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Optimizing parametric light shelf system performance in deep office spaces / Doha Mohamed Saied ; Supervised Ahmed Ahmed Fekry , Reham ElDessuky Hamed

By: Contributor(s): Material type: TextTextLanguage: English Publication details: Cairo : Doha Mohamed Saied , 2019Description: 219 P. : charts , facsimiles , photoghraphs ; 30cmOther title:
  • تعظيم أداء عاكس الإضائة بالتصميم البارامترى للفراغات الإدارية العميقة [Added title page title]
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Dissertation note: Thesis (Ph.D.) - Cairo University - Faculty of Engineering - Department of Architectural Engineering Summary: Literature in the fields of numerical modeling and deep spaces light systems were reviewed. A reliable numerical model 2Rhino Grass Hopper3 was selected to perform a parametric study to select the adequate parameters to simulate deep office spaces to reach a reliable light system to them. Different parameters were tested and the most applicable of which were selected. This process was achieved several times until convergence was attained. A virtual deep space was set with certain dimensions and was investigated as case study. Results were obtained and analyzed from which guidelines were designated to design a light system with a reliable performance. Innovative about this study is the procedure of selecting the reliable parameters with a complicated numerical modeling technique, where 6552 and 427 runs were achieved. This technique is Parametric Genetic Algorithm, where it is inspired by natural selection to generate high-quality optimization
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Thesis Thesis قاعة الرسائل الجامعية - الدور الاول المكتبة المركزبة الجديدة - جامعة القاهرة Cai01.13.02.Ph.D.2019.Do.O (Browse shelf(Opens below)) Not for loan 01010110079133000
CD - Rom CD - Rom مخـــزن الرســائل الجـــامعية - البدروم المكتبة المركزبة الجديدة - جامعة القاهرة Cai01.13.02.Ph.D.2019.Do.O (Browse shelf(Opens below)) 79133.CD Not for loan 01020110079133000

Thesis (Ph.D.) - Cairo University - Faculty of Engineering - Department of Architectural Engineering

Literature in the fields of numerical modeling and deep spaces light systems were reviewed. A reliable numerical model 2Rhino Grass Hopper3 was selected to perform a parametric study to select the adequate parameters to simulate deep office spaces to reach a reliable light system to them. Different parameters were tested and the most applicable of which were selected. This process was achieved several times until convergence was attained. A virtual deep space was set with certain dimensions and was investigated as case study. Results were obtained and analyzed from which guidelines were designated to design a light system with a reliable performance. Innovative about this study is the procedure of selecting the reliable parameters with a complicated numerical modeling technique, where 6552 and 427 runs were achieved. This technique is Parametric Genetic Algorithm, where it is inspired by natural selection to generate high-quality optimization

Issued also as CD

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