Muhammad Zikri Bin Japri, <br/><br/>
Optimisation of noise and vibration in diesel engines using biodiesel blends / 
Muhammad Zikri Bin Japri 
 - xvi, 219 pages :  illustration  30 cm. +  1 CD-ROM. 
<br/><br/> Faculty of Mechanical and Automotive Engineering Technology 
<br/><br/>Thesis (Doctor of Philosophy) -- Universiti Malaysia Pahang - 2025 
<br/><br/>Includes bibliographical references 
<br/><br/> This 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. 
<br/><br/><label>ISBN: </label>THE0010358 (Local) 
<br/><br/><label>Subjects--Corporate Names: </label><br/>Faculty of Mechanical and Automotive Engineering Technology--Dissertations
<br/><br/><label>Subjects--Topical Terms: </label><br/>Universities and colleges--Dissertations<br/>Theses--Dissertations