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Volume 36, Issue 1
Development of a Less Dissipative Interface Variable Reconstruction to Solve the Euler Equations by Q Learning Method

Shing-Ian Huang, Sheng Chang Wu, Tsung-Yu Yang, Chi-Heng Ting, Yi-Jhen Wu & Yang-Yao Niu

DOI: 10.4208/cicp.OA-2022-0224

Commun. Comput. Phys., 36 (2024), pp. 160-199.

Published online: 2024-07

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  • Abstract

In this study, we propose a blend of the average of THINC-EM and MUSCL (ATM) methods based on the AUSMD scheme for solving detonation wave problems. It is well known that the simulation of the detonation problems can produce incorrect shock information or strong spurious due to the stiff source term. Accurate simulation of detonation problems plays a crucial role in the design of detonation engines. The proposed ATM method combines the MUSCL and THINC-EM methods with different weighting functions, the optimized parameters of which are determined by the Q-learning method in order to accurately capture detonation waves, shock waves, and expansion fans. To validate the proposed numerical method, one and two-dimensional shock tube and the detonation tube and nozzles are chosen as benchmark test cases. Our numerical results show that the proposed the ATM type AUSMD scheme has great potential for handling more complex detonation problems and pulse detonation engine flow problems.

  • Keywords

High resolution scheme, Euler equation, ATM method, discontinuity and detonation, Q-learning.

  • AMS Subject Headings

65Y04

  • Copyright

COPYRIGHT: © Global Science Press

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@Article{CiCP-36-160, author = {Huang , Shing-IanWu , Sheng ChangYang , Tsung-YuTing , Chi-HengWu , Yi-Jhen and Niu , Yang-Yao}, title = {Development of a Less Dissipative Interface Variable Reconstruction to Solve the Euler Equations by Q Learning Method}, journal = {Communications in Computational Physics}, year = {2024}, volume = {36}, number = {1}, pages = {160--199}, abstract = {

In this study, we propose a blend of the average of THINC-EM and MUSCL (ATM) methods based on the AUSMD scheme for solving detonation wave problems. It is well known that the simulation of the detonation problems can produce incorrect shock information or strong spurious due to the stiff source term. Accurate simulation of detonation problems plays a crucial role in the design of detonation engines. The proposed ATM method combines the MUSCL and THINC-EM methods with different weighting functions, the optimized parameters of which are determined by the Q-learning method in order to accurately capture detonation waves, shock waves, and expansion fans. To validate the proposed numerical method, one and two-dimensional shock tube and the detonation tube and nozzles are chosen as benchmark test cases. Our numerical results show that the proposed the ATM type AUSMD scheme has great potential for handling more complex detonation problems and pulse detonation engine flow problems.

}, issn = {1991-7120}, doi = {https://doi.org/10.4208/cicp.OA-2022-0224}, url = {http://global-sci.org/intro/article_detail/cicp/23300.html} }
TY - JOUR T1 - Development of a Less Dissipative Interface Variable Reconstruction to Solve the Euler Equations by Q Learning Method AU - Huang , Shing-Ian AU - Wu , Sheng Chang AU - Yang , Tsung-Yu AU - Ting , Chi-Heng AU - Wu , Yi-Jhen AU - Niu , Yang-Yao JO - Communications in Computational Physics VL - 1 SP - 160 EP - 199 PY - 2024 DA - 2024/07 SN - 36 DO - http://doi.org/10.4208/cicp.OA-2022-0224 UR - https://global-sci.org/intro/article_detail/cicp/23300.html KW - High resolution scheme, Euler equation, ATM method, discontinuity and detonation, Q-learning. AB -

In this study, we propose a blend of the average of THINC-EM and MUSCL (ATM) methods based on the AUSMD scheme for solving detonation wave problems. It is well known that the simulation of the detonation problems can produce incorrect shock information or strong spurious due to the stiff source term. Accurate simulation of detonation problems plays a crucial role in the design of detonation engines. The proposed ATM method combines the MUSCL and THINC-EM methods with different weighting functions, the optimized parameters of which are determined by the Q-learning method in order to accurately capture detonation waves, shock waves, and expansion fans. To validate the proposed numerical method, one and two-dimensional shock tube and the detonation tube and nozzles are chosen as benchmark test cases. Our numerical results show that the proposed the ATM type AUSMD scheme has great potential for handling more complex detonation problems and pulse detonation engine flow problems.

Huang , Shing-IanWu , Sheng ChangYang , Tsung-YuTing , Chi-HengWu , Yi-Jhen and Niu , Yang-Yao. (2024). Development of a Less Dissipative Interface Variable Reconstruction to Solve the Euler Equations by Q Learning Method. Communications in Computational Physics. 36 (1). 160-199. doi:10.4208/cicp.OA-2022-0224
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