In the last century, a large number of architects and engineers developed a variety of form-finding strategies, and some of them looked to natural systems with the aim of transfering their principles into architecture. Through digital techniques, the designer can emulate or invent new processes to create architectural forms characterized by the same efficiency and beauty of natural systems. In particular, the efficiency of living systems is the result of a slow evolutionary process, as explained by Darwin's theory of evolution. The possibility to apply this process to architecture through genetic algorithms puts in the hands of the designer a powerful tool, which can be used in a wide variety of applications. In this chapter, by means of a case study, a form-finding strategy based on genetic algorithms is structured. A generative model able to adapt to different contexts is designed, and the research of the final shape is driven by a multifunctional optimization process aiming to reduce the energy consumption of the building and the weight of its structure.

Optimization and evolution in architectural morphogenesis: Evolutionary principles applied to mass housing

Alessandro Buffi;Marco Filippucci;Fabio Bianconi
2018

Abstract

In the last century, a large number of architects and engineers developed a variety of form-finding strategies, and some of them looked to natural systems with the aim of transfering their principles into architecture. Through digital techniques, the designer can emulate or invent new processes to create architectural forms characterized by the same efficiency and beauty of natural systems. In particular, the efficiency of living systems is the result of a slow evolutionary process, as explained by Darwin's theory of evolution. The possibility to apply this process to architecture through genetic algorithms puts in the hands of the designer a powerful tool, which can be used in a wide variety of applications. In this chapter, by means of a case study, a form-finding strategy based on genetic algorithms is structured. A generative model able to adapt to different contexts is designed, and the research of the final shape is driven by a multifunctional optimization process aiming to reduce the energy consumption of the building and the weight of its structure.
2018
9781522539933
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11391/1427978
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