TY  - BOOK
AU  - Doha Mohamed Saied
AU  - Ahmed Ahmed Fekry , 
AU  - Reham ElDessuky Hamed , 
TI  - Optimizing parametric light shelf  system performance in deep office spaces / 
PY  - 2019///
CY  - Cairo : 
PB  - Doha Mohamed Saied , 
KW  - Deep spaces
KW  - Light shelf system
KW  - Parametric
N1  - Thesis (Ph.D.) - Cairo University - Faculty of Engineering - Department of Architectural Engineering; Issued also as CD
N2  - 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
UR  - http://172.23.153.220/th.pdf
ER  -