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Critical point calculations of multicomponent reservoir fluids using nature inspired metaheuristic algorithms / Moataz Nabil Shehata Sheha ; Supervised Mai K. Fouad , Seif Eddeen K. Fateen

By: Contributor(s): Material type: TextTextLanguage: English Publication details: Cairo : Moataz Nabil Shehata Sheha , 2016Description: 64 P. : charts , plans ; 30cmOther title:
  • حسابات النقطة الحرجة لسوائل الخزانات المتعددة العناصر باستخدام خوارزميات الأدلة العليا المستوحاة من الطبيعة [Added title page title]
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Dissertation note: Thesis (M.Sc.) - Cairo University - Faculty of Engineering - Department of Chemical Engineering Summary: This study introduces the application of nature-inspired metaheuristic algorithms for performing critical point calculations in multicomponent reservoir fluids. These algorithms are Monkey-Krill Herd Hybrid (MAKHA), Intelligent Firefly Algorithm (IFA), Covariance Matrix Adaptation Evolution Strategy (CMAES), Artificial Bee Colony (ABC), Cuckoo Search (CS), Bare Bones Particle Swarm Optimization (BBPSO) and Flower Pollination Algorithm (FPA). Capabilities and limitations of these optimizers have been analyzed using black oil, volatile oil, and condensate reservoir fluids with fifty components. Results showed that BBPSO, IFA and FPA outperformed other nature-inspired methods for critical point calculations in tested fluids. In particular, BBPSO offered the best efficiency-reliability tradeoff for the accurate prediction of critical points in multicomponent mixtures
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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.C (Browse shelf(Opens below)) Not for loan 01010110070534000
CD - Rom CD - Rom مخـــزن الرســائل الجـــامعية - البدروم المكتبة المركزبة الجديدة - جامعة القاهرة Cai01.13.04.M.Sc.2016.Mo.C (Browse shelf(Opens below)) 70534.CD Not for loan 01020110070534000

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

This study introduces the application of nature-inspired metaheuristic algorithms for performing critical point calculations in multicomponent reservoir fluids. These algorithms are Monkey-Krill Herd Hybrid (MAKHA), Intelligent Firefly Algorithm (IFA), Covariance Matrix Adaptation Evolution Strategy (CMAES), Artificial Bee Colony (ABC), Cuckoo Search (CS), Bare Bones Particle Swarm Optimization (BBPSO) and Flower Pollination Algorithm (FPA). Capabilities and limitations of these optimizers have been analyzed using black oil, volatile oil, and condensate reservoir fluids with fifty components. Results showed that BBPSO, IFA and FPA outperformed other nature-inspired methods for critical point calculations in tested fluids. In particular, BBPSO offered the best efficiency-reliability tradeoff for the accurate prediction of critical points in multicomponent mixtures

Issued also as CD

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