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The CLEAN-Gas Innovative Training Network
CLEAN-Gas is a “European Joint Doctorate” programme for highly motivated young scientists, where state-of-the-art research is combined with a comprehensive training programme.
The CLEAN-Gas Consortium
The network, coordinated by Politecnico di Milano, consists of 4 academic partner institutions and 4 industrial partners from 4 different countries in Europe.
Host Institution: Université Libre de Bruxelles (Belgium)
Project Title: Optimization of kinetic mechanisms for non-conventional combustion regimes
Aero-Thermo-Mechanical Department, Université Libre de Bruxelles
The main research area which I am interested in is related to CFD simulations of new and non-conventional combustion processes, such as flameless combustion and Oxy-fuel combustion. My research will focus on the uncertainties of the chemical kinetics and also ways to reduce the chemical kinetic mechanisms for these kind of simulations.
Firstly to improve the confidence in the chemical kinetics, important parameters will be determined and analyzed with methods like sensitivity analysis. Example of these parameters are the Arrhenius constant, the activation energy, third body efficiencies, etc. These parameters will then be evaluated and adjusted to improve the results of the simulations, which will be validated by using experimental data available from literature.
Then the reduction of the chemical kinetic mechanism will be evaluated through the use of different mechanism reduction methods, such as Direct Relations Graph (DRG), DRG with Error Propagation (DRGEP), Path Flux Analysis (PFA), Dynamic Adaptive Chemistry (DAC), Element Flux Analysis (EFA), etc. The goal is to speed up the simulations by eliminating chemical species that are not of importance and also to reduce the amount of chemical reactions in the mechanism without losing fidelity in the simulations.
These two combined will improve the confidence for CFD simulations of non-conventional combustion regimes and reduce the computational time needed.
Project title: Optimization of kinetic mechanisms for non-conventional combustion regimes
Objectives. The purpose of this ESR is to improve confidence in kinetic models and optimize their coupling with CFD simulations of novel combustion technologies such as MILD and oxy-MILD combustion. Methods like sensitivity analysis will be employed, to determine relative parameter importance and focus on the parameters showing the biggest influence on predictions. Once important parameters are identified, global sensitivity methods will be used to quantify the model behavior over the whole range of parameter uncertainties, which can be kinetic parameters such as Arrhenius parameters, activation energy, thermodynamic properties, and third body efficiencies. The kinetic schemes will be primarily validated using experimental data available in the literature. Validation/ optimization of the kinetic mechanisms will rely on the simulation of simple idealized reactors (e.g. PSR, batch, PFR) for species, temperatures and ignition delay times. Laminar premixed and counter diffusion flames will be then employed to validate the mechanisms for the prediction of minor species and pollutants
Expected results. The PhD will develop appropriate methodologies for the validation and uncertainty quantification of kinetic mechanisms in the framework of new combustion processes such as MILD combustion. The student will focus on the use/optimization of appropriate screening/sampling techniques, response surface methods (to reduce the function evaluation time for computationally intensive simulations). The final objective will be that of assessing the uncertainty associated to the use of a kinetic mechanism (e.g. the one developed in ESR1 for methane combustion) and its consistency with the available experimental data. The PhD will also focus on the effect of mechanism reduction and solution tabulation on the prediction, in the perspective of optimizing chemistry reduction approaches for the coupling of realistic chemistry in relatively large-scale simulations.
Planned secondment. IT-POLIMI (8-10 months). Optimization/Uncertainty Quantification of kinetic mechanisms.