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This paper develops a multi-fidelity optimization under uncertainty method that uses a database of past model evaluations to serve as an approximate model. In the presented examples, the method reduces the cost of solving an optimization under uncertainty problem by up to 90%.
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This page is a summary of: Monte Carlo Information-Reuse Approach to Aircraft Conceptual Design Optimization Under Uncertainty, Journal of Aircraft, March 2016, American Institute of Aeronautics and Astronautics (AIAA),
DOI: 10.2514/1.c033352.
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