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- W2076227218 abstract "Inverse analysis for structural damage identification often involves an optimization process that minimizes the discrepancies between the computed responses and the measured responses. Conventional single-objective optimization approach defines the objective function by combining multiple error terms into a single one, which leads to a weaker constraint in solving the identification problem. A multi-objective approach is proposed, which minimizes multiple error terms simultaneously. Its non-domination-based convergence provides a stronger constraint that enables robust identification of damages with lower false-negative detection rate. Another merit of the proposed approach is quantified confidence in damage detection through processing Pareto-optimal solutions. Numerical examples that simulate static testing are provided to compare the proposed approach with conventional formulation based on single-objective optimization. Copyright © 2009 John Wiley & Sons, Ltd." @default.
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- W2076227218 date "2009-01-01" @default.
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- W2076227218 title "Robust structural damage identification based on multi-objective optimization" @default.
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- W2076227218 doi "https://doi.org/10.1002/nme.2726" @default.
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