Development of a predictive capability of short-pulse laser-driven broadband x-ray radiography
- 1 June 2020
- journal article
- research article
- Published by IOP Publishing in Plasma Physics and Controlled Fusion
- Vol. 62 (6), 065001
- https://doi.org/10.1088/1361-6587/ab8413
Abstract
High intensity, short-pulse laser interaction with a solid metal target produces broadband hard x-rays potentially for various applications of x-ray radiography. Here experimental benchmarking of numerical modelling for short-pulse laser-driven broadband x-ray radiography is presented. Angular dependent x-ray spectra are first calculated with a hybrid particle-in-cell code, Large Scale Plasma (LSP), using fast electron parameters inferred from an analysis of measured bremsstrahlung signals. Subsequently, a calculated x-ray spectrum in the direction of radiography is used in photon transport calculations using a Monte Carlo code, Particle and Heavy Ion Transport code System (PHITS), to simulate a radiographic image including a modelled 3D test object, an x-ray attenuation filter and an image plate detector. Simulated radiographic images are compared with measurements obtained in an experiment using a 50-TW Leopard short-pulse laser at the University of Nevada Reno. Results show that simulations reproduce the experimental images well for three different attenuation filters (plastic, aluminium, and brass), while 1D transmission profiles for the plastic and aluminium filters are quantitatively in good agreement. The modelling approach established in this work could be used as a predictive tool to simulate radiographic images of complex 3D solid objects at any arbitrary angular position or to optimize experimental components such as the source spectrum, x-ray attenuation filters and a detector type depending on a radiographic object without carrying out radiographic experiments.Keywords
Funding Information
- US Department of Energy, Office of Fusion Energy Sciences (DE-AC52-07NA27344, DE-FG02-05ER54834)
- NSF/DOE Partnership in Basic Plasma Science and Engineering (1707357)
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