Comparison of Simulation Results to Gas-Puff Z-Pinch Diagnostics

Gas-puff Z-pinch (GPZP) targets have demonstrated HED conditions and thermonuclear neutron production with modest sized pulsed-power drivers such as the linear transformer driver CESZAR at University of California San Diego. GPZP are formed by the injection of different gas species as shells between the anode and cathode of a fast pulsed power machine. The current pulse ionizes the gas and radial Lorentz forces produce the subsequent axial pinch. GPZPs typically utilize an array of diagnostics that are subject to uncertainty from various noise sources. Kalman filtering is a recursive Bayes filter known for its abilities to filter out noise from sensor measurements. Here, 2D cylindrical GPZP simulations of recent experiments conducted on the CESZAR machine are performed using the open-source FLASH code. A comparison between the results of the simulation and previously published experiments shows good qualitative agreement, demonstrating that FLASH captures the physics of GPZP. Further, synthetic Gaussian noise is added to simulation results and a Kalman filter is shown to recover the initial results. Kalman filters developed from simulations in this way could prove to be a powerful tool for aiding in the analysis of data from GPZP plasma diagnostics.