Computational mechanics of multiphase materials-modeling strategies at different scales
Journal Title: Computer Assisted Methods in Engineering and Science - Year 2011, Vol 18, Issue 1
Abstract
The paper addresses various scale-bridging modeling and discretization strategies for multiphase porous materials, starting with a micromechanics model for ion transport within the pore space to generate homogenized diffusion coefficients. Using homogenized macroscopic properties, the theory of poromechanics provides the modeling framework for the macroscopic representation of transport and phase change processes as it is demonstrated for freezing of porous materials using a three-field formulation. The theory of poromechanics is again employed as an appropriate representation of more or less intact porous materials, in conjunction with a two-field Extended Finite Element model as a scale bridging tool to describe coupled hydro-mechanical processes in cracked porous materials at a macroscopic level.
Authors and Affiliations
Günther Meschke, Dirk Leonhart, Jithender J. Timothy, Meng-Meng Zhou
Keywords
Related Articles
- EP ID EP73970
- DOI -
- Views 170
- Downloads 0
A meshless method using global radial basis functions for creating 3-D wind fields from sparse meteorological data
An efficient, global meshless method has been developed for creating 3-D wind fields utilizing sparse meteorological tower data. Meshless methods do not require the need for a mesh in order to connect node points. In thi...
A distributed implementation of parallel genetic algorithm for slope stability evaluation. (Received in the final form October 13, 2010)
Parallel processing, the method of considering many small tasks to solve one large problem, has emerged as a key enabling technology in modern computing. Parallel computers can be simply classified into shared memory sys...
Neural networks for the analysis of mine-induced building vibrations
A study of the capabilities of artificial neural networks in respect of selected problems of the analysis of mine-induced building vibrations is presented. Neural network technique was used for the prediction of building...
Efficient Markov chain Monte Carlo sampling for electrical impedance tomography
This paper studies electrical impedance tomography (EIT) using Bayesian inference [1]. The resulting posterior distribution is sampled by Markov chain Monte Carlo (MCMC) [2]. This paper studies a toy model of EIT as the...
Regularization using truncated singular value decomposition for estimating the Fourier spectrum of a noised space distribution over an extended support
This paper is devoted to a theoretical and numerical study of different ways of calculating the Fourier transform of a noisy signal where the boundary conditions at the lateral boundaries of the measurement interval are...