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Title: Determining the combustion kinetics of vegetable oil based fuels
Author: Sahasrabudhe, Mayuresh Arun
ISNI:       0000 0004 5922 4244
Awarding Body: Heriot-Watt University
Current Institution: Heriot-Watt University
Date of Award: 2014
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In last few years’ interest in application of Bio Diesel as an alternative fuel in commercial diesel engines has been increased. However, combustion kinetics is required to predict and model combustion performance of a fuel. The chemical kinetic mechanisms are available for hydrocarbon (C4 to C16) combustion, but not for commercial Biofuel’s combustion. The aim of this research work is to investigate combustion kinetics of Rapeseed oil Methyl Ester (RME) by experimentally in Jet Stirred Reactor and modeling using CHEMKIN a software package at 1 and 10 bar for different fuel conditions. Rapeseed Oil (RSO) combustion kinetics will also be predicted using related theory and chemistry difference between RME and RSO. RME oxidation experiments and comparison with commercial Diesel showed that RME oxidation performance was better at fuel-lean conditions and higher temperatures in terms of profile trends of pollutants, especially at higher pressure suggesting higher Air/Fuel ratio is more suitable for RME combustion. RME oxidation was simulated taking unique approach of using surrogate fuels (nhexadecane, Methyl Acetate) as a model fuel, and RME as a model fuel. The surrogate fuel model results showed that oxidation of commercial biodiesel like RME can be simulated using surrogate model-fuels, but with some limitations and less accuracy. The modeling with RME as model fuel gives good agreement between the model and experimental data in terms of profile trends of key oxidation components. However model needs improvement at high pressure (10 bar). The RME reaction mechanism consists of 496 species and 2652 reversible reactions. The chemical kinetic mechanism for RSO oxidation is represented by Oleic acid (C18H34O2) oxidation. The reaction mechanism consists of 485 species and 2531 reversible reactions. The model is validated against RME oxidation data. The model is able to produce to reproduce profile trends of key oxidation components with some discrepancy.
Supervisor: White, Graeme ; Pekdemir, Turgay ; Dagaut, Philippe Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available