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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 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

CLAS Database for Studies of the Structure of Hadrons in Electromagnetic Processes

The CLAS Physics Database (CLAS DB) has been developed in collaboration between SINP at MSU and Hall B at Jefferson Lab. CLAS DB contains most experimental results on inclusive, semi-inclusive, and exclusive reactions on proton and nuclei obtained with the CLAS detector. The substantial part of these experimental results represents the only data sets available in the world. The results and analysis tools provided by the CLAS DB are of particular importance for studies of the structure of the ground and excited hadron states, offering insight into strong nonperturbative QCD dynamics, which underlie the generation of hadrons from quarks and gluons.

Chesnokov, V. V.↗
DOE OSTI2025

SlimIO: Lightweight I/O Path Design for Write Isolation in FDP-backed In-Memory Databases

In-Memory Databases (IMDBs) are widely used with HPC applications to manage transient data, often using snapshot-based persistence for backups. Redis, a representative IMDB, employs both snapshot and Write-Ahead Log (WAL) mechanisms, storing data on persistent devices via the traditional kernel I/O path. This method incurs syscall overhead, I/O contention between processes, and SSD garbage collection (GC) delays. To address these issues, we propose SlimIO, which adopts I/O passthru to minimize syscall overhead and inter-process I/O interference. Additionally, it leverages Flexible Data Placement (FDP) SSDs as backup storage to avoid performance degradation from SSD GC. Experimental results show that SlimIO reduces snapshot time by up to 25%, increases query throughput by up to 30% during non-snapshot periods, and lowers 99.9%-ile latency by up to 50%. Furthermore, it achieves a write amplification factor (WAF) of 1.00, indicating no redundant internal writes, thus extending SSD lifespan.

Lee, Sangyun [Sogang University]↗
DOE OSTI2026

Engineering Controls Database

Cyber-Informed Engineering (CIE) addresses the reality that cyber attacks on engineered systems can have consequences far beyond data loss or disruption of digital networks. When control systems are compromised, safety, reliability, and performance of the physical process itself may be threatened. This database is meant to establish clear examples and guidance for defining and applying engineered controls in CIE. It explains what engineered controls are, how they differ from information security measures, and how they are integrated into system design. The goal is to ensure that resilience is engineered into systems from the outset. Unlike cybersecurity protections that defend the digital layer, engineered controls act directly at the physical and algorithmic levels to guarantee that unacceptable consequences are prevented or limited. CIE keeps the consequences of a cyber attack from impacting the safety, reliability, and performance of engineered systems.

Source record↗
DOE OSTI2022

The Ice Particle and Aggregate Simulator (IPAS). Part II: Analysis of a Database of Theoretical Aggregates for Microphysical Parameterization

Abstract Bulk ice-microphysical models parameterize the dynamic evolution of ice particles from advection, collection, and sedimentation through a cloud layer to the surface. Frozen hydrometeors can grow to acquire a multitude of shapes and sizes, which influence the distribution of mass within cloud systems. Aggregates, defined herein as the collection of ice particles, have a variety of formations based on initial ice particle size, shape, falling orientation, and the number of particles that collect. This work focuses on using the Ice Particle and Aggregate Simulator (IPAS) as a statistical tool to repetitively collect ice crystals of identical properties to derive bulk aggregate characteristics. A database of 9 744 000 aggregates is generated with resulting properties analyzed. After 150 single ice crystals (monomers) collect, the most extreme aggregate aspect ratio calculations asymptote toward and ϕ ca ≈ 0.50 for aggregates composed of quasi-horizontally oriented and randomly oriented monomers, respectively. The results presented are largely consistent with both a previous theoretical study and estimates derived from ground-based observations from two different geographic locations. Particle falling orientation highly influences newly formed aggregate aspect ratios from the collection of particles with extreme aspect ratios; quasi-horizontally oriented particles can produce aggregate aspect ratios an order of magnitude more extreme than randomly oriented particles but can also produce near-spherical aggregates as the number of monomers comprising the aggregate reach approximately 100. Finally, a majority of collections result in aggregates that are closer to prolate than oblate spheroids.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Patterns in the Use of Axillary Operations for Patients with Node-Positive Breast Cancer After Neoadjuvant Chemotherapy: A National Cancer Database (NCDB) Analysis

Background: The American College of Surgeons Oncology Group (ACOSOG) Z1071 and Sentinel Neoadjuvant (SENTINA) trials of sentinel node biopsy for node-positive breast cancer treated with neoadjuvant chemotherapy (NAC) demonstrated false-negative rates that varied on the basis of surgical technique. This study evaluated trends in axillary operations before and after publication of these trials. Methods: This study analyzed patients from National Cancer Database (NCDB) with clinical T0 through T4, N1 and N2, M0 breast cancer who received NAC from 1 January 2012 to 31 December 2015 and sentinel lymph node biopsy (SNB) or axillary lymph node dissection (ALND). The patients were divided into the following groups: SNB, ALND, and (SNB + ALND). Results: Of the 32,036 evaluable patients identified in this study. 5565 had SNB, 19,930 had ALND, and 6541 had SNB + ALND. Compared with the ALND group, the SNB group was younger, had more invasive ductal cancers, and had lower clinical T- and N-stage disease (p < 0.001). The patients in the SNB group had a higher rate of estrogen receptor-positive and triple-negative breast cancers, but a lower rate of human epidermal growth factor receptor 2 (HER2)-positive cancer (p < 0.001). The nodal pathologic complete response (PCR) rate, defined as no residual invasive cancer, was 66.5% in the SNB group and 33.1% in the ALND group. Since 2013, the rate of ALND has decreased from 88.7 to 77.1% in both community and academic institutions (p < 0.001). Conclusion: Since publication of the ACOSOG Z1071 and SENTINA trials, the national rates of ALND in node positive breast cancer treated with NAC have decreased despite reported false-negative SNB rates and lack of prospective outcome data regarding the oncologic safety of ALND omission.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2019

Surgical Management of the Axilla in Clinically Node-Positive Patients Receiving Neoadjuvant Chemotherapy: A National Cancer Database Analysis

Background: The feasibility of sentinel lymph node biopsy (SLNB) in patients with clinically node-positive (cN+) disease who convert to clinically node-negative (cN0) disease following neoadjuvant chemotherapy (NAC) has been evaluated in several large clinical trials, but it remains unclear whether the approach has been broadly adopted in the United States. Methods: The National Cancer Database was used to identify women diagnosed with cN+ breast cancer who received NAC followed by surgery between 2012 and 2015. Trends in axillary surgery were evaluated and multivariable logistic regression analyses performed to determine factors associated with receipt of SLNB. Results: Of 12,965 women cN+ at baseline, the use of SLNB increased from 31.8% in 2012 to 49% in 2015 (p < 0.001). Using axillary pCR as a surrogate for patients who convert to cN0 following NAC, among 5127 (39.5%) ypN0 patients, SLNB increased from 38.2 to 58.4% over the study period (p < 0.001), resulting in avoidance of axillary dissection in 42.2% of ypN0 patients by 2015. In adjusted analyses, factors significantly associated with SLNB attempt included cN1 disease, age < 45 years, treatment facility type, triple-negative and HER2-positive subtypes, and year of diagnosis. In women with residual isolated tumor cells (ITCs), micrometastases, and ypN1 disease, SLNB was the only axillary procedure performed in 36.9%, 23.6%, and 13.0% of cases. Conclusions: The use of SLNB in cN+ patients receiving NAC increased significantly between 2012 and 2015. SLNB alone was performed in more than 10% of patients with ypN1 disease, 20% with micrometastases, and 35% with ITCs; the oncologic safety of omitting axillary dissection in these patients requires further evaluation.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2020

Mining a human transcriptome database for chemical modulators of NRF2

Nuclear factor erythroid-2 related factor 2 (NRF2) encoded by the NFE2L2 gene is a transcription factor critical for protecting cells from chemically-induced oxidative stress. We developed computational procedures to identify chemical modulators of NRF2 in a large database of human microarray data. A gene expression biomarker was built from statistically-filtered gene lists derived from microarray experiments in primary human hepatocytes and cancer cell lines exposed to NRF2-activating chemicals (oltipraz, sulforaphane, CDDOIm) or in which the NRF2 suppressor Keap1 was knocked down by siRNA. Directionally consistent biomarker genes were further filtered for those dependent on NRF2 using a microarray dataset from cells after NFE2L2 siRNA knockdown. The resulting 143-gene biomarker was evaluated as a predictive tool using the correlation-based Running Fisher algorithm. Using 59 gene expression comparisons from chemically-treated cells with known NRF2 activating potential, the biomarker gave a balanced accuracy of 93%. The biomarker was comprised of many well-known NRF2 target genes (AKR1B10, AKR1C1, NQO1, TXNRD1, SRXN1, GCLC, GCLM), 69% of which were found to be bound directly by NRF2 using ChIP-Seq. NRF2 activity was assessed across ~9840 microarray comparisons from ~1460 studies examining the effects of ~2260 chemicals in human cell lines. A total of 260 and 43 chemicals were found to activate or suppress NRF2, respectively, most of which have not been previously reported to modulate NRF2 activity. Using a NRF2-responsive reporter gene in HepG2 cells, we confirmed the activity of a set of chemicals predicted using the biomarker. The biomarker will be useful for future gene expression screening studies of environmentally-relevant chemicals.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Speeding genomic island discovery through systematic design of reference database composition

Background Genomic islands (GIs) are mobile genetic elements that integrate site-specifically into bacterial chromosomes, bearing genes that affect phenotypes such as pathogenicity and metabolism. GIs typically occur sporadically among related bacterial strains, enabling comparative genomic approaches to GI identification. For a candidate GI in a query genome, the number of reference genomes with a precise deletion of the GI serves as a support value for the GI. Our comparative software for GI identification was slowed by our original use of large reference genome databases (DBs). Here we explore smaller species-focused DBs. Results With increasing DB size, recovery of our reliable prophage GI calls reached a plateau, while recovery of less reliable GI calls (FPs) increased rapidly as DB sizes exceeded ~500 genomes; i.e., overlarge DBs can increase FP rates. Paradoxically, relative to prophages, FPs were both more frequently supported only by genomes outside the species and more frequently supported only by genomes inside the species; this may be due to their generally lower support values. Setting a DB size limit for our SMA ll R anked T ailored (SMART) DB design speeded runtime ~65-fold. Strictly intra-species DBs would tend to lower yields of prophages for small species (with few genomes available); simulations with large species showed that this could be partially overcome by reaching outside the species to closely related taxa, without an FP burden. Employing such taxonomic outreach in DB design generated redundancy in the DB set; as few as 2984 DBs were needed to cover all 47894 prokaryotic species. Conclusions Runtime decreased dramatically with SMART DB design, with only minor losses of prophages. We also describe potential utility in other comparative genomics projects.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Leveraging Application Data Constraints to Optimize Database-Backed Web Applications

Exploiting the relationships among data is a classical query optimization technique. As persistent data is increasingly being created and maintained programmatically, prior work that infers data relationships from data statistics misses an important opportunity. We present Coco, the first tool that identifies data relationships by analyzing database-backed applications. Once identified, Coco leverages the constraints to optimize the application's physical design and query execution. Instead of developing a fixed set of predefined rewriting rules, Coco employs an enumerate-test-verify technique to automatically exploit the discovered data constraints to improve query execution. Each resulting rewrite is provably equivalent to the original query. Using 14 real-world web applications, our experiments show that Coco can discover numerous data constraints from code analysis and improve real-world application performance significantly.

Computer Science↗
DOE OSTI2020

Flux Seasonality Metrics Database: A companion dataset for FLUXNET annual product

This dataset include standardized phenological transition dates, and derived season lengths of active, dormant and transition seasons of ecosystem carbon and energy fluxes, as reported in FLUXNET. Such metrics are unique in that they characterize the seasonal dynamics of these fluxes in their own terms rather than in reference to traditional phenology indicators that mostly relate to vegetation structural characteristics. The Flux Seasonality Metrics Database (FSMD) generated 17 standardized seasonality metrics for 4 different fluxes including gross primary productivity (GPP), ecosystem respiration (RE), latent heat (LE) and sensible heat (H) reported in FLUXNET2015 Dataset for about 200 sites and 1500 site-years of data globally. Each metric is reported as an estimate and a confidence interval, which is a function of data coverage and flux variability. We anticipate that the FSMD will facilitate new model validation exercises, and stimulate new research in global change and Earth science disciplines where land-atmosphere exchange dynamics play a central role.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Integrated Hourly Meteorological Database of 20 Meteorological Stations (1981-2022) for Watershed Function SFA Hydrological Modeling

This dataset contains (a) a script “R_met_integrated_for_modeling.R”, and (b) associated input CSV files: 3 CSV files per location to create a 5-variable integrated meteorological dataset file (air temperature, precipitation, wind speed, relative humidity, and solar radiation) for 19 meteorological stations and 1 location within Trail Creek from the modeling team within the East River Community Observatory as part of the Watershed Function Scientific Focus Area (SFA). As meteorological forcings varied across the watershed, a high-frequency database is needed to ensure consistency in the data analysis and modeling. We evaluated several data sources, including gridded meteorological products and field data from meteorological stations. We determined that our modeling efforts required multiple data sources to meet all their needs. As output, this dataset contains (c) a single CSV data file (*_1981-2022.csv) for each location (20 CSV output files total) containing hourly time series data for 1981 to 2022 and (d) five PNG files of time series and density plots for each variable per location (100 PNG files). Detailed location metadata is contained within the Integrated_Met_Database_Locations.csv file for each point location included within this dataset, obtained from Varadharajan et al., 2023 doi:10.15485/1660962. This dataset also includes (e) a file-level metadata (flmd.csv) file that lists each file contained in the dataset with associated metadata and (f) a data dictionary (dd.csv) file that contains column/row headers used throughout the files along with a definition, units, and data type. Review the (g) ReadMe_Integrated_Met_Database.pdf file for additional details on the script, methods, and structure of the dataset.The script integrates Northwest Alliance for Computational Science and Engineering’s PRISM gridded data product, National Oceanic and Atmospheric Administration’s NCEP-NCAR Reanalysis 1 gridded data product (through the `RCNEP` R package, Kemp et al., doi:10.32614/CRAN.package.RNCEP), and analytical-based calculations. Further, this script downscales the input data into hourly frequency, which is necessary for the modeling efforts.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Growing field of materials informatics: databases and artificial intelligence

The paradigm of molecular discovery in the chemical and pharmaceutical industry has followed a repetitive succession of screening and synthesis, involving the analysis of individual molecules that were both natural and produced. This ability to generate and screen libraries of compounds has found an echo in solid-state physics with the demand to explore and produce new materials for testing. In response to this demand, a golden age of materials discovery is being developed, with progress on important areas of both basic science and device applications. The confluence of theoretical and simulation methods, together with the availability of computation resources, has established the “materials genome” approach that is used by a growing number of research groups around the world with the goal of innovating on materials through systematic discovery. Here, an overview of this group of methodologies in tackling the ever-increasing complexity of computational materials science simulations is provided. Computational simulation is highlighted as a major component of rational design and synthesis of new materials with targeted properties, describing progress on databases and large data treatment. Tools for new materials discovery, including progress on the deployment of new data repositories, the implementation of high-throughput simulation approaches, and the development of artificial intelligence algorithms, are discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2021

A representation-independent electronic charge density database for crystalline materials

In addition to being the core quantity in density functional theory, the charge density can be used in many tertiary analyses in materials sciences from bonding to assigning charge to specific atoms. The charge density is data-rich since it contains information about all the electrons in the system. With increasing utilization of machine-learning tools in materials sciences, a data-rich object like the charge density can be utilized in a wide range of applications. The database presented here provides a modern and user-friendly interface for a large and continuously updated collection of charge densities as part of the Materials Project. In addition to the charge density data, we provide the theory and code for changing the representation of the charge density which should enable more advanced machine-learning studies for the broader community.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Water Atlas Features Database

Water availability was mapped across the United States and considers multiple sources of fresh water including fresh surface and groundwater, wastewater and brackish groundwater. This dataset includes cost estimates to access, treat and convey each unique source of water. This submission contains a zip file with the Water Atlas Features Database (as an ArcGIS geodatabase).

Availability↗
DOE OSTI2021

Carbon Ore Resources Database (CORD)

The Carbon Ore Resources Database (CORD) is a working collection of 399 data files associated with carbon ore resources in the United States. The collection includes spatial/non-spatial, filtered, processed, and secondary data files with original data acquisition efforts focused on domestic coal resources. The current version 1.0 is on NETL ArcGIS Enterprise.

Carbon Ore↗
DOE OSTI2019

Implementation and Verification of the Sesame Equation of State Database into Abaqus

Towards ability to perform advanced engineering calculations of shock driven processes requiring an accurate prediction of temperature inside the shock, the Sesame equation of state database has been implemented into Abaqus explicit, a finite element analysis code commonly used in the analysis community. The interface algorithm and supporting details are discussed, and results from a simple benchmark problem comparing Abaqus predictions to other previously validated calculations and published data are presented. Features of the Sesame-Abaqus interface are also discussed and a sample input file is provided for the interested user.

42 ENGINEERING↗
DOE OSTI2019

WPEC Subgroup-38 Final Report part II: Specifications for a new database structure

This is the revision of the specifications for the Generalised Nuclear Database Structure (GNDS), corresponding to GNDS version 1.9. GNDS is designed to serve as a replacement for the Evaluated Nuclear Data Format (ENDF). Although GNDS supersedes the ENDF6 format, GNDS should be viewed as a natural evolution of the ENDF-6 format, using modern computational tools to make nuclear data more accessible.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗