The exact savings, however, are dependent on details in the use of Latin hypercubes and on the shape of the failure surfaces of the problems. By means of different numerical examples, it is shown that more than 50% of the computer effort can be saved by using Latin hypercubes instead of simple Monte Carlo in importance sampling. Different versions of Latin hypercube sampling are also successfully employed to improve the more efficient axis orthogonal importance sampling method. The efficiency improvement is then highly dependent on the choice of sampling directions. In simple importance sampling, where the sampling centre is moved from the origin to the design point, standard Monte Carlo sampling can be replaced by Latin hypercube sampling. All rights reserved.ДЄB - Latin hypercube sampling is suggested as a tool to improve the efficiency of different importance sampling methods for structural reliability analysis.

There are several advantages to using the Latin Hypercube design: the number of samples (points) is not xed, orthogonality of the sampling points, and the sampling points do not depend on the meta model that will be constructed. N2 - Latin hypercube sampling is suggested as a tool to improve the efficiency of different importance sampling methods for structural reliability analysis. the Latin Hypercube sampling method, proposed by McKay et al. T1 - On Latin hypercube sampling for structural reliability analysis