Information Technology for Aviation David Alfano Deputy Program

Information Technology for Aviation David Alfano Deputy Program Manager Information Technology Base Program

Aero-Space Technology Pillars and Goals Global Civil Aviation Safety Emissions Noise Capacity Affordability Revolutionary Technology Leaps High-Speed General Aviation Design Access to Space Reusable Space Trans. Revolutionary ST

IT Program Goal Integrated Design “Perform leading-edge research in advanced computing systems and user environments, revolutionary software technologies and pathfinding applications that enable the achievement of NASA’s missions in Aero-Space Technology” Revolutionary Software Advanced Computing

Information Technology HUMAN-CENTERED COMPUTING Integrated Design Technology HIGH-END COMPUTING Advanced Computing Technology AUTOMATED REASONING Software Technology Primary Long-Term Goals Supported “Reduce the aircraft accident rate by a factor of 5 within 10 years, and by a factor of 10 within 20 years” “Provide next-generation design tools and experimental aircraft to increase design confidence, and cut the development cycle time for aircraft and space transportation vehicles in half”

IT Program Projects Integrated Design Software Advanced Computing Analytical Tools and Environments for Design Intelligent System Controls and Operations (ISCO) (ATED) Advanced Computing, Networking & Storage Integrated Instrumentation and Testing Systems (IITS) (ACNS) Software Integrity, Productivity, and Security (SIPS)

Integrated Design Technology Virtual Prototyping Visualization Experimental Systems Design Definition Data Performance Data Knowledge Tools Modeling, Design, and Simulation

Rapid Awareness s in tion era 3 it ANALYSIS Rapid Design New Data Quality Testing AT SL PO AL S. PH A PR OC ES S: 1: E ex valu i 2: sting ate O ad bta data d i ba da ition n se t s al 3: a an I aly de dent sis s 4: ign ify n ew Ex mo ec de nito ute a cis r d n ion esi d gn Re-Design Concept Model Parts hs ont 2 m S. SENSORS PO BANK AP DATA CF CF D RU DR N UN 35 46 FO R CF CF D-RU N 12 CF D RU N 22 DR N UN 35 46 6/2/97 -2: 00 PM LE DATA FL S CL John S. Designer Flap/Slat Re-Design OP D MB-797 -12 High-Lift Test - Ames 12 ft PE I S SE PAN CT ION EN TE 48 R: % B I A M N P K L E M E N T VIS FL UA OW LIZ DG ATIO N P V PL SP O FA T 3 D ST M O N I T O R V AL S. PH RE MAC A YN H FIX O CD LDS AL ED: PH FL CM RE MAC A SL AP P H AT OS FL YNO L PO. SL AP P DS S. AT OS PO. S. IGU R CL ATIO N CD CM NF New Knowledge A � C � Q � U � I � R P� R E E S E F N U T N C T A I D O V N I S E CT IO CL NAL CD CM CP CF SE CO Design Cycle Improvement Example: Rapid Re-Design during a Wind Tunnel Test On-site Manufacturing

Virtual Flight Activity Flight Control Flight Simulation Wind-Tunnel Client NASA GRC / Engine Performance Flight Web Browser Aircraft Synthesis Wind Tunnel Server File DARWIN Server Workstation Java software CFD Design Data IC DARWIN Virtual H T T P S Web Server HTML Database F T P System Serv. IO *. nml Intelligent Flight Control

Software Technology Intelligent Flight Controls Challenge: Develop a flight control approach that can efficiently handle off nominal and unanticipated changes in air vehicle operating environments and hardware Technical Goals: • Develop a flight control concept that uses neural network technology to identify aircraft stability and control derivatives which allow optimal aircraft performance under a wide range of flight conditions • Develop a learning neural network which can update aircraft stability and control derivatives during flight and in response to off nominal events • Piloted flight demonstration using the NASA F-15 ACTIVE test aircraft

Software Technology Intelligent Flight Controls Develop and flight demonstrate a flight control technique that can effectively identify aircraft stability and control characteristics using neural networks and utilize this information to optimize aircraft performance. Impact • Enhanced Safety • Reduced Cost

Software Technology Remote Aviation Help Desk Airport Hangars Airline MOC Boeing Rapid Response Center Remote Displays Virtual Iron Bird Remote Displays Digital White Board Boeing CAD/CAE Maint. table Syst. Digital White Board Wireless Digital Wireless Bridge - Video - Audio - Non-Destructive Imaging CAD/CAE Printer - Sketchpad - Portable Maintenance Aid CAD/CAE table CAD/CAE Printer Ames Aviation Extranet & the IPG Ver 2. 0 United Maint. Syst. Digital White Board CAD/CAE Printer

Airport Approach Zone Camera System

Software Technology NAS Simulation Environment Simulations, Models Experimental databases Virtual National Air Space VNAS

Daily NAS Simulation Baseline Generation Engine Models Stabilizer Models GRC 66, 000 Stabilizer Runs 50, 000 Engine Runs 44, 000 Wing Runs Wing Models Airframe Models ARC La. RC 22, 000 Commercial US Flights a day 48, 000 Human Crew Runs Human Models Simulation Drivers (Being pulled together under the NASA Av. SP Aviation Extra. Net (AEN) Virtual National Air Space VNAS 22, 000 Airframe Impact Runs 132, 000 Landing/Take-off Gear Runs FAA Ops Data Weather Data Airline Schedule Data Digital Flight Data Radar Tracks Terrain Data Surface Data Landing Gear Models

SIPS: Advanced Aerospace Software Synthesis & Verification Technology Strategy for Impact √ • Demonstrate potential impact on Aerospace (e. g. , case studies, industry/research/NASA collaborations) Do research to make technology cost-effective Langley AILS Verification Already cost-effective when applied to limited-scale models, e. g. top-level architecture, digital hardware subsystems. Core algorithms need to scale up to larger models. Reduce human labor cost and expertise of using algorithms • Provide objective basis for certification based on largely automated technology and/or reusable core analysis. Ames DEOS Verification Scalable Deductive Program Synthesis

Advanced Computing Computational Grids Computers • Supercomputers • Experimental Facilities High-Speed Networks Collaborative Environments • Databases • Mass Storage

Advanced Computing Computational Grids

Breakout Sessions • 1: Next Generation Capacity Technologies – – • 2: Aviation Human Factors – – • 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 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 – – • 5: Capacity: Distributed Air Ground Traffic Management – – • 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 Steve Green: Moderator Steve Green: Distributed Air-Ground Traffic Management Dr. Ev Palmer: Linking Air & Ground Automation Sandy Lozito: Shared Air-Ground Separation Responsibilities 6: Improved Capacity Through Vertical Flight – – Ed Aiken: Moderator Sandy Hart: R&D for Rotorcraft Safety Mark Betzina: Tiltrotor Source Noise Abatement (Wind Tunnel Tests) Bill Decker: Tiltrotor Operational Noise Abatement (Flight & Simulation Tests)