Simple and Sophisticated Models of Taylor's Cylinder Impact

Technical Report · Tue Sep 26 00:00:00 EDT 2023

DOI:https://doi.org/10.2172/2378008· OSTI ID:2378008

Sjue, Sky K. ^[1]; Hickmann, Kyle Scott ^[1]; Nguyen-Fotiadis, Nga Thi Thuy ^[1]

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1. Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)

We present a study based on the simplest possible models for Taylor’s cylinder impact problem, in addition to examination of using convolutional neural networks (CNNs) to map cylinder profiles to strength calibrations. We find that the approximate treatments of Taylor and Hawkyard compare well with hydrodynamic simulations using an equivalent assumption of constant flow stress. The CNN models prove to be well suited to successfully infer parameterizations of the Preston-Tonks-Wallace model of plastic deformation based on the deformed profile of an impacted cylinder

• Research Organization: Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)
• Sponsoring Organization: USDOE National Nuclear Security Administration (NNSA)
• DOE Contract Number: 89233218CNA000001
• OSTI ID: 2378008
• Report Number(s): LA-UR--23-25276
• Country of Publication: United States
• Language: English

Related Subjects

36 MATERIALS SCIENCE