Sample test array and recovery (STAR) platform at the National Ignition Facility

Moore, Nathan W.; Bell, Kate; Hilborn, Haley; Woodworth, B. N.; Mesh, Mikhail; Bruss, Donald Eugene; Franke, Brian Claude; Poole, Patrick; Hohlfelder, Robert James; Zarick, Thomas Andrew; Romero, Randall; Chantler, Gary R.; Esquivel, C A; May, Mark; Flanagan, T. M.; Blue, B. E.

doi:10.1063/5.0043313

Cited by 3 publications

(1 citation statement)

References 35 publications

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“…• Establishing efficient simulation of 2D mesostructures [11] to serve as a surrogate of 3D analysis for evaluating various properties that depend on mesostructure. • Enabling effective comparisons of images of plasma facing materials before and after non-destructive hydrodynamic tests, such as those performed at the National Ignition Facility [12]. • Informing shock hydrodynamic simulations in thermalsprayed structures [13].…”

Section: Thermal-sprayed Coatingsmentioning

confidence: 99%

Automated segmentation of porous thermal spray material CT scans with predictive uncertainty estimation

et al. 2023

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Thermal sprayed metal coatings are used in many industrial applications, and characterizing the structure and performance of these materials is vital to understanding their behavior in the field. X-ray computed tomography (CT) enables volumetric, nondestructive imaging of these materials, but precise segmentation of this grayscale image data into discrete material phases is necessary to calculate quantities of interest related to material structure. In this work, we present a methodology to automate the CT segmentation process as well as quantify uncertainty in segmentations via deep learning. Neural networks (NNs) have been shown to excel at segmentation tasks; however, memory constraints, class imbalance, and lack of sufficient training data often prohibit their deployment in high resolution volumetric domains. Our 3D convolutional NN implementation mitigates these challenges and accurately segments full resolution CT scans of thermal sprayed materials with maps of uncertainty that conservatively bound the predicted geometry. These bounds are propagated through calculations of material properties such as porosity that may provide an understanding of anticipated behavior in the field.

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Section: Thermal-sprayed Coatingsmentioning

confidence: 99%

Automated segmentation of porous thermal spray material CT scans with predictive uncertainty estimation

et al. 2023

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Radiation, optical, power flow, and electrical diagnostics at the Z facility: Layout and techniques utilized to operate in the harsh environment

Webb

Bliss

Chandler

et al. 2023

Review of Scientific Instruments

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The Z machine is a current driver producing up to 30 MA in 100 ns that utilizes a wide range of diagnostics to assess accelerator performance and target behavior conduct experiments that use the Z target as a source of radiation or high pressures. We review the existing suite of diagnostic systems, including their locations and primary configurations. The diagnostics are grouped in the following categories: pulsed power diagnostics, x-ray power and energy, x-ray spectroscopy, x-ray imaging (including backlighting, power flow, and velocimetry), and nuclear detectors (including neutron activation). We will also briefly summarize the primary imaging detectors we use at Z: image plates, x-ray and visible film, microchannel plates, and the ultrafast x-ray imager. The Z shot produces a harsh environment that interferes with diagnostic operation and data retrieval. We term these detrimental processes “threats” of which only partial quantifications and precise sources are known. We summarize the threats and describe techniques utilized in many of the systems to reduce noise and backgrounds.

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In-circuit irradiation effect test of electronic components using transient high dose rate X-ray source at high power laser facility

Tao,

Pinyang,

Zongqing

et al. 2024

2024 7th International Conference on Electronics Technology (ICET)

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Sample test array and recovery (STAR) platform at the National Ignition Facility

Cited by 3 publications

References 35 publications

Automated segmentation of porous thermal spray material CT scans with predictive uncertainty estimation

Automated segmentation of porous thermal spray material CT scans with predictive uncertainty estimation

Radiation, optical, power flow, and electrical diagnostics at the Z facility: Layout and techniques utilized to operate in the harsh environment

In-circuit irradiation effect test of electronic components using transient high dose rate X-ray source at high power laser facility

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