Journal of Infrastructure Intelligence and Resilience最新文献_第6页

Recent advances in wireless sensor networks for structural health monitoring of civil infrastructure 用于土木基础设施结构健康监测的无线传感器网络的最新进展

Journal of Infrastructure Intelligence and Resilience Pub Date : 2023-11-11 DOI: 10.1016/j.iintel.2023.100066

Xiao Yu , Yuguang Fu , Jian Li , Jianxiao Mao , Tu Hoang , Hao Wang

{"title":"Recent advances in wireless sensor networks for structural health monitoring of civil infrastructure","authors":"Xiao Yu , Yuguang Fu , Jian Li , Jianxiao Mao , Tu Hoang , Hao Wang","doi":"10.1016/j.iintel.2023.100066","DOIUrl":"10.1016/j.iintel.2023.100066","url":null,"abstract":"<div><p>Wireless Smart Sensor Networks (WSSN) have seen significant advancements in recent years. They act as a core part of structural health monitoring (SHM) systems by facilitating efficient measurement, assessment, and hence maintenance of civil infrastructure. This paper presents the latest technology developments of WSSN in the last ten years, including ones for a single sensor node and those for a network of nodes. Focus is placed on critical aspects of such advancements, including event-triggered sensing, multimeric sensing, edge/cloud computing, time synchronization, real-time data acquisition, decentralized data processing, and long-term reliability. In addition, full-scale applications and demonstrations of WSSN in SHM are also summarized. Finally, the remaining challenges and future research directions of WSSN are discussed to promote the further development and applications.</p></div>","PeriodicalId":100791,"journal":{"name":"Journal of Infrastructure Intelligence and Resilience","volume":"3 1","pages":"Article 100066"},"PeriodicalIF":0.0,"publicationDate":"2023-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2772991523000415/pdfft?md5=93bc70290b7195e2b1eb2cae5826cce6&pid=1-s2.0-S2772991523000415-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135671193","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}

引用次数: 0

Blockchain empowerment in construction supply chains: Enhancing efficiency and sustainability for an infrastructure development 建筑供应链中的区块链赋能：提高基础设施开发的效率和可持续性

Journal of Infrastructure Intelligence and Resilience Pub Date : 2023-11-07 DOI: 10.1016/j.iintel.2023.100065

Ahsan Waqar, Abdul Mateen Khan, Idris Othman

{"title":"Blockchain empowerment in construction supply chains: Enhancing efficiency and sustainability for an infrastructure development","authors":"Ahsan Waqar, Abdul Mateen Khan, Idris Othman","doi":"10.1016/j.iintel.2023.100065","DOIUrl":"10.1016/j.iintel.2023.100065","url":null,"abstract":"<div><p>The construction sector is now experiencing a significant transformation, primarily motivated by the need to enhance operational efficiency and promote sustainable practices. The emergence of blockchain technology has been seen as a disruptive factor that has the potential to fundamentally transform the field of supply chain management within the construction industry. Nevertheless, the extent to which this technology has revolutionized the sector has yet to be extensively investigated. The primary objective of this study is to address the existing research void by examining the impact of blockchain technology on enhancing the capabilities of building supply chains. This study employs a thorough examination of empirical case studies and a survey conducted among 136 industry professionals to explore the many functions of blockchain technology in augmenting efficiency, transparency, and traceability within building supply chains. The significant constructs were found having impact on blockchain implementation for construction supply chains are, Transparency and Traceability (<em>β</em> = 0.202, <em>ρ</em> = 0.000, <em>t</em> = 42.560), Smart Contracts for Automation (<em>β</em> = 0.232, <em>ρ</em> = 0.000, <em>t</em> = 62.596), Quality Assurance and Compliance (<em>β</em> = 0.230, <em>ρ</em> = 0.000, <em>t</em> = 64.704), Dispute Resolution and Accountability (<em>β</em> = 0.235, <em>ρ</em> = 0.000, <em>t</em> = 79.533), Supplier Management and Verification (<em>β</em> = 0.251, <em>ρ</em> = 0.000, t = 49.404).</p></div>","PeriodicalId":100791,"journal":{"name":"Journal of Infrastructure Intelligence and Resilience","volume":"3 1","pages":"Article 100065"},"PeriodicalIF":0.0,"publicationDate":"2023-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2772991523000403/pdfft?md5=53901e856e1ac3e651bf0fde6657918e&pid=1-s2.0-S2772991523000403-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135509941","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}

引用次数: 0

Fatigue-sensitive feature extraction, failure prediction and reliability-based design optimization of the hyperloop tube 超级高铁管道疲劳敏感特征提取、失效预测及可靠性优化设计

Journal of Infrastructure Intelligence and Resilience Pub Date : 2023-11-01 DOI: 10.1016/j.iintel.2023.100064

Adrian Mungroo , Jung-Ho Lewe

{"title":"Fatigue-sensitive feature extraction, failure prediction and reliability-based design optimization of the hyperloop tube","authors":"Adrian Mungroo , Jung-Ho Lewe","doi":"10.1016/j.iintel.2023.100064","DOIUrl":"https://doi.org/10.1016/j.iintel.2023.100064","url":null,"abstract":"<div><p>Hyperloop research focuses on investigating the design and limitations of its complex subsystems. However, the existing literature overlooks the fatigue failure characteristics of the Hyperloop tube, leaving future engineers without informed estimates of its reliability. To address this gap, this study examined the occurrence and prediction of fatigue failure in the Hyperloop system. The findings revealed that both the underground and above-ground configurations showed resistance to fatigue failure, with the underground system showing greater resilience. Additionally, sensitivity analysis highlighted support spacing, tube ultimate tensile strength, and tube radius as the most influential design variables affecting fatigue sensitivity. Moreover, a reliability-based design cost optimization was performed, taking into account demand uncertainty and utilizing insights from previous analyses to determine ideal design parameters. This research sheds light on critical design aspects of the Hyperloop tube that require intensified attention to effectively mitigate the risk of fatigue failure.</p></div>","PeriodicalId":100791,"journal":{"name":"Journal of Infrastructure Intelligence and Resilience","volume":"2 4","pages":"Article 100064"},"PeriodicalIF":0.0,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2772991523000397/pdfft?md5=e6be6e5dddbce6ce48f213863809c1d2&pid=1-s2.0-S2772991523000397-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"92101434","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}

引用次数: 0

Early detection of thermal instability in railway tracks using piezo-coupled structural signatures 基于压电耦合结构特征的铁路轨道热失稳早期检测

Journal of Infrastructure Intelligence and Resilience Pub Date : 2023-10-12 DOI: 10.1016/j.iintel.2023.100063

Tathagata Banerjee, Sumedha Moharana, Lukesh Parida

{"title":"Early detection of thermal instability in railway tracks using piezo-coupled structural signatures","authors":"Tathagata Banerjee, Sumedha Moharana, Lukesh Parida","doi":"10.1016/j.iintel.2023.100063","DOIUrl":"https://doi.org/10.1016/j.iintel.2023.100063","url":null,"abstract":"<div><p>Rail accidents caused by rail track derailments have been a growing concern due to repetitive thermal changes resulting from high temperature stresses in rails due to rail traction and environmental thermal variation. This leads to thermal buckling, which can result in catastrophic failure. Structural health monitoring (SHM) using the electromechanical impedance (EMI) technique has emerged as a promising technology to detect structural deterioration and its severity before it leads to failure. This study used piezoelectric sensors to collect piezo-coupled structural signatures of different rail-joint bars for high-temperature repetitive thermal cycles, which were then analyzed using an impedance analyzer. The results show that the piezo-coupled signatures could identify structural changes, and the damage metric, could be employed for continuous monitoring of structural rail defects due to excessive thermal stress and residual strain. The method also derived piezo-equivalent structural parameters, such as mass, stiffness, and damping, which were very satisfactory in detecting significant changes and consequent damage. Overall, this study presents a pre-emptive experimental method that can see thermal deterioration and instability in rails and rail joints, thereby reducing the risk of rail accidents caused by derailments.</p></div>","PeriodicalId":100791,"journal":{"name":"Journal of Infrastructure Intelligence and Resilience","volume":"2 4","pages":"Article 100063"},"PeriodicalIF":0.0,"publicationDate":"2023-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49891237","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Multi-modal deep fusion for bridge condition assessment 基于多模态深度融合的桥梁状态评估

Journal of Infrastructure Intelligence and Resilience Pub Date : 2023-10-02 DOI: 10.1016/j.iintel.2023.100061

Mozhgan Momtaz , Tianshu Li , Devin K. Harris , David Lattanzi

{"title":"Multi-modal deep fusion for bridge condition assessment","authors":"Mozhgan Momtaz , Tianshu Li , Devin K. Harris , David Lattanzi","doi":"10.1016/j.iintel.2023.100061","DOIUrl":"https://doi.org/10.1016/j.iintel.2023.100061","url":null,"abstract":"<div><p>Bridge condition rating is a challenging task as it largely depends on the experience-level of the manual inspection and therefore is prone to human errors. The inspection report often consists of a collection of images and sequences of sentences (text) explaining the condition of the considered bridge. In a routine manual bridge inspection, an inspector collects a set of images and textual descriptions of bridge components and assigns an overall condition rating (ranging between 0 and 9) based on the collected information. Unfortunately, this method of bridge inspection has been shown to yield inconsistent condition ratings that correlate with inspector experience. To improve the consistency among image-text inspection data and further predict the accordant condition ratings, this study first provides a collective image-text dataset, extracted from the collection of bridge inspection reports from the Virginia Department of Transportation. Using this dataset, we have developed novel deep learning-base methods for an automatic bridge condition rating prediction based on data fusion between the textual and visual data from the collected report sets.</p><p>Our proposed multi modal deep fusion approach constructs visual and textual representations for images and sentences separately using appropriate encoding functions, and then fuses representations of images and text to enhance the multi-modal prediction performance of the assigned condition ratings. Moreover, we study interpretations of the deployed deep models using saliency maps to identify parts of the image-text inputs that are essential in condition rating predictions. The findings of this study point to potential improvements by leveraging consistent image-text inspection data collection as well as leveraging the proposed deep fusion model to improve the bridge condition prediction rating from both visual and textual reports.</p></div>","PeriodicalId":100791,"journal":{"name":"Journal of Infrastructure Intelligence and Resilience","volume":"2 4","pages":"Article 100061"},"PeriodicalIF":0.0,"publicationDate":"2023-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49891238","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Identifying potentially dangerous areas of frost heaving and surfacing of the buried oil pipeline 识别潜在的冻胀危险区域和埋地输油管道的地表

Journal of Infrastructure Intelligence and Resilience Pub Date : 2023-09-09 DOI: 10.1016/j.iintel.2023.100054

Alla Yu. Vladova , Yury R. Vladov

{"title":"Identifying potentially dangerous areas of frost heaving and surfacing of the buried oil pipeline","authors":"Alla Yu. Vladova , Yury R. Vladov","doi":"10.1016/j.iintel.2023.100054","DOIUrl":"https://doi.org/10.1016/j.iintel.2023.100054","url":null,"abstract":"<div><p>This scientific study aims to automatically identify potentially dangerous areas of frost heaving and surfacing of a buried oil pipeline using the geological description of soil profile. The geological description of soil profile along the proposed route of a pipeline entails the study and identification of various layers of soil to determine the soil's suitability for pipeline installation and support. Enriching the geological description of soils in the first stage was achieved by creating a family of parameters that characterize the presence of water in two states and the interaction of the buried oil pipeline with soil layers. In the second stage, missed and erroneous soil parameters were restored by searching for similar patterns along the route of the pipeline using the enriched geological description of soil profile. Afterward, the selected areas of frost heaving and surfacing were ranked by potential danger in the third stage. The algorithm developed was shown to reduce the risk of damage to the oil pipeline and enrich the geological description of soil profile without additional field works. The results of the study allowed for the allocation of potentially dangerous areas where frost heaving and surfacing occur. The methodology described in the study can be applied in the midstream segment of the oil and gas industry to minimize the risk of pipeline damage.</p></div>","PeriodicalId":100791,"journal":{"name":"Journal of Infrastructure Intelligence and Resilience","volume":"2 4","pages":"Article 100054"},"PeriodicalIF":0.0,"publicationDate":"2023-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49891239","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Structural displacement sensing techniques for civil infrastructure: A review 民用基础设施结构位移传感技术综述

Journal of Infrastructure Intelligence and Resilience Pub Date : 2023-09-01 DOI: 10.1016/j.iintel.2023.100041

Zhanxiong Ma, Jaemook Choi, Hoon Sohn

引用次数: 4

Design and implementation of sustainable solar energy harvesting for low-cost remote sensors equipped with real-time monitoring systems 为配备实时监测系统的低成本远程传感器设计和实现可持续太阳能收集

Journal of Infrastructure Intelligence and Resilience Pub Date : 2023-09-01 DOI: 10.1016/j.iintel.2023.100051

Kaveh Malek , Edgardo Ortíz Rodríguez , Yi-Chen Lee , Joshua Murillo , Ali Mohammadkhorasani , Lauren Vigil , Su Zhang , Fernando Moreu

{"title":"Design and implementation of sustainable solar energy harvesting for low-cost remote sensors equipped with real-time monitoring systems","authors":"Kaveh Malek , Edgardo Ortíz Rodríguez , Yi-Chen Lee , Joshua Murillo , Ali Mohammadkhorasani , Lauren Vigil , Su Zhang , Fernando Moreu","doi":"10.1016/j.iintel.2023.100051","DOIUrl":"https://doi.org/10.1016/j.iintel.2023.100051","url":null,"abstract":"<div><p>Data acquisition systems, such as Wireless Smart Sensor Networks (WSSNs) can increase the resilience of infrastructure by providing real-time monitoring and data collection of environmental parameters. Yet, sustainable energy supplies for sensor networks established in remote and inaccessible areas still present a challenge. Previously, researchers have attempted to address this difficulty by proposing different energy systems including solar energy harvesting, however, significant prolonged experimental data for the operation of extensive networks powered by solar energy has not been reported. This paper presents an original design and implementation of an energy system for a large WSSN and provides the sensors' power status data over a significant duration. A network of low-cost flood monitoring sensors, including twenty-six water level sensors, twenty rain gauges, and eight communication nodes were deployed and tested on summer and fall 2022 at six remote locations at the northern New Mexico Pueblo, Ohkay Owingeh. A thermometer and a humidity sensor were added to each communication node to record temperature and air's moisture level. In addition, a networked voltage monitoring system was deployed to observe the sensors energy status in real-time. The items of the WSSN are composed of two differing energy circuits suited for their energy demands. The sensors' energy circuits contain a photovoltaic panel, a lithium-polymer battery, a control device, and a DC-to-DC converter. Whereas the communication nodes contain another photovoltaic panel, a lead-acid battery, and a solar charging controller. The findings provide a perspective on the long-term field deployment of WSSNs consisting of low-cost sensors.</p></div>","PeriodicalId":100791,"journal":{"name":"Journal of Infrastructure Intelligence and Resilience","volume":"2 3","pages":"Article 100051"},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49879402","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Improvement of burst capacity model for pipelines containing surface cracks and its implication for reliability analysis 含表面裂纹管道爆破能力模型的改进及其对可靠性分析的意义

Journal of Infrastructure Intelligence and Resilience Pub Date : 2023-09-01 DOI: 10.1016/j.iintel.2023.100043

Haotian Sun, Wenxing Zhou

{"title":"Improvement of burst capacity model for pipelines containing surface cracks and its implication for reliability analysis","authors":"Haotian Sun, Wenxing Zhou","doi":"10.1016/j.iintel.2023.100043","DOIUrl":"https://doi.org/10.1016/j.iintel.2023.100043","url":null,"abstract":"<div><p>This paper presents the improvement of a widely used burst capacity model for steel oil and gas pipelines that contain longitudinal external surface cracks, namely the CorLAS model, through the addition of a correction factor that is quantified by the Gaussian process regression (GPR). The correction factor is assumed to depend on four non-dimensional input features that characterize both the crack geometry and pipe material properties. A database consisting of 212 full-scale burst tests of pipe specimens that contain longitudinal surface cracks is established based on the open literature, which is employed to train the GPR model and evaluate its performance. It is shown that GPR is highly effective in improving the accuracy of the CorLAS model predictions. The improvement is further shown to have a marked effect on the time-dependent probability of burst of pipelines containing growing surface cracks through two hypothetical pipeline examples: when employing the CorLAS model, the probabilities of burst are significantly higher, exceeding those obtained using the improved CorLAS model by more than one order of magnitude.</p></div>","PeriodicalId":100791,"journal":{"name":"Journal of Infrastructure Intelligence and Resilience","volume":"2 3","pages":"Article 100043"},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49879401","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Visualization of structural health monitoring information using Internet-of-Things integrated with building information modeling 物联网与建筑信息建模相结合的结构健康监测信息可视化

Journal of Infrastructure Intelligence and Resilience Pub Date : 2023-09-01 DOI: 10.1016/j.iintel.2023.100053

Micheal Sakr, Ayan Sadhu

{"title":"Visualization of structural health monitoring information using Internet-of-Things integrated with building information modeling","authors":"Micheal Sakr, Ayan Sadhu","doi":"10.1016/j.iintel.2023.100053","DOIUrl":"https://doi.org/10.1016/j.iintel.2023.100053","url":null,"abstract":"<div><p>Structural Health Monitoring (SHM) has become a paramount necessity in civil engineering for improving the operational performance of aging infrastructure. Recent monitoring techniques have utilized emerging technologies in Industry 4.0, such as the Internet of Things, Big Data analytics, cloud computing, and cybersecurity, to automate SHM methodologies. However, they have found challenges in linking these technologies and developing an autonomous, well-established digital framework for applications of SHM. Visualizing processed SHM data in a real-time digital interface generates multiple obstacles, such as witnessing delays in data transfer and resorting to offline tools for manual data processing. This paper, therefore, explores the integration of Building Information Modeling (BIM) and the Internet of Things (IoT) through an Arduino micro-processing unit for tracking and visualizing the data from the time and frequency domains. Strategies for enabling data monitoring and processing are developed while continuously acquiring structural responses. The query of data is established in a web-based database instead of storing the data in offline resources that await manual intervention. The proposed real-time SHM methodology is validated experimentally using two practical applications: a dynamically moving vehicle over a simply-supported bridge prototype and a randomly excited three-story model with real-time visualization of both time- and frequency-domain information under undamaged and damaged conditions. The proposed research develops an early-phase Digital Twin (DT) to present static and real-time dynamic data in a rich-fed BIM database.</p></div>","PeriodicalId":100791,"journal":{"name":"Journal of Infrastructure Intelligence and Resilience","volume":"2 3","pages":"Article 100053"},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49879400","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1