Bits to Atoms
CDFAM Computational Design Symposium
Computational Design and Machine Learning in MEP Systems for Large-Scale Architecture - Gabriel Garcia
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Computational Design and Machine Learning in MEP Systems for Large-Scale Architecture - Gabriel Garcia

ROYAL HASKONING DHV

Recorded at CDFAM Computational Design Symposium, Berlin, 2024

Using computational design and machine learning to optimize large-scale building designs, drawing parallels between building structures and the human body. It emphasizes the essential role of Mechanical, Electrical, and Plumbing (MEP) systems, akin to a building’s vital organs. The focus is on enhancing MEP installations’ efficiency, thereby reducing energy demands and carbon footprint, crucial in sustainable architecture. The presentation will cover three key areas: optimizing ventilation ductwork to reduce spatial volume, employing 3D pathfinding for efficient data cable network layouts, and achieving optimal Wi-Fi coverage with minimal hardware. These strategies aim not only for sustainability but also for reduced construction and maintenance costs, marking a step towards more environmentally responsible architectural practices.

The CDFAM Amsterdam Computational Design Symposium, 2025 program brings together leading experts in computational design from industry, academia and software development across all scales of application, from micro to mega.

This year’s keynotes will be delivered by Federico Casalegno, Executive Vice President of Design at Samsung Electronics, and Mathew Vola, Arup Fellow of Computational Design.

See the Full Program