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This paper talks about using an approach to simulate snow mass falling from roof of cab on the cowl tray of a commercial truck and predicting the durability life of the cowl tray based on this loading. It has always been a challenge for analysts to model the behavior of snow/slurry in dynamic simulations especially where the area of concern is structure and not the fluid. The conventional approach followed in most industries would be either to model snow as soft rubber or to divert from the conventional Lagrangian algorithm for mesh movement towards Eulerian method (or ALE algorithm). Although modeling snow as soft rubber captures the basic physics of the problem, it is not able to correctly simulate the fluid structure interaction behavior and the pressure wave movement inside the snow/slurry when it comes in contact with the structure.

A new total fatigue life methodology was utilized to make fatigue life predictions, where total fatigue life is defined as crack initiation and subsequent crack propagation to a crack of known size or the component’s inability to carry load. Fatigue life predictions of an A36 steel T-joint geometry were calculated using the same total fatigue life methodology for both welded and machined test specimens that have the same geometry. The only significant difference between the two analyses was the inclusion of the measured weld residual stresses in the welded specimen life predictions. Constant amplitude tests at several load levels and R ratios were analyzed along with block cycle and variable amplitude loading tests. The accuracy of the life predictions relative to experimental test lives was excellent, with most within a factor of +/- two.

Wobble and shimmy vibrations are commonly observed in commercial highway vehicles with solid-beam front axles. These vibrations are typically self-excited and manifest themselves as sustained oscillations about the kingpin and axle tramp. A study was initiated to investigate and quantify wobble and shimmy behaviors, with a primary focus on wobble. A cross functional team including test and simulation engineers evaluated a vehicle exhibiting these behaviors. The team developed an ADAMS model to reproduce the behaviors and developed a DOE to quantify the impact of variables and combinations of variables. The evaluation demonstrated that dynamic imbalance in the rotating masses is a primary source of excitation. Wheel run-out, caster angle, tire brand, tire wear and tire inflation are also significant sources. Future studies will use these findings to mitigate the concern.

The art and science of glass engineering, specifically applied to automotive projects, are not at all commonplace. Although windshields, side and backlites seem to be obvious parts of any car, truck, or bus, designing, sourcing, and manufacturing them are unique challenges. From the business perspective, cost control makes the choice of the ideal supplier a vital decision, greatly impacting availability and production. From the technical standpoint, the most creative designs can be rendered impractical due to regulations, lack of economies of scale, or convoluted logistics. Glass Engineering: Design Solutions for Automotive Applications tackles all these variables using a no-nonsense, step-by-step approach. Written by Lyn R. Zbinden, a mechanical engineer and glass specialist, this book narrows the gap between the reader and a technical subject by using language that is easy to understand, a good variety of examples, and a series of invaluable reference design tables.