Leith Al-Nazer

Determination of the Neutral Temperature of Slender Beams by Using Nonlinear Solitary Waves

AbstractSlender columns subjected to compressive stress are common in many civil structures. The rapid in situ measurement of this stress may prevent structural buckling. In this study, the authors applied an artificial neural network (ANN) to process numerical data that describe the coupling mechanism between highly nonlinear solitary waves (HNSWs) propagating along a granular system and a beam in contact with the granular medium. The aim is to evaluate the ability of HNSWs to measure stress in thermally loaded structures and to estimate the neutral temperature, i.e., the temperature at which the stress is null. Nonlinear solitary waves are compact nondispersive waves that can form and travel in nonlinear systems such as one-dimensional chains of particles, where they are conventionally generated by the mechanical impact of a striker. The authors numerically investigated a straight chain of spherical particles in contact with a prismatic beam subjected to thermal stress. The effect of the neutral tempera...

Development of Rail Temperature Predictions to Minimize Risk of Track Buckle Derailments

Track buckling due to excessive rail temperature is a major cause of derailments with serious consequences. To minimize the risk of derailments, slow orders are typically issued on sections of track in areas where an elevated rail temperature is expected and risk of track buckling is increased. While the slow orders are an important preventive safety measure, they are costly as they disrupt timetables and can affect time-sensitive shipments. Optimizing the slow order process would result in significant cost saving for the railroads.The Federal Railroad Administration’s (FRA’s) Office of Research and Development has sponsored the development of a model for predicting rail temperatures using real time weather forecast data and predefined track parameters and a web-based system for providing resulting information to operators.In cooperation with CSX Transportation (CSX), ENSCO Inc. conducted a model verification study by comparing actual rail temperatures measured by wayside sensors installed on railroad track near Folkston, GA, with the rail temperatures predicted by the model based on weather forecast data over the course of summer 2011. The paper outlines the procedure of the verification process together with correlation results, which are favorable.The paper also presents results of several case studies conducted on derailments attributed to track buckling. These investigations improve our understanding of conditions and temperature patterns leading to increased risk of rail buckles and validate further use of the Rail Temperature Prediction Model as track buckling prediction tool and as an aid to the railroads in making more informed decisions on slow order issuing process.Copyright

Rail Temperature Approximation and Heat Slow Order Best Practices

The railroad industry uses slow orders, sometimes referred to as speed restrictions, in areas where an elevated rail temperature is expected in order to minimize the risk and consequence of derailment caused by track buckling due to excessive rail temperature. Traditionally, rail temperature has been approximated by adding a constant offset, most often 30°F, to a peak ambient air temperature. When this approximated maximum rail temperature exceeds a given risk threshold, slow orders are usually issued for a predefined period of the day.This “one size fits all” approach, however, is not effective and suitable in all situations. On very warm days, the difference between rail temperature and ambient air temperature can exceed railroad-employed offsets and remain elevated for extended periods of time. A given temperature offset may be well suited for certain regions and track buckling risk-related rail temperature thresholds but less accurate for others. Almost 160,000 hours of rail temperature measurements collected in 2012 across the eastern United States by two Class I railroads and predicted ambient air temperatures based on the National Weather Service’s National Centers for Environmental Prediction (NCEP) data were analyzed using detection theory in order to establish optimal values of offsets between air and rail temperatures as well as times when slow orders should be in place based on geographical location and the track buckling risk rail temperature threshold. This paper presents the results of the analysis and describes an improved procedure to manage heat-related slow orders based on ambient air temperatures.Copyright

Automated Technology for Rail-Based Highway-Rail Grade Crossing Surveying

High-profile highway-rail crossings (HPGCs), often referred to as ‘humped crossings,’ present very serious and highly-consequential potential dangers to both railroads and motor carriers. The hazard is most commonly manifested when low-clearance trucks bottom out on these crossings and become stuck or immobilized across the tracks. This is often referred to as a ‘hang-up.’ Once a situation like this occurs, little can be done to prevent a train-truck collision. Some states have undertaken efforts to prevent hang-ups; however, multiple challenges have prevented significant progress from being made. The Federal Railroad Administration (FRA), in cooperation with the Federal Highway Administration (FHWA), is continuing previous efforts in this area by initiating a study in order to prevent such events.

Measurement of Vertical Track Modulus: Field Testing, Repeatability, and Effects of Track Geometry

The heavy axle loads and high speeds of modern freight trains produce high track stresses leading to quicker track degradation. Track loads can be increased by variations in vertical track stiffness — the relationship between vertical rail deflection and the vertical applied load — and vertical track modulus. Both low track modulus and large variations in track modulus (leading to increased dynamic loading) cause accelerated track degradation and associated increased maintenance requirements. The University of Nebraska, under sponsorship from the Federal Railroad Administration, continues to develop a method to measure vertical track deflection and modulus from a rail car traveling at revenue speed. This paper first summarizes past work to develop a method to measure vertical track deflection from a moving rail car. The measurement is made by attaching a beam to the sideframe of a loaded hopper car that extends along the rail toward the car’s center. Then the deflection of the rail is measured approximately four feet from the inner wheel using a camera/laser system. The measurement determines the offset between the rail and the line established by the two wheel/rail contact points. These deflection measurements can then be used to estimate track modulus. Results are presented for repeated tests on approximately three hundred miles of heavy axle load freight line over a period of about ten months. These results have shown that the measurements of the above system are extremely repeatable and are not significantly related to train speed. The measurements also show seasonal variations in track modulus caused by factors such as variations in subgrade moisture and ambient temperature. The system has shown a notable ability to identify locations at high risk of derailments. After each of the four tests, a “top ten” list was created indicating the largest changes in relative deflection in descending order (one top ten list corresponding to each of the four tests). The lists were created based on exception criteria presented by the authors at last year’s conference. Four derailments occurred over this ten month period and three of those derailments appear in the top ten lists (#2, #10, in list one and #1 in list four). Finally, simulation and experimental analysis that quantify and assess the co-relation between this system and track geometry is presented. Extreme track geometry variations can create errors as the relative deflection measurement is mapped into a specific value of track modulus. This effect is also quantified and described.Copyright

Solitary Waves to Infer Axial Stress in Slender Structures: A Numerical Model

In-situ testing of beams subjected to axial stress may prevent structural anomalies such as buckling. We describe the coupling mechanism between highly nonlinear solitary waves (HNSWs) propagating along a granular system and a beam in contact with the granular medium with the aim of assessing the ability of HNSWs at measuring axial stress. Nonlinear solitary waves are compact non-dispersive waves that can form and travel in nonlinear systems such as one-dimensional chains of particles. In the study presented in this article we investigated numerically straight chains of particles in contact with a prismatic beam subjected to axial stress. Two configurations were considered: one or two chains. The effect of the particles’ diameter and material was studied to find those optimal conditions that maximize the sensitivity to axial stress variation. We found that the configuration with one chain is preferable whereas certain particles’ materials and diameter are better at sensing the variation of the axial stress.

Thermal Benefits of Low Solar Absorption Coating for Preventing Rail Buckling

A low solar absorption coating for rail application is developed to reduce the peak rail temperature and buckling risk in summer months. The proposed coating system provides a highly reflective surface through white or off-white color and has constituents to provide high abrasion resistance and self-cleaning properties. The zero volatile organic content (VOC) and one hundred percent inorganic coating system has excellent adhesion to steel surfaces with minimal surface preparation. This paper presented the outdoor temperature monitoring results of the coated rail segments under hot weather. The results show that the application of coating could significantly reduce the peak rail temperature up to 10.5°C. Three-dimensional finite element (FE) models were developed to predict temperature distributions and thermal stresses in the rail. The thermal stress simulation shows that, when the rail neutral temperature (RNT) is relatively low, rail coating decreases the compressive stress in the rail up to about 50% during the hottest hours. Although increasing the RNT decreases compressive thermal stresses in the rail, it could increase the risk of rail break due to the increased tensile stresses in the rail. The coating application could reduce the high RNT requirement during rail placement and prevent rail buckling as the effective RNT decreases after traffic and maintenance. Therefore, the low solar absorption coating could serve as a proactive way to control peak temperatures and thermal stresses in the rail.Copyright

Coupling mechanism of granular medium and slender beams

We present a methodology to assess slender beams by means of highly nonlinear solitary waves. This is accomplished by understanding the coupling mechanism between highly nonlinear solitary waves propagating along a granular system and a beam in contact with the granular medium. Nonlinear solitary waves are compact non-dispersive waves that can form and travel in nonlinear systems such as one-dimensional chains of particles. In the study presented in this paper, the waves are generated by the mechanical impact of a striker and are detected by means of sensor beads located along the chain. We investigated numerically and experimentally the effect on the solitary waves of slender beams of different modulus, length, boundary condition, and axial stress. We found that the geometric and mechanical properties of the beam or thermal stress applied to the beam alter certain features of the solitary waves. In the future, these findings may be used to develop a novel sensing system for the Nondestructive Evaluation of beams.

Rail Temperature Prediction Model and Heat Slow Order Management

Track buckling due to excessive rail temperature may cause derailments with serious consequences. To minimize the risk of derailments, slow orders are typically issued on sections of track in areas where an elevated rail temperature is expected and risk of track buckling is increased. While slow orders are an important preventive safety measure, they are costly as they disrupt timetables and can affect time-sensitive shipments. Optimizing the slow order management process would result in significant cost saving for the railroads.The Federal Railroad Administration’s (FRA’s) Office of Research and Development has sponsored the development of a model for predicting rail temperatures using real time weather forecast data and predefined track parameters and a web-based system for providing resulting information to operators.In cooperation with CSX Transportation (CSX) and FRA, ENSCO Inc. conducted a comprehensive model verification study by comparing actual rail temperatures measured by wayside sensors installed at 23 measurement sites located across the CSX network with the rail temperatures predicted by the model based on weather forecast data over the course of spring and summer 2012. In addition to the correlation analysis, detection theory was used to evaluate the model’s ability to correctly identify instances when rail temperatures are elevated above a wide range of thresholds. Detection theory provides a good way of comparing the performance of the model to the performance of the current industry practice of estimating rail temperature based on constant offsets above predicted daily peak ambient air temperatures.As a next step in order to quantify the impact of implementation of the model on CSX operations, heat slow orders issued by CSX in 2012 on 10 selected subdivisions were compared to theoretical heat slow orders generated by the model.The paper outlines the analysis approach together with correlation, detection theory and slow order comparison results. The analysis results along with investigation of past heat related track buckle derailments indicate that the railroad would benefit from adopting the rail temperature prediction model along with flexible rail temperature thresholds. The implementation of the model will have a positive impact on safety by allowing for issuing of advance heat slow orders in more accurate, effective and targeted way.© 2014 ASME

Ultrasonic Tomography for Rail Flaw Imaging

There is a need in the railroad industry to have quantitative information on internal rail flaws, including flaw size and orientation. Such information can lead to knowledge-based decision making on any remedial action, and ultimately increase the safety of train operations by preventing derailments. Current ultrasonic inspection methods leave such sizing determinations to the inspector, and there can be significant variability from one inspector to another depending on experience and other factors. However, this quantitative information can be obtained accurately by 3-D imaging of the rail flaws. It is the goal of this project to develop a portable system that will improve defect classification in rails and ultimately improve public safety.This paper will present a method for 3-D imaging of internal rail flaws based on Ultrasonic Tomography. The proposed technique combines elements of ultrasonic testing with those of radar and sonar imaging to obtain high-resolution images of the flaws using a stationary array of ultrasonic transducers. The array is operated in a “full matrix capture” scheme that minimizes the number of ultrasonic transmitters, hence simplifying the practical implementation and reducing the inspection time. In this method, a full 3D image of the rail volume identifies the location, size and orientation of the defect. This will help to eliminate human error involved with a typical manual inspection using a single transducer probe inspection. The results of advanced numerical simulations, carried out on a rail profile, will be presented. The simulations show the effectiveness of the technique to image a 5% Head Area Transverse Defect in the railhead. Current efforts are aimed at developing an experimental prototype based on this technology, whose design status is also discussed in this paper.Copyright