Demonstration of ignition-driven radiation transport through a THOR Hohlraum
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Lasers↗
Engineering topics
Wilde, Carl
Publications and source records attributed to Wilde, Carl.
Source shape estimation for neutron imaging systems using convolutional neural networks
Neutron imaging systems are important diagnostic tools for characterizing the physics of inertial confinement fusion reactions at the National Ignition Facility (NIF). In particular, neutron images give diagnostic information on the size, symmetry, and shape of the fusion hot spot and surrounding cold fuel. Images are formed via collection of neutron flux from the source using a system of aperture arrays and scintillator-based detectors. Currently, reconstruction of fusion source geometry from the collected neutron images is accomplished by solving a computationally intensive maximum likelihood estimation problem via expectation maximization. In contrast, it is often useful to have simple representations of the overall source geometry that can be computed quickly. In this work, we develop convolutional neural networks (CNNs) to reconstruct the outer contours of simple source geometries. We compare the performance of the CNN for penumbral and pinhole data and provide experimental demonstrations of our methods on both non-noisy and noisy data.
Machine learning, neutron imaging, source reconstr↗
Neutron Radiography Efforts
Presentation describes past, present, and future neutron radiography efforts from May 2019 to June 2022, to include Gemini tests, GEANT4 simulations, neutron radiography at LANSCE, and neutron imaging at the Area 11 DPF facility.
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗