公路隧道结构安全与健康状态标识系统研究

发布时间：2018-04-18 19:05

本文选题：公路隧道 + 标识系统　；参考：《西南交通大学》2014年博士论文

【摘要】：隧道工程往往为高速公路的控制性工程,其在服役期间整体结构的安全状况对公路交通的顺利营运产生重大影响。目前在隧道长期安全状态方面的研究多集中在已经出现病害的隧道工程上,针对隧道长期营运过程中健康状态变化的监控数据不够充分,安全评价方法不统一。因此,针对复杂地质及环境条件的各类长大公路隧道主体结构开展长期监控研究,对隧道结构安全与健康状态进行预测、诊断,具有重要的意义。论文以重庆同期在建的大量隧道为背景,综合采用现场调研、理论分析、数值模拟、模型试验、现场测试等手段,建立了隧道长期健康监控及诊断标识系统,该系统可为同期相近区域高速公路隧道进行健康状况评估和诊断提供客观依据。本文取得了以下研究成果：1、对隧道洞身及附属结构物建成初期和运营期的受力特征进行了系统研究,有效指导了标识系统中监控断面的选取,为隧道安全等级划分及评判标准提供了依据和基础数据支撑；研究了对隧道结构出现不同损伤的位置、损伤程度进行识别的方法。2、根据隧道结构受力、岩石质量指标RQD、地下水赋存情况等多个因素构建了隧道结构安全状态评价指标,采用层次分析法确定了各评判指标的权重,建立了隧道结构安全性评价与预警体系,采用模糊理论、可拓性理论、灰色理论等方法对隧道安全状态进行了分析,实现了按Ⅳ个等级对隧道结构安全与健康状态进行评价和预警。3、针对高速公路隧道结构运营环境和不同监控手段的特点,建立了高速公路隧道长期安全状态监控网络,开发了隧道结构安全智能评价与预警软件,实现了监控数据远程自动采集、传输,接收与评价4、在对重庆地区高速公路隧道工程的场地地质环境、设计施工方法等分析的基础上,选取了摩天岭隧道作为重庆地区高速公路隧道结构安全与健康状态标识系统中的标识工程进行了具体的实施,建立了针对重庆地区高速公路隧道长期健康状态监测的标识系统,为高速公路隧道结构动态安全与健康检测体系提供标尺性的和参照性实测数据和资料,实现以了一条代表性的长大隧道的监测数据对整个区域内所有隧道的健康状况的预测、诊断。
[Abstract]:Tunnel engineering is usually the control engineering of highway. The safety of the whole structure during the period of service has great influence on the smooth operation of highway traffic.At present, the research on the long-term safety state of tunnel is mostly focused on the tunnel engineering where the disease has already appeared. The monitoring data for the change of the health state in the long-term operation of the tunnel are insufficient, and the method of safety evaluation is not uniform.Therefore, it is of great significance to carry out long-term monitoring research on the main structure of all kinds of long road tunnels with complex geological and environmental conditions, to predict and diagnose the safety and health state of tunnel structure.Based on a large number of tunnels under construction in Chongqing in the same period, a tunnel long-term health monitoring and diagnosis marking system is established by means of field investigation, theoretical analysis, numerical simulation, model test, field test and so on.The system can provide objective basis for health assessment and diagnosis of highway tunnels in the same period.This paper has obtained the following research result: 1, has carried on the systematic research to the tunnel hole body and the auxiliary structure initial period and the operation period force characteristic, has effectively guided the selection of the monitoring section in the marking system.It provides the basis and the basic data support for the tunnel safety grade division and the judgment standard, studies the method of identifying the different damage position and the damage degree of the tunnel structure, according to the tunnel structure force,Several factors, such as rock quality index RQD, groundwater occurrence and so on, are constructed to evaluate the safety state of tunnel structure. The weight of each evaluation index is determined by AHP, and the safety evaluation and early warning system of tunnel structure is established.Fuzzy theory, extension theory and grey theory are used to analyze the safe state of tunnel.The safety and health state of tunnel structure is evaluated and early warning. 3. According to the characteristics of operating environment and different monitoring means of highway tunnel structure, the long term safety state monitoring network of expressway tunnel is established.The intelligent evaluation and early warning software for tunnel structure safety is developed, and the remote automatic collection, transmission, receiving and evaluation of monitoring data are realized.Based on the analysis of design and construction methods, the skyscraper tunnel is selected as the marking project in the safety and health status marking system of expressway tunnel structure in Chongqing area.A marking system for monitoring the long-term health status of expressway tunnels in Chongqing area is established, which provides the scale and reference data and data for the dynamic safety and health detection system of expressway tunnel structures.The health condition of all tunnels in the whole region is predicted and diagnosed by a representative long tunnel monitoring data.
【学位授予单位】：西南交通大学
【学位级别】：博士
【学位授予年份】：2014
【分类号】：U456.3

【参考文献】