The automotive industry is showing high demand for efficient design of cooling systems in electric vehicles. The development of complex aero-thermodynamic systems requires reliable, high-fidelity simulations of high Reynolds number flows. We implemented a numerical solver based on the double-distribution lattice-Boltzmann method (LBM). The main advantage of the LBM, compared to the Navier-Stokes-based solvers, is its computational efficiency and intrinsic parallelism, which allows for execution on massively parallel architectures (GPUs). We have validated our GPU implementation by simulating a natural convection flow and a heated cylinder in an enclosed cavity. Both cases show very good agreement with published literature. In the future, we aim to extend the usage of the LBM framework to industry-relevant cases like the simulation of various packaging concepts for electric vehicles.     «

The automotive industry is showing high demand for efficient design of cooling systems in electric vehicles. The development of complex aero-thermodynamic systems requires reliable, high-fidelity simulations of high Reynolds number flows. We implemented a numerical solver based on the double-distribution lattice-Boltzmann method (LBM). The main advantage of the LBM, compared to the Navier-Stokes-based solvers, is its computational efficiency and intrinsic parallelism, which allows for execution...    »