Abstract Sample processing is important on extra-terrestrial surfaces for both scientific experiments and in situ resource utilization studies. Payload for this task onboard exploring spacecraft must be optimized for mass, size, reliability, and power use. The Soil Preparation System, which used micro-impact for in situ sample processing, was designed by the Hong Kong Polytechnic University for the Russian Phobos-Grunt mission to Phobos’ surface. Optimization of this payload, and similar micro-impact comminution machines, requires data on the impact fragmentation of the sampled material for accurate simulation. To provide this data, granules of Earth rocks with compositions similar to those on Phobos were impacted using a drop-weight test that simulates the machine’s micro-impacts. This study takes the fragment size data and investigates the application of continuous distribution functions to each fragmentation to build global relationship patterns. It was demonstrated that the Log-logistic, Log-normal, Grady, Gilvarry, Swebrec, and Weibull distributions are applicable distributions, with the Weibull distribution being the best fitting. The fragmentation data were used to approximate the relationship between the specific impact energy and the Weibull distribution coefficients to further the application of particle replacement fragmentation modeling for micro-impact machines. Graphical abstract
Foster et al. (Thu,) studied this question.