A review of multi-fidelity surrogates from co-kriging to neural networks for composite mechanics, with applications in prediction, optimization, and workflow integration.
Survey of multifidelity methods in uncertainty propagation, inference, and optimization.SIAM Review, 60(3):550–591, 2018
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Multi-fidelity surrogates for mechanics of composites: from co-kriging to multi-fidelity neural networks
A review of multi-fidelity surrogates from co-kriging to neural networks for composite mechanics, with applications in prediction, optimization, and workflow integration.