Computational approaches for optimal design of tailor made biofuel blends
Diminishing fossil fuel supplies and increasing awareness on environmental issues surged the need for renewable and environmentally friendly alternative fuel options for the transportation sector. Diverse biofuel components can be produced from exploitation of biomass as an energy source. Malaysia h...
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| Main Author: | |
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| Format: | Thesis |
| Language: | English |
| Published: |
2015
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| Subjects: | |
| Online Access: | http://eprints.utm.my/id/eprint/53840/1/MenakaNarayanasamyMFKChE2014.pdf |
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| Summary: | Diminishing fossil fuel supplies and increasing awareness on environmental issues surged the need for renewable and environmentally friendly alternative fuel options for the transportation sector. Diverse biofuel components can be produced from exploitation of biomass as an energy source. Malaysia having abundant palm biomass waste is prompted to efficiently utilize the available resources for production of second generation biofuel blends. However, complexity arises in designing suitable biofuel blends that comply to fuel regulation standards and generate reduced emissions while having equal performance as conventional diesel fuel. Experimental methods consume immense resources and time, require highly sophisticated equipments, and are difficult to conduct for fluid flow variations. Computational approaches adopt a systematic blend formulation process that assists on focused experimental work. In this study, optimal tailor made biofuel blends were designed and evaluated for engine performances, emissions, and in-cylinder fluid flow analyses through implementation of various computational approaches that follow an integrated framework. Systematic model based approach was applied to design tailor made biofuel blends that comply to EN590 fuel reference standard using B5 diesel, butanol, ethanol, and butyl levulinate as building blocks. Fuel blends were generated through Generalized Algebraic Modelling System and predicted fuel properties validated with experimental tests. In-cylinder fluid flow profiles were simulated through computational fluid dynamics model using ANSYS Fluent software version 13.0. Engine performances such as indicated power and indicated thermal efficiency were predicted through mathematical models where experimental validation was done for indicated power. Semi-empirical emission correlations were applied to predict nitrogen oxide, carbon monoxide, unburnt hydrocarbon, and smoke. Among the five tailor made biofuel blends formulated, Blend 4 was the most promising with enhanced performances and lower emissions in comparison to B5 diesel though nitrogen oxide emissions were higher. |
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