Dakota Reference Manual  Version 6.4
Large-Scale Engineering Optimization and Uncertainty Analysis
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The Distributed Design and Analysis of Computer Experiments (DDACE) library provides the following DACE techniques: grid sampling (grid), pure random sampling (random), orthogonal array sampling (oas), latin hypercube sampling (lhs), orthogonal array latin hypercube sampling (oa_lhs), Box-Behnken (box_behnken), and central composite design (central_composite).

It is worth noting that there is some overlap in sampling techniques with those available from the nondeterministic branch. The current distinction is that the nondeterministic branch methods are designed to sample within a variety of probability distributions for uncertain variables, whereas the design of experiments methods treat all variables as having uniform distributions. As such, the design of experiments methods are well-suited for performing parametric studies and for generating data sets used in building global approximations, but are not currently suited for assessing the effect of uncertainties characterized with probability distribution. If a design of experiments over both design/state variables (treated as uniform) and uncertain variables (with probability distributions) is desired, then sampling can support this with active all specified in the Variables specification block.

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Related Keywords

  • dace : Design and Analysis of Computer Experiments