Abstract
This work investigates the geometric statistics method to characterize the size distribution of tin fragments produced in the laser shock-loaded dynamic fragmentation process. In the shock experiments, the ejection of the tin sample with etched V-shape groove in the free surface are collected by the soft recovery technique. Subsequently, the produced fragments are automatically detected with the fine post-shot analysis techniques including the X-ray micro-tomography and the improved watershed method. To characterize the size distributions of the fragments, a theoretical random geometric statistics model based on Poisson mixtures is derived for dynamic heterogeneous fragmentation problem, which reveals linear combinational exponential distribution. The experimental data related to fragment size distributions of the laser shock-loaded tin sample are examined with the proposed theoretical model, and its fitting performance is compared with that of other state-of-the-art fragment size distribution models. The comparison results prove that our proposed model can provide far more reasonable fitting result for the laser shock-loaded tin.
Highlights
Owning to its importance in fundamental science and a variety of technological applications, dynamic fragmentation has been widely studied for many years
To verify the proposed random geometric model for the metal dynamic fragmentation under laser shock loading conditions, we have examined the fragments data processed with the aforementioned post-shot analysis techniques at different spatial resolution level
For our proposed random geometric model the number of Poisson mixture term is assigned as k = 2 (referring to Equation (9)), which means the cumulative fragment turns to a bilinear exponential function
Summary
Owning to its importance in fundamental science and a variety of technological applications, dynamic fragmentation has been widely studied for many years. And numerically, Durand et al.[11] performed molecular dynamics (MD) methods to investigate the ejecta size distribution from shock-loaded tin surface with sinusoidal roughness. They found that the MD simulation could predict the hydrodynamic behavior with the Richtmyer-Meshkov instability. While some other research has focused on improving the geometric statistical fragmentation models, i.e. the fragment size distribution models, so as to describe the relevant physical process with more fidelity One of such earliest theoretical work may date
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