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Simple and sophisticated models of Taylor’s cylinder impact

Journal Article · · AIP Conference Proceedings
DOI:https://doi.org/10.1063/12.0020511· OSTI ID:2426754

We present a study based on the simplest possible models for Taylor’s cylinder impact problem, in addition to examina-tion 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)
Grant/Contract Number:
89233218CNA000001
OSTI ID:
2426754
Report Number(s):
LA-UR--23-25276
Journal Information:
AIP Conference Proceedings, Journal Name: AIP Conference Proceedings Journal Issue: 1 Vol. 2844; ISSN 0094-243X
Publisher:
American Institute of Physics (AIP)Copyright Statement
Country of Publication:
United States
Language:
English

References (4)

A theory for the mushrooming of flat-ended projectiles impinging on a flat rigid anvil, using energy considerations journal March 1969
Model of plastic deformation for extreme loading conditions journal January 2003
Fast strength model characterization using Bayesian statistics conference January 2020
The use of flat-ended projectiles for determining dynamic yield stress I. Theoretical considerations journal September 1948

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