CumInCAD is a Cumulative Index about publications in Computer Aided Architectural Design
supported by the sibling associations ACADIA, CAADRIA, eCAADe, SIGraDi, ASCAAD and CAAD futures

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id caadria2019_104
authors Johan, Ryan, Chernyavsky, Michael, Fabbri, Alessandra, Gardner, Nicole, Haeusler, M. Hank and Zavoleas, Yannis
year 2019
title Building Intelligence Through Generative Design - Structural analysis and optimisation informed by material performance
source M. Haeusler, M. A. Schnabel, T. Fukuda (eds.), Intelligent & Informed - Proceedings of the 24th CAADRIA Conference - Volume 1, Victoria University of Wellington, Wellington, New Zealand, 15-18 April 2019, pp. 371-380
summary Generative design (GD) is the process of defining high-level goals and constraints and then using computation to automatically explore a range of solutions that meet the desired requirements. Generative processes are intelligent ways to fast-track early design stages. The outcomes are analyzed simultaneously to inform decisions for architects and engineers. Whilst material properties have been defined as a driving agent within generative systems to calculate structure, material performance or structural capacity are not linked with early decision-making. In response, this paper sets a constrained approach upon traditional and non-traditional materials to validate the feasibility of structures. A GD tool is developed within Grasshopper using C-sharp, Karamaba3D, Galapagos and various engineering formulas. The result is a script, which prioritizes the structural qualities of material as a driving factor within generative systems and facilitates communication across different expertise.
keywords Intelligent systems; generative design; material properties; structural analysis; evolutionary algorithms
series CAADRIA
email m.haeusler@unsw.edu.au
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