@article{39101,
  keywords = {bifurcation-analysis, equation-free, projective-methods, finite-element-method, homogenization, simulations, elliptic problems, coarse stability, diffusion in random media, generalized   polynomial chaos, modeling uncertainty, multiscale problem, partial-differential-equations, stochastic modeling},
  author = {Xiu and Kevrekidis},
  title = {Equation-free, multiscale computation for unsteady random diffusion},
  abstract = { <p>We present an "equation-free" multiscale approach to the simulation of unsteady diffusion in a random medium. The diffusivity of the medium is modeled as a random field with short correlation length, and the governing equations are cast in the form of stochastic differential equations. A detailed fine-scale computation of such a problem requires discretization and solution of a large system of equations and can be prohibitively time consuming. To circumvent this difficulty, we propose an equation-free approach, where the fine-scale computation is conducted only for a (small) fraction of the overall time. The evolution of a set of appropriately defined coarse-grained variables (observables) is evaluated during the fine-scale computation, and "projective integration" is used to accelerate the integration. The choice of these coarse variables is an important part of the approach: they are the coefficients of pointwise polynomial expansions of the random solutions. Such a choice of coarse variables allows us to reconstruct representative ensembles of fine-scale solutions with "correct" correlation structures, which is a key to algorithm efficiency. Numerical examples demonstrating accuracy and efficiency of the approach are presented.</p> },
  year = {2005},
  journal = {Multiscale Modeling \& Simulation},
  volume = {4},
  pages = {915-935},
  isbn = {1540-3459},
  language = {English},
}