A Realizable Filtered Intrusive Polynomial Moment Method
Graham Alldredge, Martin Frank, Jonas Kusch, Ryan McClarren

TL;DR
This paper introduces two filtering strategies for the intrusive polynomial moment method to reduce oscillations in hyperbolic problems with shocks, ensuring realizability and preserving hyperbolicity.
Contribution
It proposes realizability-preserving filters and regularization techniques for the IPM method, improving stability and accuracy in uncertain hyperbolic PDEs.
Findings
Significant reduction of spurious oscillations in numerical tests.
Filters maintain realizability and hyperbolicity of the solution.
Effective in one- and two-dimensional shock problems.
Abstract
Intrusive uncertainty quantification methods for hyperbolic problems exhibit spurious oscillations at shocks, which leads to a significant reduction of the overall approximation quality. Furthermore, a challenging task is to preserve hyperbolicity of the gPC moment system. An intrusive method which guarantees hyperbolicity is the intrusive polynomial moment (IPM) method, which performs the gPC expansion on the entropy variables. The method, while still being subject to oscillations, requires solving a convex optimization problem in every spatial cell and every time step. The aim of this work is to mitigate oscillations in the IPM solution by applying filters. Filters reduce oscillations by damping high order gPC coefficients. Naive filtering, however, may lead to unrealizable moments, which means that the IPM optimization problem does not have a solution and the method breaks down. In…
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Taxonomy
TopicsProbabilistic and Robust Engineering Design · Model Reduction and Neural Networks · Structural Health Monitoring Techniques
