DC1: Numerical study of the impact of operative conditions on combustion emissions
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DC1: Numerical study of the impact of operative conditions on combustion emissions
Problem Definition: There is a lack of tools able to predict the emissions (including minor species and soot) which are expected at the outlet of a LRE combustion chamber. There is a lack of understanding and guidelines about specific design choices that could help reducing specific emissions. The challenge is that combustion gas composition results from a coupling between several complex mechanisms: the high-pressure chemical kinetics, the turbulent reactive flow and the high thermal losses at the wall.
Research Objectives:
- Definition of species that must be tracked and how to compare experimental and numerical data
- LES simulations of DLR reference experiment will be carried out to validate the numerical framework
- Specific attention will be given on the choice of appropriate thermal wall boundary conditions, including possible conjugate heat transfer, and on the study of the local impact they may have on the flame behaviour and on pollutant generation
- Data will be provided as inputs to DC8 for the nozzle plume simulations
- Parametric studies will be carried out varying the O/F and the mass flow rate (featuring throttleable engine conditions) in a reasonable range to investigate the impact on the emissions
- Results will be provided to WP4 (DC13) for tuning of global models
Expected Results:
- A suitable LES framework for the estimation of species composition inside and at the outlet of CH4/O2 LRE combustion chamber, validated against experimental data provided by DC3
- Emission data as output for other DCs
- The impact of O/F and pressure (representing different operating phase of the engine) over the emissions
Secondments:
- Deutsches Zentrum für Luft- und Raumfahrt e.V. (DLR, Hardthausen, Germany, ca. 4 months): analysis experimental data for numerical setup and validation
- ArianeGroup SAS (AGF, Les Mureaux, France, ca. 2 months): exchange with industrial partners on available experimental data and numerical models
Main Supervisor:
Co-Supervisors:
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