Title: Drive-pressure optimization in ramp-wave compression experiments through differential evolution

Abstract

Ramp-wave dynamic-compression experiments are used to examine quasi-isentropic loading paths in materials. The gradual and continuous increase in pressure created by ramp waves make these types of experiments ideal for studying nonequilibrium material behavior, such as solidification kinetics. In ramp-wave compression experiments, the input drive pressure to the experimental setup may be exerted through one of a number of different mechanisms (e.g., magnetic fields, gas-gun-driven impactors, or high-energy lasers) and is generally required for simulating such experiments. Yet, regardless of the specific mechanism, this drive pressure cannot be measured directly (measurements are generally taken at a location near the back of the experimental setup through a transparent window), leading to an inverse problem where one must determine the drive pressure at the front of the experimental setup (i.e., the input) that corresponds to the particle velocity (the output) measured near the back of the experimental setup. Furthermore, we solve this inverse problem using a heuristic optimization algorithm, known as differential evolution, coupled with a multiphysics, hydrodynamics code that simulates the compression of the experimental setup. By running many rounds of forward simulations of the experimental setup, our optimization process iteratively searches for a drive pressure that is optimized to closelymore » reproduce the experimentally measured particle velocity near the back of the experimental setup. While our optimization methodology requires a significant number of hydrodynamics simulations to be conducted, many of these can be performed in parallel, which greatly reduces the time cost of our methodology. One novel aspect of our method for determining the drive pressure is that it does not require physical modeling of the drive mechanism and can thus be broadly applied to many types of ramp-compression experiments, regardless of the drive mechanism.« less

Authors:

Sterbentz, Dane M.  ^[1];

• Search DOE PAGES for author "Sterbentz, Dane M."
• Search DOE PAGES for ORCID "0000-0003-2447-2865"

Gambino, James R.  ^[2];

• Search DOE PAGES for author "Gambino, James R."
• Search DOE PAGES for ORCID "0000-0002-5834-7192"

Myint, Philip C.  ^[2];

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• Search DOE PAGES for ORCID "0000-0003-4383-5350"

Delplanque, Jean-Pierre  ^[1];

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• Search DOE PAGES for ORCID "0000-0003-1774-1641"

Springer, H. Keo  ^[2];

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• Search DOE PAGES for ORCID "0000-0002-5641-4515"

Marshall, Michelle C.  ^[2];

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• Search DOE PAGES for ORCID "0000-0001-8797-3005"

Belof, Jonathan L.  ^[2]

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• Search DOE PAGES for ORCID "0000-0001-6551-7439"

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+ Show Author Affiliations

1. Univ. of California, Davis, CA (United States)
2. Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

Publication Date:

Sat Nov 21 00:00:00 EST 2020

Research Org.:

Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)

Sponsoring Org.:

USDOE National Nuclear Security Administration (NNSA)

OSTI Identifier:

1735808

Report Number(s):

LLNL-JRNL-812830
Journal ID: ISSN 0021-8979; 1019988; TRN: US2205257

Grant/Contract Number:  

AC52-07NA27344; NA0003960

Resource Type:

Accepted Manuscript

Journal Name:

Journal of Applied Physics

Additional Journal Information:

Journal Volume: 128; Journal Issue: 19; Journal ID: ISSN 0021-8979

Publisher:

American Institute of Physics (AIP)

Country of Publication:

United States

Language:

English

Subject:

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND SUPERFLUIDITY; Shock waves; evolutionary computation; Hugoniot curve; equations of fluid dynamics; optimization algorithms; lasers; wave mechanics; phase transitions; velocimetry; hydrodynamics simulations