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沉管隧道运维技术发展现状综述
引用本文:丁浩,景强,闫禹,张娜,李旺林.沉管隧道运维技术发展现状综述[J].中国公路学报,2022,35(10):1-12.
作者姓名:丁浩  景强  闫禹  张娜  李旺林
作者单位:1. 招商局重庆交通科研设计院有限公司, 重庆 400067;2. 公路隧道国家工程研究中心, 重庆 400067;3. 港珠澳大桥管理局, 广东 珠海 519060;4. 重庆交通大学 土木工程学院, 重庆 400074
基金项目:国家重点研发计划项目(2019YFB1600702)
摘    要:为促进沉管隧道运维技术发展,通过文献调研、现场调查与数据挖掘等方法,系统梳理了沉管隧道的国内外概况、运营与病损情况、检测与评估技术、病害预防及处治等方面的技术成果。以沉管隧道用途、管节长度与埋置水深等关键信息为基础,阐释了其国内外发展概况;简述了沉管隧道运营现状,并重点对沉管隧道接头、主体结构、附属结构与设施的常见病损特征进行了数据挖掘;对隧道检测、监测与评估技术进行了对照剖析,阐述了目前国内外检测与评估技术的进步与不足;从前期预防与后期处治的双角度,阐述了沉管隧道的不均匀沉降、裂缝与渗漏水等常见病害的预防与处治;并从沉管隧道运维信息的角度,对其运维技术的发展趋势进行了展望。结果表明:沉管隧道建设已取得丰硕成果,但仍存在诸多运维技术难题;在役沉管隧道出现了过大(差异)沉降、裂缝、渗漏水等病损,其中管节不均匀沉降最为常见;沉管隧道检测仍以结构检测对象和传统周期性检测方法为主;沉管隧道评估诊断多侧重于沉降量控制标准的角度,考虑多因素综合角度的服役性能评估尚处于空白阶段;沉管隧道常见病害应坚持建设期预防和运营期处治双管齐下的对策。未来,沉管隧道运维将向运营环境全要素拓展,并更注重实时自动化监测技术、大数据智能评估技术与基于状态的养护策略等新技术。

关 键 词:隧道工程  沉管隧道  综述  运维  评估  监测  病害  
收稿时间:2021-12-27

Development Status Overview of Operation and Maintenance Technology of Immersed Tunnel
DING Hao,JING Qiang,YAN Yu,ZHANG Na,LI Wang-lin.Development Status Overview of Operation and Maintenance Technology of Immersed Tunnel[J].China Journal of Highway and Transport,2022,35(10):1-12.
Authors:DING Hao  JING Qiang  YAN Yu  ZHANG Na  LI Wang-lin
Affiliation:1. China Merchants Chongqing Communications Technology Research & Design Institute Co. Ltd., Chongqing 400067, China;2. National Engineering-research Center for Road Tunnel, Chongqing 400067, China;3. Hong Kong-Zhuhai-Macao Bridge Authority, Zhuhai 519060, Guangdong, China;4. School of Civil Engineering, Chongqing Jiaotong University, Chongqing 400074, China
Abstract:In order to promote the development of immersed tunnel operation and maintenance technology, through literature research, field investigation and data mining, the technical achievements of immersed tunnel at home and abroad, operation and damage situation, detection and evaluation technology, disease prevention and treatment, and development prospect of operation and maintenance technology were systematically combed. Based on the key information such as the application of immersed tunnel, length of pipe section and buried depth, the development situation at home and abroad was explained. The operation status of immersed tunnel was briefly described, and the data mining analysis was focused on the common damage characteristics of immersed tunnel joints, main structure, subsidiary structure and facilities. The tunnel detection, monitoring and evaluation technologies were compared and analyzed, and the progress and shortcomings of current detection and evaluation technologies at home and abroad were expounded. From the perspectives of early prevention and late treatment, the common diseases such as uneven settlement, cracks and water leakage of immersed tunnel were described. Based on the operation and maintenance information of immersed tunnel, the development trend of its operation and maintenance technology was prospected. The results show that the immersed tunnel construction has achieved fruitful results, but there are many technical problems in operation and maintenance. In-service immersed tunnels have been damaged by excessive (differential) settlement, cracks and water leakage, and the uneven settlement of tube joints is the most common. The detection of immersed tunnel is still based on structural detection objects and traditional periodic detection methods. The evaluation and diagnosis of immersed tunnel mostly focus on the angle of settlement control standard, and the service performance evaluation considering multi-factor comprehensive angle is still blank. The common diseases of immersed tunnel should adhere to the countermeasures of prevention in construction period and treatment in operation period. In the future, the operation and maintenance of immersed tunnel will expand to all elements of operation environment, and pay more attention to new technologies such as real-time automatic monitoring technology, big data intelligent evaluation technology and state-based maintenance strategy.
Keywords:tunnel engineering  immersed tunnel  review  operation and maintenance  assessment  monitoring  disease  
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