Full-Scale Field Experimental Investigation on the Intended Irregularity of CWR Track in Vertical Plane

The purpose of the following paper is to present the author’s experimental field investigations of a jointless railway track subjected to a generated imperfection and analysis of track response to applied static loads. An optical measurement system, Pontos, was used for the static and dynamic analysis of the track’s deflections in 3D. The investigations allow us to recommend a direct application of this system for the non-contact measurement, visualization and analysis of simulated defects in the jointless track, as presented by the author. It is stated that simulation of an effect called the hanging sleeper, a short irregularity in the railway track with the initial parameters provided (a gap and a length of irregularity), is possible. The proposed method, based on the measurement in the loaded track (a static load from the locomotive wheels), allows for a description of the effect of the changing track support condition. Moreover, it also proves its usefulness for the analysis of the changes in deflection and stress values and the force transferred from the rail on the railway sleeper and for the assumed shape of defects simulating the short irregularities arising in the operated railway track. The arising irregularity in the track affects driving comfort and the safety of travellers.

Data-Driven Railway Crosstie Support Condition Prediction Using Deep Residual Neural Network: Algorithm and Application

Ballasted track substructure is designed and constructed to provide uniform crosstie support and serve the functions of drainage and load distribution over trackbed. Poor and nonuniform support conditions can cause excessive crosstie vibration which will negatively affect the crosstie flexural bending behavior. Furthermore, ballast–tie gaps and large contact forces at the crosstie–ballast interface will result in accelerated ballast layer degradation and settlement accumulation. Inspection of crosstie support condition is therefore necessary while very challenging to implement using current methods and technologies. Based on deep learning artificial intelligence techniques and a developed residual neural network (ResNet), this paper introduces an innovative data-driven prediction approach for crosstie support conditions as demonstrated from a full-scale ballasted track laboratory experiment. The discrete element method (DEM) is leveraged to provide training and testing data sets for the proposed prediction model. K-means clustering is applied to establish ballast layer subsections with representative ballast particles and provide additional insights on layer zoning for dynamic behavior trends. When provided with DEM simulated particle vertical accelerations, the proposed deep learning ResNet could achieve 100% training and 95.8% testing accuracy. Fed with vertical acceleration measurements captured by advanced “SmartRock” sensors from a full-scale ballasted track laboratory experiment, the trained model could successfully reach a high accuracy of 92.0%. Based on the developed deep learning approach and the research findings presented in this paper, the innovative crosstie support condition prediction system is envisioned to provide railroaders accurate, timely, and repeatable inspection and monitoring opportunities without disrupting railway network operations.

Variability of support conditions and effects on the non-linear flexural response of concrete sleepers

Current structural models used for the flexural design of prestressed concrete sleepers assume that ballast bearing support is static and located within a fixed region. This assumption implies a linear relationship between wheel load and bending moment. However, field data gathered from instrumented sleepers shows that this trend is non-linear, and the difference in flexural behavior between model predictions and field-measured demand is significant. Using back-calculation techniques and the development of a sleeper support analysis tool, this paper investigates the load-dependency of sleeper support condition. It is hypothesized that a given support condition redistributes ballast reaction forces due to the mechanical interaction of ballast particles with the sleeper’s deflected shape. It was found that redistribution of support conditions can reduce the expected flexural bending moment up to 45% when compared with moments calculated using traditional design guidelines. This effect (non-linearity) is greater as wheel loads increase. Results from revenue service field experimentation provided insight into the interaction between sleeper and ballast and serve as a foundation for the development of more complex analytical models. This will facilitate revisions to the future flexural design procedures for concrete sleepers, to ensure they are optimized for their expected service loading conditions.

Breast biomechanics, exercise induced breast pain (mastalgia), breast support condition and its impact on riding position in female equestrians

Breast biomechanics, exercise-induced breast pain (EIBP) and performance effects in female athletes are established. Wearing sports bras during exercise reduces breast movement and EIBP. Despite the prevalence of female equestrians, little investigation of breast movement during horse riding exists, yet excessive breast movement, embarrassment and EIBP are reported. Breast movement relative to the torso is linked to EIBP, associated with magnitude and direction of forces generated. Equestrians may experience novel breast and upper-body movement patterns in response to large vertical excursions of the horse. This study aimed to establish relative vertical breast displacement (RVBD), EIBP and positional changes in three support conditions: ‘no support’, ‘low support’ and ‘high support’. Thirty-eight female equestrians rode a Racewood™ Equine Simulator in each breast support condition in medium walk, medium trot (sitting) and medium canter. Trials were filmed and analysed using Quintic® Biomechanics V29. Significant reductions in RVBD (P<0.001) and EIBP (P<0.001) were identified with increased breast support in all gaits. In medium trot (sitting) a significant reduction in range of movement (ROM) of shoulder-elbow-wrist (P<0.001) was seen from low to high support. ROM of torso-vertical angles were reduced from no support to low support (P<0.001) and further by high support (P<0.001). This reduction in ROM was significantly greater in large breasted riders (cup size DD-FF) (n=21) (P<0.001) compared to small breasted (cup size AA-D) (n=17). These results suggest that appropriate breast support positively impacts EIBP and riding position in female riders possibly enhancing performance. As RVBD and reported EIBP were not wholly comparative with results in female runners, further research is warranted to establish breast movement in equestrianism in three dimensions.

Masonry Dome Behavior under Gravity Loads Based on the Support Condition by Considering Variable Curves and Thicknesses

It is necessary to recognize masonry domes’ behavior under gravity loads in order to strengthen, restore, and conserve them. The neutral hoop plays a crucial role in identifying the masonry dome’s behavior to distinguish between its tensile and compressive regions. When it comes to determining the neutral hoop position in a dome with the same brick material, in addition to determining the dome’s curve and thickness, the support condition located on the boundary line is a significant parameter that has received less attention in the past. Therefore, this research aims to comprehensively define masonry dome behaviors based on the support condition’s effect on the masonry dome’s behavior, in addition to thickness and curve parameters, by determining neutral hoop(s). The method is a graphical and numerical analysis to define the sign-changing positioning in the first principal stress (hoop stress), based on the shell theory and extracted from a finite element method (FEM) Karamba3D analysis of a macro-model. The case studies are in four types of supports: condition fixed, free in the X- and Y-axes, free in all axes (domes placed on a drum), and free in all axes (domes placed on a pendentive and a drum). For each support condition, twelve curves and four varied thicknesses for each curve are considered. Results based on the dome’s variables show that, in general, four types of masonry domes behavior can be identified: single-masonry dome behavior with no neutral hoop; double-masonry dome behavior where all hoops are compressive with a single neutral hoop; double-masonry dome behavior where hoops are compressive and tensile with a single neutral hoop; and treble-masonry dome behavior with double neutral hoops.