A Simplified Boundary Closure for Second- and Third-Order Edge-Based Solvers with Implicit Edge-Based Gradients

In this paper, we introduce a simplified boundary closure for second- and third-order node-centered edge-based discretizations. The main idea is to employ the general accuracy-preserving boundary-flux quadrature formula, separate the flux contributions involving neighbor nodes, incorporate them into an interior edge loop, and then account for the remaining contributions in a loop over boundary nodes. This new approach effectively reduces the computational operations and eliminates the need to access neighbors in a boundary closure loop. Numerical results show that the approach can enhance iterative convergence and reduce computational time for second- and third-order edge-based solvers.

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Published
2025-07-16
DOI
https://doi.org/10.2514/6.2025-3675
Primary Topic
Advanced Numerical Methods in Computational Mathematics
Type
article
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article

A Simplified Boundary Closure for Second- and Third-Order Edge-Based Solvers with Implicit Edge-Based Gradients

Hiroaki Nishikawa
Advanced Numerical Methods in Computational Mathematics
article

A Simplified Boundary Closure for Second- and Third-Order Edge-Based Solvers with Implicit Edge-Based Gradients

Hiroaki Nishikawa
article en

Abstract

In this paper, we introduce a simplified boundary closure for second- and third-order node-centered edge-based discretizations. The main idea is to employ the general accuracy-preserving boundary-flux quadrature formula, separate the flux contributions involving neighbor nodes, incorporate them into an interior edge loop, and then account for the remaining contributions in a loop over boundary nodes. This new approach effectively reduces the computational operations and eliminates the need to access neighbors in a boundary closure loop. Numerical results show that the approach can enhance iterative convergence and reduce computational time for second- and third-order edge-based solvers.

National Institute of Aerospace (US)
Openalex Percentile: Top 82%
Advanced Numerical Methods in Computational Mathematics
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