ABSTRACT
Building envelope retrofit plans should be assessed before execution. However, current building energy simulation for retrofit is mainly based on parameters as they are documented instead of in their present conditions. Researchers have applied digital twins (DT) to consider more dynamic processes for such tasks. Researchers need to solve the data exchange issues between the physical and digital worlds to fully use DT in terms of its real-time and multi-fidelity simulation features. They must also solve model updating issues between building information modeling (BIM) and building energy modeling (BEM).
We propose a DT-enabled co-simulation framework for building envelope energy audits and pixel-level simulation. This framework first analyzes inputs and outputs between building physical twin (PT) and DT for energy audits and indicates current technology restrictions to transferring data from PT to DT for building energy simulation. Second, the framework analyzes requirements for as-is simulation-related building parameters and illustrates current research gaps for model updating between BIM and BEM. Third, the framework introduces co-simulation approaches for building energy simulation and indicates how data is exchanged in co-simulation and how simulation results are interpreted for generating retrofit plans. Last, the framework presents current gaps for tracing retrofit plans back to building envelopes and how information is exchanged from DT to PT. Our studies contribute to (1) studying and defining a DT-enabled framework for building energy audits and multiresolution simulation, (2) systematically visualizing the data requirements for this proposed framework, and (3) investigating current technologies and research gaps for such a framework.
- Y. Hou, M. Chen, R. Volk, and L. Soibelman, "Investigation on performance of RGB point cloud and thermal information data fusion for 3D building thermal map modeling using aerial images under different experimental conditions," J. Build. Eng., vol. 45, p. 103380, Jan. 2022 Google ScholarCross Ref
- P. Kim, L. Price, Y. Cho, and J. Park, UAV-UGV Cooperative 3D Environmental Mapping. 2019. Google ScholarCross Ref
- T. Rakha, Y. El Masri, K. Chen, E. Panagoulia, and P. De Wilde,"Building envelope anomaly characterization and simulation usingdrone time-lapse thermography," Energy Build., vol. 259, p. 111754,Mar. 2022 Google ScholarCross Ref
- H. Andersson, K. Simonsson, D. Hilding, M. Schill, E. Sigfridsson,and D. Leidermark, "Validation of a co-simulation approach forhydraulic percussion units applied to a hydraulic hammer," Adv. Eng. Softw., vol. 131, pp. 102--115, May 2019, doi: a. Google ScholarDigital Library
- L. Gryga and B. Rossi, Co-simulation of Smart Grids: Dynamically Changing Topologies in Failure Scenarios. SciTePress, 2021. Accessed: Jul. 30, 2022. [Online]. Available:https://www.muni.cz/vyzkum/publikace/1762896Google Scholar
- M. Grieves, "Digital Twin: Manufacturing Excellence through Virtual Factory Replication," Mar. 2015.Google Scholar
- C. Boje, A. Guerriero, S. Kubicki, and Y. Rezgui, "Towards a semantic Construction Digital Twin: Directions for future research," Autom. Constr., vol. 114, p. 103179, Jun. 2020 Google ScholarCross Ref
- F. Tao, Q. Qi, L. Wang, and A. Y. C. Nee, "Digital Twins and Cyber-Physical Systems toward Smart Manufacturing and Industry 4.0:Correlation and Comparison," Engineering, vol. 5, no. 4, pp. 653--a. 661, Aug. 2019 Google ScholarCross Ref
- T. Rakha and A. Gorodetsky, "Review of Unmanned Aerial System (UAS) applications in the built environment: Towards automated building inspection procedures using drones," Autom. Constr., vol. 93, pp. 252--264, Sep. 2018 Google ScholarCross Ref
- Z. Mayer, J. Kahn, Y. Hou, and R. Volk, "AI-based thermal bridge detection of building rooftops on district scale using aerial images," in EG-ICE 2021 Workshop on Intelligent Computing in Engineering. Ed.: Jimmy Abualdenien, André Borrmann, Lucian-Constantin Ungureanu, Timo Hartmann, 2021, p. 497. Accessed: Jul. 30, 2022. [Online]. Available: https://publikationen.bibliothek.kit.edu/1000136256Google Scholar
- E. Tuegel, A. Ingraffea, T. Eason, and S. Spottswood, "Reengineering Aircraft Structural Life Prediction Using a Digital Twin," 2011 Google ScholarCross Ref
- C. Li, S. Mahadevan, Y. Ling, L. Wang, and S. Choze, "A dynamic Bayesian network approach for digital twin," in 19th AIAA Non-Deterministic Approaches Conference, American Institute of Aeronautics and Astronautics. Google ScholarCross Ref
- N. Salman, A. Khan, A. H. Kemp, and C. J. Noakes, "Indoor Temperature Forecast based on the Lattice Boltzmann method and Data Assimilation," Build. Environ., vol. 210, pp. 108654--108654, Feb. 2022.Google ScholarCross Ref
- T. Li, Y. Zhao, C. Zhang, J. Luo, and X. Zhang, "A knowledge guided and data-driven method for building HVAC systems fault diagnosis," Build. Environ., vol. 198, p. 107850, Jul. 2021 Google ScholarCross Ref
- M. Otter, H. Elmqvist, and S. E. Mattsson, "Hybrid modeling in Modelica based on the synchronous data flow principle," in Proceedings of the 1999 IEEE International Symposium on ComputerAided Control System Design (Cat. No.99TH8404), Aug. 1999, pp.151--157. Google ScholarCross Ref
- M. Angelosanti, N. N. Kulkarni, and A. Sabato, "Combination of Building Information Modeling and Infrared Point Cloud for Nondestructive Evaluation," in 2022 IEEE International Workshop on Metrology for Living Environment (MetroLivEn), May 2022, pp. 269--273. Google ScholarCross Ref
- H. Rallapalli, "A Comparison of Energy Plus and eQUEST Whole Building Energy Simulation Results for a Medium Sized Office Building," undefined, 2010, Accessed: Jul. 30, 2022. [Online]. Available: https://www.semanticscholar.org/paper/A-Comparison-of-Energy-Plus-and-eQUEST-Whole-Energy-Rallapalli/eb9b00063505f2c750e6c780bdad36ebf0dcbde3Google Scholar
- M. Wetter et al., "Lifting the garage door on spawn, and open-source BEM - controls engine," p. 8, 2020.Google Scholar
- D. Blum et al., "Building optimization testing framework (BOPTEST) for simulation-based benchmarking of control strategies in buildings," J. Build. Perform. Simul., vol. 14, no. 5, pp. 586--610, Sep. 2021 Google ScholarCross Ref
- M. Wiens, T. Meyer, and P. Thomas, "The Potential of FMI for the Development of Digital Twins for Large Modular Multi-Domain Systems," Model. Conf., pp. 235--240, Sep. 2021 Google ScholarCross Ref
- P. E. Leser and J. E. Warner, "A Diagnosis-Prognosis Feedback Loop for Improved Performance Under Uncertainties," Grapevine, TX, Jan. 2017. Accessed: Jul. 30, 2022. [Online]. Available: https://ntrs.nasa.gov/citations/20170001320Google Scholar
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