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

Fungal community and functional responses to soil warming are greater than for soil nitrogen enrichment

Soil fungi are key regulators of forest carbon cycling and their responses to global change have effects that ripple throughout ecosystems. Global changes are expected to push many fungi beyond their environmental niches, but there are relatively few studies involving multiple, simultaneous global change factors. Here, we studied soil fungal diversity, community composition, co-occurrence patterns, and decomposition gene responses to 10 years of soil warming and nitrogen addition, alone and in combination. We specifically examined whether there were fungal community characteristics that could explain changes in soil carbon storage and organic matter chemistry in chronically warmed and fertilized soil. We found that fungal communities in warmed soils are less diverse and shift in composition. Warming also favored hyperdominance by a few mycorrhizal fungal species and lowered manganese peroxidase but increased hydrolytic enzyme encoding gene potentials. Nitrogen addition did not significantly affect fungal community composition but, like warming, did reduce fungal diversity and favored overdominance by a unique set of mycorrhizal taxa. Warming alone and in combination with nitrogen addition also reduced negative but increased positive fungal co-occurrence probabilities, promoting species coexistence. Negative fungal co-occurrence was positively correlated to soil carbon content, while the proportion of fungal hydrolytic enzyme encoding genes was negatively correlated with soil carbon content. This may reflect fungal life history trade-offs between competition (e.g., reduced negative co-occurrence) and resource acquisition (e.g., higher abundance of hydrolytic enzyme encoding genes) with implications for carbon storage.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Analysis of Tank 38H (HTF-38-20-7, -8) and tank 43H (HTF-43-20-9, -10) samples for Support of the Enrichment Control and Corrosion Control Programs

SRNL analyzed samples from Tank 38H and Tank 43H to support ECP and CCP. The results indicate the concentrations of most species in the Tank 38H surface sample decreased significantly from the previous surface sample. The Tank 38H sub-surface sample shows only small changes in concentration for most major species in the solution from the previous sample. The large differences in the concentrations of major components between the Tank 38H surface and sub-surface samples indicate significant stratification of solution species within the tank. The Tank 38H sub-surface sample contained a small amount of sludge solids (<1 wt%).

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Analysis of Tank 38H (HTF-38-20-62, -63) and Tank 43H (HTF-43-20-60, -61) Samples for Support of the Enrichment Control and Corrosion Control Programs

SRNL analyzed samples from Tank 38H and Tank 43H to support ECP and CCP. The results indicate the concentrations of most species in the Tank 38H surface sample increased from the previous surface sample. The Tank 38H sub-surface sample shows only small changes in concentration for most major species in the solution from the previous sample. The large differences in the concentrations of major components between the Tank 38H surface and sub-surface samples indicate significant stratification of solution species within the tank. The Tank 38H surface and sub-surface samples both contained a small amount of sludge solids (<1 wt%). The Tank 43H surface and sub-surface samples are slightly more dilute than the previous samples. The Tank 43H sub-surface sample exhibits a composition more concentrated than the surface sample indicating some stratification within the tank. The Tank 38H surface and sub-surface sample both show large increases in the concentrations of uranium and plutonium likely due to the presence of sludge solids in both samples. (Note: the samples were digested and analyzed without filtration.) The total uranium concentrations of the two Tank 43H samples are similar to the previous sample results. The plutonium concentration in both Tank 43H samples appear to have decreased from the previous samples; however, the surface sample concentrations are close to the detection limit.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

Analysis of Tank 38H (HTF-38-20-103, -104) and Tank 43H (HTF-43-20-105, -106) Samples for Support of the Enrichment Control and Corrosion Control Programs

SRNL analyzed samples from Tank 38H and Tank 43H to support ECP and CCP. The results indicate the concentrations of most species in the Tank 38H surface sample decreased from the previous surface sample. The Tank 38H sub-surface sample shows only minor changes in concentration for soluble species in the solution (e.g., Na, Al, Cs-137) but a large drop in concentrations for species typically associated with sludge solids (e.g., U, Pu, Fe, Si) likely because of a decrease in sludge solids from the previous sample. The large differences in the concentrations of major components between the Tank 38H surface and sub-surface samples indicate significant stratification of solution species within the tank.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

Analysis of Tank 38H (HTF-38-21-95, -96) and Tank 43H (HTF-43-21-97, -98) Samples for Support of the Enrichment Control and Corrosion Control Programs

SRNL analyzed samples from Tank 38H and Tank 43H to support ECP and CCP. The results indicate the concentrations of most species in the Tank 38H surface sample increased from the previous surface sample. The Tank 38H sub-surface sample shows only minor changes in concentration for soluble species in the solution (e.g., Na, Al, Cs-137) relative to the previous sample, but a small decrease in concentrations for species typically associated with sludge solids (e.g., U, Pu, Fe, Si) likely because of a decrease in sludge solids from the previous sample. The large differences in the concentrations of major components between the Tank 38H surface and sub-surface samples indicate significant stratification of solution species within the tank.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

Nuclear Deactivation and Downgrade of Enriched Uranium Facilities at the Y-12 National Security Complex

Facility Disposition and Modernization Partnership includes 1) Leading modernization efforts through infrastructure investments, technology development, and facility stewardship; 2) Development and implementation of the nuclear deactivation and downgrade strategy for nuclear facilities; 3) Reduction of risk to the environment, public, and workers; 4) Shrinking the DOE legacy footprint.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

High Flux Isotope Reactor Low Enriched Uranium U-10Mo Fuel Design Parameters

Activities to convert the HFIR from HEU to LEU are ongoing as part of the US Department of Energy (DOE) National Nuclear Security Administration (NNSA) nuclear nonproliferation mission. Design activities to study the conversion of HFIR from HEU to LEU fuel explored different fuel design features and shapes with a uranium-molybdenum (U-10Mo) monolithic alloy fuel. This high-density alloy contains 90 wt % uranium and 10 wt % molybdenum and has a uranium density of 15.318gU/cm 3 . The goal of these studies is to generate several candidate HFIR LEU fuel designs of varying fuel fabrication complexity that meet the current HEU performance metrics and safety requirements. Recent advancements in modeling and simulation tools and design methods enabled a thorough analysis of the available design space with U-10Mo fuel. A surrogate model used this analysis as training data to quickly determine the performance of a design given specific design parameters. An optimization module used this surrogate model to quickly search this multidimensional search space given specific desired performance characteristics. This approach was made possible by the large available design space with U-10Mo fuel. Shift, a Monte Carlo tool optimized for high-performance computing (HPC) architectures, was used for faster calculation and better data management for reactor physics simulations. Once most of these design studies were complete, a new suite called the Python HFIR Analysis and Measurement Engine (PHAME) was developed to connect all fuel design analysis steps, making design studies more efficient and reproducible. The post-processing capabilities of these new tools are leveraged for the information provided herein. Leveraging these tools, several candidate fuel designs were selected with varying levels of feature complexity and reactor performance. This report provides design feature details for four selected HFIR LEU U-10Mo fuel designs and their corresponding performance and safety metrics. Nominal best-estimate design parameters and irradiation conditions, including fission rate densities, power densities, heat fluxes, and cumulative fission densities, are provided. Simulations show that the high uranium density of U-10Mo fuel provides a large potential design space that enables various LEU designs to meet HEU core performance metrics and safety requirements with a power increase from 85 MW (HEU) to 95 MW or 100 MW (LEU).

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Analysis of Tank 38H (HTF-38-22-31, -32) and Tank 43H (HTF-43-22-33, -34) Samples for Support of the Enrichment Control and Corrosion Control Programs

SRNL analyzed samples from Tank 38H and Tank 43H to support ECP and CCP. The results indicate the concentrations of most soluble species in the Tank 38H surface sample increased from the previous surface sample. The Tank 38H sub-surface sample shows changes in concentration for soluble species in the solution with some increasing and some decreasing. The current Tank 38H sub-surface sample contains less sludge solids than the previous sample based on visual appearance. The small differences in the concentrations of major components between the Tank 38H surface and sub-surface samples indicate only minimal stratification of solution species within the tank.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

The Power of Priors: Improved Enrichment Safeguards

International safeguards currently rely on material accountancy to verify that declared nuclear material is present and unmodified. Although effective, material accountancy for large bulk facilities can be expensive to implement due to the high precision instrumentation required to meet regulatory targets. Process monitoring has long been considered to improve material accountancy. However, effective integration of process monitoring has been met with mixed results. Given the large successes in other domains, machine learning may present a solution for process monitoring integration. Past work has shown that unsupervised approaches struggle due to measurement error. Although not studied in depth for a safeguards context, supervised approaches often have poor generalization for unseen classes of data (e.g., unseen material loss patterns). This work shows that engineered datasets, when used for training, can improve the generalization of supervised approaches. Further, the underlying models needed to generate these datasets need only accurately model certain high importance features.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗