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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 433 records · Page 24
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NASA NTRS1981

Inference of precipitation through thermal infrared measurements of soil moisture

The physics of microwave radiative transfer is well understood so that causal models can be assembled which relate the observed brightness temperatures to assumed distributions of hydrometeors (both liquid and ice), non-precipitating clouds, water vapor oxygen, and surface conditions. Present models assume a Marshall Palmer size distribution of liquid hydrometers from the surface to the freezing level (near the 0 C isotherm) and a variable thickness of frozen hydrometeors above that with various reasonable distribution of the other relevant constituents. The validity of such models is discussed. All uncertainties in the rain rate retrieval algorithms can be expressed in terms of specific model uncertainties which can be addressed through appropriate measurements. Those factors which must be known to achieve umambiguous results can be identified so that rainfall measuring algorithms can be developed and improved. The emissivity of the underlying surface significantly affects the contrast that may be measured between areas covered by rain and those which are dry. Sensing strategies for measuring rain over the ocean and rain over land are reviewed.

Wetzel, P. J.↗
NASA NTRS1985

Results from observations of the 15 June 1983 occultation by the Neptune system

Observations of eight Neptune occultations from six sites in the southwestern Pacific on June 15, 1983. The data were used to search for evidence of rings around Neptune down to a distance of 0.03 Neptune radii from the planetary surface, but the results were negative. An astrometric analysis of the timings yielded solution for the equatorial radius a(0) of Neptune at 1 microbar pressure and the oblatness e at this level. The results are: a(0) = 25,295 + or - 50 km; e = 0.022 + or - 0.004, from which a value for a(1) (equatorial radius at 1 bar pressure) of 24,830 + or - 100 km; and a rotation period of P = 15 h (+3, -2 h) is derived. These results are based on a recent determination of Neptune's pole position and mass quadruple moment, and are consistent with the hypothesis that Neptune and Uranus have homologous mass distributions, although the constraint on interior structure is a weak one. If the probable uncertainty of the pole position is taken into account, error bars on e and derived quantities should be increased by about 50 percent. The present determinations of Neptune atmospheric temperatures at 1 microbar are consistent with earlier results and when combined with all previous data give an average value of 156 + or - 10 K. There is only slight evidence for any latitude dependence in the temperatures. Profiles with a high signal-to-noise ratio suggest the possible presence of an absorbing layer at altitudes higher than the 1-microbar level.

Hubbard, W. B.↗
NASA NTRS2004

MOBI: Microgravity Observations of Bubble Interactions

One of the greatest uncertainties affecting the design of multiphase flow technologies for space exploration is the spatial distribution of phases that will arise in microgravity or reduced gravity. On Earth, buoyancy-driven motion predominates whereas the shearing of the bubble suspension controls its behavior in microgravity. We are conducting a series of ground-based experiments and a flight experiment spanning the full range of ratios of buoyancy to shear. These include: (1) bubbles rising in a quiescent liquid in a vertical channel; (2) weak shear flow induced by slightly inclining the channel; (3) moderate shear flow in a terrestrial vertical pipe flow; and (4) shearing of a bubble suspension in a cylindrical Couette cell in microgravity. We consider nearly monodisperse suspensions of 1 to 1.8 mm diameter bubbles in aqueous electrolyte solutions. The liquid velocity disturbance produced by bubbles in this size range can often be described using an inviscid analysis. Electrolytic solutions lead to hydrophilic repulsion forces that stabilize the bubble suspension without causing Marangoni stresses. We will discuss the mechanisms that control the flow behavior and phase distribution in the ground-based experiments and speculate on the factors that may influence the suspension flow and bubble volume fraction distribution in the flight experiment.

Koch, Donald L.↗
NASA NTRS2011

Markov Chain Monte Carlo Bayesian Learning for Neural Networks

Conventional training methods for neural networks involve starting al a random location in the solution space of the network weights, navigating an error hyper surface to reach a minimum, and sometime stochastic based techniques (e.g., genetic algorithms) to avoid entrapment in a local minimum. It is further typically necessary to preprocess the data (e.g., normalization) to keep the training algorithm on course. Conversely, Bayesian based learning is an epistemological approach concerned with formally updating the plausibility of competing candidate hypotheses thereby obtaining a posterior distribution for the network weights conditioned on the available data and a prior distribution. In this paper, we developed a powerful methodology for estimating the full residual uncertainty in network weights and therefore network predictions by using a modified Jeffery's prior combined with a Metropolis Markov Chain Monte Carlo method.

Goodrich, Michael S.↗
NASA NTRS2012

Recent Progress on Deep Blue Aerosol Algorithm as Applied TO MODIS, SEA WIFS, and VIIRS, and Their Intercomparisons with Ground Based and Other Satellite Measurements

The impact of natural and anthropogenic sources of aerosols has gained increasing attention from scientific communities in recent years. Indeed, tropospheric aerosols not only perturb radiative energy balance by interacting with solar and terrestrial radiation, but also by changing cloud properties and lifetime. Furthermore, these anthropogenic and natural air particles, once generated over the source regions, can be transported out of the boundary layer into the free troposphere and can travel thousands of kilometers across oceans and continents resulting in important biogeochemical impacts on the ecosystem. With the launch of SeaWiFS in 1997, Terra/MODIS in 1999, and Aqua/MODIS in 2002, high quality comprehensive aerosol climatology is becoming feasible for the first time. As a result of these unprecedented data records, studies of the radiative and biogeochemical effects due to tropospheric aerosols are now possible. In this talk, we will demonstrate how this newly available SeaWiFS/MODIS aerosol climatology can provide an important piece of puzzles in reducing the uncertainty of estimated climatic forcing due to aerosols. We will start with the global distribution of aerosol loading and their variabilities over both land and ocean on short- and long-term temporal scales observed over the last decade. The recent progress made in Deep Blue aerosol algorithm on improving accuracy of these Sea WiFS / MODIS aerosol products in particular over land will be discussed. The impacts on quantifying physical and optical processes of aerosols over source regions of adding the Deep Blue products of aerosol properties over bright-reflecting surfaces into Sea WiFS / MODIS as well as VIIRS data suite will also be addressed. We will also show the intercomparison results of SeaWiFS/MODIS retrieved aerosol optical thickness with data from ground based AERONET sunphotometers over land and ocean as well as with other satellite measurements. The trends observed in global aerosol loadings of both natural and anthropogenic sources based upon more than a decade of combined MODIS/SeaWiFS data (1997-2011) will be discussed. We will also address the importance of various key issues such as differences in spatial-temporal sampling rates and observation time between different satellite measurements could potentially impact these intercomparisons results, especially for using the monthly mean data, and thus on estimates of long-term aerosol trends.

Hsu, N. Christina↗
NASA NTRS2021

Less Atmospheric Radiative Heating By Dust Due to the Synergy of Coarser Size and Aspherical Shape

Mineral dust aerosols cool and warm the atmosphere by scattering and absorbing solar (shortwave: SW) and thermal (longwave: LW) radiation. However, significant uncertainties remain in dust radiative effects, largely due to differences in the dust size distribution and spectral optical properties simulated in Earth system models. Dust models typically underestimate the coarse dust load (more than 2.5 µm in diameter) and assume a spherical shape, which leads to an overestimate of the fine dust load (less than 2.5 µm) after the dust emissions in the models are scaled to match observed dust aerosol optical depth at 550 nm (DAOD550). Here, we improve the simulated dust properties with data sets that leverage measurements of size-resolved dust concentration, asphericity factor, and refractive index in a coupled global chemical transport model with a radiative transfer module. After the adjustment of size-resolved dust concentration and spectral optical properties, the global and annual average of DAOD550 from the simulation increases from 0.023 to 0.029 and falls within the range of a semi-observationally based estimate (0.030 ± 0.005). The reduction of fine dust load after the adjustment leads to a reduction of the SW cooling at the top of the atmosphere (TOA). To improve agreement against a semi-observationally based estimate of the radiative effect efficiency at TOA, we find that a less absorptive SW dust refractive index is required for coarser aspherical dust. Thus, only a minor difference is estimated for the net global dust radiative effect at TOA (−0.08 vs. −0.00 W m−2 on a global scale). Conversely, our sensitivity simulations reveal that the surface warming is substantially enhanced near the strong dust source regions (less cooling to −0.23 from −0.60 W m−2 on a global scale). Thus, less atmospheric radiative heating is estimated near the major source regions (less heating to 0.15 from 0.59 W m−2 on a global scale), because of enhanced LW warming at the surface by the synergy of coarser size and aspherical shape.

simulated dust properties↗
NASA NTRSDate not supplied

A Reference Ocean Surface Emission and Backscatter Model from Microwaves to Infrared

Satellite observations are vital for the initialization of Numerical Weather Prediction models, and very important for climate monitoring and prediction, as well as other applications such as hydrology and flood awareness prediction. Knowledge of radiative contributions from the Earth's surface is needed to sound the lower troposphere from space. The lack of a reference quality ocean emission and backscatter model is a major gap in our ability to provide absolute calibration of the satellite based observing system. Uncertainty in emissivity models is not well characterized and different models are used for different spectral bands, for active and passive instruments. An International Space Science Institute (ISSI) team was put together [4] to address these issues. The objectives of the team are to provide a reference model as a community software (i.e., documented and freely available code), that is maintained and supported, has traceable uncertainty estimations, and that enables new science from microwaves to infrared with bidirectional reflectance distribution function (BRDF) capability. We will present the model and its various components, discussing the choices between various parameterizations, building on the LOCEAN model of [2]. The model predictions will be evaluated at various frequencies, including comparisons to radiometric observations by SMAP, AMSR2 and GMI (e.g., [5]). We will discuss early model evaluation in the infrared and for active microwave sensors. Areas of ongoing research include improving the foam parametrization (coverage and emissivity) to provide consistent performances across frequencies, building on [1], and the azimuthal dependence of the active and passive signals. The model will be used to generate training data for fast models e.g., Fastem, [3], that are used in operational data assimilation and climate re-analysis.

Emmanuel Dinnat↗
NASA NTRS2012

Comparison of Aerosol Classification Results from Airborne High Spectral Resolution Lidar (HSRL) Measurements and the Calipso Vertical Feature Mask

Knowledge of the vertical profile, composition, concentration, and size of aerosols is required for assessing the direct impact of aerosols on radiation, the indirect effects of aerosols on clouds and precipitation, and attributing these effects to natural and anthropogenic aerosols. Because anthropogenic aerosols are predominantly submicrometer, fine mode fraction (FMF) retrievals from satellite have been used as a tool for deriving anthropogenic aerosols. Although column and profile satellite retrievals of FMF have been performed over the ocean, such retrievals have not yet been been done over land. Consequently, uncertainty in satellite estimates of the anthropogenic component of the aerosol direct radiative forcing is greatest over land, due in large part to uncertainties in the FMF. Satellite measurements have been used to detect and evaluate aerosol impacts on clouds; however, such efforts have been hampered by the difficulty in retrieving vertically-resolved cloud condensation nuclei (CCN) concentration, which is the most direct parameter linking aerosol and clouds. Recent studies have shown correlations between average satellite derived column aerosol optical thickness (AOT) and in situ measured CCN. However, these same studies, as well as others that use detailed airborne in situ measurements have noted that vertical variability of the aerosol distribution, impacts of relative humidity, and the presence of coarse mode aerosols such as dust introduce large uncertainties in such relations.

Burton, S. P.↗
NASA NTRS2006

Model Calculations of Solar Spectral Irradiance in the 3.7 Micron Band for Earth Remote Sensing Applications

Since the launch of the first Advanced Very High Resolution Radiometer (AVHRR) instrument aboard TIROS-N, measurements in the 3.7 micron atmospheric window have been exploited for use in cloud detection and screening, cloud thermodynamic phase and surface snow/ice discrimination, and quantitative cloud particle size retrievals. The utility of the band has led to the incorporation of similar channels on a number of existing satellite imagers and future operational imagers. Daytime observations in the band include both reflected solar and thermal emission energy. Since 3.7 micron channels are calibrated to a radiance scale (via onboard blackbodies), knowledge of the top-of-atmosphere solar irradiance in the spectral region is required to infer reflectance. Despite the ubiquity of 3.7 micron channels, absolute solar spectral irradiance data comes from either a single measurement campaign (Thekaekara et al. 1969) or synthetic spectra. In this study, we compare historical 3.7 micron band spectral irradiance data sets with the recent semi-empirical solar model of the quiet-Sun by Fontenla et al. (2006). The model has expected uncertainties of about 2 % in the 3.7 pm spectral region. We find that channel-averaged spectral irradiances using the observations reported by Thekaekara et al. are 3.2-4.1% greater than those derived from the Fontenla et al. model for MODIS and AVHRR instrument bandpasses; the Kurucz spectrum (1995) as included in the MODTRAN4 distribution, gives channel-averaged irradiances 1.2-1.5 % smaller than the Fontenla model. For the MODIS instrument, these solar irradiance uncertainties result in cloud microphysical retrievals uncertainties comparable with other fundamental reflectance error sources.

Platnick, Steven↗
NASA NTRS2008

Tolerance and UQ4SIM: Nimble Uncertainty Documentation and Analysis Software

Ultimately, scientific numerical models need quantified output uncertainties so that modeling can evolve to better match reality. Documenting model input uncertainties and variabilities is a necessary first step toward that goal. Without known input parameter uncertainties, model sensitivities are all one can determine, and without code verification, output uncertainties are simply not reliable. The basic premise of uncertainty markup is to craft a tolerance and tagging mini-language that offers a natural, unobtrusive presentation and does not depend on parsing each type of input file format. Each file is marked up with tolerances and optionally, associated tags that serve to label the parameters and their uncertainties. The evolution of such a language, often called a Domain Specific Language or DSL, is given in [1], but in final form it parallels tolerances specified on an engineering drawing, e.g., 1 +/- 0.5, 5 +/- 10%, 2 +/- 10 where % signifies percent and o signifies order of magnitude. Tags, necessary for error propagation, can be added by placing a quotation-mark-delimited tag after the tolerance, e.g., 0.7 +/- 20% 'T_effective'. In addition, tolerances might have different underlying distributions, e.g., Uniform, Normal, or Triangular, or the tolerances may merely be intervals due to lack of knowledge (uncertainty). Finally, to address pragmatic considerations such as older models that require specific number-field formats, C-style format specifiers can be appended to the tolerance like so, 1.35 +/- 10U_3.2f. As an example of use, consider figure 1, where a chemical reaction input file is has been marked up to include tolerances and tags per table 1. Not only does the technique provide a natural method of specifying tolerances, but it also servers as in situ documentation of model uncertainties. This tolerance language comes with a utility to strip the tolerances (and tags), to provide a path to the nominal model parameter file. And, as shown in [1], having the ability to quickly mark and identify model parameter uncertainties facilitates error propagation, which in turn yield output uncertainties.

Kleb, Bil↗
NASA NTRS2008

CFD Modeling of Superheated Fuel Sprays

An understanding of fuel atomization and vaporization behavior at superheat conditions is identified to be a topic of importance in the design of modern supersonic engines. As a part of the NASA aeronautics initiative, we have undertaken an assessment study to establish baseline accuracy of existing CFD models used in the evaluation of a ashing jet. In a first attempt towards attaining this goal, we have incorporated an existing superheat vaporization model into our spray solution procedure but made some improvements to combine the existing models valid at superheated conditions with the models valid at stable (non-superheat) evaporating conditions. Also, the paper reports some validation results based on the experimental data obtained from the literature for a superheated spray generated by the sudden release of pressurized R134A from a cylindrical nozzle. The predicted profiles for both gas and droplet velocities show a reasonable agreement with the measured data and exhibit a self-similar pattern similar to the correlation reported in the literature. Because of the uncertainty involved in the specification of the initial conditions, we have investigated the effect of initial droplet size distribution on the validation results. The predicted results were found to be sensitive to the initial conditions used for the droplet size specification. However, it was shown that decent droplet size comparisons could be achieved with properly selected initial conditions, For the case considered, it is reasonable to assume that the present vaporization models are capable of providing a reasonable qualitative description for the two-phase jet characteristics generated by a ashing jet. However, there remains some uncertainty with regard to the specification of certain initial spray conditions and there is a need for experimental data on separate gas and liquid temperatures in order to validate the vaporization models based on the Adachi correlation for a liquid involving R134A.

Raju, M. S.↗
NASA NTRS1993

The hot stellar component in elliptical galaxies and spiral bulges. I - The far-ultraviolet spectrum of the bulge of M31

An analysis of the M31 spectrum is presented and compared to the spectrum of NGC 1399. There are significant differences between the two spectra that cannot easily be explained by uncertainties in extinction. The M31 spectrum requires a contribution from stars hotter than those that dominate the NGC 1399 spectral energy distribution. It is found that an acceptable fit to the M31 spectrum can be produced by assuming that it consists of stars like those in NGC 1399, combined with a much higher proportion of classical post-asymptotic giant branch stars. This result is not completely conclusive because of uncertainties in extinction, but it agrees with the idea that as metallicity increases, so does the contribution from extreme horizontal branch stars, post-early-AGB stars, and AGB-Manque stars.

Ferguson, Henry C.↗
NASA NTRS2015

Random Predictor Models for Rigorous Uncertainty Quantification: Part 2

This and a companion paper propose techniques for constructing parametric mathematical models describing key features of the distribution of an output variable given input-output data. By contrast to standard models, which yield a single output value at each value of the input, Random Predictors Models (RPMs) yield a random variable at each value of the input. Optimization-based strategies for calculating RPMs having a polynomial dependency on the input and a linear dependency on the parameters are proposed. These formulations yield RPMs having various levels of fidelity in which the mean, the variance, and the range of the model's parameter, thus of the output, are prescribed. As such they encompass all RPMs conforming to these prescriptions. The RPMs are optimal in the sense that they yield the tightest predictions for which all (or, depending on the formulation, most) of the observations are less than a fixed number of standard deviations from the mean prediction. When the data satisfies mild stochastic assumptions, and the optimization problem(s) used to calculate the RPM is convex (or, when its solution coincides with the solution to an auxiliary convex problem), the model's reliability, which is the probability that a future observation would be within the predicted ranges, is bounded rigorously.

Crespo, Luis G.↗
NASA NTRS2015

Random Predictor Models for Rigorous Uncertainty Quantification: Part 1

This and a companion paper propose techniques for constructing parametric mathematical models describing key features of the distribution of an output variable given input-output data. By contrast to standard models, which yield a single output value at each value of the input, Random Predictors Models (RPMs) yield a random variable at each value of the input. Optimization-based strategies for calculating RPMs having a polynomial dependency on the input and a linear dependency on the parameters are proposed. These formulations yield RPMs having various levels of fidelity in which the mean and the variance of the model's parameters, thus of the predicted output, are prescribed. As such they encompass all RPMs conforming to these prescriptions. The RPMs are optimal in the sense that they yield the tightest predictions for which all (or, depending on the formulation, most) of the observations are less than a fixed number of standard deviations from the mean prediction. When the data satisfies mild stochastic assumptions, and the optimization problem(s) used to calculate the RPM is convex (or, when its solution coincides with the solution to an auxiliary convex problem), the model's reliability, which is the probability that a future observation would be within the predicted ranges, can be bounded tightly and rigorously.

Crespo, Luis G.↗
NASA NTRS2017

Direct Estimation of the Global Distribution of Vertical Velocity Within Cirrus Clouds

Cirrus clouds determine the radiative balance of the upper troposphere and the transport of water vapor across the tropopause.The representation of vertical wind velocity, W, in atmospheric models constitutes the largest source of uncertainty in the calculation of the cirrus formation rate. Using global atmospheric simulations with a spatial resolution of 7 kilometers we obtain for the first time a direct estimate of the distribution of W at the scale relevant for cirrus formation, validated against long-term observations at two different ground sites. The standard deviation in W, sigma (sub W), varies widely over the globe with the highest values resulting from orographic uplift and convection, and the lowest occurring in the Arctic. Globally about 90 of the simulated sigma (sub W) values are below 0.1 meters per second and about one in 10 (sup 4) cloud formation events occur in environments with sigma (sub W) greater than 0.8 meters per second. Combining our estimate with reanalysis products and an advanced cloud formation scheme results in lower homogeneous ice nucleation frequency than previously reported, and a decreasing average ice crystal concentration with decreasing temperature. These features are in agreement with observations and suggest that the correct parameterization of sigma (sub W) is critical to simulate realistic cirrus properties.

Radiative Balance↗
NASA NTRS2004

Probabilistic Aeroelastic Analysis of Turbomachinery Components

A probabilistic approach is described for aeroelastic analysis of turbomachinery blade rows. Blade rows with subsonic flow and blade rows with supersonic flow with subsonic leading edge are considered. To demonstrate the probabilistic approach, the flutter frequency, damping and forced response of a blade row representing a compressor geometry is considered. The analysis accounts for uncertainties in structural and aerodynamic design variables. The results are presented in the form of probabilistic density function (PDF) and sensitivity factors. For subsonic flow cascade, comparisons are also made with different probabilistic distributions, probabilistic methods, and Monte-Carlo simulation. The approach shows that the probabilistic approach provides a more realistic and systematic way to assess the effect of uncertainties in design variables on the aeroelastic instabilities and response.

Reddy, T. S. R.↗
NASA NTRS2018

Influence of Precipitation Forcing Uncertainty on Hydrological Simulations with the NASA South Asia Land Data Assimilation System

Accurate meteorological estimates are critical for process-based hydrological simulationand prediction. This presents a significant challenge in mountainous Asia where in situmeteorological stations are limited and major river basins cross international borders. In thiscontext, remotely sensed and model-derived meteorological estimates are often necessary inputsfor distributed hydrological analysis. However, these datasets are difficult to evaluate on accountof limited access to ground data. In this case, the implications of uncertainty associated withprecipitation forcing for hydrological simulations is explored by driving the South Asia Land DataAssimilation System (South Asia LDAS) using a range of meteorological forcing products.MERRA2, GDAS, and CHIRPS produce a wide range of estimates for rainfall, which causes awidespread simulated streamflow and evapotranspiration. A combination of satellite-derived andlimited in situ data are applied to evaluate model simulations and, by extension, to constrain theestimates of precipitation. The results show that available gridded precipitation estimates based onin situ data may systematically underestimate precipitation in mountainous regions and thatperformance of gridded satellite-derived or modeled precipitation estimates varies systematicallyacross the region. Since no station-based data or product including station data is satisfactoryeverywhere, our results suggest that the evaluation of the hydrological simulation of streamflowand ET can be used as an indirect evaluation of precipitation forcing based on ground-basedproducts or in-situ data. South Asia LDAS produces reasonable evapotranspiration and streamflowwhen forced with appropriate meteorological forcing and the choice of meteorological forcingshould be made based on the geographical location as well as on the purpose of the simulations.

South Asia land data assimilation system (South As↗
NASA NTRS1978

Navier-Stokes calculations for laminar and turbulent hypersonic flow over indented nosetips

A time-accurate finite-difference Navier-Stokes code has been used to calculate the viscous flow over a severely indented blunt body in a supersonic stream. An algebraic turbulence model is used and the results are compared with experimental data from wind-tunnel tests. Qualitative agreement is obtained for the surface pressure distribution and flow-field structure, including the separated bubble in the indented region. However, uncertainties still exist in the heating calculations, which are attributed to the turbulence model. For both laminar and turbulent calculations, the flow exhibits a fundamental unsteady character at a frequency of about 50 kHz.

Rakich, J. V.↗