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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS1997

Automated Test Systems for Toxic Vapor Detectors

The NASA Toxic Vapor Detection Laboratory (TVDL) at the Kennedy Space Center (KSC), Florida, has been using Personal Computer based Data Acquisition and Control Systems (PCDAS) for about nine years. These systems control the generation of toxic vapors of known concentrations under controlled conditions of temperature and humidity. The PCDAS also logs the test conditions and the test article responses in data files for analysis by standard spreadsheets or custom programs. The PCDAS was originally developed to perform standardized qualification and acceptance tests in a search for a commercial off-the-shelf (COTS) toxic vapor detector to replace the hydrazine detectors for the Space Shuttle launch pad. It has since become standard test equipment for the TVDL and is indispensable in producing calibration standards for the new hydrazine monitors at the 10 part per billion (ppb) level. The standard TVDL PCDAS can control two toxic vapor generators (TVG's) with three channels each and two flow/ temperature / humidity (FTH) controllers and it can record data from up to six toxic vapor detectors (TVD's) under test and can deliver flows from 5 to 50 liters per minute (L/m) at temperatures from near zero to 50 degrees Celsius (C) using an environmental chamber to maintain the sample temperature. The concentration range for toxic vapors depends on the permeation source installed in the TVG. The PCDAS can provide closed loop control of temperature and humidity to two sample vessels, typically one for zero gas and one for the standard gas. This is required at very low toxic vapor concentrations to minimize the time required to passivate the sample delivery system. Recently, there have been several requests for information about the PCDAS by other laboratories with similar needs, both on and off KSC. The purpose of this paper is to inform the toxic vapor detection community of the current status and planned upgrades to the automated testing of toxic vapor detectors at the Kennedy Space Center.

Mattson, C. B.↗
DOE OSTI2018

Use of the Wilshire Equations to Correlate and Extrapolate Creep Data of Inconel 617 and Nimonic 105

Advanced power plant alloys must endure high temperatures and pressures for durations at which creep data are often not available, necessitating the extrapolation of creep life. A recently developed creep life extrapolation method is the Wilshire equations, with which multiple approaches can be used to increase the goodness of fit of available experimental data and improve the confidence level of calculating long-term creep strength at times well beyond the available experimental data. In this article, the Wilshire equation is used to extrapolate the creep life of Inconel 617 and Nimonic 105 to 100,000 h. The use of (a) different methods to determine creep activation energy, (b) region splitting, (c) heat- and processing-specific tensile strength data, and (d) short-duration test data were investigated to determine their effects on correlation and extrapolation. For Inconel 617, using the activation energy of lattice self-diffusion as Q C * resulted in a poor fit with the experimental data. Additionally, the error of calculated rupture times worsened when splitting regions. For Nimonic 105, the error was reduced when heat- and processing-specific tensile strengths were used. Extrapolating Inconel 617 creep strength to 100,000 h life gave conservative results when compared to values calculated by the European Creep Collaborative Committee.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Characterization of the Pulsed Radiation Environment in FREC-II at the ACRR

Ongoing tests at the Annular Core Research Reactor (ACRR) at Sandia National Laboratories aim to measure temperature and strain in materials exposed to a transient neutron-photon environment. Radiation transport and finite element analysis codes are used to predict the thermal-structural response of test articles exposed in the reactor. Strain and temperature sensors fielded on test articles provide validation data for finite element models, while active and passive radiation dosimetry provides data for MCNP models. The ACRR is able to provide pulse energies of 40 - 300 MJ per pulse with pulse times of 7 - 100 milliseconds. The pulse power is higher than many of the other research reactors due to its unique high heat capacity UO{sub 2}-BeO fuel in the central reactor. Additionally, the Fuel Ringed External Cavity (FREC-II) contains U-ZrH fuel. Future tests at the ACRR plan to field test assemblies in the Fuel Ringed External Cavity (FREC-II) and expose the test articles to the transient anisotropic radiation field experienced in the cavity. The FREC-II is coupled with the ACRR core and is used to test larger specimens, and the radiation environment can be shaped/modified to the needs of the experiment. The FREC-II was designed to provide an irradiation cavity with a strong flux gradient favoring the central cavity side. Neutron fluence also varies by height in the cavity, with a peak level slightly below the fuel rod vertical centerline. Tests were conducted in 2014 to measure the thermal-structural response of test articles exposed in the central cavity. Those tests in the central cavity fielded Nickel activation foils to record the neutron fluence at various locations around the test assembly. Foil data was later used to highlight uncertainties between thermo-structural response models and the measured temperature and strain. Studies performed in 2015 exposed large arrays of activation foils and thermo-luminescent dosimeters (TLD) in the FREC-II cavity in order to map out the neutron and photon spectrum at many locations. This type of passive measurement was shown to be too simple for performing thermo-structural simulations of a test article in response to multiple pulsed-reactor exposures. The Depleted Uranium Strain and Temperature - Enhanced Response (DUSTER-II) experiments will expose test assemblies to reactor pulses in the FREC-II cavity. To prepare for these experiments, the MCNP model will be compared with June 2016 experimental results from the pulses with the FREC-II coupled with the ACRR. These comparisons will provide an accurate model to be implemented in further studies. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2018

RETRACTED: PRMT1 mediates podocyte injury and glomerular fibrosis through phosphorylation of ERK pathway

This article has been retracted: please see Elsevier Policy on Article Withdrawal (https://www.elsevier.com/about/our-business/policies/article-withdrawal). This article has been retracted at the request of the author and the author's University, Shanghai Tongji University School of Medicine. The author conducted all the experiments and prepared the data shown in the article by herself without informing her supervisor, and subsequently, an investigative committee at the University of Tongji University School of Medicine found the article to lack original data for some figures and not to abide by local or international ethical standards for using human samples shown in Figure 1A. The author of this article would like to apologize to all affected parties.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Big data analytics in the building industry

Catalyzed by recent market, technology, and policy trends, energy data collection in the building industry is becoming more widespread. This wealth of information allows more data-driven decision-making by designers, commissioning agents, facilities staff, and energy service providers during the course of building design, operation and retrofit. The U.S. Department of Energy’s Building Performance Database (BPD) has taken advantage of this wealth of building asset- and energy-related data by collecting, cleansing, and standardizing data from across the U.S. on over 870,00 buildings, and is designed to support building benchmarking, energy efficiency project design, and buildings-related policy development with real-world data. Here, this article explores the promises and perils energy professionals are faced with when leveraging such tools, presenting example analyses for commercial and residential buildings, highlighting potential issues, and discussing solutions and best practices that will enable designers, operators and commissioning agents to make the most of ‘big data’ resources such as the BPD.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2016

Thermodynamic database for the Co-Pr system

In this article, we describe data on (1) compositions for both as-cast and heat treated specimens were summarized in Table 1; (2) the determined enthalpy of mixing of liquid phase is listed in Table 2; (3) thermodynamic database of the Co-Pr system in TDB format for the research articled entitle Chemical partitioning for the Co-Pr system: First-principles, experiments and energetic calculations to investigate the hard magnetic phase W.

36 MATERIALS SCIENCE↗
DOE OSTI2019

The Prognostic Value of a Pathologic Complete Response After Neoadjuvant Therapy for Digestive Cancer: Systematic Review and Meta-Analysis of 21 Studies

Background: Neoadjuvant therapy (NAT) before radical excision has become the preferred initial option for locally advanced digestive cancers such as esophageal cancer (EC), esophagogastric junction adenocarcinoma (EGJAC), gastric adenocarcinoma (GAC), rectal cancer (RC), and pancreatic cancer (PC). Although some patients reportedly achieve a pathologic complete response (pCR) after neoadjuvant therapy, the published data are inconsistent regarding whether pCR yields a survival benefit. The current meta-analysis was performed to assess the potential prognostic value of pCR after preoperative therapy for patients with digestive cancers. Methods: An extensive electronic search in PubMed, Web of Science, and the Cochrane Library was performed for relevant articles, from which data relative to independent correlations of pCR with overall survival (OS) and disease-free survival (DFS) were extracted for analysis. A random-effects model was used to calculate the pooled hazard ratios (HRs) with their corresponding 95% confidence intervals (CIs). Results: The study identified 6780 patients who met the inclusion and exclusion criteria. The results showed that pCR was significantly correlated with better OS (HR, 0.50; 95% CI, 0.43–0.58; P < 0.001) and DFS (HR, 0.49; 95% CI, 0.40–0.60; P < 0.001) for the digestive cancer patients who achieved pCR than for those who did not achieve pCR. Subgroup analysis showed that the correlation of pCR with OS was significant in EC (HR, 0.57; 95% CI, 0.47–0.69; P < 0.001), EGJAC/GAC (HR, 0.38; 95% CI, 0.17–0.86; P = 0.02), RC (HR, 0.48; 95% CI, 0.28–0.81; P = 0.006), and PC (HR, 0.41; 95% CI, 0.17–0.97; P = 0.04). In addition, the survival benefit for pCR patients was of similar magnitude, irrespective of the type of study, type of NAT, or ethnicity. Conclusions: A pCR is correlated with favorable survival outcomes compared with a non-pCR for digestive cancer patients after NAT.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2019

Data Mining Scientific Literature Demonstrates Use of Biological and Medical Data Across Scientific Disciplines

The Protein Data Bank (PDB) was established as the 1st open access digital data resource in biology and medicine. Today, the PDB archive contains over 140,000 atomic‐level biomolecular structures determined by crystallography, NMR spectroscopy, and 3D electron microscopy. About 20 new structures are deposited daily. PDB data is used in basic and applied research, patent applications, discovery of lifesaving drugs, product innovation, and education. About 80% of all PDB structures deposited have a “primary citation,” which is the first paper to describe the molecule and its structure and function. In turn, these primary citations have contributed to more than 1 million publications. An initial study by Clarivate Analytics on the Nucleic Acids Research publication demonstrated that PDB data drive high‐impact research in diverse scientific fields. To build on this study, we used Python programming to perform several data mining studies to understand the impact of these structures in fundamental biology, biomedicine, and energy in the scientific literature. The scientific literature database, Web of Science, tracks scientific article metrics such as the number of times cited, subject category, year published, funding source, and keywords. Web of Science data for PDB primary citations was compiled as used as the data set. Two main investigations were performed. In the first, we examined the number of citations per article (data overall and by individual subject categories) to develop “top 10 cited structures” lists and analyzed for trends. In the second investigation, we extended our data mining analysis to consider for each main subject category, the papers with the most citations and the structures they cite, and the most frequently occuring keywords. We have observed different aspects of biological data utility in various subject areas, at times in ways unanticipated from the structures' primary citation. This research demonstrates the value of biological data from the PDB by showing the diverse ways in which the data are being used. Support or Funding Information RCSB PDB is funded by a grant (DBI‐1338415) from the National Science Foundation, the National Institutes of Health, and the US Department of Energy. This abstract is from the Experimental Biology 2019 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .

Verdiguel, Natalie↗
DOE OSTI2023

Accelerating scientific discoveries through data-driven innovations

Developing artificial intelligence (AI) and machine learning (ML) methods that can accelerate scientific discoveries and advance science has become one of the important research directions for the AI/ML research community. It has been gaining increasing attention from researchers in diverse scientific areas, including biomedical science, materials science, climate science, physics, chemistry, and many others. Data-driven AI/ML innovations to enable reliable predictions and optimal decision making for scientific discoveries face several critical challenges, among which are high system complexity, large search space, incomplete knowledge, and small data, all of which demand novel strategies to effectively address them. Meeting these challenges and thereby accelerating scientific discoveries and industrial innovations, calls for research that can take full advantage of the latest advances in AI/ML to integrate data-driven techniques with scientific knowledge and is able to execute them in modern high-performance computing (HPC) environments at scale. This Patterns special collection "Accelerating scientific discoveries through data-driven innovations" features articles that showcase the promising roles of AI/ML and data-driven modeling in accelerating scientific discoveries and may inspire the next wave of data-driven innovations in various scientific domains.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Utah FORGE: Direct Shear Test Data for Investigating Seismic Precursors to Shear Failure of Fractures

This dataset includes results of direct shear tests to investigate the mechanical and geophysical response of dry and saturated fractures in Indiana limestone and Sierra White granite. Direct shear tests were performed on tensile-induced fractures in Indiana limestone and Sierra White granite in a custom water-pressurized chamber. The provided Excel files include the representative seismic wave signals and the normalized wave amplitudes of ultrasonic wave transducers. A link to the published journal article presenting the data and describing the experiment in detail is provided as well.

15 GEOTHERMAL ENERGY↗
NASA NTRS1996

Estimating the Cost of Doing a Cost Estimate

This article provides a model for estimating the cost required to do a cost estimate...Our earlier work provided data for high technology projects. This article adds data from the construction industry which validates the model over a wider range of technology.

Cost cost estimating budgets budget estimating pro↗
DOE OSTI2016

Condor : a simulation tool for flash X-ray imaging

Flash X-ray imaging has the potential to determine structures down to molecular resolution without the need for crystallization. The ability to accurately predict the diffraction signal and to identify the optimal experimental configuration within the limits of the instrument is important for successful data collection. This article introduces Condor , an open-source simulation tool to predict X-ray far-field scattering amplitudes of isolated particles for customized experimental designs and samples, which the user defines by an atomic or a refractive index model. The software enables researchers to test whether their envisaged imaging experiment is feasible, and to optimize critical parameters for reaching the best possible result. It also aims to support researchers who intend to create or advance reconstruction algorithms by simulating realistic test data. Condor is designed to be easy to use and can be either installed as a Python package or used from its web interface (http://lmb.icm.uu.se/condor). X-ray free-electron lasers have high running costs and beam time at these facilities is precious. Data quality can be substantially improved by using simulations to guide the experimental design and simplify data analysis.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS2026

Long-Term Evaluation of Landsat 9 Oli Data Product Uniformity at Focal Plane Module-Boundaries Using Earth Scenes

The uniformity performance characteristic in remote sensing data products is a metric that helps evaluate how an image accurately represents radiometric responses to geophysical variability at the Earth’s surface or within the atmosphere. These uniformity attributes are used in Earth remote sensing science applications such as investigating water quality, land-cover/land-use classifications, and crop health assessments. To ensure these applications perform effectively, it is crucial to maintain and regularly assess the uniformity of calibrated remote sensing data products. In the Landsat missions, data from the onboard radiometric reference Solar diffuser device are used as the standard approach to derive the calibration parameters, ensuring the maintenance of both absolute radiance and radiometric uniformity through quarterly updates. This publication presents an alternative approach that leverages Earth scene data to assess the on-orbit uniformity performance of the Landsat 9 (L9) mission. The analysis characterizes uniformity at a specific set of spatial positions (the focal-plane boundary zones) that are intrinsic to the Operational Land Imager (OLI) focal plane design. By employing these Earth data statistics, the article further explores the temporal trends in the radiometric uniformity results. The results shown in this article demonstrate that for pushbroom imaging design systems with staggered sensor chip focal plane architectures, the co-registered pixels, i.e., overlapping measurements of the same ground target viewed by different detectors, offer a self-contained mechanism for assessing product uniformity. Remarkably, this alternative approach achieves a level of radiometric quality comparable to that delivered by a stable, well-characterized onboard Solar diffuser calibration device. The findings demonstrate the potential and capability of such Earth scene statistics in maintaining radiometric uniformity in calibrated data products to better than 1% (1-sigma) throughout the mission’s operational lifetime.

trend↗
NASA NTRS2003

International Space Station Power System Telemetry Compared With Analytically Derived Data for Shadowed Cases

This article highlights fiscal year 2002 work performed by NASA Glenn Research Center personnel to validate algorithms and data developed in-house to predict shadowing effects on the International Space Station (ISS) solar arrays power generation. The validation effort utilized video footage and on-orbit telemetry for cases spanning a 1-yr period. Validation was required because of the uncertainty of various aspects involved in shadowing analysis. Results show that a good comparison exists between actual and predicted shadowed power system performance for solar array front and backside shadowing.

Fincannon, H. James↗
DOE OSTI2026

Thermal Performance of Spandrel Assemblies in Glazed Wall Systems: Laboratory Test Design – Challenges and Test Results

Accurate thermal performance calculation procedures for opaque spandrel areas in curtain wall and window wall systems are essential for rating systems when comparing spandrel systems. However, there is a lack of consensus in thermal modeling needed for accurately characterizing heat transfer through spandrel assemblies due to the complex arrangement of materials and structural components. Several studies indicate that conventional 2D thermal simulations may overestimate R-values by 30% compared to physical testing and 3D simulations. Detailed simulations and well-curated laboratory test data are necessary to build confidence in simulation models, which will later be used to develop correlations to improve widely used conventional 2D thermal simulations. This study aims to experimentally test heat transfer through various spandrel assemblies to validate 3D simulation models. Also, the challenges of conducting a thorough testing design along with the solutions would be documented. The team developed a design for testing spandrel assemblies, making appropriate modifications to the existing heat, air, and moisture (HAM) chamber to accommodate the testing needs. Two moveable baffles were designed and fabricated to guide airflow direction parallel to the test article surface. The data acquisition capabilities in the chamber were upgraded to add more than two hundred sensors to the climate and indoor side of the chamber. The goal is to provide a quality dataset for validating complex 3D modeling simulations, which will be used to develop improved thermal simulation techniques that more accurately represent the thermal behavior of spandrel assemblies and their integration within the building envelope. This paper will summarize the results for the boundary conditions of the testing and the temperature variation across different locations of the spandrel assemblies.

Kunwar, Niraj [ORNL] (ORCID:0000000263457652)↗
DOE OSTI2024

Classification of compact objects and model comparison using EOS knowledge

Nuclear theory and experiments, alongside astrophysical observations, constrain the equation of state (EOS) of supranuclear-dense matter. Conversely, knowledge of the EOS allows an improved interpretation of nuclear or astrophysical data. In this article, we use several established constraints on the EOS and the new NICER measurement of PSR J0437-4715 to comment on the nature of the primary companion in GW230529 and the companion of PSR J0514-4002E. We find that, with a probability of ≳84% and ≳68%, respectively, both objects are black holes. These likelihoods increase to above 95% when one uses GW170817’s remnant as an upper limit on the TOV mass. We also demonstrate that the current knowledge of the EOS substantially disfavors high masses and radii for PSR J⁢0030+0451, inferred recently when combining NICER with XMM-Newton background data and using particular hot-spot models. Lastly, we also use our obtained EOS knowledge to comment on measurements of the nuclear symmetry energy, finding that the large value predicted by the PREX-II measurement displays some mild tension with other constraints on the EOS.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

Advances in utilizing event based data structures for neutron scattering experiments

This article strives to expand on existing work to demonstrate advancements in data processing made available using event mode measurements. Most spallation neutron sources in the world have data acquisition systems that provide event recording. The new science that is enabled by utilizing event mode has only begun to be explored. In the past, these studies were difficult to perform because histograms forced dealing with either large chunks of time or a large number of files. With event based data collection, data can be explored and rebinned long after the measurement has completed. This article will review some of the principles of event data and how the method opens up new possibilities for in situ measurements, highlighting techniques that can be used to explore changes in the data. We also demonstrate the statistical basis for determining data quality and address the challenge of determining how long to measure mid-measurement. Lastly, we demonstrate a model independent method of grouping data via hierarchical clustering methods that can be used to improve calibration, reduction, and data exploration.

74 ATOMIC AND MOLECULAR PHYSICS↗