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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
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

GeoNEX-ML: A Machine Learning System for Earth Observations

Improved capabilities of earth monitoring satellites are enabling a wide range of studies on the environmental effects of climate change, often leveraging the recent advancements in machine learning. At the same time, the new capabilities, including higher spatial resolution and temporal frequency, are expanding the amount of data generated at exponential rates. At the NASA Earth eXchange (NEX), we build deep learning methods to learn from cross sensor satellite-based Earth observations for generating new datasets with efficient processing techniques. Using current generation geostationary satellites on NEX, we present an interchangeable set of machine models to perform spectral adjustment, physical model emulation, LEO-GEO emulation, and optical flow. These tools are used to generate consistent virtual observations across sensors, perform atmospheric correction and cloud detection, and estimate land surface temperature and atmospheric winds. This approach aims to improve the robustness of remotely sensed data processing by learning from diverse sets of observations while enabling near real-time and on-demand capabilities.

Geostationary↗
NASA NTRSDate not supplied

Atmospheric winds with deep optical flow

Improved capabilities of earth monitoring satellites are enabling a wide range of studies on the environmental effects of climate change, often leveraging the recent advancements in machine learning. At the same time, the new capabilities, including higher spatial resolution and temporal frequency, are expanding the amount of data generated at exponential rates. At the NASA Earth eXchange (NEX), we build deep learning methods to learn from cross sensor satellite-based Earth observations for generating new datasets with efficient processing techniques. Using current generation geostationary satellites on NEX, we present an interchangeable set of machine models to perform spectral adjustment, physical model emulation, LEO-GEO emulation, and optical flow. These tools are used to generate consistent virtual observations across sensors, perform atmospheric correction and cloud detection, and estimate land surface temperature and atmospheric winds. This approach aims to improve the robustness of remotely sensed data processing by learning from diverse sets of observations while enabling near real-time and on-demand capabilities.

Atmospheric winds↗
NASA NTRSDate not supplied

Coupling CFD and Material Response for Analysis of Mars Entry

In computing the response of an ablating thermal protection system during atmospheric entry, the aerothermal environment and material response are generally computed separately with a blowing correction term in the material response model to account for the blowing of char and pyrolysis gases [1]. In this work, we apply a coupled approach in which pyrolysis blowing gases, computed in the PATO material response code [2], are used with a blowing boundary condition in the DPLR hypersonic CFD code [3]. This leads to an iterative method in which blowing products from PATO are input into DPLR to update surface heating estimates. The full iterative method, with the addition of radiative heating estimates using the NEQAIR radiation solver [4], is shown in Fig. 1. The method is demonstrated on a sphere case with the environment and material properties based on the Mars Science Laboratory entry. Future work includes utilizing this method in computing full 3D material response during the Mars 2020 entry.

Heat Transfer↗
NASA NTRSDate not supplied

Coupling CFD and Material Response for Analysis of Mars Entry

In computing the response of an ablating thermal protection system during atmospheric entry, the aerothermal environment and material response are generally computed separately with a blowing correction term in the material response model to account for the blowing of char and pyrolysis gases. In this work, we apply a coupled approach in which pyrolysis blowing gases, computed in the PATO material response code, are used with a blowing boundary condition in the DPLR hypersonic CFD code. This leads to an iterative method in which blowing products from PATO are input into DPLR to update surface heating estimates. The full iterative method, with the addition of radiative heating estimates using the NEQAIR radiation solver, is shown in Fig. 1. The method is demonstrated on a sphere case with the environment and material properties based on the Mars Science Laboratory entry. Future work includes utilizing this method in computing full 3D material response during the Mars 2020 entry.

Ablation↗
NASA NTRS2023

A Multi-Satellite Framework to Rapidly Evaluate Extreme Biosphere Cascades: The Western US 2021 Drought and Heatwave

The increasing frequency and intensity of climate extremes and complex ecosystem responses motivate the need for integrated observational studies at low-latency to determine biosphere responses and carbon-climate feedbacks. Here, we develop a satellite-based rapid attribution workflow and demonstrate its use at a 1–2-month latency to attribute drivers of the carbon cycle feedbacks during the 2020-2021 Western US drought and heatwave. In the first half of 2021, concurrent negative photosynthesis anomalies and large positive column CO 2 anomalies were detected with satellites. Using a simple atmospheric mass balance approach, we estimate a surface carbon efflux anomaly of 132 TgC in June 2021, a magnitude corroborated 28 independently with a dynamic global vegetation model. Integrated satellite observations of hydrologic processes, representing the soil-plant-atmosphere continuum (SPAC), show that these surface carbon flux anomalies are largely due to substantial reductions in photosynthesis because of a spatially widespread moisture-deficit propagation through the SPAC between 2020 and 2021. A causal model indicates deep soil moisture stores partially drove photosynthesis, maintaining its values in 2020 and driving its declines throughout 2021. The causal model also suggests legacy effects may have amplified photosynthesis deficits in 2021 beyond the direct effects of environmental forcing. The integrated, observation framework presented here provides a valuable first assessment of a biosphere extreme response and an independent testbed for improving drought propagation and mechanisms in models. The rapid identification of extreme carbon anomalies and hotspots can also aid mitigation and adaptation decisions.

Causal model↗
NASA NTRSDate not supplied

Kalman Filtering and RTS Smoothing for Arc-Jet Sample Edge Tracking

Accurate and temporally consistent measurements of test-article recession are required to characterize material response during arc-jet ablation experiments. However, image-based boundary measurements are often affected by segmentation noise, brightness variations, and frame-to-frame variability. This work extends arcjetCV [1] with filtering methods for tracking the evolving boundaries of hemispherical and ISO-Q test articles. Two boundary-tracking approaches based on Kalman filtering [2] were implemented. The first applies a point-wise Kalman filter followed by a Rauch–Tung–Striebel smoother [3] to individual boundary-point locations. The second applies the same filtering and smoothing framework to a reduced set of geometry-dependent shape parameters. The point-wise method reduces local frame-to-frame fluctuations while preserving spatial details along the detected boundary. The shape-parameter method provides a compact and geometrically constrained estimate of the sample contour. Figure 1 illustrates the two approaches for a hemispherical test article. Both methods improve temporal consistency and support more robust estimation of surface recession from arc-jet imagery. The two filtering approaches provide complementary representations of boundary evolution and improve the reliability of image-based recession measurements during arc-jet experiments.

recession measurement↗
NASA NTRS1999

The Martian Surface Boundary Layer

The acquisition of meteorological data from the surface of Mars by the two Viking Landers and Mars Pathfinder make it possible to estimate atmospheric boundary layer parameters and surface properties at three different locations on the planet. Because the Martian atmosphere is so thin the majority of the solar radiance is converted to heat at the surface. The difference between surface and atmospheric temperature can also constraint surface albedo, thermal inertia, and infrared emissivity. The Mars Pathfinder Atmospheric Structure Instrument/Meteorological package (ASI/MET) was the most capable weather monitoring system ever sent to the surface of another planet to date. One of the prime objectives of the ASI/MET package is to characterize the surface boundary layer parameters, particularly the heat and momentum fluxes, scaling temperature and friction velocity, and estimate surface roughness. Other important boundary layer parameters, such as Richardson Number, Monin-Obukhov length, analysis of turbulence characteristics of wind and temperature, and atmospheric stability class can also be determined from these measurements.

Wilson, G. R.↗
NASA NTRS1984

Modelling the atmospheric boundary layer for remotely sensed estimates of daily evaporation

An energy and moisture balance model of the soil surface was used to estimate daily evaporation from wheat and barley fields in West Germany. The model was calibrated using remotely sensed surface temperature estimates. Complete atmospheric boundary layer models are difficult to use because of the number of parameters involved and a simplified model was used here. The resultant evaporation estimates were compared to eddy correlation evaporation estimates and good agreement was found.

Gurney, R. J.↗
NASA NTRS1986

The First International Satellite Land Surface Climatology Project (ISLSCP) field experiment FIFE

The purpose of ISLSCP is to verify the use of satellite data for the estimation of land-surface properties. This is to be done through a series of field experiments using a combination of point measurements on the ground and areal measurements from aircraft overflights. In addition to validating satellite estimates of surface properties, approaches for obtaining areal averages of the radiation, moisture, and heat fluxes from remotely sensed data are to be studied. The procedure for doing this is to combine the surface point measurements of the fluxes with the aircraft areal observations using a surface-energy-balance model. This should make it possible to interpolate between the point estimates of these fluxes and calculate area-averaged quantities. The surface parameters to be estimated from aircraft observations include: surface radiation temperature, albedo, land-cover or vegetation index, and surface soil moisture.

Schmugge, T. J.↗
NASA NTRS1979

The effect of surface reflection and clouds on the estimation of total ozone from satellite measurements

The total amount of ozone in a vertical column is being measured by Nimbus 4 and 7 observations of the intensity of ultraviolet sunlight scattered from the earth. The algorithm for deriving the amount of ozone from the observations uses the assumption that the surface reflects the light isotropically and the albedo is independent of wavelength. The effects of anisotropic surfaces and clouds on the estimate of total ozone are computed for models of the earth-atmosphere system.

Fraser, R. S.↗
NASA NTRS1995

Accuracy of sea ice temperature derived from the advanced very high resolution radiometer

The accuracy of Arctic sea ice surface temperatures T(sub s) dericed from advanced very high resolution radiometer (AVHRR) thermal channels is evaluated in the cold seasons by comparing them with surface air temperatures T(sub air) from drifting buoys and ice stations. We use three different estimates of satellite surface temperatures, a direct estimate from AVHRR channel 4 with only correction for the snow surface emissivity but not for the atmosphere, a single-channel regression of T(sub s) with T(sub air), and Key and Haefliger's (1992) polar multichannel algorithm. We find no measurable bias in any of these estimates and few differences in their statistics. The similar performance of all three methods indicates that an atmospheric water vapor correction is not important for the dry winter atmosphere in the central Arctic, given the other sources of error that remain in both the satellite and the comparison data. A record of drifting station data shows winter air temperature to be 1.4 C warmer than the snow surface temperature. `Correcting' air temperatures to skin temperature by subtracting this amount implies that satellite T(sub s) estimates are biased warm with respect to skin temperature by about this amount. A case study with low-flying aircraft data suggests that ice crystal precipitation can cause satellite estimates of T(sub s) to be several degrees warmer than radiometric measurements taken close to the surface, presumably below the ice crystal precipitation layer. An analysis in which errors are assumed to exist in all measurements, not just the satellite measurements, gives a standard deviation in the satellite estimates of 0.9 C, about half the standard deviation of 1.7 C estimated by assigning all the variation between T(sub s) and T(sub air) to errors in T(sub s).

Yu, Y.↗
NASA NTRS1982

The equivalent angle-of-attack method for estimating the nonlinear aerodynamic characteristics of missile wings and control surfaces

A method has been developed for estimating the nonlinear aerodynamic characteristics of missile wing and control surfaces. The method is based on the following assumption: if a fin on a body has the same normal-force coefficient as a wing alone composed of two of the same fins joined together at their root chords, then the other force and moment coefficients of the fin and the wing alone are the same including the nonlinearities. The method can be used for deflected fins at arbitrary bank angles and at high angles of attack. In the paper, a full derivation of the method is given, its accuracy demonstrated and its use in extending missile data bases is shown.

Hemsch, M. J.↗
NASA NTRS1981

Remote sensing of soil moisture content over bare field at 1.4 GHz frequency

An algorithm for estimating moisture content of a bare soil from the observed brightness temperature at 1.4 GHz is discussed and applied to a limited data base. The method is based on a radiative transfer model calculation, which has been successfully used in the past to account for many observational results, with some modifications to take into account the effect of surface roughness. Besides the measured brightness temperatures, the three additional inputs required by the method are the effective soil thermodynamic temperature, the precise relation between moisture content and the smooth field brightness temperatures and a pair of parameters related to surface roughness. The procedures of estimating surface roughness parameters and of obtaining moisture content from observed brightness temperature are discussed. The algorithm is applied to observations from truck mounted and airborne radiometers. The estimated moisture contents compare favorably with the observations in the top 2 cm layer.

Wang, J. R.↗
NASA NTRS1990

Boundary-layer heat and moisture budgets from FIFE

Aircraft stacks were flown upwind and downwind of the First International Satellite Land Surface Climatology Project Field Experiment site in Kansas to measure the heat and moisture budgets of the boundary layer under fairly clear skies for four daytime periods. The terms in the conservation equation are evaluated. The vertical flux divergence and advection do not account for the difference between surface and low-level aircraft flux estimates. Budget estimates of the surface fluxes using the aircraft data agree well with surface flux measurements, but extrapolation of the aircraft fluxes gives surface fluxes that are too low.

Desjardins, R. L.↗