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Title: Development of combustion models for RANS and LES applications in SI engines
Authors: Ranasinghe, Chathura P.
Keywords: RANS
LES
KIVA
BML
DPIK
Combustion modelling
Spark ignition engines
Wall flame quenching
Flame surface density
Issue Date: 2013
Publisher: © R.A. Chathura Prasad Ranasinghe
Abstract: Prediction of flow and combustion in IC engines remains a challenging task. Traditional Reynolds Averaged Navier Stokes (RANS) methods and emerging Large Eddy Simulation (LES) techniques are being used as reliable mathematical tools for such predictions. However, RANS models have to be further refined to make them more predictive by eliminating or reducing the requirement for application based fine tuning. LES holds a great potential for more accurate predictions in engine related unsteady combustion and associated cycle-tocycle variations. Accordingly, in the present work, new advanced CFD based flow models were developed and validated for RANS and LES modelling of turbulent premixed combustion in SI engines. In the research undertaken for RANS modelling, theoretical and experimental based modifications have been investigated, such that the Bray-Moss-Libby (BML) model can be applied to wall-bounded combustion modelling, eliminating its inherent wall flame acceleration problem. Estimation of integral length scale of turbulence has been made dynamic providing allowances for spatial inhomogeneity of turbulence. A new dynamic formulation has been proposed to evaluate the mean flame wrinkling scale based on the Kolmogorov Pertovsky Piskunow (KPP) analysis and fractal geometry. In addition, a novel empirical correlation to quantify the quenching rates in the influenced zone of the quenching region near solid boundaries has been derived based on experimentally estimated flame image data. Moreover, to model the spark ignition and early stage of flame kernel formation, an improved version of the Discrete Particle Ignition Kernel (DPIK) model was developed, accounting for local bulk flow convection effects. These models were first verified against published benchmark test cases. Subsequently, full cycle combustion in a Ricardo E6 engine for different operating conditions was simulated. An experimental programme was conducted to obtain engine data and operating conditions of the Ricardo E6 engine and the formulated model was validated using the obtained experimental data. Results show that, the present improvements have been successful in eliminating the wall flame acceleration problem, while accurately predicting the in-cylinder pressure rise and flame propagation characteristics throughout the combustion period. In the LES work carried out in this research, the KIVA-4 RANS code was modified to incorporate the LES capability. Various turbulence models were implemented and validated in engine applications. The flame surface density approach was implemented to model the combustion process. A new ignition and flame kernel formation model was also developed to simulate the early stage of flame propagation in the context of LES. A dynamic procedure was formulated, where all model coefficients were locally evaluated using the resolved and test filtered flow properties during the fully turbulent phase of combustion. A test filtering technique was adopted to use in wall bounded systems. The developed methodology was then applied to simulate the combustion and associated unsteady effects in Ricardo E6 spark ignition engine at different operating conditions. Results show that, present LES model has been able to resolve the evolution of a large number of in-cylinder flow structures, which are more influential for engine performance. Predicted heat release rates, flame propagation characteristics, in-cylinder pressure rise and their cyclic variations are also in good agreement with measurements.
Description: A Doctoral Thesis. Submitted in partial fulfilment of the requirements for the award of Doctor of Philosophy of Loughborough University.
URI: https://dspace.lboro.ac.uk/2134/12507
Appears in Collections:PhD Theses (Mechanical, Electrical and Manufacturing Engineering)

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