This workshop introduces a data-driven workflow for optimizing office design through carbon, energy, and comfort using parametric simulation tools.
In this workshop, we will focus on an office building typology, emphasizing the balance between human-centric comfort and building performance. Set within an existing urban context, the design will prioritize data-driven metrics without sacrificing architectural articulation.
We will start with weather data analysis using Ladybug, followed by rapid, early-stage site context evaluation utilizing the Forma Rhino plugin for wind and microclimate studies. Once the baseline is established, we will use Cyclops to run interactive daylight and solar hours simulations. To assess deeper building performance, Ladybug and Honeybee will be utilized to configure the building's energy setup and calculate thermal comfort.
To navigate the massive amount of data generated by these simulations, we will set up an advanced data management framework. This will allow us to generate a brute-force dataset of design iterations, which participants will analyze using a custom, in-house Design Explorer. Finally, we will use Galapagos for single-objective optimization and Opossum for multi-objective criteria, iteratively refining the building before blending the technical outputs with AI-generated visual aesthetics.
Participants will work individually throughout the workshop. A robust parametric framework will be provided, utilizing Telepathy, Pufferfish, and Wombat to demonstrate best practices for data management and script optimization. This workflow, along with its logic, will be explained during the introductory session.
Once the performance scripts (Forma, Cyclops, Honeybee) are in place, participants will explore two distinct methodologies for design selection: navigating a brute-force iteration space using the Design Explorer, and utilizing evolutionary solvers (Galapagos and Opossum) for algorithmic optimization.
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