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At least 523 records · Page 29
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Evaluation of U-net-based Image Segmentation Model to Digital Mammography

Detecting suspicious lesions in medical imaging is the important first step in computer-aided detection (CAD) systems. However, detecting abnormalities in breast tissue is difficult due to the lesion's varying size, shape, margin, and contrast with the background tissue. We focused on mass segmentation, a method that provides notable morphological features by outlining contours of masses. Accurate segmentation is crucial for correct diagnosis. Recent advancements in deep learning have improved object detection and segmentation, and these techniques are also being applied to medical imaging studies. We focused on U-net, which is a recently developed mass segmentation algorithm based on a fully convolutional network. The U-net architecture consists of (1) a contracting path to increase the resolution of the output and (2) a symmetric expanding path to better locate the region of interest. The performance of a U-net model was tested with 63 digital mammograms from INbreast, a publicly available database. We trained the model with images resized to 40x40 pixels and conducted 10-fold cross-validation to prevent overfitting. The model's performance with respect to breast density and the lesion's BI-RADS rating was also investigated. Dice coefficients (DC) were used as a performance measure to compare the predicted segmentation of the model with the ground truth. Logistic regression and an analysis of variance were performed to determine the significance of the DCs with regards to breast density and lesion behavior and to calculate the 95% confidence interval. The average DC was 0.80. The difference between DCs for BI-RADS 2 and 4c and for BI-RADS 2 and 5 were significant, suggesting that the model has more difficulty in segmenting benign lesions.

Cho, Priscilla↗
DOE OSTI2025

Investigation of a U(IV)/U(III) Thermodynamic Reference Electrode for High-Temperature Molten Fluoride Salts

While thermodynamic reference electrodes with known and stable potentials are common in traditional aqueous systems, the high temperature and corrosive environment of a molten fluoride salt makes achieving long term stability with a thermodynamic reference electrode challenging, especially at temperatures of 600°C or higher. In this work, a thermodynamic reference electrode consisting of U(IV)/U(III) in a boron nitride compartment was evaluated for use in FLiBe at temperatures ≥ 600°C. FLiBe used in the study was purified by AlphaTech's proprietary process and characterized by ICP-MS and square wave voltammetry. The free oxide concentration was <2 ppm. Using the purified FLiBe, the U(IV)/U(III) thermodynamic reference electrode was shown to provide a stable, well-defined, and reproducible potential for more than 600+ hours of use in different tests. Moreover, the thermodynamic reference electrode showed a consistent potential with no signs of failure, even after being cooled between tests and then reheated for reuse. Thus, the U(IV)/U(III) reference electrode is suitable for use in rigorous electrochemical studies in molten fluoride salts. As a result, it may be useful as a common standard, facilitating the advancement of nuclear applications such as isotope separation or online monitoring of reactor systems through improved certainty in the measurement of thermodynamic potentials.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Prediction of electron density and pressure profile shapes on NSTX-U using neural networks

A new model for prediction of electron density and pressure profile shapes on NSTX and NSTX-U has been developed using neural networks. The model has been trained and tested on measured profiles from experimental discharges during the first operational campaign of NSTX-U. By projecting profiles onto empirically derived basis functions, the model is able to efficiently and accurately reproduce profile shapes. In order to project the performance of the model to upcoming NSTX-U operations, a large database of profiles from the operation of NSTX is used to test performance as a function of available data. The rapid execution time of the model is well suited to the planned applications, including optimization during scenario development activities, and real-time plasma control. A potential application of the model to real-time profile estimation is demonstrated.

Boyer, Mark↗
DOE OSTI2024

Development of a Full-Scale Connected U-Net for Reflectivity Inpainting in Spaceborne Radar Blind Zones

CloudSat’s Cloud Profiling Radar is a valuable tool for remotely monitoring high-latitude snowfall, but its ability to observe hydrometeor activity near the Earth’s surface is limited by a radar blind zone caused by ground clutter contamination. This study presents the development of a deeply supervised U-Net-style convolutional neural network to predict cold season reflectivity profiles within the blind zone at two Arctic locations. The network learns to predict the presence and intensity of near-surface hydrometeors by coupling latent features encoded in blind zone-aloft clouds with additional context from collocated atmospheric state variables (i.e., temperature, specific humidity, and wind speed). Results show that the U-Net predictions outperform traditional linear extrapolation methods, with low mean absolute error, a 38% higher Sørensen–Dice coefficient, and vertical reflectivity distributions 60% closer to observed values. The U-Net is also able to detect the presence of near-surface cloud with a critical success index (CSI) of 72% and cases of shallow cumuliform snowfall and virga with 18% higher CSI values compared to linear methods. An explainability analysis shows that reflectivity information throughout the scene, especially at cloud edges and at the 1.2-km blind zone threshold, along with atmospheric state variables near the tropopause, are the most significant contributors to model skill. This surface-trained generative inpainting technique has the potential to enhance current and future remote sensing precipitation missions by providing a better understanding of the nonlinear relationship between blind zone reflectivity values and the surrounding atmospheric state.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Utility Finder (U-Finder) Tool

U-Finder allows users to search for and identify local utility partners and electric vehicle charger incentives by state or ZIP code. U-Finder pulls from the Homeland Infrastructure Foundation-Level Database of Electric Retail Service Territories to identify utility service territories. Utility incentive listings are provided by utility associations, and state government incentive listings are pulled from the Alternative Fuels Data Center Laws and Incentives website. ![U Finder landing page](ufinder-landing.png)

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

AmeriFlux FLUXNET-1F US-xPU NEON Pu'u Maka'ala Natural Area Reserve (PUUM)

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-xPU NEON Pu'u Maka'ala Natural Area Reserve (PUUM). This is the FLUXNET version of the carbon flux data for the site US-xPU NEON Pu'u Maka'ala Natural Area Reserve (PUUM) produced by applying the standard ONEFlux (1F) software. Site Description - NEON's PUUM field site is located in the Pu'u Maka'ala Natural Area Reserve (NAR) on the eastern side of Hawaii’s “Big Island,” managed by the Hawaii Division of Forestry and Wildlife (DOFAW). More than 18,000 acres in size, the NAR is home to a rainforest with many native species, some of them endangered. It was established to protect some of the Big Island’s best wet native forest and unique geologic features.

Network), NEON (National Ecological Observatory [N↗
DOE OSTI2021

Fission TPC FY2020 Report (Mid Q2 FY2021): Preliminary 235 U(n,f)/ 6 Li(n,t)α Cross Section Ratio Analysis & Update on the 239 Pu(n,f) Data Collection

Fission TPC L2 Milestone Description: The fission TPC experimental campaign is in its final stages of collecting high precision (n,f) cross section data aimed at improving our understanding of the 239 Pu fission process. During FY 2019 235 U(n,f)/ 6 Li(n,t) ratio data collection began at WNR/LANSCE. This data is the first step in demonstrating the efficacy of 6 Li(n,t) as a diagnostic standard for a 239 Pu(n,f) ratio measurement. In FY 2020 and FY2021, the NIFFTE Collaboration will analyze 235 U(n,f)/ 6 Li(n,t) data already collected to establish this technique in preparation for 239 Pu(n,f)/ 6 Li(n,t) ratio data. Additionally, the ability to vapor deposit 239 Pu was developed in 2019, greatly improving target quality. As access to experimental facilities allows, 239 Pu/ 235 U and 239 Pu/ 6 Li data will be collected to provide new inputs for evaluation of the 239 Pu(n,f) cross section.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Report to NCSP on FY21 DANCE and NEUANCE measurements of 233 U(η, γ)

The experiment was performed by the end of the CY20 runcycle at LANSCE. Due to transportation issues the material arrived at LANL on 1st December. Two 233 U samples, of 20 mg and 10 mg were produced at LANL by stippling, which has proved a robust, cost-effective method for producing actinide samples in the range of 1-20 mg in a small (<1 cm) diameter with very high efficiency. The 20 mg sample was placed inside NEUANCE on FP14 on 11th December, was measured over 10 days, and the 10 mg sample was placed in the beam for 1 day. The rest of the beam time was used to measure radioactive γ sources for calibration, background measurements and tests to define the 233 U windows required during the data taking, also some measurements were done with a 235 U sample to cross-check the performance and the systematics.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Report to NCSP on FY21 DANCE and NEUANCE measurements of 233 U(n, γ)

In order to complete the statistics needed above 10 keV after the experiment performed in December 2020, a production measurement of the 233 U capture cross section, using the thick target (~20 mg) was proposed for the CY21 runcycle. Through collaboration with the DANCE experimental team, we arranged for the NEUANCE array to stay in place in the CY21 run cycle until the 233 U measurement was complete in June-July 2021, further reducing systematic uncertainties in the measurement. The measurement was performed over 10 days with the 20 mg sample, and the 10 mg sample was placed in the beam for 1 day. The rest of the beam time was used to measure radioactive γ sources for energy calibration, and background measurements and tests to define the 233 U windows required during the data taking. The NEUANCE detector placed inside the DANCE cavity is shown.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

2021 Microbial U (Summary Report)

The US nuclear industry is on the cusp of significant growth in the areas of advanced reactors, SMRs, and microreactors. The existing commercial nuclear reactor fleet is considering expanding the life of the reactor cores by slightly increasing enrichment of their fuel. The common thread is the demand for High Assay Low Enriched Uranium (HALEU). A technical challenge exists with a blend down of Highly Enriched Uranium (HEU) from spent nuclear fuel (SNF) to meet the American Society for Testing and Materials (ASTM) and the “Y12” specifications. U-236 impacts reactor performance and is not desired in fresh fuel cores. In order to meet tight specifications, U-236 must be diluted by addition of fresh HEU. Fresh HEU is highly sought after and not plentiful in the US. A solution to this issue lies in the application of a technology to selectively remove the U-236 with non-hazardous microorganisms, which will be evaluated in this project by experimentally separating different isotopes of uranium.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Producing ENDF/B-quality Evaluations of 239 Pu(n,f) and 235 U(n,f) Average Prompt Neutron Multiplicities using the CGMF Model

This report documents evaluations of the neutron-induced 239 Pu and 235 U average prompt neutron multiplicities, $\overline{v}_p$, using the CGMF model developed at LANL. These evaluations are not updates of existing ENDF/B-VIII.0 nuclear data, but were both re-done from "scratch". That is, all experimental data were extracted from EXFOR, re-normalized to the newest nuclear data representing monitor observables, and detailed uncertainties were estimated from information in EXFOR as well as from templates of expected measurement uncertainties. We also included experimental data that were not yet available for ENDF/B-VIII.0, for instance, the data of Marini et al. for 239 Pu(n,f) $\overline{v}_p$ or the data of Khoklov et al. for 235 U(n,f) $\overline{v}_p$. Finally, we include the CGMF model; it computes $\overline{v}_p$ based on model parameters that at the same time calculate fission fragments as a function of mass, Y (A), the average total kinetic energy as a function of incident-neutron energy, $\langle TKE \rangle$(E inc ), etc. Such a detailed fission model that ties together many fission quantities has not been used to date for any $\overline{v}_p$ evaluation in ENDF/B. Here, we show that we can get evaluated 235 U(n,f) and 239 Pu $\overline{v}_p$ that not only correspond well to experimental $\overline{v}_p$, but that the associated evaluated model parameters also yield parameterizations of Y (A), $\langle TKE \rangle$(E inc ), etc., that correspond well to their respective experimental data. The new evaluated 239 Pu(n,f) $\overline{v}_p$ was also combined into a 239 Pu test file with the newest nuclear data for the 239 Pu prompt-fission neutron spectrum and fission cross sections. This new 239 Pu file performed reasonably well in predicting PU-MET-FAST assemblies, reaction rates in Jezebel and Flattop and three LLNL pulsed spheres. Due to that, the new 239 Pu(n,f) $\overline{v}_p$ evaluation presented here is being considered for ENDF/B-VIII.1. Hence, we can show here that CGMF is able to produce ENDF/B quality $\overline{v}_p$ nuclear data.

239Pu, 235U, Average Prompt-fission Neutron Multip↗
DOE OSTI2021

Assembly of MiniFuel Targets for Irradiation of U-Mo Fuel Specimens in the High Flux Isotope Reactor

To support the development of advanced low-enriched uranium for use in nuclear reactors, irradiation testing of U-Mo disk specimens was performed at the Oak Ridge National Laboratory (ORNL) High Flux Isotope Reactor (HFIR) to collect experimental irradiation data on this type of fuel at pressurized water reactor–relevant temperatures. U-Mo is a uranium alloy that has superior dimensional stability relative to alpha-phase uranium metal and has a substantially higher uranium density compared to UO 2 . U-Mo disks specimens were fabricated at Idaho National Laboratory and inserted into MiniFuel targets for HFIR irradiation. Three MiniFuel targets were successfully assembled, welded, tested, and delivered to HFIR, along with their quality assurance documentation. The targets were inserted into HFIR’s inner vertical experiment facility within the permanent beryllium reflector. Each target contains six disk specimens and will be irradiated in HFIR for three, four, and eight cycles, with target temperatures between 250 and 500°C. This report summarizes the experiment design, test matrix, pre-characterization of specimens, and experiment assembly.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Casting and Characterization of U-50Zr

Uranium alloyed with 50 wt% zirconium (U-50Zr) is a proposed light water reactor (LWR) nuclear fuel by Lightbridge Corporation (LTBR). The proposed method for making the U-50Zr alloy is to arc-melt master alloys and then remelt in a vacuum induction melter (VIM) to consolidate the material and cast into an intermediate shape. After casting, the material will eventually need to be formed into a desired fuel shape. The work discussed in this report resulted from a joint effort between Ltbr and Pacific Northwest National Laboratory (PNN) to investigate a 500g – 1kg scale casting process to produce the U-50Zr alloy in the desired δ-UZr 2 phase and characterize the impurities and microstructure that result from the casting process. Master alloys were fabricated in an arc melter, then five castings were carried out in a VIM with multiple inert coating and crucible materials to find an appropriate combination. Both ZrO 2 and graphite crucibles were used and different combinations of Y 2 O 3 , CaZrO 3 , and TiC to identify which would contain the molten metal with the least reaction. On each casting, the C, O, N, H impurities were analyzed as well as the phase by x-ray diffraction and microstructure. Of the five castings, two resulted in majority of δ-UZr 2 phase-pure material and had impurity levels within acceptable ranges. The two most successful castings utilized a graphite crucible with a TiC undercoating and a Y 2 O 3 overcoat. The O and N levels were below 1000 ppm and the C content was variable but did not result in measurable carbide formation. The highest success casting resulted in an average of 282 ppm C, 567 ppm O, 217 ppm N and 79 ppm H. This casting's crucible and inert coating material was repeated with slightly different casting parameters and resulted in higher C numbers but similar phase identification. The differences between each casting are discussed and recommendations are made for future experiments to better decide on a casting process to go forward with.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

FY22 NCSP accomplishments for U and Pu Evaluations [Slides]

This presentation covers fiscal year 2022 for Nuclear Criticality Safety Program (NCSP) accomplishments for Uranium (U) and Plutonium (Pu) evaluations. This presentation includes an overview on plutonium and uranium. Additionally, this presentation covers the inclusion of sub-thermal data for 235 U and the inclusion of LANL ratio capture-to-fission data for 233 U and 235 Pu. The presentation ends with a discussion on 239 Pu Primary fit of Mosby's data as reported and a look at the uncertainty quantification.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Predicted thermophysical properties of UN, PuN and (U,Pu)N

Molecular dynamics and density functional theory simulations are used to predict the lattice and electronic contributions of thermophysical properties for UN, PuN, and mixed (U,Pu)N systems. The properties predicted include the lattice parameter, linear thermal expansion, enthalpy, and specific heat capacity, as a function of temperature. The simulation predictions for high temperature specific heat capacity are compared against experimental measurements to understand the behavior, and why differences in the experimental measurements are observed. The influence of adding U vacancies, N interstitials, and Pu to UN is also examined. For this, a new PuN potential parameter set is developed and used with the Kocevski UN potential, enabling the dynamics of mixed (U,Pu)N systems to be studied. How defects impact the thermophysical properties is important for understanding fuel behavior under different reactor conditions, and these mechanistic predictions can be used to support fuel performance codes where data is scarce.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

U-gas +Cool GTL™ - A New Integrated Process for Direct Biomass Conversion to Liquid Fuels

The U-Gas gasification technology, marketed by Sungas, is a proven fluid bed gasification technology for biomass conversion. U-Gas has been tested on a wide variety of biomass feeds including wood and waste streams. The U-Gas Technology has successfully converted wood for more than 20 years in a gasification plant in Skive Denmark at the 150t/d size. GTI has also recently developed the Cool GTL process for converting biogas to high quality gasoline, jet, and diesel fuels. The technoeconomics and LCA for the combination of the two technologies results an integrated optimized process, which will be discussed. The Cool GTL process is still in development and the development should be complete by 2023. Cool GTL converts high CO2 content feeds to synthesis gas with a 2-2.4/1 H2/CO ratio suitable for fuels synthesis. The process is based on a novel, highly stabile CO2/steam reforming catalyst. The 2.0-2.4/1 H2/CO synthesis gas ratio is always achieved, independently of feed CO2 content, by adjusting the amount of water added according to the amount of CO2 in the feed. The reformer catalyst has been tested for 500 hours and shows no measurable deactivation. The product from the reformer then goes directly to a low temperature slurry bed Fischer Tropsch reactor with an integrated finishing hydroisomerization reactor which makes hydrocarbon liquids from the synthesis gas. With this configuration no wax is produced. The technoeconomics and carbon intensity for the integration of UGas and the Cool GTL processes will be compared to other biomass conversion approaches. The use of electrolysis to boost H2 in the feed and increase liquid production will also be analyzed as a potential process improvement with sensitivities to the cost of electricity and the use of renewable electricity.

09 BIOMASS FUELS↗
DOE OSTI2023

Evaluation of the Reconstruction Accuracy of the Ultrasound Model–Based Image Reconstruction (U-MBIR) Method for Concrete to Optimize Damage Detection

Reinforced concrete is a critical structural material used to construct nuclear power plants (NPPs). As such, its safety and performance must be thoroughly examined throughout the life cycle of the NPP infrastructure system. Ultrasonic measurements have been an industry standard for both surface and subsurface inspections. To support the development of these techniques, Oak Ridge National Laboratory (ORNL) has researched and developed advanced image reconstruction algorithms to capture internal damage. The results and discussion presented herein summarize the current state of the ultrasonic model–based iterative reconstruction (U-MBIR) algorithm developed at ORNL. In the work documented in this report, the U-MBIR methodology was applied to four sets of ultrasonic data collected from concrete specimens. The results demonstrate that the U-MBIR algorithm can successfully detect defects within the four concrete samples. The reconstruction images help identify the specimen thickness, regions of delamination, and location of rebar embedded within the concrete. The reconstruction images allow engineers and technicians to characterize the internal defects within concrete specimens and structural members. Ultimately, this knowledge can guide engineers in making informed decisions regarding the performance, safety, and reliability of structural materials (i.e., reinforced concrete) throughout the life cycle of NPPs.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Complete Performance Comparison Between the Optimized Image Construction Algorithm (U-MBIR) and the Existing Reconstruction Algorithm for Detecting Defects and Damage in Concrete

Reinforced concrete (RC) is a composite material subjected to mechanical, thermal, and chemical loads throughout its service life. Because of these external stressors and the susceptibility of RC structural members to shrinkage and microcracking, the material degrades throughout its life cycle. This deterioration can lead to a decrease in member capacity and, ultimately, poses a threat to the structural integrity. Thus, it is crucial that the damage caused by aging and degradation be monitored and assessed at regular intervals throughout the material’s service life. Since coring of the material is typically not feasible for in-service structural systems, non-destructive evaluation (NDE) methodologies are used to assess remaining structural capacity. NDE methods enable surface and subsurface examination without damaging or degrading the medium. Moreover, RC is a critical component of nuclear power plants; thus, its safety and reliability must be thoroughly examined throughout the life cycle of the structural system. Ultrasonic measurements have been an industry standard for both surface and subsurface inspections. To this end, Oak Ridge National Laboratory (ORNL) has researched and developed advanced image reconstruction algorithms to capture internal damage. The results and discussion presented herein summarize the current state of the ultrasonic model–based iterative reconstruction (U-MBIR) algorithm developed at ORNL. More specifically, this report presents a comparison between reconstruction images produced via a widely employed ultrasonic NDE technique—the synthetic aperture focusing technique (SAFT)—and the ORNL-developed U-MBIR algorithm. These NDE methodologies are demonstrated using ultrasonic data collected from four concrete specimens. Overall, the U-MBIR algorithm eliminates artifacts and noise that are typically present within the SAFT reconstructions, and it shows defects and anomalies more clearly than the SAFT images. In conclusion, this algorithm is suitable for identifying concrete defects, although more improvements and optimization could be done to better define internal defects.

36 MATERIALS SCIENCE↗