Simulation Analysis of Geometry and Material Effects for Dropkinson Bar

Abstract

The reported research is motivated by the need to address a key issue affecting the Dropkinson bar apparatus. This unresolved issue is the interference of the stress wave reflected from the bar-beam boundary with the measurement of the stress-strain response of a material tested in the apparatus. The purpose of the wave beam that is currently connected to the bar is to dissipate the stress wave, but the portion of the wave reflected from the bar-beam boundary is still significant. First, we focused on understanding which parameters affect the reflected wave's arrival time at a strain gauge. Specifically, we used finite-element numerical simulations with the Sierra/SM module to study the effects of various bar-beam connection fixities, alternative wave beam materials, and alternative geometries of the Dropkinson bar system based on a monolithic design. The conclusion of this study is that a partial reflection always occurs at the bar-beam boundary (or, for a monolithic design, at a point where the bar geometry changes). Therefore, given a fixed total length of the bar, it is impossible to increase the reflected wave's arrival time by any significant amount. After reaching this conclusion, we focused instead on trying to minimize the energy of the reflected stress wave circulating up and down through the bar over a relatively long period of time (10 ms). Once again, we used numerical simulations with the Sierra/SM module to investigate the effects of various bar-beam connection fixities, alternative wave beam materials, and parameters of an asymmetric monolithic design of the bar-and-beam system. This study demonstrated that various parameters can significantly affect the energy of the wave reflections, with the difference between best and worst configurations being about one order of magnitude in terms of energy. Based on the obtained results, we conclude with concrete takeaways for Dropkinson bar users and propose potential directions for future research and optimization.