In-cylinder diesel spray combustion simulations using parallel computation: A performance benchmarking study

In the present study, in-cylinder diesel combustion simulation was performed with parallel processing on an Intel Xeon Quad-Core platform to allow both fluid dynamics and chemical kinetics of the surrogate diesel fuel model to be solved simultaneously on multiple processors. Here, Cartesian Z-Coordinate was selected as the most appropriate partitioning algorithm since it computationally bisects the domain such that the dynamic load associated with fuel particle tracking was evenly distributed during parallel computations. Other variables examined included number of compute nodes, chemistry sizes and in situ adaptive tabulation (ISAT) parameters. Based on the performance benchmarking test conducted, parallel configuration of 4-compute node was found to reduce the computational runtime most efficiently whereby a parallel efficiency of up to 75.4% was achieved. The simulation results also indicated that accuracy level was insensitive to the number of partitions or the partitioning algorithms. The effect of reducing the number of species on computational runtime was observed to be more significant than reducing the number of reactions. Besides, the study showed that an increase in the ISAT maximum storage of up to 2 GB reduced the computational runtime by 50%. Also, the ISAT error tolerance of 10−3 was chosen to strike a balance between results accuracy and computational runtime. The optimised parameters in parallel processing and ISAT, as well as the use of the in-house reduced chemistry model allowed accurate results to be produced with reduced computational runtime, especially in simulating in-cylinder reacting spray jet and soot characteristics on standard computing platforms.

► A performance benchmarking exercise is conducted for diesel combustion simulations.
► The reduced chemical mechanism shows its advantages over base and skeletal models.
► High efficiency and great reduction of CPU runtime are achieved through 4-node solver.
► Increasing ISAT memory from 0.1 to 2 GB reduces the CPU runtime by almost 35%.
► Combustion and soot processes are predicted well with minimal computational cost.