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Police investigators worldwide use lineups to test an eyewitness's memory of a perpetrator. A typical lineup consists of one suspect (who is innocent or guilty) plus five or more fillers who resemble the suspect and who are known to be innocent. Although eyewitness identification decisions were once biased by police pressure and poorly constructed lineups, decades of social science research led to the development of reformed lineup procedures that provide a more objective test memory. Under these improved testing conditions, cognitive models of memory can be used to better understand and ideally enhance eyewitness identification performance. In this regard, one question that has bedeviled the field for decades is how similar the lineup fillers should be to the suspect to optimize performance. Here, we model the effects of manipulating filler similarity to better understand why such manipulations have the intriguing effects they do. Our findings suggest that witnesses rely on a decision variable consisting of the degree to which the memory signal for a particular face in the lineup stands out relative to the crowd of memory signals generated by the set of faces in the lineup. The use of that decision variable helps to explain why discriminability is maximized by choosing fillers that match the suspect on basic facial features typically described by the eyewitness (e.g., age, race, gender) but who otherwise are maximally

The post-smolt phase is considered a critical period for Atlantic salmon ( Salmo salar). Hence, identifying migration routes used by post-smolts is needed to protect the habitats they require to successfully complete their life cycle. We used a biophysical model coupled with output from a water circulation model (FVCOM) to simulate dispersal of Atlantic salmon post-smolts in a semi-enclosed bay: Passamaquoddy Bay, New Brunswick, Canada. The model was run with nine post-smolt behaviours and six swimming speeds, and then tested against acoustic telemetry data. While no modelled behaviour entirely captured observed salmon migration routes, we identified some behaviours that could allow salmon to successfully leave the bay and resulted in predictions that matched observations reasonably well (e.g., swimming southwest, negative, or tide-varying rheotaxis). We could also rule out several behaviours as unlikely to be used by Atlantic salmon post-smolts in this area (e.g., passive dispersal, orienting based on salinity or temperature, and positive rheotaxis). Hence, with suitable behaviours and models, this approach can provide estimates of the essential habitats and migration routes of wild post-smolts.

The simultaneous six-pack photo lineup is a standard eyewitness identification procedure, consisting of one police suspect plus five physically similar fillers. The photo lineup is either a target-present array (the suspect is guilty) or a target-absent array (the suspect is innocent). The eyewitness is asked to search the six photos in the array with respect to a target template stored in memory (namely, the memory of the perpetrator's face). If the witness determines that the perpetrator is in fact in the lineup (detection), then the next step is to specify the position of the perpetrator's face in the lineup (localization). The witness may also determine that the perpetrator is not present and reject the lineup. In other words, a police lineup is a detection-plus-localization visual search task. Signal detection concepts that have long guided thinking about visual search have recently had a significant impact on our understanding of police lineups.

Currently, there are two types of defect detection systems used to monitor the health of freight railcar bearings in service: wayside hot-box detection systems and trackside acoustic detection systems. These systems have proven to be inefficient in accurately determining bearing health, especially in the early stages of defect development. To that end, a prototype onboard bearing condition monitoring system has been developed and validated through extensive laboratory testing and a designated field test in 2015 at the Transportation Technology Center, Inc. in Pueblo, CO. The devised system can accurately and reliably characterize the health of bearings based on developed vibration thresholds and can identify defective tapered-roller bearing components with defect areas smaller than 12.9 cm2 while in service.

The perceived replication crisis and the reforms designed to address it are grounded in the notion that science is a binary signal detection problem. However, contrary to null hypothesis significance testing (NHST) logic, the magnitude of the underlying effect size for a given experiment is best conceptualized as a random draw from a continuous distribution, not as a random draw from a dichotomous distribution (null vs. alternative). Moreover, because continuously distributed effects selected using a P < 0.05 filter must be inflated, the fact that they are smaller when replicated (reflecting regression to the mean) is no reason to sound the alarm. Considered from this perspective, recent replication efforts suggest that most published P < 0.05 scientific findings are “true” (i.e., in the correct direction), with observed effect sizes that are inflated to varying degrees. We propose that original science is a screening process, one that adopts NHST logic as a useful fiction for selecting true effects that are potentially large enough to be of interest to other scientists. Unlike original science, replication science seeks to precisely measure the underlying effect size associated with an experimental protocol via large- N direct replication, without regard for statistical significance. Registered reports are well suited to (often resource-intensive) direct replications, which should focus on influential findings and be published regardless of outcome. Conceptual replications play an important but separate role in validating theories. However, because they are part of NHST-based original science, conceptual replications cannot serve as the field’s self-correction mechanism. Only direct replications can do that.

Recent work has established that high-confidence identifications (IDs) from a police lineup can provide compelling evidence of guilt. By contrast, when a witness rejects the lineup, it may offer only limited evidence of innocence. Moreover, confidence in a lineup rejection often provides little additional information beyond the rejection itself. Thus, although lineups are useful for incriminating the guilty, they are less useful for clearing the innocent of suspicion. Here, we test predictions from a signal-detection-based model of eyewitness ID to create a lineup that is capable of increasing information about innocence.Our model-based simulations suggest that high-confidence rejections should exonerate many more innocent suspects and do so with higher accuracy if, after a witness rejects a lineup but before they report their confidence, they are shown the suspect and asked, "How sure are you that this person isParticipants (The reveal procedure increased both the accuracy and frequency of high-confidence rejections relative to the standard simultaneous lineup.Collecting a confidence rating about the suspect after a lineup is rejected may make it possible to quickly clear innocent suspects of suspicion and reduce the amount of contact that innocent people have with the legal system. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

As part of a criminal investigation, the police often administer a recognition memory task known as a photo lineup. A typical 6-person photo lineup consists of one suspect (who may or may not be guilty) and five physically similar foils (all known to be innocent). The photos can be shown simultaneously (i.e., all at once) or sequentially (i.e., one at a time). Approximately 30% of U.S. police departments have moved to using the sequential lineup procedure over the last 30 years, yet its theoretical underpinnings remain poorly understood. A simple signal detection model makes several unexpected predictions about how the sequential lineup procedure should affect the ability of eyewitnesses to discriminate innocent from guilty suspects. For example, empirical discriminability (area under the receiver operating characteristic) should decrease as the position of the suspect in the lineup increases. In addition, under some conditions, a fair sequential lineup should not yield higher discriminability than a single-person (non-lineup) recognition test known as a showup. The results of two experiments reported here confirmed these predictions. Counterintuitively, even though empirical discriminability decreased as the suspect’s sequential position increased, a signal detection model fit to the data indicated that theoretical discriminability exhibited a small effect in the opposite direction (increasing with the sequential position of the suspect). The latter result is consistent with diagnostic feature-detection theory of eyewitness identification.

A typical police lineup contains a photo of one suspect (who is innocent in a target-absent lineup and guilty in a target-present lineup) plus photos of five or more fillers who are known to be innocent. To create a fair lineup in which the suspect does not stand out, two filler selection methods are commonly used. In the first, fillers are selected if they are similar in appearance to the suspect. In the second, fillers are selected if they possess facial features included in the witness's description of the culprit (e.g., "20-y-old white male"). The police sometimes use a combination of the two methods by selecting description-matched fillers whose appearance is also similar to that of the suspect in the lineup. Decades of research on which approach is better remains unsettled. Here, we tested a counterintuitive prediction made by a formal model based on signal detection theory: From a pool of acceptable description-matched photos, selecting fillers whose appearance is otherwise dissimilar to the suspect should increase the hit rate without affecting the false-alarm rate (increasing discriminability). In Experiment 1, we confirmed this prediction using a standard mock-crime paradigm. In Experiment 2, the effect on discriminability was reversed (as also predicted by the model) when fillers were matched on similarity to the perpetrator in both target-present and target-absent lineups. These findings suggest that signal-detection theory offers a useful theoretical framework for understanding eyewitness identification decisions made from a police lineup.

Efforts to increase replication rates in psychology generally consist of recommended improvements to methodology, such as increasing sample sizes to increase power or using a lower alpha level. However, little attention has been paid to how the prior odds ( R) that a tested effect is true can affect the probability that a significant result will be replicable. The lower R is, the less likely a published result will be replicable even if power is high. It follows that if R is lower in one set of studies than in another, then all else being equal, published results will be less replicable in the set with lower R. We illustrate this point by presenting an analysis of data from the social-psychology and cognitive-psychology studies that were included in the Open Science Collaboration’s (2015) replication project. We found that R was lower for the social-psychology studies than for the cognitive-psychology studies, which might explain why the rate of successful replications differed between these two sets of studies. This difference in replication rates may reflect the degree to which scientists in the two fields value risky but potentially groundbreaking (i.e., low- R) research. Critically, high- R research is not inherently better or worse than low- R research for advancing knowledge. However, if they wish to achieve replication rates comparable to those of high- R fields (a judgment call), researchers in low- R fields would need to use an especially low alpha level, conduct experiments that have especially high power, or both.

In our target article (1), we note that signal detection theory evolved (2) from Fisher’s (3) null hypothesis significance testing (NHST) approach ( H : δ = 0, H 1: δ ≠ 0) as elaborated by Neyman and Pearson (4), who additionally proposed considering the specific magnitude of the alternative hypothesis ( H : δ = 0, H 1: δ = μ). We then argue that this perspective is a useful fiction, not an accurate depiction of underlying reality. The true, underlying effect size (δ) associated with an experimental protocol is more reasonably conceptualized as having been drawn from a continuous distribution, and it is never equal to zero. Pek et al. (5) argue that the Fisherian perspective can be revised by dropping the null hypothesis fiction … [↵][1]1To whom correspondence may be addressed. Email: b6wilson{at}ucsd.edu or jwixted{at}ucsd.edu. [1]: #xref-corresp-1-1

The recent collection (2009) of an American talon crab, Euchirograpsus americanus A. Milne-Edwards, 1880, in the Bay of Fundy, Canada has expanded the known distribution of this enigmatic plagusiid crab species typically found in subtropical and tropical waters of the Gulf of Mexico, Caribbean, and Carolinas. Although historical records are limited, they document a northward range expansion of the species with occurrences off North Carolina in 1962, Delaware in 1979, and further to New Jersey in 1981, which would discount these northerly records as independent, accidental introductions. The present exclusive record of the talon crab in Canadian waters is also from the shallowest (6.3 m) and coldest waters (8.3°C) that the species has thus far been documented in. The literature, until now, indicated an affinity for sandy or rocky bottom between 31 and 510 m depth at temperatures of 11-24°C. While establishment of the species in the region remains uncertain, the present record is perhaps indicative of large-scale processes, such as climate change, that are altering species distributions.

Face recognition memory is often tested by the police using a photo lineup, which consists of one suspect, who is either innocent or guilty, and five or more physically similar fillers, all of whom are known to be innocent. For many years, lineups were investigated in lab studies without guidance from standard models of recognition memory. More recently, signal detection theory has been used to conceptualize lineup memory and to motivate receiver operating characteristic (ROC) analysis of lineup performance. Here, we describe three competing signal-detection models of lineup memory, derive their likelihood functions, and fit them to empirical ROC data. We also introduce the notion that memory signals generated by the faces in a lineup are likely to be correlated because, by design, those faces share features. The models we investigate differ in their predictions about the effect that correlated memory signals should have on the ability to discriminate innocent from guilty suspects. A popular compound signal detection model known as the Integration model predicts that correlated memory signals should impair discriminability. Empirically, this model performed so poorly that, going forward, it should probably be abandoned. The best-fitting model incorporates a principle known as “ensemble coding,” which predicts that correlated memory signals should enhance discriminability. The ensemble model aligns with a previously proposed theory of eyewitness identification according to which the simultaneous presentation of faces in a lineup enhances discriminability compared to when faces are presented in isolation because it permits eyewitnesses to detect and discount non-diagnostic facial features.

The effect of mindfulness meditation on false-memory susceptibility was examined in three experiments. Because mindfulness meditation encourages judgment-free thoughts and feelings, we predicted that participants in the mindfulness condition would be especially likely to form false memories. In two experiments, participants were randomly assigned to either a mindfulness induction, in which they were instructed to focus attention on their breathing, or a mind-wandering induction, in which they were instructed to think about whatever came to mind. The overall number of words from the Deese-Roediger-McDermott paradigm that were correctly recalled did not differ between conditions. However, participants in the mindfulness condition were significantly more likely to report critical nonstudied items than participants in the control condition. In a third experiment, which tested recognition and used a reality-monitoring paradigm, participants had reduced reality-monitoring accuracy after completing the mindfulness induction. These results demonstrate a potential unintended consequence of mindfulness meditation in which memories become less reliable.

The effects of lamellar duplex microstructure within grains that contain alternating phases of cementite and ferrite on ultrasonic scattering in railroad wheel steel are evaluated using a diffuse ultrasonic backscatter technique. A new singly scattered response (SSR) model that considers the lamellar duplex microstructure within grains is developed based on a previous SSR model. The results show that the amplitude of ultrasonic scattering decreases with decreasing lamellar space. Corresponding experiments are performed with 10 MHz and 15 MHz focused transducers by scanning both unquenched and quenched wheels. The experimental results show that the ultrasonic scattering amplitudes drop dramatically near the quenched tread surface, a result which is attributed to the creation of duplex microstructure (pearlite phase) within grains due to the quenching process. The lamellar spacing within grains increases progressively from the tread surface to the deeper locations due to the non-uniform cooling rate. The distribution of lamellar spacing within grains as a function of depth is quantified with the modified SSR model. Good agreement with optical microscopy is observed. The diffuse ultrasonic backscatter technique exhibits strong sensitivity to microstructure changes, an outcome that may be applicable for quality control during manufacturing.

The rolling surface for railroad wheels can be a heat source that may have an impact on the performance of the wheel bearing. In this study, experimental data from an electrically-heated railroad wheel set is analyzed by constructing thermal models of the wheel set. A steady finite-element model, a steady-analytical model, and a transient lumped-parameter model are discussed. Model parameters are determined from careful comparisons with the experimental data. The lumped-parameter model given here is intended as a simple predictive tool for determining when wheel heating caused by rail operations will have an impact on bearing temperature. The model parameters found in this study will also be useful as experimentally-validated boundary conditions in ongoing finite-element studies of heated wheels.

Exact solutions are given for the transient temperature in flux-base fins with the method of Green’s functions (GF) in the form of infinite series for three different tip conditions. The speed of convergence is improved by replacing the steady part by a closed-form steady solution. For the insulated-tip case, a quasi-steady solution is presented. Numerical values are presented and the conditions under which the quasi-steady solution is accurate are determined. An experimental example is given for estimation of the heat transfer coefficient (HTC) on a non-rotating roller bearing, in which the outer bearing race is treated as a transient fin.

Based on this initial work, several laboratory experiments were conducted using heaters embedded in two rollers to study the dynamics of heating in railroad tapered-roller bearings. This paper describes the results of these heat transfer experiments. The paper begins with a review of current detection methods and previous studies that investigated bearing heating due to the presence of defects. Next, the experimental setup and procedures are explained in detail, which is then followed by the development of zero- and first-order models that were used to fit the experimental data in order to estimate overall heat transfer coefficients for the bearing. The paper wraps up with a discussion of the results and a summary.

The assessment of corrosion on the USS Arizona included the pioneering development of a minimum-impact cost-effective technique to determine the corrosion rate of steel-hulled shipwrecks in seawater. The technique, with potential application worldwide, is illustrated in this paper with the application to a World War II Japanese midget submarine submerged in deep waters off the Oahu, Hawaii, coast.

Fatigue spall initiation is one of the major modes of premature bearing failure. The spall initiation is often exacerbated by the presence of impurities in the near-surface region (∼400 μm) of the bearing raceways. Once a spall initiates, it can propagate rapidly, leading to abnormal bearing operation and possible catastrophic failure if not detected early. Testing performed at the University of Texas-Pan American (UTPA) has focused on ultrasonically scanned tapered roller bearings found to have inclusion content within 400 μm of the surface of the raceways. These bearings undergo accelerated service life tests in which spall initiation is detected and tracked over time while documenting spall growth. The work presented here provides several study cases that document the spall initiation and propagation on ultrasonically scanned tapered roller bearing components. Results show that spalls generally initiate on locations corresponding to sites of subsurface inclusions, and they grow many times their original size within relatively short operating periods. The study also shows that spalls tend to initiate and propagate at a faster rate on bearing cups (outer rings) than on cones (inner rings).Copyright © 2015 by ASME

The importance of steel cleanliness for the performance of tapered roller bearings has been clearly established and has led to on-going improvements in steel production methods. The presence of non-metallic impurities within the steel can result in hard/brittle inclusions that may serve as initiation sites for damage due to sub-surface rolling contact fatigue (RCF) if the inclusions lie within the near-race of the bearing components due to the high mechanical stress present. Current inspection standards define steel cleanliness with respect to bulk inclusion morphology, which limits inspection to a small area that may or may not be representative of the entire steel heat. In this presentation, ultrasonic surface wave methods are described for detecting subsurface inclusions directly on finished bearing inner and outer rings. We expand on our previous work to exploit the different inspection depths that can be achieved with different measurement frequencies. The impact of the different inspection depths is quantified through simulated service life testing with heavy axle loading conditions. For this study, bearing components were first subjected to ultrasonic surface wave testing at three different frequencies to identify near-race inclusions. The simulated service life testing was then used to assess the onset and propagation of RCF failure. RCF spall initiations correlated highly with the positions identified by the ultrasonic inspections suggesting that this approach has a predictive potential. However, additional research is needed to establish the specific criteria needed for such predictions with respect to the inclusion location along the race, the depth from the race surface, the inclusion morphology and the inclusion mechanical properties. This work is anticipated to improve the understanding of RCF damage initiation which will lead a higher level of safety for railroad operations.Copyright © 2015 by ASME

Current research on USS Arizona is focused on a minimum-impact technique for calculating corrosion rate of the battleship's steel hull by analysing physical and chemical properties of marine encrustation covering the exposed hull. An equation is derived that allows concretion thickness, density, and total iron content to be used to calculate corrosion rate of steel hull plate. © 2006 The Authors

Increasing freight car loads demand higher performance tapered roller bearings. As the stress state on railway bearing applications continues to increase, further advancement in the modeling tools and methods used for subsurface contact stress evaluations are needed. Heat treat specifications and contact geometries for railway bearings were originally developed for ideal load conditions. However, in railroad applications, tapered roller bearings are exposed to a vast range of load conditions that are seldom perfect. Moreover, when comparing global rail markets, there are often differences in bearing loads, railcar wear conditions, maintenance practices, and reliability versus utilization expectations. Advanced modeling techniques need to be developed by bearing designers in order to meet the specific needs of each individual rail market. Prior research has shown that subsurface stresses, resulting from rolling contact, are the primary factor in the development of fatigue cracks in railway bearings. In addition, finite element modeling software has previously been used to analyze Hertzian contact stresses under rolling contact. Recent advancements in the technology and computational power of finite element methods can be used to numerically analyze more detailed simulations of complex geometries and biased load conditions in railway bearings. These improvements in the tapered roller bearing modeling methodology are necessary to determine the material, heat treat specifications, and geometry required to meet the demands of specific railway bearing applications. Furthermore, the specific risks associated with some common railway bearing design and modeling assumptions will be evaluated. An exploratory list of these assumptions include: line versus point contact, load deflection factor, zero contact angle, rigid body assumptions, linear material behavior, neglect for overload, and uniform loading on the bearing. Emphasis will be placed on potential improvements in the theoretical and finite element prediction of surface and subsurface stresses in railway bearings under rolling contact with a review of prior research on the subject.

In this article, the measurement of quench depth in railroad wheels is demonstrated using a diffuse ultrasonic backscatter technique. A singly-scattered response (SSR) model that accounts for the gradation of lamellar spacing (duplex microstructure) within grains in the direction of ultrasonic propagation is developed based on the previous single-phase model. The effects of a graded microstructure on ultrasonic scattering are observed by comparing the spatial variance curve measured from the tread surface to that measured from the cross section. The experimental results show that the graded SSR model fits the spatial variance curve from the tread surface much better than the uniform SSR model. The spatial variance peaks increase in amplitude and shift to later times when the material path is increased (deeper focus). The experimental variance curve from the tread surface is then fit with the model in a least-squares sense such that the quench depth can be estimated. The diffuse ultrasonic backscatter technique can be used not only to distinguish microstructure changes, but also to quantify the quench depth, an outcome that may be applicable for quality control during manufacturing.

The development of a tool called the Service Load Factor (SLF) for railway tapered roller bearings using residual stress and retained austenite data is presented. Case-carburized tapered roller bearings used in the railroad industry are manufactured with a dual-phase microstructure that consists primarily of tempered martensite and retained austenite. The retained austenite phase is metastable, and will transform to martensite with sufficient thermal or mechanical energy during service. The increase in surface volume because of transformation, and the subsequent increase in compressive residual stress could indicate the onset of certain failure modes, including fatigue spalling. In addition, retained austenite transformation can lead to an increase in bore diameter, which could result in a loss of fit on the axle journal. Several bearing inner races with various service histories were measured with a Siemens X-ray diffractometer using chromium radiation. Results indicated that the transformation of retained austenite and resultant increase in compressive residual stress are interrelated with load and rolling cycles. Results indicate that the SLF is a useful tool that correlates well with current Association of American Railroads failure criteria.

Objectives We examined whether a sugary drink limit would still be effective if larger-sized drinks were converted into bundles of smaller-sized drinks. Methods In a behavioral simulation, participants were offered varying food and drink menus. One menu offered 16 oz, 24 oz, or 32 oz drinks for sale. A second menu offered 16 oz drinks, a bundle of two 12 oz drinks, or a bundle of two 16 oz drinks. A third menu offered only 16 oz drinks for sale. The method involved repeated elicitation of choices, and the instructions did not mention a limit on drink size. Results Participants bought significantly more ounces of soda with bundles than with varying-sized drinks. Total business revenue was also higher when bundles rather than only small-sized drinks were sold. Conclusions Our research suggests that businesses have a strong incentive to offer bundles of soda when drink size is limited. Restricting larger-sized drinks may have the unintended consequence of increasing soda consumption rather than decreasing it.

Bearing steel cleanliness is directly linked to failures caused by the interaction of subsurface defects and rolling contact fatigue (RCF). Optical analysis of as-received steel coupled with ultrasonic inspection on finished components minimizes the occurrence of defects in the near race. While useful as a preventative measure, these methods do not ensure that critical areas of components subjected to RCF are free of defects that act as stress concentrators and contribute to premature failure. This presentation provides a brief summary of the current technology and standards utilized in the industry. The deficiencies of the current methods for the particular case at hand are identified and a surface wave scanning method is introduced. The development and production of reference parts for this type of scanning are then discussed. The production method entails both traditional electro-discharge machining (EDM) and femtosecond laser machining (FLM) on finished bearing components such that the reference part microstructure resembles that of a finished part. Experimental results utilizing surface wave scanning are given for two types of assembly-ready bearing components that are then subjected to realistic service loads and mileage to the point of failure. The results of the service life simulations are then correlated with surface wave scanning results and are shown to be in good agreement. This work is anticipated to impact any field in which components are subjected to RCF.Copyright © 2012 by ASME

With the need for rail systems to provide long distance and highly reliable operations, problems that could arise should be quickly detected and addressed such that they do not become major issues. If undetected, sudden component faults can result in costly and difficult repair scenarios, and in the worst case, derailments, which can be catastrophic if they occur in populated areas. One such problem, Bearing Burn-off, can result in significant damage to the cars as well as to the rail infrastructure, often before the symptoms can be detected by rail crews and in most situations by wayside mounted infrastructure. A system developed by IONX for railroad operations is designed to monitor rail car bearings to detect potential burn-off conditions before they arise and before they become destructive. This system is comprised of a Central Monitoring Unit (CMU) and Wireless Sensor Nodes (WSNs) which continuously monitor bearing temperatures as well as the current ambient temperature. The application of various algorithms not only conducts trend analysis to anticipate burn-off events, but also reports events at predetermined temperature limits to provide early warning and immediately actionable feedback to locomotive engineers. With these alerts, the driver or train controller can then decide on the appropriate action to be taken and destructive consequences can be avoided saving operational and infrastructure costs. For this pilot study, a total of ten freight cars and fifteen locomotives were equipped, operated, and monitored for an initial three month period. This paper presents preliminary operational results for these tests demonstrating the benefits of predictive condition monitoring systems in real-world applications.

In the railroad industry, distressed bearings in service are primarily identified using wayside hot-box detectors (HBDs). Current technology has expanded the role of these detectors to monitor bearings that appear to “warm trend” relative to the average temperatures of the remainder of bearings on the train. Several bearings set-out for trending and classified as nonverified, meaning no discernible damage, revealed that a common feature was discoloration of rollers within a cone (inner race) assembly. Subsequent laboratory experiments were performed to determine a minimum temperature and environment necessary to reproduce these discolorations and concluded that the discoloration is most likely due to roller temperatures greater than 232 °C (450 °F) for periods of at least 4 h. The latter finding sparked several discussions and speculations in the railroad industry as to whether it is possible to have rollers reaching such elevated temperatures without heating the bearing cup (outer race) to a temperature significant enough to trigger the HBDs. With this motivation, and based on previous experimental and analytical work, a thermal finite element analysis (FEA) of a railroad bearing pressed onto an axle was conducted using ALGOR 20.3™. The finite element (FE) model was used to simulate different heating scenarios with the purpose of obtaining the temperatures of internal components of the bearing assembly, as well as the heat generation rates and the bearing cup surface temperature. The results showed that, even though some rollers can reach unsafe operating temperatures, the bearing cup surface temperature does not exhibit levels that would trigger HBD alarms.

This paper discusses the benefits of using on-board hand brake sensors to determine whether a freight car hand brake is applied or released in service. Unreleased hand brakes are a significant source of wheel tread damage, which can lead to wheel removals, and in extreme cases can cause damage and derailments. Also, hand brake-related accidents are a significant cause of North American railroad accidents. Wheel tread damage and wayside wheel impact load detectors (WILD) are reviewed, along with AAR why made codes for wheel removals. Wheel failures and other wheel impact associated damage are discussed, along with operational considerations for hand brakes. Further, on-board sensors in general, and hand brake sensors in particular, are described in detail and service data from monitored cars is presented. Additionally, possible safety and operational improvements related to use of hand brake sensors are discussed, along with comments on the use of sensors to assist with proactive maintenance of freight cars.Copyright © 2011 by ASME

At present there are no existing bearing health monitoring systems capable of continuous monitoring and tracking of railroad bearings on freight cars. Current wayside equipment is used to garner intermittent bearing cup temperatures, which at times could be every 65 km (∼40 mi) or more. Such devices are not designed to provide continuous condition monitoring which would enable users to assess the rate of bearing health degradation and predict when a bearing will require service. To this end, IONX, LLC, a subsidiary of Amsted Rail, Inc., has developed low power Wireless Sensor Nodes (WSNs) which can be retrofitted to existing bearing adapters. The WSNs provide continuous monitoring of bearing temperatures as well as the current ambient temperature. Since the nodes are affixed to the bearing adapter surface, a correlation is necessary to estimate the bearing cup temperature using the measured adapter surface temperature. This paper describes research conducted at The University of Texas-Pan American (UTPA) to devise a reliable mathematical model to correlate both temperatures. Additionally, these wireless nodes are currently in use on ten railroad cars that are part of an Australian fleet. The nodes have been collecting data since March 2010. The acquired data was used to devise and test a series of metrics that can automatically detect distressed bearings and predict time to maintenance. The development of bearing health monitoring metrics and their use to assess bearings in the Australian fleet is also discussed in this paper.

Catastrophic bearing failure is a major concern for the railroad industry because it can lead to costly train stoppages and even derailments. Excessive heat buildup within the bearing is one of the main factors that can warn of impending failure. A question is often raised regarding the transfer of heat from a wheel during braking and whether this can lead to false setouts. Therefore, this work was motivated by the need to understand and quantify the heat transfer paths to the tapered roller bearing within the railroad wheel assembly when wheel heating occurs. A series of experiments and finite element (FE) analyses were conducted in order to identify the different heat transfer mechanisms, with emphasis on radiation. The experimental setup consisted of a train axle with two wheels and bearings pressed onto their respective journals. One of the wheels was heated using an electric tape placed around the outside of the rim. A total of 32 thermocouples scattered throughout the heated wheel, the axle, and the bearing circumference measured the temperature distribution within the assembly. In order to quantify the heat radiated to the bearing, a second set of experiments was developed; these included, in addition to the axle and the wheel pair, a parabolic reflector that blocked body-to-body radiation to the bearing. The appropriate boundary conditions including ambient temperature, emissivity, and convection coefficient estimates were measured or calculated from the aforementioned experiments. The FE thermal analysis of the wheel assembly was performed using the ALGOR™ software. Experimental temperature data along the radius of the heated wheel, the bearing circumference, and at selected locations on the axle were compared to the results of the FE model to verify its accuracy. The results indicate that the effect of thermal radiation from a hot wheel on the cup temperature of the adjacent bearing is minimal when the wheel tread temperature is at 135°C (275°F), and does not exceed 17°C (31°F) when the wheel tread is at 315°C (600°F).

Over the past two years, a series of papers have been published concerning bearing temperature trending and a mechanism to explain this troubling phenomenon. In September of 2008, a collaborative field test between The Union Pacific Railroad (UP), Amsted Rail, Rail Sciences Inc. (RSI), and The University of Texas-Pan American (UTPA) was conducted to corroborate the findings of laboratory research and testing. Field and laboratory results confirm that temperature trended bearings exhibit vibration signals that can be distinguished from healthy bearings. Distinct primary frequencies and overtones associated with the axle, cone, cage, and rollers can be readily identified within a bearing vibration signal. In a previous paper, it was demonstrated that a trended bearing exhibits vibrations of higher magnitude. However, all characteristic frequencies appear in both healthy and trended bearings, but those that dominate, i.e., have higher magnitude, are distinct for trended bearings when compared to healthy bearings. The latter can be repeatedly demonstrated in both field and laboratory experiments. Moreover, the current work identifies and distinguishes between the primary bearing frequencies and those linked to roller misalignment, which is known to increase friction and wear, and consequently raise the bearing temperature.Copyright © 2009 by ASME

Over the last three years, numerous laboratory tests have been conducted with the goal of identifying the root cause of the temperature trending phenomenon observed in tapered roller bearings during their field service. The experimental efforts were successful in duplicating the temperature trending phenomenon in the lab, and concluded that vibration induced roller misalignment was responsible for this troubling phenomenon; yet field verification of these findings was still missing. To this end, a collaborative on-track field test was carefully planned and executed by The Amsted Rail Company, The Union Pacific Railroad (UP), Rail Sciences Inc. (RSI), and The University of Texas-Pan American (UTPA). A locomotive, a business car, and two coal cars — one fully loaded and one empty — were made available by the UP for the purposes of this test. Four bearings that exhibited temperature trending during the laboratory testing, and two other bearings that were set-out for temperature trending by the UP, were mounted next to six high impact wheels of at least 70 kips. The impact wheels were used as external vibration sources. Three of these wheels were placed under the fully loaded coal car, and the other three under the empty car. The remaining components used in the test were all defect free bearings and wheels. All sixteen bearings were instrumented with thermocouples and accelerometers, with four additional accelerometers monitoring the track joints and defects and the car pitch and bounce. This paper provides a summary of the initial analysis of the acquired data which indicates that the field test was successful in verifying the laboratory findings.

A predictive life tool for case-carburized railcar tapered roller bearings, called the Service Load Factor (SLF), makes use of residual stress and retained austenite data to assess the condition of bearings as a result of service history. It is well known that the interaction between retained austenite transformation and the development of residual stresses are primary factors contributing to cone bore growth and decreased resistance to raceway spalling. This paper attempts to quantify these changes throughout the life of a bearing to provide insight into the predicted remaining service life of the bearing. Also, this paper will cover the use of the SLF as a failure analysis tool in order to quantify bearing damage due to shifted lading or worn adapters.Copyright © 2008 by ASME

One of the most important issues for bearing grade steels is the cleanliness of the steel. Impurities present in a cast steel can manifest as hard/brittle inclusions, which are detrimental to a bearing in service. An advanced ultrasonic measurement technique is developed to determine the inclusion size and density in bearing components. Using ultrasonic C-Scan, a map of the inclusions can be developed that pinpoints the worst areas in an entire cone or cup section nondestructively. A threshold is developed for determining good or bad locations so that specific gate settings can parse those discontinuities considered to be detrimental to rolling contact performance. In addition, multiple transducer sizes and frequencies are investigated to determine an optimized scanning configuration. This protocol can then be adapted to perform quality control specific scans capable of investigating numerous parts and determining a failure rate using the rejection criteria.

Bearing temperature trending is an ongoing problem that is receiving considerable attention in the railroad industry. Currently, bearings that display this phenomenon are removed from service since a trended bearing exhibits similar behavior to a burn-off bearing at the end of its life. The removal and replacement of these bearings is a costly process, in addition to causing undesirable time delays. Even though this topic has received ample attention, to date, research efforts have been unable to identify the mechanism(s), or the root cause(s), of this troubling phenomenon. Motivated by the latter, the study presented here focuses on identifying the root cause of the bearing temperature trending seen in service. To this effect, eight laboratory experiments were performed using three bearings that had been removed from service due to temperature trending, along with their mates. Laboratory experiments were performed on a test rig that accommodates four Class F bearings simultaneously rotating at a speed of 536 rpm, which corresponds to a train traveling with a velocity of approximately 57 mph (91.7 km/h). The laboratory study was successful in duplicating the bearing temperature trending phenomenon seen in service, and consequently identifying the main source of this problem. Data presented will include both temperature and vibration profiles measured during normal and trending phases, along with inspection results.

In the railroad industry, bearing hot-box detectors are the primary tools utilized for the removal of distressed bearings from service. Current technology has expanded the role of these detectors to monitor bearings that appear to “warm trend” relative to the average temperatures of the remainder of bearings on the train. Several bearings set-out for trending and classified as non-verified revealed that a common feature was discoloration of rollers within a cone assembly. A number of laboratory tests were performed to determine a minimum temperature and environment needed to reproduce these discolorations. In addition, a metallurgical examination concluded that microhardness profiles from discolored rollers exhibited evidence of heating, which lead to softening of the case microstructure, and a reduction in case depth. In order to determine a cause for the internal heat leading to the discoloration of rollers, selected laboratory experiments were carried out in a simulated service environment. Testing focused on exploring certain defects or hypothetical scenarios that may raise the bearing cup temperature above that of normal operating conditions. None of the examined cases resulted in similar roller discolorations to those observed in the trended set-outs. The studies presented in this paper comprise the initial work aimed at determining the root cause of warm bearing trending that some tapered roller bearings experience during service.Copyright © 2008 by ASME