Real time bridge scour monitoring with magneto-inductive field coupling

2013 ◽  
Author(s):  
Andriy Radchenko ◽  
David Pommerenke ◽  
Genda Chen ◽  
Pratik Maheshwari ◽  
Satyajeet Shinde ◽  
...  
Keyword(s):  
Real Time ◽  
Bridge Scour ◽  
Field Coupling ◽  
Scour Monitoring

scholarly journals Machine Learning Solutions for Bridge Scour Forecast Based on Monitoring Data

2021 ◽  
pp. 036119812110126
Author(s):  
Negin Yousefpour ◽  
Steve Downie ◽  
Steve Walker ◽  
Nathan Perkins ◽  
Hristo Dikanski
Keyword(s):  
Machine Learning ◽  
Real Time ◽  
Monitoring Data ◽  
Sensor Data ◽  
Monitoring Systems ◽  
Bridge Scour ◽  
Scour Monitoring ◽  
Novel Approach ◽  
Bayesian Inference Method ◽  
Water Level Variations

Bridge scour is a challenge throughout the U.S.A. and other countries. Despite the scale of the issue, there is still a substantial lack of robust methods for scour prediction to support reliable, risk-based management and decision making. Throughout the past decade, the use of real-time scour monitoring systems has gained increasing interest among state departments of transportation across the U.S.A. This paper introduces three distinct methodologies for scour prediction using advanced artificial intelligence (AI)/machine learning (ML) techniques based on real-time scour monitoring data. Scour monitoring data included the riverbed and river stage elevation time series at bridge piers gathered from various sources. Deep learning algorithms showed promising in prediction of bed elevation and water level variations as early as a week in advance. Ensemble neural networks proved successful in the predicting the maximum upcoming scour depth, using the observed sensor data at the onset of a scour episode, and based on bridge pier, flow and riverbed characteristics. In addition, two of the common empirical scour models were calibrated based on the observed sensor data using the Bayesian inference method, showing significant improvement in prediction accuracy. Overall, this paper introduces a novel approach for scour risk management by integrating emerging AI/ML algorithms with real-time monitoring systems for early scour forecast.

scholarly journals Web-based real time bridge scour monitoring system for disaster management

2014 ◽  
Vol 9 (1) ◽  
pp. 17-25 ◽  
Author(s):  
Mirosław Skibniewski ◽  
Hui-Ping Tserng ◽  
Shen-Haw Ju ◽  
Chung-Wei Feng ◽  
Chih-Ting Lin ◽  
...  
Keyword(s):  
Real Time ◽  
Monitoring System ◽  
Disaster Management ◽  
Bridge Scour ◽  
Web Based ◽  
Scour Monitoring

Monitoring systems for the assessment of water infrastructure hazards due to extreme climatic conditions

2020 ◽  
Author(s):  
Manousos Valyrakis ◽  
Panagiotis Michalis ◽  
Yi Xu ◽  
Pablo Gaston Latessa
Keyword(s):  
Real Time ◽  
Climatic Conditions ◽  
Bridge Scour ◽  
Civil Infrastructure ◽  
Water Infrastructure ◽  
Monitoring Method ◽  
Infrastructure Systems ◽  
International Conference ◽  
Scour Monitoring ◽  
Climatic Hazards

<p>Ageing infrastructure alongside with extreme climatic conditions pose a major threat for the sustainability of civil infrastructure systems with significant societal and economic impacts [1]. A main issue also arises from the fact that past and existing methods that incorporate the risk of climatic hazards into infrastructure design and assessment methods are based on historical records [2].</p><p>Major flood incidents are the factor of evolving geomorphological processes, which cause a drastic reduction in the safe capacity of structures (e.g. bridges, dams). Many efforts focused on the development and application of monitoring techniques to provide real-time assessment of geomorphological conditions around structural elements [1, 3, 4]. However, the current qualitative visual inspection practice cannot provide reliable assessment of geomorphological effects at bridges and other water infrastructure.</p><p>This work presents an analysis of the useful experience and lessons learnt from past monitoring efforts applied to assess geomorphological conditions at bridges and other types of water infrastructure. The main advantages and limitations of each monitoring method is summarized and compared, alongside with the key issues behind the failure of existing instrumentation to provide a solution. Finally, future directions on scour monitoring is presented focusing on latest advances in soil and remote sensing methods to provide modern and reliable alternatives for real-time monitoring and prediction [5, 6] of climatic hazards of infrastructure at risk.</p><p> </p><p>References</p><p>[1] Michalis, P., Konstantinidis, F. and Valyrakis, M. (2019) The road towards Civil Infrastructure 4.0 for proactive asset management of critical infrastructure systems. Proceedings of the 2nd International Conference on Natural Hazards & Infrastructure (ICONHIC2019), Chania, Greece, 23–26 June 2019.</p><p>[2] Pytharouli, S., Michalis, P. and Raftopoulos, S. (2019) From Theory to Field Evidence: Observations on the Evolution of the Settlements of an Earthfill Dam, over Long Time Scales. Infrastructures 2019, 4, 65.</p><p>[3] Koursari, E., Wallace, S., Valyrakis, M. and Michalis, P. (2019). The need for real time and robust sensing of infrastructure risk due to extreme hydrologic events, 2019 UK/ China Emerging Technologies (UCET), Glasgow, United Kingdom, 2019, pp. 1-3. doi: 10.1109/UCET.2019.8881865</p><p>[4] Michalis, P., Saafi, M. and M.D. Judd. (2012) Integrated Wireless Sensing Technology for Surveillance and Monitoring of Bridge Scour. Proceedings of the 6th International Conference on Scour and Erosion, France, Paris, pp. 395-402.</p><p>[5] Valyrakis, M., Diplas, P., and Dancey, C.L. (2011) Prediction of coarse particle movement with adaptive neuro-fuzzy inference systems, Hydrological Processes, 25 (22). pp. 3513-3524. ISSN 0885-6087, doi:10.1002/hyp.8228.</p><p>[6] Valyrakis, M., Michalis, P. and Zhang, H. (2015) A new system for bridge scour monitoring and prediction. Proceedings of the 36th IAHR World Congress, The Hague, the Netherlands, pp. 1-4.</p>

A New Structural Health Monitoring System to Assess Bridge Scour

2021 ◽  
Author(s):  
Panagiotis Michalis ◽  
Manousos Valyrakis ◽  
Elissavet Vintzilaiou
Keyword(s):  
Structural Health Monitoring ◽  
Real Time ◽  
Health Monitoring ◽  
Early Warning ◽  
Early Warning System ◽  
Warning System ◽  
Bridge Scour ◽  
Flood Hazards ◽  
Health Monitoring System ◽  
Scour Monitoring

<p>Scour action still remains the leading cause of numerous bridge failures each year and is considered one of the most destructive flood related hazards occurring around underwater foundation elements [1]. Undetected erosion related processes are therefore the cause of major disruptions to the transportation network with significant socio-economic losses and disruption to users, maintainers and asset owners. Recent cases of bridge failures due to extreme climatic events have highlighted the need for a reliable scour monitoring and early warning system to assess flood and geo-related hazards in real-time, providing advanced key info for repair and maintenance actions. Despite the past efforts to provide such a system for scour assessment, most of these instruments have not managed to realise a solution for scour monitoring due to technical and cost issues. The existing practices to assess, manage and maintain transportation assets are mainly based on visual inspection procedure which is also considered to be insufficient [2]. As a result there currently exists a gap in the knowledge and understanding of scour mechanism during flood incidents.</p><p>This study presents the architecture of ‘Climatic Hazard Monitoring and Bridge Scour Early Warning System’ (CliHaMoS) project, which is expected to significantly assist towards the optimisation of bridge performance against scour issues with a real-time data driven approach. CliHaMoS platform comprises of a new structural health monitoring system based on a novel bio-inspired sensing system aiming to deliver key information under different hydrodynamic events for real-time and forecasted assessment of flood hazards at bridges. The sensing solution is coupled by an early warning system, with advanced interoperability characteristics, to provide a holistic interactive platform and ensure that risks associated with flood hazards are properly and timely communicated to end-users. The obtained information is expected to enable stakeholders to plan adaptation strategies and proactively manage and maintain transportation infrastructure.</p><p>[1] Michalis, P., Saafi, M., and Judd. M. (2013) Capacitive sensors for offshore scour monitoring. Proceedings of the ICE – Energy, 166 (4), pp. 189-197</p><p>[2] Michalis, P., Saafi, M. and Judd, M. (2012) Wireless sensor networks for surveillance and monitoring of bridge scour. Proceedings of the XI International Conference Protection and Restoration of the Environment - PRE XI. Thessaloniki, Greece, pp. 1345–1354.</p><p><em>ACKNOWLEDGMENT:</em></p><p>This research is co-financed by Greece and the European Union (European Social FundESF) through the Operational Programme «Human Resources Development, Education and 4 Lifelong Learning» in the context of the project “Reinforcement of Postdoctoral Researchers - 2nd Cycle” (MIS-5033021), implemented by the State Scholarships Foundation (ΙΚΥ).</p>

scholarly journals Laboratory Evaluation of Time-Domain Reflectometry for Bridge Scour Measurement: Comparison with the Ultrasonic Method

2010 ◽  
Vol 2010 ◽  
pp. 1-12 ◽  
Author(s):  
Xinbao Yu ◽  
Xiong Yu
Keyword(s):  
Real Time ◽  
Time Domain ◽  
Ultrasonic Method ◽  
Time Domain Reflectometry ◽  
Laboratory Evaluation ◽  
Bridge Scour ◽  
Analysis Algorithm ◽  
Ultrasonic Methods ◽  
Scour Monitoring ◽  
The Time Domain

Bridge scour is a major factor causing instability of bridges crossing waterways. Excessive scour contributes to their high construction and maintenance costs. Design of innovative scour-monitoring instrumentation is essential to ensure the safety of scour-critical bridges. The ability of real-time surveillance is important since the most severe scour typically happens near the peak flood discharge. A new scour-monitoring instrument based on the Time Domain Reflectometry (TDR) principle has been developed to provide real-time monitoring of scour evolution. A framework based on dielectric mixing model has been developed, which can be easily incorporated into an automatic analysis algorithm. This paper introduces a comparative study of TDR method and ultrasonic method for scour measurements. The results indicate that both TDR and ultrasonic methods can accurately estimate scour depth. TDR method, with the developed analysis algorithm, yields information on the river properties such as the electrical conductivity of river water and the density of sediments. TDR methods are also found less influenced by turbulence and air bubbles, both likely to occur during flood events.

A Preliminary Assessment of Low-Cost Bridge Scour Monitoring Methods and Tools

2021 ◽  
Author(s):  
Eftychia Koursari ◽  
Stuart Wallace ◽  
Panagiotis Michalis ◽  
Manousos Valyrakis ◽  
Scott Paton
Keyword(s):  
Climate Change ◽  
Low Cost ◽  
Scour Depth ◽  
Bridge Scour ◽  
Monitoring Methods ◽  
Preliminary Assessment ◽  
Medium Scale ◽  
Scour Monitoring ◽  
Surface Shaping ◽  
Scale Structures

<p>Scour is a major cause of bridge collapse worldwide.</p><p>Climate change has resulted in flood events increasing both in frequency and in magnitude. Climate change, together with the current uncertainty about maximum scour depth around structures, make scour and other hydraulic actions some of the most important challenges for engineering going forward.</p><p>This study offers a preliminary assessment of bridge scour monitoring methods considering scour as a dynamical earth surface shaping process, and discusses how these methods can be used to improve predictive models for bridge scour depth.</p><p>Current methods used to monitor scour are mostly reactive. A vast amount of research has been carried out, aiming towards the implementation of various approaches to assist in the monitoring of scour; however, most methods used are either still reactive, or extremely costly and therefore not practical to be used for small to medium scale structures. This study aims in addressing major challenges faced by establishing a new, innovative framework for the monitoring of scour, while considering relevant approaches in literature. It discusses the development of an innovative, sustainable and low-cost framework, that can be used for small to medium scale structures. This will ensure a proactive response in the event of catastrophic scour occurring, safeguarding infrastructure and the travelling public.</p>

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

2020 ◽  
pp. 147592172095657
Author(s):  
Andrea Maroni ◽  
Enrico Tubaldi ◽  
Dimitri V Val ◽  
Hazel McDonald ◽  
Daniele Zonta
Keyword(s):  
Bayesian Networks ◽  
Bayesian Network ◽  
River Flow ◽  
Flow Characteristics ◽  
The United States ◽  
Monitoring Systems ◽  
Scour Depth ◽  
Bridge Scour ◽  
Railway Bridges ◽  
Scour Monitoring

Flood-induced scour is among the most common external causes of bridge failures worldwide. In the United States, scour is the cause of 22 bridges fails every year, whereas in the UK, it contributed significantly to the 138 collapses of bridges in the last century. Scour assessments are currently based on visual inspections, which are time-consuming and expensive. Nowadays, 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 feasible. A way to overcome this limitation is to instal scour monitoring systems at critical bridge locations, and then extend the piece of information gained to the other assets exploiting the correlations present in the system. In this article, we propose a scour hazard model for road and railway bridge scour management that utilises information from a limited number of scour monitoring systems to achieve a more confined estimate of the scour risk for a bridge network. A Bayesian network is used to describe the conditional dependencies among the involved random variables and to update the scour depth distribution using data from monitoring of scour and river flow characteristics. This study constitutes the first application of Bayesian networks to bridge scour risk assessment. The proposed probabilistic framework is applied to a case study consisting of several road bridges in Scotland. The bridges cross the same river, and only one of them is instrumented with a scour monitoring system. It is demonstrated how the Bayesian network approach allows to significantly reduce the uncertainty in the scour depth at unmonitored bridges.

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