Hourly yield prediction of a double-slope solar still hybrid with rubber scrapers in low-latitude areas based on the particle swarm optimization technique

Several studies have attempted to improve the productivity of solar stills and build expressive models for yield prediction. However, most of these models do not consider the amount of condensed water that falls from the condensing cover towards the solar still basin, especially in the case of small...

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Main Authors: Al-Sulttani, Ali Omran Muhsin, Ahsan, Amimul, Hanoon, Ammar Nasiri, Rahman, Ataur, Nik Daud, Nik Norsyahariati, Idrus, Syazwani
Format: Article
Language:English
Published: Elsevier 2017
Online Access:http://psasir.upm.edu.my/id/eprint/62040/1/Hourly%20yield%20prediction%20of%20a%20double-slope%20solar%20still%20hybrid%20.pdf
http://psasir.upm.edu.my/id/eprint/62040/
https://www.sciencedirect.com/science/article/pii/S0306261917307699
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spelling my.upm.eprints.620402019-03-20T06:18:46Z http://psasir.upm.edu.my/id/eprint/62040/ Hourly yield prediction of a double-slope solar still hybrid with rubber scrapers in low-latitude areas based on the particle swarm optimization technique Al-Sulttani, Ali Omran Muhsin Ahsan, Amimul Hanoon, Ammar Nasiri Rahman, Ataur Nik Daud, Nik Norsyahariati Idrus, Syazwani Several studies have attempted to improve the productivity of solar stills and build expressive models for yield prediction. However, most of these models do not consider the amount of condensed water that falls from the condensing cover towards the solar still basin, especially in the case of small-slope covers. This oversight can significantly affect the accuracy of these models. In this study, we developed a fairly simple method to estimate the amount of distilled water produced every hour from the double-slope solar still hybrid with rubber scrapers (DSSSHS) in low-latitude areas. The proposed model is based on the determination of the best values for the unknown constant (C) and the exponent (n) for the Nusselt number expression used to formulate the equation for the estimation of the hourly yield of a solar still (HYSS). This was achieved by solving an optimization problem using the particle swarm optimization (PSO) algorithm in which the optimal yields were determined by estimating the optimal values of the unknown C and nparameters. This technique, which is used for the first time in this study to build a yield prediction model, avoided the conventional trial-and-error approach to calculating unknown coefficients in a proposed model. Furthermore, the use of rubber scrapers to collect the condensed water that accumulates on the inner surfaces of the condensing cover enhanced the accuracy of the measurement of solar still experimental yields, which consequently improved the accuracy of the model. The proposed model was validated against the experimental data collected in this study. The results showed that the built model was able to accurately estimate the HYSS values. Elsevier 2017-10 Article PeerReviewed text en http://psasir.upm.edu.my/id/eprint/62040/1/Hourly%20yield%20prediction%20of%20a%20double-slope%20solar%20still%20hybrid%20.pdf Al-Sulttani, Ali Omran Muhsin and Ahsan, Amimul and Hanoon, Ammar Nasiri and Rahman, Ataur and Nik Daud, Nik Norsyahariati and Idrus, Syazwani (2017) Hourly yield prediction of a double-slope solar still hybrid with rubber scrapers in low-latitude areas based on the particle swarm optimization technique. Applied Energy, 203. 280 - 303. ISSN 0306-2619; ESSN: 1872-9118 https://www.sciencedirect.com/science/article/pii/S0306261917307699 10.1016/j.apenergy.2017.06.011
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
language English
description Several studies have attempted to improve the productivity of solar stills and build expressive models for yield prediction. However, most of these models do not consider the amount of condensed water that falls from the condensing cover towards the solar still basin, especially in the case of small-slope covers. This oversight can significantly affect the accuracy of these models. In this study, we developed a fairly simple method to estimate the amount of distilled water produced every hour from the double-slope solar still hybrid with rubber scrapers (DSSSHS) in low-latitude areas. The proposed model is based on the determination of the best values for the unknown constant (C) and the exponent (n) for the Nusselt number expression used to formulate the equation for the estimation of the hourly yield of a solar still (HYSS). This was achieved by solving an optimization problem using the particle swarm optimization (PSO) algorithm in which the optimal yields were determined by estimating the optimal values of the unknown C and nparameters. This technique, which is used for the first time in this study to build a yield prediction model, avoided the conventional trial-and-error approach to calculating unknown coefficients in a proposed model. Furthermore, the use of rubber scrapers to collect the condensed water that accumulates on the inner surfaces of the condensing cover enhanced the accuracy of the measurement of solar still experimental yields, which consequently improved the accuracy of the model. The proposed model was validated against the experimental data collected in this study. The results showed that the built model was able to accurately estimate the HYSS values.
format Article
author Al-Sulttani, Ali Omran Muhsin
Ahsan, Amimul
Hanoon, Ammar Nasiri
Rahman, Ataur
Nik Daud, Nik Norsyahariati
Idrus, Syazwani
spellingShingle Al-Sulttani, Ali Omran Muhsin
Ahsan, Amimul
Hanoon, Ammar Nasiri
Rahman, Ataur
Nik Daud, Nik Norsyahariati
Idrus, Syazwani
Hourly yield prediction of a double-slope solar still hybrid with rubber scrapers in low-latitude areas based on the particle swarm optimization technique
author_facet Al-Sulttani, Ali Omran Muhsin
Ahsan, Amimul
Hanoon, Ammar Nasiri
Rahman, Ataur
Nik Daud, Nik Norsyahariati
Idrus, Syazwani
author_sort Al-Sulttani, Ali Omran Muhsin
title Hourly yield prediction of a double-slope solar still hybrid with rubber scrapers in low-latitude areas based on the particle swarm optimization technique
title_short Hourly yield prediction of a double-slope solar still hybrid with rubber scrapers in low-latitude areas based on the particle swarm optimization technique
title_full Hourly yield prediction of a double-slope solar still hybrid with rubber scrapers in low-latitude areas based on the particle swarm optimization technique
title_fullStr Hourly yield prediction of a double-slope solar still hybrid with rubber scrapers in low-latitude areas based on the particle swarm optimization technique
title_full_unstemmed Hourly yield prediction of a double-slope solar still hybrid with rubber scrapers in low-latitude areas based on the particle swarm optimization technique
title_sort hourly yield prediction of a double-slope solar still hybrid with rubber scrapers in low-latitude areas based on the particle swarm optimization technique
publisher Elsevier
publishDate 2017
url http://psasir.upm.edu.my/id/eprint/62040/1/Hourly%20yield%20prediction%20of%20a%20double-slope%20solar%20still%20hybrid%20.pdf
http://psasir.upm.edu.my/id/eprint/62040/
https://www.sciencedirect.com/science/article/pii/S0306261917307699
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