Predicting the Extinction Condition for Gas Turbine Combustors

Capturing flame blow-off (BO) or extinction limits early in the combustor design process is essential for ensuring reliable performance and reducing development time and cost. This study investigates the applicability of a low-order extinction prediction model based on a stochastic formulation of the Imperfectly Stirred Reactor (sISR) approach to rank different injector designs according to their BO behaviour. Using turbulence statistics extracted from CFD solutions near blow-off conditions, the framework reproduces air–fuel-ratio-based limits within approximately 20–30% and correctly ranks the injector designs, providing a low-cost pathway for early design screening. Building on this validated baseline, parametric studies across engine-relevant conditions reveal that the critical dissipation rate increases monotonically from idle to climb as pressure and oxidizer temperature rise, reflecting the changing balance between chemical and mixing time scales. Sensitivity analyses show robustness to the CFD-derived inputs to the model and in the number of stochastic realizations. We also assess dimensionless scaling criteria and find that empirically-corrected groups provide an approximate collapse across the investigated operating conditions, reducing variability by about 90%. Collectively, the results position sISR as an efficient, physics-based tool for predicting blow-off and for guiding targeted experiments during preliminary design of low-emission aero-engine combustors, at a fraction of the computational cost of high-fidelity LES-based methods.