AN AUTOMATED PROCESS FOR SOLVING DUCTILE DAMAGE PARAMETER SELECTION USING MACHINE LEARNING AND FINITE ELEMENT ANALYSIS

In this work we show how a machine learning algorithm based on a Bayesian optimization framework can be used in conjunction with finite element analysis to autonomously select parameter values for a ductile damage model representative of experimental test data.
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