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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,099 records · Page 61
All sourcesNASA NTRSDOE OSTI
NASA NTRS2023

Earth/Moon System Star Tracking Sensor for Improved Deep Space Laser Communications

The goal of this research is to improve deep space communication links by exploring a new concept in stellar navigation that uses images of the Earth/Moon system to obtain precise pointing information so that the laser signal from the satellite can be directed at the ground station with unprecedented accuracy. Currently, the concept for satellite pointing relies on a dual axis star tracker that compares images of the celestial sphere to a star catalog to obtain a 3-axis orientation solution. Most star trackers are designed with a wide field of view (required to obtain enough bright starts to achieve a navigational fix) and only provide reliable pitch and yaw estimates thus necessitating the use of a second star tracker looking at an axis perpendicular to the first one to obtain an accurate estimate of the roll of the spacecraft. In the new concept the optical design will be modified to ensure that both the Earth and the Moon will be within a narrow field of view centered on Earth relative to the field of view of most star tracking systems. Because of the proximity of the bodies, it is possible to obtain highly accurate estimates of the pitch, yaw and roll of the spacecraft relative to the Earth/Moon system. The new tracker will allow for accurate 3-axis control of the spacecraft from a single tracker thus allowing the second star tracker, which would normally be pointed in a direction perpendicular to the one pointed at earth, to obtain the spacecraft roll estimate. This wide field star tracker facilitates functions like the initial satellite pointing during the acquisition phase of establishing the laser communication link or solving the lost in space problem should the system need to be reset. This new design will be tested in simulation and compared for 3-axis pointing accuracy against a standard commercial star tracker.

Star tracker↗
NASA NTRS1989

A scheme for fault tolerance in earth sensors

A system is presented that uses dual-redundant earth sensors to measure pitch and roll errors of a three-axis stabilized spacecraft, with provision for (1) autonomously detecting and identifying a faulty earth sensor, and (2) automatically selecting the outputs of the fault-free sensor for closed-loop attitude control, before failures cause major problems. A brief description is given of the system, and various failure modes of earth sensors and their effects are discussed. Novel techniques and algorithms for automatic fault detection, identification, and reconfiguration (FDIR) of dual-redundant earth sensors are developed. The algorithms are validated through computer simulations, and the results are presented. The proposed scheme can easily be implemented without much penalty on hardware, power consumption, and processing time.

Murugesan, S.↗
NASA NTRS2007

Compact and Integrated Liquid Bismuth Propellant Feed System

Operation of Hall thrusters with bismuth propellant has been shown to be a promising path toward high-power, high-performance, long-lifetime electric propulsion for spaceflight missions [1]. There has been considerable effort in the past three years aimed at resuscitating this promising technology and validating earlier experimental results indicating the advantages of a bismuth-fed Hall thruster. A critical element of the present effort is the precise metering of propellant to the thruster, since performance cannot be accurately assessed without an accurate accounting of mass flow rate. Earlier work used a pre./post-test propellant weighing scheme that did not provide any real-time measurement of mass flow rate while the thruster was firing, and makes subsequent performance calculations difficult. The motivation of the present work is to develop a precision liquid bismuth Propellant Management System (PMS) that provides hot, molten bismuth to the thruster while simultaneously monitoring in real-time the propellant mass flow rate. The system is a derivative of our previous propellant feed system [2], but the present system represents a more compact design. In addition, all control electronics are integrated into a single unit and designed to reside on a thrust stand and operate in the relevant vacuum environment where the thruster is operating, significantly increasing the present technology readiness level of liquid metal propellant feed systems. The design of various critical components in a bismuth PMS are described. These include the bismuth reservoir and pressurization system, 'hotspot' flow sensor, power system and integrated control system. Particular emphasis is given to selection of the electronics employed in this system and the methods that were used to isolate the power and control systems from the high-temperature portions of the feed system and thruster. Open loop calibration test results from the 'hotspot' flow sensor are reported, and results of integrated thruster/PMS tests demonstrate operation of the feed system in the relevant environment.

Polzin, Kurt A.↗
NASA NTRS1965

Development of electrostatic sensors for scout systems evaluation vehicle, 131r

In the course of a Scout vehicle mission, a static charge may build up on the vehicle and reach sufficiently high values to become potentially dangerous to the vehicle mission. The development of electrostatic sensors for monitoring the potential build-up on a Scout vehicle is discussed in this report. The investigation and studies, which produced the theories tor the electrostatic sensor concepts, are also discussed. The sensors were designed, fabricated and installed on Scout vehicle 131R. Results of the sensor development program are discussed in full; however, at the time this report was completed, the flight experiment had not been accomplished.

Scout Project↗
DOE OSTI2022

Development of a Multi-Sensor Data Science System Used for Signature Development on Solvent Extraction Processes in support of safeguards- an overview

A new nuclear fuel cycle test bed is being built at Idaho National Laboratory to support the purification of special nuclear material recovered from used fuel. The test bed provides an opportunity to research process flow and the application of computational tools in solvent extraction processes. A deeper understanding of process and equipment behavior coupled with real time data collection can indicate whether a process failure is accidental or purposeful. The goal of this project is to develop a system that utilizes non-traditional measurement sources such as vibration, acoustics, current, light, flow, and temperature in conjunction with data-based, machine learning techniques that will allow for signal discovery. This multi-sensor data can support the development of safeguards by design and security by design measures for such a facility. Additionally, it can aid in early detection and identification of removed materials indicating diversion, which is essential for initiating material recovery and actor identification. This overview encompasses the current research and testing of sensors to develop a spectrum of process signatures. To be followed by planned experiments aimed to characterize said signatures and study potential feature extraction techniques to identify a fault in the system (i.e. flow diversion).

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2021

Landscape-scale Characterization of Arctic Tundra Vegetation Composition, Structure, and Function with a Multi-sensor Unoccupied Aerial System: Supporting Data.

Airborne remote sensing data collected using the Brookhaven National Laboratory's (BNL) heavy-lift unoccupied aerial system (UAS) octocopter platform, the Osprey, operated by the Terrestrial Ecosystem Science and Technology (TEST) group (https://www.bnl.gov/testgroup). This package includes data from three flights flown over the NGEE-Arctic Council, Kougarok and Teller sites in July, 2018. The Osprey is a multi-sensor UAS platform that simultaneously measures very high spatial resolution optical red/green/blue (RGB) and thermal infrared (TIR) surface 'skin' temperature imagery, as well as surface reflectance at 1 nm intervals in the visible to near-infrared spectral range 350 - 1000 nm measured at regular intervals along each flight path. Derived image products include ortho-mosaiced RGB and TIR images, an RGB-based digital surface model (DSM) using the structure from motion (SfM) technique, digital terrain model (DTM), and a canopy height model (CHM). In addition, a VNIR surface reflectance file is provided for the trigger locations collected during each flight campaign. Ancillary aircraft data, flight mission parameters, and general flight conditions provided by the onboard flight and data collection computers are also included. Unprocessed and processed data products are included in this package (processing levels 0-3). Data and metadata are provided as text (*.txt, *.json, *.kml, *hdr, *.enp), tabular (*.dat, *.csv, *.waypoint, ENVI format (no extension)), point cloud (*.laz) and image (*.jpg, *.tif, *png) formats. This metadata document contains flight campaign, instrument and file metadata, along with a description of data processing levels, data products and file naming scheme.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy?s Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Preliminary Results of a Multi-Sensor Data Science System for Monitoring a Solvent Extraction Process

Idaho National Laboratory is building a test bed to allow researchers the opportunity to study nuclear fuel processing operations. This includes studying the solvent extraction process and the use of centrifugal contactors. The goal of this project is to develop a system that utilizes non-traditional measurement sources such as vibration, acoustics, current, color, flow, and temperature in conjunction with data-based, machine learning techniques that will allow for signal discovery. This multi-sensor data supports the development of safeguards by design, provides operator process awareness, and aids in the discovery of process anomalies. This paper highlights some of the preliminary results from initial data collection campaigns and shares some of the lessons learned.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
NASA NTRS1978

Remote sensing data handbook

A digest of information on remote sensor data systems is given. It includes characteristics of spaceborne sensors and the supportive systems immediately associated therewith. It also includes end-to-end systems information that will assist the user in appraising total data system impact produced by a sensor. The objective is to provide a tool for anticipating the complexity of systems and potential data system problems as new user needs are generated. Materials in this handbook span sensor systems from the present to those planned for use in the 1990's. Sensor systems on all planned missions are presented in digest form, condensed from data as available at the time of compilation. Projections are made of anticipated systems.

Source record↗
NASA NTRS2005

Towards an Automated Development Methodology for Dependable Systems with Application to Sensor Networks

A general-purpose method to mechanically transform system requirements into a probably equivalent model has yet to appeal: Such a method represents a necessary step toward high-dependability system engineering for numerous possible application domains, including sensor networks and autonomous systems. Currently available tools and methods that start with a formal model of a system and mechanically produce a probably equivalent implementation are valuable but not su8cient. The "gap" unfilled by such tools and methods is that their. formal models cannot be proven to be equivalent to the system requirements as originated by the customel: For the classes of systems whose behavior can be described as a finite (but significant) set of scenarios, we offer a method for mechanically transforming requirements (expressed in restricted natural language, or in other appropriate graphical notations) into a probably equivalent formal model that can be used as the basis for code generation and other transformations.

Hinchey, Michael G.↗
DOE OSTI2020

A Multi-Sensor Unoccupied Aerial System Improves Characterization of Vegetation Composition and Canopy Properties in the Arctic Tundra: Supporting Data

Remote sensing data collected from Brookhaven National Laboratory's (BNL) heavy-lift unoccupied aerial system (UAS) octocopter platform - the Osprey - operated by the Terrestrial Ecosystem Science and Technology (TEST) group. Data was collected from a single flight over the Kougarok hillslope site on 26 July, 2018. The Osprey is a multi-sensor UAS platform that simultaneously measures very high spatial resolution optical red/green/blue (RGB) and thermal infrared (TIR) surface "skin" temperature imagery, as well as surface reflectance at 1nm intervals in the visible to near-infrared spectral range from ~350-1000 nm measured at regular intervals along each flight path. Derived image products include ortho-mosaiced RGB and TIR images, an RGB-based digital surface model (DSM) using the structure from motion (SfM) technique, digital terrain model (DTM), and a canopy height model. Ancillary aircraft data, flight mission parameters, and general flight conditions are also included. This dataset includes *.pdf, *.txt, *.tif, *.dat, and *.csv with most zipped in *.tar.gz files. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1984

A Fault Tolerant System for an Integrated Avionics Sensor Configuration

An aircraft sensor fault tolerant system methodology for the Transport Systems Research Vehicle in a Microwave Landing System (MLS) environment is described. The fault tolerant system provides reliable estimates in the presence of possible failures both in ground-based navigation aids, and in on-board flight control and inertial sensors. Sensor failures are identified by utilizing the analytic relationships between the various sensors arising from the aircraft point mass equations of motion. The estimation and failure detection performance of the software implementation (called FINDS) of the developed system was analyzed on a nonlinear digital simulation of the research aircraft. Simulation results showing the detection performance of FINDS, using a dual redundant sensor compliment, are presented for bias, hardover, null, ramp, increased noise and scale factor failures. In general, the results show that FINDS can distinguish between normal operating sensor errors and failures while providing an excellent detection speed for bias failures in the MLS, indicated airspeed, attitude and radar altimeter sensors.

Caglayan, A. K.↗
DOE OSTI2023

Edge-computing with enhanced standoff sensors

A system senses analytes through one or more sensors that detect or measure a physical characteristic. The one or more sensor generate a spectroscopic-data signal corresponding to the detection. An edge device communicatively couples the one or more sensors that communicatively couples a wide-area network coupling a cloud service. The edge device includes a data acquisition device that receives spectroscopic data signals from the one or more sensor and a processor that processes the spectroscopic-data signals to identify an analyte. The edge device also includes a transceiver that transmits data identifying the analytes to the cloud service.

Passian, Ali↗
NASA NTRS1992

Interactive Scene Analysis Module - A sensor-database fusion system for telerobotic environments

Accomplishing a task with telerobotics typically involves a combination of operator control/supervision and a 'script' of preprogrammed commands. These commands usually assume that the location of various objects in the task space conform to some internal representation (database) of that task space. The ability to quickly and accurately verify the task environment against the internal database would improve the robustness of these preprogrammed commands. In addition, the on-line initialization and maintenance of a task space database is difficult for operators using Cartesian coordinates alone. This paper describes the Interactive Scene' Analysis Module (ISAM) developed to provide taskspace database initialization and verification utilizing 3-D graphic overlay modelling, video imaging, and laser radar based range imaging. Through the fusion of taskspace database information and image sensor data, a verifiable taskspace model is generated providing location and orientation data for objects in a task space. This paper also describes applications of the ISAM in the Intelligent Systems Research Laboratory (ISRL) at NASA Langley Research Center, and discusses its performance relative to representation accuracy and operator interface efficiency.

Cooper, Eric G.↗
NASA NTRS2003

Foam Sensor Structures Would be Self-Deployable and Survive Hard Landings

A document proposes systems of sensors encased in cold hibernated elastic memory (CHEM) structures for exploring remote planets. Lightweight structures that can be compressed for storage and later expanded, then rigidified for use are made from foams of shape-memory polymers (SMPs). According to the instant proposal, a CHEM sensor structure would be fabricated at full size from SMP foam at a temperature below its glass-transition temperature (Tg). It would then be heated above Tg and compacted to a small volume, then cooled below Tg and kept below Tg during launch, flight, and landing. At landing, the inelastic yielding of the rigid compacted foam would absorb impact energy, thereby enabling the structure to survive the landing. The structure would then be solar heated above Tg, causing it to revert to its original size and shape. Finally, the structure would be rigidified by cooling it below Tg by the cold planetary or space environment. Besides surviving hard landing, this sensor system will provide a soft, stick-at-the-impact-site landing to access scientifically and commercially interesting sites, including difficult and hard-to-reach areas.

Sokolowski, Witold↗
DOE OSTI2022

An Overview in the Development of a Multi-Sensor Data Science System for Monitoring a Solvent Extraction Process

To enhance nuclear nonproliferation stewardship, Idaho National Laboratory is building the Beartooth nuclear fuel cycle processing test bed. The Beartooth test bed will allow researchers the opportunity to study nuclear fuel processing operations including the use of centrifugal contactors in solvent extraction processes. The test bed is designed to support data collection and machine learning to monitor process operations. As part of this project, researchers will study data collected from a host of sensors that have not been typically used to monitor solvent extraction processes such as vibration, acoustic, colormetric, and thermal measurement data. The goal of this research is to employ machine learning and data analytics to study the confluence of signals collected from both traditionally and non-traditionally used sensors to provide operator process awareness and discover process anomalies. An overview of planned sensors and experiments that will focus on signal discovery will be presented.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

An Overview in the Development of a Multi-Sensor Data Science System for Monitoring a Solvent Extraction Process

To enhance nuclear nonproliferation stewardship, Idaho National Laboratory is building the Beartooth nuclear fuel cycle processing test bed. The Beartooth test bed will allow researchers the opportunity to study nuclear fuel processing operations including the use of centrifugal contactors in solvent extraction processes. The test bed is designed to support data collection and machine learning to monitor process operations. As part of this project, researchers will study data collected from a host of sensors that have not been typically used to monitor solvent extraction processes such as vibration, acoustic, colormetric, and thermal measurement data. The goal of this research is to employ machine learning and data analytics to study the confluence of signals collected from both traditionally and non-traditionally used sensors to provide operator process awareness and discover process anomalies. An overview of planned sensors and experiments that will focus on signal discovery will be presented.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Anomalous behavior detection by an artificial intelligence-enabled system with multiple correlated sensors

Multi-metric artificial intelligence (AI)/machine learning (ML) models for detection of anomalous behavior of a machine/system are disclosed. The multi-metric AI/ML models are configured to detect anomalous behavior of systems having multiple sensors that measure correlated sensor metrics such as coolant distribution units (CDUs). The multi-metric AI/ML models perform the anomalous system behavior detection in a manner that enables both a reduction in the amount of sensor instrumentation needed to monitor the system's operational behavior as well as a corresponding reduction in the complexity of the firmware that controls the sensor instrumentation. As such, AI-enabled systems and corresponding methods for anomalous behavior detection disclosed herein offer a technical solution to the technical problem of increased failure rates of existing multi-sensor systems, which is caused by the presence of redundant sensor instrumentation that necessitates complex firmware for controlling the sensor instrumentation.

Serebryakov, Sergey↗