Journal
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
Volume 197, Issue 43-44, Pages 3560-3573Publisher
ELSEVIER SCIENCE SA
DOI: 10.1016/j.cma.2008.03.020
Keywords
stochastic partial differential equations; random heterogeneous media; microstructure; sparse grids; multiscale modeling; model reduction
Funding
- Computational Mathematics program of AFOSR [F49620-00-1-0373]
Ask authors/readers for more resources
A simple stochastic up-scaling strategy is presented for incorporating the effects of micro-scale variations of thermal conductivity in the thermal analysis of macro-scale systems. Incomplete characterization of the fine-scale variation necessitates posing the thermal conductivity as a stochastic multiscale random field. A data-driven approach coupled with a non-linear dimension reduction algorithm is used to construct a low-dimensional stochastic descriptor of the fine-scale variation of the stochastic conductivity. A representative volume element (RVE) argument is utilized to construct a simple model for up-scaling the stochastic thermal conductivity. In this model, the effective stochastic thermal conductivity is estimated by virtually interrogating the stochastic RV. A realistic example of the proposed stochastic multiscale diffusion strategy is illustrated utilizing limited experimental data. (C) 2008 Elsevier B.V. All rights reserved.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available