Bound-Preserving Point-Average-Moment PolynomiAl-Interpreted (PAMPA) Scheme: One-Dimensional Case

We propose a bound-preserving (BP) Point-Average-Moment PolynomiAl-interpreted (PAMPA) scheme by blending third-order and first-order constructions. The originality of the present construction is that it does not need any explicit reconstruction within each element, and therefore the construction is very flexible. The scheme employs a classical blending approach between a first-order BP scheme and a high-order scheme that does not inherently preserve bounds. The proposed BP PAMPA scheme demonstrates effectiveness across a range of problems, from scalar cases to systems such as the Euler equations of gas dynamics. We derive optimal blending parameters for both scalar and system cases, with the latter based on the recent geometric quasi-linearization (GQL) framework of [Wu & Shu, SIAM Review, 65 (2023), pp. 1031–1073]. This yields explicit, optimal blending coefficients that ensure positivity and control spurious oscillations in both point values and cell averages. This framework incorporates a convex blending of fluxes and residuals from both high-order and first-order updates, facilitating a rigorous BP property analysis. Sufficient conditions for the BP property are established, ensuring robustness while preserving high-order accuracy. Numerical tests confirm the effectiveness of the BP PAMPA scheme on several challenging problems.

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Publication Details

Journal
Universität Zürich, ZORA
Published
2025-12-14
DOI
https://doi.org/10.5167/uzh-281403
Primary Topic
Advanced Numerical Methods in Computational Mathematics
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article
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article

Bound-Preserving Point-Average-Moment PolynomiAl-Interpreted (PAMPA) Scheme: One-Dimensional Case

Yongle Liu, Miaosen Jiao, Rémi Abgrall, Kailiang Wu
Universität Zürich, ZORA
Advanced Numerical Methods in Computational Mathematics
article

Bound-Preserving Point-Average-Moment PolynomiAl-Interpreted (PAMPA) Scheme: One-Dimensional Case

Yongle Liu, Miaosen Jiao, Rémi Abgrall, Kailiang Wu
article en

Abstract

We propose a bound-preserving (BP) Point-Average-Moment PolynomiAl-interpreted (PAMPA) scheme by blending third-order and first-order constructions. The originality of the present construction is that it does not need any explicit reconstruction within each element, and therefore the construction is very flexible. The scheme employs a classical blending approach between a first-order BP scheme and a high-order scheme that does not inherently preserve bounds. The proposed BP PAMPA scheme demonstrates effectiveness across a range of problems, from scalar cases to systems such as the Euler equations of gas dynamics. We derive optimal blending parameters for both scalar and system cases, with the latter based on the recent geometric quasi-linearization (GQL) framework of [Wu & Shu, SIAM Review, 65 (2023), pp. 1031–1073]. This yields explicit, optimal blending coefficients that ensure positivity and control spurious oscillations in both point values and cell averages. This framework incorporates a convex blending of fluxes and residuals from both high-order and first-order updates, facilitating a rigorous BP property analysis. Sufficient conditions for the BP property are established, ensuring robustness while preserving high-order accuracy. Numerical tests confirm the effectiveness of the BP PAMPA scheme on several challenging problems.

Universität Zürich, ZORA
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Advanced Numerical Methods in Computational Mathematics
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Bound-Preserving Point-Average-Moment PolynomiAl-Interpreted (PAMPA) Scheme: One-Dimensional Case — Yongle Liu, Miaosen Jiao, et al. · Universität Zürich, ZORA (2025) | TGRS Research Map | TGRS