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  • A practical framework for generating cross correlated 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 defined by a cross correlation coefficient. Such relations result in specific properties of eigenvectors of covariance matrices of discretized field over the domain. These properties are used to decompose the eigenproblem which must normally be solved in computing the series expansion into two smaller eigenproblems. Such a decomposition represents a significant reduction of computational effort. Non-Gaussian components of a multivariate random field are proposed to be simulated via memoryless transfor
  • A practical framework for generating cross correlated 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 defined by a cross correlation coefficient. Such relations result in specific properties of eigenvectors of covariance matrices of discretized field over the domain. These properties are used to decompose the eigenproblem which must normally be solved in computing the series expansion into two smaller eigenproblems. Such a decomposition represents a significant reduction of computational effort. Non-Gaussian components of a multivariate random field are proposed to be simulated via memoryless transfor (en)
Title
  • Simulation of simply cross correlated random fields bz series expansion methods
  • Simulation of simply cross correlated random fields bz series expansion methods (en)
skos:prefLabel
  • Simulation of simply cross correlated random fields bz series expansion methods
  • Simulation of simply cross correlated random fields bz series expansion methods (en)
skos:notation
  • RIV/00216305:26110/08:PU80166!RIV10-GA0-26110___
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • P(GP103/06/P086)
http://linked.open...iv/cisloPeriodika
  • 4
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
http://linked.open.../riv/druhVysledku
http://linked.open...iv/duvernostUdaju
http://linked.open...titaPredkladatele
http://linked.open...dnocenehoVysledku
  • 394884
http://linked.open...ai/riv/idVysledku
  • RIV/00216305:26110/08:PU80166
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • Simulation, random fields, method, expansion methods (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...odStatuVydavatele
  • US - Spojené státy americké
http://linked.open...ontrolniKodProRIV
  • [C6B1F8445410]
http://linked.open...i/riv/nazevZdroje
  • Structural Safety
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...vavai/riv/projekt
http://linked.open...UplatneniVysledku
http://linked.open...v/svazekPeriodika
  • 30
http://linked.open...iv/tvurceVysledku
  • Vořechovský, Miroslav
issn
  • 0167-4730
number of pages
http://localhost/t...ganizacniJednotka
  • 26110
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