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Activity Number: 462 - Making an Impact When Things Make Impacts
Type: Topic Contributed
Date/Time: Wednesday, July 31, 2019 : 8:30 AM to 10:20 AM
Sponsor: Uncertainty Quantification in Complex Systems Interest Group
Abstract #304781 Presentation
Title: Calibrating Strength Model Parameters Using Taylor Anvil Data
Author(s): Kathleen Schmidt* and Jason Bernstein and Ana Kupresanin and Nathan Barton and David Rivera and Jeffrey Florando
Companies: Lawrence Livermore National Laboratory and Lawrence Livermore National Laboratory and Lawrence Livermore National Laboratory and Lawrence Livermore National Laboratory and Lawrence Livermore National Laboratory and Lawrence Livermore National Laboratory
Keywords: Uncertainty Quantification; Materials Science; Bayesian inference; Surrogate models
Abstract:

In a Taylor anvil test, a cylinder is projected against a rigid structure and deformed upon impact. To infer the strength of the material from this data, we first employed a high-fidelity computer code, which utilizes a parametric strength model, to build an emulator model for the deformation profile of the cylinder after impact. We then performed Bayesian calibration of the strength model from digitized points of a post-experiment photo of a deformed tantalum cylinder. Moreover, we utilized data fusion techniques to simultaneously calibrate strength model parameters using both Taylor anvil data as well as data from other types of strength experiments.

LLNL-ABS-766548 This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.


Authors who are presenting talks have a * after their name.

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