Year: 2024
Type: article
Abstract: In this work, we detail a novel application of inverse design and advanced manufacturing to rapidly develop and experimentally validate modifications to a shaped charge jet analog. The shaped charge jet analog comprises a copper liner, a high explosive (HE), and a silicone buffer. We apply a genetic algorithm to determine an optimal buffer design that can be placed between the liner and the HE that results in the largest possible change in jet velocity. The use of a genetic algorithm allows for discoveries of unintuitive, complex, yet optimal buffer designs. Experiments using the optimal design verified the effectiveness of the buffer and validated the machine learning approach to hydrodynamic design optimization.
Source: Journal of Applied Physics
DOI: 10.1063/5.0180712
Authors: Dylan J. Kline, Michael P. Hennessey, David K. Amondson, Steve Lin, Michael D. Grapes, Massimiliano Ferrucci, Peggy Li, H. Keo Springer, Robert V. Reeves, Kyle T. Sullivan, Jonathan L. Belof
Institution: Lawrence Livermore National Laboratory
Language: English
Subfield: Materials Chemistry
Field: Materials Science
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $3,500
OpenAlex ID: W4391878157