SAE2.py : a python script to automate parameter studies using SCREAMER with application to magnetic switching on Z.

Abstract

The SCREAMER simulation code is widely used at Sandia National Laboratories for designing and simulating pulsed power accelerator experiments on super power accelerators. A preliminary parameter study of Z with a magnetic switching retrofit illustrates the utility of the automating script for optimizing pulsed power designs. SCREAMER is a circuit based code commonly used in pulsed-power design and requires numerous iterations to find optimal configurations. System optimization using simulations like SCREAMER is by nature inefficient and incomplete when done manually. This is especially the case when the system has many interactive elements whose emergent effects may be unforeseeable and complicated. For increased completeness, efficiency and robustness, investigators should probe a suitably confined parameter space using deterministic, genetic, cultural, ant-colony algorithms or other computational intelligence methods. I have developed SAE2 - a user-friendly, deterministic script that automates the search for optima of pulsed-power designs with SCREAMER. This manual demonstrates how to make input decks for SAE2 and optimize any pulsed-power design that can be modeled using SCREAMER. Application of SAE2 to magnetic switching on model of a potential Z refurbishment illustrates the power of SAE2. With respect to the manual optimization, the automated optimization resulted in 5% greater peak current (10% greater energy) and a 25% increase in safety factor for the most highly stressed element