Abstract
Direct simulation of physical processes on a kinetic level is prohibitively expensive in aerospace applications due to the extremely high dimension of the solution spaces. In this paper, we consider the moment system of the Boltzmann equation, which projects the kinetic physics onto the hydrodynamic scale. The unclosed moment system can be solved in conjunction with the entropy closure strategy. Using an entropy closure provides structural benefits to the physical system of partial differential equations. Usually computing such closure of the system spends the majority of the total computational cost, since one needs to solve an ill-conditioned constrained optimization problem. Therefore, we build a neural network surrogate model to close the moment system, which preserves the structural properties of the system by design, but reduces the computational cost significantly. Numerical experiments are conducted to illustrate the performance of the current method in comparison to the traditional closure.
| Original language | English |
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| Title of host publication | AIAA Aviation and Aeronautics Forum and Exposition, AIAA AVIATION Forum 2021 |
| Publisher | American Institute of Aeronautics and Astronautics Inc, AIAA |
| ISBN (Print) | 9781624106101 |
| DOIs | |
| State | Published - 2021 |
| Event | AIAA Aviation and Aeronautics Forum and Exposition, AIAA AVIATION Forum 2021 - Virtual, Online Duration: Aug 2 2021 → Aug 6 2021 |
Publication series
| Name | AIAA Aviation and Aeronautics Forum and Exposition, AIAA AVIATION Forum 2021 |
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Conference
| Conference | AIAA Aviation and Aeronautics Forum and Exposition, AIAA AVIATION Forum 2021 |
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| City | Virtual, Online |
| Period | 08/2/21 → 08/6/21 |
Funding
The work of Cory Hauck is sponsored by the Office of Advanced Scientific Computing Research, U.S. Department of Energy, and performed at the Oak Ridge National Laboratory, which is managed by UT-Battelle, LLC under Contract No. De-AC05-00OR22725 with the U.S. Department of Energy. The United States Government retains and the publisher, by accepting the article for publication, acknowledges that the United States Government retains a non-exclusive, paid-up, irrevocable, world-wide license to publish or reproduce the published form of this manuscript, or allow others to do so, for United States Government purposes. The Department of Energy will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan (http://energy.gov/downloads/doe-public-access-plan). The authors acknowledge support by the state of Baden-Württemberg through bwHPC. Furthermore, the authors would like to thank Dr. Jonas Kusch for fruitful discussions about realizability and the minimal entropy closures as well as Jannick Wolters for support in scientific computing matters. The research is funded by the Alexander von Humboldt Foundation (Ref3.5-CHN-1210132-HFST-P).