2008
DOI: 10.1016/j.strusafe.2007.05.002
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Simulation of simply cross correlated random fields by series expansion methods

Abstract: A practical framework for generating cross correlated random fields with a specified marginal distribution function, an autocorrelation function and cross correlation coefficients is presented in the paper. The approach relies on well-known series expansion methods for simulation of a Gaussian random field. The proposed method requires all cross correlated fields over the domain to share an identical autocorrelation function and the cross correlation structure between each pair of simulated fields to be simply… Show more

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Cited by 119 publications
(85 citation statements)
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“…The Expansion Optimal Linear Estimation method (EOLE) and its extension to cover the case of non-Gaussian random fields are used herein to generate the two random fields of c and φ. Notice that EOLE was first proposed by [4] for the case of uncorrelated Gaussian fields, and then extended by [5] to cover the case of correlated and uncorrelated non-Gaussian fields. In this method, one should first define a stochastic grid composed of q grid points (or nodes)   …”
Section: Methods Of Generation Of Anisotropic Non-gaussian Random Fieldsmentioning
confidence: 99%
“…The Expansion Optimal Linear Estimation method (EOLE) and its extension to cover the case of non-Gaussian random fields are used herein to generate the two random fields of c and φ. Notice that EOLE was first proposed by [4] for the case of uncorrelated Gaussian fields, and then extended by [5] to cover the case of correlated and uncorrelated non-Gaussian fields. In this method, one should first define a stochastic grid composed of q grid points (or nodes)   …”
Section: Methods Of Generation Of Anisotropic Non-gaussian Random Fieldsmentioning
confidence: 99%
“…In other words, these parameters are cross correlated. Cross correlation structure between each pair of simulated elds was simply de ned by a cross correlation coe cient [29,30]. Cross correlated Gaussian random eld is expressed as follows:…”
Section: Cross Correlated Lognormal Random Eldsmentioning
confidence: 99%
“…Herein, fibers are placed uniformly at random in the domain, except for the influence of domain boundaries. Alternatively, by placing fibers using spatially correlated random fields [16], it has been demonstrated that regions with fewer fibers act as potential sites for fracture localization, limiting the strain capacity of the composite material [17].…”
Section: Fiber Reinforcementmentioning
confidence: 99%