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A Workflow for a Building Information Modeling-Based Thermo-Hygrometric Digital Twin: An Experimentation in an Existing Building

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  • Tullio De Rubeis

    (Department of Civil, Construction-Architectural and Environmental Engineering, University of L’Aquila, Piazzale Pontieri 1, Monteluco di Roio, 67100 L’Aquila, Italy)

  • Annamaria Ciccozzi

    (Department of Industrial and Information Engineering and Economics, University of L’Aquila, Piazzale Pontieri 1, Monteluco di Roio, 67100 L’Aquila, Italy)

  • Mattia Ragnoli

    (Department of Industrial and Information Engineering and Economics, University of L’Aquila, Piazzale Pontieri 1, Monteluco di Roio, 67100 L’Aquila, Italy)

  • Vincenzo Stornelli

    (Department of Industrial and Information Engineering and Economics, University of L’Aquila, Piazzale Pontieri 1, Monteluco di Roio, 67100 L’Aquila, Italy)

  • Stefano Brusaporci

    (Department of Civil, Construction-Architectural and Environmental Engineering, University of L’Aquila, Piazzale Pontieri 1, Monteluco di Roio, 67100 L’Aquila, Italy)

  • Alessandra Tata

    (Department of Civil, Construction-Architectural and Environmental Engineering, University of L’Aquila, Piazzale Pontieri 1, Monteluco di Roio, 67100 L’Aquila, Italy)

  • Dario Ambrosini

    (Department of Industrial and Information Engineering and Economics, University of L’Aquila, Piazzale Pontieri 1, Monteluco di Roio, 67100 L’Aquila, Italy)

Abstract

Building Information Modeling (BIM)-based digital twin (DT) could play a fundamental role in overcoming the limitations of traditional monitoring methods by driving the digitalization of the construction sector. While existing studies on the topic have provided valuable insights, significant knowledge gaps remain, which continue to hinder the large-scale adoption of this approach. Moreover, to date, there is no standardized procedure available, able to guide the step-by-step creation of a DT. Another significant challenge concerns the choice of technologies able to integrate perfectly with each other throughout the process. This paper outlines a comprehensive workflow for creating a digital twin (DT) of an existing building and proposes various solutions to improve the integration of different technologies involved. These enhancements aim to address the limitations of current monitoring methods and leverage the advantages of BIM and DT for accessing and managing monitoring data, ultimately facilitating the implementation of energy-efficient interventions. This work examines the concept of “Living Lab” in an office building also used as an academic laboratory. The created DT allowed for real-time remote monitoring of four rooms, each with a different functional and occupational characteristic, useful also for future predictive analyses.

Suggested Citation

  • Tullio De Rubeis & Annamaria Ciccozzi & Mattia Ragnoli & Vincenzo Stornelli & Stefano Brusaporci & Alessandra Tata & Dario Ambrosini, 2024. "A Workflow for a Building Information Modeling-Based Thermo-Hygrometric Digital Twin: An Experimentation in an Existing Building," Sustainability, MDPI, vol. 16(23), pages 1-30, November.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:23:p:10281-:d:1528163
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    References listed on IDEAS

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    1. Smarra, Francesco & Jain, Achin & de Rubeis, Tullio & Ambrosini, Dario & D’Innocenzo, Alessandro & Mangharam, Rahul, 2018. "Data-driven model predictive control using random forests for building energy optimization and climate control," Applied Energy, Elsevier, vol. 226(C), pages 1252-1272.
    2. Tran Duong Nguyen & Sanjeev Adhikari, 2023. "The Role of BIM in Integrating Digital Twin in Building Construction: A Literature Review," Sustainability, MDPI, vol. 15(13), pages 1-26, July.
    3. Annamaria Ciccozzi & Tullio de Rubeis & Domenica Paoletti & Dario Ambrosini, 2023. "BIM to BEM for Building Energy Analysis: A Review of Interoperability Strategies," Energies, MDPI, vol. 16(23), pages 1-45, November.
    4. Tullio de Rubeis & Mattia Ragnoli & Alfiero Leoni & Dario Ambrosini & Vincenzo Stornelli, 2024. "A Proposal for A Human-in-the-Loop Daylight Control System—Preliminary Experimental Results," Energies, MDPI, vol. 17(3), pages 1-18, January.
    5. Zhang, Fan & de Dear, Richard & Hancock, Peter, 2019. "Effects of moderate thermal environments on cognitive performance: A multidisciplinary review," Applied Energy, Elsevier, vol. 236(C), pages 760-777.
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