As part of the OXY3C project (PEPR SPLEEN), IFP Energies Nouvelles (IFPEN) is seeking a postdoctoral researcher to develop innovative approaches for modeling soot formation in Computational Fluid Dynamics (CFD) simulations of oxygen-free reactors. The study focuses on the fuel reactor of Chemical Loop Combustion (CLC) processes, where gaseous fuel can undergo pyrolysis into soot due to high temperatures and the absence of gaseous oxygen.
The objective is to accelerate the resolution of gas-phase chemical kinetics and the prediction of soot emissions to make them compatible with CFD simulations. This starts with the reduction of detailed mechanisms. The reduced mechanisms will be used to create databases for neural network training, replacing kinetic solvers to further accelerate simulations.
The coupling of accelerated kinetic models with soot models will be investigated to ensure prediction consistency. Machine Learning techniques will also be explored to further improve the acceleration of soot modeling. The postdoctoral researcher will validate these models and explore their application in 3D CFD simulations if feasible.
The Ph.D. degree must have been obtained no more than three years before the start of the postdoctoral contract.
Reduction of detailed gas-phase chemical mechanisms for application in CFD simulations of CLC processes.
- Generation of databases for chemistry tabulation or neural network training to accelerate soot modeling.
- A priori validation of the trained models by comparison with experimental data from project partners.
- Collaboration with internal and external partners to ensure consistency between model development and experimental validation.
Déplacements occasionnels de quelques jours en France et à l’étranger.
Le poste est partiellement télétravaillable
Ph.D. in Chemical Engineering, Applied Mathematics, Combustion, or a related field.
For further information and to apply, please contact:
damien.aubagnac@ifpen.fr
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