Contribution to a conference proceedings/Contribution to a book FZJ-2024-06445

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A Backward-Characteristics Monotonicity Preserving Method for Stiff Transport Problems

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2024
Springer Heidelberg
ISBN: 978-3-031-63785-8 (print), 978-3-031-63783-4 (electronic)

24th International Conference on Computational Science, ICCS2024, MalagaMalaga, Spain, 2 Jul 2024 - 4 Jul 20242024-07-022024-07-04 Heidelberg : Springer, Lecture Notes in Computer Science 14838, () [10.1007/978-3-031-63783-4_4]

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Abstract: Convection-diffusion problems in highly convective flows can exhibit complicated features such as sharp shocks and shear layers which involve steep gradients in their solutions. As a consequence, developing an efficient computational solver to capture these flow features requires the adjustment of the local scale difference between convection and diffusion terms in the governing equations. In this study, we propose a monotonicity preserving backward characteristics scheme combined with a second-order BDF2-Petrov-Galerkin finite volume method to deal with the multiphysics nature of the problem. Unlike the conventional Eulerian techniques, the two-step backward differentiation procedure is applied along the characteristic curves to obtain a second-order accuracy. Numerical results are presented for several benchmark problems including sediment transport in coastal areas. The obtained results demonstrate the ability of the new algorithm to accurately maintain the shape of the computed solutions in the presence of sharp gradients and shocks.


Contributing Institute(s):
  1. Jülich Supercomputing Center (JSC)
Research Program(s):
  1. 5112 - Cross-Domain Algorithms, Tools, Methods Labs (ATMLs) and Research Groups (POF4-511) (POF4-511)

Appears in the scientific report 2024
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 Record created 2024-11-26, last modified 2025-02-03


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