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Meeting 2019 TMS Annual Meeting & Exhibition
Symposium Computational Approaches for Big Data, Artificial Intelligence and Uncertainty Quantification in Computational Materials Science
Presentation Title A Reification Approach to Modeling Material Response by Fitting Johnson Cook Parameters
Author(s) Jaylen James, Austin Gerlt, Manny Gonzales, Eric Payton, Reji John, Ibrahim Karaman, Raymundo Arroyave, Douglas Allaire
On-Site Speaker (Planned) Jaylen James
Abstract Scope The dynamic stress-strain response of a material can be described by a number of different models of varying fidelity. However, the inherent fidelity of the model itself can be hindered by experimental variability. A reification approach is presented for fitting a model to experimental measurements with inherent scatter, and is demonstrated for determining optimum parameters of a Johnson-Cook (J-C) model. Quasi-static and high-strain-rate tensile and compression tests with nominally identical input parameters were performed and fused to obtain the reified stress-strain data. Next, an optimization was performed to determine the best fit J-C parameters for the fused model. The parameters of the fused model are used to simulate the upper and lower bounds of material response in simulated Taylor Anvil tests. The reified J-C model is then compared with the J-C model fitted to the mean response of the stress-strain experimental curves.
Proceedings Inclusion? Planned: Supplemental Proceedings volume

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