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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 1,117 records · Page 62
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Triso Analysis Tool For Predictive Source Terms

Source term modeling for TRi-structural ISOtropic (TRISO) fuel has been performed for previous reactor designs, but few are available in the open literature. Thus, there is a need to develop a simple, versatile, and mechanistic model of fission product release and transport in gas reactor cores that can be applied to a variety of reactors through user inputs and reactor-specific radionuclide inventories. To meet this need, the TRISO Analysis Tool for Predictive Source terms (TRISO-ATOPS) was developed. This model calculates the release of the key safety-important fission products by diffusion through the kernel, silicon carbide and graphite based on fuel and graphite temperatures in the reactor under normal operation. These releases from the fuel enter the coolant where they can plate-out on cooler surfaces. A clean-up model is included for designs with a coolant purification system for removing fission gases. This initial distribution of fission products in the reactor serves as an initial condition for potential releases under postulated accident conditions. From this initial condition, the model calculates the fission product release for any transient temperature profile, and the fission product releases can then be used to assess radiological dose to the workers and the public using conventional radiological dose tools. Data on the diffusion of fission products is based on historic German TRISO experiments and the more current Department of Energy Advanced Gas Reactor TRISO fuel development program. The example cases in this work demonstrate the flexibility of the model

Stoyer, Benjamin [Idaho National Laboratory (INL),↗
DOE OSTI2026

Object-Based Evaluation of Dynamical and Statistical Downscaled Precipitation Products over CONUS

High-resolution precipitation data, generated through dynamical downscaling (DD) or statistical downscaling (SD) of global climate model output, provide critical information for regional climate assessment and adaptation planning. Most downscaling development and validation have focused on accurate gridscale precipitation construction and ignored the spatial structure of precipitation across model grids and at the event scale. However, many applications, e.g., hydrologic modeling and the analysis using the downscaled precipitation, require a reasonable representation of the spatial structure of precipitation within watersheds. Therefore, a set of standard metrics to evaluate the representation of the spatial structure of individual storms across diverse downscaled precipitation products is desired. To address this need, we conducted an object-based evaluation of precipitation in decades-long DD and SD products over the contiguous United States (CONUS). Specifically, we evaluate their ability to reproduce various features of precipitation objects in the observations: total volume, precipitation area, peak intensity, and spatial structure. Multiple metrics (bias, Perkins score, and nonparametric statistical tests) are used to quantify model performance. Our evaluation reveals notable variations in performance among individual products across different climate zones and seasons, as well as between extreme and nonextreme events. In general, most DD products exhibit balanced performance across the four precipitation object features, while SD products vary more significantly in their performance across products. Based on this comprehensive evaluation, we provide guidance on choosing downscaled products for specific regions, seasons, and precipitation object features. These findings and recommendations can inform precipitation-relevant modeling and analysis over CONUS, guide future downscaling technique developments, and provide actionable information for climate impact assessment and adaptation.

Downscaling↗
DOE OSTI2026

Object-Based Evaluation of Dynamical and Statistical Downscaled Precipitation Products over CONUS

High-resolution precipitation data, generated through dynamical downscaling (DD) or statistical downscaling (SD) of global climate model output, provide critical information for regional climate assessment and adaptation planning. Most downscaling development and validation have focused on accurate gridscale precipitation construction and ignored the spatial structure of precipitation across model grids and at the event scale. However, many applications, e.g., hydrologic modeling and the analysis using the downscaled precipitation, require a reasonable representation of the spatial structure of precipitation within watersheds. Therefore, a set of standard metrics to evaluate the representation of the spatial structure of individual storms across diverse downscaled precipitation products is desired. To address this need, we conducted an object-based evaluation of precipitation in decades-long DD and SD products over the contiguous United States (CONUS). Specifically, we evaluate their ability to reproduce various features of precipitation objects in the observations: total volume, precipitation area, peak intensity, and spatial structure. Multiple metrics (bias, Perkins score, and nonparametric statistical tests) are used to quantify model performance. Our evaluation reveals notable variations in performance among individual products across different climate zones and seasons, as well as between extreme and nonextreme events. In general, most DD products exhibit balanced performance across the four precipitation object features, while SD products vary more significantly in their performance across products. Based on this comprehensive evaluation, we provide guidance on choosing downscaled products for specific regions, seasons, and precipitation object features. These findings and recommendations can inform precipitation-relevant modeling and analysis over CONUS, guide future downscaling technique developments, and provide actionable information for climate impact assessment and adaptation.

Environmental sciences↗
DOE OSTI2020

Leading magnetic fusion energy science into the big-and-fast data lane

To crack the code of unlimited clean energy from magnetic fusion, researchers collaborate among numerous facilities that are scattered around the globe. Probing hot fusion plasmas with sophisticated diagnostics, they routinely generate fast streams of high-dimensional time-series data. We present the adaptation of a production code-base for a plasma diagnostic to the big-and-fast data lane. The new code-base is used to stream measurements, made in Korea, into a Top-15 computing facility in the US for remote analysis. We discuss software and design choices made for this new HPC-enabled scientific workflow.

Kube, Ralph↗
DOE OSTI2023

Measurement of the Deeply Virtual Neutral Pion Electroproduction Cross Section off the Proton at 10.6 GeV using the CLAS12 Detector

Deeply virtual exclusive reactions provide unique channels to study both transverse and longitudinal properties of the nucleon simultaneously, allowing for a 3D image of nucleon substructure. This presentation will discuss work towards extracting an absolute cross section for one such exclusive process, deeply virtual neutral pion production, using 10.6 GeV electron scattering data off a proton target from the CLAS12 experiment in Jefferson Lab Hall B. This measurement is important as exclusive meson production has unique access to the chiral odd Generalized Parton Distributions, and is also a background for other exclusive processes such as Deeply Virtual Compton Scattering, making the determination of this cross section crucial for other exclusive analyses.

Johnston, Robert↗
DOE OSTI2023

Neutron Absorber Plate Characterization Plan for Criticality Experiments Design [Slides]

The goal of this presentation is to show the feasibility of performing a critical experiment with a B 4 C/Aluminum alloy neutron absorber plate. The motivation of this experiment is to provide integral data on modern neutron absorber product “Boralcan” by Rio Tinto. In 2020, used in about 20% of spent fuel pools in the US, and in casks for storage and transportation in the US and in Europe. The added value of this experiment: Neutron absorber plate modeling method verification: homogeneous or not, a lot of potential savings by relaxing boron loading credit limits. No available critical benchmark involving Boralcan, other boron-related experiments are relatively old. Nuclear data validation for B, C, and Al in the form of B 4 C in Al matrix.

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

Recurrent neural networks for short-term and long-term prediction of geothermal reservoirs

Accurate prediction of geothermal reservoir responses to alternative energy production scenarios is critical for optimizing the development of the underlying resources. While the conventional physics-based models offer a comprehensive prediction tool, data-driven models provide an efficient alternative to build fit-for-purpose predictive models by extracting and using the statistical patterns in the collected data to make predictions. The recurrent neural network (RNN) is a data-driven model that is commonly applied to predict time series sequences. This paper presents a variant of RNN that also utilizes the efficiency of convolutional neural networks (CNN) for the prediction of energy production from geothermal reservoirs. Specifically, a CNN–RNN architecture is developed that takes historical well controls as input (features) and their corresponding production response data as output (labels) to learn an input-output mapping that can predict the future well production responses/performance for any given future well control inputs. The model is paired with a labeling scheme to handle real field disturbances that create data gaps. In addition to the model structure, we introduce a thorough workflow for applying the model, which includes data pre-processing, feature selection, as well as different training strategies for short-term and long-term prediction. Finally, the performance and accuracy of the model are evaluated by applying it to multiple datasets, including a field reservoir model.

15 GEOTHERMAL ENERGY↗
DOE OSTI2023

Modeling Global Vegetation Gross Primary Productivity, Transpiration and Hyperspectral Canopy Radiative Transfer Simultaneously Using a Next Generation Land Surface Model—CliMA Land

Recent progress in satellite observations has provided unprecedented opportunities to monitor vegetation activity at global scale. However, a major challenge in fully utilizing remotely sensed data to constrain land surface models (LSMs) lies in inconsistencies between simulated and observed quantities. For example, gross primary productivity (GPP) and transpiration (T) that traditional LSMs simulate are not directly measurable from space, although they can be inferred from spaceborne observations using assumptions that are inconsistent with those LSMs. In comparison, canopy reflectance and fluorescence spectra that satellites can detect are not modeled by traditional LSMs. To bridge these quantities, we presented an overview of the next generation land model developed within the Climate Modeling Alliance (CliMA), and simulated global GPP, T, and hyperspectral canopy radiative transfer (RT; 400–2,500 nm for reflectance, 640–850 nm for fluorescence) at hourly time step and 1° spatial resolution using CliMA Land. CliMA Land predicts vegetation indices and outgoing radiances, including solar-induced chlorophyll fluorescence (SIF), normalized difference vegetation index (NDVI), enhanced vegetation index (EVI), and near infrared reflectance of vegetation (NIRv) for any given sun-sensor geometry. The spatial patterns of modeled GPP, T, SIF, NDVI, EVI, and NIRv correlate significantly with existing data-driven products (mean R 2 = 0.777 for 9 products). CliMA Land would be also useful in high temporal resolution simulations, for example, providing insights into when GPP, SIF, and NIRv diverge.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Compositional evidence for chondrule origins of low‐Ca pyroxenes in comet Wild 2 and a giant cluster IDP

Abstract A literature compilation of 1136 low‐Ca pyroxene compositions from chondrules from 12 primitive type 2–3 carbonaceous, ordinary and enstatite chondrite groups define unique regions on an Al 2 O 3 and Cr 2 O 3 diagram when compared to low‐Ca pyroxenes from equilibrated type 4‐6 chondrites. Measured compositions of 100 low‐Ca pyroxenes from comet Wild 2 and a giant cluster IDP of probable cometary origin are similar to each other and fall in the type 2–3 chondrite chondrule region suggesting that most of the pyroxenes likely formed in the solar nebula like conventional chondrules. The data imply that most low Ca‐pyroxenes from comet Wild 2 and the giant cluster IDP formed from igneous crystallization processes and did not experience significant thermal metamorphism, indicating that the low‐Ca pyroxenes were unlikely incorporated into large parent bodies prior to accretion in their respective comet bodies. An intriguing group of nine low‐Ca pyroxenes from comet Wild 2 with low Cr and Al that fall where type 4–6 chondrites are located are interpreted as products of condensation. The compositional data combined with previously measured oxygen isotopes on 17 low‐Ca pyroxenes support earlier conclusions that comet samples have links with carbonaceous, ordinary, and possibly enstatite chondrite groups. Our results provide additional evidence that comets accreted materials from multiple chondrule reservoirs throughout the solar nebula.

Geochemistry & Geophysics↗
DOE OSTI2021

A Possible Observation of Sigma-nn Continuum Structures and A Bound Sigma-NN State Using the (e, e 'K+) Reaction

The E12-17-003 (e, e'K+) experiment was carried out in the experimental Hall A facility of Jefferson Lab in November 2018. The experiment aimed at providing the experimental data for the unknown Lambda-n interaction by measuring the bound state or the resonance state as indicated by the HypHI experiment. The so obtained Lambda-n interaction was assumed to solve the existing charge symmetry breaking problem in the case of Lambda-N interaction. The experiment used Hall A high resolution spectrometers (both left and right spectrometers) positioned symmetrically at constant angle 13.2 deg. each. A 25 cm long aluminum cylinder filled with H-3 gas was used as a production target. The major calibration data were taken with the H target contained in an identical aluminum cylinder. The electroproduction of Lambda and Sigma^0 via p(e, e'K+)Lambda, Sigma^0 reactions was used to calibrate the absolute energy scale with the known masses of the Lambda and Sigma^0. Then by using the (e, e'K+) Sigma-reaction, two possible Lambda-nn resonance states and one NN bound state were observed. The observed states have the energy resolution about 1.6 MeV (FWHM), however, great r statistics are required to solidly confirm the observed states. The A = 3 and 4 Sigma bound states have been predicted long ago but only the A = 4 Sigma hypernucleus, that is He-4/Sigma, was found in the (K-, pi-) reaction. A careful Monte Carlo study was conducted to study the A (nuclear mass number) dependence on the missing mass resolution by using the identical experimental conditions. The simulated and experimentally obtained Lambda and Sigma^0 channels agreed within 100 keV in sigma, where sigma is the standard deviation. The intrinsic missing mass resolution of A = 3 (3/Lambda-n) resonance was predicted about sigma = 0.67 MeV with a natural width of about 0.6 MeV. However, due to the low statistics the precision does not permit sufficient constrain on the determination of the Lambda-n interaction. The reason of having such low statistics is due to the use of unoptimized Hall A system which was definitely feasible but not ideal for this experiment. In addition, the cross section was found to be much smaller than expected.

Pandey, Bishnu↗
DOE OSTI2021

CMM Sequential Analysis Program

This report documents a design agency (DA) method to evaluate coordinate measuring machine (CMM) data by constructing an algorithm that is equivalent to the production agency (PA) algorithm for processing the raw CMM data. Several refinements of the CMM analyses were implemented at both the PA and the DA to process inherent limitations of the raw data, such as the absence of measurements at the exact ends of the connector-adapter assembly (CAA) and the recovery from these limitations through (worst-case) adjustments to the the positional errors. Also, inherent errors of the CMM measurements were accommodated by introducing a guard band, which effectively lowered the tolerance so that the CMM code could not pass bad parts. The DA and the PA showed remarkable agreement in all areas of analysis. The ultimate comparison is shown in Figures 13a and 13b, where the effect of using a guard band and end adjustments to the CMM measurements were clearly shown.

42 ENGINEERING↗
DOE OSTI2022

Accessing subnuclear fluctuations and saturation with multiplicity dependent J/ψ production in p+p and p+Pb collisions

We study the production of J/ψ vector mesons as a function of charged hadron multiplicity in p+p and p+Pb collisions at LHC energies. We employ the color glass condensate framework, using running coupling Balitsky-Kovchegov evolved dipole amplitudes, to compute gluon and cc¯-pair production. We use fragmentation functions to obtain charged hadrons, and explore two different hadronization schemes for the J/ψ: non-relativistic quantum chromodynamics and the improved color evaporation model. In our framework, event-by-event multiplicity fluctuations of both hadrons and J/ψ are driven by geometric and saturation scale normalization fluctuations. Studying the correlation between J/ψ and hadron multiplicity, we show that the characteristic difference between forward and backward rapidity in p+Pb collisions is a result of different degrees of saturation probed at different rapidities. We demonstrate that experimental data on heavy-flavor production as a function of event activity provide stringent constraints on the fluctuating proton structure

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

2021 U.S. Geothermal Power Production and District Heating Market Report

This report, the 2021 U.S. Geothermal Power Production and District Heating Market Report, provides policymakers, regulators, developers, researchers, engineers, financiers, and other stakeholders with up-to-date information and data reflecting the 2019 geothermal power production and district heating markets, technologies, and trends in the United States. Analysis of the current state of the U.S. geothermal market and industry for both the power production and district heating sectors is presented, with consideration of developing power projects. Geothermal heat pumps, although a key technology in the wider use of geothermal resources, were considered outside the scope of this report. In addition, the report evaluates the impact of state and federal policy, presents current research on geothermal development, and describes future opportunities for the U.S. geothermal market and industry.

15 GEOTHERMAL ENERGY↗
DOE OSTI2023

Reaction nanoscopy of ion emission from sub-wavelength propanediol droplets

Abstract Droplets provide unique opportunities for the investigation of laser-induced surface chemistry. Chemical reactions on the surface of charged droplets are ubiquitous in nature and can provide critical insight into more efficient processes for industrial chemical production. Here, we demonstrate the application of the reaction nanoscopy technique to strong-field ionized nanodroplets of propanediol (PDO). The technique’s sensitivity to the near-field around the droplet allows for the in-situ characterization of the average droplet size and charge. The use of ultrashort laser pulses enables control of the amount of surface charge by the laser intensity. Moreover, we demonstrate the surface chemical sensitivity of reaction nanoscopy by comparing droplets of the isomers 1,2-PDO and 1,3-PDO in their ion emission and fragmentation channels. Referencing the ion yields to gas-phase data, we find an enhanced production of methyl cations from droplets of the 1,2-PDO isomer. Density functional theory simulations support that this enhancement is due to the alignment of 1,2-PDO molecules on the surface. The results pave the way towards spatio-temporal observations of charge dynamics and surface reactions on droplets.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Tencoder: tensor-product encoder-decoder architecture for predicting solutions of PDEs with variable boundary data

It is widely hoped that artificial intelligence will boost data-driven surrogate models in science and engineering. However, fundamental spatial aspects of AI surrogate models remain under-studied. We investigate the ability of neural-network surrogate models to predict solutions to PDEs under variable boundary values. We do not wish to retrain the model when the boundary values change but to make them inputs to the model and infer the solution of the PDE under those boundary conditions. Such a capability is essential to making AI-based surrogate models practically useful. While simple feedforward networks are used for one-dimensional (1D) Poisson equation, an encoder-decoder architecture with a tensor-product layer is developed for the two-dimensional Poisson equation posed on a rectangular domain. We show that it is indeed possible to infer solutions to PDEs from variable boundary data using neural networks in this relatively simple setting, and point to future directions.

Kashi, Aditya↗
DOE OSTI2024

Utah FORGE: Wells 16A(78)-32 and 16B(78)-32 Stimulation Program Report - May 2024

This dataset consists of a comprehensive report documenting the stimulation program conducted in May 2024 on Utah FORGE wells 16A(78)-32 and 16B(78)-32. It includes detailed accounts of operational and scientific objectives, stimulation methodologies, and testing outcomes. The report describes the hydraulic fracturing activities, equipment setups, proppant and fluid usage, and the execution of a nine-hour circulation test. It also includes observations from seismic and fiber optic monitoring systems, providing data on microseismic activity and fracture propagation. Detailed parameters for each stimulation stage are provided, alongside operational challenges and solutions. The dataset includes analyses of injection and production rates, well temperatures, and pressure data, supported by graphical illustrations and logs.

15 GEOTHERMAL ENERGY↗
DOE OSTI2023

SPRUCE Vegetation Phenology in Experimental Plots from Phenocam Imagery, 2015-2022

This data set consists of PhenoCam data from the SPRUCE experiment from the beginning of whole ecosystem warming (Hanson et al. 2017) in August 2015 through March 31 of 2023, with start- and end-of-season phenological transition dates derived through the end of autumn 2022. Digital cameras, or phenocams, installed in each SPRUCE enclosure track seasonal variation in vegetation “greenness”, a proxy for vegetation phenology and associated physiological activity. Three separate regions of interest (ROIs) were defined for each camera field of view, corresponding to different vegetation types and demarcating (1) Picea trees (vegetation type EN, for evergreen needleleaf); (2) Larix trees (vegetation type DN, for deciduous needleleaf); and (3) the mixed shrub layer (vegetation type SH). This data set consists of three sets of data files: 3-day summary product files: One file for each camera and each ROI (i.e. vegetation type), characterizing vegetation color at a 3-day time step Contains 35 files in *.csv format inside a compressed (*.zip) file. Transition date file: Estimates “greenness rising” (spring) and “greenness falling” (autumn) transition dates derived from the smoothed daily green chromatic coordinate (GCC) values, for each camera and each ROI (i.e. vegetation type) Contains one file in *.csv format Snow flag files: Indicate days with snow on trees or snow on ground for each experimental enclosure Contains two files in *.csv format, one for snow on trees and one for snow on ground This data set consists of two sets of companion files: Accompanying HTML files show the 90th quantiles of the mean GCC plotted together with transition dates for each vegetation type and plot. Contains three files in HTML format, one for each vegetation type One additional file in HTML format with the transition dates plotted for each vegetation type, by year R files for processing Phenocam files and flags. Contains five files in R file (*.R) format in one compressed (*.zip) file User Note: All imagery is posted in near-real time to the PhenoCam Project web page (http://phenocam.sr.unh.edu/), where it is publicly available. Scroll to “spruce” in the Gallery or link directly to the 29 SPRUCE cameras at https://tinyurl.com/y7z5mau7. The data reported here are based on the complete camera record from SPRUCE and supersedes the previously released phenocam datasets (see Related Data Sets). The estimated transition dates for previously released datasets may differ slightly (in most cases, by ±3 days or less), because following standard PhenoCam processing protocols (Richardson et al. 2018, Scientific Data), smoothing and interpolation, outlier removal, and transition date estimation are always conducted using the full data record.

SPRUCE Experiment, Marcell Experimental Forest, Sp↗
DOE OSTI2024

AmeriFlux US-OPE Optimizing Production Inputs for Economic and Environmental Enhancement (OPE3)

This is the AmeriFlux version of the carbon flux data for the site US-OPE Optimizing Production Inputs for Economic and Environmental Enhancement (OPE3). Site Description - The Optimizing Production Inputs for Economic and Environmental Enhancement (OPE3) site is located at the Beltsville Agricultural Research Center in Prince George's County, MD, and consists of a 22-ha production field, with an adjacent riparian wetland and first-order stream. Scientists from several U.S. Federal agencies, universities (foreign and domestic), and private industry have conducted multidisciplinary research at this location since 1998.

Alfieri, Joe↗