Publication | Closed Access
Overview of Modern Design of Experiments Methods for Computational Simulations (Invited)
374
Citations
12
References
2003
Year
Numerical AnalysisEngineeringDirect Numerical SimulationMonte Carlo MethodsOptimal Experimental DesignSimulationModern DesignExperiments MethodsDoe TechniquesComputational MechanicsSimulation MethodologyNumerical SimulationSystems EngineeringNumerical ExperimentModeling And SimulationModern Doe MethodsMonte CarloDesignComputational SimulationsComputer EngineeringLarge-scale SimulationMonte Carlo SamplingComputational ScienceSoftware TestingMonte Carlo Method
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.
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