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http://dx.doi.org/10.12989/acd.2022.7.2.153

A hybrid approach of generative design methods for designing tall-buildings form  

Tofighi Pouria (School of Architecture and Environmental Design, Iran University of Science and Technology)
Ekhlassi, Ahmad (School of Architecture and Environmental Design, Iran University of Science and Technology)
Rahbar, Morteza (School of Architecture and Environmental Design, Iran University of Science and Technology)
Publication Information
Advances in Computational Design / v.7, no.2, 2022 , pp. 153-171 More about this Journal
Abstract
The present study aimed to find a way to create forms that can simultaneously meet several architectural requirements by applying generative design methods specifically focused on cellular automata. In other words, it is tried to find various forms of architecture that all have common features. Because of the useful features of cellular automata, we decided to use it to generate various forms, but make a relation between the discrete nature of cellular automata and the continuous nature of architecture, was the major problem of our project. To achieve this goal, three consecutive stages were designed. In the first stage, independent variables including the location of the building, the height of the building, and the building area were considered as the inputs of the model. In the second stage, after locating the building, the building's main shell was designed as a hidden geometry for the cellular automata and then the cellular automata were determined based on this shell. The main result of this research is establishing a logical relationship between the discrete geometry of the cellular automata and the continuous search space such that it creates various optimized forms. Although we specify the site plan of this project at Iran-Tehran, this research can be generalized to various design sites as well as different projects, allowing the architectsto alter the cell dimensions, cell density, etc., based on their opinion and project needs.
Keywords
cellular automata; generative design; genetic algorithm; parametric design; rule-based design;
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