@Article{CiCP-6-509,
author = {},
title = {A Comparative Study of Stochastic Collocation Methods for Flow in Spatially Correlated Random Fields},
journal = {Communications in Computational Physics},
year = {2009},
volume = {6},
number = {3},
pages = {509--535},
abstract = {<p style="text-align: justify;">Stochastic collocation methods as a promising approach for solving stochastic
partial differential equations have been developed rapidly in recent years. Similar
to Monte Carlo methods, the stochastic collocation methods are non-intrusive in that
they can be implemented via repetitive execution of an existing deterministic solver
without modifying it. The choice of collocation points leads to a variety of stochastic
collocation methods including tensor product method, Smolyak method, Stroud 2 or 3
cubature method, and adaptive Stroud method. Another type of collocation method,
the probabilistic collocation method (PCM), has also been proposed and applied to
flow in porous media. In this paper, we discuss these methods in terms of their accuracy,
efficiency, and applicable range for flow in spatially correlated random fields.
These methods are compared in details under different conditions of spatial variability
and correlation length. This study reveals that the Smolyak method and the PCM
outperform other stochastic collocation methods in terms of accuracy and efficiency.
The random dimensionality in approximating input random fields plays a crucial role
in the performance of the stochastic collocation methods. Our numerical experiments
indicate that the required random dimensionality increases slightly with the decrease
of correlation scale and moderately from one to multiple physical dimensions.</p>},
issn = {1991-7120},
doi = {https://doi.org/},
url = {http://global-sci.org/intro/article_detail/cicp/7690.html}
}