The Experts below are selected from a list of 22623 Experts worldwide ranked by ideXlab platform
Christopher P L Barkan - One of the best experts on this subject based on the ideXlab platform.
-
Freight-train derailment rates for railroad safety and risk analysis.
Accident; analysis and prevention, 2016Co-Authors: Xiang Liu, M. Rapik Saat, Christopher P L BarkanAbstract:Derailments are the most common type of train accident in the United States. They cause damage to infrastructure, rolling stock and lading, disrupt service, and have the potential to cause casualties, and harm the environment. Train safety and risk analysis relies on accurate assessment of derailment likelihood. Derailment rate - the number of Derailments normalized by traffic exposure - is a useful statistic to estimate the likelihood of a derailment. Despite its importance, derailment rate analysis using multiple factors has not been previously developed. In this paper, we present an analysis of derailment rates on Class I railroad mainlines based on data from the U.S. Federal Railroad Administration and the major freight railroads. The point estimator and confidence interval of train and car derailment rates are developed by FRA track class, method of operation and annual traffic density. The analysis shows that signaled track with higher FRA track class and higher traffic density is associated with a lower derailment rate. The new accident rates have important implications for safety and risk management decisions, such as the routing of hazardous materials.
-
optimization of ultrasonic rail defect inspection for improving railway transportation safety and efficiency
Journal of Transportation Engineering-asce, 2014Co-Authors: Xiang Liu, Rapik M Saat, Tyler Dick, Alexander Lovett, Christopher P L BarkanAbstract:Broken rails are the most frequent cause of freight-train Derailments in the United States. Consequently, reducing their occurrence is a high priority for the rail industry and the U.S. Federal Railroad Administration. Current practice is to periodically inspect rails to detect defects using nondestructive technology such as ultrasonic inspection. Determining the optimal rail inspection frequency is critical to efficient use of infrastructure management resources and maximizing the beneficial impact on safety. Minimization of derailment risk, costs of inspection vehicle operation, rail defect repair, and corresponding train delay are all affected by rail inspection frequency. However, no prior research has incorporated all of these factors into a single integrated framework. The objective of this paper is to develop an analytical model to address the trade-offs among various factors related to rail defect inspection frequency, so as to maximize railroad safety and efficiency. The analysis shows that the optimal inspection frequency will vary with traffic density, rail age, inspection technology reliability, and other factors. The optimization model provides a tool that can be used to aid development of better-informed, more effective infrastructure management and accident prevention policies and practices.
-
understanding the risk of level crossing Derailments
Railway Gazette international, 2014Co-Authors: Samantha G Chadwick, Rapik Saat, Tyler Dick, Christopher P L BarkanAbstract:One of the biggest remaining safety risks to rail operations in many countries is posed by level crossings. In order to help prioritize investment in the upgrading or removal of crossings, it is important to develop a tool to identify the potential risk of train Derailments. A crossing derailment prediction model has been developed, for which it is necessary to understand the chain of events leading to a given consequence and identify the probability of each event occurring. The impact of faster train speeds is an area of concern, and with limited funds available to spend on upgrading level crossings, targeted improvements need to be made. It is suggested that combining the level crossing models and models for other risks into a systems-wide analysis tool would be beneficial to the rail industry as a whole, as well as to surrounding communities so that they can create better risk mitigation strategies. This in turn would provide a tool to aid in decision making regarding infrastructure improvements and the allocation of limited funds available.
-
analysis of u s freight train derailment severity using zero truncated negative binomial regression and quantile regression
Accident Analysis & Prevention, 2013Co-Authors: Rapik M Saat, Christopher P L BarkanAbstract:Derailments are the most common type of freight-train accidents in the United States. Derailments cause damage to infrastructure and rolling stock, disrupt services, and may cause casualties and harm the environment. Accordingly, derailment analysis and prevention has long been a high priority in the rail industry and government. Despite the low probability of a train derailment, the potential for severe consequences justify the need to better understand the factors influencing train derailment severity. In this paper, a zero-truncated negative binomial (ZTNB) regression model is developed to estimate the conditional mean of train derailment severity. Recognizing that the mean is not the only statistic describing data distribution, a quantile regression (QR) model is also developed to estimate derailment severity at different quantiles. The two regression models together provide a better understanding of train derailment severity distribution. Results of this work can be used to estimate train derailment severity under various operational conditions and by different accident causes. This research is intended to provide insights regarding development of cost-efficient train safety policies.
-
analysis of causes of major train derailment and their effect on accident rates
Transportation Research Record, 2012Co-Authors: Xiang Liu, Mohd Rapik Saat, Christopher P L BarkanAbstract:Analysis of the causes of train accidents is critical for rational allocation of resources to reduce accident occurrence in the most cost-effective manner possible. Train derailment data from the FRA rail equipment accident database for the interval 2001 to 2010 were analyzed for each track type, with accounting for frequency of occurrence by cause and number of cars derailed. Statistical analyses were conducted to examine the effects of accident cause, type of track, and derailment speed. The analysis showed that broken rails or welds were the leading derailment cause on main, yard, and siding tracks. By contrast to accident causes on main tracks, bearing failures and broken wheels were not among the top accident causes on yard or siding tracks. Instead, human factor-related causes such as improper use of switches and violation of switching rules were more prevalent. In all speed ranges, broken rails or welds were the leading cause of Derailments; however, the relative frequency of the next most common a...
Xiang Liu - One of the best experts on this subject based on the ideXlab platform.
-
Probabilistic Risk Analysis of Broken Rail-Caused Train Derailments
2020 Joint Rail Conference, 2020Co-Authors: Zhipeng Zhang, Kang Zhou, Xiang LiuAbstract:Abstract Broken-rail prevention and risk management have been being a major activity for a long time for the railroad industry. The major objective of this research is to evaluate and analyze the broken rail-caused derailment risk using Artificial Intelligence (AI) approaches. The risk model is primarily built upon 1) broken rail probability; 2) probability of broken-rail derailment given a broken rail; and 3) derailment severity, measured by the number of cars derailed. The train derailment risk accounts for derailment probability and derailment consequences simultaneously. Due to the low frequency of broken-rail Derailments, it is desirable to estimate the probability of broken rail-caused Derailments through the broken rail occurrence. The estimation of the probability of broken rail-caused derailment includes the conditional probability of derailment given broken rail occurrence and the probability of broken rail occurrence. More specially, the probability of broken-rail derailment given a broken rail can be estimated by the statistical relationship between broken-rail derailment and broken rail, given specific variables (e.g., track curvature, signal condition, and annual traffic). The probability of broken rails can be estimated using machine learning techniques based on railroad big data, including maintenance, track layout, traffic and historical inspection records. In terms of derailment consequence, it is defined as the number of cars (both loaded and empty) derailed per derailment that would be estimated based on potentially affecting factors, such as train length, train speed, and train tonnage. The quantitative estimation and analysis of broken rail-caused Derailments are based upon the historical records from one Class I railroad company from 2012 to 2016, covering over 20,000 track miles on mainlines. The developed integrated risk model is able to contribute to the prediction of location-centric broken rail-caused derailment risk. Ultimately, the identification of high-risk locations can ultimately aid the railroads to mitigate broken rail risk in a cost-efficient manner and improve railroad safety.
-
Freight-train derailment rates for railroad safety and risk analysis.
Accident; analysis and prevention, 2016Co-Authors: Xiang Liu, M. Rapik Saat, Christopher P L BarkanAbstract:Derailments are the most common type of train accident in the United States. They cause damage to infrastructure, rolling stock and lading, disrupt service, and have the potential to cause casualties, and harm the environment. Train safety and risk analysis relies on accurate assessment of derailment likelihood. Derailment rate - the number of Derailments normalized by traffic exposure - is a useful statistic to estimate the likelihood of a derailment. Despite its importance, derailment rate analysis using multiple factors has not been previously developed. In this paper, we present an analysis of derailment rates on Class I railroad mainlines based on data from the U.S. Federal Railroad Administration and the major freight railroads. The point estimator and confidence interval of train and car derailment rates are developed by FRA track class, method of operation and annual traffic density. The analysis shows that signaled track with higher FRA track class and higher traffic density is associated with a lower derailment rate. The new accident rates have important implications for safety and risk management decisions, such as the routing of hazardous materials.
-
optimization of ultrasonic rail defect inspection for improving railway transportation safety and efficiency
Journal of Transportation Engineering-asce, 2014Co-Authors: Xiang Liu, Rapik M Saat, Tyler Dick, Alexander Lovett, Christopher P L BarkanAbstract:Broken rails are the most frequent cause of freight-train Derailments in the United States. Consequently, reducing their occurrence is a high priority for the rail industry and the U.S. Federal Railroad Administration. Current practice is to periodically inspect rails to detect defects using nondestructive technology such as ultrasonic inspection. Determining the optimal rail inspection frequency is critical to efficient use of infrastructure management resources and maximizing the beneficial impact on safety. Minimization of derailment risk, costs of inspection vehicle operation, rail defect repair, and corresponding train delay are all affected by rail inspection frequency. However, no prior research has incorporated all of these factors into a single integrated framework. The objective of this paper is to develop an analytical model to address the trade-offs among various factors related to rail defect inspection frequency, so as to maximize railroad safety and efficiency. The analysis shows that the optimal inspection frequency will vary with traffic density, rail age, inspection technology reliability, and other factors. The optimization model provides a tool that can be used to aid development of better-informed, more effective infrastructure management and accident prevention policies and practices.
-
analysis of causes of major train derailment and their effect on accident rates
Transportation Research Record, 2012Co-Authors: Xiang Liu, Mohd Rapik Saat, Christopher P L BarkanAbstract:Analysis of the causes of train accidents is critical for rational allocation of resources to reduce accident occurrence in the most cost-effective manner possible. Train derailment data from the FRA rail equipment accident database for the interval 2001 to 2010 were analyzed for each track type, with accounting for frequency of occurrence by cause and number of cars derailed. Statistical analyses were conducted to examine the effects of accident cause, type of track, and derailment speed. The analysis showed that broken rails or welds were the leading derailment cause on main, yard, and siding tracks. By contrast to accident causes on main tracks, bearing failures and broken wheels were not among the top accident causes on yard or siding tracks. Instead, human factor-related causes such as improper use of switches and violation of switching rules were more prevalent. In all speed ranges, broken rails or welds were the leading cause of Derailments; however, the relative frequency of the next most common a...
-
analysis of Derailments by accident cause evaluating railroad track upgrades to reduce transportation risk
Transportation Research Record, 2011Co-Authors: Xiang Liu, Christopher P L Barkan, Rapik M SaatAbstract:The risk of train derailment associated with rail transportation is an ongoing concern for the rail industry, government, and the public. Various approaches have been considered or adopted to analyze, manage, and reduce risk. Upgrading track quality has been identified as one possible strategy for preventing derailment. The quality of freight railroad track is commonly divided into five principal classes by FRA on the basis of track structure, track geometry, and inspection frequency and method. The higher the track class, the more stringent are the track safety standards and thus a higher maximum train speed is allowed. Upgrading track class is likely to prevent certain track-related Derailments; however, this upgrade may also increase the risk of certain types of equipment failure that are more likely to occur at higher speeds. Consequently, more sophisticated approaches need to be developed to examine the interactions among accident causes that may be differently affected by upgrades to track infrastru...
Liang Ling - One of the best experts on this subject based on the ideXlab platform.
-
assessment of road rail crossing collision Derailments on curved tracks
Australian Journal of Structural Engineering, 2017Co-Authors: Liang Ling, Manicka Dhanasekar, David ThambiratnamAbstract:AbstractCollision incidents involving trains and road vehicles at road-rail crossings are common occurrences, which are fatal and incur significant economic and societal costs. The existing studies of train collision Derailments mainly focus on the rail vehicles running on straight tracks, while the Derailments induced by train-truck collision at a road-rail crossing in curved tracks are rarely investigated, although such crossings are more common. This paper presents a study of the derailment assessment of passenger trains due to the collision with heavy road trucks stuck across the curved road-rail crossing by means of train-track dynamics simulations. For this purpose, a nonlinear three-dimensional model of a passenger train impacting a road truck stuck on curved tracks is developed based on the multi-body dynamics theory. Sensitivity of key design parameters such as the curve radius, the collision point at the curved track section, and the impact direction between the train and the truck, and their ef...
-
Minimising lateral impact derailment potential at level crossings through guard rails
International Journal of Mechanical Sciences, 2016Co-Authors: Liang Ling, Manicka Dhanasekar, David Thambiratnam, Yan Quan SunAbstract:Derailments due to lateral collisions between heavy road vehicles and passenger trains at level crossings (LCs) are serious safety issues. A variety of countermeasures in terms of traffic laws, communication technology and warning devices are used for minimising LC accidents; however, innovative civil infrastructure solution is rare. This paper presents a study of the efficacy of guard rail system (GRS) to minimise the derailment potential of trains laterally collided by heavy road vehicles at LCs. For this purpose, a three-dimensional dynamic model of a passenger train running on a ballasted track fitted with guard rail subject to lateral impact caused by a road truck is formulated. This model is capable of predicting the lateral collision-induced Derailments with and without GRS. Based on dynamic simulations, derailment prevention mechanism of the GRS is illustrated. Sensitivities of key parameters of the GRS, such as the flange way width, the installation height and contact friction, to the efficacy of GRS are reported. It is shown that guard rails can enhance derailment safety against lateral impacts at LCs.
-
Lateral impact derailment mechanisms, simulation and analysis
International Journal of Impact Engineering, 2016Co-Authors: Liang Ling, Manicka Dhanasekar, David Thambiratnam, Yan Quan SunAbstract:Lateral collisions between heavy road vehicles and passenger trains at level crossings and the associated Derailments are serious safety issues. This paper presents a detailed investigation of the dynamic responses and derailment mechanisms of trains under lateral impact using a multi-body dynamics simulation method. Formulation of a three-dimensional dynamic model of a passenger train running on a ballasted track subject to lateral impact caused by a road truck is presented. This model is shown to predict derailment due to wheel climb and car body overturning mechanisms through numerical examples. Sensitivities of the truck speed and mass, wheel/rail friction and the train suspension to the lateral stability and derailment of the train are reported. It is shown that improvements to the design of train suspensions, including secondary and inter-vehicle lateral dampers have higher potential to mitigate the severity of the collision-induced Derailments.
David Thambiratnam - One of the best experts on this subject based on the ideXlab platform.
-
assessment of road rail crossing collision Derailments on curved tracks
Australian Journal of Structural Engineering, 2017Co-Authors: Liang Ling, Manicka Dhanasekar, David ThambiratnamAbstract:AbstractCollision incidents involving trains and road vehicles at road-rail crossings are common occurrences, which are fatal and incur significant economic and societal costs. The existing studies of train collision Derailments mainly focus on the rail vehicles running on straight tracks, while the Derailments induced by train-truck collision at a road-rail crossing in curved tracks are rarely investigated, although such crossings are more common. This paper presents a study of the derailment assessment of passenger trains due to the collision with heavy road trucks stuck across the curved road-rail crossing by means of train-track dynamics simulations. For this purpose, a nonlinear three-dimensional model of a passenger train impacting a road truck stuck on curved tracks is developed based on the multi-body dynamics theory. Sensitivity of key design parameters such as the curve radius, the collision point at the curved track section, and the impact direction between the train and the truck, and their ef...
-
Minimising lateral impact derailment potential at level crossings through guard rails
International Journal of Mechanical Sciences, 2016Co-Authors: Liang Ling, Manicka Dhanasekar, David Thambiratnam, Yan Quan SunAbstract:Derailments due to lateral collisions between heavy road vehicles and passenger trains at level crossings (LCs) are serious safety issues. A variety of countermeasures in terms of traffic laws, communication technology and warning devices are used for minimising LC accidents; however, innovative civil infrastructure solution is rare. This paper presents a study of the efficacy of guard rail system (GRS) to minimise the derailment potential of trains laterally collided by heavy road vehicles at LCs. For this purpose, a three-dimensional dynamic model of a passenger train running on a ballasted track fitted with guard rail subject to lateral impact caused by a road truck is formulated. This model is capable of predicting the lateral collision-induced Derailments with and without GRS. Based on dynamic simulations, derailment prevention mechanism of the GRS is illustrated. Sensitivities of key parameters of the GRS, such as the flange way width, the installation height and contact friction, to the efficacy of GRS are reported. It is shown that guard rails can enhance derailment safety against lateral impacts at LCs.
-
Lateral impact derailment mechanisms, simulation and analysis
International Journal of Impact Engineering, 2016Co-Authors: Liang Ling, Manicka Dhanasekar, David Thambiratnam, Yan Quan SunAbstract:Lateral collisions between heavy road vehicles and passenger trains at level crossings and the associated Derailments are serious safety issues. This paper presents a detailed investigation of the dynamic responses and derailment mechanisms of trains under lateral impact using a multi-body dynamics simulation method. Formulation of a three-dimensional dynamic model of a passenger train running on a ballasted track subject to lateral impact caused by a road truck is presented. This model is shown to predict derailment due to wheel climb and car body overturning mechanisms through numerical examples. Sensitivities of the truck speed and mass, wheel/rail friction and the train suspension to the lateral stability and derailment of the train are reported. It is shown that improvements to the design of train suspensions, including secondary and inter-vehicle lateral dampers have higher potential to mitigate the severity of the collision-induced Derailments.
Rapik M Saat - One of the best experts on this subject based on the ideXlab platform.
-
optimization of ultrasonic rail defect inspection for improving railway transportation safety and efficiency
Journal of Transportation Engineering-asce, 2014Co-Authors: Xiang Liu, Rapik M Saat, Tyler Dick, Alexander Lovett, Christopher P L BarkanAbstract:Broken rails are the most frequent cause of freight-train Derailments in the United States. Consequently, reducing their occurrence is a high priority for the rail industry and the U.S. Federal Railroad Administration. Current practice is to periodically inspect rails to detect defects using nondestructive technology such as ultrasonic inspection. Determining the optimal rail inspection frequency is critical to efficient use of infrastructure management resources and maximizing the beneficial impact on safety. Minimization of derailment risk, costs of inspection vehicle operation, rail defect repair, and corresponding train delay are all affected by rail inspection frequency. However, no prior research has incorporated all of these factors into a single integrated framework. The objective of this paper is to develop an analytical model to address the trade-offs among various factors related to rail defect inspection frequency, so as to maximize railroad safety and efficiency. The analysis shows that the optimal inspection frequency will vary with traffic density, rail age, inspection technology reliability, and other factors. The optimization model provides a tool that can be used to aid development of better-informed, more effective infrastructure management and accident prevention policies and practices.
-
analysis of u s freight train derailment severity using zero truncated negative binomial regression and quantile regression
Accident Analysis & Prevention, 2013Co-Authors: Rapik M Saat, Christopher P L BarkanAbstract:Derailments are the most common type of freight-train accidents in the United States. Derailments cause damage to infrastructure and rolling stock, disrupt services, and may cause casualties and harm the environment. Accordingly, derailment analysis and prevention has long been a high priority in the rail industry and government. Despite the low probability of a train derailment, the potential for severe consequences justify the need to better understand the factors influencing train derailment severity. In this paper, a zero-truncated negative binomial (ZTNB) regression model is developed to estimate the conditional mean of train derailment severity. Recognizing that the mean is not the only statistic describing data distribution, a quantile regression (QR) model is also developed to estimate derailment severity at different quantiles. The two regression models together provide a better understanding of train derailment severity distribution. Results of this work can be used to estimate train derailment severity under various operational conditions and by different accident causes. This research is intended to provide insights regarding development of cost-efficient train safety policies.
-
analysis of factors affecting train Derailments at highway rail grade crossings
Transportation Research Board 91st Annual MeetingTransportation Research Board, 2012Co-Authors: Samantha G Chadwick, Rapik M Saat, Christopher P L BarkanAbstract:Implementation of highway-rail grade crossing warning systems, educational programs and research on crossings have all contributed to a steady reduction in the risk to highway users of grade crossings over the past several decades. Much less attention has been given to understanding the effect of grade crossings on train safety and risk. Collisions at highway-rail grade crossings can have serious consequences for the public and the railroads alike, especially in the form of train Derailments. The goal of this research is to identify and understand the factors leading to these Derailments. This paper focuses on three factors affecting train Derailments at highway-rail grade crossings. An examination of the effect of highway vehicle type on derailment occurrence showed that large highway vehicles, such as tractor-semitrailers, cause a disproportionate number of Derailments but that vehicle size does not affect derailment severity. Examinations of highway vehicle collision speed and train collision speed showed that Derailments are more likely to occur at higher vehicle speeds and lower train speeds.
-
analysis of Derailments by accident cause evaluating railroad track upgrades to reduce transportation risk
Transportation Research Record, 2011Co-Authors: Xiang Liu, Christopher P L Barkan, Rapik M SaatAbstract:The risk of train derailment associated with rail transportation is an ongoing concern for the rail industry, government, and the public. Various approaches have been considered or adopted to analyze, manage, and reduce risk. Upgrading track quality has been identified as one possible strategy for preventing derailment. The quality of freight railroad track is commonly divided into five principal classes by FRA on the basis of track structure, track geometry, and inspection frequency and method. The higher the track class, the more stringent are the track safety standards and thus a higher maximum train speed is allowed. Upgrading track class is likely to prevent certain track-related Derailments; however, this upgrade may also increase the risk of certain types of equipment failure that are more likely to occur at higher speeds. Consequently, more sophisticated approaches need to be developed to examine the interactions among accident causes that may be differently affected by upgrades to track infrastru...