Soot and NOx modeling dedicated to Diesel engine

European rules are more and more restrictive concerning pollutants emissions. This work deals with the modeling of NOx and soot particles. The final aim is to provide modeling tools in order to analyse the mechanismes leading to reduce these emissions in the combustion chamber. First, a tabulated NO prediction model has been developed. This model (called NORA: NO Relaxation Approach) is based on equilibrium state perturbation method. NORA is simple to use, robust and totally independent of the turbulent combustion model. The use of the NORA allows a significative improvement of the results compared to the direct resolution of the Zel'dovich mechanism with a reduce chemistry. In a second part, this work deals with soot predictions with the final aim the prediction of the soot volume fraction and the particle size distribution function (PSDF). The sectional method approach was first implemented in a 1-D flame solver and validated against experimental flames data. The question of the coupling between the soot sectional model and a turbulent combustion model has been addressed. Studies show that the coupling between gaseous and solid phase is non-negligible. A first mixed combustion model (called MTKS) using a tabulated method and a kinetic solver in the burned gases has been coupled to the soot sectional model. The MTKS approach has been tested in heterogeneous variable volume reactors and results are promising.

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Source https://theses.hal.science/tel-00685123
Author Vervisch, Pauline
Maintainer CCSD
Last Updated May 22, 2026, 18:32 (UTC)
Created May 22, 2026, 18:32 (UTC)
Identifier NNT: 2012ECAP0007
Language en
Rights https://about.hal.science/hal-authorisation-v1/
contributor Laboratoire d'Énergétique Moléculaire et Macroscopique, Combustion (EM2C) ; CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-Université Paris Saclay (COmUE)
creator Vervisch, Pauline
date 2012-01-25T00:00:00
harvest_object_id 98d05a07-7a7f-42e3-bea4-50a7204becac
harvest_source_id 3374d638-d20b-4672-ba96-a23232d55657
harvest_source_title test moissonnage SELUNE
metadata_modified 2026-03-30T00:00:00
set_spec type:THESE