Establishing a Scour Monitoring

2005 ◽  
Author(s):  
Beatrice E. Hunt
Keyword(s):  
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

scholarly journals A Study on the Development of Scour Monitoring System Using TDR

2018 ◽  
Vol 18 (5) ◽  
pp. 239-245
Author(s):  
Jung-Doung Yu ◽  
Jong-Sub Lee ◽  
Myeong-Ho Bae ◽  
Junghee Park ◽  
Hyung-Koo Yoon
Keyword(s):  
Monitoring System ◽  
Scour Monitoring

scholarly journals Scour Monitoring Development for Two Bridges in Texas

2010 ◽  
Author(s):  
C. Yao ◽  
C. Darby ◽  
S. Hurlebaus ◽  
G. R. Price ◽  
H. Sharma ◽  
...  
Keyword(s):  
Scour Monitoring

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.

scholarly journals Densely distributed and real-time scour hole monitoring using piezoelectric rod sensors

2019 ◽  
Vol 22 (16) ◽  
pp. 3395-3411
Author(s):  
Morgan L Funderburk ◽  
Shieh-Kung Huang ◽  
Chin-Hsiung Loh ◽  
Kenneth J Loh
Keyword(s):  
Monitoring System ◽  
Fundamental Frequency ◽  
Polyvinylidene Fluoride ◽  
Three Dimensional ◽  
Piezoelectric Element ◽  
Direct Calculation ◽  
Thin Strip ◽  
Scour Depth ◽  
Scour Monitoring ◽  
Dry Conditions

This study aims to validate a piezoelectric driven-rod scour monitoring system that can sense changes in scour depth along the entire rod at its instrumented location. The proposed sensor is a polymeric slender rod with a thin strip of polyvinylidene fluoride that runs through its midline. Extraction of the fundamental frequency allows the direct calculation of the exposed length (or scour depth) of the slender rod undergoing fluid flow excitation. First, laboratory validation in dry conditions is presented. Second, hydrodynamic testing of the sensor system in a soil-bed flume is discussed. Each rod was installed using a three-dimensional-printed footing designed for ease of installation and stabilization during testing. The sensors were installed in a layout designed to capture symmetric scour conditions around a scaled pier. In order to analyze the system out of steady-state conditions, water velocity was increased in stages during testing to induce different degrees of scour. As ambient water flow excited the portion of the exposed rods, the embedded piezoelectric element outputted a time-varying voltage signal. Different methods were then employed to extract the fundamental frequency of each rod, and the results were compared. Further testing was also performed to characterize the relationship between frequency outputs and flow velocity, which were previously thought to be independent. In general, the proposed driven-rod scour monitoring system successfully captured changing frequencies under varied flow conditions.

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