Development of a Less Dissipative Interface Variable Reconstruction to Solve the Euler Equations by Q Learning Method (Communications in Computational Physics, 2024)
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 incorrectshock information or strong spurious due to the stiff source term. Accurate simulationof detonation problems plays a crucial role in the design of detonation engines. Theproposed ATM method combines the MUSCL and THINC-EM methods with differentweighting functions, the optimized parameters of which are determined by the Q-learning method in order to accurately capture detonation waves, shock waves, andexpansion fans. To validate the proposed numerical method, one and two-dimensionalshock 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 hasgreat potential for handling more complex detonation problems and pulse detonationengine flow problems.
Keywords: High resolution scheme; Euler equation; ATM method; discontinuity and detonation; Q-learning.