Abstract
We propose an extension to recently developed Relativistic Lattice Boltzmann solvers (RLBM), which allows the simulation of flows close to the free streaming limit. Following previous works Ambruş and Blaga (2018), we use product quadrature rules and select weights and nodes by separately discretizing the radial and the angular components. This procedure facilitates the development of quadrature-based RLBM with increased isotropy levels, thus improving the accuracy of the method for the simulation of flows beyond the hydrodynamic regime. In order to quantify the improvement of this discretization procedure over existing methods, we perform numerical tests of shock waves in one and two spatial dimensions in various kinetic regimes across the hydrodynamic and the free-streaming limits.
Original language | English |
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Article number | 101320 |
Number of pages | 9 |
Journal | Journal of Computational Science |
Volume | 51 |
DOIs | |
Publication status | Published - Apr 2021 |
Bibliographical note
Funding Information:The authors would like to thank Luciano Rezzolla and Lukas Weih for useful discussions. DS has been supported by the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No. 765048 . SS acknowledges funding from the European Research Council under the European Union’s Horizon 2020 framework programme (No. P/2014-2020 )/ERC Grant Agreement No. 739964 (COPMAT). AG would like to thank professor Michael Günther and professor Matthias Ehrhardt for their kind hospitality at Wuppertal University. All numerical work has been performed on the COKA computing cluster at Università di Ferrara.
Funding
The authors would like to thank Luciano Rezzolla and Lukas Weih for useful discussions. DS has been supported by the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No. 765048. SS acknowledges funding from the European Research Council under the European Union's Horizon 2020 framework programme (No. P/2014-2020)/ERC Grant Agreement No. 739964 (COPMAT). AG would like to thank professor Michael G?nther and professor Matthias Ehrhardt for their kind hospitality at Wuppertal University. All numerical work has been performed on the COKA computing cluster at Universit? di Ferrara. The authors would like to thank Luciano Rezzolla and Lukas Weih for useful discussions. DS has been supported by the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No. 765048 . SS acknowledges funding from the European Research Council under the European Union’s Horizon 2020 framework programme (No. P/2014-2020 )/ERC Grant Agreement No. 739964 (COPMAT). AG would like to thank professor Michael Günther and professor Matthias Ehrhardt for their kind hospitality at Wuppertal University. All numerical work has been performed on the COKA computing cluster at Università di Ferrara.
Funders | Funder number |
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European Union's Horizon 2020 - Research and Innovation Framework Programme | |
Università di Ferrara | |
European Union's Horizon 2020 - Research and Innovation Framework Programme | 739964 |
Marie Skłodowska‐Curie | 765048 |
University of Wuppertal | |
H2020 European Research Council | |
European Union's Horizon 2020 - Research and Innovation Framework Programme |