Generative design involves creating a large number of design alternatives. It is emerging as a frequently used computational design paradigm in exploring alternative designs. The practical use of generative design demands evaluating the alternatives generated using their form and performance data. We propose to further develop DesignSense, a design (data) analytics tool from the Computational Design Lab and experiment with its use during generative design workflows at Perkins and Will.
This project will assess the value in measuring sustainability outcomes according to place-specific baselines rather than universal thresholds set by rating systems and frameworks. It seeks a stronger foundation for sustainable design that can acknowledge place-specific factors. Ultimately, this work will lead to the establishment of a decision-making protocol about sustainable design options and outcomes that can be applied in a range of contexts, for better choices, made more justifiably, better understanding of impact, and a better sense of progress across projects.
The research undertaken through the Regenerative Neighbourhoods Project explores the ways that specific building and infrastructure projects can act as catalysts for transformational change at the neighbourhood scale with respect to sustainability objectives. It encompasses both substantive performance improvements and the changes in the project delivery processes required to achieve them.
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