New Study Reveals a Game-Changing Way to Improve Building Energy Models

A new study has demonstrated a novel approach to integrating Building Information Modeling (BIM) with Building Energy Modeling (BEM) to improve energy simulations and design efficiency.

Concept of environmentally sound, modern timber construction.
Study: From BIM to BEM—Modern Thermal Simulations Using a Building Information Management Model: A Case Study. Image Credit: anatoliy_gleb/Shutterstock.com

A recent study published in Applied Sciences examined the feasibility of developing a BIM model using existing libraries from Czech manufacturers and suppliers of building materials. The research also explored how this model could be utilized for BEM. The computational modeling results were then compared with real-world data collected from a timber structure in Ostrava, Czech Republic.

Background

BIM consolidates all building-related data into a single digital model, improving communication among stakeholders throughout a building's lifecycle and reducing errors. By enhancing efficiency, BIM helps lower costs while enabling the simulation and prediction of a building’s real-world performance.

A specific aspect of BIM, known as six-dimensional (6D) BIM, links internal and external energy parameters. Architects often use 6D BIM to analyze energy performance and optimize building designs. However, integrating 6D BIM with BEM remains challenging due to interoperability issues, leading to data loss and inefficiencies in energy simulations.

Additionally, many simulation tools require advanced programming knowledge, posing a barrier to widespread adoption. This study aimed to address these challenges by leveraging the gbXML format to enhance interoperability, particularly within the context of Central Europe.

Methods

A case study was conducted on a timber structure built in 2012 to assess how effectively gbXML could improve energy simulations and streamline design processes. The primary objective was to validate the model-derived data by comparing them with real measurements taken from the structure. The study also provided recommendations for improving data transfer efficiency between BIM and BEM platforms.

The research involved computational simulations of thermal energy changes over time, focusing on temperature redistribution in specific rooms. These simulations were compared with real-world data obtained through on-site measurements. Temperature data was collected using SW Stabil software, while ArchiCAD was used to export the energy model in the gbXML format. The boundary conditions were set based on a 20-year temperature average for the location.

To further refine the model, the study analyzed 26 years of local climate data, including air temperature and solar irradiation, and compared them with official reference-year datasets. The researchers conducted multiple simulations using 26 different datasets, incorporating variables such as air exchange influenced by occupant behavior.

Results and Discussion

The study demonstrated that the developed model effectively captured the overall thermal dynamics of the timber structure. The quasi-cyclic nature of the data and the strong correlation between datasets reinforced the model’s reliability. Measurements indicated that indoor temperatures remained stable even during harsh winter conditions, confirming the structure’s ability to maintain thermal comfort.

However, short-term temperature fluctuations and occasional inconsistencies highlighted areas for improvement. Specifically, refinements were needed in the assumptions regarding thermal inertia and wind effects. The study suggested that more precise input parameters and potential revisions to mathematical models, physical formulations, and computational algorithms could enhance accuracy. Further calibration, particularly for hot summer conditions or controlled heating scenarios in winter, could refine the model’s predictive capabilities.

The research also identified challenges in data transfer that impacted simulation accuracy. These included inconsistencies in geometric data processing due to gbXML’s limitations, discrepancies in defining boundary conditions (such as solar gains and thermal loads), and differences in software standards supporting the gbXML format.

To address these issues, the researchers recommended several technological and process improvements, such as incorporating data validation into the BIM-BEM workflow, expanding gbXML’s capabilities, integrating with more advanced simulation tools, standardizing import/export procedures, and fostering greater collaboration among software developers.

Conclusion

Through an experimental case study on a timber structure in Ostrava, the research successfully demonstrated how BIM and BEM can be integrated to enhance energy modeling. By comparing measured and simulated temperature data, the study identified key factors influencing thermal dynamics and assessed the accuracy of computational simulations.

The findings indicate that while advanced modeling techniques provide higher accuracy and flexibility, standardized formats like gbXML offer an accessible and practical solution for most applications. As a result, these methods can be incorporated into everyday design practices.

The researchers also emphasized that, although this study focused on a timber structure, the proposed methodology is adaptable to other building types, such as steel or concrete structures. By adjusting input data and material properties accordingly, the approach can be applied more broadly across the construction industry.

Journal Reference

Průša, D. et al. (2025). From BIM to BEM—Modern Thermal Simulations Using a Building Information Management Model: A Case Study. Applied Sciences15(6), 2878. DOI: 10.3390/app15062878, https://www.mdpi.com/2076-3417/15/6/2878

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Nidhi Dhull

Written by

Nidhi Dhull

Nidhi Dhull is a freelance scientific writer, editor, and reviewer with a PhD in Physics. Nidhi has an extensive research experience in material sciences. Her research has been mainly focused on biosensing applications of thin films. During her Ph.D., she developed a noninvasive immunosensor for cortisol hormone and a paper-based biosensor for E. coli bacteria. Her works have been published in reputed journals of publishers like Elsevier and Taylor & Francis. She has also made a significant contribution to some pending patents.  

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