https://www.scipedia.com/wd/index.php?action=history&feed=atom&title=Nauleau_et_al_2022aNauleau et al 2022a - Revision history2026-04-06T20:10:24ZRevision history for this page on the wikiMediaWiki 1.27.0-wmf.10https://www.scipedia.com/wd/index.php?title=Nauleau_et_al_2022a&diff=262806&oldid=prevMove page script: Move page script moved page Nauleau et al 1970a to Nauleau et al 2022a2022-11-25T15:06:39Z<p>Move page script moved page <a href="/public/Nauleau_et_al_1970a" class="mw-redirect" title="Nauleau et al 1970a">Nauleau et al 1970a</a> to <a href="/public/Nauleau_et_al_2022a" title="Nauleau et al 2022a">Nauleau et al 2022a</a></p>
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</td></tr></table>Move page scripthttps://www.scipedia.com/wd/index.php?title=Nauleau_et_al_2022a&diff=261708&oldid=prevJSanchez: JSanchez moved page Draft Sanchez Pinedo 984183300 to Nauleau et al 1970a2022-11-23T11:13:39Z<p>JSanchez moved page <a href="/public/Draft_Sanchez_Pinedo_984183300" class="mw-redirect" title="Draft Sanchez Pinedo 984183300">Draft Sanchez Pinedo 984183300</a> to <a href="/public/Nauleau_et_al_1970a" class="mw-redirect" title="Nauleau et al 1970a">Nauleau et al 1970a</a></p>
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</td></tr></table>JSanchezhttps://www.scipedia.com/wd/index.php?title=Nauleau_et_al_2022a&diff=261707&oldid=prevJSanchez at 11:13, 23 November 20222022-11-23T11:13:32Z<p></p>
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<td colspan='2' style="background-color: white; color:black; text-align: center;">Revision as of 11:13, 23 November 2022</td>
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<tr><td class='diff-marker'> </td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"><div>== Abstract ==</div></td><td class='diff-marker'> </td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"><div>== Abstract ==</div></td></tr>
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</table>JSanchezhttps://www.scipedia.com/wd/index.php?title=Nauleau_et_al_2022a&diff=261705&oldid=prevJSanchez at 11:13, 23 November 20222022-11-23T11:13:30Z<p></p>
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<td colspan='2' style="background-color: white; color:black; text-align: center;">Revision as of 11:13, 23 November 2022</td>
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<tr><td class='diff-marker'> </td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"></td><td class='diff-marker'> </td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"><div>This paper inscribes itself in the ongoing doctoral work of the first author which aims at adapting the immersed boundary conditions (IBC) technique to three-dimensional (3D) large eddy simulations (LES) of viscous hypersonic flows around complex vehicles. The work relies on a pre-existing in-house IBC code, HYPERION (HYPERsonic vehicle design using Immersed bOuNdaries), originally developed in two dimensions (2D) as a proof of concept that it is possible to use IBC in the presence of strongly shocked flows [4]. As a first step towards the optimization of the 3D HYPERION, we discuss in this paper a novel MPI/Open MP hybrid rasterization algorithm allowing for the detection of immersed cells in record time even for very large problems. We then consider the least-square-based reconstruction algorithm from HYPERION [4]. It was shown in the original paper that the number of neighbors used in the reconstruction is directly related to the condition number of the least-square matrix and an optimum can be found when the condition number reaches an asymptote. In 3D configurations it is found that the number of neighbors has to be very high to ensure the proper conditioning of the least-square matrix. If the computation is distributed on several MPI processes (as is always the case in 3D for realistic return times), gathering the information from that many neighbors can cause obvious communication issues it amounts to covering large stencils with unrealistically large MPI halos. We therefore introduce an algorithm designed for a hybrid MPI/OpenMP environment based on migratable tasks and the consensus algorithm developed by [9] to remedy the former shortcoming. Finally, we discuss the premise of the implementation of LES capabilities in HYPERION. The last milestone of the main author's doctoral work is indeed to study the feasibility of embedding wall laws in the IBC modeling and reconstruction algorithm to try and counteract the low accuracy of the near-wall phenomena caused by the lack of body-fitted mesh.</div></td><td class='diff-marker'> </td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"><div>This paper inscribes itself in the ongoing doctoral work of the first author which aims at adapting the immersed boundary conditions (IBC) technique to three-dimensional (3D) large eddy simulations (LES) of viscous hypersonic flows around complex vehicles. The work relies on a pre-existing in-house IBC code, HYPERION (HYPERsonic vehicle design using Immersed bOuNdaries), originally developed in two dimensions (2D) as a proof of concept that it is possible to use IBC in the presence of strongly shocked flows [4]. As a first step towards the optimization of the 3D HYPERION, we discuss in this paper a novel MPI/Open MP hybrid rasterization algorithm allowing for the detection of immersed cells in record time even for very large problems. We then consider the least-square-based reconstruction algorithm from HYPERION [4]. It was shown in the original paper that the number of neighbors used in the reconstruction is directly related to the condition number of the least-square matrix and an optimum can be found when the condition number reaches an asymptote. In 3D configurations it is found that the number of neighbors has to be very high to ensure the proper conditioning of the least-square matrix. If the computation is distributed on several MPI processes (as is always the case in 3D for realistic return times), gathering the information from that many neighbors can cause obvious communication issues it amounts to covering large stencils with unrealistically large MPI halos. We therefore introduce an algorithm designed for a hybrid MPI/OpenMP environment based on migratable tasks and the consensus algorithm developed by [9] to remedy the former shortcoming. Finally, we discuss the premise of the implementation of LES capabilities in HYPERION. The last milestone of the main author's doctoral work is indeed to study the feasibility of embedding wall laws in the IBC modeling and reconstruction algorithm to try and counteract the low accuracy of the near-wall phenomena caused by the lack of body-fitted mesh.</div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color:black; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;"></ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color:black; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">== Abstract ==</ins></div></td></tr>
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</table>JSanchezhttps://www.scipedia.com/wd/index.php?title=Nauleau_et_al_2022a&diff=261703&oldid=prevJSanchez at 11:13, 23 November 20222022-11-23T11:13:28Z<p></p>
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<td colspan='2' style="background-color: white; color:black; text-align: center;">Revision as of 11:13, 23 November 2022</td>
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<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color:black; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">                                </ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color:black; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">==Summary==</ins></div></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"></td><td class='diff-marker'> </td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color:black; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">This paper inscribes itself in the ongoing doctoral work of the first author which aims at adapting the immersed boundary conditions (IBC) technique to three-dimensional (3D) large eddy simulations (LES) of viscous hypersonic flows around complex vehicles. The work relies on a pre-existing in-house IBC code, HYPERION (HYPERsonic vehicle design using Immersed bOuNdaries), originally developed in two dimensions (2D) as a proof of concept that it is possible to use IBC in the presence of strongly shocked flows [4]. As a first step towards the optimization of the 3D HYPERION, we discuss in this paper a novel MPI/Open MP hybrid rasterization algorithm allowing for the detection of immersed cells in record time even for very large problems. We then consider the least-square-based reconstruction algorithm from HYPERION [4]. It was shown in the original paper that the number of neighbors used in the reconstruction is directly related to the condition number of the least-square matrix and an optimum can be found when the condition number reaches an asymptote. In 3D configurations it is found that the number of neighbors has to be very high to ensure the proper conditioning of the least-square matrix. If the computation is distributed on several MPI processes (as is always the case in 3D for realistic return times), gathering the information from that many neighbors can cause obvious communication issues it amounts to covering large stencils with unrealistically large MPI halos. We therefore introduce an algorithm designed for a hybrid MPI/OpenMP environment based on migratable tasks and the consensus algorithm developed by [9] to remedy the former shortcoming. Finally, we discuss the premise of the implementation of LES capabilities in HYPERION. The last milestone of the main author's doctoral work is indeed to study the feasibility of embedding wall laws in the IBC modeling and reconstruction algorithm to try and counteract the low accuracy of the near-wall phenomena caused by the lack of body-fitted mesh.</ins></div></td></tr>
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</table>JSanchezhttps://www.scipedia.com/wd/index.php?title=Nauleau_et_al_2022a&diff=261702&oldid=prevJSanchez: Created blank page2022-11-23T11:13:27Z<p>Created blank page</p>
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