Description of the thesis topic

Context:
Gas turbine (GT) technology for power generation is and will be needed in the medium/long future to compensate for the intermittent output of renewable energy sources. GTs have been operated for decades with natural gas (NG) and other fossil fuels. According to the International Energy Agency (IEA), industrial GTs accounted for 14% of global energy-related CO2 emissions in 20192. To reduce the footprint of greenhouse gas (GHG) emissions and their climate impact, the next generation of GTs must be able to safely burn carbon-free fuels. Hydrogen and ammonia are the main decarbonized fuel envisioned as the main substitute to NG. While pure H2 promotes flashback and combustion instabilities, ammonia flames induce stabilization problem and produce nitrogen oxydes. Blends of ammonia and hydrogen is an interesting soultion to combine the benefits of both fuels while mitigating their limitations. There is however a significant knowledge gap concerning the combustion dynamics of NH3/H2 blends that limits the potential of their usage in practical industrial applications.

Subject:

The Phd studies will be carried out in the EU ACHIEVE collaborative project framework (https://www.zabala.eu/projects/achieve/). The main objective are to develop novel computational tools to enhance the predictive capability of high fidelity CFD of unconventional H2 blends.

The PhD student will first focus on simplyfing the chemistry of NH3/H2 blend combustion as the direct use of detailed chemical scheme is too expensive for conducting practical LES simulation. The methodology will rely on the virtual chemistry method developed at EM2C lab, which consists in introducing virtual species and reactions whose thermodynamic and chemical properties are optimized by machine learning algorithms to retrieve properties of reference flames gathered in a learning base. The elementary reactions between the virtual species do not represent real chemical processes but form a mathematical architecture designed to reproduce user-defined targets


The PhD student will optimize a virtual mechanism for predicting heat release, consumption speed, and NOx formation in NH3/H2/Air flames. It involves designing first a virtual primary mechanism for predicting heat release and consumption speed, accounting for differential diffusion effects using a learning database of flamelets with detailed chemistry. Kinetics rate constants and species Lewis number will be optimized using machine learning. Secondly, a virtual satellite sub-mechanism will be designed to predict NOx formation, optimizing species and reactions using a novel strategy based on CSP methodology.

In a second step, the virtual chemistry methodology will be implemented in a CFD flow solver. A dedicated turbulent combustion model will be developed for that purpose. In particular, an analytical sub grid scale wrinkling model will be improved to capture the impact of differential diffusion on the flame turbulence interactions. This numerical strategy will be challenged on premixed burner experimented in TU Delft, within ACHIEVE project. A first focus will be made on the ability of the virtual chemistry strategy to capture both resolved and unresolved intrinsic flame instabilities caused by differential diffusion. Then the performance of the satellite NOx sub- mechanism will be addressed by comparing numerical solutions against numerical data.

Work Context

The EM2C Laboratory (CNRS/INSIS and Université Paris-Saclay/CentraleSupélec http://em2c.centralesupelec.fr/), through its high-level academic research in energy and combustion and its applied studies in partnership with the most prominent companies or research centers in the field of transport and energy, contribute significantly to the progress of knowledge on these critical issues, both for the climate and for the environment. To meet these challenges, the laboratory's research activities are organized around three axes entitled Combustion, Out-of-Equilibrium Plasmas, Transfer Physics, and a transversal action in Applied Mathematics. You will be included in the Combustion axe and more precisely in the Aeronautical Propulsion group. As PhD student, you will be registered in the SMEMAG (SCIENCES MÉCANIQUES et ÉNERGÉTIQUES, MATÉRIAUX et GÉOSCIENCES) Doctoral school.

The position is located in a sector under the protection of scientific and technical potential (PPST), and therefore requires, in accordance with the regulations, that your arrival is authorized by the competent authority of the MESR.