Improved analysis of converging shock radiographs

TL;DR

This paper introduces an improved, faster analysis method for converging shock radiographs that enhances accuracy and reduces uncertainties by using a more efficient parameterization of shock states and opacities.

Contribution

A new analysis technique for shock radiograph data that is numerically better-conditioned, faster, and provides more accurate representation of shock states.

Findings

The new method reduces uncertainties in shock state measurements.

Polynomial functions effectively model shock-related properties.

The approach outperforms previous parameterization methods.

Abstract

We previously reported an experimental platform to induce a spherically-convergent shock in a sample using laser-driven ablation, probed with time-resolved x-ray radiography, and an analysis method to deduce states along the principal shock Hugoniot simultaneously with the x-ray opacity. We have now developed a modified method of analysis that is numerically better-conditioned and faster, and usually provides a better representation of the radiograph with correspondingly lower uncertainties. The previous approach was based on optimizing parameters in a model of the density distribution as a function of radius and time, warped to follow loci such as the shock and the outside of the sample. The converging shock configuration can be described more efficiently in terms of the shocked density and sound speed, expressed as functions of the shock speed Studies of the Hugoniot from various theoretical equations of state (EOS) indicate that, in the typical range of states explored by these experiments, these functions can be described by low-order polynomials. Similarly, few-parameter functions were found suitable for representing the variation of x-ray opacity with shock pressure. This approach was found to perform better in most cases than an alternative method based on parameterization of the EOS.