Open Access
ARTICLE
Yueshun Chen1,2,*, Yupeng Zhou1, Cao Yin3
Structural Durability & Health Monitoring, DOI:10.32604/sdhm.2024.057005
（This article belongs to the Special Issue: Sensing Data Based Structural Health Monitoring in Engineering)
Abstract Computed tomography (CT) can inspect the internal structure of concrete with high resolution, but improving the accuracy of measurements remains a key challenge due to the reliance on complex image processing and significant manual intervention. This study aims to optimize CT scanning parameters to enhance the accuracy of measuring crack widths and rebar volumes in reinforced concrete. Nine sets of specimens, each with varying rebar diameters and concrete cover thicknesses, were scanned before and after corrosion using an Optima CT scanner, followed by three-dimensional reconstructions using Avizo software. The effects of threshold values and “Erosion” More >
Open Access
REVIEW
Chengquan Wang1,2, Lei Xu3, Xinquan Wang1, Yun Zou3,*, Kangyu Wang4, Boyan Ping5, Xiao Li1
Structural Durability & Health Monitoring, DOI:10.32604/sdhm.2024.055096
（This article belongs to the Special Issue: Advancements in Smart Materials Dynamic Analysis for Novel Approaches of Structural Control and Healthy Monitoring)
Abstract Kinked rebar is a special type of steel material, which is installed in beam column nodes and frame beams. It effectively enhances the blast resilience, seismic collapse resistance, and progressive collapse resistance of reinforced concrete (RC) structures without imposing substantial cost burdens, thereby emerging as a focal point of recent research endeavors. On the basis of explaining the working principle of kinked rebars, this paper reviews the research status of kinked rebars at home and abroad from three core domains: the tensile mechanical properties of kinked rebars, beam column nodes with kinked rebars, and concrete… More >
Open Access
ARTICLE
Zhao-Jun Zhang1, Jing-Shui Zhen1, Bo-Cheng Li1, De-Cheng Cai1, Yang-Yang Du1, Wen-Wei Wang2,*
Structural Durability & Health Monitoring, DOI:10.32604/sdhm.2024.054671
（This article belongs to the Special Issue: Sensing Data Based Structural Health Monitoring in Engineering)
Abstract To mitigate the challenges in managing the damage level of reinforced concrete (RC) pier columns subjected to cyclic reverse loading, this study conducted a series of cyclic reverse tests on RC pier columns. By analyzing the outcomes of destructive testing on various specimens and fine-tuning the results with the aid of the IMK (Ibarra Medina Krawinkler) recovery model, the energy dissipation capacity coefficient of the pier columns were able to be determined. Furthermore, utilizing the calibrated damage model parameters, the damage index for each specimen were calculated. Based on the obtained damage levels, three distinct More >
Open Access
ARTICLE
Ruikun Xu1, Jiu Li1, Wenjie Li1, Wei Zhang2,*
Structural Durability & Health Monitoring, DOI:10.32604/sdhm.2024.057513
Abstract This study investigates the bond performance at the interfacial region shared by Ultra-High Performance Concrete (UHPC) and steel tubes through push-out tests. This study examines how changes in steel fiber volumetric ratio and thickness of steel tube influence the bond strength characteristics. The results show that as the enhancement of the steel tube wall thickness, the ultimate bond strength at the interface improves significantly, whereas the initial bond strength exhibits only slight variations. The influence of steel fiber volumetric ratio presents a nonlinear trend, with initial bond strength decreasing at low fiber content and increasing More >
Open Access
ARTICLE
Menghui Hao1, Shanshan Zhou1, Yongchao Han1, Zhanwei Zhu1, Qiang Yang2, Panxu Sun2,*, Jiajun Fan2
Structural Durability & Health Monitoring, DOI:10.32604/sdhm.2024.056250
（This article belongs to the Special Issue: Advanced Data Mining in Bridge Structural Health Monitoring)
Abstract As an evaluation index, the natural frequency has the advantages of easy acquisition and quantitative evaluation. In this paper, the natural frequency is used to evaluate the performance of external cable reinforced bridges. Numerical examples show that compared with the natural frequencies of first-order modes, the natural frequencies of higher-order modes are more sensitive and can reflect the damage situation and external cable reinforcement effect of T-beam bridges. For damaged bridges, as the damage to the T-beam increases, the natural frequency value of the bridge gradually decreases. When the degree of local damage to the… More >
Open Access
ARTICLE
Zhi-Xiang Wei1, Wen-Wei Wang2,*, Yan-Jie Xue3, Wu-Tong Zhang2, Qiu-Di Huang2
Structural Durability & Health Monitoring, DOI:10.32604/sdhm.2024.054559
（This article belongs to the Special Issue: Advancements in Smart Materials Dynamic Analysis for Novel Approaches of Structural Control and Healthy Monitoring)
Abstract To investigate the performance of utilizing the shape memory effect of SMA (Shape Memory Alloy) wire to generate recovery stress, this paper performed single heating recovery stress tests and reciprocating heating-cooling
recovery stress tests on SMA wire under varying initial strain conditions. The effects of various strains and different energized heating methods on the recovery stress of SMA wires were explored in the single heating tests.
The SMA wire was strained from 2% to 8% initially, and two distinct heating approaches were employed: one
using a large current interval for rapid heating and one using… More >
Open Access
ARTICLE
Yao Jin1, Yuan Ren1, Chong-Yuan Guo2, Chong Li3, Zhao-Yuan Guo1,4, Xiang Xu1,*
Structural Durability & Health Monitoring, DOI:10.32604/sdhm.2024.055265
（This article belongs to the Special Issue: Advanced Data Mining in Bridge Structural Health Monitoring)
Abstract To improve the accuracy of thermal response estimation and overcome the limitations of the linear regression model and Artificial Neural Network (ANN) model, this study introduces a deep learning estimation method specifically based on the Long Short-Term Memory (LSTM) network, to predict temperature-induced girder end displacements of the Dasha Waterway Bridge, a suspension bridge in China. First, to enhance data quality and select target sensors, preprocessing based on the sigma rule and nearest neighbor interpolation is applied to the raw data. Furthermore, to eliminate the high-frequency components from the displacement signal, the wavelet transform is… More >
Open Access
ARTICLE
Yi Wang1, Bing Wang2, Changwen Li2, Feng Zheng1, Yong Liu2, Shaohua He3,*
Structural Durability & Health Monitoring, DOI:10.32604/sdhm.2024.054761
（This article belongs to the Special Issue: Health Monitoring and Rapid Evaluation of Infrastructures)
Abstract Complex bridge structures designed and constructed by humans often necessitate extensive on-site execution, which carries inherent risks. Consequently, a variety of engineering practices are employed to monitor bridge construction. This paper presents a case study of a large-span prestressed concrete (PC) variable-section continuous girder bridge in China, proposing a feedback system for construction monitoring and establishing a finite element (FE) analysis model for the entire bridge. The alignment of the completed bridge adheres to the initial design expectations, with maximum displacement and pre-arch differences from the ideal state measuring 6.39 and 17.7 mm, respectively, which More >
Open Access
ARTICLE
Yongfeng Tai1, Xingyu Yan2, Xiangyi Geng3, Lin Mu4, Mingshun Jiang2, Faye Zhang2,*
Structural Durability & Health Monitoring, DOI:10.32604/sdhm.2024.053998
（This article belongs to the Special Issue: Health Monitoring and Rapid Evaluation of Infrastructures)
Abstract The remaining useful life prediction of rolling bearing is vital in safety and reliability guarantee. In engineering scenarios, only a small amount of bearing performance degradation data can be obtained through accelerated life testing. In the absence of lifetime data, the hidden long-term correlation between performance degradation data is challenging to mine effectively, which is the main factor that restricts the prediction precision and engineering application of the residual life prediction method. To address this problem, a novel method based on the multi-layer perception neural network and bidirectional long short-term memory network is proposed. Firstly,… More >
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