Pub Date : 2023-09-04DOI: 10.3390/infrastructures8090132
Haneen AlTawaiha, Fadi Alhomaidat, Tamer Eljufout
The incorporation of nanotechnology has led to significant strides in the concrete industry, ushering in innovative construction methodologies. Various nanomaterials, including nano-silica (NS), have undergone comprehensive scrutiny as potential partial substitutes for cement in concrete formulations. This article aims to provide a comprehensive overview of the impacts of NS on several mechanical properties of concrete, encompassing compressive, split tensile, and flexural strengths. Additionally, the review delves into the influence of NS on the concrete’s durability, including microstructural characterization and the eradication of structural micropores. NS has demonstrated the capacity to bolster both strength and durability while concurrently diminishing structural micropores. Moreover, this review explores the contemporary status of NS application in cement concrete and presents avenues for prospective research. The assessment of engineering attributes becomes imperative for concrete infused with nano-silica. This encompasses aspects like bond strength, creep, shrinkage, and more. A rigorous evaluation of fresh and hardened properties is necessary to discern the material’s thermal and acoustical characteristics. Such a comprehensive understanding contributes to a holistic evaluation of the material’s adaptability across diverse applications.
{"title":"A Review of the Effect of Nano-Silica on the Mechanical and Durability Properties of Cementitious Composites","authors":"Haneen AlTawaiha, Fadi Alhomaidat, Tamer Eljufout","doi":"10.3390/infrastructures8090132","DOIUrl":"https://doi.org/10.3390/infrastructures8090132","url":null,"abstract":"The incorporation of nanotechnology has led to significant strides in the concrete industry, ushering in innovative construction methodologies. Various nanomaterials, including nano-silica (NS), have undergone comprehensive scrutiny as potential partial substitutes for cement in concrete formulations. This article aims to provide a comprehensive overview of the impacts of NS on several mechanical properties of concrete, encompassing compressive, split tensile, and flexural strengths. Additionally, the review delves into the influence of NS on the concrete’s durability, including microstructural characterization and the eradication of structural micropores. NS has demonstrated the capacity to bolster both strength and durability while concurrently diminishing structural micropores. Moreover, this review explores the contemporary status of NS application in cement concrete and presents avenues for prospective research. The assessment of engineering attributes becomes imperative for concrete infused with nano-silica. This encompasses aspects like bond strength, creep, shrinkage, and more. A rigorous evaluation of fresh and hardened properties is necessary to discern the material’s thermal and acoustical characteristics. Such a comprehensive understanding contributes to a holistic evaluation of the material’s adaptability across diverse applications.","PeriodicalId":13601,"journal":{"name":"Infrastructures","volume":" ","pages":""},"PeriodicalIF":2.6,"publicationDate":"2023-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48829161","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 : 2023-09-01DOI: 10.3390/infrastructures8090131
V. Kovalchuk, M. Sysyn, Majid Movahedi Rad, S. Fischer
Methods of increasing the bearing capacity of corrugated metal structures of transport constructions using transversal stiffening ribs in the form of additional corrugation and stiffeners are given. Based on the theory of elasticity, a mathematical model for estimating the stress-strain state of transport constructions made of corrugated metal structures reinforced with stiffening ribs in the form of double corrugation was developed. The method of determining equivalent forces during rolling stock passage is offered. It has been established that double corrugation increases the bearing capacity of corrugated metal structures. Therefore, additional corrugation of corrugated metal structures reduces stresses by up to 20% and deflections by 50%. The obtained results show that the increase in rolling stock speed does not lead to a significant increase in stresses and strains in CMS when the railway track corresponds to the design state.
{"title":"Investigation of the Bearing Capacity of Transport Constructions Made of Corrugated Metal Structures Reinforced with Transversal Stiffening Ribs","authors":"V. Kovalchuk, M. Sysyn, Majid Movahedi Rad, S. Fischer","doi":"10.3390/infrastructures8090131","DOIUrl":"https://doi.org/10.3390/infrastructures8090131","url":null,"abstract":"Methods of increasing the bearing capacity of corrugated metal structures of transport constructions using transversal stiffening ribs in the form of additional corrugation and stiffeners are given. Based on the theory of elasticity, a mathematical model for estimating the stress-strain state of transport constructions made of corrugated metal structures reinforced with stiffening ribs in the form of double corrugation was developed. The method of determining equivalent forces during rolling stock passage is offered. It has been established that double corrugation increases the bearing capacity of corrugated metal structures. Therefore, additional corrugation of corrugated metal structures reduces stresses by up to 20% and deflections by 50%. The obtained results show that the increase in rolling stock speed does not lead to a significant increase in stresses and strains in CMS when the railway track corresponds to the design state.","PeriodicalId":13601,"journal":{"name":"Infrastructures","volume":" ","pages":""},"PeriodicalIF":2.6,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41711256","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 : 2023-08-26DOI: 10.3390/infrastructures8090130
Yuxiang Zhang, Reamonn MacReamoinn, P. Cardiff, J. Keenahan
Aerodynamic performance is of critical importance to the design of long-span bridges. Computational fluid dynamics (CFD) modelling offers bridge designers an opportunity to investigate aerodynamic performance for long-span bridges during the design phase as well as during operation of the bridge. It offers distinct advantages when compared with the current standard practice of wind tunnel testing, which can have several limitations. The proposed revisions to the Eurocodes offer CFD as a methodology for wind analysis of bridges. Practicing engineers have long sought a computationally affordable, viable, and robust framework for industrial applications of using CFD to examine wind effects on long-span bridges. To address this gap in the literature and guidance, this paper explicitly presents a framework and demonstrates a workflow of analyzing wind effects on long-span bridges using open-source software, namely FreeCAD, OpenFOAM, and ParaView. Example cases are presented, and detailed configurations and general guidance are discussed during each step. A summary is provided of the validation of this methodology with field data collected from the structural health monitoring (SHM) systems of two long-span bridges.
{"title":"Analyzing Wind Effects on Long-Span Bridges: A Viable Numerical Modelling Methodology Using OpenFOAM for Industrial Applications","authors":"Yuxiang Zhang, Reamonn MacReamoinn, P. Cardiff, J. Keenahan","doi":"10.3390/infrastructures8090130","DOIUrl":"https://doi.org/10.3390/infrastructures8090130","url":null,"abstract":"Aerodynamic performance is of critical importance to the design of long-span bridges. Computational fluid dynamics (CFD) modelling offers bridge designers an opportunity to investigate aerodynamic performance for long-span bridges during the design phase as well as during operation of the bridge. It offers distinct advantages when compared with the current standard practice of wind tunnel testing, which can have several limitations. The proposed revisions to the Eurocodes offer CFD as a methodology for wind analysis of bridges. Practicing engineers have long sought a computationally affordable, viable, and robust framework for industrial applications of using CFD to examine wind effects on long-span bridges. To address this gap in the literature and guidance, this paper explicitly presents a framework and demonstrates a workflow of analyzing wind effects on long-span bridges using open-source software, namely FreeCAD, OpenFOAM, and ParaView. Example cases are presented, and detailed configurations and general guidance are discussed during each step. A summary is provided of the validation of this methodology with field data collected from the structural health monitoring (SHM) systems of two long-span bridges.","PeriodicalId":13601,"journal":{"name":"Infrastructures","volume":" ","pages":""},"PeriodicalIF":2.6,"publicationDate":"2023-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44764888","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 : 2023-08-25DOI: 10.3390/infrastructures8090128
Vishnupriya Jonnalagadda, J. Y. Lee, Jie Zhao, S. Ghasemi
The nation’s transportation systems are complex and are some of the highest valued and largest public assets in the United States. As a result of repeated natural hazards and their significant impact on transportation functionality and the socioeconomic health of communities, transportation resilience has gained increasing attention in recent years. Previous studies on transportation resilience have heavily emphasized network functionality during and/or following a scenario hazard event by implicitly assuming that sufficient knowledge of structural capacity and environmental/service conditions is available at the time of an extreme event. However, such assumptions often fail to consider uncertainties that arise when an extreme hazard event occurs in the future. Thus, it is essential to quantify and reduce uncertainties to better prepare for extreme events and accurately assess transportation resilience. To this end, this paper proposes a dynamic Bayesian network-based resilience assessment model for a large-scale roadway network that can explicitly quantify uncertainties in all phases of the assessment and investigate the role of inspection and monitoring programs in uncertainty reduction. Specifically, the significance of data reliability is investigated through a sensitivity analysis, where various sets of data having different reliabilities are used in updating system resilience. To evaluate the effectiveness of the model, a benchmark problem involving a highway network in South Carolina, USA is utilized, showcasing the systematic quantification and reduction of uncertainties in the proposed model. The benchmark problem result shows that incorporating monitoring and inspection data on important variables could improve the accuracy of predicting the seismic resilience of the network. It also suggests the need to consider equipment reliability when designing monitoring and inspection programs. With the recent development of a wide range of monitoring and inspection techniques, including nondestructive testing, health monitoring equipment, satellite imagery, LiDAR, etc., these findings can be useful in assisting transportation managers in identifying necessary equipment reliability levels and prioritizing inspection and monitoring efforts.
{"title":"Quantification and Reduction of Uncertainty in Seismic Resilience Assessment for a Roadway Network","authors":"Vishnupriya Jonnalagadda, J. Y. Lee, Jie Zhao, S. Ghasemi","doi":"10.3390/infrastructures8090128","DOIUrl":"https://doi.org/10.3390/infrastructures8090128","url":null,"abstract":"The nation’s transportation systems are complex and are some of the highest valued and largest public assets in the United States. As a result of repeated natural hazards and their significant impact on transportation functionality and the socioeconomic health of communities, transportation resilience has gained increasing attention in recent years. Previous studies on transportation resilience have heavily emphasized network functionality during and/or following a scenario hazard event by implicitly assuming that sufficient knowledge of structural capacity and environmental/service conditions is available at the time of an extreme event. However, such assumptions often fail to consider uncertainties that arise when an extreme hazard event occurs in the future. Thus, it is essential to quantify and reduce uncertainties to better prepare for extreme events and accurately assess transportation resilience. To this end, this paper proposes a dynamic Bayesian network-based resilience assessment model for a large-scale roadway network that can explicitly quantify uncertainties in all phases of the assessment and investigate the role of inspection and monitoring programs in uncertainty reduction. Specifically, the significance of data reliability is investigated through a sensitivity analysis, where various sets of data having different reliabilities are used in updating system resilience. To evaluate the effectiveness of the model, a benchmark problem involving a highway network in South Carolina, USA is utilized, showcasing the systematic quantification and reduction of uncertainties in the proposed model. The benchmark problem result shows that incorporating monitoring and inspection data on important variables could improve the accuracy of predicting the seismic resilience of the network. It also suggests the need to consider equipment reliability when designing monitoring and inspection programs. With the recent development of a wide range of monitoring and inspection techniques, including nondestructive testing, health monitoring equipment, satellite imagery, LiDAR, etc., these findings can be useful in assisting transportation managers in identifying necessary equipment reliability levels and prioritizing inspection and monitoring efforts.","PeriodicalId":13601,"journal":{"name":"Infrastructures","volume":" ","pages":""},"PeriodicalIF":2.6,"publicationDate":"2023-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47538847","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 : 2023-08-25DOI: 10.3390/infrastructures8090129
S. Maalek, Reza Maalek, Bahareh Maalek
This paper examined the opportunities of composite double-layer grid superstructures in short-to-medium span bridge decks. It was empirically shown here that a double-layer grid deck system in composite action with a thin layer of two−way reinforced concrete slab introduced several structural advantages over the conventional composite plate-girder superstructure system. These advantages included improved seismic performance, increased structural rigidity, reduced deck vibration, increased failure capacity, and so on. Optimally proportioned space grid superstructures were found to be less prone to progressive collapse, increasing structural reliability and resilience, while reducing the risk of sudden failure. Through a set of dynamic time-series experiments, considerable enhancement in load transfer efficiency in the transverse direction under dynamic truck loading was gained. Furthermore, the multi-objective generative optimization of the proposed spatial grid bridge (with integral variable depth) using evolutionary optimization methods was examined. Finally, comprehensive discussions were given on: (i) mechanical properties, such as fatigue behavior, corrosion, durability, and behavior in cold environments; (ii) health monitoring aspects, such as ease of inspection, maintenance, and access for the installation of remote monitoring devices; (iii) sustainability considerations, such as reduction of embodied Carbon and energy due to reduced material waste, along with ease of demolition, deconstruction and reuse after lifecycle design; and (iv) lean management aspects, such as support for industrialized construction and mass customization. It was concluded that the proposed spatial grid system shows promise for building essential and sustainable infrastructures of the future.
{"title":"Intrinsic Properties of Composite Double Layer Grid Superstructures","authors":"S. Maalek, Reza Maalek, Bahareh Maalek","doi":"10.3390/infrastructures8090129","DOIUrl":"https://doi.org/10.3390/infrastructures8090129","url":null,"abstract":"This paper examined the opportunities of composite double-layer grid superstructures in short-to-medium span bridge decks. It was empirically shown here that a double-layer grid deck system in composite action with a thin layer of two−way reinforced concrete slab introduced several structural advantages over the conventional composite plate-girder superstructure system. These advantages included improved seismic performance, increased structural rigidity, reduced deck vibration, increased failure capacity, and so on. Optimally proportioned space grid superstructures were found to be less prone to progressive collapse, increasing structural reliability and resilience, while reducing the risk of sudden failure. Through a set of dynamic time-series experiments, considerable enhancement in load transfer efficiency in the transverse direction under dynamic truck loading was gained. Furthermore, the multi-objective generative optimization of the proposed spatial grid bridge (with integral variable depth) using evolutionary optimization methods was examined. Finally, comprehensive discussions were given on: (i) mechanical properties, such as fatigue behavior, corrosion, durability, and behavior in cold environments; (ii) health monitoring aspects, such as ease of inspection, maintenance, and access for the installation of remote monitoring devices; (iii) sustainability considerations, such as reduction of embodied Carbon and energy due to reduced material waste, along with ease of demolition, deconstruction and reuse after lifecycle design; and (iv) lean management aspects, such as support for industrialized construction and mass customization. It was concluded that the proposed spatial grid system shows promise for building essential and sustainable infrastructures of the future.","PeriodicalId":13601,"journal":{"name":"Infrastructures","volume":" ","pages":""},"PeriodicalIF":2.6,"publicationDate":"2023-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42004873","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 : 2023-08-24DOI: 10.3390/infrastructures8090127
Carlos M. Chang, Gianine Tejada Salinas, Teresa Salinas Gamero, Stella Schroeder, Mario A. Vélez Canchanya, Syeda Lamiya Mahnaz
Over the next decades, people will continue moving to urban areas all over the world, increasing infrastructure needs to satisfy economic, environmental, and social demands. The connection between civil urban infrastructure and smart cities is strong due to the common goal of fulfilling public service demands. Infrastructure management contributes to the development, evolution, and sustainability of smart cities. The main problem with traditional approaches to the development, evolution, and sustainability of smart cities is the lack of a holistic, integrated vision of infrastructure management. The main objective of this research is to introduce an infrastructure management humanistic approach with a smart city conceptual model that also considers an educational perspective. A mixed research methodology that combines quantitative and qualitative approaches was used, applying inductive-deductive tools. The paper concludes with the development of an infrastructure management framework for smart cities with five dimensions: (1) Environmental, (2) financial-economic, (3) political-governance, (4) social-people, and (5) technological. Two case studies for the cities of Lima and Piura in Perú illustrate how to incorporate this framework into practice. The research products are relevant because they foster an inclusive better quality of life for all citizens by preserving civil infrastructure systems.
{"title":"An Infrastructure Management Humanistic Approach for Smart Cities Development, Evolution, and Sustainability","authors":"Carlos M. Chang, Gianine Tejada Salinas, Teresa Salinas Gamero, Stella Schroeder, Mario A. Vélez Canchanya, Syeda Lamiya Mahnaz","doi":"10.3390/infrastructures8090127","DOIUrl":"https://doi.org/10.3390/infrastructures8090127","url":null,"abstract":"Over the next decades, people will continue moving to urban areas all over the world, increasing infrastructure needs to satisfy economic, environmental, and social demands. The connection between civil urban infrastructure and smart cities is strong due to the common goal of fulfilling public service demands. Infrastructure management contributes to the development, evolution, and sustainability of smart cities. The main problem with traditional approaches to the development, evolution, and sustainability of smart cities is the lack of a holistic, integrated vision of infrastructure management. The main objective of this research is to introduce an infrastructure management humanistic approach with a smart city conceptual model that also considers an educational perspective. A mixed research methodology that combines quantitative and qualitative approaches was used, applying inductive-deductive tools. The paper concludes with the development of an infrastructure management framework for smart cities with five dimensions: (1) Environmental, (2) financial-economic, (3) political-governance, (4) social-people, and (5) technological. Two case studies for the cities of Lima and Piura in Perú illustrate how to incorporate this framework into practice. The research products are relevant because they foster an inclusive better quality of life for all citizens by preserving civil infrastructure systems.","PeriodicalId":13601,"journal":{"name":"Infrastructures","volume":" ","pages":""},"PeriodicalIF":2.6,"publicationDate":"2023-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43796059","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 : 2023-08-14DOI: 10.3390/infrastructures8080125
A. Ghanizadeh, Ahmad Aziminejad, P. G. Asteris, D. J. Armaghani
Earthquake-induced soil liquefaction (EISL) can cause significant damage to structures, facilities, and vital urban arteries. Thus, the accurate prediction of EISL is a challenge for geotechnical engineers in mitigating irreparable loss to buildings and human lives. This research aims to propose a binary classification model based on the hybrid method of a wavelet neural network (WNN) and particle swarm optimization (PSO) to predict EISL based on cone penetration test (CPT) results. To this end, a well-known dataset consisting of 109 datapoints has been used. The developed WNN-PSO model can predict liquefaction with an overall accuracy of 99.09% based on seven input variables, including total vertical stress (σv), effective vertical stress (σv′), mean grain size (D50), normalized peak horizontal acceleration at ground surface (αmax), cone resistance (qc), cyclic stress ratio (CSR), and earthquake magnitude (Mw). The results show that the proposed WNN-PSO model has superior performance against other computational intelligence models. The results of sensitivity analysis using the neighborhood component analysis (NCA) method reveal that among the seven input variables, qc has the highest degree of importance and Mw has the lowest degree of importance in predicting EISL.
{"title":"Soft Computing to Predict Earthquake-Induced Soil Liquefaction via CPT Results","authors":"A. Ghanizadeh, Ahmad Aziminejad, P. G. Asteris, D. J. Armaghani","doi":"10.3390/infrastructures8080125","DOIUrl":"https://doi.org/10.3390/infrastructures8080125","url":null,"abstract":"Earthquake-induced soil liquefaction (EISL) can cause significant damage to structures, facilities, and vital urban arteries. Thus, the accurate prediction of EISL is a challenge for geotechnical engineers in mitigating irreparable loss to buildings and human lives. This research aims to propose a binary classification model based on the hybrid method of a wavelet neural network (WNN) and particle swarm optimization (PSO) to predict EISL based on cone penetration test (CPT) results. To this end, a well-known dataset consisting of 109 datapoints has been used. The developed WNN-PSO model can predict liquefaction with an overall accuracy of 99.09% based on seven input variables, including total vertical stress (σv), effective vertical stress (σv′), mean grain size (D50), normalized peak horizontal acceleration at ground surface (αmax), cone resistance (qc), cyclic stress ratio (CSR), and earthquake magnitude (Mw). The results show that the proposed WNN-PSO model has superior performance against other computational intelligence models. The results of sensitivity analysis using the neighborhood component analysis (NCA) method reveal that among the seven input variables, qc has the highest degree of importance and Mw has the lowest degree of importance in predicting EISL.","PeriodicalId":13601,"journal":{"name":"Infrastructures","volume":" ","pages":""},"PeriodicalIF":2.6,"publicationDate":"2023-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47069983","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 : 2023-08-14DOI: 10.3390/infrastructures8080126
V. Jover, Z. Major, A. Németh, D. Kurhan, M. Sysyn, S. Fischer
In the 21st century, one of the key requirements is to develop and maintain our infrastructure facilities most efficiently using the available resources. Tramways are of significant national economic importance and represent an important national asset. There are currently seven different types of superstructure systems in Hungary, based on the national regulations and the related requirements currently in force. This paper compares the paved tramway superstructure systems in the context of track geometry, through-rolled axle tons of track, and the age of track sections. Paved tracks have many benefits, but the main ones are easier maintenance and road traffic use. Elastically supported continuous rail bedding (ESCRB; in Hungary, this is known as “RAFS”) and “large” slab superstructure systems are used to create paved superstructure systems. Road crossings use the latter systems, while heavily loaded lines use several ESCRB systems. This article examines the geometrical changes in several ESCRB superstructure systems. A TrackScan 4.01 instrument was used to take measurements in June and September 2021 and in April 2022, September 2022, and May 2023. Track gauge, alignment, and longitudinal level are examined. Regardless of the ESCRB superstructure system or age, a medium-loaded line’s track gauge trendline increases, which means that the track gauge is widening and, regardless of traffic load or age, the average longitudinal level is constantly increasing from year to year. When it is a medium-loaded line, the average value of alignment increases slightly, and the trendline is almost straight, but it decreases when it is an extremely heavily loaded line. The authors will analyze how the reference track section will change in the future. Based on the results, it is important to assess how subsequent measurements affect the trend lines. Because the data evaluations show similar results, comparing open tramway tracks to paved ones is crucial.
{"title":"Investigation of the Geometrical Deterioration of Paved Superstructure Tramway Tracks in Budapest (Hungary)","authors":"V. Jover, Z. Major, A. Németh, D. Kurhan, M. Sysyn, S. Fischer","doi":"10.3390/infrastructures8080126","DOIUrl":"https://doi.org/10.3390/infrastructures8080126","url":null,"abstract":"In the 21st century, one of the key requirements is to develop and maintain our infrastructure facilities most efficiently using the available resources. Tramways are of significant national economic importance and represent an important national asset. There are currently seven different types of superstructure systems in Hungary, based on the national regulations and the related requirements currently in force. This paper compares the paved tramway superstructure systems in the context of track geometry, through-rolled axle tons of track, and the age of track sections. Paved tracks have many benefits, but the main ones are easier maintenance and road traffic use. Elastically supported continuous rail bedding (ESCRB; in Hungary, this is known as “RAFS”) and “large” slab superstructure systems are used to create paved superstructure systems. Road crossings use the latter systems, while heavily loaded lines use several ESCRB systems. This article examines the geometrical changes in several ESCRB superstructure systems. A TrackScan 4.01 instrument was used to take measurements in June and September 2021 and in April 2022, September 2022, and May 2023. Track gauge, alignment, and longitudinal level are examined. Regardless of the ESCRB superstructure system or age, a medium-loaded line’s track gauge trendline increases, which means that the track gauge is widening and, regardless of traffic load or age, the average longitudinal level is constantly increasing from year to year. When it is a medium-loaded line, the average value of alignment increases slightly, and the trendline is almost straight, but it decreases when it is an extremely heavily loaded line. The authors will analyze how the reference track section will change in the future. Based on the results, it is important to assess how subsequent measurements affect the trend lines. Because the data evaluations show similar results, comparing open tramway tracks to paved ones is crucial.","PeriodicalId":13601,"journal":{"name":"Infrastructures","volume":" ","pages":""},"PeriodicalIF":2.6,"publicationDate":"2023-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42298555","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 : 2023-08-11DOI: 10.3390/infrastructures8080123
R. Trach
Recently, the bridge infrastructure in Ukraine has faced the problem of having a significant number of damaged bridges. It is obvious that the repair and restoration of bridges should be preceded by a procedure consisting of visual inspection and evaluation of the technical condition. The problem of fast and high-quality collection, processing and storing large datasets is gaining more and more relevance. An effective way to solve this problem is to use various machine learning methods in bridge infrastructure management. The purpose of this study was to create a model based on convolutional neural networks (CNNs) for classifying images of concrete bridge elements into four classes: “defect free”, “crack”, “spalling” and “popout”. The eight CNN models were created and used to conduct its training, validation and testing. In general, it can be stated that all CNN models showed high performance. The analysis of loss function (categorical cross-entropy) and quality measure (accuracy) showed that the model on the MobileNet architecture has optimal values (loss, 0.0264, and accuracy, 94.61%). This model can be used further without retraining, and it can classify images on datasets that it has not yet “seen”. Practical use of such a model allows for the identification of three damage types.
{"title":"A Model Classifying Four Classes of Defects in Reinforced Concrete Bridge Elements Using Convolutional Neural Networks","authors":"R. Trach","doi":"10.3390/infrastructures8080123","DOIUrl":"https://doi.org/10.3390/infrastructures8080123","url":null,"abstract":"Recently, the bridge infrastructure in Ukraine has faced the problem of having a significant number of damaged bridges. It is obvious that the repair and restoration of bridges should be preceded by a procedure consisting of visual inspection and evaluation of the technical condition. The problem of fast and high-quality collection, processing and storing large datasets is gaining more and more relevance. An effective way to solve this problem is to use various machine learning methods in bridge infrastructure management. The purpose of this study was to create a model based on convolutional neural networks (CNNs) for classifying images of concrete bridge elements into four classes: “defect free”, “crack”, “spalling” and “popout”. The eight CNN models were created and used to conduct its training, validation and testing. In general, it can be stated that all CNN models showed high performance. The analysis of loss function (categorical cross-entropy) and quality measure (accuracy) showed that the model on the MobileNet architecture has optimal values (loss, 0.0264, and accuracy, 94.61%). This model can be used further without retraining, and it can classify images on datasets that it has not yet “seen”. Practical use of such a model allows for the identification of three damage types.","PeriodicalId":13601,"journal":{"name":"Infrastructures","volume":" ","pages":""},"PeriodicalIF":2.6,"publicationDate":"2023-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45822049","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 : 2023-08-11DOI: 10.3390/infrastructures8080124
Ammar Alnmr, Ashraf Sheble, R. Ray, H. Ahmad
The growing demand for transportation tunnels in densely populated urban areas has led to the widespread adoption of twin tunnel configurations in contemporary infrastructure projects. This research focuses on investigating the complex interaction between soil, structures, and the excavation of twin tunnels. The study employs the tunnel boring machine (TBM) method and utilizes two-dimensional numerical modeling based on the finite element method (FEM). The numerical model is validated by comparing its results with field measurements obtained from a twin tunnel project in Italy, specifically the New Milan Metro Line 5. A comprehensive parametric study is conducted to analyze various parameters that influence soil–structure interaction during tunnel excavation. These parameters include the positioning of the tunnels in relation to each other, the spacing between them, the presence of structures above the tunnels, eccentricity between the structure axis and tunnel axis, and tunnel depth and diameter. Moreover, a comparative analysis is performed between scenarios with and without structures to elucidate the impact of structure presence on the interaction phenomenon. The research findings provide valuable insights into the intricate behavior of twin tunnels and their interaction with the surrounding soil and structures.
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