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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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Advances in our understanding and ability to predict changes in our environment will require more comprehensive and coordinated measurements, data delivery systems, and modeling tools.
Hughes Aircraft Company and the University of Chicago propose to transfer existing medical imaging registration algorithms to the area of multi-sensor data fusion. The University of Chicago's algorithms have been successfully demonstrated to provide pixel by pixel comparison capability for medical sensors with different characteristics. The research will attempt to fuse GOES (Geostationary Operational Environmental Satellite), AVHRR (Advanced Very High Resolution Radiometer), and SSM/I (Special Sensor Microwave Imager) sensor data which will benefit a wide range of researchers. The algorithms will utilize data visualization and algorithm development tools created by Hughes in its EOSDIS (Earth Observation SystemData/Information System) prototyping. This will maximize the work on the fusion algorithms since support software (e.g. input/output routines) will already exist. The research will produce a portable software library with documentation for use by other researchers.
A history of texture analysis (TA) evolution is shown, beginning from the first experimental and theoretical attempts to find and characterize preferred orientations of crystal lattices of grains in real polycrystalline samples. Stages of formation of TA theoretical apparatus, its basic elements, and also application of its capabilities for quantitatively describing anisotropic properties of textured samples are discussed. Attention is also paid to the limitations and difficulties associated with the analysis. The application of the quantitative TA apparatus is demonstrated by example describing elastic properties of textured materials up to multiphase samples containing pores and cracks. A wide scope of TA includes the analysis based on neutron scattering which has been effectively developed at the Frank Laboratory of Neutron Physics. A practical opportunity to determine the bulk crystallographic textures of single-phase and multiphase materials is offered by the use of modern neutron diffractometers, including the SKAT diffractometer at the IBR-2 pulsed reactor. This is especially important for studying samples of natural rocks. The examples given show how the neutron scattering data for the quantitative TA are used in combination with other physical and petrological methods for solving fundamental problems of geology and geophysics based on the analysis of a structure and properties of the Earth’s lithosphere matter. The review includes a detailed list of references of original works concerning the TA elaboration, overview publications and monographs, and also information on the most popular TA-related software.
The cover image incorporates high resolution stereo pairs acquired from the DigitalGlobe(R) QuickBird sensor. It shows a digital elevation model of Meteor Crater, Arizona at approximately 1.3 meter point-spacing. Image analysts used the Leica Photogrammetry Suite to produce the DEM. The outside portion was computed from two QuickBird panchromatic scenes acquired October 2006, while an Optech laser scan dataset was used for the crater s interior elevations. The crater s terrain model and image drape were created in a NASA Constellation Program project focused on simulating lunar surface environments for prototyping and testing lunar surface mission analysis and planning tools. This work exemplifies NASA s Scientific Data Purchase legacy and commercial high resolution imagery applications, as scientists use commercial high resolution data to examine lunar analog Earth landscapes for advanced planning and trade studies for future lunar surface activities. Other applications include landscape dynamics related to volcanism, hydrologic events, climate change, and ice movement.
The Jet Propulsion Laboratory (JPL) and Ames Research Center (ARC) are partnering in the CubeSat Hydrometric Atmospheric Radiometer Mission (CHARM), a water vapor radiometer integrated on a 3U CubeSat platform, selected for implementation under NASA Hands-On Project Experience (HOPE-3). CHARM will measure 4 channels at 183 GHz water vapor line, subsets of measurements currently performed by larger and more costly spacecraft (e.g. ATMS, AMSU-B and SSMI/S). While flying a payload that supports SMD science objectives, CHARM provides a hands-on opportunity to develop technical, leadership, and project skills. CHARM will furthermore advance the technology readiness level (TRL) of the 183 GHz receiver subsystem from TRL 4 to TRL 6 and the CubeSat 183 GHz radiometer system from TRL 4 to TRL 7.
Gross primary production (GPP), the amount of carbon dioxide (CO 2 ) assimilated by plants through photosynthesis, is one of the most variable and uncertain components of the global carbon cycle. Global GPP has been estimated with a number of process-based models, data-driven, and hybrid approaches. Dynamic global vegetation models (DGVMs), driven by observed environmental changes, are used for global carbon budget assessments and long-term (climate) prediction. Benchmarking these and other models globally with data-driven GPP estimates is critical for understanding the land sink and ensuring accurate forecasts of the carbon cycle. In addition, global data-driven GPP estimates are crucial for studies of interannual variability, including trends that are linked to mechanisms with large uncertainties, such as the indirect CO 2 fertilization effect related to greening. In response to a community need for a GPP data set that well captures spatio-temporal variability, we developed FluxSat, a data-driven approach that optimizes the use of satellite reflectance data from the NASA MODerate-resolution Imaging Spectroradiometer (MODIS) on the Terra and Aqua satellites, calibrated using ground-based eddy covariance (EC) data. We are enhancing (spatially, higher resolution) and extending FluxSat (in time, with additional sensors) to create a high quality long term GPP Earth System Data Record (ESDR) for use in model benchmarking, carbon cycle modeling, and studies of trends and interannual variability. Our team’s objectives are to: 1. Update and document the current MODIS FluxSat GPP (daily, 0.05o and 0.5o resolutions) products with latest available MODIS and EC data sets; 2. Extend FluxSat GPP record forward in time with the Visible Infrared Imaging Radiometer Suite (VIIRS) on operational weather satellites going forward; 3. Extend FluxSat GPP record backward in time using the Advanced Very High Resolution Radiometer (AVHRR) on weather satellites dating back to 1981; 4. Provide higher spatial resolution MODIS and VIIRS GPP (0.0083o). 5. Thoroughly evaluate all FluxSat products with independent data; and 6. Create a homogenized long-term GPP record spanning 40+ years. We will discuss plans for this long-term data set that is supported through the NASA Making Earth System Data Records for Use in Research Environments (MEaSUREs) program.
This paper presents the validation results of GOES-16 Satellite's Advanced Baseline Imager (ABI) obtained from a reflectance-based field campaign undertaken at the Salar de Uyuni in Bolivia in June 2017. In situ ground measurements are used to characterize the surface reflectance and the atmosphere in order to constrain the radiative transfer code and predict at-sensor reflectance (also referred to as top-of-atmosphere (TOA) reflectance) to compare with concurrent GOES-16 ABI measurements. The five-day field campaign provided repeated TOA reflectance estimates, allowing assessment not only of the calibration accuracy of the ABI reflective channels 1, 2, 3, 5 and 6, but also of its stability over the duration of the campaign. The results show that the accuracy of the ABI reflective channels calibration is within specification for channels 1, 3, 5, and 6 - average biases within 2%; for channel 2 the bias is 5%. The estimated uncertainty on the derived biases is 2–2.4%. Some calibration stability issues were present in the ABI calibration at the time of the campaign: (i) a jump on the order of 2% in channels 1 and 6, coincident with an ABI solar calibration event, reflects an instability of the ABI gains in these channels, and (ii) short-term variability in channels 1 and 2 is due to striping (ABI detector-todetector calibration differences). Continued validation and subsequent reprocessing of ABI reflectance imagery would allow Earth scientists to fully benefit from the high spatial and spectral fidelity of the GOES-16 ABI diurnal measurements at the continental scale.
The Artemis Lunar program is providing opportunity for young scientists and engineers to contribute towards leading edge design concepts regarding early on-surface work areas that are aligned with major national initiatives. Therefore, it is imperative in any discovery process that those young scientists and engineers be provided the bandwidth or operating in a ‘greenfield’ technology environment that encourages new ideas, and perhaps the discovery of ideas that would not be realized within typical structured engineering constraints. To facilitate this concept, the use of unbounded teaching methods was utilized to provide a low-constraint environment from which students can design and discover the requirements that are bounded by the natural environment of the lunar surface, and then build up design requirements un-hindered by budgetary and/or logistics realizations of the moment funding capabilities. Specifically, this design exercise provided the students to operate with unlimited budgets, and unlimited up-mass lifts to the lunar surface to develop a preliminary feasible process for establishing a working lunar research based upon the near-area permanently shadowed regions within the lunar surface. In concept, working near PSRs will be advantageous as they receive near eternal shielding from solar radiation and may potentially host numerous volatile substances such as water ice, methane, hydrogen sulfide and helium-3 that will be the target of scientific investigation and in-situ resource utilization ISRU. The advantage of an upstream working area is that the quality of return materials could potentially be exponential when including an upstream analysis prior to earth-return missions. Furthermore, it’s well known within the scientific and engineering community that working with the base materials in front of human eyes elucidates new features and observations that may not survive when stored and shipped to Earth. Finally, it is theorized that these methods and techniques developing on the lunar surface would be applicable to other planets or cometary surfaces.
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This report describes the development of algorithms to derive accurate surface roughness and displacement height values from NASA satellite data for both urban and vegetation environments and to evaluate the potential benefit of improved surface data characterization on atmospheric transport and dispersion modeling. One of the key factors limiting the accuracy of near-surface wind profile modeling and dispersion simulations is the lack of location-specific and seasonally-dependent surface characteristic values. Currently, land use category look-up tables are commonly used to provide grid-cell estimates of surface characteristics values, even though surface roughness values can vary significantly within the same land-use category. This report documents: i) the derivation of surface characteristic values by Goddard Space Flight Center (GSFC) and Stennis Space Center (SSC) from NASA satellite multispectral imagery, ii) their incorporation into atmospheric meteorological and transport models, and iii) the results of a dispersion modeling study for Oklahoma City and the surrounding region to evaluate the impact of GSFC/SSC roughness on National Atmospheric Release Advisory Center (NARAC) / Interagency Modeling and Atmospheric Assessment Center (IMAAC) emergency response dispersion predictions.
Understanding the physics of flow and transport in the subsurface environment is crucial to several National Security applications. In the Energy Security realm, some examples include characterizing radioactive waste disposal, exploring natural gas extraction and sequestering CO2. An example in the Global Security arena is to be able to distinguish between anthropogenic and naturally occurring seismic disturbances, the former being of particular concern as underground nuclear testing activity has seen an increase in recent years. A common theme across these applications is the ability to accurately model fluid flow in porous and/or fractured subsurface media. For decades, researchers have grappled with how to include the effects of uncertainties in these models, including but not limited to heterogeneity, unknown initial and boundary conditions and issues with scalability. More recently advances in computing and machine learning methodologies have allowed a broader exploration of the uncertainty space as we strive for real time decision making. I will present an overview of the field and discuss a few examples of how my own research in these topics has evolved over nearly two decades.
With the expected growth of electric vehicles (EV) in the transportation sector, recycling or upcycling spent battery materials will be required to reduce EV costs, lessen waste, and ease critical material supply chain pressure for EV battery applications. “Direct” recycling or upcycling is an alternative to current industrial approaches. Many challenges remain for viable direct battery upcycling, including upgrading the transition metal ratio in the costliest component (cathode oxide); separation of transition metal ions in the exit stream; battery disassembly; improving cathode exfoliation which can lead to a new way of direct recycling; and lithium metal anode recycling -- including safety concerns. We devise and deploy a suite of methods to deal with these challenges. The results pave the way to future work on battery recycling, in areas of technological/commercial readiness level ranging from basic research to large-scale commercialization.
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Guidelines for the preparation of systems analysis and programming work statements are presented. The data is geared toward the efficient administration of available monetary and equipment resources. Language standards and the application of good management techniques to software development are emphasized.
The behavior of finite element models employing different constitutive relations to describe the stress-strain behavior of soils is investigated. Three models, which assume small strain theory is applicable, include a nondilatant, a dilatant and a strain hardening constitutive relation. Two models are formulated using large strain theory and include a hyperbolic and a Tresca elastic perfectly plastic constitutive relation. These finite element models are used to analyze retaining walls and footings. Methods of improving the finite element solutions are investigated. For nonlinear problems better solutions can be obtained by using smaller load increment sizes and more iterations per load increment than by increasing the number of elements. Suitable methods of treating tension stresses and stresses which exceed the yield criteria are discussed.