Adaptive Variable Fidelity Analysis and Design Using Dynamic Fidelity Indicators
The purpose of the current study is to develop a decision making model of a dynamic fidelity indicator (DFI) for adaptive variable fidelity (VF) analysis and to apply it to practical engineering problems, including computational design optimization. The biggest advantage is considerable computation efficiency while satisfying solution accuracy. Bayesian based DFI and difference based DFI are formulated as probabilistic model validation metrics to quantify model form uncertainties attributed to the VF analysis. Two adaptive VF surrogate models of the VF kriging with regression and sample reinterpolation and the simple VF kriging with an additive bridge function are developed. The VF kriging models are integrated with the DFIs into an efficient global optimization design framework for the design problems, which was further improved by the multipoint and multi objective infill sampling criteria. Validation of the developed framework is carried out with two analytic functions for solution optimality and compu.