ERROR EVALUATION OF 3 RANDOM-FIELD GENERATORS

The use of multidimensional random fields to model real engineering systems is gaining acceptance as personal computer systems become increasingly powerful. The accuracy of such models depends directly on the accuracy of the algorithm used to generate realizations of the representative random fields; there is a need to evaluate and compare various random-field generators. To address the issue, three common random field generators are considered in this paper: (1) The fast Fourier transform (FFT) method; (2) the Turning bands method (TBM); and (3) the local average subdivision (LAS) method. For each, an ensemble of realizations of a two-dimensional homogeneous Gauss-Markov process is generated and the field mean, variance, and covariance structures are checked for statistical accuracy. Concerns such as ease of use and efficiency are also considered. All three methods have distinct advantages and disadvantages, and the choice of algorithm will depend on the particular application. A number of guidelines and suggestions are made to help avoid or minimize problems associated with each method.