COMPARATIVE ANALYSES OF COMPUTATIONAL IMPLEMENTATIONS FOR HEALTHCARE BUILDING DESIGN | ||||
| JES. Journal of Engineering Sciences | ||||
| Article 3, Volume 47, No 5, September and October 2019, Page 627-643 PDF (1.79 MB) | ||||
| Document Type: Research Paper | ||||
| DOI: 10.21608/jesaun.2019.115729 | ||||
 View on SCiNiTO | ||||
| Authors | ||||
| Randa M. A. Mahmoud; Nady M. Abdel Karim; Amr M. A. Youssef | ||||
| Department of Architectural Engineering, Assiut University, Assiut 71518, Egypt | ||||
| Abstract | ||||
| Recently, the automation of architectural design process has been focused specifically in Healthcare buildings (HCB) for easier implementation and faster feedback. Hence, a great evolution of Computational Implementations (CIs) were appeared and studied for early stages of design process of HCB, such as generating design solutions, evaluation of design solutions or others to provide helpful tools for designers. This paper provides comparative analyses of a set of CIs that can be applied on different architectural design stages in HCB, these stages includes: a) architectural programming and topological diagram, b) generating design alternatives and c) evaluation of design solutions. The focused CIs in this study have been classified to computational tools, computational algorithms, computational approaches and hybrid methods; they are compared using a set of criteria with various evaluation methods. This comparative analysis helps designers to determine the appropriate CI or CIs’ combinations for each main early stage of HCB design, and also the possibilities of connecting two of the studied CIs in a framework to get wider outcomes were studied. The main study findings are the capabilities, limitation and features of each CI, in addition to the best selections in each early stage for different HCB design cases. Also, possible connections between different CIs were discussed on simple examples as a fruitful outcome of analyzing CIs’ combinations. | ||||
| Keywords | ||||
| Computational implementations; healthcare building design; architectural design automation; generating design alternatives; computational design | ||||
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