TY - JOUR
T1 - Hierarchical micro-macro acceleration for moment models of kinetic equations
AU - Koellermeier, Julian
AU - Vandecasteele, Hannes
PY - 2023/9/1
Y1 - 2023/9/1
N2 - Fluid dynamical simulations are often performed using cheap macroscopic models like the Euler equations. For rarefied gases under near-equilibrium conditions, however, macroscopic models are not sufficiently accurate and a simulation using more accurate microscopic models is often expensive. In this paper, we introduce a hierarchical micro-macro acceleration based on moment models that combines the speed of macroscopic models and the accuracy of microscopic models. The hierarchical micro-macro acceleration is based on a flexible four step procedure including a micro step, restriction step, macro step, and matching step. We derive several new micro-macro methods from that and compare to existing methods. In 1D and 2D test cases, the new methods achieve high accuracy and a large speedup.
AB - Fluid dynamical simulations are often performed using cheap macroscopic models like the Euler equations. For rarefied gases under near-equilibrium conditions, however, macroscopic models are not sufficiently accurate and a simulation using more accurate microscopic models is often expensive. In this paper, we introduce a hierarchical micro-macro acceleration based on moment models that combines the speed of macroscopic models and the accuracy of microscopic models. The hierarchical micro-macro acceleration is based on a flexible four step procedure including a micro step, restriction step, macro step, and matching step. We derive several new micro-macro methods from that and compare to existing methods. In 1D and 2D test cases, the new methods achieve high accuracy and a large speedup.
UR - https://doi.org/10.1016/j.jcp.2023.112194
U2 - 10.1016/j.jcp.2023.112194
DO - 10.1016/j.jcp.2023.112194
M3 - Article
SN - 0021-9991
VL - 488
JO - Journal of computational physics
JF - Journal of computational physics
M1 - 112194
ER -