Zobrazeno 1 - 10
of 13 562
pro vyhledávání: '"Klingenberg, A."'
Active flux methods for hyperbolic conservation laws -- flux vector splitting and bound-preservation
The active flux (AF) method is a compact high-order finite volume method that simultaneously evolves cell averages and point values at cell interfaces. Within the method of lines framework, the existing Jacobian splitting-based point value update inc
Externí odkaz:
http://arxiv.org/abs/2411.00065
Numerically the reconstructability of unknown parameters in inverse problems heavily relies on the chosen data. Therefore, it is crucial to design an experiment that yields data that is sensitive to the parameters. We approach this problem from the p
Externí odkaz:
http://arxiv.org/abs/2409.15906
This paper studies the active flux (AF) methods for two-dimensional hyperbolic conservation laws, focusing on the flux vector splitting (FVS) for the point value update and bound-preserving (BP) limitings, which is an extension of our previous work [
Externí odkaz:
http://arxiv.org/abs/2407.13380
We develop a second-order accurate central scheme for the two-dimensional hyperbolic system of in-homogeneous conservation laws. The main idea behind the scheme is that we combine the well-balanced deviation method with the Kurganov-Tadmor (KT) schem
Externí odkaz:
http://arxiv.org/abs/2406.07185
In this paper, we propose a new MUSCL scheme by combining the ideas of the Kurganov and Tadmor scheme and the so-called Deviation method which results in a well-balanced finite volume method for the hyperbolic balance laws, by evolving the difference
Externí odkaz:
http://arxiv.org/abs/2405.08549
The active flux (AF) method is a compact high-order finite volume method that evolves cell averages and point values at cell interfaces independently. Within the method of lines framework, the point value can be updated based on Jacobian splitting (J
Externí odkaz:
http://arxiv.org/abs/2405.02447
Autor:
Achille, Alessandro, Steeg, Greg Ver, Liu, Tian Yu, Trager, Matthew, Klingenberg, Carson, Soatto, Stefano
Quantifying the degree of similarity between images is a key copyright issue for image-based machine learning. In legal doctrine however, determining the degree of similarity between works requires subjective analysis, and fact-finders (judges and ju
Externí odkaz:
http://arxiv.org/abs/2402.08919
Recent advances in wave modeling use sufficiently accurate fine solver outputs to train a neural network that enhances the accuracy of a fast but inaccurate coarse solver. In this paper we build upon the work of Nguyen and Tsai (2023) and present a n
Externí odkaz:
http://arxiv.org/abs/2402.02304
Publikováno v:
Army History, 2024 Apr 01(131), 36-62.
Externí odkaz:
https://www.jstor.org/stable/48778760
In this article, we present the foam-dg project, which provides a bridge between OpenFOAM(R) and the high-order DG (discontinuous Galerkin) framework BoSSS. Thanks to the flexibility of the coupling approach, mixed calculations where some parts of th
Externí odkaz:
http://arxiv.org/abs/2310.03573