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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
NASA NTRS2010

Real-Time Visualization of Spacecraft Telemetry for the GLAST and LRO Missions

GlastCam and LROCam are closely-related tools developed at NASA Goddard Space Flight Center for real-time visualization of spacecraft telemetry, developed for the Gamma-Ray Large Area Space Telescope (GLAST) and Lunar Reconnaissance Orbiter (LRO) missions, respectively. Derived from a common simulation tool, they use related but different architectures to ingest real-time spacecraft telemetry and ground predicted ephemerides, and to compute and display features of special interest to each mission in its operational environment. We describe the architectures of GlastCam and LROCam, the customizations required to fit into the mission operations environment, and the features that were found to be especially useful in early operations for their respective missions. Both tools have a primary window depicting a three-dimensional Cam view of the spacecraft that may be freely manipulated by the user. The scene is augmented with fields of view, pointing constraints, and other features which enhance situational awareness. Each tool also has another "Map" window showing the spacecraft's groundtrack projected onto a map of the Earth or Moon, along with useful features such as the Sun, eclipse regions, and TDRS satellite locations. Additional windows support specialized checkout tasks. One such window shows the star tracker fields of view, with tracking window locations and the mission star catalog. This view was instrumental for GLAST in quickly resolving a star tracker mounting polarity issue; visualization made the 180-deg mismatch immediately obvious. Full access to GlastCam's source code also made possible a rapid coarse star tracker mounting calibration with some on the fly code adjustments; adding a fine grid to measure alignment offsets, and introducing a calibration quaternion which could be adjusted within GlastCam without perturbing the flight parameters. This calibration, from concept to completion, took less than half an hour. Both GlastCam and LROCam were developed in the C language, with non-proprietary support libraries, for ease of customization and portability. This no-blackboxes aspect enables engineers to adapt quickly to unforeseen circumstances in the intense operations environment. GlastCam and LROCam were installed on multiple workstations in the operations support rooms, allowing independent use by multiple subsystems, systems engineers and managers, with negligible draw on telemetry system resources.

Stoneking, Eric T.↗
NASA NTRS2008

Testing the Efficacy of Synthetic Vision during Non-Normal Operations as an Enabling Technology for Equivalent Visual Operations

Synthetic Vision (SV) may serve as a revolutionary crew/vehicle interface enabling technology to meet the challenges of the Next Generation Air Transportation System Equivalent Visual Operations (EVO) concept that is, the ability to achieve or even improve on the safety of Visual Flight Rules (VFR) operations, maintain the operational tempos of VFR, and potentially retain VFR procedures independent of actual weather and visibility conditions. One significant challenge lies in the definition of required equipage on the aircraft and on the airport to enable the EVO concept objective. An experiment was conducted to evaluate the effects of the presence or absence of SV, the location (head-up or head-down) of this information during an instrument approach, and the type of airport lighting information on landing minima. Another key element of the testing entailed investigating the pilot s awareness and reaction to non-normal events (i.e., failure conditions) that were unexpectedly introduced into the experiment. These non-normals are critical determinants in the underlying safety of all-weather operations. This paper presents the experimental results specific to pilot response to non-normal events using head-up and head-down synthetic vision displays.

Kramer, Lynda J.↗
NASA NTRS2005

Java Radar Analysis Tool

Java Radar Analysis Tool (JRAT) is a computer program for analyzing two-dimensional (2D) scatter plots derived from radar returns showing pieces of the disintegrating Space Shuttle Columbia. JRAT can also be applied to similar plots representing radar returns showing aviation accidents, and to scatter plots in general. The 2D scatter plots include overhead map views and side altitude views. The superposition of points in these views makes searching difficult. JRAT enables three-dimensional (3D) viewing: by use of a mouse and keyboard, the user can rotate to any desired viewing angle. The 3D view can include overlaid trajectories and search footprints to enhance situational awareness in searching for pieces. JRAT also enables playback: time-tagged radar-return data can be displayed in time order and an animated 3D model can be moved through the scene to show the locations of the Columbia (or other vehicle) at the times of the corresponding radar events. The combination of overlays and playback enables the user to correlate a radar return with a position of the vehicle to determine whether the return is valid. JRAT can optionally filter single radar returns, enabling the user to selectively hide or highlight a desired radar return.

Zaczek, Mariusz P.↗
NASA NTRS2014

Real-Time Science Operations to Support a Lunar Polar Volatiles Rover Mission

Future human exploration of the Moon will likely rely on in situ resource utilization (ISRU) to enable long duration lunar missions. Prior to utilizing ISRU on the Moon, the natural resources (in this case lunar volatiles) must be identified and characterized, and ISRU demonstrated on the lunar surface. To enable future uses of ISRU, NASA and the CSA are developing a lunar rover payload that can (1) locate near subsurface volatiles, (2) excavate and analyze samples of the volatile-bearing regolith, and (3) demonstrate the form, extractability and usefulness of the materials. Such investigations are important both for ISRU purposes and for understanding the scientific nature of these intriguing lunar volatile deposits. Temperature models and orbital data suggest near surface volatile concentrations may exist at briefly lit lunar polar locations outside persistently shadowed regions. A lunar rover could be remotely operated at some of these locations for the approx. 2-14 days of expected sunlight at relatively low cost. Due to the limited operational time available, both science and rover operations decisions must be made in real time, requiring immediate situational awareness, data analysis, and decision support tools. Given these constraints, such a mission requires a new concept of operations. In this paper we outline the results and lessons learned from an analog field campaign in July 2012 which tested operations for a lunar polar rover concept. A rover was operated in the analog environment of Hawaii by an off-site Flight Control Center, a rover navigation center in Canada, a Science Backroom at NASA Ames Research Center in California, and support teams at NASA Johnson Space Center in Texas and NASA Kennedy Space Center in Florida. We find that this type of mission requires highly efficient, real time, remotely operated rover operations to enable low cost, scientifically relevant exploration of the distribution and nature of lunar polar volatiles. The field demonstration illustrated the need for science operations personnel in constant communications with the flight mission operators and the Science Backroom to provide immediate and continual science support and validation throughout the mission. Specific data analysis tools are also required to enable immediate data monitoring, visualization, and decision making. The field campaign demonstrated that this novel methodology of real-time science operations is possible and applicable to providing important new insights regarding lunar polar volatiles for both science and exploration.

Moon; Volatiles; Rover; Missions↗
DOE OSTI2023

Efficient Network Partitioning: Application for Decentralized State Estimation in Power Distribution Grids: Preprint

Increase in the proliferation of DERs requires real-time situational awareness for efficient grid operations. State estimation plays an important role for real time control and management of the power grid. As the sensing infrastructure grows, aggregating and handling high volumes of data at a centralized location is extremely difficult. To address this challenge, this paper first proposes a novel and efficient hierarchical spectral clustering-based network partition algorithm followed by a decentralized compressive sensing (DCS) based state estimation. The applicability of the proposed network partitioning algorithm is tested on IEEE-123 bus, IEEE-8500 node, and a 6204-node distribution network. The results shows that the proposed approach efficiently divides the network into multiple sub-networks with the minimum edge connections among the neighbors. Then, we perform DCS-based state estimation on the 6204-node distribution network after dividing the network into 18 optimal partitions. Simulation results show that DCS-based state estimation recovers the system states with high accuracy and low complexity.

ADMM↗
DOE OSTI2020

COVID-19 Joint Pandemic Modeling and Analysis Platform

The non-pharmaceutical intervention to reduce the impact and spread of COVID-19 requires the development of policies and guidance through a collaborative effort among government, academia, medicine, and citizens. To operationalize this effort, we have developed an all-encompassing situational awareness platform that can process multi-modal and multi-source data allowing informed decision making. Besides, showing the current spread of infection, the platform also captures the impact of human dynamics on the infection spread, location, and availability of critical infrastructure, prediction, and high-performance computing driven simulation. The platform is extensible, allowing third-party integration and services to consume the curated data and analytics in near real-time. We believe the platform will augment critical decision making for reducing the impact and spread of the pandemic.

Thakur, Gautam↗
NASA NTRS2000

Comparison of Pilots' Situational Awareness While Monitoring Autoland Approaches Using Conventional and Advanced Flight Display Formats

A simulation experiment was performed to assess situation awareness (SA) and workload of pilots while monitoring simulated autoland operations in Instrument Meteorological Conditions with three advanced display concepts: two enhanced electronic flight information system (EFIS)-type display concepts and one totally synthetic, integrated pictorial display concept. Each concept incorporated sensor-derived wireframe runway and iconic depictions of sensor-detected traffic in different locations on the display media. Various scenarios, involving conflicting traffic situation assessments, main display failures, and navigation/autopilot system errors, were used to assess the pilots' SA and workload during autoland approaches with the display concepts. From the results, for each scenario, the integrated pictorial display concept provided the pilots with statistically equivalent or substantially improved SA over the other display concepts. In addition to increased SA, subjective rankings indicated that the pictorial concept offered reductions in overall pilot workload (in both mean ranking and spread) over the two enhanced EFIS-type display concepts. Out of the display concepts flown, the pilots ranked the pictorial concept as the display that was easiest to use to maintain situational awareness, to monitor an autoland approach, to interpret information from the runway and obstacle detecting sensor systems, and to make the decision to go around.

Kramer, Lynda J.↗
DOE OSTI2023

Efficient Network Partitioning: Application for Decentralized State Estimation in Power Distribution Grids

Increase in the proliferation of distributed energy resources require real-time situational awareness for efficient grid operations. State estimation plays an important role for the real-time control and management of the power grid. As the sensing infrastructure grows, aggregating and handling high volumes of data at a centralized location is extremely difficult. To address this challenge, this paper first proposes a novel and efficient hier-archical spectral clustering-based network partitioning algorithm followed by a decentralized compressive sensing (DCS)-based state estimation. The applicability of the proposed network partitioning algorithm is tested on an IEEE 123-bus network, an IEEE 8,500-node system, and a 6,000+ node distribution network. The results shows that the proposed approach efficiently divides the network into multiple sub-networks with the minimum number of edge connections among the neighbors. Then, we perform DCS-based state estimation on the 6,000+ node distribution network after dividing the network into 18 optimal partitions. Simulation results show that the DCS-based state estimation recovers the system states with high accuracy and low complexity.

alternating direction method of multipliers↗
DOE OSTI2023

Advanced Grid Operational Technology Edge-Level Threat Detection

This report presents a deployable solution to improve the cybersecurity situational awareness of the legacy SCADA system infrastructure in power grids. The main goal of this project is to provide system owners and operators a highly trusted, intelligent alarm system and comprehensive situational awareness of ongoing or potential cybersecurity threats on the grid network. The key contributions of this project include: (1) the development of software, the Intrusion Detection Visualizer for the Operational Technology Network (IViz-OT), to visualize and locate intrusions on the grid network; (2) testing the signature-based Hybrid Intrusion Detection for Energy Systems (HIDES) for different types of intrusions; (3) the integration of HIDES and IViz-OT into the visualization dashboard; and (4) real-time testing using a hardware-in-the-loop test bed.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Technology Impact and Resource Assessment of Existing and Planned U.S. Biofuel Production: Life Cycle Water Consumption, Water Stress, Land Use, and Criteria Air Pollutants

Biofuels have the potential to strengthen the U.S. energy supply, enhance energy security, and promote economic development. As the United States continues to expand biofuel production, quantifying resource requirements and location-specific constraints is crucial for planning, siting, and technology development to support long-term viability. Accordingly, this work assesses the life cycle resource consumption (water consumption, and land use), water stress and criteria air pollutants associated with expanded U.S. biofuel production over the 2020–2035 period, based on producers’ plans. We perform a bottom-up technology impact assessment and resource assessment by integrating facility-level production statistics with Argonne’s Research and Development (R&D) GREET model and county-level water-stress characterization factors from Available Water Remaining for the United States (AWARE-US) model. Results suggest that by 2035, biofuels could meaningfully contribute to U.S. energy demand, driven primarily by first-generation and waste-based feedstocks with plans for substantial capacity expansion, although cellulosic and e-fuel technologies remain limited. However, growth must be managed to minimize impacts on water resources and land use. These impacts vary by fuel type and facility location, specifically, projected expansion increases water consumption and can elevate water-stress impacts in certain regions like Nebraska, Kansas, Colorado, Idaho, California and North Texas. Direct land use also increases overall, particularly for first-generation feedstocks such as corn and soybeans. These findings underscore the need for continued technological improvements and innovative strategies to manage resource demands as the industry scales and to support complementary deployment within the evolving U.S. energy system.

09 BIOMASS FUELS↗
NASA NTRS2016

The Search for Surviving Direct Samples of Early Solar System Water

We have become increasingly aware of the fundamental importance of water, and aqueous alteration, on primitive solar-system bodies. All classes of astromaterials studied show some degree of interaction with aqueous fluids. Nevertheless, we are still lacking fundamental information such as the location and timing of the aqueous alteration and the detailed nature of the aqueous fluids. Halite crystals in two meteorite regolith breccias were found to contain aqueous fluid inclusions (brines) trapped approx. 4.5 BYBP. Heating/freezing studies of the aqueous fluid inclusions in these halites demonstrated that they were trapped near 25 C. The initial results of our O and H isotopic measurements on these brine inclusions can be explained by a simple model mixing asteroidal and cometary water. We have been analyzing solids and organics trapped alongside the brines in the halites by FTIR, C-XANES, SXRD and Raman, as clues to the origin of the water. The organics show thermal effects that span the entire range witnessed by organics in all chondrite types. Since we identified water-soluble aromatics, including partially halogenated methanol, in some of the halite, we suspected amino acids were also present, but have thus far found that levels of amino acids were undetectable (which is very interesting). We have also been locating aqueous fluid inclusions in other astromaterials, principally carbonates in CI and CM chondrites. Although we have advanced slowly towards detailed analysis of these ancient brines, since they require techniques right at or just beyond current analytical capabilities, their eventual full characterization will completely open the window onto the origin and activity of early solar system water.

Zolensky, Michael↗
DOE OSTI2021

Adding power of artificial intelligence to situational awareness of large interconnections dominated by inverter‐based resources

Abstract Large‐scale power systems exhibit more complex dynamics due to the increasing integration of inverter‐based resources (IBRs). Therefore, there is an urgent need to enhance the situational awareness capability for better monitoring and control of power grids dominated by IBRs. As a pioneering Wide‐Area Measurement System, FNET/GridEye has developed and implemented various advanced applications based on the collected synchrophasor measurements to enhance the situational awareness capability of large‐scale power grids. This study provides an overview of the latest progress of FNET/GridEye. The sensors, communication, and data servers are upgraded to handle ultra‐high density synchrophasor and point‐on‐wave data to monitor system dynamics with more details. More importantly, several artificial intelligence (AI)‐based advanced applications are introduced, including AI‐based inertia estimation, AI‐based disturbance size and location estimation, AI‐based system stability assessment, and AI‐based data authentication.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS2017

Aeronautical Situational Awareness - Airport Surface

This paper advocates for a specific design approach, based on simple principals, yet addresses challenges faced by the system engineers when designing complex data and information infrastructure. The document provides guidance for breaking out various work elements in the overall network architecture design, so that communication systems are conceived and effectively realized regardless of their location, size and local specifics. Although targeted at the Global Airspace System (GAS) and National Airspace System (NAS), this framework can be applied to any network-centric architecture.

networking↗
DOE OSTI2021

Blockchain for Fault-Tolerant Grid Operations

Distribution system fault/failure has a direct impact on customers. Distribution systems are not designed with the contingency of one or more elements failing as the transmission system, however, distribution systems are more likely to have faults in comparison to transmission and generation systems. Most of the distribution systems have a radial design with the protection system assumption of unidirectional power flow. The radial design results in the disconnection of customers for any given component failure. The rapid deployment of distributed energy resources conflicts with the assumption of unidirectional power flow. To maintain/improve the distribution system fault tolerance for a grid with high penetration of distributed energy resources requires improvement. Blockchain can add value to improve fault-tolerant grid operations. That can be achieved using blockchain’s core features of distributed consensus-based decision-making process and immutability. In the process of preparing for an event or system restoration, there is a need for reliable data and system situational awareness. The system situational awareness enables accurate planning for possible scenarios and system restoration after an event, an area where blockchain’s distributed architecture can help. The value of blockchain for a fault-tolerant grid operation is elaborated with three use cases: 1) fault location, isolation, and service restoration; 2) topology identification; and 3) data configuration. These use cases demonstrate how blockchain-based architecture can facilitate bridging the vulnerabilities of the existing implementation.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1989

Spatial cognition and navigation

An experiment that provides data for the development of a cognitive model of pilot flight navigation is described. The experiment characterizes navigational awareness as the mental alignment of two frames of reference: (1) the ego centered reference frame that is established by the forward view out of the cockpit and (2) the world centered reference frame that is established by the aircraft's location on a map. The data support a model involving at least two components: (1) the perceptual encoding of the navigational landmarks and (2) the mental rotation of the map's world reference frame into alignment with the ego centered reference frame. The quantitative relationships of these two factors are provided as possible inputs for a computational model of spatial cognition during flight navigation.

Aretz, Anthony J.↗
NASA NTRS2008

An Autonomous Sensor System Architecture for Active Flow and Noise Control Feedback

Multi-channel sensor fusion represents a powerful technique to simply and efficiently extract information from complex phenomena. While the technique has traditionally been used for military target tracking and situational awareness, a study has been successfully completed that demonstrates that sensor fusion can be applied equally well to aerodynamic applications. A prototype autonomous hardware processor was successfully designed and used to detect in real-time the two-dimensional flow reattachment location generated by a simple separated-flow wind tunnel model. The success of this demonstration illustrates the feasibility of using autonomous sensor processing architectures to enhance flow control feedback signal generation.

Humphreys, William M, Jr.↗
NASA NTRS2016

Initial Demonstration of the Real-Time Safety Monitoring Framework for the National Airspace System Using Flight Data

As new operational paradigms and additional aircraft are being introduced into the National Airspace System (NAS), maintaining safety in such a rapidly growing environment becomes more challenging. It is therefore desirable to have an automated framework to provide an overview of the current safety of the airspace at different levels of granularity, as well an understanding of how the state of the safety will evolve into the future given the anticipated flight plans, weather forecast, predicted health of assets in the airspace, and so on. Towards this end, as part of our earlier work, we formulated the Real-Time Safety Monitoring (RTSM) framework for monitoring and predicting the state of safety and to predict unsafe events. In our previous work, the RTSM framework was demonstrated in simulation on three different constructed scenarios. In this paper, we further develop the framework and demonstrate it on real flight data from multiple data sources. Specifically, the flight data is obtained through the Shadow Mode Assessment using Realistic Technologies for the National Airspace System (SMART-NAS) Testbed that serves as a central point of collection, integration, and access of information from these different data sources. By testing and evaluating using real-world scenarios, we may accelerate the acceptance of the RTSM framework towards deployment. In this paper we demonstrate the framework's capability to not only estimate the state of safety in the NAS, but predict the time and location of unsafe events such as a loss of separation between two aircraft, or an aircraft encountering convective weather. The experimental results highlight the capability of the approach, and the kind of information that can be provided to operators to improve their situational awareness in the context of safety.

Real-time Safety Monitoring↗