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20232026
most citedActive flux methods for hyperbolic conservation laws -- flux vector splitting and bound-preservation

9 citations · 9 across the 15 of their papers we have counts for

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Showing 2024Show all

6 papers · 1 filter

math.NA2024

Analysis of the multi-dimensional semi-discrete Active Flux method using the Fourier transform

Wasilij Barsukow, Janina Kern, Christian Klingenberg +1

The degrees of freedom of Active Flux are cell averages and point values along the cell boundaries. These latter are shared between neighbouring cells, which gives rise to a global…

math.NA2024★ 9 cited

Active flux methods for hyperbolic conservation laws -- flux vector splitting and bound-preservation

Junming Duan, Wasilij Barsukow, Christian Klingenberg

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 f…

math.NA2024

Local sensitivity-preserving random data down-sampling for experimental design

Kathrin Hellmuth, Christian Klingenberg, Qin Li

The quality of numerical reconstructions for unknown parameters in inverse problems depends fundamentally on the selection of experimental data. To ensure a robust reconstruction,…

math.NA2024

Active flux methods for hyperbolic conservation laws -- flux vector splitting and bound-preservation: Two-dimensional case

Junming Duan, Wasilij Barsukow, Christian Klingenberg

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-p…

math.NA2024

Active flux methods for hyperbolic conservation laws -- flux vector splitting and bound-preservation: One-dimensional case

Junming Duan, Wasilij Barsukow, Christian Klingenberg

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 fr…

math.AP2024

Efficient Numerical Wave Propagation Enhanced By An End-to-End Deep Learning Model

Luis Kaiser, Richard Tsai, Christian Klingenberg

In a variety of scientific and engineering domains, the need for high-fidelity and efficient solutions for high-frequency wave propagation holds great significance. Recent advances…