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Sensitivity-analysis guided Bayesian optimization for crystal plasticity parameter identification
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DOI：10.1016/j.ijmecsci.2026.111205.png)
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Abstract
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• The framework integrates sensitivity analysis and Bayesian optimization • Sensitivity analysis cuts parameter dimension by 50–75% without sacrificing accuracy • Bayesian optimization outcompetes gradient-based and heuristic algorithms • Enable efficient and robust identification of crystal plasticity model parameters • Versatile in handling crystal plasticity models of varying complexities
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9.4
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4.5W
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