics were adopted to assess the segmentation accuracy quantitatively. The volume overlap metrics were volume difference (VD, mm 3 ) and Dice similarity coefficient (DSC, %). The surface distance metrics were average symmetric surface distance (ASSD, mm), RMS (root mean square) symmetric surface distance (RMSSSD, mm), and maximum symmetric surface distance (MSSD, mm). Computation time was recorded to assess the efficiency. The performance of the proposed method has been compared with two state-of-the-art methods. Results: For the tested CBCT images, the VD, DSC, ASSD, RMSSSD, and MSSD for the incisor were 38.16 ± 12.94 mm 3 , 88.82 ± 2.14%, 0.29 ± 0.03 mm, 0.32 ± 0.08 mm, and 1.25 ± 0.58 mm, respectively; the VD, DSC, ASSD, RMSSSD, and MSSD for the canine were 49.12 ± 9.33 mm 3 , 91.57 ± 0.82%, 0.27 ± 0.02 mm, 0.28 ± 0.03 mm
Modelling mitigation options to reduce diffuse nitrogen water pollution from agriculture.
Bouraoui, Fayçal; Grizzetti, Bruna
2014-01-15
Agriculture is responsible for large scale water quality degradation and is estimated to contribute around 55% of the nitrogen entering the European Seas. The key policy instrument for protecting inland, transitional and coastal water resources is the Water Framework Directive (WFD). Reducing nutrient losses from agriculture is crucial to the successful implementation of the WFD. There are several mitigation measures that can be implemented to reduce nitrogen losses from agricultural areas to surface and ground waters. For the selection of appropriate measures, models are useful for quantifying the expected impacts and the associated costs. In this article we review some of the models used in Europe to assess the effectiveness of nitrogen mitigation measures, ranging from fertilizer management to the construction of riparian areas and wetlands. We highlight how the complexity of models is correlated with the type of scenarios that can be tested, with conceptual models mostly used to evaluate the impact of reduced fertilizer application, and the physically-based models used to evaluate the timing and location of mitigation options and the response times. We underline the importance of considering the lag time between the implementation of measures and effects on water quality. Models can be effective tools for targeting mitigation measures (identifying critical areas and timing), for evaluating their cost effectiveness, for taking into consideration pollution swapping and considering potential trade-offs in contrasting environmental objectives. Models are also useful for involving stakeholders during the development of catchments mitigation plans, increasing their acceptability. © 2013.
CREATING DIGITAL ELEVATION MODEL USING A MOBILE DEVICE
Directory of Open Access Journals (Sweden)
A. İ. Durmaz
2017-11-01
Full Text Available DEM (Digital Elevation Models is the best way to interpret topography on the ground. In recent years, lidar technology allows to create more accurate elevation models. However, the problem is this technology is not common all over the world. Also if Lidar data are not provided by government agencies freely, people have to pay lots of money to reach these point clouds. In this article, we will discuss how we can create digital elevation model from less accurate mobile devices’ GPS data. Moreover, we will evaluate these data on the same mobile device which we collected data to reduce cost of this modeling.
Metamodeling Techniques to Aid in the Aggregation Process of Large Hierarchical Simulation Models
National Research Council Canada - National Science Library
Rodriguez, June F
2008-01-01
.... More specifically, investigating how to accurately aggregate hierarchical lower-level (higher resolution) models into the next higher-level in order to reduce the complexity of the overall simulation model...
Galbraith, Eric D.; Dunne, John P.; Gnanadesikan, Anand; Slater, Richard D.; Sarmiento, Jorge L.; Dufour, Carolina O.; de Souza, Gregory F.; Bianchi, Daniele; Claret, Mariona; Rodgers, Keith B.; Marvasti, Seyedehsafoura Sedigh
2015-12-01
Earth System Models increasingly include ocean biogeochemistry models in order to predict changes in ocean carbon storage, hypoxia, and biological productivity under climate change. However, state-of-the-art ocean biogeochemical models include many advected tracers, that significantly increase the computational resources required, forcing a trade-off with spatial resolution. Here, we compare a state-of-the art model with 30 prognostic tracers (TOPAZ) with two reduced-tracer models, one with 6 tracers (BLING), and the other with 3 tracers (miniBLING). The reduced-tracer models employ parameterized, implicit biological functions, which nonetheless capture many of the most important processes resolved by TOPAZ. All three are embedded in the same coupled climate model. Despite the large difference in tracer number, the absence of tracers for living organic matter is shown to have a minimal impact on the transport of nutrient elements, and the three models produce similar mean annual preindustrial distributions of macronutrients, oxygen, and carbon. Significant differences do exist among the models, in particular the seasonal cycle of biomass and export production, but it does not appear that these are necessary consequences of the reduced tracer number. With increasing CO2, changes in dissolved oxygen and anthropogenic carbon uptake are very similar across the different models. Thus, while the reduced-tracer models do not explicitly resolve the diversity and internal dynamics of marine ecosystems, we demonstrate that such models are applicable to a broad suite of major biogeochemical concerns, including anthropogenic change. These results are very promising for the further development and application of reduced-tracer biogeochemical models that incorporate "sub-ecosystem-scale" parameterizations.
Towards accurate emergency response behavior
International Nuclear Information System (INIS)
Sargent, T.O.
1981-01-01
Nuclear reactor operator emergency response behavior has persisted as a training problem through lack of information. The industry needs an accurate definition of operator behavior in adverse stress conditions, and training methods which will produce the desired behavior. Newly assembled information from fifty years of research into human behavior in both high and low stress provides a more accurate definition of appropriate operator response, and supports training methods which will produce the needed control room behavior. The research indicates that operator response in emergencies is divided into two modes, conditioned behavior and knowledge based behavior. Methods which assure accurate conditioned behavior, and provide for the recovery of knowledge based behavior, are described in detail
Kainmueller, Dagmar
2014-01-01
? Segmentation of anatomical structures in medical image data is an essential task in clinical practice. Dagmar Kainmueller introduces methods for accurate fully automatic segmentation of anatomical structures in 3D medical image data. The author's core methodological contribution is a novel deformation model that overcomes limitations of state-of-the-art Deformable Surface approaches, hence allowing for accurate segmentation of tip- and ridge-shaped features of anatomical structures. As for practical contributions, she proposes application-specific segmentation pipelines for a range of anatom
Accurate phenotyping: Reconciling approaches through Bayesian model averaging.
Directory of Open Access Journals (Sweden)
Carla Chia-Ming Chen
Full Text Available Genetic research into complex diseases is frequently hindered by a lack of clear biomarkers for phenotype ascertainment. Phenotypes for such diseases are often identified on the basis of clinically defined criteria; however such criteria may not be suitable for understanding the genetic composition of the diseases. Various statistical approaches have been proposed for phenotype definition; however our previous studies have shown that differences in phenotypes estimated using different approaches have substantial impact on subsequent analyses. Instead of obtaining results based upon a single model, we propose a new method, using Bayesian model averaging to overcome problems associated with phenotype definition. Although Bayesian model averaging has been used in other fields of research, this is the first study that uses Bayesian model averaging to reconcile phenotypes obtained using multiple models. We illustrate the new method by applying it to simulated genetic and phenotypic data for Kofendred personality disorder-an imaginary disease with several sub-types. Two separate statistical methods were used to identify clusters of individuals with distinct phenotypes: latent class analysis and grade of membership. Bayesian model averaging was then used to combine the two clusterings for the purpose of subsequent linkage analyses. We found that causative genetic loci for the disease produced higher LOD scores using model averaging than under either individual model separately. We attribute this improvement to consolidation of the cores of phenotype clusters identified using each individual method.
International Nuclear Information System (INIS)
SivaRanjan, Uppala; Ramachandran, Ramesh
2014-01-01
A quantum-mechanical model integrating the concepts of reduced density matrix and effective Hamiltonians is proposed to explain the multi-spin effects observed in rotational resonance (R 2 ) nuclear magnetic resonance (NMR) experiments. Employing this approach, the spin system of interest is described in a reduced subspace inclusive of its coupling to the surroundings. Through suitable model systems, the utility of our theory is demonstrated and verified with simulations emerging from both analytic and numerical methods. The analytic results presented in this article provide an accurate description/interpretation of R 2 experimental results and could serve as a test-bed for distinguishing coherent/incoherent effects in solid-state NMR
Energy Technology Data Exchange (ETDEWEB)
SivaRanjan, Uppala; Ramachandran, Ramesh, E-mail: rramesh@iisermohali.ac.in [Department of Chemical Sciences, Indian Institute of Science Education and Research (IISER) Mohali, Sector 81, Manauli, P.O. Box-140306, Mohali, Punjab (India)
2014-02-07
A quantum-mechanical model integrating the concepts of reduced density matrix and effective Hamiltonians is proposed to explain the multi-spin effects observed in rotational resonance (R{sup 2}) nuclear magnetic resonance (NMR) experiments. Employing this approach, the spin system of interest is described in a reduced subspace inclusive of its coupling to the surroundings. Through suitable model systems, the utility of our theory is demonstrated and verified with simulations emerging from both analytic and numerical methods. The analytic results presented in this article provide an accurate description/interpretation of R{sup 2} experimental results and could serve as a test-bed for distinguishing coherent/incoherent effects in solid-state NMR.
A model for reducing health care employee turnover.
Nowak, Paul; Holmes, Gary; Murrow, Jim
2010-01-01
Explaining the rationale as to why employees leave their jobs has led to many different strategies to retain employees. The model presented here seeks to explain why employees choose to stay or to leave their place of employment. The information from the analysis will provide managers with well-tested tools to reduce turnover and to ascertain what employees value from their work environment in order to help the organization to retain those employees. The model identifies key factors that management can utilize to provide barriers to exit and retain professional employees in their health care units. Recommendations are provided that reward loyalty and build barriers to exit.
Reduced-Order Direct Numerical Simulation of Solute Transport in Porous Media
Mehmani, Yashar; Tchelepi, Hamdi
2017-11-01
Pore-scale models are an important tool for analyzing fluid dynamics in porous materials (e.g., rocks, soils, fuel cells). Current direct numerical simulation (DNS) techniques, while very accurate, are computationally prohibitive for sample sizes that are statistically representative of the porous structure. Reduced-order approaches such as pore-network models (PNM) aim to approximate the pore-space geometry and physics to remedy this problem. Predictions from current techniques, however, have not always been successful. This work focuses on single-phase transport of a passive solute under advection-dominated regimes and delineates the minimum set of approximations that consistently produce accurate PNM predictions. Novel network extraction (discretization) and particle simulation techniques are developed and compared to high-fidelity DNS simulations for a wide range of micromodel heterogeneities and a single sphere pack. Moreover, common modeling assumptions in the literature are analyzed and shown that they can lead to first-order errors under advection-dominated regimes. This work has implications for optimizing material design and operations in manufactured (electrodes) and natural (rocks) porous media pertaining to energy systems. This work was supported by the Stanford University Petroleum Research Institute for Reservoir Simulation (SUPRI-B).
[Accurate 3D free-form registration between fan-beam CT and cone-beam CT].
Liang, Yueqiang; Xu, Hongbing; Li, Baosheng; Li, Hongsheng; Yang, Fujun
2012-06-01
Because the X-ray scatters, the CT numbers in cone-beam CT cannot exactly correspond to the electron densities. This, therefore, results in registration error when the intensity-based registration algorithm is used to register planning fan-beam CT and cone-beam CT. In order to reduce the registration error, we have developed an accurate gradient-based registration algorithm. The gradient-based deformable registration problem is described as a minimization of energy functional. Through the calculus of variations and Gauss-Seidel finite difference method, we derived the iterative formula of the deformable registration. The algorithm was implemented by GPU through OpenCL framework, with which the registration time was greatly reduced. Our experimental results showed that the proposed gradient-based registration algorithm could register more accurately the clinical cone-beam CT and fan-beam CT images compared with the intensity-based algorithm. The GPU-accelerated algorithm meets the real-time requirement in the online adaptive radiotherapy.
Accurately Detecting Students' Lies regarding Relational Aggression by Correctional Instructions
Dickhauser, Oliver; Reinhard, Marc-Andre; Marksteiner, Tamara
2012-01-01
This study investigates the effect of correctional instructions when detecting lies about relational aggression. Based on models from the field of social psychology, we predict that correctional instruction will lead to a less pronounced lie bias and to more accurate lie detection. Seventy-five teachers received videotapes of students' true denial…
a Semi-Empirical Topographic Correction Model for Multi-Source Satellite Images
Xiao, Sa; Tian, Xinpeng; Liu, Qiang; Wen, Jianguang; Ma, Yushuang; Song, Zhenwei
2018-04-01
Topographic correction of surface reflectance in rugged terrain areas is the prerequisite for the quantitative application of remote sensing in mountainous areas. Physics-based radiative transfer model can be applied to correct the topographic effect and accurately retrieve the reflectance of the slope surface from high quality satellite image such as Landsat8 OLI. However, as more and more images data available from various of sensors, some times we can not get the accurate sensor calibration parameters and atmosphere conditions which are needed in the physics-based topographic correction model. This paper proposed a semi-empirical atmosphere and topographic corrction model for muti-source satellite images without accurate calibration parameters.Based on this model we can get the topographic corrected surface reflectance from DN data, and we tested and verified this model with image data from Chinese satellite HJ and GF. The result shows that the correlation factor was reduced almost 85 % for near infrared bands and the classification overall accuracy of classification increased 14 % after correction for HJ. The reflectance difference of slope face the sun and face away the sun have reduced after correction.
Accurately tracking single-cell movement trajectories in microfluidic cell sorting devices.
Jeong, Jenny; Frohberg, Nicholas J; Zhou, Enlu; Sulchek, Todd; Qiu, Peng
2018-01-01
Microfluidics are routinely used to study cellular properties, including the efficient quantification of single-cell biomechanics and label-free cell sorting based on the biomechanical properties, such as elasticity, viscosity, stiffness, and adhesion. Both quantification and sorting applications require optimal design of the microfluidic devices and mathematical modeling of the interactions between cells, fluid, and the channel of the device. As a first step toward building such a mathematical model, we collected video recordings of cells moving through a ridged microfluidic channel designed to compress and redirect cells according to cell biomechanics. We developed an efficient algorithm that automatically and accurately tracked the cell trajectories in the recordings. We tested the algorithm on recordings of cells with different stiffness, and showed the correlation between cell stiffness and the tracked trajectories. Moreover, the tracking algorithm successfully picked up subtle differences of cell motion when passing through consecutive ridges. The algorithm for accurately tracking cell trajectories paves the way for future efforts of modeling the flow, forces, and dynamics of cell properties in microfluidics applications.
Accurately tracking single-cell movement trajectories in microfluidic cell sorting devices.
Directory of Open Access Journals (Sweden)
Jenny Jeong
Full Text Available Microfluidics are routinely used to study cellular properties, including the efficient quantification of single-cell biomechanics and label-free cell sorting based on the biomechanical properties, such as elasticity, viscosity, stiffness, and adhesion. Both quantification and sorting applications require optimal design of the microfluidic devices and mathematical modeling of the interactions between cells, fluid, and the channel of the device. As a first step toward building such a mathematical model, we collected video recordings of cells moving through a ridged microfluidic channel designed to compress and redirect cells according to cell biomechanics. We developed an efficient algorithm that automatically and accurately tracked the cell trajectories in the recordings. We tested the algorithm on recordings of cells with different stiffness, and showed the correlation between cell stiffness and the tracked trajectories. Moreover, the tracking algorithm successfully picked up subtle differences of cell motion when passing through consecutive ridges. The algorithm for accurately tracking cell trajectories paves the way for future efforts of modeling the flow, forces, and dynamics of cell properties in microfluidics applications.
Hybrid Reduced Order Modeling Algorithms for Reactor Physics Calculations
Bang, Youngsuk
Reduced order modeling (ROM) has been recognized as an indispensable approach when the engineering analysis requires many executions of high fidelity simulation codes. Examples of such engineering analyses in nuclear reactor core calculations, representing the focus of this dissertation, include the functionalization of the homogenized few-group cross-sections in terms of the various core conditions, e.g. burn-up, fuel enrichment, temperature, etc. This is done via assembly calculations which are executed many times to generate the required functionalization for use in the downstream core calculations. Other examples are sensitivity analysis used to determine important core attribute variations due to input parameter variations, and uncertainty quantification employed to estimate core attribute uncertainties originating from input parameter uncertainties. ROM constructs a surrogate model with quantifiable accuracy which can replace the original code for subsequent engineering analysis calculations. This is achieved by reducing the effective dimensionality of the input parameter, the state variable, or the output response spaces, by projection onto the so-called active subspaces. Confining the variations to the active subspace allows one to construct an ROM model of reduced complexity which can be solved more efficiently. This dissertation introduces a new algorithm to render reduction with the reduction errors bounded based on a user-defined error tolerance which represents the main challenge of existing ROM techniques. Bounding the error is the key to ensuring that the constructed ROM models are robust for all possible applications. Providing such error bounds represents one of the algorithmic contributions of this dissertation to the ROM state-of-the-art. Recognizing that ROM techniques have been developed to render reduction at different levels, e.g. the input parameter space, the state space, and the response space, this dissertation offers a set of novel
Spectrally accurate contour dynamics
International Nuclear Information System (INIS)
Van Buskirk, R.D.; Marcus, P.S.
1994-01-01
We present an exponentially accurate boundary integral method for calculation the equilibria and dynamics of piece-wise constant distributions of potential vorticity. The method represents contours of potential vorticity as a spectral sum and solves the Biot-Savart equation for the velocity by spectrally evaluating a desingularized contour integral. We use the technique in both an initial-value code and a newton continuation method. Our methods are tested by comparing the numerical solutions with known analytic results, and it is shown that for the same amount of computational work our spectral methods are more accurate than other contour dynamics methods currently in use
Srivastava, R. C.; Coen, J. L.
1992-01-01
The traditional explicit growth equation has been widely used to calculate the growth and evaporation of hydrometeors by the diffusion of water vapor. This paper reexamines the assumptions underlying the traditional equation and shows that large errors (10-30 percent in some cases) result if it is used carelessly. More accurate explicit equations are derived by approximating the saturation vapor-density difference as a quadratic rather than a linear function of the temperature difference between the particle and ambient air. These new equations, which reduce the error to less than a few percent, merit inclusion in a broad range of atmospheric models.
Gowda, Dhananjaya; Airaksinen, Manu; Alku, Paavo
2017-09-01
Recently, a quasi-closed phase (QCP) analysis of speech signals for accurate glottal inverse filtering was proposed. However, the QCP analysis which belongs to the family of temporally weighted linear prediction (WLP) methods uses the conventional forward type of sample prediction. This may not be the best choice especially in computing WLP models with a hard-limiting weighting function. A sample selective minimization of the prediction error in WLP reduces the effective number of samples available within a given window frame. To counter this problem, a modified quasi-closed phase forward-backward (QCP-FB) analysis is proposed, wherein each sample is predicted based on its past as well as future samples thereby utilizing the available number of samples more effectively. Formant detection and estimation experiments on synthetic vowels generated using a physical modeling approach as well as natural speech utterances show that the proposed QCP-FB method yields statistically significant improvements over the conventional linear prediction and QCP methods.
Reduced order methods for modeling and computational reduction
Rozza, Gianluigi
2014-01-01
This monograph addresses the state of the art of reduced order methods for modeling and computational reduction of complex parametrized systems, governed by ordinary and/or partial differential equations, with a special emphasis on real time computing techniques and applications in computational mechanics, bioengineering and computer graphics. Several topics are covered, including: design, optimization, and control theory in real-time with applications in engineering; data assimilation, geometry registration, and parameter estimation with special attention to real-time computing in biomedical engineering and computational physics; real-time visualization of physics-based simulations in computer science; the treatment of high-dimensional problems in state space, physical space, or parameter space; the interactions between different model reduction and dimensionality reduction approaches; the development of general error estimation frameworks which take into account both model and discretization effects. This...
Accurate determination of process variables in a solid-state fermentation system
Smits, J.P.; Rinzema, A.; Tramper, J.; Schlösser, E.E.; Knol, W.
1996-01-01
The solid-state fermentation (SSF) method described enabled accurate determination of variables related to biological activity. Growth, respiratory activity and production of carboxymethyl-cellulose-hydrolysing enzyme (CMC-ase) activity by Trichoderma reesei QM9414 on wheat bran was used as a model
Xiang, Hong-Jun; Zhang, Zhi-Wei; Shi, Zhi-Fei; Li, Hong
2018-04-01
A fully coupled modeling approach is developed for piezoelectric energy harvesters in this work based on the use of available robust finite element packages and efficient reducing order modeling techniques. At first, the harvester is modeled using finite element packages. The dynamic equilibrium equations of harvesters are rebuilt by extracting system matrices from the finite element model using built-in commands without any additional tools. A Krylov subspace-based scheme is then applied to obtain a reduced-order model for improving simulation efficiency but preserving the key features of harvesters. Co-simulation of the reduced-order model with nonlinear energy harvesting circuits is achieved in a system level. Several examples in both cases of harmonic response and transient response analysis are conducted to validate the present approach. The proposed approach allows to improve the simulation efficiency by several orders of magnitude. Moreover, the parameters used in the equivalent circuit model can be conveniently obtained by the proposed eigenvector-based model order reduction technique. More importantly, this work establishes a methodology for modeling of piezoelectric energy harvesters with any complicated mechanical geometries and nonlinear circuits. The input load may be more complex also. The method can be employed by harvester designers to optimal mechanical structures or by circuit designers to develop novel energy harvesting circuits.
2015-10-28
techniques such as regression analysis, correlation, and multicollinearity assessment to identify the change and error on the input to the model...between many of the independent or predictor variables, the issue of multicollinearity may arise [18]. VII. SUMMARY Accurate decisions concerning
Maiorano, Andrea; Martre, Pierre; Asseng, Senthold; Ewert, Frank; Mueller, Christoph; Roetter, Reimund P.; Ruane, Alex C.; Semenov, Mikhail A.; Wallach, Daniel; Wang, Enli
2016-01-01
To improve climate change impact estimates and to quantify their uncertainty, multi-model ensembles (MMEs) have been suggested. Model improvements can improve the accuracy of simulations and reduce the uncertainty of climate change impact assessments. Furthermore, they can reduce the number of models needed in a MME. Herein, 15 wheat growth models of a larger MME were improved through re-parameterization and/or incorporating or modifying heat stress effects on phenology, leaf growth and senescence, biomass growth, and grain number and size using detailed field experimental data from the USDA Hot Serial Cereal experiment (calibration data set). Simulation results from before and after model improvement were then evaluated with independent field experiments from a CIMMYT worldwide field trial network (evaluation data set). Model improvements decreased the variation (10th to 90th model ensemble percentile range) of grain yields simulated by the MME on average by 39% in the calibration data set and by 26% in the independent evaluation data set for crops grown in mean seasonal temperatures greater than 24 C. MME mean squared error in simulating grain yield decreased by 37%. A reduction in MME uncertainty range by 27% increased MME prediction skills by 47%. Results suggest that the mean level of variation observed in field experiments and used as a benchmark can be reached with half the number of models in the MME. Improving crop models is therefore important to increase the certainty of model-based impact assessments and allow more practical, i.e. smaller MMEs to be used effectively.
Second-order accurate volume-of-fluid algorithms for tracking material interfaces
International Nuclear Information System (INIS)
Pilliod, James Edward; Puckett, Elbridge Gerry
2004-01-01
We introduce two new volume-of-fluid interface reconstruction algorithms and compare the accuracy of these algorithms to four other widely used volume-of-fluid interface reconstruction algorithms. We find that when the interface is smooth (e.g., continuous with two continuous derivatives) the new methods are second-order accurate and the other algorithms are first-order accurate. We propose a design criteria for a volume-of-fluid interface reconstruction algorithm to be second-order accurate. Namely, that it reproduce lines in two space dimensions or planes in three space dimensions exactly. We also introduce a second-order, unsplit, volume-of-fluid advection algorithm that is based on a second-order, finite difference method for scalar conservation laws due to Bell, Dawson and Shubin. We test this advection algorithm by modeling several different interface shapes propagating in two simple incompressible flows and compare the results with the standard second-order, operator-split advection algorithm. Although both methods are second-order accurate when the interface is smooth, we find that the unsplit algorithm exhibits noticeably better resolution in regions where the interface has discontinuous derivatives, such as at corners
Accurate predictions for the LHC made easy
CERN. Geneva
2014-01-01
The data recorded by the LHC experiments is of a very high quality. To get the most out of the data, precise theory predictions, including uncertainty estimates, are needed to reduce as much as possible theoretical bias in the experimental analyses. Recently, significant progress has been made in computing Next-to-Leading Order (NLO) computations, including matching to the parton shower, that allow for these accurate, hadron-level predictions. I shall discuss one of these efforts, the MadGraph5_aMC@NLO program, that aims at the complete automation of predictions at the NLO accuracy within the SM as well as New Physics theories. I’ll illustrate some of the theoretical ideas behind this program, show some selected applications to LHC physics, as well as describe the future plans.
Structural and reduced-form modeling and forecasting with application to Armenia
Poghosyan, K.
2012-01-01
The thesis deals with structural and reduced-form modeling and forecasting of key macroeconomic variables (real growth of GDP, inflation, exchange rate, and policy interest rate). The central part of the thesis (Chapters 2-4) consists of three chapters. Chapter 2 considers the structural DSGE model
Numerical simulation of drag-reducing channel flow by using bead-spring chain model
International Nuclear Information System (INIS)
Fujimura, M.; Atsumi, T.; Mamori, H.; Iwamoto, K.; Murata, A.; Masuda, M.; Ando, H.
2017-01-01
Highlights: • Numerical simulations of drag-reduced turbulent flow by polymer additives were performed by using a discrete element model. • A decreasing pressure-strain correlation mainly contributes to drag reduction by polymer addition. • Energy transport by the polymer attenuates the turbulence. • The viscoelastic effects on the drag-reducing flow are intensified with increasing relaxation time of polymer. • The polymer energy transport is related to the orientation of the polymer. - Abstract: Numerical simulations of the drag-reducing turbulent channel flow caused by polymer addition are performed. A bead-spring chain model is employed as a model of polymer aggregation. The model consists of beads and springs to represent the polymer dynamics. Three drag-reduction cases are studied with different spring constants that correspond to the relaxation time of the polymer. The energy budget is mainly focused upon to discuss the drag-reduction mechanism. Our results show that a decreasing pressure-strain correlation mainly contributes to strengthening the anisotropy of the turbulence. Furthermore, energy transport by the polymer models attenuates the turbulence. These viscoelastic effects on the drag-reducing flow are intensified with decreasing spring constant. By visualizing the flow field, it is found that this polymer energy transport is related to the orientation of the polymer.
The Adaptive QSE-reduced Nuclear Reaction Network for Silicon Burning
International Nuclear Information System (INIS)
Parete-Koon, Suzanne; Hix, William Raphael; Thielemann, Friedrich-Karl W.
2008-01-01
The nuclei of the 'iron peak' are formed in massive stars shortly before core collapse and during their supernova outbursts as well as during thermonuclear supernovae. Complete and incomplete silicon burning during these events are responsible for the production of a wide range of nuclei with atomic mass numbers from 28 to 64. Because of the large number of nuclei involved, accurate modeling of silicon burning is computationally expensive. However, examination of the physics of silicon burning has revealed that the nuclear evolution is dominated by large groups of nuclei in mutual equilibrium. We present an improvement on our hybrid equilibrium-network scheme which takes advantage of this quasi-equilibrium in order to reduce the number of independent variables calculated. Because the size and membership of these groups vary as the temperature, density and electron faction change, achieving maximal efficiency requires dynamic adjustment of group number and membership. Toward this end, we are implementing a scheme beginning with 2 QSE groups at appropriately high temperature, then progressing through, 3 and 3* group stages (with successively more independent variables) as temperature declines. This combination allows accurate prediction of the nuclear abundance evolution, deleptonization and energy generation at a further reduced computational cost when compared to a conventional nuclear reaction network or our previous 3 fixed group QSE-reduced network. During silicon burning, the resultant QSE-reduced network is up to 20 times faster than the full network it replaces without significant loss of accuracy. These reductions in computational cost and the number of species evolved make QSE-reduced networks well suited for inclusion within hydrodynamic simulations, particularly in multi-dimensional applications
Dynamics and bistability in a reduced model of the lac operon
Yildirim, Necmettin; Santillán, Moisés; Horike, Daisuke; Mackey, Michael C.
2004-06-01
It is known that the lac operon regulatory pathway is capable of showing bistable behavior. This is an important complex feature, arising from the nonlinearity of the involved mechanisms, which is essential to understand the dynamic behavior of this molecular regulatory system. To find which of the mechanisms involved in the regulation of the lac operon is the origin of bistability, we take a previously published model which accounts for the dynamics of mRNA, lactose, allolactose, permease and β-galactosidase involvement and simplify it by ignoring permease dynamics (assuming a constant permease concentration). To test the behavior of the reduced model, three existing sets of data on β-galactosidase levels as a function of time are simulated and we obtain a reasonable agreement between the data and the model predictions. The steady states of the reduced model were numerically and analytically analyzed and it was shown that it may indeed display bistability, depending on the extracellular lactose concentration and growth rate.
Can we Use Low-Cost 360 Degree Cameras to Create Accurate 3d Models?
Barazzetti, L.; Previtali, M.; Roncoroni, F.
2018-05-01
360 degree cameras capture the whole scene around a photographer in a single shot. Cheap 360 cameras are a new paradigm in photogrammetry. The camera can be pointed to any direction, and the large field of view reduces the number of photographs. This paper aims to show that accurate metric reconstructions can be achieved with affordable sensors (less than 300 euro). The camera used in this work is the Xiaomi Mijia Mi Sphere 360, which has a cost of about 300 USD (January 2018). Experiments demonstrate that millimeter-level accuracy can be obtained during the image orientation and surface reconstruction steps, in which the solution from 360° images was compared to check points measured with a total station and laser scanning point clouds. The paper will summarize some practical rules for image acquisition as well as the importance of ground control points to remove possible deformations of the network during bundle adjustment, especially for long sequences with unfavorable geometry. The generation of orthophotos from images having a 360° field of view (that captures the entire scene around the camera) is discussed. Finally, the paper illustrates some case studies where the use of a 360° camera could be a better choice than a project based on central perspective cameras. Basically, 360° cameras become very useful in the survey of long and narrow spaces, as well as interior areas like small rooms.
On an efficient and accurate method to integrate restricted three-body orbits
Murison, Marc A.
1989-01-01
This work is a quantitative analysis of the advantages of the Bulirsch-Stoer (1966) method, demonstrating that this method is certainly worth considering when working with small N dynamical systems. The results, qualitatively suspected by many users, are quantitatively confirmed as follows: (1) the Bulirsch-Stoer extrapolation method is very fast and moderately accurate; (2) regularization of the equations of motion stabilizes the error behavior of the method and is, of course, essential during close approaches; and (3) when applicable, a manifold-correction algorithm reduces numerical errors to the limits of machine accuracy. In addition, for the specific case of the restricted three-body problem, even a small eccentricity for the orbit of the primaries drastically affects the accuracy of integrations, whether regularized or not; the circular restricted problem integrates much more accurately.
Persson, Bjorn M; Ainge, James A; O'Connor, Akira R
2016-07-01
Current animal models of episodic memory are usually based on demonstrating integrated memory for what happened, where it happened, and when an event took place. These models aim to capture the testable features of the definition of human episodic memory which stresses the temporal component of the memory as a unique piece of source information that allows us to disambiguate one memory from another. Recently though, it has been suggested that a more accurate model of human episodic memory would include contextual rather than temporal source information, as humans' memory for time is relatively poor. Here, two experiments were carried out investigating human memory for temporal and contextual source information, along with the underlying dual process retrieval processes, using an immersive virtual environment paired with a 'Remember-Know' memory task. Experiment 1 (n=28) showed that contextual information could only be retrieved accurately using recollection, while temporal information could be retrieved using either recollection or familiarity. Experiment 2 (n=24), which used a more difficult task, resulting in reduced item recognition rates and therefore less potential for contamination by ceiling effects, replicated the pattern of results from Experiment 1. Dual process theory predicts that it should only be possible to retrieve source context from an event using recollection, and our results are consistent with this prediction. That temporal information can be retrieved using familiarity alone suggests that it may be incorrect to view temporal context as analogous to other typically used source contexts. This latter finding supports the alternative proposal that time since presentation may simply be reflected in the strength of memory trace at retrieval - a measure ideally suited to trace strength interrogation using familiarity, as is typically conceptualised within the dual process framework. Copyright © 2016 Elsevier Inc. All rights reserved.
On the Nonlinear Structural Analysis of Wind Turbine Blades using Reduced Degree-of-Freedom Models
DEFF Research Database (Denmark)
Holm-Jørgensen, Kristian; Larsen, Jesper Winther; Nielsen, Søren R.K.
2008-01-01
, modelling geometrical and inertial nonlinear couplings in the fundamental flap and edge direction. The purpose of this article is to examine the applicability of such a reduced-degree-of-freedom model in predicting the nonlinear response and stability of a blade by comparison to a full model based...... on a nonlinear co-rotating FE formulation. By use of the reduced-degree-of-freedom model it is shown that under strong resonance excitation of the fundamental flap or edge modes, significant energy is transferred to higher modes due to parametric or nonlinear coupling terms, which influence the response...... of the small number of included modes. The qualitative erratic response and stability prediction of the reduced order models take place at frequencies slightly above normal operation. However, for normal operation of the wind turbine without resonance excitation 4 modes in the reduced-degree-of-freedom model...
How accurately can 21cm tomography constrain cosmology?
Mao, Yi; Tegmark, Max; McQuinn, Matthew; Zaldarriaga, Matias; Zahn, Oliver
2008-07-01
There is growing interest in using 3-dimensional neutral hydrogen mapping with the redshifted 21 cm line as a cosmological probe. However, its utility depends on many assumptions. To aid experimental planning and design, we quantify how the precision with which cosmological parameters can be measured depends on a broad range of assumptions, focusing on the 21 cm signal from 6noise, to uncertainties in the reionization history, and to the level of contamination from astrophysical foregrounds. We derive simple analytic estimates for how various assumptions affect an experiment’s sensitivity, and we find that the modeling of reionization is the most important, followed by the array layout. We present an accurate yet robust method for measuring cosmological parameters that exploits the fact that the ionization power spectra are rather smooth functions that can be accurately fit by 7 phenomenological parameters. We find that for future experiments, marginalizing over these nuisance parameters may provide constraints almost as tight on the cosmology as if 21 cm tomography measured the matter power spectrum directly. A future square kilometer array optimized for 21 cm tomography could improve the sensitivity to spatial curvature and neutrino masses by up to 2 orders of magnitude, to ΔΩk≈0.0002 and Δmν≈0.007eV, and give a 4σ detection of the spectral index running predicted by the simplest inflation models.
REDUCING PROCESS VARIABILITY BY USING DMAIC MODEL: A CASE STUDY IN BANGLADESH
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Ripon Kumar Chakrabortty
2013-03-01
Full Text Available Now-a-day's many leading manufacturing industry have started to practice Six Sigma and Lean manufacturing concepts to boost up their productivity as well as quality of products. In this paper, the Six Sigma approach has been used to reduce process variability of a food processing industry in Bangladesh. DMAIC (Define,Measure, Analyze, Improve, & Control model has been used to implement the Six Sigma Philosophy. Five phases of the model have been structured step by step respectively. Different tools of Total Quality Management, Statistical Quality Control and Lean Manufacturing concepts likely Quality function deployment, P Control chart, Fish-bone diagram, Analytical Hierarchy Process, Pareto analysis have been used in different phases of the DMAIC model. The process variability have been tried to reduce by identify the root cause of defects and reducing it. The ultimate goal of this study is to make the process lean and increase the level of sigma.
Accurate mass measurements on neutron-deficient krypton isotopes
Rodríguez, D.; Äystö, J.; Beck, D.; Blaum, K.; Bollen, G.; Herfurth, F.; Jokinen, A.; Kellerbauer, A.; Kluge, H.-J.; Kolhinen, V.S.; Oinonen, M.; Sauvan, E.; Schwarz, S.
2006-01-01
The masses of $^{72–78,80,82,86}$Kr were measured directly with the ISOLTRAP Penning trap mass spectrometer at ISOLDE/CERN. For all these nuclides, the measurements yielded mass uncertainties below 10 keV. The ISOLTRAP mass values for $^{72–75}$Kr being more precise than the previous results obtained by means of other techniques, and thus completely determine the new values in the Atomic-Mass Evaluation. Besides the interest of these masses for nuclear astrophysics, nuclear structure studies, and Standard Model tests, these results constitute a valuable and accurate input to improve mass models. In this paper, we present the mass measurements and discuss the mass evaluation for these Kr isotopes.
Accurate estimate of the relic density and the kinetic decoupling in nonthermal dark matter models
International Nuclear Information System (INIS)
Arcadi, Giorgio; Ullio, Piero
2011-01-01
Nonthermal dark matter generation is an appealing alternative to the standard paradigm of thermal WIMP dark matter. We reconsider nonthermal production mechanisms in a systematic way, and develop a numerical code for accurate computations of the dark matter relic density. We discuss, in particular, scenarios with long-lived massive states decaying into dark matter particles, appearing naturally in several beyond the standard model theories, such as supergravity and superstring frameworks. Since nonthermal production favors dark matter candidates with large pair annihilation rates, we analyze the possible connection with the anomalies detected in the lepton cosmic-ray flux by Pamela and Fermi. Concentrating on supersymmetric models, we consider the effect of these nonstandard cosmologies in selecting a preferred mass scale for the lightest supersymmetric particle as a dark matter candidate, and the consequent impact on the interpretation of new physics discovered or excluded at the LHC. Finally, we examine a rather predictive model, the G2-MSSM, investigating some of the standard assumptions usually implemented in the solution of the Boltzmann equation for the dark matter component, including coannihilations. We question the hypothesis that kinetic equilibrium holds along the whole phase of dark matter generation, and the validity of the factorization usually implemented to rewrite the system of a coupled Boltzmann equation for each coannihilating species as a single equation for the sum of all the number densities. As a byproduct we develop here a formalism to compute the kinetic decoupling temperature in case of coannihilating particles, which can also be applied to other particle physics frameworks, and also to standard thermal relics within a standard cosmology.
Data-assisted reduced-order modeling of extreme events in complex dynamical systems.
Wan, Zhong Yi; Vlachas, Pantelis; Koumoutsakos, Petros; Sapsis, Themistoklis
2018-01-01
The prediction of extreme events, from avalanches and droughts to tsunamis and epidemics, depends on the formulation and analysis of relevant, complex dynamical systems. Such dynamical systems are characterized by high intrinsic dimensionality with extreme events having the form of rare transitions that are several standard deviations away from the mean. Such systems are not amenable to classical order-reduction methods through projection of the governing equations due to the large intrinsic dimensionality of the underlying attractor as well as the complexity of the transient events. Alternatively, data-driven techniques aim to quantify the dynamics of specific, critical modes by utilizing data-streams and by expanding the dimensionality of the reduced-order model using delayed coordinates. In turn, these methods have major limitations in regions of the phase space with sparse data, which is the case for extreme events. In this work, we develop a novel hybrid framework that complements an imperfect reduced order model, with data-streams that are integrated though a recurrent neural network (RNN) architecture. The reduced order model has the form of projected equations into a low-dimensional subspace that still contains important dynamical information about the system and it is expanded by a long short-term memory (LSTM) regularization. The LSTM-RNN is trained by analyzing the mismatch between the imperfect model and the data-streams, projected to the reduced-order space. The data-driven model assists the imperfect model in regions where data is available, while for locations where data is sparse the imperfect model still provides a baseline for the prediction of the system state. We assess the developed framework on two challenging prototype systems exhibiting extreme events. We show that the blended approach has improved performance compared with methods that use either data streams or the imperfect model alone. Notably the improvement is more significant in
Data-assisted reduced-order modeling of extreme events in complex dynamical systems.
Directory of Open Access Journals (Sweden)
Zhong Yi Wan
Full Text Available The prediction of extreme events, from avalanches and droughts to tsunamis and epidemics, depends on the formulation and analysis of relevant, complex dynamical systems. Such dynamical systems are characterized by high intrinsic dimensionality with extreme events having the form of rare transitions that are several standard deviations away from the mean. Such systems are not amenable to classical order-reduction methods through projection of the governing equations due to the large intrinsic dimensionality of the underlying attractor as well as the complexity of the transient events. Alternatively, data-driven techniques aim to quantify the dynamics of specific, critical modes by utilizing data-streams and by expanding the dimensionality of the reduced-order model using delayed coordinates. In turn, these methods have major limitations in regions of the phase space with sparse data, which is the case for extreme events. In this work, we develop a novel hybrid framework that complements an imperfect reduced order model, with data-streams that are integrated though a recurrent neural network (RNN architecture. The reduced order model has the form of projected equations into a low-dimensional subspace that still contains important dynamical information about the system and it is expanded by a long short-term memory (LSTM regularization. The LSTM-RNN is trained by analyzing the mismatch between the imperfect model and the data-streams, projected to the reduced-order space. The data-driven model assists the imperfect model in regions where data is available, while for locations where data is sparse the imperfect model still provides a baseline for the prediction of the system state. We assess the developed framework on two challenging prototype systems exhibiting extreme events. We show that the blended approach has improved performance compared with methods that use either data streams or the imperfect model alone. Notably the improvement is more
Can Measured Synergy Excitations Accurately Construct Unmeasured Muscle Excitations?
Bianco, Nicholas A; Patten, Carolynn; Fregly, Benjamin J
2018-01-01
Accurate prediction of muscle and joint contact forces during human movement could improve treatment planning for disorders such as osteoarthritis, stroke, Parkinson's disease, and cerebral palsy. Recent studies suggest that muscle synergies, a low-dimensional representation of a large set of muscle electromyographic (EMG) signals (henceforth called "muscle excitations"), may reduce the redundancy of muscle excitation solutions predicted by optimization methods. This study explores the feasibility of using muscle synergy information extracted from eight muscle EMG signals (henceforth called "included" muscle excitations) to accurately construct muscle excitations from up to 16 additional EMG signals (henceforth called "excluded" muscle excitations). Using treadmill walking data collected at multiple speeds from two subjects (one healthy, one poststroke), we performed muscle synergy analysis on all possible subsets of eight included muscle excitations and evaluated how well the calculated time-varying synergy excitations could construct the remaining excluded muscle excitations (henceforth called "synergy extrapolation"). We found that some, but not all, eight-muscle subsets yielded synergy excitations that achieved >90% extrapolation variance accounted for (VAF). Using the top 10% of subsets, we developed muscle selection heuristics to identify included muscle combinations whose synergy excitations achieved high extrapolation accuracy. For 3, 4, and 5 synergies, these heuristics yielded extrapolation VAF values approximately 5% lower than corresponding reconstruction VAF values for each associated eight-muscle subset. These results suggest that synergy excitations obtained from experimentally measured muscle excitations can accurately construct unmeasured muscle excitations, which could help limit muscle excitations predicted by muscle force optimizations.
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K. M. Strassmann
2018-05-01
Full Text Available The Bern Simple Climate Model (BernSCM is a free open-source re-implementation of a reduced-form carbon cycle–climate model which has been used widely in previous scientific work and IPCC assessments. BernSCM represents the carbon cycle and climate system with a small set of equations for the heat and carbon budget, the parametrization of major nonlinearities, and the substitution of complex component systems with impulse response functions (IRFs. The IRF approach allows cost-efficient yet accurate substitution of detailed parent models of climate system components with near-linear behavior. Illustrative simulations of scenarios from previous multimodel studies show that BernSCM is broadly representative of the range of the climate–carbon cycle response simulated by more complex and detailed models. Model code (in Fortran was written from scratch with transparency and extensibility in mind, and is provided open source. BernSCM makes scientifically sound carbon cycle–climate modeling available for many applications. Supporting up to decadal time steps with high accuracy, it is suitable for studies with high computational load and for coupling with integrated assessment models (IAMs, for example. Further applications include climate risk assessment in a business, public, or educational context and the estimation of CO2 and climate benefits of emission mitigation options.
Study on dynamic characteristics of reduced analytical model for PWR reactor internal structures
International Nuclear Information System (INIS)
Yoo, Bong; Lee, Jae Han; Kim, Jong Bum; Koo, Kyeong Hoe
1993-01-01
The objective of this study is to establish the procedure of the reduced analytical modeling technique for the PWR reactor internal(RI) structures and to carry out the sensitivity study of the dynamic characteristics of the structures by varying the structural parameters such as the stiffness, the mass and the damping. Modeling techniques for the PWR reactor internal structures and computer programs used for the dynamic analysis of the reactor internal structures are briefly investigated. Among the many components of RI structures, the dynamic characteristics for CSB was performed. The sensitivity analysis of the dynamic characteristics for the reduced analytical model considering the variations of the stiffnesses for the lower and upper flanges of the CSB and for the RV Snubber were performed to improve the dynamic characteristics of the RI structures against the external loadings given. In order to enhance the structural design margin of the RI components, the nonlinear time history analyses were attempted for the RI reduced models to compare the structural responses between the reference model and the modified one. (Author)
Technical Note: Reducing the spin-up time of integrated surface water–groundwater models
Ajami, H.
2014-12-12
One of the main challenges in the application of coupled or integrated hydrologic models is specifying a catchment\\'s initial conditions in terms of soil moisture and depth-to-water table (DTWT) distributions. One approach to reducing uncertainty in model initialization is to run the model recursively using either a single year or multiple years of forcing data until the system equilibrates with respect to state and diagnostic variables. However, such "spin-up" approaches often require many years of simulations, making them computationally intensive. In this study, a new hybrid approach was developed to reduce the computational burden of the spin-up procedure by using a combination of model simulations and an empirical DTWT function. The methodology is examined across two distinct catchments located in a temperate region of Denmark and a semi-arid region of Australia. Our results illustrate that the hybrid approach reduced the spin-up period required for an integrated groundwater–surface water–land surface model (ParFlow.CLM) by up to 50%. To generalize results to different climate and catchment conditions, we outline a methodology that is applicable to other coupled or integrated modeling frameworks when initialization from an equilibrium state is required.
Directory of Open Access Journals (Sweden)
Rajib Kar
2010-09-01
Full Text Available This work presents an accurate and efficient model to compute the delay and slew metric of on-chip interconnect of high speed CMOS circuits foe ramp input. Our metric assumption is based on the Burr’s Distribution function. The Burr’s distribution is used to characterize the normalized homogeneous portion of the step response. We used the PERI (Probability distribution function Extension for Ramp Inputs technique that extends delay metrics and slew metric for step inputs to the more general and realistic non-step inputs. The accuracy of our models is justified with the results compared with that of SPICE simulations.
Energy Technology Data Exchange (ETDEWEB)
Martin, Katherine J.; Patrick, Denis R.; Bissell, Mina J.; Fournier, Marcia V.
2008-10-20
One of the major tenets in breast cancer research is that early detection is vital for patient survival by increasing treatment options. To that end, we have previously used a novel unsupervised approach to identify a set of genes whose expression predicts prognosis of breast cancer patients. The predictive genes were selected in a well-defined three dimensional (3D) cell culture model of non-malignant human mammary epithelial cell morphogenesis as down-regulated during breast epithelial cell acinar formation and cell cycle arrest. Here we examine the ability of this gene signature (3D-signature) to predict prognosis in three independent breast cancer microarray datasets having 295, 286, and 118 samples, respectively. Our results show that the 3D-signature accurately predicts prognosis in three unrelated patient datasets. At 10 years, the probability of positive outcome was 52, 51, and 47 percent in the group with a poor-prognosis signature and 91, 75, and 71 percent in the group with a good-prognosis signature for the three datasets, respectively (Kaplan-Meier survival analysis, p<0.05). Hazard ratios for poor outcome were 5.5 (95% CI 3.0 to 12.2, p<0.0001), 2.4 (95% CI 1.6 to 3.6, p<0.0001) and 1.9 (95% CI 1.1 to 3.2, p = 0.016) and remained significant for the two larger datasets when corrected for estrogen receptor (ER) status. Hence the 3D-signature accurately predicts breast cancer outcome in both ER-positive and ER-negative tumors, though individual genes differed in their prognostic ability in the two subtypes. Genes that were prognostic in ER+ patients are AURKA, CEP55, RRM2, EPHA2, FGFBP1, and VRK1, while genes prognostic in ER patients include ACTB, FOXM1 and SERPINE2 (Kaplan-Meier p<0.05). Multivariable Cox regression analysis in the largest dataset showed that the 3D-signature was a strong independent factor in predicting breast cancer outcome. The 3D-signature accurately predicts breast cancer outcome across multiple datasets and holds prognostic
From spiking neuron models to linear-nonlinear models.
Ostojic, Srdjan; Brunel, Nicolas
2011-01-20
Neurons transform time-varying inputs into action potentials emitted stochastically at a time dependent rate. The mapping from current input to output firing rate is often represented with the help of phenomenological models such as the linear-nonlinear (LN) cascade, in which the output firing rate is estimated by applying to the input successively a linear temporal filter and a static non-linear transformation. These simplified models leave out the biophysical details of action potential generation. It is not a priori clear to which extent the input-output mapping of biophysically more realistic, spiking neuron models can be reduced to a simple linear-nonlinear cascade. Here we investigate this question for the leaky integrate-and-fire (LIF), exponential integrate-and-fire (EIF) and conductance-based Wang-Buzsáki models in presence of background synaptic activity. We exploit available analytic results for these models to determine the corresponding linear filter and static non-linearity in a parameter-free form. We show that the obtained functions are identical to the linear filter and static non-linearity determined using standard reverse correlation analysis. We then quantitatively compare the output of the corresponding linear-nonlinear cascade with numerical simulations of spiking neurons, systematically varying the parameters of input signal and background noise. We find that the LN cascade provides accurate estimates of the firing rates of spiking neurons in most of parameter space. For the EIF and Wang-Buzsáki models, we show that the LN cascade can be reduced to a firing rate model, the timescale of which we determine analytically. Finally we introduce an adaptive timescale rate model in which the timescale of the linear filter depends on the instantaneous firing rate. This model leads to highly accurate estimates of instantaneous firing rates.
Probabilistic error bounds for reduced order modeling
Energy Technology Data Exchange (ETDEWEB)
Abdo, M.G.; Wang, C.; Abdel-Khalik, H.S., E-mail: abdo@purdue.edu, E-mail: wang1730@purdue.edu, E-mail: abdelkhalik@purdue.edu [Purdue Univ., School of Nuclear Engineering, West Lafayette, IN (United States)
2015-07-01
Reduced order modeling has proven to be an effective tool when repeated execution of reactor analysis codes is required. ROM operates on the assumption that the intrinsic dimensionality of the associated reactor physics models is sufficiently small when compared to the nominal dimensionality of the input and output data streams. By employing a truncation technique with roots in linear algebra matrix decomposition theory, ROM effectively discards all components of the input and output data that have negligible impact on reactor attributes of interest. This manuscript introduces a mathematical approach to quantify the errors resulting from the discarded ROM components. As supported by numerical experiments, the introduced analysis proves that the contribution of the discarded components could be upper-bounded with an overwhelmingly high probability. The reverse of this statement implies that the ROM algorithm can self-adapt to determine the level of the reduction needed such that the maximum resulting reduction error is below a given tolerance limit that is set by the user. (author)
Xie, Weihong; Yu, Yang
2017-01-01
Robot-assisted motion compensated beating heart surgery has the advantage over the conventional Coronary Artery Bypass Graft (CABG) in terms of reduced trauma to the surrounding structures that leads to shortened recovery time. The severe nonlinear and diverse nature of irregular heart rhythm causes enormous difficulty for the robot to realize the clinic requirements, especially under arrhythmias. In this paper, we propose a fusion prediction framework based on Interactive Multiple Model (IMM) estimator, allowing each model to cover a distinguishing feature of the heart motion in underlying dynamics. We find that, at normal state, the nonlinearity of the heart motion with slow time-variant changing dominates the beating process. When an arrhythmia occurs, the irregularity mode, the fast uncertainties with random patterns become the leading factor of the heart motion. We deal with prediction problem in the case of arrhythmias by estimating the state with two behavior modes which can adaptively “switch” from one to the other. Also, we employed the signal quality index to adaptively determine the switch transition probability in the framework of IMM. We conduct comparative experiments to evaluate the proposed approach with four distinguished datasets. The test results indicate that the new proposed approach reduces prediction errors significantly. PMID:29124062
Directory of Open Access Journals (Sweden)
Fan Liang
2017-01-01
Full Text Available Robot-assisted motion compensated beating heart surgery has the advantage over the conventional Coronary Artery Bypass Graft (CABG in terms of reduced trauma to the surrounding structures that leads to shortened recovery time. The severe nonlinear and diverse nature of irregular heart rhythm causes enormous difficulty for the robot to realize the clinic requirements, especially under arrhythmias. In this paper, we propose a fusion prediction framework based on Interactive Multiple Model (IMM estimator, allowing each model to cover a distinguishing feature of the heart motion in underlying dynamics. We find that, at normal state, the nonlinearity of the heart motion with slow time-variant changing dominates the beating process. When an arrhythmia occurs, the irregularity mode, the fast uncertainties with random patterns become the leading factor of the heart motion. We deal with prediction problem in the case of arrhythmias by estimating the state with two behavior modes which can adaptively “switch” from one to the other. Also, we employed the signal quality index to adaptively determine the switch transition probability in the framework of IMM. We conduct comparative experiments to evaluate the proposed approach with four distinguished datasets. The test results indicate that the new proposed approach reduces prediction errors significantly.
Accurate Evaluation of Quantum Integrals
Galant, D. C.; Goorvitch, D.; Witteborn, Fred C. (Technical Monitor)
1995-01-01
Combining an appropriate finite difference method with Richardson's extrapolation results in a simple, highly accurate numerical method for solving a Schrodinger's equation. Important results are that error estimates are provided, and that one can extrapolate expectation values rather than the wavefunctions to obtain highly accurate expectation values. We discuss the eigenvalues, the error growth in repeated Richardson's extrapolation, and show that the expectation values calculated on a crude mesh can be extrapolated to obtain expectation values of high accuracy.
Aspirin reduces lipopolysaccharide-induced pulmonary inflammation in human models of ARDS.
Hamid, U; Krasnodembskaya, A; Fitzgerald, M; Shyamsundar, M; Kissenpfennig, A; Scott, C; Lefrancais, E; Looney, M R; Verghis, R; Scott, J; Simpson, A J; McNamee, J; McAuley, D F; O'Kane, C M
2017-11-01
Platelets play an active role in the pathogenesis of acute respiratory distress syndrome (ARDS). Animal and observational studies have shown aspirin's antiplatelet and immunomodulatory effects may be beneficial in ARDS. To test the hypothesis that aspirin reduces inflammation in clinically relevant human models that recapitulate pathophysiological mechanisms implicated in the development of ARDS. Healthy volunteers were randomised to receive placebo or aspirin 75 or 1200 mg (1:1:1) for seven days prior to lipopolysaccharide (LPS) inhalation, in a double-blind, placebo-controlled, allocation-concealed study. Bronchoalveolar lavage (BAL) was performed 6 hours after inhaling 50 µg of LPS. The primary outcome measure was BAL IL-8. Secondary outcome measures included markers of alveolar inflammation (BAL neutrophils, cytokines, neutrophil proteases), alveolar epithelial cell injury, systemic inflammation (neutrophils and plasma C-reactive protein (CRP)) and platelet activation (thromboxane B2, TXB2). Human lungs, perfused and ventilated ex vivo (EVLP) were randomised to placebo or 24 mg aspirin and injured with LPS. BAL was carried out 4 hours later. Inflammation was assessed by BAL differential cell counts and histological changes. In the healthy volunteer (n=33) model, data for the aspirin groups were combined. Aspirin did not reduce BAL IL-8. However, aspirin reduced pulmonary neutrophilia and tissue damaging neutrophil proteases (Matrix Metalloproteinase (MMP)-8/-9), reduced BAL concentrations of tumour necrosis factor α and reduced systemic and pulmonary TXB2. There was no difference between high-dose and low-dose aspirin. In the EVLP model, aspirin reduced BAL neutrophilia and alveolar injury as measured by histological damage. These are the first prospective human data indicating that aspirin inhibits pulmonary neutrophilic inflammation, at both low and high doses. Further clinical studies are indicated to assess the role of aspirin in the
Comparison of Predictive Modeling Methods of Aircraft Landing Speed
Diallo, Ousmane H.
2012-01-01
Expected increases in air traffic demand have stimulated the development of air traffic control tools intended to assist the air traffic controller in accurately and precisely spacing aircraft landing at congested airports. Such tools will require an accurate landing-speed prediction to increase throughput while decreasing necessary controller interventions for avoiding separation violations. There are many practical challenges to developing an accurate landing-speed model that has acceptable prediction errors. This paper discusses the development of a near-term implementation, using readily available information, to estimate/model final approach speed from the top of the descent phase of flight to the landing runway. As a first approach, all variables found to contribute directly to the landing-speed prediction model are used to build a multi-regression technique of the response surface equation (RSE). Data obtained from operations of a major airlines for a passenger transport aircraft type to the Dallas/Fort Worth International Airport are used to predict the landing speed. The approach was promising because it decreased the standard deviation of the landing-speed error prediction by at least 18% from the standard deviation of the baseline error, depending on the gust condition at the airport. However, when the number of variables is reduced to the most likely obtainable at other major airports, the RSE model shows little improvement over the existing methods. Consequently, a neural network that relies on a nonlinear regression technique is utilized as an alternative modeling approach. For the reduced number of variables cases, the standard deviation of the neural network models errors represent over 5% reduction compared to the RSE model errors, and at least 10% reduction over the baseline predicted landing-speed error standard deviation. Overall, the constructed models predict the landing-speed more accurately and precisely than the current state-of-the-art.
Challenges in reducing the computational time of QSTS simulations for distribution system analysis.
Energy Technology Data Exchange (ETDEWEB)
Deboever, Jeremiah [Georgia Inst. of Technology, Atlanta, GA (United States); Zhang, Xiaochen [Georgia Inst. of Technology, Atlanta, GA (United States); Reno, Matthew J. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Broderick, Robert Joseph [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Grijalva, Santiago [Georgia Inst. of Technology, Atlanta, GA (United States); Therrien, Francis [CME International T& D, St. Bruno, QC (Canada)
2017-06-01
The rapid increase in penetration of distributed energy resources on the electric power distribution system has created a need for more comprehensive interconnection modelling and impact analysis. Unlike conventional scenario - based studies , quasi - static time - series (QSTS) simulation s can realistically model time - dependent voltage controllers and the diversity of potential impacts that can occur at different times of year . However, to accurately model a distribution system with all its controllable devices, a yearlong simulation at 1 - second resolution is often required , which could take conventional computers a computational time of 10 to 120 hours when an actual unbalanced distribution feeder is modeled . This computational burden is a clear l imitation to the adoption of QSTS simulation s in interconnection studies and for determining optimal control solutions for utility operations . Our ongoing research to improve the speed of QSTS simulation has revealed many unique aspects of distribution system modelling and sequential power flow analysis that make fast QSTS a very difficult problem to solve. In this report , the most relevant challenges in reducing the computational time of QSTS simulations are presented: number of power flows to solve, circuit complexity, time dependence between time steps, multiple valid power flow solutions, controllable element interactions, and extensive accurate simulation analysis.
Accurate location estimation of moving object In Wireless Sensor network
Directory of Open Access Journals (Sweden)
Vinay Bhaskar Semwal
2011-12-01
Full Text Available One of the central issues in wirless sensor networks is track the location, of moving object which have overhead of saving data, an accurate estimation of the target location of object with energy constraint .We do not have any mechanism which control and maintain data .The wireless communication bandwidth is also very limited. Some field which is using this technique are flood and typhoon detection, forest fire detection, temperature and humidity and ones we have these information use these information back to a central air conditioning and ventilation.In this research paper, we propose protocol based on the prediction and adaptive based algorithm which is using less sensor node reduced by an accurate estimation of the target location. We had shown that our tracking method performs well in terms of energy saving regardless of mobility pattern of the mobile target. We extends the life time of network with less sensor node. Once a new object is detected, a mobile agent will be initiated to track the roaming path of the object.
New Fokker-Planck derivation of heavy gas models for neutron thermalization
International Nuclear Information System (INIS)
Larsen, E.W.; Williams, M.M.R.
1990-01-01
This paper is concerned with the derivation of new generalized heavy gas models for the infinite medium neutron energy spectrum equation. Our approach is general and can be used to derive improved Fokker-Planck approximations for other types of kinetic equations. In this paper we obtain two distinct heavy gas models, together with estimates for the corresponding errors. The models are shown in a special case to reduce to modified heavy gas models proposed earlier by Corngold (1962). The error estimates show that both of the new models should be more accurate than Corngold's modified heavy gas model, and that the first of the two new models should generally be more accurate than the second. (author)
Dral, Pavlo O.; Owens, Alec; Yurchenko, Sergei N.; Thiel, Walter
2017-06-01
We present an efficient approach for generating highly accurate molecular potential energy surfaces (PESs) using self-correcting, kernel ridge regression (KRR) based machine learning (ML). We introduce structure-based sampling to automatically assign nuclear configurations from a pre-defined grid to the training and prediction sets, respectively. Accurate high-level ab initio energies are required only for the points in the training set, while the energies for the remaining points are provided by the ML model with negligible computational cost. The proposed sampling procedure is shown to be superior to random sampling and also eliminates the need for training several ML models. Self-correcting machine learning has been implemented such that each additional layer corrects errors from the previous layer. The performance of our approach is demonstrated in a case study on a published high-level ab initio PES of methyl chloride with 44 819 points. The ML model is trained on sets of different sizes and then used to predict the energies for tens of thousands of nuclear configurations within seconds. The resulting datasets are utilized in variational calculations of the vibrational energy levels of CH3Cl. By using both structure-based sampling and self-correction, the size of the training set can be kept small (e.g., 10% of the points) without any significant loss of accuracy. In ab initio rovibrational spectroscopy, it is thus possible to reduce the number of computationally costly electronic structure calculations through structure-based sampling and self-correcting KRR-based machine learning by up to 90%.
Jacobian projection reduced-order models for dynamic systems with contact nonlinearities
Gastaldi, Chiara; Zucca, Stefano; Epureanu, Bogdan I.
2018-02-01
In structural dynamics, the prediction of the response of systems with localized nonlinearities, such as friction dampers, is of particular interest. This task becomes especially cumbersome when high-resolution finite element models are used. While state-of-the-art techniques such as Craig-Bampton component mode synthesis are employed to generate reduced order models, the interface (nonlinear) degrees of freedom must still be solved in-full. For this reason, a new generation of specialized techniques capable of reducing linear and nonlinear degrees of freedom alike is emerging. This paper proposes a new technique that exploits spatial correlations in the dynamics to compute a reduction basis. The basis is composed of a set of vectors obtained using the Jacobian of partial derivatives of the contact forces with respect to nodal displacements. These basis vectors correspond to specifically chosen boundary conditions at the contacts over one cycle of vibration. The technique is shown to be effective in the reduction of several models studied using multiple harmonics with a coupled static solution. In addition, this paper addresses another challenge common to all reduction techniques: it presents and validates a novel a posteriori error estimate capable of evaluating the quality of the reduced-order solution without involving a comparison with the full-order solution.
SPARC: MASS MODELS FOR 175 DISK GALAXIES WITH SPITZER PHOTOMETRY AND ACCURATE ROTATION CURVES
Energy Technology Data Exchange (ETDEWEB)
Lelli, Federico; McGaugh, Stacy S. [Department of Astronomy, Case Western Reserve University, Cleveland, OH 44106 (United States); Schombert, James M., E-mail: federico.lelli@case.edu [Department of Physics, University of Oregon, Eugene, OR 97403 (United States)
2016-12-01
We introduce SPARC ( Spitzer Photometry and Accurate Rotation Curves): a sample of 175 nearby galaxies with new surface photometry at 3.6 μ m and high-quality rotation curves from previous H i/H α studies. SPARC spans a broad range of morphologies (S0 to Irr), luminosities (∼5 dex), and surface brightnesses (∼4 dex). We derive [3.6] surface photometry and study structural relations of stellar and gas disks. We find that both the stellar mass–H i mass relation and the stellar radius–H i radius relation have significant intrinsic scatter, while the H i mass–radius relation is extremely tight. We build detailed mass models and quantify the ratio of baryonic to observed velocity ( V {sub bar}/ V {sub obs}) for different characteristic radii and values of the stellar mass-to-light ratio (ϒ{sub ⋆}) at [3.6]. Assuming ϒ{sub ⋆} ≃ 0.5 M {sub ⊙}/ L {sub ⊙} (as suggested by stellar population models), we find that (i) the gas fraction linearly correlates with total luminosity; (ii) the transition from star-dominated to gas-dominated galaxies roughly corresponds to the transition from spiral galaxies to dwarf irregulars, in line with density wave theory; and (iii) V {sub bar}/ V {sub obs} varies with luminosity and surface brightness: high-mass, high-surface-brightness galaxies are nearly maximal, while low-mass, low-surface-brightness galaxies are submaximal. These basic properties are lost for low values of ϒ{sub ⋆} ≃ 0.2 M {sub ⊙}/ L {sub ⊙} as suggested by the DiskMass survey. The mean maximum-disk limit in bright galaxies is ϒ{sub ⋆} ≃ 0.7 M {sub ⊙}/ L {sub ⊙} at [3.6]. The SPARC data are publicly available and represent an ideal test bed for models of galaxy formation.
Friedman, Lee; Harvey, Robert J.
1986-01-01
Job-naive raters provided with job descriptive information made Position Analysis Questionnaire (PAQ) ratings which were validated against ratings of job analysts who were also job content experts. None of the reduced job descriptive information conditions enabled job-naive raters to obtain either acceptable levels of convergent validity with…
Startle reduces recall of a recently learned internal model.
Wright, Zachary; Patton, James L; Ravichandran, Venn
2011-01-01
Recent work has shown that preplanned motor programs are released early from subcortical areas by the using a startling acoustic stimulus (SAS). Our question is whether this response might also contain a recently learned internal model, which draws on experience to predict and compensate for expected perturbations in a feedforward manner. Studies of adaptation to robotic forces have shown some evidence of this, but were potentially confounded by cocontraction caused by startle. We performed a new adaptation experiment using a visually distorted field that could not be confounded by cocontraction. We found that in all subjects that exhibited startle, the startle stimulus (1) reduced performance of the recently learned task (2) reduced after-effect magnitudes. Because startle reduced but did not eliminate the recall of learned control, we suggest that multiple neural centers (cortical and subcortical) are involved in such learning and adaptation, which can impact training areas such as piloting, teleoperation, sports, and rehabilitation. © 2011 IEEE
DEFF Research Database (Denmark)
Johansen, Søren
2008-01-01
The reduced rank regression model is a multivariate regression model with a coefficient matrix with reduced rank. The reduced rank regression algorithm is an estimation procedure, which estimates the reduced rank regression model. It is related to canonical correlations and involves calculating...
Energy Technology Data Exchange (ETDEWEB)
Johnson, Brian B [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Purba, Victor [University of Minnesota; Jafarpour, Saber [University of California, Santa Barbara; Bullo, Francesco [University of California, Santa Barbara; Dhople, Sairaj [University of Minnesota
2017-08-31
Given that next-generation infrastructures will contain large numbers of grid-connected inverters and these interfaces will be satisfying a growing fraction of system load, it is imperative to analyze the impacts of power electronics on such systems. However, since each inverter model has a relatively large number of dynamic states, it would be impractical to execute complex system models where the full dynamics of each inverter are retained. To address this challenge, we derive a reduced-order structure-preserving model for parallel-connected grid-tied three-phase inverters. Here, each inverter in the system is assumed to have a full-bridge topology, LCL filter at the point of common coupling, and the control architecture for each inverter includes a current controller, a power controller, and a phase-locked loop for grid synchronization. We outline a structure-preserving reduced-order inverter model for the setting where the parallel inverters are each designed such that the filter components and controller gains scale linearly with the power rating. By structure preserving, we mean that the reduced-order three-phase inverter model is also composed of an LCL filter, a power controller, current controller, and PLL. That is, we show that the system of parallel inverters can be modeled exactly as one aggregated inverter unit and this equivalent model has the same number of dynamical states as an individual inverter in the paralleled system. Numerical simulations validate the reduced-order models.
Accurate Electromagnetic Modeling Methods for Integrated Circuits
Sheng, Z.
2010-01-01
The present development of modern integrated circuits (IC’s) is characterized by a number of critical factors that make their design and verification considerably more difficult than before. This dissertation addresses the important questions of modeling all electromagnetic behavior of features on
Viceconti, Marco; Davinelli, Mario; Taddei, Fulvia; Cappello, Angelo
2004-10-01
Most of the finite element models of bones used in orthopaedic biomechanics research are based on generic anatomies. However, in many cases it would be useful to generate from CT data a separate finite element model for each subject of a study group. In a recent study a hexahedral mesh generator based on a grid projection algorithm was found very effective in terms of accuracy and automation. However, so far the use of this method has been documented only on data collected in vitro and only for long bones. The present study was aimed at verifying if this method represents a procedure for the generation of finite element models of human bones from data collected in vivo, robust, accurate, automatic and general enough to be used in clinical studies. Robustness, automation and numerical accuracy of the proposed method were assessed on five femoral CT data sets of patients affected by various pathologies. The generality of the method was verified by processing a femur, an ileum, a phalanx, a proximal femur reconstruction, and the micro-CT of a small sample of spongy bone. The method was found robust enough to cope with the variability of the five femurs, producing meshes with a numerical accuracy and a computational weight comparable to those found in vitro. Even when the method was used to process the other bones the levels of mesh conditioning remained within acceptable limits. Thus, it may be concluded that the method presents a generality sufficient to cope with almost any orthopaedic application.
Energy Technology Data Exchange (ETDEWEB)
Nakhleh, Luay
2014-03-12
I proposed to develop computationally efficient tools for accurate detection and reconstruction of microbes' complex evolutionary mechanisms, thus enabling rapid and accurate annotation, analysis and understanding of their genomes. To achieve this goal, I proposed to address three aspects. (1) Mathematical modeling. A major challenge facing the accurate detection of HGT is that of distinguishing between these two events on the one hand and other events that have similar "effects." I proposed to develop a novel mathematical approach for distinguishing among these events. Further, I proposed to develop a set of novel optimization criteria for the evolutionary analysis of microbial genomes in the presence of these complex evolutionary events. (2) Algorithm design. In this aspect of the project, I proposed to develop an array of e cient and accurate algorithms for analyzing microbial genomes based on the formulated optimization criteria. Further, I proposed to test the viability of the criteria and the accuracy of the algorithms in an experimental setting using both synthetic as well as biological data. (3) Software development. I proposed the nal outcome to be a suite of software tools which implements the mathematical models as well as the algorithms developed.
Karam, Ayman M.
2016-12-01
Membrane Distillation (MD) is an emerging sustainable desalination technique. While MD has many advantages and can be powered by solar thermal energy, its main drawback is the low water production rate. However, the MD process has not been fully optimized in terms of its manipulated and controlled variables. This is largely due to the lack of adequate dynamic models to study and simulate the process. In addition, MD is prone to membrane fouling, which is a fault that degrades the performance of the MD process. This work has three contributions to address these challenges. First, we derive a mathematical model of Direct Contact Membrane Distillation (DCMD), which is the building block for the next parts. Then, the proposed model is extended to account for membrane fouling and an observer-based fouling detection method is developed. Finally, various control strategies are implemented to optimize the performance of the DCMD solar-powered process. In part one, a reduced-order dynamic model of DCMD is developed based on lumped capacitance method and electrical analogy to thermal systems. The result is an electrical equivalent thermal network to the DCMD process, which is modeled by a system of nonlinear differential algebraic equations (DAEs). This model predicts the water-vapor flux and the temperature distribution along the module length. Experimental data is collected to validate the steady-state and dynamic responses of the proposed model, with great agreement demonstrated in both. The second part proposes an extension of the model to account for membrane fouling. An adaptive observer for DAE systems is developed and convergence proof is presented. A method for membrane fouling detection is then proposed based on adaptive observers. Simulation results demonstrate the performance of the membrane fouling detection method. Finally, an optimization problem is formulated to maximize the process efficiency of a solar-powered DCMD. The adapted method is known as Extremum
Development of a High Resolution 3D Infant Stomach Model for Surgical Planning
Chaudry, Qaiser; Raza, S. Hussain; Lee, Jeonggyu; Xu, Yan; Wulkan, Mark; Wang, May D.
Medical surgical procedures have not changed much during the past century due to the lack of accurate low-cost workbench for testing any new improvement. The increasingly cheaper and powerful computer technologies have made computer-based surgery planning and training feasible. In our work, we have developed an accurate 3D stomach model, which aims to improve the surgical procedure that treats the infant pediatric and neonatal gastro-esophageal reflux disease (GERD). We generate the 3-D infant stomach model based on in vivo computer tomography (CT) scans of an infant. CT is a widely used clinical imaging modality that is cheap, but with low spatial resolution. To improve the model accuracy, we use the high resolution Visible Human Project (VHP) in model building. Next, we add soft muscle material properties to make the 3D model deformable. Then we use virtual reality techniques such as haptic devices to make the 3D stomach model deform upon touching force. This accurate 3D stomach model provides a workbench for testing new GERD treatment surgical procedures. It has the potential to reduce or eliminate the extensive cost associated with animal testing when improving any surgical procedure, and ultimately, to reduce the risk associated with infant GERD surgery.
Gray, Alan; Harlen, Oliver G; Harris, Sarah A; Khalid, Syma; Leung, Yuk Ming; Lonsdale, Richard; Mulholland, Adrian J; Pearson, Arwen R; Read, Daniel J; Richardson, Robin A
2015-01-01
Despite huge advances in the computational techniques available for simulating biomolecules at the quantum-mechanical, atomistic and coarse-grained levels, there is still a widespread perception amongst the experimental community that these calculations are highly specialist and are not generally applicable by researchers outside the theoretical community. In this article, the successes and limitations of biomolecular simulation and the further developments that are likely in the near future are discussed. A brief overview is also provided of the experimental biophysical methods that are commonly used to probe biomolecular structure and dynamics, and the accuracy of the information that can be obtained from each is compared with that from modelling. It is concluded that progress towards an accurate spatial and temporal model of biomacromolecules requires a combination of all of these biophysical techniques, both experimental and computational.
Technical Note: Reducing the spin-up time of integrated surface water–groundwater models
Ajami, H.
2014-06-26
One of the main challenges in catchment scale application of coupled/integrated hydrologic models is specifying a catchment\\'s initial conditions in terms of soil moisture and depth to water table (DTWT) distributions. One approach to reduce uncertainty in model initialization is to run the model recursively using a single or multiple years of forcing data until the system equilibrates with respect to state and diagnostic variables. However, such "spin-up" approaches often require many years of simulations, making them computationally intensive. In this study, a new hybrid approach was developed to reduce the computational burden of spin-up time for an integrated groundwater-surface water-land surface model (ParFlow.CLM) by using a combination of ParFlow.CLM simulations and an empirical DTWT function. The methodology is examined in two catchments located in the temperate and semi-arid regions of Denmark and Australia respectively. Our results illustrate that the hybrid approach reduced the spin-up time required by ParFlow.CLM by up to 50%, and we outline a methodology that is applicable to other coupled/integrated modelling frameworks when initialization from equilibrium state is required.
Fitting neuron models to spike trains
Directory of Open Access Journals (Sweden)
Cyrille eRossant
2011-02-01
Full Text Available Computational modeling is increasingly used to understand the function of neural circuitsin systems neuroscience.These studies require models of individual neurons with realisticinput-output properties.Recently, it was found that spiking models can accurately predict theprecisely timed spike trains produced by cortical neurons in response tosomatically injected currents,if properly fitted. This requires fitting techniques that are efficientand flexible enough to easily test different candidate models.We present a generic solution, based on the Brian simulator(a neural network simulator in Python, which allowsthe user to define and fit arbitrary neuron models to electrophysiological recordings.It relies on vectorization and parallel computing techniques toachieve efficiency.We demonstrate its use on neural recordings in the barrel cortex andin the auditory brainstem, and confirm that simple adaptive spiking modelscan accurately predict the response of cortical neurons. Finally, we show how a complexmulticompartmental model can be reduced to a simple effective spiking model.
Barker, John R.; Martinez, Antonio
2018-04-01
Efficient analytical image charge models are derived for the full spatial variation of the electrostatic self-energy of electrons in semiconductor nanostructures that arises from dielectric mismatch using semi-classical analysis. The methodology provides a fast, compact and physically transparent computation for advanced device modeling. The underlying semi-classical model for the self-energy has been established and validated during recent years and depends on a slight modification of the macroscopic static dielectric constants for individual homogeneous dielectric regions. The model has been validated for point charges as close as one interatomic spacing to a sharp interface. A brief introduction to image charge methodology is followed by a discussion and demonstration of the traditional failure of the methodology to derive the electrostatic potential at arbitrary distances from a source charge. However, the self-energy involves the local limit of the difference between the electrostatic Green functions for the full dielectric heterostructure and the homogeneous equivalent. It is shown that high convergence may be achieved for the image charge method for this local limit. A simple re-normalisation technique is introduced to reduce the number of image terms to a minimum. A number of progressively complex 3D models are evaluated analytically and compared with high precision numerical computations. Accuracies of 1% are demonstrated. Introducing a simple technique for modeling the transition of the self-energy between disparate dielectric structures we generate an analytical model that describes the self-energy as a function of position within the source, drain and gated channel of a silicon wrap round gate field effect transistor on a scale of a few nanometers cross-section. At such scales the self-energies become large (typically up to ~100 meV) close to the interfaces as well as along the channel. The screening of a gated structure is shown to reduce the self
A semi-implicit, second-order-accurate numerical model for multiphase underexpanded volcanic jets
Directory of Open Access Journals (Sweden)
S. Carcano
2013-11-01
Full Text Available An improved version of the PDAC (Pyroclastic Dispersal Analysis Code, Esposti Ongaro et al., 2007 numerical model for the simulation of multiphase volcanic flows is presented and validated for the simulation of multiphase volcanic jets in supersonic regimes. The present version of PDAC includes second-order time- and space discretizations and fully multidimensional advection discretizations in order to reduce numerical diffusion and enhance the accuracy of the original model. The model is tested on the problem of jet decompression in both two and three dimensions. For homogeneous jets, numerical results are consistent with experimental results at the laboratory scale (Lewis and Carlson, 1964. For nonequilibrium gas–particle jets, we consider monodisperse and bidisperse mixtures, and we quantify nonequilibrium effects in terms of the ratio between the particle relaxation time and a characteristic jet timescale. For coarse particles and low particle load, numerical simulations well reproduce laboratory experiments and numerical simulations carried out with an Eulerian–Lagrangian model (Sommerfeld, 1993. At the volcanic scale, we consider steady-state conditions associated with the development of Vulcanian and sub-Plinian eruptions. For the finest particles produced in these regimes, we demonstrate that the solid phase is in mechanical and thermal equilibrium with the gas phase and that the jet decompression structure is well described by a pseudogas model (Ogden et al., 2008. Coarse particles, on the other hand, display significant nonequilibrium effects, which associated with their larger relaxation time. Deviations from the equilibrium regime, with maximum velocity and temperature differences on the order of 150 m s−1 and 80 K across shock waves, occur especially during the rapid acceleration phases, and are able to modify substantially the jet dynamics with respect to the homogeneous case.
Accurate atom-mapping computation for biochemical reactions.
Latendresse, Mario; Malerich, Jeremiah P; Travers, Mike; Karp, Peter D
2012-11-26
The complete atom mapping of a chemical reaction is a bijection of the reactant atoms to the product atoms that specifies the terminus of each reactant atom. Atom mapping of biochemical reactions is useful for many applications of systems biology, in particular for metabolic engineering where synthesizing new biochemical pathways has to take into account for the number of carbon atoms from a source compound that are conserved in the synthesis of a target compound. Rapid, accurate computation of the atom mapping(s) of a biochemical reaction remains elusive despite significant work on this topic. In particular, past researchers did not validate the accuracy of mapping algorithms. We introduce a new method for computing atom mappings called the minimum weighted edit-distance (MWED) metric. The metric is based on bond propensity to react and computes biochemically valid atom mappings for a large percentage of biochemical reactions. MWED models can be formulated efficiently as Mixed-Integer Linear Programs (MILPs). We have demonstrated this approach on 7501 reactions of the MetaCyc database for which 87% of the models could be solved in less than 10 s. For 2.1% of the reactions, we found multiple optimal atom mappings. We show that the error rate is 0.9% (22 reactions) by comparing these atom mappings to 2446 atom mappings of the manually curated Kyoto Encyclopedia of Genes and Genomes (KEGG) RPAIR database. To our knowledge, our computational atom-mapping approach is the most accurate and among the fastest published to date. The atom-mapping data will be available in the MetaCyc database later in 2012; the atom-mapping software will be available within the Pathway Tools software later in 2012.
The MIDAS touch for Accurately Predicting the Stress-Strain Behavior of Tantalum
Energy Technology Data Exchange (ETDEWEB)
Jorgensen, S. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
2016-03-02
Testing the behavior of metals in extreme environments is not always feasible, so material scientists use models to try and predict the behavior. To achieve accurate results it is necessary to use the appropriate model and material-specific parameters. This research evaluated the performance of six material models available in the MIDAS database [1] to determine at which temperatures and strain-rates they perform best, and to determine to which experimental data their parameters were optimized. Additionally, parameters were optimized for the Johnson-Cook model using experimental data from Lassila et al [2].
Simulation of reactive nanolaminates using reduced models: II. Normal propagation
Energy Technology Data Exchange (ETDEWEB)
Salloum, Maher; Knio, Omar M. [Department of Mechanical Engineering, The Johns Hopkins University, Baltimore, MD 21218-2686 (United States)
2010-03-15
Transient normal flame propagation in reactive Ni/Al multilayers is analyzed computationally. Two approaches are implemented, based on generalization of earlier methodology developed for axial propagation, and on extension of the model reduction formalism introduced in Part I. In both cases, the formulation accommodates non-uniform layering as well as the presence of inert layers. The equations of motion for the reactive system are integrated using a specially-tailored integration scheme, that combines extended-stability, Runge-Kutta-Chebychev (RKC) integration of diffusion terms with exact treatment of the chemical source term. The detailed and reduced models are first applied to the analysis of self-propagating fronts in uniformly-layered materials. Results indicate that both the front velocities and the ignition threshold are comparable for normal and axial propagation. Attention is then focused on analyzing the effect of a gap composed of inert material on reaction propagation. In particular, the impacts of gap width and thermal conductivity are briefly addressed. Finally, an example is considered illustrating reaction propagation in reactive composites combining regions corresponding to two bilayer widths. This setup is used to analyze the effect of the layering frequency on the velocity of the corresponding reaction fronts. In all cases considered, good agreement is observed between the predictions of the detailed model and the reduced model, which provides further support for adoption of the latter. (author)
An Accurate Transmitting Power Control Method in Wireless Communication Transceivers
Zhang, Naikang; Wen, Zhiping; Hou, Xunping; Bi, Bo
2018-01-01
Power control circuits are widely used in transceivers aiming at stabilizing the transmitted signal power to a specified value, thereby reducing power consumption and interference to other frequency bands. In order to overcome the shortcomings of traditional modes of power control, this paper proposes an accurate signal power detection method by multiplexing the receiver and realizes transmitting power control in the digital domain. The simulation results show that this novel digital power control approach has advantages of small delay, high precision and simplified design procedure. The proposed method is applicable to transceivers working at large frequency dynamic range, and has good engineering practicability.
Reynolds, Sheila M.; Bilmes, Jeff A.; Noble, William Stafford
2010-01-01
DNA in eukaryotes is packaged into a chromatin complex, the most basic element of which is the nucleosome. The precise positioning of the nucleosome cores allows for selective access to the DNA, and the mechanisms that control this positioning are important pieces of the gene expression puzzle. We describe a large-scale nucleosome pattern that jointly characterizes the nucleosome core and the adjacent linkers and is predominantly characterized by long-range oscillations in the mono, di- and tri-nucleotide content of the DNA sequence, and we show that this pattern can be used to predict nucleosome positions in both Homo sapiens and Saccharomyces cerevisiae more accurately than previously published methods. Surprisingly, in both H. sapiens and S. cerevisiae, the most informative individual features are the mono-nucleotide patterns, although the inclusion of di- and tri-nucleotide features results in improved performance. Our approach combines a much longer pattern than has been previously used to predict nucleosome positioning from sequence—301 base pairs, centered at the position to be scored—with a novel discriminative classification approach that selectively weights the contributions from each of the input features. The resulting scores are relatively insensitive to local AT-content and can be used to accurately discriminate putative dyad positions from adjacent linker regions without requiring an additional dynamic programming step and without the attendant edge effects and assumptions about linker length modeling and overall nucleosome density. Our approach produces the best dyad-linker classification results published to date in H. sapiens, and outperforms two recently published models on a large set of S. cerevisiae nucleosome positions. Our results suggest that in both genomes, a comparable and relatively small fraction of nucleosomes are well-positioned and that these positions are predictable based on sequence alone. We believe that the bulk of the
Directory of Open Access Journals (Sweden)
Sheila M Reynolds
2010-07-01
Full Text Available DNA in eukaryotes is packaged into a chromatin complex, the most basic element of which is the nucleosome. The precise positioning of the nucleosome cores allows for selective access to the DNA, and the mechanisms that control this positioning are important pieces of the gene expression puzzle. We describe a large-scale nucleosome pattern that jointly characterizes the nucleosome core and the adjacent linkers and is predominantly characterized by long-range oscillations in the mono, di- and tri-nucleotide content of the DNA sequence, and we show that this pattern can be used to predict nucleosome positions in both Homo sapiens and Saccharomyces cerevisiae more accurately than previously published methods. Surprisingly, in both H. sapiens and S. cerevisiae, the most informative individual features are the mono-nucleotide patterns, although the inclusion of di- and tri-nucleotide features results in improved performance. Our approach combines a much longer pattern than has been previously used to predict nucleosome positioning from sequence-301 base pairs, centered at the position to be scored-with a novel discriminative classification approach that selectively weights the contributions from each of the input features. The resulting scores are relatively insensitive to local AT-content and can be used to accurately discriminate putative dyad positions from adjacent linker regions without requiring an additional dynamic programming step and without the attendant edge effects and assumptions about linker length modeling and overall nucleosome density. Our approach produces the best dyad-linker classification results published to date in H. sapiens, and outperforms two recently published models on a large set of S. cerevisiae nucleosome positions. Our results suggest that in both genomes, a comparable and relatively small fraction of nucleosomes are well-positioned and that these positions are predictable based on sequence alone. We believe that the
Reynolds, Sheila M; Bilmes, Jeff A; Noble, William Stafford
2010-07-08
DNA in eukaryotes is packaged into a chromatin complex, the most basic element of which is the nucleosome. The precise positioning of the nucleosome cores allows for selective access to the DNA, and the mechanisms that control this positioning are important pieces of the gene expression puzzle. We describe a large-scale nucleosome pattern that jointly characterizes the nucleosome core and the adjacent linkers and is predominantly characterized by long-range oscillations in the mono, di- and tri-nucleotide content of the DNA sequence, and we show that this pattern can be used to predict nucleosome positions in both Homo sapiens and Saccharomyces cerevisiae more accurately than previously published methods. Surprisingly, in both H. sapiens and S. cerevisiae, the most informative individual features are the mono-nucleotide patterns, although the inclusion of di- and tri-nucleotide features results in improved performance. Our approach combines a much longer pattern than has been previously used to predict nucleosome positioning from sequence-301 base pairs, centered at the position to be scored-with a novel discriminative classification approach that selectively weights the contributions from each of the input features. The resulting scores are relatively insensitive to local AT-content and can be used to accurately discriminate putative dyad positions from adjacent linker regions without requiring an additional dynamic programming step and without the attendant edge effects and assumptions about linker length modeling and overall nucleosome density. Our approach produces the best dyad-linker classification results published to date in H. sapiens, and outperforms two recently published models on a large set of S. cerevisiae nucleosome positions. Our results suggest that in both genomes, a comparable and relatively small fraction of nucleosomes are well-positioned and that these positions are predictable based on sequence alone. We believe that the bulk of the
Huang, Guo-Jiao; Bai, Chao-Ying; Greenhalgh, Stewart
2013-09-01
The traditional grid/cell-based wavefront expansion algorithms, such as the shortest path algorithm, can only find the first arrivals or multiply reflected (or mode converted) waves transmitted from subsurface interfaces, but cannot calculate the other later reflections/conversions having a minimax time path. In order to overcome the above limitations, we introduce the concept of a stationary minimax time path of Fermat's Principle into the multistage irregular shortest path method. Here we extend it from Cartesian coordinates for a flat earth model to global ray tracing of multiple phases in a 3-D complex spherical earth model. The ray tracing results for 49 different kinds of crustal, mantle and core phases show that the maximum absolute traveltime error is less than 0.12 s and the average absolute traveltime error is within 0.09 s when compared with the AK135 theoretical traveltime tables for a 1-D reference model. Numerical tests in terms of computational accuracy and CPU time consumption indicate that the new scheme is an accurate, efficient and a practical way to perform 3-D multiphase arrival tracking in regional or global traveltime tomography.
Directory of Open Access Journals (Sweden)
Rob Eling
2016-09-01
Full Text Available Journal bearings are used to support rotors in a wide range of applications. In order to ensure reliable operation, accurate analyses of these rotor-bearing systems are crucial. Coupled analysis of the rotor and the journal bearing is essential in the case that the rotor is flexible. The accuracy of prediction of the model at hand depends on its comprehensiveness. In this study, we construct three bearing models of increasing modeling comprehensiveness and use these to predict the response of two different rotor-bearing systems. The main goal is to evaluate the correlation with measurement data as a function of modeling comprehensiveness: 1D versus 2D pressure prediction, distributed versus lumped thermal model, Newtonian versus non-Newtonian fluid description and non-mass-conservative versus mass-conservative cavitation description. We conclude that all three models predict the existence of critical speeds and whirl for both rotor-bearing systems. However, the two more comprehensive models in general show better correlation with measurement data in terms of frequency and amplitude. Furthermore, we conclude that a thermal network model comprising temperature predictions of the bearing surroundings is essential to obtain accurate predictions. The results of this study aid in developing accurate and computationally-efficient models of flexible rotors supported by plain journal bearings.
Stress-reducing preventive maintenance model for a unit under stressful environment
International Nuclear Information System (INIS)
Park, J.H.; Chang, Woojin; Lie, C.H.
2012-01-01
We develop a preventive maintenance (PM) model for a unit operated under stressful environment. The PM model in this paper consists of a failure rate model and two cost models to determine the optimal PM scheduling which minimizes a cost rate. The assumption for the proposed model is that stressful environment accelerates the failure of the unit and periodic maintenances reduce stress from outside. The failure rate model handles the maintenance effect of PM using improvement and stress factors. The cost models are categorized into two failure recognition cases: immediate failure recognition and periodic failure detection. The optimal PM scheduling is obtained by considering the trade-off between the related cost and the lifetime of a unit in our model setting. The practical usage of our proposed model is tested through a numerical example.
Rising Temperatures Reduce Global Wheat Production
Asseng, S.; Ewert, F.; Martre, P.; Rötter, R. P.; Lobell, D. B.; Cammarano, D.; Kimball, B. A.; Ottman, M. J.; Wall, G. W.; White, J. W.;
2015-01-01
Crop models are essential tools for assessing the threat of climate change to local and global food production. Present models used to predict wheat grain yield are highly uncertain when simulating how crops respond to temperature. Here we systematically tested 30 different wheat crop models of the Agricultural Model Intercomparison and Improvement Project against field experiments in which growing season mean temperatures ranged from 15 degrees C to 32? degrees C, including experiments with artificial heating. Many models simulated yields well, but were less accurate at higher temperatures. The model ensemble median was consistently more accurate in simulating the crop temperature response than any single model, regardless of the input information used. Extrapolating the model ensemble temperature response indicates that warming is already slowing yield gains at a majority of wheat-growing locations. Global wheat production is estimated to fall by 6% for each degree C of further temperature increase and become more variable over space and time.
Improved fingercode alignment for accurate and compact fingerprint recognition
CSIR Research Space (South Africa)
Brown, Dane
2016-05-01
Full Text Available Alignment for Accurate and Compact Fingerprint Recognition Dane Brown∗† and Karen Bradshaw∗ ∗Department of Computer Science Rhodes University Grahamstown, South Africa †Council for Scientific and Industrial Research Modelling and Digital Sciences Pretoria.... The experimental analysis and results are discussed in Section IV. Section V concludes the paper. II. RELATED STUDIES FingerCode [1] uses circular tessellation of filtered finger- print images centered at the reference point, which results in a circular ROI...
Probability-based collaborative filtering model for predicting gene–disease associations
Zeng, Xiangxiang; Ding, Ningxiang; Rodríguez-Patón, Alfonso; Zou, Quan
2017-01-01
Background Accurately predicting pathogenic human genes has been challenging in recent research. Considering extensive gene–disease data verified by biological experiments, we can apply computational methods to perform accurate predictions with reduced time and expenses. Methods We propose a probability-based collaborative filtering model (PCFM) to predict pathogenic human genes. Several kinds of data sets, containing data of humans and data of other nonhuman species, are integrated in our mo...
Dechow, C D; Rogers, G W
2018-05-01
Expectation of genetic merit in commercial dairy herds is routinely estimated using a 4-path genetic selection model that was derived for a closed population, but commercial herds using artificial insemination sires are not closed. The 4-path model also predicts a higher rate of genetic progress in elite herds that provide artificial insemination sires than in commercial herds that use such sires, which counters other theoretical assumptions and observations of realized genetic responses. The aim of this work is to clarify whether genetic merit in commercial herds is more accurately reflected under the assumptions of the 4-path genetic response formula or by a genetic lag formula. We demonstrate by tracing the transmission of genetic merit from parents to offspring that the rate of genetic progress in commercial dairy farms is expected to be the same as that in the genetic nucleus. The lag in genetic merit between the nucleus and commercial farms is a function of sire and dam generation interval, the rate of genetic progress in elite artificial insemination herds, and genetic merit of sires and dams. To predict how strategies such as the use of young versus daughter-proven sires, culling heifers following genomic testing, or selective use of sexed semen will alter genetic merit in commercial herds, genetic merit expectations for commercial herds should be modeled using genetic lag expectations. Copyright © 2018 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.
International Nuclear Information System (INIS)
Chang, Chih-Hao; Liou, Meng-Sing
2007-01-01
In this paper, we propose a new approach to compute compressible multifluid equations. Firstly, a single-pressure compressible multifluid model based on the stratified flow model is proposed. The stratified flow model, which defines different fluids in separated regions, is shown to be amenable to the finite volume method. We can apply the conservation law to each subregion and obtain a set of balance equations. Secondly, the AUSM + scheme, which is originally designed for the compressible gas flow, is extended to solve compressible liquid flows. By introducing additional dissipation terms into the numerical flux, the new scheme, called AUSM + -up, can be applied to both liquid and gas flows. Thirdly, the contribution to the numerical flux due to interactions between different phases is taken into account and solved by the exact Riemann solver. We will show that the proposed approach yields an accurate and robust method for computing compressible multiphase flows involving discontinuities, such as shock waves and fluid interfaces. Several one-dimensional test problems are used to demonstrate the capability of our method, including the Ransom's water faucet problem and the air-water shock tube problem. Finally, several two dimensional problems will show the capability to capture enormous details and complicated wave patterns in flows having large disparities in the fluid density and velocities, such as interactions between water shock wave and air bubble, between air shock wave and water column(s), and underwater explosion
An accurate and simple large signal model of HEMT
DEFF Research Database (Denmark)
Liu, Qing
1989-01-01
A large-signal model of discrete HEMTs (high-electron-mobility transistors) has been developed. It is simple and suitable for SPICE simulation of hybrid digital ICs. The model parameters are extracted by using computer programs and data provided by the manufacturer. Based on this model, a hybrid...
Sparsity enabled cluster reduced-order models for control
Kaiser, Eurika; Morzyński, Marek; Daviller, Guillaume; Kutz, J. Nathan; Brunton, Bingni W.; Brunton, Steven L.
2018-01-01
Characterizing and controlling nonlinear, multi-scale phenomena are central goals in science and engineering. Cluster-based reduced-order modeling (CROM) was introduced to exploit the underlying low-dimensional dynamics of complex systems. CROM builds a data-driven discretization of the Perron-Frobenius operator, resulting in a probabilistic model for ensembles of trajectories. A key advantage of CROM is that it embeds nonlinear dynamics in a linear framework, which enables the application of standard linear techniques to the nonlinear system. CROM is typically computed on high-dimensional data; however, access to and computations on this full-state data limit the online implementation of CROM for prediction and control. Here, we address this key challenge by identifying a small subset of critical measurements to learn an efficient CROM, referred to as sparsity-enabled CROM. In particular, we leverage compressive measurements to faithfully embed the cluster geometry and preserve the probabilistic dynamics. Further, we show how to identify fewer optimized sensor locations tailored to a specific problem that outperform random measurements. Both of these sparsity-enabled sensing strategies significantly reduce the burden of data acquisition and processing for low-latency in-time estimation and control. We illustrate this unsupervised learning approach on three different high-dimensional nonlinear dynamical systems from fluids with increasing complexity, with one application in flow control. Sparsity-enabled CROM is a critical facilitator for real-time implementation on high-dimensional systems where full-state information may be inaccessible.
Reduced order surrogate modelling (ROSM) of high dimensional deterministic simulations
Mitry, Mina
Often, computationally expensive engineering simulations can prohibit the engineering design process. As a result, designers may turn to a less computationally demanding approximate, or surrogate, model to facilitate their design process. However, owing to the the curse of dimensionality, classical surrogate models become too computationally expensive for high dimensional data. To address this limitation of classical methods, we develop linear and non-linear Reduced Order Surrogate Modelling (ROSM) techniques. Two algorithms are presented, which are based on a combination of linear/kernel principal component analysis and radial basis functions. These algorithms are applied to subsonic and transonic aerodynamic data, as well as a model for a chemical spill in a channel. The results of this thesis show that ROSM can provide a significant computational benefit over classical surrogate modelling, sometimes at the expense of a minor loss in accuracy.
Optimized efficiency in InP nanowire solar cells with accurate 1D analysis
Chen, Yang; Kivisaari, Pyry; Pistol, Mats-Erik; Anttu, Nicklas
2018-01-01
Semiconductor nanowire arrays are a promising candidate for next generation solar cells due to enhanced absorption and reduced material consumption. However, to optimize their performance, time consuming three-dimensional (3D) opto-electronics modeling is usually performed. Here, we develop an accurate one-dimensional (1D) modeling method for the analysis. The 1D modeling is about 400 times faster than 3D modeling and allows direct application of concepts from planar pn-junctions on the analysis of nanowire solar cells. We show that the superposition principle can break down in InP nanowires due to strong surface recombination in the depletion region, giving rise to an IV-behavior similar to that with low shunt resistance. Importantly, we find that the open-circuit voltage of nanowire solar cells is typically limited by contact leakage. Therefore, to increase the efficiency, we have investigated the effect of high-bandgap GaP carrier-selective contact segments at the top and bottom of the InP nanowire and we find that GaP contact segments improve the solar cell efficiency. Next, we discuss the merit of p-i-n and p-n junction concepts in nanowire solar cells. With GaP carrier selective top and bottom contact segments in the InP nanowire array, we find that a p-n junction design is superior to a p-i-n junction design. We predict a best efficiency of 25% for a surface recombination velocity of 4500 cm s-1, corresponding to a non-radiative lifetime of 1 ns in p-n junction cells. The developed 1D model can be used for general modeling of axial p-n and p-i-n junctions in semiconductor nanowires. This includes also LED applications and we expect faster progress in device modeling using our method.
Multi-resolution voxel phantom modeling: a high-resolution eye model for computational dosimetry.
Caracappa, Peter F; Rhodes, Ashley; Fiedler, Derek
2014-09-21
Voxel models of the human body are commonly used for simulating radiation dose with a Monte Carlo radiation transport code. Due to memory limitations, the voxel resolution of these computational phantoms is typically too large to accurately represent the dimensions of small features such as the eye. Recently reduced recommended dose limits to the lens of the eye, which is a radiosensitive tissue with a significant concern for cataract formation, has lent increased importance to understanding the dose to this tissue. A high-resolution eye model is constructed using physiological data for the dimensions of radiosensitive tissues, and combined with an existing set of whole-body models to form a multi-resolution voxel phantom, which is used with the MCNPX code to calculate radiation dose from various exposure types. This phantom provides an accurate representation of the radiation transport through the structures of the eye. Two alternate methods of including a high-resolution eye model within an existing whole-body model are developed. The accuracy and performance of each method is compared against existing computational phantoms.
Startle stimuli reduce the internal model control in discrete movements.
Wright, Zachary A; Rogers, Mark W; MacKinnon, Colum D; Patton, James L
2009-01-01
A well known and major component of movement control is the feedforward component, also known as the internal model. This model predicts and compensates for expected forces seen during a movement, based on recent experience, so that a well-learned task such as reaching to a target can be executed in a smooth straight manner. It has recently been shown that the state of preparation of planned movements can be tested using a startling acoustic stimulus (SAS). SAS, presented 500, 250 or 0 ms before the expected "go" cue resulted in the early release of the movement trajectory associated with the after-effects of the force field training (i.e. the internal model). In a typical motor adaptation experiment with a robot-applied force field, we tested if a SAS stimulus influences the size of after-effects that are typically seen. We found that in all subjects the after-effect magnitudes were significantly reduced when movements were released by SAS, although this effect was not further modulated by the timing of SAS. Reduced after-effects reveal at least partial existence of learned preparatory control, and identify startle effects that could influence performance in tasks such as piloting, teleoperation, and sports.
Experimental Evaluation of Acoustic Engine Liner Models Developed with COMSOL Multiphysics
Schiller, Noah H.; Jones, Michael G.; Bertolucci, Brandon
2017-01-01
Accurate modeling tools are needed to design new engine liners capable of reducing aircraft noise. The purpose of this study is to determine if a commercially-available finite element package, COMSOL Multiphysics, can be used to accurately model a range of different acoustic engine liner designs, and in the process, collect and document a benchmark dataset that can be used in both current and future code evaluation activities. To achieve these goals, a variety of liner samples, ranging from conventional perforate-over-honeycomb to extended-reaction designs, were installed in one wall of the grazing flow impedance tube at the NASA Langley Research Center. The liners were exposed to high sound pressure levels and grazing flow, and the effect of the liner on the sound field in the flow duct was measured. These measurements were then compared with predictions. While this report only includes comparisons for a subset of the configurations, the full database of all measurements and predictions is available in electronic format upon request. The results demonstrate that both conventional perforate-over-honeycomb and extended-reaction liners can be accurately modeled using COMSOL. Therefore, this modeling tool can be used with confidence to supplement the current suite of acoustic propagation codes, and ultimately develop new acoustic engine liners designed to reduce aircraft noise.
Data Mining for Efficient and Accurate Large Scale Retrieval of Geophysical Parameters
Obradovic, Z.; Vucetic, S.; Peng, K.; Han, B.
2004-12-01
Our effort is devoted to developing data mining technology for improving efficiency and accuracy of the geophysical parameter retrievals by learning a mapping from observation attributes to the corresponding parameters within the framework of classification and regression. We will describe a method for efficient learning of neural network-based classification and regression models from high-volume data streams. The proposed procedure automatically learns a series of neural networks of different complexities on smaller data stream chunks and then properly combines them into an ensemble predictor through averaging. Based on the idea of progressive sampling the proposed approach starts with a very simple network trained on a very small chunk and then gradually increases the model complexity and the chunk size until the learning performance no longer improves. Our empirical study on aerosol retrievals from data obtained with the MISR instrument mounted at Terra satellite suggests that the proposed method is successful in learning complex concepts from large data streams with near-optimal computational effort. We will also report on a method that complements deterministic retrievals by constructing accurate predictive algorithms and applying them on appropriately selected subsets of observed data. The method is based on developing more accurate predictors aimed to catch global and local properties synthesized in a region. The procedure starts by learning the global properties of data sampled over the entire space, and continues by constructing specialized models on selected localized regions. The global and local models are integrated through an automated procedure that determines the optimal trade-off between the two components with the objective of minimizing the overall mean square errors over a specific region. Our experimental results on MISR data showed that the combined model can increase the retrieval accuracy significantly. The preliminary results on various
Computer-based personality judgments are more accurate than those made by humans.
Youyou, Wu; Kosinski, Michal; Stillwell, David
2015-01-27
Judging others' personalities is an essential skill in successful social living, as personality is a key driver behind people's interactions, behaviors, and emotions. Although accurate personality judgments stem from social-cognitive skills, developments in machine learning show that computer models can also make valid judgments. This study compares the accuracy of human and computer-based personality judgments, using a sample of 86,220 volunteers who completed a 100-item personality questionnaire. We show that (i) computer predictions based on a generic digital footprint (Facebook Likes) are more accurate (r = 0.56) than those made by the participants' Facebook friends using a personality questionnaire (r = 0.49); (ii) computer models show higher interjudge agreement; and (iii) computer personality judgments have higher external validity when predicting life outcomes such as substance use, political attitudes, and physical health; for some outcomes, they even outperform the self-rated personality scores. Computers outpacing humans in personality judgment presents significant opportunities and challenges in the areas of psychological assessment, marketing, and privacy.
Evaluation of reduced chemical kinetic mechanisms used for modeling mild combustion for natural gas
Directory of Open Access Journals (Sweden)
Hamdi Mohamed
2009-01-01
Full Text Available A numerical and parametric study was performed to evaluate the potential of reduced chemistry mechanisms to model natural gas chemistry including NOx chemistry under mild combustion mode. Two reduced mechanisms, 5-step and 9-step, were tested against the GRI-Mech3.0 by comparing key species, such as NOx, CO2 and CO, and gas temperature predictions in idealized reactors codes under mild combustion conditions. It is thus concluded that the 9-step mechanism appears to be a promising reduced mechanism that can be used in multi-dimensional codes for modeling mild combustion of natural gas.
Geodetic analysis of disputed accurate qibla direction
Saksono, Tono; Fulazzaky, Mohamad Ali; Sari, Zamah
2018-04-01
Muslims perform the prayers facing towards the correct qibla direction would be the only one of the practical issues in linking theoretical studies with practice. The concept of facing towards the Kaaba in Mecca during the prayers has long been the source of controversy among the muslim communities to not only in poor and developing countries but also in developed countries. The aims of this study were to analyse the geodetic azimuths of qibla calculated using three different models of the Earth. The use of ellipsoidal model of the Earth could be the best method for determining the accurate direction of Kaaba from anywhere on the Earth's surface. A muslim cannot direct himself towards the qibla correctly if he cannot see the Kaaba due to setting out process and certain motions during the prayer this can significantly shift the qibla direction from the actual position of the Kaaba. The requirement of muslim prayed facing towards the Kaaba is more as spiritual prerequisite rather than physical evidence.
Reniers, Jorn M.; Mulder, Grietus; Ober-Blöbaum, Sina; Howey, David A.
2018-03-01
The increased deployment of intermittent renewable energy generators opens up opportunities for grid-connected energy storage. Batteries offer significant flexibility but are relatively expensive at present. Battery lifetime is a key factor in the business case, and it depends on usage, but most techno-economic analyses do not account for this. For the first time, this paper quantifies the annual benefits of grid-connected batteries including realistic physical dynamics and nonlinear electrochemical degradation. Three lithium-ion battery models of increasing realism are formulated, and the predicted degradation of each is compared with a large-scale experimental degradation data set (Mat4Bat). A respective improvement in RMS capacity prediction error from 11% to 5% is found by increasing the model accuracy. The three models are then used within an optimal control algorithm to perform price arbitrage over one year, including degradation. Results show that the revenue can be increased substantially while degradation can be reduced by using more realistic models. The estimated best case profit using a sophisticated model is a 175% improvement compared with the simplest model. This illustrates that using a simplistic battery model in a techno-economic assessment of grid-connected batteries might substantially underestimate the business case and lead to erroneous conclusions.
Video-Quality Estimation Based on Reduced-Reference Model Employing Activity-Difference
Yamada, Toru; Miyamoto, Yoshihiro; Senda, Yuzo; Serizawa, Masahiro
This paper presents a Reduced-reference based video-quality estimation method suitable for individual end-user quality monitoring of IPTV services. With the proposed method, the activity values for individual given-size pixel blocks of an original video are transmitted to end-user terminals. At the end-user terminals, the video quality of a received video is estimated on the basis of the activity-difference between the original video and the received video. Psychovisual weightings and video-quality score adjustments for fatal degradations are applied to improve estimation accuracy. In addition, low-bit-rate transmission is achieved by using temporal sub-sampling and by transmitting only the lower six bits of each activity value. The proposed method achieves accurate video quality estimation using only low-bit-rate original video information (15kbps for SDTV). The correlation coefficient between actual subjective video quality and estimated quality is 0.901 with 15kbps side information. The proposed method does not need computationally demanding spatial and gain-and-offset registrations. Therefore, it is suitable for real-time video-quality monitoring in IPTV services.
International Nuclear Information System (INIS)
Silva, Goncalo; Talon, Laurent; Ginzburg, Irina
2017-01-01
The present contribution focuses on the accuracy of reflection-type boundary conditions in the Stokes–Brinkman–Darcy modeling of porous flows solved with the lattice Boltzmann method (LBM), which we operate with the two-relaxation-time (TRT) collision and the Brinkman-force based scheme (BF), called BF-TRT scheme. In parallel, we compare it with the Stokes–Brinkman–Darcy linear finite element method (FEM) where the Dirichlet boundary conditions are enforced on grid vertices. In bulk, both BF-TRT and FEM share the same defect: in their discretization a correction to the modeled Brinkman equation appears, given by the discrete Laplacian of the velocity-proportional resistance force. This correction modifies the effective Brinkman viscosity, playing a crucial role in the triggering of spurious oscillations in the bulk solution. While the exact form of this defect is available in lattice-aligned, straight or diagonal, flows; in arbitrary flow/lattice orientations its approximation is constructed. At boundaries, we verify that such a Brinkman viscosity correction has an even more harmful impact. Already at the first order, it shifts the location of the no-slip wall condition supported by traditional LBM boundary schemes, such as the bounce-back rule. For that reason, this work develops a new class of boundary schemes to prescribe the Dirichlet velocity condition at an arbitrary wall/boundary-node distance and that supports a higher order accuracy in the accommodation of the TRT-Brinkman solutions. For their modeling, we consider the standard BF scheme and its improved version, called IBF; this latter is generalized in this work to suppress or to reduce the viscosity correction in arbitrarily oriented flows. Our framework extends the one- and two-point families of linear and parabolic link-wise boundary schemes, respectively called B-LI and B-MLI, which avoid the interference of the Brinkman viscosity correction in their closure relations. The performance of LBM
Energy Technology Data Exchange (ETDEWEB)
Silva, Goncalo, E-mail: goncalo.nuno.silva@gmail.com [Irstea, Antony Regional Centre, HBAN, 1 rue Pierre-Gilles de Gennes CS 10030, 92761 Antony cedex (France); Talon, Laurent, E-mail: talon@fast.u-psud.fr [CNRS (UMR 7608), Laboratoire FAST, Batiment 502, Campus University, 91405 Orsay (France); Ginzburg, Irina, E-mail: irina.ginzburg@irstea.fr [Irstea, Antony Regional Centre, HBAN, 1 rue Pierre-Gilles de Gennes CS 10030, 92761 Antony cedex (France)
2017-04-15
The present contribution focuses on the accuracy of reflection-type boundary conditions in the Stokes–Brinkman–Darcy modeling of porous flows solved with the lattice Boltzmann method (LBM), which we operate with the two-relaxation-time (TRT) collision and the Brinkman-force based scheme (BF), called BF-TRT scheme. In parallel, we compare it with the Stokes–Brinkman–Darcy linear finite element method (FEM) where the Dirichlet boundary conditions are enforced on grid vertices. In bulk, both BF-TRT and FEM share the same defect: in their discretization a correction to the modeled Brinkman equation appears, given by the discrete Laplacian of the velocity-proportional resistance force. This correction modifies the effective Brinkman viscosity, playing a crucial role in the triggering of spurious oscillations in the bulk solution. While the exact form of this defect is available in lattice-aligned, straight or diagonal, flows; in arbitrary flow/lattice orientations its approximation is constructed. At boundaries, we verify that such a Brinkman viscosity correction has an even more harmful impact. Already at the first order, it shifts the location of the no-slip wall condition supported by traditional LBM boundary schemes, such as the bounce-back rule. For that reason, this work develops a new class of boundary schemes to prescribe the Dirichlet velocity condition at an arbitrary wall/boundary-node distance and that supports a higher order accuracy in the accommodation of the TRT-Brinkman solutions. For their modeling, we consider the standard BF scheme and its improved version, called IBF; this latter is generalized in this work to suppress or to reduce the viscosity correction in arbitrarily oriented flows. Our framework extends the one- and two-point families of linear and parabolic link-wise boundary schemes, respectively called B-LI and B-MLI, which avoid the interference of the Brinkman viscosity correction in their closure relations. The performance of LBM
International Nuclear Information System (INIS)
Feng, Y.; Sardei, F.; Kisslinger, J.
2005-01-01
The paper presents a new simple and accurate numerical field-line mapping technique providing a high-quality representation of field lines as required by a Monte Carlo modeling of plasma edge transport in the complex magnetic boundaries of three-dimensional (3D) toroidal fusion devices. Using a toroidal sequence of precomputed 3D finite flux-tube meshes, the method advances field lines through a simple bilinear, forward/backward symmetric interpolation at the interfaces between two adjacent flux tubes. It is a reversible field-line mapping (RFLM) algorithm ensuring a continuous and unique reconstruction of field lines at any point of the 3D boundary. The reversibility property has a strong impact on the efficiency of modeling the highly anisotropic plasma edge transport in general closed or open configurations of arbitrary ergodicity as it avoids artificial cross-field diffusion of the fast parallel transport. For stellarator-symmetric magnetic configurations, which are the standard case for stellarators, the reversibility additionally provides an average cancellation of the radial interpolation errors of field lines circulating around closed magnetic flux surfaces. The RFLM technique has been implemented in the 3D edge transport code EMC3-EIRENE and is used routinely for plasma transport modeling in the boundaries of several low-shear and high-shear stellarators as well as in the boundary of a tokamak with 3D magnetic edge perturbations
Energy Technology Data Exchange (ETDEWEB)
Lynch, A.H.; McIlwaine, S. [PAOS/CIRES, Univ. of Colorado, Boulder, CO (United States); Beringer, J. [Inst. of Arctic Biology, Univ. of Alaska, Fairbanks (United States); Bonan, G.B. [National Center for Atmospheric Research, Boulder, CO (United States)
2001-05-01
In an illustration of a model evaluation methodology, a multivariate reduced form model is developed to evaluate the sensitivity of a land surface model to changes in atmospheric forcing. The reduced form model is constructed in terms of a set of ten integrative response metrics, including the timing of spring snow melt, sensible and latent heat fluxes in summer, and soil temperature. The responses are evaluated as a function of a selected set of six atmospheric forcing perturbations which are varied simultaneously, and hence each may be thought of as a six-dimensional response surface. The sensitivities of the land surface model are interdependent and in some cases illustrate a physically plausible feedback process. The important predictors of land surface response in a changing climate are the atmospheric temperature and downwelling longwave radiation. Scenarios characterized by warming and drying produce a large relative response compared to warm, moist scenarios. The insensitivity of the model to increases in precipitation and atmospheric humidity is expected to change in applications to coupled models, since these parameters are also strongly implicated, through the representation of clouds, in the simulation of both longwave and shortwave radiation. (orig.)
Accurate estimation of dose distributions inside an eye irradiated with 106Ru plaques
International Nuclear Information System (INIS)
Brualla, L.; Sauerwein, W.; Sempau, J.; Zaragoza, F.J.; Wittig, A.
2013-01-01
Background: Irradiation of intraocular tumors requires dedicated techniques, such as brachytherapy with 106 Ru plaques. The currently available treatment planning system relies on the assumption that the eye is a homogeneous water sphere and on simplified radiation transport physics. However, accurate dose distributions and their assessment demand better models for both the eye and the physics. Methods: The Monte Carlo code PENELOPE, conveniently adapted to simulate the beta decay of 106 Ru over 106 Rh into 106 Pd, was used to simulate radiation transport based on a computerized tomography scan of a patient's eye. A detailed geometrical description of two plaques (models CCA and CCB) from the manufacturer BEBIG was embedded in the computerized tomography scan. Results: The simulations were firstly validated by comparison with experimental results in a water phantom. Dose maps were computed for three plaque locations on the eyeball. From these maps, isodose curves and cumulative dose-volume histograms in the eye and for the structures at risk were assessed. For example, it was observed that a 4-mm anterior displacement with respect to a posterior placement of a CCA plaque for treating a posterior tumor would reduce from 40 to 0% the volume of the optic disc receiving more than 80 Gy. Such a small difference in anatomical position leads to a change in the dose that is crucial for side effects, especially with respect to visual acuity. The radiation oncologist has to bring these large changes in absorbed dose in the structures at risk to the attention of the surgeon, especially when the plaque has to be positioned close to relevant tissues. Conclusion: The detailed geometry of an eye plaque in computerized and segmented tomography of a realistic patient phantom was simulated accurately. Dose-volume histograms for relevant anatomical structures of the eye and the orbit were obtained with unprecedented accuracy. This represents an important step toward an optimized
An efficient and accurate 3D displacements tracking strategy for digital volume correlation
Pan, Bing; Wang, Bo; Wu, Dafang; Lubineau, Gilles
2014-07-01
Owing to its inherent computational complexity, practical implementation of digital volume correlation (DVC) for internal displacement and strain mapping faces important challenges in improving its computational efficiency. In this work, an efficient and accurate 3D displacement tracking strategy is proposed for fast DVC calculation. The efficiency advantage is achieved by using three improvements. First, to eliminate the need of updating Hessian matrix in each iteration, an efficient 3D inverse compositional Gauss-Newton (3D IC-GN) algorithm is introduced to replace existing forward additive algorithms for accurate sub-voxel displacement registration. Second, to ensure the 3D IC-GN algorithm that converges accurately and rapidly and avoid time-consuming integer-voxel displacement searching, a generalized reliability-guided displacement tracking strategy is designed to transfer accurate and complete initial guess of deformation for each calculation point from its computed neighbors. Third, to avoid the repeated computation of sub-voxel intensity interpolation coefficients, an interpolation coefficient lookup table is established for tricubic interpolation. The computational complexity of the proposed fast DVC and the existing typical DVC algorithms are first analyzed quantitatively according to necessary arithmetic operations. Then, numerical tests are performed to verify the performance of the fast DVC algorithm in terms of measurement accuracy and computational efficiency. The experimental results indicate that, compared with the existing DVC algorithm, the presented fast DVC algorithm produces similar precision and slightly higher accuracy at a substantially reduced computational cost.
An efficient and accurate 3D displacements tracking strategy for digital volume correlation
Pan, Bing
2014-07-01
Owing to its inherent computational complexity, practical implementation of digital volume correlation (DVC) for internal displacement and strain mapping faces important challenges in improving its computational efficiency. In this work, an efficient and accurate 3D displacement tracking strategy is proposed for fast DVC calculation. The efficiency advantage is achieved by using three improvements. First, to eliminate the need of updating Hessian matrix in each iteration, an efficient 3D inverse compositional Gauss-Newton (3D IC-GN) algorithm is introduced to replace existing forward additive algorithms for accurate sub-voxel displacement registration. Second, to ensure the 3D IC-GN algorithm that converges accurately and rapidly and avoid time-consuming integer-voxel displacement searching, a generalized reliability-guided displacement tracking strategy is designed to transfer accurate and complete initial guess of deformation for each calculation point from its computed neighbors. Third, to avoid the repeated computation of sub-voxel intensity interpolation coefficients, an interpolation coefficient lookup table is established for tricubic interpolation. The computational complexity of the proposed fast DVC and the existing typical DVC algorithms are first analyzed quantitatively according to necessary arithmetic operations. Then, numerical tests are performed to verify the performance of the fast DVC algorithm in terms of measurement accuracy and computational efficiency. The experimental results indicate that, compared with the existing DVC algorithm, the presented fast DVC algorithm produces similar precision and slightly higher accuracy at a substantially reduced computational cost. © 2014 Elsevier Ltd.
Free surface modelling with two-fluid model and reduced numerical diffusion of the interface
International Nuclear Information System (INIS)
Strubelj, Luka; Tiselj, Izrok
2008-01-01
Full text of publication follows: The free surface flows are successfully modelled with one of existing free surface models, such as: level set method, volume of fluid method (with/without surface reconstruction), front tracking, two-fluid model (two momentum equations) with modified interphase force and others. The main disadvantage of two-fluid model used for simulations of free surface flows is numerical diffusion of the interface, which can be significantly reduced using the method presented in this paper. Several techniques for reduction of numerical diffusion of the interface have been implemented in the volume of fluid model and are based on modified numerical schemes for advection of volume fraction near the interface. The same approach could be used also for two-fluid method, but according to our experience more successful reduction of numerical diffusion of the interface can be achieved with conservative level set method. Within the conservative level set method, continuity equation for volume fraction is solved and after that the numerical diffusion of the interface is reduced in such a way that the thickness of the interface is kept constant during the simulation. Reduction of the interface diffusion can be also called interface sharpening. In present paper the two-fluid model with interface sharpening is validated on Rayleigh-Taylor instability. Under assumptions of isothermal and incompressible flow of two immiscible fluids, we simulated a system with the fluid of higher density located above the fluid of smaller density in two dimensions. Due to gravity in the system, fluid with higher density moves below the fluid with smaller density. Initial condition is not a flat interface between the fluids, but a sine wave with small amplitude, which develops into a mushroom-like structure. Mushroom-like structure in simulation of Rayleigh-Taylor instability later develops to small droplets as result of numerical dispersion of interface (interface sharpening
Ji, Songsong; Yang, Yibo; Pang, Gang; Antoine, Xavier
2018-01-01
The aim of this paper is to design some accurate artificial boundary conditions for the semi-discretized linear Schrödinger and heat equations in rectangular domains. The Laplace transform in time and discrete Fourier transform in space are applied to get Green's functions of the semi-discretized equations in unbounded domains with single-source. An algorithm is given to compute these Green's functions accurately through some recurrence relations. Furthermore, the finite-difference method is used to discretize the reduced problem with accurate boundary conditions. Numerical simulations are presented to illustrate the accuracy of our method in the case of the linear Schrödinger and heat equations. It is shown that the reflection at the corners is correctly eliminated.
International Nuclear Information System (INIS)
Fu, Y; Xu, O; Yang, W; Zhou, L; Wang, J
2017-01-01
To investigate time-variant and nonlinear characteristics in industrial processes, a soft sensor modelling method based on time difference, moving-window recursive partial least square (PLS) and adaptive model updating is proposed. In this method, time difference values of input and output variables are used as training samples to construct the model, which can reduce the effects of the nonlinear characteristic on modelling accuracy and retain the advantages of recursive PLS algorithm. To solve the high updating frequency of the model, a confidence value is introduced, which can be updated adaptively according to the results of the model performance assessment. Once the confidence value is updated, the model can be updated. The proposed method has been used to predict the 4-carboxy-benz-aldehyde (CBA) content in the purified terephthalic acid (PTA) oxidation reaction process. The results show that the proposed soft sensor modelling method can reduce computation effectively, improve prediction accuracy by making use of process information and reflect the process characteristics accurately. (paper)
Accurate localization of intracavitary brachytherapy applicators from 3D CT imaging studies
International Nuclear Information System (INIS)
Lerma, F.A.; Williamson, J.F.
2002-01-01
Purpose: To present an accurate method to identify the positions and orientations of intracavitary (ICT) brachytherapy applicators imaged in 3D CT scans, in support of Monte Carlo photon-transport simulations, enabling accurate dose modeling in the presence of applicator shielding and interapplicator attenuation. Materials and methods: The method consists of finding the transformation that maximizes the coincidence between the known 3D shapes of each applicator component (colpostats and tandem) with the volume defined by contours of the corresponding surface on each CT slice. We use this technique to localize Fletcher-Suit CT-compatible applicators for three cervix cancer patients using post-implant CT examinations (3 mm slice thickness and separation). Dose distributions in 1-to-1 registration with the underlying CT anatomy are derived from 3D Monte Carlo photon-transport simulations incorporating each applicator's internal geometry (source encapsulation, high-density shields, and applicator body) oriented in relation to the dose matrix according to the measured localization transformations. The precision and accuracy of our localization method are assessed using CT scans, in which the positions and orientations of dense rods and spheres (in a precision-machined phantom) were measured at various orientations relative to the gantry. Results: Using this method, we register 3D Monte Carlo dose calculations directly onto post insertion patient CT studies. Using CT studies of a precisely machined phantom, the absolute accuracy of the method was found to be ±0.2 mm in plane, and ±0.3 mm in the axial direction while its precision was ±0.2 mm in plane, and ±0.2 mm axially. Conclusion: We have developed a novel, and accurate technique to localize intracavitary brachytherapy applicators in 3D CT imaging studies, which supports 3D dose planning involving detailed 3D Monte Carlo dose calculations, modeling source positions, shielding and interapplicator shielding
Predictive modeling and reducing cyclic variability in autoignition engines
Hellstrom, Erik; Stefanopoulou, Anna; Jiang, Li; Larimore, Jacob
2016-08-30
Methods and systems are provided for controlling a vehicle engine to reduce cycle-to-cycle combustion variation. A predictive model is applied to predict cycle-to-cycle combustion behavior of an engine based on observed engine performance variables. Conditions are identified, based on the predicted cycle-to-cycle combustion behavior, that indicate high cycle-to-cycle combustion variation. Corrective measures are then applied to prevent the predicted high cycle-to-cycle combustion variation.
Models for Battery Reliability and Lifetime
Energy Technology Data Exchange (ETDEWEB)
Smith, K.; Wood, E.; Santhanagopalan, S.; Kim, G. H.; Neubauer, J.; Pesaran, A.
2014-03-01
Models describing battery degradation physics are needed to more accurately understand how battery usage and next-generation battery designs can be optimized for performance and lifetime. Such lifetime models may also reduce the cost of battery aging experiments and shorten the time required to validate battery lifetime. Models for chemical degradation and mechanical stress are reviewed. Experimental analysis of aging data from a commercial iron-phosphate lithium-ion (Li-ion) cell elucidates the relative importance of several mechanical stress-induced degradation mechanisms.
Effective and accurate processing and inversion of airborne electromagnetic data
DEFF Research Database (Denmark)
Auken, Esben; Christiansen, Anders Vest; Andersen, Kristoffer Rønne
Airborne electromagnetic (AEM) data is used throughout the world for mapping of mineral targets and groundwater resources. The development of technology and inversion algorithms has been tremendously over the last decade and results from these surveys are high-resolution images of the subsurface....... In this keynote talk, we discuss an effective inversion algorithm, which is both subjected to intense research and development as well as production. This is the well know Laterally Constrained Inversion (LCI) and Spatial Constrained Inversion algorithm. The same algorithm is also used in a voxel setup (3D model......) and for sheet inversions. An integral part of these different model discretization is an accurate modelling of the system transfer function and of auxiliary parameters like flight altitude, bird pitch,etc....
An accurate expression for radial distribution function of the Lennard-Jones fluid
International Nuclear Information System (INIS)
Morsali, Ali; Goharshadi, Elaheh K.; Ali Mansoori, G.; Abbaspour, Mohsen
2005-01-01
A simple and accurate expression for radial distribution function (RDF) of the Lennard-Jones fluid is presented. The expression explicitly states the RDF as a continuous function of reduced interparticle distance, temperature, and density. It satisfies the limiting conditions of zero density and infinite distance imposed by statistical thermodynamics. The distance dependence of this expression is expressed by an equation which contains 11 adjustable parameters. These parameters are fitted to 353 RDF data, obtained by molecular dynamics calculations, and then expressed as functions of reduced distance, temperature and density. This expression, having a total of 65 constants, reproduces the RDF data with an average root-mean-squared deviation of 0.0152 for the range of state variables of 0.5= * = * = * =ρσ 3 are reduced temperature and density, respectively). The expression predicts the pressure and the internal energy of the Lennard-Jones fluid with an uncertainty that is comparable to that obtained directly from the molecular dynamics simulations
A New Multiscale Technique for Time-Accurate Geophysics Simulations
Omelchenko, Y. A.; Karimabadi, H.
2006-12-01
Large-scale geophysics systems are frequently described by multiscale reactive flow models (e.g., wildfire and climate models, multiphase flows in porous rocks, etc.). Accurate and robust simulations of such systems by traditional time-stepping techniques face a formidable computational challenge. Explicit time integration suffers from global (CFL and accuracy) timestep restrictions due to inhomogeneous convective and diffusion processes, as well as closely coupled physical and chemical reactions. Application of adaptive mesh refinement (AMR) to such systems may not be always sufficient since its success critically depends on a careful choice of domain refinement strategy. On the other hand, implicit and timestep-splitting integrations may result in a considerable loss of accuracy when fast transients in the solution become important. To address this issue, we developed an alternative explicit approach to time-accurate integration of such systems: Discrete-Event Simulation (DES). DES enables asynchronous computation by automatically adjusting the CPU resources in accordance with local timescales. This is done by encapsulating flux- conservative updates of numerical variables in the form of events, whose execution and synchronization is explicitly controlled by imposing accuracy and causality constraints. As a result, at each time step DES self- adaptively updates only a fraction of the global system state, which eliminates unnecessary computation of inactive elements. DES can be naturally combined with various mesh generation techniques. The event-driven paradigm results in robust and fast simulation codes, which can be efficiently parallelized via a new preemptive event processing (PEP) technique. We discuss applications of this novel technology to time-dependent diffusion-advection-reaction and CFD models representative of various geophysics applications.
Energy Technology Data Exchange (ETDEWEB)
Gray, Alan [The University of Edinburgh, Edinburgh EH9 3JZ, Scotland (United Kingdom); Harlen, Oliver G. [University of Leeds, Leeds LS2 9JT (United Kingdom); Harris, Sarah A., E-mail: s.a.harris@leeds.ac.uk [University of Leeds, Leeds LS2 9JT (United Kingdom); University of Leeds, Leeds LS2 9JT (United Kingdom); Khalid, Syma; Leung, Yuk Ming [University of Southampton, Southampton SO17 1BJ (United Kingdom); Lonsdale, Richard [Max-Planck-Institut für Kohlenforschung, Kaiser-Wilhelm-Platz 1, 45470 Mülheim an der Ruhr (Germany); Philipps-Universität Marburg, Hans-Meerwein Strasse, 35032 Marburg (Germany); Mulholland, Adrian J. [University of Bristol, Bristol BS8 1TS (United Kingdom); Pearson, Arwen R. [University of Leeds, Leeds LS2 9JT (United Kingdom); University of Hamburg, Hamburg (Germany); Read, Daniel J.; Richardson, Robin A. [University of Leeds, Leeds LS2 9JT (United Kingdom); The University of Edinburgh, Edinburgh EH9 3JZ, Scotland (United Kingdom)
2015-01-01
The current computational techniques available for biomolecular simulation are described, and the successes and limitations of each with reference to the experimental biophysical methods that they complement are presented. Despite huge advances in the computational techniques available for simulating biomolecules at the quantum-mechanical, atomistic and coarse-grained levels, there is still a widespread perception amongst the experimental community that these calculations are highly specialist and are not generally applicable by researchers outside the theoretical community. In this article, the successes and limitations of biomolecular simulation and the further developments that are likely in the near future are discussed. A brief overview is also provided of the experimental biophysical methods that are commonly used to probe biomolecular structure and dynamics, and the accuracy of the information that can be obtained from each is compared with that from modelling. It is concluded that progress towards an accurate spatial and temporal model of biomacromolecules requires a combination of all of these biophysical techniques, both experimental and computational.
Newly developed integrated model to reduce risks in the electricity market
International Nuclear Information System (INIS)
Mo, Birger
2001-01-01
A new model which integrates hydro-scheduling and financial hedging has been developed in cooperation with Norsk Hydro. We believe the new tool will be useful for owners of hydropower plants that want to reduce risks in the power market. The model development started in 1997 and was financed by Norsk Hydro. As of 1998, the main financial contributor has been the Research Council of Norway through a project in the Strategic Institute Programme. (author)
Deeb, Asma; Yousef, Hana; Abdelrahman, Layla; Tomy, Mary; Suliman, Shaker; Attia, Salima; Al Suwaidi, Hana
2016-01-01
Introduction. Diabetic Ketoacidosis (DKA) is a serious complication that can be life-threatening. Management of DKA needs admission in a specialized center and imposes major constraints on hospital resources. Aim. We plan to study the impact of adapting a diabetes-educator care model on reducing the frequency of hospital admission of children and adolescents presenting with DKA. Method. We have proposed a model of care led by diabetes educators for children and adolescents with diabetes. The team consisted of highly trained nurses. The model effectiveness is measured by comparing the rate of hospital admission for DKA over 4-year period to the baseline year prior to implementing the model. Results. There were 158 admissions for DKA over a 5-year period. Number of patients followed up in the outpatient diabetes clinics increased from 37 to 331 patients at the start and the end of the study years. Admission rate showed a downward trend over the five-year period. Percentage of admission for DKA is reduced from 210% to 1.8% (P 0.001). Conclusion. Diabetes educator care model is an effective and a sustainable measure to reduce hospital admission for DKA in children and adolescents.
A new approach to determine accurately minority-carrier lifetime
International Nuclear Information System (INIS)
Idali Oumhand, M.; Mir, Y.; Zazoui, M.
2009-01-01
Electron or proton irradiations introduce recombination centers, which tend to affect solar cell parameters by reducing the minority-carrier lifetime (MCLT). Because this MCLT plays a fundamental role in the performance degradation of solar cells, in this work we present a new approach that allows us to get accurate values of MCLT. The relationship between MCLT in p-region and n-region both before and after irradiation has been determined by the new method. The validity and accuracy of this approach are justified by the fact that the degradation parameters that fit the experimental data are the same for both short-circuit current and the open-circuit voltages. This method is applied to the p + /n-InGaP solar cell under 1 MeV electron irradiation
DEFF Research Database (Denmark)
Mihet-Popa, Lucian; Camacho, Oscar Mauricio Forero; Nørgård, Per Bromand
2013-01-01
This paper presents a battery test platform including two Li-ion battery designed for hybrid and EV applications, and charging/discharging tests under different operating conditions carried out for developing an accurate dynamic electro-thermal model of a high power Li-ion battery pack system....... The aim of the tests has been to study the impact of the battery degradation and to find out the dynamic characteristics of the cells including nonlinear open circuit voltage, series resistance and parallel transient circuit at different charge/discharge currents and cell temperature. An equivalent...... circuit model, based on the runtime battery model and the Thevenin circuit model, with parameters obtained from the tests and depending on SOC, current and temperature has been implemented in MATLAB/Simulink and Power Factory. A good alignment between simulations and measurements has been found....
Modelling the physics in iterative reconstruction for transmission computed tomography
Nuyts, Johan; De Man, Bruno; Fessler, Jeffrey A.; Zbijewski, Wojciech; Beekman, Freek J.
2013-01-01
There is an increasing interest in iterative reconstruction (IR) as a key tool to improve quality and increase applicability of X-ray CT imaging. IR has the ability to significantly reduce patient dose, it provides the flexibility to reconstruct images from arbitrary X-ray system geometries and it allows to include detailed models of photon transport and detection physics, to accurately correct for a wide variety of image degrading effects. This paper reviews discretisation issues and modelling of finite spatial resolution, Compton scatter in the scanned object, data noise and the energy spectrum. Widespread implementation of IR with highly accurate model-based correction, however, still requires significant effort. In addition, new hardware will provide new opportunities and challenges to improve CT with new modelling. PMID:23739261
International Nuclear Information System (INIS)
Paglia, Gianluca; Rohl, Andrew L.; Gale, Julian D.; Buckley, Craig E.
2005-01-01
We have performed an extensive computational study of γ-Al 2 O 3 , beginning with the geometric analysis of approximately 1.47 billion spinel-based structural candidates, followed by derivative method energy minimization calculations of approximately 122 000 structures. Optimization of the spinel-based structural models demonstrated that structures exhibiting nonspinel site occupancy after simulation were more energetically favorable, as suggested in other computational studies. More importantly, none of the spinel structures exhibited simulated diffraction patterns that were characteristic of γ-Al 2 O 3 . This suggests that cations of γ-Al 2 O 3 are not exclusively held in spinel positions, that the spinel model of γ-Al 2 O 3 does not accurately reflect its structure, and that a representative structure cannot be achieved from molecular modeling when the spinel representation is used as the starting structure. The latter two of these three findings are extremely important when trying to accurately model the structure. A second set of starting models were generated with a large number of cations occupying c symmetry positions, based on the findings from recent experiments. Optimization of the new c symmetry-based structural models resulted in simulated diffraction patterns that were characteristic of γ-Al 2 O 3 . The modeling, conducted using supercells, yields a more accurate and complete determination of the defect structure of γ-Al 2 O 3 than can be achieved with current experimental techniques. The results show that on average over 40% of the cations in the structure occupy nonspinel positions, and approximately two-thirds of these occupy c symmetry positions. The structures exhibit variable occupancy in the site positions that follow local symmetry exclusion rules. This variation was predominantly represented by a migration of cations away from a symmetry positions to other tetrahedral site positions during optimization which were found not to affect the
Simulation of local instabilities with the use of reduced order models
International Nuclear Information System (INIS)
Dykin, V.; Demaziere, C.; Lange, C.; Hennig, D.
2011-01-01
The development of an advanced reduced order model (ROM) with four heated channels, taking into account local, regional and core-wide oscillations, is described. The ROM contains three sub-models: a neutron-kinetic model (describing neutron transport), a thermal- hydraulic model (describing the coolant flow) and a heat transfer model (describing heat transfer between the fuel and the coolant). All these three models are coupled to each other, using two feedback mechanisms: void feedback and doppler feedback. Each of the sub-models is described by a set of reduced ordinary differential equations, derived from the corresponding time space-dependent partial differential equations by using different types of approximations and mathematical techniques. All three models were developed from past ROMs and, subsequently, were modified in order to fit the purpose of our investigations. One of the novelties of the present ROM is that it takes into account the effect of the first three neutronic modes, namely the fundamental, the first and the second azimuthal modes, as well as the effect of local oscillations on these modes. In order to have a proper representation of both azimuthal modes, a four heated channel ROM was developed. Another modification, compared to earlier work, is the determination of the coupling reactivity coefficients for both void fraction and fuel temperature, which were calculated explicitly by evaluating cross-section perturbations with the help of the SIMULATE-3 and the CORESIM codes. The ROM was thereafter applied to a channel instability event that occurred at the Swedish Forsmark-1 BWR in 1996/1997. The time signals for each of the modes were generated from the ROM and compared with the measurements, performed at the plant. Some qualitative comparison between the ROM and the measurements was made. The results could bear some significance in understanding the instability event and its coupling mechanism to core-wide oscillations. (author)
Informing Investment to Reduce Inequalities: A Modelling Approach.
Directory of Open Access Journals (Sweden)
Andrew McAuley
Full Text Available Reducing health inequalities is an important policy objective but there is limited quantitative information about the impact of specific interventions.To provide estimates of the impact of a range of interventions on health and health inequalities.Literature reviews were conducted to identify the best evidence linking interventions to mortality and hospital admissions. We examined interventions across the determinants of health: a 'living wage'; changes to benefits, taxation and employment; active travel; tobacco taxation; smoking cessation, alcohol brief interventions, and weight management services. A model was developed to estimate mortality and years of life lost (YLL in intervention and comparison populations over a 20-year time period following interventions delivered only in the first year. We estimated changes in inequalities using the relative index of inequality (RII.Introduction of a 'living wage' generated the largest beneficial health impact, with modest reductions in health inequalities. Benefits increases had modest positive impacts on health and health inequalities. Income tax increases had negative impacts on population health but reduced inequalities, while council tax increases worsened both health and health inequalities. Active travel increases had minimally positive effects on population health but widened health inequalities. Increases in employment reduced inequalities only when targeted to the most deprived groups. Tobacco taxation had modestly positive impacts on health but little impact on health inequalities. Alcohol brief interventions had modestly positive impacts on health and health inequalities only when strongly socially targeted, while smoking cessation and weight-reduction programmes had minimal impacts on health and health inequalities even when socially targeted.Interventions have markedly different effects on mortality, hospitalisations and inequalities. The most effective (and likely cost
Accurate wind farm development and operation. Advanced wake modelling
Energy Technology Data Exchange (ETDEWEB)
Brand, A.; Bot, E.; Ozdemir, H. [ECN Unit Wind Energy, P.O. Box 1, NL 1755 ZG Petten (Netherlands); Steinfeld, G.; Drueke, S.; Schmidt, M. [ForWind, Center for Wind Energy Research, Carl von Ossietzky Universitaet Oldenburg, D-26129 Oldenburg (Germany); Mittelmeier, N. REpower Systems SE, D-22297 Hamburg (Germany))
2013-11-15
The ability is demonstrated to calculate wind farm wakes on the basis of ambient conditions that were calculated with an atmospheric model. Specifically, comparisons are described between predicted and observed ambient conditions, and between power predictions from three wind farm wake models and power measurements, for a single and a double wake situation. The comparisons are based on performance indicators and test criteria, with the objective to determine the percentage of predictions that fall within a given range about the observed value. The Alpha Ventus site is considered, which consists of a wind farm with the same name and the met mast FINO1. Data from the 6 REpower wind turbines and the FINO1 met mast were employed. The atmospheric model WRF predicted the ambient conditions at the location and the measurement heights of the FINO1 mast. May the predictability of the wind speed and the wind direction be reasonable if sufficiently sized tolerances are employed, it is fairly impossible to predict the ambient turbulence intensity and vertical shear. Three wind farm wake models predicted the individual turbine powers: FLaP-Jensen and FLaP-Ainslie from ForWind Oldenburg, and FarmFlow from ECN. The reliabilities of the FLaP-Ainslie and the FarmFlow wind farm wake models are of equal order, and higher than FLaP-Jensen. Any difference between the predictions from these models is most clear in the double wake situation. Here FarmFlow slightly outperforms FLaP-Ainslie.
Modeling of automotive driveline system for reducing gear rattles
Shangguan, Wen-Bin; Liu, Xue-Lai; Yin, Yuming; Rakheja, Subhash
2018-03-01
A nonlinear torsional model for a driveline system with 4 degrees of freedom is proposed for studying gear rattle if a car is at idle. The time-varying meshing stiffness of geared teeth, gear backlash, and the damping from oil film are included in the model. The dynamic responses of the driveline system, such as clutch angular displacement, meshing force and relative displacement between geared teeth, are calculated using the presented model. The influences of stiffness and damping of a clutch on gear rattle of geared teeth in a generic transmission are investigated. Based on the calculation and analysis results, a design guideline to select clutch's stiffness and damping is developed to reduce gear rattle for a car at idle. Taking a generic driveline system of a passenger car as an example, the developed method is experimentally validated by comparing the baseline clutch and revised clutch, in terms of the measured noise inside engine compartment and cab and vibrations at transmission housing.
McLawhorn, Alexander S; Carroll, Kaitlin M; Blevins, Jason L; DeNegre, Scott T; Mayman, David J; Jerabek, Seth A
2015-10-01
Template-directed instrumentation (TDI) for total knee arthroplasty (TKA) may streamline operating room (OR) workflow and reduce costs by preselecting implants and minimizing instrument tray burden. A decision model simulated the economics of TDI. Sensitivity analyses determined thresholds for model variables to ensure TDI success. A clinical pilot was reviewed. The accuracy of preoperative templates was validated, and 20 consecutive primary TKAs were performed using TDI. The model determined that preoperative component size estimation should be accurate to ±1 implant size for 50% of TKAs to implement TDI. The pilot showed that preoperative template accuracy exceeded 97%. There were statistically significant improvements in OR turnover time and in-room time for TDI compared to an historical cohort of TKAs. TDI reduces costs and improves OR efficiency. Copyright © 2015 Elsevier Inc. All rights reserved.
Tobacco Town: Computational Modeling of Policy Options to Reduce Tobacco Retailer Density.
Luke, Douglas A; Hammond, Ross A; Combs, Todd; Sorg, Amy; Kasman, Matt; Mack-Crane, Austen; Ribisl, Kurt M; Henriksen, Lisa
2017-05-01
To identify the behavioral mechanisms and effects of tobacco control policies designed to reduce tobacco retailer density. We developed the Tobacco Town agent-based simulation model to examine 4 types of retailer reduction policies: (1) random retailer reduction, (2) restriction by type of retailer, (3) limiting proximity of retailers to schools, and (4) limiting proximity of retailers to each other. The model examined the effects of these policies alone and in combination across 4 different types of towns, defined by 2 levels of population density (urban vs suburban) and 2 levels of income (higher vs lower). Model results indicated that reduction of retailer density has the potential to decrease accessibility of tobacco products by driving up search and purchase costs. Policy effects varied by town type: proximity policies worked better in dense, urban towns whereas retailer type and random retailer reduction worked better in less-dense, suburban settings. Comprehensive retailer density reduction policies have excellent potential to reduce the public health burden of tobacco use in communities.
Afzal, Mohammad Atif Faiz; Cheng, Chong; Hachmann, Johannes
2018-06-01
Organic materials with a high index of refraction (RI) are attracting considerable interest due to their potential application in optic and optoelectronic devices. However, most of these applications require an RI value of 1.7 or larger, while typical carbon-based polymers only exhibit values in the range of 1.3-1.5. This paper introduces an efficient computational protocol for the accurate prediction of RI values in polymers to facilitate in silico studies that can guide the discovery and design of next-generation high-RI materials. Our protocol is based on the Lorentz-Lorenz equation and is parametrized by the polarizability and number density values of a given candidate compound. In the proposed scheme, we compute the former using first-principles electronic structure theory and the latter using an approximation based on van der Waals volumes. The critical parameter in the number density approximation is the packing fraction of the bulk polymer, for which we have devised a machine learning model. We demonstrate the performance of the proposed RI protocol by testing its predictions against the experimentally known RI values of 112 optical polymers. Our approach to combine first-principles and data modeling emerges as both a successful and a highly economical path to determining the RI values for a wide range of organic polymers.
de Léséleuc, Sylvain; Weber, Sebastian; Lienhard, Vincent; Barredo, Daniel; Büchler, Hans Peter; Lahaye, Thierry; Browaeys, Antoine
2018-03-01
We study a system of atoms that are laser driven to n D3 /2 Rydberg states and assess how accurately they can be mapped onto spin-1 /2 particles for the quantum simulation of anisotropic Ising magnets. Using nonperturbative calculations of the pair potentials between two atoms in the presence of electric and magnetic fields, we emphasize the importance of a careful selection of experimental parameters in order to maintain the Rydberg blockade and avoid excitation of unwanted Rydberg states. We benchmark these theoretical observations against experiments using two atoms. Finally, we show that in these conditions, the experimental dynamics observed after a quench is in good agreement with numerical simulations of spin-1 /2 Ising models in systems with up to 49 spins, for which numerical simulations become intractable.
Directory of Open Access Journals (Sweden)
Jie Li
Full Text Available The classical form of α1-antitrypsin deficiency (ATD is associated with hepatic fibrosis and hepatocellular carcinoma. It is caused by the proteotoxic effect of a mutant secretory protein that aberrantly accumulates in the endoplasmic reticulum of liver cells. Recently we developed a model of this deficiency in C. elegans and adapted it for high-content drug screening using an automated, image-based array scanning. Screening of the Library of Pharmacologically Active Compounds identified fluphenazine (Flu among several other compounds as a drug which reduced intracellular accumulation of mutant α1-antitrypsin Z (ATZ. Because it is representative of the phenothiazine drug class that appears to have autophagy enhancer properties in addition to mood stabilizing activity, and can be relatively easily re-purposed, we further investigated its effects on mutant ATZ. The results indicate that Flu reverses the phenotypic effects of ATZ accumulation in the C. elegans model of ATD at doses which increase the number of autophagosomes in vivo. Furthermore, in nanomolar concentrations, Flu enhances the rate of intracellular degradation of ATZ and reduces the cellular ATZ load in mammalian cell line models. In the PiZ mouse model Flu reduces the accumulation of ATZ in the liver and mediates a decrease in hepatic fibrosis. These results show that Flu can reduce the proteotoxicity of ATZ accumulation in vivo and, because it has been used safely in humans, this drug can be moved rapidly into trials for liver disease due to ATD. The results also provide further validation for drug discovery using C. elegans models that can be adapted to high-content drug screening platforms and used together with mammalian cell line and animal models.
Clausner, Tommy; Dalal, Sarang S; Crespo-García, Maité
2017-01-01
The performance of EEG source reconstruction has benefited from the increasing use of advanced head modeling techniques that take advantage of MRI together with the precise positions of the recording electrodes. The prevailing technique for registering EEG electrode coordinates involves electromagnetic digitization. However, the procedure adds several minutes to experiment preparation and typical digitizers may not be accurate enough for optimal source reconstruction performance (Dalal et al., 2014). Here, we present a rapid, accurate, and cost-effective alternative method to register EEG electrode positions, using a single digital SLR camera, photogrammetry software, and computer vision techniques implemented in our open-source toolbox, janus3D . Our approach uses photogrammetry to construct 3D models from multiple photographs of the participant's head wearing the EEG electrode cap. Electrodes are detected automatically or semi-automatically using a template. The rigid facial features from these photo-based models are then surface-matched to MRI-based head reconstructions to facilitate coregistration to MRI space. This method yields a final electrode coregistration error of 0.8 mm, while a standard technique using an electromagnetic digitizer yielded an error of 6.1 mm. The technique furthermore reduces preparation time, and could be extended to a multi-camera array, which would make the procedure virtually instantaneous. In addition to EEG, the technique could likewise capture the position of the fiducial markers used in magnetoencephalography systems to register head position.
International Nuclear Information System (INIS)
Verma, Vibha; Yu, Qiming J.; Connell, Des W.
2015-01-01
The Reduced Life Expectancy (RLE) Model (LC 50 = [ln(NLE) – ln(LT 50 )]/d) has been proposed as an alternative to Haber's Rule. The model is based on a linear relationship between LC 50 (Lethal Exposure Concentration) and lnLT 50 (Lethal Exposure Time) and uses NLE (Normal Life Expectancy) as a limiting point as well as a long term data point (where d is a constant). The purposes of this paper were to compare the RLE Model with Haber's Rule with available toxicity data and to evaluate the strengths and weaknesses of each approach. When LT 50 is relatively short and LC 50 is high, Haber's Rule is consistent with the RLE model. But the difference between the two was evident in the situation when LT 50 is relatively long and LC 50 is low where the RLE model is a marked departure from Haber's Rule. The RLE Model can be used to appropriately evaluate long term effects of exposure. - Highlights: • The strength and weakness of Haber's Rule in relation to the RLE model is needed. • Haber's Rule now used universally is quite inappropriate for environmental toxicity. • Normal life expectancy, a new parameter l is used to evaluate effects of exposure time on toxicity. • According to RLE model when LC 50 approaches zero, then LT 50 = Normal Life Expectancy. • The RLE model can be used to evaluate long term effects of exposure-accurately and easily. - The RLE approach is a more appropriate alternative particularly to evaluate long term effects of exposure. It can be easily used to estimate long term effects of exposure
A forecasting method to reduce estimation bias in self-reported cell phone data.
Redmayne, Mary; Smith, Euan; Abramson, Michael J
2013-01-01
There is ongoing concern that extended exposure to cell phone electromagnetic radiation could be related to an increased risk of negative health effects. Epidemiological studies seek to assess this risk, usually relying on participants' recalled use, but recall is notoriously poor. Our objectives were primarily to produce a forecast method, for use by such studies, to reduce estimation bias in the recalled extent of cell phone use. The method we developed, using Bayes' rule, is modelled with data we collected in a cross-sectional cluster survey exploring cell phone user-habits among New Zealand adolescents. Participants recalled their recent extent of SMS-texting and retrieved from their provider the current month's actual use-to-date. Actual use was taken as the gold standard in the analyses. Estimation bias arose from a large random error, as observed in all cell phone validation studies. We demonstrate that this seriously exaggerates upper-end forecasts of use when used in regression models. This means that calculations using a regression model will lead to underestimation of heavy-users' relative risk. Our Bayesian method substantially reduces estimation bias. In cases where other studies' data conforms to our method's requirements, application should reduce estimation bias, leading to a more accurate relative risk calculation for mid-to-heavy users.
Directory of Open Access Journals (Sweden)
Jianzhong Zhou
2017-12-01
Full Text Available Model simulation and control of pumped storage unit (PSU are essential to improve the dynamic quality of power station. Only under the premise of the PSU models reflecting the actual transient process, the novel control method can be properly applied in the engineering. The contributions of this paper are that (1 a real-time accurate equivalent circuit model (RAECM of PSU via error compensation is proposed to reconcile the conflict between real-time online simulation and accuracy under various operating conditions, and (2 an adaptive predicted fuzzy PID controller (APFPID based on RAECM is put forward to overcome the instability of conventional control under no-load conditions with low water head. Respectively, all hydraulic factors in pipeline system are fully considered based on equivalent lumped-circuits theorem. The pretreatment, which consists of improved Suter-transformation and BP neural network, and online simulation method featured by two iterative loops are synthetically proposed to improve the solving accuracy of the pump-turbine. Moreover, the modified formulas for compensating error are derived with variable-spatial discretization to improve the accuracy of the real-time simulation further. The implicit RadauIIA method is verified to be more suitable for PSUGS owing to wider stable domain. Then, APFPID controller is constructed based on the integration of fuzzy PID and the model predictive control. Rolling prediction by RAECM is proposed to replace rolling optimization with its computational speed guaranteed. Finally, the simulation and on-site measurements are compared to prove trustworthy of RAECM under various running conditions. Comparative experiments also indicate that APFPID controller outperforms other controllers in most cases, especially low water head conditions. Satisfying results of RAECM have been achieved in engineering and it provides a novel model reference for PSUGS.
Computer-based personality judgments are more accurate than those made by humans
Youyou, Wu; Kosinski, Michal; Stillwell, David
2015-01-01
Judging others’ personalities is an essential skill in successful social living, as personality is a key driver behind people’s interactions, behaviors, and emotions. Although accurate personality judgments stem from social-cognitive skills, developments in machine learning show that computer models can also make valid judgments. This study compares the accuracy of human and computer-based personality judgments, using a sample of 86,220 volunteers who completed a 100-item personality questionnaire. We show that (i) computer predictions based on a generic digital footprint (Facebook Likes) are more accurate (r = 0.56) than those made by the participants’ Facebook friends using a personality questionnaire (r = 0.49); (ii) computer models show higher interjudge agreement; and (iii) computer personality judgments have higher external validity when predicting life outcomes such as substance use, political attitudes, and physical health; for some outcomes, they even outperform the self-rated personality scores. Computers outpacing humans in personality judgment presents significant opportunities and challenges in the areas of psychological assessment, marketing, and privacy. PMID:25583507
Dynamic and reduced-dynamic precise orbit determination of satellites in low earth orbits
International Nuclear Information System (INIS)
Swatschina, P.
2009-01-01
The precise positioning of satellites in Low Earth Orbits (LEO) has become a key technology for advanced space missions. Dedicated satellite missions, such as CHAMP, GRACE and GOCE, that aim to map the Earths gravity field and its variation over time with unprecedented accuracy, initiated the demand for highly precise orbit solutions of LEO satellites. Furthermore, a wide range of additional science opportunities opens up with the capability to generate accurate LEO orbits. For all considered satellite missions, the primary measurement system for navigation is a spaceborne GPS receiver. The goal of this thesis is to establish and implement methods for Precise Orbit Determination (POD) of LEO satellites using GPS. Striving for highest precision using yet efficient orbit generation strategies, the attained orbit solutions are aimed to be competitive with the most advanced solutions of other institutions. Dynamic and reduced-dynamic orbit models provide the basic concepts of this work. These orbit models are subsequently adjusted to the highly accurate GPS measurements. The GPS measurements are introduced at the zero difference level in the ionosphere free linear combination. Appropriate procedures for GPS data screening and editing are established to detect erroneous data and to employ measurements of good quality only. For the dynamic orbit model a sophisticated force model, especially designed for LEO satellites, has been developed. In order to overcome the limitations that are induced by the deficiencies of the purely dynamical model, two different types of empirical parameters are introduced into the force model. These reduced-dynamic orbit models allow for the generation of much longer orbital arcs while preserving the spacecraft dynamics to the most possible extent. The two methods for reduced-dynamic orbit modeling are instantaneous velocity changes (pulses) or piecewise constant accelerations. For both techniques highly efficient modeling algorithms are
Low-order aeroelastic models of wind turbines for controller design
DEFF Research Database (Denmark)
Sønderby, Ivan Bergquist
Wind turbine controllers are used to optimize the performance of wind turbines such as to reduce power variations and fatigue and extreme loads on wind turbine components. Accurate tuning and design of modern controllers must be done using low-order models that accurately captures the aeroelastic...... response of the wind turbine. The purpose of this thesis is to investigate the necessary model complexity required in aeroelastic models used for controller design and to analyze and propose methods to design low-order aeroelastic wind turbine models that are suited for model-based control design....... The thesis contains a characterization of the dynamics that influence the open-loop aeroelastic frequency response of a modern wind turbine, based on a high-order aeroelastic wind turbine model. One main finding is that the transfer function from collective pitch to generator speed is affected by two low...
Influential Factors for Accurate Load Prediction in a Demand Response Context
DEFF Research Database (Denmark)
Wollsen, Morten Gill; Kjærgaard, Mikkel Baun; Jørgensen, Bo Nørregaard
2016-01-01
Accurate prediction of a buildings electricity load is crucial to respond to Demand Response events with an assessable load change. However, previous work on load prediction lacks to consider a wider set of possible data sources. In this paper we study different data scenarios to map the inﬂuence....... Next, the time of day that is being predicted greatly inﬂuence the prediction which is related to the weather pattern. By presenting these results we hope to improve the modeling of building loads and algorithms for Demand Response planning.......Accurate prediction of a buildings electricity load is crucial to respond to Demand Response events with an assessable load change. However, previous work on load prediction lacks to consider a wider set of possible data sources. In this paper we study different data scenarios to map the inﬂuence...
Modeling Friction Performance of Drill String Torsional Oscillation Using Dynamic Friction Model
Directory of Open Access Journals (Sweden)
Xingming Wang
2017-01-01
Full Text Available Drill string torsional and longitudinal oscillation can significantly reduce axial drag in horizontal drilling. An improved theoretical model for the analysis of the frictional force was proposed based on microscopic contact deformation theory and a bristle model. The established model, an improved dynamic friction model established for drill strings in a wellbore, was used to determine the relationship of friction force changes and the drill string torsional vibration. The model results were in good agreement with the experimental data, verifying the accuracy of the established model. The analysis of the influence of drilling mud properties indicated that there is an approximately linear relationship between the axial friction force and dynamic shear and viscosity. The influence of drill string torsional oscillation on the axial friction force is discussed. The results indicated that the drill string transverse velocity is a prerequisite for reducing axial friction. In addition, low amplitude of torsional vibration speed can significantly reduce axial friction. Then, increasing the amplitude of transverse vibration speed, the effect of axial reduction is not significant. In addition, by involving general field drilling parameters, this model can accurately describe the friction behavior and quantitatively predict the frictional resistance in horizontal drilling.
Evaporator modeling - A hybrid approach
International Nuclear Information System (INIS)
Ding Xudong; Cai Wenjian; Jia Lei; Wen Changyun
2009-01-01
In this paper, a hybrid modeling approach is proposed to model two-phase flow evaporators. The main procedures for hybrid modeling includes: (1) Based on the energy and material balance, and thermodynamic principles to formulate the process fundamental governing equations; (2) Select input/output (I/O) variables responsible to the system performance which can be measured and controlled; (3) Represent those variables existing in the original equations but are not measurable as simple functions of selected I/Os or constants; (4) Obtaining a single equation which can correlate system inputs and outputs; and (5) Identify unknown parameters by linear or nonlinear least-squares methods. The method takes advantages of both physical and empirical modeling approaches and can accurately predict performance in wide operating range and in real-time, which can significantly reduce the computational burden and increase the prediction accuracy. The model is verified with the experimental data taken from a testing system. The testing results show that the proposed model can predict accurately the performance of the real-time operating evaporator with the maximum error of ±8%. The developed models will have wide applications in operational optimization, performance assessment, fault detection and diagnosis
Disturbance estimation of nuclear power plant by using reduced-order model
International Nuclear Information System (INIS)
Tashima, Shin-ichi; Wakabayashi, Jiro
1983-01-01
An estimation method is proposed of multiplex disturbances which occur in a nuclear power plant. The method is composed of two parts: (i) the identification of a simplified model of multi-input and multi-output to describe the related system response, and (ii) the design of a Kalman filter to estimate the multiplex disturbance. Concerning the simplified model, several observed signals are firstly selected as output variables which can well represent the system response caused by the disturbances. A reduced-order model is utilized for designing the disturbance estimator. This is based on the following two considerations. The first is that the disturbance is assumed to be of a quasistatic nature. The other is based on the intuition that there exist a few dominant modes between the disturbances and the selected observed signals and that most of the non-dominant modes which remain may not affect the accuracy of the disturbance estimator. The reduced-order model is furtherly transformed to a single-output model using a linear combination of the output signals, where the standard procedure of the structural identification is evaded. The parameters of the model thus transformed are calculated by the generalized least square method. As for the multiplex disturbance estimator, the Kalman filtering method is applied by compromising the following three items : (a) quick response to disturbance, (b) reduction of estimation error in the presence of observation noises, and (c) the elimination of cross-interference between the disturbances to the plant and the estimates from the Kalman filter. The effectiveness of the proposed method is verified through some computer experiments using a BWR plant simulator. (author)
A Reduced Order, One Dimensional Model of Joint Response
Energy Technology Data Exchange (ETDEWEB)
DOHNER,JEFFREY L.
2000-11-06
As a joint is loaded, the tangent stiffness of the joint reduces due to slip at interfaces. This stiffness reduction continues until the direction of the applied load is reversed or the total interface slips. Total interface slippage in joints is called macro-slip. For joints not undergoing macro-slip, when load reversal occurs the tangent stiffness immediately rebounds to its maximum value. This occurs due to stiction effects at the interface. Thus, for periodic loads, a softening and rebound hardening cycle is produced which defines a hysteretic, energy absorbing trajectory. For many jointed sub-structures, this hysteretic trajectory can be approximated using simple polynomial representations. This allows for complex joint substructures to be represented using simple non-linear models. In this paper a simple one dimensional model is discussed.
Zuñiga, Cristal; Li, Chien-Ting; Huelsman, Tyler; Levering, Jennifer; Zielinski, Daniel C; McConnell, Brian O; Long, Christopher P; Knoshaug, Eric P; Guarnieri, Michael T; Antoniewicz, Maciek R; Betenbaugh, Michael J; Zengler, Karsten
2016-09-01
The green microalga Chlorella vulgaris has been widely recognized as a promising candidate for biofuel production due to its ability to store high lipid content and its natural metabolic versatility. Compartmentalized genome-scale metabolic models constructed from genome sequences enable quantitative insight into the transport and metabolism of compounds within a target organism. These metabolic models have long been utilized to generate optimized design strategies for an improved production process. Here, we describe the reconstruction, validation, and application of a genome-scale metabolic model for C. vulgaris UTEX 395, iCZ843. The reconstruction represents the most comprehensive model for any eukaryotic photosynthetic organism to date, based on the genome size and number of genes in the reconstruction. The highly curated model accurately predicts phenotypes under photoautotrophic, heterotrophic, and mixotrophic conditions. The model was validated against experimental data and lays the foundation for model-driven strain design and medium alteration to improve yield. Calculated flux distributions under different trophic conditions show that a number of key pathways are affected by nitrogen starvation conditions, including central carbon metabolism and amino acid, nucleotide, and pigment biosynthetic pathways. Furthermore, model prediction of growth rates under various medium compositions and subsequent experimental validation showed an increased growth rate with the addition of tryptophan and methionine. © 2016 American Society of Plant Biologists. All rights reserved.
An Online Method for Interpolating Linear Parametric Reduced-Order Models
Amsallem, David; Farhat, Charbel
2011-01-01
A two-step online method is proposed for interpolating projection-based linear parametric reduced-order models (ROMs) in order to construct a new ROM for a new set of parameter values. The first step of this method transforms each precomputed ROM into a consistent set of generalized coordinates. The second step interpolates the associated linear operators on their appropriate matrix manifold. Real-time performance is achieved by precomputing inner products between the reduced-order bases underlying the precomputed ROMs. The proposed method is illustrated by applications in mechanical and aeronautical engineering. In particular, its robustness is demonstrated by its ability to handle the case where the sampled parameter set values exhibit a mode veering phenomenon. © 2011 Society for Industrial and Applied Mathematics.
Fast and Accurate Prediction of Stratified Steel Temperature During Holding Period of Ladle
Deodhar, Anirudh; Singh, Umesh; Shukla, Rishabh; Gautham, B. P.; Singh, Amarendra K.
2017-04-01
Thermal stratification of liquid steel in a ladle during the holding period and the teeming operation has a direct bearing on the superheat available at the caster and hence on the caster set points such as casting speed and cooling rates. The changes in the caster set points are typically carried out based on temperature measurements at the end of tundish outlet. Thermal prediction models provide advance knowledge of the influence of process and design parameters on the steel temperature at various stages. Therefore, they can be used in making accurate decisions about the caster set points in real time. However, this requires both fast and accurate thermal prediction models. In this work, we develop a surrogate model for the prediction of thermal stratification using data extracted from a set of computational fluid dynamics (CFD) simulations, pre-determined using design of experiments technique. Regression method is used for training the predictor. The model predicts the stratified temperature profile instantaneously, for a given set of process parameters such as initial steel temperature, refractory heat content, slag thickness, and holding time. More than 96 pct of the predicted values are within an error range of ±5 K (±5 °C), when compared against corresponding CFD results. Considering its accuracy and computational efficiency, the model can be extended for thermal control of casting operations. This work also sets a benchmark for developing similar thermal models for downstream processes such as tundish and caster.
Directory of Open Access Journals (Sweden)
Ruixian Fang
2016-09-01
Full Text Available This work uses the adjoint sensitivity model of the counter-flow cooling tower derived in the accompanying PART I to obtain the expressions and relative numerical rankings of the sensitivities, to all model parameters, of the following model responses: (i outlet air temperature; (ii outlet water temperature; (iii outlet water mass flow rate; and (iv air outlet relative humidity. These sensitivities are subsequently used within the “predictive modeling for coupled multi-physics systems” (PM_CMPS methodology to obtain explicit formulas for the predicted optimal nominal values for the model responses and parameters, along with reduced predicted standard deviations for the predicted model parameters and responses. These explicit formulas embody the assimilation of experimental data and the “calibration” of the model’s parameters. The results presented in this work demonstrate that the PM_CMPS methodology reduces the predicted standard deviations to values that are smaller than either the computed or the experimentally measured ones, even for responses (e.g., the outlet water flow rate for which no measurements are available. These improvements stem from the global characteristics of the PM_CMPS methodology, which combines all of the available information simultaneously in phase-space, as opposed to combining it sequentially, as in current data assimilation procedures.
G-Consistent Subsets and Reduced Dynamical Quantum Maps
Ceballos, Russell R.
A quantum system which evolves in time while interacting with an external environ- ment is said to be an open quantum system (OQS), and the influence of the environment on the unperturbed unitary evolution of the system generally leads to non-unitary dynamics. This kind of open system dynamical evolution has been typically modeled by a Standard Prescription (SP) which assumes that the state of the OQS is initially uncorrelated with the environment state. It is here shown that when a minimal set of physically motivated assumptions are adopted, not only does there exist constraints on the reduced dynamics of an OQS such that this SP does not always accurately describe the possible initial cor- relations existing between the OQS and environment, but such initial correlations, and even entanglement, can be witnessed when observing a particular class of reduced state transformations termed purity extractions are observed. Furthermore, as part of a more fundamental investigation to better understand the minimal set of assumptions required to formulate well defined reduced dynamical quantum maps, it is demonstrated that there exists a one-to-one correspondence between the set of initial reduced states and the set of admissible initial system-environment composite states when G-consistency is enforced. Given the discussions surrounding the requirement of complete positivity and the reliance on the SP, the results presented here may well be found valuable for determining the ba- sic properties of reduced dynamical maps, and when restrictions on the OQS dynamics naturally emerge.
Accurate estimation of dose distributions inside an eye irradiated with {sup 106}Ru plaques
Energy Technology Data Exchange (ETDEWEB)
Brualla, L.; Sauerwein, W. [Universitaetsklinikum Essen (Germany). NCTeam, Strahlenklinik; Sempau, J.; Zaragoza, F.J. [Universitat Politecnica de Catalunya, Barcelona (Spain). Inst. de Tecniques Energetiques; Wittig, A. [Marburg Univ. (Germany). Klinik fuer Strahlentherapie und Radioonkologie
2013-01-15
Background: Irradiation of intraocular tumors requires dedicated techniques, such as brachytherapy with {sup 106}Ru plaques. The currently available treatment planning system relies on the assumption that the eye is a homogeneous water sphere and on simplified radiation transport physics. However, accurate dose distributions and their assessment demand better models for both the eye and the physics. Methods: The Monte Carlo code PENELOPE, conveniently adapted to simulate the beta decay of {sup 106}Ru over {sup 106}Rh into {sup 106}Pd, was used to simulate radiation transport based on a computerized tomography scan of a patient's eye. A detailed geometrical description of two plaques (models CCA and CCB) from the manufacturer BEBIG was embedded in the computerized tomography scan. Results: The simulations were firstly validated by comparison with experimental results in a water phantom. Dose maps were computed for three plaque locations on the eyeball. From these maps, isodose curves and cumulative dose-volume histograms in the eye and for the structures at risk were assessed. For example, it was observed that a 4-mm anterior displacement with respect to a posterior placement of a CCA plaque for treating a posterior tumor would reduce from 40 to 0% the volume of the optic disc receiving more than 80 Gy. Such a small difference in anatomical position leads to a change in the dose that is crucial for side effects, especially with respect to visual acuity. The radiation oncologist has to bring these large changes in absorbed dose in the structures at risk to the attention of the surgeon, especially when the plaque has to be positioned close to relevant tissues. Conclusion: The detailed geometry of an eye plaque in computerized and segmented tomography of a realistic patient phantom was simulated accurately. Dose-volume histograms for relevant anatomical structures of the eye and the orbit were obtained with unprecedented accuracy. This represents an important step
Calculation of accurate small angle X-ray scattering curves from coarse-grained protein models
DEFF Research Database (Denmark)
Stovgaard, Kasper; Andreetta, Christian; Ferkinghoff-Borg, Jesper
2010-01-01
, which is paramount for structure determination based on statistical inference. Results: We present a method for the efficient calculation of accurate SAXS curves based on the Debye formula and a set of scattering form factors for dummy atom representations of amino acids. Such a method avoids......DBN. This resulted in a significant improvement in the decoy recognition performance. In conclusion, the presented method shows great promise for use in statistical inference of protein structures from SAXS data....
Wheeler, M.F.
2010-09-06
For many years there have been formulations considered for modeling single phase ow on general hexahedra grids. These include the extended mixed nite element method, and families of mimetic nite di erence methods. In most of these schemes either no rate of convergence of the algorithm has been demonstrated both theoret- ically and computationally or a more complicated saddle point system needs to be solved for an accurate solution. Here we describe a multipoint ux mixed nite element (MFMFE) method [5, 2, 3]. This method is motivated from the multipoint ux approximation (MPFA) method [1]. The MFMFE method is locally conservative with continuous ux approximations and is a cell-centered scheme for the pressure. Compared to the MPFA method, the MFMFE has a variational formulation, since it can be viewed as a mixed nite element with special approximating spaces and quadrature rules. The framework allows han- dling of hexahedral grids with non-planar faces by applying trilinear mappings from physical elements to reference cubic elements. In addition, there are several multi- scale and multiphysics extensions such as the mortar mixed nite element method that allows the treatment of non-matching grids [4]. Extensions to the two-phase oil-water ow are considered. We reformulate the two- phase model in terms of total velocity, capillary velocity, water pressure, and water saturation. We choose water pressure and water saturation as primary variables. The total velocity is driven by the gradient of the water pressure and total mobility. Iterative coupling scheme is employed for the coupled system. This scheme allows treatments of di erent time scales for the water pressure and water saturation. In each time step, we rst solve the pressure equation using the MFMFE method; we then Center for Subsurface Modeling, The University of Texas at Austin, Austin, TX 78712; mfw@ices.utexas.edu. yCenter for Subsurface Modeling, The University of Texas at Austin, Austin, TX 78712; gxue
Zuñiga, Cristal; Li, Chien-Ting; Zielinski, Daniel C.; Guarnieri, Michael T.; Antoniewicz, Maciek R.; Zengler, Karsten
2016-01-01
The green microalga Chlorella vulgaris has been widely recognized as a promising candidate for biofuel production due to its ability to store high lipid content and its natural metabolic versatility. Compartmentalized genome-scale metabolic models constructed from genome sequences enable quantitative insight into the transport and metabolism of compounds within a target organism. These metabolic models have long been utilized to generate optimized design strategies for an improved production process. Here, we describe the reconstruction, validation, and application of a genome-scale metabolic model for C. vulgaris UTEX 395, iCZ843. The reconstruction represents the most comprehensive model for any eukaryotic photosynthetic organism to date, based on the genome size and number of genes in the reconstruction. The highly curated model accurately predicts phenotypes under photoautotrophic, heterotrophic, and mixotrophic conditions. The model was validated against experimental data and lays the foundation for model-driven strain design and medium alteration to improve yield. Calculated flux distributions under different trophic conditions show that a number of key pathways are affected by nitrogen starvation conditions, including central carbon metabolism and amino acid, nucleotide, and pigment biosynthetic pathways. Furthermore, model prediction of growth rates under various medium compositions and subsequent experimental validation showed an increased growth rate with the addition of tryptophan and methionine. PMID:27372244
New process model proves accurate in tests on catalytic reformer
Energy Technology Data Exchange (ETDEWEB)
Aguilar-Rodriguez, E.; Ancheyta-Juarez, J. (Inst. Mexicano del Petroleo, Mexico City (Mexico))
1994-07-25
A mathematical model has been devised to represent the process that takes place in a fixed-bed, tubular, adiabatic catalytic reforming reactor. Since its development, the model has been applied to the simulation of a commercial semiregenerative reformer. The development of mass and energy balances for this reformer led to a model that predicts both concentration and temperature profiles along the reactor. A comparison of the model's results with experimental data illustrates its accuracy at predicting product profiles. Simple steps show how the model can be applied to simulate any fixed-bed catalytic reformer.
Düben, Peter D.; Subramanian, Aneesh; Dawson, Andrew; Palmer, T. N.
2017-03-01
The use of reduced numerical precision to reduce computing costs for the cloud resolving model of superparameterized simulations of the atmosphere is investigated. An approach to identify the optimal level of precision for many different model components is presented, and a detailed analysis of precision is performed. This is nontrivial for a complex model that shows chaotic behavior such as the cloud resolving model in this paper. It is shown not only that numerical precision can be reduced significantly but also that the results of the reduced precision analysis provide valuable information for the quantification of model uncertainty for individual model components. The precision analysis is also used to identify model parts that are of less importance thus enabling a reduction of model complexity. It is shown that the precision analysis can be used to improve model efficiency for both simulations in double precision and in reduced precision. Model simulations are performed with a superparameterized single-column model version of the OpenIFS model that is forced by observational data sets. A software emulator was used to mimic the use of reduced precision floating point arithmetic in simulations.
Melimine-Coated Antimicrobial Contact Lenses Reduce Microbial Keratitis in an Animal Model.
Dutta, Debarun; Vijay, Ajay K; Kumar, Naresh; Willcox, Mark D P
2016-10-01
To determine the ability of antimicrobial peptide melimine-coated contact lenses to reduce the incidence of microbial keratitis (MK) in a rabbit model of contact lens wear. In vitro antimicrobial activity of melimine-coated contact lenses was determined against Pseudomonas aeruginosa by viable count and a radiolabeled assay. The amount of lipopolysaccharide (LPS) associated with bacteria bound to melimine-coated and control lenses was determined. Ocular swabs from rabbit eyes were collected for assessment of ocular microflora. A rabbit model for MK was developed that used overnight wear of contact lenses colonized by P. aeruginosa in the absence of a corneal scratch. During lens wear, detailed ocular examinations were performed, and the incidence of MK was investigated. Bacteria associated with worn lenses and infected corneas were determined by viable plate count. Inhibition in viable and total P. aeruginosa adhesion by melimine-coated contact lenses was 3.1 log10 and 0.4 log10, respectively. After colonization, the amount of LPS on lenses was approximately the same with or without melimine. Gram-positive bacteria were found in all the ocular swabs followed by fungus (42%). Melimine-coated lens wear was protective and significantly (odds ratio 10.12; P = 0.012) reduced the incidence of P. aeruginosa-driven MK in the rabbit model. The antimicrobial lenses were associated with significantly (P lenses can produce MK without corneal epithelial defect in an animal model. Melimine-coated contact lenses reduced the incidence of MK associated with P. aeruginosa in vivo. Development of MK requires viable bacteria adherent to contact lenses, and bacterial debris adherent at the lens surface did not cause keratitis.
Obtaining accurate amounts of mercury from mercury compounds via electrolytic methods
Grossman, M.W.; George, W.A.
1987-07-07
A process is described for obtaining pre-determined, accurate rate amounts of mercury. In one embodiment, predetermined, precise amounts of Hg are separated from HgO and plated onto a cathode wire. The method for doing this involves dissolving a precise amount of HgO which corresponds to a pre-determined amount of Hg desired in an electrolyte solution comprised of glacial acetic acid and H[sub 2]O. The mercuric ions are then electrolytically reduced and plated onto a cathode producing the required pre-determined quantity of Hg. In another embodiment, pre-determined, precise amounts of Hg are obtained from Hg[sub 2]Cl[sub 2]. The method for doing this involves dissolving a precise amount of Hg[sub 2]Cl[sub 2] in an electrolyte solution comprised of concentrated HCl and H[sub 2]O. The mercurous ions in solution are then electrolytically reduced and plated onto a cathode wire producing the required, pre-determined quantity of Hg. 1 fig.
A Taxonomic Reduced-Space Pollen Model for Paleoclimate Reconstruction
Wahl, E. R.; Schoelzel, C.
2010-12-01
Paleoenvironmental reconstruction from fossil pollen often attempts to take advantage of the rich taxonomic diversity in such data. Here, a taxonomically "reduced-space" reconstruction model is explored that would be parsimonious in introducing parameters needing to be estimated within a Bayesian Hierarchical Modeling context. This work involves a refinement of the traditional pollen ratio method. This method is useful when one (or a few) dominant pollen type(s) in a region have a strong positive correlation with a climate variable of interest and another (or a few) dominant pollen type(s) have a strong negative correlation. When, e.g., counts of pollen taxa a and b (r >0) are combined with pollen types c and d (r logistic generalized linear model (GLM). The GLM can readily model this relationship in the forward form, pollen = g(climate), which is more physically realistic than inverse models often used in paleoclimate reconstruction [climate = f(pollen)]. The specification of the model is: rnum Bin(n,p), where E(r|T) = p = exp(η)/[1+exp(η)], and η = α + β(T); r is the pollen ratio formed as above, rnum is the ratio numerator, n is the ratio denominator (i.e., the sum of pollen counts), the denominator-specific count is (n - rnum), and T is the temperature at each site corresponding to a specific value of r. Ecological and empirical screening identified the model (Spruce+Birch) / (Spruce+Birch+Oak+Hickory) for use in temperate eastern N. America. α and β were estimated using both "traditional" and Bayesian GLM algorithms (in R). Although it includes only four pollen types, the ratio model yields more explained variation ( 80%) in the pollen-temperature relationship of the study region than a 64-taxon modern analog technique (MAT). Thus, the new pollen ratio method represents an information-rich, reduced space data model that can be efficiently employed in a BHM framework. The ratio model can directly reconstruct past temperature by solving the GLM equations