Optimizing Power Consumption of Freight Railroad Bearings Using Laboratory Experimental Data

Based on projected freight truck fuel efficiency, freight railroad and equipment suppliers need to identify, evaluate and implement technologies and/or operating practices to maintain traditional railroad economic competitiveness. The railway industry uses systems that record the total energy efficiency of a train but not energy efficiency or consumption by components. Lowering the energy consumption of certain train components will result in an increase in its overall energy efficiency, which will yield cost benefits for all the stakeholders. One component of interest is the railroad bearing whose power consumption varies depending on several factors that include railcar load, train speed, condition of bearing whether it is healthy or defective, and type of defect. Being able to quantify the bearing power consumption, as a function of the variables mentioned earlier, would make it possible to obtain optimal operating condition ranges that minimize energy consumption and maximize train energy efficiency. Several theoretical studies were performed to estimate the power consumption within railroad bearings, but those studies lacked experimental validation. For almost a decade now, the University Transportation Center for Railway Safety (UTCRS) at the University of Texas Rio Grande Valley (UTRGV) has been collecting power consumption data for railroad bearings under various loads, speeds, ambient temperatures, and bearing condition. The objective of this ongoing study is to use the experimentally acquired power consumption to come up with a correlation that can be used to quantify the bearing power consumption as a function of load, speed, ambient temperature, and bearing condition. Once obtained, the model can then be used to determine optimal operating practices that maximize the railroad bearing energy efficiency. In addition, the developed model will provide insight into possible areas of improvement for the next generation of energy efficient railroad bearings. This paper will discuss ongoing work including experimental setup and findings of energy consumption of bearings as function of railcar load, train speed, condition of bearing whether it is healthy or defective, and type of defect. Findings of energy consumption are converted into approximations of diesel gallons to quantify the effect of nominal energy consumption of the bearings and show economic value and environmental impact.

Characterize Rail Crack Pattern Through Image Analysis

Railway provides more than 40% of the freight ton-miles moved in the U.S. each year, surpassing all other modes of transportation. In addition to moving more tonnage farther than other modes, trains have better fuel efficiency than trucks and airplanes due to the low friction between the wheels and the rails. With traffic accumulation, rails will degrade which may lead to different types of defects, including but not limited to spalling, separation, crack, and corrugation. Rail head fissures or surface crack is often associated with rolling fatigue and must be addressed through grinding or other maintenance activities to restore the smooth-running surface. This ensures the riding conforms to operational safety requirements. The growth pattern of rail surface cracks has not been thoroughly understood or well-quantified yet due to the difficulties of rail crack inspection and insufficient data. This paper presents a study that uses image analysis techniques to detect and quantify cracks in images of rail segments that were taken in the field. Various crack detection techniques were tested and compared with visual inspection, including thresholding, edge detection, and bottom-hat filtering. The crack length, direction, and curvature were also quantified with each approach. Cracks were found to grow not perpendicular to the rail head, but with a certain angle from the vertical direction and relatively evenly distributed along the rail. The bottom-hat filtering technique was found to be the best in terms of accuracy among the methods tested in this study. The results from the study fill the gap of the literature by quantitatively characterizing the rail crack growth pattern and helping to identify possible approaches for future autonomous crack detection.

A North American Historical Review of Three-Axle Freight Trucks

At first glance, it seems appealing to suggest additional wheelsets under a given railcar type. From the track’s viewpoint, and in a simplistic analysis, trading a particular car’s four-axles for the use of six should allow half again more car weight. This paper will examine efforts to test this concept over the past century. Indeed, the railway marketplace has investigated the three-axle truck in both the freight and passenger car arenas multiple times over the past century. Except in heavy-duty flatcars, the record shows that each implementation has proven to be only temporary. In general, three-axle freight trucks were developed for use with steam locomotive tenders in the early 20th century. These designs were then adapted to other car types over several decades, involving thousands of individual cars. Today, three-axle trucks are nearly extinct. This paper will address the history and status of three-axle freight trucks (or bogies) as used in North American railcar operations. Various past 20th-century applications will be discussed. International efforts will be reviewed as well. The very limited and remaining current usage of three-axle trucks is also discussed.

Sharing Tracks With High Speed Trains in Urban Area: Risk due to Drivers and Pedestrian Perception

Sharing operations of high-speed passenger and heavy slow freight trains on the same rail tracks presents additional risks to vehicle and pedestrians who cross the tracks. This is due to increase in rail traffic at crossing; drivers and pedestrians overestimate the amount of time they have to cross the intersection in front of a higher speed train; and due to the fact that circuited crossings are not adaptable and might lead to confusion and bad decisions. From human perception point of view these accidents happen in particular when the high speed trains were just introduced since the drivers as well as the pedestrians are used to interact with slower trains. Looming is a major factor that contributes to the perception error experiences by a driver or pedestrian. On one hand a faster train is being detected at farther distance than a slower one but its time to contact (the time it will reach the crossing) is shorter. Thus, a pedestrian might think that he has enough time to cross the railroad but actually he does not. Horn sound has the same effect on human perception. This paper discusses issues related to human perception which contribute to accidents in these cases.

Train Sideswipe Accidents and Passengers’ Injury

Train sideswipe accidents happen when two trains are traveling next to each other in the same or opposite directions and their sides come into contact. In most cases the relative velocity between the trains is very low. In these accidents, standing passengers might lose their balance, fall and impact with objects in their surroundings. Also, in extreme cases seated passenger might be ejected from their seat and get injured by impacting hard objects like handles and edges. These falls are caused by the acceleration and jerk exerted on the passengers during the impact. The train Event Data Recorder (EDR) does not record the train’s acceleration during the collision, as common in vehicle’s EDR, but provides only velocity information that is sampled in very low rate. To determine acceleration and jerk, train’s velocity is extracted from the train Event Data Recorder (EDR) and is used to estimate their value in order for the purpose of evaluation of the severity of the accident. The analysis of actual data extracted from an EDR of a train, that was that was involved in sideswipe accident is presented and compared to current standards. The results indicate that a standing person in case might lose his balance and fall. This results was verified since the two conductors who were walking along the isle lost their balance, fell and were injured feel and injure.

Field Testing Plan for Positive Train Control Enforcement in Passenger Terminals

In the United States, a train moving onto a terminating track at a passenger terminal relies on the train engineer’s operation. Currently, there are no mechanisms installed at the U.S. passenger terminals that are able to automatically stop a train before reaching the end of the track if an engineer fails to do so. The engineer’s actions determine whether the train will safely stop before the end of the terminating track. Thus, incapacitated or inattentive engineer operation would result in end-of-track collisions, such as the New Jersey Transit train accident at Hoboken Terminal in 2016. Currently, PTC enforcement is not required in passenger terminals. In an ongoing project tasked by the Federal Railroad Administration, we study the cost-effectiveness and operational impact of possible PTC enforcement to prevent end-of-track collisions. Specifically, a Concept of Operations (ConOps) was developed to outline the proposed plans to implement two of the most widely used PTC types, namely the Advanced Civil Speed Enforcement System (ACSES) and Interoperable Electronic Train Management System (I-ETMS). This paper describes in-field testing of the ConOps in ACSES-type terminal. In the planned field test, a train equipped with one locomotive and at least one passenger coach would be tested on platform tracks in a selected passenger terminal. These are three major testing components, which are test equipment, test track, and recorded information for each test sequence. Firstly, in terms of equipment, a traffic cone will be placed on the track to simulate a bumping post. In ACSES system, two sets of transponders are programmed to require a positive stop within a specified distance and mounted to the cross ties at specified positions. Secondly, a yard track will be used to test the feasibility of this exercise at the beginning. Upon successfully completing the test multiple times, a series of tests will also be made on the studied platform track. Thirdly, each test run should record the distance from the head end of the test train and the traffic cone for each test run. In addition, ACSES system should also record the information on the ACSES display as it passes the first and second transponder set, respectively. Overall, the field tests presented in this paper, along with previous work in benefit-cost analysis and operational impact assessment, can contribute to an assessment of the proposed PTC implementation at stub-end terminals in the United States in order to effectively and efficiently prevent end-of-track collisions.

Probabilistic Risk Analysis of Broken Rail-Caused Train Derailments

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.

A Numerical Investigation of Laterally Loaded Steel Fin Pile Foundations

The present study comprehensively evaluates the improvement in lateral load-carrying capacity of steel pipe piles by adding steel plates (fins) at grade level. This configuration of steel fin pile foundations (SFPFs) is effective for applications where high lateral loads are encountered and rapid pile installation is advantageous. An integrated finite element analysis (FEA) was conducted. The FEA utilized an Abaqus model, first developed to account for the nonlinear soil-pile interaction, and then calibrated and validated against well-documented experimental and filed tests in the literature. The validated FEA model was subsequently used to conduct a parametric study to understand the effect of fin geometry on the load transfer mechanism and the response of SFPFs subjected to lateral loading at pile head. The behavior of SFPFs at different displacement levels and load levels was studied. The effect of the relative density of soil on the performance of SFPFs was also investigated. Based on the numerical simulation results, the optimal fin width for maximum improvement in lateral load-carrying capacity was suggested and the underlining mechanism affecting the efficiency of fins was explained.

Vibration Control of a Rigid and Flexible High-Speed Railway Vehicle

In this paper, the vertical carbody dynamics of the railway vehicle excited by random track inputs are investigated. The multi-objective ℋ∞ controllers for carbody weight of the actual, heavy and a mass confined in a polytopic range have been designed with the aim of reducing the wheel forces, heave, pitch and roll body accelerations of the vehicle. Later, the carbody mass is modelled as a free-free Euler Bernoulli beam and the low frequency flexural vibrations of the train body are examined. An omnibus ℋ∞ controller is synthesized to suppress both the rigid and low frequencies flexible modes of the railway vehicle. The performances of the ℋ∞ controllers are verified by using the passive and active suspension responses on the right and left rail track disturbances that are represented by the power spectral density functions authenticated for the stochastic real track data collected from the Qinhuangdao-Shenyang passenger railway line in China. Simulation results showed that all controllers exhibit a very good performance by effectively reducing the car-body accelerations in vicinity of the resonanat frequencies while keeping the wheel-rail forces in the allowable limit.

Thermal Effects on Wheel Performance Based on Twin Disc Testing

This paper presents the results and findings from a testing program conducted to investigate how temperature at the wheel-rail interface may affect wheel surface performance; i.e., development of rolling contact fatigue (RCF) and wear. Under this testing program, a twin disc test machine was used to test two different types of wheel specimens (cast and forged) under a range of temperatures (ambient to 800° F) and slip ratios from 0 to 0.75 percent. This testing program included a total of 32 tests, covering two wheel materials, four different temperatures, four slip ratios, and various traction coefficients as a ratio of longitudinal and vertical wheel/rail contact forces.