Recognition of how to Computational Simulate the Formation Processes of Biological Phenomena in Algorithmic Architecture

Yashar Gharachamani Asl, Mohammad Baharvand, Sahar Toofan

Abstract


There is a long history behind the idea of contemplating the natural world and paying attention to the ways biological phenomena develop and grow rather than trying to merely imitate them in a superficial manner. However, until recently the scientific and technological capabilities had not advanced enough to implement this concept. This was perhaps the result of a superficial selection of complex and ungraspable subjects that could not be implemented due to a lack of scientific knowledge and technical capabilities. However, nowadays it is possible to have a deeper understanding of the principles of form creation thanks to the technical and scientific developments in the past few decades. The patterning and imitation processes go beyond the formal scope to encompass the entire knowledge of how biological components are formed, providing valuable area for pattern generation. Such a new method of imitating nature can be found in algorithmic design, which is to make use of computation as the main part of computer activities through algorithms and codes and programs, like a genome in nature. The main goal of this research is to provide a clear framework and a systematic approach to the role of computational generative systems in the form generation process. For this purpose, the present study uses a descriptive-analytical method based on library research, to study and categorize and describe characteristics, mechanism of the computational systems used in form creation and Compare them. It concludes that computational systems inspired by biological principles can play an important role in the process of computational form generation in architecture.

 Keywords: Algorithmic Architecture, generative systems, biological systems, growth pattern, computation.


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© European Journal of Sustainable Development

ISSN 2239-5938 (print)
ISSN 2239-6101 (online)