Anisotropic mesh adaptation for high-Order meshes in two dimensions

Error estimation and mesh adaptation are essential for accurate and efficient computational fluid dynamics simulations, but traditional approaches for high-order curved meshes face significant robustness issues. Traditionally, curved meshes are first made linear and then adapted and re-curved at the end of the adaptation process. Making the mesh linear and re-curving the mesh risks creating negative Jacobians for anisotropic elements, which adversely affects the robustness of the mesh adaptation process. We developed a novel method for performing anisotropic mesh adaptation on high-order curved meshes. This process extends existing edge primitive operations for mesh adaptation to high-order meshes. In contrast to the traditional procedure, our method keeps the mesh valid and curved during the entire adaptation process, leading to more robust mesh adaptation. The method extends traditional linear mesh modification operators to arbitrary-order curved meshes. Results for four test cases demonstrate that this method produces valid curved meshes with various aspect ratios. The test cases show that our method recovers optimal high-order error convergence rates and performs similarly to existing global remeshing strategies. This appraoch enables reliable automated of mesh adaptation which is necessary to realize the benefits of high-order computational fluid dynamics methods.

Authors

Institutions

Publication Details

Journal
Journal of Computational Physics
Published
2025-11-05
DOI
https://doi.org/10.1016/j.jcp.2025.114506
Citations
1
Primary Topic
Computational Fluid Dynamics and Aerodynamics
Type
article
Field-Weighted Citation Impact
1.33
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Anisotropic mesh adaptation for high-Order meshes in two dimensions

Joaquim R. R. A. Martins, Krzysztof Fidkowski, Alexander Coppeans
1 citations
Journal of Computational Physics
Computational Fluid Dynamics and Aerodynamics
1.33
article

Anisotropic mesh adaptation for high-Order meshes in two dimensions

Joaquim R. R. A. Martins, Krzysztof Fidkowski, Alexander Coppeans
article en
1 citations

Abstract

Error estimation and mesh adaptation are essential for accurate and efficient computational fluid dynamics simulations, but traditional approaches for high-order curved meshes face significant robustness issues. Traditionally, curved meshes are first made linear and then adapted and re-curved at the end of the adaptation process. Making the mesh linear and re-curving the mesh risks creating negative Jacobians for anisotropic elements, which adversely affects the robustness of the mesh adaptation process. We developed a novel method for performing anisotropic mesh adaptation on high-order curved meshes. This process extends existing edge primitive operations for mesh adaptation to high-order meshes. In contrast to the traditional procedure, our method keeps the mesh valid and curved during the entire adaptation process, leading to more robust mesh adaptation. The method extends traditional linear mesh modification operators to arbitrary-order curved meshes. Results for four test cases demonstrate that this method produces valid curved meshes with various aspect ratios. The test cases show that our method recovers optimal high-order error convergence rates and performs similarly to existing global remeshing strategies. This appraoch enables reliable automated of mesh adaptation which is necessary to realize the benefits of high-order computational fluid dynamics methods.

Journal of Computational PhysicsVol. 545
University of Michigan (US)
Openalex Percentile: Top 17%
Computational Fluid Dynamics and Aerodynamics
1.33
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.