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At least 451 records · Page 25

Risk-Aware Measurement Synchronization and Recovery for DSSE With Heterogeneous Data Sources

Power distribution systems are increasingly integrating heterogeneous sensors with varying data reporting rates and types, which pose challenges to achieving observability at the desired temporal resolution of distribution system state estimation (DSSE). Multisensor failures caused by extreme events exacerbate these issues, introducing substantial uncertainties into DSSE. This article proposes a novel solution to these challenges by ensuring high-resolution system observability despite heterogeneous data sources and multisensor failures. First, a deep learning architecture combining long short-term memory (LSTM) and graph convolutional network (GCN) is employed to synchronize meters with different reporting rates, aiming to achieve system observability. A random-walk-model-based approach is introduced to generate pseudo-measurements while properly characterizing their uncertainties under multisensor failures. Finally, a disaster-risk-informed observability metric (RiOM) is defined to quantify the uncertainty associated with state estimation results. The proposed framework offers deeper insights into the system observability on the fly compared with conventional analysis. The effectiveness of the framework is demonstrated on an IEEE standard test case and a large-scale real-world distribution feeder in mid-Minnesota in the U.S.

97 MATHEMATICS AND COMPUTING↗

3D-CHESS: Decentralized, Distributed, Dynamic, and Context-aware Heterogeneous Sensor Systems

This paper describes the objectives and current status of the 3D-CHESS project which aims to demonstrate a new Earth observing strategy based on a context-aware Earth observing sensor web. This sensor web consists of a set of nodes with a knowledge base, heterogeneous sensors, edge computing, and autonomous decision-making capabilities. Context awareness is defined as the ability for the nodes to gather, exchange, and leverage contextual information (e.g., state of the Earth system, state and capabilities of itself and of other nodes in the network, and how those states relate to the dy- namic mission objectives) to improve decision making and planning. The current goal of the project is to demonstrate proof of concept by comparing the performance of a 3D- CHESS sensor web with that of status quo architectures in the context of a multi-sensor inland hydrologic and ecologic monitoring system.

David, Cedric H.↗

TECHEDSAT-7 and 10: The Little Spacecraft That Could

The NOW (Nanosatellite Orbital Workshop) of NASA Ames Research Center (ARC) has two cubesats in orbit at this time: 6 U TechEdSat-10 (T-10) and the 3U TechEdSat-7 (T-7). T10 was jettisoned from the ISS via the NANORACKS system 7/13/2020, and T-7 was launched via Virgin Orbit 1/17/2021. Both were built by the Nano-satellite Orbital Workshop (NOW) at NASA ARC, and designed and fabricated by interns and students in collaboration with educational institutions. Prototyping novel technologies for non-powered re-entry and communications from orbit are primary research interests, however all subsystems including power generation and distribution, subsystem control, navigation, positioning, heat management etc. extend current technologies. Use of distributed processors using open software platforms and standards other based technologies and software is integral to all segments of spacecraft design. Here, we will present an overview of the spacecraft, experiments, and accomplishments – as well as the next three flight experiments. Some of these experiments include: The exo-brake re-entry system is being developed to enable sample return and end of life disposal; Internal communications for sensors, inter-subsystem and experiments uses both a Zigbee based PAN and internal Wi-Fi for high-speed inter-device communications; The Iridium small message LEO system (Short Burst Data) is used to both command the spacecraft and send data to the ground; Experimental use of the Global-Star system for L-band system comparison and back-up; Collaborative NOAA an experiment to communicate from LEO to the GOES geostationary satellite using the DCS (Data Collection System) with on-board Doppler correction; Mars and Lunar experimental communication systems for future cis-lunar and interplanetary nano-satellites; First demonstration of the NASA Near Earth Network systems with nano-satellites at NASA/Wallops Island; Solar array design and implementation for unique future flexible structures; Power distribution using Tardigrade rad-hard processor omni-board (designed by the team); Distributed processors with internal Wi-Fi connectivity; and Initial experiments with AI/Machine Learning.

M Murbach↗

Distribution System State Estimation in the Presence of High Solar Penetration

In recent years, the low-to-medium voltage distribution networks are experiencing rising levels of distributed energy resources, including renewable generation, along with improved sensing, communication and automation infrastructure. As such, state estimation methods for distribution systems are becoming increasingly relevant as a means to enable better control strategies that can both leverage the benefits and mitigate the risks associated with high penetration of variable and uncertain distributed generation resources. Primary challenges of this problem include modeling complexities (nonlinear non-convex power-flow equations), limited availability of sensor measurements, and high penetration of uncertain renewable generation. This paper formulates the distribution system state estimation as a nonlinear weighted least squares problem, based on sensor measurements as well as forecasts data (both load and generation). We investigate the sensitivity of state estimator accuracy to (load/generation) forecast uncertainties, sensor accuracy, and sensor coverage levels.

Distribution system state estimation, nonlinear op↗

Asynchronous interactive control systems

A class of interactive control systems is derived by generalizing interactive manipulator control systems. The general structural properties of such systems are discussed and an appropriate general software implementation is proposed. This is based on the fact that tasks of interactive control systems can be represented as a network of a finite set of actions which have specific operational characteristics and specific resource requirements, and which are of limited duration. This has enabled the decomposition of the overall control algorithm into a set of subalgorithms, called subcontrollers, which can operate simultaneously and asynchronously. Coordinate transformations of sensor feedback data and actuator set-points have enabled the further simplification of the subcontrollers and have reduced their conflicting resource requirements. The modules of the decomposed control system are implemented as parallel processes with disjoint memory space communicating only by I/O. The synchronization mechanisms for dynamic resource allocation among subcontrollers and other synchronization mechanisms are also discussed in this paper. Such a software organization is suitable for the general form of multiprocessing using computer networks with distributed storage.

Vuskovic, M. I.↗

Use of 2d-video Disdrometer to Derive Mean Density-size and Ze-SR Relations: Four Snow Cases from the Light Precipitation Validation Experiment

The application of the 2D-video disdrometer to measure fall speed and snow size distribution and to derive liquid equivalent snow rate, mean density-size and reflectivity-snow rate power law is described. Inversion of the methodology proposed by Böhm provides the pathway to use measured fall speed, area ratio and '3D' size measurement to estimate the mass of each particle. Four snow cases from the Light Precipitation Validation Experiment are analyzed with supporting data from other instruments such as Precipitation Occurrence Sensor System (POSS), Snow Video Imager (SVI), a network of seven snow gauges and three scanning C9 band radars. The radar-based snow accumulations using the 2DVD-derived Ze-SR relation are in good agreement with a network of seven snow gauges and outperform the accumulations derived from a climatological Ze-SR relation used by the Finnish Meteorological Institute (FMI). The normalized bias between radar-derived and gauge accumulation is reduced from 96% when using the fixed FMI relation to 28% when using the Ze-SR relations based on 2DVD data. The normalized standard error is also reduced significantly from 66% to 31%. For two of the days with widely different coefficients of the Ze-SR power law, the reflectivity structure showed significant differences in spatial variability. Liquid water path estimates from radiometric data also showed significant differences between the two cases. Examination of SVI particle images at the measurement site corroborated these differences in terms of unrimed versus rimed snow particles. The findings reported herein support the application of Böhm's methodology for deriving the mean density-size and Ze-SR power laws using data from 2D-video disdrometer.

radar↗

NASA Tech Briefs, January 2012

Contents of this issue are: (1) Energy-Based Tetrahedron Sensor for High-Temperature, High-Pressure Environments (2) Handheld Universal Diagnostic Sensor (3) Large-Area Vacuum Ultraviolet Sensors (4) Fiber Bragg Grating Sensor System for Monitoring Smart Composite Aerospace Structures (5) Health-Enabled Smart Sensor Fusion Technology (6) Extended-Range Passive RFID and Sensor Tags (7) Hybrid Collaborative Learning for Classification and Clustering in Sensor Networks (8) Self-Healing, Inflatable, Rigidizable Shelter (9) Improvements in Cold-Plate Fabrication (10) Technique for Radiometer and Antenna Array Calibration - TRAAC (11) Real-Time Cognitive Computing Architecture for Data Fusion in a Dynamic Environment (12) Programmable Digital Controller (13) Use of CCSDS Packets Over SpaceWire to Control Hardware (14) Key Decision Record Creation and Approval Module (15) Enhanced Graphics for Extended Scale Range (16) Debris Examination Using Ballistic and Radar Integrated Software (17) Data Distribution System (DDS) and Solar Dynamic Observatory Ground Station (SDOGS) (18) Integration Manager (19) Eclipse-Free-Time Assessment Tool for IRIS (20) Automated and Manual Rocket Crater Measurement Software (21) MATLAB Stability and Control Toolbox Trim and Static Stability Module (22) Patched Conic Trajectory Code (23) Ring Image Analyzer (24) SureTrak Probability of Impact Display (25) Implementation of a Non-Metallic Barrier in an Electric Motor (26) Multi-Mission Radioisotope Thermoelectric Generator Heat Exchangers for the Mars Science Laboratory Rover (27) Uniform Dust Distributor for Testing Radiative Emittance of Dust-Coated Surfaces (28) MicroProbe Small Unmanned Aerial System (29) Highly Stable and Active Catalyst for Sabatier Reactions (30) Better Proton-Conducting Polymers for Fuel-Cell Membranes (31) CCD Camera Lens Interface for Real-Time Theodolite Alignment (32) Peregrine 100-km Sounding Rocket Project (33) SOFIA Closed- and Open-Door Aerodynamic Analyses (34) Sonic Thermometer for High-Altitude Balloons (35) Near-Infrared Photon-Counting Camera for High-Sensitivity Observations (36) Integrated Optics Achromatic Nuller for Stellar Interferometry (37) High-Speed Digital Interferometry (38) Ultra-Miniature Lidar Scanner for Launch Range Data Collection (39) Shape and Color Features for Object Recognition Search (40) Explanation Capabilities for Behavior-Based Robot Control (41) A DNA-Inspired Encryption Methodology for Secure, Mobile Ad Hoc Networks (42) Quality Control Method for a Micro-Nano-Channel Microfabricated Device (43) Corner-Cube Retroreflector Instrument for Advanced Lunar Laser Ranging (44) Electrospray Collection of Lunar Dust (45) Fabrication of a Kilopixel Array of Superconducting Microcalorimeters with Microstripline Wiring Spacecraft Attitude Tracking and Maneuver Using Combined Magnetic Actuators (46) Coherent Detector for Near-Angle Scattering and Polarization Characterization of Telescope Mirror Coatings

Source record↗

NEON AOP Survey of Upper East River CO Watersheds: Waveform LiDAR Binary Data

The waveform Light Detection and Ranging (LiDAR) data in this package were generated through a National Ecological Observatory Network Airborne Observation Platform (NEON AOP) acquisition over watersheds of interest surrounding Crested Butte, Colorado. The remote sensing imagery acquired by the NEON AOP supports an interdisciplinary project on hydrology, biogeochemistry, and ecosystem functioning in a snow-dominated headwater environment. These waveform LiDAR data enable spatially continuous estimation of vegetation structure parameters to facilitate analyses of the major environmental drivers of structural and compositional variability. The package contains 97 compressed file archives in 7-zip (.7z) format, each corresponding to one acquisition flightpath. Within each .7z archive is a set of constituent files describing properties of the LiDAR waveforms, such as return intensity, geolocation, outgoing pulse and other behavior of the sensor and signals. Once downloaded, the files must first be unzipped using the widely distributed command-line software utility 7z, using the command '7z x \[filename\].7z \[target_directory\]'. All files within the .7z archives can be opened in IDL, MatLab, or the open-source R statistical computing environment. Further details about the data package are in the attached user guide (neon_aop_crbu_waveformlidar_userguide.pdf). This work was supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231.

2018 NEON and 2025 CHESS Campaigns↗

A recyclable self-healing composite with advanced sensing property

Polymer-based composites frequently encounter damage, often lurking beneath the surface and proving challenges to their early detection and repair. While material-based sensors show promise for encoding self-sensing properties within these composites, their in situ healing and reprocessability remain significant challenges. Therefore, the overarching goal of this study is the creation of a reprocessable polymeric composite encoded with self-healing attributes and the ability to autonomously sense damage. At the core of this innovation are vitrimers, a polymeric material characterized by a covalently adaptive dynamic network responsive to external factors such as heat. They combine thermoset-like resilience with thermoplastic-like flowability on demand under external stimuli. We nanoengineer a polyester-based vitrimeric polymer by incorporating piezoresistive carbon nanotubes (CNTs) as reinforcing elements that not only enhance its mechanical strength but also create a percolation network within the composite, thereby enabling piezoresistive self-sensing properties, all the while preserving the intrinsic self-healing capabilities offered by the vitrimeric matrix. The fabrication process of the composite involves a solvent-free in situ polymerization method that combines epoxy and anhydride-containing monomers with ~ 0.1 wt.% of CNTs. Once it was established that the introduction of CNTs into the polymeric matrix did not compromise the mechanical properties of the composite, their strain-sensing properties were characterized by applying cyclic loading while measuring their electrical resistance. Strikingly, CNT-enhanced vitrimer composite consistently retains its mechanical and sensing properties through repeated cycles of reshaping and reprocessing, underscoring its potential as a robust distributed strain sensor. This polyester-based vitrimeric composite is also easily recyclable without harsh chemical treatments. Preliminary findings from this study conclusively demonstrate that the bulk composite boasts both self-sensing capabilities and in situ detect healing properties, charting a promising course towards the development of a mechanically resilient multifunctional composite that seamlessly integrates selfsensing and healing capabilities.

Rohewal, Sargun Singh↗

Real-Time Wireless Data Acquisition System

Current and future aerospace requirements demand the creation of a new breed of sensing devices, with emphasis on reduced weight, power consumption, and physical size. This new generation of sensors must possess a high degree of intelligence to provide critical data efficiently and in real-time. Intelligence will include self-calibration, self-health assessment, and pre-processing of raw data at the sensor level. Most of these features are already incorporated in the Wireless Sensors Network (SensorNet(TradeMark)), developed by the Instrumentation Group at Kennedy Space Center (KSC). A system based on the SensorNet(TradeMark) architecture consists of data collection point(s) called Central Stations (CS) and intelligent sensors called Remote Stations (RS) where one or more CSs can be accommodated depending on the specific application. The CS's major function is to establish communications with the Remote Stations and to poll each RS for data and health information. The CS also collects, stores and distributes these data to the appropriate systems requiring the information. The system has the ability to perform point-to-point, multi-point and relay mode communications with an autonomous self-diagnosis of each communications link. Upon detection of a communication failure, the system automatically reconfigures to establish new communication paths. These communication paths are automatically and autonomously selected as the best paths by the system based on the existing operating environment. The data acquisition system currently under development at KSC consists of the SensorNet(TradeMark) wireless sensors as the remote stations and the central station called the Radio Frequency Health Node (RFHN). The RFF1N is the central station which remotely communicates with the SensorNet(TradeMark) sensors to control them and to receive data. The system's salient feature is the ability to provide deterministic sensor data with accurate time stamps for both time critical and non-time critical applications. Current wireless standards such as Zigbee(TradeMark) and Bluetooth(Registered TradeMark) do not have these capabilities and can not meet the needs that are provided by the SensorNet technology. Additionally, the system has the ability to automatically reconfigure the wireless communication link to a secondary frequency if interference is encountered and can autonomously search for a sensor that was perceived to be lost using the relay capabilities of the sensors and the secondary frequency. The RFHN and the SensorNet designs are based on modular architectures that allow for future increases in capability and the ability to expand or upgrade with relative ease. The RFHN and SensorNet sensors .can also perform data processing which forms a distributed processing architecture allowing the system to pass along information rather than just sending "raw data points" to the next higher level system. With a relatively small size, weight and power consumption, this system has the potential for both spacecraft and aircraft applications as well as ground applications that require time critical data.

Valencia, Emilio J.↗

Science Rationale for a Micro-Met Mission to Augment InterMarsNet

The 2003 opportunity has the potential to carry out for the first time in Mars exploration history, coordinated measurements from the surface and from orbit that can address fundamental issues associated with the Martian global circulation and climate system. Coordinated measurements are defined here to mean collecting meteorological data from a network of 12-16 globally distributed surface stations simultaneously with an orbiter carrying an atmospheric sounder. With such measurements it is possible to define the horizontally varying (barotropic) and vertically varying (baroclinic) components of the global circulation from which the full 3-dimensional horizontal wind field can be reconstructed. It is also possible to precisely define the CO2 cycle, the main component of the current climate system. InterMarsNet, as currently envisioned, consists of 3-4 landers with a supporting communications orbiter that may carry some instrumentation. The landers are likely to touch down in low latitudes and will probably be configured to optimize seismological objectives. We propose to augment the InterMarsNet meteorological objectives by flying an additional 10-15 "MicroMet" landers equipped to measure surface pressure and nothing else. Surface pressure is the most fundamental meteorological parameter and it is the easiest to measure. The sensors are light, operate with minimal power, and do not require orientation or deployment. Consequently the landers can be very small (< 10 kg) and 10-15 of them can be delivered by a Med-lite launcher. This would enable global network science for meteorology and, when combined wAh the more sophisticated measurements from the InterMarsNet landers and the simultaneous temperature and dust profiling measurements from an atmospheric sounder aboard the orbiter, it would enable us to reconstruct global scale circulation patterns.

Haberle, Robert M.↗

Localization of Ad-Hoc Lunar Constellations in Communication Failure Modes for Distributed Spacecraft Autonomy

As lunar missions increase in complexity inspired by NASA’s Artemis Program, they will require reliable and sufficient capability of the Position, Navigation, and Timing (PNT) system to support their scientific objectives. In addition, NASA's Commercial Lunar Payload Services (CLPS) program initiates the proliferation of public and private exploration partnerships using small satellites from commercial and private organizations, expanding traditionally confined low Earth orbit to be used for missions beyond geosynchronous orbit (Zucherman et al., 2022). Therefore, the Lunar PNT system is also required to provide navigation services compatible with the smaller platforms being sent by the public and private sectors, like CubeSats. However, traditional approaches to deep space missions’ navigation based on ground radio facilities have difficulties in providing sufficient support for the increasing number of users and communication at a distance from the Earth (Kaplev et al., 2022). In particular, the existing Lunar navigation technologies such as weak signal global positioning system (GPS) and deep space network (DSN) are not able to ensure operations of the upcoming small-scale Lunar missions due to their limitations in localization performance as well as capacity aspects. Another way to provide Lunar PNT service is to create a dedicated Lunar global navigation satellite system (GNSS) constellation, like GNSS systems on Earth. Space agencies like NASA, ESA, and JAXA are now developing the lunar communications relay and navigation systems (LCRNS) and Lunar navigation satellite systems (LNSS). In their systems, satellites will be deployed in moon orbits to provide the communication, positioning, navigation, and timing (CPNT) service at the lunar south pole region where the Artemis base camp will be expected (Murata et al., 2022). Meanwhile, common challenges considered in lunar PNT research arise from poor geometry of the terrestrial GNSS satellites when seen from the lunar user, highly perturbed lunar orbits, and limitations in power, size, and cost of the equipment on lunar satellites (Iiyama et al., 2023). It is also not clear if there will be enough Lunar users to support the cost and resources this would require as the Low-cost surface missions may not be able to support the large power, mass, and weight requirements that these navigation solutions entail (Niemoeller et al., 2022). As an alternative, existing Lunar science and exploration assets could be used to create a low-cost, autonomous, ad-hoc, and on-demand mission-centric Lunar PNT swarm capable of providing PNT services to these low-cost lunar missions (Hagenau et al., 2021). Introducing the non-dedicated and ad-hoc Lunar navigation constellation gives a way to provide PNT services on-demand. The non-dedicated swarm assets of Lunar constellations are designed to localize themselves with minimal interaction with Earth by adding cooperative autonomous localization to lunar missions, freeing up valuable bandwidth and ground segment resources. An autonomous localization of Lunar constellations is based on the concept of the decentralized PNT system with a distributed extended Kalman filter (DEKF) approach to state estimation for minimal onboard operating costs. In the distributed data processing algorithm, computation is broken down and assigned to each satellite, resulting in a considerably decreased computational amount while maintaining the accuracy of the orbit ephemeris and clock offsets as the result of centralized data processing (Wen et al., 2019). The DEKF requires spacecraft to perform two-way ranging operations with each other to communicate simultaneously, leveraging neighbor two-way intersatellite link (ISL) measurements such as pseudoranges to, and relative velocities between, visible satellites as sensor values (Frank et al., 2021). The Lunar autonomous PNT simulation (LAPS) demonstrated the feasibility of orbital asset localization among ad-hoc Lunar small-sat constellations based on the DEKF in Hagenau et al. (2021) and evaluated the matching algorithm proposed by Frank et al. (2021) in scheduling position estimation updates. In previous papers, all assets and measurements are assumed to be always available without consideration of the impact of intermittent and permanent communication failure. This study presents localization performance with increasing levels of network degradation for swarm assets and users to demonstrate the robustness of the decentralized Lunar PNT service in more realistic scenarios. Main issues arising from communication failure include spacecraft permanent or transient loss, antenna failures, message delays, etc. We tested four possible reasons for network degradation for 7 days in 21 satellites frozen with an altitude of 5500 km, evenly spaced around 3 circular, 40 inclination orbital planes where each spacecraft has two directional antennas. As anchor nodes with an independent estimate of their position are required in the DEKF approach, two ground nodes in each pole and one node in the gateway were implemented in the simulation. First, the most probable failure scenario involves the loss of a single spacecraft due to solar interference and technical malfunctions of the assets. Losing the availability of a single spacecraft means losing the two-way ISL measurement of the asset in the DEKF update. In order to provide the best possible quality of PNT service with limited time and resources, the distributed Lunar constellations must schedule the communication activities. The scheduler leverages mixed-integer linear programming (MILP) for the coordination and scheduling of the desired “as-needed” localization service (Niemoeller et al., 2022). We assume the scheduler has completely excluded the spacecraft information before the DEKF update in the failure scenario. When a random spacecraft has been turned off at a specific time, the robustness of the autonomous Lunar PNT system is evaluated. The simulation results give an 11.5% degradation in median position accuracy compared to the idealized performance excluding the asset loss. Second, a large number of assets may vanish due to major hardware problems or meteor strikes around the moon. A multiple spacecraft loss can degrade the localization performance very fast by losing the communication ability to do cross-plane measurements and in-plane measurements in a 3-plane constellation. When the matching-based scheduler is aware of ISL availability, we investigate a large number of in-plane and cross-plane asset vanishments both in close proximity and equally spaced throughout the orbital plane. According to the simulations, the loss of in-plane measurements gives 40.2% degradation while cross-plane measurements degrade 50.5% of asset localization performance among available assets. Therefore, it is concluded that cross-plane measurements are more important in improving the position estimation accuracy. Third, spacecraft failure information can be lost due to the internal message delay, resulting in the DEKF update scheduler to solve the matching problem with unavailable assets. The DEKF update cycle is comprised of network setup, communication, and computations where a global broadcast network and a 2-way ISL network setup take 6 minutes in total (Frank et al., 2021). Once the broadcast network successfully transmits and receives information, a random spacecraft may lose its availability right before solving the matching problem. This means the matching solution is no longer optimal, resulting in degradation in the localization performance. A numerical assessment shows the matching-based scheduler with knowing failure holds 11.5% of position accuracy degradation, whereas the scheduler without knowing failure gives 34% degraded localization performance without asset loss. Fourth, a transient loss of a single or multiple spacecraft may occur due to their antenna outages. After losing the two-way ISL availability for a few DEKF update cycles, the availability of spacecraft can easily be recovered as their states have been independently updated using measurements from anchor nodes. It is likely that the longer failure will result in worse localization performance. We have tested the transient failure of a random single asset for 30 min in the simulation, which is losing 3 update cycles in the DEKF system. From the simulation results, the position accuracy has been degraded to 4.84% which is better than the degraded localization performance of 11.5% from the permanent loss scenario among available assets. In conclusion, the autonomous Lunar PNT system based on the DEKF approach shows the ability to maintain resilience and robustness in the possible communication failure scenarios, ensuring that localization accuracy is preserved across various network degradation and outages. Future studies on investigating user localization performance near the South Pole and the broadcast network system will be continued in the following months.

Yeji Kim↗

Data-Driven PMU Noise Emulation Framework using Gradient-Penalty-Based Wasserstein GAN

Availability of phasor measurement unit (PMUs) data has led to research on data-driven algorithms for event monitoring, control and ensuring stability of the grid. Unavailability of infrequent critical event field PMU data with component failures is driving the need to generate realistic synthetic PMU data for research. The synthetic data from power system simulation software often neglect noise profiles of received phasors, thus creating some discrepancies between real PMU data and synthetic ones. To address this issue, this work presents an initial study on the noise characteristics of PMUs, as well as presenting models for recreating their unique noise signatures. The proposed method, utilizing the Wasserstein generative adversarial network with gradient penalty (WGAN-GP) architecture, provides an excellent benchmark for matching the noise distribution. One can use a well-learned GAN model to draw noise signatures from a distribution that seemingly mirrors the real PMU noise distribution, while also being able to be detached from the PMU data once the training is done. Based on the observed results and employed data-driven methodology, it is expected that the proposed methods can be adapted to replicate the behavior of other sensors, providing research and other applications with a tool for data synthesis and sensor characterization.

PMU↗

Interactive and cooperative sensing and control for advanced teleoperation

This paper presents the paradigm of interactive and cooperative sensing and control as a fundamental mechanism of integrating and fusing the strengths of man and machine for advanced teleoperation. The interactive and cooperative sensing and control is considered as an extended and generalized form of traded and shared control. The emphasis of interactive and cooperative sensing and control is given to the distribution of mutually nonexclusive subtasks to man and machine, the interactive invocation of subtasks under the man/machine symbiotic relationship, and the fusion of information and decisionmaking between man and machine according to their confidence measures. The proposed interactive and cooperative sensing and control system is composed of such major functional blocks as the logical sensor system, the sensor-based local autonomy, the virtual environment formation, and the cooperative decision-making between man and machine. The Sensing-Knowledge-Command (SKC) fusion network is proposed as a fundamental architecture for implementing cooperative and interactive sensing and control. Simulation results are shown.

Lee, Sukhan↗

NASA In Situ Data Needs to Support the Operational Calibration and Validation of Ocean Color Satellite Data Products

Calibrating ocean color satellite instruments and validating their data products requires temporal and spatial abundances of high quality in situ oceanographic data. The Consortium for Ocean Leadership Ocean Observing Initiative (OOl) is currently implementing a distributed array of in-water sensors that could provide a significant contribution to future ocean color activities. This workshop will scope the optimal way to use and possibly supplement the planned OOl infrastructure to maximize its utility and relevance for calibration and validation activities that support existing and planned NASA ocean color missions. Here, I present the current state of the art of NASA validation of ocean color data products, with attention to autonomous time-series (e.g., the AERONET -OC network of above-water radiometers), and outline NASA needs for data quality assurance metrics and adherence to community-vetted data collection protocols

Werdel, P. Jeremy↗

Weather Considerations for Ground-Based Optical Space Situational Awareness Site Selection

Continuous surveillance of the night sky with ground-based optical sensors requires a number of sites distributed around the globe. Due to variable cloud cover, the number of sites required to guarantee nightly observation of all Geosynchronous Earth Orbit slots is greater than that simply required to provide partial coverage. Combining this consideration with the requirements for dark sky sites and adequate supporting infrastructure presents additional limitations on where ground- based telescopes can be located. The authors examine this problem and present results of an optimization approach that can both recommend sites and networks of sites, as well as provide insight into the utility of any individual geographic location.

54 ENVIRONMENTAL SCIENCES↗

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↗

Embedded Optical Sensing Systems For Distribution Transformer Monitoring

Traditional utility monitoring systems do not provide real-time visibility into the condition of transformers or accurate performance measurements. This has resulted in the use of lagging indicators, such as oil sample analysis, typically requiring expensive field visits, grid outages, and laboratory sample testing. This presentation reviews the use of optical sensing systems for managing transformers and improving grid resiliency and safety. The sensing systems allow direct internal monitoring of critical transformer components. Versatility covering different monitoring parameters of interest in embedded configurations for new transformers and a retrofittable configuration for older transformers is achieved by applying hair-thin multiplexed fiber-optic and other low-profile optical sensors in combination with a high-resolution optical readout and advanced analytics. Under an initiative funded by the DOE Office of Electricity, PARC, GE and Con Edison built, tested, and qualified commercial network transformers with embedded optical sensing systems. The parameters monitored were validated across a range of scenarios with lab instruments typically used for qualification testing. An ongoing field trial to demonstrate the robustness of the technology for remote monitoring through the industrial internet under demanding grid deployment conditions in New York City is showing promise toward scale-up of the technology. This presentation will provide an overview of the typical pain points in managing transformers and parameters for monitoring. It will also cover the requirements for highly constrained installations that need to have a larger capacity and flexible rating but that must fit into a tight space. The unique capabilities of optical sensing systems and a low-cost approach to interpreting the signals from sensors in transformers for predictive maintenance will be covered. The presentation will discuss the compatibility of the sensors in the transformer environment. It will discuss the validation testing per IEEE standards that enabled the solution to be implemented in field-deployable commercial transformers. The initial results from the field deployment and the potential for the technology to provide systematic alerts for unsafe/unexpected events will be discussed. The technology could enable utility professionals to gain information they can use to better plan for maintenance/management, and improve grid performance. This would in turn accommodate DERs and other evolving grid market dynamics.

24 POWER TRANSMISSION AND DISTRIBUTION↗