Universiti Teknologi Malaysia Institutional Repository

Prediction of meso-scale combustion using different turbulence model

Chen, King Sing (2017) Prediction of meso-scale combustion using different turbulence model. Masters thesis, Universiti Teknologi Malaysia, Faculty of Mechanical Engineering.

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Abstract

An investigation on the adequacy of different 2-equations turbulence models to characterize the non-premixed meso-scale swirl flow combustion is presented in this paper. The RAS 2-equations turbulence models studied include the standard k-ε model, RNG (Renormalization Group) k-ε and SST (Shear Stress Transport) k-ω turbulence models. The open source CFD software openFOAM is utilized to characterize high resolution flow feature and to determine simulated results of the turbulence models investigated that best capture the combustion characteristics in terms of temperature prediction at various equivalence ratios and graphical representation of the stoichiometric mixture fractions that can be correlated to the outlet flame feature produced in experimental setup as well as to generate comparison of the temperature and velocity profiles captured along the length of the meso-scale combustor. The examination of the velocity and pressure contour also reveal that the velocity decays along the length of combustor with prediction of adverse velocity in centre axis near the outlet induced by the pressure gradient between the lower and upper half of the combustor denoting one of the main feature of the swirl flow. The simulated results show that SST k-ω turbulence models produces the highest proximity with the experimental data with the lowest overall percentage error around 4.26% registered while the stoichiometric mixture fraction graphical presentation measured in terms of its development of surface features with increasing equivalence ratio demonstrates that SST k-ω turbulence model produces the most steady development among the other tested turbulence model against the outlet flame features.

Item Type:Thesis (Masters)
Additional Information:Thesis (Sarjana Sains (Kejuruteraan Mekanikal)) - Universiti Teknologi Malaysia, 2017; Supervisor : Dr. Mohd. Fairus Mohd. Yasin
Subjects:T Technology > TJ Mechanical engineering and machinery
Divisions:Mechanical Engineering
ID Code:78542
Deposited By: Fazli Masari
Deposited On:27 Aug 2018 03:22
Last Modified:27 Aug 2018 03:22

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