Conceptual design of buildings with artificial intellgence
Data di pubblicazione02-12-2021
Data di priorità04-03-2021
TitolarePolitecnico di Milano
DipartimentoDepartment of Architecture, Built Environment and Construction Engineering
Autori<p>Alper Kanyilmaz, Daniele Loiacono, Patricia Raquel Navarro Tichell</p>
The invention refers to an Artificial Intelligence (AI) conceptual design assistant tool “suSTruct.ai” based on Genetic Algorithms (GAs) to assist senior engineers in the decision-making process of building design. The design scope is focused on medium-rise buildings with a rectangular plan and equally distributed span distances. The design variables to be determined by suSTruct.ai include the structural materials, building and grid dimensions, floor system type, and the type of foundations.
The conceptual design stage is the most crucial part of the development of functional and resource-efficient buildings. However, due to the open-ended nature of the design projects, it is a difficult and time-consuming task to discover the most promising solutions out of the wide scope of possibilities. Consequently, the current approach for the conceptual building design often results in excessive usage of materials and in a high environmental impact, suggesting that there is a large room for optimization of this process.
The approach involves a multi-objective optimization that considers three major conceptual design objectives: minimizing structural cost, maximizing free space, and minimizing the environmental impact. suSTruct.ai has been validated using design examples found in the literature. It provides the user with a graphical representation of the best feasible and optimized structural solutions, their cost, and the CO2 equivalent emissions in a short computational time (<2 min. per run)