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Random field representation methods

version (27.5 KB) by Felipe Uribe
Implementation of EOLE, OSE and K-L (Discrete, Galerkin & Nyström) methods for 1D random fields


Updated 03 Aug 2015

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Different covariance/correlation kernels are defined in order to illustrate the implementation of three series expansion methods for the representation of 1D random fields: the 'expansion optimal linear estimator (EOLE)', the orthogonal series expansion (OSE)' and the 'Karhunen-Loève (K-L)' methods. The K-L method is particularly implemented using Discrete, Nyström and Galerkin methods (with local and global shape functions). The main references were the report "Stochastic finite element methods and reliability" by Sudret and Der Kiureghian, but also the book "Stochastic finite elements: A spectral approach" by Ghanem and Spanos.
Several references to equations and useful comments are written in order to provide a better understanding of the codes. The programs estimate the corresponding eigenvalues and eigenvectors of the covariance kernel, and plot the variance of the estimators and several random field realizations.
It is worth mentioning that a different implementation of these methods can be found in the FERUM software

Any suggestions, corrections and/or improvements will be kindly accepted :-)

Comments and Ratings (4)

zhang hongbo

do you have any reference for your functions?

Did you compare your EOLE simulation results with FERUM implementation by any chance?


MATLAB Release Compatibility
Created with R2014a
Compatible with any release
Platform Compatibility
Windows macOS Linux