bluuebunny/crossref_metadata_2025_split huggingface dataset:
Evaluation of Phase Transformation Strain and Its Influence on Residual Stress Generation in Laser Welded Ti–6Al–4V Alloy
Authors: Kumar Bikash , Bag Swarup , Ruhul Amin M. 
Published: June 2022

Abstract
The assessment of welding-induced residual stress is always of significant interest due to its adverse effect on the structural stability and mechanical performance of the welded structure. Incorporation of intricate phenomena, in particular, thermal gradient, phase development, volumetric dilation, and phase transformation strain during FE modelling, not only acts as a reliable method for residual stress calculation but also serves as a directive to reduce tensile residual stress in a weldment which is sensitive to the selection of materials. In order to investigate the same for continuous and pulse laser-welded Ti–6Al–4V alloy, the sequentially coupled thermal–metallurgical–mechanical models are established. The internal state-dependent variables (SDVs) are implemented to capture the growth of phase evolved during diffusionless β → α′ transformation using Koistinen–Marburger (K–M) theory in the cooling cycle. The role played by a phase transformation induced strain on the generation of residual stress is systematically investigated. The volumetric dilation and associated phase fraction form the basis for the estimation of phase transformation strain in the present study. The accomplishment of highest martensitic fraction (∼95%) produced a phase transformation strain of 7.95 × 10−3 in pulse mode of operation. As a result, reversal of residual stress from tensile to compressive is perceived for pulse laser-welded specimen. Similarly, a sign of enriched martensitic transformation is noticed that puts the weld surface into a compression state and mitigates the overall tensile residual stress. The assumption of diffusional phase transformation during heating cycle and non-diffusional transformation during cooling phase in laser welding is more appropriate to predict the residual stress using thermal–metallurgical–mechanical model.
Thermal Model of a Parabolic Trough Solar Field With a Closed-Loop Operation During Sunrise Period
Authors: Lekhal R. , Ait-Ali M. A. , Ahmed Zaid T. 
Published: June 2022

Abstract
This work presents a numerical simulation of a thermal model for a solar loop with parabolic trough collectors (PTCs) considering fluid recirculation at closed-loop (CL) operation during sunrise. At the beginning of the day, the heat transfer fluid (HTF) is recirculated in a CL to obtain the inlet loop operating temperature without resorting to additional preheating energy. Energy balances are carried out on the HTF, the absorber tube, and the glass envelope as a function of optical and thermo-physical parameters of the heat collector element (HCE). A system of second-order differential equations was established, and mathematical model was resolved by finite difference and Newton–Raphson methods for solution. This model has been well validated by comparing the results with the existing experimental and numerical data. Three typical days of winter, spring, and summer were simulated for the solar loop operation considering a CL fluid recirculation at start-up conditions. Results show a more flexible CL operation at relatively large flowrates compared to the open-loop (OL) operation, which requires substantial preheating energy at the same conditions; the start-up solar field using the CL strategy allows us both operational autonomy and significant energy savings. Solar loop thermal and optical powers gained and lost are plotted for the typical days considered; we observe that maximum thermal efficiency of 66.53% is achieved at 2.27 p.m. for the summer day.
Data-Driven Simulation of Fisher–Kolmogorov Tumor Growth Models Using Dynamic Mode Decomposition
Authors: Viguerie Alex , Grave Malú , Barros Gabriel F. , Lorenzo Guillermo , Reali Alessandro , Coutinho Alvaro L. G. A. 
Published: June 2022

Abstract
The computer simulation of organ-scale biomechanistic models of cancer personalized via routinely collected clinical and imaging data enables to obtain patient-specific predictions of tumor growth and treatment response over the anatomy of the patient's affected organ. These patient-specific computational forecasts have been regarded as a promising approach to personalize the clinical management of cancer and derive optimal treatment plans for individual patients, which constitute timely and critical needs in clinical oncology. However, the computer simulation of the underlying spatiotemporal models can entail a prohibitive computational cost, which constitutes a barrier to the successful development of clinically-actionable computational technologies for personalized tumor forecasting. To address this issue, here we propose to utilize dynamic-mode decomposition (DMD) to construct a low-dimensional representation of cancer models and accelerate their simulation. DMD is an unsupervised machine learning method based on the singular value decomposition that has proven useful in many applications as both a predictive and a diagnostic tool. We show that DMD may be applied to Fisher–Kolmogorov models, which constitute an established formulation to represent untreated solid tumor growth that can further accommodate other relevant cancer phenomena (e.g., therapeutic effects, mechanical deformation). Our results show that a DMD implementation of this model over a clinically relevant parameter space can yield promising predictions, with short to medium-term errors remaining under 1% and long-term errors remaining under 20%, despite very short training periods. In particular, we have found that, for moderate to high tumor cell diffusivity and low to moderate tumor cell proliferation rate, DMD reconstructions provide accurate, bounded-error reconstructions for all tested training periods. Additionally, we also show that the three-dimensional DMD reconstruction of the tumor field can be leveraged to accurately reconstruct the displacement fields of the tumor-induced deformation of the host tissue. Thus, we posit the proposed data-driven approach has the potential to greatly reduce the computational overhead of personalized simulations of cancer models, thereby facilitating tumor forecasting, parameter identification, uncertainty quantification, and treatment optimization.
Landslide Risk Assessment in Cut Locations Using Right of Way Videos and Artificial Intelligence
Authors: Palese Michael , Zarembski Allan M. , Palese Joseph 
Published: June 2022

Abstract
Sidehill and through cuts are often used in the construction of new rail systems to reduce the length, curvature, and grade of the route to increase operation efficiency. Consequently, rights-of-way that utilize cuts are susceptible to damage from slope failure events such as shallow-rapid landslides and rock-falls. At-risk slopes, or geohazards, are traditionally assigned severity grades using slope stability analysis methods derived from intensive field investigations and historical failures. Anticipating slope failures that may occur due to common weather events in the region helps protect railroad assets and ensure safe operations. This research aimed to create a new slope stability analysis method by processing digital images of the railroad right-of-way recorded by inspection vehicles. Computer vision techniques were used to identify and quantify geohazard features that indicated slope instability. Specifically, an object detection algorithm was trained with a set of right-of-way images where features of concern were labeled and located. These features, along with digital elevation maps of the track section, can then be used to develop a relative risk assessment algorithm to grade each geohazard’s landslide likelihood. The resulting algorithm would provide a geohazard risk index that can be determined from publicly available data and video recordings from inspection vehicles and can be used by railroads to mitigate the potential damage from a landslide event.
Performance of a Thermoelectric-Based Energy Harvesting Device on a Realistic Railroad Route
Authors: Amaro Martin , Tarawneh Constantine , Foltz Heinrich , Aguilera Toro Ruben , Peña Curtis 
Published: June 2022

Abstract
Researchers at the University Transportation Center for Railway Safety (UTCRS) have developed an onboard wireless monitoring device to gauge the health of freight railcar rolling stock. A wireless system will allow for preemptive maintenance to occur, potentially saving millions of dollars in damages and ensuring the safety of passengers and cargo. A prototype energy harvester has been developed that can extend the battery life of the wireless monitoring device. It uses Thermoelectric Generators (TEGs) mounted on the bearing adapter to convert heat generated from the bearings to electricity. Previous results have shown that, under optimal conditions, TEGs have been able to produce enough energy to meet the power demands of low-power circuit boards. This paper summarizes the proof-of-concept validation of the complete energy harvesting device which includes the performance of the TEGs, heat sinks, boost converter, and the Battery Management Chip (BMC) working in tandem. The testing results were acquired by replicating field service conditions using a test plan that reproduces speeds encountered on a realistic railroad route and run on a laboratory dynamic bearing test rig. The test plan simulates a train completing a round trip between Billings, MT and Council Bluffs, IA. Preliminary testing results show that, over an average trip where train speeds vary, the energy harvesting system can significantly extend the battery life by producing enough energy to maintain or increase the charge of the battery while also powering the sensors and wireless transceiver for the duration of the trip.
Wheel-Rail Contact Force and Traction Analysis Under Wet and Oil-Contaminated Conditions
Authors: Radmehr Ahmad , Pan Yu , Tajaddini Ali , Vollebregt Edwin , Ahmadian Mehdi 
Published: June 2022

Abstract
The changes in wheel-rail traction coefficients under wet and oil-contaminated rail surfaces are evaluated using the state-of-the-art Virginia Tech-Federal Railroad Administration (VT-FRA) roller rig. This one-fourth scaled test rig provides a controlled environment to measure real-time contact forces under pre-defined conditions. In addition, the rig is equipped with a high-precision fluid dispenser to apply the exact amount of fluids onto the rolling surfaces. Two series of experiments are conducted with water and oil applied individually at the wheel-rail contact with 0.02cc, 0.10cc, and 0.50cc, using a precise dispensing system at a low flow rate of 0.3cc/min, a medium flow rate of 1.5cc/min, and a high flow rate of 7.5cc/min, respectively. The tests include three or fewer cycles of water or oil applications for 4.1s under stable traction conditions. All other test conditions, including creepage, duration, and wheel load, are maintained unchanged throughout the tests, to focus on the effect of water on traction values. The results indicate a high correlation between the amount of water or oil applied to the surface and reduction in traction, in some cases for a short duration and in some over a long period of time. For low and medium flow rates of water, traction reduces immediately upon the application of water but recovers quickly after a short duration to nearly the same level as the dry condition. The duration of reduced traction is directly proportional to the volume of water. A distinctly different result is observed for oil. Even a small amount of oil (0.3cc/min) causes a significant reduction in traction that prolongs over an extended period of time. For the medium application of oil (1.5cc/min), traction remains low for a long period of time and only recovers to approximately 1/2 of the dry condition. For high oil application (7.5cc/min), traction remains extremely low (approximately 1/5 of dry condition) for the duration of the test and does not show any indication of recovery. Oil residue can be felt at the running surface when rubbing a finger over the roller surface. The results indicate that both water and oil cause a significant reduction in traction, with traction recovering to its dry level shortly after the source of water (i.e., rain) stops. When oil is applied to the rail, even a small amount can significantly diminish traction for a prolonged period of time. This is attributed to the possible seasoning of the rail due to oil.
Deep Autoencoder for Ultrasound-Based Rail Flaw Detection
Authors: Wu Yuning , Zhu Xuan , Baillargeon Jay 
Published: June 2022

Abstract
Safety is the principal concern of the railway industry, and rail internal defects can pose significant risks to safe and efficient railroad operations. Effective rail flaw detection, especially for transverse defects, is critical to prevent accidents and derailments due to broken rails. Both industrial and research communities have invested much effort in solving this problem. For example, the rail industry relies heavily on ultrasonic bulk waves and, more recently, began exploring ultrasonic guided waves for rail internal defect detection. This study developed an improved semi-supervised learning algorithm based on a deep autoencoder (DAE) for ultrasound-based rail flaw detection. The DAE algorithm identifies observations in a dataset that deviate significantly from the remaining observations. First, the team trained a DAE to reconstruct ultrasonic signals obtained from clean rail segments. To improve the robustness for defect detection, we then optimized the architecture and hyperparameters of the DAE models. Also, we adopted mean squared error (MSE) as a feature to highlight rail defects. Lastly, the team fed the test set of ultrasonic signals into the trained DAE model and evaluated its capability for rail defect detection. We found the proposed DAE can support a superior and robust ultrasonic rail defect detection capability compared to conventional knowledge-driven approaches.
Examination of Fast Track Geometry and Vehicle/Track Interaction Exceptions
Authors: Meddah Abe , Galván-Núñez Silvia 
Published: June 2022

Abstract
Track conditions can change rapidly when operating in a revenue service heavy axle load environment. Because the assessment of track health for safe railroad operations is a fundamental priority for the railroad industry in North America, various track monitoring technologies, such as Track Geometry Measurement Vehicles (TGMVs) and unattended Vehicle/Track Interaction (V/TI) systems, are regularly deployed to determine whether track maintenance attention is warranted. To investigate the track condition monitoring differences between TGMV and V/TI technologies in a controlled environment where rapid tonnage is accumulated, Transportation Technology Center, Inc. (TTCI) engineers conducted a study on the High Tonnage Loop (HTL) at the Facility for Accelerated Service Testing (FAST) in Pueblo, CO. This study used TTCI’s rail-bound TGMV and a TTCI-developed Instrumented Freight Car (IFC), an autonomous car-based V/TI monitoring technology designed to run with the FAST train for continuous track condition assessment in a heavy axle load environment. In this investigation, funded by the Association of American Railroads (AAR) Strategic Research Initiatives (SRI) program, a total of six TGMV and IFC tests were conducted at different intervals with over 87.4 million gross tons (MGT) accumulated since the first track geometry baseline test was conducted. Compliance with track geometry standards was determined based on the Federal Railroad Administration (FRA) regulatory geometry defects for track Classes 1 through 5. Exception track locations were identified for the IFC when empirically derived, pre-set performance limits were exceeded. This paper both examines and contrasts the findings of the testing results of both the IFC and TGMV technologies as studied at FAST.
Friction-Slip Curves – The Pathway From Twin-Disc Tribo Measurements to Full-Scale Locomotive Multibody Simulations
Authors: Bernal Esteban , Spiryagin Maksym , Stichel Sebastian , Bosso Nicola , Lewis Roger , Bosomworth Christopher , Wu Qing , Cole Colin 
Published: June 2022

Abstract
Locomotive multibody simulations are commonly used as a cost-effective tool to study, energy efficiency, wheel-rail wear, rolling contact fatigue, etc. The accuracy of the wheel-rail contact forces from multibody simulations depends on the correct modelling of the friction conditions. The friction coefficient is a function of the slip velocity, and it is influenced by several tribological parameters including, for example, material mechanical properties, environmental conditions and the presence of third body layers that vary spatially and temporally along the track. In most cases, generic friction-slip curves obtained from publications and public reports are used as inputs to the wheel-rail contact model in the locomotive simulations, as direct friction measurements using full-scale experimental set-ups are generally cost-prohibitive. A pathway to produce friction-slip curves from tribo-machine friction measurements is proposed in this paper. The pathway involves manufacturing discs from actual wheel and rail material samples to measure the traction coefficient at a spectrum of slip set points using a twin-disc tribo-machine. The tribo-machine results are scaled to be used in a locomotive multibody model that uses the modified Fastsim and a traction system co-simulation approach. Two friction curves for wet and dry conditions are processed and exemplified in a dynamic model.
Implementation of the Contact Roughness at the Wheel-Rail Contact Model for Locomotive Traction Studies
Authors: Spiryagin Maksym , Ahmad Sanjar , Bernal Esteban , Oldknow Kevin , Persson Ingemar , Wu Qing , Cole Colin , Mcsweeney Tim 
Published: June 2022

Abstract
This paper introduces a solution to deliver the relation between the contour and real contact areas considering characteristics of surface geometry based on the adaptation of a tribological method [1] for calculation of the real area of contact and the real pressure between two rough surfaces.
The implementation in the wheel-rail coupling architecture is kept the same as per the previously developed wheel-rail multibody couplings [2,3] based on the modified Fastsim [4] and Extended Contact [5] algorithms, which allows switching between the previous and new developed coupling for a comparative analysis. The results obtained, and limitations, are stated in this paper.
Associations Between Kindergarten Participation in Organized Physical Activity and Subsequent Healthy Body Weight and Leg Strength by the End of Second Grade
Authors: Kosak Laurie-Anne , Harandian Kianoush , Harbec Marie-Josée , Pagani Linda S. 
Published: June 2022

Background: Childhood sport helps children develop growth and maturation, while simultaneously offering self-regulation, motor, and social skills training. This study aims to estimate the influence of sport participation at age 6 years on indicators of health at age 8 years, using a prospective longitudinal birth cohort design. Methods: Participants were 1492 children aged 6–8 years from the Quebec Longitudinal Study of Child Development. Lower muscular power was measured with the standing long jump test. Girth used the children’s waist circumference in centimeters. Body mass index was computed from child height and weight. We regressed these directly measured health indicators at age 8 years on parent-reported physical activity at age 6 years using linear Ordinary Least Squares regression. Results: Boys who participated in more physical activity at age 6 years had better lower muscular power (b = 2.368; 95% CI, 0.341 to 4.395) and higher body mass index (b = 0.340; 95% CI, 0.055 to 0.626). No significant results were found for girls. Conclusions: Our findings suggest that physical activity in kindergarten has a positive impact on muscular power by the end of the second grade in boys. This supports the pertinence of implementing physical activity to a routine early in life to help children improve their general health.
Preferences of Australian healthcare providers regarding education on long-term health after hypertensive disorders of pregnancy: a qualitative study
Authors: Roth Heike , Morcos Veronica , Roberts Lynne M , Hanley Lisa , Homer Caroline S E , Henry Amanda 
Published: June 2022

Objectives)To explore Australian healthcare providers’ (HCPs’) preferred content, format and access to education regarding long-term health after hypertensive disorder of pregnancy (HDP), in order to guide the development of education programmes.Design and settingA qualitative study using a framework analysis was undertaken. Registered HCP who were practising in Australia and previously completed a survey about long-term health after HDP were invited to participate.ParticipantsTwenty HCP were interviewed, including midwives, specialist obstetrician/gynaecologists, general practitioners with a diploma in obstetrics and gynaecology, and cardiologists.Primary and secondary outcome measuresExploration of preferred content, format and distribution of educational material post-HDP.ResultsTwenty HCP were interviewed in April to May 2020. Four main categories were identified. ‘Obtaining evidence-based information for own learning’ addressing own learning with preference for multi-disciplinary education, preferably endorsed or facilitated by professional organisations. ‘Optimising the referral process from hospital to community health services’ was about the need for structured long-term follow-up to transition from hospital to community health and align with HDP guidelines. ‘Facilitating women’s health literacy’ addressed the need for evidence-based, print or web-based material to assist risk discussions with women. ‘Seizing educational opportunities’ addressed the responsibility of all HCP to identify education opportunities to initiate key health discussions with women.Conclusion(sHCP provided ideas on content, format and access of education regarding long-term health post-HDP within the parameters of the Australian healthcare context. This evidence will guide educational developments for HCP on post-HDP health to ensure they can better care for women and families.