Advancing the Conditional Source-Term Estimation (CSE) Framework for Turbulent Combustion Modeling and Application to Alternative Aviation Fuels

Abstract

The aviation sector faces increasing pressure to reduce greenhouse gas emissions and pollutant formation while meeting projected growth in global air traffic. Alternative aviation fuels (AAFs), including oxygenated fuels and hydrogen, represent promising pathways toward cleaner combustion, provided that their complex chemistry--turbulence interaction can be accurately predicted. Numerical simulation plays a critical role in this effort, but its reliability depends on the availability of combustion models that are both computationally efficient and sufficiently accurate for complex fuels and turbulent flow regimes. This thesis focuses on the development, assessment, and extension of the Conditional Source-term Estimation (CSE) model for the simulation of turbulent non-premixed flames, with particular emphasis on alternative aviation fuels. First, several CSE formulations are systematically evaluated, including traditional Tikhonov-regularized inversion and a Bernstein-polynomial-based approach, with the aim of improving numerical stability, accuracy, and computational efficiency. Next, a new CSE framework incorporating direct integration of detailed chemical kinetics is introduced, eliminating the reliance on pre-tabulated chemistry and enabling more robust predictions for fuels and conditions that are not well represented by conventional chemistry manifolds. The proposed developments are validated against well-documented laboratory-scale turbulent jet flames, including methane, dimethyl ether (DME), and hydrogen flames, covering different fuels and flow scenarios. The effects of differential diffusion are incorporated into the CSE-direct chemistry framework for hydrogen flames, addressing a key limitation of previous CSE implementations. An adaptive and automated CSE ensemble definition strategy is also presented and tested in large eddy simulation (LES) to capture local extinction dynamics. Overall, this work advances the CSE methodology by enhancing its flexibility, physical fidelity, and applicability to alternative aviation fuels. The results demonstrate that CSE with direct chemistry integration can achieve accurate turbulence–chemistry interaction predictions while maintaining computational efficiency, thereby providing a viable modeling framework for future simulations of advanced combustion systems relevant to sustainable aviation.