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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,459 records · Page 81
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Building morphologies of the USA structures database; a gauntlet feature set

In recent years there has been a proliferation of methods and data to extract building footprints from satellite imagery. However there has been very little effort to provide additional insight about these buildings beyond their spatial location and shape. Features derived from their geometries can be used to better characterize these buildings which are critical for further research and development. In this work a set of 65 unique features for every building for more than 131 million buildings covering the US has been developed. This rich feature dataset will enable researchers, policymakers and various agencies to derive additional building characteristics like height, occupancy type, and help to gain valuable and new insights of the built environment.

Environmental sciences↗
DOE OSTI2018

The Chemical and Products Database, a resource for exposure-relevant data on chemicals in consumer products

Quantitative data on product chemical composition is a necessary parameter for characterizing near-field exposure. This data set comprises reported and predicted information on more than 75,000 chemicals and more than 15,000 consumer products. The data’s primary intended use is for exposure, risk, and safety assessments. The data set includes specific products with quantitative or qualitative ingredient information, which has been publicly disclosed through material safety data sheets (MSDS) and ingredient lists. A single product category from a refined and harmonized set of categories has been assigned to each product. The data set also contains information on the functional role of chemicals in products, which can inform predictions of the concentrations in which they occur. These data will be useful to exposure and risk assessors evaluating chemical and product safety.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Summation Calculations for Reactor Antineutrino Spectra, Decay Heat and Delayed Neutron Fractions Involving New TAGS Data and Evaluated Databases

Fallot, M.; Giot, L.; Guadilla-Gomez, V.; Le Meur, L.; Porta, A.; Algora, A.; Tain, J. -L.; Briz, J. A.; Agramunt, J.; Aysto, J.; Cormon, S.; Cucoanes, A.; Eronen, T.; Fraile, L. M.; Ganogliu, E.; Gelletly, W.; Gorelov, D.; Hakala, J.; Jokinen, A.; Jordan, M. D.; Kankainen, A.; Kolhinen, V. S.; Koponen, J.; Lebois, M.; Martinez, T.; Monserrate, M.; Montaner-Piza, A.; Moore, I.; Nacher, E.; Orrigo, S. E. A.; Penttila, H.; Pohjalainen, I.; Reinikainen, J.; Reponen, M.; Rinta-Antila, S.; Rytkonen, K.; Rubio, B.; Shiba, T.; Sonnenschein, V.; Valencia, E.; Vedia, V.; Voss, A.; Weber, C.; Wilson, J. N.; Zakari-Issoufou, A. -A.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2026

Nuclear Isomer Discovery Database Released

Nuclear isomers correspond to excited states in nuclides with finite lifetimes. Here, after the discovery of isotopes–different nuclides of the same element–in 1913 by Frederick Soddy [Citation1], Otto Hahn postulated in 1921 [Citation2] that there are even different metastable states within one isotope. In analogy to chemical isomers, which are the same compounds with distinct structures, nuclear isomers have the same number of protons and neutrons but in different configurations.

Thoennessen, Michael [Michigan State University, E↗
DOE OSTI2013

ESTIMATING PHOTOMETRIC REDSHIFTS OF QUASARS VIA THE k-NEAREST NEIGHBOR APPROACH BASED ON LARGE SURVEY DATABASES

We apply one of the lazy learning methods, the k-nearest neighbor (kNN) algorithm, to estimate the photometric redshifts of quasars based on various data sets from the Sloan Digital Sky Survey (SDSS), the UKIRT Infrared Deep Sky Survey (UKIDSS), and the Wide-field Infrared Survey Explorer (WISE; the SDSS sample, the SDSS-UKIDSS sample, the SDSS-WISE sample, and the SDSS-UKIDSS-WISE sample). The influence of the k value and different input patterns on the performance of kNN is discussed. kNN performs best when k is different with a special input pattern for a special data set. The best result belongs to the SDSS-UKIDSS-WISE sample. The experimental results generally show that the more information from more bands, the better performance of photometric redshift estimation with kNN. The results also demonstrate that kNN using multiband data can effectively solve the catastrophic failure of photometric redshift estimation, which is met by many machine learning methods. Compared with the performance of various other methods of estimating the photometric redshifts of quasars, kNN based on KD-Tree shows superiority, exhibiting the best accuracy.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2013

The first astrophysical detection, terahertz spectrum, and database for the monodeuterated species of methyl formate HCOOCH{sub 2}D

Based on new measurements carried out in the laboratory from 0.77 to 1.2 THz and on a line-frequency analysis of these new data, along with previously published data, we build a line list for HCOOCH{sub 2}D that leads to its first detection in the Orion KL nebula. The observed lines, both in space and in the laboratory, involve the cis D-in-plane and trans D-out-of-plane conformations of HCOOCH{sub 2}D and the two tunneling states arising from the large-amplitude motion connecting the two trans configurations. The model used in the line position calculation accounts for both cis and trans conformations, as well as the large-amplitude motion.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

REANALYSES OF ANOMALOUS GRAVITATIONAL MICROLENSING EVENTS IN THE OGLE-III EARLY WARNING SYSTEM DATABASE WITH COMBINED DATA

We reanalyze microlensing events in the published list of anomalous events that were observed from the Optical Gravitational Lensing Experiment (OGLE) lensing survey conducted during the 2004–2008 period. In order to check the existence of possible degenerate solutions and extract extra information, we conduct analyses based on combined data from other survey and follow-up observation and consider higher-order effects. Among the analyzed events, we present analyses of eight events for which either new solutions are identified or additional information is obtained. We find that the previous binary-source interpretations of five events are better interpreted by binary-lens models. These events include OGLE-2006-BLG-238, OGLE-2007-BLG-159, OGLE-2007-BLG-491, OGLE-2008-BLG-143, and OGLE-2008-BLG-210. With additional data covering caustic crossings, we detect finite-source effects for six events including OGLE-2006-BLG-215, OGLE-2006-BLG-238, OGLE-2006-BLG-450, OGLE-2008-BLG-143, OGLE-2008-BLG-210, and OGLE-2008-BLG-513. Among them, we are able to measure the Einstein radii of three events for which multi-band data are available. These events are OGLE-2006-BLG-238, OGLE-2008-BLG-210, and OGLE-2008-BLG-513. For OGLE-2008-BLG-143, we detect higher-order effects induced by the changes of the observer’s position caused by the orbital motion of the Earth around the Sun. In addition, we present degenerate solutions resulting from the known close/wide or ecliptic degeneracy. Finally, we note that the masses of the binary companions of the lenses of OGLE-2006-BLG-450 and OGLE-2008-BLG-210 are in the brown-dwarf regime.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Selecting durable building envelope systems with machine learning assisted hygrothermal simulations database

Hygrothermal simulations provide insight into the energy performance and moisture durability of building envelope components under dynamic conditions. The inputs required for hygrothermal simulations are extensive, and carrying out simulations and analyses requires expert knowledge. An expert system, the Building Science Advisor (BSA), has been developed to predict the performance and select the energy-efficient and durable building envelope systems for different climates. The BSA consists of decision rules based on expert opinions and thousands of parametric simulation results for selected wall systems. The number of potential wall systems results in millions, too many to simulate all of them. We present how machine learning can help predict durability data, such as mold growth, while minimizing the number of simulations needed to run. The simulation results are used for training and validation of machine learning tools for predicting wall durability. We tested Artificial Neural Network (ANN) and Gradient Boosted Decision Trees (GBDT) for their applicability and model accuracy. Models developed with both methods showed adequate prediction performance (root mean square error of 0.195 and 0.209, respectively). Finally, we introduce how the information supports guidance for envelope design via an easy-to-use web-based tool that does not require the end-user to run hygrothermal simulations.

Salonvaara, Mikael↗
DOE OSTI2013

Scalable metagenomic taxonomy classification using a reference genome database

Motivation: Deep metagenomic sequencing of biological samples has the potential to recover otherwise difficult-to-detect microorganisms and accurately characterize biological samples with limited prior knowledge of sample contents. Existing metagenomic taxonomic classification algorithms, however, do not scale well to analyze large metagenomic datasets, and balancing classification accuracy with computational efficiency presents a fundamental challenge. Results: A method is presented to shift computational costs to an offline computation by creating a taxonomy/genome index that supports scalable metagenomic classification. Scalable performance is demonstrated on real and simulated data to show accurate classification in the presence of novel organisms on samples that include viruses, prokaryotes, fungi and protists. Taxonomic classification of the previously published 150 giga-base Tyrolean Iceman dataset was found to take520 h on a single node 40 core large memory machine and provide new insights on the metagenomic contents of the sample.

59 BASIC BIOLOGICAL SCIENCES↗