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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
NASA NTRS1988

Absolute solar spectral irradiance 120 nm-400 nm (Results from the Solar Ultraviolet Spectral Irradiance Monitor-SUSIM-Experiment on board Spacelab 2)

The Solar UV Spectral Irradiance Monitor experiment flown on the Spacelab-2 mission measured the absolute solar spectral irradiance in the ultraviolet spectral range 120 nm-400 nm with two spectral passbands, 0.15 and 5 nm. The photometric error was + or - 5.0 percent relative to three different absolute calibration standards. Calibration procedures and error budget are discussed. The results are reported and compared with other measurements.

Vanhoosier, Michael E.↗
NASA NTRS1995

Solution of acoustic workshop problems by a spectral multidomain method

We use a new staggered grid Chebyshev spectral multidomain method to solve three of the Workshop benchmark problems. The method defines solution unknowns at the nodes of the Chebyshev Gauss quadrature, and the fluxes at the nodes of the Chebyshev Gauss-Lobatto quadrature. The Chebyshev spectral method gives exponentially convergent phase and dissipation errors. The multidomain approximation gives the method flexibility. Using the method, we solve problems in Categories 1 and 5 of the benchmark problems.

Kopriva, Davis A.↗
NASA NTRS2002

Mountain-Top-to-Mountain-Top Optical Link Demonstration

A mountain-top-to-mountain-top optical communications demonstration was conducted between the JPL Table Mountain Facility (TMF), Wrightwood, California, and Strawberry Peak (SP), Lake Arrowhead, California, during the months of August and September of 2000. The link was nearly horizontal at an altitude of 2 km and spanned a range of 46.8 km. A 780-nm multibeam beacon broadcast from TMF was received by the JPL Optical Communications Demonstrator (OCD) located at SP. The received beacon was utilized as a pointing reference to retransmit an 852-nm communications laser beam, modulated at 400 Mb/s by a PN7 pseudo-random bit stream (PRBS) sequence. The long atmospheric path resulted in atmospheric-turbulence-induced angle-of-arrival fluctuations of the beacon at the OCD aperture. A .ne-steering control loop was used to track the resulting beacon centroid motion and update the pointing of the communications laser beam transmitted from SP to TMF. Fried parameters, or r0, inferred from focal spot sizes received at SP were 4 to 5 cm whereas, using the spot sizes received at TMF, they were 2 to 3 cm. In both cases, theory predicts larger r0 values. The predicted angle-of-arrival fluctuations compare well with measured rms displacements exhibited by the focal spots at either end of the link. An uncompensated error of ~1.1 rad in the x-axis and ~2 rad in the y-axis was obtained using centroid data logged by the OCD. Average bit-error rates of 10-5 were recorded for extended periods of time. An atmospheric coherence length r0 of 3 to 5 cm was inferred using the focal-plane spot size measured on the CCD tracking sensor and compared to a predicted value of 5 to 7 cm using reasonable atmospheric models. The irradiance bounds required for the CCD tracking sensor to perform centroiding was found to range from 2000 to 3000 integrated pixel counts, although a more reliable range was 600 to 3000, indicating a dynamic range of 6 to 11 dB. The motion of the spot on the focal plane was also recorded and yielded rms angle-of-arrival-induced focal-plane displacement of 9 to 11 m, compared to a predicted value of 7.8 to 11 m. The irradiance measurements made with the OCD clearly indicate that best tracking performance is obtained when the mean received signal is 2000 to 2200 counts. The best tracking performance resulted in an rms uncompensated error of 1.1 rad. The uncompensated error appeared to increase with either an increase or decrease in mean beacon-signal level. The rms uncompensated error determined by deriving the beacon displacement power spectral density from the beacon centroid-versustime data and the rejection function of the control loop yielded a higher value of 3.4 rad.

Biswas, A.↗
NASA NTRS2007

Absolute Radiometric Calibration of EUNIS-06

The Extreme-Ultraviolet Normal-Incidence Spectrometer (EUNIS) is a soundingrocket payload that obtains imaged high-resolution spectra of individual solar features, providing information about the Sun's corona and upper transition region. Shortly after its successful initial flight last year, a complete end-to-end calibration was carried out to determine the instrument's absolute radiometric response over its Longwave bandpass of 300 - 370A. The measurements were done at the Rutherford-Appleton Laboratory (RAL) in England, using the same vacuum facility and EUV radiation source used in the pre-flight calibrations of both SOHO/CDS and Hinode/EIS, as well as in three post-flight calibrations of our SERTS sounding rocket payload, the precursor to EUNIS. The unique radiation source provided by the Physikalisch-Technische Bundesanstalt (PTB) had been calibrated to an absolute accuracy of 7% (l-sigma) at 12 wavelengths covering our bandpass directly against the Berlin electron storage ring BESSY, which is itself a primary radiometric source standard. Scans of the EUNIS aperture were made to determine the instrument's absolute spectral sensitivity to +- 25%, considering all sources of error, and demonstrate that EUNIS-06 was the most sensitive solar E W spectrometer yet flown. The results will be matched against prior calibrations which relied on combining measurements of individual optical components, and on comparisons with theoretically predicted 'insensitive' line ratios. Coordinated observations were made during the EUNIS-06 flight by SOHO/CDS and EIT that will allow re-calibrations of those instruments as well. In addition, future EUNIS flights will provide similar calibration updates for TRACE, Hinode/EIS, and STEREO/SECCHI/EUVI.

Thomas, R. J.↗
NASA NTRS2012

Modeling and Assimilating Ocean Color Radiances

Radiances are the source of information from ocean color sensors to produce estimates of biological and geochemical constituents. They potentially provide information on various other aspects of global biological and chemical systems, and there is considerable work involved in deriving new information from these signals. Each derived product, however, contains errors that are derived from the application of the radiances, above and beyond the radiance errors. A global biogeochemical model with an explicit spectral radiative transfer model is used to investigate the potential of assimilating radiances. The results indicate gaps in our understanding of radiative processes in the oceans and their relationships with biogeochemical variables. Most important, detritus optical properties are not well characterized and produce important effects of the simulated radiances. Specifically, there does not appear to be a relationship between detrital biomass and its optical properties, as there is for chlorophyll. Approximations are necessary to get beyond this problem. In this reprt we will discuss the challenges in modeling and assimilation water-leaving radiances and the prospects for improving our understanding of biogeochemical process by utilizing these signals.

Gregg, Watson↗
NASA NTRS2017

NeMO-Net: The Neural Multi-Modal Observation and Training Network for Global Coral Reef Assessment

In the past decade, coral reefs worldwide have experienced unprecedented stresses due to climate change, ocean acidification, and anthropomorphic pressures, instigating massive bleaching and die-off of these fragile and diverse ecosystems. Furthermore, remote sensing of these shallow marine habitats is hindered by ocean wave distortion, refraction and optical attenuation, leading invariably to data products that are often of low resolution and signal-to-noise (SNR) ratio. However, recent advances in UAV and Fluid Lensing technology have allowed us to capture multispectral 3D imagery of these systems at sub-cm scales from above the water surface, giving us an unprecedented view of their growth and decay. Exploiting the fine-scaled features of these datasets, machine learning methods such as MAP, PCA, and SVM can not only accurately classify the living cover and morphology of these reef systems (below 8 percent error), but are also able to map the spectral space between airborne and satellite imagery, augmenting and improving the classification accuracy of previously low-resolution datasets. We are currently implementing NeMO-Net, the first open-source deep convolutional neural network (CNN) and interactive active learning and training software to accurately assess the present and past dynamics of coral reef ecosystems through determination of percent living cover and morphology. NeMO-Net will be built upon the QGIS platform to ingest UAV, airborne and satellite datasets from various sources and sensor capabilities, and through data-fusion determine the coral reef ecosystem makeup globally at unprecedented spatial and temporal scales. To achieve this, we will exploit virtual data augmentation, the use of semi-supervised learning, and active learning through a tablet platform allowing for users to manually train uncertain or difficult to classify datasets. The project will make use of Pythons extensive libraries for machine learning, as well as extending integration to GPU and High-End Computing Capability (HECC) on the Pleiades supercomputing cluster, located at NASA Ames. The project is being supported by NASAs Earth Science Technology Office (ESTO) Advanced Information Systems Technology (AIST-16) Program.

NeMO-Net↗
NASA NTRS2017

NeMO-Net The Neural Multi-Modal Observation Training Network for Global Coral Reef Assessment

In the past decade, coral reefs worldwide have experienced unprecedented stresses due to climate change, ocean acidification, and anthropomorphic pressures, instigating massive bleaching and die-off of these fragile and diverse ecosystems. Furthermore, remote sensing of these shallow marine habitats is hindered by ocean wave distortion, refraction and optical attenuation, leading invariably to data products that are often of low resolution and signal-to-noise (SNR) ratio. However, recent advances in UAV and Fluid Lensing technology have allowed us to capture multispectral 3D imagery of these systems at sub-cm scales from above the water surface, giving us an unprecedented view of their growth and decay. Exploiting the fine-scaled features of these datasets, machine learning methods such as MAP, PCA, and SVM can not only accurately classify the living cover and morphology of these reef systems (below 8 error), but are also able to map the spectral space between airborne and satellite imagery, augmenting and improving the classification accuracy of previously low-resolution datasets.We are currently implementing NeMO-Net, the first open-source deep convolutional neural network (CNN) and interactive active learning and training software to accurately assess the present and past dynamics of coral reef ecosystems through determination of percent living cover and morphology. NeMO-Net will be built upon the QGIS platform to ingest UAV, airborne and satellite datasets from various sources and sensor capabilities, and through data-fusion determine the coral reef ecosystem makeup globally at unprecedented spatial and temporal scales. To achieve this, we will exploit virtual data augmentation, the use of semi-supervised learning, and active learning through a tablet platform allowing for users to manually train uncertain or difficult to classify datasets. The project will make use of Pythons extensive libraries for machine learning, as well as extending integration to GPU and High-End Computing Capability (HECC) on the Pleiades supercomputing cluster, located at NASA Ames. The project is being supported by NASAs Earth Science Technology Office (ESTO) Advanced Information Systems Technology (AIST-16) Program.

Remote Sensin↗
NASA NTRS2021

ACIX-Aqua: A Global Assessment of Atmospheric Correction Methods for Landsat-8 and Sentinel-2 Over Lakes, Rivers, and Coastal Waters

Atmospheric correction over inland and coastal waters is one of the major remaining challenges in aquatic remote sensing, often hindering the quantitative retrieval of biogeochemical variables and analysis of their spatial and temporal variability within aquatic environments. The Atmospheric Correction Intercomparison Exercise (ACIX-Aqua), a joint NASA – ESA activity, was initiated to enable a thorough evaluation of eight state-of-the-art atmospheric correction (AC) processors available for Landsat-8 and Sentinel-2 data processing. Over 1000 radiometric matchups from both freshwaters (rivers, lakes, reservoirs) and coastal waters were utilized to examine the quality of derived aquatic reflectances (ρ̂w). This dataset originated from two sources: Data gathered from the international scientific community (henceforth called Community Validation Database, CVD), which captured predominantly inland water observations, and the Ocean Color component of AERONET measurements (AERONET-OC), representing primarily coastal ocean environments. This volume of data permitted the evaluation of the AC processors individually (using all the matchups) and comparatively (across seven different Optical Water Types, OWTs) using common matchups. We found that the performance of the AC processors differed for CVD and AERONET-OC matchups, likely reflecting inherent variability in aquatic and atmospheric properties between the two datasets. For the former, the median errors in ρ̂w560 and ρ̂w664 were found to range from 20 to 30% for best-performing processors. Using the AERONET-OC matchups, our performance assessments showed that median errors within the 15–30% range in these spectral bands may be achieved. The largest uncertainties were associated with the blue bands (25 to 60%) for best-performing processors considering both CVD and AERONET-OC assessments. We further assessed uncertainty propagation to the downstream products such as near-surface concentration of chlorophyll-a (Chla) and Total Suspended Solids (TSS). Using satellite matchups from the CVD along with in situ Chla and TSS, we found that 20–30% uncertainties in ρ̂w490≤λ≤743nm yielded 25–70% uncertainties in derived Chla and TSS products for top-performing AC processors. We summarize our results using performance matrices guiding the satellite user community through the OWT-specific relative performance of AC processors. Our analysis stresses the need for better representation of aerosols, particularly absorbing ones, and improvements in corrections for sky- (or sun-) glint and adjacency effects, in order to achieve higher quality downstream products in freshwater and coastal ecosystems.

Nima Pahlevan↗
DOE OSTI2022

Advanced Graphite Creep Uncertainty Analysis

Radiation damage estimation is an important component of the post irradiation analysis of the Advanced Graphite Creep (AGC) experiment. It depends primarily on the fast fluence, which is determined using well established methods of spectral adjustment. These are based on best estimates from models such as Monte Carlo N-Particle (MCNP), input cross-sections, and measured activities from flux wires in the experiment. Each of these parameters can propagate uncertainties which will affect the uncertainty in the calculated dose levels for AGC, or any experiment irradiated within a reactor. While the methods of propagating uncertainty are well-established, the final uncertainty estimates they provide are only as good as the estimates of uncertainty in the inputs on which they are based. The purpose of this work is to outline some deficiencies in the ways these input uncertainties are presently estimated, and to outline a methodology by which they can be improved. The fast fluence and radiation damage received by graphite specimens irradiated in the Advanced Graphite Creep (AGC) experiments is presently estimated using spectral adjustment methods that are based on both flux wire activity measurements, and MCNP model predictions. This work describes an ongoing effort to quantify and propagate uncertainties in inputs to the spectral adjustment process, and thereby quantify the resultant error in radiation damage (dpa) estimates. The effort is multi-faceted, and we consider the impacts of both the set of flux wires selected, and the counting process. An expanded set of flux wires is identified that provides a more comprehensive data set on the fast spectrum. To address the counting process itself, a series of round-robin measurements in several reactor metrology laboratories across the Department of Energy (DOE) complex and nuclear industry are being undertaken to refine the American Society for Testing and Materials (ASTM) standards for flux wire measurements. To address the contribution of uncertainty in the MCNP model predictions, an uncertainty quantification (UQ) tool has been developed that statistically samples the model input parameters, runs a series of cases, and assimilates the results to provide an overall uncertainty. The impact of the MCNP UQ tool results is demonstrated by re-analyzing previous AGC flux wire and irradiation data. While the expanded flux wire set obviously cannot be added to these experiments retroactively, plans for future graphite irradiations are outlined.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

The Sixth Data Release of the Radial Velocity Experiment (RAVE). I. Survey Description, Spectra, and Radial Velocities

The Radial Velocity Experiment (Rave) is a magnitude-limited (9 < I < 12) spectroscopic survey of Galactic stars randomly selected in Earth’s southern hemisphere. The Rave medium-resolution spectra (R ~ 7500) cover the Ca-triplet region (8410–8795 Å). The sixth and final data release (DR6) is based on 518,387 observations of 451,783 unique stars. Rave observations were taken between 2003 April 12 and 2013 April 4. Here we present the genesis, setup, and data reduction of Rave as well as wavelength-calibrated and flux-normalized spectra and error spectra for all observations in Rave DR6. Furthermore, we present derived spectral classification and radial velocities for the Rave targets, complemented by cross-matches with Gaia DR2 and other relevant catalogs. A comparison between internal error estimates, variances derived from stars with more than one observing epoch, and a comparison with radial velocities of Gaia DR2 reveals consistently that 68% of the objects have a velocity accuracy better than 1.4 km s{sup –1}, while 95% of the objects have radial velocities better than 4.0 km s{sup –1}. Stellar atmospheric parameters, abundances and distances are presented in a subsequent publication. The data can be accessed via the Rave website (http://rave-survey.org) or the Vizier database.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2011

Power Spectrum of Uplink Array Signals with Random Phase and Delay Errors

Link Array signals emanating from different antennas must be compensated for Doppler and delay in order to achieve the N(sup 2) array gain predicted by theory. However compensation is never perfect, leaving residual errors that cause losses in array gain and degradation in signal quality. Here we develop a mathematical model for Uplink Array signals in the presence of phase and delay errors, similar to well-known multipath analyses but with features unique to this problem. The resulting losses and distortions are described, and the power spectral density of the array signal derived first conditioned on a given error vector, then averaged over distributions deemed suitable for Uplink Array applications. The impact of phase and delay errors on array gain and signal distortion are addressed, and the maximum data throughput is quantified in terms of the assumed error statistics.

uplinks arrays↗
NASA NTRS2020

Planning In-Flight Calibration for XRISM

The XRISM X-ray observatory will fly two advanced instruments, the Resolve high-resolution spectrometer and the Xtend wide-field imager. These instruments, particularly Resolve, pose calibration challenges due to the unprecedented combination of spectral resolution, spectral coverage, and effective area, combined with a need to characterize the imaging fidelity of the full instrument system to realize the mission’s ambitious science goals. We present the status of the XRISM in-flight calibration plan, building on lessons from Hitomi and other X-ray missions. We present a discussion of targets and observing strategies to address the needed calibration measurements, with a focus on developing methodologies to plan a thorough and flexible calibration campaign and provide insight on calibration systematic error. We also discuss observations that exploit Resolve’s spectral resolution to calibrate atomic codes, and cross-calibration between the XRISM instruments and with other observatories.

Eric D Miller↗
DOE OSTI2022

Trends in Downwelling Longwave Radiance Over the Southern Great Plains

Downwelling longwave radiation is an important part of the surface energy budget. Spectral trends in the downwelling longwave radiance (DLR) provide insight into the radiative drivers of climate change. In this research, we process and analyze a 23-year DLR record measured by the Atmospheric Emitted Radiance Interferometer (AERI) at the U.S. Department of Energy Atmospheric Radiation Program Southern Great Plains (SGP) site. Two AERIs were deployed at SGP with an overlapping observation period of about 10 years, which allows us to examine the consistency and accuracy of the measurements and to account for discrepancies between them due to errors associated with the instruments themselves. We then analyzed the all-sky radiance trends in DLR, which are associated with the surface warming trend at SGP during this same period and also the complex changes in meteorological conditions. For instance, the observed radiance in the CO2 absorption band follows closely the near-surface air temperature variations. The significant positive radiance trends in weak absorption channels, such as in the wings of the CO 2 band and in the weak absorption channels in the H 2 O vibration-rotational band, show earlier detectability of climate change. The magnitude of the radiance trend uncertainty in the DLR record mainly results from internal climate variability rather than from measurement error, which highlights the importance of continuing the DLR spectral measurements to unambiguously detect and attribute climate change.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRSDate not supplied

Deriving Essential Climate Variable Data from Multiple Satellite Remote Sensors Using a Consistent Fingerprinting Method

Hyperspectral observations from satellite-based sensors provide high information content for the Earth’s atmospheric and surface properties. Traditionally, long-term climate products are derived by performing spatial and temporal averaging of level-2 satellite products. It is a time-consuming process to generate level-2 data products since modern hyperspectral satellite sensors have millions of observations each day with thousands of spectral channels for each observation. Additionally, differences in level-2 retrieval algorithms can lead to errors in the climate products when fusing data from different satellite sensors. We have developed a radiometrically consistent spectral fingerprinting method, which overcomes the above-mentioned shortcomings, to derive climate change signals from multiple satellite sensors using spatiotemporally averaged level-1 data. We have applied this method to Atmospheric Infrared Sounder (AIRS) and Cross-track Infrared Sounder (CrIS) data and generated decade-long climate data records for atmospheric temperature, water vapor, cloud, trace gases, and surface skin temperature. A key component to this work is a set of observational-based radiative kernels produced from CrIS level-1 data using a single field of view (SFOV) optimal estimation retrieval algorithm. Only limited CrIS level-1 data (e.g., 1-2 years of data) are needed to the derive radiative kernels. Our Principal Component-based Radiative Model (PCRTM) enables us to perform SFOV retrievals under all sky conditions and provides radiative kernels (including those for clouds) needed by the spectral fingerprinting method. In this presentation, we will describe the basic methodology, the details of the algorithm, and results from NASA Aqua AIRS and Suomi-NPP CrIS data. The method can be applied to study future hyperspectral remote sensors such as CLARREO (Climate Absolute Radiance and Refractivity Observatory) Pathfinder (CPF), Tropospheric Emissions: Monitoring of Pollution (TEMPO), Surface Biology and Geology (SBG), Aerosol and Cloud, Convection and Precipitation (ACCP).

Xu Liu↗
NASA NTRS1994

Spectroscopy of Solid State Laser Materials

We retrieved the vertical distribution of ozone from a series 0.005-0.013/cm resolution infrared solar spectra recorded with the McMath Fourier Transform spectrometer at the Kitt Peak National Solar Observatory. The analysis is based on a multi-layer line-by-line forward model and a semi-empirical version of the optimal estimation inversion method by Rodgers. The 1002.6-1003.2/cm spectral interval has been selected for the analysis on the basis of synthetic spectrum calculations. The characterization and error analysis of the method have been performed. It was shown that for the Kitt Peak spectral resolution and typical signal-to-noise ratio (greater than or equal to 100) the retrieval is stable, with the vertical resolution of approximately 5 km attainable near the surface degrading to approximately 10 km in the stratosphere. Spectra recorded from 1980 through 1993 have been analyzed. The retrieved total ozone and vertical profiles have been compared with total ozone mapping spectrometer (TOMS) satellite total columns for the location and dates of the Kitt Peak Measurements and about 100 ozone ozonesoundings and Brewer total column measurements from Palestine, Texas, from 1979 to 1985. The total ozone measurements agree to +/- 2%. The retrieved profiles reproduce the seasonally averaged variations with altitude, including the ozone spring maximum and fall minimum measured by Palestine sondes, but up to 15% differences in the absolute values are obtained.

Buoncristiani, A. M.↗
NASA NTRS1995

Thermal infrared spectra of the Moon

Contrary to recent assertions in the literature, lunar emission spectra obtained at an altitude of 32 km with a balloon-borne telescope are virtually undistorted by atmospheric absorption, except in the ozone region. These spectra have been found to correlate closely with laboratory emission spectra of returned lunar samples measured in a simulated lunar environment. Thus, lunar spectra obtained with the balloon-borne telescope system are the standards against which groundbased spectral measurements of the Moon should be compared. Comparison of balloon-borne measurements with recent groundbased spectral measurements suggests that the latter suffer from some source of systematic error. When high-quality lunar spectra are available, they will be best interpreted by comparison with returned lunar samples, rather than terrestrial minerals or rocks, because of subtle spectral differences between lunar and terrestrial minerals perhaps associated with incipient alteration of the latter.

Salisbury, John W.↗
NASA NTRS1976

Performance of convolutionally encoded noncoherent MFSK modem in fading channels

The performance of a convolutionally encoded noncoherent multiple-frequency shift-keyed (MFSK) modem utilizing Viterbi maximum-likelihood decoding and operating on a fading channel is described. Both the lognormal and classical Rician fading channels are considered for both slow and time-varying channel conditions. Primary interest is in the resulting bit error rate as a function of the ratio between the energy per transmitted information bit and noise spectral density, parameterized by both the fading channel and code parameters. Fairly general upper bounds on bit error probability are provided and compared with simulation results in the two extremes of zero and infinite channel memory. The efficacy of simple block interleaving in combatting channel memory effects are thoroughly explored. Both quantized and unquantized receiver outputs are considered.

Modestino, J. W.↗
NASA NTRS1976

Ozone spectroscopy with a CO2 waveguide laser

Ozone spectral measurements were conducted with a waveguide CO2 laser, which was continuously tunable over a + or - 450-MHz region, about several lines in the P-branch of the band near the 9.5-micron wavelength region. A passively stabilized low-pressure CO2 laser was also used to provide reference CO2 frequencies. The frequencies of several ozone lines were determined in the nu-3 band, which are near CO2 laser line frequencies in the 9.5-micron wavelength region. The absolute measurement accuracy is estimated to be + or - 6 MHz, and the measurements indicate that the ozone line frequencies listed in currently available spectral compilations are 0.003-0.006 per cm too high. The size of this error is small by conventional IR standards, but extremely important when CO2 laser instruments are used to monitor stratospheric ozone, where line widths in this spectral region are typically 0.001/cm. Empirically determined absorption curves must be constructed in order to calibrate laser differential absorption instrument properly when low-altitude ozone measurements are conducted.

Menzies, R. T.↗