(untitled) (Communications in Computational Physics, 2023)
The iterative solution of the sequence of linear systems arising from three-temperature (3-T) energy equations is an essential component in the numerical simulation of radiative hydrodynamic (RHD) problem. However, due to the complicated application features of the RHD problems, solving 3-T linear systems with classical preconditioned iterative techniques is challenging. To address this difficulty, a physical-variable based coarsening two-level (PCTL) preconditioner has been proposed by dividing the fully coupled system into four individual easier-to-solve subsystems. Despite its nearly optimal complexity and robustness, the PCTL algorithm suffers from poor efficiency because of the overhead associated with the construction of setup phase and the solution of subsystems. Furthermore, the PCTL algorithm employs a fixed strategy for solving the sequence of 3-T linear systems, which completely ignores the dynamically and slowly changing features of these linear systems. To address these problems and to efficiently solve the sequence of 3-T linear systems, we propose an adaptive two-level preconditioner based on the PCTL algorithm, referred to as αSetup-PCTL. The adaptive strategies of the αSetup-PCTL algorithm are inspired by those of αSetup-AMG algorithm, which is an adaptive-setup-based AMG solver for sequence of sparse linear systems. The proposed αSetup-PCTL algorithm could adaptively employ the appropriate strategies for each linear system, and thus increase the overall efficiency. Numerical results demonstrate that, for 36 linear systems, the αSetup-PCTL algorithm achieves an average speedup of 2.2, and a maximum speedup of 4.2 when compared to the PCTL algorithm.