Related references
Note: Only part of the references are listed.
Article
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Eugene J. OBrien et al.
Summary: This paper proposes a new method to detect multiple scour locations using wavelet-based analysis. By measuring the accelerations at each support point of a multi-span bridge, the method estimates the scour location through frequency-spatial domain transformation and introduces a damage indicator to differentiate healthy and scoured pier locations.
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(2023)
Review
Engineering, Civil
Wen Xiong et al.
Summary: Hydraulic factors have become the main causes of bridge failures since the 1990s, accounting for about 50% of failures in the authors' database. These failures occur without early warning and have destructive consequences, which are expected to continue due to climate change. This paper provides a comprehensive review of hydraulic bridge failures caused by scour, flood, and floe ices, including historical statistics, failure modes, prediction methods, and current practices. It aims to equip researchers and engineers with the necessary information to understand the mechanisms and address the issues of hydraulic bridge failures.
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Meteorology & Atmospheric Sciences
Ali Khosronejad et al.
Summary: The interaction between flow, sediment transport, and bed topography plays a crucial role in the formation of bedforms and channel migration in meandering rivers. Predicting these interactions is vital for river engineering and geoscience research. Researchers conducted simulations to study the morphodynamics and bed deformation in 42 meandering rivers with different planform shapes. The simulations revealed the formation of scour and deposition patterns near the outer and inner banks and the variation of point bars and scour regions around the meander bends.
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COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING
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Article
Engineering, Mechanical
Konstantinos Agathos et al.
Summary: In this work, parametric reduced order models (pROMs) were developed for cracked shells and applied to crack detection problems. Mesh morphing was used for parameterization of the models with respect to crack location and size, and a clustering approach was adopted to partition the parameter space into sub-domains with efficient local reduced order models. The proposed ROMs were then utilized as forward simulators for identifying crack locations within an inverse problem setting.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
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Article
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Jinzhao Li et al.
Summary: This paper presents a numerical investigation on tsunami-induced scour around bridge piers, showing that the scour depth highly depends on the tsunami period and peak velocity. The study demonstrates that a reliable CFD model can accurately predict the scour development and final depth, offering a practical engineering methodology to estimate tsunami-induced pier scour.
Article
Engineering, Geological
Guochen Zhao et al.
Summary: Selecting spectrum-matched ground motions is a critical problem in seismic analysis and design. The commonly used sum of square errors (SSE) is inadequate in capturing the two-dimensional plane feature of response spectrum. In this study, a new method based on Siamese Convolutional Neural Networks (SCNNs) is proposed. Experimental results show that the proposed method achieves satisfactory training results, with the selected ground motions matching the target spectrum. Compared to existing methods, the proposed method has a smaller standard deviation.
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Article
Computer Science, Interdisciplinary Applications
Matteo Torzoni et al.
Summary: This study proposes a method for real-time damage localization using a Siamese convolutional neural network. By learning the mapping of vibration measurements, the method can identify the damage locations in structural systems without the need for predefined target classes and decision boundaries.
COMPUTERS & STRUCTURES
(2022)
Article
Engineering, Civil
Wen Xiong et al.
Summary: A bridge scour identification method based on time-frequency analysis and probabilistic trend change detection is proposed in this paper. The method reveals the trend change induced by scour by considering the random variations in the natural frequencies caused by interference. It is effective in identifying scour and does not require underwater devices and operations, making it convenient to integrate into a bridge structural health monitoring system.
JOURNAL OF BRIDGE ENGINEERING
(2022)
Article
Engineering, Mechanical
Xudong Jian et al.
Summary: This study conducts a 3D simulation of vehicle-bridge interaction and proposes a novel frequency-domain method to identify bridge natural frequencies. The proposed method has the potential to fast inspect large quantities of bridges, making it valuable for indirect bridge structural identification.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2022)
Article
Engineering, Marine
Zhou Huang et al.
Summary: This study proposes a novel physics-guided data-driven method that incorporates physical perception into a neural network model for improved structural damage identification.
Article
Computer Science, Interdisciplinary Applications
Luca Rosafalco et al.
Summary: This study proposes a simulation-based classification strategy within a structural health monitoring framework to achieve online damage localization by combining parametric Model Order Reduction techniques and Fully Convolutional Networks. The trained classifier is able to accurately map vibrational recordings to the actual damage state, providing information on damage existence and location. The strategy has been validated through two case studies with significant speed improvements and high accuracy achieved after training.
COMPUTERS & STRUCTURES
(2021)
Article
Engineering, Multidisciplinary
Muhammad Arslan Khan et al.
Summary: This article presents a new approach using modal analysis to detect bridge scour at shallow pad foundations and extract modal information. Testing on a numerical model showed that using modal analysis can help locate scour damage on bridges.
STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL
(2021)
Article
Engineering, Mechanical
Kun Feng et al.
Summary: This paper presents a k-Nearest Neighbours (kNN) algorithm for locating and quantifying bridge damage based on the time-varying forced frequencies due to a moving truck. The algorithm utilizes eigenvalue analysis and a vast sample of patterns generated to determine the location and severity of the damage. Field measurements are simulated using dynamic transient analysis for theoretical testing purposes.
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