Journal of Infrastructure Intelligence and Resilience最新文献_第8页

Analyzing connectivity reliability and critical units for highway networks in high-intensity seismic region using Bayesian network 基于贝叶斯网络的高烈度地震区公路网连通性可靠性及关键单元分析

Journal of Infrastructure Intelligence and Resilience Pub Date : 2022-12-01 DOI: 10.1016/j.iintel.2022.100006

Liguo Jiang, Shuping Huang

{"title":"Analyzing connectivity reliability and critical units for highway networks in high-intensity seismic region using Bayesian network","authors":"Liguo Jiang, Shuping Huang","doi":"10.1016/j.iintel.2022.100006","DOIUrl":"10.1016/j.iintel.2022.100006","url":null,"abstract":"<div><p>It is important to evaluate the connectivity reliability of highway networks for the emergency response and rehabilitation of transportation systems in high-intensity seismic regions. Given the complexity and uncertainty of seismic damages of highway networks in high-intensity seismic region, this paper describes a Bayesian network (BN) model for evaluating the network connectivity reliability and identifying critical units. The empirical prediction method is employed to compute the connectivity probability of highway units based on the structural damage of units under earthquakes. A success tree is used to construct the network connectivity graph. Then, the network connectivity graph is converted into the BN model by BN method with the connectivity probability of highway units as prior probability. Sensitivity analysis and Bayesian updating are performed in BN to identify critical units and dynamically assess the connectivity reliability of highway network. The proposed model is applied to a highway network composed of G213 and S9 in the Wenchuan Earthquake. The results show that the BN model integrates the structural damage of units with the functional performance of the highway network in high-intensity seismic region. Bayesian updating allows the posterior probability of segments and origin–destination pairs to be computed, providing an online evaluation of the functional performance of the highway network. The identification of critical units at each stage enables seismic reinforcement priority, thus contributing to the rehabilitation on connectivity reliability of network system.</p></div>","PeriodicalId":100791,"journal":{"name":"Journal of Infrastructure Intelligence and Resilience","volume":"1 2","pages":"Article 100006"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2772991522000068/pdfft?md5=be55827b511115c726fe2fafd3a4eff9&pid=1-s2.0-S2772991522000068-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85596146","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: 5

Computer vision-based generating and updating of the public transit bus stop inventories 基于计算机视觉的公交站点清单生成与更新

Journal of Infrastructure Intelligence and Resilience Pub Date : 2022-12-01 DOI: 10.1016/j.iintel.2022.100016

Seyed Masoud Shameli , Ehsan Rezazadeh Azar

{"title":"Computer vision-based generating and updating of the public transit bus stop inventories","authors":"Seyed Masoud Shameli , Ehsan Rezazadeh Azar","doi":"10.1016/j.iintel.2022.100016","DOIUrl":"10.1016/j.iintel.2022.100016","url":null,"abstract":"<div><p>An updated asset inventory enables public transit agencies to make informed decisions on the maintenance and improvement of their physical assets. Conventional asset inventory surveys mainly rely on manual site visits and subsequent analysis, which are time consuming and expensive. Many research projects developed methods to automate condition assessment of civil infrastructure assets, such as road surfaces, structures, and sewage systems; however, research on the automated detection and condition assessment of public transit infrastructure is very limited. This research aims to contribute to addressing this gap by introducing an automated computer vision-based system to detect main assets in transit bus stops and update asset inventories using video frames captured by on-board cameras on operating buses. This system uses existing hardware systems on public buses to gather required data and then uses Deep Convolutional Neural Networks (DCNNs) to recognize public transit assets. In addition, a related method was proposed to process manually collected images for semi-automated asset inventory updating. The experimental results showed more than 95% detection rates in videos, which demonstrate potentials for practical applications.</p></div>","PeriodicalId":100791,"journal":{"name":"Journal of Infrastructure Intelligence and Resilience","volume":"1 2","pages":"Article 100016"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2772991522000160/pdfft?md5=aa343d14b03a169b1ecf025217d0f517&pid=1-s2.0-S2772991522000160-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81977586","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: 1

inside back cover: using Editorial Board page 内封底:使用编委会页面

Journal of Infrastructure Intelligence and Resilience Pub Date : 2022-12-01 DOI: 10.1016/S2772-9915(22)00022-6

引用次数: 0

Hybrid method for full-field response estimation using sparse measurement data based on inverse analysis and static condensation 基于逆分析和静态凝聚的稀疏测量数据全场响应估计混合方法

Journal of Infrastructure Intelligence and Resilience Pub Date : 2022-12-01 DOI: 10.1016/j.iintel.2022.100017

Ashish Pal , Wei Meng , Satish Nagarajaiah

{"title":"Hybrid method for full-field response estimation using sparse measurement data based on inverse analysis and static condensation","authors":"Ashish Pal , Wei Meng , Satish Nagarajaiah","doi":"10.1016/j.iintel.2022.100017","DOIUrl":"10.1016/j.iintel.2022.100017","url":null,"abstract":"<div><p>In structural health monitoring, measuring the accurate and spatially dense response near critical locations of the structure can be advantageous to estimate damage to the structure. Due to several physical restrictions or limitations of the sensing method, it may not always be possible to generate reliable data at critical locations. In this study, a hybrid method is presented that makes use of the measured displacement data and finite element (FE) model of the structure to predict dense full-field response. The presented method can incorporate unknown boundary conditions and unknown body forces by applying correction/fictitious forces to match predicted and measured responses. Using static condensation followed by inverse analysis, these additional forces are found by setting up a least square problem. Due to the problem being ill-posed, L2-penalty is used to control the prediction error. Numerical simulation of a plate subjected to body force showed an accurate prediction of full-field response except for a few boundary locations. To handle this, the proposed method is used in conjunction with linear interpolation near boundary locations. The method is validated in a laboratory experiment for a plate with a notch having displacement measured using Digital Image Correlation (DIC). On comparing strains calculated using predicted displacements, FEM, and DIC, the predicted strains show better agreement with the FEM than DIC. This affirms that the proposed hybrid technique can be used at critical locations where DIC fails to provide reliable strain data.</p></div>","PeriodicalId":100791,"journal":{"name":"Journal of Infrastructure Intelligence and Resilience","volume":"1 2","pages":"Article 100017"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2772991522000172/pdfft?md5=6d2c7c1ccddc77065298632ddb539c7c&pid=1-s2.0-S2772991522000172-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80286328","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

A computer vision-based method to identify the international roughness index of highway pavements 基于计算机视觉的公路路面国际粗糙度指数识别方法

Journal of Infrastructure Intelligence and Resilience Pub Date : 2022-09-01 DOI: 10.1016/j.iintel.2022.100004

Jiangyu Zeng, Mustafa Gül, Qipei Mei

{"title":"A computer vision-based method to identify the international roughness index of highway pavements","authors":"Jiangyu Zeng, Mustafa Gül, Qipei Mei","doi":"10.1016/j.iintel.2022.100004","DOIUrl":"10.1016/j.iintel.2022.100004","url":null,"abstract":"<div><p>The International Roughness Index (IRI) is one of the most critical parameters in the field of pavement performance management. Traditional methods for the measurement of IRI rely on expensive instrumented vehicles and well-trained professionals. The equipment and labor costs of traditional measurement methods limit the timely updates of IRI on the pavements. In this article, a novel imaging-based Deep Neural Network (DNN) model, which can use pavement photos to directly identify the IRI values, is proposed. This model proved that it is possible to use 2-dimensional (2D) images to identify the IRI other than the typically used vertical accelerations or 3-dimensional (3D) images. Due to the fast growth in photography equipment, small and convenient sports action cameras such as the GoPro Hero series are able to capture smooth videos at a high framerate with built-in electronic image stabilization systems. These significant improvements make it not only more convenient to collect high-quality 2D images, but also easier to process them than vibrations or accelerations. In the proposed method, 15% of the imaging data were randomly selected for testing and had never been touched during the training steps. The testing results showed an averaged coefficient of determination (R square) of 0.6728 and an averaged root mean square error (RMSE) of 0.50.</p></div>","PeriodicalId":100791,"journal":{"name":"Journal of Infrastructure Intelligence and Resilience","volume":"1 1","pages":"Article 100004"},"PeriodicalIF":0.0,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2772991522000044/pdfft?md5=3d6f5ea84c6810cd18a9880bf91b4461&pid=1-s2.0-S2772991522000044-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89419075","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: 4

Resilience and sustainability for educational buildings 教育建筑的弹性和可持续性

Journal of Infrastructure Intelligence and Resilience Pub Date : 2022-09-01 DOI: 10.1016/j.iintel.2022.100005

Fabio Casciati, Sara Casciati, Lucia Faravelli

引用次数: 1

Rayleigh scattering based, thermal-induced displacement measurement along a steel plate at high temperature 基于瑞利散射的高温下沿钢板热致位移测量

Journal of Infrastructure Intelligence and Resilience Pub Date : 2022-09-01 DOI: 10.1016/j.iintel.2022.100002

Yanping Zhu, Genda Chen

{"title":"Rayleigh scattering based, thermal-induced displacement measurement along a steel plate at high temperature","authors":"Yanping Zhu, Genda Chen","doi":"10.1016/j.iintel.2022.100002","DOIUrl":"10.1016/j.iintel.2022.100002","url":null,"abstract":"<div><p>This study aims to quantify Rayleigh scattering based measurement accuracy of distributed fiber optic sensors under a heating-holding load protocol and characterize the effect of polymer coating on the sensors as the polymer softens and melts away at elevated temperatures. Two segments of a coated single-mode optical fiber were loosely attached and firmly bonded to a steel plate, respectively. When locally heated up to 405 <span><math><mo>°</mo><mtext>C</mtext></math></span> in a furnace, the two segments were used to measure temperature alone and thermal-induced strain. The axial displacement associated with the strain measurement was compared with that of a dial gauge. A temperature increment of 13 °C (≪ 20 °C) is recommended to ensure successful correlation analysis of Rayleigh scattering signals. The polymer was found to start softening at 155 <span><math><mrow><mo>°</mo><mtext>C</mtext></mrow></math></span> and melting at 267 °C. As temperature sensors, optical fibers with an insulation sheath can accurately measure temperature untill 155 °C without and till 267 °C with thermo-mechanical analysis of sheath-fiber bonding behavior. As strain sensors, optical fibers with temperature compensation are accurate for strain measurement up to 155 °C, above which strain transfer analysis is required due to softening of the fiber coating. Under a large temperature gradient covering 155–267 °C, the fibers attached on steel plates with epoxy function like an extensometer as a center portion of the coating with the high-end temperature is melted as verified by microscopic analysis.</p></div>","PeriodicalId":100791,"journal":{"name":"Journal of Infrastructure Intelligence and Resilience","volume":"1 1","pages":"Article 100002"},"PeriodicalIF":0.0,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2772991522000020/pdfft?md5=a2ce9f274b3adf0934ba96857e7ed327&pid=1-s2.0-S2772991522000020-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79116465","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: 1

inside back cover: using Editorial Board page 内封底:使用编委会页面

Journal of Infrastructure Intelligence and Resilience Pub Date : 2022-09-01 DOI: 10.1016/j.iintel.2022.100014

引用次数: 0

Letter from Editors-in-Chief 总编辑的来信

Journal of Infrastructure Intelligence and Resilience Pub Date : 2022-09-01 DOI: 10.1016/j.iintel.2022.100007

Yaozhi Luo, Michael Havbro Faber, Yi-Qing Ni, Andrew W. Smyth

引用次数: 0

Defect-mode-induced energy localization/harvesting of a locally resonant phononic crystal plate: Analysis of line defects 局部共振声子晶体板的缺陷模式诱导能量局域化/收获:线缺陷分析

Journal of Infrastructure Intelligence and Resilience Pub Date : 2022-09-01 DOI: 10.1016/j.iintel.2022.100001

Dong-Xing Cao , Sha-Sha Li , Chang-Hai Zhan , Yi-Ming Lu , Jia-Jia Mao , Siu-Kai Lai

{"title":"Defect-mode-induced energy localization/harvesting of a locally resonant phononic crystal plate: Analysis of line defects","authors":"Dong-Xing Cao , Sha-Sha Li , Chang-Hai Zhan , Yi-Ming Lu , Jia-Jia Mao , Siu-Kai Lai","doi":"10.1016/j.iintel.2022.100001","DOIUrl":"10.1016/j.iintel.2022.100001","url":null,"abstract":"<div><p>Phononic crystals that are artificially engineered structures have recently been introduced for vibration energy harvesting and sensing applications due to their unique features of band gaps and wave propagation control. Conventional energy harvesters made of phononic crystals are mainly designed for acoustic energy harvesting at a high-frequency vibration source (i.e., kHz levels). In this work, a defect-mode-induced energy harvester is designed for low-frequency excitations in the range of 0–300 Hz. The entire system that is a locally resonant phononic crystal (LRPC) plate with line defect patterns is consisted of elastic-wrapped core scatterers periodically embedded in epoxy resin. A two-dimensional (2D) three-component unit cell structure is arranged on the plate and the band gap property is analyzed to optimize the geometric parameters. Defects are then introduced to the LRPC plate with a 7 × 7 point array for analysis. In addition, numerical and experimental studies are conducted to investigate the performance of energy harvesting when attaching a piezoelectric patch on the defect points. The results demonstrate that the proposed LRPC vibration energy harvester having a line defect mode (with continuous or alternate points) shows good performance in energy harvesting, in which a peak power output of 42.72 mV can be achieved under 10 m/s<sup>2</sup> and 252 Hz. The performance is almost 6 times more than that of the single-point defect model under the same excitation conditions. The present LRPC-type energy harvester with a line defect mode is more suitable for energy harvesting for low-frequency and broadband conditions.</p></div>","PeriodicalId":100791,"journal":{"name":"Journal of Infrastructure Intelligence and Resilience","volume":"1 1","pages":"Article 100001"},"PeriodicalIF":0.0,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2772991522000019/pdfft?md5=b938ae73514bc4239591024bf8ace575&pid=1-s2.0-S2772991522000019-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81830318","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: 2