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Results for “variable selection”

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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
NASA NTRS1976

Characteristics of IR variable stars as observed from orbit

A selection of infrared variable stars was studied at wavelength 2.7 microns during 1971-1975 with data from U.S. Air Force satellites. Stars observed in this program are classified as long-period variable stars, semiregular variables, and irregular variables and are among the strongest stellar sources at this wavelength. In addition, a few new, as yet unclassified variable stars were identified during the course of the investigation. Time scales of reproducible variations range from a few weeks to a few years, and amplitudes of variation are as large as a factor of three for stars with periods of order one year. The minimum infrared flux density of a long-period star repeats accurately from one cycle to the next, whereas the maximum flux density was found to be unstable. The correlation of 2.7 micron and radio emission line data from one, well-studied long-period variable is consistent with the hypothesis that the H2O and OH circumstellar masers are saturated, if pumped by the stellar infrared flux near 2.7 microns.

Maran, S. P.↗
DOE OSTI2020

Supramolecular Tuning Enables Selective Oxygen Reduction Catalyzed by Cobalt Porphyrins for Direct Electrosynthesis of Hydrogen Peroxide

Abstract We report a supramolecular strategy for promoting the selective reduction of O 2 for direct electrosynthesis of H 2 O 2 . We utilized cobalt tetraphenylporphyrin (Co‐TPP), an oxygen reduction reaction (ORR) catalyst with highly variable product selectivity, as a building block to assemble the permanently porous supramolecular cage Co‐PB‐1(6) bearing six Co‐TPP subunits connected through twenty‐four imine bonds. Reduction of these imine linkers to amines yields the more flexible cage Co‐rPB‐1(6). Both Co‐PB‐1(6) and Co‐rPB‐1(6) cages produce 90–100 % H 2 O 2 from electrochemical ORR catalysis in neutral pH water, whereas the Co‐TPP monomer gives a 50 % mixture of H 2 O 2 and H 2 O. Bimolecular pathways have been implicated in facilitating H 2 O formation, therefore, we attribute this high H 2 O 2 selectivity to site isolation of the discrete molecular units in each supramolecule. The ability to control reaction selectivity in supramolecular structures beyond traditional host–guest interactions offers new opportunities for designing such architectures for a broader range of catalytic applications.

Smith, Peter T.↗
DOE OSTI2020

Supramolecular Tuning Enables Selective Oxygen Reduction Catalyzed by Cobalt Porphyrins for Direct Electrosynthesis of Hydrogen Peroxide

Abstract We report a supramolecular strategy for promoting the selective reduction of O 2 for direct electrosynthesis of H 2 O 2 . We utilized cobalt tetraphenylporphyrin (Co‐TPP), an oxygen reduction reaction (ORR) catalyst with highly variable product selectivity, as a building block to assemble the permanently porous supramolecular cage Co‐PB‐1(6) bearing six Co‐TPP subunits connected through twenty‐four imine bonds. Reduction of these imine linkers to amines yields the more flexible cage Co‐rPB‐1(6). Both Co‐PB‐1(6) and Co‐rPB‐1(6) cages produce 90–100 % H 2 O 2 from electrochemical ORR catalysis in neutral pH water, whereas the Co‐TPP monomer gives a 50 % mixture of H 2 O 2 and H 2 O. Bimolecular pathways have been implicated in facilitating H 2 O formation, therefore, we attribute this high H 2 O 2 selectivity to site isolation of the discrete molecular units in each supramolecule. The ability to control reaction selectivity in supramolecular structures beyond traditional host–guest interactions offers new opportunities for designing such architectures for a broader range of catalytic applications.

Smith, Peter T.↗
NASA NTRS1991

NASA/DOD Aerospace Knowledge Diffusion Research Project. Paper 17: The relationship between seven variables and the use of US government technical reports by US aerospace engineers and scientists

A study was undertaken to investigate the relationship between the use of U.S. government technical reports by U.S. aerospace engineers and scientists and seven selected sociometric variables. Data were collected by means of a self-administered mail survey which was distributed to a randomly drawn sample of American Institute of Aeronautics and Astronautics (AIAA) members. Two research questions concerning the use of conference meeting papers, journal articles, in-house technical reports, and U.S. government technical reports were investigated. Relevance, technical quality, and accessibility were found to be more important determinants of the overall extent to which U.S. government technical reports and three other information products were used by U.S. aerospace engineers and scientists.

Pinelli, Thomas E.↗
DOE OSTI2024

High allelic diversity in Arabidopsis NLRs is associated with distinct genomic features

Plants rely on Nucleotide-binding, Leucine-rich repeat Receptors (NLRs) for pathogen recognition. Highly variable NLRs (hvNLRs) show remarkable intraspecies diversity, while their low-variability paralogs (non-hvNLRs) are conserved between ecotypes. At a population level, hvNLRs provide new pathogen-recognition specificities, but the association between allelic diversity and genomic and epigenomic features has not been established. Our investigation of NLRs in Arabidopsis Col-0 has revealed that hvNLRs show higher expression, less gene body cytosine methylation, and closer proximity to transposable elements than non-hvNLRs. hvNLRs show elevated synonymous and nonsynonymous nucleotide diversity and are in chromatin states associated with an increased probability of mutation. Diversifying selection maintains variability at a subset of codons of hvNLRs, while purifying selection maintains conservation at non-hvNLRs. How these features are established and maintained, and whether they contribute to the observed diversity of hvNLRs is key to understanding the evolution of plant innate immune receptors.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1976

Monte Carlo investigation of thrust imbalance of solid rocket motor pairs

The Monte Carlo method of statistical analysis is used to investigate the theoretical thrust imbalance of pairs of solid rocket motors (SRMs) firing in parallel. Sets of the significant variables are selected using a random sampling technique and the imbalance calculated for a large number of motor pairs using a simplified, but comprehensive, model of the internal ballistics. The treatment of burning surface geometry allows for the variations in the ovality and alignment of the motor case and mandrel as well as those arising from differences in the basic size dimensions and propellant properties. The analysis is used to predict the thrust-time characteristics of 130 randomly selected pairs of Titan IIIC SRMs. A statistical comparison of the results with test data for 20 pairs shows the theory underpredicts the standard deviation in maximum thrust imbalance by 20% with variability in burning times matched within 2%. The range in thrust imbalance of Space Shuttle type SRM pairs is also estimated using applicable tolerances and variabilities and a correction factor based on the Titan IIIC analysis.

Sforzini, R. H.↗
NASA NTRS1982

Multispectral determination of soil moisture-2

Soil moisture data obtained using scatterometers, modular multispectral scanners and passive microwave radiometers were revised and grouped into four field cover types for statistical anaysis. Guymon data are grouped as alfalfa, bare, milo with rows perpendicular to the field view, and milo viewed parallel to the field of view. Dalhart data are grouped as bare combo, stubble, disked stubble, and corn field. Summary graphs combine selected analyses to compare the effects of field cover. The analysis for each of the cover types is presented in tables and graphs. Other tables show elementary statistics, correlation matrices, and single variable regressions. Selected eigenvectors and factor analyses are included and the highest correlating sensor typs for each location are summarized.

Estes, J. E.↗
NASA NTRS1995

Adaptive Finite Element Methods for Continuum Damage Modeling

The paper presents an application of adaptive finite element methods to the modeling of low-cycle continuum damage and life prediction of high-temperature components. The major objective is to provide automated and accurate modeling of damaged zones through adaptive mesh refinement and adaptive time-stepping methods. The damage modeling methodology is implemented in an usual way by embedding damage evolution in the transient nonlinear solution of elasto-viscoplastic deformation problems. This nonlinear boundary-value problem is discretized by adaptive finite element methods. The automated h-adaptive mesh refinements are driven by error indicators, based on selected principal variables in the problem (stresses, non-elastic strains, damage, etc.). In the time domain, adaptive time-stepping is used, combined with a predictor-corrector time marching algorithm. The time selection is controlled by required time accuracy. In order to take into account strong temperature dependency of material parameters, the nonlinear structural solution a coupled with thermal analyses (one-way coupling). Several test examples illustrate the importance and benefits of adaptive mesh refinements in accurate prediction of damage levels and failure time.

Min, J. B.↗
NASA NTRS2002

Variability and Predictability of Land-Atmosphere Interactions: Observational and Modeling Studies

The overall goal of this project is to increase our understanding of seasonal to interannual variability and predictability of atmosphere-land interactions. The project objectives are to: 1. Document the low frequency variability in land surface features and associated water and energy cycles from general circulation models (GCMs), observations and reanalysis products. 2. Determine what relatively wet and dry years have in common on a region-by-region basis and then examine the physical mechanisms that may account for a significant portion of the variability. 3. Develop GCM experiments to examine the hypothesis that better knowledge of the land surface enhances long range predictability. This investigation is aimed at evaluating and predicting seasonal to interannual variability for selected regions emphasizing the role of land-atmosphere interactions. Of particular interest are the relationships between large, regional and local scales and how they interact to account for seasonal and interannual variability, including extreme events such as droughts and floods. North and South America, including the Global Energy and Water Cycle Experiment Continental International Project (GEWEX GCIP), MacKenzie, and LBA basins, are currently being emphasized. We plan to ultimately generalize and synthesize to other land regions across the globe, especially those pertinent to other GEWEX projects.

Roads, John↗
NASA NTRS2014

Multi-point Adjoint-Based Design of Tilt-Rotors in a Noninertial Reference Frame

Optimization of tilt-rotor systems requires the consideration of performance at multiple design points. In the current study, an adjoint-based optimization of a tilt-rotor blade is considered. The optimization seeks to simultaneously maximize the rotorcraft figure of merit in hover and the propulsive efficiency in airplane-mode for a tilt-rotor system. The design is subject to minimum thrust constraints imposed at each design point. The rotor flowfields at each design point are cast as steady-state problems in a noninertial reference frame. Geometric design variables used in the study to control blade shape include: thickness, camber, twist, and taper represented by as many as 123 separate design variables. Performance weighting of each operational mode is considered in the formulation of the composite objective function, and a build up of increasing geometric degrees of freedom is used to isolate the impact of selected design variables. In all cases considered, the resulting designs successfully increase both the hover figure of merit and the airplane-mode propulsive efficiency for a rotor designed with classical techniques.

Jones, William T.↗
DOE OSTI2019

Solute Transport and Transformation in an Intermittent, Headwater Mountain Stream with Diurnal Discharge Fluctuations

Time-variable discharge is known to control both transport and transformation of solutes in the river corridor. Still, few studies consider the interactions of transport and transformation together. Here, we consider how diurnal discharge fluctuations in an intermittent, headwater stream control reach-scale solute transport and transformation as measured with conservative and reactive tracers during a period of no precipitation. One common conceptual model is that extended contact times with hyporheic zones during low discharge conditions allows for increased transformation of reactive solutes. Instead, we found tracer timescales within the reach were related to discharge, described by a single discharge-variable StorAge Selection function. We found that Resazurin to Resorufin (Raz-to-Rru) transformation is static in time, and apparent differences in reactive tracer were due to interactions with different ages of storage, not with time-variable reactivity. Overall we found reactivity was highest in youngest storage locations, with minimal Raz-to-Rru conversion in waters older than about 20 h of storage in our study reach. Therefore, not all storage in the study reach has the same potential biogeochemical function and increasing residence time of solute storage does not necessarily increase reaction potential of that solute, contrary to prevailing expectations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Evaluating proxies for the drivers of natural gas productivity using machine-learning models

We report the extensive development of unconventional reservoirs using horizontal drilling and multistage hydraulic fracturing has generated large volumes of reservoir characterization and production data. The analysis of this abundant data using statistical methods and advanced machine-learning (ML) techniques can provide data-driven insights into well performance. Most predictive modeling studies have focused on the impact that different well completion and stimulation strategies have on well production but have not fully exploited the available in situ rock property data to determine its role in reservoir productivity. We have used machine-learning techniques to rank rock mechanical properties, microseismic attributes, and stimulation parameters in the order of their significance for predicting natural gas production from an unconventional reservoir. The data for this study came from a hydraulically fractured well in the Marcellus Shale in Monongalia County, West Virginia. The data classes included measurements aggregated by well completion stage that included (1) gas production, (2) well-log-derived measurements including bulk density, elastic moduli, shear impedance, compressional impedance, brittleness, and gamma measurements, (3) microseismic attributes, (4) long-period long-duration (LPLD) event counts, (5) fracture counts, and (6) stimulation parameters that included the fluid injection volume and average pumping pressure. To identify observable proxies for the drivers of gas production, we evaluated five commonly used ML approaches including multivariate adaptive regression spline, Gaussian mixture model, random forest, gradient boosting, and neural network. We selected five variables including LPLD event count, seismogenic b-value, hydraulic diffusivity, cumulative moment, and fluid volume as the features most likely to impact gas productivity at the stage level in the study area. The data-driven selection of these parameters for their importance in determining gas production can help reservoir engineers design more effective hydraulic-fracture treatments in the Marcellus Shale and other similar unconventional reservoirs. Plain language summary: We use machine-learning methods and data-driven selection of reservoir parameters to rank and better understand their importance in determining gas production, which can help reservoir engineers design more effective hydraulic-fracture treatments in the Marcellus Shale and other similar unconventional reservoirs.

58 GEOSCIENCES↗
DOE OSTI2021

diyepw: A Python package for Do-It-Yourself EnergyPlus weather file generation

diyepw allows for quick and easy generation of a set of EnergyPlus weather (EPW) files for a given location over a given historical period. The user can obtain weather files using an open-source, automated workflow by simply specifying the location of interest using the World Meteorological Organization weather station ID number, and specifying a year or set of years for which to generate EPW files. Building energy modelers can use these auto-generated weather files in building performance simulations to represent the actual observed weather conditions in the location(s) of interest, based on meteorological observations obtained from the National Oceanic and Atmospheric Administration's Integrated Surface Database. Because observed weather data are not available for every meteorological variable specified in the EPW format, diyepw starts with a widely-used set of typical meteorological year (TMY) files, using them as the template to generate new EPW files by substituting in the observed values of selected meteorological variables that are known to affect building energy performance. Its output is a weather file or group of weather files that conform to the data standards associated with the EPW format so they can be used with any building performance simulation software employing EnergyPlus as its simulation engine.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2003

CFD-Based Design Optimization for Single Element Rocket Injector

To develop future Reusable Launch Vehicle concepts, we have conducted design optimization for a single element rocket injector, with overall goals of improving reliability and performance while reducing cost. Computational solutions based on the Navier-Stokes equations, finite rate chemistry, and the k-E turbulence closure are generated with design of experiment techniques, and the response surface method is employed as the optimization tool. The design considerations are guided by four design objectives motivated by the consideration in both performance and life, namely, the maximum temperature on the oxidizer post tip, the maximum temperature on the injector face, the adiabatic wall temperature, and the length of the combustion zone. Four design variables are selected, namely, H2 flow angle, H2 and O2 flow areas with fixed flow rates, and O2 post tip thickness. In addition to establishing optimum designs by varying emphasis on the individual objectives, better insight into the interplay between design variables and their impact on the design objectives is gained. The investigation indicates that improvement in performance or life comes at the cost of the other. Best compromise is obtained when improvements in both performance and life are given equal importance.

Vaidyanathan, Rajkumar↗
NASA NTRS2000

Uncertainty Analysis of Decomposing Polyurethane Foam

Sensitivity/uncertainty analyses are necessary to determine where to allocate resources for improved predictions in support of our nation's nuclear safety mission. Yet, sensitivity/uncertainty analyses are not commonly performed on complex combustion models because the calculations are time consuming, CPU intensive, nontrivial exercises that can lead to deceptive results. To illustrate these ideas, a variety of sensitivity/uncertainty analyses were used to determine the uncertainty associated with thermal decomposition of polyurethane foam exposed to high radiative flux boundary conditions. The polyurethane used in this study is a rigid closed-cell foam used as an encapsulant. Related polyurethane binders such as Estane are used in many energetic materials of interest to the JANNAF community. The complex, finite element foam decomposition model used in this study has 25 input parameters that include chemistry, polymer structure, and thermophysical properties. The response variable was selected as the steady-state decomposition front velocity calculated as the derivative of the decomposition front location versus time. An analytical mean value sensitivity/uncertainty (MV) analysis was used to determine the standard deviation by taking numerical derivatives of the response variable with respect to each of the 25 input parameters. Since the response variable is also a derivative, the standard deviation was essentially determined from a second derivative that was extremely sensitive to numerical noise. To minimize the numerical noise, 50-micrometer element dimensions and approximately 1-msec time steps were required to obtain stable uncertainty results. As an alternative method to determine the uncertainty and sensitivity in the decomposition front velocity, surrogate response surfaces were generated for use with a constrained Latin Hypercube Sampling (LHS) technique. Two surrogate response surfaces were investigated: 1) a linear surrogate response surface (LIN) and 2) a quadratic response surface (QUAD). The LHS techniques do not require derivatives of the response variable and are subsequently relatively insensitive to numerical noise. To compare the LIN and QUAD methods to the MV method, a direct LHS analysis (DLHS) was performed using the full grid and timestep resolved finite element model. The surrogate response models (LIN and QUAD) are shown to give acceptable values of the mean and standard deviation when compared to the fully converged DLHS model.

Hobbs, Michael L.↗
NASA NTRS1983

Application of advanced reliability methods to local strain fatigue analysis

When design factors are considered as random variables and the failure condition cannot be expressed by a closed form algebraic inequality, computations of risk (or probability of failure) might become extremely difficult or very inefficient. This study suggests using a simple, and easily constructed, second degree polynomial to approximate the complicated limit state in the neighborhood of the design point; a computer analysis relates the design variables at selected points. Then a fast probability integration technique (i.e., the Rackwitz-Fiessler algorithm) can be used to estimate risk. The capability of the proposed method is demonstrated in an example of a low cycle fatigue problem for which a computer analysis is required to perform local strain analysis to relate the design variables. A comparison of the performance of this method is made with a far more costly Monte Carlo solution. Agreement of the proposed method with Monte Carlo is considered to be good.

Wu, T. T.↗
NASA NTRS1984

Advanced reliability method for fatigue analysis

When design factors are considered as random variables and the failure condition cannot be expressed by a closed form algebraic inequality, computations of risk (or probability of failure) may become extremely difficult or very inefficient. This study suggests using a simple and easily constructed second degree polynomial to approximate the complicated limit state in the neighborhood of the design point; a computer analysis relates the design variables at selected points. Then a fast probability integration technique (i.e., the Rackwitz-Fiessler algorithm) can be used to estimate risk. The capability of the proposed method is demonstrated in an example of a low cycle fatigue problem for which a computer analysis is required to perform local strain analysis to relate the design variables. A comparison of the performance of this method is made with a far more costly Monte Carlo solution. Agreement of the proposed method with Monte Carlo is considered to be good.

Wu, Y.-T.↗
DOE OSTI2022

Extreme Variability Quasars in Their Various States. I. The Sample Selection and Composite SDSS Spectra

Extremely variable quasars (EVQs) are a population of sources showing large optical photometric variability revealed by time-domain surveys. The physical origin of such extreme variability is yet unclear. In this first paper of a series, we construct the largest-ever sample of 14,012 EVQs using more than 15 yr of photometric data from Sloan Digital Sky Survey (SDSS) and Pan-STARRS1. We divide the EVQs into five subsamples according to the relative brightness of each EVQ during SDSS spectroscopic observation compared with the mean brightness from photometric observations. Corresponding control samples of normal quasars are built with matched redshift, bolometric luminosity, and supermassive black hole mass. We obtain the composite SDSS spectra of EVQs in various states and their corresponding control samples. We find EVQs exhibit clearly bluer SDSS spectra during bright states and clearly redder spectra during dim states, consistent with the "bluer-when-brighter" trend widely seen in normal quasars. We further find that the line equivalent widths (EWs) of broad Mg II, C IV and [O III] (but not broad Hβ, which is yet puzzling) gradually decreases from the dim state to the bright state, similar to the so-called intrinsic Baldwin effect commonly seen in normal active galactic nuclei. In addition, EVQs have consistently larger line EWs compared with the control samples. We also see that EVQs show slight excess in the very broad line component compared with control samples. Possible explanations for the discoveries are discussed. Our findings support the hypothesis that EVQs are in the tail of a broad distribution of quasar properties but are not a distinct population.

79 ASTRONOMY AND ASTROPHYSICS↗