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Underrun Protection devices (UPDs) are specially designed barriers fitted to the front, side, or rear of heavy trucks. In case of accidents, these devices prevent small vehicles such as bikes and passenger cars going underneath and thus minimizing the severity of such accident. Design and strength of UPD is such that it absorbs the impact energy and offers impact resistance to avoid the vehicle under run. Compliance to UPD safety regulations provides stringent requirements in terms of device design, dimensions, and its behavior under impact loading. Since accuracy of Computer Aided Engineering (CAE) predictions have improved, numerical tools like Finite element method (FEM) are extensively used for design, development, optimization, and performance verification with respect to target regulatory performance requirements. For improved accuracy of performance prediction through FEA, correct FE representation of sub-systems is very important.

The brake system is one of the most critical systems in the automotive vehicle. Its design is a challenging task since stringent performance and packaging requirements are to be fully met - optimizing the brake performance and weight of the brake system. The brake disc is an important component in the braking system which is expected to withstand and dissipate the heat generated during the braking event. Validation of brake disc design through CAE/FEA is presented in this paper. The procedure for prediction of thermal performance was developed in-house, tuned and verified by correlating with Test data available for existing-design and then applied to the new-design brake disc. The correlation achieved for the existing-design brake disc (both solid and ventilated), procedure for prediction of thermo-mechanical performance (heat transfer coefficient estimation, temperature distribution etc.) are also included.

In the automotive industry many components face fatigue failure due to prolonged vibrations. This is commonly known as Vibration Induced Fatigue (VIF). There are two approaches to evaluate this; time & frequency domain. A straight forward and widely used method is the rainflow counting technique in the time domain. This counting algorithm is readily available and, apart from the time history, it needs only one variable input (the number of stress ranges). In case of high cycle fatigue, longer time histories are required for a statistically representative fatigue estimate, which makes the time domain approach consume large amounts of time and resources. This shifts our interest towards frequency domain methods. In the frequency domain, Dirlik's method is proven to be robust and gives closer results to the time domain.