Optimal Discretization of Random Fields
Publication: Journal of Engineering Mechanics
Volume 119, Issue 6
Abstract
A new method for efficient discretization of random fields (i.e., their representation in terms of random variables) is introduced. The efficiency of the discretization is measured by the number of random variables required to represent the field with a specified level of accuracy. The method is based on principles of optimal linear estimation theory. It represents the field as a linear function of nodal random variables and a set of shape functions, which are determined by minimizing an error variance. Further efficiency is achieved by spectral decomposition of the nodal covariance matrix. The new method is found to be more efficient than other existing discretization methods, and more practical than a series expansion method employing the Karhunen‐Loève theorem. The method is particularly useful for stochastic finite element studies involving random media, where there is a need to reduce the number of random variables so that the amount of required computations can be reduced.
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Information & Authors
Information
Published In
Journal of Engineering Mechanics
Volume 119 • Issue 6 • June 1993
Pages: 1136 - 1154
Copyright
Copyright © 1993 American Society of Civil Engineers.
History
Received: Apr 20, 1992
Published online: Jun 1, 1993
Published in print: Jun 1993
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