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Percolation threshold in ceramic composites with isotropic conducting nanoparticles

JOURNAL OF THE EUROPEAN CERAMIC SOCIETY 2020年第4期40卷 1684-1691页

作者： Ambrozic, M. Lazar, A. Kocjan, A. Univ Maribor Fac Math & Nat Sci Koroska 160 Maribor Slovenia Fac Ind Engn Segova 112 Novo Mesto Slovenia Jozef Stefan Inst Jamova 39 Ljubljana Slovenia Jozef Stefan Int Postgrad Sch Ljubljana 1000 Slovenia

The percolation threshold for electrical conductivity of a binary system of electrically insulating and conducting spheres was studied theoretically to yield a roadmap for electrically conductive ceramic composites. Although the crystal grains in such matrix are of irregular shape, the spheres of different sizes are used in the model to keep calculations tractable, where insulating spheres (matrix) are considered to be much larger than conducting ones (filler). This difference influences spatial distribution of conducting spheres. Besides the rough analytical estimation of the percolation threshold, we also use the metropolis algorithm. The latter must be adapted for the system of conducting spheres which are positioned at the surface of large insulating spheres. We give a suggestion for the modification of this algorithm. Analytical estimation and metropolis method give qualitatively similar dependence of the percolation threshold on the radii of geometrical objects, but there are significant quantitative differences in the results.

关键词： Electrical conductivity Percolation Ceramics metropolis algorithm

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Bayesian calibration of Vehicle-Terrain Interface algorithms for wheeled vehicles on loose sands

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JOURNAL OF TERRAMECHANICS 2017年 71卷 45-56页

作者： Dettwiller, Ian Rais-Rohani, Masoud Vahedifard, Farshid Mason, George L. Priddy, Jody D. Mississippi State Univ Dept Aerosp Engn Mississippi State MS 39762 USA Mississippi State Univ Ctr Adv Vehicular Syst Mississippi State MS 39762 USA Mississippi State Univ Dept Civil & Environm Engn Mississippi State MS 39762 USA US Army Engn Res & Dev Ctr 3909 Halls Ferry Rd Vicksburg MS 39180 USA Univ Maine Dept Mech Engn Orono ME 04469 USA

The Vehicle-Terrain Interface (VTI) model is commonly used to predict off-road mobility to support virtual prototyping. The Database Records for Off-road Vehicle Environments (DROVE), a recently developed database of tests conducted with wheeled vehicles operating on loose, dry sand, is used to calibrate three equations used within the VTI model: drawbar pull, traction, and motion resistance. A two-stage Bayesian calibration process using the metropolis algorithm is implemented to improve the performance of the three equations through updating of their coefficients. Convergence of the Bayesian calibration process to a calibrated model is established through evaluation of two indicators of convergence. Improvements in root-mean square error (RMSE) are shown for all three equations: 17.7% for drawbar pull, 5.5% for traction, and 23.1% for motion resistance. Improvements are also seen in the coefficient of determination (R-2) performance of the equations for drawbar pull, 2.8%, and motion resistance, 2.5%. Improvements are also demonstrated in the coefficient of determination for drawbar pull, 2.8%, and motion resistance, 2.5%, equations, while the calibrated traction equation performs similar to the VTI equation. A randomly selected test dataset of about 10% of the relevant observations from DROVE is used to validate the performance of each calibrated equation. (C) 2017 ISTVS. Published by Elsevier Ltd. All rights reserved.

关键词： Off-road mobility Vehicle Terrain Interface (VTI) model Bayesian calibration metropolis algorithm Sand Drawbar pull (DP) Traction Motion resistance Database Records for Off-road Vehicle Environments (DROVE)

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Finite size scaling of the spontaneous symmetry breaking model of X-chromosome inactivation

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PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS 2009年第6期388卷 843-850页

作者： Barker, D. Griffiths, A. Univ Warwick Dept Phys Coventry CV4 7AL W Midlands England

X-Chromosome inactivation is the process whereby one of the two X-chromosomes in female cells is silenced to prevent the cell producing too much of any X-linked proteins and RNA. The proposed blocking-factor mechanism of X-inactivation is not well understood and hence is the subject of much current research. In this paper we investigated the nature of the phase transition predicted to exist in the spontaneous symmetry breaking model of X-inactivation proposed by Nicodemi and Prisco [Mario Nicodemi, Antonella Prisco, Symmetry breaking model for x-chromosome inactivation, Phs. Rev. Lett. 98 (2007) 108104]. Finite size effects were investigated by using an on lattice Monte Carlo simulation. From the scaling it is concluded that the transition is in general abrupt. The critical temperature of the system was determined to be 1.68 +/- 0.01 E(0)/k(B) in the thermodynamic limit when the concentration C = 0.025 blocking-factors per lattice site. (C) 2008 Elsevier B.V. All rights reserved.

关键词： Monte Carlo Lattice gas X-chromosome inactivation Symmetry breaking metropolis algorithm Phase transition Finite size scaling

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An Ising model of transcription polarity in bacterial chromosomes

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PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS 2006年第2期362卷 403-422页

作者： Baran, RH Ko, H Korea Univ Dept Elect & Comp Engn Seoul 136701 South Korea

Bacterial genes form clusters of the same transcription polarity and typically exhibit a preference to be coded on the leading strand of replication. An Ising model is proposed to quantify these two phenomena by analogy to the behavior of magnetic dipoles (spins) in a one-dimensional lattice. Corresponding to magnetic forces that co-orient adjacent spins and align them with an externally applied field, we imagine pseudo-forces that influence transcription polarity. Bonds of uniform strength 1/2J between adjacent sites will model the adhesive (or repulsive) interactions while a polarity entraining force of strength H has the direction of replication. Ten bacterial chromosomes are reduced to spin configurations from which the model parameters are estimated by the method of maximum likelihood under the assumption of thermal equilibrium, following the application of established methods to locate replication origins and termini. chi(2)-tests show that the model fits the data well in about half the cases but cluster size exhibits excess variance in general. These findings lead to a speculative interpretation of the pseudo-forces as the net effects of numerous insertions and deletions that succeed or fail according to their impact on the motions of enzymatic complexes involved in replication and transcription. (c) 2005 Elsevier B.V. All rights reserved.

关键词： Ising model genome organization Gibbs-Markov equivalence metropolis algorithm

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Improving accuracy of vehicle-terrain interface algorithms for wheeled vehicles on fine-grained soils through Bayesian calibration

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JOURNAL OF TERRAMECHANICS 2018年 77卷 59-68页

作者： Dettwiller, Ian Vahedifard, Farshid Rais-Rohani, Masoud Mason, George L. Priddy, Jody D. US Army ERDC 3909 Halls Ferry Rd Vicksburg MS 39180 USA Mississippi State Univ Dept Aerosp Engn Mississippi State MS 39762 USA Mississippi State Univ CAVS Mississippi State MS 39762 USA Mississippi State Univ Dept Civil & Environm Engn Mississippi State MS 39762 USA Univ Maine Dept Mech Engn Orono ME 04469 USA

The Vehicle-Terrain Interface (VTI) model for off-road vehicle performance is often used in virtual prototyping to support preliminary vehicle design. Five VTI algorithms for wheeled vehicles on fine-grained soils are calibrated in this study using a Bayesian calibration technique and the Database Records for Off-road Vehicle Environments (DROVE): powered and unpowered sinkage, drawbar pull, motion resistance, and gross traction. These algorithms are improved through a two-stage Bayesian calibration technique utilizing the metropolis algorithm with three separate calibration strategies. The VII and proposed algorithms are compared for performance in coefficient of determination and root-mean square error. The results from each algorithm were validated through k-fold cross validation with five folds. The final algorithms from the best performing strategy after accounting for increased complexity for each of the five performance parameters are reported as calibrated algorithms. Validated improvements in coefficient of determination are recorded for all five parameters: 7.8% for powered sinkage, 1.4% for unpowered sinkage, 6.4% for drawbar pull, 0.9% for motion resistance, and 12.5% for gross traction. Improvements are also seen in the normalized root-mean square error performance: 13.4% for powered sinkage, 1.9% for unpowered sinkage, 7.6% for drawbar pull, 17.5% for motion resistance, and 23.2% for gross traction. (C) 2018 ISTVS. Published by Elsevier Ltd. All rights reserved.

关键词： Off-road mobility Vehicle Terrain Interface (VTI) model Bayesian calibration metropolis algorithm Fine-grained soils Sinkage Drawbar pull Traction Motion resistance Database Records for Off-road Vehicle Environments (DROVE)

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Estimation of parameters in complex ¹⁵N tracing models by Monte Carlo sampling

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SOIL BIOLOGY & BIOCHEMISTRY 2007年第3期39卷 715-726页

作者： Mueller, Christoph Ruetting, T. Kattge, J. Laughlin, R. J. Stevens, R. J. Univ Giessen Dept Plant Ecol D-35392 Giessen Germany Max Planck Inst Biogeochem D-07745 Jena Germany Agri Food & Biosci Inst Agr Food & Environm Sci Div Belfast BT9 5PX Antrim North Ireland

The most widely used method to quantify gross N transforination rates in soils is based on N-15 dilution and enrichment principles. To identify rate parameters, N-15-tracing experiments are analysed by models that are linked to algorithins that try to minimize the misfit between modelled and observed data. In Currently available N-15-tracing models optimization algorithms are based oil the Levenberg-Marquardt method that is suitable for the determination of small number of parameters. Therefore, these models are restricted to a few processes. Methods based on Monte Carlo sampling have the potential to overcome restrictions on parameter numbers but have not been tested for application in N-15-tracing models. Here, for the first time, we use a Markov chain Monte Carlo (MCMC) method with a tracing model to simultaneously determine the probability density functions (PDFs) of the whole set of parameters for a previously published data set [Muller, C., Stevens, R.J., Laughlin, R.J., 2004. A N-15 tracing model to analyse N transformations in old grassland soil. Soil Biology & Biochemistry 36, 619-632]. We show that the MCMC method can simultaneously determine PDFs of more than 8 parameters and demonstrate for the first time that it is possible to optimize models where transformations are described by Michaelis-Menten kinetics. Setting the NH4+ oxidation rate to Michaelis-Menten kinetics reduced the misfit by 19%. Together with monitoring diagnostics for parameter convergence, the MCMC method is a very efficient and robust technique to determine PDFs for parameters in N-15-tracing models that Contain large number of N transformations and complex process descriptions. (c) 2006 Elsevier Ltd. All rights reserved.

关键词： N-15 tracing model N transformations metropolis algorithm Monte Carlo sampling Markov chain Michaelis-Menten kinetics

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Particle filtering and ensemble Kalman filtering for state updating with hydrological conceptual rainfall-runoff models

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WATER RESOURCES RESEARCH 2006年第9期42卷 9403-1-9403-1页

作者： Weerts, Albrecht H. El Serafy, Ghada Y. H. WL Delft Hydraul NL-2600 MH Delft Netherlands

[ 1] Sequential importance resampling (SIR) filter, residual resampling filter (RR), and an ensemble Kalman (EnKF) filter that can handle dynamic nonlinear/non-Gaussian models are compared to correct erroneous model inputs and to obtain a rainfall-runoff update with a conceptual rainfall-runoff model HBV-96 for flood forecasting purposes. EnKF performs best with a low number of ensemble members. The RR filter performs best at intermediate and high number of particles, although differences are small. With all filters the rainfall error could be estimated during a synthetic experiment when the soil is not too dry and the measurement error on the discharge is not dominant. The temperature error could only be estimated when the temperature is close to 0 degrees C. When applying these methods to a real case, good results are obtained. For low flows, EnKF outperforms both particle filters, because it is less sensitive to misspecification of the model and uncertainties. These methods are feasible and easy to implement in real flood forecasting systems. Further research on the assumptions on model uncertainties and measurement uncertainties is recommended.

关键词： STOCHASTIC HYDROMETEOROLOGICAL MODEL MONTE-CARLO METHODS PARAMETER-ESTIMATION metropolis algorithm DATA ASSIMILATION UNCERTAINTY SYSTEMS FLOOD

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Bayesian approach for nonlinear random effects models

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BIOMETRICS 1997年第4期53卷 1239-1252页

作者： Dey, DK Chen, MH Chang, H Univ Connecticut Dept Stat Storrs CT 06269 USA Worcester Polytech Inst Dept Math Sci Worcester MA 01609 USA Coopers & Lybrand LLP Boston MA 02110 USA

In this paper, we propose a general model-determination strategy based on Bayesian methods for nonlinear mixed effects models. Adopting an exploratory data analysis viewpoint, we develop diagnostic tools based on conditional predictive ordinates that conveniently get tied in with Markov chain Monte Carlo fitting of models. Sampling-based methods are used to carry out these diagnostics. Two examples are presented to illustrate the effectiveness of these criteria. The first one is the famous Langmuir equation, commonly used in pharmacokinetic models, whereas the second model is used in the growth curve model for longitudinal data.

关键词： Gibbs sampler longitudinal data metropolis algorithm noninformative prior nonlinear models predictive distributions pseudo-Bayes factor random effects models

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When physics meets signal processing: Image and video denoising based on Ising theory

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SIGNAL PROCESSING-IMAGE COMMUNICATION 2015年 34卷 14-21页

作者： Cohen, Eliahu Heiman, Ron Carmi, Maya Hadar, Ofer Cohen, Asaf Tel Aviv Univ Sch Phys & Astron IL-6997801 Tel Aviv Israel Ben Gurion Univ Negev Dept Elect & Comp Engn IL-84105 Beer Sheva Israel

In this work we suggest a novel model for automatic noise estimation and image denoising. In particular, we investigate the useful affinity which arises between statistical mechanics and image processing, and describe a framework from which novel denoising algorithms can be derived: Ising-like models and simulated annealing techniques. This is the first time such algorithms are used for colored images and video denoising. Results, as well as benchmarks, suggest a significant gain in PSNR and SSIM in comparison to other filters, mainly in cases of low impulse noise. When hybridizing our models with other image processing techniques they are shown to be even more effective. Their major disadvantages- high complexity and limited applicability, are also discussed. (C) 2015 Elsevier B.V. All rights reserved.

关键词： Image denoising Ising model Monte-Carlo methods metropolis algorithm Simulated annealing Statistical physics

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Efficient prediction uncertainty approximation in the calibration of environmental simulation models

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WATER RESOURCES RESEARCH 2008年第4期44卷 W04411-1-W04411-1页

作者： Tolson, Bryan A. Shoemaker, Christine A. Univ Waterloo Dept Civil & Environm Engn Waterloo ON N2L 3G1 Canada Cornell Univ Sch Civil & Environm Engn Ithaca NY 14853 USA

[ 1] This paper is aimed at improving the efficiency of model uncertainty analyses that are conditioned on measured calibration data. Specifically, the focus is on developing an alternative methodology to the generalized likelihood uncertainty estimation ( GLUE) technique when pseudolikelihood functions are utilized instead of a traditional statistical likelihood function. We demonstrate for multiple calibration case studies that the most common sampling approach utilized in GLUE applications, uniform random sampling, is much too inefficient and can generate misleading estimates of prediction uncertainty. We present how the new dynamically dimensioned search ( DDS) optimization algorithm can be used to independently identify multiple acceptable or behavioral model parameter sets in two ways. DDS could replace random sampling in typical applications of GLUE. More importantly, we present a new, practical, and efficient uncertainty analysis methodology called DDS-approximation of uncertainty ( DDS-AU) that quantifies prediction uncertainty using prediction bounds rather than prediction limits. Results for 13, 14, 26, and 30 parameter calibration problems show that DDS-AU can be hundreds or thousands of times more efficient at finding behavioral parameter sets than GLUE with random sampling. Results for one example show that for the same limited computational effort, DDS-AU prediction bounds can simultaneously be smaller and contain more of the measured data in comparison to GLUE prediction bounds. We also argue and then demonstrate that within the GLUE framework, when behavioral parameter sets are not sampled frequently enough, Latin hypercube sampling does not offer any improvements over simple random sampling.

关键词： WATER-QUALITY MODELS metropolis algorithm BAYESIAN-ESTIMATION GLUE METHODOLOGY EQUIFINALITY CATCHMENT PARAMETER SENSITIVITY OPTIMIZATION INFORMATION

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