IEEE VIS 2024 Content: BEMTrace: Visualization-driven approach for deriving Building Energy Models from BIM

BEMTrace: Visualization-driven approach for deriving Building Energy Models from BIM

Andreas Walch - VRVis Zentrum für Virtual Reality und Visualisierung Forschungs-GmbH, Vienna, Austria

Attila Szabo - VRVis Zentrum für Virtual Reality und Visualisierung Forschungs-GmbH, Vienna, Austria

Harald Steinlechner - VRVis Zentrum für Virtual Reality und Visualisierung Forschungs-GmbH, Vienna, Austria

Thomas Ortner - Independent Researcher, Vienna, Austria

Eduard Gröller - Institute of Visual Computing . Human-Centered Technology, Vienna, Austria

Johanna Schmidt - VRVis Zentrum für Virtual Reality und Visualisierung Forschungs-GmbH, Vienna, Austria

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Room: Bayshore VII

2024-10-16T14:27:00ZGMT-0600Change your timezone on the schedule page
2024-10-16T14:27:00Z
Exemplar figure, described by caption below
BEMTrace enhances the data curation process from a Building Information Model (BIM) to a Building Energy Model (BEM) by providing visual support for the BIM-to-BEM conversion. Users can access various views to better understand the complex data transformation, including the BIM World, BEM World, and the Relationship View, which illustrates the transition between them. Context-adaptive selections assist users in navigating these views, allowing for detailed exploration of different data aspects. This approach ensures a clearer understanding of the conversion process and helps in resolving any arising conflicts.
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Keywords

BIM, BEM, BIM-to-BEM, 3D Data Wrangling, 3D selections, Visualization for trust building

Abstract

Building Information Modeling (BIM) describes a central data pool covering the entire life cycle of a construction project. Similarly, Building Energy Modeling (BEM) describes the process of using a 3D representation of a building as a basis for thermal simulations to assess the building’s energy performance. This paper explores the intersection of BIM and BEM, focusing on the challenges and methodologies in converting BIM data into BEM representations for energy performance analysis. BEMTrace integrates 3D data wrangling techniques with visualization methodologies to enhance the accuracy and traceability of the BIM-to-BEM conversion process. Through parsing, error detection, and algorithmic correction of BIM data, our methods generate valid BEM models suitable for energy simulation. Visualization techniques provide transparent insights into the conversion process, aiding error identification, validation, and user comprehension. We introduce context-adaptive selections to facilitate user interaction and to show that the BEMTrace workflow helps users understand complex 3D data wrangling processes.