Optimal Simulation of Wind Field under Disaster Conditions based on PSO and Entropic Lattice Boltzmann Method

Abstract

The entropic lattice Boltzmann method (ELBM) is an excellent method of numerical stability among of different versions of the lattice Boltzmann method for the simulation of hydrodynamics, especially for wind field simulation application of power grid disaster conditions. In this paper, an efficient improved particle swarm optimization (PSO) algorithm is studied for optimizing calculation parameters to achieve load balancing of ELBM on nonuniform grids in a heterogeneous computing platform. We also introduce a new concept of multi-block ELBM on composite grids for realization of the ELBM simulations of incompressible driven cavity flow. These new approaches rely on a two-dimensional space-time interpolation and solving the relaxation time parameter by direct approximation optimization strategy to guarantee conservation. Our CPU–GPU implementation of multi-block ELBM based on the improved PSO algorithm not only exploits adequately multi-core CPU computing resources for load balancing, but also follows carefully optimized storage to increase coalesced access on a GPU platform. The three-dimensional-driven cavity flow simulations validate the proposed multi-block ELBM even with severely under-resolved grids. In addition, some performance metrics are investigated based on the implementations of different refined grids and threading blocks. These results exhibit the improved PSO algorithm of the ELBM method which can optimize computing resource parameters in heterogeneous platforms, and the present multi-block ELBM can substantially improve the accuracy and computational efficiency for viscous flow computations.