BEMTrace: Visualization-Driven Approach for Deriving Building Energy Models from BIM

2024-07-28

IEEE Transactions on Visualization and Computer Graphics

AI Summary

To address core challenges in BIM-to-BEM conversion—including data distortion, poor traceability, and low user interpretability—this paper proposes a visualization-driven, context-adaptive interactive conversion method. The approach integrates IFC parsing, geometry-semantic co-validation, real-time WebGL-based 3D visualization, context-aware selection algorithms, and automated EnergyPlus IDF generation, establishing a high-fidelity, verifiable energy modeling pipeline. It introduces a novel paradigm of semantic consistency verification coupled with algorithmic error correction, significantly enhancing conversion transparency and user controllability. Evaluated across multiple real-world projects, the method achieves 100% syntactically valid BEM outputs, improves error identification efficiency by 3.2×, and reduces average user task completion time by 47%. These advances collectively strengthen cross-disciplinary collaboration trust and model reliability.

Technology Category

• Natural Language Processing: Code Generation / Program Synthesis from Natural Language
• Cognitive Modeling & Cognitive Systems: Simulating Human Behavior
• Intelligent Robots: Multimodal Perception & Sensor Fusion

Application Category

• User Modeling, Personalization and Recommendation: User modeling and simulation for interactive and conversational systems
• Semantics and Knowledge: Methods to enhance, augment, integrate or synergize semantic models such as knowledge graphs and LLMs
• Systems and Infrastructure for Web, Mobile and WoT: Energy management for devices in mobile Web and WoT environments

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.

Problem

• Convert BIM to BEM for energy analysis
• Enhance accuracy in BIM-to-BEM conversion
• Use visualization for error detection in conversion

Innovation

• 3D data wrangling techniques
• Visualization-driven conversion process
• Algorithmic correction of BIM data