Using ML to predict the carbon footprint of building structures
DBF and Karamba3D are teaming up for DigitalFutures 2022. Join our workshop and you will learn new ways to improve the performance of your next project.
Why NetZero Structural Design?
One way to help reduce the global carbon emissions is address the lifecycle carbon footprint of buildings in the early design stages.
However, building certification systems do not address the impact implications of embodied carbon emissions from the energy used to construct a building and during production.
How we can reimaging the way we design buildings through the lens of embodied carbon?
To answer this question, DBF (Singapore) and Karamba3D (Vienna) are joining forces to host a joint workshop for DigitalFutures 2022. During the 3 day collaboration, we will explore the use of Machine Learning (ML) and synthetic data generation to bridge the gap between massing and structural design.
Workshop participants will explore the following topics:
- Synthesizing massing data and its structural behavior
- Cleaning, storing, and training the dataset,
- Develop a machine learning model,
- Visualization of structural systems prediction integrated with embodied carbon analysis utilizing a user-friendly platform.
This workshop culminate in several experiments exploring structural design generation and carbon emission calculations using Machine Learning for architecture.
About DBF : DBF is a Singapore-based SaaS startup, which is creating a digital operating system to assist the development of sustainable cities. We have created the most user-friendly digital platform for designing Zero Emission Buildings and Districts collaboratively. Our web-based design platform, united designers, software, and data in order to accelerate carbon-negative building design, construction, and operation.
About Karamba3D: Karamba3D is a parametric structural engineering tool that provides accurate analysis of spatial trusses, frames, and shells. Karamba3D is fully embedded in the parametric design environment of Grasshopper, a plug-in for the 3d modeling tool Rhinoceros. This makes it easy to combine parameterized geometric models, finite element calculations, and optimization algorithms like Galapagos or Wallacei.
