We leverage computational design as an extension of thought process – enabling the rapid, precise generation and analysis of complex data sets in the service of improving design. We use parametric modeling tools to rapidly test ideas during the early stages of the design process. With this methodology, varied spatial relationships and formal operations are quickly generated for evaluation. We review these options in digital and physical form, produced by means of 3D printing and CNC fabrication. Additionally, our in-house computational design team develops software that embeds environmental data within our digital models to challenge massing options with real-time building performance analysis. Incorporating our expertise in building science from the outset of the design process foregrounds our commitment to environmentally responsible architecture.
Our group focuses on understanding dynamic relationships between people, space and data. We develop new ways to represent design problems through interactive analysis tools using custom and ready-made scripting frameworks. Our survey, evaluation and forecasting tools establish clear links between analysis and design solutions. The goal is a more comprehensive picture of reality, which reveals underlying connections and prompts us to question our biases. This process is a fundamental step in our design methodology from planning and concept design to post occupancy evaluations. We believe insightful data analysis should inform decision-making.
Each year we generate exponentially more data about our buildings and receive increasingly valuable data from clients about their existing infrastructure. As data becomes a larger part of our practice and our design process, we needed to find new ways of understanding it to better inform our building designs.