Latin hypercube designs (LHDs) are widely used in many applications. As the number of design points or factors becomes large, the total number of LHDs grows exponentially. The large number of feasible designs makes the search for optimal LHDs a difficult discrete optimization problem. To tackle this problem, we propose a new population-based algorithm named LaPSO that is adapted from the standa...

Abstract This work conducts a probabilistic inquiry on how the variability of parameter defining soil deformability affects settlement foundation located soil. The analysis addresses random model to relevantly estimate probability allowable deflection exceedance. constitutive is based either single variable or field. computations incorporate direct Monte Carlo sampling and variance reduction te...

Space filling designs, which satisfy a uniformity property, are widely used in computer experiments. In the present paper the performance of non-uniform experimental designs which locate more points in a neighborhood of the boundary of the design space is investigated. These designs are obtained by a quantile transformation of the one-dimensional projections of commonly used space filling desig...

Monte Carlo simulation provides the benchmark for computational methods in reliability assessment in terms of both accuracy and robustness. However, Monte Carlo methods are well-known to be computationally expensive and, in many cases, intractable. Several improvements have been proposed to increase their computational efficiency for reliability analysis including Latin hypercube sampling; see ...

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Nested Latin hypercube designs (LHDs) are proposed for conducting multiple computer experiments with different levels of accuracy. Orthogonality is shown to be an important feature. Little is known about the construction of nested orthogonal LHDs. We present methods to construct them with two or more layers, making use of orthogonal designs. The constructed designs possess the property that the...

In this article, a novel method for the extension of sample size in Latin Hypercube Sampling (LHS) is suggested. The method can be applied when an initial LH design is employed for the analysis of functions g of a random vector. The article explains how the statistical, sensitivity and reliability analyses of g can be divided into a hierarchical sequence of simulations with subsets of samples o...

Abstract This paper presents a robust ABAQUS ® plug-in called Virtual Data Generator ( VDGen ) for generating virtual data identifying the uncertain material properties in unidirectional lamina through artificial neural networks (ANNs). The supports 3D finite element models of unit cells with square and hexagonal fibre arrays, uses Latin-Hypercube sampling methods robustly imposes periodic boun...