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Correct identification of limiting water data for water network synthesis

Data extraction is one of the most critical steps in carrying out a process integration study for managing water usage and discharge. Correct identification of limiting water data during process integration for water minimisation has a significant impact on the water savings achievable for a given p...

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Main Authors: Foo, Dominic Chwan Yee, Manan, Zainuddin Abdul, El-Halwagi, Mahmoud M.
Format: Article
Published: Springer Verlag 2006
Online Access:http://eprints.utm.my/id/eprint/9086/
http://dx.doi.org/10.1007/s10098-006-0037-8
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spelling my.utm.90862009-07-27T03:28:33Z http://eprints.utm.my/id/eprint/9086/ Correct identification of limiting water data for water network synthesis Foo, Dominic Chwan Yee Manan, Zainuddin Abdul El-Halwagi, Mahmoud M. Data extraction is one of the most critical steps in carrying out a process integration study for managing water usage and discharge. Correct identification of limiting water data during process integration for water minimisation has a significant impact on the water savings achievable for a given process. This paper presents the procedure and heuristics to extract the correct limiting water data from a process plant. In addition to limiting data on pollutant concentration, the paper discusses the optimal data extraction rules pertaining to flowrate of water demand and segregation of mixed streams. The paper also quantifies the consequences of inappropriate data extraction. Two case studies are used to illustrate the insights and consequences of data extraction in water minimisation problems. Springer Verlag 2006 Article PeerReviewed Foo, Dominic Chwan Yee and Manan, Zainuddin Abdul and El-Halwagi, Mahmoud M. (2006) Correct identification of limiting water data for water network synthesis. Clean Technologies and Environmental Policy, 8 (2). pp. 96-104. ISSN 1618-954X http://dx.doi.org/10.1007/s10098-006-0037-8 10.1007/s10098-006-0037-8
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/
description Data extraction is one of the most critical steps in carrying out a process integration study for managing water usage and discharge. Correct identification of limiting water data during process integration for water minimisation has a significant impact on the water savings achievable for a given process. This paper presents the procedure and heuristics to extract the correct limiting water data from a process plant. In addition to limiting data on pollutant concentration, the paper discusses the optimal data extraction rules pertaining to flowrate of water demand and segregation of mixed streams. The paper also quantifies the consequences of inappropriate data extraction. Two case studies are used to illustrate the insights and consequences of data extraction in water minimisation problems.
format Article
author Foo, Dominic Chwan Yee
Manan, Zainuddin Abdul
El-Halwagi, Mahmoud M.
spellingShingle Foo, Dominic Chwan Yee
Manan, Zainuddin Abdul
El-Halwagi, Mahmoud M.
Correct identification of limiting water data for water network synthesis
author_facet Foo, Dominic Chwan Yee
Manan, Zainuddin Abdul
El-Halwagi, Mahmoud M.
author_sort Foo, Dominic Chwan Yee
title Correct identification of limiting water data for water network synthesis
title_short Correct identification of limiting water data for water network synthesis
title_full Correct identification of limiting water data for water network synthesis
title_fullStr Correct identification of limiting water data for water network synthesis
title_full_unstemmed Correct identification of limiting water data for water network synthesis
title_sort correct identification of limiting water data for water network synthesis
publisher Springer Verlag
publishDate 2006
url http://eprints.utm.my/id/eprint/9086/
http://dx.doi.org/10.1007/s10098-006-0037-8
_version_ 1643645115008286720
score 13.211869

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