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008			260220t20252025my a|||fr|||| 000 0 eng d
020			_aTHE0010358 (Local) _qHardback
040			_aUMPSA _beng _cUMPSA _erda
090			_aFTKMA .Z557 2025 r Thesis
100	1		_aMuhammad Zikri Bin Japri, _eauthor.
245	1	0	_aOptimisation of noise and vibration in diesel engines using biodiesel blends / _cMuhammad Zikri Bin Japri
264		1	_aKuantan, Pahang : _bUMPSA, _c2025
264		4	_c© 2025
300			_axvi, 219 pages : _billustration _c30 cm. + _e1 CD-ROM.
336			_2rdacontent _atext
337			_2rdamedia _aunmediated
338			_2rdacarrier _avolume
347			_2rda _atext file _bPDF
500			_aFaculty of Mechanical and Automotive Engineering Technology
502			_aThesis (Doctor of Philosophy) -- Universiti Malaysia Pahang - 2025
504			_aIncludes bibliographical references
520	3		_aThis study examines the noise and vibration characteristics of a single-cylinder diesel engine fuelled with a blend of palm oil methyl ester (POME) and waste plastic oil (WPO) biodiesel at varying engine speeds and loads. The vibration was measured in the piston axis and analysed in the low-frequency region, while the noise emission was quantified in intensity and analysed in the localised noise source mapping and its level. The analysis demonstrates that both biodiesels effectively reduce noise and vibration levels compared to conventional diesel. POME, characterised by its higher cetane number, density, and kinematic viscosity, minimises the noise and vibration through a shortened ignition delay and reduced combustion intensity, with the highest reduction of 29.23% and 1.77% reduction noticeable in the average vibration amplitude and noise level generated using POME5 and POME10. In contrast, WPO achieves smoother combustion via improved atomisation despite its longer ignition delay. The highest reductions of 29.56% and 2.47% were obtained in the average vibration amplitude and noise radiated through WPO5. The enhanced oxygen content in both fuels facilitates more complete and prolonged combustion, thereby preventing abrupt in-cylinder pressure peaks contributing to noise and vibration. Further, the noise emission analysis identifies combustion-related components—such as the piston, crankshaft, and flywheel—as the primary noise sources, with the engine support structure also playing a significant role. Integrating the artificial neural network with five different optimisation algorithms, namely ant colony optimisation (ACO), genetic algorithm (GA), moth-flame optimisation (MFO), particle swarm optimisation (PSO), and tiki-taka algorithm (TTA), have found that POME7 and WPO11 are optimal for vibration minimisation, achieving 0.2158 and 0.2282 mm/s, which bring 11.78% and 3.57% reduction, respectively. Meanwhile, POME11 and WPO13 excel in noise reduction, recording emissions of 83.444 and 83.666 dB, respectively, contributing to 1.45% and 0.73% reduction. The optimisation results indicate that POME yields slightly lower noise and vibration levels than WPO at a smaller biodiesel proportion, enhancing efficiency and sustainability. Based on the convergence plot, the algorithm performance assessment shows that ACO and TTA are emerging as the most effective due to their rapid convergence rates and robust performance. GA, PSO, and MFO also display competitive optimisation capabilities, offering viable alternatives for engineering applications. The findings highlight the potential of POME and WPO to reduce environmental impact while maintaining high engine performance, thereby supporting the transition to cleaner and quieter diesel engine technologies.
610	2	0	_aFaculty of Mechanical and Automotive Engineering Technology _xDissertations
650		0	_aUniversities and colleges _xDissertations
650		0	_aTheses _xDissertations
942			_2lcc _cTHESIS
999			_c104211 _d104217