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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Dose Rate Evaluation for the ES-3100 Package with HEU Content Using MCNP, ADVANTG, Monaco, and MAVRIC

Here, this paper presents a comparative study of dose rate calculations for the ES-3100 package with highly enriched uranium (HEU) content for different source configurations using computer codes: (1) MCNP; (2) Automated Variance Reduction Generator (ADVANTG)/MCNP; (3) Monaco; and (4) Monaco with Automated Variance Reduction using Importance Calculations (MAVRIC). The Model ES-3100 package was developed at the Y-12 National Security Complex for domestic and international transportation of Type B fissile radioactive material. In this study, six different source configurations (i.e., solid cylinder, cylindrical hemi-shell, cylindrical shell, rectangular plate, cylindrical rod, or cylindrical segment form) having 36 kg of HEU metal inside the package containment vessel (based on configurations in the ES-3100/HEU safety analysis report for packaging) are evaluated. Dose rates at the package surfaces and 1 m from the package surfaces are calculated for these different source configurations. MCNP and Monaco cases are run without any biasing options to accelerate the convergence. Consistent Adjoint Driven Importance Sampling (CADIS) and Forward-Weighted CADIS (FW-CADIS) methods developed at the Oak Ridge National Laboratory are implemented in ADVANTG/MCNP and MAVRIC codes to accelerate the convergence. ADVANTG generates variance reduction parameters using Denovo code, and MCNP is used with the variance reduction parameters to accelerate the convergence. MAVRIC uses Denovo code to construct an importance map and a biased source distribution that are supplied to Monaco to accelerate the Monte Carlo simulation. The FW-CADIS option in ADVANTG and MAVRIC is used to accelerate the convergence in this study. The accelerated convergence cases (ADVANTG/MCNP and MAVRIC) are about 100 times faster with 100 times less particle simulation than those cases run without biasing options (analog MCNP and analog Monaco). Lastly, the MCNP, ADVANTG/MCNP, Monaco, and MAVRIC calculated dose rates at the package surfaces and at 1 m from the package surfaces for the different source configurations are compared and are found to be in general agreement.

42 ENGINEERING↗
DOE OSTI2018

Dose Rate Evaluation for the ES-3100 Package with HEU Content Using MCNP, ADVANTG, Monaco, and MAVRIC

This paper presents a comparative study of dose rate calculations for the ES-3100 package with highly enriched uranium (HEU) content for different source configurations using computer codes: (1) MCNP; (2) Automated Variance Reduction Generator (ADVANTG)/MCNP; (3) Monaco; and (4) Monaco with Automated Variance Reduction using Importance Calculations (MAVRIC). The Model ES-3100 package was developed at the Y-12 National Security Complex for domestic and international transportation of Type B fissile radioactive material. In this study, six different source configurations (i.e., solid cylinder, cylindrical hemi-shell, cylindrical shell, rectangular plate, cylindrical rod, or cylindrical segment form) having 36 kg of HEU metal inside the package containment vessel (based on configurations in the ES-3100/HEU safety analysis report for packaging) are evaluated. Dose rates at the package surfaces and 1 m from the package surfaces are calculated for these different source configurations. MCNP and Monaco cases are run without any biasing options to accelerate the convergence. Consistent Adjoint Driven Importance Sampling (CADIS) and Forward-Weighted CADIS (FW-CADIS) methods developed at the Oak Ridge National Laboratory are implemented in ADVANTG/MCNP and MAVRIC codes to accelerate the convergence. ADVANTG generates variance reduction parameters using Denovo code, and MCNP is used with the variance reduction parameters to accelerate the convergence. MAVRIC uses Denovo code to construct an importance map and a biased source distribution that are supplied to Monaco to accelerate the Monte Carlo simulation. The FW-CADIS option in ADVANTG and MAVRIC is used to accelerate the convergence in this study. The accelerated convergence cases (ADVANTG/MCNP and MAVRIC) are about 100 times faster with 100 times less particle simulation than those cases run without biasing options (analog MCNP and analog Monaco). The MCNP, ADVANTG/MCNP, Monaco, and MAVRIC calculated dose rates at the package surfaces and at 1 m from the package surfaces for the different source configurations are compared and are found to be in general agreement.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS2011

Transverse Pupil Shifts for Adaptive Optics Non-Common Path Calibration

A simple new way of obtaining absolute wavefront measurements with a laboratory Fizeau interferometer was recently devised. In that case, the observed wavefront map is the difference of two cavity surfaces, those of the mirror under test and of an unknown reference surface on the Fizeau s transmission flat. The absolute surface of each can be determined by applying standard wavefront reconstruction techniques to two grids of absolute surface height differences of the mirror under test, obtained from pairs of measurements made with slight transverse shifts in X and Y. Adaptive optics systems typically provide an actuated periscope between wavefront sensor (WFS) and commonmode optics, used for lateral registration of deformable mirror (DM) to WFS. This periscope permits independent adjustment of either pupil or focal spot incident on the WFS. It would be used to give the required lateral pupil motion between common and non-common segments, analogous to the lateral shifts of the two phase contributions in the lab Fizeau. The technique is based on a completely new approach to calibration of phase. It offers unusual flexibility with regard to the transverse spatial frequency scales probed, and will give results quite quickly, making use of no auxiliary equipment other than that built into the adaptive optics system. The new technique may be applied to provide novel calibration information about other optical systems in which the beam may be shifted transversely in a controlled way.

Bloemhof, Eric E.↗
DOE OSTI2026

Simplex‐based model for nanoparticle grain identification in four‐dimensional scanning transmission electron microscopy data

Grain identification in polycrystalline nanoparticles, for example, determining which crystal phases are present at each spatial location, is fundamental to materials characterisation. This is particularly challenging when grains overlap extensively, as commonly occurs in four-dimensional scanning transmission electron microscopy (4D-STEM) datasets. We propose a simplex-based model (SBM) in which each simplex vertex represents the diffraction pattern (DP) of a pure grain, and the simplex edges and interior represent overlapping grains. Our SBM grain identification algorithm operates on the Bragg disk (BD) data matrix distilled from the 4D-STEM data to identify the grain membership at each scan position, together with a BD feature matrix whose columns represent the DPs for each constituent grain, which is important for identifying the crystal structure of each grain. We solve the model using a two-stage algorithm. In Stage 1, we adapt a linear mixing algorithm to estimate an initial BD feature matrix whose columns represent DPs of potentially overlapping grains. Our Stage 2 algorithm incorporates sparsity considerations to transform the initial BD feature matrix so that its columns represent DPs of pure grains. Using simulated datasets with various grain configurations, we demonstrate that SBM recovers both the BD feature matrix and membership maps more accurately than existing methods, even when a grain lacks any pure region and completely overlaps with other grains.

4D-STEM segmentation↗
NASA NTRS2010

Estimates of the Lightning NOx Profile in the Vicinity of the North Alabama Lightning Mapping Array

The NASA Marshall Space Flight Center Lightning Nitrogen Oxides Model (LNOM) is applied to August 2006 North Alabama Lightning Mapping Array (NALMA) data to estimate the (unmixed and otherwise environmentally unmodified) vertical source profile of lightning nitrogen oxides, NOx = NO + NO2. Data from the National Lightning Detection Network (Trademark) (NLDN) is also employed. This is part of a larger effort aimed at building a more realistic lightning NOx emissions inventory for use by the U.S. Environmental Protection Agency (EPA) Community Multiscale Air Quality (CMAQ) modeling system. Overall, special attention is given to several important lightning variables including: the frequency and geographical distribution of lightning in the vicinity of the NALMA network, lightning type (ground or cloud flash), lightning channel length, channel altitude, channel peak current, and the number of strokes per flash. Laboratory spark chamber results from the literature are used to convert 1-meter channel segments (that are located at a particular known altitude; i.e., air density) to NOx concentration. The resulting lightning NOx source profiles are discussed.

Koshak, William J.↗
DOE OSTI2020

Development of Gamma Background Radiation Digital Twin with Machine Learning Algorithms: Application of Unsupervised Machine Learning to Detection of Anomalies and Nuisances in Gamma Background Radiation Environmental Screening Data

Environmental screening of gamma radiation consists of detecting weak nuisance and anomaly signal in the presence of strong and highly varying background. In a typical scenario, a mobile detector-spectrometer continuously measures gamma radiation spectra in short, e.g., one-second, signal acquisition intervals. The measurement data is a 2D matrix, where one dimension is gamma ray energy, and the other dimension is the number of measurements or total time. In principle, gamma radiation sources can be detected and identified from the measured data by their unique spectral lines. Detecting sources from data measured in a search scenario is difficult due to the highly varying background because of naturally occurring radioactive material (NORM), and low signal-to-noise ratio (S/N) of spectral signal measured during one-second acquisition intervals. The objective of this work is to explore unsupervised machine learning (ML) algorithms for development of a digital twin of gamma radiation background, and for detection and identification of weak nuisances and anomalies events in the presence of highly fluctuating background. In one segment of work, we developed a gamma background estimation model using a Longshort term memory (LSTM) network for one-step CPS time series prediction. The LSTM model was validated with two data sets of measurements from two independent NaI detectors positioned on a mobile platform. The data sets contained background radiation only and no orphan isotope sources. The LSTM model was constructed and tested using data from one of the detectors. Performance of the LSTM model was validate through one-step prediction of CPS time series of another NaI detector without re-training. This approach allows to create a digital twin for nuclear background estimation. Using LSTM, it could be possible to detect a source through subtraction of the estimated counts from the measured background. In another segment of work, we investigated detection of gamma emitting sources in the presence of complex background using unsupervised machine learning. Spectral lines of isotopes are difficult to observe in one-second measurements. Averaging over the entire measurement campaign data set reveals spectral lines of most common background isotopes. Spectral lines of orphan sources, which might appear only in a few measurements during the campaign, will be washed out if averaging is performed over the entire measurement data set. The approach we have explored consists of extracting one-second measurements containing weak spectral features through data clustering. Averaging one-second spectra in a cluster should reveal the presence of anomaly sources. We created two ML models using K-means clustering and Neural Network Self-organizing Map (SOM). Performance of these ML models was benchmarked using search data. One data set contained 137 Cs source, and another dataset contained 131 I source.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2010

Estimates of the Lightning NOx Profile in the Vicinity of the North Alabama Lightning Mapping Array

The NASA Marshall Space Flight Center Lightning Nitrogen Oxides Model (LNOM) is applied to August 2006 North Alabama Lightning Mapping Array (LMA) data to estimate the raw (i.e., unmixed and otherwise environmentally unmodified) vertical profile of lightning nitrogen oxides, NOx = NO + NO 2 . This is part of a larger effort aimed at building a more realistic lightning NOx emissions inventory for use by the U.S. Environmental Protection Agency (EPA) Community Multiscale Air Quality (CMAQ) modeling system. Data from the National Lightning Detection Network TM (NLDN) is also employed. Overall, special attention is given to several important lightning variables including: the frequency and geographical distribution of lightning in the vicinity of the LMA network, lightning type (ground or cloud flash), lightning channel length, channel altitude, channel peak current, and the number of strokes per flash. Laboratory spark chamber results from the literature are used to convert 1-meter channel segments (that are located at a particular known altitude; i.e., air density) to NOx concentration. The resulting raw NOx profiles are discussed.

Koshak, William J.↗
NASA NTRS2012

Ground and Airborne Methane Measurements using Optical Parametric Amplifiers

We report on an initial airborne demonstration of atmospheric methane column measurements at 1.65 micrometers using a widely tunable, seeded optical parametric amplifier (OPA) lidar and a photon counting detector. Methane is an important greenhouse gas and accurate knowledge of its sources and sinks is needed for climate modeling. Our lidar system uses 20 pulses at increasing wavelengths and integrated path differential absorption (IPDA) to map a methane line at 1650.9 nanometers. The wavelengths are generated by using a Nd:YAG pump laser at 1064.5 nanometers and distributed feedback diode laser at 1650.9 nanometers and a periodically-poled lithium niobate (PPLN) crystal. The pulse width was 3 nanoseconds and the pulse repetition rate was 6.28 KHz. The outgoing energy was approximately 13 microJoules/pulse. A commercial 20 nanometer diameter fiber-coupled telescope with a photon counting detector operated in analog mode with a 0.8 nanometer bandpass filter was used as the lidar receiver. The lidar system was integrated on NASA's DC-8 flying laboratory, based at Dryden Airborne operations Facility (DAOF) in Palmdale CA. Three flights were performed in the central valley of California. Each flight lasted about 2.5 hours and it consisted of several flight segments at constant altitudes at approximately 3, 4.5, 6, 7.6, 9.1, 10.6 km (l0, 15, 20, 25, 30, 35 kft). An in-situ cavity ring down spectrometer made by Picarro Inc. was flown along with the lidar instrument provided us with the "truth" i.e. the local CH4, CO2 and H2O concentrations at the constant flight altitude segments. Using the aircraft's altitude, GPS, and meteorological data we calculated the theoretical differential optical depth of the methane absorption at increasing altitudes. Our results showed good agreement between the experimentally derived optical depth measurements from the lidar instrument and theoretical calculations as the flight altitude was increased from 3 to 10.6 kilometers, assuming a constant methane mixing ratio of 1.8 parts per million. The in-situ spectrometer did not show any significant deviations from the ambient concentrations. Further analysis using meteorological data from the Global Modeling and Assimilation Office (http://gmao.gsfc.nasa.gov/) to derive the theoretical optical depth also showed good agreement with the experimentally derived values. The OPA lidar system with slight modifications has also been used to measure CO2, water vapor, and CO in the near and mid-infrared spectral regions on the ground.

Riris, Haris↗
DOE OSTI2019

Implementation of a Spacer Grid Rod Thermal-Hydraulic Reconstruction (ROTHCON) Capability into the Thermal-Hydraulic Subchannel Code CTF

The Consortium for Advanced Simulation of Light Water Reactors is developing a core simulator capability known as the Virtual Environment for Reactor Applications (VERA) to address nuclear industry challenge problems such as crud-induced power shift (CIPS). The CTF thermal-hydraulic (T/H) subchannel code provides thermal feedback in the coupled neutronics, T/H, crud chemistry simulation that VERA performs. It has been discovered that the coarse meshing approach used by CTF (in which fuel rods are discretized into four azimuthal segments) can be a source of error in predicting crud growth and boron distribution in VERA CIPS calculations. Spacer grid effects lead to complex rod-to-fluid heat transfer behavior that, when not resolved, can lead to error in the prediction of crud growth and boron deposition. A higher-fidelity computational fluid dynamics approach can be used instead of CTF, but this leads to excessive simulation times. This paper presents an approach for using high-fidelity computational fluid dynamics data to create shape functions that are used in CTF to reconstruct rod surface heat transfer behavior as a function of spacer grid geometry. The approach is demonstrated for a 5 × 5 rod bundle facility with five mixing vane grids under a range of operating conditions encountered in nominal pressurized water reactor conditions. Furthermore, it is demonstrated that the grid heat transfer maps are successful at introducing a higher-fidelity heat transfer modeling capability into CTF.

CFD-informed↗
NASA NTRS1998

An Object-Oriented Interface to the CCSDS Ground Telecommand Services

The Telecommand Data Routing and Channel Services defined by the Consultative Committee for Space Data Systems (CCSDS) are flexible enough to support a myriad of commanding models. Because the standard is so broad, the traditional approach has been to implement only the portion of the standard needed by the particular spacecraft being tested/operated. Tasked with providing Telecommand Services for an entire class of spacecraft, where each spacecraft may choose any valid CCSDS commanding model, NASA Code 584 designed a common architecture capable of handling the full CCSDS protocol. The solution uses another CCSDS standard - the Standard Formatted Data Unit (SFDU) as the interface to the Telecommand Services. SFDUs provide a consistent way of labelling data objects, as well as allowing data objects to encapsulate other data objects. The resulting interface is: - Flexible: The full Data Routing and Channel Services are available via a single interface. The client (i.e. the command source) may enter commands at any layer within the protocol stack, specify any of the data aggregation or segmentation methods, and dynamically set any configuration parameter defined in the standard. - Object-oriented: Each object specifies both the data and the actions to be performed with the data. An object may contain other objects. - Expandable: New capabilities are added by defining new objects. Objects pass thru the protocol layers until they reach the applicable layer. The resulting design is: - Modular: The logic for each protocol layer is contained in a separate Application Program Interface (API). The objects used for the external interface are also used for communication between layers. - Distributable: The design can be split along any layer boundary for distribution across multiple machines. The objects ensure data consistency across platforms. This paper describes the SFDU-based interface and the resulting protocol implementation. The implementation is currently used by NASA (National Aeronautics and Space Administration) for integration & test of the microwave Anisotropy Probe (MAP) and Earth observer-I (EO-l) spacecraft. It will be used for post-launch operations of these spacecraft as well as the Imager for Magnetopause to Aurora Global Exploration (IMAGE) spacecraft.

Ray, Timothy Joseph↗
NASA NTRS1993

Comparison of marine gravity from shipboard and high-density satellite altimetry along the Mid-Atlantic Ridge, 30.5-35.5 deg S

We compare new marine gravity fields derived from satellite altimetry with shipboard measurements over a region of more than 120,000 sq km in the central South Atlantic. Newly declassified satellite data were employed to construct free-air anomaly maps on 0.05 degree grids. An extensive gravity and bathymetry data set from four cruises along the Mid-Atlantic Ridge from 30.5-35.5 deg S provides a benchmark for testing the 2D resolution and accuracy of the satellite measurements where their crosstrack spacing is near their widest. The satellite gravity signal is coherent with bathymetry in this region down to wavelengths of 26 km, compared to 12.5 km for shipboard gravity. Residuals between the shipboard and satellite data sets have a roughly normal distribution. The standard deviation of satellite gravity with respect to shipboard measurements is nearly 7 mGal in a region of 140 mGal total variation, whereas the internal standard deviation at crossovers for GPS-navigated shipboard data is 1.8 mGal. The differences between shipboard and satellite data are too large to use satellite gravity to determine crustal thickness variations within a typical ridge segment.

Neumann, Gregory A.↗
DOE OSTI2021

3D reconstruction identifies loci linked to variation in angle of individual sorghum leaves

Selection for yield at high planting density has reshaped the leaf canopy of maize, improving photosynthetic productivity in high density settings. Further optimization of canopy architecture may be possible. However, measuring leaf angles, the widely studied component trait of leaf canopy architecture, by hand is a labor and time intensive process. Here, we use multiple, calibrated, 2D images to reconstruct the 3D geometry of individual sorghum plants using a voxel carving based algorithm. Automatic skeletonization and segmentation of these 3D geometries enable quantification of the angle of each leaf for each plant. The resulting measurements are both heritable and correlated with manually collected leaf angles. This automated and scaleable reconstruction approach was employed to measure leaf-by-leaf angles for a population of 366 sorghum plants at multiple time points, resulting in 971 successful reconstructions and 3,376 leaf angle measurements from individual leaves. A genome wide association study conducted using aggregated leaf angle data identified a known large effect leaf angle gene, several previously identified leaf angle QTL from a sorghum NAM population, and novel signals. Genome wide association studies conducted separately for three individual sorghum leaves identified a number of the same signals, a previously unreported signal shared across multiple leaves, and signals near the sorghum orthologs of two maize genes known to influence leaf angle. Automated measurement of individual leaves and mapping variants associated with leaf angle reduce the barriers to engineering ideal canopy architectures in sorghum and other grain crops.

3D reconstruction↗
NASA NTRS1993

Security aspects of space operations data

This paper deals with data security. It identifies security threats to European Space Agency's (ESA) In Orbit Infrastructure Ground Segment (IOI GS) and proposes a method of dealing with its complex data structures from the security point of view. It is part of the 'Analysis of Failure Modes, Effects Hazards and Risks of the IOI GS for Operations, including Backup Facilities and Functions' carried out on behalf of the European Space Operations Center (ESOC). The security part of this analysis has been prepared with the following aspects in mind: ESA's large decentralized ground facilities for operations, the multiple organizations/users involved in the operations and the developments of ground data systems, and the large heterogeneous network structure enabling access to (sensitive) data which does involve crossing organizational boundaries. An IOI GS data objects classification is introduced to determine the extent of the necessary protection mechanisms. The proposal of security countermeasures is oriented towards the European 'Information Technology Security Evaluation Criteria (ITSEC)' whose hierarchically organized requirements can be directly mapped to the security sensitivity classification.

Schmitz, Stefan↗
NASA NTRS2000

Hurricane Directional Wave Spectrum Spatial Variation in the Open Ocean and at Landfall

The sea surface directional wave spectrum was measured for the first time in all quadrants of a hurricane in open water using the NASA airborne scanning radar altimeter (SRA) carried aboard one of the NOAA WP-3D hurricane hunter aircraft at 1.5 km height. The SRA measures the energetic portion of the directional wave spectrum by generating a topographic map of the sea surface. At 8 Hz, the SRA sweeps a radar beam of 1' half-power width (two-way) across the aircraft ground track over a swath equal to 0.8 of the aircraft height, simultaneously measuring the backscattered power at its 36 GHz (8.3 mm) operating frequency and the range to the sea surface at 64 positions. These slant ranges are multiplied by the cosine of the off-nadir angles to determine the vertical distances from the aircraft to the sea surface. Subtracting these distances from the aircraft height produces the sea surface elevation map. The sea surface topography is interpolated to a uniform grid, transformed by a two dimensional FFT, and Doppler corrected. The open-ocean data were acquired on 24 August 1998 when hurricane Bonnie was east of the Bahamas and moving toward 330 deg at about 5 m/s. Individual waves up to 18 m height were observed and the spatial variation of the wave field was dramatic. The dominant waves generally propagated at significant angles to the downwind direction. At some positions there were three different wave fields of comparable energy crossing each other. The NOAA aircraft spent over five hours within 180 km of the eye, and made five eye penetrations. On 26 August 1998, the NOAA aircraft flew at 2.2 km height when hurricane Bonnie was making landfall near Wilmington, NC, documenting the directional wave spectrum in the region between Charleston, SC and Cape Hatteras, NC. The aircraft flight lines included segments near and along the shoreline as well as far offshore. Animations of the directional wave spectrum spatial variation along the aircraft tracks on the two flights will be presented using a 100: 1 time compression.

Walsh, Edward J.↗
NASA NTRS2015

The Role of the NASA Global Hawk Link Module as an Information Nexus For Atmospheric Mapping Missions

The Link Module described in this paper was developed for the NASA Uninhabited Aerial System (UAS) Global Hawk Pacific Mission (GloPAC) Airborne Science Campaign; four flights of 30 hour duration, supporting the Aura Validation Experiment (AVE). It was used again during the Genesis and Rapid Intensification Processes (GRIP) experiment, a NASA Earth Science field experiment to better understand how tropical storms form and develop into major hurricanes. In these missions, the Link Module negotiated all communication over the high bandwidth Ku satellite link, archived all the science data from onboard experiments in a spatially enabled database, routed command and control of the instruments from the Global Hawk Operations Center, and re-transmitted select data sets directly to experimenters control and analysis systems. The availability of aggregated information from collections of sensors, and remote control capabilities, in real-time, is revolutionizing the way Airborne Science is being conducted. The Link Module NG now being flown in support of the NASA Earth Venture missions, the Hurricane and Severe Storm Sentinel (HS3) mission, and Airborne Tropical Tropopause Experiment (A TTREX) mission, has advanced data fusion technologies that are further advancing the Scientific productivity, flexibility and robustness of these systems. On-the-fly traffic shaping has been developed to allow the high definition video, used for critical flight control segments, to dynamically allocate variable bandwidth on demand. Historically, the Link Module evolved from the instrument and communication interface controller used by NASA's Pathfinder and Pathfinder plus solar powered UAS's in the late 1990' s. It later was expanded for use in the AIRDAS four channel scanner flown on the NASA Altus UAS, and then again to a module in the AMS twelve channel multispectral scanner flying on the NASA (Predator-b) Ikhana UAS. The current system is the answer to the challenges imposed by extremely long duration UASs, with on-board multi-instrument (>= 12) Sensor Webs.

Hurricanes↗
DOE OSTI2023

Temperature dependence of resistivity of carbon micro/nanostructures: Microscale spatial distribution with mixed metallic and semiconductive behaviors

The temperature coefficient of resistivity (θ T ) of carbon-based materials is a critical property that directly determines their electrical response upon thermal impulses. It could have metal- (positive) or semiconductor-like (negative) behavior, depending on the combined temperature dependence of electron density and electron scattering. Its distribution in space is very difficult to measure and is rarely studied. Here, for the first time, we report that carbon-based micro/nanoscale structures have a strong non-uniform spatial distribution of θ T . This distribution is probed by measuring the transient electro-thermal response of the material under extremely localized step laser heating and scanning, which magnifies the local θ T effect in the measured transient voltage evolution. For carbon microfibers (CMFs), after electrical current annealing, θ T varies from negative to positive from the sample end to the center with a magnitude change of >130% over <1 mm. This θ T sign change is confirmed by directly testing smaller segments from different regions of an annealed CMF. For micro-thick carbon nanotube bundles, θ T is found to have a relative change of >125% within a length of ~2 mm, uncovering strong metallic to semiconductive behavior change in space. In conclusion, our θ T scanning technique can be readily extended to nm-thick samples with μm scanning resolution to explore the distribution of θ T and provide a deep insight into the local electron conduction.

36 MATERIALS SCIENCE↗
NASA NTRS2020

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

We present NeMO-Net, the Srst open-source deep convolutional neural network (CNN) and interactive learning and training software aimed at assessing the present and past dynamics of coral reef ecosystems through habitat mapping into 10 biological and physical classes. Shallow marine systems, particularly coral reefs, are under significant pressures due to climate change, ocean acidification, and other anthropogenic pressures, leading to rapid, often devastating changes, in these fragile and diverse ecosystems. Historically, remote sensing of shallow marine habitats has been limited to meter-scale imagery due to the optical effects of ocean wave distortion, refraction, and optical attenuation. NeMO-Net combines 3D cm-scale distortion-free imagery captured using NASA FluidCam and Fluid lensing remote sensing technology with low resolution airborne and spaceborne datasets of varying spatial resolutions, spectral spaces, calibrations, and temporal cadence in a supercomputer-based machine learning framework. NeMO-Net augments and improves the benthic habitat classification accuracy of low-resolution datasets across large geographic ad temporal scales using high-resolution training data from FluidCam.NeMO-Net uses fully convolutional networks based upon ResNet and ReSneNet to perform semantic segmentation of remote sensing imagery of shallow marine systems captured by drones, aircraft, and satellites, including WorldView and Sentinel. Deep Laplacian Pyramid Super-Resolution Networks (LapSRN) alongside Domain Adversarial Neural Networks (DANNs) are used to reconstruct high resolution information from low resolution imagery, and to recognize domain-invariant features across datasets from multiple platforms to achieve high classification accuracies, overcoming inter-sensor spatial, spectral and temporal variations.Finally, we share our online active learning and citizen science platform, which allows users to provide interactive training data for NeMO-Net in 2D and 3D, integrated within a deep learning framework. We present results from the PaciSc Islands including Fiji, Guam and Peros Banhos 1 1 2 1 3 1 where 24-class classification accuracy exceeds 91%.

Chirayath, Ved↗
NASA NTRS2012

Airborne Hyperspectral Imaging System

A document discusses a hyperspectral imaging instrument package designed to be carried aboard a helicopter. It was developed to map the depths of Greenland's supraglacial lakes. The instrument is capable of telescoping to twice its original length, allowing it to be retracted with the door closed during takeoff and landing, and manually extended in mid-flight. While extended, the instrument platform provides the attached hyperspectral imager a nadir-centered and unobstructed view of the ground. Before flight, the instrument mount is retracted and securely strapped down to existing anchor points on the floor of the helicopter. When the helicopter reaches the destination lake, the door is opened and the instrument mount is manually extended. Power to the instrument package is turned on, and the data acquisition computer is commanded via a serial cable from an onboard user-operated laptop to begin data collection. After data collection is complete, the instrument package is powered down and the mount retracted, allowing the door to be closed in preparation for landing. The present design for the instrument mount consists of a three-segment telescoping cantilever to allow for a sufficient extended length to see around the landing struts and provide a nadir-centered and unobstructed field of view for the hyperspectral imager. This instrument works on the premise that water preferentially absorbs light with longer wavelengths on the red side of the visible spectrum. This property can be exploited in order to remotely determine the depths of bodies of pure freshwater. An imager flying over such a lake receives light scattered from the surface, the bulk of the water column, and from the lake bottom. The strength of absorption of longer-wavelength light depends on the depth of the water column. Through calibration with in situ measurements of the water depths, a depth-determining algorithm may be developed to determine lake depth from these spectral properties of the reflected sunlight.

Behar, Alberto E.↗