Pareto-efficient combustion framework for predicting transient ignition dynamics in turbulent flames: Application to a pulsed jet-in-hot-coflow flame

The Pareto-efficient combustion (PEC) framework is extended for predicting transient ignition in turbulent flames. PEC formulation utilizes a drift term to assess the compliance of specific submodels with underlying flow-field representation. This consider autoignition delay as process interest, and time homogeneous isobaric reactor utilized surrogate. Combustion models considered are steady-state flamelet/progress variable (FPV) model finite-rate chemistry (FRC) model. Large-eddy simulations performed proposed (PEC-AI) demonstrated identify localized regions that require description order accurately capture dynamics. employed examine stochasticity environment by performing ensemble construct probability distributions locations. Comparisons measurements show ability PEC-AI capturing dynamics flame lift-off through drift-term adaptation comparable accuracy FRC at reduced cost. These results illustrate versatility targeting different response functions not only include species emissions but also processes.