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Infrastructures, Volume 9, Issue 2 (February 2024) – 19 articles

Cover Story (view full-size image): Research on roller-compacted concrete (RCC) pavements focuses on their progressive deterioration influenced by vehicular loads and ambient factors such as relative humidity and temperature, which vary with geographic location. This study examines the effect of drying shrinkage under vehicular loads using a computational model calibrated with typical ambient conditions. Laboratory experiments and numerical modeling were conducted, and statistical analyses validated these results. The importance of considering ambient effects in the structural design of pavements is highlighted, demonstrating that these can alter pavement stresses by up to 10% and underlining the significance of the proposed models for predicting the durability and performance of RCC pavements. View this paper
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29 pages, 6655 KiB  
Article
Development of a Network-Level Road Safety Assessment Procedure Based on Human Factors Principles
by Andrea Paliotto and Monica Meocci
Infrastructures 2024, 9(2), 35; https://doi.org/10.3390/infrastructures9020035 - 16 Feb 2024
Cited by 1 | Viewed by 2229
Abstract
Road safety is a central issue in the management and development of a road network. Road agencies must try to identify the most dangerous sections of their network and act on them to improve safety. The most used procedure for this purpose is [...] Read more.
Road safety is a central issue in the management and development of a road network. Road agencies must try to identify the most dangerous sections of their network and act on them to improve safety. The most used procedure for this purpose is about considering the indicators based on crashes. However, a mature road safety management system must be able to assess the safety of a road section before accidents occur. The European community is moving in this direction with the update of Directive 2008/96/EC (Directive 1936/2019). This paper proposes a new methodology for carrying out a network-wide road safety assessment on rural single-carriageways and two-lane two-way roads. This procedure accounts for the influence of road characteristics on drivers’ perceptions. The methodology has been developed based on the human factors concepts from PIARC, and it includes a series of checklists that guide an inspector in carrying out a visual inspection of single-carriageway roads. The results from the checklist are then processed into an algorithm, and the level of risk in the analyzed section is provided. The objectives of the procedure are (a) to account for the perceptive aspects that are one of the major causes of road accidents, (b) to provide a proactive procedure in line with the requirements of the European Directive, and (c) to provide a useful instrument that can be easily implemented by road agencies and integrated with other analysis procedures. The procedure has been applied and tested on a case study of six different stretches of two-lane, two-way rural highways in Italy, Germany, and Slovenia (about 65 km). The results show a high degree of concordance with a risk classification based on the accident rate, mainly considering high-risk sections. Therefore, the procedure demonstrated its potential to be a useful instrument to be included in network safety assessments. Road agencies should consider the use of this procedure in their network safety analysis and ranking. Full article
(This article belongs to the Special Issue Road Systems and Engineering)
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<p>Conceptual scheme of the procedure.</p>
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<p>Example of PCL identification: PCLs of the road SR2 stretch. The numbers in brackets are the number of each PCL of that type along the stretch.</p>
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<p>Example of EXSE identification on the road SR2 stretch.</p>
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<p>Scheme of the CHT and HFES definition process.</p>
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<p>Merging of overlapping CHTs and identification of HFESs.</p>
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<p>Example of NAS composition: light blue and red lines identify HFESs in the ascending direction and descending direction, respectively (considering the Km posts). The green line is the road track.</p>
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<p>Example and format of NAS final Risk Code (RC).</p>
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<p>Satellite view of the different roads.</p>
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<p>Distribution and linear correlation between values assigned to the RC and accident rate values.</p>
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<p>Distribution and linear correlation between values assigned to the RC and accident rate values averaged within each RC.</p>
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<p>Graphical representation of the risk level obtained for each NAS for each different NAS segmentation, road SR2.</p>
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<p>Graphical representation of the risk level obtained for each NAS for each different NAS segmentation, road B38.</p>
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20 pages, 25029 KiB  
Article
Asphalt Pavement Damage Detection through Deep Learning Technique and Cost-Effective Equipment: A Case Study in Urban Roads Crossed by Tramway Lines
by Marco Guerrieri, Giuseppe Parla, Masoud Khanmohamadi and Larysa Neduzha
Infrastructures 2024, 9(2), 34; https://doi.org/10.3390/infrastructures9020034 - 16 Feb 2024
Cited by 8 | Viewed by 3735
Abstract
Asphalt pavements are subject to regular inspection and maintenance activities over time. Many techniques have been suggested to evaluate pavement surface conditions, but most of these are either labour-intensive tasks or require costly instruments. This article describes a robust intelligent pavement distress inspection [...] Read more.
Asphalt pavements are subject to regular inspection and maintenance activities over time. Many techniques have been suggested to evaluate pavement surface conditions, but most of these are either labour-intensive tasks or require costly instruments. This article describes a robust intelligent pavement distress inspection system that uses cost-effective equipment and the ‘you only look once’ detection algorithm (YOLOv3). A dataset for flexible pavement distress detection with around 13,135 images and 30,989 bounding boxes of damage was used during the neural network training, calibration, and validation phases. During the testing phase, the model achieved a mean average precision of up to 80%, depending on the type of pavement distress. The performance metrics (loss, precision, recall, and RMSE) that were applied to estimate the object detection accuracy demonstrate that the technique can distinguish between different types of asphalt pavement damage with remarkable accuracy and precision. Moreover, the confusion matrix obtained in the validation process shows a distress classification sensitivity of up to 98.7%. The suggested technique was successfully implemented in an inspection car. Measurements conducted on urban roads crossed by tramway lines in the city of Palermo proved the real-time ability and great efficacy of the detection system, with potentially remarkable advances in asphalt pavement examination efficacy due to the high rates of correct distress detection. Full article
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<p>Pavement distress types.</p>
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<p>Examples of distress [<a href="#B1-infrastructures-09-00034" class="html-bibr">1</a>,<a href="#B2-infrastructures-09-00034" class="html-bibr">2</a>,<a href="#B3-infrastructures-09-00034" class="html-bibr">3</a>,<a href="#B4-infrastructures-09-00034" class="html-bibr">4</a>,<a href="#B5-infrastructures-09-00034" class="html-bibr">5</a>,<a href="#B6-infrastructures-09-00034" class="html-bibr">6</a>,<a href="#B7-infrastructures-09-00034" class="html-bibr">7</a>].</p>
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<p>Image analysis method.</p>
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<p>One-stage and two-stage pavement distress detection flows: (<b>a</b>) two-stage distress detection; (<b>b</b>) one-stage distress detection.</p>
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<p>YOLOv3 network structure (adapted from [<a href="#B21-infrastructures-09-00034" class="html-bibr">21</a>]).</p>
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<p>Darknet-53 architecture ([<a href="#B24-infrastructures-09-00034" class="html-bibr">24</a>]).</p>
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<p>IoU determination.</p>
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<p>Location prediction in a bounding box (adapted from [<a href="#B28-infrastructures-09-00034" class="html-bibr">28</a>]).</p>
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<p>Survey vehicle.</p>
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<p>Some phases of camera calibration.</p>
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<p>Camera parameter representation.</p>
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<p>An example of distress annotation.</p>
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<p>(<b>a</b>) Sample of images used for different types of damage; (<b>b</b>) object size variance across classes.</p>
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<p>Base learning rate related to the number of iterations.</p>
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<p>Loss related to the number of iterations.</p>
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<p>RMSE related to the number of iterations.</p>
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<p>Precision–recall curves for six types of pavement damage (cf. <a href="#infrastructures-09-00034-t004" class="html-table">Table 4</a>).</p>
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<p>Confusion matrix (zero values omitted for clarity). The diagonal shows the true positive values for each class (i.e., those labelled and classified as that class).</p>
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<p>The IPM method used in this research.</p>
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<p>Algorithm for tracking pavement distress.</p>
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<p>Tramway track details: (<b>a</b>) ballasted track and (<b>b</b>) slab track.</p>
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<p>Construction phases of the tramway track on the analysed urban roads. (<b>a</b>) casting of a lean concrete layer and curb construction; (<b>b</b>) laying of steel reinforcement bars; (<b>c</b>) laying of the flat framework; (<b>d</b>) casting of the concrete slab and paving.</p>
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<p>Photos of the analysed road pavement (via Antonio Laudicina)—class E tramway line.</p>
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<p>Photos of the analysed road pavement (via Carlo Gulì)—class B tramway line.</p>
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<p>Examples of damage detection and surface estimation.</p>
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<p>Examples of damage detection and surface estimation.</p>
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<p>The correct detection rate for a sample of ten clips.</p>
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25 pages, 5983 KiB  
Article
Investigation of Subgrade Stabilization Life-Extending Benefits in Flexible Pavements Using a Non-Linear Mechanistic-Empirical Analysis
by Ali Reza Ghanizadeh, Mandana Salehi, Anna Mamou, Evangelos I. Koutras, Farhang Jalali and Panagiotis G. Asteris
Infrastructures 2024, 9(2), 33; https://doi.org/10.3390/infrastructures9020033 - 14 Feb 2024
Cited by 6 | Viewed by 3428
Abstract
This paper investigates the effect of subgrade soil stabilization on the performance and life extension of flexible pavements. Several variables affecting soil stabilization were considered, including subgrade soil type (CL or CH), additive type and content (3, 6, and 9% of hydrated lime, [...] Read more.
This paper investigates the effect of subgrade soil stabilization on the performance and life extension of flexible pavements. Several variables affecting soil stabilization were considered, including subgrade soil type (CL or CH), additive type and content (3, 6, and 9% of hydrated lime, 5, 10, and 15% of class C fly ash (CFA), and 5, 10, and 15% of cement kiln dust (CKD)), three stabilization thicknesses (15, 30, and 45 cm), and four pavement sections with varying thicknesses. The effects of these variables were investigated using four different damage mechanisms, including the fatigue life of the asphalt concrete (AC) and stabilized subgrade layers, the crushing life of the stabilized subgrade soil, and the rutting life of the pavement, using a non-linear mechanistic-empirical methodology. The results suggest that the optimum percentage that maximizes the pavement life occurs at 3% of lime for subgrade soil type CL, 6% of lime for subgrade type CH, and 15% of CFA and CKD for both subgrade soil types. The maximum pavement life increase occurred in the section with the lowest thickness and the highest stabilization thickness, which was 1890% for 3% of lime in the CL subgrade and 568% for 6% of lime in the CH subgrade. The maximum increase in the pavement life of subgrade stabilization with 15% of CFA was 2048% in a CL subgrade, and 397% in a CH subgrade, and life extension due to subgrade stabilization with 15% of CKD was 2323% in a CL subgrade and 797% in a CH subgrade. Full article
(This article belongs to the Section Smart Infrastructures)
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<p>NonPAS procedure for non-linear analysis of flexible pavements.</p>
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<p>Pavement cross-sections in this study.</p>
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<p>Shift factor for the effective fatigue life of cemented material [<a href="#B60-infrastructures-09-00033" class="html-bibr">60</a>].</p>
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<p>Stress and response locations in pavement non-linear analysis.</p>
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<p>Percentage increase in fatigue life for CL type subgrade, depending on the type and content of additives and for three thicknesses of stabilization (15, 30, and 45 cm).</p>
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<p>Percentage increase in fatigue life for CH type subgrade, depending on the type and content of additives and for three thicknesses of stabilization (15, 30, and 45 cm).</p>
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<p>Percentage increase in rutting life for CL type subgrade, depending on the type and content of additives and for three thicknesses of stabilization (15, 30, and 45 cm).</p>
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<p>Percentage increase in rutting life for CH type subgrade, depending on the type and content of additives and for three thicknesses of stabilization (15, 30, and 45 cm).</p>
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<p>The <span class="html-italic">N<sub>f</sub></span> of the stabilized layer for CL type subgrade in different sections, depending on the type and content of additives and for three thicknesses of stabilization (15, 30, and 45 cm).</p>
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<p>The <span class="html-italic">N<sub>f</sub></span> of the stabilized layer for CH type subgrade in different sections, depending on the type and content of additives and for three thicknesses of stabilization (15, 30, and 45 cm).</p>
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22 pages, 11072 KiB  
Article
Contribution to Rail System Revitalization, Development, and Integration Projects Evaluation: A Case Study of the Zadar Urban Area
by Maja Ahac, Saša Ahac, Igor Majstorović and Željko Stepan
Infrastructures 2024, 9(2), 32; https://doi.org/10.3390/infrastructures9020032 - 13 Feb 2024
Cited by 1 | Viewed by 2311
Abstract
This paper aims to contribute to the process of evaluating urban rail infrastructure projects through the presentation of the methodology and the results of a preliminary feasibility study concerning the revitalization, development, and (re)integration of the rail with road, maritime, and air transportation [...] Read more.
This paper aims to contribute to the process of evaluating urban rail infrastructure projects through the presentation of the methodology and the results of a preliminary feasibility study concerning the revitalization, development, and (re)integration of the rail with road, maritime, and air transportation in the Zadar urban area. The analysis included the identification and evaluation of rail infrastructure alignment variants that would ensure the revitalization of the existing railway infrastructure, relocation of freight rail traffic from the narrow and densely developed suburban coastal area, promotion of intermodal passenger and freight transportation, improvement of urban and regional accessibility and connectivity, increase of traffic safety, reduction of travel time and operating costs, and decrease of traffic impacts on the environment. By consulting legal frameworks, spatial planning documentation, and analyzing the socio-economic context and existing transportation infrastructure function, six variants for the (re)development of the rail infrastructure were designed. As their design approached the area’s transportation issues from different angles and could contribute differently to the area’s economic, social, and territorial issues, a multi-criteria analysis supplemented with a partial cost–benefit analysis was conducted to select the most suitable variant. The evaluation was based on seven weighted criteria quantified by the normalization of 32 indicator values, scored from 1 to 5, where a score of 5 was considered the highest. Weighting the scores according to the ratios determined through a consultation process with stakeholders resulted in ranking the best variant with a total score of 3.7 and the worst one with a total score of 2.6. To avoid potential objections that the set of criteria weights used was subjective and the result biased, a sensitivity analysis was carried out by systematically varying the weights among criteria. The results showed that the best-ranked variant was also the least sensitive to applied weight shifts, with a score range of 0.2. Full article
(This article belongs to the Special Issue Sustainable Infrastructures for Urban Mobility)
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<p>Investigation methodology.</p>
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<p>ZUA transportation infrastructure [<a href="#B2-infrastructures-09-00032" class="html-bibr">2</a>].</p>
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<p>Annual volume of passengers in thousands of passengers based on transportation mode, plotted by the authors according to the data given in [<a href="#B23-infrastructures-09-00032" class="html-bibr">23</a>,<a href="#B27-infrastructures-09-00032" class="html-bibr">27</a>,<a href="#B28-infrastructures-09-00032" class="html-bibr">28</a>].</p>
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<p>Annual cargo volume in thousands of tons based on transportation mode, plotted by the authors according to the data given in [<a href="#B23-infrastructures-09-00032" class="html-bibr">23</a>,<a href="#B27-infrastructures-09-00032" class="html-bibr">27</a>,<a href="#B28-infrastructures-09-00032" class="html-bibr">28</a>].</p>
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<p>Modal split based on population age structure, plotted by the authors according to the data given in [<a href="#B29-infrastructures-09-00032" class="html-bibr">29</a>].</p>
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<p>One-way door-to-door travel time in minutes outside of and during the tourist season, plotted by the authors according to the data given in [<a href="#B29-infrastructures-09-00032" class="html-bibr">29</a>].</p>
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<p>Planned infrastructure development in ZUA [<a href="#B2-infrastructures-09-00032" class="html-bibr">2</a>].</p>
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<p>Horizontal alignment of six proposed variants of railway routes in ZUA, Phase I shown in blue, Phase II shown in red, Phase III shown in orange, and Phase IV shown in green: (<b>a</b>) Variant 1; (<b>b</b>) Variant 2; (<b>c</b>) Variant 3; (<b>d</b>) Variant 4; (<b>e</b>) Variant 5; (<b>f</b>) Variant 6 [<a href="#B2-infrastructures-09-00032" class="html-bibr">2</a>].</p>
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<p>Cost criterium indicator values.</p>
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<p>Environment criterium indicator values.</p>
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<p>Institutional analysis criterium indicator values.</p>
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13 pages, 3940 KiB  
Article
A Method for Measuring the Mass of a Railroad Car Using an Artificial Neural Network
by Mark A. Denisenko, Alina S. Isaeva, Alexander S. Sinyukin and Andrey V. Kovalev
Infrastructures 2024, 9(2), 31; https://doi.org/10.3390/infrastructures9020031 - 10 Feb 2024
Cited by 1 | Viewed by 2263
Abstract
The fast, convenient, and accurate determination of railroad cars’ load mass is critical to ensure safety and allow asset counting in railway infrastructure. In this paper, we propose a method for modeling the mechanical deformations that occur in the rail web under the [...] Read more.
The fast, convenient, and accurate determination of railroad cars’ load mass is critical to ensure safety and allow asset counting in railway infrastructure. In this paper, we propose a method for modeling the mechanical deformations that occur in the rail web under the influence of a static load transmitted through a railway wheel. According to the proposed method, a railroad car’s weight can be determined from the rail deformation values. A solid model of a track section, including a railroad tie, rail, and wheel, is developed, and a multi-physics simulation technique that allows for the determination of the values of deformations and mechanical stresses in the strain gauge installation areas is presented. The influence of the loaded mass, the temperature of the rail, and the wheel position relative to the strain gauge location is considered. We also consider the possibility of using artificial neural networks to determine railroad cars’ weight without specifying the coordinates of the wheel position. The effect of noise in the data on the accuracy of determining the railroad car weight is considered. Full article
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<p>Solid-state model for simulation of the static loads that occur on the rail under the influence of the railroad car weight. (<b>a</b>) Solid-state model of an R50-type rail and a solid-rolled railway wheel. (<b>b</b>) Shape of the contact patch.</p>
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<p>Sketch of the proposed model: 1. The first point of strain gauge attachment; 2. The second point of strain gauge attachment; 3. The third point of strain gauge attachment; 4. The fourth point of strain gauge attachment.</p>
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<p>Scheme of the used neural network applied for load mass determination.</p>
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<p>Deformation at the measurement point versus coordinates for different masses and temperatures. (<b>a</b>) Dependences of rail deformations for deformation measurement points 1 and 4 on the loaded mass and the coordinates at a rail temperature of 22 °C. (<b>b</b>) Dependences of rail deformations for deformation measurement points 1 and 4 on the loaded mass and the coordinates at a rail temperature of 50 °C. (<b>c</b>) Dependences of rail deformations for deformation measurement points 1 and 4 on the loaded mass and the coordinates at a rail temperature of −20 °C. (<b>d</b>) Influence of rail temperature on the amount of deformation at deformation measurement point 4.</p>
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<p>Dependences of the test data classification accuracy by a neural network on the noise level with (blue) and without (red) taking into account the temperature of the rail.</p>
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<p>Confusion matrix of the network trained on test data for a noise value of 0.1%.</p>
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<p>Confusion matrix of the network trained on test data for a noise value of 1%.</p>
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<p>Confusion matrix of the network trained on test data for a noise value of 10%.</p>
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16 pages, 766 KiB  
Article
Lessons from Bridge Structural Health Monitoring (SHM) and Their Implications for the Development of Cyber-Physical Systems
by Emin Aktan, Ivan Bartoli, Branko Glišić and Carlo Rainieri
Infrastructures 2024, 9(2), 30; https://doi.org/10.3390/infrastructures9020030 - 7 Feb 2024
Cited by 8 | Viewed by 5082
Abstract
This paper summarizes the lessons learned after several decades of exploring and applying Structural Health Monitoring (SHM) in operating bridge structures. The challenges in real-time imaging and processing of large amounts of sensor data at various bandwidths, synchronization, quality check and archival, and [...] Read more.
This paper summarizes the lessons learned after several decades of exploring and applying Structural Health Monitoring (SHM) in operating bridge structures. The challenges in real-time imaging and processing of large amounts of sensor data at various bandwidths, synchronization, quality check and archival, and most importantly, the interpretation of the structural condition, performance, and health are necessary for effective applications of SHM to major bridges and other infrastructures. Writers note that such SHM applications have served as the forerunners of cyber infrastructures, which are now recognized as the key to smart infrastructures and smart cities. Continued explorations of SHM in conjunction with control, therefore, remain vital for assuring satisfactory infrastructure system performance at the operational, damageability, and safety limit-states in the future. Researchers in the SHM of actually constructed systems, given their experience in monitoring major structures in the field, are well positioned to contribute to these vital needs. Especially, SHM researchers who have learned how to integrate the contributions from various disciplines such as civil, electrical, mechanical, and materials engineering; computer and social sciences; and architecture and urban planning would appear to be well equipped and could become instrumental in assessing the health and performance of urban regions, which today must function by optimizing and balancing the needs of Livability, Sustainability, and Resilience (LSR). Full article
(This article belongs to the Special Issue Advances in Structural Health Monitoring of the Built Environment)
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<p>Principal SHM activities [<a href="#B31-infrastructures-09-00030" class="html-bibr">31</a>].</p>
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<p>Cyber-Physical Systems [<a href="#B60-infrastructures-09-00030" class="html-bibr">60</a>].</p>
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13 pages, 7907 KiB  
Article
Fatigue Characteristics of Steel–Concrete Composite Beams
by Ayman El-Zohairy, Hani Salim, Hesham Shaaban and Mahmoud T. Nawar
Infrastructures 2024, 9(2), 29; https://doi.org/10.3390/infrastructures9020029 - 4 Feb 2024
Cited by 1 | Viewed by 2257
Abstract
Fatigue in steel–concrete composite beams can result from cyclic loading, causing stress fluctuations that may lead to cumulative damage and eventual failure over an extended period. In this paper, the experimental findings from fatigue loading tests on composite beams with various arrangements are [...] Read more.
Fatigue in steel–concrete composite beams can result from cyclic loading, causing stress fluctuations that may lead to cumulative damage and eventual failure over an extended period. In this paper, the experimental findings from fatigue loading tests on composite beams with various arrangements are presented. Fatigue tests were performed up to 1,000,000 cycles using four-point loading, encompassing various ranges of shear stress at a consistent amplitude. Additionally, the effects of external post-tensioning and the strength of the shear connection were investigated. Static tests were run until failure to assess the enduring strength of the specimens subjected to fatigue. The cyclic mid-span deflections, slippages, and strains were measured during the testing. Based on the experimental findings, it was found that the damage region that the shear studs caused in the concrete slab, which resulted in a reduction in stiffness within the shear connection, grew as the loading cycles increased, leading to an increase in residual deflections and plastic slippages. Controlling the longitudinal fatigue cracks in the concrete slab was largely dependent on the strength of the shear connection between the steel beams and concrete slabs. Moreover, the applied fatigue loading range affected the propagation and distribution of fatigue cracks in the concrete slab. The strains in different parts of the composite specimens were significantly reduced by applying the external post-tensioning. With no signs of distress at the anchors, the tendons displayed excellent fatigue performance. Full article
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<p>Dimensions of the composite specimens (mm). (<b>a</b>) Specimens RSB 1, FSB 2 and FSB 3. (<b>b</b>) Specimen FSB 4. (<b>c</b>) Specimen FSB 5. (<b>d</b>) Specimens PRSB 6 and FPSB 7.</p>
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<p>Dimensions of the composite specimens (mm). (<b>a</b>) Specimens RSB 1, FSB 2 and FSB 3. (<b>b</b>) Specimen FSB 4. (<b>c</b>) Specimen FSB 5. (<b>d</b>) Specimens PRSB 6 and FPSB 7.</p>
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<p>Post-tensioning system. (<b>a</b>) Schematic layout. (<b>b</b>) On-site photo.</p>
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<p>Test setup (mm). (<b>a</b>) Fatigue test. (<b>b</b>) Static test.</p>
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<p>Instrumentations. (<b>a</b>) Strain gauges and LVDTs layout. (<b>b</b>) Slippage LVDT and post-tensioning load cells. (<b>c</b>) Shear stud’s strain gauges.</p>
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<p>Development and dispersion of fatigue cracks in the concrete slabs (cycle counts are displayed in thousands). (<b>a</b>) Specimen FSB 2. (<b>b</b>) Specimen FSB 3. (<b>c</b>) Specimen FSB 4. (<b>d</b>) Specimen FSB 5. (<b>e</b>) Specimen PFSB 7.</p>
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<p>Development and dispersion of fatigue cracks in the concrete slabs (cycle counts are displayed in thousands). (<b>a</b>) Specimen FSB 2. (<b>b</b>) Specimen FSB 3. (<b>c</b>) Specimen FSB 4. (<b>d</b>) Specimen FSB 5. (<b>e</b>) Specimen PFSB 7.</p>
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<p>Cyclic deformations. (<b>a</b>) Cyclic deflection. (<b>b</b>) Cyclic slippage.</p>
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<p>Cyclic strains in the shear connectors.</p>
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<p>Cyclic strains in the concrete slabs and steel beams. (<b>a</b>) Concrete slab. (<b>b</b>) Steel beam.</p>
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<p>Fatigue variations in the post-tensioning force.</p>
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<p>Static residual deformations. (<b>a</b>) Residual deflection. (<b>b</b>) Residual slippage.</p>
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<p>Static residual strains in the extreme fibers of the composite sections. (<b>a</b>) Concrete slab. (<b>b</b>) Steel beam.</p>
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<p>Static residual post-tensioning force.</p>
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15 pages, 2231 KiB  
Article
Vehicle Driving Safety of Underground Interchanges Using a Driving Simulator and Data Mining Analysis
by Zhen Liu, Qifeng Yang, Anlue Wang and Xingyu Gu
Infrastructures 2024, 9(2), 28; https://doi.org/10.3390/infrastructures9020028 - 2 Feb 2024
Cited by 16 | Viewed by 2359
Abstract
In the process of driving in an underground interchange, drivers are faced with many challenges, such as being in a closed space, visual changes alternating between light and dark conditions, complex road conditions in the confluence section, and dense signage, which directly affect [...] Read more.
In the process of driving in an underground interchange, drivers are faced with many challenges, such as being in a closed space, visual changes alternating between light and dark conditions, complex road conditions in the confluence section, and dense signage, which directly affect the safety and comfort of drivers in an underground interchange. Thus, driving simulation, building information modeling (BIM), and data mining were used to analyze the impact of underground interchange safety facilities on driving safety and comfort. Acceleration disturbance and steering wheel comfort loss values were used to assist the comfort analysis. The CART algorithm, classification decision trees, and neural networks were used for data mining, which uses a dichotomous recursive partitioning technique where multiple layers of neurons are superimposed to fit and replace very complex nonlinear mapping relationships. Ten different scenarios were designed for comparison. Multiple linear regression combined with ANOVA was used to calculate the significance of the control variables for each scenario on the evaluation index. The results show that appropriately reducing the length of the deceleration section can improve driving comfort, setting reasonable reminder signs at the merge junction can improve driving safety, and an appropriate wall color can reduce speed oscillation. This study indicates that the placement of traffic safety facilities significantly influences the safety and comfort of driving in underground interchanges. This study may provide support for the optimization of the design of underground interchange construction and internal traffic safety facilities. Full article
(This article belongs to the Special Issue Recent Progress in Transportation Infrastructures)
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<p>Three-dimensional scene of UI: (<b>a</b>) 3D modeling and (<b>b</b>) driving simulation scenario.</p>
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<p>Driving scenario of test personnel in driving simulation experiment.</p>
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<p>Area division of underground interchange: (<b>a</b>) entrance, (<b>b</b>) DC1, (<b>c</b>) DC2, and (<b>d</b>) exit.</p>
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<p>CART analysis results of the entrance section.</p>
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<p>Prediction results of neural network under different entrance distances of entrance segment.</p>
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<p>CART analysis results: (<b>a</b>) <span class="html-italic">V</span> of DC1, (<b>b</b>) <span class="html-italic">a</span> of DC2, and (<b>c</b>) <span class="html-italic">V</span> of exit section.</p>
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11 pages, 3730 KiB  
Article
Sustainable Transportation Infrastructures in Iowa—Goals and Practices
by Hosin Lee, Byungkyu Moon and Jeongbeom Lee
Infrastructures 2024, 9(2), 27; https://doi.org/10.3390/infrastructures9020027 - 1 Feb 2024
Cited by 1 | Viewed by 2186
Abstract
The need to incorporate sustainability principles and practices is increasing for environmental and economic reasons. It is imperative to identify and operationalize sustainability strategies into core administrative, planning, design, construction, operational, and maintenance activities for the transportation infrastructure systems by integrating sustainability into [...] Read more.
The need to incorporate sustainability principles and practices is increasing for environmental and economic reasons. It is imperative to identify and operationalize sustainability strategies into core administrative, planning, design, construction, operational, and maintenance activities for the transportation infrastructure systems by integrating sustainability into decision-making processes. The primary goal of this study is to develop an implementation plan for achieving more sustainable transportation infrastructure systems in Iowa. This research aims to guide the adoption of sustainable strategies, balancing cost, performance, and environmental impact in transportation infrastructure development. This paper presents efforts to develop a methodology for identifying the best sustainable practices for implementation in transportation infrastructure practices in Iowa by surveying state DOTs to learn about their sustainability goals and practices, identifying existing sustainability attributes and sustainable practices, and developing a GIS database where construction, materials and performance data of sustainable practices can be stored and analyzed. Full article
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<p>Triple bottom line of sustainability [<a href="#B6-infrastructures-09-00027" class="html-bibr">6</a>].</p>
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<p>Users of infrastructure voluntary evaluation sustainability tool [<a href="#B5-infrastructures-09-00027" class="html-bibr">5</a>].</p>
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<p>Screenshot of DOSPIR on ArcGIS Pro.</p>
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<p>Illustration of asphalt pavement recycling and performance database.</p>
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<p>Illustration of high-friction surface treatment and crash database.</p>
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<p>Illustration of UHPC bridge and performance database.</p>
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<p>Illustration of roundabout and crash data analysis results.</p>
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24 pages, 21460 KiB  
Article
Strength and Deformation of Concrete-Encased Grouting-Filled Steel Tubes Columns Exposed to Monotonic Quasi-Static Loading Conditions
by Ahlam A. Abbood, Nazar Oukaili, Abbas A. Allawi and George Wardeh
Infrastructures 2024, 9(2), 26; https://doi.org/10.3390/infrastructures9020026 - 1 Feb 2024
Cited by 3 | Viewed by 2144
Abstract
This study aimed to evaluate the effectiveness of a novel concrete-encased column (CE) using small circular steel tubes filled with cementitious grouting material (GFST) as the primary reinforcement instead of traditional steel bars. The research involved three different types of reinforcement: conventional steel [...] Read more.
This study aimed to evaluate the effectiveness of a novel concrete-encased column (CE) using small circular steel tubes filled with cementitious grouting material (GFST) as the primary reinforcement instead of traditional steel bars. The research involved three different types of reinforcement: conventional steel bars, concrete-filled steel tubes with 30% of the reinforcement ratio of steel bars, and concrete-filled steel tubes with the same reinforcement ratio as steel bars. Twenty-four circular concrete columns were tested and categorized into six groups based on the type of reinforcement employed. Each group comprised four columns, with one subjected to concentric axial load, two subjected to eccentric axial load (with eccentricities of 25 mm and 50 mm, respectively), and one tested under lateral flexural loads. To validate the experimental results, finite element (FE) analysis was conducted using ABAQUS software version 6.14. The experimental findings for concentric load reveal that columns with the second type of reinforcement, concrete-filled steel tubes with 30% of the reinforcement ratio of steel bars exhibited a failure load 19% lower than those with steel bars, while columns with the third type of reinforcement, concrete-filled steel tubes with the same reinforcement ratio as steel bars achieved a failure load 17% greater than the traditional steel bars. The FE analysis demonstrates good agreement with the experimental outcomes in terms of ultimate strength, deformation, and failure modes. Full article
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<p>Cross-sections of CE-CFST columns [<a href="#B8-infrastructures-09-00026" class="html-bibr">8</a>].</p>
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<p>Schematic of cross-section dimensions and reinforcement details of tested specimens.</p>
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<p>Steel loading heads and saddles were used in the test.</p>
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<p>Typical test setup and instrumentation for (<b>a</b>) column specimen; (<b>b</b>) beam specimen.</p>
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<p>Typical test setup and instrumentation for (<b>a</b>) column specimen; (<b>b</b>) beam specimen.</p>
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<p>The mesh size of all parts of the tested specimen.</p>
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<p>FE boundary conditions and applied load were used in the analysis.</p>
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<p>Stress–strain curves of material (<b>a</b>) unconfined concrete in compression; (<b>b</b>) confined grouting material in compression; (<b>c</b>) concrete and grouting material in tension; (<b>d</b>) stress–strain for steel tube.</p>
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<p>Ultimate load of all tested specimens under various loading conditions.</p>
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<p>Effect of spiral spacing on ultimate load for specimens tested under various loading conditions.</p>
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<p>Experimental and numerical load–axial deformation curves of the concentric specimens.</p>
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<p>Experimental and numerical load–lateral deformation curves of eccentric specimens.</p>
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<p>Experimental and numerical load–deflection curves of flexural specimens.</p>
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<p>Ductility index of tested specimens under eccentric and flexural loads.</p>
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<p>Experimental and numerical failure mode of specimens under concentric load.</p>
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<p>Experimental and numerical failure mode of specimens under concentric load.</p>
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<p>Experimental and numerical failure mode of specimens under 25 mm eccentric load.</p>
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<p>Experimental and numerical failure mode of specimens under 25 mm eccentric load.</p>
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<p>Experimental and numerical failure mode of specimens under 50 mm eccentric load.</p>
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<p>Experimental and numerical failure mode of specimens under 50 mm eccentric load.</p>
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<p>Experimental and numerical failure mode of specimens under flexural load.</p>
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<p>Experimental and numerical failure mode of specimens under flexural load.</p>
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<p>Experimental and numerical strength interaction diagrams for the six groups.</p>
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<p>Experimental and numerical strength interaction diagrams for the six groups.</p>
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16 pages, 3364 KiB  
Article
Exploring the Efficacy of Amine-Free Anti-Stripping Agent in Improving Asphalt Characteristics
by Zaid Hazim Al-Saffar, Heja Ghazi Mohamed Hasan and Salam Ridha Oleiwi Aletba
Infrastructures 2024, 9(2), 25; https://doi.org/10.3390/infrastructures9020025 - 31 Jan 2024
Cited by 1 | Viewed by 2356
Abstract
This research addresses the significant challenge posed by early water damage in highway asphalt pavement, a critical concern affecting pavement service performance. To counteract this issue, the utilization of anti-stripping agents in asphalt is explored as a highly effective technical intervention. In this [...] Read more.
This research addresses the significant challenge posed by early water damage in highway asphalt pavement, a critical concern affecting pavement service performance. To counteract this issue, the utilization of anti-stripping agents in asphalt is explored as a highly effective technical intervention. In this investigation, a carefully selected amine-free additive was employed to modify the asphalt binder. A comprehensive array of physical and rheological tests, covering aspects such as storage stability, penetration, softening point, ductility, elastic recovery, rolling thin-film oven, retained penetration, the ductility of residue, and rotational viscometer assessments, were conducted to examine the multifaceted impact of the anti-stripping agent on the asphalt binder. Additionally, we assessed the asphalt mixture’s sensitivity to moisture through Marshall stability tests after conditioning for 40 min and 24 h, followed by an enhanced immersion test and moisture susceptibility measurement. The results reveal a nuanced interplay of chemical and physical mechanisms influencing the behavior of the asphalt binder. Notably, the incorporation of an anti-stripping agent at a concentration of 0.25–0.5% (by weight of asphalt binder) led to a substantial improvement in the tensile strength ratio (TSR) to 94.9%, a noteworthy enhancement compared to the 80.6% observed with virgin asphalt mixture. Furthermore, the retained stability index (RSI) exhibited a remarkable increase to 98.1%, surpassing the 87.6% recorded for virgin asphalt. This study not only provides crucial insights into the intricate dynamics of asphalt binder performance but also emphasizes the pivotal role of anti-stripping agents in augmenting the structural integrity and resilience of asphalt pavement. Full article
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<p>Equipment for conventional tests.</p>
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<p>Equipment for conventional tests.</p>
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<p>Penetration results of asphalt binders.</p>
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<p>Softening point of asphalt binder.</p>
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<p>Ductility results of asphalt binder.</p>
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<p>Rotational viscometer results.</p>
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<p>Marshall stability results after 40 min conditioning.</p>
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<p>Marshall stability after 24 h conditioning.</p>
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<p>ITS and TSR results.</p>
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22 pages, 2269 KiB  
Article
Identification and Ranking of Factors Affecting the Delay Risk of High-Rise Construction Projects Using AHP and VIKOR Methods
by Mehran Vahedi Nikbakht, Mohammad Gheibi, Hassan Montazeri, Reza Yeganeh Khaksar, Reza Moezzi and Amir Vadiee
Infrastructures 2024, 9(2), 24; https://doi.org/10.3390/infrastructures9020024 - 31 Jan 2024
Cited by 7 | Viewed by 3610
Abstract
Construction projects, especially those for commercial purposes, require thorough planning and control to ensure success within predetermined budgets and timelines. This research, conducted in Mashhad, Iran, employs the analytic hierarchy process (AHP) and VIKOR methods to identify and rank factors influencing delays in [...] Read more.
Construction projects, especially those for commercial purposes, require thorough planning and control to ensure success within predetermined budgets and timelines. This research, conducted in Mashhad, Iran, employs the analytic hierarchy process (AHP) and VIKOR methods to identify and rank factors influencing delays in high-rise projects. The study, based on a sample of 40 projects, emphasizes the comprehensive nature of our research method. The scale for features in project selection includes societal importance (with different applications including cultural hubs, affordable housing initiatives, and urban renewal for social equity), size (less and more than 20 units in residential projects), and diversity (mixed-use development, inclusive infrastructure, and cultural and recreational spaces), contributing to a comprehensive analysis of construction delays. Expert project managers and engineers provided insights through two questionnaires, and their responses underwent thorough analysis. Our findings not only underscore the significance of factors contributing to project success but also rank their impact on the likelihood of delays. The study reveals that the negative effects of these factors on cost, time, and project quality vary. Time emerges as the most influential parameter, with approximately six times more impact on cost and nine times more on quality. Contractor financial weakness, delays in allocating financial and credit resources, insufficient project resource allocation, contractor technical and executive weakness, and a lack of proper implementation and project control are identified as the most important factors contributing to delays. Full article
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<p>Research road map of this study.</p>
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<p>The map of the case study used in the present research.</p>
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<p>The specification and frequency of participants as per (<b>a</b>) gender, (<b>b</b>) degree, (<b>c</b>) work experience, (<b>d</b>) position, and (<b>e</b>) age.</p>
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<p>Hierarchical design of factors affecting project delays.</p>
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<p>Comparison matrix of data obtained from respondents and the degree of noncompliance entered into ExpertChoice.</p>
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<p>The weight and rank derived from the pairwise comparison matrix calculations for the main criteria.</p>
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<p>The combined weight of all research sub-criteria and their rankings.</p>
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22 pages, 7929 KiB  
Technical Note
Seismic Behavior of Rock-Filled Concrete Dam Compared with Conventional Vibrating Concrete Dam Using Finite Element Method
by Can Tang, Xinchao Hou, Yanjie Xu and Feng Jin
Infrastructures 2024, 9(2), 23; https://doi.org/10.3390/infrastructures9020023 - 30 Jan 2024
Viewed by 3096
Abstract
A rock-filled concrete (RFC) dam is an original dam construction technology invented in China nearly 20 years ago. The technology has been continuously improved and innovated upon, and the accumulated rich practical experience gradually formed a complete dam design and construction technology. Seismic [...] Read more.
A rock-filled concrete (RFC) dam is an original dam construction technology invented in China nearly 20 years ago. The technology has been continuously improved and innovated upon, and the accumulated rich practical experience gradually formed a complete dam design and construction technology. Seismic design is a key design area for RFC dams that still requires more investigation; therefore, this article attempts to address some questions in this area. In the article, the seismic design for a curved gravity dam, currently under construction, is compared for RFC and conventional vibrating concrete (CVC) dam alternatives based on American design documents. The conclusions drawn from investigations include the following: The displacement and stress distributions in both the CVC and RFC alternatives are similar, but the maximum computed values for the RFC dam model are slightly smaller than those for the CVC one, while the sliding resistance of both dam alternatives can meet the requirements of the specifications. Regarding the nonlinear seismic analysis results, the extent of damage in the RFC dam model is significantly reduced when compared with the CVC model, which can be explained by the higher cracking resistance of RFC. In general, the seismic performance of the investigated dam made of RFC appears to be better than that of CVC. Full article
(This article belongs to the Special Issue Advances in Dam Engineering of the 21st Century)
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<p>The geometry of the dam profile.</p>
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<p>Finite element model of the non-overflow section of the gravity dam.</p>
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<p>The gravity dam RFC dam scheme material zoning map.</p>
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<p>The standard design response spectrum comparison diagram.</p>
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<p>Seismic time records used in the analysis: (<b>a</b>) OBE; (<b>b</b>) SEE.</p>
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<p>Schematic diagram of lifting pressure distribution on the foundation surface of a gravity dam.</p>
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<p>Concrete constitutive relation diagram.</p>
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<p>Vibration pattern of the first five modes of the RFC dam.</p>
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<p>Horizontal displacement of the gravity dam body profile with different materials under OBE conditions (unit: cm): (<b>a</b>) CVC dam; (<b>b</b>) RFC dam. Maximum values are marked in red.</p>
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<p>Maximum principal stress of the gravity dam body profile with different materials under OBE conditions (unit: MPa): (<b>a</b>) CVC dam; (<b>b</b>) RFC dam. Maximum values are marked in red.</p>
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<p>Minimum principal stress of the gravity dam body profile with different materials under OBE conditions (unit: MPa): (<b>a</b>) CVC dam; (<b>b</b>) RFC dam. Maximum values are marked in red.</p>
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<p>Maximum principal stress of the gravity dam body profile with different materials under MCE conditions (unit: MPa): (<b>a</b>) CVC dam; (<b>b</b>) RFC dam. Maximum values are marked in red.</p>
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<p>Minimum principal stress of the gravity dam body profile with different materials under MCE conditions (unit: MPa): (<b>a</b>) CVC dam; (<b>b</b>) RFC dam. Minimum values are marked in red.</p>
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<p>Performance/damage acceptance for gravity dam.</p>
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<p>DCR value distribution of the gravity dam under MCE conditions: (<b>a</b>) CVC dam; (<b>b</b>) RFC dam. Contour lines with values of 1.0 and 2.0 are marked in red.</p>
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<p>Maximum principal stress time-history curve of the gravity dam body section under MCE conditions: (<b>a</b>) CVC dam; (<b>b</b>) RFC dam. The maximum value is marked with a star.</p>
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<p>Performance curve of the gravity dam model under MCE conditions: (<b>a</b>) CVC dam; (<b>b</b>) RFC dam. The CID under the specific DCR is marked with a square.</p>
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<p>Damage distribution under massless foundation model under MCE conditions: (<b>a</b>) CVC dam; (<b>b</b>) RFC dam.</p>
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<p>Schematic diagram of anti-sliding stability calculation plane of the gravity dam. Red lines indicate candidate sliding profiles.</p>
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<p>Time-history diagram of the safety factor of the foundation surface of the gravity dam under MCE conditions: (<b>a</b>) CVC dam; (<b>b</b>) RFC dam.</p>
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26 pages, 13540 KiB  
Article
Effects of Relative Humidity and Temperature on the Drying Shrinkage of Roller-Compacted Concrete Pavements
by Julián Pulecio-Díaz, Miguel Sol-Sánchez and Fernando Moreno-Navarro
Infrastructures 2024, 9(2), 22; https://doi.org/10.3390/infrastructures9020022 - 30 Jan 2024
Cited by 1 | Viewed by 2466
Abstract
Roller-compacted concrete (RCC) pavements have been the subject of studies focused on their increasing deterioration over time due to the influence of vehicular loading and ambient factors in humidity and temperature conditions ranging from medium to low (40% relative humidity and 25 °C [...] Read more.
Roller-compacted concrete (RCC) pavements have been the subject of studies focused on their increasing deterioration over time due to the influence of vehicular loading and ambient factors in humidity and temperature conditions ranging from medium to low (40% relative humidity and 25 °C temperature). Therefore, it is necessary to understand how they behave under various relative humidity and temperature conditions since these parameters vary in each geographic region. In this context, this research focused on analyzing the effect of drying shrinkage on RCC pavements under the influence of vehicular loading using a computational model calibrated with data obtained under typical ambient conditions. For this purpose, laboratory experiments were performed, numerical modeling was used, and the results for RCC pavements were validated using statistical analysis. The results revealed validated models providing moisture content and drying shrinkage curves. These results also underline the importance of considering ambient effects when calculating pavement stresses as a response variable in structural designs. In particular, these effects are highlighted as they can generate changes in pavement stresses of up to 10%, emphasizing the relevance of the models proposed in this study as they consider this phenomenon when predicting the performance and durability of RCC pavements. Full article
(This article belongs to the Section Infrastructures Materials and Constructions)
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<p>Relative humidity (RH), temperature (T), and g of water vapor/kg of air behavior. Source: [<a href="#B32-infrastructures-09-00022" class="html-bibr">32</a>].</p>
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<p>Gradation for roller-compacted concrete (RCC) pavement.</p>
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<p>Laboratory procedures.</p>
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<p>Moisture content test.</p>
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<p>Free shrinkage strain test.</p>
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<p>Compressive strength test.</p>
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<p>Flexural strength test.</p>
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<p>Cube sample for moisture content test for the finite element method (FEM).</p>
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<p>Computational modeling of the moisture content test.</p>
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<p>Computational modeling of the free shrinkage strain test.</p>
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<p>Beam sample used for the free shrinkage strain test employing the finite element method (FEM).</p>
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<p>Roller-compacted concrete (dark grey), base (yellow), and subgrade.</p>
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<p>Displacement–load curves and elastic moduli of the roller-compacted concrete material subjected to various ambient conditions.</p>
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<p>Experimental (Exp) moisture profiles with different relative humidity and temperature values for wet and dry ambient conditions. <sup>1</sup> [<a href="#B20-infrastructures-09-00022" class="html-bibr">20</a>]; <sup>2</sup> [<a href="#B21-infrastructures-09-00022" class="html-bibr">21</a>].</p>
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<p>Evolution of the experimental (Exp) free shrinkage strain of the roller-compacted concrete material under different wet and dry ambient conditions.</p>
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<p>Evolution of the numerical (employing the finite element method (FEM)) and experimental (Exp) moisture profiles under different relative humidity and temperature conditions. Results according to the ABAQUS modeling. <sup>1</sup> [<a href="#B20-infrastructures-09-00022" class="html-bibr">20</a>]; <sup>2</sup> [<a href="#B21-infrastructures-09-00022" class="html-bibr">21</a>].</p>
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<p>Moisture content after 90 days for cubes of 100 mm × 100 mm × 100 mm: (<b>a</b>) ambient condition of 85% RH and 25 °C; (<b>b</b>) ambient condition of 20% RH and 25 °C; and (<b>c</b>) ambient condition of 10% RH and 40 °C.</p>
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<p>Moisture content after 90 days for cubes of 100 mm × 100 mm × 100 mm: (<b>a</b>) ambient condition of 85% RH and 25 °C; (<b>b</b>) ambient condition of 20% RH and 25 °C; and (<b>c</b>) ambient condition of 10% RH and 40 °C.</p>
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<p>Evolution of the numerical (employing the finite element method (FEM)) and experimental free shrinkage strain under different relative humidity and temperature conditions.</p>
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<p>Shrinkage strain after 90 days for beams of 100 mm × 100 mm × 285 mm: (<b>a</b>) ambient condition of 85% RH and 25 °C; (<b>b</b>) ambient condition of 20% RH and 25 °C; and (<b>c</b>) ambient condition of 10% RH and 40 °C.</p>
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<p>Maximum principal stress (MPa) of the pavement under corner loading (<b>a</b>) without being subjected to ambient conditions of 85% RH and 25 °C and (<b>b</b>) being subjected to ambient conditions of 85% RH and 25 °C.</p>
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<p>Maximum principal stress (MPa) of the pavement under corner loading (<b>a</b>) without being subjected to ambient conditions of 20% RH and 25 °C and (<b>b</b>) being subjected to ambient conditions of 20% RH and 25 °C.</p>
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<p>Maximum principal stress (MPa) of the pavement under corner loading (<b>a</b>) without being subjected to an ambient condition of 10% RH and 40 °C and (<b>b</b>) being subjected to an ambient condition of 10% RH and 40 °C.</p>
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<p>Maximum principal stress (MPa) of the pavement under corner loading (<b>a</b>) without being subjected to an ambient condition of 10% RH and 40 °C and (<b>b</b>) being subjected to an ambient condition of 10% RH and 40 °C.</p>
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<p>Numerical maximum principal stress of the pavement under corner loading subjected to different relative humidity and temperature conditions employing the finite element method (FEM).</p>
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23 pages, 1581 KiB  
Article
Analysis of the Impact of New Generation Narrow-Body Aircraft on Flexible and Rigid Regional Airport Pavements
by Greg White
Infrastructures 2024, 9(2), 21; https://doi.org/10.3390/infrastructures9020021 - 27 Jan 2024
Viewed by 2568
Abstract
Airport pavements have always evolved to keep pace with the demands of new aircraft. As aircraft weights and tyre pressures increase, stronger, new pavements are designed and existing pavements are rehabilitated or upgraded. The narrow-body commercial jet aircraft, including the A320 and B737 [...] Read more.
Airport pavements have always evolved to keep pace with the demands of new aircraft. As aircraft weights and tyre pressures increase, stronger, new pavements are designed and existing pavements are rehabilitated or upgraded. The narrow-body commercial jet aircraft, including the A320 and B737 families, are examples of aircraft that have retained the same number of wheels, with the same wheel spacing and the same wingspan, but have increased in weight and tyre pressure by approximately 50%. This places significant demand on airport pavements that were designed for the lighter variants but now face the introduction of the newer, heavier and more demanding variants. This research quantified the impact of the new A320 and B737 narrow-body aircraft variants on rigid and flexible regional airport pavements, where these are the critical aircraft, as well as demonstrating the importance of understanding the operational weight limitations of these aircraft, which is often well below the published maximum weight. Within the context of the pavements considered, the additional pavement thickness required for the heaviest aircraft variants, compared to the lightest variants, was 51%. Based on four examples from real regional airports in Australia, it was found that the additional embodied carbon associated with these new aircraft variants was 2.1–85.3 kg·eCO2/m2 of pavement, while the additional financial cost was AUD 6–219/m2 of pavement. It was concluded that airport pavement thickness designers must challenge the weight of the design aircraft and not take the simple and conservative approach of adopting the maximum weight of the heaviest variant within each aircraft family. By doing so, significant additional pavement thickness will be constructed for no practical benefit, creating an environmental (embodied carbon) and economic (financial cost) burden. Full article
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<p>Schematic flow of research methods.</p>
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<p>Schematic (<b>a</b>) flexible and (<b>b</b>) rigid pavement compositions.</p>
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<p>Aircraft Classification Rating by year of aircraft introduction.</p>
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<p>Aircraft tyre pressure increases with aircraft weight increases.</p>
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<p>Effect of aircraft variant on fixed flexible pavement thickness for (<b>a</b>) A320 on thin pavement, (<b>b</b>) B737 on thin pavement, (<b>c</b>) A320 on thick pavement and (<b>d</b>) B737 on thick pavement.</p>
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<p>Effect of aircraft variant on fixed rigid pavement thickness for (<b>a</b>) A320 on thin pavement, (<b>b</b>) B737 on thin pavement, (<b>c</b>) A320 on thick pavement and (<b>d</b>) B737 on thick pavement.</p>
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<p>Flexible pavement thicknesses for (<b>a</b>) A320 and (<b>b</b>) B737 aircraft.</p>
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<p>Rigid pavement thicknesses for (<b>a</b>) A320 and (<b>b</b>) B737 aircraft.</p>
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<p>Additional asphalt thickness as a function of A321XLR operating weight.</p>
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<p>Additional embodied carbon and financial cost of heavy A312XLR aircraft.</p>
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<p>Relative embodied carbon and financial cost savings. Note: R and F indicate the flexible and rigid pavements where both pavement types were considered for the sample example airport.</p>
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16 pages, 3466 KiB  
Article
Characterizing Bridge Thermal Response for Bridge Load Rating and Condition Assessment: A Parametric Study
by Artem Marchenko, Rolands Kromanis and André G. Dorée
Infrastructures 2024, 9(2), 20; https://doi.org/10.3390/infrastructures9020020 - 26 Jan 2024
Cited by 3 | Viewed by 2650
Abstract
Temperature is the main driver of bridge response. It is continuously applied and may have complex distributions across the bridge. Daily temperature loads force bridges to undergo deformations that are larger than or equal to peak-to-peak traffic loads. Bridge thermal response must therefore [...] Read more.
Temperature is the main driver of bridge response. It is continuously applied and may have complex distributions across the bridge. Daily temperature loads force bridges to undergo deformations that are larger than or equal to peak-to-peak traffic loads. Bridge thermal response must therefore be accounted for when performing load rating and condition assessment. This study assesses the importance of characterizing bridge thermal response and separating it from traffic-induced response. Numerical replicas (i.e., fine element models) of a steel girder bridge are generated to validate the proposed methodology. Firstly, a variety of temperature distribution scenarios, such as those resulting from extreme weather conditions due to climate change, are modelled. Then, nominal traffic load scenarios are simulated, and bridge response is characterized. Finally, damage is modelled as a reduction in material stiffness due to corrosion. Bridge response to applied traffic load is different before and after the introduction of damage; however, it can only be correctly quantified when the bridge thermal response is accurately accounted for. The study emphasizes the importance of accounting for distributed temperature loads and characterizing bridge thermal response, which are important factors to consider both in bridge design and condition assessment. Full article
(This article belongs to the Special Issue Advances in Structural Health Monitoring of the Built Environment)
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<p>Methodology flowchart.</p>
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<p>The DAD method for condition assessment of bridges.</p>
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<p>The UT Campus bridge from the east side of Hogekamp (<b>left</b>) and its geolocation (<b>right</b>).</p>
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<p>A plan view of the UT Campus bridge with selected sensors. Numbers and letters in the circles indicate structural axes.</p>
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<p>Sun path in (<b>a</b>) June and (<b>b</b>) December.</p>
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<p>Strain and temperature measurements on (<b>a</b>) a sunny day and (<b>b</b>) a cloudy day.</p>
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<p>FEM of the UT Campus bridge.</p>
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<p>Dynamic behaviour of the UT Campus bridge: (<b>left</b>) the first vertical bending mode at 2.47 Hz and (<b>right</b>) the first torsional mode at 4.23 Hz.</p>
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<p>Loading scenarios L<sub>A</sub> and L<sub>B</sub>.</p>
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<p>Temperature distribution scenarios (T-i, i = 1, 2, 3, 4, 5).</p>
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<p>Bridge static response for girders A (<b>left</b>), B (<b>middle</b>), and C (<b>right</b>).</p>
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<p>(<b>a</b>) FEM showing the deformed shape and temperature distribution (scenario T3) of the UT Campus bridge; (<b>b</b>–<b>f</b>) displacement of girders along the length of the bridge for scenarios T1 to T5, respectively.</p>
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<p>Traffic and thermal load responses for (<b>a</b>–<b>c</b>) for scenarios T1 to T3 and (<b>d</b>) for scenario T5, respectively.</p>
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<p>Simulated damage shown in the cross-section of the bridge.</p>
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<p>Girder A (<b>left</b>), B (<b>middle</b>), and C (<b>right</b>) vertical deflections at baseline and damaged conditions for both loading scenarios.</p>
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<p>DAD for all temperature scenarios and static loads <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>L</mi> </mrow> <mrow> <mi>A</mi> </mrow> </msub> </mrow> </semantics></math> (<b>left</b>) and <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>L</mi> </mrow> <mrow> <mi>B</mi> </mrow> </msub> </mrow> </semantics></math> (<b>right</b>) at damage state (D). Colour and grey bars give DAD results for conditions with the thermal response characterized and not characterized (NC).</p>
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18 pages, 2599 KiB  
Article
Exploring the Effect of Near-Field Ground Motions on the Fragility Curves of Multi-Span Simply Supported Concrete Girder Bridges
by Hassan Soltanmohammadi, Mohammadreza Mashayekhi, Mohammad Mahdi Memarpour, Denise-Penelope N. Kontoni and Masoud Mirtaheri
Infrastructures 2024, 9(2), 19; https://doi.org/10.3390/infrastructures9020019 - 26 Jan 2024
Viewed by 2402
Abstract
Investigating the impact of near-field ground motions on the fragility curves of multi-span simply supported concrete girder bridges is the main goal of this paper. Fragility curves are valuable tools for evaluating seismic risks and vulnerabilities of bridges. Numerous studies have investigated the [...] Read more.
Investigating the impact of near-field ground motions on the fragility curves of multi-span simply supported concrete girder bridges is the main goal of this paper. Fragility curves are valuable tools for evaluating seismic risks and vulnerabilities of bridges. Numerous studies have investigated the impact of ground motions on the fragility curves of bridges. Ground motions are commonly categorized into two sets, based on the distance of the recorded station from the seismic source: far-field and near-field. Studies examining the influence of near-field records on bridge fragility curves vary depending on the specific bridge type and type of fragility curve being analyzed. Due to the widespread use of multi-span simply supported concrete girder bridges in the Central and Southeastern United States, this study makes use of this bridge type. This research investigates the component fragility curves for column curvatures, bearing deformations, and abutment displacements by employing 3-D analytical models and conducting nonlinear time history analysis. These curves illustrate the impact of near-field ground motions on different components. The component fragility curves for two sets of records, 91 near-field ground motions and 78 far-field ground motions, were obtained and compared. These findings demonstrate that near-field ground motions have a greater damaging effect on columns and abutments than far-field earthquakes. When it comes to bearing deformations, the far-field earthquake impact is more severe at lower intensities, whereas the impact of the near-field ground motion is stronger at higher intensities. Full article
(This article belongs to the Special Issue Geotechnical Earthquake Engineering)
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<p>Creating fragility curves.</p>
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<p>Under study bridge model elevation.</p>
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<p>Bridge configuration: (<b>a</b>) pier and deck, (<b>b</b>) bent beam section, (<b>c</b>) column section.</p>
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<p>Elastomeric bearings used for bridge girders: (<b>a</b>) expansion bearing, and (<b>b</b>) fixed bearing.</p>
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<p>An example of a near-field record acceleration time history.</p>
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<p>Acceleration spectrum of selected records: (<b>a</b>) near-field records, (<b>b</b>) far-field records, and (<b>c</b>) a median comparison between near-field and far-field records.</p>
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<p>Probabilistic seismic demand models for abutment displacement: (<b>a</b>) passive state, and (<b>b</b>) active state.</p>
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<p>Fragility curves of abutment displacement in passive state: (<b>a</b>) slight damage state, and (<b>b</b>) moderate damage state.</p>
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<p>Fragility curves of abutment displacement in the active state: (<b>a</b>) slight damage state, (<b>b</b>) moderate damage state, and (<b>c</b>) extensive damage state.</p>
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<p>Fragility curves of column curvature: (<b>a</b>) slight damage state, (<b>b</b>) moderate damage state, (<b>c</b>) extensive damage state, and (<b>d</b>) complete collapse damage state.</p>
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<p>Fragility curves of fixed bearings deformation: (<b>a</b>) slight damage state, (<b>b</b>) moderate damage state, (<b>c</b>) extensive damage state, and (<b>d</b>) complete collapse damage state.</p>
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<p>Fragility curves of expansion bearings deformation: (<b>a</b>) slight damage state, (<b>b</b>) moderate damage state, (<b>c</b>) extensive damage state, and (<b>d</b>) complete collapse damage state.</p>
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24 pages, 8021 KiB  
Article
The “M and P” Technique for Damage Identification in Reinforced Concrete Bridges
by Athanasios Bakalis, Triantafyllos Makarios and Vassilis Lekidis
Infrastructures 2024, 9(2), 18; https://doi.org/10.3390/infrastructures9020018 - 25 Jan 2024
Cited by 1 | Viewed by 2140
Abstract
The seismic damage in reinforced concrete bridges is identified in this study using the “M and P” hybrid technique initially developed for planar frames, where M signifies “Monitoring” and P denotes “Pushover analysis”. The proposed methodology involves a series of pushover [...] Read more.
The seismic damage in reinforced concrete bridges is identified in this study using the “M and P” hybrid technique initially developed for planar frames, where M signifies “Monitoring” and P denotes “Pushover analysis”. The proposed methodology involves a series of pushover and instantaneous modal analyses with a progressively increasing target deck displacement along the longitudinal direction of the bridge. From the results of these analyses, the diagram of the instantaneous eigenfrequency of the bridge, ranging from the health state to near collapse, is plotted against the inelastic seismic deck displacement. By pre-determining the eigenfrequency of an existing bridge along its longitudinal direction through “monitoring and frequency identification”, the target deck displacement corresponding to the damage state can directly be found from this diagram. Subsequently, the damage can be identified by examining the results of the pushover analysis at the step where the target deck displacement is indicated. The effectiveness of this proposed technique is evaluated in the context of straight multiple span bridges with unequal pier heights, illustrated through an example of a four-span bridge. The findings demonstrate that the damage potential in bridge piers can be successfully identified by combining the results of a monitoring process and pushover analysis. Full article
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<p>Pushover curve of a multispan RC bridge along the longitudinal direction (target displacement at the Near Collapse (NC) state).</p>
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<p>Instantaneous eigenfrequency diagram of the RC bridge, in the nonlinear area.</p>
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<p>(<b>a</b>) Simply supported straight bridge with N-1 spans of various lengths and N-piers of various heights; (<b>b</b>) chord rotation <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>θ</mi> </mrow> <mrow> <mi>c</mi> </mrow> </msub> </mrow> </semantics></math> of the bridge piers in pushover analysis with lateral force at the deck level.</p>
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<p>Base section analysis of a cantilever pier in the RC bridge, with a height equal to the shear span length <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>L</mi> </mrow> <mrow> <mi>v</mi> </mrow> </msub> </mrow> </semantics></math>. This includes the calculation of curvature <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>φ</mi> </mrow> <mrow> <mi>y</mi> </mrow> </msub> </mrow> </semantics></math> (rad/m), chord rotation <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>θ</mi> </mrow> <mrow> <mi>y</mi> </mrow> </msub> </mrow> </semantics></math> (rad), and secant stiffness at yield <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>Ε</mi> <mi>I</mi> </mrow> <mrow> <mi>s</mi> <mi>e</mi> <mi>c</mi> </mrow> </msub> </mrow> </semantics></math> (kN·m<sup>2</sup>) according to EN1998-3 [<a href="#B33-infrastructures-09-00018" class="html-bibr">33</a>].</p>
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<p>Effective moment of inertia ratio <math display="inline"><semantics> <mrow> <mrow> <mrow> <msub> <mrow> <mi>I</mi> </mrow> <mrow> <mi>e</mi> <mi>f</mi> <mi>f</mi> </mrow> </msub> </mrow> <mo>/</mo> <mrow> <msub> <mrow> <mi>I</mi> </mrow> <mrow> <mi>g</mi> </mrow> </msub> </mrow> </mrow> </mrow> </semantics></math> of the ductile piers of the RC bridge at various performance levels (damage states) as a function of the chord rotation <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>θ</mi> </mrow> <mrow> <mi>p</mi> <mi>r</mi> </mrow> </msub> </mrow> </semantics></math> (rad) at their base section.</p>
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<p>Flowchart for the application of the “<span class="html-italic">M</span> and <span class="html-italic">P</span>” technique in RC bridges.</p>
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<p>(<b>a</b>) Straight RC bridge with four spans and with (2 column) piers of various heights; (<b>b</b>) dynamic model of RC bridge (SDOF) for modal analysis; (<b>c</b>) static model of RC bridge for pushover analysis.</p>
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<p>(<b>a</b>) Section aa at pier 5 of the RC bridge; (<b>b</b>) lane set-up and live loads on lanes.</p>
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<p>Pier 2: (<b>a</b>) section; (<b>b</b>) elevation.</p>
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<p>Stress–strain diagrams for both unconfined and confined concrete.</p>
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<p>Stress–strain diagram for steel reinforcement bars.</p>
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<p>Capacity curve of the RC bridge along the longitudinal direction according to various stiffness scenarios. Ref. [<a href="#B33-infrastructures-09-00018" class="html-bibr">33</a>].</p>
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<p>Capacity curve of the RC bridge and of the various (2 columns) piers along the longitudinal direction according to the stiffness scenario for the NC state.</p>
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<p>Instantaneous eigenfrequency diagram combined with the seismic capacity curve of the RC bridge along the longitudinal direction (key diagram).</p>
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<p>Yield state and sequence of yield of the bridge piers at deck target displacement <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>u</mi> </mrow> <mrow> <mi>i</mi> </mrow> </msub> <mo>=</mo> <mn>0.08</mn> <mtext> </mtext> <mi mathvariant="normal">m</mi> </mrow> </semantics></math>.</p>
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<p>Capacity curve of the RC bridge piers for a deck target displacement <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>u</mi> </mrow> <mrow> <mi>d</mi> <mi>e</mi> <mi>c</mi> <mi>k</mi> </mrow> </msub> <mo>=</mo> <mn>0.08</mn> <mtext> </mtext> <mi mathvariant="normal">m</mi> </mrow> </semantics></math>, in terms of base shear and <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>θ</mi> </mrow> <mrow> <mi>p</mi> <mi>r</mi> </mrow> </msub> </mrow> </semantics></math>.</p>
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<p>Percentage deviation of the damage stiffness <math display="inline"><semantics> <mrow> <msub> <mrow> <mi mathvariant="sans-serif">Δ</mi> <mi>k</mi> </mrow> <mrow> <mi>i</mi> </mrow> </msub> </mrow> </semantics></math> for the RC bridge and the bridge piers at the inelastic <span class="html-italic">i</span>-step corresponding to the seismic deck displacement <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>u</mi> </mrow> <mrow> <mi>d</mi> <mi>e</mi> <mi>c</mi> <mi>k</mi> <mo>,</mo> <mi>i</mi> </mrow> </msub> <mo>=</mo> <mn>0.08</mn> <mtext> </mtext> <mi mathvariant="normal">m</mi> </mrow> </semantics></math>.</p>
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19 pages, 12314 KiB  
Article
Durability, Capillary Rise and Water Absorption Properties of a Fiber-Reinforced Cement-Stabilized Fly Ash–Stone Dust Mixture
by Sanjeeb Kumar Mohanty, Nirmal Kumar Pandit, Pawan Kumar Sah, Niraj Mahaseth, Rajesh Yadav, Dipti Ranjan Biswal, Benu Gopal Mohapatra, Brundaban Beriha, Ramachandra Pradhan and Sujit Kumar Pradhan
Infrastructures 2024, 9(2), 17; https://doi.org/10.3390/infrastructures9020017 - 25 Jan 2024
Cited by 1 | Viewed by 2792
Abstract
The management of unutilized fly ash poses challenges due to concerns about storage and its potential groundwater contamination. Within the road industry, where the bulk utilization of fly ash is feasible, its unsuitability for use in the base and sub-base layers of pavements [...] Read more.
The management of unutilized fly ash poses challenges due to concerns about storage and its potential groundwater contamination. Within the road industry, where the bulk utilization of fly ash is feasible, its unsuitability for use in the base and sub-base layers of pavements due to its low strength and a high proportion of fine particles has been a limitation. The incorporation of stone dust alongside fly ash, treated with lime or cement, yields superior strength and stiffness. Apart from strength, the stabilized mix’s durability, capillary rise, and water absorption properties are crucial for determining its suitability for pavement applications. Observations from this study reveal that fiber-reinforced cement-stabilized fly ash–stone aggregate specimens treated with 4% and 6% cement, with and without fibers, met the limiting mass loss of 20%, as specified in IRC SP: 89. The mass loss decreases with an increase in cement and fiber content. However, the capillary rise in the mixes increases with a higher percentage of fly ash and fiber content but decreases with increased cement content. Cement addition results in a reduction in water absorption; however, the addition of fibers results in an increase in water absorption. A linear correlation has been established between mass loss and UCS and IDT, which can be used to evaluate the suitability of materials for the structural layer without conducting a wet–dry durability test, which typically takes one month. This study proposes that cement-stabilized fly ash and stone aggregate mixtures with 4% and 6% cement can be used as the subbase and base of pavement based on wet–dry mass loss criteria and water absorption criteria. Observations from this study reveal that fiber-reinforced cement-stabilized fly ash–stone aggregate specimens treated with 4% and 6% cement, with and without fibers, met the limiting mass loss of 20%, as specified in IRC SP: 89. The mass loss decreases with an increase in cement and fiber content. However, the capillary rise in the mixes increases with a higher percentage of fly ash and fiber content but decreases with increased cement content. Cement addition results in reduction in water absorption. However, the addition of fibers results in increase in water absorption. A linear correlation is established between mass loss and UCS and IDT, which can be used to evaluate the suitability of materials for the structural layer without conducting wet–dry durability tests, which take one month. This study proposes that cement-stabilized fly ash and stone aggregate mixtures with 4% and 6% cement can be used as the subbase and base of pavement based on wet–dry mass loss criteria and water absorption criteria. Full article
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<p>Materials used in present study.</p>
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<p>Particle size distribution of FA–SD mixtures at various ratios.</p>
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<p>Steps of wet–dry durability test. (<b>a</b>) Cylindrical samples after 7 days of curing; (<b>b</b>) samples immersed in water for 5 h; (<b>c</b>) samples in oven at 72 °C for 42 h; (<b>d</b>) samples under hand brushing.</p>
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<p>Schematic drawing showing capillary rise test. (<b>a</b>) initial stage of water absorption and capillary rise test; (<b>b</b>) water absorption and capillary rise test after time t.</p>
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<p>Specimens undergoing the water absorption and capillary rise test procedure.</p>
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<p>Degraded samples after 12 cycles.</p>
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<p>Effect of cement on mass loss of FA–SD mixes (0% fiber).</p>
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<p>XRD test results of (<b>a</b>) fly ash and (<b>b</b>) stabilized fly ash.</p>
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<p>SEM photographs. (<b>a</b>) Fly ash; (<b>b</b>) fly ash + cement + fibers.</p>
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<p>Mass loss in percentage of the fiber-reinforced cement-stabilized fly ash–stone aggregate mix.</p>
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<p>Correlation between mass loss (%) and unsoaked UCS of FA–SD samples at 7 days of curing.</p>
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<p>Correlation between mass loss and IDT.</p>
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<p>Capillary rise of fly ash–stone mixes with time.</p>
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<p>Effect of fibers on the capillary rise of FA–SD mixes.</p>
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<p>Water absorption of FA–SD mixes.</p>
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<p>Correlation between fiber percentages and water absorption for FA–SD mixes.</p>
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