Experimental stress analysis of a steel light truck wheel

The development of a new automotive wheel requires extensive testing and possible design changes. The wheel investigated had three major changes during development. These three designs were subjected to a stress analysis, by experimental methods, to allow a comparison to be made between each design. The experimental program tested the wheels under conditions designed to simulate the loading of the front wheels whilst cornering. A loading frame was built for this purpose and all testing was performed statically by multiple loading for different directions of bending moment. Brittle lacquer coatings were used on each wheel to highlight high strain areas and indicate optimum locations for the placement of strain gauges. The strain gauges were then used to evaluate the strains. Wheel stud loads were also monitored via strain gauges applied to two of the wheel studs. All data was stored on magnetic tapes and the stress analysis performed by means of a minicomputer. The results of the stress analysis showed quantitatively the improvement in design from the first to the third wheel design. The analysis of the stud loads and their variation during loading indicated the optimum wheel mounting face geometry to ensure nut loosening would not occur in service.

The association between attributions of responsibility for motor vehicle accidents and patient satisfaction: a study within a no-fault injury compensation system

This study set out to test the relationship between attributions of responsibility for motor vehicle accidents and satisfaction with personal injury compensation systems.

Attributions of responsibility for motor vehicle accidents and post-injury outcomes.

 This thesis explored the relationship between attributions of responsibility for motor vehicle accidents and post-injury outcomes among a large sample of TAC clients. Results demonstrated that, despite similar levels of physical injury, people who attribute responsibility for accidents to other persons or circumstances experience poorer physical and mental health recovery in comparison to those who attribute responsibility to themselves.

Big data analytics and visualization with spatio-temporal correlations for traffic accidents

Big data analytics for traffic accidents is a hot topic and has significant values for a smart and safe traffic in the city. Based on the massive traffic accident data from October 2014 to March 2015 in Xiamen, China, we propose a novel accident occurrences analytics method in both spatial and temporal dimensions to predict when and where an accident with a specific crash type will occur consequentially by whom. Firstly, we analyze and visualize accident occurrences in both temporal and spatial view. Second, we illustrate spatio-temporal visualization results through two case studies in multiple road segments, and the impact of weather on crash types. These findings of accident occurrences analysis and visualization would not only help traffic police department implement instant personnel assignments among simultaneous accidents, but also inform individual drivers about accident-prone sections and the time span which requires their most attention.