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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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NASA NTRS1997

Measurement and Validation of Bidirectional Reflectance of Space Shuttle and Space Station Materials for Computerized Lighting Models

Task illumination has a major impact on human performance: What a person can perceive in his environment significantly affects his ability to perform tasks, especially in space's harsh environment. Training for lighting conditions in space has long depended on physical models and simulations to emulate the effect of lighting, but such tests are expensive and time-consuming. To evaluate lighting conditions not easily simulated on Earth, personnel at NASA Johnson Space Center's (JSC) Graphics Research and Analysis Facility (GRAF) have been developing computerized simulations of various illumination conditions using the ray-tracing program, Radiance, developed by Greg Ward at Lawrence Berkeley Laboratory. Because these computer simulations are only as accurate as the data used, accurate information about the reflectance properties of materials and light distributions is needed. JSC's Lighting Environment Test Facility (LETF) personnel gathered material reflectance properties for a large number of paints, metals, and cloths used in the Space Shuttle and Space Station programs, and processed these data into reflectance parameters needed for the computer simulations. They also gathered lamp distribution data for most of the light sources used, and validated the ability to accurately simulate lighting levels by comparing predictions with measurements for several ground-based tests. The result of this study is a database of material reflectance properties for a wide variety of materials, and lighting information for most of the standard light sources used in the Shuttle/Station programs. The combination of the Radiance program and GRAF's graphics capability form a validated computerized lighting simulation capability for NASA.

Fletcher, Lauren E.↗

NASA NTRS2018

LaSRC (Land Surface Reflectance Code): Overview, Application and Validation Using MODIS, VIIRS, LANDSAT and Sentinel 2 Data's

This paper presents a generic approach developed to derive surface reflectance over land from a variety of sensors. This technique builds on the extensive dataset acquired by the Terra platform by combining MODIS and MISR to derivean explicit and dynamic map of band ratio's between blue and red channels and is a refinement of the operational approach used for MODIS and LANDSAT over the past 15 years. We will present the generic approach and the application to MODIS VIIRS, LANDSAT and Sentinel 2 data's and its validation using the AERONET data.

validation↗

NASA NTRS1972

Criticality experiments and analysis of molybdenum reflected cylindrical uranyl fluoride water solution reactors

Clean criticality data were obtained from molybdenum-reflected cylindrical uranyl-fluoride-water solution reactors. Using ENDF/B molybdenum cross sections, a nine energy group two-dimensional transport calculation of a reflected reactor configuration predicted criticality to within 7 cents of the experimental value. For these reactors, it was necessary to compute the reflector resonance integral by a detailed transport calculation at the core-reflector interface volume in the energy region of the two dominant resonances of natural molybdenum.

Fieno, D.↗

DOE OSTI2020

ENDF/B-VIII.0 Augmented Covariance Data The first iteration [Slides]

Nuclear data are necessary for reliable modeling and simulation of the next generation of nuclear reactors. However, the variation in the ratio of the computed to experimental values (C/E) for certain types of nuclear systems is much less than predicted by evaluated nuclear data file (ENDF)/B covariances. Figure 1 provides an example of a set of metal-plutonium-fueled, fast-spectrum (PU-MET-FAST) integral experiments from the International Criticality Safety Benchmark Evaluation Project (ICSBEP) in the Oak Ridge National Laboratory (ORNL) VALID database. The variation in the C/E values, shown with one standard deviation error bars, is 100% covered by both the SCALE and ENDB/VIII.0 covariance data. This is due to the comparisons to integral data that are essential during the evaluation process. However, the ENDF evaluations represent uncertainties and correlations in differential data only; they do not reflect the impact of the comparison to integral data in the covariance evaluations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2019

ENDF/B-VIII.0 Augmented Covariance Data The first iteration [Slides]

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

NASA NTRS2021

A Chlorophyll-a Algorithm for Landsat-8 Based on Mixture Density Networks

Retrieval of aquatic biogeochemical variables, such as the near-surface concentration of chlorophyll-a (Chla) in inland and coastal waters via remote observations, has long been regarded as a challenging task. This manuscript applies Mixture Density Networks (MDN) that use the visible spectral bands available by the Operational Land Imager (OLI) aboard Landsat-8 to estimate Chla. We utilize a database of co-located in situ radiometric and Chla measurements (N = 4,354), referred to as Type A data, to train and test an MDN model (MDN(A)). This algorithm’s performance, having been proven for other satellite missions, is further evaluated against other widely used machine learning models (e.g., support vector machines), as well as other domain-specific solutions (OC3), and shown to offer significant advancements in the field. Our performance assessment using a held-out test data set suggests that a 49% (median) accuracy with near-zero bias can be achieved via the MDN(A) model, offering improvements of 20 to 100% in retrievals with respect to other models. The sensitivity of the MDN(A) model and benchmarking methods to uncertainties from atmospheric correction (AC) methods, is further quantified through a semi-global matchup dataset (N = 3,337), referred to as Type B data. To tackle the increased uncertainties, alternative MDN models (MDN(B)) are developed through various features of the Type B data (e.g., Rayleigh-corrected reflectance spectra ρ(s)). Using held-out data, along with spatial and temporal analyses, we demonstrate that these alternative models show promise in enhancing the retrieval accuracy adversely influenced by the AC process. Results lend support for the adoption of MDN(B) models for regional and potentially global processing of OLI imagery, until a more robust AC method is developed. Index Terms—Chlorophyll-a, coastal water, inland water, Landsat-8, machine learning, ocean color, aquatic remote sensing.

Brandon Smith↗

DOE OSTI2019

ENDF/B-VIII.0 Augmented Covariance Data: The first iteration

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

NASA NTRS1985

Estimation of total above-ground phytomass production using remotely sensed data

Remote sensing potentially offers a quick and nondestructive method for monitoring plant canopy condition and development. In this study, multispectral reflectance and thermal emittance data were used in conjunction with micrometeorological data in a simple model to estimate above-ground total dry phytomass production of several spring wheat canopies. The fraction of absorbed photosynthetic radiation (PAR) by plants was estimated from measurements of visible and near-infrared canopy reflectance. Canopy radiation temperature was used as a crop stress indicator in the model. Estimated above-ground phytomass values based on this model were strongly correlated with the measured phytomass values for a wide range of climate and plant-canopy conditions.

Asrar, G.↗

DOE OSTI2021

A New Approach to Predict Hydrogeological Parameters Using Shear Waves from the Multichannel Analysis of Surface Waves Method

For near-surface contaminant characterization, the accurate prediction of hydrogeological parameters in anisotropic and heterogeneous environments has been a challenge since the last decades. However, recent advances in near-surface geophysics have facilitated the use of geophysical data for hydrogeological characterization in the last few years. A pseudo 3-D high resolution P-wave shallow seismic reflection survey was performed at the P Reactor Area, Savannah River Site, South Carolina in order to delineate and predict migration pathways of a large contaminant plume including trichloroethylene. This contaminant plume originates from the northwest section of the reactor facility that is located within the Upper Atlantic Coastal Plain. The data were collected with 40 Hz geophones, an accelerated weight-drop as seismic source and 1 m receiver spacing with near- and far-offsets of 0.5 and 119.5 m, respectively. In such areas with near-surface contaminants, a detailed subsurface characterization of the vadose zone hydraulic parameters is very important. Indeed, an inexpensive method of deriving such parameters by the use of seismic reflection surveys is beneficial, and our approach uses the relationship between seismic velocity and hydrogeological parameters together with empirical observations relating porosity to permeability and hydraulic conductivity. Shear wave velocity ( V s ) profiles were estimated from surface wave dispersion analysis of the seismic reflection data and were subsequently used to derive hydraulic parameters such as porosity, permeability, and hydraulic conductivity. Additional geophysical data including core samples, vertical seismic profiling, surface electrical resistivity tomography, natural gamma and electrical resistivity logs allowed for a robust assessment of the validity and geological significance of the estimated V s and hydrogeological models. The results demonstrate the usefulness of this approach for the upper 15 m of shallow unconsolidated sediments even though the survey design parameters were not optimal for surface wave analysis due to the higher than desired frequency geophones.

Engineering↗

NASA NTRS1993

Thermal infrared emission spectroscopy of natural surfaces: Application to desert varnish coatings on rocks

Thermal infrared spectroscopy has become an increasingly important tool for remote compositional analysis and geologic mapping. Most published laboratory measurements have been obtained in bidirectional reflection or transmission, whereas remotely sensed thermal infrared data are obtained by measuring the emitted energy. Section 2 of this paper describes a laboratory technique for determining calibrated emissivities of natural surfaces. Equations are developed to account for the energy reflected from the environment and to determine directly the sample temperature from measurements of hot and cold blackbody targets. Two methods for determining emissivity are developed: one in which only a hot sample measurement is made and the reflected background energy is removed by modeling, and a second in which the sample is cooled and the reflected energy is measured directly. Relative emissivity can be obtained to approximately 1% and absolute emissivities can be obtained to 2-15%, depending on the validity of the assumption that the emissivity of the sample is unity at some wavelength. The emission data agree well within the hemispherically integrated reflection data but point out probelms associated with bidirectional reflectance measurements. Section 3 applies emissivity measurements to the study of layered surfaces consisting of desert varnish coatings on granite and granodiorite rock suites. Two linear models are developed: the first assumes linear mixing of independent emission from the substrate and varnish (checkerboard model); the second models tansmission through an absorbing/emitting medium. Regardless of whether the varnish is or is not relatively transparant and strongly absorptive, the spectral effect of varnish increases linearly with varnish thickness, indicating that thick patches of varnish dominate the spectral properties. As a result, medium varnish thickness can be determined from spectral measurements. In addition, the composition of a substrate can be estimated through varnish layers up to 40-50 micrometers in median thickness, and the composition of the varnish material can be determined if the substrate material is known. The varnishes studied are composed primarily of clay materials, consistent with previous studies of varnish composition.

Christensen, Philip R.↗

NASA NTRS1991

Biophysical information in asymmetric and symmetric diurnal bidirectional canopy reflectance

The authors present a theory for partitioning the information content in diurnal bidirectional reflectance measurements in order to detect differences potentially related to biophysical variables. The theory, which divides the canopy reflectance into asymmetric and symmetric functions of solar azimuth angle, attributes asymmetric variation to diurnal changes in the canopy biphysical properties. The symmetric function is attributed to the effects of sunlight interacting with a hypothetical average canopy which would display the average diurnal properties of the actual canopy. The authors analyzed radiometer data collected diurnally in the Thematic Mapper wavelength bands from two walnut canopies that received differing irrigation treatments. The reflectance of the canopies varied with sun and view angles and across seven bands in the visible, near-infrared, and middle infrared wavelength regions. Although one of the canopies was permanently water stressed and the other was stressed in mid-afternoon each day, no water stress signature was unambiguously evident in the reflectance data.

Vanderbilt, Vern C.↗

DOE OSTI2024

Long-Range Biometric Identification in Real World Scenarios: A Comprehensive Evaluation Framework Based on Missions

The considerable body of data available for evaluating biometric recognition systems in Research and Development (R&D) environments has contributed to the increasingly common problem of target performance mismatch. Biometric algorithms are frequently tested against data that may not reflect the real world applications they target. From a Testing and Evaluation (T&E) standpoint, this domain mismatch causes difficulty assessing when improvements in State-of-the-Art (SOTA) research actually translate to improved applied outcomes. This problem can be addressed with thoughtful preparation of data and experimental methods to reflect specific use-cases and scenarios.To that end, this paper evaluates research solutions for identifying individuals at ranges and altitudes, which could support various application areas such as counterterrorism, protection of critical infrastructure facilities, military force protection, and border security. We address challenges including image quality issues and reliance on face recognition as the sole biometric modality. By fusing face and body features, we propose developing robust biometric systems for effective long-range identification from both the ground and steep pitch angles. Preliminary results show promising progress in whole-body recognition. This paper presents these early findings and discusses potential future directions for advancing long-range biometric identification systems based on mission-driven metrics.

Aykac, Deniz↗

NASA NTRS1992

Toxic substances registry system: Index of material safety data sheets

The Material Safety Data Sheets (MSDSs) listed reflect product inventories and associated MSDSs which were submitted to the Toxic Substance Registry data base maintained by the Base Operations Contractors of the Biomedical Operations and Research Office of NASA Kennedy. The purpose of the index is to provide a means of accessing information on the hazards associated with the toxic and otherwise hazardous chemicals stored and used at NASA Kennedy. Indices are provided for manufacturers, trademarks, and stock numbers.

Source record↗

NASA NTRS2007

Electric Fields, Cloud Microphysics, and Reflectivity in Anvils of Florida Thunderstorms

A coordinated aircraft - radar project that investigated the electric fields, cloud microphysics and radar reflectivity of thunderstorm anvils near Kennedy Space Center is described. Measurements from two cases illustrate the extensive nature of the microphysics and electric field observations. As the aircraft flew from the edges of anvils into the interior, electric fields very frequently increased abruptly from approximately 1 to more than 10 kV m(exp -1) even though the particle concentration and radar reflectivity increased smoothly. The abrupt increase in field usually occurred when the aircraft entered regions with a reflectivity of 10 to 15 dBZ. It is suggested that the abrupt increase in electric field may be because the charge advection from the storm core did not occur across the entire breadth of the anvil and was not constant in time. Screening layers were not detected near the edges of the anvils. Some long-lived anvils showed subsequent enhancement of electric field and reflectivity and growth of particles, which if localized, might be a factor in explaining the abrupt change of field in some cases. Comparisons of electric field magnitude with particle concentration or reflectivity for a combined data set that included all anvil measurements showed a threshold behavior. When the average reflectivity, such as in a 3-km cube, was less than approximately 5 dBZ, the electric field magnitude was les than kV m(exp -1). Based on these findings, the Volume Averaged Height Integrated Radar Reflectivity (VAHIRR) is now being used by NASA, the Air Force and Federal Aviation Administration in new Lightning Launch Commit Criteria as a diagnostic for high electric fields in anvils.

Dye, J. E.↗

NASA NTRS2006

Electric Fields, Cloud Microphysics, and Reflectivity in Anvils of Florida Thunderstorms

A coordinated aircraft - radar project that investigated the electric fields, cloud microphysics and radar reflectivity of thunderstorm anvils near Kennedy Space Center is described. Measurements from two cases illustrate the extensive nature of the microphysics and electric field observations. As the aircraft flew from the edges of anvils into the interior, electric fields very frequently increased abruptly from approx.1 to >10 kV/m even though the particle concentrations and radar reflectivity increased smoothly. The abrupt increase in field usually occurred when the aircraft entered regions with a reflectivity of 10 to 15 dBZ. It is suggested that the abrupt increase in electric field may be because the charge advection from the storm core did not occur across the entire breadth of the anvil and was not constant in time. Screening layers were not detected near the edges of the anvils. Some long-lived anvils showed subsequent enhancement of electric field and reflectivity and growth of particles, which if localized, might be a factor in explaining the abrupt change of field in some cases. Comparisons of electric field magnitude with particle concentration or reflectivity for a combined data set that included all anvil measurements showed a threshold behavior. When the average reflectivity, such as in a 3-km cube, was less than approximately 5 dBZ, the electric field magnitude was <3 kV/m. Based on these findings, the Volume Averaged Height Integrated Radar Reflectivity (VAHIRR) is now being used by NASA, the Air Force and Federal Aviation Administration in new Lightning Launch Commit Criteria as a diagnostic for high electric fields in anvils.

Dye, J. E.↗

NASA NTRS2022

Using Desis and EO-1 Hyperion Reflectance Time Series for the Assessment of Vegetation Traits and Gross Primary Production (GPP)

This study evaluates the potential of the DLR Earth Sensing Imaging Spectrometer (DESIS) visible through near-infrared (VNIR) surface reflectance to augment the EO-1 Hyperion full spectrum (400-2400 nm) reflectance collection over vegetated flux sites to extend the reflectance time series up to the present. We compared DESIS and Hyperion surface reflectance magnitude and variability at a pseudo-invariant site (PICS) and a vegetated flux site (VFS). VNIR reflectance magnitudes between the two sensors did not significantly differ at the PICS. However, DESIS variability was higher, likely due to differences in the data acquisition time and observation geometry. Using empirical and biophysical models, both DESIS and Hyperion datasets captured the seasonal variations in gross primary production (GPP) and canopy bio-physical parameters such as chlorophyll content, leaf area index (LAI), and senescent material at the VFS. Differences in the magnitudes of the bio-physical parameters were observed, likely due to the differences in the sensors spectral range and resolution. Using VNIR reflectance from EO-1 Hyperion with DESIS convolved to Hyperion spectral resolution to estimate canopy chlorophyll and GPP, we demonstrate that combining historic and current space-based reflectance data in a common multi-sensor approach is feasible. This is of importance for extending the reflectance record established with EO-1 Hyperion to provide continuity with the current orbital instruments (e.g., DESIS/ISS, PRISMA/ASI) and the forthcoming NASA Surface Biology and Geology (SBG), ESA CHIME and DLR EnMAP satellite missions, which is of key importance for comparisons of current and past trends in the seasonal dynamics of vegetation traits and photosynthetic function.

DESIS↗

NASA NTRS1970

Multispectral analysis of limestone, dolomite, and granite, Mill Creek, Oklahoma

Spectral reflectance and thermal emission data were collected at the Mill Creek, Oklahoma test site during NASA missions 132 and 133 in June 1970. The data were collected by three aircraft flown several times during the diurnal cycle at altitudes of 150 to 17,000 m above mean terrain. Reflectance of the main rock types (limestone, dolomite, and granite) was determined from the data collected using a 12-channel multispectral scanner during mission 133 and from thermal infrared images recorded during mission 132 on an RS-7 scanner from 17,000 m above terrain. A preliminary rock recognition map was generated automatically using data collected from 900 m above terrain. The discrimination provided by the map is reasonably accurate. Misidentification occurred in areas of unusually high dolomite reflectivity. High altitude thermal infrared (10 to 12 micrometers) images show regional folds and faults distinguished by the presence of thermally contrasting materials. Linear and curvilinear structural features two to three times smaller than the nominal 17 m resolution could be detected.

Rowan, L. C.↗

DOE OSTI2021

Detection of the Metabolic Response to Drought Stress Using Hyperspectral Reflectance

Drought is the most important limitation on crop yield. Understanding and detecting drought stress in crops is vital for improving water use efficiency through effective breeding and management. Leaf reflectance spectroscopy offers a rapid, non-destructive alternative to traditional techniques for measuring plant traits involved in a drought response. We measured drought stress in six glasshouse-grown agronomic species using physiological, biochemical and spectral data. In contrast to physiological traits, leaf metabolite concentrations revealed drought stress before it was visible to the naked eye. We used full-spectrum leaf reflectance data to predict metabolite concentrations using partial least-squares regression, with validation R2 values of 0.49 to 0.87. We show for the first time that spectroscopy may be used for the quantitative estimation of proline and abscisic acid, demonstrating the first use of hyperspectral data to detect a phytohormone. We used linear discriminant analysis and partial least squares discriminant analysis to differentiate between droughted and watered plants based on measured traits (accuracy: 71%) and raw spectral data (66%). Finally, we validated our glasshouse-developed models in an independent field trial. We demonstrate that spectroscopy can detect drought stress via underlying biochemical changes, before visual differences occur, representing a powerful advance for measuring limitations on yield.

54 ENVIRONMENTAL SCIENCES↗