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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 631 records · Page 35
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Coordination environment of Si in calcium silicate hydrates, silicate minerals, and blast furnace slags: A XANES database

Understanding the silicate polymerization of calcium silicate hydrate (C-S-H) gel and its crystalline polymorphs is important in cement science. NMR can determine Si environments, but the measurement can be time-consuming and provides no spatial information. X-ray absorption near-edge structure (XANES) spectroscopy is a fast tool for probing Si coordination, possibly with spatial information. However, there lacks an understanding of Si K-edge XANES spectra of cement-related silicate phases. Here, a Si K-edge XANES spectral database of nanocrystalline C-S-H, C-S-H minerals, blast-furnace slags, and metakaolin is provided. Si K-edge of C-S-H minerals shifts to higher energies with higher polymerized Si and lower CaSi connectivity in the Si second nearest neighbor shell. Si K-edge energy shows weak correlations with Ca/Si ratio, average SiO bond length, and SiO{sub 4} distortion due to the structural complexity of silicates. The substitution of Al for Si shifts the Si K-edge of tobermorite and slags to higher energies.

36 MATERIALS SCIENCE↗
DOE OSTI2012

Investigation of the Relationship Between Gross Tumor Volume Location and Pneumonitis Rates Using a Large Clinical Database of Non-Small-Cell Lung Cancer Patients

Purpose: Studies have suggested that function may vary throughout the lung, and that patients who have tumors located in the base of the lung are more susceptible to radiation pneumonitis. The purpose of our study was to investigate the relationship between gross tumor volume (GTV) location and pneumonitis rates using a large clinical database of 547 patients with non-small-cell lung cancer. Methods and Materials: The GTV centroids of all patients were mapped onto one common coordinate system, in which the boundaries of the coordinate system were defined by the extreme points of each individual patient lung. The data were qualitatively analyzed by graphing all centroids and displaying the data according to the presence of severe pneumonitis, tumor stage, and smoking status. The centroids were grouped according to superior-inferior segments, and the pneumonitis rates were analyzed. In addition, we incorporated the GTV centroid information into a Lyman-Kutcher-Burman normal tissue complication probability model and tested whether adding spatial information significantly improved the fit of the model. Results: Of the 547 patients analyzed, 111 (20.3%) experienced severe radiation pneumonitis. The pneumonitis incidence rates were 16%, 23%, and 21% for the superior, middle, and inferior thirds of the lung, respectively. Qualitatively, the GTV centroids of nonsmokers were notably absent from the superior portion of the lung. In addition, the GTV centroids of patients who had Stage III and IV clinical staging were concentrated toward the medial edge of the lung. The comparison between the GTV centroid model and the conventional dose-volume model did not yield a statistically significant difference in model fit. Conclusions: Lower pneumonitis rates were noted for the superior portion of the lung; however the differences were not statistically significant. For our patient cohort, incorporating GTV centroid information did not lead to a statistically significant improvement in the fit of the pneumonitis model.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2012

Adjuvant Radiation Therapy and Survival for Pure Tubular Breast Carcinoma-Experience From the SEER Database

Purpose: Pure tubular carcinoma of the breast (PTCB) represents a distinct subtype of invasive ductal carcinoma (IDC) that is generally thought to be associated with better prognosis than even low-grade IDC. There has been controversy as to the role of adjuvant radiation therapy (RT) in this population. We hypothesized that adjuvant RT would demonstrate a survival improvement. Methods and Materials: We queried the Surveillance, Epidemiology and End Results database for the years 1992-2007 to identify patients with pure tubular carcinomas of the breast. Patient demographics, tumor characteristics, and surgical and RT treatments were collected. Survival analysis was performed using the Kaplan-Meier method for univariate comparisons and Cox proportional hazards modeling for multivariate comparisons, stratifying on the basis of age with a cutoff age of 65. Results: A total of 6465 patients were identified: 3624 (56.1%) patients underwent lumpectomy with RT (LUMP+RT), 1525 (23.6%) patients underwent lumpectomy alone (LUMP), 1266 (19.6%) patients received mastectomy alone (MAST), and 50 (0.8%) patients underwent mastectomy with RT (MAST+RT). When we compared the LUMP+RT and LUMP groups directly, those receiving adjuvant RT tended to be younger and were less likely to be hormone receptor-positive. Overall survival was 95% for LUMP+RT and 90% for LUMP patients at 5 years. For those 65 or younger, the absolute overall survival benefit of LUMP+RT over LUMP was 1% at 5 years and 3% at 10 years. On stratified multivariate analysis, adjuvant RT remained a significant predictor in both age groups (P=.003 in age {<=}65 and P=.04 in age >65 patients). Other significant unfavorable factors were older age and higher T stage (age >65 only). Conclusions: Since sufficiently powered large scale clinical trials are unlikely, we would recommend that adjuvant radiation be considered in PTCB patients age 65 or younger, although consideration of the small absolute survival benefit is important. Adjuvant radiation can be omitted for patients older than 65.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2013

Impact of Neoadjuvant Prostate-Specific Antigen Kinetics on Biochemical Failure and Prostate Cancer Mortality: Results From a Prospective Patient Database

Purpose: To confirm findings from an earlier report showing that neoadjuvant (NA) prostate-specific antigen (PSA) halving time (PSAHT) impacts biochemical failure (BF) rates, and to examine its association with prostate cancer-specific survival (PCSS), in a large prospective cohort of patients. Methods and Materials: A total of 502 patients were selected from a prospective database, who had localized prostate adenocarcinoma treated with 2-12 months of neoadjuvant androgen deprivation therapy (N-ADT) followed by external beam radiation therapy (EBRT) between 1994 and 2000, and had at least 2 NA PSA values. Seventy-four percent of patients had high-risk prostate cancer. Median initial PSA value, N-ADT duration, total ADT duration, and radiation therapy dose were 14 ng/mL, 6.9 months, 10.8 months, and 68 Gy, respectively. Results: At a median follow-up of 9.9 years, 210 patients have had a BF. Median PSAHT was 18 days. On univariate analysis, PSAHT was not shown to predict for BF (P=.69) or PCSS (P=.28). However, NA nadir PSA (nanPSA) and post-therapy nadir PSA (ptnPSA), when analyzed as continuous or categoric variables, predicted for BF (P<.001) and PCSS (P<.001). On multivariate analysis, nanPSA (P=.037) and ptnPSA (P<.001) continued to be significantly associated with BF. However, N-ADT duration lost significance (P=.67), and PSAHT remained a nonsignificant predictor (P=.97). For PCSS, multivariate analysis showed nanPSA (P=.049) and ptnPSA (P<.001) to be significant. Again PSAHT (P=.49) remained nonsignificant. Conclusions: In this large, prospective cohort of patients, NA PSA kinetics, expressed as PSAHT, did not predict BF or PCSS. However, nadir PSAs, in both the NA and post-therapy settings, were significant predictors of BF and PCSS. Optimization of therapy could potentially be based on early PSA response, with shorter durations of ADT for those predicted to do favorably, and intensification of therapy for those likely to have poorer outcomes.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2013

The Role of Postoperative Radiation Therapy in the Treatment of Meningeal Hemangiopericytoma—Experience From the SEER Database

Purpose: The aim of this study was to examine the effect of postoperative radiation therapy (RT) on cause-specific survival in patients with meningeal hemangiopericytomas. Methods and Materials: The Surveillance, Epidemiology, and End Results database from 1990-2008 was queried for cases of surgically resected central nervous system hemangiopericytoma. Patient demographics, tumor location, and extent of resection were included in the analysis as covariates. The Kaplan-Meier product-limit method was used to analyze cause-specific survival. A Cox proportional hazards regression analysis was conducted to determine which factors were associated with cause-specific survival. Results: The mean follow-up time is 7.9 years (95 months). There were 76 patients included in the analysis, of these, 38 (50%) underwent gross total resection (GTR), whereas the other half underwent subtotal resection (STR). Postoperative RT was administered to 42% (16/38) of the patients in the GTR group and 50% (19/38) in the STR group. The 1-year, 10-year, and 20-year cause-specific survival rates were 99%, 75%, and 43%, respectively. On multivariate analysis, postoperative RT was associated with significantly better survival (HR = 0.269, 95% CI 0.084-0.862; P=.027), in particular for patients who underwent STR (HR = 0.088, 95% CI: 0.015-0.528; P<.008). Conclusions: In the absence of large prospective trials, the current clinical decision-making of hemangiopericytoma is mostly based on retrospective data. We recommend that postoperative RT be considered after subtotal resection for patients who could tolerate it. Based on the current literature, the practical approach is to deliver limited field RT to doses of 50-60 Gy while respecting the normal tissue tolerance. Further investigations are clearly needed to determine the optimal therapeutic strategy.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2018

Phase stability and thermodynamic database validation in a set of non-equiatomic Al-Co-Cr-Fe-Nb-Ni high-entropy alloys

A series of six high-entropy alloys in non-equiatomic proportions were produced to study the phase stability across a range of compositions within the Al-Co-Cr-Fe-Nb-Ni system. Phase identification was performed using SEM, TEM, and XRD and computational tools were employed for comparison to the experimental findings. Complex microstructures were obtained following exposure at 900 °C with precipitation of Laves, NiAl, γ' and δ phases. Primary and secondary Laves populations were identified and found to become more stable with increasing Fe and Nb content. Additions of Nb promoted the formation of thin, plate-like, δ phase at the expense of the secondary Laves. The NiAl phase was observed to precipitate in the alloys with high Fe content, above the γ' solvus temperature. Overall, the thermodynamic predictions using Thermo-Calc with the TCNi8 database were accurate with respect to identifying the phase composition, while TTNi8 provided good phase stability results. Furthermore, significant differences were observed with respect to the solvus temperatures of the precipitate phases.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Scintillator Library: A database of inorganic and organic scintillator properties

The Scintillator Library (scintillator.lbl.gov) is a database of scintillator properties hosted by Lawrence Berkeley National Laboratory in a web-accessible format. It contains a variety of measured inorganic and organic scintillator properties extracted from peer-reviewed literature and manufacturer specifications. Data housed within the Scintillator Library supply an important resource for developers of scintillator-based detection systems and an aid for scientists seeking to establish connections between fundamental material and chemical properties and the associated scintillation performance.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Improved correlations of the fuel/cladding liquid penetration rate with the out-of-pile transient database

Here, utilizing data from the Out-of-Pile Transient Database (OPTD), we developed advanced correlations for the cladding liquid penetration rate in metallic fuels used in sodium-cooled fast reactors (SFRs). Based on the available OPTD data, our research highlights the key role of Pu concentration in influencing the liquid penetration behavior, showing different threshold fuel-cladding interaction temperatures, with burnup playing a substantial role, particularly in fuels with a 19% Pu concentration. The penetration rate exhibits a parabolic, diffusion-limited behavior, thereby facilitating predictions of maximum liquid penetration depth over time. These correlations are significantly more accurate, under a variety of conditions, compared to existing single-parameter models, and enhance our understanding of SFR metallic fuel behavior, promoting safer and more efficient reactor operations.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2013

Mining Software Usage with the Automatic Library Tracking Database (ALTD)

Tracking software usage is important for HPC centers, computer vendors, code developers and funding agencies to provide more efficient and targeted software support, and to forecast needs and guide HPC software effort towards the Exascale era. However, accurately tracking software usage on HPC systems has been a challenging task. In this paper, we present a tool called Automatic Library Tracking Database (ALTD) that has been developed and put in production on several Cray systems. The ALTD infrastructure prototype automatically and transparently stores information about libraries linked into an application at compilation time and also the executables launched in a batch job. We will illustrate the usage of libraries, compilers and third party software applications on a system managed by the National Institute for Computational Sciences.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Performance and wake flow characterization of a 1:8.7-scale reference USDOE MHKF1 hydrokinetic turbine to establish a verification and validation test database

As hydrokinetic turbine technologies continue to advance towards commercialization, public datasets on the performance characteristics for these devices and their flow field effects are invaluable to advance our understanding of these technologies and to validate analytical and numerical models. The Applied Research Laboratory at The Pennsylvania State University (ARL Penn State) collaborated with Sandia National Laboratories and the University of California at Davis to design, fabricate (at a 1:8.7 scale), and experimentally test a novel hydrokinetic turbine rotor design to provide an open platform and dataset for further study and development. The water tunnel test of this three-bladed, horizontal-axis rotor recorded power production, blade loading, the near-wake flow, cavitation effects, and noise generation. These state-of-the-art measurements demonstrate much of the complex physics associated with the flow through an unducted, horizontal-axis turbine, and they elucidate the performance characteristics and flow field effects at an unprecedented fidelity, accuracy and resolution. Measurements of powering coefficients (power, torque and thrust) as a function of tip-speed-ratio were performed. The dataset also includes unsteady measurements of driveshaft loading, blade strain, tower pressures, and radiated noise. Detailed flow mapping using laser Doppler velocimetry, and planar and stereo particle image velocimetry includes measurements of mean velocity and Reynolds stresses. Although the wake measurements are limited to less than half a diameter, they reveal the complex flow patterns in the near-wake structure of the rotor. The full database, available at the United States Department of Energy’s marine and hydrokinetic data repository, includes tunnel and model Computer Aided Design geometry files and inflow data sufficient for a “Model-the-Test” computational Verification and Validation study.

13 HYDRO ENERGY↗
DOE OSTI2022

Physics-guided machine learning for improved accuracy of the National Solar Radiation Database

The National Solar Radiation Database (NSRDB) provides high-resolution spatiotemporal solar irradiance data for the entire globe. The NSRDB uses a two-step Physical Solar Model (PSM) to compute the effects of clouds and other atmospheric variables on the solar radiation reaching the surface of the Earth. Physical and optical cloud properties are fundamental inputs to the PSM and are derived from the National Oceanic and Atmospheric Administration's Geostationary Operational Environmental Satellites. This paper describes recent improvements to the NSRDB driven by physics-guided machine learning methods for cloud property retrieval. The impacts of these new methods on the NSRDB irradiance data are validated using an extensive set of ground measurement sites, showing significant improvement for all sites. We report on average, the mean absolute percentage error for global horizontal irradiance and direct normal irradiance show reductions of 2.16 and 3.95 percentage points respectively for all daylight conditions, 5.92 and 17.39 percentage points respectively for cloudy conditions, and 9.00 and 22.59 percentage points respectively for gap-filled cloudy conditions. These new methods will help improve the quality and accuracy of the irradiance and cloud data in the NSRDB.

14 SOLAR ENERGY↗
DOE OSTI2023

Integration of a physics-based direct normal irradiance ($\mathrm{DNI}$) model to enhance the National Solar Radiation Database ($\mathrm{NSRDB}$)

The National Solar Radiation Database (NSRDB) is an extensively used dataset that furnishes satellite-retrieved solar resource data across the United States and an expanding list of other countries. Although the NSRDB uses a physical model to compute global horizontal irradiance (GHI), it currently employs an empirical approach based on surface observations to estimate cloudy-sky direct normal irradiance (DNI). Recently, a new physics-based approach, known as the Fast All-sky Radiation Model for Solar applications with DNI (FARMS-DNI), was developed to improve DNI forecasting. FARMS-DNI integrates direct and scattered solar radiances within the circumsolar region, resulting in improved day-ahead forecasting of DNI by incorporating it into the Weather Research and Forecasting model with Solar extensions (WRF-Solar). This study incorporates FARMS-DNI into the NSRDB algorithm to produce high-spatiotemporal-resolution DNI data from satellite data. The accuracy of the NSRDB based on FARMS-DNI is analyzed using surface observations from 19 sites situated within the National Oceanic and Atmospheric Administration (NOAA) Surface Radiation Budget (SURFRAD) and Solar Radiation (SOLRAD) networks, the University of Oregon (UO) network, the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) network, and at the National Renewable Energy Laboratory (NREL). The results demonstrate that FARMS-DNI reduces the significant overestimation of DNI in the conventional NSRDB at all surface sites, particularly in cloud overcast conditions classified using both satellite retrievals and surface observations. Consequently, this new model can effectively improve the overall accuracy of the NSRDB. The results also suggest that further improvement of DNI estimates at individual time steps, however, requires advanced satellite techniques and precise identification of clouds and retrieval of cloud properties.

14 SOLAR ENERGY↗
DOE OSTI2018

Inverse Band Structure Design via Materials Database Screening: Application to Square Planar Thermoelectrics

Electronic band structure contains a wealth of information on the electronic properties of a solid and is routinely computed. However, the more difficult problem of designing a solid with a desired band structure is an outstanding challenge. In order to address this inverse band structure design problem, we devise an approach using materials database screening with materials attributes based on the constituent elements, nominal electron count, crystal structure, and thermodynamics. Our strategy is tested in the context of thermoelectric materials, for which a targeted band structure containing both flat and dispersive components with respect to crystal momentum is highly desirable. We screen for thermodynamically stable or metastable compounds containing d 8 transition metals coordinated by anions in a square planar geometry in order to mimic the properties of recently identified oxide thermoelectrics with such a band structure. In doing so, we identify 157 compounds out of a total of over half a million candidates. After further screening based on electronic band gap and structural anisotropy, we explicitly compute the band structures for the several of the candidates in order to validate the approach. We successfully find two new oxide systems that achieve the targeted band structure. Electronic transport calculations on these two compounds, Ba 2 PdO 3 and La 4 PdO 7 , confirm promising thermoelectric power factor behavior for the compounds. This methodology is easily adapted to other targeted band structures and should be widely applicable to a variety of design problems.

36 MATERIALS SCIENCE↗
DOE OSTI2014

Fast and accurate database searches with MS-GF+Percolator

To identify peptides and proteins from the large number of fragmentation spectra in mass spectrometrybased proteomics, researches commonly employ so called database search engines. Additionally, postprocessors like Percolator have been used on the results from such search engines, to assess confidence, infer peptides and generally increase the number of identifications. A recent search engine, MS-GF+, has previously been showed to out-perform these classical search engines in terms of the number of identified spectra. However, MS-GF+ generates only limited statistical estimates of the results, hence hampering the biological interpretation. Here, we enabled Percolator-processing for MS-GF+ output, and observed an increased number of identified peptides for a wide variety of datasets. In addition, Percolator directly reports false discovery rate estimates, such as q values and posterior error probabilities, as well as p values, for peptide-spectrum matches, peptides and proteins, functions useful for the whole proteomics community.

Environmental Molecular Sciences Laboratory↗
DOE OSTI2018

Aurorasaurus database of real-time, crowd-sourced aurora data for space weather research

This work documents the details of Aurorasaurus citizen science data for the period spanning 2015 and 2016 as well as its routine data filtering protocols. Aurorasaurus citizen science data is a collection of auroral sightings submitted to the project via its website or apps and mined from social media. It is a robust data set and particularly abundant during strong geomagnetic storms when auroral precipitation models have the highest uncertainty. This data is offered to the scientific community for use through an open-access database in its raw and scientific formats, each of which is described in detail in this technical report. Furthermore, by demonstrating its scientific utility, we aim to encourage its integration into auroral research.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2013

Liquid chromatography quadrupole time-of-flight mass spectrometry characterization of metabolites guided by the METLIN database

Untargeted metabolomics provides a comprehensive platform for identifying metabolites whose levels are altered between two or more populations. By using liquid chromatography quadrupole time-of-flight mass spectrometry (LC-Q-TOF-MS), hundreds to thousands of peaks with a unique m/z ratio and retention time are routinely detected from most biological samples in an untargeted profiling experiment. Each peak, termed a metabolomic feature, can be characterized on the basis of its accurate mass, retention time and tandem mass spectral fragmentation pattern. Here a seven-step protocol is suggested for such a characterization by using the METLIN metabolite database. The protocol starts from untargeted metabolomic LC-Q-TOF-MS data that have been analyzed with the bioinformatics program XCMS, and it describes a strategy for selecting interesting features as well as performing subsequent targeted tandem MS. The seven steps described will require 2-4 h to complete per feature, depending on the compound.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

HypoRiPPAtlas as an Atlas of hypothetical natural products for mass spectrometry database search

Abstract Recent analyses of public microbial genomes have found over a million biosynthetic gene clusters, the natural products of the majority of which remain unknown. Additionally, GNPS harbors billions of mass spectra of natural products without known structures and biosynthetic genes. We bridge the gap between large-scale genome mining and mass spectral datasets for natural product discovery by developing HypoRiPPAtlas, an Atlas of hypothetical natural product structures, which is ready-to-use for in silico database search of tandem mass spectra. HypoRiPPAtlas is constructed by mining genomes using seq2ripp, a machine-learning tool for the prediction of ribosomally synthesized and post-translationally modified peptides (RiPPs). In HypoRiPPAtlas, we identify RiPPs in microbes and plants. HypoRiPPAtlas could be extended to other natural product classes in the future by implementing corresponding biosynthetic logic. This study paves the way for large-scale explorations of biosynthetic pathways and chemical structures of microbial and plant RiPP classes.

60 APPLIED LIFE SCIENCES↗