Early warning decision support system for the management of underwater scour risk for road and railway bridges

公路铁路桥梁水下冲刷风险管理预警决策支持系统

• 批准号: NE/R009090/1
• 负责人: Daniele Zonta
• 金额: $ 12.3万
• 依托单位: University of Strathclyde
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2017
• 资助国家: 英国
• 起止时间: 2017 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=NE%2FR009090%2F1
• 关键词: Early; warning; decision; support; system

PARTNERS- Transport Scotland (TS), Network Rail (NR), SEPA, Arup.CHALLENGE- Flood induced scour is by far the leading cause of bridge failures, resulting in loss of lives, traffic disruption and significant economic losses. TS is responsible for 1,567 bridges, 8% of these currently classified as needing scour protection measures and costing £2m per annum in routine inspections. Similarly, NR Scotland Route includes 1,750 structures susceptible to scour requiring an annual inspection spend of £0.4m. Inspections are expensive and time consuming, and often the information collected is qualitative and subjective.OBJECTIVE- To develop a prototype of a Decision Support System (DSS) for scour risk management for NR's and TS's bridges, which enhances users' safety, while minimizing traffic disruptions and transport agencies' operational cost. The system will estimate, and continuously update, the present and future scour failure risk using (i) real-time information from monitoring of scour depth (ii) rainfall forecast and (iii) river flow characteristics.INNOVATION- Sensor and communication technologies offer the possibility to assess in real time the scour depth at critical bridge locations; yet monitoring an entire infrastructure network is not economically sustainable. A way to overcome this limitation is to install monitoring systems on a limited number of critical locations and use a probabilistic approach to extend this information to the entire asset. In the occurrence of a flood, monitoring observations are used to give the real-time best estimate of bridge failure probability. The sensing technology proposed is a prototype of smart probe with integrated electromagnetic sensors designed to detect changes in the dielectric permittivity of the surrounding bridge foundation, designed and calibrated to detect scour and sediment deposition in various soil types.KEY ACTIVITIES- Collect data from past scour inspection on NR's and TS's inspection records; define formal vulnerability model based on the fragility curve method.- Define flood hazard models based on SEPA rainfall and river flow datasets, and accounting for CCRA climate change prediction.- Model correlation in hazard and vulnerability among different bridges, using Bayesian networks.- Collect data from TS pilot scour monitoring system.- Implement algorithms for updating fragility curves and state variables of the Bayesian network based on real-time information from monitoring system.- Develop a prototype DSS that continuously updates bridge failure risk using real-time information from pilot monitoring system and rainfall forecast.- Produce an exploitation plan.DELIVERABLES- The BRIDGE VULNERABILITY MODEL, the FLOOD HAZARD MODEL and the SCOUR HAZARD MODEL will provide NR and TS with quantitative up-to-date information on the probability of scour failure of each bridge. Before a flood event, this will allow prioritising inspections according to risk and, when necessary, to introduce precautionary bridge closures or traffic management. This framework can be equally used to simulate the impact of potential extreme weather events on travel agencies' network, and to plan in advance appropriate emergency procedures and countermeasures. The TS PILOT SCOUR MONITORING SYSTEM will provide validation to a new technology for direct assessment of underwater scour, which can complement traditional NR's and TS's river-bank visual assessments. The DECISION SUPPORT SYSTEM will provide information for long term prediction of future scour risk to drive strategic maintenance, repair and rehabilitation actions. The same DSS can be used as an early warning system that automatically takes action when the risk estimated exceeds a given threshold. The EXPLOITATION PLAN will set a roadmap to transfer the new technology and knowledge to other infrastructure systems and geographical areas.DURATION- 12 monthsCOST- £94,763.02

合作伙伴 - 苏格兰运输（TS），网络铁路（NR），SEPA，Arup.Challenge-洪水引起的冲浪是迄今为止桥梁故障的主要原因，导致生命损失，交通中断和重大的经济损失。 TS负责1,567座桥梁，其中8％被归类为需要进行冲洗保护措施，并且每年的常规检查费用为2000万英镑。同样，NR苏格兰的路线包括1,750个结构，易于搜寻，要求年度检查支出为440万英镑。检查是昂贵且耗时的，通常收集的信息是定性和主观的，可以为NR和TS的桥梁开发决策支持系统（DSS）的原型，以增强用户的安全性，同时最大程度地减少交通中断和运输机构的运营成本。该系统将使用（i）通过（i）监视冲洗深度（II）降雨预测和（iii）河流流量特征的实时信息的当前和未来冲突故障风险进行估计，并不断更新。传感器和通信技术可提供实时评估关键桥梁位置的冲刷深度；然而，监视整个基础设施网络在经济上并不可持续。克服此限制的一种方法是在有限数量的关键位置安装监视系统，并使用概率方法将此信息扩展到整个资产。在发生洪水时，使用监测观察结果可为桥梁故障概率提供实时最佳估计。提出的灵敏度技术是智能探针的原型，其集成电子传感器旨在检测周围桥基础基础的延伸介电常数的变化，该桥梁基础的延伸介电常数是设计和校准的，以检测各种土壤类型中的Scour和沉积物沉积。基于脆弱性曲线方法定义形式的漏洞模型。-定义基于SEPA降雨和河流流量数据集的洪水危险模型，并考虑CCRA气候变化预测的核算。-使用贝叶斯的危险和脆弱性的模型相关性，使用贝叶斯的危险性和脆弱性，使用贝叶斯的贝叶斯网络中的贝叶斯网络。从监视系统开始。-开发一个原型DSS，该原型DSS继续使用试点监控系统和降雨预测的实时信息来更新桥梁故障风险。-生产剥削计划。剥削计划 - 拆卸漏洞模型，洪水危害模型和SCOUR危险模型将为NR和TS提供有关每种桥梁失败的概率的NR和TS，并为NR和TS提供量的nr和TS。在发生洪水事件之前，这将允许根据风险进行优先检查，并在必要时引入预防性的桥梁关闭或交通管理。该框架可以同样用于模拟潜在的极端天气事件对旅行社网络的影响，并提前计划适当的紧急程序和对策。 TS试点冲刷监测系统将为新技术提供直接评估水下搜索的验证，该技术可以补充传统的NR和TS的河岸视觉评估。决策支持系统将提供信息，以长期预测未来的冲刷风险，以推动战略维护，维修和康复措施。相同的DSS可以用作预警系统，当估计的风险超过给定阈值时，它会自动采取行动。剥削计划将设定路线图，将新技术和知识转移到其他基础设施系统和地理区域。Duration-12个月cost-£94,763.02

项目成果

A Decision Support System for scour management of road and railway bridges based on Bayesian Networks

基于贝叶斯网络的公路铁路桥梁冲刷管理决策支持系统

• 发表时间: 2019
• 作者: Maroni A

Using Bayesian networks for the assessment of underwater scour for road and railway bridges

• DOI: 10.1177/1475921720956579
• 发表时间: 2018-05
• 期刊: Structural Health Monitoring
• 作者: Andrea Maroni;E. Tubaldi;D. Val;H. McDonald;D. Zonta

A Bayesian network approach to assess underwater scour around bridge foundations

用于评估桥梁基础周围水下冲刷的贝叶斯网络方法

• 发表时间: 2018
• 作者: Maroni A

Managing bridge scour risk using Structural Health Monitoring

使用结构健康监测管理桥梁冲刷风险

• 发表时间: 2019
• 作者: Maroni A

SHM-based Decision Support System for bridge scour management

基于SHM的桥梁冲刷管理决策支持系统

• 发表时间: 2019
• 作者: Maroni A