Empowering Data-Driven Decisions

2024, Luisa Claus, Simon Joller

Empowering Data-Driven Decisions - Towards a generalised prediction model for thermal performance in buildings

In an era defined by the urgency of addressing the climate crisis, improving the thermal performance of buildings - reducing energy consumption while maintaining occupant comfort - has become a critical objective. Despite increasing research in sustainable building design, recent reports from institutions such as the UN show little progress in reducing energy use in the building sector, pointing to a persistent gap between research and practical implementation.

Enhancing building performance is inherently complex, involving unpredictable factors, limited project information, and intricate interrelations. While physics-based building performance simulations offer accurate analysis, they often demand precise input data beyond the typical user’s knowledge. Emerging data-driven approaches present a promising alternative, providing valuable feedback from less detailed inputs and guiding towards more sustainable design decisions. However, these models tend to be highly case-specific, with inputs tailored to predefined project phases.

This research aims to bridge the gap between research and practice by applying a user-centred methodology which culminates in the development of a tool, called Energenie, capable of accommodating varying levels of user knowledge. By training a generalised data-driven model using TRNSYS simulation data and integrating it into a Grasshopper interface, Energenie offers a flexible, intuitive solution. The tool shows significant potential to empower practitioners to make more informed and sustainable design decisions, contributing to energy efficiency in the building sector.

 

ITECH M.Sc. Thesis Project 2024: Empowering Data-Driven Decisions - Towards a generalised prediction model for thermal performance in buildings
Luisa Claus, Simon Joller

Thesis Advisers: Xiliu Yang, Max Zorn, with support of Christian Fenzel (Transsolar)

Thesis Supervisor: Prof. Achim Menges
Second Supervisor: Prof. Thomas Wortmann

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