BIM Powers Digital Twins for Energy Efficiency?

By Nidhi DhullReviewed by Susha Cheriyedath, M.Sc.Dec 3 2024

A recent article published in Sustainability proposed a comprehensive workflow to create a digital twin (DT) of an existing building with improved integration of different technologies, including building information modeling (BIM). This workflow, aiming to enhance energy efficiency, was tested in an office building through the “Living Lab” concept. 

Background

The evolution of BIM and related technology has resulted in a growing interest in real-time monitoring and control of buildings to enhance security, comfort, and overall quality of life. However, traditional monitoring systems have limited data visualization and processing capabilities and are not accessible on a large scale.

The DT technology can overcome certain limitations of current monitoring methods while facilitating integration between architecture and energy systems. A DT is a dynamic digital representation of a physical asset, updated continuously with real-time data deriving from sensors or other sources.

A DT can enhance a static data-rich BIM model for design, construction, and management by incorporating live data and analytics during a building's operation. This enables real-time monitoring, predictive maintenance, and scenario simulation. Therefore, this study exploited the synergy between BIM and DT technologies to create a real-time indoor environment monitoring and visualization workflow.

Methods

The office building chosen for this case study was part of a complex of university buildings housing the Engineering Departments of the University of L‘Aquila. To prepare the workflow, a real-time connection between the physical and virtual building was created using a middleware tool (Autodesk Tandem), allowing continuous information exchange between the wireless sensors installed in the building and the BIM model of the building.

The proposed workflow was divided into three macro phases. Phase 1 involved the physical study of the building through technical drawings and surveys. The building, “Solar House,” was made of reinforced concrete in the 1970s. Notably, the roof was designed to accommodate solar and photovoltaic panels; however, none were present during this study.

This first part of Phase 2 involved configuring wireless sensor networks (WNS) in the building’s four rooms, including a hallway, a lighting laboratory, and two offices (I and II), each with different functional and occupational characteristics. Wireless sensors were installed in these areas to detect air temperature and humidity and were accurately positioned to capture the room occupant’s thermal exchanges. The recorded data was sent to a remote server through a wireless connection.

In the second part of Phase 2, a three-dimensional (3D) BIM model of the chosen building was prepared using Autodesk Revit 2023. The available two-dimensional executive technical drawings, integrated with infrared thermography analysis, were used to prepare the BIM model. This BIM model was imported onto an online platform using Autodesk Tandem to create a DT of the building in the final phase of the workflow.

Results and Discussion

Initial assessments revealed that the temperature and humidity of the monitored rooms varied from 19.61 to 26.51 °C and 33.73% to 66.37%, respectively. The hallway had a minimum humidity and maximum temperature, which was attributed to its central location inside the building.

Alternatively, office I had the maximum humidity and minimum temperature. This was linked to the presence of large glazing in this room, which favored heat dispersion despite low external temperatures. Meanwhile, the average humidity and temperature recorded during the two weeks of monitoring were within the limits imposed by the national decree in force for all rooms except the hallway, where the average temperature exceeded the threshold of 0.38 °C.

A low correlation was observed between the temperatures and relative humidity values due to numerous factors influencing the humidity in each monitored room and their complex interaction. Additionally, the relation between internal humidity and temperature and the external climate was negligible. This was probably due to several factors, including occupancy, human activities, and the behavior of the building envelope.

The developed DT enabled a constant display of the parameters simply and quickly during monitoring, enabling real-time updating of the thermo-hygrometric condition of the different rooms at any instant, even remotely. Therefore, the DT could guide the facility managers to implement appropriate proactive and corrective maintenance interventions for energy efficiency. 

Conclusion and Future Prospects

Overall, the researchers presented a detailed workflow to create a DT through standard guidelines, which can be applied to various case studies. The developed workflow, tested on an office building, integrated real-time data collected through a WNS with a 3D BIM model that automatically combined the monitored data.

This study was an initial exploration of the DT technology, focusing on the second stage of DT evolution according to the Verdantix maturity model. The researchers suggest conducting repeated monitoring at different times of the year to broader understand the building’s performance. Additionally, the influence of other parameters, like indoor environmental quality, should also be considered.

Journal Reference

Rubeis, T.D. et al. (2024). A Workflow for a Building Information Modeling-Based Thermo-Hygrometric Digital Twin: An Experimentation in an Existing Building. Sustainability, 16(23), 10281. DOI: 10.3390/su162310281, https://www.mdpi.com/2071-1050/16/23/10281

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