Lai, C-M, Loo, DL, Teoh, YH, How, HG, Le, TD, Nguyen, HT, Ghfar, AA and Sher, F ORCID: https://orcid.org/0000-0003-2890-5912, 2023. Optimization and performance characteristics of diesel engine using green fuel blends with nanoparticles additives. Fuel, 347: 128462. ISSN 0016-2361
Full text not available from this repository.Abstract
The optimized experiment model is often developed to provide fewer costs, time consumed and error for experiment. Nanoparticles can be utilized as fuel additives to improve lubrication performance. Nevertheless, the concentration of nanoparticles is crucial for fuel lubricity. This work describes the use of response surface methodology (RSM) based Box-Behnken design to optimize the tribological behaviour of several types of nanoparticles combined in tyre pyrolysis oil-biodiesel-diesel blended fuel using a four-ball tribometer. The study aims to identify the ideal values for applied load, rotation speed and nanoparticles concentration to enhance the fuel's tribological behaviour. The applied load, rotation speed and nanoparticles concentration range from 20 to 60 kg, 1000 to 1400 RPM and 0–0.2 wt%, respectively are used to determine the coefficient of friction (COF), wear scar diameter (WSD), and surface roughness (Ra). The result revealed that MgO, graphene and Al2O3 nano-fuel shows improvement in the tribological behaviour. MgO nano-fuel model, the optimum speed, load and concentration values were 1000 RPM, 26.99 kg and 0.0531 wt% for graphene nano-fuel model, the optimum speed, load and concentration values were 1161.73 RPM, 21.83 kg and 0.105 wt% and for Al2O3 nano-fuel model, the optimum speed, load and concentration values were 1109.3 RPM, 30.37 kg and 0.0107 wt% respectively. The investigation results demonstrated that the tribological behaviour of the nano fuels made of MgO, graphene and Al2O3 had been improved. In contrast to MgO and graphene nano fuel, the optimized Al2O3 nano fuel demonstrated the best tribological performance with the lowest concentration, price, load and speed.
Item Type: | Journal article |
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Publication Title: | Fuel |
Creators: | Lai, C.-M., Loo, D.L., Teoh, Y.H., How, H.G., Le, T.D., Nguyen, H.T., Ghfar, A.A. and Sher, F. |
Publisher: | Elsevier BV |
Date: | September 2023 |
Volume: | 347 |
ISSN: | 0016-2361 |
Identifiers: | Number Type 10.1016/j.fuel.2023.128462 DOI 1827092 Other |
Divisions: | Schools > School of Science and Technology |
Record created by: | Jeremy Silvester |
Date Added: | 27 Oct 2023 15:39 |
Last Modified: | 27 Oct 2023 15:39 |
URI: | https://irep.ntu.ac.uk/id/eprint/50161 |
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