Search Results

One of the primary reasons that FMVSS 111 currently requires flat rearview mirrors as original equipment on the driver's side of passenger cars is a concern that convex mirrors might reduce safety by causing drivers to overestimate the distances to following vehicles. Several previous studies of the effects of convex rearview mirrors have indicated that they do cause overestimations of distance, but of much lower magnitude than would be expected based on the mirrors' levels of image minification and the resulting visual angles experienced by drivers. Previous studies have investigated mirrors with radiuses of curvature up to 2000 mm. The present empirical study was designed to investigate the effects of mirrors with larger radiuses (up to 8900 mm). Such results are of interest because of the possible use of large radiuses in some aspheric mirror designs, and because of the information they provide about the basic mechanisms by which convex mirrors affect distance perception.

Some of the best teaching methods are laboratory courses in which students experience application of the principles being presented. Preparing young engineering students for a career in the automotive industry challenges us to provide comparable opportunities to explore the dynamic performance of motor vehicles in a controlled environment. Today we are fortunate to have accurate and easy-to-use software programs making it practical for students to simulate the performance of motor vehicles on “virtual” proving grounds. At the University of Michigan the CarSim® vehicle dynamics simulation program has been introduced as such a tool to augment the learning experience. The software is used in the Automotive Engineering course to supplement homework exercises analyzing acceleration, braking, aerodynamics, and cornering performance. This paper provides an overview of the use of simulation in this setting.

When structures may have dynamic instability complex eigenvalue analysis is a useful tool to predict it. Although the accurate prediction itself is significant, it is also crucial to obtain sensitivity of unstable eigensolutions in order to eliminate instability efficiently. Since the mathematical relationship between stiffness matrix and design variables may seldom be found in reality, finite difference method has been typically used to approximate the sensitivity. The novel way to accurately calculate the sensitivity is developed without implementing finite difference method. This paper shows the advantages of analytical sensitivity analysis compared to other methods for choosing the most important components' eigenvalues. It also provides necessary amount of frequency shift for each chosen components' eigenvalue to eliminate unstable eigenvalues.