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Hat-sections, single and double, made of steel are frequently encountered in automotive body structural components. These components play a significant role in terms of impact energy absorption during vehicle crashes thereby protecting occupants of vehicles from severe injury. However, with the need for higher fuel economy and for compliance to stringent emission norms, auto manufacturers are looking for means to continually reduce vehicle body weight either by employing lighter materials like aluminum and fiber-reinforced plastics, or by using higher strength steel with reduced gages, or by combinations of these approaches. Unlike steel hat-sections which have been extensively reported in published literature, the axial crushing behavior of hat-sections made of fiber-reinforced composites may not have been adequately probed.

Load cells and accelerometers are commonly used sensors for capturing impact responses. The basic objective of the present study is to assess the accuracy of responses recorded by the said transducers when these are mounted on a moving impactor. In the present work, evaluation of the responses obtained from a drop-weight impact testing set-up for an axially loaded specimen has been carried out with the aid of an equivalent lumped parameter model (LPM) of the set-up. In this idealization, a test component such as a steel double hat section subjected to axial impact load is represented with a nonlinear spring. Both the load cell and the accelerometer are represented with linear springs, while the impactor comprising a hammer and a main body with the load cell in between are modelled as rigid masses. An experimentally obtained force-displacement response is assumed to be a true behavior of a specimen.

Hat sections, single and double, made of steel are frequently encountered in automotive body structural components such as front rails, B-Pillar, and rockers of unitized-body cars. These components can play a significant role in terms of impact energy absorption during collisions thereby protecting occupants of vehicles from severe injury. Modern vehicle safety design relies heavily on computer-aided engineering particularly in the form of explicit finite element analysis tools such as LS-DYNA for virtual assessment of crash performance of a vehicle body structure. There is a great need for the analysis-based predictions to yield close correlation with test results which in turn requires well-proven modeling procedures for nonlinear material modeling with strain rate dependence, effective representation of spot welds, sufficiently refined finite element mesh, etc.

Hat sections made of steel are frequently encountered in automotive body structural components such as front rails. These components can absorb significant amount of impact energy during collisions thereby protecting occupants of vehicles from severe injury. In the initial phase of vehicle design, it will be prudent to incorporate the sectional details of such a component based on an engineering target such as peak load, mean load, energy absorption, or total crush, or a combination of these parameters. Such a goal can be accomplished if efficient and reliable data-based models are available for predicting the performance of a section of given geometry as alternatives to time-consuming and detailed engineering analysis typically based on the explicit finite element method.