Simple and deep surrogate models for Taylor cylinders and shaped charges

We characterize strength model sensitivities of Taylor cylinders and shaped charges using ensembles of simulations based on the FLAG hydrocode from Los Alamos National Laboratory. We apply singular value decomposition and neural networks, for regression and parameter estimation, based on simulations and experimental data. Results will be presented for the Preston-Tonks-Wallace and Johnson-Cook models of plastic deformation.