Pareto-hierarchical clustering framework for biodiesel transesterification

Biodiesel is commonly produced via transesterification process, usually through the use of batch type reactor. There are significant gaps in batch reactor technologies, where the importance of operating conditions are often concluded based on the steady-state conditions. In this study, a Pareto-Hier...

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Main Authors: Wong, Kang Yao, Ng, Jo Han, Chong, Cheng Tung, Lam, Su Shiung, Chong, Wen Tong
Format: Article
Published: Elsevier 2021
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Online Access:http://eprints.um.edu.my/25933/
https://doi.org/10.1016/j.seta.2021.101160
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spelling my.um.eprints.259332021-05-03T07:51:24Z http://eprints.um.edu.my/25933/ Pareto-hierarchical clustering framework for biodiesel transesterification Wong, Kang Yao Ng, Jo Han Chong, Cheng Tung Lam, Su Shiung Chong, Wen Tong TJ Mechanical engineering and machinery Biodiesel is commonly produced via transesterification process, usually through the use of batch type reactor. There are significant gaps in batch reactor technologies, where the importance of operating conditions are often concluded based on the steady-state conditions. In this study, a Pareto-Hierarchical framework were employed, based on results of a 4-factor 3-level full factorial Design of Experiments. Four parameters of interest such as agitation speed, catalyst loading, methanol-to-oil ratio, and temperature, were firsts analysed using transient Pareto approach followed by hierarchical clustering. The results indicate that low methanol: oil ratio favours transesterification at the beginning, with increasing importance as the process proceeds. From it, the magnitude of standardised effect increases from 0.38 to 14.21, representing an over 37-fold improvement. Conversely, agitation speed showed a reduction of 37-fold in standardised effect throughout the transesterification process, plateauing around mid-way of the reaction. Catalyst loading and temperature shared similar trends, as they influence the activation energy. Their standardised effects peak at 180 s which is in the middle of the physical-limiting regime. Therefore, this study provides a framework to develop an analyses to make dynamic optimisation strategy better in terms of economics and yield efficiency. © 2021 Elsevier 2021 Article PeerReviewed Wong, Kang Yao and Ng, Jo Han and Chong, Cheng Tung and Lam, Su Shiung and Chong, Wen Tong (2021) Pareto-hierarchical clustering framework for biodiesel transesterification. Sustainable Energy Technologies and Assessments, 45. p. 101160. ISSN 2213-1388 https://doi.org/10.1016/j.seta.2021.101160 doi:10.1016/j.seta.2021.101160
institution Universiti Malaya
building UM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaya
content_source UM Research Repository
url_provider http://eprints.um.edu.my/
topic TJ Mechanical engineering and machinery
spellingShingle TJ Mechanical engineering and machinery
Wong, Kang Yao
Ng, Jo Han
Chong, Cheng Tung
Lam, Su Shiung
Chong, Wen Tong
Pareto-hierarchical clustering framework for biodiesel transesterification
description Biodiesel is commonly produced via transesterification process, usually through the use of batch type reactor. There are significant gaps in batch reactor technologies, where the importance of operating conditions are often concluded based on the steady-state conditions. In this study, a Pareto-Hierarchical framework were employed, based on results of a 4-factor 3-level full factorial Design of Experiments. Four parameters of interest such as agitation speed, catalyst loading, methanol-to-oil ratio, and temperature, were firsts analysed using transient Pareto approach followed by hierarchical clustering. The results indicate that low methanol: oil ratio favours transesterification at the beginning, with increasing importance as the process proceeds. From it, the magnitude of standardised effect increases from 0.38 to 14.21, representing an over 37-fold improvement. Conversely, agitation speed showed a reduction of 37-fold in standardised effect throughout the transesterification process, plateauing around mid-way of the reaction. Catalyst loading and temperature shared similar trends, as they influence the activation energy. Their standardised effects peak at 180 s which is in the middle of the physical-limiting regime. Therefore, this study provides a framework to develop an analyses to make dynamic optimisation strategy better in terms of economics and yield efficiency. © 2021
format Article
author Wong, Kang Yao
Ng, Jo Han
Chong, Cheng Tung
Lam, Su Shiung
Chong, Wen Tong
author_facet Wong, Kang Yao
Ng, Jo Han
Chong, Cheng Tung
Lam, Su Shiung
Chong, Wen Tong
author_sort Wong, Kang Yao
title Pareto-hierarchical clustering framework for biodiesel transesterification
title_short Pareto-hierarchical clustering framework for biodiesel transesterification
title_full Pareto-hierarchical clustering framework for biodiesel transesterification
title_fullStr Pareto-hierarchical clustering framework for biodiesel transesterification
title_full_unstemmed Pareto-hierarchical clustering framework for biodiesel transesterification
title_sort pareto-hierarchical clustering framework for biodiesel transesterification
publisher Elsevier
publishDate 2021
url http://eprints.um.edu.my/25933/
https://doi.org/10.1016/j.seta.2021.101160
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score 13.211869