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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 469 records · Page 26
All sourcesNASA NTRSDOE OSTI
NASA NTRS2021

Detection and Tracking of Aircraft in the Far-Field from Small Unmanned Aerial Systems

Onboard far-field aircraft detection is needed for safe non-cooperative traffic mitigation in autonomous small Unmanned Aerial System (sUAS) operations. Machine vision systems, based on standard optics and visible light detectors, possess the ideal size, weight, and power (SWaP) requirements for sUAS. This work presents the design and analysis of a novel aircraft detection and tracking pipeline based on optical sensing alone. Key contributions of the work include a refined range inequality model based on sensing and detection with FAA well-clear separation assurance distances between aircraft in mind, a detector fusion method to maximize the benefit of two image detectors, and a comparative analysis of Linear Kalman-filtering and Extended Kalman-filtering to seek optimal tracking performance. The pipeline is evaluated offline against multiple intruder platforms, using two types of flight encounters: multirotor sUAS vs. fixed-wing sUAS and multirotor sUAS vs. general aviation(GA)plane. Analysis is restricted to the rate-limiting head-on and departing collision volume cases vertically separated for safety. Results indicate that it is feasible to use the proposed optical spatial-temporal tracking algorithm to provide adequate alerting time to prevent penetration of well-clear separation volumes for both sUAS and GA aircraft.

Unmanned Aerial System↗
NASA NTRS1990

Real-time adaptive aircraft scheduling

One of the most important functions of any air traffic management system is the assignment of ground-holding times to flights, i.e., the determination of whether and by how much the take-off of a particular aircraft headed for a congested part of the air traffic control (ATC) system should be postponed in order to reduce the likelihood and extent of airborne delays. An analysis is presented for the fundamental case in which flights from many destinations must be scheduled for arrival at a single congested airport; the formulation is also useful in scheduling the landing of airborne flights within the extended terminal area. A set of approaches is described for addressing a deterministic and a probabilistic version of this problem. For the deterministic case, where airport capacities are known and fixed, several models were developed with associated low-order polynomial-time algorithms. For general delay cost functions, these algorithms find an optimal solution. Under a particular natural assumption regarding the delay cost function, an extremely fast (O(n ln n)) algorithm was developed. For the probabilistic case, using an estimated probability distribution of airport capacities, a model was developed with an associated low-order polynomial-time heuristic algorithm with useful properties.

Kolitz, Stephan E.↗
NASA NTRS1993

SATCOM simulator speeds MSS deployment and lowers costs

Mobile satellite systems (MSS) are being proposed and licensed at an accelerating rate. How can the design, manufacture, and performance of these systems be optimized at costs that allow a reasonable return on investment? The answer is the use of system simulation techniques beginning early in the system design and continuing through integration, pre- and post-launch monitoring, and in-orbit monitoring. This paper focuses on using commercially available, validated simulation instruments to deliver accurate, repeatable, and cost effective measurements throughout the life of a typical mobile satellite system. A satellite communications test set is discussed that provides complete parametric test capability with a significant improvement in measurement speed for manufacturing, integration, and pre-launch and in-orbit testing. The test set can simulate actual up and down link traffic conditions to evaluate the effects of system impairments, propagation and multipath on bit error rate (BER), channel capacity and transponder and system load balancing. Using a standard set of commercial instruments to deliver accurate, verifiable measurements anywhere in the world speeds deployment, generates measurement confidence, and lowers total system cost.

Carey, Tim↗
NASA NTRS2006

Space-based Networking Technology Developments in the Interplanetary Network Directorate Information Technology Program

Described recent development of communications protocols, services, and associated tools targeted to reduce risk, reduce cost and increase efficiency of IND infrastructure and supported mission operations. Space-based networking technologies developed were: a) Provide differentiated quality of service (QoS) that will give precedence to traffic that users have selected as having the greatest importance and/or time-criticality; b) Improve the total value of information to users through the use of QoS prioritization techniques; c) Increase operational flexibility and improve command-response turnaround; d) Enable new class of networked and collaborative science missions; e) Simplify applications interfaces to communications services; and f) Reduce risk and cost from a common object model and automated scheduling and communications protocols. Technologies are described in three general areas: communications scheduling, middleware, and protocols. Additionally developed simulation environment, which provides comprehensive, quantitative understanding of the technologies performance within overall, evolving architecture, as well as ability to refine & optimize specific components.

scheduling↗
NASA NTRS2006

Scheduling Aircraft Landings under Constrained Position Shifting

Optimal scheduling of airport runway operations can play an important role in improving the safety and efficiency of the National Airspace System (NAS). Methods that compute the optimal landing sequence and landing times of aircraft must accommodate practical issues that affect the implementation of the schedule. One such practical consideration, known as Constrained Position Shifting (CPS), is the restriction that each aircraft must land within a pre-specified number of positions of its place in the First-Come-First-Served (FCFS) sequence. We consider the problem of scheduling landings of aircraft in a CPS environment in order to maximize runway throughput (minimize the completion time of the landing sequence), subject to operational constraints such as FAA-specified minimum inter-arrival spacing restrictions, precedence relationships among aircraft that arise either from airline preferences or air traffic control procedures that prevent overtaking, and time windows (representing possible control actions) during which each aircraft landing can occur. We present a Dynamic Programming-based approach that scales linearly in the number of aircraft, and describe our computational experience with a prototype implementation on realistic data for Denver International Airport.

Balakrishnan, Hamsa↗
NASA NTRS2023

Analysis of Strategic Conflict Management Approaches as Applied to Simulated UAM Operations

This report presents the results of a comparison analysis of candidate Strategic Conflict Management (SCM) strategies as applied to Urban Air Mobility (UAM) operations. The SCM strategies investigated included: no SCM, resource scheduling (RS), resource flow rates (FR), area-based flow rates (AR), and conflict detection and resolution (CR). The study evaluated each strategy against the same 3 levels of flight demand in a representative airspace construct for the Dallas/Fort Worth region. The study also accounted for different levels of uncertainty in operational planning and equivalent levels of trajectory following error. In the analysis, we compared the SCM strategies’ effectiveness in reducing the need for the tactical conflict management layer to act and looked at the metrics of unmitigated losses-of-separation (LOS), flight delays imposed by strategic planning, and throughput of the overall airspace. The study results indicated that the CR strategy was the most effective at reducing LOS and percentage of flights with LOS, even in the presence of trajectory error when uncertainty is accounted for in planning. Thus, if the objective is to reduce the number of actions that the tactical conflict management layer will have to take, in terms of conflicts that may need to be resolved, CR is the strategy to use. The FR strategy was found to be the worst at reducing LOS and percentage of flights with LOS. Thus, it is not very effective at reducing the actions required by a tactical conflict management layer. In the airspace tested, the demand was high enough to produce unacceptable levels of flight delay and reductions of throughput when the SCM strategies were implemented. This was especially evident at the higher levels of trajectory uncertainty and error. The need to account for expected levels of uncertainty becomes more and more important as the demand level increases and as the level of trajectory error increases. This is because the likelihood of flights with LOS increases as the density of operations increases and as the level of trajectory error increases. Accounting for uncertainty in the SCM strategies improves the strategy effectiveness with respect to LOS but increases delays and reduces throughput. Thus, there is a tradeoff between scalability and allowable levels of uncertainty. That is, we can implement an air traffic management construct that allows high levels of uncertainty, but we can expect that same system to have limits on scalability that may be evident even at small demand levels, such as those used in this study. Therefore, the results in this study indicate that an air traffic system should attempt to implement mechanisms appropriate for reducing uncertainty where possible in order to increase the chances for scalability. And this increased level of predictability of operations needs to be balanced with mechanisms for ensuring flexibility when operational conditions and plans need to change, even though those types of changes should be the exception rather than the rule under normal conditions. The study also introduced a trade space that could serve as a mechanism for selecting the appropriate SCM strategy in a trade-off between uncertainty and error, mean flight delay, and the LOS metrics (which this study equates to the potential for tactical conflict management actions). The optimal solution for a given airspace, demand level, and other factors, could likely be a combination of SCM strategies, although this study only compared the use of a single SCM strategy at a time. The CR strategy appeared to have the best opportunity for scalability by limiting the number of potential tactical actions to nearly zero.

Strategic Conflict Management↗
DOE OSTI2024

Investigation of Debonding Effect in Internal Replacement Pipe System Under Lateral Loading

The aging pipeline infrastructure around the world necessitates immediate rehabilitation. Internal replacement pipe (IRP) is a trenchless system offering a versatile and cost-effective solution across a variety of industries, including oil, natural gas, water, and wastewater. As a structural pipeline repair system, IRPs are subject to lateral deformation because of surface traffic loading. The present study evaluates the impact of adhesion between the host pipe and the IRP, with a focus on assessing the debonding effect on the behavior of the repair system under lateral deformation and bending. This was achieved using a comprehensive approach, including experimental, numerical, and analytical techniques. Varying levels of adhesive strength resulting from different methods of surface preparation were considered. The effectiveness of the IRP system on both discontinuous host pipes with various crack widths and continuous host pipes was also investigated. The results demonstrate that adhesive strength exerts a significant influence on the repair system, especially in the case of narrow circumferential cracks, while its impact on the continuous system is minimal. For optimal performance, it is essential to choose adhesives that possess sufficient shear strength while also accounting for the required debonding length. This approach ensures that minor discontinuities are effectively controlled, thereby enhancing the system′s fatigue life. The reliable determination of the maximum allowable shear strength for the adhesive or the debonding length can ensure that it does not negatively affect fatigue life. The findings presented in this study offer new insights into the development of trenchless repair techniques that can enhance system performance and extend service life.

Tien, Tri C. M.↗
NASA NTRS1990

Investigation of air transportation technology at Princeton University, 1988-1989

The Air Transportation Technology Program at Princeton University, a program emphasizing graduate and undergraduate student research, proceeded along several avenues during the past year. A study of optimal trajectories for penetration of microbursts when encounter is unavoidable was conducted. The emphasis of current wind shear research is on developing an expert system for wind shear avoidance. A knowledge-based reconfigurable flight control system that is implemented with the Pascal programming language using parallel microprocessors was developed. This expert system could be considered a prototype for a failure-tolerant control system that can be constructed using existing hardware. Development of a real-time cockpit simulator continued during the year. The simulator provides a single-person crew station with both conventional and advanced control devices; it currently is programmed to simulate the Navion single-engine general aviation airplane. Alternatives for the air traffic control system giving particular attention to the institutional structure of the FAA are analyzed. A simple numerical procedure for estimating the stochastic robustness of control systems is being investigated. The revitalization of the general aviation industry is also discussed.

Stengel, Robert F.↗
DOE OSTI2025

Incentivizing Cooperative Merging Control: Insights from Multi-Agent Deep Reinforcement Learning

Cooperative driving automation enables connected and automated vehicles (CAVs) to devise cooperative merging control, introducing great potentials to alleviate traffic congestion, reduce energy consumption, and enhance safety for highway on-ramp operations. Although numerous CAV cooperative merging algorithms have been developed to improve energy and traffic performance, the agreement-seeking among CAV users and their local benefits have been understudied. This can lead to rejections of cooperative merging plans and jeopardizing CAV performance, as a cooperation may entail certain CAVs to sacrifice their local benefits to achieve a system optimum. To address this issue, the study first leverages multi-agent deep reinforcement learning (MADRL) factoring both local reward and regional reward to demonstrate the discrepancies between CAV users’ local benefits and system optimum. Next, the existence of a correlated equilibrium is proved to characterize the convergence of MADRL training. This further facilitates the incorporation of incentives (computed based on reward discrepancies) to compensate for CAV users’ local benefits and facilitate system-optimal agreements in cooperative merging operations.

Zhou, Anye [ORNL] (ORCID:0000000301455579)↗
NASA NTRS2017

Efficient Trajectory Options Allocation for the Collaborative Trajectory Options Program

The Collaborative Trajectory Options Program (CTOP) is a Traffic Management Initiative (TMI) intended to control the air traffic flow rates at multiple specified Flow Constrained Areas (FCAs), where demand exceeds capacity. CTOP allows flight operators to submit the desired Trajectory Options Set (TOS) for each affected flight with associated Relative Trajectory Cost (RTC) for each option. CTOP then creates a feasible schedule that complies with capacity constraints by assigning affected flights with routes and departure delays in such a way as to minimize the total cost while maintaining equity across flight operators. The current version of CTOP implements a Ration-by-Schedule (RBS) scheme, which assigns the best available options to flights based on a First-Scheduled-First-Served heuristic. In the present study, an alternative flight scheduling approach is developed based on linear optimization. Results suggest that such an approach can significantly reduce flight delays, in the deterministic case, while maintaining equity as defined using a Max-Min fairness scheme.

Rodionova, O.↗
NASA NTRS1997

Advanced Free Flight Planner and Dispatcher's Workstation: Preliminary Design Specification

The National Aeronautics and Space Administration (NASA) has implemented the Advanced Air Transportation Technology (AATT) program to investigate future improvements to the national and international air traffic management systems. This research, as part of the AATT program, developed preliminary design requirements for an advanced Airline Operations Control (AOC) dispatcher's workstation, with emphasis on flight planning. This design will support the implementation of an experimental workstation in NASA laboratories that would emulate AOC dispatch operations. The work developed an airline flight plan data base and specified requirements for: a computer tool for generation and evaluation of free flight, user preferred trajectories (UPT); the kernel of an advanced flight planning system to be incorporated into the UPT-generation tool; and an AOC workstation to house the UPT-generation tool and to provide a real-time testing environment. A prototype for the advanced flight plan optimization kernel was developed and demonstrated. The flight planner uses dynamic programming to search a four-dimensional wind and temperature grid to identify the optimal route, altitude and speed for successive segments of a flight. An iterative process is employed in which a series of trajectories are successively refined until the LTPT is identified. The flight planner is designed to function in the current operational environment as well as in free flight. The free flight environment would enable greater flexibility in UPT selection based on alleviation of current procedural constraints. The prototype also takes advantage of advanced computer processing capabilities to implement more powerful optimization routines than would be possible with older computer systems.

Wilson, J.↗
NASA NTRS2008

Quiet Cruise Efficient Short Take-off and Landing Subsonic Transport System

This NASA funded study conceived a revolutionary airplane concept to enable future traffic growth by using regional air space. This requires a very quiet airplane with STOL capability. Starting with a Blended Wing Body that is cruise efficient with inherent low noise characteristics from forward noise shielding and void of aft downward noise reflections, integration of embedded distributed propulsion enables incorporation of the revolutionary concept for jet noise shielding. Embedded distributed propulsion also enables incorporation of a fan bleed internally blown flap for quiet powered lift. The powered lift provides STOL capability for operation at regional airports with rapid take-off and descent to further reduce flyover noise. This study focused on configuring the total engine noise shielding STOL concept with a BWB airplane using the Boeing Phantom Works WingMOD multidisciplinary optimization code to define a planform that is pitch controllable. The configuration was then sized and mission data developed to enable NASA to assess the flyover and sideline noise. The foundational technologies needed are identified including military dual use benefits.

Kawai, Ron↗
NASA NTRS2004

NASA Tech Briefs, October 2004

Topics include: Relative-Motion Sensors and Actuators for Two Optical Tables; Improved Position Sensor for Feedback Control of Levitation; Compact Tactile Sensors for Robot Fingers; Improved Ion-Channel Biosensors; Suspended-Patch Antenna With Inverted, EM-Coupled Feed; System Would Predictively Preempt Traffic Lights for Emergency Vehicles; Optical Position Encoders for High or Low Temperatures; Inter-Valence-Subband/Conduction-Band-Transport IR Detectors; Additional Drive Circuitry for Piezoelectric Screw Motors; Software for Use with Optoelectronic Measuring Tool; Coordinating Shared Activities; Software Reduces Radio-Interference Effects in Radar Data; Using Iron to Treat Chlorohydrocarbon-Contaminated Soil; Thermally Insulating, Kinematic Tensioned-Fiber Suspension; Back Actuators for Segmented Mirrors and Other Applications; Mechanism for Self-Reacted Friction Stir Welding; Lightweight Exoskeletons with Controllable Actuators; Miniature Robotic Submarine for Exploring Harsh Environments; Electron-Spin Filters Based on the Rashba Effect; Diffusion-Cooled Tantalum Hot-Electron Bolometer Mixers; Tunable Optical True-Time Delay Devices Would Exploit EIT; Fast Query-Optimized Kernel-Machine Classification; Indentured Parts List Maintenance and Part Assembly Capture Tool - IMPACT; An Architecture for Controlling Multiple Robots; Progress in Fabrication of Rocket Combustion Chambers by VPS; CHEM-Based Self-Deploying Spacecraft Radar Antennas; Scalable Multiprocessor for High-Speed Computing in Space; and Simple Systems for Detecting Spacecraft Meteoroid Punctures.

Source record↗
NASA NTRSDate not supplied

Machine Learning based Aircraft Performance Model Estimation for Trajectory Prediction

The accurate prediction of aircraft trajectory by ground-based decision support tools is a critical component of air traffic management in the US National Airspace System (NAS). Accurate predictions of where the aircraft will be in the future or when they will arrive at specific locations (e.g., fixes) is a key enabler for sequencing and efficient arrival management of flights. Traditional physics based aircraft trajectory prediction relies on a simplified point-mass total energy model whose parameters are referred to as Aircraft Performance Model (APM) parameters. Even though the performance coefficients and weight of an aircraft are a vital part of the aircraft performance model’s predictions and accuracy, these coefficients are proprietary in nature and therefore, unavailable to decision-support tools. Current approaches freeze some coefficients to default base of aircraft data (BADA) values and optimize others. However, the APM parameters are highly coupled by the flight dynamics and prioritizing one parameter over others leads to bias and skewed predictions. To alleviate this problem, we provide a combined optimization framework to predict all the critical (thrust, drag and weight) APM parameters. This paper is focused on training Machine Learning (ML) models that map historical flights to optimized APM parameters that provide the best fit (in terms of prediction error). Our dataset obtained from NASA’s Sherlock data warehouse is comprised of thousands of historical flights and includes weather and track data collected from 2019. Using different subsets of relevant features (e.g., aircraft type), we trained several ML models to estimate the aircraft’s take off weight, drag polar coefficients (both parasitic and lift induced), and thrust settings (multiplier applied to the maximum engine thrust). The chosen flights are from three of the most common aircraft types (B738, B737, and A320) arriving at four airports (LAX, DEN, MSP, and DFW). Our ML approach is comprised of two different solutions: 1- using a subset of features that are known prior to the flight departure and do not change during flight (such as engine type, current temperature at departure & destination airports, aircraft type) and 2 - using a subset of temporal features of the flight trajectory (such as cruise altitude, Mach, airspeed, and rate of climb) in addition to the pre-departure features from the first solution. The labels or target variables are the APM parameters that were obtained by an optimized ordinary differential equations (ODE) fitting process (applied to individual flights). The ODE-fitting is very time intensive and is therefore performed offline. Thus, training an ML model to learn the relationship between the flight features and ODE-generated labels enables faster estimation of the APM parameters and is therefore amenable to real-time prediction. Various ML models including linear regression, random forest, XGBoost, and neural network were trained, and the results are compared. After model validation and hyperparameter-tuning, we observed that the Random Forest model outperformed the other three models by the overall mean square error (MSE) of 2% for the first solution and 1.5% for the second solution. Finally, the ML-derived parameters are compared against default BADA APM parameters using NASA’s Autonomy Development toolkit (ADK) simulation software. The simulation results for one of each aircraft type is shown and discussed.

Aida Sharif Rohani↗
NASA NTRS2011

Flying Unmanned Aircraft: A Pilot's Perspective

The National Aeronautics and Space Administration (NASA) is pioneering various Unmanned Aircraft System (UAS) technologies and procedures which may enable routine access to the National Airspace System (NAS), with an aim for Next Gen NAS. These tools will aid in the development of technologies and integrated capabilities that will enable high value missions for science, security, and defense, and open the door to low-cost, extreme-duration, stratospheric flight. A century of aviation evolution has resulted in accepted standards and best practices in the design of human-machine interfaces, the displays and controls of which serve to optimize safe and efficient flight operations and situational awareness. The current proliferation of non-standard, aircraft-specific flight crew interfaces in UAS, coupled with the inherent limitations of operating UAS without in-situ sensory input and feedback (aural, visual, and vestibular cues), has increased the risk of mishaps associated with the design of the "cockpit." The examples of current non- or sub- standard design features range from "annoying" and "inefficient", to those that are difficult to manipulate or interpret in a timely manner, as well as to those that are "burdensome" and "unsafe." A concerted effort is required to establish best practices and standards for the human-machine interfaces, for the pilot as well as the air traffic controller. In addition, roles, responsibilities, knowledge, and skill sets are subject to redefining the terms, "pilot" and "air traffic controller", with respect to operating UAS, especially in the Next-Gen NAS. The knowledge, skill sets, training, and qualification standards for UAS operations must be established, and reflect the aircraft-specific human-machine interfaces and control methods. NASA s recent experiences flying its MQ-9 Ikhana in the NAS for extended duration, has enabled both NASA and the FAA to realize the full potential for UAS, as well as understand the implications of current limitations. Ikhana is a Predator-B/Reaper UAS, built by General Atomics, Aeronautical Systems, Inc., and modified for research. Since 2007, the aircraft has been flown seasonally with a wing-mounted pod containing an infrared scanner, utilized to provide real-time wildfire geo-location data to various fire-fighting agencies in the western U.S. The multi-agency effort included an extensive process to obtain flight clearance from the FAA to operate under special provisions, given that UAS in general do not fully comply with current airspace regulations (e.g. sense-and-avoid requirements).

Pestana, Mark E.↗
NASA NTRS1999

A Simple Two Aircraft Conflict Resolution Algorithm

Conflict detection and resolution methods are crucial for distributed air-ground traffic management in which the crew in the cockpit, dispatchers in operation control centers and air traffic controllers in the ground-based air traffic management facilities share information and participate in the traffic flow and traffic control imctions.This paper describes a conflict detection and a conflict resolution method. The conflict detection method predicts the minimum separation and the time-to-go to the closest point of approach by assuming that both the aircraft will continue to fly at their current speeds along their current headings. The conflict resolution method described here is motivated by the proportional navigation algorithm. It generates speed and heading commands to rotate the line-of-sight either clockwise or counter-clockwise for conflict resolution. Once the aircraft achieve a positive range-rate and no further conflict is predicted, the algorithm generates heading commands to turn back the aircraft to their nominal trajectories. The speed commands are set to the optimal pre-resolution speeds. Six numerical examples are presented to demonstrate the conflict detection and resolution method.

Chatterji, Gano B.↗
NASA NTRS2010

A Criteria Standard for Conflict Resolution: A Vision for Guaranteeing the Safety of Self-Separation in NextGen

Distributed approaches for conflict resolution rely on analyzing the behavior of each aircraft to ensure that system-wide safety properties are maintained. This paper presents the criteria method, which increases the quality and efficiency of a safety assurance analysis for distributed air traffic concepts. The criteria standard is shown to provide two key safety properties: safe separation when only one aircraft maneuvers and safe separation when both aircraft maneuver at the same time. This approach is complemented with strong guarantees of correct operation through formal verification. To show that an algorithm is correct, i.e., that it always meets its specified safety property, one must only show that the algorithm satisfies the criteria. Once this is done, then the algorithm inherits the safety properties of the criteria. An important consequence of this approach is that there is no requirement that both aircraft execute the same conflict resolution algorithm. Therefore, the criteria approach allows different avionics manufacturers or even different airlines to use different algorithms, each optimized according to their own proprietary concerns.

Munoz, Cesar↗
NASA NTRS2019

Human Performance Contributions to Safety in Commercial Aviation

Every day in aviation, pilots, air traffic controllers, and other front-line personnel perform countless correct judgments and actions in a variety of operational environments. These judgments and actions are often the difference between an accident and a non-event. Ironically, data on these behaviors are rarely collected or analyzed. Data-driven decisions about safety management and design of safety-critical systems are limited by the available data, which influence how decision makers characterize problems and identify solutions. Large volumes of data are collected on the failures and errors that result in infrequent incidents and accidents, but in the absence of data on behaviors that result in routine successful outcomes, safety management and system design decisions are based on a small sample of nonrepresentative safety data. This assessment aimed to find and document “safety successes” made possible by human operators. With many Aeronautics Research Mission Directorate (ARMD) Programs and Projects focusing on increased automation and autonomy and decreased human involvement, failure to fully consider the human contributions to successful system performance in civil aviation represents a significant risk — a risk that has not been recognized to date. Without understanding how humans contribute to safety, any estimate of predicted safety of autonomous capabilities is incomplete and inherently suspect. Furthermore, understanding the ways in which humans contribute to safety can promote strategic interactions among safety technologies, functions, procedures and the people using them. Without this understanding, the full benefits of an integrated, optimized human/technology or autonomous system will not be realized. Historically, safety has been consistently defined in terms of the occurrence of accidents or recognized risks (i.e., in terms of things that go wrong). These adverse outcomes are explained by identifying their causes, and safety is restored by eliminating or mitigating these causes. An alternative to this approach is to focus on what goes right and identify how to replicate that process. Focusing on the rare cases of failures attributed to “human error” provides little information about why human performance routinely prevents adverse events. Hollnagel has proposed that things go right because people continuously adjust their work to match their operating conditions. These adjustments become increasingly important as systems continue to grow in complexity. Thus, the definition of safety should reflect not only “avoiding things that go wrong” but “ensuring that things go right.” The basis for safety management requires developing an understanding of everyday activities. However, few mechanisms to monitor everyday work exist in the aviation domain, which limits opportunities to learn how designs function in reality. This concept of safety thinking and safety management is reflected in the emerging field of resilience engineering. According to Hollnagel, a system is resilient if it can sustain required operations under expected and unexpected conditions by adjusting its functioning prior to, during, or following changes, disturbances, and opportunities. To explore “positive” behaviors that contribute to resilient performance in commercial aviation, the assessment team examined a range of existing sources of data about pilot and air traffic control (ATC) tower controller performance, including subjective interviews with domain experts and objective aircraft flight data records. These data were used to identify strategies that support resilient performance, methods for exploring and refining those strategies in existing data, and proposed methods for capturing and analyzing new data.

Null, Cynthia H.↗