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Design Loop: Calibration of a Simulation of Productive Congestion Through Real-World Data for Generative Design Frameworks

Design Modeling Symposium
2019

Abstract

This paper extends the applicability of generative design for space planning frameworks for ongoing and guided post-occupancy modifications. It involves the comparison of a graph-based productive-congestion simulation with empirical data and the use of a metaheuristic search algorithm to calibrate and fine-tune simulation parameters for greater accuracy. This methodology is demonstrated through a real-world generative designed case-study and the post-occupancy collection and processing of movement data through custom computer vision workflows.

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Project Discover is a workflow for generative design for architecture. It involves the integration of a rule-based geometric system, a series of measurable goals, and a system for automatically generating, evaluating, and evolving a very large number of design options.  The result is a tool to explore a wide design space, and get closer and closer to achieving all of the goals simultaneously.

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