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Modeling and optimization of a solar forward osmosis pilot plant by response surface methodology

M. Khayet, J.A. Sanmartino, M. Essalhi, M.C. García-Payo, N. Hilal, Nidal Hilal

Solar Energy, Volume: 137, Pages: 290 - 302

Swansea University Author: Nidal Hilal

DOI (Published version): 10.1016/j.solener.2016.07.046

Abstract

Forward osmosis (FO) is a water treatment/separation technology of emerging interest. Due to its complex nature involvingvarious operating parameters, modeling of this separation process is challenging. A solar thermal and photovoltaic-powered FO pilot plant has been optimized by means of a statisti...

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Published in: Solar Energy
Published: 2016
URI: https://cronfa.swan.ac.uk/Record/cronfa29390
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spelling 2016-10-03T15:43:04.1555856 v2 29390 2016-08-02 Modeling and optimization of a solar forward osmosis pilot plant by response surface methodology 3acba771241d878c8e35ff464aec0342 Nidal Hilal Nidal Hilal true false 2016-08-02 FGSEN Forward osmosis (FO) is a water treatment/separation technology of emerging interest. Due to its complex nature involvingvarious operating parameters, modeling of this separation process is challenging. A solar thermal and photovoltaic-powered FO pilot plant has been optimized by means of a statistical experimental design and response surfacemethodology. Predictive models were developed for simulation and optimization of different responses such as the waterpermeate flux, the reverse solute permeate flux and the FO specific performance index that includes the water and reversesolute permeate fluxes together with the energy consumption. The considered input variables of the FO pilot plant werethe feed flow rate, the permeate flow rate and the temperature. The developed response models have been tested using theanalysis of variance. A Monte Carlo Simulation method has been conducted to determine the optimum operating conditionsof the FO pilot plant. The obtained optimum parameters were confirmed experimentally. Regeneration of the drawsolution can be performed by means of an optimized solar powered reverse osmosis (RO) pilot plant with an optimumFO specific performance index ranging from 25.79 to 0.62 L/g kW h achieved under the FO optimal conditions, 0.83 L/min feed flow rate, 0.31 L/min draw solution flow rate and 32.65 °C temperature. The FO energy consumption is only14.1% the total energy consumption of the FO/RO hybrid system. Journal Article Solar Energy 137 290 302 1 11 2016 2016-11-01 10.1016/j.solener.2016.07.046 COLLEGE NANME Science and Engineering - Faculty COLLEGE CODE FGSEN Swansea University 2016-10-03T15:43:04.1555856 2016-08-02T07:45:29.0257925 Faculty of Science and Engineering School of Engineering and Applied Sciences - Uncategorised M. Khayet 1 J.A. Sanmartino 2 M. Essalhi 3 M.C. García-Payo 4 N. Hilal 5 Nidal Hilal 6 0029390-03102016151645.pdf khayet2016v2.pdf 2016-10-03T15:16:45.6530000 Output 1242899 application/pdf Accepted Manuscript true 2017-08-23T00:00:00.0000000 true
title Modeling and optimization of a solar forward osmosis pilot plant by response surface methodology
spellingShingle Modeling and optimization of a solar forward osmosis pilot plant by response surface methodology
Nidal Hilal
title_short Modeling and optimization of a solar forward osmosis pilot plant by response surface methodology
title_full Modeling and optimization of a solar forward osmosis pilot plant by response surface methodology
title_fullStr Modeling and optimization of a solar forward osmosis pilot plant by response surface methodology
title_full_unstemmed Modeling and optimization of a solar forward osmosis pilot plant by response surface methodology
title_sort Modeling and optimization of a solar forward osmosis pilot plant by response surface methodology
author_id_str_mv 3acba771241d878c8e35ff464aec0342
author_id_fullname_str_mv 3acba771241d878c8e35ff464aec0342_***_Nidal Hilal
author Nidal Hilal
author2 M. Khayet
J.A. Sanmartino
M. Essalhi
M.C. García-Payo
N. Hilal
Nidal Hilal
format Journal article
container_title Solar Energy
container_volume 137
container_start_page 290
publishDate 2016
institution Swansea University
doi_str_mv 10.1016/j.solener.2016.07.046
college_str Faculty of Science and Engineering
hierarchytype
hierarchy_top_id facultyofscienceandengineering
hierarchy_top_title Faculty of Science and Engineering
hierarchy_parent_id facultyofscienceandengineering
hierarchy_parent_title Faculty of Science and Engineering
department_str School of Engineering and Applied Sciences - Uncategorised{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Engineering and Applied Sciences - Uncategorised
document_store_str 1
active_str 0
description Forward osmosis (FO) is a water treatment/separation technology of emerging interest. Due to its complex nature involvingvarious operating parameters, modeling of this separation process is challenging. A solar thermal and photovoltaic-powered FO pilot plant has been optimized by means of a statistical experimental design and response surfacemethodology. Predictive models were developed for simulation and optimization of different responses such as the waterpermeate flux, the reverse solute permeate flux and the FO specific performance index that includes the water and reversesolute permeate fluxes together with the energy consumption. The considered input variables of the FO pilot plant werethe feed flow rate, the permeate flow rate and the temperature. The developed response models have been tested using theanalysis of variance. A Monte Carlo Simulation method has been conducted to determine the optimum operating conditionsof the FO pilot plant. The obtained optimum parameters were confirmed experimentally. Regeneration of the drawsolution can be performed by means of an optimized solar powered reverse osmosis (RO) pilot plant with an optimumFO specific performance index ranging from 25.79 to 0.62 L/g kW h achieved under the FO optimal conditions, 0.83 L/min feed flow rate, 0.31 L/min draw solution flow rate and 32.65 °C temperature. The FO energy consumption is only14.1% the total energy consumption of the FO/RO hybrid system.
published_date 2016-11-01T03:35:43Z
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score 11.013148

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