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Rubery, Michael

Publications and source records attributed to Rubery, Michael.

9 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

First look at neutron emission shape characteristics of ignition hotspots at the National Ignition Facility (invited)

The nuclear imaging system has been capturing neutron images of inertial confinement fusion (ICF) driven implosions for over a decade at the National Ignition Facility. This imaging system has evolved from one to three nearly orthogonal lines-of-sight, allowing for the study of three-dimensional shape characteristics of ignition shots. Limited-view tomography algorithms help visualize the burning hotspot in 3D and assess neutron source geometry using Legendre mode parameters. With its neutron, gamma-ray, and x-ray image reconstruction capabilities, NIS has provided critical insight into mechanisms that have limited implosion performance, such as fill tube diameter for ignition-type targets. This comprehensive diagnostic suite opens a window into the shape characteristics of ignition shots and how symmetry affects ICF implosion performance. In more recent ignition shots, neutron yields have visibly increased. Analyzing the shape and size of the reconstructed neutron source has shown an expansion of the burn volume, which is indicative of more efficient alpha heating during the implosion process.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

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↗
DOE OSTI2024

Source localization for neutron imaging systems using convolutional neural networks

The nuclear imaging system at the National Ignition Facility (NIF) is a crucial diagnostic for determining the geometry of inertial confinement fusion implosions. The geometry is reconstructed from a neutron aperture image via a set of reconstruction algorithms using an iterative Bayesian inference approach. An important step in these reconstruction algorithms is finding the fusion source location within the camera field-of-view. Currently, source localization is achieved via an iterative optimization algorithm. In this paper, we introduce a machine learning approach for source localization. Specifically, we train a convolutional neural network to predict source locations given a neutron aperture image. We show that this approach decreases computation time by several orders of magnitude compared to the current optimization-based source localization while achieving similar accuracy on both synthetic data and a collection of recent NIF deuterium–tritium shots.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Source localization for neutron imaging systems using convolutional neural networks

The nuclear imaging system at the National Ignition Facility (NIF) is a crucial diagnostic for determining the geometry of inertial confinement fusion implosions. The geometry is reconstructed from a neutron aperture image via a set of reconstruction algorithms using an iterative Bayesian inference approach. An important step in these reconstruction algorithms is finding the fusion source location within the camera field-of-view. Currently, source localization is achieved via an iterative optimization algorithm. In this paper, we introduce a machine learning approach for source localization. Specifically, we train a convolutional neural network to predict source locations given a neutron aperture image. We show that this approach decreases computation time by several orders of magnitude compared to the current optimization-based source localization while achieving similar accuracy on both synthetic data and a collection of recent NIF deuterium–tritium shots.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Measurements of dense fuel hydrodynamics in the NIF burning plasma experiments using backscattered neutron spectroscopy

The hydrodynamics of the dense confining fuel shell is of great importance in defining the behavior of the burning plasma and burn propagation regimes of inertial confinement fusion experiments. However, it is difficult to probe due to its low emissivity in comparison with the central fusion core. In this work, we utilize the backscattered neutron spectroscopy technique to directly measure the hydrodynamic conditions of the dense fuel during fusion burn. Experimental data are fit to obtain dense fuel velocities and apparent ion temperatures. Trends of these inferred parameters with yield and velocity of the burning plasma are used to investigate their dependence on alpha heating and low mode drive asymmetry. It is shown that the dense fuel layer has an increased outward radial velocity as yield increases, showing that burn has continued into re-expansion, a key signature of hotspot ignition. A comparison with analytic and simulation models shows that the observed dense fuel parameters are displaying signatures of burn propagation into the dense fuel layer, including a rapid increase in dense fuel apparent ion temperature with neutron yield.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Gas scintillation mitigation in gas Cherenkov detectors for inertial confinement fusion (invited)

Gas Cherenkov detectors provide a time resolved measurement of the fusion burn in inertial confinement fusion experiments. The fusion rate delivers critical benchmark figures, such as burn width and bang time. Recent detector improvements pushed temporal resolution to 10 ps to make burn width measurements on igniting targets possible. First high temporal resolution measurements using CO 2 gas fills had a background signal with a long decay length (tail), which was caused by gas scintillation. This gas scintillation limits the ability of the detector to resolve short burn width and high frequency features in the fusion rate measurements. A thorough investigation of the cause of the tail and mitigation options for gas scintillation is presented here. As a near-term resolution, neon gas is being used to extract fusion burn histories. Paths forward for the next generation of gas Cherenkov detectors are identified including the usage of oxygen as a Cherenkov medium.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Comparison of ablators for the polar direct drive exploding pusher platform

We examine the performance of pure boron, boron carbide, high density carbon, and boron nitride ablators in the polar direct drive exploding pusher (PDXP) platform. The platform uses the polar direct drive conguration at the National Ignition Facility to drive high ion temperatures in a room temperature capsule and has potential applications for plasma physics studies and as a neutron source. The higher tensile strength of these materials compared to plastic enables a thinner ablator to support higher gas pressures, which could help optimize its performance for plasma physics experiments, while ablators containing boron enable the possiblity of collecting addtional data to constrain models of the platform. Applying recently developed and experimentally validated equation of state models for the boron materials, we examine the performance of these materials as ablators in 2D simulations, with particular focus on changes to the ablator and gas areal density, as well as the predicted symmetry of the inherently 2D implosion.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗