Youcef SEHILI thesis defense

Internal combustion engines play a crucial role in our modern society, powering a variety of applications ranging from transportation to power generators. Given the growing challenges related to efficiency, emissions, and sustainability, a deep understanding and precise modeling of combustion are essential. This thesis is devoted to modeling dual fuel engines. The aim is to make significant contributions to the understanding, modeling, and optimization of combustion in these engines. Contributions include the improvement of existing models, experimental validation, characterization of engine performance in various combustion modes, and the proposal of modeling and optimization strategies to reduce emissions and improve energy efficiency. The thesis presents several lines of exploitation based on various tools and approaches. A 0D predictive model was developed developed for dual fuel engine operating with a mixture of natural gas and hydrogen as the primary fuel. Subsequently, the thesis addresses the modeling of issues limiting the operation of the dual fuel engine, such as knocking and injector overheating. The decarbonization of dual fuel engines is then implemented using alternative fuels such as ammonia and methanol, based on 3D simulations. Finally, innovative meta-models have been developed for engine optimization, including a new multi-fidelity modeling approach and multi-objective optimization. The thesis results provide significant advancements in the modeling and optimization of internal combustion engines operating in dual fuel mode, proposing potential solutions to improve energy efficiency and reduce emissions, thereby addressing current and future environmental and energy challenges.