A lattice Boltzmann model for the compressible Euler equations with second-order accuracy

2009 ◽  
Vol 60 (1) ◽  
pp. 95-117 ◽  
Author(s):  
Jianying Zhang ◽  
Guangwu Yan ◽  
Xiubo Shi ◽  
Yinfeng Dong
2017 ◽  
Vol 2017 ◽  
pp. 1-5 ◽  
Author(s):  
Y. Peng ◽  
J. P. Meng ◽  
J. M. Zhang

Inspired by the recent success of applying multispeed lattice Boltzmann models with a non-space-filling lattice for simulating transcritical shallow water flows, the capabilities of their space-filling counterpart are investigated in this work. Firstly, two lattice models with five integer discrete velocities are derived by using the method of matching hydrodynamics moments and then tested with two typical 1D problems including the dam-break flow over flat bed and the steady flow over bump. In simulations, the derived space-filling multispeed models, together with the stream-collision scheme, demonstrate better capability in simulating flows with finite Froude number. However, the performance is worse than the non-space-filling model solved by finite difference scheme. The stream-collision scheme with second-order accuracy may be the reason since a numerical scheme with second-order accuracy is prone to numerical oscillations at discontinuities, which is worthwhile for further study.


2021 ◽  
Vol 8 (3) ◽  
pp. 1-30
Author(s):  
Matthias Maier ◽  
Martin Kronbichler

We discuss the efficient implementation of a high-performance second-order collocation-type finite-element scheme for solving the compressible Euler equations of gas dynamics on unstructured meshes. The solver is based on the convex-limiting technique introduced by Guermond et al. (SIAM J. Sci. Comput. 40, A3211–A3239, 2018). As such, it is invariant-domain preserving ; i.e., the solver maintains important physical invariants and is guaranteed to be stable without the use of ad hoc tuning parameters. This stability comes at the expense of a significantly more involved algorithmic structure that renders conventional high-performance discretizations challenging. We develop an algorithmic design that allows SIMD vectorization of the compute kernel, identify the main ingredients for a good node-level performance, and report excellent weak and strong scaling of a hybrid thread/MPI parallelization.


Sign in / Sign up

Export Citation Format

Share Document