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A knowledge graph-based framework to automate the generation of building energy models using geometric relation checking and HVAC topology establishment

Wang, Meng; Lilis, Georgios N; Mavrokapnidis, Dimitris; Katsigarakis, Kyriakos; Korolija, Ivan; Rovas, Dimitrios; (2024) A knowledge graph-based framework to automate the generation of building energy models using geometric relation checking and HVAC topology establishment. Energy and Buildings , 325 , Article 115035. 10.1016/j.enbuild.2024.115035. Green open access

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Abstract

Building Energy Models (BEM) are widely utilized throughout all stages of a building's lifecycle to understand and enhance energy usage. However, creating these models demands significant effort, particularly for larger buildings or those with complex HVAC systems. While a substantial amount of information can be extracted from Building Information Models (BIM) — which are increasingly accessible and provide necessary data for geometric and HVAC contexts — this information is not readily usable in setting up BEM and typically requires manual translation. To address this challenge, this paper introduces a BIM-to-BEM (BIM2BEM) framework that focuses on automating the generation of HVAC parts of BEM models from BIM data. Core to the methodology is the extraction of HVAC system topologies from the BIM model and the creation of a knowledge graph with the HVAC topology. The topology transformation unfolds in three key stages: first, a geometry-induced knowledge graph is established by examining the geometric relationships among HVAC elements; second, this graph is converted into an informative HVAC topology with enhanced properties from additional data sources; and finally, the informative topology is simplified into a BEM-oriented HVAC topology compliant with BEM platforms such as EnergyPlus. A case study of a large university building with a complex HVAC system showcases that the proposed framework achieves automatic and precise generation of building performance simulation models. The model's predictions are then validated against actual measurements from the building.

Type: Article
Title: A knowledge graph-based framework to automate the generation of building energy models using geometric relation checking and HVAC topology establishment
Open access status: An open access version is available from UCL Discovery
DOI: 10.1016/j.enbuild.2024.115035
Publisher version: https://doi.org/10.1016/j.enbuild.2024.115035
Language: English
Additional information: © The Author(s), 2024. This is an Open Access article distributed under the terms of the Creative Commons Attribution Licence (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. https://creativecommons.org/licenses/by/4.0/
Keywords: Building digital twins, BIM2BEM, Ontology, HVAC topology, Geometric relation checking
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of the Built Environment
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of the Built Environment > Bartlett School Env, Energy and Resources
URI: https://discovery.ucl.ac.uk/id/eprint/10200308
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