Generation of Energy-Efficient Patio Houses with GENE_ARCH: Combining an Evolutionary Generative Design System with a Shape Grammar

GENE_ARCH is a Generative Design System that combines Pareto Genetic Algorithms with an advanced building energy simulation engine. This work explores its integration with a Shape Grammar, acting as GENE_ARCHís shape generation module. The urban patio house typology is readdressed in a contemporary context, both by improving its energy-effi ciency standards, and by rethinking its role in the genesis of high-density urban areas, while respecting its specifi c spatial organization and cultural grounding. Field work was carried out in Marrakesh, surveying a number of patio houses which became the Corpus of Design, from where a Shape Grammar was extracted. The computational implementation of the patio house grammar was done within GENE_ARCH. The resulting program was able to generate new, alternative patio houses designs that were more energy effi cient, while respecting the traditional rules captured from the analysis of existing houses. After the computational system was fully implemented, it was possible to complete different sets of experiments. The first experiments kept more restrained rules, thus generating new designs that closer resembled the existing ones. The progressive relaxation of rules and constraints allowed for a larger number of variations to emerge. Analysis of energy results provide insight into the main patterns resulting from the evolutionary search processes, namely in terms of form factors of generated solutions, and urban densities achieved