Uncertainty quantification of cylindrical test through Wiener chaos with basis adaptation and projection

LIANG Xiao; WANG Ruili

doi:10.11883/bzycj-2018-0253

Volume 39 Issue 4

Mar. 2019

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LIANG Xiao, WANG Ruili. Uncertainty quantification of cylindrical test through Wiener chaos with basis adaptation and projection[J]. Explosion And Shock Waves, 2019, 39(4): 041408. doi: 10.11883/bzycj-2018-0253

Citation:

LIANG Xiao, WANG Ruili. Uncertainty quantification of cylindrical test through Wiener chaos with basis adaptation and projection[J]. Explosion And Shock Waves, 2019, 39(4): 041408. doi: 10.11883/bzycj-2018-0253

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Uncertainty quantification of cylindrical test through Wiener chaos with basis adaptation and projection

doi: 10.11883/bzycj-2018-0253

LIANG Xiao^{1, 2
,},
WANG Ruili^{2
,
,}

1.
Department of Mathematics, Shandong University of Science and Technology, Qingdao 266590, Shandong, China
2.
Institute of Applied Physics and Computational Mathematics, Beijing 100089, China

Received Date: 2018-07-10
Rev Recd Date: 2018-10-01

Available Online: 2019-04-25

Publish Date: 2019-04-01

Abstract

Abstract

The mathematical-physical model used to describe the detonation dynamics has many uncertain factors due to the complexity and lack of knowledge for detonation phenomenon. Quantifying and assessing the impact of input uncertainties on output of detonation systems has a direct influence on reducing the risk based on the numerical model and simulation results for detonation. The Wiener chaos based on adapted basis is used to deal with the uncertainty quantification of high-dimensional random variables for detonation simulation. The rotation transformation and projection method is used to reduce the length of truncation number. Rosenblatt transformation is used to transform the set of dependent random variables into independent random variables. The equality of probability principle is used to change the non-Gaussian random variables into standard random variables. Uncertainty quantifications of the cylinder test with high dimensional input uncertainties are studied. The statistical informations such as mean, standard deviations, and confidence intervals are presented. The simulation results coincide with the experimental data, and the accuracy of the model is validated.
- cylinder test,
- uncertainty quantification,
- adapted basis,
- JWL EOS,
- Rosenblatt transform

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References(16)

References

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