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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 721 records · Page 40

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NASA NTRS1976

Two-phase choked flow of subcooled oxygen and nitrogen

Data are presented for two-phase critical flow through nozzles. Test results from two converging-diverging nozzles and two separate test facilities are in excellent agreement. The critical flow rate and critical flow pressure ratio data conclusively demonstrate that the principle of corresponding states can be applied to two-phase choked flow through nozzles. Normalizing parameters were developed to correlate these data, and current theories can provide an adequate means for extrapolating to other fluids. Such information can be useful for cryogenic fluid storage applications.

Hendricks, R. C.↗

NASA NTRS1976

Accelerated iterative calculation of transonic nacelle flowfields

A method is presented for the calculation of inviscid, supercritical flowfields about axisymmetric inlet cowls. A finite-difference calculation is performed in a simple, rectangular domain obtained from the nacelle geometry by a nearly-conformal mapping procedure. Type-dependent finite-differences are constructed using a coordinate-independent, 'rotated' differencing scheme. Methods of accelerating convergence of the iterative solution are demonstrated including a hybrid fast-Poisson-solver/relaxation scheme and an extrapolated relaxation procedure. Calculated pressure distributions are compared with experimental data for a variety of Mach numbers and mass-flow ratios, and show generally good agreement.

Caughey, D. A.↗

NASA NTRS1978

Determination of volume fraction in multiphase systems using incomplete pole figures

The determination of the volume fraction of a second phase in a multiphase sample by X-ray diffraction becomes more difficult if the diffracting planes have a preferred orientation. Lopata and Kula have described a method of treating this problem using complete pole figures for each of the phases. With some samples, it is not always possible or convenient to obtain data over the full hemisphere. Equations and an example are given which require X-ray data over a limited range of approximately 0 to 75 deg. This can be obtained by reflection without a specially cut sample or transmission data. A series of Legendre polynomials are fitted to data collected while spinning the sample about its normal. An extrapolation is made possible by introducing two conditions on the end points which must be satisfied if the extrapolation functions are to be valid.

Houska, C. R.↗

NASA NTRS1981

Seasat altimeter height calibration

The Seasat altimeter was calibrated for height bias using four overflight passes of Bermuda which were supported by the Bermuda laser. The altimeter data was corrected for: tides, using recorded tide gauge data; propagation effects, using meteorological data taken around the time of each pass; acceleration lag; and sea state bias, including both surface effects and instrumental effects. Altimeter data for each of the four passes was smoothed and extrapolated across the island. Interpolation between passes then produced an equivalent altimeter measurement to the geoid at the laser site, so that the altimeter bias could be estimated without the use of a geoid model. The estimated height bias was 0.0 + or - 0.07.

Kolenkiewicz, R.↗

NASA NTRS1982

Sensitivity analysis of cool-down strategies for a transonic cryogenic tunnel

Guidelines and suggestions substantiated by real-time simulation data to ensure optimum time and energy use of injected liquid nitrogen for cooling the Langley 0.3-Meter Transonic Cryogenic Tunnel (TCT) are presented. It is directed toward enabling operators and researchers to become cognizant of criteria for using the 0.3-m TCT in an energy- or time-efficient manner. Operational recommendations were developed based on information collected from a validated simulator of the 0.3-m TCT and experimental data from the tunnel. Results and trends, however, can be extrapolated to other similarly constructed cryogenic wind tunnels.

Thibodeaux, J. J.↗

NASA NTRS1983

The Tunguska event - No cometary signature in evidence

It is suggested that existing data on the 1908 Tunguska fall precludes an interpretation of the object as an either active or extinct comet fragment. Because a fireball of the Tunguska mass is not efficiently decelerated by the earth's atmosphere, it would at an entry velocity of about 30 km/sec have had to resist aerodynamic pressures greater than one billon dyn/sq cm before disintegrating. The inherently extremely fragile cometary material could not have survived a load of this magnitude. The data on Type II fireballs with prominent terminal flares are extrapolated, to estimate Tunguska's critical dynamic pressure at the same time of explosion as being of the order of 200 million dyn/sq cm, and its preexplosion velocity as about 10 km/sec, thereby ruling out a comet-like orbit. The Tunguska object is most consistently described as a small Apollo-type asteroid, 90-190 m across.

Sekanina, Z.↗

NASA NTRS1985

On stellar X-ray emission

Stellar X-ray astronomy represents an entirely new astronomical discipline which has emerged during the past five years. It lies at the crossroads of solar physics, stellar physics, and general astrophysics. The present review is concerned with the main physical problems which arise in connection with a study of the stellar X-ray data. A central issue is the extent to which the extrapolation from solar physics is justified and the definition (if possible) of the limits to such extrapolation. The observational properties of X-ray emission from stars are considered along with the solar analogy and the modeling of X-ray emission from late-type stars, the modeling of X-ray emission from early-type stars, the physics of stellar X-ray emission, stellar X-ray emission in the more general astrophysical context, and future prospects.

Rosner, R.↗

NASA NTRS1988

The fatigue damage behavior of a single crystal superalloy

The uniaxial fatigue behavior of a single crystal superalloy, PWA 1480, is described. Both monotonic tensile and constant amplitude fatigue tests were conducted at room temperature, in an effort to assess the applicability of polycrystalline-based fatigue life prediction methods to a single crystal superalloy. The observed constant amplitude behavior correlated best using a stress-based life criterion. Nearly all specimens failed at surface or slightly subsurface microporosity; this is thought to be responsible for the unusually large amount of scatter in the test results. An additional term is developed in the stress-life equation for the purpose of accounting for the effect of microporosity on fatigue life. The form chosen is a function of the effective area of the failure-producing microporosity projected on a plane perpendicular to the loading axis, as well as the applied stress. This additional term correlated the data to within factors of two on life. Although speculative, extrapolation of the microporosity relation to zero micropore area indicates that approximately an order of magnitude improvement in fatigue life should result.

Mcgaw, Michael A.↗

NASA NTRS1994

Ultraviolet interstellar polarization observed with the Hubble Space Telescope

We have used the Faint Object Spectrograph of the Hubble Space Telescope to observe interstellar linear polarization from 1300 to 3300 A in two stars with well-studied interstellar polarization at visible wavelenths. The wavelength dependence of linear polarization declines smoothly with decreasing wavelength and is devoid of structure associated with the prominent 2175 A absorption bump in the interstellar extinction curve. The data for one star (HD 161056) are consistent with an extrapolation based on the Serkowski formula of a fit to the ground-based polariztion; the other star (HD 7252) shows excess (super-Serkowski) polarization relative to the extrapolation. Out of a total of 10 stars now studied by means of spectropolarimetry in the satellite ultraviolet, including eight obseved with the Wisconsin Ultraviolet Photopolarimeter, five (those of longest lambda (sub max)) show Serkowski behavior, and four others show super-Serkowski behavior; only one (HD 197770) shows evidence for polarization associated with the 2175 A bump. These results place important constraints on the nature of the bump feature.

Somerville, W. B.↗

NASA NTRS1997

Rendering Three-Dimensional Solar Coronal Structures

An X-ray or EUV image of the corona or chromosphere is a 2D representation of an extended 3D complex for which a general inversion process is impossible. A specific model must be incorporated in order to understand the full 3D structure. We approach this problem by modeling a set of optically-thin 3D plasma flux tubes which we render these as synthetic images. The resulting images allow the interpretation of the X-ray/EUV observations to obtain information on (1) the 3D structure of X-ray images, i.e., the geometric structure of the flux tubes, and on (2) the internal structure using specific plasma characteristics, i.e., the physical structure of the flux tubes. The data-analysis technique uses magnetograms to characterize photospheric magnetic fields and extrapolation techniques to form the field lines. Using a new set of software tools, we have generated 3D flux tube structures around these field lines and integrated the plasma emission along the line of sight to obtain a rendered image. A set of individual flux-tube images is selected by a non-negative least-squares technique to Provide a match with an observed X-ray image. The scheme minimizes the squares of the differences between the synthesized image and the observed image with a non-negative constraint on the coefficients of the brightness of the individual flux-tube loops. The derived images are used to determine the specific photospheric foot points and physical data, i.e., scaling laws for densities and loop lengths. The development has led to Computer efficient integration and display software that is compatible for comparison with observations (e.g., Yohkoh SXT data, NIXT, or EIT). This analysis is important in determining directly the magnetic field configuration, which provides the structure of coronal loops, and indirectly the electric currents or waves, which provide the energy for the heating of the plasma. We have used very simple assumptions (i.e., potential magnetic fields and isothermal corona) to provide an initial test of the techniques before complex models are introduced. We have separated the physical and geometric contributions of the emission for a set of flux tubes and concentrated, in this initial study, on the geometric contributions by making approximations to the physical contributions. The initial results are consistent with the scaling laws derived from Yohkoh SXT data.

Gary, G. Allen↗

DOE OSTI2025

Equation of State for the Thermodynamic Properties of Trans-1,2-dichloroethene [R-1130(E)]

We present an empirical equation of state in terms of the Helmholtz energy for trans-1,2-dichloroethene [R-1130(E)]. The range of validity is from the triple-point temperature, 223.31 K to 525 K with pressures up to 30 MPa. It may be used to calculate all thermodynamic properties in the fluid phase, including liquid, gas, and supercritical regions. Comparisons are given with existing literature data and estimated uncertainties are provided. In addition, checks were made for correct extrapolation behavior so that the equation behaves in a physically realistic manner when used outside of its range of validity, enabling its use in mixture models. The estimated uncertainties (at a k = 2 or 95 % level of confidence) are based on comparisons with critically assessed data and are 0.25 % for vapor pressure for temperatures in the range 300 K < T < 454 K, rising to 1.5 % as the temperature decreases from 300 K to 265 K. For density in the liquid phase the estimated uncertainty is 0.14 % for temperatures 270 K < T < 410 K and for pressures up to 30 MPa. For the vapor phase the estimated uncertainty in density is 3 %. The uncertainty for liquid-phase heat capacity is 1 % at atmospheric pressure over the temperature range 268 K < T < 309 K, and the uncertainty for the speed of sound in the liquid phase is 0.25 % for temperatures 230 K < T < 420 K and for pressures up to 30 MPa. The uncertainties are larger outside of these specified ranges and in the critical region.

1,2-Dichloroethene↗

NASA NTRS2014

BioSentinel: Monitoring DNA Damage Repair Beyond Low Earth Orbit on a 6U Nanosatellite

We are designing and developing a 6U nanosatellite as a secondary payload to fly aboard NASAs Space Launch System (SLS) Exploration Mission (EM) 1, scheduled for launch in late 2017. For the first time in over forty years, direct experimental data from biological studies beyond low Earth orbit (LEO) will be obtained during BioSentinels 12- to 18-month mission. BioSentinel will measure the damage and repair of DNA in a biological organism and allow us to compare that to information from onboard physical radiation sensors. This data will be available for validation of existing models and for extrapolation to humans.The BioSentinel experiment will use the organism Saccharomyces cerevisiae (yeast) to report DNA double-strand-break (DSB) events that result from space radiation. DSB repair exhibits striking conservation of repair proteins from yeast to humans. The flight strain will include engineered genetic defects that prevent growth and division until a radiation-induced DSB activates the yeasts DNA repair mechanisms. The triggered culture growth and metabolic activity directly indicate a DSB and its repair. The yeast will be carried in the dry state in independent microwells with support electronics. The measurement subsystem will sequentially activate and monitor wells, optically tracking cell growth and metabolism. BioSentinel will also include TimePix radiation sensors implemented by JSCs RadWorks group. Dose and Linear Energy Transfer (LET) data will be compared directly to the rate of DSB-and-repair events measured by the S. cerevisiae biosentinels. BioSentinel will mature nanosatellite technologies to include: deep space communications and navigation, autonomous attitude control and momentum management, and micropropulsion systems to provide an adaptable nanosatellite platform for deep space uses.

cosmic rays↗

NASA NTRS1997

Neural Network Research on Tilt-Rotor Hover Performance

Results from a neural network study on XV-15 tilt-rotor hover performance are presented. Two XV-15 test data bases, acquired during separate tests conducted in the National Full-Scale Aerodynamics Complex at NASA Ames, were used in this study. The two XV-15 test data bases used were: the 1997 80- by 120-Foot Wind Tunnel test data base and the 1984 Outdoor Aerodynamic Research Facility (OARF) test data base. The objectives associated with the 80- by 120-Foot Wind Tunnel test data were to conduct data quality checks, obtain neural network representations, and demonstrate sensitivity to test conditions. The objectives associated with the OARF outdoor test data were to obtain a 'zero wind' neural network representation, and formulate and implement a neural network based wind correction procedure. An additional objective, common to both test data bases, was to conduct error comparisons. The conclusions from the present study were as follows: Compared to measured parameters (i.e., collective pitch angle), derived parameters (i.e., thrust coefficient) were found preferable as neural network inputs. For the 80- by 120-Foot Wind Tunnel test data base, the neural network based figure of merit representations did not extrapolate rotor stall. Using the OARF outdoor test database, a neural network based wind correction procedure was formulated and successfully implemented. Based on an error comparison, the present neural network based wind correction procedure was found to be more accurate compared to the existing, momentum-theory-based wind correction procedure. Also, a separate error comparison showed that the 80- by 120-Foot Wind Tunnel hover performance data were comparable to non-wind-corrected outdoor test data.

Kozapalli, S.↗

NASA NTRSDate not supplied

Synthetic Hyperspectral Data for Global Water Quality Algorithm Development

Eutrophication and increasing prevalence of potentially toxic algal blooms (cyanoHABs) among global inland water bodies have become a major ecological concern and require direct attention. There is now a growing necessity to develop pragmatic approaches that allow timely and effective extrapolation of local aquatic processes, to spatially resolved global products. Planned aquatic biogeochemistry remote sensing data products from hyperspectral imagers such as NASA’s Surface Biology and Geology (SBG) mission and relevant aquatic sensor sensitivity precursor airborne imaging spectrometer data provide unprecedented radiometric resolution and sensor sensitivity for characterizing complex aquatic ecosystems. However, scarcity of high-quality freshwater in-situ optical data hinders our capability to develop and validate robust retrieval algorithms. A state-of-the-art synthetic dataset of paired top-of-atmosphere, bottom-of-atmosphere, and optical and biogeophysical data was developed through radiative transfer modeling to simulate natural freshwater ecosystems. A synthetic or precursor dataset for SBG is being used to train robust machine learning models to derive water quality products pertinent to SBG mission objectives. The dataset is also used to show the potential of performing vigorous aquatic sensitivity studies and explored pathways for how best to optimize hyperspectral data for machine learning development. A processing pipeline and resultant global synthetic/precursor dataset for inland waters is presented to establish the innovation for water quality studies of inland waters globally. Optical Society of America Imaging and Applied Optics Congress, Hyperspectral Imaging and Sounding of the Environment (OSA HISE) Meeting, 19-23 July 2021, Virtual Meeting, https://www.osa.org/enus/meetings/osa_meetings/optical_sensors_and_sensing_congress/program/hyperspectral_imaging_and_sounding_of_the_environm/

Synthetic↗

DOE OSTI2026

Analytical desmearing of Bonse–Hart ultra-small-angle neutron scattering data via truncated Abel inversion

A non-iterative analytical framework based on the truncated Abel inversion is developed for desmearing Bonse–Hart ultra-small-angle neutron scattering (USANS) data. The method directly inverts the slit-averaged intensity without empirical extrapolation or iterative regularization, establishing a closed-form relationship between the measured and intrinsic scattering profiles. Numerical benchmarks on representative models, including a rigid-line form factor, a Lorentzian function and a fractal structural model, demonstrate quantitative recovery of the ground-truth intensity across the full Q range. Application to a deuterated polystyrene/poly(2-vinylpyridine) blend further confirms that the approach yields smooth continuous profiles consistent with companion small-angle neutron scattering data. The truncated Abel inversion thus provides a stable, model-independent and physically transparent route for accurate desmearing of Bonse–Hart USANS measurements.

Huang, Guan-Rong [National Tsing Hua University, T↗

DOE OSTI2022

Data and scripts associated with the manuscript "Encoding Diel Hysteresis and the Birch Effect in Dryland Soil Respiration Models through Knowledge-Guided Deep Learning"

This package contains the data and scripts used in "Encoding Diel Hysteresis and the Birch Effect in Dryland Soil Respiration Models through Knowledge-Guided Deep Learning" (Jiang et al., 2022). The data.zip file contains the flux tower and automated chamber observations used for developing the deep learning model for modeling soil respiration. The scripts.zip file contains the Jupyter notebooks and python scripts for preprocessing the data, training the deep learning models, and postprocessing the results. The src.zip contains the source code for training the deep learning model, performing mutual information analysis, and plotting functions. The trained_models.zip contains multiple folders used for hosting the trained deep-learning models and the associated soil respiration predictions. The whole process is performed using python. We include the REAMD.md to document the python package requirements.Soil respiration in dryland ecosystems is challenging to model due to its complex interactions with environmental drivers. Knowledge-guided deep learning provides a much more effective means of accurately representing these complex interactions than traditional Q10-based models. Mutual information analysis revealed that future soil temperature shares more information with soil respiration than past soil temperature, consistent with their clockwise diel hysteresis. We explicitly encoded diel hysteresis, soil drying, and soil rewetting effects on soil respiration dynamics in a newly designed Long Short Term Memory (LSTM) model. The model takes both past and future environmental drivers as inputs to predict soil respiration. The new LSTM model substantially outperformed three Q10-based models and the Community Land Model when reproducing the observed soil respiration dynamics in a semi-arid ecosystem. The new LSTM model clearly demonstrated its superiority for temporally extrapolating soil respiration dynamics, such that the resulting correlation with observational data is up to 0.7 while the correlations of both Q10-based models and the Community Land Model (CLM) are less than 0.4. Our results underscore the high potential for knowledge-guided deep learning to replace Q10-based soil respiration modules in Earth system models.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

Henry’s Solubility and Diffusion Coefficients for 29 Volatile Organic Compounds in Polydimethylsiloxane Sylgard 184 at 293 K

Two-dimensional (2D) inverse gas chromatography (IGC) enables simultaneous determination of Henry’s solubility and Fickian diffusion coefficients for volatile organic compounds (VOCs) in polymer films. This technique offers a significant advantage over traditional cylindrical column IGC by providing precise control and measurement of the film thickness (here, 0.064 ± 0.002 mm), which is the critical length scale for accurate diffusivity determination. We apply this methodology to characterize VOC transport in Sylgard 184, a widely used polydimethylsiloxane (PDMS)-based polymer containing substantial silica filler content. At room temperature (20 °C), we measured solubility and diffusion coefficients for 29 common VOCs spanning diverse chemical functionalities, including alkanes, aromatics, chlorinated solvents, ketones, esters, and alcohols. Comparison with literature data for pure PDMS reveals that VOC solubility in Sylgard 184 is generally higher; for most non-hydrogen-bonding compounds it remains within a factor of 2 of pure PDMS, whereas alcohols are enhanced by roughly 1.8 to 3.7 times, which we attribute to favorable interactions with residual silanol groups on the silanized silica filler. Diffusion coefficients range from 1.0 × 10 –6 cm 2 /s (n-undecane) to 8.9 × 10–5 cm 2 /s (acetonitrile) and align well with extrapolated literature values for PDMS. This study provides essential thermodynamic and transport data for predicting VOC permeation in Sylgard 184 while demonstrating the utility of 2D IGC as a robust technique for characterizing rubbery polymer membranes across diverse industrial applications.

organic↗

DOE OSTI2022

Machine learning predictions of irradiation embrittlement in reactor pressure vessel steels

Abstract Irradiation increases the yield stress and embrittles light water reactor (LWR) pressure vessel steels. In this study, we demonstrate some of the potential benefits and risks of using machine learning models to predict irradiation hardening extrapolated to low flux, high fluence, extended life conditions. The machine learning training data included the Irradiation Variable for lower flux irradiations up to an intermediate fluence, plus the Belgian Reactor 2 and Advanced Test Reactor 1 for very high flux irradiations, up to very high fluence. Notably, the machine learning model predictions for the high fluence, intermediate flux Advanced Test Reactor 2 irradiations are superior to extrapolations of existing hardening models. The successful extrapolations showed that machine learning models are capable of capturing key intermediate flux effects at high fluence. Similar approaches, applied to expanded databases, could be used to predict hardening in LWRs under life-extension conditions.

36 MATERIALS SCIENCE↗