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DOE OSTI2015

Study of seismic diffractions caused by a fracture zone at In Salah carbon dioxide storage project

The In Salah CO 2 storage project in Algeria has injected over 3 million tonnes of carbon dioxide into a water filled tight sand formation. Interferometric Synthetic Aperture Radar (InSAR) range change data revealed a double lobbed pattern of deformation that has been modeled as the opening of a sub-vertical fracture, or damage, zone. The location and geometry of the linear feature were subsequently verified using a seismic reflection survey. The elastic properties of the fracture zone, including anisotropic Poisson ratio ( ν ), Young's ( E ) and shear ( G ) moduli, were estimated from coupled geomechanical and hydrological modeling of surface deformation and pressure variations in the injection well. The elastic moduli reflect the fracture properties after CO 2 flow through the fracture zone. Thus, the seismic signature of the fracture zone could be used for monitoring the CO 2 plume. Using the estimated fracture model, we built two and three dimensional models consisting of an anisotropic fracture zone embedded within an isotropic background. Finite-difference modeling of seismic shot gathers allows us to estimate the effects of scattering from the fracture zone, potentially further constraining the geomechanical model. From the seismic modeling results, we find diffracted waves, induced by the fracture zone, which behave similar to point source diffractions. This modeling is intended to guide a search for diffraction events in the 3D surface seismic field data. The modeling results indicate that using the moduli estimated from geomechanical modeling, fracture scattered events would be 100 times lower amplitude than the interface reflections, and thus would be hard to detect. While diffracted waves are observed in the field data, which may imply the need for revision of the fracture model, including shape and elastic moduli, we are not able to match the field observation with our modeled events. This article presents a frontier study on the integration of geomechanical and geophysical methods at the In Salah site as a means to test the estimate of the subsurface CO 2 flooded fracture properties.

58 GEOSCIENCES↗
NASA NTRS2008

NASA Tech Briefs, November 2008

Topics covered include: Digital Phase Meter for a Laser Heterodyne Interferometer; Vision System Measures Motions of Robot and External Objects; Advanced Precipitation Radar Antenna to Measure Rainfall From Space; Wide-Band Radar for Measuring Thickness of Sea Ice; Vertical Isolation for Photodiodes in CMOS Imagers; Wide-Band Microwave Receivers Using Photonic Processing; L-Band Transmit/Receive Module for Phase-Stable Array Antennas; Microwave Power Combiner/Switch Utilizing a Faraday Rotator; Compact Low-Loss Planar Magic-T; Using Pipelined XNOR Logic to Reduce SEU Risks in State Machines; Quasi-Optical Transmission Line for 94-GHz Radar; Next Generation Flight Controller Trainer System; Converting from DDOR SASF to APF; Converting from CVF to AAF; Documenting AUTOGEN and APGEN Model Files; Sequence History Update Tool; Extraction and Analysis of Display Data; MRO DKF Post-Processing Tool; Rig Diagnostic Tools; MRO Sequence Checking Tool; Science Activity Planner for the MER Mission; UAVSAR Flight-Planning System; Templates for Deposition of Microscopic Pointed Structures; Adjustable Membrane Mirrors Incorporating G-Elastomers; Hall-Effect Thruster Utilizing Bismuth as Propellant; High-Temperature Crystal-Growth Cartridge Tubes Made by VPS; Quench Crucibles Reinforced with Metal; Deep-Sea Hydrothermal-Vent Sampler; Mars Rocket Propulsion System; Two-Stage Passive Vibration Isolator; Improved Thermal Design of a Compression Mold; Enhanced Pseudo-Waypoint Guidance for Spacecraft Maneuvers; Altimetry Using GPS-Reflection/Occultation Interferometry; Thermally Driven Josephson Effect; Perturbation Effects on a Supercritical C7H16/N2 Mixing Layer; Gold Nanoparticle Labels Amplify Ellipsometric Signals; Phase Matching of Diverse Modes in a WGM Resonator; WGM Resonators for Terahertz-to-Optical Frequency Conversion; Determining Concentration of Nanoparticles from Ellipsometry; Microwave-to-Optical Conversion in WGM Resonators; Four-Pass Coupler for Laser-Diode-Pumped Solid-State Laser; Low-Resolution Raman-Spectroscopy Combustion Thermometry; Temperature Sensors Based on WGM Optical Resonators; Varying the Divergence of Multiple Parallel Laser Beams; Efficient Algorithm for Rectangular Spiral Search; Algorithm-Based Fault Tolerance Integrated with Replication; Targeting and Localization for Mars Rover Operations; Terrain-Adaptive Navigation Architecture; Self-Adjusting Hash Tables for Embedded Flight Applications; Schema for Spacecraft-Command Dictionary; Combined GMSK Communications and PN Ranging; System-Level Integration of Mass Memory; Network-Attached Solid-State Recorder Architecture; Method of Cross-Linking Aerogels Using a One-Pot Reaction Scheme; An Efficient Reachability Analysis Algorithm.

Source record↗
DOE OSTI2025

3D-Printed mmWave Quasi-Holographic Antenna for 2-D Beamforming

This paper presents the design and manufacturing of a novel 2D-scanning antenna that integrates a 3D-printed Rotman lens with a quasi-holographic leaky-wave antenna (HLWA). The proposed design achieved beam-scanning capabilities by leveraging the beamforming of the Rotman lens and the high-gain directive properties of the quasi-HLWA. The Rotman lens (RL) enables beam steering in the elevation plane by switching between input ports. The quasi-HLWA, designed using holographic principles, achieves frequency-controlled beam scanning in the azimuth plane. The entire antenna structure was fabricated using additive manufacturing with an Ink1092 substrate and silver ink for the conductive traces. This approach provides greater control over material placement and design freedom compared to traditional methods. A 25° transmission linear substrate taper was used to ensure good impedance matching between the Rotman lens and the quasi-HLWA, allowing greater gain while maintaining a good scanning range. The experimental results validate the 2D scanning capability of the proposed antenna. The antenna system provides coverage from −54° to 54° in the elevation θ plane and −28° to 28° in the azimuth plane ϕ , with a maximum measured gain of 21.3 dBi at 28 GHz with an average radiation efficiency η=60 %. The fabricated prototype was tested, and the performance was in good agreement with the simulated performance.

Rotman lens↗
NASA NTRS1993

Ionospheric calibration for single frequency altimeter measurements

This report investigates the potential of using Global Positioning System (GPS) data and a model of the ionosphere to supply a measure of the sub-satellite Total Electron Current (TEC) of the required accuracy (10 TECU rms) for the purpose of calibrating single frequency radar altimeter measurements. Since climatological (monthly mean) models are known to be in error by as much as 50 percent, this work focused on the Parameterized Real-Time Ionospheric Specification Model (PRISM) which has the capability to improve model accuracy by ingesting (adjusting to) in situ ionospheric measurements. A set of globally distributed TEC measurements were generated using GPS data and were used as input to improve the accuracy of the PRISM model. The adjusted PRISM TEC values were compared to TOPEX dual frequency TEC measurements (which are considered truth) for a number of TOPEX sub-satellite tracks. The adjusted PRISM values generally compared to the TOPEX measurements within the 10 TECU accuracy requirements when the sub-satellite track passed within 300 to 400 km of the GPS TEC data or when the track passed through a night time ionosphere. However, when the sub-satellite points were greater than 300 to 400 km away from the GPS TEC data or when a local noon ionosphere was sampled, the adjusted PRISM values generally differed by greater than 10 TECU rms with data excursions from the TOPEX TEC measurements of as much as 40 TECU (an 8 cm path delay error at K band). Therefore, it can be concluded from this analysis that an unrealistically large number of GPS stations would be needed to predict sub-satellite TEC at the 10 TECU level in the day time ionosphere using a model such as PRISM. However, a technique currently being studied at the Jet Propulsion Laboratory (JPL) may provide a means of supplying adequate TEC data to meet the 10 TECU ionospheric correction accuracy when using a realistic number of ionospheric stations. This method involves using global GPS TEC data to estimate a global grid of vertical ionospheric TEC as a function of time (i.e. every one half hour) in a sun-fixed longitude frame. Working in a sun-fixed longitude frame, one is not limited by the spatial decorrelation distance of the ionosphere, but instead is limited more by the temporal correlations of the ionosphere in the sun-fixed frame which are a smaller effect. It is the opinion of the authors that using the global sun-fixed TEC grid data, in particular, ingesting it into PRISM, offers the best possibility of meeting the 10 TECU ionospheric correction accuracy requirement, and should be the subject of further study.

Schreiner, William S.↗
NASA NTRS2020

Monitoring Water-Related Ecosystems with Earth Observation Data in Support of Sustainable Development Goal (SDG) 6 Reporting

Lack of national data on water-related ecosystems is a major challenge to achieving the Sustainable Development Goal (SDG) 6 targets by 2030. Monitoring surface water extent, wetlands, and water quality from space can be an important asset for many countries in support of SDG 6reporting. We demonstrate the potential for Earth observation (EO) data to support country reporting for SDG Indicator 6.6.1, ‘Change in the extent of water-related ecosystems over time’ and identify important considerations for countries using these data for SDG reporting. The spatial extent of water-related ecosystems, and the partial quality of water within these ecosystems is investigated for seven countries. Data from the Moderate Resolution Imaging Spectroradiometer (MODIS) and Landsat 5, 7, and 8 with Shuttle Radar Topography Mission (SRTM) are used to measure surface water extent at 250 m and 30 m spatial resolution, respectively, in Cambodia, Jamaica, Peru, the Philippines, Senegal, Uganda, and Zambia. The extent of mangroves is mapped at 30 m spatial resolution using Landsat 8 Operational Land Imager (OLI), Sentinel-1, and SRTM data for Jamaica, Peru, and Senegal. Using Landsat 8 and Sentinel 2A imagery, total suspended solids and chlorophyll-a are mapped overtime for a select number of large surface water bodies in Peru, Senegal, and Zambia. All of the EO datasets used are of global coverage and publicly available at no cost. The temporal consistency and long time-series of many of the datasets enable replicability over time, making reporting of change from baseline values consistent and systematic. We find that statistical comparisons between different surface water data products can help provide some degree of confidence for countries during their validation process and highlight the need for accuracy assessments when using EO-based land change data for SDG reporting. We also raise concern that EO data in the context of SDG Indicator 6.6.1reporting may be more challenging for some countries, such as small island nations, than others to use in assessing the extent of water-related ecosystems due to scale limitations and climate variability. Country-driven validation of the EO data products remains a priority to ensure successful data integration in support of SDG Indicator 6.6.1 reporting. Multi-country studies such as this one can be valuable tools for helping to guide the evolution of SDG monitoring methodologies and provide a useful resource for countries reporting on water-related ecosystems. The EO data analyses and statistical methods used in this study can be easily replicated for country-driven validation of EO data products in the future.

Raha Hakimdavar↗
NASA NTRS2020

Monitoring Water-Related Ecosystems with Earth Observation Data in Support of Sustainable Development Goal (SDG) 6 Reporting

Lack of national data on water-related ecosystems is a major challenge to achieving the Sustainable Development Goal (SDG) 6 targets by 2030. Monitoring surface water extent, wetlands, and water quality from space can be an important asset for many countries in support of SDG 6 reporting. We demonstrate the potential for Earth observation (EO) data to support country reporting for SDG Indicator 6.6.1, ‘Change in the extent of water-related ecosystems over time’ and identify important considerations for countries using these data for SDG reporting. The spatial extent of water-related ecosystems, and the partial quality of water within these ecosystems is investigated for seven countries. Data from the Moderate Resolution Imaging Spectroradiometer (MODIS) and Landsat 5, 7, and 8 with Shuttle Radar Topography Mission (SRTM) are used to measure surface water extent at 250 m and 30 m spatial resolution, respectively, in Cambodia, Jamaica, Peru, the Philippines, Senegal, Uganda, and Zambia. The extent of mangroves is mapped at 30 m spatial resolution using Landsat 8 Operational Land Imager (OLI), Sentinel-1, and SRTM data for Jamaica, Peru, and Senegal. Using Landsat 8 and Sentinel 2A imagery, total suspended solids and chlorophyll-a are mapped over time for a select number of large surface water bodies in Peru, Senegal, and Zambia. All of the EO datasets used are of global coverage and publicly available at no cost. The temporal consistency and long time-series of many of the datasets enable replicability over time, making reporting of change from baseline values consistent and systematic. We find that statistical comparisons between different surface water data products can help provide some degree of confidence for countries during their validation process and highlight the need for accuracy assessments when using EO-based land change data for SDG reporting. We also raise concern that EO data in the context of SDG Indicator 6.6.1 reporting may be more challenging for some countries, such as small island nations, than others to use in assessing the extent of water-related ecosystems due to scale limitations and climate variability. Country-driven validation of the EO data products remains a priority to ensure successful data integration in support of SDG Indicator 6.6.1 reporting. Multi-country studies such as this one can be valuable tools for helping to guide the evolution of SDG monitoring methodologies and provide a useful resource for countries reporting on water-related ecosystems. The EO data analyses and statistical methods used in this study can be easily replicated for country-driven validation of EO data products in the future.

water-related ecosystems; surface water extent; ma↗
NASA NTRS2011

Towards an Optimal Noise Versus Resolution Trade-Off in Wind Scatterometry

A scatterometer is a radar that measures the normalized radar cross section sigma(sup 0) of the Earth's surface. Over the ocean this signal is related to the wind via the geophysical model function (GMF). The objective of wind scatterometry is to estimate the wind vector field from sigma(sup 0) measurements; however, there are many subtleties that complicate this problem-making it difficult to obtain a unique wind field estimate. Conventionally, wind estimation is split into two stages: a wind retrieval stage in which several ambiguous solutions are obtained, and an ambiguity removal stage in which ambiguities are chosen to produce an appropriate wind vector field estimate. The most common approach to wind field estimation is to grid the scatterometer swath into wind vector cells and estimate wind vector ambiguities independently for each cell. Then, field wise structure is imposed on the solution by an ambiguity selection routine. Although this approach is simple and practical, it neglects field wise structure in the retrieval step and does not account for the spatial correlation imposed by the sampling. This makes it difficult to develop a theoretically appropriate noise versus resolution trade-off using pointwise retrieval. Fieldwise structure may be imposed in the retrieval step using a model-based approach. However, this approach is generally only practical if a low order wind field model is applied, which may discard more information than is desired. Furthermore, model-based approaches do not account for the structure imposed by the sampling. A more general fieldwise approach is to estimate all the wind vectors for all the WVCs simultaneously from all the measurements. This approach can account for structure of the wind field as well as structure imposed by the sampling in the wind retrieval step. Williams and Long in 2010 developed a fieldwise retrieval method based on maximum a posteriori estimation (MAP). This MAP approach can be extended to perform a noise versus resolution trade-off, and deal with ambiguity selection. This paper extends the fieldwise MAP estimation approach and investigates both the noise versus resolution trade-off as well as ambiguity removal in the fieldwise wind retrieval step. The method is then applied to the Sea Winds scatterometer and the results are analyzed. This paper extends the fieldwise MAP estimation approach and investigates both the noise versus resolution trade-off as well as ambiguity removal in the fieldwise wind retrieval step. The method is then applied to the Sea Winds scatterometer and the results are analyzed.

soil moisture↗
NASA NTRS2012

Constraints on the Recent Rate of Lunar Regolith Accumulation from Diviner Observations

Many large craters on the lunar nearside show radar CPR signatures consistent with the presence of blocky ejecta blankets, to distances pre dicted to be covered by continuous ejecta. However, most of these sur faces show limited enhancements in both derived rock abundance and rock-free regolith temperatures calculated from Diviner nighttime infrar ed observations. This indicates that the surface rocks are covered by a layer of thermally insulating regolith material. By matching the results of one-dimensional thermal models to Diviner nighttime temperat ures, we have constrained the thermophysical properties of the upper regolith, and the thickness of regolith overlying proximal ejecta. We find that for all of the regions surveyed (all in the nearside highla nds), the nighttime cooling curves are best fit by a density profile that varies exponentially with depth, consistent with a linear mixture of rocks and regolith fines, with increasing rock content with depth . Our results show significant spatial variations in the density e-folding depth, H, among young crater ejecta regions, indicating differen ces in the thickness of accumulated regolith. However, away from youn g craters, the average regional "equilibrium" value of H (Heq) is remarkably consistent, and is on the order of 5 cm. As expected, near-rim ejecta associated with young craters show lower values of H, indicating a high rock content in the shallow subsurface; for older craters, the average value of H approaches the regional value of Heq. Calculat ed H values for young craters show a clear correlation with published ages, providing the first observational constraint on the recent rate of lunar regolith accumulation. In addition, this result may help to resolve the apparent discrepancy between ages calculated from small crater counts on melt ponds versus counts on continuous ejecta (e.g., King crater; Ashley et al., 2011, LPSC 42, abstract 2437). This method could, in principle, be extended to other airless bodies (e.g., aste roids), which would in turn constrain the recent impactor flux.

Ghent, R. R.↗
NASA NTRS2017

Nominal 30-M Cropland Extent Map of Continental Africa by Integrating Pixel-Based and Object-Based Algorithms Using Sentinel-2 and Landsat-8 Data on Google Earth Engine

A satellite-derived cropland extent map at high spatial resolution (30-m or better) is a must for food and water security analysis. Precise and accurate global cropland extent maps, indicating cropland and non-cropland areas, is a starting point to develop high-level products such as crop watering methods (irrigated or rainfed), cropping intensities (e.g., single, double, or continuous cropping), crop types, cropland fallows, as well as assessment of cropland productivity (productivity per unit of land), and crop water productivity (productivity per unit of water). Uncertainties associated with the cropland extent map have cascading effects on all higher-level cropland products. However, precise and accurate cropland extent maps at high spatial resolution over large areas (e.g., continents or the globe) are challenging to produce due to the small-holder dominant agricultural systems like those found in most of Africa and Asia. Cloud-based Geospatial computing platforms and multi-date, multi-sensor satellite image inventories on Google Earth Engine offer opportunities for mapping croplands with precision and accuracy over large areas that satisfy the requirements of broad range of applications. Such maps are expected to provide highly significant improvements compared to existing products, which tend to be coarser in resolution, and often fail to capture fragmented small-holder farms especially in regions with high dynamic change within and across years. To overcome these limitations, in this research we present an approach for cropland extent mapping at high spatial resolution (30-m or better) using the 10-day, 10 to 20-m, Sentinel-2 data in combination with 16-day, 30-m, Landsat-8 data on Google Earth Engine (GEE). First, nominal 30-m resolution satellite imagery composites were created from 36,924 scenes of Sentinel-2 and Landsat-8 images for the entire African continent in 2015-2016. These composites were generated using a median-mosaic of five bands (blue, green, red, near-infrared, NDVI) during each of the two periods (period 1: January-June 2016 and period 2: July-December 2015) plus a 30-m slope layer derived from the Shuttle Radar Topographic Mission (SRTM) elevation dataset. Second, we selected Cropland/Non-cropland training samples (sample size 9791) from various sources in GEE to create pixel-based classifications. As supervised classification algorithm, Random Forest (RF) was used as the primary classifier because of its efficiency, and when over-fitting issues of RF happened due to the noise of input training data, Support Vector Machine (SVM) was applied to compensate for such defects in specific areas. Third, the Recursive Hierarchical Segmentation (RHSeg) algorithm was employed to generate an object-oriented segmentation layer based on spectral and spatial properties from the same input data. This layer was merged with the pixel-based classification to improve segmentation accuracy. Accuracies of the merged 30-m crop extent product were computed using an error matrix approach in which 1754 independent validation samples were used. In addition, a comparison was performed with other available cropland maps as well as with LULC maps to show spatial similarity. Finally, the cropland area results derived from the map were compared with UN FAO statistics. The independent accuracy assessment showed a weighted overall accuracy of 94, with a producers accuracy of 85.9 (or omission error of 14.1), and users accuracy of 68.5 (commission error of 31.5) for the cropland class. The total net cropland area (TNCA) of Africa was estimated as 313 Mha for the nominal year 2015.

Cropland mapping; cropland areas; 30-m; Landsat-8;↗
NASA NTRS2014

Enabling Technologies for Entrepreneurial Opportunities in 3D printing of SmallSats

A consortium of innovative experts in additive manufacturing (AM) comprising Northrup Grumman Technical Services, University of Texas at El Paso (UTEP), Configurable Space Microsystems Innovations & Applications Center (COSMIAC), NASA Glenn Research Center (GRC), and Youngstown State University, have made significant breakthroughs in the goal of creating the first complete 3D printed small satellite. Since AM machines are relatively inexpensive, this should lead to many entrepreneurial opportunities for the small satellite community. Our technology advancements are focused on the challenges of embedding key components within the structure of the article. We have demonstrated, using advanced fused deposition modeling techniques, complex geometric shapes which optimize the spacecraft design. The UTEP Keck Center has developed a method that interrupts the printing process to insert components into specific cavities, resulting in a spacecraft that has minimal internal space allocated for what traditionally were functional purposes. This allows us to increase experiment and instrument capability by provided added volume in a confined small satellite space. Leveraging initial progress made on a NASA contract, the team investigated the potential of new materials that exploit the AM process, producing candidate compositions that exceed the capabilities of traditional materials. These "new materials" being produced and tested include some that have improved radiation shielding, increased permeability, enhanced thermal properties, better conductive properties, and increased structural performance. The team also investigated materials that were previously not possible to be made. Our testing included standard mechanical tests such as vibration, tensile, thermal cycling, and impact resistance as well as radiation and electromagnetic tests. The initial results of these products and their performance will be presented and compared with standard properties. The new materials with the highest probability to disrupt the future of small satellite systems by driving down costs will be highlighted, in conjunction with the electronic embedding process.

Communications↗
NASA NTRSDate not supplied

Evaluating SAR Radiometric Terrain Correction products: Optimal products for applied users

Operational applications for Synthetic Aperture Radar (SAR) are under development around the world, driven by the free-and-open access of SAR C-band observations that Sentinel-1 of Copernicus has been providing since 2014. Groups like SERVIR, a joint initiative between NASA and USAID, are at the forefront of remote sensing applied uses, and have made many significant contributions to lower the barrier to access, process, and apply SAR for ecosystem services. A takeaway from the SERVIR experience in using SAR is the need to use the appropriate SAR polarimetric product. Radiometric Terrain Correction (RTC) is a key entry-level product for multiple applications that range from ecosystems to hazards. Many software packages exist to create RTC products from SLC or GRD-type Level-1 SAR data, some of which were released only recently, e.g. Interferometric SAR Computing Environment (ISCE) added an RTC module in April 2020. In addition, new versions of open source softwares are expected to address known issues from previous versions, such as Sentinel-1 Toolbox from the European Space Agency (SNAP-7). Despite the growing availability of RTC software solutions, little work has been done to identify differences between RTC products from different softwares. And to address the question, which open-source software produces the most accurate RTC product? This work evaluates Sentinel-1 RTC products created with three different softwares and approaches, including SNAP-7, ISCE-2, and a pseudo RTC product derived from GEE. The GAMMA-derived RTC product, a known optimal RTC and implemented by Alaska Satellite Facility (ASF), is used as a reference. Time series stacks over ten different sites representing varied terrain and ecosystems are evaluated. Products are evaluated for geolocation quality, absolute radiometric calibration, and for the fidelity of the radiometric terrain flattening. The results provide direct guidance and recommendations about the quality of the RTC products obtained from open source methods. This understanding is key to develop operational applications that rely on SAR Sentinel-1 data that need affordable and scalable solutions.

Africa Flores-Anderson↗
NASA NTRS2010

NASA Tech Briefs, May 2010

Topics covered include: Instrument for Analysis of Greenland's Glacier Mills Cryogenic Moisture Apparatus; A Transportable Gravity Gradiometer Based on Atom Interferometry; Three Methods of Detection of Hydrazines; Crossed, Small-Deflection Energy Analyzer for Wind/Temperature Spectrometer; Wavefront Correction for Large, Flexible Antenna Reflector; Novel Micro Strip-to-Waveguide Feed Employing a Double-Y Junction; Thin-Film Ferro Electric-Coupled Microstripline Phase Shifters With Reduced Device Hysteresis; Two-Stage, 90-GHz, Low-Noise Amplifier; A 311-GHz Fundamental Oscillator Using InP HBT Technology; FPGA Coprocessor Design for an Onboard Multi-Angle Spectro-Polarimetric Imager; Serrating Nozzle Surfaces for Complete Transfer of Droplets; Turbomolecular Pumps for Holding Gases in Open Containers; Triaxial Swirl Injector Element for Liquid-Fueled Engines; Integrated Budget Office Toolbox; PLOT3D Export Tool for Tecplot; Math Description Engine Software Development Kit; Astronaut Office Scheduling System Software; ISS Solar Array Management; Probabilistic Structural Analysis Program; SPOT Program; Integrated Hybrid System Architecture for Risk Analysis; System for Packaging Planetary Samples for Return to Earth; Offset Compound Gear Drive; Low-Dead-Volume Inlet for Vacuum Chamber; Simple Check Valves for Microfluidic Devices; A Capillary-Based Static Phase Separator for Highly Variable Wetting Conditions; Gimballing Spacecraft Thruster; Finned Carbon-Carbon Heat Pipe with Potassium Working Fluid; Lightweight Heat Pipes Made from Magnesium; Ceramic Rail-Race Ball Bearings; Improved OTEC System for a Submarine Robot; Reflector Surface Error Compensation in Dual-Reflector Antennas; Enriched Storable Oxidizers for Rocket Engines; Planar Submillimeter-Wave Mixer Technology with Integrated Antenna; Widely Tunable Mode-Hop-Free External-Cavity Quantum Cascade Laser; Non-Geiger-Mode Single-Photon Avalanche Detector with Low Excess Noise; Using Whispering-Gallery-Mode Resonators for Refractometry; RF Device for Acquiring Images of the Human Body; Reactive Collision Avoidance Algorithm; Fast Solution in Sparse LDA for Binary Classification; Modeling Common-Sense Decisions in Artificial Intelligence; Graph-Based Path-Planning for Titan Balloons; Nanolaminate Membranes as Cylindrical Telescope Reflectors; Air-Sea Spray Airborne Radar Profiler Characterizes Energy Fluxes in Hurricanes; Large Telescope Segmented Primary Mirror Alignment; and Simplified Night Sky Display System.

Source record↗
NASA NTRS2023

Safety Case for Small Uncrewed Aircraft Systems (sUAS) Beyond Visual Line of Sight (BVLOS) Operations at NASA Langley Research Center

This Technical Memorandum (TM) is written to provide for dissemination of the methods and safety considerations for operations of small Uncrewed Aerial Systems (sUAS) Beyond Visual Line-of-Sight (BVLOS)at NASA Langley Research Center. It includes the Safety Case used to acquire a BVLOS Certificate of Authorization (COA) from the FAA and is being published to enable others to benefit from this work. The intended operations, subject to approval from the Federal Aviation Administration (FAA) and the National Aeronautics and Space Administration (NASA), will include a combination of Within Visual Line of Sight (WVLOS) and Beyond Visual Line of Sight (BVLOS) flights, comprising of at most five sUAS operating concurrently, with no more than three operating BVLOS. Flights will occur in a subset of the Langley Air Force Base (LAFB) Class D airspace (KLFI) at a maximum altitude of 400 ft AGL. Most operations within this subset will take place in the City Environment Range Testing for Autonomous Integrated Navigation (CERTAIN) Range. The CERTAIN Range includes airspace inside the borders of NASA Langley Research Center (LaRC). Additional airspace over the northern section of CERTAIN will be requested as part of the Certificate of Authorization (COA). NASA LaRC BVLOS operations on the CERTAIN Range can be broken down into five critical components needed to meet the 14 CFR § 91.113 see and avoid requirement: 1) procedural deconfliction with LAFB for UAS operations at or below 400 ft and manned aircraft at or above 900’ AGL; 2) ground equipment for detection of intruder aircraft and to support communications between crewmembers ; 3) sUAS vehicles with advanced onboard automation capable of autonomously maintaining safe separation; 4) BVLOS standardized operating procedures (SOPs); 5) and personnel to execute the flight operations in accordance with the SOPs and respond to airborne contingencies. The introduction of new ground equipment includes the use of the Remote Operations for Autonomous Missions (ROAM) UAS Operations Center, development and use of an Integrated Airspace Display (IAD), use of the L-STAR and GA-9120 radars, and the incorporation of standardized Vertiports. The ROAM Operations Center will be the central point for all BVLOS sUAS operations. All command and control (C2), voice communications and airspace awareness displays will reside inside ROAM. The IAD will provide raw data from ADS-B, FLARM, radar tracks and telemetered GPS vehicle positions for interpretation by an Airspace Monitor. The radars will search the class D airspace around the CERTAIN Range and serve as a backup to procedural deconfliction procedures coordinated with LAFB. In the event of a procedural deconfliction breakdown, radar detections of non-participating aircraft will be available so that the 91.113 see and avoid requirement can still be safely met. Finally, the incorporation of Vertiports will have video and network connectivity that enables large numbers of sUAS launches and recoveries from a single location. This is a continuation of the remote command and control of unpiloted aircraft component focused on evaluating unpiloted aircraft flight crew roles and responsibilities, control interfaces and the associated data links needed to operate a fleet of aircraft within a UAM Ecosystem. This work supports the development of future aviation operational concepts based on an Urban Air Mobility Maturity Level (UML) 4 environment (Patterson, 2020). It is assumed that future airspace will include hundreds of simultaneous aircraft operations within the airspace, therefore scalable operations are essential for enabling this future airspace to become a reality. Follow on work includes envisioned flights that expand operations beyond the CERTAIN range and lead to an effective Maritime Surveillance capability.

Matthew W Coldsnow↗
DOE OSTI2018

Aerial Lidar and Geomorphic Change Detection Software- Tools for Monitoring Canyon Sediments at LANL - 18668

The Los Alamos National Laboratory Environmental Remediation program has conducted extensive geomorphic surveys of sediment deposits in the canyon bottoms within and surrounding the facility. The goal of the geomorphic surveys was to provide basic information needed to characterize chemical inventories of the sediments downstream of historical release sites. Sediment units were mapped based on depositional setting and age. Representative characterization samples were collected for each unit and submitted for chemical analysis. Chemical inventories were estimated by calculating the total volume of each depositional unit and multiplying by average chemical concentration. This method of characterization provides a spatial distribution of chemical data based on fluvial processes. In general, for the canyon bottom sediments, the higher concentrations of industrial chemicals were associated with fine-grained floodplain deposits closest to the source. Since initial characterization, many of the reaches have undergone changes in response to post-wildfire floods and severe rain events. These events impacted the channel and floodplain deposits. Much of the elevated concentrations are confined to the over-bank deposits distal from the primary channel. In order to ensure that the sediment units containing elevated chemical concentrations are stable, repeat aerial light detection and ranging (LiDAR) surveys are conducted and changes are assessed using the Geomorphic Change Detection (GCD) plug-in for ArcGIS. These tools provide high confidence uncertainty estimates and extensive areal coverage. This is a valuable method for long-term monitoring of surface sediments with low-level but widespread contaminant distributions. All of the monitored canyon bottom reaches pass risk assessment and present technically infeasible sediment removal options. Following the 2014 monsoon season, aerial LiDAR data has been collected annually and the resulting digital elevation models (DEMs) processed using the GCD method. Changes are identified using GCD and are verified by field walk downs. If erosion is identified in areas which are vulnerable to mobilizing contaminated sediment, enhanced controls can be installed to stabilize banks or other areas with high erosion potential. Annual sediment monitoring samples are collected where there is evidence for flow and deposition within the past year. Since 2014, no severe floods have been catalogued using the LiDAR surveys and GCD software. The recent rainfall/runoff events have not caused major changes to the canyon bottom channels and floodplains. Geomorphic processes identified in the monitoring results include channel aggradation and incision that over the course of a monsoon season results in minor changes to the system. Other active processes contributing to observed changes are minor slides, flows, slumps, and falls of unconsolidated sediment on steep bedrock or soil surfaces. A comprehensive baseline has been established by geomorphic mapping and characterization sampling. Periodic monitoring consists of LiDAR surveys and GCD analysis which offers an effective and defensible methodology for documenting stability of surface sediments. (authors)

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DOE OSTI2017

Residential greenness and allergic respiratory diseases in children and adolescents – A systematic review and meta-analysis

Background: The aetiology of allergic respiratory disease in children is not yet fully understood. Environmental factors are believed to play a major part. The amount of green vegetation surrounding the home (residential greenness) has been recently identified as a potentially important exposure Objectives: Our goal was to provide a systematic review and quantitative summary of the evidence regarding the relationship between residential greenness and allergic respiratory diseases in children. Methods: Peer-reviewed literature published prior to 1 March 2017 was systematically searched using nine electronic databases. Meta-analyses were conducted if at least three studies published risk estimates for the same outcome and exposure measures. Results: We included 11 articles across broad outcomes of asthma and allergic rhinitis. Reported effects were inconsistent with varying measures to define residential greenness. Only limited meta-analysis could be conducted, with the pooled odds ratios for asthma (OR 1.01 95%CI 0.93, 1.09; I{sup 2} 68.1%) and allergic rhinitis (OR 0.99 95%CI 0.87, 1.12; I{sup 2} 72.9%) being significantly heterogeneous. Conclusions: Inconsistencies between the studies were too large to accurately assess the association between residential greenness and allergic respiratory disease. A standardised global measure of greenness which accounts for seasonal variation at a specific relevant buffer size is needed to create a more cohesive body of evidence and for future examination of the effect of residential greenness on allergic respiratory diseases. - Highlights: • We included 11 studies of asthma and/or allergic rhinitis. • This review demonstrated substantive exposure measurement issues. • These issues hindered the creation of a cohesive body of evidence. • Meta-analysis was limited, with significantly heterogeneous pooled odds ratios rhinitis.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Lidar Mapping and Surveillance of Nuclear Infrastructure

Wear is unavoidable, whether it occurs in a nuclear facility or abridge on the highway its detection is crucial to preventing the failure of a system. While tools capable of detecting localized damage exist, industry lacks methods to evaluate the health of larger infrastructure. Routine inspection of nuclear facilities must be undertaken to ensure the safety of personnel and proper containment of nuclear materials. Most systems in a nuclear facility are designated as radioactive and confined spaces. To constantly monitor such systems in person would be hazardous but with a remote inspection tool it can be done in a safer and easier way. Lidar: Operates by emitting a laser pulse and looking for the reflected light. Allows user to gain 3D information of the environment. Project Objective: To develop an inspection tool for evaluating the health of large scale infrastructure using Lidar and machine learning. Autonomous Platform + Lidar + Data Fusion + Big Data. Use SLAM to build a 2D map of the environment. Point cloud created by transforming the points between reference frames. Point cloud to Surface: Inherent representation of surface geometry; Difficult to process with conventional techniques. Point cloud to Image: Easily processed by conventional machine learning algorithms. The quantity of data generated will necessitate a big data framework to manage the data for processing. Additional Sensors: Detecting the temperature (a) chemical makeup (b) and radiation emission (c) of a surface could assist in detecting problems. Human inspection can detect irregularities in both physical objects and their point-cloud representations. This is a good indication that mapping nuclear sites using Lidar will provide qualitative insight into the health of the facility. If deep learning can be used to automatically identify problem areas then the completed tool could become an invaluable asset.

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DOE OSTI2020

Savannah River Site H-Canyon Advancing Technologies for Remote Inspections - 20345

In 2017, the DOE Environmental Management Office of Technology Development (DOE-EM TD) sponsored the H-Canyon Advanced Technology Demonstration (ATD) to demonstrate to DOE facilities the value of using new commercial-off-the-shelf (COTS) and near-ready technologies to solve difficult problems and enhance worker safety. The DOE Savannah River Site (SRS) H-Canyon Air Exhaust Tunnel (HCAEX) inspection task was identified as representative of the hazardous, human denied environments which could benefit from advanced technologies. The HCAEX underground concrete tunnel is visually inspected biannually using a camera mounted on a remotely operated vehicle (ROV) designed and built by SRNL. While tunnel images have provided valuable visual information, it is desirable to have a higher order of understanding of the environment to support a more thorough structural integrity (SI) analysis and for long term planning purposes. As part of the ATD, the Concrete Integrated Product Team (CIPT) was formed to identify and evaluate available sensors and methods mature enough to remotely obtain tunnel concrete characterization data of high value and with a high probability of success. The team included SMEs and H-Canyon stakeholders in the field of concrete, nondestructive examination (NDE), structural integrity, sensors and remote systems from SRNL, SRNS, LANL, DOE-SR and the Army Corps of Engineering. The CIPT completed an in-depth identification of customer concrete inspection needs and potential technology solutions. Sensors and methods were evaluated on performance, data usefulness, cost and the feasibility of a successful deployment given the unique tunnel access challenges and environment. Two technologies were identified as promising by the CIPT for near term demonstration and evaluation: Lidar (Light Detection and Ranging) 3-dimensional (3D) mapping and remote robotic deployment of NDE instrumentation. Laser spectroscopy to characterize tunnel surface chemical changes was also of interest, but presently cost prohibitive. This paper will include a discussion of the two efforts underway to evaluate and implement the CIPT recommendations. First, the status of the November 2019 deployment of Lidar at a single location into the tunnel is presented. This initial deployment provided the team a learning curve and lessons learned on the challenges of tunnel deployment to include remote operation and data collection, stabilization of the sensor in high air flow (∼30 mph), ability to achieve a tolerance accuracy of 0.25-inches, and the probability to identify change in tunnel dimensions over time. Secondly, a discussion on the development of the Robotic Arm Concrete Inspection Test Bed capable of deploying NDE instruments to examine custom concrete forms will be presented. Concrete forms simulating the rough concrete surfaces, strength, composition and potential structural defects that can be found at our DOE EM facilities have been designed and built for the test bed. Two state-of-the art concrete NDE instruments have been identified as having potential to work on rough concrete walls, they are being tested and characterized as to their ability to provide desired structural integrity data to include wall thickness and defect identification on the developed test beams. Lastly, lessons learned, and the path forward will be presented. (authors)

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