Augmented Large-eddy simulations of an internal combustion engine fueled with hydrogen

Electrification of vehicles and improved efficiency of internal combustion engines (ICE) are the main levers to reduce greenhouse gas emissions. The second priority of the French strategy for the deployment of low-carbon hydrogen is the development of renewable hydrogen for use in fuel cells or for combustion in a spark-ignition engine (SIE). However, for the latter technology, many challenges must be tackled before meeting real driving emissions expectation due to the diversification and complexity of hybrid applications. For flow aerodynamics, mixing and combustion down to the individual engine cycle, challenges are for example associated to robustness of concepts on a cycle basis, rapid variations of engine loads, the occurrence of extreme cycles for a wider range of operating conditions. Large-Eddy Simulation (LES) is an essential tool for the design of robust concepts. However, epistemic uncertainties prevent precise predictions in real systems. Therefore, progress is now crucial to obtain optimal and robust design. 
This PhD is integrated in the ALEKCIA project funded by the National Research Agency. Its  main objective is to develop game-changing tools for improved prediction and analysis of turbulent reactive flows. In that respect, a coupled experimental and numerical approache using an optical access spark-ignition engine fueled with hydrogen will be used.. The main goals of the PhD will be to develop numerical methodologies enabling to perform optimized Large-Eddy simulations (LES) and to integrate in the LES simulation the measurement data obtained in extreme cycles using a Data Assimilation technique. The detailed analysis of results will determine which key parameters are responsible for such sporadic phenomena and cyclic variability.
The original nature of the work will allow publications in high quality scientific journals..

Keywords: CFD, Large-eddy simulation, uncertainty and sensitivity analysis, calibration / optimization, spark ignition engine, hydrogen combustion, empirical mode decomposition

• Academic supervisor    Dr, HDR Stephane JAY, IFP Energies nouvelles
• Doctoral School    SMEMAG (ED 579), Univ Paris-Saclay, web site
• IFPEN supervisor    Dr Karine TRUFFIN, karine.truffin@ifpen.fr
• IFPEN co-supervisor    Dr. Delphine SINOQUET, IFP Energies nouvelles
• PhD location    IFP Energies nouvelles, Rueil-Malmaison, France  
• Duration and start date    3 years, starting in November, 2022
• Employer    IFP Energies nouvelles, Rueil-Malmaison, France
• Academic requirements    MSc Fluid mechanics and/or Energetic and / or Applied mathematics
• Language requirements    Fluency in English, willingness to learn French
• Other requirements   UQ / optimization methods, Computational fluid mechanics, programming (C/C++ and Python), interest in the field of new energy technologies
   
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