Hydrodynamic Instabilities in Inertial Confinement Fusion: Physics, Numerical Methods, and Implementation

Sam Miller, PhD Defense, Advised by Professor Valeri Goncharov

Monday, April 11, 2022
1 p.m.

LLE Coliseum or Zoom


Performance degradation in laser-driven inertial confinement fusion (ICF) implosions is caused by several effects, one of which is Rayleigh–Taylor instability growth. This thesis examines the evolution of internal perturbations that create seeds for instability growth during shock-transit (or early-time), as well as the influence of the finite Atwood number of the fuel-shell interface on perturbation evolution during shell deceleration in room temperature targets. Defects in ICF targets such as internal voids and surface roughness create instability seeds during the initial phase of implosions. A comprehensive understanding of seeding mechanisms is essential to characterize the impact of target defects on inflight shell integrity and mass injection into the central, lower-density vapor region. Analysis of early-time behavior of both single-mode shell mass modulations and isolated voids is informed by examining the evolution of the acoustic waves launched by these target imperfections. A systematic study of localized perturbation growth as a function of defect placement and size is presented. The use of low-density ablator materials (such as foams) is suggested as a potential mitigation strategy to improve target robustness against the impact of defect-initiated growth.


To perform this detailed study of internal defect evolution, two new high-fidelity physics codes were developed to track characteristic wave propagation in the ICF context using low-noise, low-dissipation, high-order spatial accuracy solution methods. Modern high-performance computing (HPC) systems have becoming increasingly complex and adapting existing or new software to fully utilize them is a significant development challenge. Each code in this thesis examines the feasibility of different approaches: a modern design in a well-known HPC-centric language (Fortran), and a new language (Julia), which emphasizes developer productivity and shows the potential to be well-suited for HPC workloads.