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Research and TechnologyN A S A A m e s R e s e a r c h

Research and Technology

Ames Research Center

National Aeronautics and Space Administration

Ames Research CenterMoffett Field, California

NASA TM-112195

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Foreword

The mission of NASA Ames Research Center is to research, develop, verify, and transfer advanced aeronautics,space, and related technologies; to advance and communicate scientific knowledge and understanding of theuniverse, the solar system, and the Earth; and to enable the development of space for human enterprise. Empha-sis is placed on information systems technologies for aeronautics and space applications; on aviation operationssystems; and on the discipline of astrobiology, the study of life in the universe encompassing the Earth, space,and life sciences.

This report highlights the challenging work accomplished during fiscal year 1996 by Ames research scientists,engineers, and technologists. It discusses research and technologies that enable the Information Age, thatexpand the frontiers of knowledge for aeronautics and space, and that help to maintain U. S. leadership inaeronautics and space research and technology development. The accomplishments span the range of goals ofNASA’s four Strategic Enterprises: Aeronautics and Space Transportation Technology, Space Science, HumanExploration and Development of Space, and Mission to Planet Earth.

The primary purpose of this report is to communicate information—to inform our stakeholders, customers, andpartners, and the people of the United States about the scope and diversity of Ames’ mission, the nature ofAmes’ research and technology activities, and the stimulating challenges ahead. The accomplishments citedillustrate the contributions that Ames is making to improve the quality of life for our citizens and the economicposition of the United States in the world marketplace.

For further information on Ames research and technology projects, please contact the person designatedas the point of contact at the end of each article. An electronic version of this report is available atURL http//jit.arc.nasa.gov/atrs/index.html.

Henry McDonaldDirector

http://atrs.arc.nasa.gov/

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Aeronautics Enterprise

Overview ................................................................................................................................................. 1

Global Civil Aviation/Safety

Aviation Performance Measuring System.................................................................................................. 3Irving C. Statler

Aviation Safety Reporting System ............................................................................................................. 4Linda J. Connell

Crew Activity Tracking System ................................................................................................................. 5Todd J. Callantine

Study of Line Oriented Flight Training ...................................................................................................... 6Key R. Dismukes

Measuring Air Traffic Complexity ............................................................................................................. 7Irene V. Laudeman, Connie Brasil, Robert Branstrom

Operational Interventions to Human Error in Aircraft Maintenance .......................................................... 8Barbara G. Kanki, Vicki Dulchinos

Aircraft Separation Risk Model ................................................................................................................. 9Mary M. Connors

The Final Approach Spacing Tool ............................................................................................................ 11Tom Davis

Air/Ground Integration ............................................................................................................................. 11R. Slattery

The Traffic Management Advisor .............................................................................................................. 12Harry N. Swenson

Surface Movement Advisor ...................................................................................................................... 13Brian J. Glass

Simplified Vision Models for Display Quality Assessment ........................................................................ 14Al Ahumada

Perceptually Tuned Visual Simulation ...................................................................................................... 15Mary K. Kaiser

Entropy Masking in Visual Displays.......................................................................................................... 17Andrew B. Watson

Vertical Motion Simulator Advanced Simulator Network ......................................................................... 18William B. Cleveland

Intelligent Aircraft Control System ............................................................................................................ 19Charles C. Jorgensen

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Aeronautics Enterprise (continued)

Global Civil Aviation/Affordability

Facilitating User Route Preferences in En Route Airspace ......................................................................... 20Bob Vivona, Mark Ballin, Steve Green, Ralph Bach, Dave McNally

Conflict Probability Estimation for Free Flight ........................................................................................... 21Russell A. Paielli, Heinz Erzberger

Conflict Prediction Algorithms: Initial Field Test ....................................................................................... 23Dave McNally, Bob Vivona, Karl Bilimoria, Gerd Kanning, Steve Green, Ralph Bach,Allan McCrary, Ed Lewis

Assessing Controller Performance Under Simulated Free-Flight Conditions .............................................. 24Roger Remington, James Johnston, Eric Ruthruff, Maria Romera

Evaluating Cockpit Display of Traffic Information Displays and Route Assessment Toolsfor a Free Flight Environment ................................................................................................................... 25

Vernol Battiste, Walter W. Johnson

Cockpit Displays for Low-Visibility Taxiing .............................................................................................. 27David Foyle, Elizabeth M. Wenzel, Durand R. Begault

Multi-Sensor Image Registration ............................................................................................................... 29Misha Pavel, Al Ahumada, Barbara Sweet

Flow Visualization of a Full-Scale Rotor in Hover .................................................................................... 29Benton H. Lau, Alan J. Wadcock, Gloria K. Yamauchi

Skin-Friction Measurements on a Hovering Rotor ..................................................................................... 30Alan J. Wadcock, Gloria K. Yamauchi

Rotor Data Correlation ............................................................................................................................. 31Randall Peterson

Canard Rotor/Wing Hover Test ................................................................................................................ 32Stephen Swanson, John Madden

In-flight Dynamic Stall Research .............................................................................................................. 34Robert Kufeld, William Bousman

Stall Control of Helicopter Rotors ............................................................................................................. 34Khanh Q. Nguyen

Apache AH-64D Flight Test Predictions ................................................................................................... 35Earl P. N. Duque

Rotor-Wake/Fuselage Interaction.............................................................................................................. 36Paul M. Stremel

Navier-Stokes Simulation of High-Lift Aerodynamics ............................................................................... 37Karlin Roth, Stuart Rogers

Lift-Jet Effects on Powered-Lift STOVL Model ........................................................................................... 38Karlin Roth

Vortex Core Detection for Computational Grid Refinement ...................................................................... 38David Kenwright

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Global Civil Aviation/Affordability (continued)

Wingtip Vortex Flows............................................................................................................................... 39Jennifer Dacles-Mariani, Dochan Kwak

Transonic Overset Potential Solver ........................................................................................................... 40Terry Holst

Real-Time Particle Tracing in Time-Varying Flows ................................................................................... 41David Kenwright, David Kao

NASA Metacenter .................................................................................................................................... 42Mary Hultquist

Portable Batch System .............................................................................................................................. 43David Tweten

Developing a Cluster Computer from Workstations .................................................................................. 43Reese L. Sorenson

Planar Doppler Velocimetry Using Pulsed Lasers ..................................................................................... 44Robert L. McKenzie

Pressure-Sensitive Paint and Photogrammetry for Aeroelastic Experiments ............................................... 45Edward T. Schairer, Lawrence A. Hand

Visualizing Wind-Tunnel Experimental Data ............................................................................................ 47Samuel P. Uselton, Glenn Deardorff, Leslie Keely, Yinsyi Hung, Arsi Vaziri

Surface Tension Effects on Skin Friction Measurements ............................................................................ 48G. Zilliac, A. Celic

Fullerene Gear Design, Simulation, and Visualization .............................................................................. 49Albert Globus

Global Civil Aviation/Environmental Compatibility

Civil Tiltrotor Noise Abatement Approaches ............................................................................................ 51William A. Decker, Rickey C. Simmons

XV-15 Blade-Vortex Interaction Noise...................................................................................................... 52C. W. Acree, Megan S. McCluer, Cahit Kitaplioglu

Tiltrotor Aeroacoustic Model .................................................................................................................... 53Larry Young

Predicting and Analyzing Rotorcraft Noise ............................................................................................... 54Roger C. Strawn, Rupak Biswas, Lenny Oliker

Airframe Noise Measurements: Atmospheric Pressure .............................................................................. 55W. Clifton Horne, Julie A. Hayes, Michael E. Watts, Paul H. Bent

Airframe Noise Measurements: Pressures to 4.7 Atmospheres .................................................................. 56W. Clifton Horne, Stephen M. Jaeger, Mahendra Joshi, James R. Underbrink

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Revolutionary Technology Leaps/Innovative Technology and Tools

X-36 Pioneers Advanced Aerodynamics and Flight Controls .................................................................... 57Rodney Bailey, Mark Sumich

Closed-Loop Neural Control of Rotorcraft Vibration ................................................................................. 57Sesi Kottapalli

Coupled Navier–Stokes and Optimizer Analysis of a Transonic Wing ...................................................... 58Roxana M. Greenman, Samson Cheung, Eugene L. Tu

Parallel Unstructured Mesh Adaption ....................................................................................................... 59Rupak Biswas, Leonid Oliker, Roger Strawn

Load Balancing Adaptive Unstructured Meshes........................................................................................ 59Rupak Biswas, Leonid Oliker, Andrew Sohn

Initial Release of the Field Encapsulation Library ...................................................................................... 61Steve Bryson

RANS-MP: Portable Parallel Navier–Stokes Solver .................................................................................... 61R. Van der Wijngaart, Maurice Yarrow

Parallel Tools for Parallel and Distributed Computer Systems ................................................................... 63D. DiNucci, M. Frumkin, R. Hood, H. Jin, L. Lopez, R. Papasin, C. Schulbach, J. Yan

Numerical Aerodynamic Simulation Parallel Benchmarks 2.2 .................................................................. 65William Saphir, R. Van der Wijngaart, Alex Woo, Maurice Yarrow

Large-Scale Parallel Semiconductor Simulation ........................................................................................ 65Subhash Saini

Revolutionary Technology Leaps/Supersonic Technology

Nonlinear Aerodynamic Shape Optimization of High-Speed Research Configurations ............................. 66Susan Cliff, James Reuther, Ray Hicks

Surface Operations Behavioral Evaluation Interim Testbed for High-Speed Research ............................... 68Mary K. Kaiser

Revolutionary Technology Leaps/Access to Space

Propulsion Checkout and Control System................................................................................................. 69Ann Patterson-Hine

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Space Science Enterprise

Overview ................................................................................................................................................. 71

Progress in Exobiology

Remote Analysis of Martian Surface Materials .......................................................................................... 74D. Blake, P. Sarrazin, D. Bish, D. Vaniman, S. Chipera, S. A. Collins, T. Elliott

Stable Isotope Biogeochemistry of Hydrothermal Systems ........................................................................ 76David J. Des Marais

Fossilization Processes in Thermal Springs ............................................................................................... 77Jack Farmer, Sherry Cady, David J. Des Marais

Molecular Biomarkers for Stromatolite-Building Cyanobacteria ................................................................ 78Linda L. Jahnke, Roger E. Summons, Harold P. Klein

Earth-Threatening Comets Leave Tell-Tale Dust Trails .............................................................................. 80Peter Jenniskens, David Morrison

Capturing Cosmic Dust on Mir ................................................................................................................. 81Kenji Nishioka, Ted Bunch, Mark Fonda, Glenn Carle, Sherwood Chang, James Ryder, Janet Borg

Simple Peptides at Water-Membrane Interfaces ........................................................................................ 82Andrew Pohorille, Christophe Chipot

Silicon-Micromachined Gas Chromatography System .............................................................................. 84Thomas Shen, James Suminto, Frank Yang, Daniel Kojiro, Glenn Carle

Nitrogen Sources and Sinks on Early Earth ............................................................................................... 85David P. Summers

Progress in Planetary Systems

Planetary Rings ........................................................................................................................................ 86Jeff Cuzzi

Planetesimal Formation in the Protoplanetary Nebula .............................................................................. 87Jeff Cuzzi

PASCAL: A Mars Climate Network Mission .............................................................................................. 87Robert M. Haberle, David C. Catling, Steven C. Merrihew

The Center for Star Formation .................................................................................................................. 88D. Hollenbach, P. Cassen

Energetic Trapped Particles near Jupiter ................................................................................................... 89John D. Mihalov

Wavelet Software ..................................................................................................................................... 90Jeff Scargle

Time-Dependent Structures in Galaxies ................................................................................................... 90Bruce F. Smith, Richard A. Gerber, Richard H. Miller, Thomas Y. Steiman-Cameron

Galileo Encounters Jupiter: Results from the Probe ................................................................................... 91Richard E. Young

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Space Science Enterprise (continued)

Progress in Planetary Systems (continued)

Regolith Effects on Mars’ Climate ............................................................................................................. 92Aaron Zent

The Nature of the Martian Oxidants ......................................................................................................... 92Aaron Zent

A Thermo-Acoustic Oxidant Sensor ......................................................................................................... 93Aaron Zent

Progress in Astrophysics

Astrobiology in the Astrochemistry Laboratory ......................................................................................... 93Louis J. Allamandola, Scott Sandford, Max Bernstein, Robert Walker, Dave Deamer

Spectrum Synthesis of Hot Water in Sunspots and Selected Cool Stars ..................................................... 94Duane F. Carbon, David Goorvitch

A High-Altitude Site Survey for SOFIA...................................................................................................... 95Michael R. Haas, Leonhard Pfister

Kepler Mission Educational and Public Outreach Software ...................................................................... 96David Koch

Mid-Infrared Studies of Diffuse Interstellar Material .................................................................................. 97Thomas L. Roellig

Infrared Observations of G0.18-0.04 ........................................................................................................ 98Janet P. Simpson, Sean W. J. Colgan, Angela S. Cotera, Edwin F. Erickson, Michael R. Haas,Mark Morris, Robert H. Rubin

New 3.405-Micron Interstellar Emission from Organic Hydrocarbons ...................................................... 99Gregory C. Sloan, Jesse D. Bregman

Progress in Space Technologies

Assessment of the Cassini Command and Data Subsystem ....................................................................... 101Edward A. Addy

Automatic Telescope Project .................................................................................................................... 101John Bresina

Guide Star Tracker for Gravity Probe B Relativity Mission ........................................................................ 103John H. Goebel

Pulse-Tube Cryocooler Development ....................................................................................................... 103Peter Kittel

Automated Space System Experimental Testbed Project ........................................................................... 105Christopher Kitts

Amphion and Meta-Amphion................................................................................................................... 105Michael Lowry

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Space Science Enterprise (continued)

Progress in Space Technologies (continued)

Focal-Plane Sensor Array Development for Astronomy in Space .............................................................. 106Mark E. McKelvey, Robert E. McMurray, Jr., Craig R. McCreight

Intelligent Execution for Autonomous Spacecraft ...................................................................................... 108Barney Pell

New Millennium Program Deep Space 1 Flight Software Program Management ...................................... 108Scott Sawyer

Human Exploration and Development of Space Enterprise

Overview ................................................................................................................................................. 111

Astronaut Health/Science

Biochemical Markers of Bone Metabolism in a Rat Spaceflight Model ..................................................... 114Meena Navidi, Jeanne Wren, Sara Arnaud

Cerebrovascular Responses Prior to Fainting ............................................................................................ 115Kana Kuriyama, Toshiaki Ueno, Richard E. Ballard, Donald E. Watenpaugh,Suzanne M. Fortney, Alan R. Hargens

Chronic Exposure to Hyper-G Suppresses Otolith-Spinal Reflex in the Rat ............................................... 116Nancy G. Daunton, Merylee Corcoran, Robert A. Fox, Li-Chun Wu

“Dual Adaptation” to Space-Related Sensory Rearrangements .................................................................. 118Robert B. Welch

Technology Applications to Human Health

Virtual Environment Surgery Workbench ................................................................................................. 119Muriel D. Ross

Noninvasive Estimation of Pulsatile Intracranial Pressure Using Ultrasound ............................................. 120Toshiaki Ueno, Richard E. Ballard, John H. Cantrell, William T. Yost, Alan R. Hargens

MRI-Compatible Spinal Compression Harness ......................................................................................... 122Richard E. Ballard, Donald E. Watenpaugh, Iwane Mitsui, Klaus P. Fechner,Douglas S. Schwandt, Alan R. Hargens

Near-Infrared Spectroscopy to Monitor Forearm Muscle Oxygenation ..................................................... 123Gita Murthy, Alan R. Hargens

BIONA 1—Blood Flow Ion Analyzer........................................................................................................ 125John W. Hines, Christopher J. Somps

Intelligent Controller for Neurosurgery ..................................................................................................... 126Robert Mah

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Human Exploration and Development of Space Enterprise (continued)

Technology Applications to Human Health (continued)

Center for Health Applications of Aerospace Related Technologies (CHAART) ........................................ 128Byron Wood, Louisa Beck, Sheri Dister, Brad Lobitz

Telemedicine Spacebridge to Russia ........................................................................................................ 128Steve N. Kyramarios

Progress in Improving Space Travel

Advanced Life Support/Human Exploration and Development of Space Enterprise Activities ................... 129Dick Lamparter, Mark Kliss

Mir Hardware—Stepping Stone to Station ................................................................................................ 130Bonnie P. Dalton, James Connolly, Gary Jahns, Paul Savage

Wireless Network Experiment for Space Shuttle/Mir ................................................................................. 131Richard Alena

Engine Diagnostic Filter System................................................................................................................ 132Tarang Patel

Formal Lightweight Approaches to Validation of Requirements Specifications ......................................... 133Steve Easterbrook

Astronaut Health/Countermeasures

Autogenic-Feedback Training as a Potential Treatment for Postflight Orthostatic Intolerance ................... 135Patricia S. Cowings, William B. Toscano

Exercise for Long-Duration Spaceflight ..................................................................................................... 138Donald E. Watenpaugh, Richard E. Ballard, Karen J. Hutchinson, Jaqueline M. William,Andrew C. Ertl, Suzanne M. Fortney, Lakshi Putcha, Wanda L. Boda, Stuart M. C. Lee,Alan R. Hargens

Keiser SX-1 Variable Resistance Exercise Device ...................................................................................... 139Jennifer Pedley, Anthony Artino, Richard Ballard, Alan R. Hargens

Dehydration at Airline Cabin Altitude ...................................................................................................... 141John E. Greenleaf, Peter A. Farrell, Helmut Hinghofer-Szalkay

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Mission to Planet Earth Enterprise

Overview ................................................................................................................................................. 145

Ecosystem Science and Technology

AIRDAS—Use of Remote Sensing for Disaster Assessment and Management ........................................... 147James Brass, Vincent Ambrosia, Robert Slye

Bay Area Digital Georesource .................................................................................................................. 147Edwin Sheffner, Sheri Dister, Don Sullivan

Brazil/United States Environmental Monitoring and Global Change Program ........................................... 148James Brass, Vincent Ambrosia

Carnegie/Ames/Stanford Approach Model ................................................................................................ 149Christopher Potter

Digital Array Scanning Interferometer ...................................................................................................... 149Steve Dunagan, Philip Hammer

Effect of Landuse on Regional Estimates of Coniferous Forest Water and Carbon Budgets ........................ 151Joseph Coughlan, Jennifer Dungan

Landsat Program ...................................................................................................................................... 152Edwin Sheffner

Leaf Modeling .......................................................................................................................................... 152Lee F. Johnson, Chris Hlavka, Philip D. Hammer, David L. Peterson

Mapping Northern Ecosystems: Applications for Circumpolar Methane Exchange.................................... 153Vern Vanderbilt, Guillaume Perry, Joel Stearn

Modern Ecosystems Research: Effects of Increased UV-B Radiation.......................................................... 153Hector L. D’Antoni, J. W. Skiles

Optimizing an Ecosystem Model for Use on Parallel/Distributed Processors ............................................. 154J. W. Skiles, Cathy Schulbach

Paleoenvironmental Research .................................................................................................................. 155Hector L. D’Antoni

Scientists’ Intelligent Graphical Modeling Assistant .................................................................................. 155Jennifer Dungan

Atmospheric Chemistry

Airborne Natural Radionuclide Measurements in the Development and Validation ofGlobal Three-Dimensional Models .......................................................................................................... 156

Mark Kritz, Stefan Rosner, Robert Chatfield, Leonard Pfister

Reactive Nitrogen Data from the Upper Troposphere and Lower Stratosphere ......................................... 156Hanwant B. Singh, Alakh Thakur, Peter Mariani

Airborne Autotracking Sunphotometry ..................................................................................................... 157Philip B. Russell, John M. Livingston, James Hanratty, Damon Ried, Jill Bauman

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Mission to Planet Earth Enterprise (continued)

Atmospheric Chemistry (continued)

Analysis of Stratosphere/Troposphere Exchange ....................................................................................... 157Leonhard Pfister, Henry Selkirk

Use of Argus in Atmospheric Studies ........................................................................................................ 158Max Loewenstein

Airborne Tunable Laser Absorption Spectrometer ..................................................................................... 158Max Loewenstein, James R. Podolske

Convectively Generated Gravity Waves ................................................................................................... 159Leonhard Pfister

The ER-2 and DC-8 Meteorological Measurement Systems ...................................................................... 159K. Roland Chan, T. Paul Bui, Antonio A. Trias, Stuart W. Bowen, Jonathan Dean-Day

Environmental Research Aircraft and Sensor Technology ......................................................................... 160Steve Wegener

Global Emissions Inventories for Radon and the Cosmogenic Radionuclides ............................................ 161Mark Kritz

The Great African Plume: Tropical Carbon Monoxide and Ozone Simulation .......................................... 162Robert B. Chatfield

Instrument for Tropospheric Nitrogen Studies ........................................................................................... 163James R. Podolske

Reactive Nitrogen and Oxygenated Hydrocarbon Measurements during the PacificExploratory Mission.................................................................................................................................. 163

Hanwant B. Singh, W. Viezee, R. Chatfield, Y. Chen, D. Herlth, R. Kolye

Subsonic Aircraft: Contrail and Cloud Effects Special Study...................................................................... 163Owen B. Toon, Steve Hipskind, Duane Allen, Paul Bui, Roland Chan, Mike Craig, Guy Ferry,Steve Gaines, Warren Gore, Eric Jensen, Joe Jordan, Stefan Kinne, Bill McKie, Peter Pilewskie,Rudi Pueschel, Tony Strawa, Annette Walker

Stratospheric Tracers of Atmospheric Transport ........................................................................................ 164Stephen Hipskind, Michael Craig

Tropospheric Aerosol Radiative Forcing Observational Experiment .......................................................... 165Philip B. Russell, John M. Livingston, Wendy Whiting

Atmospheric Physics

Fine Particle Emissions by Aircraft ............................................................................................................ 166Rudolf F. Pueschel, Guy V. Ferry, Anthony W. Strawa, Duane Allen

FIRE Phase III ........................................................................................................................................... 166Peter Pilewskie, Warren Gore

Laboratory Spectroscopy of Carbon Dioxide in Support of Planetary Atmospheres Research .................... 167Lawrence P. Giver, Charles Chackerian, Jr.

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Mission to Planet Earth Enterprise (continued)

Atmospheric Physics (continued)

Near-Infrared Remote Sensing of Cloud Liquid Water .............................................................................. 167Peter Pilewskie, Warren Gore

Quantitative Infrared Spectroscopy of Minor Constituents of the Earth’s Atmosphere ............................... 168Charles Chackerian, Jr., Lawrence P. Giver

Stratospheric Transport ............................................................................................................................. 169Rudolf F. Pueschel, Guy V. Ferry, Anthony W. Strawa, Duane Allen

SUCCESS Irradiance Measurements ......................................................................................................... 170Peter Pilewskie, Warren Gore

Appendix

Color Plates (1–22) ................................................................................................................................... 172

Aeronautics and Space Transportation Technology Enterprise

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O v e r v i e wNASA’s mission for the Aeronau-

tics and Space Transportation Tech-nology (ASTT) Enterprise is to pioneerthe identification, verification,transfer, application, and commercial-ization of high-payoff aeronautics andspace transportation technologies.Ames’ researchers and technologistssupport this mission by seekingenabling revolutionary technologicaladvances that will provide air andspace travel for anyone, anytime,anywhere more safely and moreaffordably, and with less effect on theenvironment and with improvedbusiness opportunities and globalsecurity.

This pursuit of revolutionarytechnologies addresses bold, mid-term and long-term goals of theASTT Enterprise to enable dramaticimprovements in aviation and spacetransportation. This reflects nationalpriorities as outlined by the NationalScience and Technology Council.These goals are grouped into threeareas, or as they are called, threepillars: “Global Civil Aviation,”“Revolutionary Technology Leaps,”and “Access to Space.” The followingsections outline these goals andAmes’ FY96 accomplishments towardachieving them.

Pillar 1: Global Civil AviationToday, with over 11,000 air-

planes in commercial service world-wide, the United States faces stronginternational competition in this vitalarea whose products are the largestpositive industrial contributor to theU.S. balance of trade. Projects linkedto world economic growth suggestthat air travel demand will triple overthe next 20 years. Therefore, topreserve our Nation’s economichealth and the welfare of the travelingpublic, NASA must provide high-risktechnology advances that willcontribute to safer, more affordable,more environmentally compatible airtravel.

The highlighted FY96 accom-plishments address the followinggoals of the Global Civil Aviationpillar:1. Safety goal: Reduce the aircraft

accident rate by a factor of 5within 10␣ years, and by a factorof 10 within 20 years.

2. Affordability goals: (a) Whilemaintaining safety, triple theaviation system throughput, inall weather conditions, within10␣ years and (b) reduce the costof air travel by 25% within10␣ years, and by 50% within20␣ years.

3. Environmental compatibility goal:Reduce the perceived noise levelsof future aircraft by a factor of 2(from those of today’s subsonicaircraft) within 10␣ years, and by afactor of 4 within 20 years.

Research and developmentconducted by the ASTT Enterprise hasbeen structured to be led by specifiedNASA research centers according tothe primary roles and missions thathave been assigned to each center.Ames is the lead center for the HighPerformance Computing and Com-munications (HPCC) Program and forthe research and technology (R&T)base programs in aviation operationssystems, information technology, androtorcraft. In addition, Ames leads theEnterprise core competencies in theareas of human factors, air-trafficmanagement, information systemtechnologies, and rotorcraft R&T.

Ames’ significant involvementin the safety goal includes humanfactors, information technology, andcondition-based maintenance. Amesmade significant contributions towardaddressing this goal, contributionsthat led to advances in aviationperformance measuring, aviationsafety reporting, crew activity track-ing, air-traffic complexity, aircraft-separation risk modeling, air andground integration, and human errorin aircraft maintenance.

Airlines and businesses losebillions of dollars annually as a result

A E R O N A U T I C S A N D S P A C E T R A N S P O R T A T I O NT E C H N O L O G Y E N T E R P R I S E

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of delays and lost productivity owingto weather and congestion in theairspace system. Under affordabilitygoal (a) (above), Ames’ major effortin research and development of air-traffic management automationconstitutes virtually all of NASA’swork in that area. Accomplishmentsinclude articles on controller perfor-mance under simulated free-flightconditions, techniques for low-visibility taxi and ground-collisionavoidance, and conflict-predictionalgorithms.

Reducing the costs of aircraftoperation and maintenance is a majorchallenge. NASA’s test facilities andcore expertise in materials, structures,aerodynamics, propulsion, analyticalmethods, and computational tools arekey elements in helping to revolution-ize aircraft design and manufacturing.NASA’s research efforts are focusedon innovative design techniques andstructural concepts. Ames’ contribu-tions to affordability goal (b) comefrom rotorcraft, national taskingfacilities, and research and develop-ment of computational tools. SeveralAmes projects contributed to rotor-craft research and technologyactivities, which include rotor aero-dynamics, testing of new concepts,stall control, in-flight dynamic stallresearch, and vortex flows. Examplesof accomplishments that enhancecomputational tools are vortex-coredetection and tracking of particles intime-varying flows. Improvements inthe use of facilities are highlighted inthe following pages by articles onplanar Doppler velocimetry, pressure-sensitive paint and photogrammetry,and visualization of experimentaldata. A high-risk, long-term researcheffort directed to the manufacture offullerene nanotechnology gears is alsodescribed.

For research related to theenvironmental compatibility goal,Ames has significant aeroacousticresearch and testing capabilities, themost recent advance in those capa-bilities being the Aeroacoustic

Modification Project at Ames’National Full-Scale AerodynamicsComplex (NFAC), which is currentlybeing completed. In this report,accomplishments related to helicopternoise and airframe noise arepresented.

Pillar 2: Revolutionary TechnologyLeaps

NASA’s charter is to explore high-risk technology areas that can revolu-tionize air travel and create newmarkets for U.S. industry. The tech-nology challenges for NASA includeaccelerating the application oftechnology advances, eliminatingthe barriers to affordable supersonictravel, and expanding generalaviation,

The highlighted FY96 accom-plishments address the following twogoals of the Revolutionary Technol-ogy Leaps pillar:1. Provide next-generation design

tools and experimental aircraft toincrease design confidence, andcut the aircraft developmentcycle time in half.

2. Reduce the travel time to the FarEast and Europe by 50% within20 years, and do so at today’ssubsonic ticket prices.

The next-generation design toolsand experimental aircraft goal willdramatically affect the way in whichbusiness is conducted. Its effect willbe felt across the three pillars, contrib-uting to every technology goal. Ameshas significant work in integrateddesign systems and the X-36 aircraft.Research is done at Ames in informa-tion technology to elevate the powerof computing tools through fuzzylogic, neural networks, and artificialintelligence. These tools will integratemultidisciplinary product develop-ment activities to dramatically cutdesign cycle times. Examples ofaccomplishments include neuralcontrol of rotorcraft vibration, cou-pling of flow-field computation toolswith design optimization tools, andparallel computational tools and

computations. Experimental aircraftare also invaluable tools for exploringnew ideas. An example is providedwith the use of advanced aero-dynamics and flight controls on theX-36 aircraft.

Under the high-speed transportgoal, Ames has diverse activities inwind-tunnel testing and simulation,external visibility, sonic boomminimization, and wing aerodynamicoptimization. Articles are presented inthis report to highlight these activities.

Pillar 3: Access to SpaceIn coming decades, NASA

envisions the space frontier as a busycrossroads of U.S.-led internationalscience, research, commerce, andexploration. Experience with this vastresource has already yielded newtreasures of scientific knowledge, life-enhancing applications for use onEarth, and fantastic celestial discover-ies. The potential for the future seemsalmost limitless.

Ames addresses the followinggoal of the third pillar, Access toSpace:1. Reduce the payload cost to

low-Earth orbit by an order ofmagnitude, from $10,000 to$1,000 per pound, within10␣ years.

As NASA’s lead center forthermal protection systems (TPSs)technology, Ames is charged withdeveloping new thermal protectionsystems that will enable vehiclesof the future to be built more eco-nomically and that will enableexisting ones to be upgraded atreduced cost. Ames maintains one ofthe world’s premier arc-jet complexesfor providing realistic simulations ofentry environments. These simulationsare essential for technology develop-ment, system validation, and systemqualifications. Ames supports the U.S.aerospace community in developingTPSs that will be necessary for thenation’s future space vehicles.


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GLOBAL CIVIL AVIATION/SAFETY

Aviation PerformanceMeasuring SystemIrving C. Statler

Flight Operations QualityAssurance (FOQA) programs usingflight-recorded data have beenproviding critical safety informationto non-U.S. airlines for over twodecades. Although the benefits ofthese programs have been demon-strated, the U.S. air carriers havefound them impractical to imple-ment because of the extensivelabor required to process the greatamounts of data that would typicallybe generated. A collaborative effortwas initiated in August 1993between the Federal AviationAdministration (FAA) and NASA toestablish and demonstrate thefeasibility of developing a set oftools that would allow very largequantities of flight data to be pro-

cessed automatically in order toaddress questions relating to opera-tional performance and safety.

The Aviation PerformanceMeasuring System (APMS) is provid-ing technical tools to facilitate thelarge-scale implementation of flight-data analyses at both the air-carrierand the national-airspace levels.APMS enhances the existingCommercial Off The Shelf (COTS)capabilities of FOQA, including thecapability of analyzing all the datacollected, in addition to merelyidentifying “exceedances” or“special events” (the figure showsthe APMS functions).

Phase 1 of the APMS effortended in December 1995. Phase 2focuses on three tasks: (1) selectionand implementation of an APMSclient-server database architecture;(2) development of a knowledge-based system for verifying anddiagnosing “special events” flaggedby COTS packages; and (3) construc-tion of a friendly user-interface in

Visual Basic. The client-serverdatabase architecture and methodfor the initial build have beenselected. Teledyne Control’sFLIDRAS software has been acquiredto read Flight Data Recorder rawdata parameters, to convert the datainto engineering units, and toperform data dumps into the data-base management system. As theflight database is built, the baselinesof various routine operations will beestablished. Knowledge-based tools,currently under development by theAPMS team, will, in later iterationswhen an adequate database isavailable, provide statistical trendingand predictive capabilities. The firstprototype system was delivered inJuly 1996 to the first airline partner.The prototype system is now opera-tional and currently being used toprocess airline flight data.

With the industry becomingaware of the capabilities of theAPMS suite of tools, the team isbeing approached by other airlinesthat had not been solicited toparticipate in the research project.So far, one additional major airlineand one major cargo airline haveasked to participate in the program.User-needs studies have beencompleted with four U.S. airlinesand a fifth has been started. Agree-ments have been signed with twoof these to cooperatively developcustomized suites of APMS tools.The APMS effort continues to workwith collaborators to improve systemdesign.

Point of Contact: I. Statler(650) [email protected]

G L O B A L C I V I L A V I A T I O N / S a f e t y

GLOBAL CIVIL AVIATION/SAFETY

Fig. 1. APMS functions.

Screening forspecial events

Statisticalanalysis

Flightanimation

Databaseexploration

Database

1997 1998 1999 200019961995

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4

Aviation Safety ReportingSystemLinda J. Connell

The Aviation Safety ReportingSystem (ASRS) solicits, processes,and analyzes aviation safety incidentreports from pilots, air-traffic control-lers and others and uses the data itcollects to further aviation safety.The ASRS (1) codifies the reports itreceives (31,096 in FY96) and insertsthem into a computer database;(2)␣ issues alerting messages onpressing safety problems describedby incoming reports; (3) providesdata retrieval services (searchrequests) for aviation safety research-ers and others; (4) publishes amonthly safety bulletin, CALLBACK,and a periodic safety journal,DIRECTLINE; (5) performs QuickResponse analytic efforts for theFederal Aviation Administration(FAA), the National TransportationSafety Board (NTSB), and othergovernmental entities; and (6) doesapplied research on aviation opera-tional problems, especially thoseinvolving human performance (seethe figure). The ASRS is heavilyreliant on information technology,and a portion of program resourcesis devoted to maintaining andupgrading that technology.

The following list is a summaryof some of ASRS’s FY96 activities. InFY96, the ASRS program:␣ ␣ •␣ ␣ Initiated an ASRS Internet site in

November 1995. Through itsWeb site, ASRS offers its publi-cations, program information,and downloadable (using anAdobe Acrobat reader) versionsof the NASA Incident ReportingForms.

␣ ␣ •␣ ␣ Accomplished a Multi-EngineTurbojet Uncommanded UpsetsStructured Callback Analysis forthe NTSB. The analysis wassubsequently adopted into theUSAir B-737 accident investiga-tion report.

␣ ␣ •␣ ␣ Completed a GPS Safety ImpactAnalysis for the FAA AssociateAdministrator of Research andAcquisitions.

␣ ␣ •␣ ␣ Accomplished a Quick Responseanalysis of Runway Transgres-sion Data for the FAA Office ofSystem Safety. These data weresubsequently presented to theFAA deputy administrator.

␣ ␣ •␣ ␣ Completed Quick ResponseNo.␣ 289 entitled “Near Mid-AirCollision Data Analysis” for theFAA Office of System Safety.

␣ ␣ •␣ ␣ Accomplished the secondinstallment of the Wake Turbu-lence Structured CallbackProject Reports; it included theanalysis of 51 wake turbulenceincidents and was submitted tothe FAA.

␣ ␣ •␣ ␣ Produced search requests for theNTSB and the FAA on DC-9cabin/cockpit smoke and aircraftequipment problems in supportof the investigation of the DC-9accident near Miami, Florida, onMay 11, 1996.

␣ ␣ •␣ ␣ Produced a Quick Responseanalysis of Part 135 AircraftIncidents for the AustralianBureau of Air Safety Investiga-tion. The data are being used todevelop a proactive aviationsafety hazard monitoring system.

Quick responsesto FAA & NTSB

Monthly safetynewsletter

Quarterly safetybulletin

Research

Safetyalerts

Databasesearch

requests

DatabaseCD ROM

Incident reports

ASRS

1997 1998 1999 200019961995

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Fig. 1. ASRS products.



5

␣ ␣ •␣ ␣ Transmitted 30 runway-incursion reports at Cleveland-Hopkins Airport, Ohio, to theFAA Office of System Safety andthe Air Line Pilots Association.As a result of ALPA and FAAfollow-up actions, revisedground-control procedures wereimplemented for departuresusing runways 23L/23R.

␣ ␣ •␣ ␣ Transmitted 24 reports to FAAand ALPA involving altitudedeviations at FUELR Intersectionon the CIVET ONE ARRIVAL toLos Angeles InternationalAirport. Subsequent investiga-tion by the FAA determined thatthe recent installation of a newILS had changed the glidepathangle at FUELR.

␣ •␣ ␣ Published one issue ofDIRECTLINE in FY96. Itsresearch articles addressedaircraft call-sign confusion andramp safety.

␣ ␣ •␣ ␣ Developed a trial version of theASRS Intranet communicationssystem. It runs on an NT Serverand is available to the ASRSstaff. The decision was made inJanuary 1996 to develop thisinternal Intranet communica-tions system based on existingInternet applications in order tolower costs and increase effi-ciency internally at the ASRS.

␣ ␣ •␣ ␣ Commenced a collaborativeresearch project betweenNASA and its French counter-part, ONERA, to evaluate anONERA human factors codingscheme and taxonomy forpossible application to ASRSincident data.

␣ ␣ •␣ ␣ Completed a conceptual andeditorial review for a secondNASA project, a study on theuse of modes in human-machineinteractions. This study, whichwas completed, made use ofASRS data.

Point of Contact: L. Connell(650) [email protected]

Crew Activity TrackingSystemTodd J. Callantine

Human operators supervisingadvanced automation systems canhave difficulties that have thepotential to compromise safety. Forexample, a recent study found thatover 44% of flight deck problemscited in a large body of incident andaccident reports were related toautomation. Autoflight systemmodes, in particular, are oftenimplicated because they can cause

unexpected behavior. One remedyis to develop technology that candetect potential operator errors andprovide the operator with context-sensitive advice and reminders. Tobe effective, such technology mustincorporate knowledge aboutoperator-automation interaction incontext; for flight deck application,this includes knowledge about modemanagement.

This research addresses anenabling technology called activitytracking, a way of inferring intent. Asthe name implies, the Crew ActivityTracking System (CATS) is anarchitecture that implements amethod for activity tracking (see thefirst figure). CATS represents knowl-edge about the operator’s tasks usingan explicit, task-analytic modelbased on the goal-based decomposi-tion of tasks into subgoals andprimitive tasks. CATS uses the modelto predict operator intentions and tointerpret subsequent operatoractions. The predictions and inter-pretations are designed to supply theknowledge required for intelligentaiding and training systems.

Constraints onoperation

Controlledsystem

Crew activity model

Humanoperators Crew

actions

Constraintson operation

Stateinformation

Contextspecifiers

Interpretations

[to aid or training system]

Predictions

Actionmanager

CATS

OFM-ACM

Fig. 1. The Crew Activity Tracking System in context.


6

CATS was implemented to trackthe activities of Boeing 757 pilotsusing autopilot flight modes undernormal operating conditions. Anexperimental evaluation was con-ducted to assess the effectiveness ofthe CATS method. Ten type-ratedline pilots from a major airlineparticipated in the study. Each flewfive experimental scenarios on areal-time part-task simulation of theBoeing 757. Of the 2,089 pilotactions detected in the study, CATScorrectly interpreted 81%. A subse-quent analysis identified adjustmentsto the CATS model and processingscheme that would allow CATS tocorrectly interpret 94% of pilotactions.

Current research seeks to extendthe capabilities of CATS and toexplore new applications. Specifi-cally, the objective is to enableCATS to predict and interpret theactions of two-person crews by usingcomplex functions of the FlightManagement Computer Control andDisplay Unit (FMC CDU), and data-link communications. These activi-ties are critical for procedures that

are being developed for use withnew air-traffic control automation.

The second figure shows asimplified task decomposition fromthe enhanced CATS model, fromwhich most cognitive, verbal, andperceptual activities are omitted. Thetask shown supports a new descentprocedure that uses an assigneddescent point (“adp”), in addition tothe top-of-descent point computedby the FMC. When the crew hasbeen cleared for the procedure,CATS uses this portion of the modelto predict and interpret the CDUprogramming activities required toperform the task. For example, CATSfirst predicts which pilot is respon-sible for programming the assigneddescent point to go to the CDULEGS page. CATS next predicts thata reference way point will be built inthe CDU scratchpad, then line-selected to the appropriate place onthe LEGS page, and so on. As theseactions are performed, CATS checksthe entered values for accuracy andthen either interprets the actions tosupport the task of entering the

assigned descent point or signals apotential error.

A Boeing 747-400 simulatorstudy to investigate pilot perfor-mance on a new descent procedurewas conducted at Ames ResearchCenter. The data show that althoughpilots performed the new procedureeffectively in most cases, there werestill a number of compliance viola-tions. These data are used to investi-gate a new application of CATS:tracking crew activities to automati-cally identify departures from theprocedure and capture the contextin which these departures occurred.With this information, the proceduremay be refined to address problems,and thereby improve compliance.

Point of Contact: T. Callantine(650) [email protected]

Study of Line OrientedFlight TrainingKey R. Dismukes

Airlines train pilots to worktogether as safe, efficient crews byusing a realistic full-mission flightsimulation approach called LineOriented Flight Training (LOFT). Inthis annual recurrent training, crewsencounter challenging situations thatthey must manage by coordinatingtheir efforts, exercising good judg-ment and decision-making, anddrawing upon all availableresources. After the LOFT, theinstructor leads the crew in adebriefing in which they areexpected to analyze what happened,evaluate their own performance,

Fig. 2. A simplified task decomposition from the enhanced CATS model.

enter-ctas-adp-ref-dist

build-ctas-adp-ref-dist

enter-ctas-adp-ref-wpt

build-ctas-adp-ref-wpt

access-LEGS-pg

verify-ctas-adp

execute-ctas-adp

program-ctas-adp

put-ref-dist-LEGS-pg

put-ref-dist-scr-pad

put-ref-wpt-LEGS-pg

put-ref-wpt-scr-pad

push-LEGS-key

SOP-talk

push-EXEC-key



7

and identify ways to improveperformance. Because the LOFT is avery busy, intense experience, howmuch the crews learn from the LOFTand take back to line operationshinges on the effectiveness of thedebriefing.

Both the airlines and the FAAespouse the idea that LOFT instruc-tors should refrain from lecturing thecrews in the traditional “teacher-tell”manner. Instead, instructors areencouraged to “facilitate” self-analysis by the crew so that they willlearn more deeply. However, therehas been little study of how tofacilitate this self-analysis; as aconsequence, the airlines have nothad good data-based techniques fortraining their instructors in debriefingprocedures.

Human factors scientists atAmes recently completed a study,in collaboration with major U.S.airlines, to evaluate LOFT debrief-ings and to provide guidelines fortraining instructors. The studyevaluated the effectiveness of LOFTdebriefings at a cross section ofairlines, analyzed facilitationtechniques, and identified commonerrors. The study demonstrated thatinstructors who are effective infacilitating self-analysis substantiallyincrease the depth of crew participa-tion and self-analysis; however,individual instructors differed greatlyin their effectiveness as facilitators.

In conjunction with the techni-cal report of the study, the researchteam prepared a detailed manual foruse in training instructors to facilitatedebriefings. This manual explainsthe concepts of facilitation, describeseffective techniques, explains how

and when to use these techniques,and shows how to engage crews thatdo not initially respond. Immediatelyafter receiving the study materials,several major airlines reprinted themanual for the use of their instruc-tors. Other airlines have overhauledtheir training of instructors toincorporate the findings from thestudy; they later reported significantbenefits to their crew trainingprograms.

Point of Contact: K. Dismukes(650) [email protected]

Measuring Air TrafficComplexityIrene V. Laudeman, Connie Brasil,Robert Branstrom

An important goal in advancedair-traffic operations is that ofproviding more system flexibility tothe user. The idea of sharing theresponsibility for aircraft separation,in which pilots and air-trafficcontrollers work together to ensureseparation, is designed to providesuch flexibility. Currently, underinstrument flight rules the air-trafficcontroller is tasked with ensuring theproper separation of aircraft. Undershared separation-responsibilityprocedures, pilots in appropriatelyequipped aircraft would assumesome responsibility for the manage-ment of aircraft separation. Theproportion of responsibility assignedto pilots and air-traffic controllers

would be a function of the complex-ity of the airspace.

Shifts in operational procedureswill be specified as a function ofairspace complexity, making thedevelopment of separation proce-dures dependent on the develop-ment of a complexity metric. Thecomplexity of air-traffic patterns, andhence the workload related to themanagement of air traffic, is knownto include more than a simple countof aircraft contained in a volume ofairspace. However, the trafficcomplexity factors beyond that ofaircraft number have not beenclearly identified, nor has anyrelationship among the factors beenestablished.

A human-in-the-loop simulationstudy was conducted to evaluatethree modes of separation responsi-bility and to provide data for use indeveloping a complexity metric. Tengroups of four currently qualified air-traffic controllers participated in ninesimulation scenarios. In each groupone participant acted as the control-ler in a sector of airspace and threeparticipants acted as pilots.

Aircraft data in the form oflatitude, longitude, heading, altitude,and speed were collected for all ofthe aircraft in each of the nine30-minute scenarios. The complexityof the simulated airspace wascomputed from the aircraft data atevery 2 minutes of the 30-minutescenarios. Complexity functionswere computed as a sum of trafficfactors that included aircraft count,aircraft converging at the samealtitude, and aircraft changingheading, speed, or altitude.


8

The complexity functionspredicted an operational shift relatedto the sharing of separation responsi-bility (see the figure) indicating thatsuch functions might be useful inspecifying shared separation respon-sibility procedures.

Point of Contact: I. Laudeman(650) [email protected]

Operational Interventionsto Human Error in AircraftMaintenanceBarbara G. Kanki, Vicki Dulchinos

A significant proportion ofaviation accidents and incidents areknown to be tied to human error.However, research of flight opera-tional errors has shown thatso-called “pilot error” often involvesa variety of human factors issuesand not a simple lack of individualtechnical skills. In aircraft mainte-nance operations, there is similarconcern that maintenance errorswhich may lead to incidents andaccidents are related to a largevariety of human factors problems.

Although industry initiatives involv-ing human factors training inmaintenance have become increas-ingly accepted as one type ofmaintenance error intervention,there remains a dual challenge:(1)␣ to develop human factors inter-ventions that are directly supportedby reliable human error data, and(2)␣ to integrate human factorsconcepts into the procedures andpractices of everyday technical tasks.

These challenges are beingaddressed at Ames Research Center.First, industry-wide incidentsreported to the Aviation SafetyReporting System are being analyzedin order to identify and characterizehigh priority problem areas. Whenanalyzed for contributing factors, atleast 50% of the incidents involvedmore than one technician—othermaintenance personnel, flight crewmembers, and airport personnel.

Consistent with these findings,research is being conducted thatfocuses on human factors interven-tions related to practices andprocedures; namely, structuredon-the-job training and procedurere-design. In both areas, particularattention is being centered on areasin which maintenance tasks requirecoordination both within andbetween maintenance teams.

In the area of structured on-the-job training, field applications ofthe Task Analytic Training System—a performance-based system thatinvolves full workforce participationin its design, development, andimplementation—have beenconducted.

8 10 12 14

Scenario 1 shared (3)Scenario 1 shift

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Fig. 1. Air-traffic complexity functions and points at which separationresponsibility was shifted for two types of traffic scenarios.



9

Human factors principles mayalso be incorporated into themaintenance procedures themselves.When Boeing modified its B-737CFM56-7 engine-change procedure,the efficiency of the engine-changeprocess was significantly improved.A 14% increase in efficiency,attributed to changes in the mainte-nance manual alone, presented anopportunity to conduct a systematiccomparison between original andrevised procedures. The goal was toanalyze the specific modificationsthat led to the improvement inefficiency and to identify the contri-bution of human factors. Some

results of this item-by-item compari-son are found in the summary offunctional changes shown in thefigure.

Finally, a collaborative relation-ship has been established with thehuman factors team at KennedySpace Center; a series of workshopsfor discussing human factors issuesin aviation and space vehiclemaintenance is being conducted.The first workshop was held at AmesResearch Center in September 1966;it focused on error analysis (inci-dents, accidents, mishaps, and close-calls). This workshop facilitated the

free exchange of human factorsinformation between aircraft andshuttle maintenance operations.

Point of Contact: B. Kanki(650) [email protected]

Aircraft SeparationRisk ModelMary M. Connors

Increased demand for air traveltranslates into a need to accommo-date more aircraft in the terminalairspace. Separations betweenaircraft pairs must be small enoughto be efficient while remainingsufficiently large to be safe. Presentseparation standards are consideredsafe for the equipment and condi-tions that presently prevail. It ispossible that new technologies couldresult in maintaining the presentsafety level while permitting thedistances between aircraft pairs tobe reduced. What is needed is aquantitative method of evaluatingsafety. The objective of this researchis to develop a computer model thatwill provide this link betweenaircraft separation and a quantitativemethod of assessing safety risk.

The model, called the ReducedAircraft Separation Risk AssessmentModel (RASRAM), evaluates safetyrisks for a variety of flight scenariosrelating to final approach, landing,and rollout for parallel and singlerunways. The basic approach ofRASRAM is to quantify the riskassociated with current separationstandards and to then compare itwith that for reduced separation

Fig. 1. Distribution of reason codes in the revised procedure(N = 735 procedural steps).

A. 5%

B. 8%

C. 12%

D. 4%

E. 19%

F. 33%

X. 19%

A. Situation awareness/Time task management (n=38)

B. Planning/Communication-new resources (n=62)

C. Planning/Communication of task sequence (n=85)

D. Clarification/Formatting - Simplified English (n=28)

E. Clarification/Formatting consistency (n=139)

F. Process improvement (n=243)

X. No functional change (n=140)


10

operations during instrumentmeteorological conditions, consider-ing procedural and technologicalchanges. The research is beingperformed for Ames Research Centeras an integral part of NASA’s Termi-nal Area Productivity (TAP) program,and in coordination with the FederalAviation Administration.

RASRAM includes the followingtwo scenarios that measure the effectof separation on safety: lateralseparation for parallel approaches;and in-trail separation during singlerunway operations, accounting forrunway occupancy and wake vortexeffects. The figure illustrates theparallel approach scenario, forwhich independent approaches toparallel runways constitute theoperational context. The primaryseparation criterion is the distancebetween the runway centerlines forthe two approach paths. The defin-ing characteristic of the scenario inthe model is a blundering aircraftthat strays from its own finalapproach, crossing the path of theother approach stream. The safety ofthe scenario (for current operations)

is determined (1) by the performanceof the controller in detecting theblunder and issuing breakoutinstructions to the evader aircraft,and (2) by the performance of thepilot and aircraft in completing theevasive maneuver. RASRAM modelsall of these effects and quantifies thesafety of the operation. The standardrisk measure is the probability thatthe blundering aircraft will approachwithin 500 feet of an aircraft in theother approach stream.

NASA’s TAP Program anticipatesprocedural changes for terminal-areaoperations along with the introduc-tion of new technologies. These newtechnologies include DifferentialGPS (DGPS), Automatic DependentSurveillance (ADS-B), and severaltechnologies under development bythe NASA TAP program: the Center-TRACON Automation System(CTAS), the Aircraft Vortex SpacingSystem (AVOSS), the DynamicRunway Occupancy Measurement(DROM), and the Airborne Informa-tion for Lateral Spacing (AILS).RASRAM begins the process of

quantifying the safety risk associatedwith the effects of these technologieson separation standards. The modelcan also be used to provide arelative comparison of the safety ofproposed new procedures with thesafety of current operations andtechnologies. Using RASRAM, thesafety of further separation reduc-tions for parallel approaches thatrely on new technologies can beanalyzed and compared with currentprocedures. Similarly, the safety ofreductions of in-trail separation canbe compared with current proce-dures. Although it is being devel-oped for initial application to finalapproach and landing, the basicapproach to modeling separationrisk has direct application to allphases of flight. The potentialapplication of these models to enroute and approach airspace is beingundertaken in the Advanced AirTransportation Technology programat Ames.

Point of Contact: M. Connors(650) [email protected]

Runwayseparation

Blunder path

MD = miss distance

Evader aircraft

No transgression zone

3° Glide path

Blunder aircraft MD

Fig. 1. Parallel approach lateral separation geometry.



11

The Final ApproachSpacing ToolTom Davis

The Center/TRACON Automa-tion System (CTAS) is an air-trafficcontrol automation system underdevelopment at Ames ResearchCenter. The system is designed tosupport increasing demands forcapacity and efficiency in theNational Airspace System. Theterminal-area component of thesystem, the Final Approach SpacingTool (FAST), is designed to assistterminal air-traffic controllers inefficiently managing and controllingarrival air traffic for the last 40 milesof flight down to the runway. TheFAST system issues the controllersa series of sequencing, runway,heading, and speed advisories toachieve an efficient flow of trafficthat increases airport capacity,reduces delays, and reduces control-ler workloads.

The objective of the researchand development effort is to test theFAST system operationally in a seriesof phased functionality enhance-ments at the Dallas/Fort WorthTRACON (Terminal Radar ApproachControl) (see figure (see ColorPlate␣ 1 in the Appendix)). Theoperational field testing of the FASTsystem allows researchers to furtherdevelop and assess the system withthe end-users, that is, with the air-traffic controllers. The assessmentsinclude a series of observations withthe FAST system operating in ashadow mode on live traffic data,real-time simulation evaluations of

the FAST system at Ames and at theFAA Technical Center, and a limitedoperational assessment of theFAST system functionalities atDallas/Fort Worth.

Development and field testing ofthe FAST system achieved a signifi-cant milestone during FY96; the“Passive” FAST functionality, whichincludes the sequence and runwayadvisories, underwent operationaltesting at the Dallas/Fort WorthTRACON. The tests, which wereconducted in cooperation with theFAA, the National Air Traffic Con-trollers Association, and the AirlineTransport Association, began inJanuary 1996 and continued throughJuly 1996. The objectives of the testwere: (1) to confirm the technicalperformance of the Passive FASTfunctionalities, (2) to assess theairport delay and capacity benefitsof Passive FAST, and (3) to assessthe controller workload benefits ofPassive FAST. The testing demon-strated an arrival rate improvementat Dallas/Fort Worth of 13%, adeparture queue backlog reductionof 9%, and an overall increase intotal airport operations (arrivals anddepartures) of 13%, all with noincrease in taxi times and withlittle or no increase in controllerworkload. The system has receivedoverwhelmingly positive supportfrom all participants.

The Active FAST systemfunctionalities, including speed andheading advisories, remain to bedeveloped and operationally evalu-ated. The Active FAST system willundergo operational testing similar

to that of the Passive FAST before anational deployment system isspecified.

Point of Contact: T. Davis(650) [email protected]

Air/Ground IntegrationR. Slattery

The Center/TRACON Automa-tion System (CTAS) was developedfor use in the air traffic-controlenvironment. As part of the TerminalArea Productivity Air Traffic Man-agement program, research hasbegun to expand CTAS to coordinatewith aircraft that are equipped withFlight Management Systems (FMSs)using data-link. A large portion ofthe commercial aircraft fleet is soequipped and many older aircraftare being retrofitted with an FMS.However, busy air-traffic controllersdo not often allow pilots to fullyutilize the FMS. An FMS calculatesthe most efficient trajectory, thussaving fuel, and then follows thetrajectory very accurately, increasingtrajectory prediction accuracy. Thus,if the CTAS helps the controllers takeadvantage of the FMS trajectory, theperformance of the airspace systemshould be improved.

The objectives of the researchand development effort are toquantify the actual benefits of theair/ground system with both control-lers and pilots in the loop. Theoreti-cal benefits have been studied,under the assumption that thetrajectories are followed with the


12

maximum accuracy possible for theFMS. These benefits may be dimin-ished, however, by the extraworkload imposed on the controllersand pilots; also, they may not berealizable because of operator error.

A piloted simulation wasperformed using the CVSRF 747-400simulator. Since the simulator wasnot equipped with data-link at thetime, the routes were defined asstored arrivals in the FMS (anexample is shown in the figure).The pilots were issued FMS routechanges, while still performing therest of their normal duties. For abaseline comparison, equivalentroutes were flown using currentcontroller clearances. The aircraftwas flown in the Dallas/Fort Worthterminal area, starting at the two

eastern arrival gates into theTRACON (Terminal Radar ApproachControl) and finishing at the runway.The accuracy of the horizontal routeincreased for the FMS cases, but thevertical predictability was lower.This was because the vertical portionof the FMS route is entered ascrossing altitudes at way points. Aslong as the pilots meet the requiredaltitude, the point at which theybegin their descent and the way inwhich they make the descent areopen. Offsetting the achievableaccuracy, the pilots felt that the FMSroute changes produced far moreworkload with current generationFMS systems than did currentprocedures. They also expressedconcerns about the amount ofheads-down time spent loading the

trajectory while in the busy terminalarea. There were also more errors inloading and in following the FMSroute, though these should bereduced by data-link and by inter-face changes to the FMS.

Point of Contact: R. Slattery(650) [email protected]

The Traffic ManagementAdvisorHarry N. Swenson

The growth of commercial airtravel within the United States hasput a severe strain on the nation’s airtraffic capacity. This, coupled withthe “hub-and-spoke” proceduresused by the major air carriers andthe marketing requirements foraircraft to take off and land atoptimum times, has required animprovement in the Air TrafficControl System. The Center-TRACON Automation System (CTAS)is a decision-support concept beingdeveloped to improve airportcapacity and to reduce delays whilemaintaining controller workload ata reasonable level. The extendedterminal-area component of thesystem is the Traffic ManagementAdvisor (TMA). The TMA is a time-based strategic planning tool thatprovides traffic management coordi-nators and en␣ route air trafficcontrollers the ability to efficientlyoptimize the capacity of a demand-impacted airport. The TMA consistsof trajectory prediction, constraint-based runway scheduling, traffic

KINGGREFLE2: Cross at 210K

IAS. Cross at 4,000'

17LGT

JIFFYCross at 170K IAS

REFLE1

REFLE2 NOVEL

SWIFTREFLE1: Cross at 210K

IAS. Cross at 4,000'

SEAGOCross at 250K IAS.

Cross at 11,000'

SCY

REFILCross at 210K IAS.

Cross at 11,000'

Fig. 1. Scurry FMS arrivals, REFLE1 and REFLE2.



13

flow visualization, and controllerarrival sequence, time, and delayadvisories.

The TMA and all other CTAStools are being developed to demon-strate user benefits both to air-trafficcontrollers and commercial aircarriers. Air-traffic control is a verycomplex multivariable problemrequiring teams of highly skilledindividuals to safely and efficientlymove traffic from terminal departurepoint to terminal arrival. Thisextended complexity requires thatautomation aids designed to assistthese teams be proven and validatedin actual operations. The objectiveof the TMA 1996 research anddevelopment effort was focusedtoward an operational evaluationat the Ft. Worth Air Route TrafficControl Center, Ft. Worth, Texas.The evaluations also focus researchinto areas and concepts that provideuser benefits.

The TMA achieved severalmajor milestones in this focusedeffort toward operational evalua-tions. The first was controller andoperational hardware in-the-loopsimulations at the William J. HughesFAA Technical Center with theNational Air Traffic ControllersAssociation (NATCA) Ft. WorthCenter System Design Team. Thiswas followed by the installation andcheckout of the TMA hardware/software components at theFt. Worth Center, the nation’s fifthbusiest Center, which manages andcontrols traffic into the secondbusiest airport in the world (Dallas/Ft. Worth). Upon completion of thesystem installations, on-site shadowevaluations and nighttime simula-

tions were conducted. Subsequently,the formal operational evaluationswere conducted. The TMAdemonstrated delay reductions of1–2 minutes per aircraft, as well asa significant reduction in controllerworkload. The original plan was toremove the TMA upon completionof the formal evaluation, but, basedon the benefits achieved, the FAA,the Air Transport Association, andNATCA requested that NASAoperationally support the TMA on acontinuous basis. NASA has com-plied with that request, and the TMAhas been used operationally sincethe completion of the formal evalua-tions. Since the evaluations, a 10%capacity increase has been attributedto TMA operations.

Point of Contact: H. Swenson(650) [email protected]

Surface MovementAdvisorBrian J. Glass

Recurrent delays during depar-ture taxiing at large airports havebecome commonplace with theprevalence of “hub-and-spoke”airline operations, as large numbersof aircraft attempt to land, taxi, beserviced, taxi, and depart, all within60–90 minute “banks.” Airfieldtower controllers strive to avoidimbalances and bottlenecks byintegrating data from visual cuesand from a variety of other sources.However, lengthy, imbalanced taxi

queues are evidence that althoughsufficient and safe, the controller’smental planning process (givencurrent data sources) is not necessar-ily optimal. By providing data fusionand automated optimal taxi planadvisories to the ground controller,the controller can operate withimproved data-gathering andplanning capabilities. Improveddynamic taxi routing, and hencesmoother airport operations withless surface taxi delay should result.Eventual national implementationof the Surface Movement Advisorsystems (SMA) at the 13 largest U.S.airports is projected to save users atleast 5% of the $1.6 billion annualground-delay costs incurred as aresult of inefficient taxi and runwayqueuing—based on recent FAAsimulations and Air TransportAssociation cost figures.

The SMA is a series of succes-sive airfield data systems that isbeing developed as a joint effortbetween Ames Research Center andthe Federal Aviation Administration(FAA). The first proof-of-conceptSMA (Build-1) electronically con-nects the air-traffic control, airline,and airport operations users atAtlanta-Hartsfield airport (ATL) tofacilitate information-sharing anddata fusion. SMA Build-1 has beenin use on a daily basis at ATL byairlines and airport ramp towerssince June 1996 and was broughtonline in the FAA control towerin September 1996. The figureshows an overview of the SMAsystem that was deployed to Atlantain 1996.


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Running in a commercialtransaction-processing database onan off-the-shelf UNIX server, theSMA software currently contains itsown tracking, time estimation, datafusion, monitoring and predictionsoftware modules. SMA furnishesdata as an ASCII text stream toairline servers, or as separateX/Motif-based touchscreen-capablegraphical-user interfaces for the FAA,airline, and airport operationspersonnel.

Point of Contact: B. Glass(650) [email protected]

Simplified Vision Modelsfor Display QualityAssessmentAl Ahumada

Detection and recognition ofobstacles (aircraft, trucks, etc.) iscrucial for safe aviation operation inthe terminal area. Vision models canmake an important contribution todisplay design by allowing computa-tional predictions of the visualadequacy of potential designs forobstacle detection and recognition.The first figure shows a pair ofsimulated display images, one(panel b) with an obstacle on therunway and one without. Investiga-tors have been measuring the ability

of human observers to make suchdiscriminations and have beenconstructing and testing computa-tional models to predict theirabilities.

Image discrimination modelsthat have been used as image-qualitymetrics range in complexity fromsingle filter models to multiple-channel models with channels thatare selective in spatial frequency andorientation. The simple filter modelscan be thought of as representing thevisual information at precorticallevels of the visual system. Thesemodels can predict the variations inthe visibility of targets that occur asthe target spatial frequency changes.The multiple-channel models

Fig. 1. Overview of the SMA system deployed to Atlanta in 1996.

LockheedValuJet

Other airlines

DeltaAirlines

City of Atlantaairport authority

Performancehistograms

Predictionalgorithms

Airport operationsprocedures

Statisticalanalysis

Outputmanager

SMA server

Inputmanager

Monitoring andpredictions

Highspeednetwork backbone

Flight plans

FAAtower Real-time

radar data

Weatherdata

Real-time aircraftstatus updates

Airlineschedules



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simulate the orientation and spatialfrequency selectivity of cortical cells.Because the channel outputs arenonlinear, the channel modelspredict masking of targets in high-contrast image regions. For example,the channel models outperformcontrast-sensitivity filter models inpredicting the detectability of targetsin a natural background.

Some recent vision modelsinclude between-channel interac-tions that allow the models topredict masking from image compo-nents exciting different channelsfrom those responding to the target.These models have even greatercomputational complexity. Assum-ing homogeneity of these interac-tions leads to a simple contrastmasking correction. The secondfigure diagrams the image discrimi-nation model that results from

applying this correction to acontrast-sensitivity filter model. Incomparing the predictions of thismodel with those of the complexmodels, it is found that the simplemodel predicts human visualdetection performance just as well.

Point of Contact: A. Ahumada(650) [email protected]

Perceptually Tuned VisualSimulationMary K. Kaiser

Human factors engineering isrequired to improve the quality ofvisual displays in aerospace systems.Advanced computer-generatedimagery (CGI) systems are used tocreate compelling visual displays fornavigation/control systems, vehicle/system simulation, telerobotics, andscientific visualization applications.The quality of these displays canaffect the safety and productivity offlight and ground-based operations.Inevitably, the realism of thesedisplays is constrained by limitationsin CGI hardware and software,especially if images need to begenerated in real-time. Despiterapid advances in image-generationtechnology, human operators desiremore realistic, higher-fidelitydisplays; it is likely that this demandfor improved fidelity will continuefor the foreseeable future.

Research is being conductedto examine techniques aimed atreducing the computational costrequired to achieve a desired level ofimage quality and frame rate. These

CSF

Background

Target +Background

RMS

C=1

1n

nfi

2Σ

Masking

1+( )2cc

CSF

Euclideandistance

1

ndi

2Σ

XX

d'

(a)

(b)

Fig. 1. Panel (a) is a 128 x 128 pixelgray-scale digital image of asimulated airport runway scene.Panel (b) shows the runway scenewith an aircraft obstacle.

Fig. 2. Schematic of the simple image discrimination model. At the left, theupper image is the background image and the lower image is the target-plus-background image. After the luminance images are converted to contrastimages (a step not illustrated), the contrast images are filtered by a contrastsensitivity function (CSF). On the top path, the masking parameter c is therms value of the background-filtered contrast values fi. On the bottom path,the corresponding filtered values from the image are differenced and thevector length of these di values is divided by the contrast factor to get thepredicted number of just-noticeable-differences between the two images.


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techniques exploit principles ofvisual processing to reduce thecomputational load. This multi-disciplinary research involves acollaboration among researchscientists at the Ames ResearchCenter; professors in computerscience at Carnegie Mellon Univer-sity and in psychology/biomedicalengineering at the University ofVirginia; and designers and engi-neers at various industry sites.

A set of techniques has beendeveloped for rendering images withenhanced apparent resolution.NASA has applied for a patent forthis process (NASA Case: ARC12080-1). In using this process tocreate stereo displays, images withdifferent resolutions are shown to thetwo eyes; examples of this techniqueare shown in the figures below. Thefirst figure demonstrates varyingtexture complexity; the second

demonstrates varying polygonalcomplexity. The resulting fusedimage appears to possess the higher-resolution detail. User studiesconducted with these “hi-lo” stereodisplays indicate that people areable to extract stereo-specified depthwith these displays about as well asthey do with traditional (“hi-hi”)displays. Further, no interferencewith normal stereo vision resultsfrom exposure to the hi-lo displays.

Present efforts focus on furtherevaluation of the algorithms, theextension of techniques to largerobject classes, and the developmentof generalizable tools suitable forinclusion in a graphics modelingtoolbox. Coordination with hard-ware and software developers seeksto maximize the utility of thesetechniques and to ensure compat-ibility with hardware architecture.

The development of a number ofrendering techniques that signifi-cantly enhance the performance ofgraphics systems is expected. Thegoal is to both extend the upperrange of graphical rendering perfor-mance and to enable lower-endsystems to produce visual imagerythat currently can be produced onlywith high-end systems.

Point of Contact: M. Kaiser(650) [email protected]

Fig. 1. Only the image presented to the left eye in this stereo pair has texturemapping. Nonetheless, the resulting stereo percept appears textured.

Fig. 2. Another example of “hi-lo” stereo images. Here the left image iscreated with far more detail (that is, a larger number

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