Case Study
Aivaliotis, P., K. Georgoulias, Z. Arkouli, and S. Makris. (2019). Methodology for Enabling Digital Twin Using Advanced Physics-Based Modelling in Predictive Maintenance. Procedia CIRP. 81: 417-422.
10.1016/j.procir.2019.03.072Ansari, F., R. Glawar, and T. Nemeth. (2019). PriMa: A Prescriptive Maintenance Model for Cyber-Physical Production Systems. International Journal of Computer Integrated Manufacturing. 32(4-5): 482-503.
10.1080/0951192X.2019.1571236Boje, C., A. Guerriero, S. Kubicki, and Y. Rezgui. (2020). Towards a Semantic Construction Digital Twin: Directions for Future Research. Automation in Construction. 114: 103179.
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Booyse, W., D. N. Wilke, and S. Heyns. (2020). Deep Digital Twins for Detection, Diagnostics and Prognostics. Mechanical Systems and Signal Processing. 140: 106612.
10.1016/j.ymssp.2019.106612BSI (British Standards Institution). (2018). BS EN ISO 19650-1; Organization and Digitization of Information about Buildings and Civil Engineering Works, including Building Information Modelling (BIM) - Information Management Using Building Information Modelling. Part 1, Concepts and Principles. Retrieved from https://www.iso.org/obp/ui/#iso:std:iso:19650:-1:ed-1:v1:en
Byun, N., W. S. Han, Y. W. Kwon, and Y. J. Kang. (2021). Development of BIM-Based Bridge Maintenance System Considering Maintenance Data Schema and Information System. Sustainability. 13(9): 4858.
10.3390/su13094858Chakraborty, S. and S. Adhikari. (2021). Machine Learning Based Digital Twin for Dynamical Systems with Multiple Time-Scales. Computers and Structures. 243: 106410.
10.1016/j.compstruc.2020.106410Cimino, C., E. Negri, and L. Fumagalli. (2019). Review of Digital Twin Applications in Manufacturing. Computers in Industry. 113: 103130.
10.1016/j.compind.2019.103130Cuong, N. D., M. Kang, D. Jang, and C. Shim. (2022). Developing Mixed Reality-Based Digital Twin Model for Bridge Maintenance System. Proceedings of the 22nd International Conference on Construction Applications of Virtual Reality.
Dan, D., Y. Ying, and L. Ge. (2022). Digital Twin System of Bridges Group Based on Machine Vision Fusion Monitoring of Bridge Traffic Load. IEEE Transactions on Intelligent Transportation Systems. 23(11): 22190-22205.
10.1109/TITS.2021.3130025Dang, H. V., M. Tatipamula, and H. X. Nguyen. (2022). Cloud-Based Digital Twinning for Structural Health Monitoring Using Deep Learning. IEEE Transactions on Industrial Informatics. 18(6): 3820-3830.
10.1109/TII.2021.3115119Davtalab, O. (2017). Benefits of Real-Time Data Driven BIM for FM Departments in Operations Control and Maintenance. In Congress on Computing in Civil Engineering, Proceedings. American Society of Civil Engineers (ASCE). 202-210.
10.1061/9780784480823.025Errandonea, I., S. Beltrán, and S. Arrizabalaga. (2020). Digital Twin for Maintenance: A Literature Review. Computers in Industry. 123(11): 103316.
10.1016/j.compind.2020.103316Evans, S., C. Savian, A. Burns, and C. Cooper. (2019). Digital Twins for the Built Environment. Retrieved from https://www.theiet.org/impact-society/factfiles/built-environment-factfiles/digital-twins-for-the-built-environment/
Fang, Z., Q. Lu, X. Xie, A. K. Parlikad, J. Schooling, and M. Pitt. (2022). Definitions and Principles of Digital Twins. In Digital Twins in the Built Environment. ICE Publishing. 5-27.
10.1680/dtbe.65802.005Febrianto, E., L. Butler, M. Girolami, and F. Cirak. (2021). Digital Twinning of Self-Sensing Structures Using the Statistical Finite Element Method. ArXiv. https://doi.org/10.48550/arXiv.2103.13729
10.1017/dce.2022.28Franciosi, M., M. Kasser, and M. Viviani. (2024). Digital Twins in Bridge Engineering for Streamlined Maintenance and Enhanced Sustainability. Automation in Construction. 168(Part A): 105834.
10.1016/j.autcon.2024.105834Gao, Y., G. Xiong, Z. Hu, and C. Chai. (2024). Bridge Digital Twin for Practical Bridge Operation and Maintenance by Integrating GIS and BIM. Buildigs. 14(12): 3731.
10.3390/buildings14123731Gordon, C. A. K., B. Burnak, M. Onel, and E. N. Pistikopoulos. (2020). Data-Driven Prescriptive Maintenance: Failure Prediction Using Ensemble Support Vector Classification for Optimal Process and Maintenance Scheduling. Industrial and Engineering Chemistry Research. 59(44): 19607-19622.
10.1021/acs.iecr.0c03241Grieves, M. (2014). Digital Twin: Manufacturing Excellence through Virtual Factory Replication. White Paper (March). 1-7. Retrieved from https://www.researchgate.net/publication/275211047_Digital_Twin_Manufacturing_Excellence_through_Virtual_Factory_Replication
Gürdür Broo, D., M. Bravo-Haro, and J. Schooling. (2022). Design and Implementation of a Smart Infrastructure Digital Twin. Automation in Construction. 136: 104171.
10.1016/j.autcon.2022.104171He, Z., W. Li, H. Salehi, H. Zhang, H. Zhou, and P. Jiao. (2022). Integrated Structural Health Monitoring in Bridge Engineering. Automation in Construction. 136: 104168.
10.1016/j.autcon.2022.104168Heng, J., L. Lai, Y. Dong, S. Kaewunruen, and C. Baniotopoulos. (2024). Digital Twin for Intelligent Maintenance Towards Sustainable Bridges. Bridge Maintenance, Safety, Management, Digitalization and Sustainability - Proceedings of the 12th International Conference on Bridge Maintenance, Safety and Management (IABMAS 2024). 693-700.
10.1201/9781003483755-80Hielscher, T., S. Khalil, N. Virgona, and S. A. Hadigheh. (2023). A Neural Network Based Digital Twin Model for the Structural Health Monitoring of Reinforced Concrete Bridges. Structures. 57: 105248.
10.1016/j.istruc.2023.105248Jang, J. H., H. H. An, S. H. Lee, and J. H. Jung. (2023). Organize Real-Time Monitoring Data and Link to Digital Twins for Cable Bridge. Proceedings of the KSCE 2023 Convention. 93-94.
Jeon, C. H., C. S. Shim, Y. H. Lee, and J. Schooling. (2024). Prescriptive Maintenance of Prestressed Concrete Bridges considering Digital Twin and Key Performance Indicator. Engineering Structures. 302: 117383.
10.1016/j.engstruct.2023.117383Jeon, C.-H., Nguyen, D.-C., Roh, G., and Shim, C.-S. (2023). Development of BrIM-Based Bridge Maintenance System for Existing Bridges. Buildings. 13(9): 2332.
10.3390/buildings13092332JSCE (Japan Society of Civil Engineers). (2007). Standard Specifications for Concrete Structures - 2007; Maintenance. Retrieved from https://www.jsce-int.org/system/files/JGC15_Standard_Specifications_Design_1.0.pdf
Kaewunruen, S., J. Sresakoolchai, W. Ma, and O. Phil-Ebosie. (2021). Digital Twin Aided Vulnerability Assessment and Risk-Based Maintenance Planning of Bridge Infrastructures Exposed to Extreme Conditions. Sustainability. 13(4): 1-19.
10.3390/su13042051Kang, J. S., K. Chung, and E. J. Hong. (2021). Multimedia Knowledge-Based Bridge Health Monitoring Using Digital Twin. Multimedia Tools and Applications. 80: 34609-34624.
10.1007/s11042-021-10649-xKim, J., Y. Ahn, and H. Yeo. (2016). A Comparative Study of Time-Based Maintenance and Condition-Based Maintenance for Optimal Choice of Maintenance Policy. Structure and Infrastructure Engineering. 12(12): 1525-1536.
10.1080/15732479.2016.1149871Kim, Y.-W., S. Yoo, H. Lee, and S. H. Kim. (2020). Characterization of Digital Twin. Retrieved from https://www.researchgate.net/publication/353930234_Characterization_of_Digital_Twin
Koutamanis, A. (2020). Dimensionality in BIM: Why BIM Cannot Have More Than Four Dimensions? Automation in Construction. 114: 103153.
10.1016/j.autcon.2020.103153Kritzinger, W., M. Karner, G. Traar, J. Henjes, and W. Sihn. (2018). Digital Twin in Manufacturing: A Categorical Literature Review and Classification. IFAC-PapersOnLine. 51(11): 1016-1022.
10.1016/j.ifacol.2018.08.474Lai, X., Z. Kan, W. Sun, X. Song, B. Tian, and T. Yuan. (2024). Digital Twin-Based Non-Destructive Testing for Structural Health Monitoring of Bridges. Nondestructive Testing and Evaluation. 39(1): 57-74.
10.1080/10589759.2023.2239434Lin, K., Y. L. Xu, X. Lu, Z. Guan, and J. Li. (2021). Digital Twin-Based Collapse Fragility Assessment of a Long-Span Cable-Stayed Bridge under Strong Earthquakes. Automation in Construction. 123: 103547.
10.1016/j.autcon.2020.103547Liu, Z., N. Meyendorf, and N. Mrad. (2018). The Role of Data Fusion in Predictive Maintenance Using Digital Twin. In AIP Conference Proceedings. American Institute of Physics Inc. 1949(1): 020023.
10.1063/1.5031520Lu, Q., A. K. Parlikad, P. Woodall, G. Don Ranasinghe, X. Xie, Z. Liang, and J. Schooling. (2020). Developing a Digital Twin at Building and City Levels: Case Study of West Cambridge Campus. Journal of Management in Engineering. 36(3).
10.1061/(ASCE)ME.1943-5479.0000763Lu, Q., X. Xie, A. K. Parlikad, J. M. Schooling, and E. Konstantinou. (2021). Moving from Building Information Models to Digital Twins for Operation and Maintenance. Proceedings of the Institution of Civil Engineers - Smart Infrastructure and Construction. 174(2): 46-56.
10.1680/jsmic.19.00011Mahmoodian, M., F. Shahrivar, S. Setunge, and S. Mazaheri. (2022). Development of Digital Twin for Intelligent Maintenance of Civil Infrastructure. Sustainability. 14(14): 8664.
10.3390/su14148664Nicał, A. K. and W. Wodyński. (2016). Enhancing Facility Management through BIM 6D. Procedia Engineering. 164: 299-306.
10.1016/j.proeng.2016.11.623Opoku, D. G. J., S. Perera, R. Osei-Kyei, and M. Rashidi. (2021). Digital Twin Application in the Construction Industry: A Literature Review. Journal of Building Engineering. 40: 102726.
10.1016/j.jobe.2021.102726Padovano, A., F. Longo, L. Nicoletti, L. Gazzaneo, A. Chiurco, and S. Talarico. (2021). A Prescriptive Maintenance System for Intelligent Production Planning and Control in a Smart Cyber-Physical Production Line. Procedia CIRP. 104: 1819-1824.
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Ritto, T. G. and F. A. Rochinha. (2021). Digital Twin, Physics-Based Model, and Machine Learning Applied to Damage Detection in Structures. Mechanical Systems and Signal Processing. 155: 107614.
10.1016/j.ymssp.2021.107614Seo, J., J. W. Hu, and J. Lee. (2016). Summary Review of Structural Health Monitoring Applications for Highway Bridges. Journal of Performance of Constructed Facilities. 30(4): 1-9.
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Shim, C. S., N. S. Dang, S. Lon, and C. H. Jeon. (2019). Development of a Bridge Maintenance System for Prestressed Concrete Bridges Using 3D Digital Twin Model. Structure and Infrastructure Engineering. 15(10): 1319-1332.
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10.3390/s2309423037177433PMC10181214Sun, L., Z. Shang, Y. Xia, S. Bhowmick, and S. Nagarajaiah. (2020). Review of Bridge Structural Health Monitoring Aided by Big Data and Artificial Intelligence: From Condition Assessment to Damage Detection. Journal of Structural Engineering. 146(5).
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Wang, J., L. Ye, R. X. Gao, C. Li, and L. Zhang. (2019). Digital Twin for Rotating Machinery Fault Diagnosis in Smart Manufacturing. International Journal of Production Research. 57(12): 3920-3934.
10.1080/00207543.2018.1552032- Publisher :Korean Society of Disaster and Security
- Publisher(Ko) :한국방재안전학회
- Journal Title :Journal of Korean Society of Disaster and Security
- Journal Title(Ko) :한국방재안전학회 논문집
- Volume : 17
- No :4
- Pages :51-62
- Received Date : 2024-11-09
- Revised Date : 2024-11-18
- Accepted Date : 2024-11-18
- DOI :https://doi.org/10.21729/ksds.2024.17.4.51