Numerical approximation of elliptic problems with log-normal random coefficients
Document Type
Article
Publication Date
1-1-2019
Abstract
In this work, we consider a non-standard preconditioning strategy for the numerical approximation of the classical elliptic equations with log-normal random coefficients. In earlier work, a Wick-type elliptic model was proposed by modeling the random flux through the Wick product. Due to the lower-triangular structure of the uncertainty prop-agator, this model can be approximated efficiently using the Wiener chaos expansion in the probability space. Such a Wick-type model provides, in general, a second-order approximation of the classical one in terms of the standard deviation of the underlying Gaussian process. Furthermore, when the correlation length of the underlying Gaussian process goes to infinity, the Wick-type model yields the same solution as the classical one. These observations imply that the Wick-type elliptic equation can provide an effective preconditioner for the classical random elliptic equation under appropriate conditions. We use the Wick-type elliptic model to accelerate the Mont .
Publication Source (Journal or Book title)
International Journal for Uncertainty Quantification
First Page
161
Last Page
186
Recommended Citation
Wan, X., & Yu, H. (2019). Numerical approximation of elliptic problems with log-normal random coefficients. International Journal for Uncertainty Quantification, 9 (2), 161-186. https://doi.org/10.1615/Int.J.UncertaintyQuantification.2019029046