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Results for “radiography and advanced imaging development”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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24 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Using X-ray radiography to study oxygen flow in a proton exchange membrane electrolyzer operating under balanced pressure conditions

Of the various water electrolyzer technologies, the proton exchange membrane electrolyzer (PEMWE) is one of the best solutions for producing clean hydrogen without releasing CO 2 . In order to allow for widespread use of clean hydrogen, it is necessary to decrease its cost, which is intrinsically related to system operation. Current PEMWE plants operate in differential mode, directly pressurizing hydrogen and benefiting from thermodynamic compression, which increases overall system efficiency. However, high differential pressure above 30 bar can cause membrane stress, resulting in membrane creeping and failure. Pressurizing the water and operating at balanced pressure allows hydrogen to be produced at higher pressures while preserving the integrity of the membrane and porous layers. Nevertheless, the impact of pressurizing water on PEMWE performance must be better understood to maximize performance under balanced pressure conditions. Here, this study examined the impact of water pressure on two-phase flow. A high-pressure electrolyzer setup was developed to perform operando X-ray radiography and examine oxygen transport with high temporal resolution. The imaging segmentation process, developed to capture bubble properties in the channel, was applied to a specific experiment. The results clearly showed that as pressure increased up to 30 bars, the initial bubbly flow transitioned to slug flow, which led to channel saturation with oxygen. This work demonstrates that two-phase flow in an electrolyzer can be studied using X-ray radiography, which has the advantages of fast measurements and the ability to probe dense materials, such as those required for pressurized electrolyzers.

Balanced high pressure operation↗
DOE OSTI2025

Development and scaling of MeV x-ray radiography at NIF-ARC

We investigate the generation of MeV x-rays using the Advanced Radiography Capability laser system at the National Ignition Facility using 1, 10, and 38 ps pulse durations, with laser energies reaching up to 4 kJ and using compound parabolic concentrators. Hydrodynamic simulations using up-to-date measurements of the contrast of the ARC laser are conducted, allowing us to employ an electron scaling model that incorporates scale length and pulse duration, which aligns closely with the observed temperature distributions. Comparable x-ray sources, in terms of dose, are generated when using a 10 ps pulse duration with 2.4 kJ at ∼1.9 ± 0.4 × 10 18 W/cm 2 and when using a 38 ps pulse duration with 4 kJ at 9.9 ± 0.4 × 10 17 W/cm 2 , both achieving ∼16 rad in air at 1 m for x-ray energies > 0.5 MeV. Radiographs performed on the laser “line-of-sight” show significant improvements in image quality than radiographs performed at 65 degrees to the laser axis. We verify the radiography performance using Monte Carlo Simulations.

Physics - Plasma physics↗
DOE OSTI2021

High resolution >40 keV x-ray radiography using an edge-on micro-flag backlighter at NIF-ARC

Radiography of low-contrast features in high-density materials evolving on a nanosecond timescale requires a bright photon source in the tens of keV range with high temporal and spatial resolution. One application for sources in this category is the study of dynamic material strength in samples compressed to Mbar pressures at the National Ignition Facility, high-resolution measurements of plastic deformation under conditions relevant to meteor impacts, geophysics, armor development, and inertial confinement fusion. Here, we present radiographic data and the modulation transfer function (MTF) analysis of a multi-component test object probed at ~100 keV effective backlighter energy using a 5 μm-thin dysprosium foil driven by the NIF Advanced Radiographic Capability (ARC) short-pulse laser (~2 kJ, 10 ps). The thin edge of the foil acts as a bright line-projection source of hard x rays, which images the test object at 13.2× magnification into a filtered and shielded image plate detector stack. The system demonstrates a superior contrast of shallow (5 μm amplitude) sinusoidal ripples on gold samples up to 90 μm thick as well as enhanced spatial and temporal resolution using only a small fraction of the laser energy compared to an existing long-pulse-driven backlighter used routinely at the NIF for dynamic strength experiments.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

X-ray phase-contrast imaging of strong shocks on OMEGA EP

The ongoing improvement in laser technology and target fabrication is opening new possibilities for diagnostic development. An example is x-ray phase-contrast imaging (XPCI), which serves as an advanced x-ray imaging diagnostic in laser-driven experiments. In this work, we present the results of the XPCI platform that was developed at the OMEGA EP Laser-Facility to study multi-Mbar single and double shocks produced using a kilojoule laser driver. Two-dimensional radiation-hydrodynamic simulations agree well with the shock progression and the spherical curvature of the shock fronts. It is demonstrated that XPCI is an excellent method to determine with high accuracy the front position of a trailing shock wave propagating through an expanding CH plasma that was heated by a precursor Mbar shock wave. Furthermore, the interaction between the rarefaction wave and the shock wave results in a clear signature in the radiograph that is well reproduced by radiation-hydrodynamic simulations.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

First Examination of Irradiated Fuel with Pulsed Neutrons at LANSCE (Preliminary Results)

We present preliminary results on the characterization of an irradiated U-lOZr-lPd fuel sample that was prepared from the irradiated AFC-3A-R5A sample. U-lOZr metallic fuels are researched as host materials for potential transmutation fuels and the addition of palladium strives to bind lanthanides, thus preventing fuel-cladding chemical interactions (FCCI). These interactions limit the lifetime of metallic fuels and are caused by migration of lanthanide fission products to the periphery of the fuel slug, where they start to interact with the D9 or HT9 steel cladding, ultimately leading to failure of the mechanical integrity of the cladding. Neutrons offer bulk characterization of irradiated materials for which X-ray tomography methods are not suitable due to the immense gamma background emitted from the samples. In particular pulsed neutrons provide information from the ability to resolve the neutron energy using their time-of-flight and thus the potential to utilize neutron absorption resonance to characterize the spatial distribution of isotopes. This, in turn, may allow to characterize the distribution of fission and neutron capture products non-destructively and may ultimately be applied to the bulk of an irradiation capsule prior to destructive post-irradiation examination to identify regions of interest. To allow the characterization of entire irradiation capsules, a cask is under development in the advanced post-irradiation work package at LANL and progress on this development was reported elsewhere. In parallel, an irradiated U-lOZr-lPd sample cut from the AFC-3AR5A irradiation was shipped to LANL and will be fully characterized with an NSUF funded rapid turnaround experiment (RTE) in the 2020 LANSCE run cycle. The sample emits at a dose rate of ~3R/hr on contact and is therefore manageable with remote handling, without requiring a cask. The disk-shaped material is larger than samples prepared for analysis using electron or X-ray methods and is therefore an intermediate step towards characterization of bulk samples at LANSCE. However, since it covers the full diameter of the irradiated fuel slug, some insight on redistribution of elements, spatially resolved information on microstructure, e.g. phase composition and texture, will be possible using the pulsed neutron-based methods developed for fuel characterization at LANSCE. This report describes the development of procedures to handle the sample at LANSCE as well as preliminary data and results from tests conducted in December 2019 on the energy-resolved neutron imaging (ERNI) beam line at flight path 5 and the high pressure-preferred orientation diffractometer (HIPPO) at LANSCE. This effort is a collaboration between LANL, INL, and ORNL. To compare our capabilities with prior work, we present an overview of previously reported bulk characterization of irradiated or spent fuels. The overview addresses neutron diffraction and neutron absorption resonance spectroscopy, both of which have only few reported applications on irradiated or spent nuclear fuel, as well as neutron radiography. This literature review was already described in a previous report but is repeated here to put our current efforts in context of previous work.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Deep learning with mixup augmentation for improved pore detection during additive manufacturing

In additive manufacturing (AM), process defects such as keyhole pores are difficult to anticipate, affecting the quality and integrity of the AM-produced materials. Hence, considerable efforts have aimed to predict these process defects by training machine learning (ML) models using passive measurements such as acoustic emissions. This work considered a dataset in which keyhole pores of a laser powder bed fusion (LPBF) experiment were identified using X-ray radiography and then registered both in space and time to acoustic measurements recorded during the LPBF experiment. Due to AM’s intrinsic process controls, where a pore-forming event is relatively rare, the acoustic datasets collected during monitoring include more non-pores than pores. In other words, the dataset for ML model development is imbalanced. Moreover, this imbalanced and sparse data phenomenon remains ubiquitous across many AM monitoring schemes since training data is nontrivial to collect. Hence, we propose a machine learning approach to improve this dataset imbalance and enhance the prediction accuracy of pore-labeled data. Specifically, we investigate how data augmentation helps predict pores and non-pores better. This imbalance is improved using recent advances in data augmentation called Mixup, a weak-supervised learning method. Convolutional neural networks (CNNs) are trained on original and augmented datasets, and an appreciable increase in performance is reported when testing on five different experimental trials. When ML models are trained on original and augmented datasets, they achieve an accuracy of 95% and 99% on test datasets, respectively. We also provide information on how dataset size affects model performance. Lastly, we investigate the optimal Mixup parameters for augmentation in the context of CNN performance.

36 MATERIALS SCIENCE↗