Automated split Hopkinson pressure bar for high throughput dynamic experiments

Abstract

Designing novel materials for impact applications and predicting material behavior using data-driven techniques require extensive datasets, which can be challenging to obtain through conventional experimental methods. While high throughput characterization is feasible at the sample micro and nanoscale, there remains a critical need for an experimental tool capable of facilitating high-throughput measurements at the macroscale. This paper presents the design and development of a fully automated split Hopkinson pressure bar (SHPB) with full-field diagnostics for performing dynamic compression experiments on different materials. The automated SHPB experiments consist of four main components: 1) striker launch and retrieval system, 2) bar repositioning mechanism, 3) automated sample placement system, and 4) diagnostics. Each of these systems employs various electromechanical devices and actuators programmed to work collaboratively to automate the SHPB experimental setup. A data analysis tool has been developed to automate the post-processing of the data obtained from the setup. The setup also incorporates automated high-speed imaging, enabling full-field strain measurement capabilities. To benchmark the setup, fully automated dynamic compression experiments were conducted on 45 Copper 101 samples and 20 3D-printed resin samples. The stress-strain curve was extracted from the raw data using the automated data analysis tool. The efficiency of the data analysis tool is validated by comparing the data with existing data analysis tools for SHPB. The stress-strain response obtained from the copper experiments aligned well with existing data on copper. Furthermore, the full-field strain measurements in experiments show strain values comparable to those of the strain gauge measurements. This advancement has enabled dynamic compression experiments on materials at a rate of 60 samples per hour.