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

By: Contributor(s): Material type: TextTextLanguage: 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 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 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

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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