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DOE OSTI2024

Automated Inspection of Criticality Control Overpacks for Surplus Plutonium Disposition: Qualification Update – 25313

In an effort to reduce the amount of nuclear waste in South Carolina, the Department of Energy (DOE) tasked the Savannah River Site (SRS) with diluting and disposing of the amount of plutonium in the state. This process involves the movement and shipment of over 100,000 criticality control overpacks (CCOs) throughout the project lifespan, lending itself to the use of automation to reduce worker radiation exposure and more efficiently utilize human capital. Due to the large scope, this overarching process was broken down into several different “automation projects” to be developed. The first opportunity pursued was the receipt and inspection of empty CCO drums coming into SRS, identified as Automation Project 1 (AP1), and is the focus of this paper. AP1 was developed to unpack incoming CCOs and inspect them for unwanted foreign objects and any damage to the drum or its contents. This process is accomplished by the combination of an automated guided vehicle (AGV) that delivers CCOs to a robotic arm which uses a suite of custom tools to disassemble a CCO, inspect the inside and outside of the CCO and its inner criticality control container (CCC), reassemble the CCC and CCO, and apply a tamper indicating device (TID) to the inspected drum. In past years, the robotic work cell had been developed in a small-scale testing facility for proof-of-concept. This year, major improvements were made to the robotic work cell to perform the process, including integration into the final facility where CCOs will be inspected. Other technical improvements include the implementation of sensor feedback and safety relays into the control system to allow the state of the work cell to be better tracked, and additional development of the TID application process to complete the robotic inspection. Further enhancements were made to the robotic vision processes and robot pathing, as well as development on a computer vision inspection process to detect inspection criteria anomalies in CCOs. In addition to developmental improvements, the work cell underwent a six-month testing period to ensure the project requirements were met. Results of this testing period demonstrate the work cell’s capability to meet project throughput goals at an acceptable level, successfully document the status of each CCO inspected, and reduce the toll on technical operations’ human power by two thirds. At the time of this paper, the work cell is capable of autonomously handling up to eight CCOs with an AGV, delivering CCOs to and from the robot work cell, and having a robotic arm perform a full receipt and inspection procedure on each CCO. Moving forward, repeatability will be improved so that these CCOs can be run back-to-back seamlessly, as well as improving the system to handle more significant edge cases and failure modes.

Spivey, Nicholas↗

DOE OSTI2019

Understanding the Response of Photosynthetic Metabolism in Tropical Forests to Seasonal Climate Variations

We propose a study focused on the basic question: What controls the response of photosynthesis in Amazonian forests to seasonal variations in climate? This question, despite its apparent simplicity, remains difficult for modern earth system models to answer, and is also the subject of continuing controversy in the remote-sensing literature. For example, in the modeling arena, four cutting-edge earth system models (ESM’s) show significant divergence in their seasonal patterns of photosynthesis from observed whole-system photosynthetic fluxes at two sites in the central Amazon. The overall objective of the project is to guide improvements in earth system models of tropical forest photosynthesis by collecting and integrating a suite of observations to 1) test several hypotheses (three core, conceptual hypotheses for explaining observed photosynthetic seasonality and a methodological hypotheses for scaling from leaves to canopy with hyperspectral cameras), and 2) perform a synthesis activity that applies our empirical work to earth system models of terrestrial carbon cycling. The project will provide an extensive suite of new and unique datasets that enable us to fill, through advanced modeling techniques and analysis, critical knowledge gaps in current understanding of what controls the response of canopy photosynthesis and related functions in Amazonian forests to seasonal variation in climate. Three major types of datasets and data products will be delivered: (1) in situ leaf and tree-scale measurements from intensive ecophysiological and ecohydological field campaigns, (2) time-series observations of leaf-to-crown scale forest reflectance properties and atmospheric radiation from two innovative, ground-based imaging sensors (respectively, the Hyperspectral Vegetation Imaging System and the High Dynamic Range All-Sky Imaging System), and (3) results from state-of-the-art models of 3-dimensional canopy processes for radiative transfer and photosynthesis that integrate and link our observations to tropical forest processes. These data products and the improved knowledge we achieve with them will contribute to testing and improving the treatment of tropical forest processes in ESMs. They will contribute data to and leverage related data from of the GOAmazon campaign, and make significant contributions to support the overall goals of GOAmazon. This work will also help establish a foundation for the Next Generation Ecosystem Experiments (NGEE) in the Tropics.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2007

Robotic Vision-Based Localization in an Urban Environment

A system of electronic hardware and software, now undergoing development, automatically estimates the location of a robotic land vehicle in an urban environment using a somewhat imprecise map, which has been generated in advance from aerial imagery. This system does not utilize the Global Positioning System and does not include any odometry, inertial measurement units, or any other sensors except a stereoscopic pair of black-and-white digital video cameras mounted on the vehicle. Of course, the system also includes a computer running software that processes the video image data. The software consists mostly of three components corresponding to the three major image-data-processing functions: Visual Odometry This component automatically tracks point features in the imagery and computes the relative motion of the cameras between sequential image frames. This component incorporates a modified version of a visual-odometry algorithm originally published in 1989. The algorithm selects point features, performs multiresolution area-correlation computations to match the features in stereoscopic images, tracks the features through the sequence of images, and uses the tracking results to estimate the six-degree-of-freedom motion of the camera between consecutive stereoscopic pairs of images (see figure). Urban Feature Detection and Ranging Using the same data as those processed by the visual-odometry component, this component strives to determine the three-dimensional (3D) coordinates of vertical and horizontal lines that are likely to be parts of, or close to, the exterior surfaces of buildings. The basic sequence of processes performed by this component is the following: 1. An edge-detection algorithm is applied, yielding a set of linked lists of edge pixels, a horizontal-gradient image, and a vertical-gradient image. 2. Straight-line segments of edges are extracted from the linked lists generated in step 1. Any straight-line segments longer than an arbitrary threshold (e.g., 30 pixels) are assumed to belong to buildings or other artificial objects. 3. A gradient-filter algorithm is used to test straight-line segments longer than the threshold to determine whether they represent edges of natural or artificial objects. In somewhat oversimplified terms, the test is based on the assumption that the gradient of image intensity varies little along a segment that represents the edge of an artificial object.

Mchenry, Michael↗

NASA NTRS2006

NASA Tech Briefs, October 2006

Topics covered include: Protein Sensors Based on Optical Ring Resonators; Phase Sensor for Aligning a Segmented Telescope Mirror; Control Software for Advanced Video Guidance Sensor; Generating Control Commands From Gestures Sensed by EMG; Multiple-Flat-Panel System Displays Multidimensional Data; 3D X-Ray Luggage-Screening System; Probe Station and Near-Field Scanner for Testing Antennas; Photodetector Arrays for Multicolor Visible/Infrared Imaging; Semiconductor Bolometers Give Background-Limited Performance; Multichannel X-Band Dielectric-Resonator Oscillator; Automatic Alignment of Displacement-Measuring Interferometer; Earth Observing System Data Gateway; Power User Interface; Mercury Shopping Cart Interface; Cassini Archive Tracking System; Architecture Adaptive Computing Environment; Computing Fault Displacements from Surface Deformations; Oxygen-Permeable, Hydrophobic Membranes of Silanized alpha-Al2O3; SiC Composite Turbine Vanes; Retaining Device for the Interior Structure of a Spacecraft Payload; Tool for Torquing Circular Electrical-Connector Collars; System for Continuous Deaeration of Hydraulic Oil; Solar-Powered Cooler and Heater for an Automobile Interior; Improved Oxygen-Beam Texturing of Glucose-Monitoring Optics; Tool for Two Types of Friction Stir Welding; Stationary Apparatus Would Apply Forces of Walking to Feet; Instrument Would Detect and Collect Biological Aerosols; Boundary Condition for Modeling Semiconductor Nanostructures; Miniature Distillation Column for Producing LOX From Air; Even Illumination from Fiber-Optic-Coupled Laser Diodes; Optically Driven Deformable Mirrors; Algorithm for Automated Detection of Edges of Clouds; Exploiting Quantum Resonance to Solve Combinatorial Problems; Hybrid Terrain Database; On Release of Microbe-Laden Particles from Mars Landers; A Concept for Run-Time Support of the Chapel Language; Thermoelectric Inhomogeneities in (Ag(sub 1-y)SbTe2)(sub x)(PbTe)(sub 1-x); and Spacecraft Escape Capsule.

Source record↗

DOE OSTI2012

Recent improvements of the JET lithium beam diagnostic

A 60 kV neutral lithium diagnostic beam probes the edge plasma of JET for the measurement of electron density profiles. This paper describes recent enhancements of the diagnostic setup, new procedures for calibration and protection measures for the lithium ion gun during massive gas puffs for disruption mitigation. New light splitting optics allow in parallel beam emission measurements with a new double entrance slit CCD spectrometer (spectrally resolved) and a new interference filter avalanche photodiode camera (fast density and fluctuation studies).

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

NASA NTRS1990

Flight elements: Fault detection and fault management

Fault management for an intelligent computational system must be developed using a top down integrated engineering approach. An approach proposed includes integrating the overall environment involving sensors and their associated data; design knowledge capture; operations; fault detection, identification, and reconfiguration; testability; causal models including digraph matrix analysis; and overall performance impacts on the hardware and software architecture. Implementation of the concept to achieve a real time intelligent fault detection and management system will be accomplished via the implementation of several objectives, which are: Development of fault tolerant/FDIR requirement and specification from a systems level which will carry through from conceptual design through implementation and mission operations; Implementation of monitoring, diagnosis, and reconfiguration at all system levels providing fault isolation and system integration; Optimize system operations to manage degraded system performance through system integration; and Lower development and operations costs through the implementation of an intelligent real time fault detection and fault management system and an information management system.

Lum, H.↗

NASA NTRS2016

Translational Cellular Research on the International Space Station

The emerging field of Translational Research aims to coalesce interdisciplinary findings from basic science for biomedical applications. To complement spaceflight research using human subjects, translational studies can be designed to address aspects of space-related human health risks and help develop countermeasures to prevent or mitigate them, with therapeutical benefits for analogous conditions experienced on Earth. Translational research with cells and model organisms is being conducted onboard the International Space Station (ISS) in connection with various human systems impacted by spaceflight, such as the cardiovascular, musculoskeletal, and immune systems. Examples of recent cell-based translational investigations on the ISS include the following. The JAXA investigation Cell Mechanosensing seeks to identify gravity sensors in skeletal muscle cells to develop muscle atrophy countermeasures by analyzing tension fluctuations in the plasma membrane, which changes the expression of key proteins and genes. Earth applications of this study include therapeutic approaches for some forms of muscular dystrophy, which appear to parallel aspects of muscle wasting in space. Spheroids is an ESA investigation examining the system of endothelial cells lining the inner surface of all blood vessels in terms of vessel formation, cellular proliferation, and programmed cell death, because injury to the endothelium has been implicated as underpinning various cardiovascular and musculoskeletal problems arising during spaceflight. Since endothelial cells are involved in the functional integrity of the vascular wall, this research has applications to Earth diseases such as atherosclerosis, diabetes, and hypertension. The goal of the T-Cell Activation in Aging NASA investigation is to understand human immune system depression in microgravity by identifying gene expression patterns of candidate molecular regulators, which will provide further insight into factors that may play a critical role in immune function loss during aging. In addition, Omics investigations with cells have synergistic applications ranging from the evaluation of pharmacological countermeasures to drug discovery. Thus, cell-based translational research onboard the ISS is bidirectionally bridging cutting-edge cellular and molecular approaches with space bioastronautics and human health methodologies on Earth.

Love, John↗

DOE OSTI2022

Smart connected worker edge platform for smart manufacturing: Part 2—Implementation and on‐site deployment case study

Abstract In this paper, we describe specific deployments of the Smart Connected Worker (SCW) Edge Platform for Smart Manufacturing through implementation of four instructive real‐world use cases that illustrate the role of people in a Smart Manufacturing paradigm through which affordable, scalable, accessible, and portable (ASAP) information technology (IT) acquires and contextualizes data into information for transmission to operation technologies (OT). For case one, the platform captures the relationships between energy consumption and human workflows for improved energy productivity while workers interact with machines during semiconductor manufacturing. The platform utilizes human cognition to identify anomalous machine behavior for root cause analysis of system faults via neural network (NN) that recognize alarm postures of workers with cameras. For case two, a smart assembly line is demonstrated for state monitoring and fault detection. Machine learning (ML) models are used to recognize system states and identify fault scenarios with human intervention. For case three, the platform monitors human–machine interactions to classify manufacturing machine states for proper operations and energy productivity. Internal energy states of individual or collections of manufacturing equipment are determined via NN based algorithms that disaggregate signals associated with smart metering typically deployed at manufacturing facilities. These methods predict the real time energy profile of each machine from the total energy profile of a manufacturing site. For case four, a software defined sensor system built with scientific workflow engines is demonstrated for contextualizing data from laser surface refraction for characterization, and diagnostics in the processing of additively manufactured titanium alloy.

Donovan, Richard P.↗

NASA NTRS2018

A Multi-Satellite Assimilation and Modeling Platform to Construct a Global and Complete view of the Hydrologic Cycle

What captivates me about the research field of satellite remote sensing of the earth system science is the opportunity to help human beings by addressing challenging questions related to the current and future availability of natural resources for domestic, agricultural, and industrial needs. For example, a continuously varying climate poses a threat to the water resource, not only in developing countries, but also in economically well-developed regions, creating the urgent need to characterize and predict its spatial and temporal availability. Specifically, my curiosity is driven by the challenge of merging cutting-edge space technology and earth observations (i.e., remote sensing) with state-of-the-art models for the purpose of improving our scientific knowledge about the variability and the change of the hydrologic cycle.The only practical way to observe the land surface processes (e.g., hydrologic cycle) on continental to global scales is via satellite remote sensing. Though remote sensing can make spatially comprehensive measurements of various components of the land surface system, it cannot provide direct information on the entire system, and the measurements represent only a snapshot in time. Physical based models may be used to continuously predict the temporal and spatial earth processes, but these predictions are often poor, due to model initialization, parameter and meteorological forcing errors, and inadequate model physics and/or resolution. Thus, an attractive prospect is to combine the strengths of land surface models and observations (and minimize the weaknesses of both) to provide a superior land surface state estimate. This is the goal of land surface data assimilation. Data assimilation provides a better estimate of the environmental states than either models or observations could individually do. The broad concept of data assimilation can be applied to various disciplines such as hydrology, ecology, environmental hazards, agriculture and economy.My research is targeted to integrating multiple satellite information having multi-sensor and multi-resolution assimilation within today's state-of-the-art hydrologic models. Multi-sensor and multi-resolution assimilation techniques represent a necessary milestone in future earth science applications because they offer the capability of comprehensively integrating disparate types of earth observations via deep-learning techniques. A multi-satellite assimilation and modeling platform will ultimately provide a robust and complete dataset to more fully understand earth's dynamics. In fact, the multi-satellite assimilation platforms build a comprehensive description of the earth processes that is geared toward accurately representing the complexity of natural and anthropogenic interactions in land surface processes. Most importantly, these platforms are suitable as decision support tools for applications across different aspects of earth system science.My recent work has focused on recent multi-sensor data assimilation techniques targeted at improving snow, soil moisture, groundwater, and terrestrial water storage hydrological states.

Girotto, Manuela↗

NASA NTRS2020

Linkage among Ice Crystal Microphysics, Mesoscale Dynamics and Cloud and Precipitation Structures Revealed By Collocated Microwave Radiometer and Multi-Frequency Radar Observations

Ice clouds and falling snow are ubiquitous globally and play important roles in the Earth’s radiation budget and precipitation processes. Ice particle microphysical properties (e.g., size, habit and orientation) are not only influenced by ambient environment’s dynamic and thermodynamic conditions, but also intimately connect to the cloud radiative effects and particle fall speeds, which therefore impact up to the future climate projection and down to the details of the surface precipitation (e.g., onset-time, location, type and strength). Our previous work revealed that high-frequency Polarimetric radiance Difference (PD) from passive microwave sensors is a good indicator of the bulk aspect ratio of horizontally oriented ice particles that are often occur inside anvil clouds and/or stratiform precipitations. In this current work, we further investigate the dynamic/thermodynamic mechanisms and cloud/precipitation structures associated with ice-phase microphysics corresponding to different PD signals. In order to do so, collocated CloudSat radar (W-band) and Global Precipitation Measurement Dual-frequency Precipitation Radar (GPM-DPR, Ku/Ka bands) observations as well as European Centre for Medium-Range Weather Forecasts (ECMWF) atmosphere background profiles are grouped according to the magnitude of PD for only stratiform precipitation and/or anvil cloud scenes. We found that horizontally-oriented snow aggregates or large snow particles are likely the major contributor to the high-PD signals at 166 GHz, while low-PD magnitudes can be attributed to small cloud ice, randomly oriented snow aggregates, riming snow or super-cooled water. Further, high (low) PD scenes are found to be associated with stronger (weaker) wind shear and higher (lower) ambient humidity, both of which help promote (prohibit) the growth of frozen particles and the organization of convective systems. An ensemble of squall line cases is studied at the end to demonstrate that the PD asymmetry in the leading and trailing edges of the deep convection line is closely tied to the anvil cloud and stratiform precipitation layers respectively, suggesting the potential usefulness of PD as a proxy of stratiform/convective precipitation flag, as well as a proxy of convection life stage.

Ice crystal microphysics↗

NASA NTRS2024

Evaluation of Vertical Patterns in Chlorophyll-A Derived From A Data Assimilating Model of Satellite-Based Ocean Color

Satellite-based sensors of ocean color have become the primary tool to infer changes in surface chlorophyll, while BGC-Argo floats are now filling the information gap at depth. Here we use BGC-Argo data to assess depth-resolved information on chlorophyll-a derived from an ocean biogeochemical model constrained by the assimilation of surface ocean color remote sensing. The data-assimilating model replicates well the general seasonality and meridional gradients in surface and depth-resolved chlorophyll-a inferred from the float array in the Southern Ocean. On average, the model tends to overestimate float-based chlorophyll, particularly at times and locations of high productivity such as the beginning of the spring bloom, subtropical deep chlorophyll maxima, and non-iron limited regions of the Southern Ocean. The highest model RMSE in the upper 50 m with respect to the float array is of 0.6 mg Chl m −3 , which should allow the detection of seasonal changes in float-based biomass (varying between 0.01 and >1 mg Chl m −3 ) but might hinder the identification of subtle changes in chlorophyll at narrow local scales. Both model and float profiling data show good agreement with in situ data from station ALOHA, with model estimates showing a slight accuracy edge in inferring depth-resolved observations. Uncertainties in float bio-optical estimates impede their use as a reliable benchmark for validation, but the general qualitative agreement between model and float data provides confidence in the ability of model to replicate biogeochemical features below the surface, where data is not directly constrained by the assimilation of satellite ocean color.

Lionel A Quintero↗

NASA NTRS2018

Armstrong Flight Research Center Research Technology and Engineering 2017

I am delighted to present this report of accomplishments at NASA's Armstrong Flight Research Center. Our dedicated innovators possess a wealth of performance, safety, and technical capabilities spanning a wide variety of research areas involving aircraft, electronic sensors, instrumentation, environmental and earth science, celestial observations, and much more. They not only perform tasks necessary to safely and successfully accomplish Armstrong's flight research and test missions but also support NASA missions across the entire Agency. Armstrong's project teams have successfully accomplished many of the nation's most complex flight research projects by crafting creative solutions that advance emerging technologies from concept development and experimental formulation to final testing. We are developing and refining technologies for ultra-efficient aircraft, electric propulsion vehicles, a low boom flight demonstrator, air launch systems, and experimental x-planes, to name a few. Additionally, with our unique location and airborne research laboratories, we are testing and validating new research concepts. Summaries of each project highlighting key results and benefits of the effort are provided in the following pages. Technology areas for the projects include electric propulsion, vehicle efficiency, supersonics, space and hypersonics, autonomous systems, flight and ground experimental test technologies, and much more. Additional technical information is available in the appendix, as well as contact information for the Principal Investigator of each project. I am proud of the work we do here at Armstrong and am pleased to share these details with you. We welcome opportunities for partnership and collaboration, so please contact us to learn more about these cutting-edge innovations and how they might align with your needs.

yearbook↗

NASA NTRS1994

Planar rotational magnetic micromotors with integrated shaft encoder and magnetic rotor levitation

Deep x-ray lithography and electroplating may be combined to form a fabrication tool for micromechanical devices with large structural heights, to 500 micron, and extreme edge acuities, less than 0.1 micron-run-out per 100 micron of height. This process concept which originated in Germany as LIGA may be further extended by adding surface micromachining. This extension permits the fabrication of precision metal and plastic parts which may be assembled into three-dimensional micromechanical components and systems. The processing tool may be used to fabricate devices from ferromagnetic material such as nickel and nickel-iron alloys. These materials when properly heat treated exhibit acceptable magnetic behavior for current to flux conversion and marginal behavior for permanent magnet applications. The tool and materials have been tested via planar, magnetic, rotational micromotor fabrication. Three phase reluctance machines of the 6:4 configuration with 280 micron diameter rotors have been tested and analyzed. Stable rotational speeds to 34,000 rpm with output torques above 10 x 10(exp -9) N-m have been obtained. The behavior is monitored with integrated shaft encoders which are photodiodes which measure the rotor response. Magnetic levitation of the rotor via reluctance forces has been achieved and has reduced frictional torque losses to less than 1 percent of the available torque. The results indicate that high speed limits of these actuators are related to torque ripple. Hysteresis motors with magnetic bearings are under consideration and will produce high speed rotational machines with excellent sensor application potential.

Guckel, Henry↗

NASA NTRS2012

Development of Field-Controlled Smart Optic Materials (ScN, AlN) with Rare Earth Dopants

The purpose of this investigation is to develop the fundamental materials and fabrication technology for field-controlled spectrally active optics that are essential for industry, NASA, and DOD applications such as: membrane optics, filters for LIDARs, windows for sensors, telescopes, spectroscopes, cameras, flat-panel displays, etc. ScN and AlN thin films were fabricated on c-axis Sapphire (0001) or quartz substrate with the RF and DC magnetron sputtering. The crystal structure of AlN in fcc (rocksalt) and hcp (wurtzite) were controlled. Advanced electrical characterizations were performed, including I-V and Hall Effect Measurement. ScN film has a free carrier density of 5.8 x 10(exp 20)/per cubic centimeter and a conductivity of 1.1 x 10(exp 3) per centimeter. The background ntype conductivity of as-grown ScN has enough free electrons that can readily interact with the photons. The high density of free electrons and relatively low mobility indicate that these films contain a high level of shallow donors as well as deep levels. Also, the UV-Vis spectrum of ScN and AlN thin films with rare earth elements (Er or Ho) were measured at room temperature. Their optical band gaps were estimated to be about 2.33eV and 2.24eV, respectively, which are obviously smaller than that of undoped thin film ScN (2.4eV). The red-shifted absorption onset gives direct evidence for the decrease of band gap (Eg) and the energy broadening of valence band states are attributable to the doping. As the doped elements enter the ScN crystal lattices, the localized band edge states form at the doped sites with a reduction of Eg. Using a variable angle spectroscopic ellipsometer, the decrease in refractive index with applied field is observed with a smaller shift in absorption coefficient.

Kim, Hyun-Jung↗

NASA NTRS2014

Features of Point Clouds Synthesized from Multi-View ALOS/PRISM Data and Comparisons with LiDAR Data in Forested Areas

LiDAR waveform data from airborne LiDAR scanners (ALS) e.g. the Land Vegetation and Ice Sensor (LVIS) havebeen successfully used for estimation of forest height and biomass at local scales and have become the preferredremote sensing dataset. However, regional and global applications are limited by the cost of the airborne LiDARdata acquisition and there are no available spaceborne LiDAR systems. Some researchers have demonstrated thepotential for mapping forest height using aerial or spaceborne stereo imagery with very high spatial resolutions.For stereo imageswith global coverage but coarse resolution newanalysis methods need to be used. Unlike mostresearch based on digital surface models, this study concentrated on analyzing the features of point cloud datagenerated from stereo imagery. The synthesizing of point cloud data from multi-view stereo imagery increasedthe point density of the data. The point cloud data over forested areas were analyzed and compared to small footprintLiDAR data and large-footprint LiDAR waveform data. The results showed that the synthesized point clouddata from ALOSPRISM triplets produce vertical distributions similar to LiDAR data and detected the verticalstructure of sparse and non-closed forests at 30mresolution. For dense forest canopies, the canopy could be capturedbut the ground surface could not be seen, so surface elevations from other sourceswould be needed to calculatethe height of the canopy. A canopy height map with 30 m pixels was produced by subtracting nationalelevation dataset (NED) fromthe averaged elevation of synthesized point clouds,which exhibited spatial featuresof roads, forest edges and patches. The linear regression showed that the canopy height map had a good correlationwith RH50 of LVIS data with a slope of 1.04 and R2 of 0.74 indicating that the canopy height derived fromPRISM triplets can be used to estimate forest biomass at 30 m resolution.

LiDARD↗

DOE OSTI2013

Multi-view fast-ion D-alpha spectroscopy diagnostic at ASDEX Upgrade

A novel fast-ion D-alpha (FIDA) diagnostic that is based on charge exchange spectroscopy has been installed at ASDEX Upgrade. The diagnostic uses a newly developed high-photon-throughput spectrometer together with a low-noise EM-CCD camera that allow measurements with 2 ms exposure time. Absolute intensities are obtained by calibrating the system with an integrating sphere and the wavelength dependence is determined to high accuracy using a neon lamp. Additional perturbative contributions to the spectra, such as D{sub 2}-molecular lines, the Stark broadened edge D-alpha emission, and passive FIDA radiation have been identified and can be subtracted or avoided experimentally. The FIDA radiation from fast deuterium ions after charge exchange reactions can therefore be analyzed continuously without superimposed line emissions at large Doppler shifts. Radial information on the fast ions is obtained from radially distributed lines of sight. The investigation of the fast-ion velocity distribution is possible due to three different viewing geometries. The independent viewing geometries access distinct parts of the fast-ion velocity space and make tomographic reconstructions possible.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

NASA NTRS1993

Multiscale Morphological Filtering for Analysis of Noisy and Complex Images

Images acquired with passive sensing techniques suffer from illumination variations and poor local contrasts that create major difficulties in interpretation and identification tasks. On the other hand, images acquired with active sensing techniques based on monochromatic illumination are degraded with speckle noise. Mathematical morphology offers elegant techniques to handle a wide range of image degradation problems. Unlike linear filters, morphological filters do not blur the edges and hence maintain higher image resolution. Their rich mathematical framework facilitates the design and analysis of these filters as well as their hardware implementation. Morphological filters are easier to implement and are more cost effective and efficient than several conventional linear filters. Morphological filters to remove speckle noise while maintaining high resolution and preserving thin image regions that are particularly vulnerable to speckle noise were developed and applied to SAR imagery. These filters used combination of linear (one-dimensional) structuring elements in different (typically four) orientations. Although this approach preserves more details than the simple morphological filters using two-dimensional structuring elements, the limited orientations of one-dimensional elements approximate the fine details of the region boundaries. A more robust filter designed recently overcomes the limitation of the fixed orientations. This filter uses a combination of concave and convex structuring elements. Morphological operators are also useful in extracting features from visible and infrared imagery. A multiresolution image pyramid obtained with successive filtering and a subsampling process aids in the removal of the illumination variations and enhances local contrasts. A morphology-based interpolation scheme was also introduced to reduce intensity discontinuities created in any morphological filtering task. The generality of morphological filtering techniques in extracting information from a wide variety of images obtained with active and passive sensing techniques is discussed. Such techniques are particularly useful in obtaining more information from fusion of complex images by different sensors such as SAR, visible, and infrared.

Kher, A.↗

DOE OSTI2016

Hyperspectral target detection using manifold learning and multiple target spectra

Imagery collected from satellites and airborne platforms provides an important tool for remotely analyzing the content of a scene. In particular, the ability to remotely detect a specific material within a scene is of critical importance in nonproliferation and other applications. The sensor systems that process hyperspectral images collect the high-dimensional spectral information necessary to perform these detection analyses. For a d-dimensional hyperspectral image, however, where d is the number of spectral bands, it is common for the data to inherently occupy an m-dimensional space with m << d. In the remote sensing community, this has led to recent interest in the use of manifold learning, which seeks to characterize the embedded lower-dimensional, nonlinear manifold that the data discretely approximate. The research presented in this paper focuses on a graph theory and manifold learning approach to target detection, using an adaptive version of locally linear embedding that is biased to separate target pixels from background pixels. Finally, this approach incorporates multiple target signatures for a particular material, accounting for the spectral variability that is often present within a solid material of interest.

97 MATHEMATICS AND COMPUTING↗