Demonstration of ignition-driven radiation transport through a THOR Hohlraum
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Lasers↗
Engineering topics
Durocher, Mora
Publications and source records attributed to Durocher, Mora.
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↗
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↗
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↗
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 ↗
Three-Dimensional Gamma Imaging of Inertial Confinement Fusion [Slides]
Abstract not provided.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
A glimpse of stars the size of dust particles
The Nuclear Imaging System (NIS) is an important diagnostic tool used to study nuclear fusion implosions at a research facility in California. There a capsule the size of a flea is compressed until it reaches the size of a speck of dust. As the capsule collapses on itself and ignites under extreme temperature and pressure, NIS detects particles emitted from that process at a scale that would correspond to watching a 32-inch TV screen from 100 miles away. My work involves taking snapshots of one of the most minuscule, fleeting and amazing experiments on Earth in order to ensure the safety and reliability of the US nuclear stockpile and get closer to developing a new form of clean energy.
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
Nuclear imaging capabilities at the National Ignition Facility
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Durocher, Mora↗
NucD-24 Nuclear Diagnostics Development: Time resolved 12 C-rhoR on GCD and NIS technology development for polar LOS and data quality [Slides]
The Neutron Imaging team is readying for the NIS2 polar LOS development and future improvements to data quality on all LOS given consistently higher yields at NIF. Next-gen nano guide scintillators for NIS2 and CMOS cameras to replace outdated CCDs will be studied. Digital image plates will be tested for better data quality on passive imaging systems. The transition into the ignition regime is expected to show a significant signature in the ablator areal density. In the marginal ignition regime, a decrease of 12C-rhoR (ablator areal density) is expected but once the burn propagation produces a shock and compresses the ablator the trend reverses. GCD with the PD-PMT can resolve this effect in the ablator areal density by a temporal shift in the carbon signal. To give quantitative results a calibration of the detector for the Hohlraum/TMP signal is needed. Shots using Al, Si, and Au pucks will yield the needed information to move forward with this project.
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
A search for spectral hardening in HAWC sources above 56 TeV
The High Altitude Water Cherenkov (HAWC) Observatory is a wide-field-of-view gamma-ray observatory that is optimized to detect gamma rays between 300 GeV and several hundred TeV. The HAWC Collaboration recently released their third source catalog (3HWC), which contains 65 sources. One of these sources, the ultra-high-energy gamma-ray source 3HWC J1908+063, may exhibit a hardening of the spectral index at the highest energies (above 56 TeV). At least two populations of particles are needed to satisfactorily explain the highest energy emission. This second component could be leptonic or hadronic in origin. If it is hadronic in origin, it would imply the presence of protons with energies up to ~1 PeV near the source. We have searched other 3HWC sources for the presence of this spectral hardening feature. If observed, this would imply that the sources could make good PeVatron candidates.
79 ASTRONOMY AND ASTROPHYSICS↗
The Ultra-High-Energy Source MGRO J1908+06
The TeV gamma-ray source MGRO J1908+06 is one of the highest-energy sources known, with observed emission by the High Altitude Water Cherenkov (HAWC) Observatory extending well past 100 TeV. The source exhibits both energy-dependent morphology and a spatially-dependent spectral index. The emission is likely to be dominantly leptonic, and associated with the radio-quiet PSR J1907+0602. However, one-population models do not describe the data well; a second particle population is needed to explain the shape of the spectral energy distribution at the highest energies. This component can be well-described by either leptonic or hadronic hypotheses. We discuss this feature and implications for detection by multi-wavelength and multi-messenger experiments.
79 ASTRONOMY AND ASTROPHYSICS↗
Evidence of 200 TeV Photons from HAWC J1825-134
The Earth is bombarded by ultrarelativistic particles, known as cosmic rays (CRs). CRs with energies up to a few PeV (=10 15 eV), the knee in the particle spectrum, are believed to have a Galactic origin. One or more factories of PeV CRs, or PeVatrons, must thus be active within our Galaxy. The direct detection of PeV protons from their sources is not possible since they are deflected in the Galactic magnetic fields. Hundred TeV γ-rays from decaying π 0 , produced when PeV CRs collide with the ambient gas, can provide the decisive evidence of proton acceleration up to the knee. Here we report the discovery by the High Altitude Water Cerenkov (HAWC) observatory of the γ-ray source, HAWC J1825-134, whose energy spectrum extends well beyond 200 TeV without a break or cutoff. The source is found to be coincident with a giant molecular cloud. Further, the ambient gas density is as high as 700 protons cm –3 . While the nature of this extreme accelerator remains unclear, CRs accelerated to energies of several PeV colliding with the ambient gas likely produce the observed radiation.
79 ASTRONOMY AND ASTROPHYSICS↗