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A mathematical model for crack-tip fields is proposed in this paper for the response of a three-dimensional (3-D) porous elastic solid whose material moduli are dependent on the density. Such a description wherein the generalized Lam\`e…

数值分析 · 数学 2025-03-11 Kun Gou , S. M. Mallikarjunaiah

Microgels made of poly(N-isopropylacrylamide) are the prototype of soft, thermoresponsive particles widely used to study fundamental problems in condensed matter physics. However, their internal structure is far from homogeneous, and…

软凝聚态物质 · 物理学 2025-02-12 Susana Marín-Aguilar , Emanuela Zaccarelli

A diffuse-interface model for microstructure with an arbitrary number of components and phases was developed from basic thermodynamic and kinetic principles and formalized within a variational framework. The model includes a composition…

材料科学 · 物理学 2011-07-28 Daniel A. Cogswell , W. Craig Carter

Despite the ubiquity of fluid flows interacting with porous and elastic materials, we lack a validated non-empirical macroscale method for characterizing the flow over and through a poroelastic medium. We propose a computational tool to…

流体动力学 · 物理学 2017-03-24 Uǧis Lācis , Giuseppe Antonio Zampogna , Shervin Bagheri

The hypersphere model is a simple one-parameter model of the potential energy landscape of viscous liquids, which is defined as a percolating system of same-radius hyperspheres randomly distributed in $\mathbb{R}^{3N}$ in which $N$ is the…

软凝聚态物质 · 物理学 2025-05-02 Mark F. B. Railton , Eva Uhre , Jeppe C. Dyre , Thomas B. Schrøder

This paper introduces a new technique for learning probabilistic models of mass and friction distributions of unknown objects, and performing robust sliding actions by using the learned models. The proposed method is executed in two…

机器人学 · 计算机科学 2020-08-06 Changkyu Song , Abdeslam Boularias

We present a new implementation of the tracer particles algorithm based on a Monte Carlo approach for the Eulerian adaptive mesh refinement code Ramses. The purpose of tracer particles is to keep track of where fluid elements originate in…

星系天体物理 · 物理学 2019-01-23 Corentin Cadiou , Yohan Dubois , Christophe Pichon

Markov chain Monte Carlo (MCMC) samplers are numerical methods for drawing samples from a given target probability distribution. We discuss one particular MCMC sampler, the MALA-within-Gibbs sampler, from the theoretical and practical…

统计计算 · 统计学 2020-03-19 X. T. Tong , M. Morzfeld , Y. M. Marzouk

The phase separation of a simple binary mixture of incompatible linear polymers in solution is investigated using an extension of the sedimentation equilibrium method, whereby the osmotic pressure of the mixture is extracted from the…

软凝聚态物质 · 物理学 2009-09-29 Chris I. Addison , Pierre-Arnaud Artola , Jean-Pierre Hansen , Ard A. Louis

Lagrangian stochastic methods are widely used to model turbulent flows. Scarce consideration has, however, been devoted to the treatment of the near-wall region and to the formulation of a proper wall-boundary condition. With respect to…

流体动力学 · 物理学 2024-02-07 Guilhem Balvet , Jean-Pierre Minier , Yelva Roustan , Martin Ferrand

Aims. The random walk of energetic charged particles in turbulent magnetic fields is investigated. Special focus is placed on transport across the mean magnetic field, which had been found to be subdiffusive on many occasions. Therefore, a…

高能天体物理现象 · 物理学 2016-06-29 R. C. Tautz

The stochastic volatility model is a popular tool for modeling the volatility of assets. The model is a nonlinear and non-Gaussian state space model, and consequently is difficult to fit. Many approaches, both classical and Bayesian, have…

统计方法学 · 统计学 2019-07-22 Chen Gong , David S. Stoffer

A generalized approach to Wang-Landau simulations, macroscopically constrained Wang-Landau, is proposed to simulate the density of states of a system with multiple macroscopic order parameters. The method breaks a multidimensional…

统计力学 · 物理学 2017-05-11 Chor-Hoi Chan , Gregory Brown , Per Arne Rikvold

A multiscale scheme combining molecular dynamics (MD) and microscopic phase-field theory is proposed to study the structural phase transformations in solids with inhomogeneous strain field. The approach calculates strain response based on…

材料科学 · 物理学 2007-05-23 Zhi-Rong Liu , Huajian Gao

We present a multilevel Monte Carlo (MLMC) method for the uncertainty quantification of variably saturated porous media flow that are modeled using the Richards' equation. We propose a stochastic extension for the empirical models that are…

In this paper, a methodology for fine scale modeling of large scale structures is proposed, which combines the variational multiscale method, domain decomposition and model order reduction. The influence of the fine scale on the coarse…

计算工程、金融与科学 · 计算机科学 2023-07-06 Philipp Diercks , Karen Veroy , Annika Robens-Radermacher , Jörg F. Unger

Light propagation in turbid media is driven by the equation of radiative transfer. We give a formal probabilistic representation of its solution in the framework of biological tissues and we implement algorithms based on Monte Carlo methods…

统计计算 · 统计学 2014-10-16 Laura Vinckenbosch , Céline Lacaux , Samy Tindel , Magalie Thomassin , Tiphaine Obara

Functionally graded materials (FGMs) are two-phase composites with continuously changing microstructure adapted to performance requirements. Traditionally, the overall behavior of FGMs has been determined using local averaging techniques or…

材料科学 · 物理学 2011-08-31 Zahra Sharif-Khodaei , Jan Zeman

This article presents GRFsaw, an open-source software for generating two-phase (binary) microstructures with user-defined structural properties. Unlike most standard software for microstructure generation, GRFsaw is based on the concept of…

计算工程、金融与科学 · 计算机科学 2024-12-09 Lars Blatny , Henning Löwe , Johan Gaume

Gaussian processes are valuable tools for non-parametric modelling, where typically an assumption of stationarity is employed. While removing this assumption can improve prediction, fitting such models is challenging. In this work,…

统计计算 · 统计学 2019-05-02 Karla Monterrubio-Gómez , Lassi Roininen , Sara Wade , Theo Damoulas , Mark Girolami