Use of dynamic adaptive chemistry and dynamic cell clustering in computational fluid dynamics to accelerate calculation of combustion simulation of diesel engine

Based on the theory of dynamic adaptive chemistry and dynamic cell clustering, a 3D model for fuel combustion in the cylinder is constructed to study the fast calculation algorithm to accelerate the engine combustion simulation and analyze the impacts of the basic structure and the main parameters of dynamic adaptive chemistry and dynamic cell clustering on diesel engine simulation. It is found that the error threshold value of the dynamic adaptive chemistry algorithm should be set appropriately to ensure the accuracy of the simulation, and the dynamic adaptive chemistry algorithm should employ different initial search species and threshold values to meet different research objectives. Regarding the dynamic cell clustering algorithm, the data accuracy in the overall spatial range can be guaranteed, but the local location information will be missing, which will have a great impact on the prediction of pollutants. Therefore, suitable cell clustering conditions should be selected to meet the requirements of different targets.

Automated summary

A 3D model for fuel combustion in the cylinder was constructed based on the theory of dynamic adaptive chemistry and dynamic cell clustering. The study focused on developing a fast calculation algorithm to accelerate the engine combustion simulation and analyzing the impacts of dynamic adaptive chemistry and dynamic cell clustering on diesel engine simulation. The research found that appropriate error threshold values and initial search species are crucial for ensuring the accuracy of the simulation and meeting different research objectives. The study also highlighted the importance of selecting suitable cell clustering conditions to balance data accuracy and the prediction of pollutants.