Rolling stock, particularly of freight railroads, is currently maintained using regular preventative and corrective maintenance schedules. This maintenance approach recommends sets of inspections and maintenance procedures based on the average expected wear and tear across their inventory. In practice, however, this approach to scheduling preventative maintenance is not always effective. When scheduled too soon, it results in a loss of operating revenue, whereas when it is scheduled too late, equipment failure could lead to costly and disastrous derailments. Instead, proactive maintenance scheduling based on Big Data Analytics (BDA) could be utilized to replace traditional scheduling, resulting in optimized maintenance cycles for higher train safety, availability, and reliability. BDA could also be used to discover patterns and relationships that lead to train failures, identify manufacturer reliability concerns, and help validate the effectiveness of operational improvements. In this work, we introduce a train inventory simulation platform that enables the modelling of different train components such as wheels, brakes, axles, and bearings. The simulator accounts for the wear and tear in each component and generates a comprehensive data set suitable for BDA that can be used to evaluate the effectiveness of different BDA approaches in discerning patterns and extracting knowledge from the data. It provides the basis for showing that BDA algorithms such as Random Forest [9] and Linear Regression can be utilized to create models for proactive train maintenance scheduling. We also show the capability of BDA to detect hidden patterns and to predict failure of train components with high accuracy.

For a given material and set of test conditions, fatigue crack propagation behavior can be described by the relationship between cyclic crack-growth rate, da/dN and the fluctuation of stress intensity factor, △K. Such test data are usually displayed in a log-log plot. At intermediate values of △K, fatigue crack-growth data fall along a straight line such that a power-law equation may be used as a curve-fit to the data. Various numerical techniques are applied in order to (1) derive the crack-growth rate and (2) determine the parameters for the power-law equation. Using data from laboratory tests conducted on rail steels, this paper explores the various numerical methods used to characterize fatigue crack-growth behavior. Tests were conducted using two different fracture-mechanics specimens (a standard compact tension specimen and a non-standard single edge notch specimen). Three different numerical techniques were applied to determine the fatigue crack-growth rate, da/dN from test data measuring crack length, a versus number of fatigue cycles, N: (1) secant method, (2) modified secant method, and (3) incremental polynomial method. Four different least squares regression analyses were then applied to determine the parameters for the power law. Moreover, the outcome of these analyses is to determine the combination of numerical techniques which yields the least amount of error when the crack-growth rate equation is integrated and compared to the original a versus N data. Fatigue life calculations performed by integrating the crack-growth rate equation demonstrate the sensitivity of predicted growth rates to the power-law parameters derived from the different regression analyses. This paper explores the various numerical methods and techniques employed to analyze fatigue crack growth data using test data on rail steels.

The interaction of the carried cargo and the carrying vehicle involves many aspects that can affect the transport safety from different perspectives. On the one side, the lateral inertial forces developed by sloshing cargo can affect the lateral stability of the vehicle, while at long term, such dynamic forces can affect the integrity of the infrastructure’s components, which can lead to transport accidents. In this paper, a tilt-table based testing rig is presented to simulate the dynamic response of the vehicle-cargo system to lateral accelerations associated to turning maneuvers. The conceptual design and final construction/instrumentation of the equipment are described. As a first use of the testing rig, a five-parameter two-degree of freedom simplified mechanical model for the liquid cargo – vehicle interaction is calibrated, yielding a high correlation with the experimental data (0.98). The improvement of the theoretical model is further discussed, as the model underestimates the loading cycles to the infrastructure, in 20%.

In this paper, the micro-mechanical mechanisms behind the initiation and propagation of rolling contact fatigue (RCF) damages caused by the large traction forces are investigated. This study provides a three-dimensional (3D) model for studying the rolling contact fatigue in rails. Since rolling contact fatigue is highly dependent on the rail’s steel microstructure behavior, a proper 3D approach to capture the microstructure- and orientation-dependent mechanical behavior is required. A precise material model known as crystal plasticity is used for this purpose. Additionally, a cohesive zone approach is implemented to capture the crack initiation and propagation at the grain boundaries. Using the 3D finite element model which is developed for this study, we evaluate the effect of various parameters such as traction forces along the rail, and also the normal forces on the RCF response. The results reveal that the RCF cracks initiate slightly below the rail surface. These cracks start propagating toward the rail surface when the contact force is applied in repeated load cycles. The results also indicate that the depth at which RCF initiates depends on the ratio between the longitudinal traction forces and the normal loads. With larger traction forces, the cracks initiate closer, or at the rail surface, whereas larger normal loads promote the cracks initiation beneath the surface.

The railroad industry currently utilizes two wayside detection systems to monitor the health of freight railcar bearings in service: The Trackside Acoustic Detection System (TADS™) and the wayside Hot-Box Detector (HBD). TADS™ uses wayside microphones to detect and alert the conductor of high-risk defects. Many defective bearings may never be detected by TADS™ since a high-risk defect is a spall which spans more than 90% of a bearing’s raceway, and there are less than 20 systems in operation throughout the United States and Canada. Much like the TADS™, the HBD is a device that sits on the side of the rail-tracks and uses a non-contact infrared sensor to determine the temperature of the train bearings as they roll over the detector. These wayside detectors are reactive in the detection of a defective bearing and require emergency stops in order to replace the wheelset containing the defective bearing. These costly and inefficient train stoppages can be prevented if a proper maintenance schedule can be developed at the onset of a defect initiating within the bearing. This proactive approach would allow for railcars with defective bearings to remain in service operation safely until reaching scheduled maintenance. Driven by the need for a proactive bearing condition monitoring system in the rail industry, the University Transportation Center for Railway Safety (UTCRS) research group at the University of Texas Rio Grande Valley (UTRGV) has been developing an advanced onboard condition monitoring system that can accurately and reliably detect the onset of bearing failure using temperature and vibration signatures of a bearing. This system has been validated through rigorous laboratory testing at UTRGV and field testing at the Transportation Technology Center, Inc. (TTCI) in Pueblo, CO. The work presented here builds on previously published work that demonstrates the use of the advanced onboard condition monitoring system to identify defective bearings as well as the correlations developed for spall growth rates of defective bearing outer rings (cups). Hence, the system uses the root-mean-square (RMS) value of the bearing’s acceleration to assess its health. Once the bearing is determined to have a defective outer ring, the RMS value is then used to estimate the defect size. This estimated size is then used to predict the remaining service life of the bearing. The methodology proposed in this paper can prove to be a useful tool in the development of a proactive and cost-efficient maintenance cycle for railcar owners.

Remediation of environmental sites is of concern across the rail industry. Impacted sites may result from releases of chemicals to the environment along active rail lines or in rail yards; historical activities; or through acquisition of impacted property. Management of these liabilities may require investigation, planning, design, and remediation to reduce risks to human health and the environment and meet regulatory requirements. However, these investigation and remediation activities may generate unintended environmental, community, or economic impacts. To address these impacts, many organizations are focusing on the incorporation of sustainability concepts into the remediation paradigm. Sustainable remediation is defined as the use of sustainable practices during the investigation, construction, redevelopment, and monitoring of remediation sites, with the objective of balancing economic viability, conservation of natural resources and biodiversity, and the enhancement of the quality of life in surrounding communities (Sustainable Remediation Forum [SURF]). Benefits of considering and implementing measures to balance the three pillars of sustainability (i.e., society, economics, and environment) may include lower project implementation costs, reduced cleanup timeframes, and maximizing beneficial while alleviating detrimental impacts to surrounding communities. Sustainable remediation has evolved from discussions of environmental impacts of cleanups (with considerable greenwashing), to quantifying and minimizing the environmental footprint and subsequent long-term global impacts of a remedy, and currently, incorporating strategies to address all three components of sustainability — environmental, social, and economic. As organizations expand their use of more sustainable approaches to site cleanup, it is beneficial to establish consistent objectives and metrics that will guide implementation across a portfolio of sites. Sustainable remediation objectives should be consistent with corporate sustainability goals for environmental performance (e.g., greenhouse gas emissions, resource consumption, or waste generation), economic improvements (i.e., reduction of long term liability), and community engagement. In the last decade, there have been several Executive Orders (13423, 13514, 13693) that provide incrementally advanced protocols for achieving sustainability in government agency and corporate programs. Resources for remediation practitioners are available to assist in developing sustainable approaches, including SURF’s 2009 White Paper and subsequent issue papers, ITRC’s Green and Sustainable Remediation: State of the Science and Practice (GSR-1) and A Practical Framework (GSR-2), and ASTM’s Standard Guide for Greener Cleanups (E2893-16) and Standard Guide for Integrating Sustainable Objectives into Cleanup (E2876-13). These documents discuss frameworks that may be applied to projects of any size and during any phase of the remediation life cycle, and many provide best management practices (BMPs) that may be implemented to improve the environmental, social, or economic aspects of a project. Many of these frameworks encourage a tiered approach that matches the complexity of a sustainability assessment to the cost and scope of the remediation. For small remediation sites, a sustainability program may include the selection, implementation, or tracking of BMPs. A medium sized remediation site may warrant the quantification of environmental impacts (e.g., air emissions, waste generation, etc.) during the evaluation and selection of remedial alternatives. Often, only large and costly remediation sites demand detailed quantitative assessment of environmental impacts (e.g., life cycle assessment), economic modeling, or extensive community or stakeholder outreach. However, if a tiered approach is adopted by an organization, components of each of these assessments can be incorporated into projects where it makes sense to meet the needs of the stakeholders.

The ballast layer in a railroad track helps distribute loads from the superstructure to the formation; a well-designed ballast layer is also meant to prevent excessive vertical, lateral and longitudinal movement of the track under loading. When subjected to repeated loading, the granular ballast particles often undergo breakage leading to significant changes in the shear strength as well as drainage characteristics of the ballast layer. Excessive ballast degradation leads to increased vertical settlements, and is often associated with speed restrictions and increased passenger discomfort. Several researchers in the past have studied the phenomenon of ballast breakage in a laboratory setting. However, due to complexities associated with these large-scale laboratory tests, detailed parametric studies are often not feasible. In such cases, numerical modeling tools such as the Discrete Element Method (DEM) become particularly useful. This paper presents findings from an ongoing research effort at Boise State University aimed at studying the phenomenon of ballast breakage under repeated loading using a commercially available Discrete Element Package (PFC3D ® ). Ballast particles were simulated as clusters of balls bonded together, and were allowed to undergo breakage when either the maximum tensile stress or the maximum shear stress exceeded the corresponding bond strength value. Different factors studied during the parametric analysis were: (1) load amplitude; (2) loading frequency; (3) number of cycles of loading; (4) bond strength; and (5) particle size distribution. The objective was to identify the relative importance of different factors that govern the permanent deformation behavior of railroad tracks under loading.

To illustrate the metro braking performance more appropriately and comprehensively, and to explore the dynamic braking process more accurately, the consistency analysis was used in this paper, which is used for the first time in the metro brake field. Based on the stream data, several characteristic values (braking pressure setting time, maximum braking pressure and stability value of braking pressure, i.e.) were extracted to represent the dynamic process. Under similar braking conditions, such as the similar applied pressure, speed and brake level, etc., the performance of brake system is similar and stable in certain extent. The dynamic data model has been developed in this paper. Large data mining based statistics was used to analyze braking performance and the dynamic prediction during a braking cycle was provided. Investigation presented in this paper contributes to the efforts in the direction of metro braking systems performance and evaluation of service condition. The dynamic evaluation based on the stream data has been proved to provide a new way to explore the influence of metro braking system so that it is reasonable to analyze the service condition of metro brake system. Based on the LabVIEW platform, the system for analyzing stream data was built. Based on stream data, using the characteristic and statistics method, this paper provides a way to describe the service condition. The result enriches the evaluation criteria of metro service condition.

A micromechanical-based 2D framework is presented to study the rolling contact fatigue (RCF) in rail steels using finite element method. In this framework, the contact patch of rail and wheel is studied by explicitly modeling the grains and grain boundaries, to investigate the potential origin of RCF at the microstructural level. The framework incorporates Voronoi tessellation algorithm to create the microstructure geometry of rail material, and uses cohesive zone approach to simulate the behavior of grain boundaries. To study the fatigue damage caused by cyclic moving of wheels on rail, Abaqus subroutines are employed to degrade the material by increasing the number of cycles, and Jiang-Sehitoglu fatigue damage law is employed as evolution law. By applying Hertzian moving cyclic load, instead of wheel load, the effect of traction ratio and temperature change on RCF initiation and growth are studied. By considering different traction ratios (0.0 to 0.5), it is shown that increasing traction ratio significantly increases the fatigue damage. Also by increasing traction ratio, crack initiation migrates from the rail subsurface to surface. The results also show that there are no significant changes in the growth of RCF at higher temperatures, but at lower temperatures there is a measurable increase in RCF growth. This finding correlates with anecdotal information available in the rail industry about the seasonality of RCF, in which some railroads report noticing more RCF damage during the colder months.

Geogrid reinforcement of railroad ballast improves its structural response under loading, limits lateral movement of ballast particles, and reduces vertical settlement through effective geogrid-ballast interlocking. This improved performance can be linked to improved shear strength and resilient modulus properties. An ongoing research study at Boise State University is focusing on investigating the effects of different specimen and test parameters on the mechanism of geogrid-ballast interaction. A commercially available Discrete Element Modeling (DEM) program (PFC3D ® ) is being used for this purpose, and the effect of geogrid inclusion is being quantified through calculation of the “Geogrid Gain Factor”, defined as the ratio between resilient-modulus of a geogrid-reinforced ballast specimen and that of an unreinforced specimen. Typical load-unload cycles in triaxial shear strength tests are being simulated, and parametric studies are being conducted to determine the effects of particle-size distribution, geogrid aperture size, and geogrid location on railroad-ballast modulus. This paper presents findings from the research study, and presents inferences concerning implications of the study findings on design and construction of better-performing ballast layers.

Prevention of railroad bearing failures, which may lead to catastrophic derailments, is a central safety concern. Early detection of railway component defects, specifically bearing spalls, will improve overall system reliability by allowing proactive maintenance cycles rather than costly reactive replacement of failing components. A bearing health monitoring system will provide timely detection of flaws. However, absent a well verified model for defect propagation, detection can only be used to trigger an immediate component replacement. The development of such a model requires that the spall growth process be mapped out by accumulating associated signals generated by various size spalls. The addition of this information to an integrated health monitoring system will minimize operation disruption and maintain maximum accident prevention standards enabling timely and economical replacements of failing components. An earlier study done by the authors focused on bearing outer ring (cup) raceway defects. The developed model predicts that any cup raceway surface defect (i.e. spall) once reaching a critical size (spall area) will grow according to a linear correlation with mileage. The work presented here investigates spall growth within the inner rings (cones) of railroad bearings as a function of mileage. The data for this study were acquired from defective bearings that were run under various load and speed conditions utilizing specialized railroad bearing dynamic test rigs owned by the University Transportation Center for Railway Safety (UTCRS) at the University of Texas Rio Grande Valley (UTRGV). The experimental process is based on a testing cycle that allows continuous growth of railroad bearing defects until one of two conditions are met; either the defect is allowed to grow to a size that does not jeopardize the safe operation of the test rig, or the change in area of the spall is less than 10% of its previous size prior to the start of testing. The initial spall size is randomly distributed as it depends on the originating defect depth, size, and location on the rolling raceway. Periodic removal and disassembly of the railroad bearings was carried out for inspection and defect size measurement along with detailed documentation. Spalls were measured using optical techniques coupled with digital image analysis, as well as, with a manual coordinate measuring instrument with the resulting field of points manipulated in MatLab™. Castings were made of spalls using low-melting, zero-shrinkage bismuth-based alloys, so that a permanent record of the spall geometry and its growth history can be retained. The main result of this study is a preliminary model for spall growth, which can be coupled with bearing condition monitoring tools that will allow economical and effective scheduling of proactive maintenance cycles that aim to mitigate derailments, and reduce unnecessary train stoppages and associated costly delays on busy railways.

The lateral stability of the continuous welded rail (CWR) depends on a number of parameters which contribute to the progressive loss of the initial alignment of the track and its consequent predisposition to deform sideways, gradually or sharply, with serious risks for the safety both of passengers and operators. Different types of initial lateral defect, in terms of shape and size, are introduced by many authors in their own numerical and analytical model, but essentially all of them can be traced back — except for small “personalizations” — to the model proposed by Andrew Kish, who hypothesized the existence of a misalignment defect having the shape of a sine curve extended for half-wavelength, characterized by amplitude and wavelength values typical of the USA railroads. Moreover, all previous studies focused their attention on the introduction, in a geometrically perfect railway track, of a single defect confined in a zone of finite dimensions and having a rather simple geometry which qualitatively approximates the real defect, with the aim of simplifying the calculation of the buckling temperatures of the track associated with such geometry. In this paper, it was preliminarily analyzed the way the defect introduced in the track affects the critical temperature values. It started with a defect created artificially, applying to a geometrically perfect track and in the absence of thermal loads, a lateral displacement in the central transversal section of the track, and calculating, with the hypothesis of linear elastic behavior, the resulting deformed shape, which was assumed, after zeroing the corresponding stress field, as the input geometry for the subsequent buckling calculation. The deformed shape so obtained, being a Zimmermann deformed shape type, has no geometrical discontinuities near the defect and interprets in a natural way the defected geometry of the track, due to the dependence of its configuration on the flexural stiffness of the entire track in the lateral plane. Afterwards, modeling was carried out taking into account the real behavior of the track after the loss of its rectilinear configuration: the defect was created simulating the response of the track to a momentary lateral load — resulting, e.g., from train passages — which succeeded to cause a permanent displacement resulting from the elastic-plastic response of the track. The deformed shape of the track obtained in this way was used as the input geometry for the calculation of the buckling temperatures, once without resetting the stress field induced in the structure by the loading–unloading hysteresis cycle, and then considering the track free from internal stresses. The results show that both the numerical model that contemplate the defect introduced “plastically”, and that where the track is free from internal stresses, lead to more conservative results against the risk of thermal buckling in railway tracks made with CWR. A better approximation of the realistic representation of a generic defected railway track was pursued considering an indefinite number of defects distributed along the track, where each defect was characterized by different amplitude and wavelength values. The obtained results show that the presence of multiple defects further reduces the safety factor against the thermal track buckling phenomenon. The paper ends with the proposal of an evaluation criterion that takes into account the effects of multiple alignment defects on the critical buckling temperatures in continuous welded rail tracks.

DC High Speed circuit-breakers (DC-HSCB’s) and Protective Relays (PR’s) are present in all sorts of rail infrastructure. National or urban railways, tramways or metro’s, they all rely on this equipment to protect them from disastrous situations. The circuit-breakers can be installed either on board of the trains or on the trackside, in traction power substations. Protection Relays are, in most cases, part of the fixed installation. Needless to say that the DC-HSCB and PR are critical parts of the rail infrastructure. In the best case a faulty unit can cause the trains to stand still, in the worst case it can blow up parts of the infrastructure and cause casualties. The life-cycle of circuit-breakers is long, some of the units still in operation are more than 50 years old. The first digital protective relays were introduced in the eighties. Proper testing of DC-HSCB and PR is a hot topic these days as a result of a number of incidents on various LRT and tramway systems (STEVO Electric, 2015). This paper describes some issues with testing and how to resolve them.

This paper employs the finite element (FE) modeling method to investigate the contributing factors to the “horizontal” splitting cracks observed in the upper strand plane in some concrete crossties made with seven-wire strands. The concrete tie is modeled as a concrete matrix embedded with prestressing steel strands. A damaged plasticity model that can predict the onset and propagation of tensile degradation is applied to the concrete material. An elasto-plastic bond model developed in-house is applied to the steel-concrete interface to account for the interface bond-slip mechanisms and particularly the dilatational effects that can produce the splitting forces. The pretension release process is simulated statically, followed by the dynamic simulations of cyclic rail seat loading. The concrete compressive strength at which the pretension in the strands is released, or release strength, affects both the concrete behavior and the bond characteristics. Three concrete release strengths, 3500, 4500 and 6000 psi, are considered in the simulations. Concrete tie models without and with a fastening system are developed and simulated to examine the effect of embedded fastener shoulders and fastener installation. The fastener shoulders are seated relatively deeply reaching between the two rows of strands. There is instant concrete material degradation adjacent to the strand interfaces near the tie ends upon pretension release. Without the fastening system in the model, the 3500 psi release strength leads to a high degree of degradation that is coalesced and continuous in the upper and lower strand planes, respectively. The damage profiles with the higher release strengths are more discrete and disconnected. Dynamic loading appears to increase the degree of degradation over time. In all cases, the upper strand plane is not dominant in the degree or the extent of material degradation, in contrast to the field observations that the horizontal splitting occurred in the upper strand plane only. Further simulations with the fastener model at 3500 psi concrete release strength indicate that the fastener installation process does not worsen the damage profile. However, the presence of fastener shoulders in the concrete matrix changes the stress distribution and redirects more concrete damages to the upper strand plane, while leaving disconnected damages in the lower strand plane. Under repeated dynamic rail loading, this potentially reproduces the exact upper strand plane, horizontal cracking pattern observed in the field. Subjected to further experimental verification, the FE analyses identify three contributing factors to the horizontal macro-cracks occurring at the specific upper strand level: (1) relatively low concrete release strength during production, (2) embedded fastener shoulders that redistribute concrete damages to the upper strand plane, and (3) a sufficiently large number of dynamic rail loading cycles for the microscopic damages to develop into macro-cracks. The number of dynamic loading cycles needed to produce macro-cracks should increase with the increased concrete release strength.

With the increasing of the train load, the wheel-rail wear is worsening, the maintaining and replacing cycle is shortened enormously, the problem of replacing steel rail and wheel prematurely not only make the railway transportation cost increasing, but also affect the railway normal transportation. This paper proposes a novel type of active energy self-supply radial steering technology — the parallel interconnection hydraulic-electric energy-harvesting active radial steering bogie system. This system is a typical “machine – electric – hydraulic” coupling system, which includes parallel interconnection hydraulic-electric energy-harvesting suspension and active radial steering bogie, consisting of mechanical, electronic, hydraulic and control subsystems internally. In this system, the radial steering bogie is equipped with four HESA, and HESA can reuse the mechanical vibration energy which used to be transformed into waste heat by the shock absorber. In this system, the mechanical vibration energy is now used to drive power module of active radial steering bogie, so as to implement the train’s active radial steering without external power supply. This paper discusses the evolution of radial steering bogie in general, and introduces the structure and basic principle of the parallel interconnection electro-hydraulic energy-harvesting active radial steering bogie system. The system establishes a model of the parallel interconnection hydraulic-electric energy-harvesting shock absorber. The typical vertical irregularity of American track is established. In the paper, we research on the system’s damping performance and energy recovery performance through stimulation. Simulation results show that the maximum vertical acceleration of train body is reduced from 42.9% to 62.3%, and the average energy recovery power from the system increases from 217W to 1835W when the system works at the six levels of track irregularities.

This study focused on development and characterization of a multifunctional coating system for rail track applications, such as low solar absorption, long-term durability, and corrosion resistance. Both laboratory and field experiments were conducted using coated and uncoated rails exposed to sunlight at various ambient temperatures to evaluate the effectiveness of coating in reducing rail temperature. The experimental results show that the average temperature reduction provided by the coating was 10–25°F, depending on the peak air temperature and measurement method. The effect of measurement method on rail temperature was investigated using different instrumentation types (magnet sensor, thermocouple, and automated Salient system) and thermal modelling simulations. On the other hand, the coated rail segments were placed in to the accelerate corrosion testing in a customized chamber to evaluate the performance of coating under exposure of wet/dry and freeze/thaw cycles, UV radiation, and salt spray. The performance of the coated rail segments placed in the outdoor environment and the coated rail track at service were used to evaluate the durability of coating. Field application of coating demonstrates that the coating adheres well to the rails. The curing time is about an hour. The coating can be applied on active tracks with proper scheduling. The durability of the coating was observed over two winter seasons.

The research presented herein focuses on determining the amount of internal prestressing force and bending resistance that is necessary to provide a durable long-term concrete railroad tie. In order to accomplish this, the researchers conducted a systematic evaluation of existing concrete ties that successfully withstood over 25 years of service in track. An experimental method for determining the remaining prestress force in these existing prestressed concrete railroad ties is currently under development. The ties are first loaded in the upside-down orientation, with supports located at the rail seats, and two point loads applied at the center of the tie. A loading rate of 1,000 lb/min was used to initiate flexural cracking in the center of the tie. Once cracking was observed, the ties underwent 200 cycles of loading to reduce the friction between the prestressing tendons and the concrete. When the cycling was completed, the existing crack was instrumented with an extensometer to measure the Crack Opening Displacement (COD). The ties were loaded once more at 1,000 lb/min to develop a Load vs. COD relation. A systematic method of determining the load required to reopen the crack from the Load vs. COD relation is being developed using ties cast at a manufacturing plant that were instrumented with internal vibrating-wire strain gages. Using the load required to reopen the crack, along with the known cross-sectional properties at the center of the tie, the remaining prestress force is calculated through equilibrium of forces. This method allows for the determination of the remaining prestress force in a member with known section properties to be obtained through load testing.

Transportation industry at large is a major consumer of fossil fuels and contributes heavily to the global greenhouse gas emissions. A significant portion of these emissions come from freight transportation and decisions on mode/route may affect the overall scale of emissions from a specific movement. It is common to consider several alternatives for a new freight activity and compare the alternatives from economic perspective. However, there is a growing emphasis for adding emissions to this evaluation process. One of the approaches to do this is through Life Cycle Assessment (LCA); a method for estimating the emissions, energy consumption and environmental impacts of the project throughout its life cycle. Since modal/route selections are often investigated early in the planning stage of the project, availability of data and resources for analysis may become a challenge for completing a detailed LCA on alternatives. This research builds on such detailed LCA comparison performed on a previous case study by Kalluri et al. (2016), but it also investigates whether a simplified LCA process that only includes emissions from operations phase could be used as a less resource intensive option for the analysis while still providing relevant outcomes. The detailed LCA is performed using SimaPro software and simplified LCA is performed using GREET 2016 model. The results are obtained in terms of Kg CO 2 equivalents of GHG emissions. This paper introduces both detailed and simplified methodologies and applies them to a case study of a nickel and copper mine in the Upper Peninsula of Michigan. The analysis’ are done for three modal alternatives (two truck routes and one rail route) and for multiple mine lives.

Fifty years ago, the railcar industry relied entirely on classical analysis methods using fundamental solid mechanics theory to establish design and manufacturing protocols. While this method produced working designs, the assumptions required by this type of analysis often led to overdesigned railcars. In the 1950s, the generalized mathematical approach of Finite Element Analysis (FEA) was developed to model the structural behaviors of mechanical systems. FEA involves creating a numerical model by discretizing a continuous system into a finite system of grid divisions. Each grid division, or element, has an inherent geometric shape and each element is comprised of points which are referred to as nodes. The connected pattern of nodes and elements is called a mesh. A solver organizes the mesh into a matrix of differential equations and computes the displacements using linear algebraic operations from which strains and stresses are obtained. The rapid development of computing technology provided the catalyst to drive FEA from research into industry. FEA is currently the standard approach for improving product design cycle times that were previously achieved by trial and error. Moreover, simulation has improved design efficiency allowing for greater advances in weight, strength, and material optimization. While FEA had its roots planted in the aerospace industry, competitive market conditions have driven simulation into many other professional fields of engineering. For the last few decades, FEA has become essential to the submittal of new railcar designs for unrestricted interchange service across North America. All new railcar designs must be compliant to a list of structural requirements mandated by the Association of American Railroads (AAR), which are listed in its MSRP (Manual of Standards and Recommended Practices) in addition to recommended practices in Finite Element (FE) modeling procedures. The MSRP recognizes that these guidelines are not always feasible to completely simulate, allowing the analyst to justify situations where deviations are necessary. Benefits notwithstanding, FEA has inherent challenges. It is understood that FEA does not provide exact solutions, only approximations. While FEA can provide meaningful insight into actual physical behavior leading to shorter development times and lower costs, it can also create bogus solutions that lead to potential safety and engineering risks. Regardless of how appropriate the FEA assumptions may be, engineering judgment is required to interpret the accuracy and significance of the results. A constant balance is made between model fidelity and computational solve time. The purpose of this paper is to discuss the FEA approach to railcar analysis that is used by BNSF Logistics, LLC (BNSFL) in creating AAR compliant railcar designs. Additionally, this paper will discuss the challenges inherent to FEA using experiences from actual case studies in the railcar industry. These challenges originate from assumptions that are made for the analysis including element types, part connections, and constraint locations for the model. All FEA terminology discussed in this paper is written from the perspective of an ANSYS Mechanical user. Closing remarks will be given about where current advances in FEA technology may be able to further improve railcar industry standards.

The New York City Transit (NYCT) Signal Modernization Program has been ongoing since the mid-1990s. The current phase of modernization involves the procurement of Solid State Interlocking (SSI) systems that are designed to replace relay-based interlockings. SSI procurement has necessitated significant adjustments to NYCT’s system deployment processes, most notably in the areas of design, implementation, test, maintenance, and safety certification. NYCT has successfully met the challenge of applying the updated deployment processes to multiple, concurrent system procurements. The most fundamental change to the NYCT procurement approach required a shift from the traditional design-build model of acquisition for relay-based systems to a software-based development lifecycle for SSIs. The relay-based Interlocking systems’ design-build model has traditionally involved the realization of complex relay logic with well-known hardware components such as relays, trip-stops, signals and switch machines. The SSI systems’ software model however requires additional consideration of software and hardware development phases, such as designated in the V-lifecycle. V-model phases include requirement, design, implementation, and test. For SSI systems, NYCT adopted a “double” V-Life cycle approach, one V for the supplier’s SSI hardware and software (executive) platform, and one V for the SSI application (site-specific field) logic. At NYCT, the first V is dedicated to the suppliers’ executive platform. Hardware and software comprising the supplier platform are verified to meet safety and performance requirements. Safety analyses such as Fault Tree Analysis, Failure Modes and Effects Analysis, Timing Analysis, and Hazard Analysis are generated by SSI suppliers. System Safety Concepts, e.g., Numerical Assurance, Checked Redundancy, Intrinsic Fail-Safety are also assessed. NYCT’s second V is dedicated to the application software, i.e., the site-specific relay-based logic, which is implemented as Boolean logic within the SSI. For the Booleans, the process of traditional circuit checking is supplemented by Model Checking, wherein NYCT General Safety Properties are used to verify the site-specific logic. Model Checking provides assurance that safety properties are met throughout the entire interlocking design, for every system state, and does not rely on a manual review process. This paper will focus on the benefits NYCT has realized as a result of adopting Model Checking as a requirement for safety certification, along with an overview of the NYCT SSI safety certification process.