Publication | Closed Access
Metamodeling for High Dimensional Simulation-Based Design Problems
177
Citations
27
References
2010
Year
EngineeringAccelerated DesignMultidisciplinary Design OptimizationSimulationSystem-level DesignComputer-aided DesignStructural OptimizationComputational MechanicsComputational ToolsOptimal System DesignHigh DimensionalityComputer-aided EngineeringSimulation FrameworkSystems EngineeringModeling And SimulationSpace Systems DesignDesign Space ExplorationDesignComputer EngineeringFlight OptimizationRadial Basis FunctionMetamodeling TechniqueMultiscale Modeling
Computational tools such as finite element analysis and simulation are widely used in engineering, but they are mostly used for design analysis and validation. If these tools can be integrated for design optimization, it will undoubtedly enhance a manufacturer’s competitiveness. Such integration, however, faces three main challenges: (1) high computational expense of simulation, (2) the simulation process being a black-box function, and (3) design problems being high dimensional. In the past two decades, metamodeling has been intensively developed to deal with expensive black-box functions, and has achieved success for low dimensional design problems. But when high dimensionality is also present in design, which is often found in practice, there lacks of a practical method to deal with the so-called high dimensional, expensive, and black-box (HEB) problems. This paper proposes the first metamodel of its kind to tackle the HEB problem. This paper integrates the radial basis function with high dimensional model representation into a new model, RBF-HDMR. The developed RBF-HDMR model offers an explicit function expression, and can reveal (1) the contribution of each design variable, (2) inherent linearity/nonlinearity with respect to input variables, and (3) correlation relationships among input variables. An accompanying algorithm to construct the RBF-HDMR has also been developed. The model and the algorithm fundamentally change the exponentially growing computation cost to be polynomial. Testing and comparison confirm the efficiency and capability of RBF-HDMR for HEB problems.
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