GPU Accelerated LES-FGM Modelling for Industrial Combustion Applications

Abstract Due to the ever-increasing use of Large Eddy Simulation (LES) for assessing gas turbine combustor flow and mixing fields, flame position and flame dynamics, methods to reduce the computational costs of such simulations are desirable. One such method to achieve this is to utilize advanced High Performance Computing (HPC) architectures such as General Purpose Graphical Processing Units (GPGPUs). In this paper, the Simcenter STAR-CCM+® solver, with the ability to run LES and flamelet based combustion models using GPUs, is used to assess the benefits of using GPU architecture compared to traditional Central Processing Units (CPUs). LES simulations using the Flamelet Generated Manifold (FGM) combustion model are assessed across a series of test cases: A diffusion jet flame, a pressurized annular combustor and a swirl stabilized industrial gas turbine Dry Low Emission (DLE) combustor provided by Siemens Energy Industrial Turbomachinery Ltd, Lincoln, UK. Numerical simulations using GPUs and CPUs are compared in terms of solution similarity, accuracy in relation to experimental data, computational cost and power consumption. The computational performance of the FGM model with GPU is quantified through comparison to a non-reacting simulation on the same computational grid. It is demonstrated that the use of GPU architectures can result in high-fidelity combustion modelling within the required turn-around times of engineering design cycles whilst maintaining a similar solution and level of accuracy as a traditional CPU based simulation.