Data-driven materials design is a burgeoning field with the potential to rapidly accelerate new materials development, provided that large volumes of data can be efficiently generated and analyzed. The Department of Defense (DoD) is interested in data-driven design of next-generation protection materials. However, ballistic evaluation of protection materials presents a significant bottleneck: due to safety concerns and stringent testing requirements, full-scale ballistic tests are expensive and generate data at a very low rate, on the order of 10 samples/day. Sub-scale ballistic testing offers a potential alternative without such limitations, by using dramatically smaller projectiles and smaller samples to improve safety, reduce expense, and significantly increase throughput. However, to meet the demands of data-driven materials design, sub-scale testing techniques will require advancements in several areas: rate of data collection and processing, automation of analysis, development of up-scaling relationships, and development of test standards. Revolutionary development in this area presents tremendous opportunity to develop new materials an order of magnitude faster while requiring an order of magnitude less material. The goal of this effort is to develop a sub-scale ballistic testing platform as a critical tool for data-driven, high-throughput design and characterization of next-generation protection materials. This goal will be met during Phase I through the following technical objectives: (1) Develop modified Laser-Induced Particle Impact Test (LIPIT) method that employs a multi-cell design fixture; (2) Conduct subscale tests with miniature gas gun test device and draft scaling relationships; (3) Evaluate performance limits of new test methods via computational modeling and proof-of-concept testing; (4) Develop fixture automation and automated data processing plan for Phase II.
