The use of sensitivity analysis and genetic algorithms for the management of catalyst emissions from oil refineries.

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Title The use of sensitivity analysis and genetic algorithms for the management of catalyst emissions from oil refineries.
Author Whitcombe, Joshua Matthew; Cropp, Roger Allan; Braddock, Roger David; Agranovski, Igor E
Journal Name Mathematical and Computer Modelling
Editor E.Y. Rodin
Year Published 2006
Place of publication United Kingdom
Publisher Pergamon
Abstract Excessive catalyst emissions from Fluidized Catalytic Cracking Units (FCCU) during start-up situations are common, and have been deemed 'normal', with little research conducted on determining their causes. A MATLAB model found to predict trends in emission rates under normal conditions has been expanded to better represent the actual processes inside a FCCU. First and second order sensitivity analysis techniques are used to assess the interactions between various operational parameters, with a genetic algorithm used to optimize the operating conditions to minimize air emissions. These 'key' parameters may then be altered to help manage both normal and start-up emissions through operational changes. It was also found that significant scale-up issues arise with the use of the attrition models found in the literature.
Peer Reviewed Yes
Published Yes
Publisher URI http://www.elsevier.com/wps/find/journaldescription.cws_home/623/description#description
Alternative URI http://dx.doi.org/10.1016/j.mcm.2006.01.003
Copyright Statement Copyright 2006 Elsevier. This is the author-manuscript version of this paper. Reproduced in accordance with the copyright policy of the publisher. Please refer to the journal's website for access to the definitive, published version.
Volume 44
Page from 430
Page to 438
ISSN 0895-7177
Date Accessioned 2006-07-13
Date Available 2009-12-22T03:07:17Z
Language en_AU
Research Centre Atmospheric Environment Research Centre
Faculty Faculty of Environmental Sciences
Subject PRE2009-Environmental Management and Rehabilitation
URI http://hdl.handle.net/10072/13853
Publication Type Journal Articles (Refereed Article)
Publication Type Code c1

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