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- W2335460277 abstract "A level-set-based multistage metamodeling approach is developed for design optimization. Different from the existing objective-oriented sequential sampling methods, where the design objective and constraints have to be combined into a single response of interest, our method offers the flexibility of building metamodels for multiple responses (objective/constraints) simultaneously. Uncertainty quantification (UQ) is introduced for each metamodel to represent the confidence interval due to the lack of sufficient samples at the early stages of metamodeling. Based on the extreme values of the optimal solution identified within the confidence interval, the level set method (LSM), together with a series of Boolean operations, is used to identify the region(s) of interests with arbitrary topologies. Introducing LSM facilitates region manipulations, representation of disconnected regions of interest, and visualization for design exploration. Through mathematical benchmark examples and an engineering design problem, we demonstrate that the proposed method possesses a superior efficiency in design exploration to the conventional sequential sampling strategy and allows the use of multiple samples at each sampling stage. As the metamodeling process moves on, the region of interests is progressively reduced, and the optimal design is asymptotically approached. Our results are compared with those from one-stage metamodeling using the Optimal Latin Hypercubes (OLH) experiments. Our study shows that the proposed method can effectively capture the region of interests with any shape/topology and locate the optimum design with improved efficiency." @default.
- W2335460277 created "2016-06-24" @default.
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- W2335460277 date "2008-04-07" @default.
- W2335460277 modified "2023-10-05" @default.
- W2335460277 title "A Level-Set-Based Multistage Metamodeling Approach for Design Optimization" @default.
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- W2335460277 doi "https://doi.org/10.2514/6.2008-2144" @default.
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