Optimization of small scale liquefaction processes using genetic algorithm / Mohamed Ibrahim Abdelhamid Awad ; Supervised Mahmoud Abdelhakim Elrifai , Reem Sayed Ettouney , Ayat Ossama Ghallab

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Mohamed Ibrahim Abdelhamid Awad

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TextLanguage: English Publication details: Cairo : Mohamed Ibrahim Abdelhamid Awad , 2016Description: 72 P. : charts , plans , facsimiles ; 30cmOther title:

دراسة أمثلية وحدات الإسالة الصغيرة بإستخدام خوارزم التطور الجيني [Added title page title]

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Dissertation note: Thesis (M.Sc.) - Cairo University - Faculty of Engineering - Department of Chemical Engineering Summary: A new optimization scheme based on communication between the Genetic Algorithm toolbox of Matlab and HYSYS process simulation software is suggested. The power of this newly developed scheme is illustrated by considering the optimization of alternative existing nitrogen based stranded gas liquefaction technologies. The studied genetic operators included population size, selection method, and cross over probability. It is found that the application of this scheme using the range of genetic operators studied led to the establishment of optimum values of the different operating variables in alternative cycles

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Item type	Current library	Home library	Call number	Copy number	Status	Date due	Barcode
Thesis	قاعة الرسائل الجامعية - الدور الاول	المكتبة المركزبة الجديدة - جامعة القاهرة	Cai01.13.04.M.Sc.2016.Mo.O (Browse shelf(Opens below))		Not for loan		01010110070538000
CD - Rom	مخـــزن الرســائل الجـــامعية - البدروم	المكتبة المركزبة الجديدة - جامعة القاهرة	Cai01.13.04.M.Sc.2016.Mo.O (Browse shelf(Opens below))	70538.CD	Not for loan		01020110070538000

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Thesis (M.Sc.) - Cairo University - Faculty of Engineering - Department of Chemical Engineering

A new optimization scheme based on communication between the Genetic Algorithm toolbox of Matlab and HYSYS process simulation software is suggested. The power of this newly developed scheme is illustrated by considering the optimization of alternative existing nitrogen based stranded gas liquefaction technologies. The studied genetic operators included population size, selection method, and cross over probability. It is found that the application of this scheme using the range of genetic operators studied led to the establishment of optimum values of the different operating variables in alternative cycles

Issued also as CD

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