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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 595 records · Page 33
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Height Above Nearest Drainage (HAND) at Three-Meter Resolution for the State of Texas

URL: https://web.corral.tacc.utexas.edu/nfiedata/pin2flood/texas/ The current National Water Model and its Flood Inundation Mapping (FIM) service use 10-meter Height Above Nearest Drainage (HAND) hydrological terrain. In the Pin2Flood project (https://gis.tdem.texas.gov/portal/apps/storymaps/stories/72f0ec81a7654da688518f486122abed), funded by the Texas Division of Emergency Management (TDEM), ORNL computed the 3-meter HAND and associated synthetic rating curves for the State of Texas, covering 287,535 river streams (1.5km/stream) in 209 HUC8s. This archived dataset includes the HAND raster and the synthetic rating curve table for each of the 209 HUC8s in Texas. It is hosted at the Texas Advanced Computing Center (TACC). This 3-meter HAND is derived from the Fathom 3-meter DEM and NHDPlus V21 using an accelerated version of NOAA's Flood Inundation Mapping version 3 (FIM3, https://github.com/NOAA-OWP/inundation-mapping/tree/dev-fim3)

58 GEOSCIENCES↗
DOE OSTI2026

STM/S Grid LDOS Data and Analysis Code for Deciphering Majorana Zero Modes in Topological Superconductor

This dataset provides raw millikelvin scanning tunneling microscopy/spectroscopy (STM/S) grid spectroscopy data and Python analysis scripts supporting the manuscript “Deciphering Majorana Zero Modes in Topological Superconductor FeTe0.55Se0.45 with Machine-Learning-Assisted Spectral Deconvolution.” The dataset includes a raw grid spectroscopy file acquired on FeTe0.55Se0.45 at 40 mK under magnetic field, together with Python/Jupytext analysis scripts used for STM/S data processing, visualization, spectral deconvolution, Lorentzian peak fitting, feature extraction, machine-learning-assisted clustering, and figure generation. These files support the analysis of vortex-core local density of states and the identification of zero-bias-peak-related spectral components from complex in-gap states. The dataset is intended to provide a citable archival record of the data and analysis code associated with the published manuscript and to support transparency and reproducibility of the reported STM/S and machine-learning workflow.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2026

Water4Energy Tier-1 Raw Observations for TVA Seasonal Prediction, Version 1

Tier-1 (Step-1) raw observation staging collection for the Water4Energy Genesis Task-1 project on weeks-to-years prediction of Tennessee Valley temperature and precipitation. This data-only deposit includes CPC/PSL teleconnection indices, NOAA OISST monthly and ERSST sea-surface temperature, ERA5-derived daily 1° fields (t2m, tp, msl for 1980–2024), CFSv2 NMME ensemble-mean seasonal baselines, and a TVA boundary mask. The product supports seasonal teleconnection diagnostics and construction of AI ready-to-train packs published separately. Multi-terabyte hourly archives are excluded from this version.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Expanded Validation of Uranium Systems with the KENO Monte Carlo Codes and SCALE 6.2.4

The development of accident-tolerant fuel and advanced reactors fueled with high-assay low-enriched uranium has created an increased focus on systems with uranium enrichments between 5 and 20 wt % 235 U. SCALE criticality safety validation reports generated at Oak Ridge National Laboratory contain very few benchmark experiments in this range. The work presented herein is an initial investigation of expanded validation of the entire range of enrichments for uranium-fueled systems, including consideration of over 300 newly developed KENO models. The vast majority of the new models are between 4.4 wt % and 37.5 wt % enrichment and include a variety of thermal, intermediate, and mixed neutron spectra. This work finds no strong evidence of an enrichment-dependent bias, but there are indications of a spectrum-dependent bias. There are, however, only a limited number of independent experiments included at this time to distinguish intermediate enrichment effects from intermediate spectrum effects. Further work in this area is ongoing for intermediate enrichment systems. In the long run, the addition of these models to the Verified, Archived Library and Inputs and Data is planned, as funding and staff availability allow.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Calculation of neutron flux spectra of the VVER-1000 mock-up shielding benchmark with Monte Carlo code MCS utilizing mesh-based weight window

The measurements of neutron spectra compiled inside the NEA-1517/82 package from the Shielding Integral Benchmark Archive and Database (SINBAD) are chosen as benchmark cases to validate the variance reduction technique based on weight window in Monte Carlo Code MCS. A full 3D model for fixed source mode calculation with hexagonal lattice source definition is developed to simulate total of 6 points of measurements at the vicinity of the reactor and the reactor pressure vessel region. A code/code comparison against MCNP6 code is first conducted as verification element for the mesh-based weight window capability in MCS. Finally, the validation results are presented against measurements. The verification against MCNP6 code gives good agreement in addition of the insight to the importance of user understanding to determine proper reference point and reference lower weight bound for scaling which is not required in MCS code due to its capability of automatic scaling. The comparison of neutron spectra between MCS and measurements shows good agreement within 3 standard deviations for all of six detector positions.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2021

Discovery of AMPX Thermal Scattering Law Processing Issue for Solid Moderators

The 2020 edition of The International Criticality Safety Benchmark Evaluation Project (ICSBEP) Handbook includes a newly produced plastic-moderated evaluation, identified as PU-MET-MIXED-002 and referred to as PMM002. The 2021 edition should include another new plastic-moderated experiment, HEU-MET-THERM-004, referred to as HMT-004. These evaluations are of particular interest, as PMM-002 is moderated with polyethylene, and HMT-004 is moderated with polymethyl methacrylate (Lucite), allowing for investigation of the differences in the thermal scattering laws (TSLs) available for these materials. ENDF/B-VIII.0 includes newly produced data for 1 H-based scattering materials, including Lucite and yttrium hydride. Other available 1 H TSLs include polyethylene, light water, zirconium hydride. The unbound 1 H (free-gas) cross sections were also used. ENDF/B-VIII.0 also includes revisions made to the ENDF/B-VII.1 light water and polyethylene evaluations. Zirconium hydride was unchanged from ENDF/B-VII.1. As of this writing, there are no benchmarks included in the Verified, Archived Library of Inputs and Data (VALID) that are primarily moderated with any solid moderator, so validation that includes the PMM-002 and HMT-004 evaluations would expand the coverage to two new moderators. A study was undertaken at Oak Ridge National Laboratory with two purposes: to provide validation data based on systems that are primarily moderated with polyethylene and Lucite, and to demonstrate the reactivity changes that can result from use of different 1 H TSLs in these plastic-moderated systems. The first objective was mainly to test data and code for SCALE and AMPX, whereas the second objective was to provide useful data for practitioners on the potential variability of predicted $k_{eff}$ based on TSL changes. The use of an exactly correct TSL is often not possible given the materials involved (e.g., lubricants), but this study was intended to provide some indication of the magnitude of the changes among similar materials that can manifest through application of different TSLs in hydrogenous systems over a range of different neutron energy spectra. Unfortunately, the nominal $k_{eff}$ results exposed deviations between SCALE and Monte Carlo N-Particle (MCNP). Some of the results using different TSLs were also unexpected and difficult to explain. An investigation revealed a processing issue in AMPX that was caused by an ambiguous description of the data for incoherent elastic scattering in the ENDF manual. This issue is discussed in detail in a SCALE User Notification, and it affects some solid moderators, but it does not apply to 1 H bound in water. This issue highlights the importance of validating all TSLs used in safety analysis calculations. The remainder of this paper provides a more detailed examination of the results that triggered the investigation and a summary of the findings of that investigation.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Performance of the Initial Implementation of the Shift Monte Carlo Code in SCALE 6.3

The Shift Monte Carlo code will be introduced in SCALE 6.3 as an alternative to the KENO V.a, KENO-VI, and Monaco codes. Calculations were performed to establish the performance of Shift for criticality safety analyses within the criticality safety analyses sequence (CSAS) based on models in the Verified, Archived Library of Inputs and Data (VALID). This test suite contains over 600 critical experiment models covering a broad range of fissile materials and neutron energy spectra. The comparisons presented include calculated k eff values and runtime performance for serial calculations and a selection of parallel calculations. Comparisons are presented for multigroup (MG) and continuous-energy (CE) calculations for KENO V.a and KENO-VI models. Results generated with a beta version of SCALE 6.3 indicate excellent agreement in k eff values between KENO and Shift. The largest differences in the average k eff value calculated for the 15 categories of KENO V.a models are 0.00020 ± 0.00011 Δ k for MG calculations and 0.00011 ± 0.00005 Δ k for CE calculations. Similar comparisons in three categories using KENO-VI result in the largest differences for MG calculations: as 0.00004 ± 0.00003 Δ k , and -0.00002 ± 0.00003 Δ k for CE. The preliminary results also indicate that Shift is faster than KENO on a per particle basis, especially for fast spectrum systems. The uncertainty per history is also higher, however, so the Monte Carlo figure of merit is higher for KENO for thermal and intermediate spectrum systems. As expected, Shift generally has better speedup than KENO for parallel calculations, regardless of neutron energy spectrum.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Multigroup Examination of Nickel-Reflected HEU System

Critical configurations of HEU-MET-FAST-003 (HMF-003) from the International Criticality Safety Benchmark Evaluation Project Handbook were modeled for addition into the Verified, Archived Library of Inputs and Data maintained at Oak Ridge National Laboratory. HMF-003 contains models of a highly enriched uranium sphere with a spherical metal reflector of natural uranium, tungsten carbide, or nickel. For these simple models, good agreement is expected between the k eff calculated with continuous-energy (CE) and multigroup (MG) transport. However, using the CSAS5 sequence of the SCALE 6.2.4 package, the 8 in. thick nickel reflector model resulted in a difference of around 1.2 % Δ k . Results presented a clear indication of poor performance for the SCALE 252-group based on ENDF/B-VII.1 cross section library for this model. The bias was investigated over a range of nickel thickness and then compared with other MG libraries available in SCALE 6.2.4. As the nickel thickness increases, the MG k eff deviates from the CE result, confirming a performance issue with the MG calculation. Additionally, the reactions were compared between the two libraries to help determine the cause of k eff bias. Finally, additional MG libraries within SCALE 6.3 and based on ENDF/B-VII.1 and ENDF/B-VIII were reviewed. The 302-group and 1597-group result in significant improvements compared with the 252-group library. Nickel cross sections were modified from ENDF/B-VII.1 to ENDF/B-VIII. For the ENDF/B-VIII library, the deviation between the CE libraries and MG libraries is less pronounced than for ENDF/VII.1, except for the 1597-group. This examination clearly indicates the importance of validating calculations with applicable benchmark experiments and caution when using MG libraries.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

A guide to the BRAIN Initiative Cell Census Network data ecosystem

Characterizing cellular diversity at different levels of biological organization and across data modalities is a prerequisite to understanding the function of cell types in the brain. Classification of neurons is also essential to manipulate cell types in controlled ways and to understand their variation and vulnerability in brain disorders. The BRAIN Initiative Cell Census Network (BICCN) is an integrated network of data-generating centers, data archives, and data standards developers, with the goal of systematic multimodal brain cell type profiling and characterization. Emphasis of the BICCN is on the whole mouse brain with demonstration of prototype feasibility for human and nonhuman primate (NHP) brains. Here, we provide a guide to the cellular and spatial approaches employed by the BICCN, and to accessing and using these data and extensive resources, including the BRAIN Cell Data Center (BCDC), which serves to manage and integrate data across the ecosystem. We illustrate the power of the BICCN data ecosystem through vignettes highlighting several BICCN analysis and visualization tools. Finally, we present emerging standards that have been developed or adopted toward Findable, Accessible, Interoperable, and Reusable (FAIR) neuroscience. The combined BICCN ecosystem provides a comprehensive resource for the exploration and analysis of cell types in the brain.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Real-time structural motif searching in proteins using an inverted index strategy

Biochemical and biological functions of proteins are the product of both the overall fold of the polypeptide chain, and, typically, structural motifs made up of smaller numbers of amino acids constituting a catalytic center or a binding site that may be remote from one another in amino acid sequence. Detection of such structural motifs can provide valuable insights into the function(s) of previously uncharacterized proteins. Technically, this remains an extremely challenging problem because of the size of the Protein Data Bank (PDB) archive. Existing methods depend on a clustering by sequence similarity and can be computationally slow. We have developed a new approach that uses an inverted index strategy capable of analyzing >170,000 PDB structures with unmatched speed. The efficiency of the inverted index method depends critically on identifying the small number of structures containing the query motif and ignoring most of the structures that are irrelevant. Our approach (implemented at motif.rcsb.org ) enables real-time retrieval and superposition of structural motifs, either extracted from a reference structure or uploaded by the user. Herein, we describe the method and present five case studies that exemplify its efficacy and speed for analyzing 3D structures of both proteins and nucleic acids.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Effects of nitrogen fertilization and bioenergy crop type on topsoil organic carbon and total Nitrogen contents in middle Tennessee USA

Nitrogen (N) fertilization affects bioenergy crop growth and productivity and consequently carbon (C) and N contents in soil, it however remains unclear whether N fertilization and crop type individually or interactively influence soil organic carbon (SOC) and total N (TN). In a three-year long fertilization experiment in switchgrass (SG: Panicum virgatum L.) and gamagrass (GG: Tripsacum dactyloides L.) croplands in Middle Tennessee USA, soil samples (0–15cm) were collected in plots with no N input (NN), low N input (LN: 84 kg N ha -1 yr -1 in urea) and high N input (HN: 168 kg N ha -1 yr -1 in urea). Besides SOC and TN, the aboveground plant biomass was also quantified. In addition to a summary of published root morphology data based on a separated mesocosm experiment, the root leachable dissolved organic matter (DOM) of both crops was also measured using archived samples. Results showed no significant interaction of N fertilization and crop type on SOC, TN or plant aboveground biomass (ABG). Relative to NN, HN (not LN) significantly increased SOC and TN in both crops. Though SG showed a 15–68% significantly higher ABG than GG, GG showed a 9.3–12% significantly higher SOC and TN than SG. The positive linear relationships of SOC or TN with ABG were identified for SG. However, GG showed structurally more complex and less readily decomposed root DOM, a larger root volume, total root length and surface area than SG. Collectively, these suggested that intensive N fertilization could increase C and N stocks in bioenergy cropland soils but these effects may be more likely mediated by the aboveground biomass in SG and root chemistry and morphology in GG. Future studies are expected to examine the root characteristics in different bioenergy croplands under the field fertilization experiment.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Using mixed methods to construct and analyze a participatory agent-based model of a complex Zimbabwean agro-pastoral system

Complex social-ecological systems can be difficult to study and manage. Simulation models can facilitate exploration of system behavior under novel conditions, and participatory modeling can involve stakeholders in developing appropriate management processes. Participatory modeling already typically involves qualitative structural validation of models with stakeholders, but with increased data and more sophisticated models, quantitative behavioral validation may be possible as well. In this study, we created a novel agent-basedmodel applied to a specific context: Zimbabwean non-governmental organization the Muonde Trust has been collecting data on their agro-pastoral system for the last 35 years and had concerns about land-use planning and the effectiveness of management interventions in the face of climate change. We collaboratively created an agent-based model of their system using their data archive, qualitatively calibrating it to the observed behavior of the real system without tuning any parameters to match specific quantitative outputs. We then behaviorally validated the model using quantitative community-based data and conducted a sensitivity analysis to determine the relative impact of underlying parameter assumptions, Indigenous management interventions, and different rainfall variation scenarios. We found that our process resulted in a model which was successfully structurally validated and sufficiently realistic to be useful for Muonde researchers as a discussion tool. The model was inconsistently behaviorally validated, however, with some model variables matching field data better than others. We observed increased model system instability due to increasing variability in underlying drivers (rainfall), and also due to management interventions that broke feedbacks between the components of the system. Interventions that smoothed year-to-year variation rather than exaggerating it tended to improve sustainability. The Muonde trust has used the model to successfully advocate to local leaders for changes in land-use planning policy that will increase the sustainability of their system.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Predicting drug-metagenome interactions: Variation in the microbial β-glucuronidase level in the human gut metagenomes

Characterizing the gut microbiota in terms of their capacity to interfere with drug metabolism is necessary to achieve drug efficacy and safety. Although examples of drug-microbiome interactions are well-documented, little has been reported about a computational pipeline for systematically identifying and characterizing bacterial enzymes that process particular classes of drugs. The goal of our study is to develop a computational approach that compiles drugs whose metabolism may be influenced by a particular class of microbial enzymes and that quantifies the variability in the collective level of those enzymes among individuals. The present paper describes this approach, with microbial β-glucuronidases as an example, which break down drug-glucuronide conjugates and reactivate the drugs or their metabolites. We identified 100 medications that may be metabolized by β-glucuronidases from the gut microbiome. These medications included morphine, estrogen, ibuprofen, midazolam, and their structural analogues. The analysis of metagenomic data available through the Sequence Read Archive (SRA) showed that the level of β-glucuronidase in the gut metagenomes was higher in males than in females, which provides a potential explanation for the sex-based differences in efficacy and toxicity for several drugs, reported in previous studies. Our analysis also showed that infant gut metagenomes at birth and 12 months of age have higher levels of β-glucuronidase than the metagenomes of their mothers and the implication of this observed variability was discussed in the context of breastfeeding as well as infant hyperbilirubinemia. Overall, despite important limitations discussed in this paper, our analysis provided useful insights on the role of the human gut metagenome in the variability in drug response among individuals. Importantly, this approach exploits drug and metagenome data available in public databases as well as open-source cheminformatics and bioinformatics tools to predict drug-metagenome interactions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Classification of bacterial plasmid and chromosome derived sequences using machine learning

Plasmids are important genetic elements that facilitate horizonal gene transfer between bacteria and contribute to the spread of virulence and antimicrobial resistance. Most bacterial genome sequences in the public archives exist in draft form with many contigs, making it difficult to determine if a contig is of chromosomal or plasmid origin. Using a training set of contigs comprising 10,584 chromosomes and 10,654 plasmids from the PATRIC database, we evaluated several machine learning models including random forest, logistic regression, XGBoost, and a neural network for their ability to classify chromosomal and plasmid sequences using nucleotide k-mers as features. Based on the methods tested, a neural network model that used nucleotide 6-mers as features that was trained on randomly selected chromosomal and plasmid subsequences 5kb in length achieved the best performance, outperforming existing out-of-the-box methods, with an average accuracy of 89.38% ± 2.16% over a 10-fold cross validation. The model accuracy can be improved to 92.08% by using a voting strategy when classifying holdout sequences. In both plasmids and chromosomes, subsequences encoding functions involved in horizontal gene transfer—including hypothetical proteins, transporters, phage, mobile elements, and CRISPR elements—were most likely to be misclassified by the model. This study provides a straightforward approach for identifying plasmid-encoding sequences in short read assemblies without the need for sequence alignment-based tools.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Phenopacket-tools: Building and validating GA4GH Phenopackets

The Global Alliance for Genomics and Health (GA4GH) is a standards-setting organization that is developing a suite of coordinated standards for genomics. The GA4GH Phenopacket Schema is a standard for sharing disease and phenotype information that characterizes an individual person or biosample. The Phenopacket Schema is flexible and can represent clinical data for any kind of human disease including rare disease, complex disease, and cancer. It also allows consortia or databases to apply additional constraints to ensure uniform data collection for specific goals. We present phenopacket-tools, an open-source Java library and command-line application for construction, conversion, and validation of phenopackets. Phenopacket-tools simplifies construction of phenopackets by providing concise builders, programmatic shortcuts, and predefined building blocks (ontology classes) for concepts such as anatomical organs, age of onset, biospecimen type, and clinical modifiers. Phenopacket-tools can be used to validate the syntax and semantics of phenopackets as well as to assess adherence to additional user-defined requirements. The documentation includes examples showing how to use the Java library and the command-line tool to create and validate phenopackets. We demonstrate how to create, convert, and validate phenopackets using the library or the command-line application. Source code, API documentation, comprehensive user guide and a tutorial can be found at https://github.com/phenopackets/phenopacket-tools. The library can be installed from the public Maven Central artifact repository and the application is available as a standalone archive. The phenopacket-tools library helps developers implement and standardize the collection and exchange of phenotypic and other clinical data for use in phenotype-driven genomic diagnostics, translational research, and precision medicine applications.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Utah FORGE Well 16A(78)-32 Simplified Discrete Fracture Network Data

The FORGE team is making these fracture models available to researchers wanting a set of natural fractures in the FORGE reservoir for use in their own modeling work. They have been used to predict stimulation distances during hydraulic stimulation at the open toe section of well 16A(78)-32. This is a simplified DFN (discrete fracture network) dataset, that was generated using FracMan, for Utah FORGE well 16A(78)-32. A short, well-illustrated, report describing the data is also included in the provided archive file.

15 GEOTHERMAL ENERGY↗
DOE OSTI2022

Foam Fracturing Fluid Half-life Experimental Data

Foam thermal stability was studies at Temple University in collaboration with Oak Ridge National Lab (ORNL). The goal of this project is to explore thermally stable foams as hydrofracking fluid media for potential applications in enhanced geothermal system (EGS). Data generated from this project will allow researchers to explore foam as potential fracturing fluid. More than 800 data points on the half-life of foams are recorded in Excel files in the included archive resource (Half-life of Foams with Different Surfactants and Stabilizing Agents). The Excel file within each surfactant folder contains half-life data of the respective surfactant with different stabilizing agents, pressure, and temperature. The respective folders also contains Word files describing the details of the data included in the respective Excel sheet.

15 GEOTHERMAL ENERGY↗
DOE OSTI2022

Utah FORGE Phase 3 Native State Model: 2022 Update

This is the Phase 3 native state model update. The Phase 3 numerical model represents a significant subsurface volume below the FORGE site footprint. The model domain of 4.0 km x 4.0 km x 4.2 km is located approximately between depths of 4000 to 4200 meters below land surface. This data archive consists of 10 files, 4 of which are simulation input files and the remaining 6 are simulation output files. There is an included readme.txt file that contains details on each of the data files. The input files include meshes, FALCON code inputs, tabulated data of water properties, temperature values, and model boundaries. The output files include simulation outfiles and point data of modeled material properties.

15 GEOTHERMAL ENERGY↗