Soot particles are formed during the combustion of hydrocarbon/air mixtures in most combustion devices related to transportation. They are regulated for diesel engines, and will soon be for spark-ignition (SI) engines and gas turbines (GT). These regulations will concern not only the soot mass emission, but also the number of particles and finally the number of the smallest (most harmful) ones.
The objective of ASMAPE is the development of validated predictive Computational Fluid Dynamics (CFD) models for the formation and evolution of soot during the turbulent combustion processes, in both PE and GT. The ambition is to address the three main commercial fuels (CF) relevant for a present usage: gasoline, kerosene and diesel fuel. The predictive capability of the models to be developed will concern both the soot volume fraction (SVF) and the Soot Number Density Function (SNDF).
The developed CFD soot models will directly be available at the project end for the French automotive and aeronautical industry to support design work aimed at limiting soot production at the source.
The originality of ASMAPE is to propose an innovative integrated research work bringing together advanced optical diagnostics, chemical kinetics and turbulent combustion modelling, as well as work on numerical methods, applied to a wide spectrum of studies ranging from basic laminar flames to real-size piston engines (PE) and gas turbines (GT).
The first experimental results on the foal laminar flame were obtained for pure n-butane. These results were complemented by the addition of n-propylbenzene to account for the influence of aromatic components on the formation of soot.
A first valid kinetic scheme for the three fuels of interest was developed. It reproduced in a stirred reactor and shock tube a lot of experience of literature.
A first coupling model of soot tabulated with a combustion model has been developed for the calculation of diesel engines. This model was evaluated on an existing experimental base of diesel engines and the A spray of ECN (Combustion Engine Network). It has been shown that this advanced model enabled a significant improvement in the prediction of soot on all engine points considered. It will now be evaluated at high pressure / temperature, according to the experimental basis developed within ASMAPE.