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At least 1,117 records · Page 62

NASA Tech Briefs, July 2010

Topics covered include: Wirelessly Interrogated Wear or Temperature Sensors; Processing Nanostructured Sensors Using Microfabrication Techniques; Optical Pointing Sensor; Radio-Frequency Tank Eigenmode Sensor for Propellant Quantity Gauging; High-Temperature Optical Sensor; Integral Battery Power Limiting Circuit for Intrinsically Safe Applications; Configurable Multi-Purpose Processor; Squeezing Alters Frequency Tuning of WGM Optical Resonator; Automated Computer Access Request System; Range Safety for an Autonomous Flight Safety System; Fast and Easy Searching of Files in Unisys 2200 Computers; Parachute Drag Model; Evolutionary Scheduler for the Deep Space Network; Modular Habitats Comprising Rigid and Inflatable Modules; More About N2O-Based Propulsion and Breathable-Gas Systems; Ultrasonic/Sonic Rotary-Hammer Drills; Miniature Piezoelectric Shaker for Distribution of Unconsolidated Samples to Instrument Cells; Lunar Soil Particle Separator; Advanced Aerobots for Scientific Exploration; Miniature Bioreactor System for Long-Term Cell Culture; Electrochemical Detection of Multiple Bioprocess Analytes; Fabrication and Modification of Nanoporous Silicon Particles; High-Altitude Hydration System; Photon Counting Using Edge-Detection Algorithm; Holographic Vortex Coronagraph; Optical Structural Health Monitoring Device; Fuel-Cell Power Source Based on Onboard Rocket Propellants; Polar Lunar Regions: Exploiting Natural and Augmented Thermal Environments; Simultaneous Spectral Temporal Adaptive Raman Spectrometer - SSTARS; Improved Speed and Functionality of a 580-GHz Imaging Radar; Bolometric Device Based on Fluxoid Quantization; Algorithms for Learning Preferences for Sets of Objects; Model for Simulating a Spiral Software-Development Process; Algorithm That Synthesizes Other Algorithms for Hashing; Algorithms for High-Speed Noninvasive Eye-Tracking System; and Adapting ASPEN for Orbital Express.

Source record↗

Scalable fabrication of micron-scale graphene nanomeshes for high-performance supercapacitor applications

Graphene nanomeshes (GNMs) with nanoscale periodic or quasi-periodic nanoholes have attracted considerable interest because of unique features such as their open energy band gap, enlarged specific surface area, and high optical transmittance. These features are useful for applications in semiconducting devices, photocatalysis, sensors, and energy-related systems. We report on the facile and scalable preparation of multifunctional micron-scale GNMs with high-density of nanoperforations by catalytic carbon gasification. The catalytic carbon gasification process induces selective decomposition on the graphene adjacent to the metal catalyst, thus forming nanoperforations. Furthermore, the pore size, pore density distribution, and neck size of the GNMs can be controlled by adjusting the size and fraction of the metal oxide on graphene. The fabricated GNM electrodes exhibit superior electrochemical properties for supercapacitor (ultracapacitor) applications, including exceptionally high capacitance (253 F g -1 at 1 A g -1 ) and high rate capability (212 F g -1 at 100 A g -1 ) with excellent cycle stability (91% of the initial capacitance after 50 000 charge/discharge cycles). Moreover, the edge-enriched structure of GNMs plays an important role in achieving edge-selected and high-level nitrogen doping.

25 ENERGY STORAGE↗

Improved edge charge exchange recombination spectroscopy in DIII-D

The charge exchange recombination spectroscopy diagnostic on the DIII-D tokamak has been upgraded with the addition of more high radial resolution view chords near the edge of the plasma ( r/a > 0.8). The additional views are diagnosed with the same number of spectrometers by placing fiber optics side-by-side at the spectrometer entrance with a precise separation that avoids wavelength shifted crosstalk without the use of bandpass filters. The new views improve measurement of edge impurity parameters in steep gradient, H-mode plasmas with many different shapes. The number of edge view chords with 8 mm radial separation has increased from 16 to 38.As a result, new fused silica fibers have improved light throughput and clarify the observation of non-Gaussian spectra that suggest the ion distribution function can be non-Maxwellian in low collisionality plasmas.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Photoelectrochemical Etching of GaN Quantum Wires

For this Exploratory Express LDRD we investigated the use photoelectrochemical etching to demonstrate GaN quantum wires with a diameter of less than 10 nm. Although GaN nanowires with much larger sizes (200 nm – 2 microns) have been demonstrated by a number of techniques, quantum wires are much more difficult to realize due to the very small dimensions (< 10 nm). Previous demonstrations of semiconductor quantum wires have relied on colloidal methods resulting in large size distributions or complicated regrowth on the edge of a cleaved wafer. Here we propose to use photoelectrochemical etching to realize GaN quantum wires. Previously we have been able to show that this technique can be used to make InGaN quantum dots and we propose to use similar methods to realize GaN quantum wires. To our knowledge, GaN quantum wires have never been demonstrated due to growth and fabrication difficulties. Photoelectrochemical etching has also never been used to demonstrate quantum wires in any material system. If our quantum wire fabrication method is successful, it will open up a new research area centered around GaN quantum wires and related applications. Quantum wires can be used as an efficient nanoscale conduit for the transport of charge and energy and will find applications in nanoelectronics, energy harvesting (solar), nanoscale light emitters, and chem/bio sensors.

42 ENGINEERING↗

Radar Measurements of the LEO Orbital Debris Environment

Access to space and the preservation of the near-Earth space environment is of critical significance. Increased interest in issues surrounding space traffic management and the continued assessment and discussion of orbital debris at the United Nations Committee on the Peaceful Uses of Outer Space (COPUOS) illustrates the significance of the topic of orbital debris. There are currently over 20,000 tracked objects in the publicly available satellite catalog on Space-Track.org. The catalog is maintained by the US Air Force Space Command using a network of optical and radar ground-based sensors and is believed to be complete for a characteristic size of 10 cm or larger in low Earth orbit (LEO). Based on the work of the NASA Orbital Debris Program Office (ODPO) over approximately the past 40 years it is understood that the small debris population (< 10 cm) increases by orders of magnitude as characteristic size decreases. With population estimates ranging from 500,000 to 1,000,000 small debris objects (> 5 mm) in orbit, it is currently not practical to track and maintain precision orbits on every object. Instead the NASA ODPO uses powerful ground-based radars to sample the low Earth Orbit (LEO) environment and assign approximate orbits to each detection. This poses an interesting signal processing challenge as we are trying to detect the smallest objects possible on the edge of the radar's sensitivity. For approximately the last 30 years, NASA ODPO has partnered with the Massachusetts Institute of Technology Lincoln Laboratory (MIT/LL) to utilize the Haystack Ultra-wideband Satellite Imaging Radar (HUSIR - formerly the Long-Range Imaging Radar or simply Haystack) and the Haystack Auxiliary (HAX) radar to collect orbital debris radar data. Additionally, the ODPO collaborates with the NASA Jet Propulsion Laboratory (JPL) to use the Goldstone Solar System Radar. The orbital debris detections from these radars serve as inputs for statistical risk models used by the human spaceflight and satellite communities to assess risk to spacecraft posed by orbital debris. In this paper, we will describe the history of orbital debris radar measurements conducted by NASA, provide an overview of current radar measurements techniques and facilities, discuss the signal processing software used for orbital debris measurements and the inference of debris size and orbital parameters from these measurements, and discuss how orbital debris radar measurements are validated for use in models that are used throughout the aerospace industry.

Blackwell, Chris↗

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

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

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

Nitrogen-Doped Graphitic Nanoribbons: Synthesis, Characterization, and Transport

Nitrogen-doped graphitic nanoribbons (N x -GNRs), synthesized by chemical vapor deposition (CVD) using pyrazine as a nitrogen precursor, are reported for the first time. Scanning electron microscopy (SEM) and high-resolution transmission electron microscopy (HRTEM) reveal that the synthesized materials are formed by multilayered corrugated GNRs, which in most cases exhibit the formation of curved graphene edges (loops). This suggests that during growth, nitrogen atoms promote loop formation; undoped GNRs do not form loops at their edges. Transport measurements on individual pure GNRs exhibit a linear I–V (current-voltage) behavior, whereas N x -GNRs show reduced current responses following a semiconducting-like behavior, which becomes more prominent for high nitrogen concentrations. To better understand the experimental findings, electron density of states (DOS), quantum conductance for nitrogen-doped zigzag and armchair single-layer GNRs are calculated for different N doping concentrations using density functional theory (DFT) and non-equilibrium Green functions. These calculations confirm the crucial role of nitrogen atoms in the transport properties, confirming that the nonlinear I–V curves are due to the presence of nitrogen atoms within the N x -GNRs lattice that act as scattering sites. These characteristic N x -GNRs transport properties could be advantageous in the fabrication of electronic devices including sensors in which metal-like undoped GNRs are unsuitable.

Chemistry↗

Development of the sputtering yields of ArF photoresist after the onset of argon ion bombardment

Modification of an advanced ArF excimer lithographic photoresist by 400 eV Ar ion irradiation was observed in situ in real time using both infrared spectroscopy and a quartz microbalance sensor. The photoresist sputtering yields had a characteristic behavior; the sputtering yields were higher than unity at the beginning, until an ion dose of 2 Multiplication-Sign 10{sup 16} ions cm{sup -2}. Thereafter, the yields decreased immediately to almost zero and remained constant with the yield at zero until a dose of approximately 4 Multiplication-Sign 10{sup 16} ions cm{sup -2} was reached. At larger doses, the yields increased again and reached a steady-state value of approximately 0.6. This development of the sputtering yield after the onset of ion bombardment is explained by an ion-induced modification of the photoresist that includes preferential sputtering of individual groups, argon ion implantation and the generation of voids. All these effects must be taken into account to assess line-edge-roughness on a photoresist subjected to highly energetic ion irradiation.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Design and performance of the halogen occultation experiment (HALOE) remote sensor

HALOE is an optical remote sensor that measures extinction of solar radiation caused by the earth's atmosphere in eight channels, ranging in wavelength from 2.5 to 10.1 microns. These measurements, which occur twice each satellite orbit during solar occultation, are inverted to yield vertical distributions of middle atmosphere ozone (O3), water vapor, nitrogen dioxide, nitric oxide, hydrogen fluoride, hydrogen chloride, and methane. A channel located in the 2.7 region is used to infer the tangent point pressure by measuring carbon dioxide absorption. The HALOE instrument consists of a two-axis gimbal system, telescope, spectral discrimination optics and a 12-bit data system. The gimbal system tracks the solar radiometric centroid in the azimuthal plane and tracks the solar limb in the elevation plane, placing the instrument's instantaneous field-of-view 4 arcmin down from the solar top edge. The instrument gathers data for tangent altitudes ranging from 150 km to the earth's horizon. Prior to an orbital sunset and after an orbital sunrise, HALOE automatically performs calibration sequences to enhance data interpretation. The instrument is presently being tested at the NASA Langley Research Center in preparation for launch on the Upper Atmosphere Research Satellite near the end of this decade. This paper describes the instrumenmt design, operation, and functional performance.

Baker, R. L.↗

NASA Sea Ice Validation Program for the Defense Meteorological Satellite Program Special Sensor Microwave Imager

The history of the program is described along with the SSM/I sensor, including its calibration and geolocation correction procedures used by NASA, SSM/I data flow, and the NASA program to distribute polar gridded SSM/I radiances and sea ice concentrations (SIC) on CD-ROMs. Following a discussion of the NASA algorithm used to convert SSM/I radiances to SICs, results of 95 SSM/I-MSS Landsat IC comparisons for regions in both the Arctic and the Antarctic are presented. The Landsat comparisons show that the overall algorithm accuracy under winter conditions is 7 pct. on average with 4 pct. negative bias. Next, high resolution active and passive microwave image mosaics from coordinated NASA and Navy aircraft underflights over regions of the Beaufort and Chukchi seas in March 1988 were used to show that the algorithm multiyear IC accuracy is 11 pct. on average with a positive bias of 12 pct. Ice edge crossings of the Bering Sea by the NASA DC-8 aircraft were used to show that the SSM/I 15 pct. ice concentration contour corresponds best to the location of the initial bands at the ice edge. Finally, a summary of results and recommendations for improving the SIC retrievals from spaceborne radiometers are provided.

Cavalieri, Donald J.↗

Nitrogen-Doped Graphitic Nanoribbons: Synthesis, Characterization and Transport

Nitrogen-doped graphitic nanoribbons (Nx-GNRs), synthesized by chemical vapor deposition (CVD) using pyrazine as a nitrogen precursor, are reported for the first time. Scanning electron microscopy (SEM) and high-resolution transmission electron microscopy (HRTEM) reveal that the synthesized materials are formed by multi-layered corrugated graphitic nanoribbons (GNRs) which in most cases exhibit the formation of curved graphene edges (loops). This suggests that during growth, nitrogen atoms promote loop formation; undoped GNRs do not form loops at their edges. Transport measurements on individual pure carbon GNRs exhibit a linear I-V (current-voltage) behavior, whereas Nx-GNRs show reduced current responses following a semiconducting-like behavior, which becomes more prominent for high nitrogen concentrations. To better understand the experimental findings, electron density of states (DOS), quantum conductance for nitrogen doped zigzag and armchair single-layer GNRs are calculated for different N doping concentrations using Density Functional Theory (DFT) and non-equilibrium Green functions. These calculations confirm the crucial role of nitrogen atoms in the transport properties, confirming that the nonlinear I-V curves are due to the presence of nitrogen atoms within the Nx-GNRs lattice that act as scattering sites. These characteristic Nx-GNRs transport could be advantageous in the fabrication of electronic devices including sensors in which metal-like undoped GNRs are unsuitable.

Jia, Xiaoting↗

Anomaly analysis and visualization for dynamic networks through spatiotemporal graph segmentations

With recent technology advance in Internet of Things (IoT) that involves human, sensors, and mobile devices, networks are not only growing much larger but more complex and dynamic in nature. The spatiotemporal dynamics of networks are represented by both topological changes and temporal shifts of attribute information associated with network components. Understanding the pattern and trend of dynamic networks is increasingly important. While data mining approaches are generally useful in analyzing the statistical properties of networks, there has been recent trend to consider bringing human into the loop, and to examine how feedback from visualizations of large-scale dynamic networks can further improve data mining and machine learning. Traditional visualization methods based on animation and sequences of snapshot graphs are also limited by human cognitive capability. Here, we present a dynamic network analysis and visualization (DNAV) tool which explores the spatiotemporal dimensions of graph components. In particular, nodes and edges are augmented with spatiotemporal segmentation based on both topological and attribute dynamics (e.g., time and locations of connectivity). To further facilitate analysis of large dynamic networks, DNAV includes statistical dynamic overviews alongside graph views, as well as data filtering modules for scalable analysis. Using case studies on public datasets, we demonstrate the effectiveness of DNAV in understanding and analyzing anomalies in dynamic networks such as computer communication networks.

97 MATHEMATICS AND COMPUTING↗

Radial resolution enhancement of the NSTX Thomson scattering diagnostic

Current magnetic confinement plasma physics research has increased the demand for radial resolution in profile diagnostics, in particular in the edge and pedestal regions. On NSTX, an upgrade of the existing multi-point Thomson scattering diagnostic has been implemented in order to respond to the research program needs. Twelve new radial channels have been added bringing the total number of positions to 42. Four previously un-instrumented fiber bundles were put in service. Eight existing 'active' fiber bundles were divided in two sub-bundles each in order to increase spatial resolution. Twelve radial channels now cover the pedestal region with a resolution near one centimeter. Fifteen radial channels cover the core and internal transport barrier regions. Two additional channels were added, one near the inner edge and one in the outer scrape-off layer. The intersection of the focused viewing optics field of view with a finite-width laser beam results in major-radius cross talk between adjacent fiber sub-bundles. A discussion and calculation of the cross talk will be presented.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Diagnostics: Chapter 8 of the special issue: on the path to tokamak burning plasma operation

This chapter presents the activity conducted by the ITPA topical group (TG) on Diagnostics over about the last 15 years. Following a general introduction of the ITER Diagnostics led by their measurement roles, the document is organized in several subchapters detailing the design support, research and development activity conducted by each of the specialist working groups (WGs) of the TG. Please note that the magnetic diagnostics were supported at the TG without a specific WG. Their status is included in the general introduction. In the following some highlights of the subchapter’s contents are provided. Recent advances in ITER first wall (FW) diagnostics for the measurements of plasma-metallic wall interaction in support of the ITER research plan are reported. An InfraRed imaging Video Bolometer for ITER has been developed and tested on several tokamaks to measure the radiated power loss. A laser-induced breakdown spectroscopy (LIBS) technique which utilizes a pulsed laser beam to ablate locally by forming a crater, will measure local tritium inventory in the FW material. Real-time Residual Gas Analyzers will measure the neutral gas composition in a divertor port and an equatorial port during plasma operation. Due to the full metallic FW environment, the plasma-wall interaction in ITER will face several challenges such as the compromised radiated power and divertor heat flux measurements by reflection. Ray tracing and analysis codes have been developed to eliminate and correct the effects of reflection in the measurements. The characteristics of the reflecting surfaces depending on the roughness and angle of the incidence have been measured by dedicated experiments, and the results were applied to the reflection elimination. For the measurement of the metallic impurity radiation induced by eroded metallic atoms, a vacuum ultraviolet spectrometer has been developed and tested. An extensive thermonuclear diagnostic suite will be required to support the operation of ITER and the planned experimental program for future burning plasma experiments. Due to the harsh environmental conditions, the implementation of diagnostic systems in ITER is a major challenge. These conditions include high levels of neutron and gamma fluxes, neutron heating, particle bombardment. Therefore, the selection and design of diagnostic systems must take into account a number of phenomena previously unseen in diagnostic design. For this reason, the measurement of neutrons and confined or lost fast ions, with particular emphasis on alpha particles, is critical to ITER. The diagnostics associated with these measurements will be important for future plasma-burning experiments at ITER. The high neutron emission and very large plasma size in ITER make neutron diagnostics the main diagnostic method used to measure plasma parameters such as fusion power, fusion power density, ion temperature, energy of fast ions and their spatial distributions in the plasma core. Active spectroscopy techniques are methods where a neutral particle beam is injected into the plasma and information on plasma parameters is extracted from the measurement of line emission resulting from the beam-plasma interaction, either by plasma ions or by beam atoms. Spatial localization is achieved by crossing the beamline and multiple observation lines. The ITER plasma will be a high temperature, moderately dense, fully ionized collisional plasma. The plasma facing surfaces are principally metallic being fashioned from beryllium or tungsten but many other elements, arising from either structural or from operational needs, may enter this plasma. The energy range of the emitted photons range from meV (infra-red) to multi keV (x-rays) and originate from all areas of the plasma volume. The primary role of passive emission diagnostics is to identify what is in the plasma from spectral signatures. Extracting quantitative information from these measurements such as impurity content, ion temperature, rotation, degree of detachment and radiated power depends on calibrated instruments, a physics model of the atomic and molecular processes and plasma transport and an analysis workflow that takes into account environmental effects such as reflections. The particular needs for ITER have prompted a multi-machine, many-year effort to address all these aspects and this chapter reviews the work on diagnostic design, experiments and new analysis techniques. An overview of the laser diagnostics to be implemented on ITER is also provided in this paper. This includes descriptions of the Thomson scattering in the core, edge and divertor regions, polarimetry and interferometry diagnostics used for measuring plasma density and also measurements of helium density in the divertor using Laser Induced Flourescence. Techniques which can allow improvements on current measurements are also addressed in particular expanding poloidal polarimetry measurements to measure field fluctuations and proposed use of dispersion interferometery which has a number of advantages over existing methods. This paper identifies particular areas where further research and testing on existing tokamaks is useful even at this advanced stage to inform the design of diagnostics for ITER. Outstanding areas of concern for the implementation of laser diagnostics, in particular with a view to reliable operation are identified. An overview of the latest developments of microwave diagnostic systems and techniques is given. The primary focus is the contributions for ITER—the next step burning plasma experiment—which is supplemented by describing recent progress of techniques applicable for fusion experiments beyond ITER. The contributions are intentionally kept concise, and are being supplemented by a rich list of references for further studies. Radiation induced effects are receiving continuous and well-deserved attention of the ITER diagnostic community and they are in many cases one of the primary design drivers of the ITER diagnostic systems. The paper summarizes recent progress in this area focusing primarily on the ITER diagnostics but in some cases provides also outlook for the possible solutions for even more demanding radiation environment of fusion reactors beyond ITER. Despite advancements in the area of modeling and simulation of various radiation induced effects, experimental testing in a nuclear environment as close as possible to the target one is still seen as unavoidable for proper qualification of particular diagnostic functional elements. Recent advancement within three diagnostic areas: optical diagnostics, magnetics and bolometers is covered. Encouraging results on qualification of silica glass vacuum window assemblies are presented. In the area of magnetic sensors, progress of irradiation tests performed on ITER in-vessel LTCC inductive sensors is presented with outlook for novel technological approaches to inductive sensors utilizing thick printing and photolithography technologies being highlighted. Summary of advancements in the area of steady state magnetic field sensors based on Hall effect is given. New results of neutron irradiation test of the ITER borosilicate glass inserts for vacuum electrical feedthroughs are summarized finding negligible swelling at target level of neutron fluence. Off-line irradiation tests of fiber optic current sensors for plasma current measurement demonstrated that both for gamma doses up to 5 MGy and a total neutron fluence up to 10 15 cm −2 , radiation induced changes are still compatible with required measurement accuracy on ITER. The ITER bolometers are given as an example how considering radiation effects may influence the diagnostic design. Finally, outlook for future main R&D directions is outlined. All optical and laser-based diagnostics in ITER will be using mirrors to guide plasma radiation toward detectors, cameras and sensors. In the hostile plasma, radiation and particle environment the optical characteristics of diagnostic mirrors will degrade directly affecting the entire performance of involved diagnostic systems. An assessment of factors affecting mirror performance is provided. Among the prime adverse factors are deposition of plasma impurities, sputtering of mirror surface and steam ingress in the vicinity of mirrors. Within the International Tokamak Physics Activity with active support by ITER central team and domestic agencies, the structured research and development (R&D) program on mitigation of risks for diagnostic mirrors is underway. Within this program the mirror material development, the passive mitigation of mirror degradation by using diagnostic ducts and shutters along with an active mirror recovery program comprising the in-situ mirror cleaning and calibration is underway. Recent developments in diagnostic mirror R&D are described in this Chapter along with an example of their implementation of R&D solutions in ITER Infrared Thermography diagnostic. An assessment of still open engineering and physics questions, considerations on mirror risks during an early phase of ITER operation are given along with an overview of diagnostic mirror evolution in the late ITER operation stage toward the demonstration fusion power plant. Several crucial areas of diagnostic R&D outlined in ITER Research Plan are addressed. The basic control groups in a fusion reactor can be broken-down in five categories: (1) plasma position, magnetic configuration, and plasma current control, (2) profile control and confinement optimization, (3) MHD control and suppression, (4) edge dissipation control, radiation and plasma exhaust control and (5) break-down optimization. These categories are coupled via the physics (a control action in one domain will affect the other domains) and via shared actuators (e.g. ECRH for impurity accumulation avoidance, current density distribution control and MHD suppression). Consequently, a supervisory control system should determine the priority of the various control tasks, their couplings, and the interfaces with the safety and interlock system. For the systematic development of the various controllers taking the complexity of the plasma and the control system into account, a model-based approach is required. A short historical overview is given of the developments in systems and control theory and control engineering with special emphasis on those developments that are most relevant for Nuclear Fusion research and operation. An overview is given of the state of the field of fusion plasma control for the control categories. It will be shown how synthetic diagnostics are being developed in ITER and how they are used in diagnostic design and design validation and how they can be in model-based controller synthesis using relatively simple models. In modern control methods, multiple diagnostics are used to constrain relatively simple models. The constrained models provide an estimate for the state. This opens the route to state controllers, such as model predictive control. A major challenge in nuclear fusion research is the coherent combination of data from heterogeneous diagnostics and modeling codes for machine control and safety as well as physics studies. Measured data from different diagnostics often provide information about the same subset of physical parameters. Additionally, information provided by some diagnostics might be needed for the analysis of other diagnostics. A joint analysis of complementary and redundant data allows, e.g. to improve the reliability of parameter estimation, to increase the spatial and temporal resolution of profiles, to obtain synergistic effects, to consider diagnostics interdependencies and to find and resolve data inconsistencies. Physics-based modeling and parameter relationships provide additional information improving the treatment of ill-posed inversion problems. A coherent combination of all kind of available information within a probabilistic framework allows for improved data analysis results. The concept of integrated data analysis (IDA) in the framework of Bayesian probability theory is outlined and contrasted with conventional data analysis. Components of the probabilistic approach are summarized and specific ingredients beneficial for data analysis at fusion devices are discussed.

ITER↗

Long term microparticle impact fluxes on LDEF determined from optical survey of Interplanetary Dust Experiment (IDE) sensors

Many of the IDE metal-oxide-silicon (MOS) capacitor-discharge impact sensors remained active during the entire Long Duration Exposure Facility (LDEF) mission. An optical survey of impact sites on the active surfaces of these sensors has been extended to include all sensors from the low-flux sides of LDEF (i.e. the west or trailing side, the earth end, and the space end) and 5-7 active sensors from each LDEF's high-flux sides (i.e. the east or leading side, the south side, and the north side). This survey was facilitated by the presence of a relatively large (greater than 50 micron diameter) optical signature associated with each impact site on the active sensor surfaces. Of the approximately 4700 impacts in the optical survey data set, 84% were from particles in the 0.5 to 3 micron size range. An estimate of the total number of hypervelocity impacts on LDEF from particles greater than 0.5 micron diameter yields a value of approximately 7 x 10(exp 6). Impact feature dimensions for several dozen large craters on MOS sensors and germanium witness plates are also presented. Impact fluxes calculated from the IDE survey data closely matched surveys of similar size impacts (greater than or equal to 3 micron diameter craters in Al, or marginal penetrations of a 2.4 micron thick Al foil) by other LDEF investigators. Since the first year IDE data were electronically recorded, the flux data could be divided into three long term time periods: the first year, the entire 5.8 year mission, and the intervening 4.8 years (by difference). The IDE data show that there was an order of magnitude decrease in the long term microparticle impact flux on the trailing side of LDEF, from 1.01 to 0.098 x 10(exp -4) m(exp 2)/s, from the first year in orbit compared to years 2-6. The long term flux on the leading edge showed an increase from 8.6 to 11.2 x 10(exp -4) m(exp -2)/s over this same time period. (Short term flux increases up to 10,000 times the background rate were recorded on the leading side during LDEF's first year in orbit.) The overall east/west ratio was 44, but during LDEF's first year in orbit the ratio was 8.5, and during years 2-6 the ratio was 114. Long term microparticle impact fluxes on the space end decreased from 1.12 to 0.55 x 10(exp -4) m(exp -2)/s from the first year in orbit compared to years 2-6. The earth end showed the opposite trend with an increase from 0.16 to 0.38 x 10(exp -4) m(exp -2)/s. Fluxes on rows 6 and 12 decreased from 6.1 to 3.4 and 6.7 to 3.7 x 10(exp -4) m(exp -2)/s, respectively, over the same time periods. This resulted in space/earth microparticle impact flux ratios of 7.1 during the first year and 1.5 during years 2-6, while the south/north, space/north and space/south ratios remained constant at 1.1, 0.16 and 0.17, respectively, during the entire mission. This information indicates the possible identification of long term changes in discrete microparticle orbital debris component contributions to the total impact flux experienced by LDEF. A dramatic decrease in the debris population capable of striking the trailing side was detected that could possibly be attributed to the hiatus of western launch activity experienced from 1986-1989. A significant increase in the debris population that preferentially struck the leading side was also observed and could possibly be attributed to a single breakup event that occurred in September of 1986. A substantial increase in the microparticle debris population that struck the earth end of LDEF, but not the space end, was also detected and could possibly be the result of a single breakup event at low altitude. These results point to the importance of including discrete orbital debris component contribution changes in flux models in order to achieve accurate predictions of the microparticle environment that a particular spacecraft will experience in earth orbit. The only reliable, verified empirical measurements of these changes are reported in this paper. Further time-resolved in-situ measurements of these debris populations are needed to accurately assess model predictions and mitigation practices.

Simon, C. G.↗

NeuroCoreX: An Open-Source FPGA-Based Spiking Neural Network Emulator with On-Chip Learning

Spiking Neural Networks (SNNs) are computational models inspired by the event-driven communication and connectivity patterns of biological neural circuits. They enable high energy efficiency and natural support for diverse architectures ranging from layered networks to small-world and graphstructured topologies. In this work, we introduce NeuroCoreX, an open-source, FPGA-based spiking neural network emulator that provides real-time, on-chip learning and flexible network organization. NeuroCoreX supports both feedforward sensory inputs streamed directly from sensors or PCs via UART and recurrent on-chip connectivity, enabling simultaneous processing and learning from external stimuli and internal network dynamics-capabilities rarely available in existing FPGA SNN platforms. The system implements a Leaky Integrate-and-Fire (LIF) neuron model with current-based synapses and supports pair-based STDP learning on both feedforward and recurrent synapses. A lightweight Python interface enables interactive configuration, live monitoring, weight read-back, and experiment control. Importantly, NeuroCoreX is tightly integrated with the SuperNeuroMAT simulator, allowing SNN models to be transferred seamlessly from software to hardware for hardware-in-the-loop development. By combining real-time plasticity, flexible connectivity, and an open-source VHDL implementation, NeuroCoreX provides an extensible and accessible platform for neuromorphic research, algorithm-hardware co-design, and energy-efficient edge intelligence.

Gautam, Ashish [ORNL]↗

Less is More: Bigger Data from Compressive Measurements

Compressive sensing approaches are beginning to take hold in (scanning) transmission electron microscopy (S/TEM) [1,2,3]. Compressive sensing is a mathematical theory about acquiring signals in a compressed form (measurements) and the probability of recovering the original signal by solving an inverse problem [4]. The inverse problem is underdetermined (more unknowns than measurements), so it is not obvious that recovery is possible. Compression is achieved by taking inner products of the signal with measurement weight vectors. Both Gaussian random weights and Bernoulli (0,1) random weights form a large class of measurement vectors for which recovery is possible. The measurements can also be designed through an optimization process. The key insight for electron microscopists is that compressive sensing can be used to increase acquisition speed and reduce dose. Building on work initially developed for optical cameras, this new paradigm will allow electron microscopists to solve more problems in the engineering and life sciences. We will be collecting orders of magnitude more data than previously possible. The reason that we will have more data is because we will have increased temporal/spatial/spectral sampling rates, and we will be able ability to interrogate larger classes of samples that were previously too beam sensitive to survive the experiment. For example consider an in-situ experiment that takes 1 minute. With traditional sensing, we might collect 5 images per second for a total of 300 images. With compressive sensing, each of those 300 images can be expanded into 10 more images, making the collection rate 50 images per second, and the decompressed data a total of 3000 images [3]. But, what are the implications, in terms of data, for this new methodology? Acquisition of compressed data will require downstream reconstruction to be useful. The reconstructed data will be much larger than traditional data, we will need space to store the reconstructions during analysis, and the computational demands for analysis will be higher. Moreover, there will be time costs associated with reconstruction. Deep learning [5] is an approach to address these problems. Deep learning is a hierarchical approach to find useful (for a particular task) representations of data. Each layer of the hierarchy is intended to represent higher levels of abstraction. For example, a deep model of faces might have sinusoids, edges and gradients in the first layer; eyes, noses, and mouths in the second layer, and faces in the third layer. There has been significant effort recently in deep learning algorithms for tasks beyond image classification such as compressive reconstruction [6] and image segmentation [7]. A drawback of deep learning, however, is that training the model requires large datasets and dedicated computational resources (to reduce training time to a few days). A second issue is that deep learning is not user-friendly and the meaning behind the results is usually not interpretable. We have shown it is possible to reduce the data set size while maintaining model quality [8] and developed interpretable models for image classification [9], but the demands are still significant. The key to addressing these problems is to NOT reconstruct the data. Instead, we should design computational sensors that give answers to specific problems. A simple version of this idea is compressive classification [10], where the goal is to classify signal type from a small number of compressed measurements. Classification is a much simpler problem than reconstruction, so 1) much fewer measurements will be necessary, and 2) these measurements will probably not be useful for reconstruction. Other simple examples of computational sensing include determining object volume or the number of objects present in the field of view [11].

Stevens, Andrew↗

Determination of an angle of attack sensor correction for a general aviation airplane at large angles of attack as determined from wind tunnel and flight tests

A comprehensive investigation into the flow correction for an angle of attack sensor mounted ahead of the wing tip of a general aviation research airplane has been conducted at the Langley Research Center. This correction has been determined in wind tunnels using a full-scale model up to angles of attack of 45 deg and a 1/5-scale model up to 80 deg angle of attack. The flow correction has also been obtained in flight by using a standard technique at low angles of attack and in spinning flight at larger angles of attack, by using both a simple approximate technique and a parameter estimation technique. The results show the correction is significant, reaching 10 deg at a measured angle of attack of about 90 deg. The flow correction was sensitive to the angle of sideslip at measured angles of attack greater than 60 deg and was not influenced by wing leading-edge modifications or aileron deflections.

Moul, T. M.↗