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

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:
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
项目状态:
已结题
起止时间:
2017 至 --

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中文摘要
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英文摘要
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
期刊论文(8)
专著(0)
科研奖励(0)
会议论文
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
DOI: --
发表时间: 2019
期刊:
影响因子: --
作者: [Maroni A]
通讯作者: Maroni A
DOI: 10.1177/1475921720956579
发表时间: 2018-05
期刊: Structural Health Monitoring
影响因子: --
作者: [Andrea Maroni;E. Tubaldi;D. Val;H. McDonald;D. Zonta]
通讯作者: 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
DOI: --
发表时间: 2018
期刊:
影响因子: --
作者: [Maroni A]
通讯作者: 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
DOI: --
发表时间: 2019
期刊:
影响因子: --
作者: [Maroni A]
通讯作者: Maroni A
海外基金