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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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162 records · Page 9
All sourcesNASA NTRSDOE OSTI
NASA NTRS2021

Empirical Model of 10 – 130 MeV Solar Energetic Particle Spectra at 1 AU Based on Coronal Mass Ejection Speed and Direction

We present a new empirical model to predict solar energetic particle (SEP) event integrated and peak intensity spectra between 10 and 130 MeV at 1 AU, based on multi-point spacecraft measurements from the Solar TErrestrial RElations Observatory (STEREO), the Geostationary Operational Environmental Satellites (GOES), and the Payload for Antimatter Matter Exploration and Light-nuclei Astrophysics (PAMELA) satellite experiment. The analyzed data sample includes 32 SEP events occurring between 2010 and 2014, with a statistically significant proton signal at energies in excess of a few tens of MeV, unambiguously recorded at three spacecraft locations. The spatial distributions of SEP intensities are reconstructed by assuming an energy-dependent 2D Gaussian functional form, and accounting for the correlation between the intensity and the speed of the parent coronal mass ejection (CME), and the magnetic-field-line connection angle. The CME measurements used are from the Space Weather Database Of Notifications, Knowledge, Information (DONKI). The model performance, including its extrapolations to lower/higher energies, is tested by comparing with the spectra of 20 SEP events not used to derive the model parameters. Despite the simplicity of the model, the observed and predicted event-integrated and peak intensities at Earth and at the STEREO spacecraft for these events show remarkable agreement, both in the spectral shapes and their absolute values.

Alessandro Bruno↗
NASA NTRS2020

Operations Concept for Responding to Urgent Requests for NASA-ISRO Synthetic Aperture Radar (NISAR)

The NASA-ISRO Synthetic Aperture Radar, or NISAR, mission is an Earth-mapping radar observatory to be launched from Sriharikota (India) in 2022. This mission is a collaboration between the National Aeronautics and Space Administration (NASA) and the Indian Space Research Organization (ISRO). This spacecraft will carry two instruments that will operate at radar wavelengths (L and Sband) and will provide data for understanding changes in the Earth’s land surface. The scientific data from this mission will revolutionize our understanding of the causes and consequences of land surface changes on Earth, ranging from Solid Earth Deformation in the form of natural hazards like earthquakes, volcanic eruptions and landslides, to ecosystem disturbances, to changes in the cryosphere (measurements of polar ice caps, ice sheets and sea ice). A nominal Reference Observation Plan, that repeats roughly every 12-24 days, developed prior to launch by the NISAR Mission Planning team, in consultation with the Science Team, will form the basis of science data collection by the payload instruments onboard the NISAR observatory after launch. Scheduling of science observations for the mission requires accounting for limited spacecraft resources like onboard data storage, downlink capacity, energy/power, thermal limits and instrument duty cycles. In addition to nominal science data collection, the project has a Level 1 requirement to respond to requests for urgent data acquisition over disaster sites (natural or anthropogenic) by scheduling new acquisitions within 24 hrs of notification and delivering science data within 5 hours of data acquisition. This capability is to be exercised on a ‘best-efforts basis’. While the definition of what constitutes an ‘urgent request’, and how such requests would be submitted to the project, is within the domain of the Science Team, the Mission System team is responsible for developing the baseline operations concept and implementation approach for responding to such requests. Given the ‘best-efforts’ nature of this requirement, a few highlevel guidelines have been developed to help guide the formulation of the operations concept, and are presented in this paper. Requests for urgent response data will be accommodated following the guiding principle of minimal to no impact on nominal science and planned engineering activities. No change in satellite orbit or attitude will be made for urgent response. Restricting response approaches to only changing the downlink and/or ground processing priority for existing observations, and adding new observations only in areas where NISAR will not be nominally imaging, allows for minimal impact on the Reference science Observation Plan. No instrument mode changes will be allowed for urgent response (except for high-priority requests), and no new observations that impact either planned science or engineering activities will be scheduled. Additionally, data requests must fit within the available project resource margins (both spacecraft and ground resources are to be evaluated). Both JPL and ISRO will be involved at various steps of the implementation, irrespective of whether the urgent request is for L-SAR (NASA instrument) or S-SAR (ISRO instrument) or a joint dataset.

Sharma, Priyanka↗
NASA NTRS2023

Land Use Control Implementation Plan

Land Use Control (LUC) Inspections Report 2021 for John F. Kennedy Space Center(KSC), Florida. This letter report documents the quarterly LUC inspections the KSC Remediation Group conducts at sites with approved LUC Implementation Plans (LUCIPs). Land Use Control Inspections Report 2022 for John F. Kennedy Space Center, FL. This Land Use Control Implementation Plan (LUCIP) has been prepared to inform current and potential future users of Wilson Corners of institutional controls that have been implemented at the site. Although there are no current unacceptable risks to human health or the environment associated with Wilson Corners, institutional land use controls (LUCs) are necessary to prohibit the use of groundwater. Controls will include periodic inspection, condition certification and agency notification.

Christopher D Adkison↗
NASA NTRS2023

Technical Basis Related to the Posture of NASA’s Office of Safety and Mission Assurance for the Launch of Radioactive Material Other than Space Nuclear Systems: Volume 1–Overview of Analysis and Results

NASA has launched and reentered payloads containing radioactive material for over 50 years. The isotopes, their quantity, and their form have varied significantly. The handling of this material prior to its integration into the spacecraft at the launch Center (and after its return to Earth after flight, if applicable) falls under the purview of the Office of the Chief Health and Medical Officer, while after the radioactive material is integrated into the spacecraft at the launch Center, it falls under the purview of the Office of Safety and Mission Assurance’s (OSMA) Nuclear Flight Safety Program. Historically, OSMA concurrence was required for any launch or reentry involving radioactive material. However, OSMA recently revisited this posture due to changes in the Federal policy in this area, and the significant accrued experience. The current report represents the more quantitative study envisioned in the recent change in posture. More specifically, this document addresses the potential risks and other considerations associated with launching small quantities of radioactive material (below the level requiring the Federally-mandated process in National Security Presidential Memorandum- (NSPM-) 20, “Presidential Memorandum on Launch of Spacecraft Containing Space Nuclear Systems” (USG, 2019) to provide the technical basis for when such activities require OSMA concurrence versus notification, as it relates to nuclear flight safety.

Don Helton↗
NASA NTRSDate not supplied

Qualitative Data Coding of User Experience with an Urban Air Mobility Fleet Manager Interface

The NASA Aeronautics Research Mission Directorate created the High Density Vertiplex (HDV) project to integrate and evaluate a prototype Urban Air Mobility (UAM) ecosystem. Part of the HDV testing environment included a prototype operator user interface called the Fleet Manager Interface (FMI). In 2023, HDV conducted flight testing with the FMI during which a user experience (UX) study was performed to assess the quality of UX and elicit design recommendations. As a result, a large database of open-ended, qualitative responses was generated and then coded using a new qualitative data coding technique called Directive String Coding, which used a blended coding approach to generate actionable heuristics that stakeholders (e.g., researchers, UI designers, software developers) could use to answer specific research questions and make future design decisions. The key themes that arose from the coded responses showed that the UX was pleasant, system notifications should be more salient, and information across multiple screens should be integrated into a central display. As the Fleet Manger operational role is still being defined, it is vital to increase our understanding of the tools and capabilities needed for such a role. The results from HDV work will eventually feed into standards for vertiport operations that will enable safe and scalable UAM operations in the United States.

high density vertiplex↗
NASA NTRSDate not supplied

Identifying Information Needs and Tools to Support Interactions between Upper Class E Traffic Management (ETM) Operations and the Air Traffic System (ATS)

With the introduction of high-altitude long endurance (HALE) vehicles and balloons designed to operate above 60,000 feet, the frequency and duration of operations in Upper Class E airspace are expected to increase. In response to the need for scalable traffic management for these diverse operations at higher altitudes, the FAA introduced the Upper Class E Traffic Management (ETM) concept. Like the successful demonstration of Uncrewed Aircraft System (UAS) Traffic Management (UTM), the ETM concept is also designed as a community-based, industry-driven cooperative approach to traffic management. As these vehicles and balloons ascend to/descend from ETM Cooperative Areas in Upper Class E, they will transit through Class A controlled airspace where they will interact with various entities of the conventional Air Traffic System (ATS) (e.g., Air Traffic Control (ATC)). This work explores tools that will help support ETM-ATS interactions for users throughout the ATS, as well as ETM Operators. An information needs analysis using ETM-ATS interaction use cases, revealed that the needed functionalities generally grouped themselves into two main themes, the visualization of flights and airspace designations, and digital communication capabilities across various human users. In this paper, we describe two envisioned tools, 1) an Integrated Visualization Tool to display flight information and airspace designations, and 2) an Integrated Digital Communication Tool to facilitate two-way information exchange between users about vehicle position information, the coordination of airspace approvals, and notifications. The tools we describe create an integrated visual representation of vehicles and airspace designations with a set of communication capabilities to consolidate information into a single display interface. These tools may be used to guide the development of prototype tools for demonstrations at the National Aeronautics and Space Administration (NASA) Ames Research Center to further explore ETM-ATS interactions within the ETM concept.

Upper Class E Traffic Management (ETM)↗
NASA NTRSDate not supplied

Identifying Information Needs and Tools to Support Interactions between Upper Class E Traffic Management (ETM) Operations and the Air Traffic System (ATS)

With the introduction of high-altitude long endurance (HALE) vehicles and balloons designed to operate above 60,000 feet, the frequency and duration of operations in Upper Class E airspace are expected to increase. In response to the need for scalable traffic management for these diverse operations at higher altitudes, the FAA introduced the Upper Class E Traffic Management (ETM) concept. Like the successful demonstration of Uncrewed Aircraft System (UAS) Traffic Management (UTM), the ETM concept is also designed as a community-based, industry-driven cooperative approach to traffic management. As these vehicles and balloons ascend to/descend from ETM Cooperative Areas in Upper Class E, they will transit through Class A controlled airspace where they will interact with various entities of the conventional Air Traffic System (ATS) (e.g., Air Traffic Control (ATC)). This work explores tools that will help support ETM-ATS interactions for users throughout the ATS, as well as ETM Operators. An information needs analysis using ETM-ATS interaction use cases, revealed that the needed functionalities generally grouped themselves into two main themes, the visualization of flights and airspace designations, and digital communication capabilities across various human users. In this paper, we describe two envisioned tools, 1) an Integrated Visualization Tool to display flight information and airspace designations, and 2) an Integrated Digital Communication Tool to facilitate two-way information exchange between users about vehicle position information, the coordination of airspace approvals, and notifications. The tools we describe create an integrated visual representation of vehicles and airspace designations with a set of communication capabilities to consolidate information into a single display interface. These tools may be used to guide the development of prototype tools for demonstrations at the National Aeronautics and Space Administration (NASA) Ames Research Center to further explore ETM-ATS interactions within the ETM concept.

Upper Class E Traffic Management (ETM)↗
NASA NTRS2024

Land Use Control Implementation Plan

This Land Use Control Implementation Plan (LUCIP) has been prepared to inform current and potential future users of the Corrosion Atmospheric Exposure Facility (CAEF) of institutional controls that have been implemented at the site. 1 Although most areas at CAEF do not pose current unacceptable risks to human health or the environment, areas of arsenic-impacted soil exceeding the Florida Department of Environmental Protection (Florida DEP) residential soil cleanup target levels (SCTLs) have been identified. Institutional land use controls (LUCs) are necessary to prevent contact with surface and subsurface soils at the site. Controls will include periodic inspection, condition certification, and agency notification.

soil↗
NASA NTRSDate not supplied

Qualitative Data Coding of User Experience with an Urban Air Mobility Fleet Manager Interface

The NASA Aeronautics Research Mission Directorate created the High Density Vertiplex (HDV) project to integrate and evaluate a prototype Urban Air Mobility (UAM) ecosystem. Part of the HDV testing environment included a prototype operator user interface called the Fleet Manager Interface (FMI). In 2023, HDV conducted flight testing with the FMI during which a user experience (UX) study was performed to assess the quality of UX and elicit design recommendations. As a result, a large database of open-ended, qualitative responses was generated and then coded using a new qualitative data coding technique called Directive String Coding, which used a blended coding approach to generate actionable heuristics that stakeholders (e.g., researchers, UI designers, software developers) could use to answer specific research questions and make future design decisions. The key themes that arose from the coded responses showed that the UX was pleasant, system notifications should be more salient, and information across multiple screens should be integrated into a central display. As the Fleet Manger operational role is still being defined, it is vital to increase our understanding of the tools and capabilities needed for such a role. The results from HDV work will eventually feed into standards for vertiport operations that will enable safe and scalable UAM operations in the United States.

high density veriplex↗
NASA NTRSDate not supplied

Developing a Cloud-Based ArcGIS Image Service for TROPOMI Level 2 Data: Preprocessing, Transformation, and Publication

TROPOMI, the Tropospheric Monitoring Instrument aboard the Sentinel-5 Precursor satellite, provides high spatiotemporal resolution atmospheric measurements. It is essential for monitoring air quality, greenhouse gases, and other trace gases. Integrating TROPOMI Level 2 data into an ArcGIS Image Service marks a significant advancement in the accessibility and utility of satellite-derived environmental information for GIS applications. This paper details the methodology for building an ArcGIS Image Service tailored to handle TROPOMI Level 2 data, with a focus on preprocessing, transformation, and cloud-based publication. The workflow utilizes Python and ArcPy for data reformatting, reprojection, and updating, ensuring efficient processing and cloud-based notifications. By establishing a robust pipeline, the ArcGIS Image Service provides real-time access to TROPOMI Level 2 data, enabling users to visualize, analyze, and interpret atmospheric phenomena effectively.

Level 2 Data, ArcGIS, Image Service, ArcPy, OGC↗
DOE OSTI2024

Systems and methods for predictive lane change

A system includes a controller comprising at least one processor coupled to a memory storing instructions that, when executed by the at least one processor, cause the at least one processor to perform operations comprising: receiving information indicative of operation of the vehicle and of a driving condition for the vehicle; determining that a speed of the vehicle is less than a target speed for the vehicle based on the received information; determining, in response to the determination that the speed is less than the target speed, that the lane change and takeover event is at least one of feasible or efficient based on the received information; and providing, in response to the determination regarding the lane change and takeover event, a notification.

Borhan, Hoseinali↗
DOE OSTI2024

Systems, methods, and devices for failure detection of one or more energy storage devices

An energy storage device management system can include a management portion for charging/discharging an energy storage device and an ultrasound interrogation portion for passing ultrasound energy through the energy storage device during charge/discharge cycles. A memory stores a stream of capture data instances derived from ultrasound energy exiting the energy storage device and baseline ultrasound data instances corresponding with the energy storage device during normal charging/discharging thereof. A processor can compare each capture data instance with the baseline ultrasound data and detect abnormal operating states of the energy storage device. A warning system can issue a notification when abnormal operating states are detected.

Kowalski, Jeffrey A.↗
DOE OSTI2025

Improving Cyber Situational Understanding

Effective cybersecurity operations require the ability to analyze large amounts of information to assess security risks and formulate defensive strategies against adversaries. This has become more complex in recent years as the sprawl and interconnectivity of devices grows through implementation of virtualization, cloud computing, and Internet of Things (IoT). The amount of data and analysis required for effective cybersecurity command and control decisions far exceeds humans’ capacity to perform manually. We characterize the analysis problem as cyber situational understanding. The research presented to improve cyber situational understanding focuses on vulnerability analysis and threat intelligence. Regarding vulnerabilities, entities must analyze and plan work for between thousands and tens of thousands of software vulnerabilities annually. Entities heavily use network firewalls to limit vulnerability exposure. As a result, some of these vulnerabilities permit exposure to adversarial exploitation, whereas others are inaccessible and therefore present negligible risk of exploitation. Distinguishing between high and low risk software vulnerabilities requires a deep understanding of the vulnerability, network firewall protection, and characteristics of the targeted device. This problem is solved by extracting network service features from vulnerability data features using both machine-learning and natural language processing. Then, the network firewall topology is parsed to determine which vulnerabilities are reachable by adversaries. Ultimately, a state-based safety analysis ascertains which vulnerabilities are unsafe. A related vulnerability analysis problem occurs in cybersecurity operations when associating an entity’s hardware and software assets to public vulnerability databases. Assets often reveal hardware and software through installation artifacts and network service identification, and entities store these artifacts in inventory databases. However, software and hardware vendors apply a standard Common Platform Enumeration (CPE) naming convention when publicly reporting vulnerabilities. Associating these two datasets often requires many hours to days of manual inspection. The proposed solution automates the mapping approach of human analysts using fuzzy matching techniques, natural language processing, and, ultimately, machine learning to present a small set of recommendations for mapping the two datasets. The result significantly reduces human analysis time and reduces the occurrence of false positives in vulnerability notifications. Finally, cyber threat intelligence (CTI) requires associating cyber observable artifacts, such as IP addresses, URIs, and file hashes, with cyber threat tactics, techniques, and procedures. Unfortunately, most CTI data is compartmentalized across multiple organizations and cannot be shared due to the legal and reputational risk with cyber threat being associated with the entity. The approach to solving this problem inovlves using a distributed ledger with anonymous token spending and authentication. This allows a consortium of semi-trusted entities to share the workload of curating CTI for a threat sharing community’s cooperative benefit.

Huff, Philip↗
DOE OSTI2025

Correlation Between Weather Alerts and Grid Component Failures for Grid Alert

Weather events cause most grid failures. Often, we even get notifications on our phones to take cover or be prepared for an imminent event. If electric grid utilities had a similar warning that also included probable scenarios and the equipment involved, they could prepare and minimize the effects. Recent research at Idaho National Laboratory into electric grid risk analysis methods resulted in a tool that allows for the development of the most likely scenarios given failure probabilities of grid components. INL has a project with the U.S. Department of Energy’s Cybersecurity, Energy Security, and Emergency Response (CESER) program to develop a Grid Alert application that receives messages from the existing emergency alert system, filters and determines components possibly affected by the emergency event, calculates probable scenarios uses MASTERRI and then notifies the utility if there is significant risk. Historical failure data of elements that comprise the U.S. electric grid have been compiled by utilities and organizations such as the international regulatory body North American Electric Reliability Corporation (NERC). Nominal failure rates are obtained from this data. To make this tool possible, estimated failure rates are needed for different component types given the alert type, severity, and location. Historic weather-related grid element failures are correlated with historic weather events from Integrated Public Alert & Warning System (IPAWS). These correlated events and failures are used along with Bayesian updates from the historical norms to provide a modified failure rate for grid elements in the alert areas and calculate probable scenarios. This discusses the Grid Alert project plan but focuses on the data gathered and process used in determining failure rates for possible grid failure scenarios.

24 - POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Natural Hazard Forecast Alert Grid Risk System

Weather events cause most power outages. Often, we even get notifications on our phones to take cover or be prepared for an imminent event. If electric grid utilities had a similar warning that also included probable scenarios and the equipment involved, they could prepare and minimize the effects. Idaho National Laboratory had a project with the U.S. Department of Energy’s Cybersecurity, Energy Security, and Emergency Response program to develop a grid alert application that receives messages from the existing emergency alert system, filters and determines components possibly affected by the emergency event, calculates probable scenarios using MASTERRI (Modeling And Simulation for Targeted Reliability and Resilience Improvement). For high-risk events, the application can then send alert links to subscribed electric distribution utility operations staff to allow them to see and evaluate the scenarios and the impact in a web based interactive map tool. This proof of concept application used data from utilities and organizations, such as the international regulatory body North American Electric Reliability Corporation, which have complied historical failure data of elements that comprise the U.S. electric grid. Nominal failure rates are obtained from this data. To make this tool possible, estimated failure rates were calculated for different component types given the alert type, severity, and location. Historic weather-related grid element failures were correlated with historic weather events from the Integrated Public Alert & Warning System. These correlated events and failures are used along with Bayesian updates from the historical norms to provide a modified failure rate for grid elements in the alert areas and calculate probable scenarios. Working with an industry collaborator, actual grid models and data were used for demonstration cases. This report outlines the work performed for this project.

24 - POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS2015

Embedded Systems Hardware Integration and Code Development for Maraia Capsule and E-MIST

The cost of sending large spacecraft to orbit makes them undesirable for carrying out smaller scientific missions. Small spacecraft are more economical and can be tailored for missions where specific tasks need to be carried out, the Maraia capsule is such a spacecraft. Maraia will allow for samples of experiments conducted on the International Space Station to be returned to earth. The use of balloons to conduct experiments at the edge of space is a practical approach to reducing the large expense of using rockets. E-MIST is a payload designed to fly on a high altitude balloon. It can maintain science experiments in a controlled manner at the edge of space. The work covered here entails the integration of hardware onto each of the mentioned systems and the code associated with such work. In particular, the resistance temperature detector, pressure transducers, cameras, and thrusters for Maraia are discussed. The integration of the resistance temperature detectors and motor controllers to E-MIST is described. Several issues associated with sensor accuracy, code lock-up, and in-flight reset issues are mentioned. The solutions and proposed solutions to these issues are explained.

capsule↗