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The intent of this paper is to provide an overview of modern design of experiments (DOE) techniques that can be applied in computational engineering design studies. The term modern refers to DOE techniques specifically designed for use with deterministic computer simulations. In addition, this term is used to contrast classical DOE techniques that were developed for laboratory and field experiments that possess random error sources. Several types of modern DOE methods are described including pseudo-Monte Carlo sampling, quasi-Monte Carlo sampling, Latin hypercube sampling, orthogonal array sampling, and Hammersley sequence sampling.
Giunta et al. (Mon,) studied this question.