Active Scour Monitoring using Ultrasonic Time Domain Reflectometry of Buried Slender Sensors

Local scour is a growing cause of bridge failure in the United States and around the world. In the next century, the effects of climate changes will make more bridges susceptible to scour failure more than ever before. This study aims to harness the spatially continuous monitoring capabilities of ultrasonic time-domain reflectometry to detect a soil interface for the purposes of scour monitoring. In this study, a long, slender plate is coupled with two flexible piezoelectric devices that propagate Lamb waves along the length of the plate to form the scour sensor. The sensor was tested for sensitivity to external pressure using metal weights, and was able to detect the position of the pressure up at a length of up to ~ 20 feet. The sensor was tested under simulated scour conditions, being buried in sand at various depths. The results show that the Lamb wave scour sensor is capable of reliably detecting a soil interface at 1 ft intervals. The scour sensor was also able to detect uncompacted soil interfaces, which is important considering the issue of scour hole refill following an extreme event.

Advances in Vibration-Based Scour Monitoring for Bridge Foundations

Scouring around bridge foundations is one of the main factors causing structural damage of bridges. Traditional scour monitoring techniques generally require a large number of sensing devices set up underwater, which is difficult to be implemented for actual bridges. To address this issue, scour monitoring technology based on structural vibrations is paid attention gradually, because this technique can work well with less equipment and can be free from the influence of the submerged environment. This study presents a systematic summary and analysis of the selection of scour indicators, sensor deployment principles and other related research involved in scour monitoring technology based on structural vibration. On this basis, the research status of the bridge scour monitoring method based on vehicle excitation is further summarized. Finally, the prospects for the application of vibration-based bridge foundation scour monitoring technology are presented, discussing the technologies that are currently missing and urgently needed for this monitoring method and the challenges faced today.

Machine Learning Solutions for Bridge Scour Forecast Based on Monitoring Data

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.

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

<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>