The Role of Digital Twins and Their Application for the Built Environment

Halmetoja, Esa

doi:10.1007/978-3-030-82430-3_18

Cited by 9 publications

(9 citation statements)

References 14 publications

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“…Though digital twin technology offers significant potential, several challenges remain to overcome, including data processing on a large scale, data security and privacy, cost control, technical limitations, and seamless integration of the physical and digital worlds. Several additional challenges and complexity arise in the architectural field, particularly in data collection and processing, real-time monitoring, data updates, data access, personalization of user interface design, cybersecurity, and integration with intelligent solutions [7]. Professionals in related industries are actively engaged in research and development to overcome these challenges.…”

Section: Definition and Development History Of Digital Twinmentioning

confidence: 99%

Exploring the Benefits and Limitations of Digital Twin Technology in Building Energy

Tahmasebinia,

Lin,

et al. 2023

Applied Sciences

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Buildings consume a significant amount of energy throughout their lifecycle; Thus, sustainable energy management is crucial for all buildings, and controlling energy consumption has become increasingly important for achieving sustainable construction. Digital twin (DT) technology, which lies at the core of Industry 4.0, has gained widespread adoption in various fields, including building energy analysis. With the ability to monitor, optimize, and predict building energy consumption in real time. DT technology has enabled sustainable building energy management and cost reduction. This paper provides a comprehensive review of the development and application of DT technology in building energy. Specifically, it discusses the background of building information modeling (BIM) and DT technology and their application in energy optimization in buildings. Additionally, this article reviews the application of DT technology in building energy management, indoor environmental monitoring, and building energy efficiency evaluation. It also examines the benefits and challenges of implementing DT technology in building energy analysis and highlights recent case studies. Furthermore, this review emphasizes emerging trends and opportunities for future research, including integrating machine learning techniques with DT technology. The use of DT technology in the energy sector is gaining momentum as efforts to optimize energy efficiency and reduce carbon emissions continue. The advancement of building energy analysis and machine learning technologies is expected to enhance prediction accuracy, optimize energy efficiency, and improve management processes. These advancements have become the focal point of current literature and have the potential to facilitate the transition to clean energy, ultimately achieving sustainable development goals.

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Section: Definition and Development History Of Digital Twinmentioning

confidence: 99%

Exploring the Benefits and Limitations of Digital Twin Technology in Building Energy

Tahmasebinia,

Lin,

et al. 2023

Applied Sciences

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“…Even new approaches are constantly being considered and researched, it appears that more and more emphasis is being placed on the technology of Digital Twins (Chen K. et al, 2022;Halmetoja, 2022;Hosamo et al, 2022b;Xia et al, 2022). It is easy to comprehend why this would be the case, given that utilizing various approaches has the potential to assist mitigate the drawbacks of any one approach.…”

Section: Recent Researchmentioning

confidence: 99%

A review of the Digital Twin technology for fault detection in buildings

Hosamo

Nielsen

Alnmr

et al. 2022

Front. Built Environ.

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This study aims to evaluate the utilization of technology known as Digital Twin for fault detection in buildings. The strategy consisted of studying existing applications, difficulties, and possibilities that come with it. The Digital Twin technology is one of the most intriguing newly discovered technologies rapidly evolving; however, some problems still need to be addressed. First, using Digital Twins to detect building faults to prevent future failures and cutting overall costs by improving building maintenance is still ambiguous. Second, how Digital Twin technology may be applied to discover inefficiencies inside the building to optimize energy usage is not well defined. To address these issues, we reviewed 326 documents related to Digital Twin, BIM, and fault detection in civil engineering. Then out of the 326 documents, we reviewed 115 documents related to Digital Twin for fault detection in detail. This study used a qualitative assessment to uncover Digital Twin technology’s full fault detection capabilities. Our research concludes that Digital Twins need more development in areas such as scanner hardware and software, detection and prediction algorithms, modeling, and twinning programs before they will be convincing enough for fault detection and prediction. In addition, more building owners, architects, and engineers need substantial financial incentives to invest in condition monitoring before many of the strategies discussed in the reviewed papers will be used in the construction industry. For future investigation, more research needs to be devoted to exploring how machine learning may be integrated with other Digital Twin components to develop new fault detection methods.

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“…DTs can serve multiple purposes, such as performance predictions, fault detection and diagnosis, stress testing with extreme conditions to test robustness, and optimization of control strategies. Despite the potential benefits of DTs as BPS models, they remain complex models that are difficult to implement on a large scale, and there is sparse knowledge on spatial-and temporal resolutions predicting heating energy use and indoor air temperature in multi-story residential buildings [6].…”

Section: Introductionmentioning

confidence: 99%

Influence of Temporal- and Spatial Resolutions on Building Performance Simulation Models: A Danish Residential Building Case Study

Andersen,

Marszal-Pomianowska,

Jokubauskis

et al. 2023

J. Phys.: Conf. Ser.

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This study aims to assess the accuracy of a building performance simulation (BPS) model developed in IDA ICE software, focusing on heating energy use and indoor air temperatures in a low-energy multi-story residential building located in Northern Denmark. Six apartments were analyzed, and a comparative analysis was conducted between the measured parameters and the results obtained from BPS models with different spatial and temporal resolutions. The findings indicate that while the BPS models can provide reasonably accurate estimates of heating energy use, they may not fully capture the nuanced response to factors such as indoor air temperature This highlights the importance of incorporating qualitative inputs and environmental variables into these BPS models, including heating and/or cooling setpoints, internal gains, and weather conditions. Overall, this study provides insights into the limitations and opportunities of BPS models for accurately estimating heating energy use and indoor air temperatures in low-energy residential buildings.

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The Role of Digital Twins and Their Application for the Built Environment

Cited by 9 publications

References 14 publications

Exploring the Benefits and Limitations of Digital Twin Technology in Building Energy

Exploring the Benefits and Limitations of Digital Twin Technology in Building Energy

A review of the Digital Twin technology for fault detection in buildings

Influence of Temporal- and Spatial Resolutions on Building Performance Simulation Models: A Danish Residential Building Case Study

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