Autodesk @ MaRS
Architecture, Engineering, and Construction
Generative design for architecture uses the same workflow as generative design for manufacturing, but it involves more complex goals and more stakeholders. In this project, Autodesk Research began this process by collecting data from employees and managers about work styles and location preferences. The team then developed six primary and measurable goals: work style preference, adjacency preference, low distraction, interconnectivity, daylight, and views to the outside. Researchers created a geometric system with multiple configurations of work neighborhoods, amenities, circulation, and even stacked private offices. Then, the team automated the process of exploring thousands of configurations and discovering ones that managed trade-offs and scored best.
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Harnessing Game-Inspired Content Creation for Intuitive Generative Design and Optimization
A multi-scale generative design model that adapts the Wave Function…
Generative design for COVID-19 and future pathogens using stochastic multi-agent simulation
Proposing a generative design workflow that integrates a stochastic…
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