AEROSPACE OPERATIONS SYSTEMS PROGRAM

1. AEROSPACE OPERATIONS SYSTEMS PROGRAM Dr. J. Victor Lebacqz Director, Aviation System Capacity & Aerospace Operations Systems Programs NASA 14 December 1999 www.aos.nasa.gov/aosbase www.aos.nasa.gov

2. NASA Strategic Enterprises NASA Enterprises Primary Customers Ultimate Beneficiary Ultimate Resource Provider Space Science Science and Education Communities Technology Innovators Mission to Planet Earth Science, Commercial, and Education Communities Policy Makers Human Exploration and Development of Space Science and Education Communities Commercial Sectors Aero- Space Technology Aerospace and Nonaerospace Industries Other U.S. Government Agencies The Public The Public Administration and Congress Decision Makers Crosscutting Processes Manage Strategically Provide Aerospace Products and Capabilities Generate Knowledge Communicate Knowledge

3. OAT Enterprise “3 Pillars” • Global Civil Aviation • Five stretch goals • Revolutionary Technology Leaps • Three stretch goals • Access to Space • Two stretch goals

4. Five Goals for Global Civil Aviation Reduce the aircraft accident rate by a factor of five within 10 years, and by a factor of 10 within 20 years. While maintaining safety, triple the aviation system throughput, in all weather conditions, within 10 years Reduce the perceived noise levels of future aircraft by a factor of 2 within 10 years, and by 4 within 20 years Reduce emissions of future aircraft by a factor of 3 within 10 years, and by 5 within 20 years Reduce the cost of air travel by 25% within 10 years, and by 50% within 20 years

5. Growth in Operations, Safety Rate, and Frequency of Accidents (1980-2015) Courtesy Boeing

6. Goal 1: Aviation Safety Benefits: • Safer air transportation worldwide • Dramatic reduction in aviation fatalities • Eliminate safety as an inhibitor to a potential tripling of the aviation market Reduce the aircraft accident rate by a factor of five within 10 years, and by a factor of 10 within 25 years CHALLENGES OUTCOMES 1997 2000 2005 2010 2015 2020 2025 System Monitoring & Modeling 2007 2022 Monitor for Safety FAA NAS Architecture Phase I Phase II Phase III World-wide aviation monitoring allowing continuous insight and assessment of system health and operations CAPACITY — Adv. Air Traffic Technologies Real-Time Monitoring of Aviation Systems Integration of Intelligent Aviation Systems Aviation Safety Program Phase I Phase II Information Technology & Aerospace Operations Systems Accident Prevention Equip for Safety Space-Based Aviation Safety System Technologies (Code S) AGATE Flight Systems Elimination of recurring accident causes and early detection and prevention of new accident categories HSR Flight Deck Aviation Safety Program Phase I Phase II Ultra-Safe Airborne Technology Integration Aerospace Operations Systems, Rotorcraft, Propulsion, & Flight Research Accident Mitigation Design for Safety AGATE Crashworthiness Increased survivability of the rare accidents and incidents that do occur Safety-Configured X-Plane Design and Demonstration Aviation Safety Program Phase I Phase II Base R&T Program Other Agencies Systems Tech. Program; Planned and Funded Systems Tech. Program, Required but Unfunded Airframe Systems & Rotorcraft

7. OAT Aeronautics Programs Structure Information System Techs LaRC Airframe Sys Atmos Science Structures & Materials WTs & Aero, Aerothermo Facilities / Struct Test Facilities Center: Mission: COE: Facility Group Lead: ARC Aviation Ops Systems Astrobiology Info Tech Simulators Scientific & Engineering Computational Facilities DFRC Flt Rsrch Atmos Flt Ops Aircraft & Flight Facilities LeRC Aeropropulsion Turbomachinery Propulsion Facilities Programs/ Lead Centers ISE / LaRC Human Factors Exp Aircraft Flight Research Airborne Systems Turbomachinery & Combustion Safety / LaRC HPCC / ARC Inlets, Nozzles & Mechanical Engine Components Air Traffic Management Test Bed A/C Research & Ops Structures & Materials Competency Group Areas: Capacity / ARC RPV Research & Ops Propulsion Mats & Structs Aerodynamics Aero Veh Sys/LaRC Flight Test Tech & Instrument Hybrid Propulsion Mission / Sys Analysis Rotorcraft & VSTOL Techs Prop Sys/LeRC Flt Rsrch/DFRC Crew Station Design & Integ Propulsion Support Tech Av Ops Sys/ARC Info Tech/ARC Icing Technologies Hypersonic Technologies Rotorcraft/ARC

8. Aerospace Operations Systems Program • Pioneer advanced research and technology to enable revolutionary advances in Aerospace Operations Systems to support NASA Goals: • Reduce the aircraft accident rate by a factor of 5 within 10 years, and a factor of 10 within 25 years • While maintaining safety, triple the aviation system throughput, in all weather conditions, within 10 years Aerospace Operations Systems are ground, satellite, and vehicle systems, and human operators, that determine the operational safety, efficiency and capacity of vehicles operating in the airspace, including: • communication, navigation and surveillance (CNS) systems; • air traffic management systems, interfaces and procedures; • relevant cockpit systems, interfaces and procedures; • operational human factors, their impact on aviation operations, and error mitigation; • weather and hazardous environment characterization, detection and avoidance systems Safety Capacity

9. Current AOS Program Focus Areas Technology Gap Areas System Problems Weak collaboration among designers and human factors experts Failure to identify or mitigate risk factors during design phase Mode confusion in use of automated systems Human Factors in Systems Human Performance Human error still cited as a factor in majority of accidents Lack of understanding of cognitive and decision processes Inadequate attention to human limitations such as fatigue Weather Factors Prediction & Mitigation Inadequate understanding of icing conditions and effects Expensive processes to test for certification Lack of shared information regarding weather conditions

10. Human Factors in Systems Examples

11. 1.00 0.90 0.80 0.70 0.60 0.50 0.40 0.30 0.20 0.10 ΩΩ 0.00 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 300 NAV1 CLB INT LEVEL 23ooo 300 THRUST NAV1 CLB THRUST 23ooo Comparison of Flight Mode Annunciators Correct Interpretation The aircraft is level at 23,000 ft, the clearance altitude, in VNAV. The crew is waiting for a clearance to 33,000 ft, their cruse altitude. Figure of Merit Experimental FMA 16 Alternative Interpretations Observe that there are twoalternative interpretations ofthe Control FMA that are very similar to the correct interpretation. Control FMA PI: Ev Palmer, NASA Ames Research Center

12. Human Memory Constraints in Procedure Execution: Predicting Error Vulnerability Flight Control Automation 2. Speed controlled via MCP. DFW Approach Scenario 4. Aircraft fails to meet speed target for crossing restriction. 1. FMS transitions out of VNAV when altitude capture achieved. APEX Human Operator Model 3. Crew fails to recall B757 transition behavior. Results in “Habit Capture”, reversion to B737 FMS procedure. • Apex Crew Simulation • • Flight / Cockpit procedures • • Human Performance Model • • Memory Errors • • Decision Errors PI: Roger Remington, NASA Ames Research Center

13. Design of Displays and Procedures Completed part-task simulator study on Scene-Linked HUD Symbology for taxi turns. Offset poles and flags placed at a fixed distance beyond turn improves taxi centerline tracking. Pilots can use symbology’s relative distance cues to mitigate field-of-view (FOV) HUD limitations. PI: Dave Foyle, NASA Ames Research Center

14. Initial NAOMS Studies Develop a 1st generation, system-wide monitoring capability to measure and communicate the health and status of operational safety performance National Aviation Operational Monitoring Service (NAOMS): Completed study of the demographics of the NAS Conducted initial studies in support of the NAOMS Developed survey instrument to tap on-going activities and special interests Pilot Study - Survey to randomly-selected sample of commercial pilots POC Mary Connors, NASA Ames Research Center

15. Aviation Performance Measurement System GOAL: To develop data analysis capabilities to facilitate identifying causal factors, accident precursors, and unexpected features in data collected pertaining to the health, performance and safety of the National Airspace System. • APMS routinely monitors hundreds of parameters for total system performance • Customizable toolkit converts data into usable information • Continuing evolution and evaluation in collaboration with Alaska and United Airlines PI: Irv Statler, NASA Ames Research Center

16. Human Performance Examples

17. Aviation Fatigue Countermeasures GOAL: To develop interventions to reduce the effects of fatigue, sleep loss, and circadian disruption on flight crews and ATM personnel. • Completed 747-400 simulator study on effectiveness of in-flight activity breaks on flight crew alertness. Hourly in-flight activity breaks showed significant decrease in measured sleepiness and increase in reported alertness • Initiated piloted simulation to study effectiveness of online, fatigue-dependent feedback to flight crews. • Original Education and Training Module for Part 121 operations published as NASA/FAA Technical Memorandum: Crew Factors in Flight Operations X: Alertness Management in Flight Operations. PI: Dave Neri, NASA Ames Research Center

18. Icing Video (Level 3 Milestone 4Q ‘98); Activities in support of concurrent task management (Level 2 Milestone, 4th Q ‘01). Icing Training Video - Completed beta version of icing educational video for ice contaminated tailplane stall. Video contains information and graphic depiction on weather conditions conducive to icing; reviewed by customer community; 250 copies distributed (150 requested by FAA/Flight Standards) - ‘98 - Cockpit Interruptions and Distractions article - Printed in Directline and reprinted in numerous airline safety magazines - ‘99 POC: Tom Bond, NASA Glenns Research Center

19. Perceptual Models & Metrics Contrast Filter Channels Power Integrate • There is a need for a Spatial Standard Observer (SSO) to provide objective measures of visibility and contrast of spatial imagery (e.g., CIE Photometric and Colorimetric Standards) • Recent multi-lab collaborative data collection (ModelFest) provides a basis for design of SSO • NASA/PPSF-supported SSO design presented at Optical Society of America (9/26/99) Sample stimuli Contrast Threshold (dB) Gain (dB) Spatial Standard Observer Derived Contrast Sensitivity Function ModelFest Data PI: Beau Watson, NASA Ames Research Center

20. Analysis Tool for Human Depth Cue Integration Model Experiment PI: Barbara Sweet, NASA Ames Research Center

21. Weather Factors Prediction and Mitigation Examples

22. NASA Twin Otter SLD Normal Icing Particle Sizing Probe Icing Characterization Goal • Comprehensive characterization of meteorological parameters and frequency • of occurrence for icing conditions which aircraft will encounter • within current FAA aircraft icing certification envelope • conditions which fall outside envelope (e.g. - SLD) • Supports NASA goal of enhanced safety and capacity Objectives • Quantify meteorological parameters • associated with icing conditions • (water droplet size, concentration of • water in icing cloud, temperature, etc) • Support the development of improved • icing cloud instrumentation PI: Dean Miller, NASA Glenn Research Center

23. Icing Computational Modelling Ice Shape Tracing; Providing Validation Data Ice Shape Comparison Results Computational vs. Experimental PI: Mark Potapczuk, NASA Glenn Research Center

24. 1: Next Generation Capacity Technologies Dr. Tom Edwards: Moderator Dr. Heinz Erzberger: Direct-To Tool Tom Davis: Multi-Center Traffic Management Advisor Tool Dr. Len Tobias: Collaborative Arrival Planner Tool 2: Aviation Human Factors Dr. Terry Allard: Moderator Dr. Dave Neri: Fatigue Countermeasures Dr. Judith Orasanu: CRM & Training Drs. Beau Watson and Roger Remington: Vision and Cognition 3: Information Technologies for Aviation Dave Alfano: Moderator John Kaneshige: Intelligent Flight Controls Dr. Dave Korsmeyer: Design Cycle Improvements Yuri Gawdiak: Data Sharing 4: Next Generation Capacity Technologies Dr. Tom Edwards: Moderator Dr. Heinz Erzberger: Direct-To Tool Tom Davis: Multi-Center Traffic Management Advisor Tool Dr. Len Tobias: Collaborative Arrival Planner Tool 5: Capacity: Distributed Air Ground Traffic Management Steve Green: Moderator Steve Green: Distributed Air-Ground Traffic Management Dr. Ev Palmer: Linking Cockpit and Air Traffic Control Automation Sandy Lozito: Shared Air-Ground Separation Responsibilities 6: Improved Capacity Through Vertical Flight Ed Aiken: Moderator Sandy Hart: Improving Rotorcraft Safety Mark Betzina: Tiltrotor Noise Abatement (Wind Tunnel Tests) Bill Decker: Tiltrotor Noise Abatement (Simulation & Flight Tests) Dr. John Zuk: Runway-Independent Aircraft Operations Breakout Sessions