Multi-objective optimization of diesel engine performance and emission using grasshopper optimization algorithm
A recently invented algorithm called the grasshopper optimization algorithm (GOA) was used to predict and optimize palm oil biodiesel operated in a diesel engine. The work was conducted in three stages: (i) designing an experiment and performing the experiments, (ii) mathematical modeling, and (iii)...
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my.utm.1041602024-01-17T01:40:38Z http://eprints.utm.my/104160/ Multi-objective optimization of diesel engine performance and emission using grasshopper optimization algorithm Veza, Ibham Karaoglan, Aslan Deniz Ileri, Erol Afzal, Asif Anh, Tuan Hoang Tamaldin, Noreffendy Herawan, Safarudin Gazali Abbas, Muhammad Mujtaba Muhamad Said, Mohd. Farid TJ Mechanical engineering and machinery A recently invented algorithm called the grasshopper optimization algorithm (GOA) was used to predict and optimize palm oil biodiesel operated in a diesel engine. The work was conducted in three stages: (i) designing an experiment and performing the experiments, (ii) mathematical modeling, and (iii) optimization using GOA. By using regression modeling over these experimental results, the mathematical equations between the factors (biodiesel ratio (%) and load (Nm)) and the responses (BTE, BSFC, BSCO, BSNOx, BSCO2, BSHC, and Smoke) were calculated. The results showed that the factors used in the model were sufficient to explain the change in the response, and no additional factors in the mathematical models were required. The ANOVA results showed that the p-value for all the regression models were 0.000 < 0.05, which indicated their significance. Moreover, the regression models best fit the given observations with a low prediction error. The three confirmation tests also revealed satisfying results with low errors. The range of prediction error for BTE, BSFC, BSCO, BSNOx, BSCO2, BSHC, and Smoke were 0.25–3.00%, 2.55–8.20%, 4.61–11.65%, 1.71–12.20%, 1.35–3.52%, 0.02–7.75%, and 0.69–4.34%, respectively. The optimized operating conditions for the maximum engine performance and the minimum emissions was given by 50% biodiesel run at 7 Nm engine load. Elsevier Ltd 2022 Article PeerReviewed Veza, Ibham and Karaoglan, Aslan Deniz and Ileri, Erol and Afzal, Asif and Anh, Tuan Hoang and Tamaldin, Noreffendy and Herawan, Safarudin Gazali and Abbas, Muhammad Mujtaba and Muhamad Said, Mohd. Farid (2022) Multi-objective optimization of diesel engine performance and emission using grasshopper optimization algorithm. Fuel, 323 (NA). pp. 1-9. ISSN 0016-2361 http://dx.doi.org/10.1016/j.fuel.2022.124303 DOI : 10.1016/j.fuel.2022.124303 |
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TJ Mechanical engineering and machinery Veza, Ibham Karaoglan, Aslan Deniz Ileri, Erol Afzal, Asif Anh, Tuan Hoang Tamaldin, Noreffendy Herawan, Safarudin Gazali Abbas, Muhammad Mujtaba Muhamad Said, Mohd. Farid Multi-objective optimization of diesel engine performance and emission using grasshopper optimization algorithm |
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A recently invented algorithm called the grasshopper optimization algorithm (GOA) was used to predict and optimize palm oil biodiesel operated in a diesel engine. The work was conducted in three stages: (i) designing an experiment and performing the experiments, (ii) mathematical modeling, and (iii) optimization using GOA. By using regression modeling over these experimental results, the mathematical equations between the factors (biodiesel ratio (%) and load (Nm)) and the responses (BTE, BSFC, BSCO, BSNOx, BSCO2, BSHC, and Smoke) were calculated. The results showed that the factors used in the model were sufficient to explain the change in the response, and no additional factors in the mathematical models were required. The ANOVA results showed that the p-value for all the regression models were 0.000 < 0.05, which indicated their significance. Moreover, the regression models best fit the given observations with a low prediction error. The three confirmation tests also revealed satisfying results with low errors. The range of prediction error for BTE, BSFC, BSCO, BSNOx, BSCO2, BSHC, and Smoke were 0.25–3.00%, 2.55–8.20%, 4.61–11.65%, 1.71–12.20%, 1.35–3.52%, 0.02–7.75%, and 0.69–4.34%, respectively. The optimized operating conditions for the maximum engine performance and the minimum emissions was given by 50% biodiesel run at 7 Nm engine load. |
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Article |
author |
Veza, Ibham Karaoglan, Aslan Deniz Ileri, Erol Afzal, Asif Anh, Tuan Hoang Tamaldin, Noreffendy Herawan, Safarudin Gazali Abbas, Muhammad Mujtaba Muhamad Said, Mohd. Farid |
author_facet |
Veza, Ibham Karaoglan, Aslan Deniz Ileri, Erol Afzal, Asif Anh, Tuan Hoang Tamaldin, Noreffendy Herawan, Safarudin Gazali Abbas, Muhammad Mujtaba Muhamad Said, Mohd. Farid |
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Veza, Ibham |
title |
Multi-objective optimization of diesel engine performance and emission using grasshopper optimization algorithm |
title_short |
Multi-objective optimization of diesel engine performance and emission using grasshopper optimization algorithm |
title_full |
Multi-objective optimization of diesel engine performance and emission using grasshopper optimization algorithm |
title_fullStr |
Multi-objective optimization of diesel engine performance and emission using grasshopper optimization algorithm |
title_full_unstemmed |
Multi-objective optimization of diesel engine performance and emission using grasshopper optimization algorithm |
title_sort |
multi-objective optimization of diesel engine performance and emission using grasshopper optimization algorithm |
publisher |
Elsevier Ltd |
publishDate |
2022 |
url |
http://eprints.utm.my/104160/ http://dx.doi.org/10.1016/j.fuel.2022.124303 |
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1789424387634495488 |
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13.15806 |