Studying the Richtmyer-Meshkov instability in convergent geometry under high energy density conditions using the Decel platform

The Decel platform at Sandia National Laboratories investigates the Richtmyer-Meshkov instability (RMI) in converging geometry under high energy density conditions [Knapp et al., Phys. Plasmas 27, 092707 (2020)]. In Decel, the Z machine magnetically implodes a cylindrical beryllium liner filled with liquid deuterium, launching a converging shock toward an on-axis beryllium rod machined with sinusoidal perturbations. The passage of the shock deposits vorticity along the Be/D2 interface, causing the perturbations to grow. In this paper, we present platform improvements along with recent experimental results. To improve the stability of the imploding liner to the magneto Rayleigh-Taylor instability, we modified its acceleration history by shortening the Z electrical current pulse. Next, we introduce a split rod configuration that allows two axial modes to be fielded simultaneously in different axial locations along the rod, doubling our data per experiment. We then demonstrate that asymmetric slots in the return current structure modify the magnetic drive pressure on the surface of the liner, advancing the evolution on one side of the rod by multiple ns compared to its 180 & DEG; counterpart. This effectively enables two snapshots of the instability at different stages of evolution per radiograph with small deviations of the cross-sectional profile of the rod from the circular. Using this platform, we acquired RMI data at 272 and 157 mu m wavelengths during the single shock stage. Finally, we demonstrate the utility of these data for benchmarking simulations by comparing calculations using ALEGRA MHD and RageRunner. Published under an exclusive license by AIP Publishing.

Automated summary

The Decel platform at Sandia National Laboratories investigates the Richtmyer-Meshkov instability (RMI) in converging geometry under high energy density conditions. The platform has been improved to enhance stability and data acquisition, allowing for the study of RMI in different stages of evolution. Experimental results demonstrate the effectiveness of the platform and its utility for benchmarking simulations.