A minimally invasive, efficient method for propagation of full‐field uncertainty in solid dynamics

We present a minimally invasive method for forward propagation of material property uncertainty to full‐field quantities of interest in solid dynamics. Full‐field uncertainty quantification enables the design of complex systems where quantities of interest, such as failure points, are not known a pr...

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Veröffentlicht in:International journal for numerical methods in engineering 2021-12, Vol.122 (23), p.6955-6983
Hauptverfasser: Jones, Reese E., Redle, Michael T., Kolla, Hemanth, Plews, Julia A.
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container_end_page 6983
container_issue 23
container_start_page 6955
container_title International journal for numerical methods in engineering
container_volume 122
creator Jones, Reese E.
Redle, Michael T.
Kolla, Hemanth
Plews, Julia A.
description We present a minimally invasive method for forward propagation of material property uncertainty to full‐field quantities of interest in solid dynamics. Full‐field uncertainty quantification enables the design of complex systems where quantities of interest, such as failure points, are not known a priori . The method, motivated by the well‐known probability density function (PDF) propagation method of turbulence modeling, uses an ensemble of solutions to provide the joint PDF of desired quantities at every point in the domain. A small subset of the ensemble is computed exactly, and the remainder of the samples are computed with approximation of the evolution equations based on those exact solutions. Although the proposed method has commonalities with traditional interpolatory stochastic collocation methods applied directly to quantities of interest, it is distinct and exploits the parameter dependence and smoothness of the driving term of the evolution equations. The implementation is model independent, storage and communication efficient, and straightforward. We demonstrate its efficiency, accuracy, scaling with dimension of the parameter space, and convergence in distribution with two problems: a quasi‐one‐dimensional bar impact, and a two material notched plate impact. For the bar impact problem, we provide an analytical solution to PDF of the solution fields for method validation. With the notched plate problem, we also demonstrate good parallel efficiency and scaling of the method.
doi_str_mv 10.1002/nme.6818
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Full‐field uncertainty quantification enables the design of complex systems where quantities of interest, such as failure points, are not known a priori . The method, motivated by the well‐known probability density function (PDF) propagation method of turbulence modeling, uses an ensemble of solutions to provide the joint PDF of desired quantities at every point in the domain. A small subset of the ensemble is computed exactly, and the remainder of the samples are computed with approximation of the evolution equations based on those exact solutions. Although the proposed method has commonalities with traditional interpolatory stochastic collocation methods applied directly to quantities of interest, it is distinct and exploits the parameter dependence and smoothness of the driving term of the evolution equations. The implementation is model independent, storage and communication efficient, and straightforward. We demonstrate its efficiency, accuracy, scaling with dimension of the parameter space, and convergence in distribution with two problems: a quasi‐one‐dimensional bar impact, and a two material notched plate impact. For the bar impact problem, we provide an analytical solution to PDF of the solution fields for method validation. 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Full‐field uncertainty quantification enables the design of complex systems where quantities of interest, such as failure points, are not known a priori . The method, motivated by the well‐known probability density function (PDF) propagation method of turbulence modeling, uses an ensemble of solutions to provide the joint PDF of desired quantities at every point in the domain. A small subset of the ensemble is computed exactly, and the remainder of the samples are computed with approximation of the evolution equations based on those exact solutions. Although the proposed method has commonalities with traditional interpolatory stochastic collocation methods applied directly to quantities of interest, it is distinct and exploits the parameter dependence and smoothness of the driving term of the evolution equations. The implementation is model independent, storage and communication efficient, and straightforward. 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source Wiley Online Library Journals Frontfile Complete
subjects Collocation methods
Complex systems
Computation
Evolution
Exact solutions
full field uncertainty
Material properties
material property uncertainty
Mathematical models
Parameters
probability density function
Probability density functions
Propagation
Smoothness
solid dynamics
Uncertainty
uncertainty propagation
title A minimally invasive, efficient method for propagation of full‐field uncertainty in solid dynamics
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