Please use this identifier to cite or link to this item: https://doi.org/10.1016/j.probengmech.2005.05.007
DC FieldValue
dc.titleSimulation of strongly non-Gaussian processes using Karhunen-Loeve expansion
dc.contributor.authorPhoon, K.K.
dc.contributor.authorHuang, H.W.
dc.contributor.authorQuek, S.T.
dc.date.accessioned2014-06-17T08:25:07Z
dc.date.available2014-06-17T08:25:07Z
dc.date.issued2005-04
dc.identifier.citationPhoon, K.K., Huang, H.W., Quek, S.T. (2005-04). Simulation of strongly non-Gaussian processes using Karhunen-Loeve expansion. Probabilistic Engineering Mechanics 20 (2) : 188-198. ScholarBank@NUS Repository. https://doi.org/10.1016/j.probengmech.2005.05.007
dc.identifier.issn02668920
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/66175
dc.description.abstractThe non-Gaussian Karhunen-Loeve (K-L) expansion is very attractive because it can be extended readily to non-stationary and multi-dimensional fields in a unified way. However, for strongly non-Gaussian processes, the original procedure is unable to match the distribution tails well. This paper proposes an effective solution to this tail mismatch problem using a modified orthogonalization technique that reduces the degree of shuffling within columns containing empirical realizations of the K-L random variables. Numerical examples demonstrate that the present algorithm is capable of matching highly non-Gaussian marginal distributions and stationary/non-stationary covariance functions simultaneously to a very accurate degree. The ability to converge correctly to an abrupt lower bound in the target marginal distributions studied is noteworthy. © 2005 Elsevier Ltd. All rights reserved.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1016/j.probengmech.2005.05.007
dc.sourceScopus
dc.subjectKarhunen-Loeve expansion
dc.subjectLatin hypercube orthogonalization
dc.subjectNon-Gassian marginal distribution
dc.subjectNon-stationary covariance
dc.subjectSimulation
dc.subjectStationary covariance
dc.typeArticle
dc.contributor.departmentCIVIL ENGINEERING
dc.description.doi10.1016/j.probengmech.2005.05.007
dc.description.sourcetitleProbabilistic Engineering Mechanics
dc.description.volume20
dc.description.issue2
dc.description.page188-198
dc.description.codenPEMEE
dc.identifier.isiut000231329100008
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