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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 505 records · Page 28
All sourcesNASA NTRSDOE OSTI
NASA NTRS1972

Aerodynamic parameters of the Navion airplane extracted from flight

An iterative method, which is characterized as a maximum-likelihood minimum-variance technique, was used to extract the aerodynamic parameters of a Navion airplane from flight data. The purposes were to compare the results with parameters obtained from wind-tunnel tests and with results obtained by analog matching the same data, and to develop techniques for application of the parameter extraction program. Results from the study showed that the parameter-extraction program can produce aerodynamic parameters which will permit close estimation of the aircraft time histories used in the extraction process. The program determined an estimate of the standard deviations of the states and parameters. These estimates were used to indicate how well the calculated states fit the flight data and the confidence in the values of the estimated parameters. The study also showed that the values of the parameters were affected by the data and mathematical model used during the extraction process. Because of the lack of confidence in the parameters extracted by use of some of the sets of data, several parameters were estimated by other methods. By using a combination of methods, a set of parameters which gave a fit to the data was obtained.

Suit, W. T.↗
NASA NTRS1972

Monte Carlo inversion of seismic data

The analytic solution to the linear inverse problem provides estimates of the uncertainty of the solution in terms of standard deviations of corrections to a particular solution, resolution of parameter adjustments, and information distribution among the observations. It is shown that Monte Carlo inversion, when properly executed, can provide all the same kinds of information for nonlinear problems. Proper execution requires a relatively uniform sampling of all possible models. The expense of performing Monte Carlo inversion generally requires strategies to improve the probability of finding passing models. Such strategies can lead to a very strong bias in the distribution of models examined unless great care is taken in their application.

Wiggins, R. A.↗
NASA NTRS1977

Remote estimation of surface temperature in pollution measurement experiments

The procedure described was developed for inferring the effective brightness temperature (EBT) of the underlying surface (at a given altitude) from the computed value of the radiance corresponding to a known surface temperature. A standard temperature correction to EBT (termed 'base correction') is first determined by using a 'base model atmosphere' for computing the upwelling radiance. Additional temperature corrections are then determined by considering several variations of the different surface and atmospheric parameters from their 'base model' values. Empirical relations are derived between the deviations of various surface and atmospheric parameters (from their base model values) and the additional corrections required for the EBT as a result of these variations. Use of such relations for large-scale data reduction, instead of radiative transfer calculations, is expected to result in drastic cost decrease.

Gupta, S. K.↗
NASA NTRS1986

The Nimbus 7 LIMS map archival tape

The development of the Langley Map Archival Tape (LAMAT) is described. The role of the Nimbus 7 orbit characteristics in the analysis and interpretation of LAMAT data is discussed. The pressure ranges and heights for the LAMAT components are given and the synoptic fields for each pressure and latitude were modeled as Fourier series in longitude with time-dependent coefficients. Examples of LAMAT temperature fields are presented and the accuracies of the LAMAT fields are evaluated. The fit between the Langley inverted profile archival tape (LAIPAT) and LAMAT is examined by comparing averaged zonal mean fields and standard deviations. Consideration is given to diurnal variations of LAIPAT data, and the time and spatial smoothing of the data.

Haggard, K. V.↗
NASA NTRS2011

CUDA Simulation of Homogeneous, Incompressible Turbulence

We discuss very fast Compute Unified Device Architecture (CUDA) simulations of ideal homogeneous incompressible turbulence based on Fourier models. These models have associated statistical theories that predict that Fourier coefficients of fluid velocity and magnetic fields (if present) are zero-mean random variables. Prior numerical simulations have shown that certain coefficients have a non-zero mean value that can be very large compared to the associated standard deviation. We review the theoretical basis of this "broken ergodicity" as applied to 2-D and 3-D fluid and magnetohydrodynamic simulations of homogeneous turbulence. Our new simulations examine the phenomenon of broken ergodicity through very long time and large grid size runs performed on a state-of-the-art CUDA platform. Results comparing various CUDA hardware configurations and grid sizes are discussed. NS and MHD results are compared.

Morin, Lee↗
NASA NTRS2023

Split-Step Simulations to Assess the Effects of Atmospheric Boundary Layer Turbulence on the Dose Variability of N-Waves and Shaped Booms

The effects of atmospheric boundary layer turbulence on the loudness variability of a sonic boom N-wave and shaped boom are examined with split-step simulations. The shaped boom is representative of a design iteration of the NASA X-59 aircraft. Inhomogeneous atmospheric boundary layer turbulence is generated in the computational domain by a Fourier synthesis method. The N-wave and shaped boom are propagated through turbulent fields representing eight different convection levels measured at the NASA Kennedy Space Center and the NASA Armstrong Flight Research Center. Probability density functions of the formation of caustic regions along the propagation direction are computed from the N-wave results, and a parameter to collapse the caustic PDFs that accounts for both fluctuation intensities and length scales is proposed. Statistical results concerning loudness metric variability are presented, and the standard deviations of several metrics are shown to collapse across different convection levels of turbulence for small nondimensional propagation distances. The loudness metric distributions are observed to be well approximated by a normal distribution for a given range of propagation distances, and become increasingly skewed as distance increases. A model function for the dose variability is proposed, and the function parameters are found to be related to the convection level of the turbulence. The model for the dose variability distribution is compared to simulation data that were not used to find the regression parameters of the model. At several nondimensional propagation distances, agreement is observed between the model and the simulation data. These results indicate that the model may be suitable for providing quick estimates of noise dose variability in the primary carpet region across a wide range of atmospheric boundary layer conditions.

Sonic boom↗
NASA NTRS2013

A Multimodel Assessment of the Influence of Regional Anthropogenic Emission Reductions on Aerosol Direct Radiative Forcing and the Role of Intercontinental Transport

In this study, we assess changes of aerosol optical depth (AOD) and direct radiative forcing (DRF) in response to the reduction of anthropogenic emissions in four major pollution regions in the Northern Hemisphere by using results from nine global models in the framework of the Hemispheric Transport of Air Pollution (HTAP). DRF at top of atmosphere (TOA) and surface is estimated based on AOD results from the HTAP models and AOD-normalized DRF (NDRF) from a chemical transport model. The multimodel results show that, on average, a 20% reduction of anthropogenic emissions in North America, Europe, East Asia, and South Asia lowers the global mean AOD (all-sky TOA DRF) by 9.2% (9.0%), 3.5% (3.0%), and 9.4% (10.0%) for sulfate, particulate organic matter (POM), and black carbon (BC), respectively. Global annual average TOA all-sky forcing efficiency relative to particle or gaseous precursor emissions from the four regions (expressed as multimodel mean +/- one standard deviation) is -3.5 +/-0.8, -4.0 +/- 1.7, and 29.5+/-18.1mW / sq m per Tg for sulfate (relative to SO2), POM, and BC, respectively. The impacts of the regional emission reductions on AOD and DRF extend well beyond the source regions because of intercontinental transport (ICT). On an annual basis, ICT accounts for 11 +/- 5% to 31 +/- 9% of AOD and DRF in a receptor region at continental or subcontinental scale, with domestic emissions accounting for the remainder, depending on regions and species. For sulfate AOD, the largest ICT contribution of 31 +/- 9% occurs in South Asia, which is dominated by the emissions from Europe. For BC AOD, the largest ICT contribution of 28 +/- 18% occurs in North America, which is dominated by the emissions from East Asia. The large spreads among models highlight the need to improve aerosol processes in models, and evaluate and constrain models with observations.

Europe↗
DOE OSTI2026

Statistical Uncertainty of Inhalation Dose Coefficients in Consequence Management: Propagated Dose Uncertainty in ICRP 66 Human Respiratory Tract Model

Reference inhalation dose models rely on deterministic biokinetics and reference computational phantoms, limiting their applicability to the variability present in population-specific exposures encountered in emergency response scenarios. Here, this study introduces REDCAL, a Python-based computational framework developed to propagate uncertainty in inhalation dose coefficients using the International Commission on Radiological Protection (ICRP) Publication 66 Human Respiratory Tract Model. REDCAL integrates ICRP deposition and clearance models, systemic biokinetics, and governing physics principles, and leverages Sandia National Laboratories’ Dakota toolkit for uncertainty quantification via Latin Hypercube Sampling. REDCAL was validated against DCAL, with biokinetic retention results differing by less than 1% and effective dose coefficients by less than 2% across all tested radionuclides. Stochastic sampling introduced variability in dose coefficients, with geometric standard deviations (GSD) in committed effective dose coefficients (CEDC) ranging from 1.0 to 1.5, based on lognormal distribution fits. Analysis demonstrated that variations in the activity median aerodynamic diameter (AMAD) notably influenced the computed CEDC values. Smaller particles (<1 µm) increased doses by 20–30% due to deeper lung deposition and prolonged retention for alpha emitting radionuclides, such as 241 Am and 239 Pu. Radionuclides with fast clearance, such as 133 I, demonstrated a dose reduction exceeding 50%, as AMAD increased beyond 5 µm due to upper airway deposition and rapid mucociliary clearance. The greatest GSD among the radionuclides reported in this study was for 241 Am. In most cases, the largest GSDs in the CEDC were associated with larger particle sizes, an expected outcome, as ICRP Publication 66 defines GSD in particle size as a function of AMAD, resulting in an extended tail of the lognormal distribution. The findings support improved inhalation dose assessments and enhance consequence management strategies for the U.S. Federal Radiological Monitoring and Assessment Center by quantifying uncertainty in dose coefficients and strengthening decision-making for emergency response scenarios.

Biokinetic Modeling↗
NASA NTRS2019

Arctic Amplification Response to Individual Climate Drivers

The Arctic is experiencing rapid climate change in response to changes in greenhouse gases, aerosols and other climate drivers. Emission changes in general, as well as geographical shifts in emissions and transport pathways of shortlived climate forcers, make it necessary to understand the influence of each climate driver on the Arctic. In the Precipitation Driver Response Model Intercomparison Project, ten global climate models perturbed five different climate drivers separately (CO2, CH4, the solar constant, BC and SO4). We show that the annual mean Arctic amplification (defined as the ratio between Arctic and the global mean temperature change) at the surface is similar between climate drivers, ranging from 1.9 (± an intermodel standard deviation of 0.4) for the solar to 2.3 (± 0.6) for the SO4 perturbations, with minimum amplification in the summer for all drivers. The vertical and seasonal temperature response patterns indicate that the Arctic is warmed through similar mechanisms for all climate drivers except BC. For all drivers, the precipitation change per degree global temperature change is positive in the Arctic, with a seasonality following that of the Arctic amplification. We find indications that SO4 perturbations produce a slightly stronger precipitation response than the other drivers, particularly compared to CO2.

greenhouse gases↗
DOE OSTI2026

More concentrated precipitation decreases terrestrial water storage

Terrestrial water availability is a key determinant of human and ecosystem well-being. Apart from mean precipitation and evaporation changes, it is unknown how daily-scale precipitation concentration into fewer, heavier events affects hydrologic partitioning and the land water balance. Here we show observationally that more concentrated precipitation decreases land water availability across all climates globally, a drying effect as strong in magnitude as the wetting effect of increased total precipitation. Simple and complex land-surface models recover the observed effect, whereas idealized simulations show that it arises from enhanced evaporation caused by hydrologic partitioning changes at the land surface. Projected terrestrial water storage impacts of warming-driven precipitation concentration at about 2 °C of warming shift the land surface to abnormally dry conditions (≥0.5 standard deviation) for 27% of the global population, independent of any total precipitation or irrigation changes. Our results show new key determinants of the land water balance, highlighting its sensitivity to the temporal distribution of precipitation, with broad implications for future water availability.

climate change↗
NASA NTRS1979

A method for predicting the noise levels of coannular jets with inverted velocity profiles

A coannular jet was equated with a single stream equivalent jet with the same mass flow, energy, and thrust. The acoustic characteristics of the coannular jet were then related to the acoustic characteristics of the single jet. Forward flight effects were included by incorporating a forward exponent, a Doppler amplification factor, and a Strouhal frequency shift. Model test data, including 48 static cases and 22 wind tunnel cases, were used to evaluate the prediction method. For the static cases and the low forward velocity wind tunnel cases, the spectral mean square pressure correlation coefficients were generally greater than 90 percent, and the spectral sound pressure level standard deviation were generally less than 3 decibels. The correlation coefficient and the standard deviation were not affected by changes in equivalent jet velocity. Limitations of the prediction method are also presented.

Russell, J. W.↗
NASA NTRS1986

Simulated laser fluorosensor signals from subsurface chlorophyll distributions

A semianalytic Monte Carlo model has been used to simulate laser fluorosensor signals returned from subsurface distributions of chlorophyll. This study assumes the only constituent of the ocean medium is the common coastal zone dinoflagellate Prorocentrum minimum. The concentration is represented by Gaussian distributions in which the location of the distribution maximum and the standard deviation are variable. Most of the qualitative features observed in the fluorescence signal for total chlorophyll concentrations up to 1.0 microg/liter can be accounted for with a simple analytic solution assuming a rectangular chlorophyll distribution function.

Venable, D. D.↗
DOE OSTI2024

Model-independent search for pair production of new bosons decaying into muons in proton-proton collisions at $\sqrt{s}$ = 13 TeV

The results of a model-independent search for the pair production of new bosons within a mass range of 0.21 < m < 60 GeV, are presented. This study utilizes events with a four-muon final state. We use two data sets, comprising 41.5 fb −1 and 59.7 fb −1 of proton-proton collisions at $\sqrt{s}$ = 13 TeV, recorded in 2017 and 2018 by the CMS experiment at the CERN LHC. The study of the 2018 data set includes a search for displaced signatures of a new boson within the proper decay length range of 0 < cτ < 100 mm. Our results are combined with a previous CMS result, based on 35.9 fb −1 of proton-proton collisions at $\sqrt{s}$ = 13 TeV collected in 2016. No significant deviation from the expected background is observed. Results are presented in terms of a model-independent upper limit on the product of cross section, branching fraction, and acceptance. The findings are interpreted across various benchmark models, such as an axion-like particle model, a vector portal model, the next-to-minimal supersymmetric standard model, and a dark supersymmetric scenario, including those predicting a non-negligible proper decay length of the new boson. In all considered scenarios, substantial portions of the parameter space are excluded, expanding upon prior results.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

Observation of a cross-section enhancement near the production threshold in $\sqrt{s} = 13$ TeV pp collisions with the ATLAS detector

A measurement of $t\bar{t}$ production is presented in the invariant-mass region near the pair production threshold, $m_{t\bar{t}} \sim 345$ GeV, in final states with two charged leptons and multiple jets. The measurement is based on $140\,\mathrm{fb}^{-1}$ of proton–proton collision data collected at $\sqrt{s} = 13$ TeV with the ATLAS detector at the Large Hadron Collider. The data are compared to two models of $t\bar{t}$ production: a baseline model including only perturbative quantum chromodynamics (pQCD) predictions for the hard process at approximate next-to-next-to leading order accuracy in the strong coupling, and an extended model that, in addition, incorporates non-relativistic QCD simulations that also include the formation of colour-singlet quasi-bound-states near the $t\bar{t}$ threshold. The agreement between the data and the models is quantified via a profile-likelihood fit to the reconstructed $m_{t\bar{t}}$ distributions, in bins of two angular observables sensitive to spin-correlations in the $t\bar{t}$ system. An excess of events is observed over the baseline pQCD prediction, with an observed significance over 8 standard deviations. This excess is consistent with the formation of colour-singlet and spin-singlet S-wave quasi-bound $t\bar{t}$ states, as predicted by non-relativistic QCD, and corresponds to an observed cross-section of $9.3^{+1.4}_{-1.3}$ pb.

Large Hadron Collider↗
NASA NTRS2003

Historical Precision of an Ozone Correction Procedure for AMO Solar Cell Calibration

In an effort to improve the accuracy of the high altitude aircraft method for calibration of high band-gap solar cells, the ozone correction procedure has been revisited. The new procedure adjusts the measured short circuit current, Isc, according to satellite based ozone measurements and a model of the atmospheric ozone profile then extrapolates the measurements to air mass zero, AM0. The purpose of this paper is to assess the precision of the revised procedure by applying it to historical data sets. The average Isc of a silicon cell for a flying season increased 0.5% and the standard deviation improved from 0.5% to 0.3% The 12 year average Isc of a GaAs cell increased 1% and the standard deviation improved from 0.8% to 0.5%. The slight increase in measured Isc and improvement in standard deviation suggests that the accuracy of the aircraft method may improve from 1% to nearly 0.5%.

Snyder, David B.↗
NASA NTRS2005

Historical Precision of an Ozone Correction Procedure for AM0 Solar Cell Calibration

In an effort to improve the accuracy of the high altitude aircraft method for calibration of high band-gap solar cells, the ozone correction procedure has been revisited. The new procedure adjusts the measured short circuit current, Isc, according to satellite based ozone measurements and a model of the atmospheric ozone profile then extrapolates the measurements to air mass zero, AMO. The purpose of this paper is to assess the precision of the revised procedure by applying it to historical data sets. The average Isc of a silicon cell for a flying season increased 0.5% and the standard deviation improved from 0.5% to 0.3%. The 12 year average Isc of a GaAs cell increased 1% and the standard deviation improved from 0.8% to 0.5%. The slight increase in measured Isc and improvement in standard deviation suggests that the accuracy of the aircraft method may improve from 1% to nearly 0.5%.

Snyder, David B.↗
NASA NTRS2019

Version 4 of the SMAP Level-4 Soil Moisture Algorithm and Data Product

The NASA Soil Moisture Active Passive (SMAP) mission Level-4 Soil Moisture (L4_SM) product provides global, 3-hourly, 9-km resolution estimates of surface (0-5 cm) and root-zone (0-100 cm) soil moisture with a mean latency of ~2.5 days. The underlying L4_SM algorithm assimilates SMAP radiometer brightness temperature (Tb) observations into the NASA Catchment land surface model using a spatially-distributed ensemble Kalman filter. Version 4 of the L4_SM modeling system includes a reduction in the upward recharge of surface soil moisture from below under non-equilibrium conditions, resulting in reduced bias and improved dynamic range of L4_SM surface soil moisture compared to earlier versions. This change and additional technical modifications to the system reduce the mean and standard deviation of the observation-minus-forecast Tb residuals and overall soil moisture analysis increments while maintaining the skill of the L4_SM soil moisture estimates versus independent in situ measurements; the average, bias-adjusted RMSE in Version 4 is 0.039 m(exp 3) m(exp -3) for surface and 0.026 m(exp 3) m(exp -3) for root-zone soil moisture. Moreover, the coverage of assimilated SMAP observations in Version 4 is near-global owing to the use of additional satellite Tb records for algorithm calibration. L4_SM soil moisture uncertainty estimates are biased low (by 0.01-0.02 m(exp 3) m(exp -3)) against actual errors (computed versus in situ measurements). L4_SM runoff estimates, an additional product of the L4_SM algorithm, are biased low (by 35 mm year (exp -1)) against streamflow measurements. Compared to Version 3, bias in Version 4 is reduced by 46% for surface soil moisture uncertainty estimates and by 33% for runoff estimates.

RMSE↗
NASA NTRS2014

Status of the NASA GMAO Observing System Simulation Experiment

An Observing System Simulation Experiment (OSSE) is a pure modeling study used when actual observations are too expensive or difficult to obtain. OSSEs are valuable tools for determining the potential impact of new observing systems on numerical weather forecasts and for evaluation of data assimilation systems (DAS). An OSSE has been developed at the NASA Global Modeling and Assimilation Office (GMAO, Errico et al 2013). The GMAO OSSE uses a 13-month integration of the European Centre for Medium- Range Weather Forecasts 2005 operational model at T511/L91 resolution for the Nature Run (NR). Synthetic observations have been updated so that they are based on real observations during the summer of 2013. The emulated observation types include AMSU-A, MHS, IASI, AIRS, and HIRS4 radiance data, GPS-RO, and conventional types including aircraft, rawinsonde, profiler, surface, and satellite winds. The synthetic satellite wind observations are colocated with the NR cloud fields, and the rawinsondes are advected during ascent using the NR wind fields. Data counts for the synthetic observations are matched as closely as possible to real data counts, as shown in Figure 2. Errors are added to the synthetic observations to emulate representativeness and instrument errors. The synthetic errors are calibrated so that the statistics of observation innovation and analysis increments in the OSSE are similar to the same statistics for assimilation of real observations, in an iterative method described by Errico et al (2013). The standard deviations of observation minus forecast (xo-H(xb)) are compared for the OSSE and real data in Figure 3. The synthetic errors include both random, uncorrelated errors, and an additional correlated error component for some observational types. Vertically correlated errors are included for conventional sounding data and GPS-RO, and channel correlated errors are introduced to AIRS and IASI (Figure 4). HIRS, AMSU-A, and MHS have a component of horizontally correlated error. The forecast model used by the GMAO OSSE is the Goddard Earth Observing System Model, Version 5 (GEOS-5) with Gridpoint Statistical Interpolation (GSI) DAS. The model version has been updated to v. 5.13.3, corresponding to the current operational model. Forecasts are run on a cube-sphere grid with 180 points along each edge of the cube (approximately 0.5 degree horizontal resolution) with 72 vertical levels. The DAS is cycled at 6-hour intervals, with 240 hour forecasts launched daily at 0000 UTC. Evaluation of the forecasting skill for July and August is currently underway. Prior versions of the GMAO OSSE have been found to have greater forecasting skill than real world forecasts. It is anticipated that similar forecast skill will be found in the updated OSSE.

OSSE↗