{"title":"Partial-Model-Based Damage Identification of Long-Span Steel Truss Bridge Based on Stiffness Separation Method","authors":"Feng Xiao, Yuxue Mao, Geng Tian, Gang S. Chen","doi":"10.1155/2024/5530300","DOIUrl":"https://doi.org/10.1155/2024/5530300","url":null,"abstract":"<div>\u0000 <p>Damage detection in bridge structures has always been challenging, particularly for long-span bridges with complex structural forms. In this study, a partial-model-based damage detection method was proposed for the damage identification of long-span steel truss bridges. The proposed method employs partial models to estimate the parameters using the stiffness separation method. This approach obviates the need to construct complete stiffness information for the structure. In contrast, it depends solely on the arrangement of the structural members and material information in the recognized area. This technique can effectively circumvent the construction of an overall structural model and reduce the complexity of damage identification in large structures. A full-scale long-span steel truss bridge in service was used to illustrate the feasibility of the proposed method. The locations of the three partial models were considered in the model analysis, and the parameter estimation efficiency of the Nelder–Mead simplex and quasi-Newton algorithms were compared.</p>\u0000 </div>","PeriodicalId":49471,"journal":{"name":"Structural Control & Health Monitoring","volume":null,"pages":null},"PeriodicalIF":4.6,"publicationDate":"2024-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/2024/5530300","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142100296","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Flutter Control Mechanism of Dual Active Aerodynamic Flaps with Adjustable Mounting Distance for a Bridge Girder","authors":"Zilong Wang, Genshen Fang, Ke Li, Lin Zhao","doi":"10.1155/2024/5259682","DOIUrl":"https://doi.org/10.1155/2024/5259682","url":null,"abstract":"<div>\u0000 <p>Active flap is an advanced aerodynamic measure that can effectively increase the flutter performance of flexible bridges, but its control mechanism is still confusing due to the complex phenomenon of aerodynamic interference between the deck and flaps. This study proposes an assessment method to clarify the flutter control mechanism of the deck-flap system by the computational fluid dynamics (CFD) method and quantifies the contribution of the aerodynamic damping from the active flaps. It is found that the composition of active flap to the improvement of flutter performance can be divided into torque effect and interference effect. Also, the torque effect of the flaps mainly provides equivalent positive aerodynamic damping ratio under effective control parameters, but the interference effects with the deck and two flaps are not the same, and the mutual interference effect between the two flaps is very weak. For the purpose of investigating the aerodynamic interference influence between the girder and flaps, the research further discussed the impact of the distance between the deck mounting position and the bridge girder on the system flutter performance. As the distance increases, the flutter performance of the system gradually improves. Also, the torque effect of the leading and trailing flaps will increase with distance. However, the interference effects of the flaps on both sides show different rules. In total aerodynamic damping ratio of the deck-flap system, the torque effect accounts for about 70% and interference effect accounts for 30%. As the distance increases, the torque effect gradually becomes stronger and the interference effect gradually weakens.</p>\u0000 </div>","PeriodicalId":49471,"journal":{"name":"Structural Control & Health Monitoring","volume":null,"pages":null},"PeriodicalIF":4.6,"publicationDate":"2024-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/2024/5259682","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142100218","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Juan D. Aux, Bryan Castillo, Carlos Riascos, Johannio Marulanda, Peter Thomson
{"title":"Evaluation of Vertical Human-Structure Interaction on a Pedestrian Bridge Using a Predictive Human Gait Model","authors":"Juan D. Aux, Bryan Castillo, Carlos Riascos, Johannio Marulanda, Peter Thomson","doi":"10.1155/2024/8880701","DOIUrl":"https://doi.org/10.1155/2024/8880701","url":null,"abstract":"<div>\u0000 <p>Many modern pedestrian bridges exhibit flexibility and susceptibility to vibrations due to the use of lightweight and high-strength materials, which can cause discomfort for pedestrians and affect their serviceability. Although gait biomechanics have been extensively studied and optimisation techniques for gait prediction on rigid surfaces have been previously employed, there is a paucity of studies investigating the effects of human-structure interaction on pedestrian crossings over flexible structures. In this study, inverse dynamics and optimisation techniques were employed to predict human gait on a flexible structure in the sagittal plane. Gait was formulated as an optimal motor task subject to multiple constraints, with the performance criterion being the minimization of mechanical energy expenditure throughout a complete gait cycle. Segmental movements, pedestrian-applied forces, and bridge vibrations were predicted based on parameters describing gait (such as gait speed, gait frequency, and double support duration), as well as physical and dynamic parameters characterizing the pedestrian bridge (including natural frequency, damping coefficient, and bridge length).</p>\u0000 </div>","PeriodicalId":49471,"journal":{"name":"Structural Control & Health Monitoring","volume":null,"pages":null},"PeriodicalIF":4.6,"publicationDate":"2024-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/2024/8880701","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142089866","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Fiber Bragg Grating Accelerometer and Its Application to Measure Wheel-Rail Excitation","authors":"Jianzhi Li, Bohao Shen, Haoran Zhang, Ying Song","doi":"10.1155/2024/8442782","DOIUrl":"https://doi.org/10.1155/2024/8442782","url":null,"abstract":"<div>\u0000 <p>This research aims to develop and validate a fiber Bragg grating (FBG) accelerometer, designed with a bearing and flexure hinge structure, to accurately measure medium- and high-frequency vibrations caused by wheel-rail excitation. The structural parameters of the accelerometer are optimized through theoretical mechanics analysis, and its dynamic characteristics are verified by experimental vibration testing and compared with the finite element simulated results. Key findings reveal that the proposed sensor has a wide operational frequency range of 10–1200 Hz and a high acceleration sensitivity of 3 pm/m·s<sup>−2</sup>, in addition to excellent linearity and repeatability. Moreover, the sensor demonstrates immunity to temperature variations, making it suitable for use in fluctuating temperature environments. Laboratory model experiment tests of high-speed train tracks show that the FBG accelerometer effectively identifies medium- to high-frequency vibration signals caused by wheel-rail excitation, corroborated by traditional piezoelectric accelerometers. The results confirm the sensor’s ability to capture vertical axle box vibration acceleration (ABVA) and its potential for assessing axle box structural dynamics in high-speed railway applications.</p>\u0000 </div>","PeriodicalId":49471,"journal":{"name":"Structural Control & Health Monitoring","volume":null,"pages":null},"PeriodicalIF":4.6,"publicationDate":"2024-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/2024/8442782","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142041703","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Junhao Zheng, Darong Wang, Zhongguo Guan, Kaiqi Lin
{"title":"Cluster Computing-Aided Open-Source Programming Framework for Model Updating of Civil Structures","authors":"Junhao Zheng, Darong Wang, Zhongguo Guan, Kaiqi Lin","doi":"10.1155/2024/9331705","DOIUrl":"https://doi.org/10.1155/2024/9331705","url":null,"abstract":"<div>\u0000 <p>The finite element model updating (FEMU) and structural optimization of high-fidelity numerical models for large civil structures require significant computational resources and efficient optimization algorithms. However, prior research has predominantly relied on commercial software, which has more restrictions compared to open-source ones. A cluster computing-aided programming framework for the FEMU of large civil structures was developed based on the open-source platforms OpenSees and Python. The high-performance computing (HPC) cluster was built to connect the cloud/local computing resources. Then, the cluster computing-aided particle swarm optimization (PSO) algorithm, suitable for scientific computing on HPC cluster, was developed. The software interfaces were programmed to connect OpenSees with HPC cluster to achieve high-performance FEMU and structural optimization. The advantages of the framework include (1) an open-source cluster computing platform suitable for FEMU and structural design optimization is developed utilizing <i>dispy</i>; (2) the framework is convenient to use, highly efficient in computation, and is capable of fully utilizing both local and cloud computational resources to improve computational efficiency; and (3) it has strong compatibility and is flexible to be customized for various engineering problems by embedding objective functions. Four examples were used to illustrate the applications of this framework in different fields.</p>\u0000 </div>","PeriodicalId":49471,"journal":{"name":"Structural Control & Health Monitoring","volume":null,"pages":null},"PeriodicalIF":4.6,"publicationDate":"2024-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/2024/9331705","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142041704","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Damage Scenario Prediction for Concrete Bridge Columns Using Deep Generative Networks","authors":"Tzu-Kang Lin, Hao-Tun Chang, Ping-Hsiung Wang, Rih-Teng Wu, Ahmed Abdalfatah Saddek, Kuo-Chun Chang, Dzong-Chwang Dzeng","doi":"10.1155/2024/5526537","DOIUrl":"https://doi.org/10.1155/2024/5526537","url":null,"abstract":"<div>\u0000 <p>Bridges in areas with high seismic risk are constantly exposed to earthquake threats. Therefore, comprehensive bridge damage assessments are essential for postearthquake retrofitting and safety assurance. However, traditional methods of assessing damage and collecting data are time-consuming and labor-intensive. To address this issue, this study proposes a deep generative adversarial network (GAN)-based approach to predict the surface damage patterns of bridge columns. Using visual patterns from experimental tests, the proposed approach can generate surface damage to the synthetic column, such as cracks and concrete splinters. The study also investigates the effects of different data representation schemes, such as grayscale, black and white, and obstacle-removed images, and uses the corresponding damage indices as additional constraints to improve network training. The results show that the proposed approach can offer a reliable reference for bridge engineers to evaluate and repair seismic-induced bridge damage, which can significantly lower the cost of disaster reconnaissance.</p>\u0000 </div>","PeriodicalId":49471,"journal":{"name":"Structural Control & Health Monitoring","volume":null,"pages":null},"PeriodicalIF":4.6,"publicationDate":"2024-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/2024/5526537","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142013602","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"An Intelligent Two-Stage Fault Classification Model for Railway Turnout Systems Based on FastDTW","authors":"Huasheng Sun, Yingguo Fu, Sizhong Zhang, Zhongqun Yang, Fangmao Guo, Linfeng Li, Jianyang Liu","doi":"10.1155/2024/3715605","DOIUrl":"https://doi.org/10.1155/2024/3715605","url":null,"abstract":"<div>\u0000 <p>The identification and classification of railway turnout faults are essential for guaranteeing train safety. Traditional diagnostic methods for these faults face challenges due to limited accuracy, stemming from the scarcity of fault samples, and often fail to provide detailed fault classification. In response to these issues, we introduce an advanced two-stage model for the classification of railway turnout faults, utilizing the FastDTW algorithm, known for its efficient approximation of DTW (dynamic time warping) with linear time and space complexity. In the first stage, we employ a Shapelets feature extraction algorithm, based on a greedy strategy, to efficiently identify the most representative segments from long sequence action curves. Progressing to the second stage, the model tackles the inherent singularities in the FastDTW algorithm by incorporating a novel curve segmentation technique, also rooted in a greedy strategy. This technique fine-tunes the fault classification process, leading to more accurate outcomes. The effectiveness and precision of our proposed model were validated empirically using a dataset of 540 faulty curves from a specific high-speed railway station, achieving an impressive classification accuracy of 97%. This substantial accuracy in fault curve classification underscores the potential of our model to significantly enhance the safety and efficiency of railway operations, marking a notable advancement in the field of railway turnout fault classification.</p>\u0000 </div>","PeriodicalId":49471,"journal":{"name":"Structural Control & Health Monitoring","volume":null,"pages":null},"PeriodicalIF":4.6,"publicationDate":"2024-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/2024/3715605","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141994049","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A Testing Field for Studies of Environmental and Operational Effects in Structural Damage Localization of Mechanical Structures","authors":"Maximilian Rohrer, Max Moeller, Armin Lenzen","doi":"10.1155/2024/3970794","DOIUrl":"https://doi.org/10.1155/2024/3970794","url":null,"abstract":"<div>\u0000 <p>Methods of structural health monitoring (SHM) are often challenged by changing environmental and operational conditions (EOC). This paper presents a novel experimental testing field specifically designed for studying the effects of EOC on black box vibration-based output-only SHM methods. The experimental testing field consists of two identical mechanical structures that are exposed to mass and stiffness perturbations: one in a controllable laboratory setup and one under the influence of varying EOC in a field setup. The paper demonstrates the feasibility and usefulness of the dual experimental testing field for studies about EOC influences on SHM. The results of a preliminary study of the occurring EOC in the field setup are presented, and a modular measurement system that provides high-quality data is introduced. By providing the experimental acceleration data, a new experimental benchmark dataset for various studies and future use in the field of SHM is presented.</p>\u0000 </div>","PeriodicalId":49471,"journal":{"name":"Structural Control & Health Monitoring","volume":null,"pages":null},"PeriodicalIF":4.6,"publicationDate":"2024-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/2024/3970794","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141980334","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Xicheng Zhang, Leilei Liu, Zhihao Qiu, Lanhao Cui, Chengming Hu
{"title":"Replaceable Displacement-Amplifying Rotary Friction Damper: Experimental and Numerical Investigation","authors":"Xicheng Zhang, Leilei Liu, Zhihao Qiu, Lanhao Cui, Chengming Hu","doi":"10.1155/2024/9402792","DOIUrl":"https://doi.org/10.1155/2024/9402792","url":null,"abstract":"<div>\u0000 <p>Timber structures are vulnerable to failure and collapse under seismic action. To improve the seismic performance of such structures, a replaceable displacement amplification rotary friction damper was proposed and designed. Six specimens were fabricated, each varying in pretension strains and employing three different composite friction materials as control parameters, followed by low cyclic loading tests. The study investigated the working mechanism, hysteresis performance, energy dissipation capacity, performance stability, and displacement amplification effect of the dampers. A finite element model was developed to analyze the hysteresis performance of the damper and evaluate the impact of various parameters on its overall effectiveness. Furthermore, a comparative analysis of the damper’s hysteresis characteristics was conducted. The theoretical calculations and finite element analysis were validated using experimental results, showing a relative error within 10%. The specimens demonstrated a notable displacement amplification capability, which increased as the intermediate connector length decreased. By reducing the length by 200 mm, the maximum damping force could be amplified by 5.5 times, while the nodal rotation values increased by 3.92 times. Additionally, for every 50 <i>με</i> increment in pretension strain, energy consumption increases by an average of 148%, and for each unit increase in the friction coefficient, energy consumption increases by an average of 172%.</p>\u0000 </div>","PeriodicalId":49471,"journal":{"name":"Structural Control & Health Monitoring","volume":null,"pages":null},"PeriodicalIF":4.6,"publicationDate":"2024-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/2024/9402792","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141967802","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Bridge Displacement Prediction from Dynamic Responses of a Passing Vehicle Using CNN-GRU Networks","authors":"Xiao-Tong Sun, Zuo-Cai Wang, Fei Zhang, Yu Xin, Yue-Ling Jing","doi":"10.1155/2024/6954442","DOIUrl":"https://doi.org/10.1155/2024/6954442","url":null,"abstract":"<div>\u0000 <p>Dynamic displacement is an important indicator for bridge safety estimation but is difficult to measure due to economic or technological limitations. Dynamic responses of a passing vehicle include the bridge dynamic response information. This study proposes a framework utilizing artificial neural networks to efficiently and accurately predict bridge displacements from the dynamic response of a passing vehicle. The input and the output of the networks are the vehicle acceleration responses and the bridge dynamic displacement responses, respectively. The implemented framework consists of convolutional neural network (CNN) and gated recurrent units (GRU). CNN is adept at feature extraction in the microcosm of short-term time series, revealing intricate nuances. As a complement, GRU plays a crucial role in extracting features of macroscopic long-term time series. The CNN-GRU network can efficiently extract higher-order features contained in the input data. Numerical experiments are conducted using the developed vehicle-bridge interaction (VBI) system model to obtain requisite data for training the deep neural network. The impact of the presence or absence of roadway irregularities and the number of vehicles are discussed, indicating the accuracy of the framework. Furthermore, a laboratory experiment is conducted to further assess the performance of the CNN-GRU network. Results indicate that the CNN-GRU network offers an effective alternative for bridge displacement measurements.</p>\u0000 </div>","PeriodicalId":49471,"journal":{"name":"Structural Control & Health Monitoring","volume":null,"pages":null},"PeriodicalIF":4.6,"publicationDate":"2024-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/2024/6954442","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141967453","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}