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dc.contributor.authorGrigoriu, M.en_US
dc.contributor.authorBalopoulou, S.
dc.date.accessioned2010-07-29T14:16:18Zen_US
dc.date.accessioned2010-08-17T17:10:46Zen_US
dc.date.accessioned2014-02-10T20:23:45Z
dc.date.available2010-07-29T14:16:18Zen_US
dc.date.available2010-08-17T17:10:46Zen_US
dc.date.available2014-02-10T20:23:45Z
dc.date.issued1992en_US
dc.identifier92-0015en_US
dc.identifier.govdocPB93-127496en_US
dc.identifier.urihttp://hdl.handle.net/10477/752en_US
dc.description.abstractA unified method is developed for simulating realizations of real-valued stationary Gaussian processes, vector processes, fields, and vector fields. The method has direct applications to earthquake engineering. Realizations of Gaussian processes and vector processes can be used to model seismic ground accelerations at single and multiple sites. Gaussian random fields can provide representations of the spatial variation of soil properties that need to be considered in earthquake engineering when dealing with systems extending over large areas such as pipeline systems. The proposed method involves parametric random models consisting of superpositions of deterministic functions of time or space with random fields. The proposed simulation method is efficient and uses algorithms for generating realizations of random processes and fields that are similar to simulation techniques based on ARMA models. Several examples are presented to demonstrate the proposed simulation method and evaluate its efficiency and accuracy.en_US
dc.description.sponsorshipCornell Universityen_US
dc.format.extent88en_US
dc.titleA Simulation Method for Stationary Gaussian Random Functions Based on the Sampling Theoremen_US


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