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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Virtual refrigerant charge sensor for variable-speed heat pumps based on feature selection

The refrigerant charge level in heat pump systems significantly impacts their energy efficiency. Virtual refrigerant charge (VRC) sensing technology has been comprehensively investigated and well-established due to its lower cost compared to physical sensors. However, the previous VRC research often relied on expert judgment and physical reasoning for their variable selection, which can potentially select redundant (or highly correlated) or insignificant features, and it is also primarily focused on single-speed systems. To address these challenges, this study proposes a VRC algorithm for variable-speed heat pumps that selects features through a rigorous feature selection method in combination with physical insights. We also propose a piecewise linear model structure segmented by subcooling temperature to accurately predict charge levels, particularly when subcooling temperatures are substantially low. The proposed algorithm was evaluated using experimental data of a residential R410A heat pump, and the performance was compared with two baseline VRC algorithms. The results are: (1) The proposed algorithm outperforms for the case with subcooling temperature less than 1 °C. (2) The proposed algorithm achieves a tested mean absolute percentage error (MAPE) of 4.23%, and improves the overall accuracy for cooling conditions by approximately 60%, compared with the two baseline algorithms. (3) The proposed algorithm uses two fewer features and improves the accuracy for undercharge cooling conditions by 68.0%, compared with baseline algorithm 2. These improvements enhance prediction accuracy and prevent overfitting, providing a more reliable refrigerant charge level prediction and helping improve the heat pump energy efficiency.

Liang, Chenjiyu↗
NASA NTRS1976

Supersonic variable-cycle engines

The evolution and current status of selected recent variable cycle engine (VCE) studies are reviewed, and how the results were influenced by airplane requirements is described. Promising VCE concepts are described, their designs are simplified and the potential benefits in terms of aircraft performance are identified. This includes range, noise, emissions, and the time and effort it may require to ensure technical readiness of sufficient depth to satisfy reasonable economic, performance, and environmental constraints. A brief overview of closely related, ongoing technology programs in acoustics and exhaust emissions is also presented. Realistic technology advancements in critical areas combined with well matched aircraft and selected VCE concepts can lead to significantly improved economic and environmental performance relative to first generation SST predictions.

Willis, E. A.↗
NASA NTRS1998

Charting Multidisciplinary Team External Dynamics Using a Systems Thinking Approach

Using the formalism provided by the Systems Thinking approach, the dynamics present when operating multidisciplinary teams are examined in the context of the NASA Langley Research and Technology Group, an R&D organization organized along functional lines. The paper focuses on external dynamics and examines how an organization creates and nurtures the teams and how it disseminates and retains the lessons and expertise created by the multidisciplinary activities. Key variables are selected and the causal relationships between the variables are identified. Five "stories" are told, each of which touches on a different aspect of the dynamics. The Systems Thinking Approach provides recommendations as to interventions that will facilitate the introduction of multidisciplinary teams and that therefore will increase the likelihood of performing successful multidisciplinary developments. These interventions can be carried out either by individual researchers, line management or program management.

Barthelemy, Jean-Francois↗
NASA NTRS2013

The Galex Time Domain Survey. I. Selection And Classification of Over a Thousand Ultraviolet Variable Sources

We present the selection and classification of over a thousand ultraviolet (UV) variable sources discovered in approximately 40 deg(exp 2) of GALEX Time Domain Survey (TDS) NUV images observed with a cadence of 2 days and a baseline of observations of approximately 3 years. The GALEX TDS fields were designed to be in spatial and temporal coordination with the Pan-STARRS1 Medium Deep Survey, which provides deep optical imaging and simultaneous optical transient detections via image differencing. We characterize the GALEX photometric errors empirically as a function of mean magnitude, and select sources that vary at the 5 sigma level in at least one epoch. We measure the statistical properties of the UV variability, including the structure function on timescales of days and years. We report classifications for the GALEX TDS sample using a combination of optical host colors and morphology, UV light curve characteristics, and matches to archival X-ray, and spectroscopy catalogs. We classify 62% of the sources as active galaxies (358 quasars and 305 active galactic nuclei), and 10% as variable stars (including 37 RR Lyrae, 53 M dwarf flare stars, and 2 cataclysmic variables). We detect a large-amplitude tail in the UV variability distribution for M-dwarf flare stars and RR Lyrae, reaching up to absolute value(Δm) = 4.6 mag and 2.9 mag, respectively. The mean amplitude of the structure function for quasars on year timescales is five times larger than observed at optical wavelengths. The remaining unclassified sources include UV-bright extragalactic transients, two of which have been spectroscopically confirmed to be a young core-collapse supernova and a flare from the tidal disruption of a star by dormant supermassive black hole. We calculate a surface density for variable sources in the UV with NUV less than 23 mag and absolute value(Δm) greater than 0.2 mag of approximately 8.0, 7.7, and 1.8 deg(exp −2) for quasars, active galactic nuclei, and RR Lyrae stars, respectively. We also calculate a surface density rate in the UV for transient sources, using the effective survey time at the cadence appropriate to each class, of approximately 15 and 52 deg(exp −2 yr−1 for M dwarfs and extragalactic transients, respectively.

Gezari, S.↗
NASA NTRS1979

NLSCIDNT user's guide maximum likehood parameter identification computer program with nonlinear rotorcraft model

A nonlinear, maximum likelihood, parameter identification computer program (NLSCIDNT) is described which evaluates rotorcraft stability and control coefficients from flight test data. The optimal estimates of the parameters (stability and control coefficients) are determined (identified) by minimizing the negative log likelihood cost function. The minimization technique is the Levenberg-Marquardt method, which behaves like the steepest descent method when it is far from the minimum and behaves like the modified Newton-Raphson method when it is nearer the minimum. Twenty-one states and 40 measurement variables are modeled, and any subset may be selected. States which are not integrated may be fixed at an input value, or time history data may be substituted for the state in the equations of motion. Any aerodynamic coefficient may be expressed as a nonlinear polynomial function of selected 'expansion variables'.

Source record↗
NASA NTRS1993

Bounds on internal state variables in viscoplasticity

A typical viscoplastic model will introduce up to three types of internal state variables in order to properly describe transient material behavior; they are as follows: the back stress, the yield stress, and the drag strength. Different models employ different combinations of these internal variables--their selection and description of evolution being largely dependent on application and material selection. Under steady-state conditions, the internal variables cease to evolve and therefore become related to the external variables (stress and temperature) through simple functional relationships. A physically motivated hypothesis is presented that links the kinetic equation of viscoplasticity with that of creep under steady-state conditions. From this hypothesis one determines how the internal variables relate to one another at steady state, but most importantly, one obtains bounds on the magnitudes of stress and back stress, and on the yield stress and drag strength.

Freed, Alan D.↗
NASA NTRS1993

Rapid oscillations in cataclysmic variables. X - TW Pictoris (=H 0534-581)

Photometry of the X-ray-selected cataclysmic variable TW Pictoris (=H 0534-581) reveals a periodic signal at P = 6.1 hr, which is approximately the orbital period of the binary. In addition, a highly probable signal is found at P = 119.76 +/- 0.09 min. Coupled with the high excitation, the high L(x)/L(opt) ratio, and the probable detection of a similar spectroscopic period, this makes it likely that the star belongs to the 'DQ Herculis' class of cataclysmic variable in which the stable short period is the spin period of an accreting magnetic white dwarf. Theory suggests that TW Pic is a particularly attractive candidate for showing circular polarization at visual or near-infrared wavelengths.

Patterson, Joseph↗
NASA NTRS1994

The selective use of functional optical variables in the control of forward speed

Previous work on the perception and control of simulated vehicle speed has examined the contributions of optical flow rate (angular visual speed) and texture, or edge rate (frequency of passing terrain objects or markings) on the perception and control of forward speed. However, these studies have not examined the ability to selectively use edge rate or flow rate. The two studies presented here show that this ability is far greater for pilots than non-pilots, as would be expected since pilots must control vehicular speed over a variety of altitudes where flow rates change independently of forward speed. These studies also show that this ability to selectively use these variables is linked to the visual contextual information about the relative validity (linkage with speed) of the two variables. Subjective judgment data also indicated that awareness of altitude and ground texture density did not mediate ground speed awareness.

Johnson, Walter W.↗
NASA NTRS1977

Probabilistic fracture mechanics and optimum fracture control of the solid rocket motor case of the shuttle

Development of a procedure for the reliability analysis of the solid rocket motor case of the space shuttle is described. The analysis is based on probabilistic fracture mechanics and consideration of a probability distribution for the initial flaw sizes. The reliability analysis can be used to select design variables, such as the thickness of the SRM case, projected design life and proof factor, on the basis of minimum expected cost and specified reliability bounds. Effects of fracture control plans such as the non-destructive inspections and the material erosion between missions can also be considered in the developed methodology for selection of design variables. The reliability-based procedure can be easily modified to consider other similar structures and different fracture control plans.

Hanagud, S.↗
DOE OSTI2024

Estimating Sparse Direct Effects in Multivariate Regression With the Spike-and-Slab LASSO

The multivariate regression interpretation of the Gaussian chain graph model simultaneously parametrizes (i) the direct effects of p predictors on q outcomes and (ii) the residual partial covariances between pairs of outcomes. We introduce a new method for fitting sparse versions of these models with spike-and-slab LASSO (SSL) priors. We develop an Expectation Conditional Maximization algorithm to obtain sparse estimates of the p × q matrix of direct effects and the q × q residual precision matrix. Our algorithm iteratively solves a sequence of penalized maximum likelihood problems with self-adaptive penalties that gradually filter out negligible regression coefficients and partial covariances. Because it adaptively penalizes individual model parameters, our method is seen to outperform fixed-penalty competitors on simulated data. We establish the posterior contraction rate for our model, buttressing our method’s excellent empirical performance with strong theoretical guarantees. Using our method, we estimated the direct effects of diet and residence type on the composition of the gut microbiome of elderly adults.

EM algorithm↗
NASA NTRS1969

Analysis of urban residential environments using color infrared aerial photography: An examination of socioeconomic variables and physical characteristics of selected areas in the Los Angeles basin, with addendum: An application of the concepts of the Los Angeles residential environment study to the Ontario-Upland region of California

Aerial photographs taken with color infrared film were used to differentiate various types of residential areas in the Los Angeles basin, using characteristics of the physical environment which vary from one type of residential area to another. Residential areas of varying quality were classified based on these characteristics. Features of the physical environment, identifiable on CIR aerial photography were examined to determine which of these are the best indicators of quality of residential areas or social areas, as determined by the socioeconomic characteristics of the inhabitants of the selected areas. Association between several physical features and the socioeconomic variables was found to exist.

Mullens, R. H., Jr.↗
NASA NTRS2012

Characterization of New Hard X-ray Cataclysmic Variables

Aims. We aim at characterizing a sample of nine new hard X-ray selected Cataclysmic Variable (CVs), to unambiguously identify them as magnetic systems of the Intermediate Polar (IP) type. Methods. We performed detailed timing and spectral analysis by using X-ray, and simultaneous UV and optical data collected by XMM−Newton, complemented with hard X-ray data provided by INTEGRAL and Swift. The pulse arrival time were used to estimate the orbital periods. The broad band X-ray spectra were fitted using composite models consisting of different absorbing columns and emission components. Results. Strong X-ray pulses at the White Dwarf (WD) spin period are detected and found to decrease with energy. Most sources are spin-dominated systems in the X-rays, though four are beat dominated at optical wavelengths. We estimated the orbital period in all system (except for IGR J16500-3307), providing the first estimate for IGRJ08390-4833, IGRJ18308-1232, and IGR J18173-2509. All X-ray spectra are multi-temperature. V2069 Cyg and RX J0636+3535 poses a soft X-ray optically thick component at kT approx. 80 eV. An intense K (sub alpha) Fe line at 6.4 keV is detected in all sources. An absorption edge at 0.76 keV from OVII is detected in IGR J08390-4833. The WD masses and lower limits to the accretion rates are also estimated. Conclusions. We found all sources to be IPs. IGR J08390-4833, V2069 Cyg, and IGR J16500-3307 are pure disc accretors, while IGR J18308-1232, IGR J1509-6649, IGR J17195-4100, and RX J0636+3535 display a disc-overflow accretion mode. All sources show a temperature gradient in the post-shock regions and a highly absorbed emission from material located in the pre-shock flow which is also responsible for the X-ray pulsations. Reflection at the WD surface is likely the origin of the fluorescent iron line. There is an increasing evidence for the presence of a warm absorber in IPs, a feature that needs future exploration. The addition of two systems to the subgroup of soft X-ray IPs confirms a relatively large (∼ 30%) incidence.

hard X-ray↗
DOE OSTI2020

The STRong lensing Insights into the Dark Energy Survey (STRIDES) 2017/2018 follow-up campaign: discovery of 10 lensed quasars and 10 quasar pairs

Here, we report the results of the STRong lensing Insights into the Dark Energy Survey (STRIDES) follow-up campaign of the late 2017/early 2018 season. We obtained spectra of 65 lensed quasar candidates with ESO Faint Object Spectrograph and Camera 2 on the NTT and Echellette Spectrograph and Imager on Keck, confirming 10 new lensed quasars and 10 quasar pairs. Eight lensed quasars are doubly imaged with source redshifts between 0.99 and 2.90, one is triply imaged (DESJ0345-2545, z = 1.68), and one is quadruply imaged (quad: DESJ0053-2012, z = 3.8). Singular isothermal ellipsoid models for the doubles, based on high-resolution imaging from SAMI on Southern Astrophysical Research Telescope or Near InfraRed Camera 2 on Keck, give total magnifications between 3.2 and 5.6, and Einstein radii between 0.49 and 1.97 arcsec. After spectroscopic follow-up, we extract multi-epoch grizY photometry of confirmed lensed quasars and contaminant quasar + star pairs from DES data using parametric multiband modelling, and compare variability in each system’s components. By measuring the reduced χ 2 associated with fitting all epochs to the same magnitude, we find a simple cut on the less variable component that retains all confirmed lensed quasars, while removing 94 per cent of contaminant systems. Based on our spectroscopic follow-up, this variability information improves selection of lensed quasars and quasar pairs from 34-45 per cent to 51–70 per cent, with most remaining contaminants being star-forming galaxies. Using mock lensed quasar light curves we demonstrate that selection based only on variability will over-represent the quad fraction by 10 per cent over a complete DES magnitude-limited sample, explained by the magnification bias and hence lower luminosity/more variable sources in quads.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1993

A seven-year northern sky survey of Ap stars for rapid variability

A high-speed photometric survey of 120 Ap stars in the northern sky, has been conducted, between 1985 and 1991, in order to search for rapid variability. Stars of spectral types, namely from B8 to F4, have been selected for the survey. The selected pulsational variable stars occupy the hotter regions of the instability strip of the Hertzsprung-Russel diagram. Noted is the absence of pulsations in the hotter B8-A3 Ap stars; this does not, however, preclude the existence of pulsations, since HD 218495 was recently discovered to be a rapidly oscillating Ap (roAp) star. The primary result of this study is that various combinations of photometric indices, while pointing towards roAp stars having the characteristic signatures of cool, SrCrEu stars, still fail to isolate the roAp phenomenon from similar nonpulsating Ap stars. Color-magnitude and color-color diagrams are presented in order to complete this survey.

Nelson, Matthew J.↗
DOE OSTI2022

Training data selection for event classification in a highly variable environment

A problem of interest for nuclear nonproliferation is monitoring activities at nuclear facilities, where proliferation events may only take place a few times and often under variable conditions. Machine learning has revolutionized data analytics by enabling the use of measurable signatures to generate predictive models of facility operations. However, traditional methods for training these models require large, reliable data sets with labeled observations, a challenge for nonproliferation. Highly variable conditions further complicate this as events from training data may have occurred in conditions quite different from the event of interest. Our hypothesis is that when events occur in a highly variable environment, careful training data selection for each test event could outperform the standard approach of using all available training data. We developed a method to optimize training data selection for the given test event and applied it to predicting the power level of the High Flux Isotope Reactor (HFIR) at Oak Ridge National Laboratory. In this study, the reactor startup exhibits variability between occurrences due to natural variability in environmental conditions and operational procedures. Using a combination of analysis techniques, a similitude assessment was performed on data collected from HFIR to isolate clusters that were optimal for training a predictive model. Concepts such as dynamic time warping and Jaccard similarity were used in conjunction with clustering analysis. In order to validate this approach, the model was trained on every combination of unique training events and the predictive performance was compared to the performance using a subset of the training data selected by isolated clusters found through the similitude assessment.

Iyer, A↗
NASA NTRS2019

Discerning the Impact of Powder Feedstock Variability on Structure, Property, and Performance of Selective Laser Melted Alloy 718: A Principal Component Analysis (PCA) of Feedstock Variability

Extensive mechanical, chemical and microstructural analyses were conducted on additively manufactured Alloy 718 to characterize powders from multiple vendors to determine the effects of variations observed in the powders had on the consolidated material. With over 190 variables examined, it was necessary to reduce the number of variables and identify the variables and classes of variables that had the greatest effect. Principle Component Analysis (PCA) was used to reduce the number of variable to effectively 12 while identifying several classes of variables as most important.

Ellis, David↗
DOE OSTI2024

Identification of Climatological Representative Days in the Mid-Atlantic for High-Fidelity Offshore Wind Energy Modeling

The goal of reaching 30 GW of offshore wind energy by 2030 becomes more realistic with the continued approval of offshore wind energy areas by the Biden Administration. In the Mid-Atlantic, where wind energy projects are in the most advanced stages of development, there is increased research focus on the eventual interaction of these wind farms. These interactions, in the form of wakes and cluster wakes, or wakes from multiple wind farms, could have detrimental effects on power production and forecastability for downwind wind farms (Pryor et al. 2022, Golbazi et al. 2022, Rosencrans et al. 2023). To help alleviate these issues, numerical simulations in the form of numerical weather prediction (NWP) and large eddy simulations (LES) can provide insight into when cluster wake situations may occur, but running such simulations can be expensive and difficult to run for multiple years. In this study, we leverage and build upon existing techniques in the literature (Fischereit et al. 2022) to identify climatologically representative days for wind energy areas in the Mid-Atlantic where conditions would promote cluster wake situations. We select meteorological variables (wind speed, wind direction, atmospheric stability, boundary-layer height, TKE) critical to understanding wind energy production and wake propagation. We then consider two different NWP datasets of varying spatial and temporal resolution: ERA5 provides data at hourly intervals from 1940 to present at 0.25 deg (31 km) spatial resolution (Hersbach et al. 2020), and the NOW-23 dataset provides data at 5-minute resolution for 21 years at 2-km spatial resolution (Bodini et al. 2020). Our first step is to compare these two datasets for an overlapping 21-year time period. Initial results show that the required number of days to represent the long-term climate increases with each additional variable considered. In their study of the German Bight, Fischereit et al. (2022) found that they could represent the long-term wind and wave climate in a "near-perfect" way with -180 days, by reaching a Perkins Skill Score (PSS) of 0.9; our investigation of the mid-Atlantic wind resource region with ERA5 and NOW-23 data suggests that we will need -100 days to reach a PSS of 0.9. As we expand our parameter space to include multiple variables, the number of required days will likely grow. These results will ultimately be used to select case studies to best represent cluster wake conditions that apply to this region for the lifetime of likely wind farms in this mid-Atlantic region.

clusterwakes↗
DOE OSTI2024

Optimization of a High Pressure Turbine Blade and Sector-Based Annular Rig Design for Supercritical CO2 Power Cycle Representative Testing

Abstract As part of the ongoing research into the design of hardware for zero emission cycles, a first-stage high-pressure turbine (HPT) blade is optimized for a 300 MWe supercritical CO2 (sCO2) power cycle using the surrogate-assisted genetic algorithm optimizer in Numeca FINE/Design three-dimensional with objectives of increasing efficiency and decreasing heat load to the blade. Supercritical CO2 property tables are constructed from NIST REFPROP data for the condensable gas simulation in FINE/Turbo. A detailed mesh sensitivity study is performed for a baseline design to identify the proper-grid refinement and efficiently allocate resources for the optimization. Seventy design variables are selected for the initial population generation. Self-organizing maps are then used to focus the design variables on the most important ones affecting the objective functions. The optimization results in approximately 3000 three-dimensional Reynolds Averaged Navier Stokes simulations of different blade shapes with increases in efficiency of up to 0.85% and decreases in heat load of 14%. Families of blade shapes are identified for experimental testing in an annular rig at the Purdue Experimental Turbine Aerothermal Laboratory. A design to adapt the annular cascade for testing optimized geometries is introduced, which features eccentric radius sectors allowing for scaled-up geometries of sCO2 optimized blade profiles to be tested at design cycle representative conditions at high Reynolds numbers in dry air. Analysis into the effects of Reynolds number, working fluid, and geometric relations are presented to prove the efficacy of the test method.

Engineering↗