Persuasive communication aimed at public transportation-oriented residential choice and the promotion of public transport

In this study, we developed a persuasive communication program to induce public-transport-oriented residential (PTOR) choice. We implemented an experiment that targeted students from the University of Tsukuba, Japan, who were in the process of changing their residential location. These students were randomly assigned to four groups: the first group was a control group; the second group received an information brochure about apartment flats typically used by students in Tsukuba city; the third group received a brochure identical to the one given to the second group, except that it also included information about the level of bus service for every flat; and the fourth group was provided with a leaflet that provided motivation for PTOR choice, in addition to the brochure used for the third group. The residential locations were investigated 5 months after the intervention. There was a significant difference between the control group and the third and fourth groups. The ratio of PTOR choice in the group with the information was twice as high as that for the control group. Furthermore, the persuasive message also increased PTOR choice. Additionally, the target groups’ frequency of bus use from home or the university was significantly high compared with the control group.     

Fatigue life reliability prediction of a stub axle using Monte Carlo simulation

A stub axle is a part of a vehicle constant-velocity system that transfers engine power from the transaxle to the wheels. The stub axle is subjected to fatigue failures due to cyclic loads arising from various driving conditions. The aim of this paper was to introduce a probabilistic framework for fatigue life reliability analysis that addresses uncertainties that appear in the mechanical properties. Service loads in terms of response-time history signal of a Belgian pave were replicated on a multi-axial spindle-coupled road simulator. The stress-life method was used to estimate the fatigue life of the component. A fatigue life probabilistic model of a stub axle was developed using Monte Carlo simulation where the stress range intercept and slope of the fatigue life curve were selected as random variables. Applying the goodness-of-fit analysis, lognormal was found to be the most suitable distribution for the fatigue life estimates. The fatigue life of the stub axle was found to have the highest reliability between 8000–9000 cycles. Because of uncertainties associated with the size effect and machining and manufacturing conditions, the method described in this paper can be effectively applied to determine the probability of failure for mass-produced parts.