Pub Date : 2024-04-18DOI: 10.3390/infrastructures9040076
I. Akomea-Frimpong, Xiaohua Jin, R. Osei-Kyei
Public–private partnership (PPP) is a prominent tool for sustainable infrastructure development. However, the positive contributions of PPPs toward the attainment of sustainable, climate resilience and zero-carbon infrastructure projects are hampered by poor financial risk management. This problem is more prevalent in developing countries like Ghana where private investment inflow has plummeted due to the COVID-19 recession and poor project performance. Thus, this study aims to assess the key financial risk management strategies in ensuring sustainable PPP infrastructure projects in Ghana. The study utilised primary data from PPP practitioners in Ghana solicited through survey questionnaires. Factor analysis, mean scores and fuzzy synthetic analysis are the data analysis techniques for this study. The results revealed that sustainable and green funding models, effective cost-reduction initiatives, a competent team with committed leadership and emerging technologies and regulations constitute the key strategies for managing the financial risks of sustainable PPP infrastructure projects. Although future studies must expand the scope of data gathering, the findings of the study enrich the theoretical understanding of financial risks in sustainable investments in PPP infrastructures. Relevant remedies that will aid the development of practical financial risk management guidelines are also provided in this study for PPP practitioners.
{"title":"Fuzzy Analysis of Financial Risk Management Strategies for Sustainable Public–Private Partnership Infrastructure Projects in Ghana","authors":"I. Akomea-Frimpong, Xiaohua Jin, R. Osei-Kyei","doi":"10.3390/infrastructures9040076","DOIUrl":"https://doi.org/10.3390/infrastructures9040076","url":null,"abstract":"Public–private partnership (PPP) is a prominent tool for sustainable infrastructure development. However, the positive contributions of PPPs toward the attainment of sustainable, climate resilience and zero-carbon infrastructure projects are hampered by poor financial risk management. This problem is more prevalent in developing countries like Ghana where private investment inflow has plummeted due to the COVID-19 recession and poor project performance. Thus, this study aims to assess the key financial risk management strategies in ensuring sustainable PPP infrastructure projects in Ghana. The study utilised primary data from PPP practitioners in Ghana solicited through survey questionnaires. Factor analysis, mean scores and fuzzy synthetic analysis are the data analysis techniques for this study. The results revealed that sustainable and green funding models, effective cost-reduction initiatives, a competent team with committed leadership and emerging technologies and regulations constitute the key strategies for managing the financial risks of sustainable PPP infrastructure projects. Although future studies must expand the scope of data gathering, the findings of the study enrich the theoretical understanding of financial risks in sustainable investments in PPP infrastructures. Relevant remedies that will aid the development of practical financial risk management guidelines are also provided in this study for PPP practitioners.","PeriodicalId":502683,"journal":{"name":"Infrastructures","volume":" 39","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140687737","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-04-18DOI: 10.3390/infrastructures9040075
H. Hosamo, C. N. Rolfsen, Florent Zeka, Sigurd Sandbeck, Sami Said, Morten André Sætre
Exploring the integration of 5D Building Information Modeling (BIM) within the Norwegian construction sector, this study examines its transformative impact on cost estimation and project management, highlighting technological and skill-based adoption challenges. Through methodical case studies and interviews with industry experts, it is revealed that 5D BIM significantly enhances the precision of cost estimations and effectively reduces financial overruns in complex construction projects, indicating an industry shift towards its broader acceptance. The research sets out to explore current challenges and opportunities in 5D BIM, assess the usability and integration of software tools, and understand systemic barriers and skill gaps hindering further progress. These objectives lead to a detailed understanding of 5D BIM’s role in improving economic and procedural efficiencies in construction. Suggesting its pivotal role in the evolving construction management realm, the study contributes important insights into 5D BIM’s transformative potential and underscores its importance in advancing the construction industry’s digital transformation.
{"title":"Navigating the Adoption of 5D Building Information Modeling: Insights from Norway","authors":"H. Hosamo, C. N. Rolfsen, Florent Zeka, Sigurd Sandbeck, Sami Said, Morten André Sætre","doi":"10.3390/infrastructures9040075","DOIUrl":"https://doi.org/10.3390/infrastructures9040075","url":null,"abstract":"Exploring the integration of 5D Building Information Modeling (BIM) within the Norwegian construction sector, this study examines its transformative impact on cost estimation and project management, highlighting technological and skill-based adoption challenges. Through methodical case studies and interviews with industry experts, it is revealed that 5D BIM significantly enhances the precision of cost estimations and effectively reduces financial overruns in complex construction projects, indicating an industry shift towards its broader acceptance. The research sets out to explore current challenges and opportunities in 5D BIM, assess the usability and integration of software tools, and understand systemic barriers and skill gaps hindering further progress. These objectives lead to a detailed understanding of 5D BIM’s role in improving economic and procedural efficiencies in construction. Suggesting its pivotal role in the evolving construction management realm, the study contributes important insights into 5D BIM’s transformative potential and underscores its importance in advancing the construction industry’s digital transformation.","PeriodicalId":502683,"journal":{"name":"Infrastructures","volume":" 20","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140690036","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-04-16DOI: 10.3390/infrastructures9040074
S. Kao, Jhih-Sian Lin, Feng-Liang Wang, Pen-Shan Hung
While crack detection is crucial for maintaining concrete structures, existing methods often overlook the analysis of large cracks that span multiple images. Such analyses typically rely on image stitching to create a complete image of a crack. Current stitching methods are not only computationally demanding but also require manual adjustments; thus, a fast and reliable solution is still lacking. To address these challenges, we introduce a stitching method that leverages the advantages of crack image-segmentation models. This method first utilizes the Mask R-CNN model for the identification of crack regions as regions of interest (ROIs) within images. These regions are then used to calculate keypoints of the scale-invariant feature transform (SIFT), and descriptors for these keypoints are computed with the original images for image matching and stitching. Compared with traditional methods, our approach significantly reduces the computational time; by 98.6% in comparison to the Brute Force (BF) matcher, and by 58.7% with respect to the Fast Library for Approximate Nearest Neighbors (FLANN) matcher. Our stitching results on images with different degrees of overlap or changes in shooting posture show superior structural similarity index (SSIM) values, demonstrating excellent detail-matching performance. Moreover, the ability to measure complete crack images is indicated by the relative error of 7%, which is significantly better than that of traditional methods.
{"title":"A Large-Crack Image-Stitching Method with Cracks as the Regions of Interest","authors":"S. Kao, Jhih-Sian Lin, Feng-Liang Wang, Pen-Shan Hung","doi":"10.3390/infrastructures9040074","DOIUrl":"https://doi.org/10.3390/infrastructures9040074","url":null,"abstract":"While crack detection is crucial for maintaining concrete structures, existing methods often overlook the analysis of large cracks that span multiple images. Such analyses typically rely on image stitching to create a complete image of a crack. Current stitching methods are not only computationally demanding but also require manual adjustments; thus, a fast and reliable solution is still lacking. To address these challenges, we introduce a stitching method that leverages the advantages of crack image-segmentation models. This method first utilizes the Mask R-CNN model for the identification of crack regions as regions of interest (ROIs) within images. These regions are then used to calculate keypoints of the scale-invariant feature transform (SIFT), and descriptors for these keypoints are computed with the original images for image matching and stitching. Compared with traditional methods, our approach significantly reduces the computational time; by 98.6% in comparison to the Brute Force (BF) matcher, and by 58.7% with respect to the Fast Library for Approximate Nearest Neighbors (FLANN) matcher. Our stitching results on images with different degrees of overlap or changes in shooting posture show superior structural similarity index (SSIM) values, demonstrating excellent detail-matching performance. Moreover, the ability to measure complete crack images is indicated by the relative error of 7%, which is significantly better than that of traditional methods.","PeriodicalId":502683,"journal":{"name":"Infrastructures","volume":"65 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140695443","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-04-12DOI: 10.3390/infrastructures9040072
Yessica Julia Verastegui, Doris Esenarro
The objective of this research is to propose a public transport reorganization system that allows the improvement of urban vehicle flow. The lack of adequate transportation infrastructure and the existing disorder in the services provided by collective car, Microbus, Rural Public Transportation Van (Combi), Coaster, and mototaxis generate congestion in public transportation, especially during peak hours, resulting in environmental and noise pollution. The research was structured into four stages: data collection on the public and private transportation network, importing and creating the transportation network in the urban area of the Huánuco district, zoning and connectivity of the study area, and finally, creating the origin/destination (O/D) matrix for public transportation, supported by digital tools (ArcGIS 10.5, AutoCAD 2018, Excel 2017). To meet the demand of 135,343 passengers from South to North and 118,958 from North to South, the proposal includes establishing one main route and seven feeder routes, requiring 422 buses and road infrastructure, as depicted in the proposal This system will have exclusive lanes to operate the Mass Transit System, allowing it to accommodate 59% of users who prefer using public transportation. This proposal aims to offer an efficient and high-quality transportation system.
{"title":"Transportation System and the Improvement of Urban Vehicular Flow in the District of Huánuco-Perú 2022","authors":"Yessica Julia Verastegui, Doris Esenarro","doi":"10.3390/infrastructures9040072","DOIUrl":"https://doi.org/10.3390/infrastructures9040072","url":null,"abstract":"The objective of this research is to propose a public transport reorganization system that allows the improvement of urban vehicle flow. The lack of adequate transportation infrastructure and the existing disorder in the services provided by collective car, Microbus, Rural Public Transportation Van (Combi), Coaster, and mototaxis generate congestion in public transportation, especially during peak hours, resulting in environmental and noise pollution. The research was structured into four stages: data collection on the public and private transportation network, importing and creating the transportation network in the urban area of the Huánuco district, zoning and connectivity of the study area, and finally, creating the origin/destination (O/D) matrix for public transportation, supported by digital tools (ArcGIS 10.5, AutoCAD 2018, Excel 2017). To meet the demand of 135,343 passengers from South to North and 118,958 from North to South, the proposal includes establishing one main route and seven feeder routes, requiring 422 buses and road infrastructure, as depicted in the proposal This system will have exclusive lanes to operate the Mass Transit System, allowing it to accommodate 59% of users who prefer using public transportation. This proposal aims to offer an efficient and high-quality transportation system.","PeriodicalId":502683,"journal":{"name":"Infrastructures","volume":"120 18","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140708757","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-04-12DOI: 10.3390/infrastructures9040073
Arash K. Pour, Mehrdad Karami, Moses Karakouzian
This study intended to measure the efficiency of different strengthening techniques to advance the flexural characteristics of reinforced concrete (RC) beams using glass fiber-reinforced polymer (GFRP) laminates, including externally bonded reinforcement (EBR), externally bonded reinforcement on grooves (EBROG), externally bonded reinforcement in grooves (EBRIG), and the near-surface mounted (NSM) system. A new NSM technique was also established using an anchorage rebar. Then, the effect of the NSM method with and without externally strengthening GFRP laminates was studied. Twelve RC beams (150 × 200 × 1500 mm) were manufactured and examined under a bending system. One specimen was designated as the control with no GFRP laminate. To perform the NSM method, both steel and GFRP rebars were used. In the experiments, capability, as well as the deformation and ductileness of specimens, were evaluated, and a comparison was made between the experimental consequences and existing standards. Finally, a new regression was generated to predict the final resistance of RC beams bound with various retrofitting techniques. The findings exhibited that the NSM technique, besides preserving the strengthening materials, could enhance the load-bearing capacity and ductileness of RC beams up to 42.3% more than the EBR, EBROG, and EBRIG performances.
{"title":"Enhancing Flexural Strength of RC Beams with Different Steel–Glass Fiber-Reinforced Polymer Composite Laminate Configurations: Experimental and Analytical Approach","authors":"Arash K. Pour, Mehrdad Karami, Moses Karakouzian","doi":"10.3390/infrastructures9040073","DOIUrl":"https://doi.org/10.3390/infrastructures9040073","url":null,"abstract":"This study intended to measure the efficiency of different strengthening techniques to advance the flexural characteristics of reinforced concrete (RC) beams using glass fiber-reinforced polymer (GFRP) laminates, including externally bonded reinforcement (EBR), externally bonded reinforcement on grooves (EBROG), externally bonded reinforcement in grooves (EBRIG), and the near-surface mounted (NSM) system. A new NSM technique was also established using an anchorage rebar. Then, the effect of the NSM method with and without externally strengthening GFRP laminates was studied. Twelve RC beams (150 × 200 × 1500 mm) were manufactured and examined under a bending system. One specimen was designated as the control with no GFRP laminate. To perform the NSM method, both steel and GFRP rebars were used. In the experiments, capability, as well as the deformation and ductileness of specimens, were evaluated, and a comparison was made between the experimental consequences and existing standards. Finally, a new regression was generated to predict the final resistance of RC beams bound with various retrofitting techniques. The findings exhibited that the NSM technique, besides preserving the strengthening materials, could enhance the load-bearing capacity and ductileness of RC beams up to 42.3% more than the EBR, EBROG, and EBRIG performances.","PeriodicalId":502683,"journal":{"name":"Infrastructures","volume":"9 20","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140709952","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-04-09DOI: 10.3390/infrastructures9040071
A. Kharroubi, Z. Ballouch, R. Hajji, Anass Yarroudh, Roland Billen
Railway scene understanding is crucial for various applications, including autonomous trains, digital twining, and infrastructure change monitoring. However, the development of the latter is constrained by the lack of annotated datasets and limitations of existing algorithms. To address this challenge, we present Rail3D, the first comprehensive dataset for semantic segmentation in railway environments with a comparative analysis. Rail3D encompasses three distinct railway contexts from Hungary, France, and Belgium, capturing a wide range of railway assets and conditions. With over 288 million annotated points, Rail3D surpasses existing datasets in size and diversity, enabling the training of generalizable machine learning models. We conducted a generic classification with nine universal classes (Ground, Vegetation, Rail, Poles, Wires, Signals, Fence, Installation, and Building) and evaluated the performance of three state-of-the-art models: KPConv (Kernel Point Convolution), LightGBM, and Random Forest. The best performing model, a fine-tuned KPConv, achieved a mean Intersection over Union (mIoU) of 86%. While the LightGBM-based method achieved a mIoU of 71%, outperforming Random Forest. This study will benefit infrastructure experts and railway researchers by providing a comprehensive dataset and benchmarks for 3D semantic segmentation. The data and code are publicly available for France and Hungary, with continuous updates based on user feedback.
{"title":"Multi-Context Point Cloud Dataset and Machine Learning for Railway Semantic Segmentation","authors":"A. Kharroubi, Z. Ballouch, R. Hajji, Anass Yarroudh, Roland Billen","doi":"10.3390/infrastructures9040071","DOIUrl":"https://doi.org/10.3390/infrastructures9040071","url":null,"abstract":"Railway scene understanding is crucial for various applications, including autonomous trains, digital twining, and infrastructure change monitoring. However, the development of the latter is constrained by the lack of annotated datasets and limitations of existing algorithms. To address this challenge, we present Rail3D, the first comprehensive dataset for semantic segmentation in railway environments with a comparative analysis. Rail3D encompasses three distinct railway contexts from Hungary, France, and Belgium, capturing a wide range of railway assets and conditions. With over 288 million annotated points, Rail3D surpasses existing datasets in size and diversity, enabling the training of generalizable machine learning models. We conducted a generic classification with nine universal classes (Ground, Vegetation, Rail, Poles, Wires, Signals, Fence, Installation, and Building) and evaluated the performance of three state-of-the-art models: KPConv (Kernel Point Convolution), LightGBM, and Random Forest. The best performing model, a fine-tuned KPConv, achieved a mean Intersection over Union (mIoU) of 86%. While the LightGBM-based method achieved a mIoU of 71%, outperforming Random Forest. This study will benefit infrastructure experts and railway researchers by providing a comprehensive dataset and benchmarks for 3D semantic segmentation. The data and code are publicly available for France and Hungary, with continuous updates based on user feedback.","PeriodicalId":502683,"journal":{"name":"Infrastructures","volume":"10 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140727431","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-04-04DOI: 10.3390/infrastructures9040070
Kristopher Campbell, M. Lydon, N. Stevens, S. Taylor
This paper outlines an initial analysis of 20 years of data held on an electronic bridge management database for approximately 3500 arch bridges across Northern Ireland (NI) by the Department for Infrastructure. Arch bridges represent the largest group of bridge types, making up nearly 56% of the total bridge stock in NI. This initial analysis aims to identify trends that might help inform maintenance decisions in the future. Consideration of the Bridge Condition Indicator (BCI) average value for the overall arch bridge stock indicates the potential for regional variations in the overall condition and the potential for human bias in inspections. The paper presents the most prevalent structural elements and associated defects recorded in the inspections of arch bridges. This indicated a link to scour and undermining for the worst-conditioned arch bridges. An Analysis of Variance (ANOVA) analysis identified function, number of spans, and deck width as significant factors during the various deterioration stages in a bridge’s lifecycle.
{"title":"Analysis of Arch Bridge Condition Data to Identify Network-Wide Controls and Trends","authors":"Kristopher Campbell, M. Lydon, N. Stevens, S. Taylor","doi":"10.3390/infrastructures9040070","DOIUrl":"https://doi.org/10.3390/infrastructures9040070","url":null,"abstract":"This paper outlines an initial analysis of 20 years of data held on an electronic bridge management database for approximately 3500 arch bridges across Northern Ireland (NI) by the Department for Infrastructure. Arch bridges represent the largest group of bridge types, making up nearly 56% of the total bridge stock in NI. This initial analysis aims to identify trends that might help inform maintenance decisions in the future. Consideration of the Bridge Condition Indicator (BCI) average value for the overall arch bridge stock indicates the potential for regional variations in the overall condition and the potential for human bias in inspections. The paper presents the most prevalent structural elements and associated defects recorded in the inspections of arch bridges. This indicated a link to scour and undermining for the worst-conditioned arch bridges. An Analysis of Variance (ANOVA) analysis identified function, number of spans, and deck width as significant factors during the various deterioration stages in a bridge’s lifecycle.","PeriodicalId":502683,"journal":{"name":"Infrastructures","volume":"19 9","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140741067","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-04-03DOI: 10.3390/infrastructures9040069
Abdul Basit, S. Abbas, Muhammad Mubashir Ajmal, U. A. Mughal, S. Kazmi, M. Munir
This study undertakes a comprehensive experimental and numerical analysis of the structural integrity of buried RC sewerage pipes, focusing on the performance of two distinct jointing materials: cement mortar and non-shrinkage grout. Through joint shear tests on full-scale sewer pipes under single point loading conditions, notable effects on the crown and invert of the joint were observed, highlighting the critical vulnerability of these structures to internal and external pressures. Two materials—cement–sand mortar and non-shrinkage grout—were used in RC pipe joints to experimentally evaluate the joint strength of the sewerage pipes. Among the materials tested, cement–sand mortar emerged as the superior choice, demonstrating the ability to sustain higher loads up to 25.60 kN, proving its cost-effectiveness and versatility for use in various locations within RC pipe joints. Conversely, non-shrinkage grout exhibited the lowest ultimate failure load, i.e., 21.50 kN, emphasizing the importance of material selection in enhancing the resilience and durability of urban infrastructure. A 3D finite element (FE) analysis was also employed to assess the effect of various factors on stress distribution and joint deformation. The findings revealed a 10% divergence between the experimental and numerical data regarding the ultimate load capacity of pipe joints, with experimental tests indicating a 25.60 kN ultimate load and numerical simulations showing a 23.27 kN ultimate load. Despite this discrepancy, the close concordance between the two sets of data underscores the utility of numerical simulations in predicting the behavior of pipe joints accurately. This study provides valuable insights into the selection and application of jointing materials in sewerage systems, aiming to improve the structural integrity and longevity of such critical infrastructure.
{"title":"Joint Behavior of Full-Scale Precast Concrete Pipe Infrastructure: Experimental and Numerical Analysis","authors":"Abdul Basit, S. Abbas, Muhammad Mubashir Ajmal, U. A. Mughal, S. Kazmi, M. Munir","doi":"10.3390/infrastructures9040069","DOIUrl":"https://doi.org/10.3390/infrastructures9040069","url":null,"abstract":"This study undertakes a comprehensive experimental and numerical analysis of the structural integrity of buried RC sewerage pipes, focusing on the performance of two distinct jointing materials: cement mortar and non-shrinkage grout. Through joint shear tests on full-scale sewer pipes under single point loading conditions, notable effects on the crown and invert of the joint were observed, highlighting the critical vulnerability of these structures to internal and external pressures. Two materials—cement–sand mortar and non-shrinkage grout—were used in RC pipe joints to experimentally evaluate the joint strength of the sewerage pipes. Among the materials tested, cement–sand mortar emerged as the superior choice, demonstrating the ability to sustain higher loads up to 25.60 kN, proving its cost-effectiveness and versatility for use in various locations within RC pipe joints. Conversely, non-shrinkage grout exhibited the lowest ultimate failure load, i.e., 21.50 kN, emphasizing the importance of material selection in enhancing the resilience and durability of urban infrastructure. A 3D finite element (FE) analysis was also employed to assess the effect of various factors on stress distribution and joint deformation. The findings revealed a 10% divergence between the experimental and numerical data regarding the ultimate load capacity of pipe joints, with experimental tests indicating a 25.60 kN ultimate load and numerical simulations showing a 23.27 kN ultimate load. Despite this discrepancy, the close concordance between the two sets of data underscores the utility of numerical simulations in predicting the behavior of pipe joints accurately. This study provides valuable insights into the selection and application of jointing materials in sewerage systems, aiming to improve the structural integrity and longevity of such critical infrastructure.","PeriodicalId":502683,"journal":{"name":"Infrastructures","volume":"139 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140746762","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-04-01DOI: 10.3390/infrastructures9040068
Rosendo Lerma Villa, J. L. Reyes Araiza, José de Jesús Pérez Bueno, A. Manzano-Ramírez, Maria Luisa Mendoza López
Pervious concrete has great potential for use in many practical applications as a part of urban facilities that can add value through water harvesting and mitigating severe damage from floods. The construction and agricultural industries can take direct advantage of pervious concrete’s characteristics when water is a key factor included in projects as part of the useful life of a facility. Pervious concrete also has applications in vertical constructions, fountains, and pedestrian crossings. This work evidences that pervious concrete’s corrosion current increases with increasing aggregate size. Also, corrosion is a factor to consider only when steel pieces are immersed, aggravated by the presence of chlorine, but it drains water and does not retain moisture. Steel-reinforced pervious concrete was studied, and the grain size of the inert material and the corrosion process parameters were investigated. The electrochemical frequency modulation technique is proposed as a suitable test for a fast, reproducible assessment which, without damaging reinforced cement structures, particularly pervious concrete, indicates a trend of increasing corrosion current density as the size of the aggregate increases or density diminishes.
{"title":"Corrosion of Steel Rebars in Construction Materials with Reinforced Pervious Concrete","authors":"Rosendo Lerma Villa, J. L. Reyes Araiza, José de Jesús Pérez Bueno, A. Manzano-Ramírez, Maria Luisa Mendoza López","doi":"10.3390/infrastructures9040068","DOIUrl":"https://doi.org/10.3390/infrastructures9040068","url":null,"abstract":"Pervious concrete has great potential for use in many practical applications as a part of urban facilities that can add value through water harvesting and mitigating severe damage from floods. The construction and agricultural industries can take direct advantage of pervious concrete’s characteristics when water is a key factor included in projects as part of the useful life of a facility. Pervious concrete also has applications in vertical constructions, fountains, and pedestrian crossings. This work evidences that pervious concrete’s corrosion current increases with increasing aggregate size. Also, corrosion is a factor to consider only when steel pieces are immersed, aggravated by the presence of chlorine, but it drains water and does not retain moisture. Steel-reinforced pervious concrete was studied, and the grain size of the inert material and the corrosion process parameters were investigated. The electrochemical frequency modulation technique is proposed as a suitable test for a fast, reproducible assessment which, without damaging reinforced cement structures, particularly pervious concrete, indicates a trend of increasing corrosion current density as the size of the aggregate increases or density diminishes.","PeriodicalId":502683,"journal":{"name":"Infrastructures","volume":"56 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140770165","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-03-28DOI: 10.3390/infrastructures9040067
E. Sayhood, Nisreen S. Mohammed, Salam J. Hilo, Salih S. Salih
This paper presents a thorough investigation into the shear strength capacity of reinforced concrete deep beams, with a focus on improving predictive accuracy beyond existing code provisions. Analyzing 198 deep beams from 15 investigations, this study considers parameters such as the concrete compressive strength (f′c), the shear span-to-effective depth ratio (av/d), and reinforcement ratios (ps, pv, and ph). Introducing a novel predictive model, this study conducts a rigorous evaluation using a nonlinear regression analysis and statistical metrics (MAE, RMSE, and R2). The proposed model demonstrates a significant reduction in the coefficient of variation (CV) to 27.08%, surpassing existing codes’ limitations. Comparative analyses highlight the model’s robustness, revealing an improved convergence of data points and minimal sensitivity to variations in key parameters. The findings suggest that the proposed model offers enhanced predictive accuracy across diverse scenarios, making it a valuable tool for structural engineers. This research contributes to advancing the understanding of shear strength in reinforced concrete deep beams, offering a reliable and versatile predictive model with implications for refining design methodologies and enhancing safety with the efficiency of structural systems.
{"title":"Comprehensive Empirical Modeling of Shear Strength Prediction in Reinforced Concrete Deep Beams","authors":"E. Sayhood, Nisreen S. Mohammed, Salam J. Hilo, Salih S. Salih","doi":"10.3390/infrastructures9040067","DOIUrl":"https://doi.org/10.3390/infrastructures9040067","url":null,"abstract":"This paper presents a thorough investigation into the shear strength capacity of reinforced concrete deep beams, with a focus on improving predictive accuracy beyond existing code provisions. Analyzing 198 deep beams from 15 investigations, this study considers parameters such as the concrete compressive strength (f′c), the shear span-to-effective depth ratio (av/d), and reinforcement ratios (ps, pv, and ph). Introducing a novel predictive model, this study conducts a rigorous evaluation using a nonlinear regression analysis and statistical metrics (MAE, RMSE, and R2). The proposed model demonstrates a significant reduction in the coefficient of variation (CV) to 27.08%, surpassing existing codes’ limitations. Comparative analyses highlight the model’s robustness, revealing an improved convergence of data points and minimal sensitivity to variations in key parameters. The findings suggest that the proposed model offers enhanced predictive accuracy across diverse scenarios, making it a valuable tool for structural engineers. This research contributes to advancing the understanding of shear strength in reinforced concrete deep beams, offering a reliable and versatile predictive model with implications for refining design methodologies and enhancing safety with the efficiency of structural systems.","PeriodicalId":502683,"journal":{"name":"Infrastructures","volume":"20 11","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140373019","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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