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The material demands for advanced technologies have led to development of new generation, light-weight, and multi-functional materials. Aluminum matrix composites (AMCs) have captured considerable attention in aviation, space and automotive industries in recent years. Carbon nanotubes (CNT) are one of the most promising candidate of reinforcements used to improve mechanical strength and hardness of metal matrix composites (MMCs). In this study, dry sliding wear behavior of aluminum (Al) matrix (MMCs) reinforced with different amounts (0, 0.5, 1 and 2 wt%) of CNTs were prepared through ball milling, the process was followed by compaction at room temperature and pressureless sintering at 630 °C under argon atmosphere for 1hr. Wear tests were performed on a pin-on-disk tribometer against SAE 1040 steel counter body under constant load and sliding speed at room temperature.

Sloped medians provide a run-off area for errant vehicles so that they can be safely stopped off-road with or without barriers placed in the sloped median. However, in order to optimize the design of sloped medians and the containment barriers, it is essential to accurately model the behavior of vehicles on such sloped terrain surfaces. In this study, models of a vehicle fleet comprising a small sedan and a pickup truck and sloped terrain surface are developed in CarSim™ to simulate errant vehicle behavior on sloped median. Full-scale crash tests were conducted using the vehicle fleet driven across a 9.754 meters wide median with a 6:1 slope at speeds ranging from 30 to 70 km/h. Measured data such as the lateral accelerations of the vehicle as well as chassis rotations (roll and pitch) were synchronized with the vehicle motion obtained from the video data.

Aluminum metal matrix composites reinforced with particulates have attracted much attention in the automotive industry, due to their improved wear resistance in comparison to aluminum alloys, in recent years. The wear behavior is the critical factor influencing the product life and performance in engineering components. Carbon nanotubes (CNT) are one of the most promising candidates of reinforcements used to improve mechanical strength such as wear in metal matrix composites (MMCs). However, in industrial applications, wear tests are relatively expensive and prolonged. As a result, for several years, research has been increasingly concentrated on development of wear prediction models. In this study, prediction of wear behavior of aluminum (Al) matrix (MMCs) reinforced with different amounts (0, 0.5, 1 and 2 wt%) of CNTs was investigated. A nonlinear autoregressive exogenous (NARX) model structure was chosen for the modeling.

The brake friction materials in an automotive brake system play an important role in the overall braking performance of a vehicle. Metal Matrix Composites (MMCs) have been widely investigated and applied due to their advantages of improved strength, stiffness and increased wear resistance over the monolithic alloys in automobile industries. In this paper, Al/B4CP and Mg/B4CP composites were compared to find a suitable candidate material for automotive disk brake application, in terms of wear behavior results of the materials. In addition, the experimental data was also used to model this behavior by identification. The measured tangential force was considered as the input parameter, whereas the weight loss as the output parameter. Preliminary results of this work showed that B4CP addition improved wear resistance of both aluminum and magnesium matrix composites. Additionally, the study pointed out that identified models provide a reliable and cost effective tool for wear prediction.