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At least 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
NASA NTRS2017

Solar Array Mast Imagery Discussion for ISIW

SAW Mast inspection background: In 2012, NASA's Flight Safety Office requested the Micro Meteoroid and Orbital Debris (MMOD) office determine the probability of damage to the Solar Array Wing (SAW) mast based on the exposure over the life time of the ISS program. As part of the risk mitigation of the potential MMOD strikes. ISS Program office along with the Image Science and Analysis Group (ISAG) began developing methods for imaging the structural components of the Mast.

Kilgo, Gary↗
NASA NTRS2017

The Human Performance Envelope: Past Research, Present Activities and Future Directions

Air traffic controllers (ATCOs) must maintain a consistently high level of human performance in order to maintain flight safety and efficiency. In current control environments, performance-influencing factors such as workload, fatigue and situation awareness can co-occur, and interact, to effect performance. However, multifactor influences and the association with performance are under-researched. This study utilized a high fidelity human in the loop enroute air traffic control simulation to investigate the relationship between workload, situation awareness and ATCO performance. The study aimed to replicate and extend Edwards, Sharples, Wilson and Kirwans (2012) previous study and confirm multifactor interactions with a participant sample of ex-controllers. The study also aimed to extend Edwards et als previous research by comparing multifactor relationships across 4 automation conditions. Results suggest that workload and SA may interact to produce a cumulative impact on controller performance, although the effect of the interaction on performance may be dependent on the context and amount of automation present. Findings have implications for human-automation teaming in air traffic control, and the potential prediction and support of ATCO performance.

human performance envelope↗
NASA NTRS2017

NASA Super Pressure Balloon

NASA is in the process of qualifying the mid-size Super Pressure Balloon (SPB) to provide constant density altitude flight for science investigations at polar and mid-latitudes. The status of the development of the 18.8 million cubic foot SPB capable of carrying one-tone of science to 110,000 feet, will be given. In addition, the operating considerations such as launch sites, flight safety considerations, and recovery will be discussed.

Super Pressure Balloon↗
NASA NTRS2016

Multifactor Interactions and the Air Traffic Controller: The Interaction of Situation Awareness and Workload in Association with Automation

Air traffic controllers (ATCOs) must maintain a consistently high level of human performance in order to maintain flight safety and efficiency. In current control environments, performance-influencing factors such as workload, fatigue and situation awareness (SA) can co-occur, and interact, to affect performance. However, multifactor influences and the association with performance are under-researched. This study utilized a high fidelity human in the loop enroute air traffic control simulation to investigate the relationship between workload, situation awareness and ATCO performance. The study aimed to replicate and extend Edwards, Sharples, Wilson and Kirwan's (2012) previous study and confirm multifactor interactions with a participant sample of ex-controllers. The study also aimed to extend Edwards et al.'s previous research by comparing multifactor relationships across 4 automation conditions. Results suggest that workload and SA may interact to produce a cumulative impact on controller performance, although the effect of the interaction on performance may be dependent on the context and amount of automation present. Findings have implications for human-automation teaming in air traffic control, and the potential prediction and support of ATCO performance.

Workload↗
NASA NTRS2011

TPSAS-NF1676L-12617-DND

Develop innovative lightning strike mitigation technologies to minimize flight safety risks from electromagnetic environmental hazards. (Lightning & HIRF).

George N Szatkowski↗
NASA NTRSDate not supplied

Dynamic Spectrum Allocation in Urban Air Transportation System via Deep Reinforcement Learning

The emerging concepts of Urban Air Mobility (UAM) and Advanced Air Mobility (AAM) open a new paradigm for urban air transportation. A big challenge is that these new aerial vehicles will quickly saturate the already crowded aviation spectrum, which is an essential resource to ensure reliable communications for safe operations. In this paper, we consider an air transportation system where multiple aerial vehicles are operated to transport passengers or cargo from different sources to destinations along their pre-defined paths. During the flight, the minimum communication Quality of Service (QoS) requirement must be achieved to ensure flight safety. Our objective is to minimize the average mission completion time by jointly optimizing the velocity selection and spectrum allocation for all aerial vehicles. We formulate the optimization problem as a multi-stage Markov Decision Process (MDP) where the optimization variables are coupled together. A multi-agent Deep Reinforcement Learning (DRL) based solution is proposed where Value Decomposition Networks (VDN) algorithm is utilized to take discrete actions. Additionally, we propose a heuristic greedy algorithm as a baseline solution. Simulation results show that our learning based solution outperforms the heuristic greedy algorithm and another Orthogonal Multiple Access (OMA) solution in minimizing the mission completion time.

Ruixuan Han↗
NASA NTRSDate not supplied

Dynamic Spectrum Allocation in Urban Air Transportation System via Deep Reinforcement Learning

The emerging concepts of Urban Air Mobility (UAM) and Advanced Air Mobility (AAM) open a new paradigm for urban air transportation. A big challenge is that these new aerial vehicles will quickly saturate the already crowded aviation spectrum, which is an essential resource to ensure reliable communications for safe operations. In this paper, we consider an air transportation system where multiple aerial vehicles are operated to transport passengers or cargo from different sources to destinations along their pre-defined paths. During the flight, the minimum communication Quality of Service (QoS) requirement must be achieved to ensure flight safety. Our objective is to minimize the average mission completion time by jointly optimizing the velocity selection and spectrum allocation for all aerial vehicles. We formulate the optimization problem as a multi-stage Markov Decision Process (MDP) where the optimization variables are coupled together. A multi-agent Deep Reinforcement Learning (DRL) based solution is proposed where Value Decomposition Networks (VDN) algorithm is utilized to take discrete actions. Additionally, we propose a heuristic greedy algorithm as a baseline solution. Simulation results show that our learning based solution outperforms the heuristic greedy algorithm and another Orthogonal Multiple Access (OMA) solution in minimizing the mission completion time.

Ruixuan Han↗
NASA NTRSDate not supplied

Aggregate Risk Tool for Human Space Flight

This project utilized Data fusion capabilities developed from the 2020-2022 Information Fusion (IFDA) IRAD to enhance functionality of a Human Spaceflight (HSF) Aggregate Risk Product developed by the JSC Flight Safety Office. The tool compiles and presents risk data from multiple Program and Commercial Provider vehicles to provide a holistic assessment of residual risk to Program Managers and Technical Authorities prior to HSF Launches. The aggregation or coupling of risks from multiple sources (Examples: PRA, variances, anomaly data bases, Program Risk Management data bases, technical review board minutes, Hazard Analysis, etc.) when analyzed, identify potential areas of elevated risk in components, systems or mission phases that would otherwise be undetected by nonintegrated program risk management tools and possesses.

Patrick Huckaby↗
NASA NTRS2022

Aggregate Risk Tool for Human Space Flight

This tool utilizes Data fusion capabilities developed from the 2020-2022 Information Fusion (IFDA) IRAD to enhance functionality of a Human Spaceflight (HSF) Aggregate Risk Product developed by the JSC Flight Safety Office. The tool compiles and present risk data from multiple Program and Commercial Provider sources to provide a holistic assessment for Program Managers and Technical Authorities to evaluate residual risk prior to HSF Launches. The aggregation, or coupling of risks from multiple sources (Ex: PRA, variances, anomaly data bases, CRM data, technical review board minutes, Hazard Analysis, etc.) identifies areas of elevated risk in components, systems or mission phases that would otherwise be undetected by non-integrated program risk management tools and possesses. Data is then displayed in an interactive user interface/dashboard that enables users to see potential areas of concern requiring more in-depth analysis.

Patrick M Huckaby↗
NASA NTRSDate not supplied

Conjunction Assessment and Deconfliction Paradigm for Co-located Satellite Constellations with On-Spacecraft “Autonomous” Flight Dynamics Control

Constellations that employ highly-automated satellite flight dynamics can operate safely from a collision avoidance (CA) perspective using current CA screening technology and communication paradigms—except when in proximity to other highly-automated constellations: there is no existing arrangement and concept of operations to allow the low-latency CA screenings, exchange of information, and assignment/acceptance of mitigation responsibility that co-location of highly-automated constellations requires. However, the serendipitous co-location of the NASA Starling mission—an autonomously-controlled technology demonstration constellation—and the SpaceX Starlink constellation has presented an opportunity (indeed, a requirement) to develop and build out a solution for safe operations of two (or more) co-located, highly-automated satellite constellations. Such a solution has been designed and constructed, including the required ground node; and it will be exercised as a dedicated, in-flight safety experiment between the two constellations from January to September 2024. Lessons learned from this experiment are expected to feed the design of the US Department of Commerce’s Tracking Control System for Space (TraCSS) space traffic coordination solution.

conjunction assessment↗
NASA NTRSDate not supplied

Why Learning From All Operations Is Imperative

Learning from All Operations – Panel Discussion Introduction: Tzvetomir Blajev, Flight Safety Foundation Why Learning from All Operations is Imperative: Jon Holbrook, NASA Implemented Approaches to Learning from All Operations American Airlines Japan Airlines Southwest Airlines Delta Air Lines Why Learning from All Operations is Imperative (Summary): Immanuel Barshi, NASA

Jon Holbrook↗
NASA NTRS2024

Presound: UAV Diagnostic System Enabled by Vibration-Based Machine Learning

A low-weight, inexpensive small unmanned aerial system (sUAS) that takes off, performs a mission, lands, and safely stows and recharges itself has myriad future applications ranging from agricultural imaging to last-mile package delivery. Likewise, Urban Air Mobility (UAM) systems will enable people to take air taxis from point to point in cities, rapidly moving commuters long distances without concern for road traffic and congestion. Fully electric aviation systems will be cleaner and quieter than ground transport. Cities could eliminate cars and buses, and convert roads to higher capacity bike and pedestrian throughways. Yet, for sUAS as well as UAM, system reliability and assurance is a limiting factor to deploying affordable autonomous flight systems. For this bright future of aviation to be realized, aircraft must be able to autonomously and accurately self-diagnose health issues both before takeoff and during flight. The GreenSight PreSound system is designed to identify defects on aircraft through intelligent analysis of vibration. It accomplishes this by measuring structural vibrations induced by the vehicle’s own propellers, and analyzing that data using a machine learning model that determines whether a defect is present. The PreSound system is designed to require no human oversight, and to operate across a wide array of vehicles through re-training of the model for each target aircraft. PreSound has been developed and seen limited early success using data collected from the GreenSight Dreamer sUAS, a 5lb quadrotor vehicle designed for aerial imaging applications. The final detection model, trained on data with props spinning at 50% throttle, achieves excellent performance with over 99% average accuracy in detecting blade damage using a single FFT vector input. It demonstrates the ability to generalize to new types of blade damage, correctly classifying a different type of blade damage with 98% accuracy. Full test pulses were classified with 100% accuracy, and in live testing, all sets of data during blade movement were classified accurately with over 95% confidence. When trained on in-flight data, the same model achieves an average accuracy of 85% in distinguishing between undamaged and blade-damaged states in flight. The authors believe that these accuracies show significant potential of this approach to expand unmanned flight safety, with significant potential benefits in accelerating Advanced Aerial Mobility (AAM) and UAM aviation applications.

UAS↗
NASA NTRSDate not supplied

Flight Test Evaluation of Autonomous Descending-Decelerating Precision Point-in-Space Approach to the Ground

New forms of highly automated Advanced Air Mobility (AAM) aircraft, such as electric vertical take-off and landing (eVTOL) vehicles, could transform transportation, cargo delivery, and a variety of public services. The National Aeronautics and Space Administration (NASA) conducted a series of flight demonstrations in collaboration with the Defense Advanced Research Projects Agency (DARPA) and Sikorsky Aircraft (a Lockheed Martin company) to progressively evaluate autonomous technologies. The autoland flight test research is a first in series for investigating the world’s first procedural descending-decelerating automated landing with vertical guidance Instrument Flight Procedures (IFP). The Sikorsky Optionally Piloted Vehicle (OPV) experimental UH-60 Black Hawk was used to evaluate a flight path’s four-dimensional trajectory (4DT) management into primitive commands and then follow those commands to a Point-in-Space (PinS) landing to the ground. All flight procedures were manually flown to the ground at 12 degrees with a 20-knot tail wind to ensure flight safety before automation was engaged. New and novel high precision approach procedures could pave the way for all future VTOL operations.

David Zahn↗
NASA NTRS1972

Manned space flight nuclear system safety. Volume 7: Literature review. Part 1: Literature search and evaluation

A review of the literature used in conducting the manned space flight nuclear system safety study is presented. The objectives of the presentation are to identify and evaluate for potential application to study the existing related literature and to provide the information required to include the related literature in the NASA Aerospace Safety Research and Data Institute. More than 15,000 documents were evaluated and identification forms were prepared for 850 reports.

Source record↗
NASA NTRS2010

Verification and Implementation of Operations Safety Controls for Flight Missions

There are several engineering disciplines, such as reliability, supportability, quality assurance, human factors, risk management, safety, etc. Safety is an extremely important engineering specialty within NASA, and the consequence involving a loss of crew is considered a catastrophic event. Safety is not difficult to achieve when properly integrated at the beginning of each space systems project/start of mission planning. The key is to ensure proper handling of safety verification throughout each flight/mission phase. Today, Safety and Mission Assurance (S&MA) operations engineers continue to conduct these flight product reviews across all open flight products. As such, these reviews help ensure that each mission is accomplished with safety requirements along with controls heavily embedded in applicable flight products. Most importantly, the S&MA operations engineers are required to look for important design and operations controls so that safety is strictly adhered to as well as reflected in the final flight product.

Smalls, James R.↗
NASA NTRS1998

Flight Demonstration of Integrated Airport Surface Technologies for Increased Capacity and Safety

A flight demonstration was conducted to address airport surface movement area capacity and safety issues by providing pilots with enhanced situational awareness information. The demonstration presented an integration of several technologies to government and industry representatives. These technologies consisted of an electronic moving map display in the cockpit, a Differential Global Positioning system (DGPS) receiver, a high speed very high frequency (VHF) data link, an Airport Surface Detection Equipment (ASDE-3) radar, and the Airport Movement Area Safety System (AMASS). Aircraft identification was presented to an air traffic controller on an AMASS display. The onboard electronic map included the display of taxi routes, hold instructions, and clearances, which were sent to the aircraft via data link by the controller. The map also displayed the positions of other traffic and warning information, which were sent to the aircraft automatically from the ASDE-3/AMASS system. This paper describes the flight demonstration in detail, along with test results.

Jones, Denise R.↗