{"title":"Review on optimization strategies of probabilistic diagnostic imaging methods","authors":"Ning Li , Anningjing Li , Jiangfeng Sun","doi":"10.1016/j.iintel.2024.100127","DOIUrl":"10.1016/j.iintel.2024.100127","url":null,"abstract":"<div><div>With the continuous development of intelligent infrastructure, structural health monitoring (SHM) and non-destructive testing (NDT) have become major research focuses. Ultrasonic-guided wave imaging technology not only integrates the global impact of damage on structures but also provides intuitive localization and severity characterization of the damage. Probabilistic diagnostic imaging (PDI) methods, which do not require direct interpretation of guided wave signals and can achieve high-quality imaging with sparse arrays, have garnered increasing attention. This paper introduces the principles, general processes, and technical advantages of PDI methods. Based on the process of the PDI, existing optimization strategies are categorized into two types: internal process optimizations, which include sensor layout, damage indices optimization, construction of the distribution weight function, and data fusion; and external process optimizations, which include spurious image suppression, on-site environment detection, and integration of methodologies, each analyzed in detail. With the affirmation of the value of these strategies, this paper also highlights the current issues within these methods and explores potential future developments by integrating emerging technologies such as intelligent sensing, big data, and artificial intelligence. These insights provide valuable reference suggestions for the continued optimization of these methods.</div></div>","PeriodicalId":100791,"journal":{"name":"Journal of Infrastructure Intelligence and Resilience","volume":"4 1","pages":"Article 100127"},"PeriodicalIF":0.0,"publicationDate":"2024-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142586147","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"An integrated management system (IMS) approach to sustainable construction development and management","authors":"Ahsan Waqar , Saad Nisar , Muhammad Muddassir , Omrane Benjeddou","doi":"10.1016/j.iintel.2024.100126","DOIUrl":"10.1016/j.iintel.2024.100126","url":null,"abstract":"<div><div>Construction is significantly contributing to the severe environmental crisis it is facing. The sector consumes over 3 billion tons of raw materials annually, and its activities account for 40% of global CO<sub>2</sub> emissions. Traditional integrated strategies toward fragmented sustainability cannot offer total optimization. In this respect, the present research presents an integrated management system (IMS) containing a composite of metrics for sustainable construction management (SCM). This research was specifically geared to test the relationship between the elements of IMS and SCM from the perspective of the construction industry. A quantitative survey tested through 119 professionals was used for data collection. It is established through structural equation modeling (SEM) that the internal consistency of Cronbach’s Alpha 0.72–0.95 and construct validity was strong. The Fornell-Larcker criterion was realized to affirm good discriminant validity. Crucial results identified the presence of significant impacts for quality management (QM) (β = 0.643, <em>p</em> < 0.001), risk management (RM) (β = 0.53, <em>p</em> < 0.001), and safety management (SM) (β = 0.439, <em>p</em> < 0.001). Therefore, this study further enhances the scalability of IMS so that it is practically applied to improve project quality and safety, along with risk management. Future research could also focus on studying the context of the integration of IMS with SCM and continue to work using objective performance measures to validate these findings.</div></div>","PeriodicalId":100791,"journal":{"name":"Journal of Infrastructure Intelligence and Resilience","volume":"4 1","pages":"Article 100126"},"PeriodicalIF":0.0,"publicationDate":"2024-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142555002","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Quantitative risk analysis of road transportation of hazardous materials in coastal areas","authors":"Daijie Chen , Xiyong Bai","doi":"10.1016/j.iintel.2024.100124","DOIUrl":"10.1016/j.iintel.2024.100124","url":null,"abstract":"<div><p>Given the complex climate conditions in coastal areas and their role as key transportation hubs for hazardous chemicals, this study proposes a method to quantitatively and comprehensively evaluate transportation risks. Initially, accident data were analyzed to identify risk factors from five aspects: human, vehicle, materials, environment, and management, based on system safety theory. Subsequently, a risk analysis model was developed using Decision-making Trial and Evaluation Laboratory, interpretive structural model theory, and Bayesian theory to quantitatively assess accident risk levels. The model was applied to a case involving a hazardous chemical accident on a cross-sea bridge, where Bayesian backward reasoning was used to analyze the sensitivity and importance of risk factors. This approach facilitated the key risk factors affecting the safety of hazardous chemical transportation systems. Notably, the study incorporated scenarios involving hazardous material transport vehicles crossing sea bridges into the risk assessment framework, offering valuable insights for management authorities. It also considered the impact of strong side winds-a factor often overlooked-in hazardous material transport. The validation process demonstrated that the method accurately quantifies the risk of hazardous chemical transportation and identifies the key factors influencing accident occurrence. The research highlights that strong gusts of wind significantly impact safety, and human factors are crucial in the overall risk system.</p></div>","PeriodicalId":100791,"journal":{"name":"Journal of Infrastructure Intelligence and Resilience","volume":"3 4","pages":"Article 100124"},"PeriodicalIF":0.0,"publicationDate":"2024-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2772991524000434/pdfft?md5=964f153c00429cfef1e5889999414f17&pid=1-s2.0-S2772991524000434-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142274608","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Multimodal vortex-induced vibration mitigation and design approach of bistable nonlinear energy sink inerter on bridge structure","authors":"Ruihong Xie , Kun Xu , Houjun Kang , Lin Zhao","doi":"10.1016/j.iintel.2024.100123","DOIUrl":"10.1016/j.iintel.2024.100123","url":null,"abstract":"<div><div>Large-scale structures, e.g., long-span bridge structures, are prone to induce multi-modal vibrations due to their densely spaced low modal frequencies. Due to the limited frequency bandwidth of linear dynamic absorbers, they are incapable of effectively mitigating vibrations across multiple modes. To this end, the bistable nonlinear energy sink inerter (BNESI) is used to mitigate the multimodal vortex-induced vibration (VIV) of the beam structure. The highly nonlinear equilibrium differential equations of the beam-BNESI system are numerically solved, and the simulated annealing (SA) algorithm is employed to determine the optimal VIV reduction ratio and BNESI parameters. In comparison to the cubic-type nonlinear energy sink inerter (CNESI), BNESI is found to possess more stable equilibrium positions, smaller stiffness coefficients, and higher VIV mitigation efficiency. The selection of design modes has been found to influence the efficiency of multimodal VIV mitigation, with the use of the intermediate modal order as the design mode resulting in the highest efficiency for multimodal VIV mitigation. The performance-based multimodal VIV mitigation design can be realized with three parameters, i.e., inertance ratio, damping coefficient, and stiffness coefficient. Moreover, the performance-based multimodal VIV mitigation approach and models proposed in this study demonstrate a high level of precision.</div></div>","PeriodicalId":100791,"journal":{"name":"Journal of Infrastructure Intelligence and Resilience","volume":"3 4","pages":"Article 100123"},"PeriodicalIF":0.0,"publicationDate":"2024-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142421587","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Enhanced operational modal analysis and change point detection for vibration-based structural health monitoring of bridges","authors":"Serge L. Desjardins , David T. Lau","doi":"10.1016/j.iintel.2024.100121","DOIUrl":"10.1016/j.iintel.2024.100121","url":null,"abstract":"<div><div>One of the most promising uses of vibration-based structural health monitoring (VBSHM) in bridge damage detection is the tracking of modes through long-term repeated or continuous operational modal analysis (OMA). Any shifts in modal parameters over time can signal structural damage. However, in real-world applications, noise and environmental uncertainties introduce variability in the data, potentially obscuring damage-related changes. To address this, it is essential to establish and understand the temporal trends and behavior of the estimated modal parameters, enabling accurate interpretation of the engineering data. This paper presents a detailed study focusing on data-driven techniques to improve the OMA results by determining the causes of modal variability and establishing modal models to filter out these known causes of variability. It explores the use of data continuously collected over a period of one month in November 2017 on the Confederation Bridge in eastern Canada. Operational modal analysis is conducted to extract modal frequencies and mode shapes, revealing correlations with environmental and operational factors such as wind, temperature and vehicular traffic. A novel approach using the residuals from regression modal models for damage detection is proposed, utilizing a change point detection algorithm. Results indicate the potential to detect shifts in modal frequencies corresponding to damage scenarios, at lower levels than was previously possible, highlighting the feasibility of using enhanced modal features for sensitive damage identification. Overall, the paper contributes to advancing the understanding of variability in vibration-based structural health monitoring and presents a promising practical technique for improving damage detection results using enhanced operational modal estimates in realistic field applications of a real-world structure.</div></div>","PeriodicalId":100791,"journal":{"name":"Journal of Infrastructure Intelligence and Resilience","volume":"3 4","pages":"Article 100121"},"PeriodicalIF":0.0,"publicationDate":"2024-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142442385","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Fei Hu , Hong-ye Gou , Hao-zhe Yang , Huan Yan , Yi-qing Ni , You-wu Wang
{"title":"Automatic PAUT crack detection and depth identification framework based on inspection robot and deep learning method","authors":"Fei Hu , Hong-ye Gou , Hao-zhe Yang , Huan Yan , Yi-qing Ni , You-wu Wang","doi":"10.1016/j.iintel.2024.100113","DOIUrl":"10.1016/j.iintel.2024.100113","url":null,"abstract":"<div><div>Orthotropic steel bridge decks (OSD) are widely acclaimed for their lightweight, high load-carrying capacity, and adaptability, making them a popular choice in steel structure bridges. However, the complex nature of their structure makes them susceptible to fatigue cracking, posing significant safety concerns. To address the issues above, this study employs a robot equipped with an ultrasonic phased array probe to automate the detection of internal cracks within Orthotropic Steel Decks (OSD). A Deep Convolutional Generative Adversarial Network (DCGAN) is utilized to augment the training dataset of Phased Array Ultrasonic Testing (PAUT) images. The YOLO series algorithms are applied and compared for crack localization, with YOLO v7-tiny exhibiting the highest accuracy and speed. Integrating attention mechanisms into the YOLO v7-tiny algorithm to facilliate rapid and high-precision crack detection. Analyzing the echo region with an echo intensity bar enabled the identification of crack depth, with an identification error within 5%.</div></div>","PeriodicalId":100791,"journal":{"name":"Journal of Infrastructure Intelligence and Resilience","volume":"4 1","pages":"Article 100113"},"PeriodicalIF":0.0,"publicationDate":"2024-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142535895","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A systematic literature review of unmanned underwater vehicle-based structural health monitoring technologies","authors":"Joel Friesen Waldner , Ayan Sadhu","doi":"10.1016/j.iintel.2024.100112","DOIUrl":"10.1016/j.iintel.2024.100112","url":null,"abstract":"<div><p>The structural health of underwater infrastructure such as bridges, dams, and pipelines are constantly degrading due to aging, fatigue, unexpected loads, and environmental wear and tear. Historically, these structures have been inspected by human divers; however, the need for safe and cost-effective monitoring has fostered the development of unmanned underwater vehicles (UUVs) capable of performing subsea surveillance. This paper provides a concise and systematic review of emerging technologies and methodologies for deploying underwater vehicles to perform inspections. Literature is classified into two main groups: advancements to UUV designs and capabilities and advancements to instrumentation for underwater structural health monitoring. After a systematic review, the existing challenges to UUV development and implementation are discussed. Finally, recommendations for future areas of research are outlined. This systematic literature survey aims to provide researchers and practitioners with a holistic outlook on the current state and future trends of UUV-based infrastructure inspection.</p></div>","PeriodicalId":100791,"journal":{"name":"Journal of Infrastructure Intelligence and Resilience","volume":"3 4","pages":"Article 100112"},"PeriodicalIF":0.0,"publicationDate":"2024-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2772991524000318/pdfft?md5=7ec3a7a00799411ba7c6543b0bd3df9f&pid=1-s2.0-S2772991524000318-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142232391","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Vibration reduction technique of shield construction in water-rich karst strata","authors":"Jing-Rui Peng , Hua Zhou , Jing-Yi Hao , Yan-Ning Wang","doi":"10.1016/j.iintel.2024.100111","DOIUrl":"10.1016/j.iintel.2024.100111","url":null,"abstract":"<div><p>In shield tunneling within karst formations, the vibrational effects often impact the safety of surrounding residents and buildings. The study of construction vibration mitigation measures holds significant importance. Based on the shield tunneling project in the Huang-Shang section of the Xuzhou Metro Line 6, this paper studies the causes, propagation characteristics and influencing factors of ground vibration caused by shield construction. Three effective mitigation measures were identified: (1) Optimization adjustment of shield tunneling parameters; (2) Grouting with mixed bentonite; (3) Layout of vibration reduction boreholes. Each mitigation measure was individually tested for its impact on ground vibration. The comprehensive application of the three measures in shield tunnel construction was analyzed to assess their combined effectiveness. The integration of actual engineering measurements indicates that boreholes provide the best damping effect. Furthermore, the application of multiple mitigation measures resulted in an overall 60% reduction in ground vibration, significantly mitigating the impact on residential structures on the ground. This study provides valuable references for vibration reduction measures in other engineering projects.</p></div>","PeriodicalId":100791,"journal":{"name":"Journal of Infrastructure Intelligence and Resilience","volume":"3 4","pages":"Article 100111"},"PeriodicalIF":0.0,"publicationDate":"2024-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2772991524000306/pdfft?md5=9651f42ae91f31613b990f48b6f67b9b&pid=1-s2.0-S2772991524000306-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142129107","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Structural damage identification based on dual sensitivity analysis from optimal sensor placement","authors":"Tengrun Qi, Zhilong Hou, Ling Yu","doi":"10.1016/j.iintel.2024.100110","DOIUrl":"10.1016/j.iintel.2024.100110","url":null,"abstract":"<div><p>Structural damage identification (SDI) methods using incomplete modal information can avoid the extension for unmeasured degrees of freedom, but the absence of essential damage information often leads to the failure of SDI. To address this problem, a novel SDI method based on dual sensitivity analysis and optimal sensors placement technique is proposed in this study. Firstly, in the optimal sensor placement technique, an improved eigenvector sensitivity method combined with weighted modal kinetic energy is proposed, which enables the acquisition of eigenvector information related to damage sensitivity, and incorporates it into the modal strain energy sensitivity matrix to obtain the dual sensitivity analysis matrix. Then, the sparsity of structural damage is considered, and the L1 sparse regularization is selected and introduced into the dual sensitivity analysis damage equation for better SDI results. Finally, to assess the effectiveness of the proposed method, a series of numerical simulations and experimental verifications were carried out under different structural damage scenarios. The results indicate that the proposed method can efficiently localize and quantify the structural damage with minimal modal information in one single step.</p></div>","PeriodicalId":100791,"journal":{"name":"Journal of Infrastructure Intelligence and Resilience","volume":"3 3","pages":"Article 100110"},"PeriodicalIF":0.0,"publicationDate":"2024-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S277299152400029X/pdfft?md5=53f6a3a7596efb165c45cda6c77b79d6&pid=1-s2.0-S277299152400029X-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141843906","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Qi Si , Hang Li , Zhihong Pan , Junbo Jia , Qianpeng He , Yanzhang Zhu
{"title":"Experimental study on seismic behavior of RCS joints with asymmetric friction connections and slabs","authors":"Qi Si , Hang Li , Zhihong Pan , Junbo Jia , Qianpeng He , Yanzhang Zhu","doi":"10.1016/j.iintel.2024.100109","DOIUrl":"10.1016/j.iintel.2024.100109","url":null,"abstract":"<div><p>This paper introduces a new reinforced concrete column-steel beam (RCS) joint that employs asymmetric frictional connections (AFC) to improve energy dissipation and moment transfer, reducing stress concentrations within the joint’s core. Two RCS joint specimens with AFC and floor slabs were designed and tested under quasi-static loading to analyze the impact of bolt preload on seismic performance. The experimental results demonstrate that RCS joints with AFC and slabs exhibit favorable seismic behavior in terms of bearing capacity, energy dissipation, and stiffness degradation. Increasing bolt preload enhances the bearing capacity, stiffness, and energy dissipation capacity of the joints. The failure occurred at the steel beam splice connections, while only minor micro-cracks appeared in the reinforced concrete column when the joint's bearing capacity dropped below 80% of the peak load. Displacement at the column top was primarily influenced by steel beam and column deformation, with minimal contribution from joint core deformation. The use of AFC effectively reduced deformation in the joint core area, meeting seismic design code requirements for “strong columns-weak beams.”</p></div>","PeriodicalId":100791,"journal":{"name":"Journal of Infrastructure Intelligence and Resilience","volume":"3 3","pages":"Article 100109"},"PeriodicalIF":0.0,"publicationDate":"2024-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2772991524000288/pdfft?md5=2fcfd8ee85adbb7673fc9235b48d1ef5&pid=1-s2.0-S2772991524000288-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141847907","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}