journal article·2023-03-29Open access

Development of Geospatial Data Acquisition, Modeling, and Service Technology for Digital Twin Implementation of Underground Utility Tunnel

Jaewook Lee, Yonghwan Lee, Changhee Hong

Applied Sciences· Volume 13· Issue 7

Abstract

In the maintenance domain of the construction industry, digital twins have been actively introduced based on the technologies of the Fourth Industrial Revolution with growing interest in three-dimensional spatial information facility management and disaster response service using digital twin technology. In particular, disasters or abnormal situations in an underground utility tunnel (UTU) can cause serious casualties and property damage since key elements of a city such as power, communications, water supply, and heating facilities are collectively accommodated in a certain underground space. This study established the methodology for implementing an underground utility tunnel through a digital twin. The novelty of this study is demonstrating a sequential procedure of implementing digital twin technology by configuring major layers such as data acquisition, modeling, and service. This methodology can serve as reference material or a training aid for implementing a digital twin of underground facilities or underground utility tunnels in the future; the proposed methodology will be verified when an actual digital twin service is provided.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: BIM and Construction Integration · Underground infrastructure and sustainability · Digital Transformation in Industry

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Department of Future & Smart Construction Research, Korea Institute of Civil Engineering and Building Technology, Goyang-si 10223, Republic of Korea

CEO, IANSIT, Incheon 21999, Republic of Korea

Funding

an Institute of Information and Communications Technology Planning and Evaluation (IITP) grant funded by the Korean government (MSIT, MOIS, MOLIT, and MOTIE)

References (35)

Show source-provided references
1. Digitalization of construction supply chain and procurement in the built environment: Emerging technologies and opportunities for sustainable processes10.1016/j.jclepro.2021.129093 ↗
2. Construction 4.0: The future of the construction industry in South Africa
3. Agnusdei, G.P., Elia, V., and Gnoni, M.G. (2021). Is digital twin technology supporting safety management? A bibliometric and systematic review. Appl. Sci., 11.10.3390/app11062767 ↗
4. Utilizing industry 4.0 on the construction site: Challenges and opportunities10.1109/TII.2020.3002197 ↗
5. Impact of work motivation on construction labor productivity10.1061/(ASCE)ME.1943-5479.0000824 ↗
6. COVID-19 pandemic: A review of smart cities initiatives to face new outbreaks10.1049/iet-smc.2020.0044 ↗
7. Towards a semantic Construction Digital Twin: Directions for future research10.1016/j.autcon.2020.103179 ↗
8. Jacoby, M., and Usländer, T. (2020). Digital twin and internet of things—Current standards landscape. Appl. Sci., 10.10.3390/app10186519 ↗
9. Singh, M., Srivastava, R., Fuenmayor, E., Kuts, V., Qiao, Y., Murray, N., and Devine, D. (2022). Applications of Digital Twin across industries: A review. Appl. Sci., 12.10.3390/app12115727 ↗
10. From LiDAR point cloud towards digital twin city: Clustering city objects based on Gestalt principles10.1016/j.isprsjprs.2020.07.020 ↗
11. Shirowzhan, S., Tan, W., and Sepasgozar, S.M. (2020). Digital twin and CyberGIS for improving connectivity and measuring the impact of infrastructure construction planning in smart cities. ISPRS Int. J. Geo-Inf., 9.10.3390/ijgi9040240 ↗
12. Construction and maintenance of urban underground infrastructure with digital technologies10.1016/j.autcon.2022.104464 ↗
13. About the importance of autonomy and digital twins for the future of manufacturing10.1016/j.ifacol.2015.06.141 ↗
14. Hehenberger, P., and Bradley, D. (2016). Mechatronic Futures: Challenges and Solutions for Mechatronic Systems and Their Designers, Springer International Publishing.10.1007/978-3-319-32156-1 ↗
15. Grieves, M., and Vickers, J. (2017). Transdisciplinary Perspectives on Complex Systems, Springer.
16. Meierhofer, J., Schweiger, L., Lu, J., Züst, S., West, S., Stoll, O., and Kiritsis, D. (2021). Digital twin-enabled decision support services in industrial ecosystems. Appl. Sci., 11.10.3390/app112311418 ↗
17. Pang, T.Y., Pelaez Restrepo, J.D., Cheng, C.-T., Yasin, A., Lim, H., and Miletic, M. (2021). Developing a digital twin and digital thread framework for an ‘Industry 4.0’Shipyard. Appl. Sci., 11.10.20944/preprints202012.0298.v1 ↗
18. Construction of a digital twin framework using free and open-source software programs10.1109/MIC.2021.3051798 ↗
19. Developing a digital twin at building and city levels: Case study of West Cambridge campus10.1061/(ASCE)ME.1943-5479.0000763 ↗
20. Integrated digital twin and blockchain framework to support accountable information sharing in construction projects10.1016/j.autcon.2021.103688 ↗
21. The connotation of digital twin, and the construction and application method of shop-floor digital twin10.1016/j.rcim.2020.102075 ↗
22. Kaewunruen, S., Sresakoolchai, J., Ma, W., and Phil-Ebosie, O. (2021). Digital twin aided vulnerability assessment and risk-based maintenance planning of bridge infrastructures exposed to extreme conditions. Sustainability, 13.10.3390/su13042051 ↗
23. Borth, M., Verriet, J., and Muller, G. (2019, January 19–22). Digital twin strategies for SoS 4 challenges and 4 architecture setups for digital twins of SoS. Proceedings of the 2019 14th Annual Conference System of Systems Engineering (SoSE), Anchorage, AK, USA.10.1109/SYSOSE.2019.8753860 ↗
24. Digital twin aided sustainability-based lifecycle management for railway turnout systems10.1016/j.jclepro.2019.04.156 ↗
25. Majumdar, P.K., FaisalHaider, M., and Reifsnider, K. (2013, January 8–11). Multi-physics response of structural composites and framework for modeling using material geometry. Proceedings of the 54th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference, Boston, MA, USA.10.2514/6.2013-1577 ↗
26. CityGML modelling for Singapore 3d national mapping10.5194/isprs-archives-XLII-4-W7-37-2017 ↗
27. Universal digital twin-a dynamic knowledge graph10.1017/dce.2021.10 ↗
28. Digital twin: Vision, benefits, boundaries, and creation for buildings10.1109/ACCESS.2019.2946515 ↗
29. A digital twin-based decision analysis framework for operation and maintenance of tunnels10.1016/j.tust.2021.104125 ↗
30. A digital twin approach for tunnel construction safety early warning and management10.1016/j.compind.2022.103783 ↗
31. Intelligent overall planning model of underground space based on digital twin10.1016/j.compeleceng.2022.108393 ↗
32. Kim, I., Lee, Y., and Choi, J. (2020). BIM-based hazard recognition and evaluation methodology for automating construction site risk assessment. Appl. Sci., 10.10.3390/app10072335 ↗
33. Chen, Y., Lin, H., and Liu, B. (2022). Review of Research Progresses and Application of Geothermal Disaster Prevention on Large-Buried Tunnels. Appl. Sci., 12.10.3390/app122110950 ↗
34. Park, J., Lee, H., and Kim, H.Y. (2022). Risk factor recognition for automatic safety management in construction sites using fast deep convolutional neural networks. Appl. Sci., 12.10.3390/app12020694 ↗
35. Tomar, R., Piesk, J., Sprengel, H., Isleyen, E., Duzgun, S., and Rostami, J. (2019). Tunnels and Underground Cities: Engineering and Innovation Meet Archaeology, Architecture and Art, CRC Press.