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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
NASA NTRS1989

Ozone reference models for the middle atmosphere (new CIRA)

Models of ozone vertical structure were generated that were based on multiple data sets from satellites. The very good absolute accuracy of the individual data sets allowed the data to be directly combined to generate these models. The data used for generation of these models are from some of the most recent satellite measurements over the period 1978 to 1983. A discussion is provided of validation and error analyses of these data sets. Also, inconsistencies in data sets brought about by temporal variations or other factors are indicated. The models cover the pressure range from from 20 to 0.003 mb (25 to 90 km). The models for pressures less than 0.5 mb represent only the day side and are only provisional since there was limited longitudinal coverage at these levels. The models start near 25 km in accord with previous COSPAR international reference atmosphere (CIRA) models. Models are also provided of ozone mixing ratio as a function of height. The monthly standard deviation and interannual variations relative to zonal means are also provided. In addition to the models of monthly latitudinal variations in vertical structure based on satellite measurements, monthly models of total column ozone and its characteristic variability as a function of latitude based on four years of Nimbus 7 measurements, models of the relationship between vertical structure and total column ozone, and a midlatitude annual mean model are incorporated in this set of ozone reference atmospheres. Various systematic variations are discussed including the annual, semiannual, and quasibiennial oscillations, and diurnal, longitudinal, and response to solar activity variations.

Keating, G. M.↗
NASA NTRS1994

Probabilistic Material Strength Degradation Model for Inconel 718 Components Subjected to High Temperature, Mechanical Fatigue, Creep and Thermal Fatigue Effects

This thesis presents the on-going development of methodology for a probabilistic material strength degradation model. The probabilistic model, in the form of a postulated randomized multifactor equation, provides for quantification of uncertainty in the lifetime material strength of aerospace propulsion system components subjected to a number of diverse random effects. This model is embodied in the computer program entitled PROMISS, which can include up to eighteen different effects. Presently, the model includes four effects that typically reduce lifetime strength: high temperature, mechanical fatigue, creep, and thermal fatigue. Statistical analysis was conducted on experimental Inconel 718 data obtained from the open literature. This analysis provided regression parameters for use as the model's empirical material constants, thus calibrating the model specifically for Inconel 718. Model calibration was carried out for four variables, namely, high temperature, mechanical fatigue, creep, and thermal fatigue. Methodology to estimate standard deviations of these material constants for input into the probabilistic material strength model was developed. Using the current version of PROMISS, entitled PROMISS93, a sensitivity study for the combined effects of mechanical fatigue, creep, and thermal fatigue was performed. Results, in the form of cumulative distribution functions, illustrated the sensitivity of lifetime strength to any current value of an effect. In addition, verification studies comparing a combination of mechanical fatigue and high temperature effects by model to the combination by experiment were conducted. Thus, for Inconel 718, the basic model assumption of independence between effects was evaluated. Results from this limited verification study strongly supported this assumption.

Bast, Callie Corinne Scheidt↗
NASA NTRS2011

MesoNAM Verification Phase II

The 45th Weather Squadron Launch Weather Officers use the 12-km resolution North American Mesoscale model (MesoNAM) forecasts to support launch weather operations. In Phase I, the performance of the model at KSC/CCAFS was measured objectively by conducting a detailed statistical analysis of model output compared to observed values. The objective analysis compared the MesoNAM forecast winds, temperature, and dew point to the observed values from the sensors in the KSC/CCAFS wind tower network. In Phase II, the AMU modified the current tool by adding an additional 15 months of model output to the database and recalculating the verification statistics. The bias, standard deviation of bias, Root Mean Square Error, and Hypothesis test for bias were calculated to verify the performance of the model. The results indicated that the accuracy decreased as the forecast progressed, there was a diurnal signal in temperature with a cool bias during the late night and a warm bias during the afternoon, and there was a diurnal signal in dewpoint temperature with a low bias during the afternoon and a high bias during the late night.

Watson, Leela R.↗
NASA NTRS1985

Calculations of microwave brightness temperature of rough soil surfaces: Bare field

A model for simulating the brightness temperatures of soils with rough surfaces is developed. The surface emissivity of the soil media is obtained by the integration of the bistatic scattering coefficients for rough surfaces. The roughness of a soil surface is characterized by two parameters, the surface height standard deviation sigma and its horizontal correlation length l. The model calculations are compared to the measured angular variations of the polarized brightness temperatures at both 1.4 GHz and 5 GHz frequences. A nonlinear least-squares fitting method is used to obtain the values of delta and l that best characterize the surface roughness. The effect of shadowing is incorporated by introducing a function S(theta), which represents the probability that a point on a rough surface is not shadowed by other parts of the surface. The model results for the horizontal polarization are in excellent agreement with the data. However, for the vertical polarization, some discrepancies exist between the calculations and data, particularly at the 1.4 GHz frequency. Possible causes of the discrepancy are discussed.

Mo, T.↗
NASA NTRS1985

Calculations of microwave brightness temperature of rough soil surfaces

A model for simulating the brightness temperatures of soils with rough surfaces is developed. The surface emissivity of the soil media is obtained by the integration of the bistatic scattering coefficients for rough surfaces. The roughness of a soil surface is characterized by two parameters, the surface height standard deviation sigma and its horizontal correlation length l. The model calculations are compared to the measured angular variations of the polarized brightness temperatures at both 1.4 GHz and 5 GHz frequencies. A nonlinear least-squares fitting method is used to obtain the values of delta and l that best characterize the surface roughness. The effect of shadowing is incorporated by introducing a function S(theta), which represents the probability that a point on a rough surface is not shadowed by other parts of the surface. The model results for the horizontal polarization are in excellent agreement with the data. However, for the vertical polarization, some discrepancies exist between the calculations and data, particularly at the 1.4 GHz frequency. Possible causes of the discrepancy are discussed.

Mo, T.↗
NASA NTRS2009

Estimating Volume, Biomass, and Carbon in Hedmark County, Norway Using a Profiling LiDAR

A profiling airborne LiDAR is used to estimate the forest resources of Hedmark County, Norway, a 27390 square kilometer area in southeastern Norway on the Swedish border. One hundred five profiling flight lines totaling 9166 km were flown over the entire county; east-west. The lines, spaced 3 km apart north-south, duplicate the systematic pattern of the Norwegian Forest Inventory (NFI) ground plot arrangement, enabling the profiler to transit 1290 circular, 250 square meter fixed-area NFI ground plots while collecting the systematic LiDAR sample. Seven hundred sixty-three plots of the 1290 plots were overflown within 17.8 m of plot center. Laser measurements of canopy height and crown density are extracted along fixed-length, 17.8 m segments closest to the center of the ground plot and related to basal area, timber volume and above- and belowground dry biomass. Linear, nonstratified equations that estimate ground-measured total aboveground dry biomass report an R(sup 2) = 0.63, with an regression RMSE = 35.2 t/ha. Nonstratified model results for the other biomass components, volume, and basal area are similar, with R(sup 2) values for all models ranging from 0.58 (belowground biomass, RMSE = 8.6 t/ha) to 0.63. Consistently, the most useful single profiling LiDAR variable is quadratic mean canopy height, h (sup bar)(sub qa). Two-variable models typically include h (sup bar)(sub qa) or mean canopy height, h(sup bar)(sub a), with a canopy density or a canopy height standard deviation measure. Stratification by productivity class did not improve the nonstratified models, nor did stratification by pine/spruce/hardwood. County-wide profiling LiDAR estimates are reported, by land cover type, and compared to NFI estimates.

Nelson, Ross↗
NASA NTRS1986

Ground-based time-guidance algorithm for control of airplanes in a time-metered air traffic control environment: A piloted simulation study

The rapidly increasing costs of flight operations and the requirement for increased fuel conservation have made it necessary to develop more efficient ways to operate airplanes and to control air traffic for arrivals and departures to the terminal area. One concept of controlling arrival traffic through time metering has been jointly studied and evaluated by NASA and ONERA/CERT in piloted simulation tests. From time errors attained at checkpoints, airspeed and heading commands issued by air traffic control were computed by a time-guidance algorithm for the pilot to follow that would cause the airplane to cross a metering fix at a preassigned time. These tests resulted in the simulated airplane crossing a metering fix with a mean time error of 1.0 sec and a standard deviation of 16.7 sec when the time-metering algorithm was used. With mismodeled winds representing the unknown in wind-aloft forecasts and modeling form, the mean time error attained when crossing the metering fix was increased and the standard deviation remained approximately the same. The subject pilots reported that the airspeed and heading commands computed in the guidance concept were easy to follow and did not increase their work load above normal levels.

Knox, C. E.↗
NASA NTRS2014

AG Channel Measurement and Modeling Results for Over-Sea Conditions

This report describes results from flight tests conducted in an over-sea environment, for the purpose of characterizing the air-to-ground (AG) channel, for future unmanned aircraft system (UAS) communication system analysis and design. These results are for the first of a set of several flight tests conducted in different ground site (GS) environments. An ultimate aim of all these tests is the development of models for the AG channel that can be used in communication system evaluation. In this report we provide measured results for propagation path loss, root-mean square delay spread (RMS-DS), and the correlation coefficient of the primary received signal components on the four antennas (two antennas for C-band, two for L-band). For path loss, the curved-earth two-ray model provides a reasonable fit to the measured data, altered by several dB at the shortest link distances by aircraft antenna pattern effects. This two-ray model also accounts for the majority of measured RMS-DS results of a few tens of nanoseconds, except for the occasional intermittent reflections from surface objects. These intermittent reflections yield RMS-DS values up to several hundred nanoseconds. For portions of the flight path that were over a harbor area highly populated with boats, the channel was found to be more "continuously dispersive," with RMS-DS reaching approximately 250 ns. A separate model will be developed for this over-harbor setting. The correlation coefficient results are still undergoing analysis; preliminary observations are that correlation between signals on the same-band antennas is generally large (>0.6) for the C-band straight flight paths, whereas for the L-band signals and for the oval-shaped flight paths the correlation is generally small (below 0.4). Inter-band correlations are typically very small, and are well modeled as zero-mean Gaussian in distribution, with a standard deviation less than 0.2. Hence the over-sea channel effects in the two bands can be considered uncorrelated, which will allow for good diversity gains in dual-band systems. We describe initial modeling approaches for the over-sea channel; complete models for this and the over-harbor setting will appear in a subsequent report.

Aircraft Communications↗
NASA NTRS1988

The effects of geopotential resonance on orbit determination for Landsat-4

Analysis is presented demonstrating improved performance for Landsat-4 orbit determination using the Goddard Trajectory Determination System with an adjusted Goddard Earth Model-9 (GEM-9) for geopotential coefficients of the 15th degree and order. The orbital state is estimated along with the sine and cosine coefficients of degree and order 15, (C, S) sub 15,15. The estimates are made for two 5-day intervals of range and doppler data, primarily from the Tracking and Data Relay Satellite, during a period of low solar activity in January 1987. The average values of the estimated coefficients (C, S) sub 15,15 are used to modify the GEM-9 model, and orbit determination performance is tested on 17 consecutive 34-hour operational tracking data arcs in January 1987. Significant reductions in the mean values and standard deviations of the along-track position difference and the drag model scaling parameter from solution to solution are observed. The approach is guided by the shallow resonance theory of geopotential orbit perturbations.

Hoge, S. L.↗
DOE OSTI2025

Test of lepton flavor universality with measurements of 𝑅⁡(𝐷 + ) and 𝑅⁡(𝐷* + ) using semileptonic 𝐵 tagging at the Belle II experiment

We report measurements of the ratios of branching fractions ℛ⁡(𝐷 (*)+ ) = ℬ⁡($\bar{𝐵}$ 0 → 𝐷 (*)+ ⁢𝜏 −⁢ $\bar{𝜈}$ 𝜏 )/ℬ⁡($\bar{𝐵}$ 0 → 𝐷 (*)+ ⁢ℓ − $\bar{𝜈}$ ℓ ), where ℓ denotes either an electron or a muon. These ratios test the universality of the charged-current weak interaction. The results are based on a 365 fb −1 data sample collected with the Belle II detector at the SuperKEKB 𝑒 + ⁢𝑒 − collider, which operates at a center-of-mass energy corresponding to the ϒ⁡(4⁢𝑆) resonance, just above the threshold for $𝐵\bar{𝐵}$ production. Signal candidates are reconstructed by selecting events in which the companion 𝐵 meson from the ϒ⁡(4⁢𝑆) → $𝐵\bar{𝐵}$ decay is identified in semileptonic modes. The 𝜏 lepton is reconstructed via its leptonic decays. We obtain ℛ⁡(𝐷 + ) = 0.418$^{+0.075}_{−0.073}$⁢(stat)$^{+0.049}_{−0.056}$⁢(syst) and ℛ⁡(𝐷 *+ ) = 0.306$^{+0.035}_{−0.033}$⁢(stat)$^{+0.016}_{−0.018⁢}$(syst), which are consistent with world average values. Accounting for the correlation between them, these values differ from the Standard Model expectation by a collective significance of 1.7 standard deviations.

bottom quark↗
DOE OSTI2025

Machine Learning for Automated Weld Quality Monitoring and Control

Resistance Spot Welding (RSW) is a critical process in the automotive industry, valued for its cost-effectiveness, short cycle time, and robustness. However, achieving consistent high-quality joints remains challenging due to the complex interplay of various factors, like materials, processes, and manufacturing uncertainties, etc. Under the collaborative project between Oak Ridge National Laboratory (ORNL) and General Motors (GM), we have developed a robust and expansible machine learning (ML) framework aimed at enhancing quality control in RSW. By harnessing the power of machine learning, we have developed the ability to ensure every aspect of the welding process, from the initial process design stage to the final weld joint quality. The framework operates by analyzing a variety of data streams, including in-line process signals, process parameters, materials, and postprocessed weld joint data. Through this analysis, the models have been trained to detect deviations from optimal quality standards, leveraging their ability to identify signature data patterns and anomalies within in-line signals and construct complex correlations between these signals and weld quality parameters. Meanwhile, the machine learning framework is designed to adapt to a variety of materials, including high strength steels and aluminum alloys, etc. Its flexible architecture facilitates the incorporation of diverse data sources and features, enabling precise modeling and prediction across a broad range of material properties and weld quality variables. The expansible ML frameworks represent a promising transformation in weld quality monitoring and control, empowering industry to achieve high levels of efficiency, consistency, and reliability in manufacturing.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2025

Machine Learning for Automated Weld Quality Monitoring and Control

Resistance Spot Welding (RSW) is a critical process in the automotive industry, valued for its cost-effectiveness, short cycle time, and robustness. However, achieving consistent high-quality joints remains challenging due to the complex interplay of various factors, like materials, processes, and manufacturing uncertainties, etc. Under the collaborative project between Oak Ridge National Laboratory (ORNL) and General Motors (GM), we have developed a robust and expansible machine learning (ML) framework aimed at enhancing quality control in RSW. By harnessing the power of machine learning, we have developed the ability to ensure every aspect of the welding process, from the initial process design stage to the final weld joint quality. The framework operates by analyzing a variety of data streams, including in-line process signals, process parameters, materials, and postprocessed weld joint data. Through this analysis, the models have been trained to detect deviations from optimal quality standards, leveraging their ability to identify signature data patterns and anomalies within in-line signals and construct complex correlations between these signals and weld quality parameters. Meanwhile, the machine learning framework is designed to adapt to a variety of materials, including high strength steels and aluminum alloys, etc. Its flexible architecture facilitates the incorporation of diverse data sources and features, enabling precise modeling and prediction across a broad range of material properties and weld quality variables. The expansible ML frameworks represent a promising transformation in weld quality monitoring and control, empowering industry to achieve high levels of efficiency, consistency, and reliability in manufacturing.

42 ENGINEERING↗
DOE OSTI2024

Heavy Neutral Leptons via Axionlike Particles at Neutrino Facilities

Heavy neutral leptons (HNLs) are often among the hypothetical ingredients behind nonzero neutrino masses. If sufficiently light, they can be produced and detected in fixed-target-like experiments. We show that if the HNLs belong to a richer—but rather generic—dark sector, their production mechanism can deviate dramatically from expectations associated with the standard-model weak interactions. In more detail, we postulate that the dark sector contains an axionlike particle (ALP) that naturally decays into HNLs. Since ALPs mix with the pseudoscalar hadrons, the HNL flux might be predominantly associated with the production of neutral mesons (e.g., π 0 , η ) as opposed to charge hadrons (e.g., π ± , K ± ). In this case, the physics responsible for HNL production and decay are not directly related and experiments like DUNE might be sensitive to HNLs that are too weakly coupled to the standard model to be produced via weak interactions, as is generically the case of HNLs that play a direct role in the type-I seesaw mechanism. Published by the American Physical Society 2024

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS1974

Removal of spacecraft-surface particulate contaminants by simulated micrometeoroid impacts

A series of hypervelocity impacts has been conducted in an exploding lithium-wire accelerator to examine with a far-field holographic system the removal of particulate contaminants from external spacecraft surfaces subjected to micrometeoroid bombardment. The impacting projectiles used to simulate the micrometeoroids were glass spheres nominally 37 microns in diameter, having velocities between 4 and 17 km/sec. The particulates were glass spheres nominally 25, 50, and 75 microns in diameter which were placed on aluminum targets. For these test, particulates detached had velocities that were log-normally distributed. The significance of the log-normal behavior of the ejected-particulate velocity distribution is that the geometric mean velocity and the geometric standard deviation are the only two parameters needed to model completely the process of particles removed or ejected from a spacecraft surface by a micrometeoroid impact.

Goad, J. H., Jr.↗
NASA NTRS1979

Instrument error analysis as it applies to wind-tunnel testing

Errors resulting from the instrumentation used to measure wind tunnel model parameters are analyzed. The pertinent parameters, their standard deviations, and the theoretical derivation of them, are given. Some BASIC programs and plots for the standard deviations of dynamic pressure, Mach number, and Reynolds number are included.

Rind, E.↗
NASA NTRS1989

Land-surface temperature measurement from space - Physical principles and inverse modeling

To apply the multiple-wavelength (split-window) method used for satellite measurement of sea-surface temperature from thermal-infrared data to land-surface temperatures, the authors statistically analyze simulations using an atmospheric radiative transfer model. The range of atmospheric conditions and surface temperatures simulated is wide enough to cover variations in clear atmospheric properties and surface temperatures, both of which are larger over land than over sea. Surface elevation is also included in the simulation as the most important topographic effect. Land covers characterized by measured or modeled spectral emissivities include snow, clay, sands, and tree leaf samples. The empirical inverse model can estimate the surface temperature with a standard deviation less than 0.3 K and a maximum error less than 1 K, for viewing angles up to 40 degrees from nadir under cloud-free conditions, given satellite measurements in three infrared channels. A band in the region from 10.2 to 11.0 microns will usually give the most reliable single-band estimate of surface temperature. In addition, a band in either the 3.5-4.0-micron region or in the 11.5-12.6-micron region must be included for accurate atmospheric correction, and a band below the ozone absorption feature at 9.6 microns (e.g., 8.2-8.8 microns) will increase the accuracy of the estimate of surface temperature.

Wan, Zhengming↗
NASA NTRS1989

Resolution of the 1,238-keV gamma-ray line from supernova 1987A

Observations of supernova 1987A from the maiden flight of the Gamma-Ray Imaging Spectrometer (GRIS) are reported. SN1987A was observed for a period of 11.1 hours on May 1, 1988. Line emission at 1238 keV and continuum emission from 60-800 keV were detected. A gaussian line profile gives an acceptable fit to the 1238 keV line. The best-fit parameters are: flux = 8.5(+ 2.3, - 2.2) x 10 to the -4th photons/sq cm/s; peak energy = 1235.4 (+ 2.2, - 2.4) keV; FWHM = 16.3 (+ 6.1, - 5.7) keV. No evidence is found for a supernova-produced red- or blueshift in the 1238 keV line. The measured linewidth is a factor of about two greater than model predictions, although the discrepancy represents only two standard deviations. The line profiles are characteristic of optically thin regions, whereas the intensity implies a mean optical depth of about two. Fragmentation or nonspherical geometry of the supernova shell are possible explanations of the data.

Teegarden, B. J.↗
NASA NTRS1995

Water vapor radiometer measurements of the tropospheric delay fluctuations at Goldstone over a full year

One year of near-continuous water vapor radiometer (WVR) measurements at DSS 13 has provided a database for characterizing the Goldstone tropospheric delay properties in a statistical sense. The results have been expressed in terms of the Allan standard deviation of delay and compared to a previous model for Goldstone fluctuations and the specifications of the Cassini Gravitational Wave Experiment (GWE). The new WVR data indicate that average fluctuation levels at hour time scales or less are approximately 30 percent lower than the earlier Goldstone model predictions. At greater than 1 h time scales, the WVR indicated fluctuation levels are in closer agreement with the model, although noise floor limitations may be artificially raising the average WVR-derived atmospheric fluctuation levels at the longer time scales. When scaled to two-way Doppler tracking at 20 deg elevation, as will occur for the GWE, these results indicate that Goldstone winter tropospheric delay fluctuations will typically be a factor of 10 larger than the GWE requirements at 1000 s and a factor of 4 larger at 10,000 s.

Keihm, S. J.↗