Mathematics and simulations of shock and detonation at Los Alamos National Laboratory
When:
 Thursday, September 24, 2020 from 3:00pm to 4:00pm
Where:
 Webex Meeting number: 120 556 7048 Password: applied
Description:

Abstract: A shock, in the mathematical sense, is a discontinuous change in a material state. Physically, shocks can be induced by highspeed impacts or explosive detonations. Modeling the physics of a material’s reaction to a shock combines the mathematics of numerical analysis, ordinary differential equations, and partial differential equations. At our national laboratories, shocks through explosives, metals, and polymers are studied by mathematicians, statisticians, experimental physicists, and engineers to better predict behavior in highenergy environments. As our ability to simulate multiphysics phenomena has improved, the importance of highfidelity shock modeling has increased. Though shocks and detonations have been modeled at Los Alamos since the 1940s, new physics phenomena are constantly discovered through experiments. Mathematical models of new phenomena are then created and these models are included in simulation. In this talk we will review the mathematical formulation of shock phenomena and demonstrate some complex shock behavior through simulation. We’ll also describe a few of the key experiments used to study shocks and explosive detonation for a range of materials and discuss some of the open research questions in the field.
Kyle Hickmann from DXCP8: Verification & Analysis, Los Alamos National Laboratory
received his PhD in mathematics at Oregon State University for work in inverse problems related to acoustic imaging methods. In particular his dissertation focused on proving theorems related to the unique reconstruction of acoustic heterogeneities from ultrasound observations in which the source is also unknown. Kyle's research has focused on the interplay between mathematical models and data leading to research in the fields of disease forecasting, space weather forecasting, inverse problems in seismic imaging, and general mathematics of inverse problems and machine learning. Currently Kyle is a staff scientist at Los Alamos National Laboratory within the Verification and Analysis group of XComputational Physics. His current work focuses on using deep neural networks to infer material properties from shockexperiment observations.
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