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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Integration of Automated Systems (IAS) Flight Test Overview

The Integration of Automated Systems (IAS) Project is conducting a series of 2023 flight tests supporting NASA's Advanced Air Mobility (AAM) and National Campaign efforts. These flights include crewed, test (i.e., ownship) and traffic (i.e., intruder) aircraft that will fly with unique technologies onboard. The presentation will include overviews of the Hazard Perception and Avoidance (HPA) and Flight Path Management (FPM) technical areas but will focus primarily on HPA. HPA will test the FAA's Airborne Collision Avoidance System X (ACAS X), a next-generation collision avoidance tool developed to support different aircraft types and operations. The rotorcraft variant, ACAS Xr, is designed to accommodate existing helicopter platforms and in-development, vertical takeoff and landing (VTOL) concepts, which are critical to the emerging AAM concept of operations. Two configurations of ACAS Xr will be examined: Collision Avoidance System (CAS, similar to the Traffic Collision Avoidance System [TCAS] II) and Detect and Avoid (DAA, previously developed to provide added situational awareness for uncrewed aircraft). Additionally, this system will be explored during cruise and low-speed flight as well as flights within en-route, structured (i.e., dense/urban), and terminal airspaces. Scripted flight conflicts will be conducted, and these conflicts will be mitigated through maneuvers that are manual (i.e., performed by the pilots) or automated (i.e., achieved by the cooperation of the program middleware and onboard ownship systems). Objective data will be collected involving system and pilot performance as well as pilot decisions; subjective data will include pilot opinions of ACAS Xr's alerting and guidance as well as the automated maneuvers.

detect and avoid↗
DOE OSTI2025

Quantifying UAS Observation Error Variance Used in Data Assimilation Systems and Its Impact on Predictive Skill

Observation error determines the weights of the observations and background state used in data assimilation to generate analyses. Quantifying observation error is critical for the optimal assimilation of observational data sets. Uncrewed Aircraft System (UAS) observations have shown potential benefits in filling observational gaps in the lower atmosphere; however, characterization of their error characteristics has been limited. To optimize the use of UAS observations in numerical weather prediction, UAS observation error is estimated based on the 3‐cornered hat diagnostic approach which uses three independent estimates of the atmospheric state. This approach is applied to data from the 2018 Lower Atmospheric Profiling Studies at Elevation‐a Remotely‐piloted Aircraft Team Experiment field campaign using collocated UAS and rawinsonde observations along with output from a set of convection‐permitting model simulations. The estimated observation error values for UAS temperature, wind, and relative humidity measurements were found to be only weakly dependent on height AGL with mean values equal to 0.5°C, 0.8 m s −1 , and 3%, respectively. Only the newly estimated observation error for temperature differed from that previously used to assimilate commercial aircraft observations into global models (1.0°C). However, using this reduced temperature observation error produced more accurate mesoscale analyses and forecasts of both terrain‐driven flows and convection initiation generated by colliding outflow boundaries within the San Luis Valley of Colorado.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

A Nonintrusive Optical Approach to Characterize Heliostats in Utility-Scale Power Tower Plants: Camera Position Sensitivity Analysis

Optics plays a major role in the effectiveness of concentrating solar power (CSP) technologies. The nonintrusive optical (NIO) approach developed by the National Renewable Energy Laboratory uses uncrewed aircraft system (UAS)-based imaging to survey heliostats in a commercial-scale power tower CSP plant and characterize their optical errors. The image processing algorithm uses photogrammetry to calculate the camera position for each image frame, and the accuracy of the estimated optical errors is highly sensitive to the calculated camera position accuracy. In this study, we simulate a series of case studies in python to examine the impact of different parameters of the sensitivity of the camera calculation, including the number of facet corners used as control points for the photogrammetric calculation, precision error in the detected pixel locations of the facet corners in the image, and precision error of the canting and mounting positions of the facets of the heliostat. The case studies consider heliostat geometry based on three commercial designs to serve as representative examples of different possible sizes of heliostats that the NIO method could be applied to. The results show that increasing the number of control points can improve accuracy for heliostats with many facets, pixel precision has a significantly larger impact on camera calculation accuracy than facet canting and mounting errors, and the camera distance and focal length must be chosen to ensure adequate pixel accuracy on the heliostat surface depending on the size of heliostat. In conclusion, based on the results, recommendations for the allowable values of each parameter are provided to achieve the required NIO optical error estimation accuracy depending on the size of heliostat.

14 SOLAR ENERGY↗
DOE OSTI2022

Adaptive Sampling for In Situ Cloud Probe (Final Report)

Clouds play a leading role in the Earth's global energy and solar radiation balance and hydrological cycle. Improving cloud models requires detailed information on the cloud microphysical properties, such as droplet size distribution and number density, liquid water content and cloud composition (droplets, ice particles), which can only be provided by aerial in situ measurements. However, for many atmospheric measurement instruments, the lack of flexibility in selecting the operational mode during operation can lead to uncertainties in sampling and measurement characteristics under continuously varying atmospheric conditions. This SBIR project is developing an advanced, compact optical imaging technology for in situ characterization of cloud hydrometeors. The development involves a deep modification of the existing Mesa Photonics’ Cloud Droplet Measurement System (CDMS) in order to implement real-time automatic adaptive sampling based on the acquired in situ data and environmental parameters. The new system, CDMS-2, implements two measurement modes: side-scatter imaging for smaller hydrometeors and direct bright-field-illumination imaging for larger hydrometeors in a significantly larger sample volume. The system measures the droplet size distribution (DSD) and number density with an added capability of discriminating between liquid water and ice hydrometeors (based on polarization-resolved side-scatter imaging). The instrument will implement automatic switching or alternating between the regular side-scatter imaging mode and sparse/large hydrometeor mode (based on the acquired data). Other adaptive sampling capabilities include variable sample volume and dynamic range (based on the measured DSD). The preferred deployment platforms are uncrewed aircraft systems (UAS) and tethered balloon/kite systems (TBS). The Phase I project achieved (or exceeded) the goals listed in the Work Plan. A CDMS-2 laboratory prototype implementing the polarization-resolved side-scatter imaging mode and direct bright-field-illumination imaging mode was designed and built. Additional capabilities included the variable illumination pulse energy and sample volume. The smallest detectable droplet diameter was improved to 3–4 μm (from the nominal 10 μm value specified for the original CDMS). Discrimination between water droplets and ice particles was experimentally demonstrated. The Phase I prototype was extensively tested and calibrated in the laboratory and also tested in the Pi Cloud Chamber at Michigan Technological University (MTU). The two intensive experimental campaigns at MTU provided unique opportunities of testing the CDMS-2 laboratory prototype under realistic warm and mixed-phase cloud conditions (stable for long periods of time), testing different sampling modes and intercomparing the CDMS-2 prototype to other co-located cloud characterization instruments. The Phase I project successfully demonstrated the feasibility of the proposed technology and identified the engineering challenges of designing a field deployable prototype instrument in Phase II. The Phase I study provides a solid basis for development, characterization and field-testing of the proposed advanced cloud probe with adaptive sampling in Phase II followed by commercialization of the technology in Phase III.

47 OTHER INSTRUMENTATION↗
DOE OSTI2026

Deliberate Motion Analytics Applied to CUAS Sensor Fusion

The Advanced Reactor Safeguards and Security (ARSS) program in the Department of Energy’s Office of Nuclear Energy (DOE-NE) seeks to identify new technology solutions for safeguards and security challenges associated with domestic deployment of advanced nuclear reactors. Research in the ARSS program is investigating alternative physical protection system (PPS) approaches that leverage new detection technologies. This report shows test results from a new form of artificial intelligence (AI) that is called deliberate motion analytics (DMA) when used to spatially and temporally fuse active radar and passive radio frequency (RF) detection that significantly improves detection of uncrewed aircraft systems (UASs). DMA is designed to filter out false positive alarms yet provide highly reliable intrusion detection at nuclear power plants (NPPs) and advanced small modular reactor (ASMR) perimeters. This form of AI is considered to be an enabling technology for security of the future and supports the ARSS investigation of alternative PPSs.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2026

Drone Fleet Summary: NNLEMS UxS Rolodex entry for Sandia

Sandia’s UAS Aviation Operations Unit (UAOU) was established in 2019 to be the single entity at Sandia conducting UAS Ops in support the labs Uncrewed Aircraft Systems (UAS) activities. The UAOU currently consists of >330 FAA Registered UAS with a large variety of primarily Class 1&2 UAS: fixed wing (>90), multi-rotor (>230), hybrids, VTOLs, jets, and balloons. Many of these are threat vehicles presented as targets to Counter-UAS (CUAS) systems as part of performance tests, with the remainder in support of other projects across Sandia often with custom payload needs. The UAOU has ~15 primary pilots and reach back to another ~45 FAA Certified Remote Pilots across Sandia. The team conducts flight and CUAS operations at many test locations, including OCONUS. Sandia was awarded the 2024 DOE Federal Aviation Safety Program Award.

42 ENGINEERING↗
DOE OSTI2023

TRACER UAS CU RAAVEN Flight Data

This dataset includes observations collected using the University of Colorado RAAVEN small Uncrewed Aircraft System (sUAS) during the TRACER Intensive Operations Period. These observations include flights conducted at two primary locations, including an area near the Brazoria National Wildlife Refuge and the University of Houston Coastal Center. Flights were conducted for approximately two weeks per month between June and the end of September, and include two primary flight modes. The first mode is a spiraling profile between the surface and 600 m above ground level, and the second mode includes flight conducted in a series of stepped altitudes between 600 and 20 m above ground level.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2022

Uncrewed Aerial Vehicles and Systems Support Safer Aeronautics Research

Area-I partnered with the NASA SBIR/STTR program to develop Uncrewed Aircraft Systems (UASs) that supported advanced aeronautics research. The company’s developments with NASA culminated in the Prototype-Technology Evaluator and Research Aircraft (PTERA), a versatile UAS enabling low-risk flight experiments that are safer than piloted tests and more dynamic than wind tunnel testing. From the initial seed funding from NASA, Area-I continued to hone its abilities in UAS development, finding success with the Department of Defense and leading to the company’s acquisition by Anduril Industries—a $4.6 billion defense technology company—in 2021.

Bruce R Cogan↗
NASA NTRSDate not supplied

Applying Formal Methods to Safety-Critical Systems

How do you know a proof is correct? Traditionally, mathematical proofs are socially verified – at least one human, following a set of implicit rules of natural language and logic, determines if the proof is believable. If the proof becomes overly tedious and/or is essential to some safety- or mission-critical application, it becomes necessary to determine the soundness to a higher standard. 'Formal methods' refer to mathematically rigorous techniques and tools that enable specification, design, and verification of hardware and software systems. The specification used in formal methods are statements in a mathematical logic while the formal verifications are deductions in that logic. Formal methods can be difficult or time/resource intensive, but offer a higher level of assurance than standard verification through testing or handwritten proofs. This talk will introduce formal methods, motivated by applications of interest to NASA, including uncrewed aircraft operations in the national airspace, urban air environments, and wildfire areas. The audience will be given a crash course in mechanically verified proofs in the Prototype Verification System (PVS), an interactive theorem prover.

Formal Methods↗
NASA NTRSDate not supplied

Chasing Spacecraft

Measurements made during actual flight on a spacecraft represent the holy grail in supporting cutting edge research and providing critical vehicle health information during exposure to the harsh environments of launch and reentry. Remote optical imaging data obtained by the Scientifically Calibrated In-Flight Imagery (SCIFLI) team at NASA Langley Research Center (LaRC) is currently being used by NASA’s Artemis and Commercial Crew Programs to ensure the safety of astronauts. This emerging capability had its genesis during the Space Shuttle Program. A look toward the future will showcase the use of high-altitude long-endurance uncrewed aircraft coupled with novel sensors to support civilian and national flight-testing interests more effectively.

Tom Horvath↗
NASA NTRSDate not supplied

NASA's New Wildland Fire Earth Observation Science & Applications Programmatic Developments

In 2021, the U.S. National Aeronautics & Space Administration (NASA) initiated new programmatic elements within the Science Mission Directorate (SMD) and the Aeronautics Research Mission Directorate (ARMD) focused on supporting wildland fire science and applications improvements, employing the vast array of NASA scientific knowledge, airborne and space-borne Earth Observations (EO) capabilities, technology development (sensor systems, etc.), and large framework modeling efforts. Within the Science Mission Directorate, the NASA Earth Science Division (ESD) will focus on improving our understanding of wildland fire through EO tools and applying rigorous-tested modeling and results of that research into operational use. The ESD Wildfire strategy is to invest in new technology and to better integrate NASA’s satellite, airborne, and ground-based observations with wildfire models to provide the wildfire stakeholders with the information they need to make informed decisions about the pre-, active-, and post-fire conditions. The Applied Science Program has restarted the Wildland Fire Applications Program with a focus on engaging wildland fire management and the fire science community in transitioning EO science efforts into routine use by land management entities at the local, state, national and international level. The NASA Aeronautics Research Mission Directorate will focus on arenas where their aeronautics science and engineering outcomes can benefit the fire management community as well, specifically in the innovative development of Uncrewed Aircraft systems, congested mixed-use platform airspace management issues, new platform configurations supporting wildland fire missions, and other aeronautics-related science / engineering capabilities which may benefit the fire management community. In total, these developments represent a major thrust forward, supporting the goals of utilizing NASA science to benefit humankind. This presentation will highlight the various wildland fire science focus areas identified through collaborations with the wildland fire science and management community and highlight the plans of this new NASA focus area.

NASA↗
NASA NTRSDate not supplied

Non-Repudiation for Drone-Related Data

Concepts for the management of Uncrewed Aircraft Systems (UAS) at scale rely on the exchange of data amongst multiple stakeholders. Even as these concepts vary from State to State and company to company as of today, the movement of data between different entities is a common theme. While there is universal agreement on the necessity of appropriate cybersecurity applied to the various systems involved in communicating these data, there has been little focus on a feasible implementation of non-repudiation in these systems. This paper highlights the current and future need for non-repudiation, supported by references to multiple international organizations, and an approach to implementing non-repudiation leveraging open standards.

Unmanned Aviation Systems Traffic Management↗
NASA NTRS2022

RF Environment Data Analysis for UAS Operations

As the usage of radio frequency spectrum and uncrewed aircraft systems continue to grow, the radio frequency environment and its implications to flight safety should be understood. This is important to ensure control and command links as well as data collection links maintain strong communications during flight. NASA System-Wide Safety (SWS) is currently developing standards of flight safety but lacks methods for establishing confidence in the availability of radio frequency space to make a go/no-go decision for drone flights. This study examines information about the radio modules used by SWS and how they interact with the RF environment though analysis of historical spectrum data. This review studies the potential effectiveness of observing the power spread and occupancy methods as they apply to the flight system radios. It has been determined that viewing the frequency and time when the environment is greater than a threshold which indicates potential interference levels may give insight into the patterns of spectrum usage.

Radio Frequency↗
NASA NTRSDate not supplied

Intercomparison of Ground and Aerial Systems for Urban Advanced Air Mobility Wind Field Campaigns

The need for accurate wind measurement data in urban areas is a rising concern for advanced air mobility such as uncrewed aircraft systems (UAS) and urban air mobility. The lack of quality observations of wind fields and other parameters presents a challenge for operability. Urban areas provide additional difficulty because of the complex terrain and varying building geometry and their associated flow fields. This has led to an extensive knowledge gap when it comes to real-time urban measurements. This paper focuses on comparison of available systems and the types of measurements for urban wind field campaigns. LiDARs and SoDARs are two of many ground instruments capable of gathering the necessary wind field information. UAS is also a viable technique of obtaining aerial wind measurements. Each of these all have specific strengths that make their measurements more suitable than others. Ground based and airborne systems are evaluated and compared to provide a thorough look into which system or instrument might provide the most accurate and definitive results for urban wind field campaigns.

Tyler L Willhite↗
NASA NTRS2022

Non-Repudiation for Drone-Related Data

Concepts for the management of Uncrewed Aircraft Systems (UAS) at scale rely on the exchange of data amongst multiple stakeholders. Even as these concepts vary across nations and industries, the movement of data between entities is a common theme. While there is universal agreement on the necessity of appropriate cybersecurity measures to address data communication, there has been minimal focus on the feasibility of implementing non-repudiation solutions for UAS systems. This means that data exchanged in support of UAS operations are open to “attack” via parties that may deny sending or receiving certain data, which can weaken the effectiveness and acceptability of these systems. This paper highlights the current and future need for non-repudiation, supported by references to multiple international organizations, and an approach to implementing non-repudiation leveraging open standards.

drone↗
NASA NTRSDate not supplied

Pathfinding for Airspace with Autonomous Vehicles (PAAV) Multi-Vehicle Operations with Digital Trajectories

The Path Finding for Airspace with Autonomous Vehicles (PAAV) subproject under ATM-X is developing concepts and solutions to allow pilots to supervise multiple uncrewed flights at a time. This line of research stems from industry's desire to leverage Uncrewed Aircraft (UA) operations to achieve maximum productivity from pilot and aircraft resources, driven partially by pilot staffing shortages. Trajectory based solutions delivered by data link offer a potential solution to the multi-vehicle (m:N) problem by minimizing the number of instructions between remote pilots and air traffic controllers. Furthermore, such solutions avoid the need for pilots to monitor multiple voice frequencies at a time for air traffic control instructions to manage multiple flights. This panel presentation will give a brief introduction to PAAV followed by a description of NASA's AutoResolver capability for generating comprehensive air traffic control clearances and communicating them via data link for controller approval and flight execution.

multi vehicle control, trajectory based operations↗
NASA NTRSDate not supplied

PAAV Tabletop 4 Results – Integrating m:N Remotely Piloted Operations

NASA's Pathfinding for Airspace with Autonomous Vehicles (PAAV) sub-project is investigating procedures and technologies to facilitate seamless integration of future UAS operations into the NAS. The Tabletop 4 activity solicited subject matter expertise to identify solutions to the potential challenges expected when the remote pilot-to-vehicle ratio scales from 1:1 to m:N, where one or more ground-based pilots control multiple uncrewed aircraft. This presentation details the method and high-level results of the PAAV Tabletop 4 activity.

m:N↗
NASA NTRSDate not supplied

Effects of Communication Modality on Pilot-Controller Coordination during a Simulated m:N Operation

The last decade or so has seen growing interest in new control paradigms and concepts of operation for uncrewed aircraft systems (UAS) in which multiple aircraft are piloted remotely by a single or relatively small number of people. Referred to as “one-to-many” and “many-to- many” (alternatively, “multi-operator, multi-vehicle”)—and frequently expressed as the corresponding ratios, 1:N and m:N—such novel configurations of aircraft and the people who manage them are seen as critical to the path to future operations involving UAS. Examples of industry domains interested in these control paradigms are small package delivery services utilizing small UAS and passenger-carrying, short-range “Urban Air Mobility” (UAM) operations. Stakeholders in such operations have identified communication and coordination of flight activity with air traffic controllers (ATC) as a barrier to operations. In contrast to present-day flight operations, in which a pilot communicates with one ATC on one radio frequency for one aircraft, multi-vehicle operations potentially entail a significant increase in pilot task load for management of comms. New concepts, such as UAS Service Suppliers (USSs) and Providers of Services to UAM (PSUs), have been proposed to address the known bottleneck for Air Traffic Management (ATM) presented by multi-vehicle operations. While progress has been steadily made over years developing USSs and PSUs, it is generally expected that initial UAM operations will rely on traditional voice-over-radio communication with ATC for purposes of ATM. The current study was a human-in-the-loop simulation that had participants, each possessing a Private Pilot License, act as the ground-based pilot-in- command for multiple vehicles in a hypothetical UAM service in the San Francisco Bay Area. The experiment utilized a 2-by-3, within-subjects design in which the pilot’s Vehicle Load (4 vs. 12) and Comm System (Voice, Datalink, and a Hybrid) were manipulated. The task given to pilots was to use the Comm System to coordinate flight activity for all aircraft with appropriate controllers, having to obtain departure and arrival clearances at “vertiport” facilities and transition clearances for any intermediate airspaces along the route. Pilots were additionally responsible for compliance with vectoring instructions issued by ATC. Subjective workload questionnaires (NASA-TLX) were administered following each experimental trial. Screen recordings of the pilot’s Ground Control Station (GCS) and audio recordings of trials were subsequently coded to obtain performance metrics: response times and error rates. Presented in this paper are results related to pilot responses to vectoring instructions issued by ATC. Workload was found to be significantly higher in the 12-Vehicle condition compared to the 4-Vehicle condition, nearly maxing out the NASA-TLX overall workload scale. There was no significant difference made by the Comm System on workload ratings. Pilots’ response times to communications were fastest in the Voice condition, although overall “service time” for compliance was shorter in Datalink and Hybrid conditions in most cases. Errors by pilots were frequent in both Vehicle Load conditions, most perniciously when using the Voice system. The results of this study suggest tradeoffs in advantages and disadvantages of the three comm systems. Recommendations for communication system design are provided taking the tradeoffs into account.

Garrett G Sadler↗