Decomposition-based optimization of tailor-made green diesel blends

This chapter presents a tailor-made green diesel blends design algorithm to solve the tailor-made green diesel blends design problem. The design algorithm obtains the optimum solutions of tailor-made green diesel blends by incorporate experimental work with the decomposition-based computer-aided app...

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Main Authors: Phoon, L. Y., Hashim, H., Mat, R., Mustaffa, A. A.
Format: Book Section
Published: Elsevier B.V. 2017
Subjects:
Online Access:http://eprints.utm.my/id/eprint/74801/
https://www.scopus.com/inward/record.uri?eid=2-s2.0-84994673511&doi=10.1016%2fB978-0-444-63683-6.00018-6&partnerID=40&md5=fd53b3e2c6367a52fe0d7eba2cfae04f
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spelling my.utm.748012017-11-28T08:38:31Z http://eprints.utm.my/id/eprint/74801/ Decomposition-based optimization of tailor-made green diesel blends Phoon, L. Y. Hashim, H. Mat, R. Mustaffa, A. A. TP Chemical technology This chapter presents a tailor-made green diesel blends design algorithm to solve the tailor-made green diesel blends design problem. The design algorithm obtains the optimum solutions of tailor-made green diesel blends by incorporate experimental work with the decomposition-based computer-aided approach. There are four main phases in the algorithm: (1) formulate the design problem into a mathematical form; (2) optimize green diesel blend using a decomposition-based computer-aided approach; (3) further enhance the shortlisted blends using fuel additives and (4) experimental validation for the physicochemical properties and engine performance of the shortlisted green diesel blends. B5 palm oil biodiesel-biochemical blends is taken as a case study to demonstrates the application of the presented algorithm. Elsevier B.V. 2017 Book Section PeerReviewed Phoon, L. Y. and Hashim, H. and Mat, R. and Mustaffa, A. A. (2017) Decomposition-based optimization of tailor-made green diesel blends. In: Computer Aided Chemical Engineering. Elsevier B.V., pp. 487-505. ISBN 978-044463683-6 https://www.scopus.com/inward/record.uri?eid=2-s2.0-84994673511&doi=10.1016%2fB978-0-444-63683-6.00018-6&partnerID=40&md5=fd53b3e2c6367a52fe0d7eba2cfae04f
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
topic TP Chemical technology
spellingShingle TP Chemical technology
Phoon, L. Y.
Hashim, H.
Mat, R.
Mustaffa, A. A.
Decomposition-based optimization of tailor-made green diesel blends
description This chapter presents a tailor-made green diesel blends design algorithm to solve the tailor-made green diesel blends design problem. The design algorithm obtains the optimum solutions of tailor-made green diesel blends by incorporate experimental work with the decomposition-based computer-aided approach. There are four main phases in the algorithm: (1) formulate the design problem into a mathematical form; (2) optimize green diesel blend using a decomposition-based computer-aided approach; (3) further enhance the shortlisted blends using fuel additives and (4) experimental validation for the physicochemical properties and engine performance of the shortlisted green diesel blends. B5 palm oil biodiesel-biochemical blends is taken as a case study to demonstrates the application of the presented algorithm.
format Book Section
author Phoon, L. Y.
Hashim, H.
Mat, R.
Mustaffa, A. A.
author_facet Phoon, L. Y.
Hashim, H.
Mat, R.
Mustaffa, A. A.
author_sort Phoon, L. Y.
title Decomposition-based optimization of tailor-made green diesel blends
title_short Decomposition-based optimization of tailor-made green diesel blends
title_full Decomposition-based optimization of tailor-made green diesel blends
title_fullStr Decomposition-based optimization of tailor-made green diesel blends
title_full_unstemmed Decomposition-based optimization of tailor-made green diesel blends
title_sort decomposition-based optimization of tailor-made green diesel blends
publisher Elsevier B.V.
publishDate 2017
url http://eprints.utm.my/id/eprint/74801/
https://www.scopus.com/inward/record.uri?eid=2-s2.0-84994673511&doi=10.1016%2fB978-0-444-63683-6.00018-6&partnerID=40&md5=fd53b3e2c6367a52fe0d7eba2cfae04f
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score 13.160551