Ignition probability prediction method based on Lagrangian flame particle tracking

A low-order ignition probability prediction method for practical engineering applications was developed using the discrete phase model (DPM) within the commercial software Fluent, combined with parallel user-defined function (UDF). The flow and mixture characteristics of the combustor were evaluated using the Lagrangian flame particle model. In addition, a kernel initialization method based on phenomenological analysis was proposed to model the energy deposition phase of the ignition process. Then, the prediction method was applied to obtain the spatial distribution of ignition probability for a typical bluff-body burner. Results indicate the following: (1) Two typical phenomena are associated with ignition failure during the ignition probability prediction process, from which the critical ignition progress factor (CIPF) for any combustor configuration can be determined; (2) Gradually increasing the number of flame particles in the initial kernel, increases the mean ignition progress factor (MIPF) and the ignition probability at the ignition position. The parameters of the initial kernel can be determined by applying the rule in conjunction with experimental data from characteristic ignition positions. (3) The spatial distribution of ignition probability for the bluff-body burner is predicted qualitatively, effectively capturing the key characteristics of the experimental results. This prediction method provides a new approach for optimizing combustor ignition in engineering design.