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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 757 records · Page 42
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Assessing Performance of Radar and Visual Sensing Techniques for Ground-To-Air Surveillance in Advanced Air Mobility

The safe integration of Unmanned Aircraft Vehicles (UAV) within the civil airspace is of great interest to NASA’s Advanced Air Mobility project, which envisions high density of operations in and around urban areas that include both UAV and AAM aircraft. To enable safe autonomous operations of both platforms, reliable airspace surveillance strategies must be designed and experimentally validated in relevant scenarios, where multiple small UAV operate flying in low altitude conditions. An example of such a scenario is described in this paper which provides performance assessment of various sensing strategies experimentally tested during flight campaigns with four UAV completing simultaneous missions from vertiports. Such campaigns are performed by the High Density Vertiplex subproject which assesses a prototype of Urban Air Mobility ecosystem. For the purposes of this work, the flights are observed from multiple sensing nodes each with radar and camera sensors. The visual detection and tracking algorithms achieved 96.1% to 99.9% average tracking coverage of the UAV above the horizon, reaching detection ranges larger than 1 kilometer for octocopter. Radar-based tracking shows a lower coverage mainly due to ground clutter removal challenges but provides comparable detection ranges and meter-level range accuracy.

Federica Vitiello↗
NASA NTRSDate not supplied

The Environmental Data Application for Analysis of Space Telemetry Data

Sensors on the International Space Station (ISS) and multiple spacecraft elsewhere in Earth orbit and in deep space continuously monitor and collect environmental data, transmitting this information back to Earth. These data include ionizing radiation and, on the ISS and spacecrafts, CO2, relative humidity levels, and temperature, and are of great importance to space biology research. Looking ahead to future long duration crewed missions beyond low Earth orbit, the ability to study how factors including CO2 levels, light cycle, temperature modulate the response to ionizing radiation and microgravity is essential. To date, access to these data has been fragmented across space agencies, spacecraft, and databases. To address this issue, NASA’s Open Science Data Repository (OSDR) has developed a user interface for interrogation of telemetry data: the Environmental Data Application (EDA). The EDA provides the capability to visualize telemetry and radiation data collected on the International Space Station and corresponding ground platforms during the Rodent Research missions. Telemetry data includes temperature, relative humidity, and CO2 levels. Radiation data includes galactic cosmic rays, the contribution of the South Atlantic Anomaly, total radiation dose rate, and accumulated radiation dose. The application allows users to view single missions, compare multiple missions, and view and download summary or full data tables. In summary, the EDA provides GUIs for data visualization and exploration, as well as means for data export, making these data FAIR (Findable, Accessible, Interoperable, and Reusable), complementing the biological data contained in OSDR, and providing the space science community with a valuable resource for scientific analyses.

telemetry↗
NASA NTRSDate not supplied

Lessons Learned From Smallsat Microwave Sounders Data Assimilation in the NASA Goddard Earth Observing System (GEOS)

The NASA Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats (TROPICS) mission is a constellation of small satellites carrying state-of-art microwave temperature and humidity sounders with 12 channels between 91 GHz and 205 GHz frequency. Including TROPICS-pathfinder, launched on 30 June 2021, five TROPICS satellites operate and provide temperature and humidity data to NWP and atmospheric retrieval communities. This study evaluates the quality of radiance data from these five satellites. It assesses data impacts on NASA Goddard Earth Observing System (GEOS) global NWP analysis and forecasts while seeking answers to the following key questions: 1. What information do TROPICS satellites bring to NWP analysis? 2. How will TROPICS data assimilation affect NWP forecasts, including tropical cyclone analysis and forecasts? 3. What are the benefits of having multiple TROPICS satellites in NWP forecasts? 4. What are the weaknesses regarding instrument stability, consistency, and data quality of these CubeSats? 5. Can multiple TROPICS make similar impacts as conventional MW sensors such as ATMS or GPM Microwave Imager (GMI)? The sensitivities of each TROPICS channel to temperature, water vapor, cloud, and precipitation are examined in various weather conditions. Results from observing system experiments assimilating TROPICS radiance are used for evaluation metrics, including forecast skills and fit to other observations such as radiosondes and microwave and infrared sounders. Finally, the lessons learned from using these cube satellite radiance data in the GEOS atmospheric data assimilation system are shared.

Min-Jeong Kim↗
NASA NTRSDate not supplied

Large-Scale Simulation of a Distributed Sensing Network Supporting Regional Urban Air Mobility Operations

Urban Air Mobility (UAM) is set to transform transportation in densely populated regions like the San Francisco Bay Area. This paper introduces an innovative simulation approach to explore large-scale UAM scenarios, emphasizing the use of distributed sensing to enhance operational efficiency and safety. The Revolutionary Vertical Lift Technology (RVLT) model is employed as the framework for simulating complex interactions among multiple vehicles within urban landscapes. Strategically deployed ground sensor nodes enable distributed sensing, enhancing situational awareness and operational effectiveness. By integrating empirical data and geographical realism, the simulations provide a systematic analysis of the feasibility, efficiency, and safety considerations associated with UAM deployment in urban environments. Factors such as air traffic density and infrastructural requirements are thoroughly examined, offering actionable insights for policymakers and industry stakeholders. This paper aims to refine the structure and scenarios for large-scale simulations based on distributed sensing, thereby contributing to the advancement of UAM operations.

UAM↗
NASA NTRSDate not supplied

Large-Scale Simulation of a Distributed Sensing Network Supporting Regional Urban Air Mobility Operations

Urban Air Mobility (UAM) is set to transform transportation in densely populated regions like the San Francisco Bay Area. This paper introduces an innovative simulation approach to explore large-scale UAM scenarios, emphasizing the use of distributed sensing to enhance operational efficiency and safety. The Revolutionary Vertical Lift Technology (RVLT) model is employed as the framework for simulating complex interactions among multiple vehicles within urban landscapes. Strategically deployed ground sensor nodes enable distributed sensing, enhancing situational awareness and operational effectiveness. By integrating empirical data and geographical realism, the simulations provide a systematic analysis of the feasibility, efficiency, and safety considerations associated with UAM deployment in urban environments. Factors such as air traffic density and infrastructural requirements are thoroughly examined, offering actionable insights for policymakers and industry stakeholders. This paper aims to refine the structure and scenarios for large-scale simulations based on distributed sensing, thereby contributing to the advancement of UAM operations.

Aircraft Mobility↗
DOE OSTI2021

Development of an Innovative Inspection Tool for Superheater Tubes in Fossil Fuel Power Plants

Fossil fuel power plants are complex systems containing multiple components that require periodic health monitoring. Failures in these systems can lead to increased downtime for the plant, reduction of power, and significant cost for repairs. Inspections of the plant’s superheater tubes are typically manual, laborious, and extremely time-consuming. This is due to their small diameter size (between 1.3 and 7.6 cm) and the coiled structure of the tubing. In addition, the tubes are often stacked close to each other, limiting access for external inspection. This paper presents the development and testing of an electrically powered pipe crawler that can navigate inside 5 cm diameter tubes and provide an assessment of their health. The crawler utilizes peristaltic motion within the tubes via interconnected modules for gripping and extending. The modular nature of the system allows it to traverse through straight sections and multiple 90° and 180° bends. Additional modules in the system include an ultrasonic sensor for tube thickness measurements, as well as environmental sensors, a light detecting and ranging (LiDAR) sensor, and camera. Furthermore, these modules utilize a gear system that allows for 360° rotation and provides a means to inspect the entire internal circumference of the tubes.

36 MATERIALS SCIENCE↗
NASA NTRSDate not supplied

A New Statistical Estimate of the Radar Coverage of the Low Earth Orbit Debris Environment

For over three decades, the NASA Orbital Debris Program Office (ODPO) has used the Goldstone Orbital Debris Radar, Haystack Ultrawideband Satellite Imaging Radar (HUSIR), and Haystack Auxiliary (HAX) radar assets to collect data on the low Earth orbit (LEO) debris environment. Each radar, with its unique beamwidth, altitude and inclination coverage, and limiting size threshold, operates in a beam park mode to statistically sample the orbital debris population in LEO. Provided that these assets are shared with other users, the orbital debris data collection is not continuous; rather, intermittent data collects are acquired and sent to the NASA ODPO. To understand the sampling process conducted by each radar over time and any related observational biases, a Statistical Confirmation of Radar Uniformity or Bias (SCRUB) code has been implemented to model the coverage of these assets for informing future operations, as well as usage of the data collected from these ground-based sensors. For this analysis, Right Ascension of the Ascending Node (RAAN) is used as a metric to measure statistical coverage. A complete survey of the LEO environment is understood to be measurements that sufficiently sample all values of RAAN for each altitude-inclination pair visible from the radar asset. Regions of incompleteness or statistical bias can help inform future observation campaigns. The SCRUB tool evaluates the coverage of the LEO environment, not by examining individual objects that may pass through a sensor’s field of view (FOV), but by determining which orbit planes pass through the FOV. Once a pointing geometry for a radar site, observation time, and range extent are configured by the user, SCRUB computes the inclinations and altitudes that are visible by the sensor. For each inclination-altitude pair, there is a distinct pair of possible RAAN values, corresponding to the ascending and descending orbit passing through that point in the sensor cone. Repeating this process for all points in the beam, and for multiple time periods during an observation window, creates a matrix of all inclination-altitude-RAAN combinations that are visible during a sensor run. This process can then be repeated for all observations within a year (for an annual survey), propagating all the RAAN values to a common epoch, typically the start of a calendar year, and combining the observations to assemble a full estimate of the RAAN coverage of the LEO environment. This RAAN coverage can then be analyzed for uniformity of sampling, within a certain inclination-altitude pair, or between larger regions of the space environment. This paper provides a general overview of the radar assets utilized by ODPO, typical analysis data products assuming circular orbits, and a discussion of the algorithms that feed between modeling and measurement operations. Following the description of the algorithm, estimates of coverage using HUSIR radar data collected from multiple years are developed and compared.

Chris L Ostrom↗
NASA NTRS1996

Fiber Optic Sensors for Smart Materials and Structures

In this paper we describe recently developed fiber sensors which are capable of monitoring the health of smart-structures. The unobstrusive geometry of these sensors make them an excellent choice for embedding the sensor in composite materials to measure internal states of strain in structures and materials. Some of these sensors have gage lengths that can be tailored from tens of microns to many meters. We will describe various demodulation schemes (Pseudo-Heterodyne, Synthetic-Heterodyne, Homodyne, Differential-Cross Multiplier, and Single Channel Phase-Tracker) to obtain high bandwidth measurements, enabling measurement of static to high frequency impact generated strains with a dynamic response exceeding tens of thousands of microstrains. In addition, we will show that we can tailor the fiber sensor to either measure only strain and reject temperature response or measure only the temperature, or measure both temperature and strain simultaneously. We will also demonstrate the ability to measure multiple strain components inside a host simultaneously using a single fiber sensor embedded in the host using a certain sensor type and transverse strain immunity using another sensor type. Additionally we will show the ability to measure temperature up to 100 C using fiber optic sensors.

Singh, H.↗
DOE OSTI2022

Smart sensor for online situational awareness in power grids

Waveforms in power grids typically reveal a certain pattern with specific features and peculiarities driven by the system operating conditions, internal and external uncertainties, etc. This prompts an observation of different types of waveforms at the measurement points (substations). An innovative next-generation smart sensor technology includes a measurement unit embedded with sophisticated analytics for power grid online surveillance and situational awareness. The smart sensor brings additional levels of smartness into the existing phasor measurement units (PMUs) and intelligent electronic devices (IEDs). It unlocks the full potential of advanced signal processing and machine learning for online power grid monitoring in a distributed paradigm. Within the smart sensor are several interconnected units for signal acquisition, feature extraction, machine learning-based event detection, and a suite of multiple measurement algorithms where the best-fit algorithm is selected in real-time based on the detected operating condition. Embedding such analytics within the sensors and closer to where the data is generated, the distributed intelligence mechanism mitigates the potential risks to communication failures and latencies, as well as malicious cyber threats, which would otherwise compromise the trustworthiness of the end-use applications in distant control centers. The smart sensor achieves a promising classification accuracy on multiple classes of prevailing conditions in the power grid and accordingly improves the measurement quality across the power grid.

Dehghanian, Payman↗
NASA NTRS2013

Embedded diagnostic, prognostic, and health management system and method for a humanoid robot

A robotic system includes a humanoid robot with multiple compliant joints, each moveable using one or more of the actuators, and having sensors for measuring control and feedback data. A distributed controller controls the joints and other integrated system components over multiple high-speed communication networks. Diagnostic, prognostic, and health management (DPHM) modules are embedded within the robot at the various control levels. Each DPHM module measures, controls, and records DPHM data for the respective control level/connected device in a location that is accessible over the networks or via an external device. A method of controlling the robot includes embedding a plurality of the DPHM modules within multiple control levels of the distributed controller, using the DPHM modules to measure DPHM data within each of the control levels, and recording the DPHM data in a location that is accessible over at least one of the high-speed communication networks.

Barajas, Leandro G.↗
NASA NTRS2013

Nanoscale Surface Plasmonics Sensor With Nanofluidic Control

Conventional quantitative protein assays of bodily fluids typically involve multiple steps to obtain desired measurements. Such methods are not well suited for fast and accurate assay measurements in austere environments such as spaceflight and in the aftermath of disasters. Consequently, there is a need for a protein assay technology capable of routinely monitoring proteins in austere environments. For example, there is an immediate need for a urine protein assay to assess astronaut renal health during spaceflight. The disclosed nanoscale surface plasmonics sensor provides a core detection method that can be integrated to a lab-on-chip device that satisfies the unmet need for such a protein assay technology. Assays based upon combinations of nanoholes, nanorings, and nanoslits with transmission surface plasmon resonance (SPR) are used for assays requiring extreme sensitivity, and are capable of detecting specific analytes at concentrations as low as picomole to femtomole level in well-controlled environments. The device operates in a transmission mode configuration in which light is directed at one planar surface of the array, which functions as an optical aperture. The incident light induces surface plasmon light transmission from the opposite surface of the array. The presence of a target analyte is detected by changes in the spectrum of light transmitted by the array when a target analyte induces a change in the refractive index of the fluid within the nanochannels. This occurs, for example, when a target analyte binds to a receptor fixed to the walls of the nanochannels in the array. Independent fluid handling capability for individual nanoarrays on a nanofluidic chip containing a plurality of nanochannel arrays allows each array to be used to sense a different target analyte and/or for paired arrays to analyze control and test samples simultaneously in parallel. The present invention incorporates transmission mode nanoplasmonics and nanofluidics into a single, microfluidically controlled device. The device comprises one or more arrays of aligned nanochannels that are in fluid communication with inflowing and outflowing fluid handling manifolds that control the flow of fluid through the arrays. The array acts as an aperture in a plasmonic sensor. Fluid, in the form of a liquid or a gas and comprising a sample for analysis, is moved from an inlet manifold through the nanochannel array, and out through an exit manifold. The fluid may also contain a reagent used to modify the interior surfaces of the nanochannels, and/or a reagent required for the detection of an analyte.

Wei, Jianjun↗
NASA NTRS1997

A Cognitive System Model for Human/Automation Dynamics in Airspace Management

NASA has initiated a significant thrust of research and development focused on providing the flight crew and air traffic managers automation aids to increase capacity in en route and terminal area operations through the use of flexible, more fuel-efficient routing, while improving the level of safety in commercial carrier operations. In that system development, definition of cognitive requirements for integrated multi-operator dynamic aiding systems is fundamental. In order to support that cognitive function definition, we have extended the Man Machine Integrated Design and Analysis System (MIDAS) to include representation of multiple cognitive agents (both human operators and intelligent aiding systems) operating aircraft, airline operations centers and air traffic control centers in the evolving airspace. The demands of this application require representation of many intelligent agents sharing world-models, and coordinating action/intention with cooperative scheduling of goals and actions in a potentially unpredictable world of operations. The MIDAS operator models have undergone significant development in order to understand the requirements for operator aiding and the impact of that aiding in the complex nondeterminate system of national airspace operations. The operator model's structure has been modified to include attention functions, action priority, and situation assessment. The cognitive function model has been expanded to include working memory operations including retrieval from long-term store, interference, visual-motor and verbal articulatory loop functions, and time-based losses. The operator's activity structures have been developed to include prioritization and interruption of multiple parallel activities among multiple operators, to provide for anticipation (knowledge of the intention and action of remote operators), and to respond to failures of the system and other operators in the system in situation-specific paradigms. The model's internal representation has been be modified so that multiple, autonomous sets of equipment will function in a scenario as the single equipment sets do now. In order to support the analysis requirements with multiple items of equipment, it is necessary for equipment to access the state of other equipment objects at initialization time (a radar object may need to access the position and speed of aircraft in its area, for example), and as a function of perception and sensor system interaction. The model has been improved to include multiple world-states as a function of equipment am operator interaction. The model has been used -1o predict the impact of warning and alert zones in aircraft operation, and, more critic-ally, the interaction of flight-deck based warning mechanisms and air traffic controller action in response to ground-based conflict prediction and alerting systems. In this operation, two operating systems provide alerting to two autonomous, but linked sets of operators, whose view of the system and whose dynamics in response are radically different. System stability and operator action was predicted using the MIDAS model.

Corker, Kevin M.↗
NASA NTRS2003

Aircraft Engine Sensor/Actuator/Component Fault Diagnosis Using a Bank of Kalman Filters

In this report, a fault detection and isolation (FDI) system which utilizes a bank of Kalman filters is developed for aircraft engine sensor and actuator FDI in conjunction with the detection of component faults. This FDI approach uses multiple Kalman filters, each of which is designed based on a specific hypothesis for detecting a specific sensor or actuator fault. In the event that a fault does occur, all filters except the one using the correct hypothesis will produce large estimation errors, from which a specific fault is isolated. In the meantime, a set of parameters that indicate engine component performance is estimated for the detection of abrupt degradation. The performance of the FDI system is evaluated against a nonlinear engine simulation for various engine faults at cruise operating conditions. In order to mimic the real engine environment, the nonlinear simulation is executed not only at the nominal, or healthy, condition but also at aged conditions. When the FDI system designed at the healthy condition is applied to an aged engine, the effectiveness of the FDI system is impacted by the mismatch in the engine health condition. Depending on its severity, this mismatch can cause the FDI system to generate incorrect diagnostic results, such as false alarms and missed detections. To partially recover the nominal performance, two approaches, which incorporate information regarding the engine s aging condition in the FDI system, will be discussed and evaluated. The results indicate that the proposed FDI system is promising for reliable diagnostics of aircraft engines.

Kobayashi, Takahisa↗
NASA NTRS1994

Improved Micromachined Transducers

Sensor systems of proposed type incorporate micromachined silicon-based structures as electrostatic force and displacement actuators and micromachined quantum-mechanical-tunneling electrodes as one form of displacement transducers, along with electronic circuits providing multiple electrical stimuli to displacement electrodes for measurement, calibration, monitoring of sensor status, and adjustment. Concept applicable to accelerometers, seismometers, geophones, magnetometers, pressure gauges, and other sensors in which phenomena of interest measured in terms of forces on, and/or displacements of, structural components. Provides completely remote measurement, control, health monitoring, treatment, and like, using telemetry commands.

Hartley, Frank T.↗
NASA NTRS2018

Playbook for UAS: UX of Goal-Oriented Planning & Execution

We are evaluating the tool Playbook, a mission planning and scheduling tool used for analog missions and research experiments at NASA. We are adapting Playbook to support an unmanned aerial vehicle (UAV) demonstration that will simulate a "search and recover" mission. To support this demonstration, we need to test this software and its usability with human subjects. Playbook will be used to plan, edit, and monitor simulated UAV swarms, and we are interested in evaluating these capabilities. Allocation of roles and responsibilities between human-automation systems is key to promoting productive cooperation between these two agents. When guiding swarms the user should not be concerned with moving waypoints, adjusting heading and altitude or any other small actions that traditional pilots control. Providing situational awareness through sensor data including radar, heat, live camera feed, and topographic information are key when managing multiple UAVs together. First responders need a good picture of disaster areas in order to make informed decisions. These sensors can initiate movements in the mission that indicate when the human should take control of single aircraft.

UAV swarms↗
DOE OSTI2023

A compact dication source for Ba 2+ tagging and heavy metal ion sensor development

Here, we present a tunable metal ion beam that delivers controllable ion currents in the picoamp range for testing of dry-phase ion sensors. Ion beams are formed by sequential atomic evaporation and single or multiple electron impact ionization, followed by acceleration into a sensing region. Controllability of the ionic charge state is achieved through tuning of electrode potentials that influence the retention time in the ionization region. Barium, lead, and cadmium samples have been used to test the system, with ion currents identified and quantified using a quadrupole mass analyzer. Realization of a clean Ba 2+ ion beam within a bench-top system represents an important technical advance toward the development and characterization of barium tagging systems for neutrinoless double beta decay searches in xenon gas. This system also provides a testbed for investigation of novel ion sensing methodologies for environmental assay applications, with dication beams of Pb 2+ and Cd 2+ also demonstrated for this purpose.

47 OTHER INSTRUMENTATION↗
NASA NTRS1994

Advanced computer architecture specification for automated weld systems

This report describes the requirements for an advanced automated weld system and the associated computer architecture, and defines the overall system specification from a broad perspective. According to the requirements of welding procedures as they relate to an integrated multiaxis motion control and sensor architecture, the computer system requirements are developed based on a proven multiple-processor architecture with an expandable, distributed-memory, single global bus architecture, containing individual processors which are assigned to specific tasks that support sensor or control processes. The specified architecture is sufficiently flexible to integrate previously developed equipment, be upgradable and allow on-site modifications.

Katsinis, Constantine↗