Pub Date : 2024-02-22DOI: 10.3390/infrastructures9030037
Matthias Arnold, Sina Keller
This paper introduces a novel nothing-on-road (NOR) bridge weigh-in-motion (BWIM) approach with deep learning (DL) and non-invasive ground-based radar (GBR) time-series data. BWIMs allow site-specific structural health monitoring (SHM) but are usually difficult to attach and maintain. GBR measures the bridge deflection contactless. In this study, GBR and an unmanned aerial vehicle (UAV) monitor a two-span bridge in Germany to gather ground-truth data. Based on the UAV data, we determine vehicle type, lane, locus, speed, axle count, and axle spacing for single-presence vehicle crossings. Since displacement is a global response, using peak detection like conventional strain-based BWIMs is challenging. Therefore, we investigate data-driven machine learning approaches to extract the vehicle configurations directly from the displacement data. Despite a small and imbalanced real-world dataset, the proposed approaches classify, e.g., the axle count for trucks with a balanced accuracy of 76.7% satisfyingly. Additionally, we demonstrate that, for the selected bridge, high-frequency vibrations can coincide with axles crossing the junction between the street and the bridge. We evaluate whether filtering approaches via bandpass filtering or wavelet transform can be exploited for axle count and axle spacing identification. Overall, we can show that GBR is a serious contender for BWIM systems.
{"title":"Machine Learning and Signal Processing for Bridge Traffic Classification with Radar Displacement Time-Series Data","authors":"Matthias Arnold, Sina Keller","doi":"10.3390/infrastructures9030037","DOIUrl":"https://doi.org/10.3390/infrastructures9030037","url":null,"abstract":"This paper introduces a novel nothing-on-road (NOR) bridge weigh-in-motion (BWIM) approach with deep learning (DL) and non-invasive ground-based radar (GBR) time-series data. BWIMs allow site-specific structural health monitoring (SHM) but are usually difficult to attach and maintain. GBR measures the bridge deflection contactless. In this study, GBR and an unmanned aerial vehicle (UAV) monitor a two-span bridge in Germany to gather ground-truth data. Based on the UAV data, we determine vehicle type, lane, locus, speed, axle count, and axle spacing for single-presence vehicle crossings. Since displacement is a global response, using peak detection like conventional strain-based BWIMs is challenging. Therefore, we investigate data-driven machine learning approaches to extract the vehicle configurations directly from the displacement data. Despite a small and imbalanced real-world dataset, the proposed approaches classify, e.g., the axle count for trucks with a balanced accuracy of 76.7% satisfyingly. Additionally, we demonstrate that, for the selected bridge, high-frequency vibrations can coincide with axles crossing the junction between the street and the bridge. We evaluate whether filtering approaches via bandpass filtering or wavelet transform can be exploited for axle count and axle spacing identification. Overall, we can show that GBR is a serious contender for BWIM systems.","PeriodicalId":502683,"journal":{"name":"Infrastructures","volume":"2 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140441372","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 : 2024-02-22DOI: 10.3390/infrastructures9030038
Davide Forcellini, J. Thamboo, Mathavanayakam Sathurshan
Resilience of systems to natural hazards has become an interesting concept in civil engineering and it is based on the determination of the losses due to the impacts of natural hazards. In the last decades, many contributions have focused on the assessment of losses that may occur at the time of the event, as generally assumed for earthquakes. However, this assumption may be incorrect when the interval between the time of occurrence and the time when the system functionality reaches the minimum value needs to be considered. This paper aims to propose a novel method to quantify this interval, which is called disruption time, by proposing a novel formulation of the loss model based on infrastructure redundancy. The proposed method was herein applied to a case study that considers landslides in Sri Lanka. The main goal of the paper is to propose a formulation that can be implemented in a more comprehensive framework to calculate more realistically the resilience of systems to natural hazards.
{"title":"A Novel Loss Model to Include the Disruption Phase in the Quantification of Resilience to Natural Hazards","authors":"Davide Forcellini, J. Thamboo, Mathavanayakam Sathurshan","doi":"10.3390/infrastructures9030038","DOIUrl":"https://doi.org/10.3390/infrastructures9030038","url":null,"abstract":"Resilience of systems to natural hazards has become an interesting concept in civil engineering and it is based on the determination of the losses due to the impacts of natural hazards. In the last decades, many contributions have focused on the assessment of losses that may occur at the time of the event, as generally assumed for earthquakes. However, this assumption may be incorrect when the interval between the time of occurrence and the time when the system functionality reaches the minimum value needs to be considered. This paper aims to propose a novel method to quantify this interval, which is called disruption time, by proposing a novel formulation of the loss model based on infrastructure redundancy. The proposed method was herein applied to a case study that considers landslides in Sri Lanka. The main goal of the paper is to propose a formulation that can be implemented in a more comprehensive framework to calculate more realistically the resilience of systems to natural hazards.","PeriodicalId":502683,"journal":{"name":"Infrastructures","volume":"5 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140438883","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 : 2024-02-21DOI: 10.3390/infrastructures9030036
Kang Zhao, Qiong Zhou, Enqiang Zhao, Guofen Li, Yanan Dou
The prediction of the water film depth (WFD) on the road surface can help with road skid resistance research and reduce the risk associated with driving on rainy days. At present, there are many empirical and analytical models based on drainage length, slope, rainfall intensity and other parameters. Considering the influence of road surface runoff and starting from the Reynolds number formula of road surface water flow, a new road surface WFD calculation formula that considers the movement state of laminar water flow is derived. The results show that the changing trends of various parameters in the prediction model (drainage length, rainfall intensity, road slope) affecting WFD are consistent with those of the existing model. It is also found that the initial water film depth, initial speed of rainwater, and rainfall angle have little impact on WFD. The predicted value of the model has a suitable matching degree compared with the classical empirical model, which provides a new approach to the prediction of road water film depth.
{"title":"A New Water Film Depth Prediction Model for Pavement Surface Drainage","authors":"Kang Zhao, Qiong Zhou, Enqiang Zhao, Guofen Li, Yanan Dou","doi":"10.3390/infrastructures9030036","DOIUrl":"https://doi.org/10.3390/infrastructures9030036","url":null,"abstract":"The prediction of the water film depth (WFD) on the road surface can help with road skid resistance research and reduce the risk associated with driving on rainy days. At present, there are many empirical and analytical models based on drainage length, slope, rainfall intensity and other parameters. Considering the influence of road surface runoff and starting from the Reynolds number formula of road surface water flow, a new road surface WFD calculation formula that considers the movement state of laminar water flow is derived. The results show that the changing trends of various parameters in the prediction model (drainage length, rainfall intensity, road slope) affecting WFD are consistent with those of the existing model. It is also found that the initial water film depth, initial speed of rainwater, and rainfall angle have little impact on WFD. The predicted value of the model has a suitable matching degree compared with the classical empirical model, which provides a new approach to the prediction of road water film depth.","PeriodicalId":502683,"journal":{"name":"Infrastructures","volume":"7 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139957930","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 : 2024-02-16DOI: 10.3390/infrastructures9020035
Andrea Paliotto, M. Meocci
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.
{"title":"Development of a Network-Level Road Safety Assessment Procedure Based on Human Factors Principles","authors":"Andrea Paliotto, M. Meocci","doi":"10.3390/infrastructures9020035","DOIUrl":"https://doi.org/10.3390/infrastructures9020035","url":null,"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 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.","PeriodicalId":502683,"journal":{"name":"Infrastructures","volume":"53 10","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139961577","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 : 2024-02-16DOI: 10.3390/infrastructures9020034
Marco Guerrieri, G. Parla, Masoud Khanmohamadi, L. Neduzha
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.
{"title":"Asphalt Pavement Damage Detection through Deep Learning Technique and Cost-Effective Equipment: A Case Study in Urban Roads Crossed by Tramway Lines","authors":"Marco Guerrieri, G. Parla, Masoud Khanmohamadi, L. Neduzha","doi":"10.3390/infrastructures9020034","DOIUrl":"https://doi.org/10.3390/infrastructures9020034","url":null,"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 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.","PeriodicalId":502683,"journal":{"name":"Infrastructures","volume":"52 12","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139961458","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 : 2024-02-14DOI: 10.3390/infrastructures9020033
A. Ghanizadeh, Mandana Salehi, A. Mamou, Evangelos I. Koutras, Farhang Jalali, P. G. Asteris
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.
{"title":"Investigation of Subgrade Stabilization Life-Extending Benefits in Flexible Pavements Using a Non-Linear Mechanistic-Empirical Analysis","authors":"A. Ghanizadeh, Mandana Salehi, A. Mamou, Evangelos I. Koutras, Farhang Jalali, P. G. Asteris","doi":"10.3390/infrastructures9020033","DOIUrl":"https://doi.org/10.3390/infrastructures9020033","url":null,"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, 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.","PeriodicalId":502683,"journal":{"name":"Infrastructures","volume":"41 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139778891","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 : 2024-02-14DOI: 10.3390/infrastructures9020033
A. Ghanizadeh, Mandana Salehi, A. Mamou, Evangelos I. Koutras, Farhang Jalali, P. G. Asteris
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.
{"title":"Investigation of Subgrade Stabilization Life-Extending Benefits in Flexible Pavements Using a Non-Linear Mechanistic-Empirical Analysis","authors":"A. Ghanizadeh, Mandana Salehi, A. Mamou, Evangelos I. Koutras, Farhang Jalali, P. G. Asteris","doi":"10.3390/infrastructures9020033","DOIUrl":"https://doi.org/10.3390/infrastructures9020033","url":null,"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, 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.","PeriodicalId":502683,"journal":{"name":"Infrastructures","volume":"93 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139838721","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 : 2024-02-13DOI: 10.3390/infrastructures9020032
Maja Ahac, Saša Ahac, Igor Majstorović, Ž. Stepan
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.
{"title":"Contribution to Rail System Revitalization, Development, and Integration Projects Evaluation: A Case Study of the Zadar Urban Area","authors":"Maja Ahac, Saša Ahac, Igor Majstorović, Ž. Stepan","doi":"10.3390/infrastructures9020032","DOIUrl":"https://doi.org/10.3390/infrastructures9020032","url":null,"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 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.","PeriodicalId":502683,"journal":{"name":"Infrastructures","volume":"7 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139841013","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 : 2024-02-13DOI: 10.3390/infrastructures9020032
Maja Ahac, Saša Ahac, Igor Majstorović, Ž. Stepan
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.
{"title":"Contribution to Rail System Revitalization, Development, and Integration Projects Evaluation: A Case Study of the Zadar Urban Area","authors":"Maja Ahac, Saša Ahac, Igor Majstorović, Ž. Stepan","doi":"10.3390/infrastructures9020032","DOIUrl":"https://doi.org/10.3390/infrastructures9020032","url":null,"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 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.","PeriodicalId":502683,"journal":{"name":"Infrastructures","volume":"114 18","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139781121","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 : 2024-02-10DOI: 10.3390/infrastructures9020031
Mark A. Denisenko, Alina S. Isaeva, A. Sinyukin, Andrey V. Kovalev
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.
{"title":"A Method for Measuring the Mass of a Railroad Car Using an Artificial Neural Network","authors":"Mark A. Denisenko, Alina S. Isaeva, A. Sinyukin, Andrey V. Kovalev","doi":"10.3390/infrastructures9020031","DOIUrl":"https://doi.org/10.3390/infrastructures9020031","url":null,"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 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.","PeriodicalId":502683,"journal":{"name":"Infrastructures","volume":"196 3-4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139847330","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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