Uncertainty quantification of turbulent premixed flames

This thesis presents an uncertainty quantification (UQ) study of turbulent premixed flames, focusing on the impact of uncertainties in operating conditions on the normalized consumption speed. Namely, temperature, pressure, and equivalence ratio are the operating conditions that are under study. Due to significant computational demands associated with direct MC methods for UQ, surrogate modeling techniques including Polynomial Chaos Expansion (PCE), Stochastic Collocation (SC), and Gaussian Process (GP) are evaluated based on efficiency and accuracy. Through this study, PCE is identified as the optimal surrogate model due to its accuracy and significantly reduced computational costs. PCE is subsequently applied to investigate how variability in temperature, pressure, and equivalence ratio affect the normalized consumption speed of turbulent premixed flames. Results highlight that the normalized consumption speed has considerable sensitivity to variations in temperature and equivalence ratio, with nonlinear behaviors shown through probability density functions and statistical metrics. Pressure variations had only small impacts on the normalized consumption speed of turbulent premixed flames. The framework employed in this study can be applied to other complex combustion simulations.