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Woven fabric carbon fiber/epoxy composites made through compression molding are one of the promising choices of material for the vehicle light-weighting strategy. Previous studies have shown that the processing conditions can have substantial influence on the performance of this type of the material. Therefore the optimization of the compression molding process is of great importance to the manufacturing practice. An efficient way to achieve the optimized design of this process would be through conducting finite element (FE) simulations of compression molding for woven fabric carbon fiber/epoxy composites. However, performing such simulation remains a challenging task for FE as multiple types of physics are involved during the compression molding process, including the epoxy resin curing and the complex mechanical behavior of woven fabric structure.

Superplastic forming (SPF) is a manufacturing process that can facilitate increased use of aluminum in automobile body structures. Despite considerable advantages with regards to formability and tooling costs, the process has been mostly limited to low volume production due to relatively long cycle times. This paper focuses on the development of a simulation capability to model a novel double-action mechanical pre-forming SPF process which can enhance formability as well as improve production efficiency by combining technology of hot stamping and conventional superplastic forming. A commercial explicit finite element analysis (FEA) code was adopted to establish feasibility of the forming process. The predictive accuracy of the FEA code was established in terms of thickness distribution and material drawn-in by correlating simulation results with experiments conducted with a deep draw die.

This study deals with general consideration points of developing a rear bumper integrated carrier system, especially in view of optimized layout for SUV.

Camera data generated in a 3D virtual environment has been used to train object detection and identification algorithms. 40 common US road traffic signs were used as the objects of interest during the investigation of these methods. Traffic signs were placed randomly alongside the road in front of a camera in a virtual driving environment, after the camera itself was randomly placed along the road at an appropriate height for a camera located on a vehicle’s rear view mirror. In order to best represent the real world, effects such as shadows, occlusions, washout/fade, skew, rotations, reflections, fog, rain, snow and varied illumination were randomly included in the generated data. Images were generated at a rate of approximately one thousand per minute, and the image data was automatically annotated with the true location of each sign within each image, to facilitate supervised learning as well as testing of the trained algorithms.

The fatigue strength and failure behavior of A5754-O adhesively bonded single lap joints by a hot-curing epoxy adhesive were investigated in this paper. The single lap joints tested include balanced substrate joints (meaning same thickness) and unbalanced substrate joints, involving combinations of different substrate thicknesses. Cyclic fatigue test results show that the fatigue strength of bonded joints increase with the increasing substrate thickness. SEM and Energy Dispersive X-ray (EDX) were employed to investigate the failure mode of the joints. Two fatigue failure modes, substrate failure and failure within the adhesive were found in the testing. The failure mode of the joint changes from cohesive failure to substrate failure as the axial load is decreased, which reveals a fatigue resistance competition between the adhesive layer and the aluminum substrate.

Multidisciplinary Design Optimization (MDO) is often required in aircraft design to address the multidisciplinary feasibility issues due to the disciplines, for example, aerodynamics, propulsion, and structures, are heavily coupled. However, in automobile designs, can we apply different type of MDO decomposition originated from aircraft design, to some MDO problem, for example, a vehicle weight reduction example? Also, to effectively and efficiently accommodate design changes, multi-party collaboration between discipline specialists, and fast decision making, a web-based MDO platform with knowledge-based repository for resource sharing, capability of version control, and enhancing data security, is very much needed. Two types of MDO decomposition: All-at-Once (AAO) and Collaborative Optimization (CO) are formulated for the weight reduction example. A typical six-step MDO process, from building single discipline work flow to comparing optimization results, is illustrated step-by-step.