Performing uncertainty quantification analysis with efficient two dimensional random fields

Abstract

Method and system are provided for uncertainty quantification analysis with efficient two dimensional (2D) random fields. The method may be used in a modeling system. The method may include providing a covariance matrix of a set of parameters with a covariance function describing an occurring real world phenomenon; and generating a random field based on the covariance matrix including a controlled rank reduction to produce a reduced-rank random field dataset provided as a data structure with data compression. Generating the random field applies rank reduction of a block circulant with circulant blocks (BCCB) representation of a covariance matrix obtained from the covariance matrix using existing symmetry of eigenvalues to eliminate redundant computations. The method may include outputting a reduced-rank random field dataset for use in a user-provided model of the modeling system for uncertainty quantification analysis and simulation of the real world phenomenon.