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The SMART-NAS Testbed

The SMART-NAS Testbed for Safe Trajectory Based Operations Project will deliver an evaluation capability, critical to the ATM community, allowing full NextGen and beyond-NextGen concepts to be assessed and developed. To meet this objective a strong focus will be placed on concept integration and validation to enable a gate-to-gate trajectory-based system capability that satisfies a full vision for NextGen. The SMART-NAS for Safe TBO Project consists of six sub-projects. Three of the sub-projects are focused on exploring and developing technologies, concepts and models for evolving and transforming air traffic management operations in the ATM+2 time horizon, while the remaining three sub-projects are focused on developing the tools and capabilities needed for testing these advanced concepts. Function Allocation, Networked Air Traffic Management and Trajectory Based Operations are developing concepts and models. SMART-NAS Test-bed, System Assurance Technologies and Real-time Safety Modeling are developing the tools and capabilities to test these concepts. Simulation and modeling capabilities will include the ability to assess multiple operational scenarios of the national airspace system, accept data feeds, allowing shadowing of actual operations in either real-time, fast-time and/or hybrid modes of operations in distributed environments, and enable integrated examinations of concepts, algorithms, technologies, and NAS architectures. An important focus within this project is to enable the development of a real-time, system-wide safety assurance system. The basis of such a system is a continuum of information acquisition, analysis, and assessment that enables awareness and corrective action to detect and mitigate potential threats to continuous system-wide safety at all levels. This process, which currently can only be done post operations, will be driven towards "real-time" assessments in the 2035 time frame.

Trajectory Based Operations↗

Autonomous Assessment and Predictive Capabilities for Low-Altitude Urban Flight Operations

The integration of unmanned aerial vehicles in the national airspace will introduce new vehicle types, technologies, and operational paradigms for which safety must be maintained and hazards mitigated. One approach is to attempt to design for possible hazards and unsafe incidents that can occur at different phases of flight (pre-flight, in-flight, and post-flight) and during ground operations. Another is to mitigate safety incidents by implementing changes to policies, procedures, regulations, and design to cover personnel, equipment, and aircraft during operations. These and other techniques, not described herein, are typically conservative or adhoc in that they reduce the likelihood of risk after safety incidents have occurred. In this work, the goal is to develop a more predictive capability to monitor and mitigate risk and hazards to safety “in-time” enough for decisions to be made. In line with NASA’s Aeronautics Mission Directorate Strategic Thrust 5 [1] (In-Time System-Wide Safety Assurance), the System-Wide Safety (SWS) project under which this work falls, is developing and demonstrating innovative and safety-oriented solutions that enable modernization and aviation transformation. To that effect, this work will detail data-driven efforts on the SWS project to develop a number of safety-critical services for in-time monitoring and mitigation of hazards to low-altitude flight operations. First, hazards to these operations are identified based on previous work by NASA [2,3] and others in the aerospace industry. These hazards include (i) unsafe proximity to other vehicles, property, and people on the ground, (ii) critical system failures such as communication signal/GPS loss, unexpected propulsion system degradation, engine/power failure, and (iii) operational/environmental issues such as severe weather and gusty winds. For these hazards, safety metrics, which can be quantified and assessed are defined, models to monitor and predict them are developed, and flight test data is generated to develop, validate, and test these models, considering the complex interplay of the different hazards that define them [4-6]. In addition, the uncertainty in the non-deterministic effects that cannot be modeled nor predicted and unknown unknowns that arise after design/testing and during operations must be handled in rigorous manner. As a result, for each of the developed safety metrics, their dependencies on one another are characterized and a framework for handling the uncertainties inherent in the modeling, algorithms, and measurements required for prediction is also developed [7]. To that effect, this presentation will describe the safety metrics and services already developed and underway under the System-Wide Safety project that utilize data-driven techniques for the identification of anomalies, precursors, and trends (APTs) to monitor and mitigate hazards to safety, in-time, for urban flight operations in low-altitude airspace.

Okolo, Wendy A.↗

Psychophysiological Methods to Assess Pilot Productive Safety Behaviors

The NASA System-Wide Safety (SWS) Project is focused on developing new technologies and operational concepts for the aviation industry to meet the increasing global demand while maintaining the current ultra-safe system safety levels. To achieve this, the SWS Project is developing research priorities, including In-time System-wide Safety Assurance (ISSA) and In-time Aviation Safety Management System (IASMS; Ellis et al., 2019). A critical component of the IASMS is the human as pilot and in other roles in aviation operations as demonstrated by SWS human factors research on rare occurrences of human error and the far more prevalent human safety producing behaviors (e.g., Hollnagel, 2016). The talk presented by Chad Stephens of NASA Langley Research Center and NASA SWS Project will describe the history of human factors research involving psychophysiological and biocybernetics methods supporting aviation safety conducted at NASA. Specific examples of recent NASA crew state monitoring research focused on a psychophysiological assessment method and system to enable Training for Attention Management will be demonstrated. Current SWS research including the SWS Operations and Technologies for Enabling Resilient In-Time Assurance (SOTERIA) flight simulation study and a data testbed created to enable study of Human Contributions to Safety (HC2S) will be presented. Ongoing collaborative research efforts with Boeing researchers will be highlighted and opportunities for further collaboration will be discussed.

psychophysiology↗

Evaluating the Use of High-Fidelity Simulator Research Methods to Study Airline Flight Crew Resilience

As it evolves, aviation will continue to require integration of a wide range of safety systems and practices, some of which are already in place and others that are yet to be developed. New concepts in system safety thinking have emerged to consider not only what may go wrong, but also what can be learned when things go right during commercial flight operations. Taken together, these complementary perspectives form a more comprehensive approach to systemsafety thinking that can help to recognize and preserve the resilient performance capabilities currently provided by humans. A need exists, however, for research methods to enable better understanding of the human contributions to aviation safety. NASA’s System-Wide Safety Project supports research on using flight simulation methods to study operator resilience and safety-producing behaviors. Building on prior NASA efforts investigating procedural non-adherences during area navigation standard terminal route arrivals, a high-fidelity commercial aviation line operational simulation (LOS) experiment has been designed to study how flight crews anticipate, monitor for, respond to, and learn from expected and unexpected disturbances during these operations. A diverse set of LOS scenarios were developed to simulate highly realistic, complex, but routinely encountered operational situations. Each scenario provided multiple opportunities to collect data on how flight crews manage threats and errors, as well as novel opportunities to observe resilient and safety-producing behaviors. The experimental design, implications for the study of safety-producing behaviors using simulation, and considerations for airline pilot training will be discussed.

Chad L Stephens↗

Simulated Versus Measured UHF Radiated Power at LaRC Street Level

The Airspace Operations and Safety Program, System-Wide Safety Project /Technical Challenge 2 – Emerging Operations at NASA Langley aims to increase the flight safety of unmanned aerial vehicles (UAV’s) by informing UAV operators of regions of airspace where the radio frequency (RF) power at designated frequencies exceeds threshold values, indicating possible damage or interference with on-board systems. WinProp electromagnetic simulation software, a commercially available ray tracing program, has been implemented to predict radiated power from known RF sources. As a test case, the NextNav geolocation system, with nine transmitters operating at 926.227 MHz, was selected and modeled together with other existing structures at Langley. The radiated power at street level was calculated and compared with measurements taken at street level by a Signal Hound receiver and an Electro-Metrics antenna mounted on a van. The two sets of results generally agreed to within about 5 dB.

electromagnetic simulation↗

Assessing Several Non-Traditional Data Sources for Value in Aviation Safety

The NASA System-Wide Safety (SWS) project and its predecessor projects have been developing Machine Learning (ML) algorithms for commercial aviation safety for many years. These algorithms have been applied to Flight Operations Quality Assurance (FOQA); radar track data (e.g., Threaded Track); and safety reports, including Aviation Safety Reporting System (ASRS) and Aviation Safety Action Plan (ASAP). SWS is working with partners to get access to other data that air carriers provide, such as maintenance data, and has been assisting carriers in working with other data, such as Line Operations Safety Audit (LOSA) data, using manual methods. However, the project has discussed whether there are other data that are not traditionally used in aviation safety analysis that may be useful. This paper discusses four sets of data and models that are not traditionally used in aviation safety but that have shown promise for such use. In the future, we plan to incorporate such data into ML algorithms to use with data that we have used before and determine the additional benefit that is actually achieved under different contexts from the inclusion of these non-traditional data sources.

Nikunj C. Oza↗

SWS TechTalk Systems Modelling for SWS Safety Demonstrator 1 (SD-1): Wildfire Response Operations

Build out a System Safety Model for System-Wide Safety’s first Technical Challenge 5 (TC5) Safety Demonstrator (SD-1), which will be a demonstration of an In-Time Aviation Safety Management System in emerging wildfire response operations. Supporting the Systems Engineer and using Model-Based Systems Engineering (MBSE) practices, languages, and tools. Summer 2022 SD1 milestones: TC5-03-01 Initial Stakeholder Engagement Concept of Operations Development milestone and the upcoming TC5-03-02 Identification of key gaps and prioritization of NASA, SWS milestone.

model-based systems engineering↗

An in-Time Aviation Safety Management System Concept of Operations and Modernization of the National Airspace System

The National Airspace System (NAS) is growing in complexity of aircraft, missions, and operations. In response, many organizations have published papers and concepts of operations (ConOps) for new and enhanced safety systems. The National Academies’ vision for an In-time Aviation Safety Management System (IASMS) is integral to Federal Aviation Administration (FAA) modernization efforts. The National Aeronautics and Space Administration (NASA) System-Wide Safety (SWS) project is conducting safety research, exploring solutions, and defining the safety needs of future missions, such as Advanced Air Mobility (AAM) and autonomous aircraft operating in a more connected, flexible, and dynamic airspace. IASMS enables and provides a path for bringing FAA’s operational vision to fruition through increasingly automated safety systems that integrate services, functions, and capabilities (SFCs). These SFCs provide the necessary responsiveness to monitor, assess, and mitigate known hazards and emergent risks. This paper describes how safety in today’s air transportation system will need to evolve, identifies key points regarding in-time safety, and explores the criticality of IASMS in the future NAS.

IASMS↗