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EN
The aim of this study is to investigate the improvement in the strength of a top-hat profile hollow-section beam used in a vehicle structure by attaching different shapes of internal reinforcements. The base structure of the beam was first considered as a hat-shape structure which was jointed to a flat plate using spot-welds. Three types of sheet metal reinforcements were formed and attached inside the beam’s structure. Then, they were tested experimentally under low-velocity lateral impact. Also, a numerical simulation is being developed using LS-DYNA explicit code and validated using experimental data. Valid numerical configuration is used to conduct an optimization study on cross-sectional shape of the internal reinforcing component. Optimizations are carried out using single- and multi-objective methods based on Genetic Algorithm approach and the suggested optimum solutions are compared with experimental results. Moreover, to discuss the feasibility of applied reinforcements on side section of a vehicle’s body-in-white, a realistic side-pole crash test is simulated using a validated vehicle model and performance of improved chassis is compared with basic model and results are presented, discussed and commented upon.
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Content available remote High-speed log-polar time to crash calculation for mobile vehicles
EN
Time to impact computation is one of the applications of the image optical flow. It is useful in vehicle crash detection or robotic navigation. A high-speed image acquisition and computation rate is necessary in most of these applications. The main problem of time to impact computation from optical flow is the accuracy : accurate results usually need complex and slow computations not affordable for the fast time reaction of a vehicle or robot. Using log-polar images reduces the amount of data to be processed thus increasing speed and accuracy of result. Most optical flow techniques are inadequate to obtain high rate time to impact measurements, since they rely on complex static calculations on few images of the sequence. In our approach the time to impact is calculated using simple but fast algorithms over a high amount of images to obtain accurate results.
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