Simming Brooklyn
Greenpoint and Williamsburg, NY
This study done in conjunction with the Newman Institute at Baruch College and a research grant from the Boston Society of Architects was the follow up of studio research done at the Yale School of Architecture.
The goals of the project were to develop tools to analyze the city’s rezoning initiative. Studies of ad hoc development in neighboring Williamsburg showed a highly eclectic set of uses in contrast to the legislated zoning in the area. The City’s plan for Greenpoint attempts to replicate the organic changes in Williamsburg while leveraging large scale development along the waterfront. Our ambition was to build upon studies done in studios at Yale to challenge the limitations of current zoning proposals that seemed less equitable than the current market patterns.
Conceptually, zoning, no matter how fine-tuned tends to generalize and limit development along restricted spatial parameters. The proposition was that tools like the video game Sim City, which uses complex computational principals, might point towards a more finely grained scale of analysis that could factor change in real time. Statistical data on the city’s program and FARs were used as simple graphics to show what would be an average program distribution for New York City that would ostensibly represent political equity in the neighborhood. Gaming the system by adding density was correlated with commercial and public program amenities. Those pixilated site plans were then shuffled to achieve a heterogeneous mix of urban programs.
In a separate project generative computer models were made to show potential behavior and beneficial adjacencies over time. These general studies were used in simulating a possible scenarios for the development of Williamsburg.
Further studies attempted to show how designed density clusters of towers might sponsor more energy efficient programmatic juxtapositions and the configuration of the tower massing shown to relate to local attractions like sun orientation, real estate value based on location within the tower and vertical distribution of semi-public spaces.