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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 631 records · Page 35
All sourcesNASA NTRSDOE OSTI
NASA NTRS2020

Investigation of Direct Force Control For Aerocapture at Neptune

In this work, a direct force control numerical predictor-corrector guidance architecture is developed to enable Neptune aerocapture using blunt body aeroshells. A linear aerodynamics model is formulated for a Mars Science Laboratory-derived aeroshell. The application of optimal control theory shows that the∆V-minimizing angle of attack and side-slip angle control laws are bang-bang. A closed-loop numerical predictor-corrector direct force control guidance algorithm is developed and numerically simulated using the Program to Optimize Simulated Trajectories II. A series of Monte Carlo simulations are conducted to assess the guidance robustness to uncertainties in vehicle aerodynamics,atmospheric density, and entry state. For the reference set of uncertainties, the direct force control vehicle achieves 99.7% successful science orbit insertion within a 330 m/s total∆V budget for periapsis raise, apoapsis, inclination,and ascending node corrections. Improved atmospheric knowledge and delivery state accuracy are shown to improve the success to 100% and reduce the∆V to 230 m/s. Direct force control is demonstrated to be an enabling technology for blunt body aerocapture at Neptune while providing comparable performance to existing slender body vehicles studied in literature

aerocapture↗
NASA NTRS1978

Performance characteristics of the electrochemical concentration cell ozonesonde

A large number of electrochemical concentration cell (ECC) ozonesondes were calibrated in relation to a UV photometric absorption ozone instrument prior to using the ozonesondes in atmospheric soundings. The two methods of measuring ozone were in reasonable agreement on the average, but there was considerable variation from one ozonesonde to another. Averaging the individual linear regressions gives an ECC ozone concentration equal to 0 + or - 8 nbar plus (0.96 + or - 0.10) times the concentration determined with the UV instrument, where uncertainties represent 90% confidence limits. Applying individual calibration corrections to atmospheric sounding data reduced the mean difference between Dobson spectrophotometric measurements of total ozone overburdens and corresponding values obtained from ozonesonde data from -8.5 + or - 8.2 to -1.4 + or - 7.3% for a series of measurements carried out in 1977. Corresponding uncorrected and corrected differences averaged 3.2 + or - 9.7 and 1.9 + or - 10.6%, respectively, for soundings carried out in 1976.

Torres, A. L.↗
NASA NTRS2014

Application of Suomi-NPP Green Vegetation Fraction and NUCAPS for Improving Regional Numerical Weather Prediction

The NASA SPoRT Center is working to incorporate Suomi‐NPP products into its research and transition activities to improve regional numerical weather prediction (NWP). Specifically, SPoRT seeks to utilize two data products from NOAA/NESDIS: (1) daily global VIIRS green vegetation fraction (GVF), and (2) NOAA Unique CrIS and ATMS Processing System (NUCAPS) temperature and moisture retrieved profiles. The goal of (1) is to improve the representation of vegetation in the Noah land surface model (LSM) over existing climatological GVF datasets in order to improve the land‐atmosphere energy exchanges in NWP models and produce better temperature, moisture, and precipitation forecasts. The goal of (2) is to assimilate NUCAPS retrieved profiles into the Gridpoint Statistical Interpolation (GSI) data assimilation system to assess the impact on a summer pre‐frontal convection case. Most regional NWP applications make use of a monthly GVF climatology for use in the Noah LSM within the Weather Research and Forecasting (WRF) model. The GVF partitions incoming energy into direct surface heating/evaporation over bare soil versus evapotranspiration processes over vegetated surfaces. Misrepresentations of the fractional coverage of vegetation during anomalous weather/climate regimes (e.g., early/late bloom or freeze; drought) can lead to poor NWP model results when land‐atmosphere feedback is important. SPoRT has been producing a daily MODIS GVF product based on the University of Wisconsin Direct Broadcast swaths of Normalized Difference Vegetation Index (NDVI). While positive impacts have been demonstrated in the WRF model for some cases, the reflectances composing these NDVI do not correct for atmospheric aerosols nor satellite view angle, resulting in temporal noisiness at certain locations (especially heavy vegetation). The method behind the NESDIS VIIRS GVF is expected to alleviate the issues seen in the MODIS GVF real‐time product, thereby offering a higher‐quality dataset for modeling applications. SPoRT is evaluating the VIIRS GVF data against the MODIS real‐time and climatology GVF in both WRF and the NASA Land Information System. SPoRT has a history of assimilating hyperspectral infrared retrieved profiles

Numerical Weather Prediction↗
NASA NTRS1984

The Atmospheric Extinction Problem

Atmospheric extinction, which is one of the main causes of errors in photometry is investigated. The incorrect determination of the extinction coefficient, and its variability, leads to an erroneous measurement. An erroneous extinction coefficient can arise from a number of causes including: (1) instrumental instabilities; (2) too few data points; (3) temporal changes in the atmosphere; and (4) differing airmasses due to components with different scale heights. While it is true that differential measuring techniques can achieve a precision approaching 0.1 percent, at higher levels of precision all of the above causes will be significant sources of error. The conditions that must be met in order to properly determine and correct for atmospheric extinction are discussed.

Angione, R. J.↗
NASA NTRS1992

Lidar analysis techniques for use in the atmospheric boundary layer

There is a growing body of observational and theoretical evidence which suggests that local climate characteristics are associated with variations in the earth's surface. The link between surface variability and local-scale processes must be made if we are to improve our understanding of the feedback mechanisms involved in surface-atmosphere dynamics. However, to understand these interactions, the surface-atmosphere interface must be studied as a large-scale spatial system. Lidars are ideal tools to study the spatial properties of the atmosphere. The described techniques were developed for use with the Los Alamos Water Raman-Lidar, but are applicable to many other types of lidar. The methodology of the analysis of lidar data is summarized in order to determine meteorological parameters in the atmospheric boundary layer. The techniques are not exhaustive but are intended to show the depth and breadth of the information which can be obtained from lidars. Two methods for the computation of water-vapor fluxes were developed. The first uses the fact that the water vapor concentration in the vertical direction follows a logarithmic profile when corrected for atmospheric stability. The second method involves using inertial dissipation techniques in which lidar-derived spatial and temporal power spectra are used to determine the flux.

Eichinger, William E.↗
NASA NTRS1990

Accuracy requirements of optical linear algebra processors in adaptive optics imaging systems

A ground-based adaptive optics imaging telescope system attempts to improve image quality by detecting and correcting for atmospherically induced wavefront aberrations. The required control computations during each cycle will take a finite amount of time. Longer time delays result in larger values of residual wavefront error variance since the atmosphere continues to change during that time. Thus an optical processor may be well-suited for this task. This paper presents a study of the accuracy requirements in a general optical processor that will make it competitive with, or superior to, a conventional digital computer for the adaptive optics application. An optimization of the adaptive optics correction algorithm with respect to an optical processor's degree of accuracy is also briefly discussed.

Downie, John D.↗
DOE OSTI2022

Harmonizing solar induced fluorescence across spatial scales, instruments, and extraction methods using proximal and airborne remote sensing: A multi-scale study in a soybean field

Solar-induced chlorophyll fluorescence (SIF) has been widely used to track vegetation photosynthesis at different scales ranging from in-situ measurements to satellite products. Airborne platforms sample SIF data at a spatial scale intermediate between in-situ and satellite, matching that of ground measurement (e.g. flux tower footprints and other field sampling), enabling us to explore causes of SIF variation and validate satellite-based SIF products. However, harmonizing SIF across sensors and platforms (correcting for systematic errors to yield a consistent, comparable SIF product) is challenging because SIF can be retrieved in different absorption windows, with different instruments and methods complicating the comparison between different observational levels (i.e., ground, airborne, satellites) and between sites equipped with different instruments with varying optical properties (spectral resolution and sampling intervals, spatial resolution). Additionally, the spatial and temporal variability of atmospheric properties can influence the retrieval of the weak SIF signal. Because of these complications, direct comparisons of airborne and ground SIF across scales are rarely attempted. Here, in this study, we combined airborne SIF data with simultaneous ‘ground truth’ data collected by stationary and mobile platforms in a soybean field in Nebraska, USA. In this effort, we tested several SIF extraction methods, including Fraunhofer Line Discrimination (FLD), improved Fraunhofer Line Discrimination (iFLD), Spectral Fitting Method (SFM), SpecFit, and a Singular Vector Decomposition (SVD) method. The SpecFit method was sensitive to the 715–740 nm water bands and removing the water bands in the fitting process yielded better agreement between the airborne and ground SIF spectra. Accurate estimation of the ground level downwelling irradiance obtained by ground measurements over a calibration target improved agreement between airborne and ground SIF retrievals at the O 2 A band, and allowed us to derive a SIF dataset with improved agreement across platforms and sampling scales. This experimental approach provided a method for generating comparable SIF signals across instruments, methods and platforms, which is critical to understanding the SIF-GPP relationship at different scales and to cross-validate the diversity of platforms used for satellite products calibration and validation.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2020

Revised and extended benchmark results for Rayleigh scattering of sunlight in spherical atmospheres

While most of traditional Earth-atmosphere satellite remote sensing relies on radiative transfer in the plane parallel geometry, effects of sphericity are important at high sun and view zenith angles. Broad understanding of these effects is limited and, contrary to the plane-parallel case, finding accurate numerical results to test spherical RT codes is not easy. This paper aims to partially fill in this gap. Using the full-spherical RT code MYSTIC (Monte Carlo), and the plane-parallel RT code VLIDORT (discrete ordinates) corrected for atmospheric sphericity in the single and multiple scattering, we reproduced with better accuracy and extended the benchmark results by Adams & Kattawar [1978].

spherical atmospheres↗
NASA NTRS1984

Interstellar Grain Mantles

Techniques for determining the composition of small dust grains in interstellar matter are discussed. The best way to study the composition of interstellar grain mantles is by infrared spectroscopy. The absorption features in a complete infrared spectrum from 2 to 15 microns can be used as fingerprints to identify the absorbing molecule. Ground-based observations around 3 microns confirmed the presence of H2O ice in interstellar grain mantles, through the detection of the 3.08 micron OH stretching vibration. The detection of other molecules, in particular the carbon bearing molecules, is however hampered by atmospheric absorption in the 5-8 micron region and the presence of the strong ice and silicate bands, which dominate the 3 and 10 micron region respectively. Kuiper Airborne Observatory observations of the 5-8 micron region of the spectrum are therefore extremely important to determine the composition of interstellar grain mantles. The 5 to 8 micron spectra of molecular cloud sources was obtained using a 24 detector grating spectrometer. An important characteristic of this spectrometer is that the whole spectrum is obtained simultaneously. It is therefore relatively easy to correct for atmospheric transmission.

Witteborn, F.↗
NASA NTRS1992

Modelling TOVS radiances of synoptic systems

Two operational analysis models, produced by ECMWF and NMC, are compared against observed satellite radiances by converting the analyzed variables into synthetic radiances using a radiative transfer model (RTM). Observed TOVS satellite radiances are used as a ground truth, since they are the only source of continuous, synoptic-scale resolution observations available over the data-sparse tropical Pacific Ocean. It is assumed that if the analysis models correctly simulate atmospheric conditions, the observed and modelled radiance fields will have similar patterns and magnitudes. In each of seven TOVS channels examined, the mean temperature difference between the models was small, but the differences between the models and the observations were large. The mean temperature difference within each channel was larger than the standard deviation in most cases. The moisture channels of the RTM were sensitive to changes in moisture content, but none of the channels were significantly affected by changes in temperature. Single-day modelled radiance analyses contain synoptic information similar to the satellite observations. ECMWF is often too noisy, producing features not verified by the satellite; NMC is often too smooth. NMC more closely resembles the TOVS contours. Modelled water vapor channel analyses resemble observed monthly and composited observations well, but do not accurately reproduce the highly-variable single-day fields. ECMWF generally has more accurate gradients. Neither model simulates the tropics well. The water vapor channels, especially channel eleven (weighted at 700 mb), most closely resembled the tropical plume composite described by McGuirk and Ulsh. The only plume evidence found in the thermal or microwave channels, in either the observations or the models, was a composite trough situated in the correct location, extending from the mid-latitudes into the subtropics. This feature was not readily discernable until the definition and mature stages. Additional information besides the modelled temperatures would be required to produce an accurate forecast for the tropics. Model patterns more closely resembled the observations in the quiescent atmosphere, though the magnitudes were not any closer. ECMWF simulates the TOVS quiescent state better than NMC. The moisture channels continue to present the most realistic patterns. The models contained more detail in the tropics than was verified by the satellite observations, apparently trying to force an active ITCZ. Lag correlations showed TOVS to be more persistent than the models. TOVS also showed a smoother lag trend, but all products appeared to have adequate ability to react to changes in the atmosphere over time.

Coe, Thomas Eddy↗
NASA NTRS1996

Monitoring Forest Regrowth Using a Multi-Platform Time Series

Over the past 50 years, the forests of western Washington and Oregon have been extensively harvested for timber. This has resulted in a heterogeneous mosaic of remaining mature forests, clear-cuts, new plantations, and second-growth stands that now occur in areas that formerly were dominated by extensive old-growth forests and younger forests resulting from fire disturbance. Traditionally, determination of seral stage and stand condition have been made using aerial photography and spot field observations, a methodology that is not only time- and resource-intensive, but falls short of providing current information on a regional scale. These limitations may be solved, in part, through the use of multispectral images which can cover large areas at spatial resolutions in the order of tens of meters. The use of multiple images comprising a time series potentially can be used to monitor land use (e.g. cutting and replanting), and to observe natural processes such as regeneration, maturation and phenologic change. These processes are more likely to be spectrally observed in a time series composed of images taken during different seasons over a long period of time. Therefore, for many areas, it may be necessary to use a variety of images taken with different imaging systems. A common framework for interpretation is needed that reduces topographic, atmospheric, instrumental, effects as well as differences in lighting geometry between images. The present state of remote-sensing technology in general use does not realize the full potential of the multispectral data in areas of high topographic relief. For example, the primary method for analyzing images of forested landscapes in the Northwest has been with statistical classifiers (e.g. parallelepiped, nearest-neighbor, maximum likelihood, etc.), often applied to uncalibrated multispectral data. Although this approach has produced useful information from individual images in some areas, landcover classes defined by these techniques typically are not consistent for the same scene imaged under different illumination conditions, especially in the mountainous regions. In addition, it is difficult to correct for atmospheric and instrumental differences between multiple scenes in a time series. In this paper, we present an approach for monitoring forest cutting/regrowth in a semi-mountainous portion of the southern Gifford Pinchot National Forest using a multisensor-time series composed of MSS, TM, and AVIRIS images.

Sabol, Donald E., Jr.↗
NASA NTRS1991

Comparison of ground and satellite based measurements of the fraction of photosynthetically active radiation intercepted by tall-grass prairie

The fraction, of photosynthetically active radiation intercepted by vegetation, F(sub ipar) is an important parameter for modeling the interactions between the land-surface and atmosphere and for estimating vegetation biomass productivity. This study was; therefore, an integral part of FIFE. The specific purpose of this experiment was to find out how well definitive measurements of F(sub ipar) on the ground relate to near-ground and satellite based spectral reflectance measurements. Concurrent measurements of F(sub ipar) and ground, helicopter, and satellite based reflectance measurements were taken at thirteen tall-grass prairie sites within the FIFE experimental area. The sites were subjected to various combinations of burning and grazing managements. The ground and helicopter based reflectance measurements were taken on the same day or few days from the time of the overpass of LANDSAT and SPOT satellites. Ground-based reflectance measurements and sun photometer readings taken at the times of the satellite overpasses were used to correct for atmospheric attenuation. Hand-held radiometer spectral indices were strongly correlated with helicopter and satellite based values (r=0.94 for helicopter, 0.93 for LANDSAT Thematic Mapper, and 0.86 for SPOT). However, the ground, helicopter, and satellite based normalized difference spectral vegetation indices showed low sensitivity to changes in F(sub ipar). Reflectance measurements were only moderately well correlated with measurements of F(sub ipar) (r=0.82 for hand-held radiometer, 0.84 for helicopter measurements, and 0.75 for the LANDSAT Thematic Mapper and SPOT). Improved spectral indices which can compensate for site differences are needed in order to monitor F(sub ipar) more reliably.

Demetriades-Shah, T. H.↗
NASA NTRS1992

Comparison of ground and satellite based measurements of the fraction of photosynthetically active radiation intercepted by tall-grass prairie

The fraction of photosynthetically active radiation intercepted by vegetation, F(sub ipar) is an important parameter for modeling the interactions between the land-surface and atmosphere and for estimating vegetation biomass productivity. This study was, therefore, an integral part of FIFE. The specific purpose of this experiment was to find out how well definitive measurements of F(sub ipar) on the ground relate to near-ground and satellite based spectral reflectance measurements. Concurrent measurements of F(sub ipar) and ground, helicopter, and satellite based reflectance measurements were taken at thirteen tall-grass prairie sites within the FIFE experimental area. The sites were subjected to various combinations of burning and grazing managements. The ground and helicopter based reflectance measurements were taken on the same day or few days from the time of the overpass of LANDSAT and SPOT satellites. Ground-based reflectance measurements and sun photometer readings taken at the times of the satellite overpasses were used to correct for atmospheric attenuation. Hand-held radiometer spectral indices were strongly correlated with helicopter and satellite based values (r = 0.94 for helicopter, 0.93 for LANDSAT Thematic Mapper, and 0.86 for SPOT). However, the ground, helicopter, and satellite based normalized difference spectral vegetation indices showed low sensitivity to changes in F(sub ipar). Reflectance measurements were only moderately well correlated with measurements of F(sub ipar) (r = 0.82 for hand-held radiometer, 0.84 for helicopter measurements, and 0.75 for the LANDSAT Thematic Mapper and SPOT). Improved spectral indices which can compensate for site differences are needed in order to monitor F(sub ipar) more reliably.

Demetriades-Shah, T. H.↗
DOE OSTI2020

Annual sea level variations in the Red Sea observed using GNSS

SUMMARY Annual sea level variations in the Red Sea have amplitudes of 15–20 cm as observed using various techniques such as tide gauges, satellite altimetry and recently Gravity Recovery and Climate Experiment (GRACE) satellite data. In this study, we demonstrate that Global Navigation Satellite System (GNSS) observations can also be used to measure the effect of these sea level variations. The extra water mass presses on the seafloor, which causes horizontal and vertical deformations. Using time-series from 10 coastal GNSS stations, we observe annual horizontal and vertical loading displacements with amplitudes of 2–5 mm. When correcting for atmospheric, hydrological and surface water loading and a residual geocentre motion, significant annual signals of approximately 0.5 and 2 mm are still observed for the horizontal and vertical components, respectively. In the northern Red Sea, the observed annual signals and predicted annual sea level loading show good agreement. This confirms that the signal is mostly a result of the variations in water mass and thermal expansion. Furthermore, we conclude that the uncertainties in the hydrological model over Ethiopia and Eritrea influence the loading over the southern Red Sea, which was underestimated in previous studies using GRACE data.

Alothman, A. O.↗
DOE OSTI2024

Monitoring of ground water table depth and soil moisture at the Point Reyes field site

Ground water table (GWT) depth and soil moisture (SM) have been monitored at several locations at the Point Reyes field site (Californian coastal grassland) from 2021 to 2024. Monitoring is still on-going and data may be added to this archive at later time. The SM data have been acquired using Teros 12 Meter soil moisture sensors placed at 10, 30, 60 and 90 cm depth at 5 locations along a small hillslope. These sensors also collect soil temperature and bulk conductance. In addition, some collocated sensors provide pore pressure and Photochemical Reflectance Index (PRI). The GWT depth has been inferred from various type of Onset pressure transducers. The pressure measurements have been corrected for atmospheric pressure variations and sensor position relative to the ground surface to infer GWT depth, as well as with RTK GPS data to infer GWT elevation. The GWT data have been acquired at 5 distinct locations from 2020 to 2024 with the sensors placed at about 4 m depth. In addition, GWT data has been acquired for the 2023-2024 period with sensors located in 1 m deep shallow wells installed near each deeper well. This data is intended to evaluate possibly different dynamic in shallow (perched) and deep aquifer. The datasets are all provided in csv format. Please note that the interpretation of the GWT data needs to be done with consideration of environmental and well characteristics at the site and uncertainty in various variables. For more information on GWT and SM data, please contact the author.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

The Optical Corrector for the Dark Energy Spectroscopic Instrument

The Dark Energy Spectroscopic Instrument (DESI) is currently measuring the spectra of 40 million galaxies and quasars, the largest such survey ever made to probe the nature of cosmological dark energy. The 4 m Mayall telescope at Kitt Peak National Observatory has been adapted for DESI, including the construction of a 3$_{.}^{°}$2 diameter prime focus corrector that focuses astronomical light onto a 0.8 m diameter focal surface with excellent image quality over the DESI bandpass of 360–980 nm. The wide-field corrector includes six lenses, as large as 1.1 m in diameter and as heavy as 237 kilograms, including two counterrotating wedged lenses that correct for atmospheric dispersion over zenith angles from 0° to 60°. The lenses, cells, and barrel assembly all meet precise alignment tolerances on the order of tens of microns. The barrel alignment is maintained throughout a range of observing angles and temperature excursions in the Mayall dome by use of a hexapod, which is itself supported by a new cage, ring, and truss structure. In this paper we describe the design, fabrication, and performance of the new corrector and associated structure, focusing on how they meet DESI requirements. In particular, we describe the prescription and specifications of the lenses, design choices and error budgeting of the barrel assembly, stray light mitigations, and integration and test at the Mayall telescope. We conclude with some validation highlights that demonstrate the successful corrector on-sky performance, and we list some lessons learned during the multiyear fabrication phase.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

The Power Curve Working Group's assessment of wind turbine power performance prediction methods

Wind turbine power production deviates from the reference power curve in real-world atmospheric conditions. Correctly predicting turbine power performance requires models to be validated for a wide range of wind turbines using inflow in different locations. The Share-3 exercise is the most recent intelligence-sharing exercise of the Power Curve Working Group, which aims to advance the modeling of turbine performance. The goal of the exercise is to search for modeling methods that reduce error and uncertainty in power prediction when wind shear and turbulence digress from design conditions. Herein, we analyze data from 55 wind turbine power performance tests from nine contributing organizations with statistical tests to quantify the skills of the prediction-correction methods. We assess the accuracy and precision of four proposed trial methods against the baseline method, which uses the conventional definition of a power curve with wind speed and air density at hub height. The trial methods reduce power-production prediction errors compared to the baseline method at high wind speeds, which contribute heavily to power production; however, the trial methods fail to significantly reduce prediction uncertainty in most meteorological conditions. For the meteorological conditions when a wind turbine produces less than the power its reference power curve suggests, using power deviation matrices leads to more accurate power prediction. We also determine that for more than half of the submissions, the data set has a large influence on the effectiveness of a trial method. Overall, this work affirms the value of data-sharing efforts in advancing power curve modeling and establishes the groundwork for future collaborations.

17 WIND ENERGY↗