Uncertainty quantification for high explosive reactant and product equations of state

Author:

Lindquist Beth A.1ORCID,Jadrich Ryan B.1ORCID,Heras Rivera Juampablo E.23ORCID,Rondini Lucia I.24ORCID

Affiliation:

1. Applied Physics, Los Alamos National Laboratory 1 , Los Alamos, New Mexico 87545, USA

2. X-Computational Physics, Los Alamos National Laboratory 2 , Los Alamos, New Mexico 87545, USA

3. Department of Mathematics and Statistics, University of New Mexico 3 , Albuquerque, New Mexico 87106, USA

4. Department of Physics, Columbia University 4 , New York City, New York 10027, USA

Abstract

Equations of state (EOSs) are typically represented as physics-informed models with tunable parameters that are adjusted to replicate calibration data as closely as possible. Uncertainty quantification (UQ) allows for the development of an ensemble of EOS parameters that are consistent with the calibration data instead of a single EOS. In this work, we perform UQ for the reactant and product EOSs for a variety of high explosives (HEs). In doing so, we demonstrate a strategy for dealing with heterogeneous (both experimental and calculated) data. We also use a statistical distance metric to quantify the differences between the various HEs using the UQ results.

Funder

U.S. Department of Energy

Publisher

AIP Publishing

Subject

General Physics and Astronomy

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Posterior Covariance Matrix Approximations;Journal of Verification, Validation and Uncertainty Quantification;2024-03-01

2. First-Principles Performance Prediction of High Explosives Enabled by Machine Learning;The Journal of Physical Chemistry C;2024-02-28

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3