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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 1,765 records · Page 98

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NASA NTRS1990

Active vibration control activities at the LaRC - Present and future

The NASA Controls-Structures-Interaction (CSI) program is presented with a description of the ground testing element objectives and approach. The goal of the CSI program is to develop and validate the technology required to design, verify and operate space systems in which the structure and the controls interact beneficially to meet the needs of future NASA missions. The operational Mini-Mast ground testbed and some sample active vibration control experimental results are discussed along with a description of the CSI Evolutionary Model testbed presently under development. Initial results indicate that embedded sensors and actuators are effective in controlling a large truss/reflector structure.

Newsom, J. R.↗

NASA NTRS2007

Analysis of Fluid Gauge Sensor for Zero or Microgravity Conditions using Finite Element Method

In this paper the Finite Element Method (FEM) is presented for mass/volume gauging of a fluid in a tank subjected to zero or microgravity conditions. In this approach first mutual capacitances between electrodes embedded inside the tank are measured. Assuming the medium properties the mutual capacitances are also estimated using FEM approach. Using proper non-linear optimization the assumed properties are updated by minimizing the mean square error between estimated and measured capacitances values. Numerical results are presented to validate the present approach.

Deshpande, Manohar D.↗

NASA NTRS2016

Ensemble-Based Assimilation of Aerosol Observations in GEOS-5

MERRA-2 is the latest Aerosol Reanalysis produced at NASA's Global Modeling Assimilation Office (GMAO) from 1979 to present. This reanalysis is based on a version of the GEOS-5 model radiatively coupled to GOCART aerosols and includes assimilation of bias corrected Aerosol Optical Depth (AOD) from AVHRR over ocean, MODIS sensors on both Terra and Aqua satellites, MISR over bright surfaces and AERONET data. In order to assimilate lidar profiles of aerosols, we are updating the aerosol component of our assimilation system to an Ensemble Kalman Filter (EnKF) type of scheme using ensembles generated routinely by the meteorological assimilation. Following the work performed with the first NASA's aerosol reanalysis (MERRAero), we first validate the vertical structure of MERRA-2 aerosol assimilated fields using CALIOP data over regions of particular interest during 2008.

LDE↗

NASA NTRS2016

Ultraviolet Satellite Measurements of Volcanic Ash

Ultraviolet (UV) remote sensing of volcanic ash and other absorbing aerosols from space began with the launch of the first Total Ozone Mapping Spectrometer (TOMS) instrument in 1978. Subsequent UV satellite missions (TOMS, GOME, SCIAMACHY, OMI, GOME-2, OMPS) have extended UV ash measurements to the present, generating a unique multidecadal record. A UV Aerosol Index (UVAI) based on two near-UV wavelengths, equally applicable to multispectral (TOMS, DSCOVR) or hyperspectral (GOME, SCIAMACHY, OMI, GOME-2, OMPS) instruments, has been used to derive a unique absorbing aerosol climatology across multiple UV satellite missions. Advantages of UV ash measurements relative to infrared (IR) techniques include the ability to detect ash at any altitude (assuming no clouds), above clouds, and over bright surfaces, where visible and IR techniques may fail. Disadvantages include the daytime-only restriction and nonspecificity to silicate ash, since UV measurements are sensitive to any UV-absorbing aerosol, including smoke, desert dust, and pollution. However, simultaneous retrieval of sulfur dioxide (SO2) abundance and UVAI provides robust discrimination of volcanic clouds. Although the UVAI is only semiquantitative, it has proved successful at detecting and tracking volcanic ash clouds from many volcanic eruptions since 1978. NASA A-Train measurements since 2006 (eg, CALIOP) have provided much improved constraints on volcanic ash altitude, and also permit identification of aerosol type through sensor synergy. Quantitative UV retrievals of ash optical depth, effective particle size, and ash column mass are possible and require assumptions of ash refractive index, particle size distribution, and ash layer altitude. The lack of extensive ash refractive index data in the UV-visible and the effects of ash particle shape on retrievals introduce significant uncertainty in the retrieved parameters, although limited validation against IR ash retrievals has been successful. In this contribution, we review UV ash detection and retrieval techniques and provide examples of volcanic eruptions detected in the approx. 37 year data record.

Multidecadal record↗

NASA NTRSDate not supplied

Generation of Merged Radar-Lidar Data Products during the IMPACTS 2020 Field Campaign

A novel, composite lidar and radar data products was created using lidar and radar data products generated from the NASA ER-2 aircraft during the NASA IMPACTS 2020 field campaign. This product is intended to supplement the raw data sources, tease out additional aspects of the mechanisms underpinning wintertime cyclones, and enhance our understanding of microphysical properties in sensor overlap regions. Initial combined products focused on generating normalized fields of ER-2 based radar and lidar data to provide a more comprehensive visualization of storm structure (precipitation bands, cloud tops, melting levels, etc.) Ongoing work has focused on developing a combined radar-lidar reflectivity product and deriving hydrometeor particle properties (type, orientation, etc.) using ER-2-based depolarization data. To validate these hydrometeor properties, we leverage coincident overpasses of the high-altitude ER-2 aircraft with the suite of cloud particle probes on the in-situ P-3 aircraft during coincident flight overpasses. This work aims to provide vital information to help IMPACTS achieve its mission goal of improving microphysical properties retrievals from airborne and spaceborne platforms for these high-impact winter storm events.

Stephen D Nicholls↗

DOE OSTI2021

Multimodal communication system

A multimodal communication system includes a vehicle controller that controls one or more systems or subsystems of an unmanned vehicle. The communication controller manages communication and logical access to the unmanned vehicle. One or more sensors in communication with the communication controller detects and measures physical properties in proximity to the unmanned vehicle. Transceivers receive the unmanned vehicle commands that are transmitted simultaneously or concurrently and a monotonic generator generates a monotonic object each time the unmanned vehicle's operating state changes. The communication controller executes the first unmanned vehicle command received that has the correct cryptographic hash validating knowledge of the unmanned vehicle's current operating state.

Duncan, Andrew M.↗

DOE OSTI2016

Fiber optic instrumentation for nuclear fuels and materials irradiations

The ability to predict the safety and reliability of new and advanced nuclear fuels and materials requires high-fidelity measurements during instrumented irradiation experiments. Optical fiber-based sensors are promising candidates for instrumentation in high-temperature (300-1200 C. degrees) irradiation environments, provided that signal attenuation due to radiation damage and/or high-temperature operation is not prohibitively large. To determine the feasibility of using silica optical fibers in instrumented irradiation capsules, a computational model has been developed to predict broadband optical attenuation in fused silica fiber materials as a function of time, temperature, and dose. Defect concentrations are calculated using a set of 11 coupled differential equations that include neutron-induced displacement, radiation-induced bond cleavage at precursor sites, and thermally-assisted molecular diffusion and defect recombination at elevated temperatures. Defect concentrations are coupled with the known optical properties of the various defects in fused silica to predict optical attenuation. The effects of radiation-induced compaction (i.e., formation of the 'metamict' phase) on the optical attenuation are also included. Results show that elevated temperatures significantly reduce attenuation resulting from defect centers (attenuation below ∼750 nm) as well as attenuation resulting from radiation-induced compaction (attenuation above ∼800 nm). The predicted attenuation is acceptable for most fiber optic-based sensor systems with a dynamic range on the order of 20-50 dB for a reasonable length (1-2 meters) of fiber in the high-flux region. Many optical components use a wavelength of 850 nm, which lies in the low-attenuation window. An irradiation campaign has been initiated to provide temperature-dependent optical attenuation data at high dose to validate the predictive model. (author)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

NASA NTRS1976

Validation of a model for investigating red cell mass changes during weightlessness

The model, both the conceptual model and simulation model, provided a convenient framework on which to demonstrate the commonality between such diverse stresses as descent from altitude, red cell infusions, bed rest, and weightlessness. The results suggest that all of these stresses induce an increased blood hematocrit leading to tissue hyperoxia and eventual inhibition of the erythyocyte producing circuit until the hyperoxic condition is relieved. The erythropoietic system was acting, in these situations, as if it were an hematocrit sensor and regulator. In these terms the decreases in red cell mass during Skylab may be explained in terms of normal feedback regulation of the erythropoietic system in the face of sustained decreases in plasma colume.

Leonard, J. I.↗

NASA NTRS1986

ERBE data and its validation

The Earth Radiation Budget Experiment (ERBE) is to be a three-satellite complement, of which two satellites were in orbit as of October 1984. Each satellite carries scanners for earth radiance sensing and one nonscanner for solar constant sensing. Of the four channels for earth scanning, two are dedicated to limb-to-limb observations and two view a swath 1000 km wide. Comparisons are made among the channel readings, thus far producing agreement to within 1 percent. Inversion techniques which are being applied to data gathered by the sensors are checked against equivalent procedures and results with the Nimbus-7 and GOES satellites.

Barkstrom, B. R.↗

DOE OSTI2019

Cross-source sensing data fusion for building occupancy prediction with adaptive lasso feature filtering

Fusing various sensing data sources can significantly improve the accuracy and reliability of building occupancy detection. Fusing environmental sensors and wireless network signals are seldom studied for its computational and technical complexity. Here, this study aims to propose an integrated adaptive lasso model that is able to extract critical data features for environmental and Wi-Fi probe dual sensing sources. Through rapid feature extraction and process simplification, the proposed method aims to improve the computational efficiency of occupancy detecting models. To validate the proposed model, an onsite experiment was conducted to examine two occupancy data resolutions, (real-time and four-level occupancy resolutions). The results suggested that, among all twelve features, eight features are most relevant. The mean absolute error of the real-time occupancy can be reduced to 2.18 and F1_accuracy is about 84.36% for the four-level occupancy.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2021

Hypothesis tests on Rayleigh wave radiation pattern shapes: a theoretical assessment of idealized source screening

SUMMARY Shallow seismic sources excite Rayleigh wave ground motion with azimuthally dependent radiation patterns. We place binary hypothesis tests on theoretical models of such radiation patterns to screen cylindrically symmetric sources (like explosions) from non-symmetric sources (like non-vertical dip-slip or non-VDS faults). These models for data include sources with several unknown parameters, contaminated by Gaussian noise and embedded in a layered half-space. The generalized maximum likelihood ratio tests that we derive from these data models produce screening statistics and decision rules that depend on measured, noisy ground motion at discrete sensor locations. We explicitly quantify how the screening power of these statistics increase with the size of any dip-slip and strike-slip components of the source, relative to noise (faulting signal strength) and how they vary with network geometry. As applications of our theory, we apply these tests to (1) find optimal sensor locations that maximize the probability of screening non-circular radiation patterns and (2) invert for the largest non-VDS faulting signal that could be mistakenly attributed to an explosion with damage, at a particular attribution probability. Finally, we quantify how certain errors that are sourced by opening cracks increase screening rate errors. While such theoretical solutions are ideal and require future validation, they remain important in underground explosion monitoring scenarios because they provide fundamental physical limits on the discrimination power of tests that screen explosive from non-VDS faulting sources.

58 GEOSCIENCES↗

DOE OSTI2017

An empirical method that separates irreversible stem radial growth from bark water content changes in trees: theory and case studies

Substantial uncertainty surrounds our knowledge of tree stem growth, with some of the most basic questions, such as when stem radial growth occurs through the daily cycle, still unanswered. Here, we employed high-resolution point dendrometers, sap flow sensors, and developed theory and statistical approaches, to devise a novel method separating irreversible radial growth from elastic tension-driven and elastic osmotically driven changes in bark water content. We tested this method using data from five case study species. Experimental manipulations, namely a field irrigation experiment on Scots pine and a stem girdling experiment on red forest gum trees, were used to validate the theory. Time courses of stem radial growth following irrigation and stem girdling were consistent with a-priori predictions. Patterns of stem radial growth varied across case studies, with growth occurring during the day and/or night, consistent with the available literature. Importantly, our approach provides a valuable alternative to existing methods, as it can be approximated by a simple empirical interpolation routine that derives irreversible radial growth using standard regression techniques. In conclusion, our novel method provides an improved understanding of the relative source–sink carbon dynamics of tree stems at a sub-daily time scale.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

Adaptive Cyber-Physical Resilience for Building Control Systems

The main goal of the project is to develop an AI-based process layer cybersecurity suite for detection, isolation and mitigation of cyber-attack effects on operation of building energy management systems (BEMS). The following constituent key technologies were developed under the program towards fulfilling the program objectives: (1) developed a high fidelity BEMS testbed for generation of training data and validation of developed technologies; (2) developed a physics informed ML based attack detection and localization module (ADL) capable of detecting high impact stealthy attacks (HISA - attacks causing 30% energy utilization but no immediate visible impact otherwise) with 98% accuracy; (3) developed a methodology to determine ’representative days’ to limit the data required for training; (4) developed a virtual sensing system that can reconstruct affected sensors with 10% error for the same HISA set; (5) developed a resilient model predictive control system that can continue operation of the BEMS without jeopardizing stability for the HISA set; and (6) integrated and deployed all the constituent modules and demonstrated the efficacy of the technology in real-time in a hardware in loop simulation.

42 ENGINEERING↗

NASA NTRS2003

BENCAL Cruise Report

This report documents the scientific activities on board the South African Fisheries Research Ship (FRS) Africana during an ocean color calibration and validation cruise in the Benguela upwelling ecosystem (BEN-CAL), 4-17 October 2002. The cruise, denoted Afncana voyage 170, was staged in the southern Benguela between Cape Town and the Orange River within the region 14-18.5 deg E,29-34 deg S, with 15 scientists participat- ing from seven different international organizations. Uniquely in October 2002, four high-precision ocean color sensors were operational, and these included the Moderate Resolution Imaging Spectroradiometer (MODIS) instruments on the Aqua and Terra spacecraft, the Medium Resolution Imaging Spectrometer (MERIS), and the Sea-viewing Wide Field-of-view Sensor (SeaWiFS). SeaWiFS imagery was transmitted daily to the ship to assist in choosing the vessel's course and selecting stations for bio-optical deployments. There were four primary objectives of the cruise. The first was to conduct bio-optical measurements with above- and in-water optical instruments to vicariously calibrate the satellite sensors. The second was to interrelate diverse measurements of the apparent optical properties (AOPs) at satellite sensor wavelengths with inherent optical properties (IOPs) and bio-optically active constituents of seawater such as particles, pigments, and dissolved compounds. The third was to determine the interrelationships between optical properties, phytoplankton pigment composition, photosynthetic rates, and primary production, while the fourth objective was to collect samples for a second pigment round-robin intercalibration experiment. Weather conditions were generally very favorable, and a range of hyperspectral and fixed wavelength AOP instruments were deployed during daylight hours. Various IOP instruments were used to determine the absorption, attenuation, scattering, and backscattering properties of particulate matter and dissolved substances, while a Fast Repetition Rate Fluorometer (FRRF) was deployed to acquire data on phytoplankton photosynthetic activity. Hydrographic profiling was conducted routinely during the cruise, and seawater samples were collected for measurements of salinity, oxygen, inorganic nutrients, pigments, particulate organic carbon, suspended particulate material, and primary production. Location of stations and times of optical deployments were selected to coincide with satellite overpasses whenever possible, and to cover a large range in trophic conditions.

Hooker, Stanford B.↗

NASA NTRS2021

Assessing within-Field Corn and Soybean Yield Variability from WorldView-3, Planet, Sentinel-2, and Landsat 8 Satellite Imagery

Crop yield monitoring is an important component in agricultural assessment. Multispectral remote sensing instruments onboard space-borne platforms such as Advanced Very High Resolution Radiometer (AVHRR), Moderate Resolution Imaging Spectroradiometer (MODIS), and Visible Infrared Imaging Radiometer Suite (VIIRS) have shown to be useful for efficiently generating timely and synoptic information on the yield status of crops across regional levels. However, the coarse spatial resolution data inherent to these sensors provides little utility at the management level. Recent satellite imagery collection advances toward finer spatial resolution (down to 1 m) alongside increased observational cadence (near daily) implies information on crops obtainable at field and within-field scales to support farming needs is now possible. To test this premise, we focus on assessing the efficiency of multiple satellite sensors, namely WorldView-3, Planet/Dove-Classic, Sentinel-2, and Landsat 8 (through Harmonized Landsat Sentinel-2 (HLS)), and investigate their spatial, spectral (surface reflectance (SR) and vegetation indices (VIs)), and temporal characteristics to estimate corn and soybean yields at sub-field scales within study sites in the US state of Iowa. Precision yield data as referenced to combine harvesters’ GPS systems were used for validation. We show that imagery spatial resolution of 3 m is critical to explaining 100% of the within-field yield variability for corn and soybean. Our simulation results show that moving to coarser resolution data of 10 m, 20 m, and 30 m reduced the explained variability to 86%, 72%, and 59%, respectively. We show that the most important spectral bands explaining yield variability were green (0.560 µm), red-edge (0.726 µm), and near-infrared (NIR - 0.865 µm). Furthermore, the high temporal frequency of Planet and a combination of Sentinel-2/Landsat 8 (HLS) data allowed for optimal date selection for yield map generation. Overall, we observed mixed performance of satellite-derived models with the coefficient of determination (R^2) varying from 0.21 to 0.88 (averaging 0.56) for the 30 m HLS and from 0.09 to 0.77 (averaging 0.30) for 3 m Planet. R^2 was lower for fields with higher yields, suggesting saturation of the satellite-collected reflectance features in those cases. Therefore, other biophysical variables, such as soil moisture and evapotranspiration, at similar fine spatial resolutions are likely needed alongside the optical imagery to fully explain the yields.

agriculture; yield; within-field; corn; soybean; r↗

NASA NTRSDate not supplied

ARCSTONE: Calibration of Lunar Spectral Reflectance from Space ESTO InVEST 2020

Long-term Objective: - Enable on-orbit high-accuracy absolute calibration for the past, current, and future reflected solar sensors in LEO and GEO by providing lunar spectral irradiance as function of satellite viewing geometry and specified wavelength. IIP Objective (complete): - Design, build, and characterize a prototype instrument demonstrating form-fit-function for a 6U CubeSat. InVEST Objective: - Demonstrate high-accuracy measurements of lunar spectral reflectance, < 0.5% (k=1), via 6U CubeSat on-orbit in LEO for 6 months, with validation and data analysis

ARCSTONE↗

NASA NTRS2023

Development of the Ames Global Hyperspectral Synthetic Data Set: Surface Bidirectional Reflectance Distribution Function

This study introduces the Ames Global Hyperspectral Synthetic Data set (AGHSD), in particular the surface bidirectional reflectance distribution function (BRDF) product, to support the NASA Surface Biology and Geology (SBG) mission development. The data set is generated based on the corresponding multispectral BRDF products from NASA's MODIS satellite sensor. Based on theories of radiative transfer in vegetation canopies, we derive a simple but robust relationship that indicates that the hyperspectral surface BRDF can be accurately approximated as a weighted sum of the soil surface reflectance, the leaf single albedo, and the canopy scattering coefficient, where the weights or coefficients are spectrally invariant and thus readily estimated from the multispectral MODIS products. We validate the algorithm with simulations by a Monte Carlo Ray Tracing model and find the results highly consistent with the theoretic derivation. Using reflectance spectra of soil and vegetation derived from existing spectral libraries, we apply the algorithm to generate the AGHSD BRDF product at 1 km and 8-day resolutions for the year of 2019. The data set is biogeochemically and biogeophysically coherent and consistent, and serves the goal to support the SBG community in developing sciences and applications for the future global imaging spectroscopy mission.

Hyperspectral Remote Sensing↗

NASA NTRS2006

Space-Based Near-Infrared CO2 Measurements: Testing the Orbiting Carbon Observatory Retrieval Algorithm and Validation Concept Using SCIAMACHY Observations over Park Falls, Wisconsin

Space-based measurements of reflected sunlight in the near-infrared (NIR) region promise to yield accurate and precise observations of the global distribution of atmospheric CO2. The Orbiting Carbon Observatory (OCO) is a future NASA mission, which will use this technique to measure the column-averaged dry air mole fraction of CO2 (XCO2) with the precision and accuracy needed to quantify CO2 sources and sinks on regional scales (approx.1000 x 1000 sq km and to characterize their variability on seasonal timescales. Here, we have used the OCO retrieval algorithm to retrieve XCO2 and surface pressure from space-based Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY) measurements and from coincident ground-based Fourier transform spectrometer (FTS) measurements of the O2 A band at 0.76 mm and the 1.58 mm CO2 band for Park Falls,Wisconsin. Even after accounting for a systematic error in our representation of the O2 absorption cross sections, we still obtained a positive bias between SCIAMACHY and FTS XCO2 retrievals of approx.3.5%. Additionally, the retrieved surface pressures from SCIAMACHY systematically underestimate measurements of a calibrated pressure sensor at the FTS site. These findings lead us to speculate about inadequacies in the forward model of our retrieval algorithm. By assuming a 1% intensity offset in the O2 A band region for the SCIAMACHY XCO2 retrieval, we significantly improved the spectral fit and achieved better consistency between SCIAMACHY and FTS XCO2 retrievals. We compared the seasonal cycle of XCO2 at Park Falls from SCIAMACHY and FTS retrievals with calculations of the Model of Atmospheric Transport and Chemistry/Carnegie-Ames-Stanford Approach (MATCH/CASA) and found a good qualitative agreement but with MATCH/CASA underestimating the measured seasonal amplitude. Furthermore, since SCIAMACHY observations are similar in viewing geometry and spectral range to those of OCO, this study represents an important test of the OCO retrieval algorithm and validation concept using NIR spectra measured from space. Finally, we argue that significant improvements in precision and accuracy could be obtained from a dedicated CO2 instrument such as OCO, which has much higher spectral and spatial resolutions than SCIAMACHY. These measurements would then provide critical data for improving our understanding of the carbon cycle and carbon sources and sinks.

carbon dioxide↗