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International Journal for Uncertainty Quantification
インパクトファクター: 3.259 5年インパクトファクター: 2.547 SJR: 0.417 SNIP: 0.8 CiteScore™: 1.52

ISSN 印刷: 2152-5080
ISSN オンライン: 2152-5099

Open Access

International Journal for Uncertainty Quantification

DOI: 10.1615/Int.J.UncertaintyQuantification.2020030630
pages 83-100

UNCERTAINTY QUANTIFICATION OF DETONATION THROUGH ADAPTED POLYNOMIAL CHAOS

Xiao Liang
School of Mathematics and System Science, Shandong University of Science and Technology, Qingdao, Shandong, China and Sony Astani Department of Civil and Environmental Engineering, University of Southern California, Los Angeles, CA
R. Wang
Institute of Applied Physics and Computational Mathematics, Beijing, China
Roger Ghanem
Sony Astani Department of Aerospace and Mechanical Engineering, University of Southern California, 210 KAP Hall, Los Angeles, California 90089, USA

要約

Mathematical models used to describe detonation consist usually of coupled nonlinear partial differential equations, with phenomena occurring at a multitude of scales. While numerical solutions of these problems require significant computational resources, the evolution of the physics along multiple spatial and temporal scales makes the associated predictions sensitive to fluctuations that are beyond normal experimental control. Modeling, characterizing, and propagating uncertainties in predictions of detonation dynamics exacerbates both the mathematical, algorithmic, and computational challenges. These challenges are addressed in the present paper by using basis adaptation in the context of polynomial chaos expansions. The multivariate Rosenblatt transformation is used to first map all the random variables to independent Gaussian variables, following which a rotation is affected on these Gaussians that is adapted to any specified quantity of interest. Thus, accurate estimates of statistical moments and even probability density functions are obtained at specified Lagrangian reference points.

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