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All sourcesNASA NTRSDOE OSTI
NASA NTRS2023

Monitoring Airspace Complexity and Determining Contributing Factors

The national airspace has evolved over many years to accommodate increased traffic demand while simultaneously maintaining air travel as one of the safest forms of transportation. One of the reasons for this success is the ability of the air traffic control system and the operators to adapt and accommodate to situations that routinely disrupt normal operations. These situations may include: adverse weather, delays, early arrivals, equipment outages, and other factors that are outside the operators’ ability to control. These factors can lead to states where automation is unable to properly handle these issues, and therefore air traffic controllers and pilots have to intervene — ultimately increasing communication between operators resulting in higher workload. As controller workload increases to handle sub-optimal operating conditions, complexity increases. This is because, under these conditions humans are required to make tactical decisions in response to external factors. This results in a departure from the original strategic plan where operations would be more efficiently managed. Human operators manage airspace complexity under rigid regulations but in a constantly changing environment. The airspace is divided into sectors and the number of aircraft assigned to each controller is limited for safe handling. Some prior studies devised airspace complexity metrics in commercial aviation and related these metrics to controller workload. The upper bounds on the system load are pre-determined. Such bounds on complexity make for a safe system, but the system cannot scale and adapt to autonomous, dense, and heterogeneous traffic — including the many types of Unmanned Aerial Vehicles (UAVs) envisioned to be added to the operations. We hypothesize that, as traffic density and heterogeneity grow, and other key metrics change, there will be phase transitions at which the way traffic should be managed changes significantly. We offer a method for in-time detection of contributing factors that lead to phase transitions, characterized by increased complexity. To the best of our knowledge, there is no tool similar to ours that identifies such contributing factors or precursor patterns.

Precursor↗
NASA NTRS2013

High-Power Single-Mode 2.65-micron InGaAsSb/AlInGaAsSb Diode Lasers

Central to the advancement of both satellite and in-situ science are improvements in continuous-wave and pulsed infrared laser systems coupled with integrated miniaturized optics and electronics, allowing for the use of powerful, single-mode light sources aboard both satellite and unmanned aerial vehicle platforms. There is a technological gap in supplying adequate laser sources to address the mid-infrared spectral window for spectroscopic characterization of important atmospheric gases. For high-power applications between 2 to 3 micron, commercial laser technologies are unsuitable because of limitations in output power. For instance, existing InP-based laser systems developed for fiber-based telecommunications cannot be extended to wavelengths longer than 2 micron. For emission wavelengths shorter than 3 micron, intersubband devices, such as infrared quantum cascade lasers, become inefficient due to band-offset limitations. To date, successfully demonstrated singlemode GaSb-based laser diodes emitting between 2 and 3 micron have employed lossy metal Bragg gratings for distributed- feedback coupling, which limits output power due to optical absorption. By optimizing both the quantum well design and the grating fabrication process, index-coupled distributed-feedback 2.65-micron lasers capable of emitting in excess of 25 mW at room temperature have been demonstrated. Specifically, lasers at 3,777/cm (2.65 micron) have been realized to interact with strong absorption lines of HDO and other isotopologues of H2O. With minor modifications of the optical cavity and quantum well designs, lasers can be fabricated at any wavelength within the 2-to-3-micron spectral window with similar performance. At the time of this reporting, lasers with this output power and wavelength accuracy are not commercially available. Monolithic ridge-waveguide GaSb lasers were fabricated that utilize secondorder lateral Bragg gratings to generate single-mode emission from InGaAsSb/ AlInGaAsSb multi-quantum well structures. The device fabrication utilizes etched index-coupled gratings in the top AlGaAsSb cladding of the laser chip along the ridge waveguide, whereas commercial lasers that emit close to this wavelength include loss-coupled metal gratings that limit the output power of the laser. Semiconductor-laser-based spectrometers can be used to replace gas sensors currently used in industry and government. With the availability of high-power laser sources at mid-infrared wavelengths, sensors can target strong fundamental gas absorption lines to maximize instrument sensitivity.

Frez, Clifford F.↗
NASA NTRSDate not supplied

A Preliminary Development of The Intelligent Change Detection System (ICDS): Using Machine Learning to Combat Change Blindness in Remote Operation Environments

The emergence of Advance Air Mobility (AAM) will increase the number and types of aerial vehicles operating in shared airspaces, which will subsequently affect the amount of actionable data that ground control station operators (GCSOs) will be expected to manage. In this environment, GCSOs are particularly susceptible to the visual perceptual phenomenon known as change blindness, in which a stimulus undergoes a change without the change being noticed by its observer. A machine agent designed to detect change blindness and mitigate the effects could improve human agent performance in a data-saturated remote operations environment. The objective of this paper is to describe a proof-of-concept system architecture that integrates real-time eye tracking and vehicle telemetry data to prevent human-agent errors resulting from change blindness while operating aircraft from a remote ground control station (GCS).

Real-Time Streaming Data Architecture↗
NASA NTRSDate not supplied

A Preliminary Development of The Intelligent Change Detection System (ICDS): Using Machine Learning to Combat Change Blindness in Remote Operation Environments

The emergence of Advance Air Mobility (AAM) will increase the number and types of aerial vehicles operating in shared airspaces, which will subsequently affect the amount of actionable data that ground control station operators (GCSOs) will be expected to manage. In this environment, GCSOs are particularly susceptible to the visual perceptual phenomenon known as change blindness, in which a stimulus undergoes a change without the change being noticed by its observer. A machine agent designed to detect change blindness and mitigate the effects could improve human agent performance in a data-saturated remote operations environment. The objective of this paper is to describe a proof-of-concept system architecture that integrates real-time eye tracking and vehicle telemetry data to prevent human-agent errors resulting from change blindness while operating aircraft from a remote ground control station (GCS).

Real-Time Streaming Data Architecture↗
NASA NTRSDate not supplied

Hybrid Modeling for Complex Systems Health Management

The research work presents application of hybrid physics-informed machine learning to a representative electric powertrain for unmanned aerial vehicles. The model is composed of physics-derived and empirical equations, integrated with connected networks that are strategically placed within the model to substitute equations that are subject to large uncertainty. Polynomial fit driven by heuristics or empirical observations can be substituted by more flexible networks that can minimize the error between model predictions and observations without being restricted to a predefined functional form. This modeling strategy allows training of networks deep inside the model and unknown parameters in a single learning stage. The powertrain model consists of Li-ion batteries, electronic speed controller with pulse-width modulation, and brush-less DC motor with connected propeller. Results obtained from combination of laboratory and simulation tests are discussed in this work.

PINNS↗
NASA NTRS2012

Requirements Flowdown for Prognostics and Health Management

Prognostics and Health Management (PHM) principles have considerable promise to change the game of lifecycle cost of engineering systems at high safety levels by providing a reliable estimate of future system states. This estimate is a key for planning and decision making in an operational setting. While technology solutions have made considerable advances, the tie-in into the systems engineering process is lagging behind, which delays fielding of PHM-enabled systems. The derivation of specifications from high level requirements for algorithm performance to ensure quality predictions is not well developed. From an engineering perspective some key parameters driving the requirements for prognostics performance include: (1) maximum allowable Probability of Failure (PoF) of the prognostic system to bound the risk of losing an asset, (2) tolerable limits on proactive maintenance to minimize missed opportunity of asset usage, (3) lead time to specify the amount of advanced warning needed for actionable decisions, and (4) required confidence to specify when prognosis is sufficiently good to be used. This paper takes a systems engineering view towards the requirements specification process and presents a method for the flowdown process. A case study based on an electric Unmanned Aerial Vehicle (e-UAV) scenario demonstrates how top level requirements for performance, cost, and safety flow down to the health management level and specify quantitative requirements for prognostic algorithm performance.

video acuity↗
NASA NTRS2010

Methods for In-Flight Wing Shape Predictions of Highly Flexible Unmanned Aerial Vehicles: Formulation of Ko Displacement Theory

The Ko displacement theory is formulated for a cantilever tubular wing spar under bending, torsion, and combined bending and torsion loading. The Ko displacement equations are expressed in terms of strains measured at multiple sensing stations equally spaced on the surface of the wing spar. The bending and distortion strain data can then be input to the displacement equations to calculate slopes, deflections, and cross-sectional twist angles of the wing spar at the strain-sensing stations for generating the deformed shapes of flexible aircraft wing spars. The displacement equations have been successfully validated for accuracy by finite-element analysis. The Ko displacement theory that has been formulated could also be applied to calculate the deformed shape of simple and tapered beams, plates, and tapered cantilever wing boxes. The Ko displacement theory and associated strain-sensing system (such as fiber optic sensors) form a powerful tool for in-flight deformation monitoring of flexible wings and tails, such as those often employed on unmanned aerial vehicles. Ultimately, the calculated displacement data can be visually displayed in real time to the ground-based pilot for monitoring the deformed shape of unmanned aerial vehicles during flight.

Ko, William L.↗
NASA NTRS2017

A Virtual Laboratory for Aviation and Airspace Prognostics Research

Integration of Unmanned Aerial Vehicles (UAVs), autonomy, spacecraft, and other aviation technologies, in the airspace is becoming more and more complicated, and will continue to do so in the future. Inclusion of new technology and complexity into the airspace increases the importance and difficulty of safety assurance. Additionally, testing new technologies on complex aviation systems and systems of systems can be challenging, expensive, and at times unsafe when implementing real life scenarios. The application of prognostics to aviation and airspace management may produce new tools and insight into these problems. Prognostic methodology provides an estimate of the health and risks of a component, vehicle, or airspace and knowledge of how that will change over time. That measure is especially useful in safety determination, mission planning, and maintenance scheduling. In our research, we develop a live, distributed, hardware- in-the-loop Prognostics Virtual Laboratory testbed for aviation and airspace prognostics. The developed testbed will be used to validate prediction algorithms for the real-time safety monitoring of the National Airspace System (NAS) and the prediction of unsafe events. In our earlier work1 we discussed the initial Prognostics Virtual Laboratory testbed development work and related results for milestones 1 & 2. This paper describes the design, development, and testing of the integrated tested which are part of milestone 3, along with our next steps for validation of this work. Through a framework consisting of software/hardware modules and associated interface clients, the distributed testbed enables safe, accurate, and inexpensive experimentation and research into airspace and vehicle prognosis that would not have been possible otherwise. The testbed modules can be used cohesively to construct complex and relevant airspace scenarios for research. Four modules are key to this research: the virtual aircraft module which uses the X-Plane simulator and X-PlaneConnect toolbox, the live aircraft module which connects fielded aircraft using onboard cellular communications devices, the hardware in the loop (HITL) module which connects laboratory based bench-top hardware testbeds and the research module which contains diagnostics and prognostics tools for analysis of live air traffic situations and vehicle health conditions. The testbed also features other modules for data recording and playback, information visualization, and air traffic generation. Software reliability, safety, and latency are some of the critical design considerations in development of the testbed.

LVC-DE↗
NASA NTRSDate not supplied

3D Representation of UAV-obstacle Collision Risk Under Off-nominal Conditions

Safe operations of autonomous unmanned aerial vehicles (UAVs) in low-altitude airspace with beyond visual line-of-sight (BVLOS) flights demand robust risk monitoring of airspace as well as of people and property on ground. One of the safety critical factors for UAV flights is the risk of collision with static and dynamic obstacles in proximity to its flight path. This paper presents a detailed formulation of risk of obstacle collision incorporating the effects of off-nominal conditions introduced by component failures, degraded controllability and environmental disturbances such as wind gusts. The risk is represented in terms of a matrix with rows corresponding to the likelihood of occurrence of collision and columns representing severity of collision to the vehicle and surrounding structures. Risk likelihood is generated using a Bayesian Belief Network (BBN) that compiles knowledge from related Failure Modes and Effects Analysis (FMEAs) and Subject Matter Experts (SMEs) to determine the probability of collision based on on-board sensor measurements indicative of vehicle health and controllability. Risk severity is computed utilizing a point-mass 3D kinematic model of the vehicle in presence of wind. The proposed risk factor is demonstrated on real flight data from experimental flights of an octocopter at NASA Langley Research Center in presence of simulated obstacles and wind conditions. Effect of varying wind conditions, level of controllability and obstacle measurement noise on the risk factor is demonstrated. The proposed approach enables risk-informed decision making for timely mitigation of current and future unsafe events in autonomous systems.

risk analysis↗
NASA NTRS2016

Multiple Views on Safety-Critical Automation: Aircraft, Autonomous Vehicles, Air Traffic Management and Satellite Ground Segments Perspectives

This SIG focuses on the engineering of automation in interactive critical systems. Automation has already been studied in a number of (sub-) disciplines and application fields: design, human factors, psychology, (software) engineering, aviation, health care, games. One distinguishing feature of the area we are focusing on is that in the field of interactive critical systems properties such as reliability, dependability, fault-tolerance are as important as usability, user experience or overall acceptance issues. The SIG targets at two problem areas: first the engineering of the user interaction with (partly-) autonomous systems: how to design, build and assess autonomous behavior, especially in cases where there is a need to represent on the user interface both autonomous and interactive objects. An example of such integration is the representation of an unmanned aerial vehicle (UAV) (where no direct interaction is possible), together with aircrafts (that have to be instructed by an air traffic controller to avoid the UAV). Second the design and engineering of user interaction in general for autonomous objects systems (for example a cruise control in a car or an autopilot in an aircraft). The goal of the SIG is to raise interest in the CHI community on the general aspects of automation and to identify a community of researchers and practitioners interested in those increasingly prominent issues of interfaces towards (semi)-autonomous systems. The expected audience should be interested in addressing the issues of integration of mainly unconnected research domains to formulate a new joint research agenda.

safety-critical automation↗
NASA NTRS2022

Applicability of Digital Flight to the Operations of Self-Piloted Unmanned Aircraft Systems in the National Airspace System

Unmanned Aircraft Systems (UAS) hold great promise for a new era of specialized missions, including personal air transportation, cargo flight operations, aerial surveys, inspections, firefighting and more. The anticipated market growth is significant. To unlock its scalability and incumbent benefits requires a human to oversee multiple flights simultaneously, focusing on multi-vehicle mission management and relinquishing to autonomous systems their active role in controlling the aircrafts’ flight paths. Key to the realization of these scalability benefits is minimally-encumbered access to the National Airspace System (NAS), which poses some unique challenges for self-piloted UAS aircraft operations. These include the requirement for compatibility with existing airspace structures and operations including Visual Flight Rules (VFR) and Instrument Flight Rules (IFR), neither of which were developed to accommodate the unique needs and capabilities of UAS. This paper explores the applicability of Digital Flight to the operations of self-piloted UAS. As proposed by NASA, Digital Flight is a flight operations capability, enabled by a set of cooperative procedures and digital technologies, in which flight operators ensure flight-path safety through automated separation and flight path management in lieu of visual procedures and Air Traffic Control separation services. Flights operating under potentially-forthcoming rules of Digital Flight employ advanced automation technologies, information sharing, connectivity to operational data, and cooperative behaviors through distributed decision-making to maintain safety and achieve mission objectives. Designed for integration with VFR and IFR operations in shared NAS airspace, potentially as a third set of flight rules, Digital Flight may provide the mechanism for UAS operators – and all aircraft operators – to scale and diversify their operations beyond what is achievable under current regulations.

DFR↗
NASA NTRS2008

Proceedings of the Sixth NASA Langley Formal Methods (LFM) Workshop

Today's verification techniques are hard-pressed to scale with the ever-increasing complexity of safety critical systems. Within the field of aeronautics alone, we find the need for verification of algorithms for separation assurance, air traffic control, auto-pilot, Unmanned Aerial Vehicles (UAVs), adaptive avionics, automated decision authority, and much more. Recent advances in formal methods have made verifying more of these problems realistic. Thus we need to continually re-assess what we can solve now and identify the next barriers to overcome. Only through an exchange of ideas between theoreticians and practitioners from academia to industry can we extend formal methods for the verification of ever more challenging problem domains. This volume contains the extended abstracts of the talks presented at LFM 2008: The Sixth NASA Langley Formal Methods Workshop held on April 30 - May 2, 2008 in Newport News, Virginia, USA. The topics of interest that were listed in the call for abstracts were: advances in formal verification techniques; formal models of distributed computing; planning and scheduling; automated air traffic management; fault tolerance; hybrid systems/hybrid automata; embedded systems; safety critical applications; safety cases; accident/safety analysis.

Rozier, Kristin Yvonne↗
NASA NTRS2003

Smart Camera System for Aircraft and Spacecraft

This paper describes a new approach to situation awareness that combines video sensor technology and synthetic vision technology in a unique fashion to create a hybrid vision system. Our implementation of the technology, called "SmartCam3D" (SC3D) has been flight tested by both NASA and the Department of Defense with excellent results. This paper details its development and flight test results. Windshields and windows add considerable weight and risk to vehicle design, and because of this, many future vehicles will employ a windowless cockpit design. This windowless cockpit design philosophy prompted us to look at what would be required to develop a system that provides crewmembers and awareness. The system created to date provides a real-time operations personnel an appropriate level of situation 3D perspective display that can be used during all-weather and visibility conditions. While the advantages of a synthetic vision only system are considerable, the major disadvantage of such a system is that it displays the synthetic scene created using "static" data acquired by an aircraft or satellite at some point in the past. The SC3D system we are presenting in this paper is a hybrid synthetic vision system that fuses live video stream information with a computer generated synthetic scene. This hybrid system can display a dynamic, real-time scene of a region of interest, enriched by information from a synthetic environment system, see figure 1. The SC3D system has been flight tested on several X-38 flight tests performed over the last several years and on an ARMY Unmanned Aerial Vehicle (UAV) ground control station earlier this year. Additional testing using an assortment of UAV ground control stations and UAV simulators from the Army and Air Force will be conducted later this year.

Delgado, Frank↗
NASA NTRS2014

A Physics-Based Modeling Framework for Prognostic Studies

Prognostics and Health Management (PHM) methodologies have emerged as one of the key enablers for achieving efficient system level maintenance as part of a busy operations schedule, and lowering overall life cycle costs. PHM is also emerging as a high-priority issue in critical applications, where the focus is on conducting fundamental research in the field of integrated systems health management. The term diagnostics relates to the ability to detect and isolate faults or failures in a system. Prognostics on the other hand is the process of predicting health condition and remaining useful life based on current state, previous conditions and future operating conditions. PHM methods combine sensing, data collection, interpretation of environmental, operational, and performance related parameters to indicate systems health under its actual application conditions. The development of prognostics methodologies for the electronics field has become more important as more electrical systems are being used to replace traditional systems in several applications in the aeronautics, maritime, and automotive fields. The development of prognostics methods for electronics presents several challenges due to the great variety of components used in a system, a continuous development of new electronics technologies, and a general lack of understanding of how electronics fail. Similarly with electric unmanned aerial vehicles, electrichybrid cars, and commercial passenger aircraft, we are witnessing a drastic increase in the usage of batteries to power vehicles. However, for battery-powered vehicles to operate at maximum efficiency and reliability, it becomes crucial to both monitor battery health and performance and to predict end of discharge (EOD) and end of useful life (EOL) events. We develop an electrochemistry-based model of Li-ion batteries that capture the significant electrochemical processes, are computationally efficient, capture the effects of aging, and are of suitable accuracy for reliable EOD prediction in a variety of usage profiles.

Li-ion Batteries↗
NASA NTRSDate not supplied

Urban Air Mobility Community Noise Test Planning

The term “Advanced Air Mobility” has been adopted by NASA to describe safe, sustainable, affordable, and accessible aviation for transformational local and intraregional missions. By this definition, Advanced Air Mobility includes both “rural” and “urban” applications including cargo and passenger transport missions, and other aerial missions (e.g., infrastructure inspection). There will be a range of aircraft types performing such missions, including small and medium Unmanned Aircraft Systems (UAS), electric Conventional Takeoff and Landing (eCTOL) aircraft, and electric Vertical Takeoff and Landing (eVTOL) aircraft. Urban Air Mobility (UAM) is a challenging use case for transporting cargo and passengers in an urban environment and is a new opportunity for aviation that could revolutionize the transportation system. The National Aeronautics and Space Administration and the Noise Division of the Federal Aviation Administration Office of Environment and Energy have initiated discussions for planning UAM community noise test(s) at the end of this decade. This presentation discusses the test goals, candidate test objectives, and some of activities needed in preparation for the test(s). It also draws distinctions between the type of study envisioned (observational vs. staged), and between it and recent and planned studies on large fixed-wing transports and commercial supersonic transports.

urban air mobility↗
NASA NTRS2010

Experimental Validation of L1 Adaptive Control: Rohrs' Counterexample in Flight

The paper presents new results on the verification and in-flight validation of an L1 adaptive flight control system, and proposes a general methodology for verification and validation of adaptive flight control algorithms. The proposed framework is based on Rohrs counterexample, a benchmark problem presented in the early 80s to show the limitations of adaptive controllers developed at that time. In this paper, the framework is used to evaluate the performance and robustness characteristics of an L1 adaptive control augmentation loop implemented onboard a small unmanned aerial vehicle. Hardware-in-the-loop simulations and flight test results confirm the ability of the L1 adaptive controller to maintain stability and predictable performance of the closed loop adaptive system in the presence of general (artificially injected) unmodeled dynamics. The results demonstrate the advantages of L1 adaptive control as a verifiable robust adaptive control architecture with the potential of reducing flight control design costs and facilitating the transition of adaptive control into advanced flight control systems.

Xargay, Enric↗