Mimetic Metrics for the DGSEM

Free-stream preservation is an essential property for numerical solvers on curvilinear grids. Key to this property is that the metric terms of the curvilinear mapping satisfy discrete metric identities, i.e., have zero divergence. Divergence-free metric terms are furthermore essential for entropy stability on curvilinear grids. We present a new way to compute the metric terms for discontinuous Galerkin spectral element methods (DGSEMs) that guarantees they are divergence-free. The proposed mimetic approach uses projections that fit within the de Rham Cohomology.

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Publication Details

Journal
Journal of Scientific Computing
Published
2025-10-14
DOI
https://doi.org/10.1007/s10915-025-03082-x
Primary Topic
Model Reduction and Neural Networks
Type
article
Field-Weighted Citation Impact
0.00

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article

Mimetic Metrics for the DGSEM

Andrés M. Rueda-Ramírez, Gregor J. Gassner, David A. Kopriva, Daniel Bach
Journal of Scientific Computing
Model Reduction and Neural Networks
article

Mimetic Metrics for the DGSEM

Andrés M. Rueda-Ramírez, Gregor J. Gassner, David A. Kopriva, Daniel Bach
article en

Abstract

Free-stream preservation is an essential property for numerical solvers on curvilinear grids. Key to this property is that the metric terms of the curvilinear mapping satisfy discrete metric identities, i.e., have zero divergence. Divergence-free metric terms are furthermore essential for entropy stability on curvilinear grids. We present a new way to compute the metric terms for discontinuous Galerkin spectral element methods (DGSEMs) that guarantees they are divergence-free. The proposed mimetic approach uses projections that fit within the de Rham Cohomology.

Journal of Scientific ComputingVol. 105(2)
Florida State University (US), University of Cologne (DE), Universidad Politécnica de Madrid (ES)
Deutsche Forschungsgemeinschaft, Bundesministerium für Bildung und Forschung
Openalex Percentile: Top 77%
Model Reduction and Neural Networks
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