|
|
数字孪生技术在城市排水系统中的进展与挑战
|
Abstract:
在城市化快速发展的背景下，城市排水系统面临着极端天气引发的洪涝、水资源供需矛盾和水环境污染等前所未有的挑战。数字孪生技术，作为一种融合了物联网、大数据、人工智能等前沿技术的创新手段，通过构建物理实体的精确数字副本，为城市水安全保障提供了全新的视角和解决方案。本文概述了数字孪生技术在城市排水系统中的多方面应用进展，分析了其在防洪减灾、水资源管理、水生态保护及水利工程智能化等方面的实际应用现状，并重点探讨了实时监测、模拟仿真、预测预警和决策支持等关键技术如何提升排水系统的效率和应对能力。最后，文章对未来发展趋势进行了展望，强调了技术创新、跨学科合作和政策支持对未来数字孪生技术发展的重要性。随着技术的不断进步，数字孪生技术将在城市排水系统中扮演更加关键的角色，提供更高效、智能的水安全保障解决方案。
Against the backdrop of urbanization, urban drainage systems are facing unprecedented challenges such as flooding, contradictions in water supply and demand, water environmental pollution, and so on. Digital twin technology, as an innovative approach which integrates cutting-edge technologies like Internet of Things, big data, and artificial intelligence, provides a new perspective and solution for urban water safety by constructing an exact digital replica of physical entities. In this paper, the advances of digital twin technology in urban drainage systems were discussed. Especially the actual applications in flooding disaster early warning, water resource management, water ecological protection, and the intelligent management of water conservancy projects were analysized. This paper also focused on how key technologies such as real-time monitoring, simulation, predictive warning, and decision support can enhance the efficiency and response capabilities of drainage systems. Finally, the article looks forward to future development trends, emphasizing the importance of technological innovation, interdisciplinary cooperation, and policy support for the future development of digital twin technology. With continuous technological advancements, digital twin technology will play a more critical role in urban drainage systems, offering more efficient and intelligent solutions for water safety.
| [1] | 徐军, 连雄伟. 数字孪生在城市排水体系中的应用研究[J]. 数据中心建设, 2022(12): 25-31. |
| [2] | 陈国标. 基于数字孪生技术的九江城市智慧水务平台设计与实现[J]. 人民珠江, 2022, 43(6): 86-93. |
| [3] | 张以晓. 论数字孪生技术与智慧水利建设[J]. 黑龙江水利科技, 2022, 50(7): 180-183. |
| [4] | Boschert, S., Heinrich, C. and Rosen, R. (2018) Next Generation Digital Twin: An Ecosystem for Mechatronic Systems? IFAC-PapersOnLine, 52, 265-270. |
| [5] | 刘大同, 郭凯, 王本宽, 等. 数字孪生技术综述与展望[J]. 仪器仪表学报, 2018, 39(11): 1-10. |
| [6] | Singh, M., Fuenmayor, E., Hinchy, E., Qiao, Y., Murray, N. and Devine, D. (2021) Digital Twin: Origin to Future. Applied System Innovation, 4, Article 36. https://doi.org/10.3390/asi4020036 |
| [7] | 刘青, 刘滨, 王冠, 等. 数字孪生的模型, 问题与进展研究[J]. 河北科技大学学报, 2019, 40(1): 67-78. |
| [8] | 封顺天, 张东, 张舒, 等. 数字孪生城市开启城市数字化转型新篇章[J]. 信息通信技术与政策, 2020, 46(3): 9-15. |
| [9] | Al-Sehrawy, R., Kumar, B. and Watson, R. (2021) A Digital Twin Uses Classification System for Urban Planning & City Infrastructure Management. Journal of Information Technology in Construction, 26, 832-862. https://doi.org/10.36680/j.itcon.2021.045 |
| [10] | Tzachor, A., Sabri, S., Richards, C.E., Rajabifard, A. and Acuto, M. (2022) Potential and Limitations of Digital Twins to Achieve the Sustainable Development Goals. Nature Sustainability, 5, 822-829. https://doi.org/10.1038/s41893-022-00923-7 |
| [11] | 王松岳, 陈凤琴, 朱照远. 数字孪生技术在智慧水利建设中的应用[J]. 山东水利, 2023(9): 13-14. |
| [12] | 马士玲. 物联网技术在智慧城市建设中的应用[J]. 物联网技术, 2012, 2(2): 3. |
| [13] | 崔雷. 数字孪生技术在现代化水利工程中的应用[J]. 科技与创新, 2023(22): 143-145, 148. |
| [14] | Tao, F., Cheng, J., Qi, Q., Zhang, M., Zhang, H. and Sui, F. (2017) Digital Twin-Driven Product Design, Manufacturing and Service with Big Data. The International Journal of Advanced Manufacturing Technology, 94, 3563-3576. https://doi.org/10.1007/s00170-017-0233-1 |
| [15] | Rathore, M.M., Shah, S.A., Shukla, D., Bentafat, E. and Bakiras, S. (2021) The Role of AI, Machine Learning, and Big Data in Digital Twinning: A Systematic Literature Review, Challenges, and Opportunities. IEEE Access, 9, 32030-32052. https://doi.org/10.1109/access.2021.3060863 |
| [16] | 付强. 云计算与边缘计算协同发展的相关探讨[J]. 中国设备工程, 2022(12): 218-220. |
| [17] | Groshev, M., Guimarães, C., Martín-Pérez, J. and de la Oliva, A. (2021) Toward Intelligent Cyber-Physical Systems: Digital Twin Meets Artificial Intelligence. IEEE Communications Magazine, 59, 14-20. https://doi.org/10.1109/mcom.001.2001237 |
| [18] | 陶飞, 刘蔚然, 刘检华, 等. 数字孪生及其应用探索[J]. 计算机集成制造系统, 2018, 24(1): 1-18. |
| [19] | 于勇, 范胜廷, 彭关伟, 等. 数字孪生模型在产品构型管理中应用探讨[J]. 航空制造技术, 2017(7): 41-45. |
| [20] | Hu, W., Zhang, T., Deng, X., Liu, Z. and Tan, J. (2021) Digital Twin: A State-Of-The-Art Review of Its Enabling Technologies, Applications and Challenges. Journal of Intelligent Manufacturing and Special Equipment, 2, 1-34. https://doi.org/10.1108/jimse-12-2020-010 |
| [21] | Wang, Z. (2020) Digital Twin Technology. In: Bányai, T. and De Felice, A.P.F., Eds., Industry 4.0—Impact on Intelligent Logistics and Manufacturing, Intech Open, 95-114. https://doi.org/10.5772/intechopen.80974 |
| [22] | 凌勇. 基于物联网的城市排水管线在线监测系统的设计与实现[D]: [硕士学位论文]. 济南: 山东大学, 2013. |
| [23] | Pedersen, A.N., Borup, M., Brink-Kjær, A., Christiansen, L.E. and Mikkelsen, P.S. (2021) Living and Prototyping Digital Twins for Urban Water Systems: Towards Multi-Purpose Value Creation Using Models and Sensors. Water, 13, Article 592. https://doi.org/10.3390/w13050592 |
| [24] | Kim, M. and Bartos, M. (2024) A Digital Twin Model for Contaminant Fate and Transport in Urban and Natural Drainage Networks with Online State Estimation. Environmental Modelling & Software, 171, Article ID: 105868. https://doi.org/10.1016/j.envsoft.2023.105868 |
| [25] | Bartos, M. and Kerkez, B. (2021) Pipedream: An Interactive Digital Twin Model for Natural and Urban Drainage Systems. Environmental Modelling & Software, 144, Article ID: 105120. https://doi.org/10.1016/j.envsoft.2021.105120 |
| [26] | Sharifi, A., Tarlani Beris, A., Sharifzadeh Javidi, A., Nouri, M., Gholizadeh Lonbar, A. and Ahmadi, M. (2024) Application of Artificial Intelligence in Digital Twin Models for Stormwater Infrastructure Systems in Smart Cities. Advanced Engineering Informatics, 61, Article ID: 102485. https://doi.org/10.1016/j.aei.2024.102485 |
| [27] | Roudbari, N.S., Punekar, S.R., Patterson, Z., Eicker, U. and Poullis, C. (2024) From Data to Action in Flood Forecasting Leveraging Graph Neural Networks and Digital Twin Visualization. Scientific Reports, 14, Article No. 18571. https://doi.org/10.1038/s41598-024-68857-y |
| [28] | Thakur, S. (2024) Based on Digital Twin Technology, an Early Warning System and Strategy for Predicting Urban Waterlogging. In: Anand, A., Sardana, A., Kumar, A., Mohapatra, S.K. and Gupta, S., Eds., Simulation Techniques of Digital Twin in Real‐Time Applications: Design Modeling and Implementation, Wiley, 301-318. |
| [29] | Park, S., Kim, J., Kim, Y. and Kang, J. (2024) Participatory Framework for Urban Pluvial Flood Modeling in the Digital Twin Era. Sustainable Cities and Society, 108, Article ID: 105496. https://doi.org/10.1016/j.scs.2024.105496 |
| [30] | Manocha, A., Sood, S.K. and Bhatia, M. (2024) Digital Twin-Assisted Fuzzy Logic-Inspired Intelligent Approach for Flood Prediction. IEEE Sensors Journal. https://doi.org/10.1109/jsen.2023.3322535 |
| [31] | Wang, A., Li, H., He, Z., Tao, Y., Wang, H., Yang, M., et al. (2024) Digital Twins for Wastewater Treatment: A Technical Review. Engineering, 36, 21-35. https://doi.org/10.1016/j.eng.2024.04.012 |
| [32] | Saddiqi, M.M., Zhao, W., Cotterill, S. and Dereli, R.K. (2023) Smart Management of Combined Sewer Overflows: From an Ancient Technology to Artificial Intelligence. WIREs Water, 10, e1635. https://doi.org/10.1002/wat2.1635 |
| [33] | Liu, W., He, S., Mou, J., Xue, T., Chen, H. and Xiong, W. (2023) Digital Twins-Based Process Monitoring for Wastewater Treatment Processes. Reliability Engineering & System Safety, 238, Article ID: 109416. https://doi.org/10.1016/j.ress.2023.109416 |
| [34] | Komulainen, T. and Johansen, H. (2022) Possible Concepts for Digital Twin Simulator for WWTP. Linköping Electronic Conference Proceedings, 21-23 September 2021, 398-404. https://doi.org/10.3384/ecp21185398 |
| [35] | 朱思宇, 杨红卫, 尹桂平, 等. 基于数字孪生的智慧水利框架体系研究[J]. 水利水运工程学报, 2023(3): 68-74. |
| [36] | Botín-Sanabria, D.M., Mihaita, A., Peimbert-García, R.E., Ramírez-Moreno, M.A., Ramírez-Mendoza, R.A. and Lozoya-Santos, J.d.J. (2022) Digital Twin Technology Challenges and Applications: A Comprehensive Review. Remote Sensing, 14, Article 1335. https://doi.org/10.3390/rs14061335 |
| [37] | Fuller, A., Fan, Z., Day, C. and Barlow, C. (2020) Digital Twin: Enabling Technologies, Challenges and Open Research. IEEE Access, 8, 108952-108971. https://doi.org/10.1109/access.2020.2998358 |
| [38] | He, Y., Guo, J. and Zheng, X. (2018) From Surveillance to Digital Twin: Challenges and Recent Advances of Signal Processing for Industrial Internet of Things. IEEE Signal Processing Magazine, 35, 120-129. https://doi.org/10.1109/msp.2018.2842228 |
| [39] | 陈婉玲, 刘青松, 林洁群. 浅析人工智能在数字孪生城市中的应用[J]. 信息通信技术与政策, 2020, 46(3): 16-19. |
| [40] | 周博. 基于数字孪生技术的智慧水利应用研究[J]. 水利电力技术与应用, 2024, 6(2): 197-199. |
| [41] | 李赟. 智慧城市数字孪生技术应用探索及标准化研究[J]. 信息技术与标准化, 2021(10): 13-19. |
| [42] | da Silva Mendonça, R., de Oliveira Lins, S., de Bessa, I.V., de Carvalho Ayres, F.A., de Medeiros, R.L.P. and de Lucena, V.F. (2022) Digital Twin Applications: A Survey of Recent Advances and Challenges. Processes, 10, Article 744. https://doi.org/10.3390/pr10040744 |
| [43] | Rasheed, A., San, O. and Kvamsdal, T. (2019) Digital Twin: Values, challenges and Enablers from a Modeling Perspective. IEEE Access, 8, 21980-22012. |
| [44] | 朱培佩. 基于云计算的大数据分析优化技术研究[J]. 现代信息科技, 2019, 3(14): 69-70, 73. |
| [45] | 全海金, 何映思. 基于云计算的大数据信息处理技术研究[J]. 机床与液压, 2019, 47(24): 118-124. |
| [46] | 王家玲, 查道懂, 张春梅. 基于区块链的数字孪生图书馆管理与服务模式研究[J]. 新世纪图书馆, 2023(5): 63-69. |
| [47] | 数字孪生城市白皮书[EB/OL]. https://www.caict.ac.cn/kxyj/qwfb/bps/202401/P020240326602142432204.pdf, 2024-10-18. |
