Flight Simulation

Year in Review

FY 01

Foreword

Aviation Systems Division

NASA Ames Research Center

Moffett Field, California 94035

30 November 2001

This document is the Fiscal Year 

2001 Annual Performance Summary of 

the NASA Ames Vertical Motion Simulation (VMS) Complex, the Crew Vehicle 

Systems Research Facility (CVSRF), 

and FutureFlight Central (FFC). It is 

intended to report the more significant 

events of FY 01. What follows are 

an Executive Summary with comments 

on future plans, the FY 01 Simulation 

Schedule, a projection of simulations to 

be performed in FY 02, performance 

summaries that report on the simulation 

investigations conducted during the 

year, and a summary of Research and 

Technology Upgrade Projects.
4 Aviation Systems Division

Acknowledgments

About the Cover

Front cover: This year’s cover depicts simulations that occurred at each of the SimLabs facilities. The ship 

pictured at top was used during the Joint Shipboard Helicopter Integration Process experiments (see pp. 

17 and 22) undertaken at the Vertical Motion Simulator. The ribbons represent airflow over the ship’s deck. 

The second image depicts the set-up of the Crew Vehicle Systems Research Facility’s Neural Flight Control 

simulation. This experiment is described in detail on p. 29. The last picture was taken from FutureFlight 

Central’s simulations of Los Angeles International Airport. Two experiments were conducted; details can be 

found on pp. 35 and 36.

Back cover: The three facilities that constitute SimLabs are capable of fully integrated simulations for a 

broad spectrum of aerospace research. All three labs have conducted studies relating to different aspects of 

commercial transport vehicles, similar to the one depicted here.

Special thanks to Tom Alderete, Dave Astill, Deborah Ballinger, Jim Blount, Dave Carothers, Girish Chachad, 

Paul Chaplin, William Chung, Bill Cleveland, Steve Cowart, Nancy Dorighi, Dean Giovannetti, Scott Malsom, 

Joe Mastroieni, Julie Mikula, Terry Rager, Kathleen Starmer, Barry Sullivan, and Nancy Tucker for contributions made to the production of this report.
Table of Contents

Foreword .............................................................................................................................. 3

Executive Summary ............................................................................................................ 7

FY 01 Simulation Schedule ................................................................................................... 9

FY 01 Project Summaries.................................................................................................... 10

FY 02 VMS Simulation Projects .......................................................................................... 12

FY 02 CVSRF Simulation Projects ...................................................................................... 13

FY 02 FFC Simulation Projects ........................................................................................... 14

VMS Project Summaries ................................................................................................... 15

Civil Tiltrotor-9 (CTR-9) .................................................................................................. 16

Joint Shipboard Helicopter Integration Process (JSHIP) ............................................... 17

Visual Scene Height Perception (PsychoPath) II........................................................... 18

Space Shuttle Vehicle 2001-1........................................................................................ 19

Civil Army Design Specification ..................................................................................... 20

AutoCue II ...................................................................................................................... 21

Joint Shipboard Helicopter Integration Process (JSHIP) II ............................................ 22

Civil Tiltrotor-10 (CTR-10) .............................................................................................. 23

Space Shuttle Vehicle 2001-2........................................................................................ 24

CVSRF Project Summaries............................................................................................... 25

Integrated Neural Flight and Propulsion Control System (INFPCS) I ............................ 26

Air Traffic Control Simulation Fidelity ............................................................................. 27

Boeing Noise I................................................................................................................ 28

Boeing 747 Neural Flight Control System...................................................................... 29

Airborne Information for Lateral Separation (AILS)........................................................ 30

Boeing Noise II............................................................................................................... 31

Distributed Air-Ground Demonstration ........................................................................... 32

FFC Project Summaries.................................................................................................... 33

AGI Ramp Controller Training........................................................................................ 34

LAX Phase I ................................................................................................................... 35

LAX Phase II .................................................................................................................. 36

Surface Management System: First Simulation............................................................. 37

Research & Technology Projects..................................................................................... 39

Rapid Integration Test Environment III........................................................................... 40

Virtual Laboratory (VLAB) .............................................................................................. 41

VMS Modernization........................................................................................................ 42

Air Traffic Control for the VMS ....................................................................................... 43

Kaiser HMD and Head Tracker...................................................................................... 44

Navigation Database: Automation.................................................................................. 45

High Level Architecture to FFC ...................................................................................... 46

Integrated Vehicle Modeling Environment Development ............................................... 47

Acronyms........................................................................................................................... 49

Appendix: Simulation Facilities ....................................................................................... 52

7 Aviation Systems Division

Executive Summary

Introduction

The staff of the National Aeronautics and Space Administration (NASA) Ames Simulation Laboratories is pleased to present the Annual Report for Fiscal Year 2001 (FY 01). 

This report documents the simulation experiments and technology projects accomplished 

in three major facilities: the Crew Vehicle Systems Research Facility (CVSRF), FutureFlight Central (FFC), and the Vertical Motion Simulator (VMS). Once again, the year 

was characterized by a highly diverse set of experiments covering a broad spectrum 

of aerospace technologies exemplified by studies to improve airport safety for cities, 

developments to improve air transportation capacity for the nation, and research and 

engineering to increase aircraft/ship interface operational safety for the military.

The Simulation Laboratories (SimLabs) are operated and managed by the Aviation 

Systems Division at NASA’s Ames Research Center. The FutureFlight Central facility was 

added to the Division’s responsibilities at the start of the fourth quarter and is being 

integrated into the overall simulation capability of the Center. With this suite of facilities, 

Ames has the unique capability to simulate all elements of aerospace vehicle and 

transportation systems to very high fidelity, including airport ground operations, air traffic 

management, crew station issues, crew/vehicle interfaces, vehicle design, dynamics, and 

handling qualities. Throughout the year, the SimLabs staff has operated all of the facilities 

with the highest levels of safety, consistently excellent quality, and complete customer 

satisfaction. The most challenging efforts have involved the planning and implementation 

of both a new business environment and new research initiatives. We will continue 

to work diligently with our new and our long-time customers and research partners to 

improve SimLabs’ operation and efficiency and to meet the challenges of future research 

and economic trends.

Some Highlights from Fiscal Year 2001

• The Crew Vehicle Systems Research Facility features the highest fidelity, fullmission, motion-based flight simulation capabilities. There are two simulator cockpit 

systems in the CVSRF: a B747-400 (B747) Level-D certified simulator and the Advanced 

Concepts Flight Simulator (ACFS). Additionally, a full-featured Air Traffic Control simulation facility is integrated with each of these simulators. One example of the many 

significant simulation experiments conducted in the CVSRF is the Integrated Neural Flight 

and Propulsion Control System (INFPCS) project. This study examined the ability of the 

INFPCS to automatically compensate for an aircraft’s damaged or failed flight control 

system. The results were very encouraging and demonstrated that the INFPCS was able 

to stabilize the aircraft without significant pilot compensation.

• FutureFlight Central is an Air Traffic Control/Air Traffic Management test facility 

featuring a 360-degree, full-scale visual simulation of an airport environment as viewed 

from within the control tower. The control tower interior space accommodates a full 

compliment of air traffic controllers and airport operations personnel. This past year, FFC 

was used by NASA, the Federal Aviation Administration (FAA), United Airlines, and the 

Los Angeles World Airports to study the FAA’s top priority problem: runway incursion. In 

the first phase of this project, FFC was configured to simulate Los Angeles International 

Airport (LAX) to evaluate the degree of realism possible in a simulation environment. 

Results were very positive, with actual LAX controllers rating the simulation “about the 

same as LAX” in several objective and subjective criteria. The second phase of the 

project identified two promising solutions to reduce the potential of runway incursions 

at LAX.

• The Vertical Motion Simulator is a complex of simulation capabilities, including five 

reconfigurable cockpits, two large multi-channel visual systems, and the world’s largestamplitude motion cueing system. A very successful program completed this year was 
8 Aviation Systems Division

the Joint Shipboard Helicopter Integration Process (JSHIP), directed by the Office of 

the Secretary of Defense. The objectives of JSHIP were to evaluate the concepts and 

address the issues that occur in joint military operations involving Army helicopter units 

onboard Navy ships. Additionally, the VMS was employed to evaluate the effectiveness of 

using simulation as an alternative to costly at-sea studies of the helicopter/ship dynamic 

interface. Varying levels of visual and motion cueing fidelity were investigated, and 

preliminary results indicate that simulation could be a plausible compliment to at-sea 

testing.

• Some of our accomplishments serve to provide a seamless operation among different 

facilities. The Virtual Laboratory (VLAB), the Rapid Integration Test Environment (RITE), 

and the interconnection of the CVSRF and FFC via a High Level Architecture interface 

are examples of progress toward an integrated, interoperable set of simulation assets and 

capabilities. These integrated tool sets provide collaborative redesign capability, access to 

design data from various sources, and participation in flight simulation evaluations from 

remote locations. A major accomplishment for RITE this year was to rapidly evaluate 

vehicle redesigns in a four-day turnaround demonstration.

Looking Ahead to Fiscal Year 2002

In planning for future simulation activities, one of our biggest challenges will involve 

adjusting our capabilities and services to meet the growing interest and requirement for 

“system level” simulations, such as will be seen with the Aviation System Technology 

Advanced Research (AvSTAR) Program, while maintaining our excellence in traditional 

flight simulation. SimLabs is responding proactively to these challenges and the new 

opportunities they represent. Fiscal Year 2002 will be a transitional year, involving adjustment to difficult financial challenges, evolution of the extant facilities into more adaptable 

and efficient configurations, and development of new simulation applications.

One of the new activities into which we plan to expand in FY 02 is the Virtual Airspace 

Simulation Technology (VAST), the system simulation portion of AvSTAR. This work will 

begin with detailed planning and definition phases. Additionally, we are working with the 

Space Launch Initiative management and planners to find ways of supporting design and 

development of the Crew Transfer Vehicle as well as other system visualization types 

of simulation. With the uncertainties of NASA’s Rotorcraft Technology Program, we are 

re-establishing our relationship with the Army’s Aeroflightdynamics Directorate to continue 

Ames’ excellence in rotorcraft simulation. These and other opportunities will be explored 

and developed to ensure the future strength and crucial contributions of SimLabs.

What Can Be Found in This Annual Report

The first section of the Annual Report contains the FY 01 Simulation Schedule, Project 

Summaries, and next year’s simulation plans. This report also contains synopses of the 

Simulation Projects completed in the CVSRF, FFC, and the VMS, as well as the Research 

and Technology Upgrade Projects. Finally, the reader will find a list of acronyms used 

throughout the report and an appendix containing facility descriptions.

For additional information about our facilities and for past annual reports, please visit 

our website at www.simlabs.arc.nasa.gov.

Tom Alderete

Chief, Simulation Planning Office

Aviation Systems Division

Barry Sullivan

Chief, Aerospace Simulation 

Operations Branch

Aviation Systems Division
9 Aviation Systems Division Aerospace Simulation Operations Branch Aviation Systems Division Ames Research Center FY 01 Simulation Schedule
10 Aviation Systems Division

FY 01 Project Summaries

Continued next page...

VMS Simulation Projects

1. Civil Tiltrotor-9

Date: Oct 2 - Nov 17, 2000 (VMS)

Aircraft type: CTR 4/95 NASA tiltrotor

Purpose: To investigate handling qualities and flight operations issues related to operating a tiltrotor aircraft at a 

vertiport.

2. Joint Shipboard Helicopter Integration Process

Date: Dec 11 - Dec 21, 2000; Jan 22 - Feb 1, 2001; 

Mar 5 - Mar 23, 2001 (VMS)

Aircraft type: UH-60A Black Hawk helicopter

Purpose: To conduct and evaluate simulated shipboard 

landings and take-offs using the LHA/UH-60A combination 

for a range of subsystem fidelity levels.

3. Visual Scene Height Perception (PsychoPath) II

Date: Feb 12 - Feb 26, 2001 (FB)

Aircraft type: Civilian helicopter

Purpose: To investigate the impact of various visual and 

motion cues in a training simulator on pilot performance 

during an autorotation maneuver. 

4. Space Shuttle Vehicle 2001-1

Date: Mar 19 - Apr 6, 2001 (VMS)

Aircraft type: Space Shuttle Orbiter

Purpose: To evaluate an updated adaptive speedbrake 

model and to provide the pilot astronaut corps with training 

in orbiter landing and rollout.

5. Civil Army Design Specification

Date: Apr 9 - May 4, 2001 (VMS)

Aircraft type: MD-500 civilian helicopter 

Purpose: To establish characteristics associated with the 

lowest levels of Stability Augmentation Systems, autopilot, 

and cockpit displays to safely operate single-pilot helicopters operating under Instrument Flight Rules.

6. AutoCue II

Date: May 5 - May 18, 2001 (VMS)

Aircraft type: UH-60A Black Hawk helicopter

Purpose: To determine the impact of various visual and 

motion cues on pilot workload and performance during an 

autorotation maneuver.

7. Joint Shipboard Helicopter Integration Process II

Date: Jun 6 - Jun 28, 2001

Aircraft type: UH-60A Black Hawk helicopter

Purpose: To define launch and recovery wind-over-deck 

flight envelopes for the UH-60A helicopter and LHA ship 

combination.

8. Civil Tiltrotor-10

Date: Jul 2 - Aug 9, 2001 (VMS); Sep 18 - Oct 4, 2001 

(FB)

Aircraft type: CTR 4/95 NASA tiltrotor

Purpose: To investigate handling qualities and flight operations related to operating a tiltrotor aircraft at a vertiport.

9. Space Shuttle Vehicle 2001-2

Date: Sep 3 - Sep 28, 2001 (VMS)

Aircraft type: Space Shuttle Orbiter

Purpose: To provide the pilot astronaut corps with training 

in Space Shuttle landing and rollout.

CVSRF Simulation Projects

1. Integrated Neural Flight and Propulsion Control 

System I

Date: Oct 2 - Nov 2, 2000 (ACFS)

Purpose: To examine the effectiveness of a Neural Flight 

Control system in controlling a damaged aircraft.

2. Air Traffic Control Simulation Fidelity

Date: Nov 29, 2000 - Mar 28, 2001 (B747)

Purpose: To evaluate the efficacy of Air Traffic Control 

simulation in providing airline aircrews with a training and 

evaluation environment comparable to actual line operations.

3. Boeing Noise I

Date: Jan 16 - Jan 19, 2001 (B747)

Purpose: To demonstrate the use of noise analysis tools 

integrated with the Boeing 747-400 flight simulator to measure noise under the flight path.

4. Boeing 747 Neural Flight Control System

Date: Apr 24 - May 14, 2001 (B747)

Purpose: To determine if NASA’s Neural Flight Control 

System could drive a cable-driven aircraft system.
11 Aviation Systems Division

FY 01 Project Summaries

FB—Fixed-Base Simulators

VMS—Vertical Motion Simulator 

ACFS—Advanced Concepts Flight Simulator 

B747—Boeing 747 Simulator 

Research & Technology Projects

1. Rapid Integration Test Environment III

Purpose: To merge advanced Information Technologies to 

facilitate flight simulation as an integral part of the design 

process.

2. Virtual Laboratory

Purpose: To enhance and deploy a collaborative engineering tool for researchers to actively interact with VMS experiments from remote locations. 

3. VMS Modernization

Purpose: To increase the reliability and maintainability of the 

VMS by replacing major system elements.

4. Air Traffic Control for the VMS

Purpose: To augment VMS simulation capability by integrating Air Traffic Control capability for the Civil Tiltrotor program.

5. Kaiser HMD and Head Tracker

Purpose: To integrate a commercial off-the-shelf helmetmounted display and head-tracking system to support a 

Comanche helicopter simulation.

6. Navigation Database: Automation

Purpose: To automate the process of updating the airport 

and runway record database files for use by the Flight Management System in the ACFS.

7. High Level Architecture to FFC

Purpose: To demonstrate simulation interoperability between 

full-motion flight simulators in the CVSRF and the airport 

surface operations simulator in FFC using the High Level 

Architecture interface.

8. Integrated Vehicle Modeling Environment Development

Purpose: To provide a flexible architecture in the ACFS to 

simulate various aircraft models.

5. Airborne Information on Lateral Separation

Date: May 7 - Jun 15, 2001 (B747)

Purpose: To study the implementation of a system that 

supports closely spaced parallel runway approaches during 

Instrument Meteorological Conditions.

6. Boeing Noise II

Date: Jul 9 - Jul 26, 2001 (B747)

Purpose: To evaluate the feasibility and human factors 

issues of current and proposed Noise Abatement Procedures in noise-sensitive airports.

7. Distributed Air-Ground Demonstration

Date: Sep 17 - Sep 19, 2001 (ACFS)

Purpose: To demonstrate technologies and procedures 

related to the Distributed Air-Ground concepts.

FFC Simulation Projects

1. AGI Ramp Controller Training

Date: Oct 30 - Oct 31, 2000

Purpose: To train ramp controllers for the new International 

Terminal “A” at San Francisco International Airport.

2. LAX Phase I

Date: Feb 20 - Feb 23, 2001

Purpose: To determine if FFC could represent LAX with sufficient realism in preparation for runway incursion studies.

3. LAX Phase II

Date: Apr 10 - Apr 12, 2001; Apr 24 - Apr 26, 2001

Purpose: To evaluate alternatives to reduce runway incursions at LAX.

4. Surface Management System: First Simulation

Date: Sep 13, 2001

Purpose: To evaluate the effectiveness of a decision-support tool that will help manage airport surface traffic.
12 Aviation Systems Division

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FY 02 VMS Simulation Projects
13 Aviation Systems Division

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14 Aviation Systems Division

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FY 02 FFC Simulation Projects
15 Aviation Systems Division

Vertical Motion Simulator

Research Facility

The Vertical Motion Simulator Complex is a world-class research and 

development facility that offers unparalleled capabilities for conducting 

some of the most exciting and 

challenging aeronautics and aerospace studies and experiments. The 

six-degree-of-freedom VMS, with its 

60-foot vertical and 40-foot lateral 

motion capability, is the world's largest 

motion-base simulator. The large 

amplitude motion system of the VMS 

was designed to aid in research issues 

relating to controls, guidance, displays, 

automation, and handling qualities of 

existing or proposed aircraft. It is an 

excellent tool for investigating issues 

relevant to nap-of-the-earth flight and 

to landing and rollout studies.

VMS

PROJECT

SUMMARIES
16 Aviation Systems Division

Civil Tiltrotor-9 (CTR-9)

Bill Decker, Dan Dugan, Jack Franklin, NASA ARC; Helmuth Koezler, Pete Klein, Bell Helicopter 

Textron; Dan Bugajski, Honeywell; Gordon Hardy, Ron Gerdes, Phil Tung, Emily Lewis, 

Steve Belsley, Northrop Grumman IT

new instrument panel to support ATC flight management. A second computer was added to provide two 

full sets of controllers for a two-person crew.

Two flight control systems, known as Stability and 

Control Augmentation Systems (SCAS), were developed. Bell Helicopter Textron’s (BHT) SCAS is a full 

authority SCAS, meaning that the system can command the actuator and control surfaces through their 

full ranges of travel. Bell also developed an autopilot 

function based on previous tiltrotor work that was 

coordinated with the Honeywell Vertical Navigation 

(VNav) system and the Mode Control Panel (MCP). 

The second SCAS was a Dynamic Inverse (DI) 

design developed by Jack Franklin of NASA Ames. 

Two versions of the DI SCAS were studied.

A full suite of avionics--including updated navigation displays, Primary Flight Displays (PFD), and 

MCP displays--were integrated into the experiment. 

Two critical flight management functions were also 

developed. These included the VNav system developed by Honeywell and a lateral navigation system 

(LNav) developed by Northrop Grumman Information 

Technology (IT). 

In preparation for FAA certification for tiltrotor aircraft, the Pseudo-Aircraft System (PAS), an ATC simulation software tool, was successfully integrated into 

the simulation. PAS generated pseudo-aircraft traffic, 

which was displayed on the navigation display and 

on the Out-The-Window (OTW) views to simulate 

other aircraft traffic in the area. Voice communications with an ATC controller were also integrated into 

the simulation.

Results

Researchers were satisfied with the performance 

of the BHT SCAS and the two DI SCAS. The autopilot 

algorithm worked correctly with some minor tuning 

required so that it worked more “tightly” with both 

SCAS. Some features on the MCP and VNav did not 

function as anticipated and were targeted for further 

development. Based on pilot comments, the TOGA 

profiles will require some redesign in the future. On 

the hardware side, the TCL will be redesigned, as 

many pilots were uncomfortable with the TCL angle.

Investigative Team

NASA Ames Research Center (ARC)

Northrop Grumman IT

Bell Helicopter Textron

Honeywell

FAA

Summary

Civil Tiltrotor (CTR)-9 was a continuation of 

the CTR series of simulations that investigated handling qualities and flight operational issues related 

to operating a tiltrotor aircraft at a vertiport. The 

simulation also investigated flight profiles designed 

for noise abatement, One-Engine-Inoperative (OEI) 

operations, and two flight control systems with autopilot functionality. This research also studied integration 

of the tiltrotor aircraft into existing airspace with Air 

Traffic Control (ATC). 

Introduction

The CTR series of simulation experiments have 

investigated certification and operational issues 

affecting terminal operations of a civil tiltrotor transport. In addition to flying qualities of the CTR inside 

and outside of the terminal area, past research has 

focused on operational issues under normal airspace 

management procedures. Recently, more emphasis 

has been placed on fitting the tiltrotor into the existing 

airspace with vertiport sites located near existing airports or in congested downtown areas. The CTR-9 

study investigated aspects of this issue, including 

noise abatement, approach and departure profiles 

and procedures, pilot workload, and pilot interaction 

with ATC controllers. 

Simulation

During the simulation, pilots flew several Take 

Off/Go Around (TOGA) profiles designed to reduce 

noise impact on surrounding areas. They also 

responded to OEI scenarios and studied two flight 

control systems with autopilot functionality. 

The cab interior was reconfigured to incorporate 

newly designed Thrust Control Levers (TCL) and a 

This is the CTR 4/95, a notional aircraft developed by 

NASA. It’s designed as a civil transport regional airliner 

and has a 40-passenger capacity.
17 Aviation Systems Division

Joint Shipboard Helicopter Integration Process (JSHIP)

Mike Roscoe, Colin Wilkinson, Bob Nicholson, Denver Sheriff, Information Spectrum, Inc.; 

Chuck Perry, Norm Bengford, Christopher Sweeney, Northrop Grumman IT

Summary

The JSHIP program of the Office of Secretary of 

Defense (OSD) is tasked with evaluating concepts 

and addressing issues related to joint military helicopters aboard Navy ships. As part of the JSHIP 

effort, the Dynamic Interface Modeling and Simulation 

System (DIMSS) team is developing a process using 

simulation to establish Wind-Over-Deck (WOD) flight 

envelopes and providing a high fidelity simulation for 

training aircrews specifically for launch and recovery 

operations at sea.

Introduction

DIMSS is tasked with defining modeling and simulation products that replicate the aircraft and pilot 

workload for launch/recovery operations from Navy 

ships. DIMSS will also develop a process to integrate 

simulation subsystems into operational flight trainers. 

The focus is on nine subsystems: flight deck, aircraft 

aerodynamics and engine, landing gear, pilot control 

force/feel, ship motion, ship airwake, body force and 

motion cueing, aural, and visual cueing. 

This simulation attempted to determine the minimum simulator fidelity required to accurately predict 

the WOD launch and recovery flight envelope for the 

UH-60A helicopter and LHA ship combination. Different fidelity levels (I, II, III, etc.) for the aural, body 

force, and visual cueing subsystems were tested in 

different combinations of sensitivity configurations. 

Pilots flew these configurations to determine the minimum levels required for WOD envelope prediction.

Simulation 

The goals of the simulation were as follows:

• Evaluate simulated shipboard landings and takeoffs using the LHA/UH-60A combination for a range 

of subsystem fidelity levels; 

• Evaluate a range of simulated shipboard Army 

Design Specification (ADS)-33 tasks or Mission Task 

Elements (MTE) for a range of fidelity levels;

• Record pilot ratings, pilot comments, and aircraft 

data with which to validate the simulation against 

real-life data; 

• Identify the minimum sensitivity configuration 

required to accurately predict the WOD envelope; 

and 

• Provide the data and experience necessary to 

develop a fidelity algorithm.

Considerable development was done in almost 

every area of the simulation. The cab was modified 

with a complete UH-60A field of view, including an 

actual UH-60A door. An existing UH-60A aerodynamic and engine model was integrated with delivered force/feel characteristics and newly modeled 

landing gear. The CARDEROCK ship motion program was modified for an LHA ship and used in a 

real-time simulation for the first time. Computational 

Fluid Dynamics (CFD)-derived ship airwake data 

files were integrated into the aerodynamic model 

at 24 separate locations and run in real-time. A 

Camber four-axis dynamic seat was reverse-engineered, tuned, and integrated into the hexapod and 

VMS motion drives. Three aural models were developed based on flight test data. For visual cueing, the 

Evans & Sutherland Image Generator (ESIG) 4530 

was updated with 3D Sea-State software, and an 

entirely new image generation system using simFUSION PCs was integrated.

Results

During five weeks of simulation, five pilots completed 1689 runs. The WOD launch and recovery 

runs were successfully simulated for the entire 

test matrix. Tests using the standard Useable Cue 

Environment (UCE) maneuvers helped differentiate 

between the simulation fidelity configurations. Results 

identified the preferred fidelity levels for different 

cueing subsystems. They were: Visual Level II (ESIG 

4530 enhanced with 3D Sea-State model), Aural 

Level II and Level III (generated using flight test 

data), and Body Force Level IV (using the VMS and 

dynamic seat motion). 

Investigative Team

JSHIP Joint Test and Evaluation Office

Information Spectrum, Inc.

NASA ARC

Northrop Grumman IT

A UH-60A Black Hawk helicopter lands on a ship.
18 Aviation Systems Division

Visual Scene Height Perception (PsychoPath) II

Munro Dearing, Jeffery Schroeder, U.S. Army/NASA Rotorcraft Division;

Robert Morrison, Northrop Grumman IT

Summary

The PsychoPath II simulation made a second evaluation of the effect of terrain representation on the 

pilot’s perception of sink rate for a helicopter on 

approach to a runway. By using significantly improved 

logic for controlling the experiment, the simulation 

sought to obtain more conclusive results, compared 

with those of the first evaluation, for the pilot’s minimum perceptible threshold of sink rate for each of 12 

different terrain representations.

Introduction 

In an emergency caused by loss of engine power 

or impaired flight controls, a helicopter pilot can usually perform an autorotation maneuver to make a 

safe landing. Successful completion of this maneuver 

requires much practice; unfortunately, practice in a 

helicopter is risky and expensive. Therefore, a lowcost autorotation simulator is needed in which pilots 

can obtain the necessary experience. For such a 

simulator to be effective, however, minimum specifications for visual cueing must be established. 

An important aspect of visual cueing is the pilot’s 

perception of sink rate, which is critical to executing 

the autorotation maneuver. This perception is influenced by the representation of terrain in the visual 

scene of the simulator. The results of the previous 

evaluation were inconclusive because of deficiencies 

in the logic used to control the experiment. With the 

deficiencies corrected, the current simulation sought 

to conclusively determine the effect of terrain representation on a pilot’s perception of sink rate.

Simulation 

SimLabs personnel significantly modified the software from the previous PsychoPath simulation to 

implement improved controlling logic, a new data 

format for end-of-run printouts, and logic for a remote 

terminal to display the data during the experiment for 

each terrain representation.

The visual scene consisted of a 600-ft-long generic 

runway with a surrounding grass infield area. The 

texture density of the runway and grass area could 

be varied from zero to the maximum value possible, 

resulting in the 12 different selectable terrain representations. The textures were derived from photographs of a runway and a random noise database. 

Vertical cues such as buildings, towers, and hangars 

were not provided.

During the simulation, each subject was presented 

with one of 12 different terrain representations. The 

subject was then given a pair of four-second runs 

with different sink rates, the subsequent run beginning one second after the initial run. In each run, 

the simulated helicopter started from 100 ft in front 

of runway threshold at a 100-ft altitude and an airspeed of 20 knots, flew level for one second before 

descending to an 80-ft altitude, and then leveled off. 

A random number generator determined whether the 

run with the fastest sink rate occurred first or last. 

After the two runs, the subject indicated which one 

had the fastest sink rate before starting the next 

pair of runs. Consecutive pairs of runs were given to 

the subject until the controlling logic determined that 

the minimum perceptible threshold of sink rate had 

been determined and that the experiment for a given 

terrain representation was complete. The simulation 

experiment was then repeated with the subject for 

each of the other terrain representations.

Results 

Fifteen subjects, eight of whom were pilots, completed a total of 14,064 data runs. The simulation 

was successful and met its objectives. Results of the 

investigation were pending at the time of this writing.

Investigative Team

U.S. Army

NASA ARC

Northrop Grumman IT

The PsychoPath II simulation made a second evaluation of 

the effect of terrain representation on the pilot’s perception 

of sink rate. The image on the left shows the most basic 

representation of a runway, while the one on the right 

depicts the highest resolution simulated.
19 Aviation Systems Division

Space Shuttle Vehicle 2001-1

Howard Law, Alan Poindexter, Ken Ham, Chris Ferguson, Greg Johnson, NASA JSC; Ed Digon, 

Boeing; Peter Dailey, Lockheed Martin; Jim Harder, United Space Alliance; 

Estela Hernandez, Jeff Homan, Northrop Grumman IT

Summary

Simulation of the Space Shuttle orbiter was performed at the VMS to provide landing and rollout 

training for the astronaut corps. The engineering 

phase of the simulation studied the adaptive speedbrake model. Improvements to the simulation model 

were made to incorporate a Global Positioning 

System (GPS), vehicle mass modifications to the 

guidance and flight control systems, and additional 

wind profiles.

Introduction

The Space Shuttle Vehicle (SSV) is simulated at 

the VMS twice each year. During these simulations, 

researchers examine issues such as modifications to 

the flight-control system, flight rules, and the basic 

simulation model. The simulations also provide astronaut training with realistic landing and rollout scenarios.

The main objective of SSV-2001-1 was to train 

upcoming mission crews through a series of flight 

simulations. To improve the training experience, 

changes were made to the math model for vehicle 

mass and wind profiles.

In addition to training, GPS capability was incorporated into the math model. An engineering study was 

also conducted, focusing on the implementation of an 

adaptive speedbrake. 

Simulation 

The first model modification entailed the addition 

of 75 flight wind profiles for improved crew training. 

During the simulation, the 102nd Shuttle crew 

returned from orbit, so the wind profile recorded 

during their landing was implemented to provide 

added realism for training. Additionally, reenactment 

of this landing allowed the pilot of the 102nd mission 

to validate the accuracy of the VMS simulation model.

The second model modification incorporated a 

separate "vehicle mass" value for guidance. Formerly, one variable in the model supplied a weight 

value to both the physics and guidance models. 

With the incorporation of a second variable, the physics model will utilize the actual weight variable, and 

the guidance model will utilize the assumed "vehicle 

mass" variable. The two separate mass variables 

result in more accurate simulations of the approach 

and landing phase.

The third change incorporated an elaborate GPS 

model. If an error occurs during launch, the Shuttle 

must be able to make a safe landing at a designated 

abort site; consequently, flight conditions are important during launch. However, the flight weather conditions currently approved for the Shuttle are far stricter 

than for other aircraft, and if minimum weather conditions aren't met, the launch must be postponed. With 

the implementation of GPS, the Shuttle will be able 

to safely navigate in a wider variety of weather conditions. This will save taxpayers millions of dollars in 

aborted launch costs.

The fourth math model change implemented the 

latest updates to the adaptive speedbrake. The orbiter's current speedbrake is positioned at several 

discrete angles during the final approach and 

landing phases, whereas an adaptive speedbrake 

will allow continuous changes in the speedbrake 

angle, providing more accurate control of descent 

velocity. Researchers incorporated adaptive speedbrake designs into the simulation to determine how to 

optimize speedbrake change effects that are dependent upon GPS accuracy. 

Results

During the three weeks of simulation, 37 astronaut 

pilots and seven mission specialists completed 692 

training runs. The researchers achieved their objectives for the three weeks of training. The crew familiarization session reinforced the importance of the 

VMS in preparing upcoming crews for the landing and 

rollout phase of the mission and for possible failures 

during that phase. The GPS model was successfully 

implemented and will be available for future experiments.

Investigative Team

NASA Johnson Space Center (JSC)

Boeing North American

Lockheed Engineering and Services Corp.

United Space Alliance

Norhrop Grumman IT

The training that astronauts receive at the VMS is 

instrumental in producing safe, successful landings of the 

Space Shuttle.
20 Aviation Systems Division

Civil Army Design Specification

Chris Blanken, Army; Roger Hoh, Alfredo Arencibia, Dave Mitchell, Hoh Aeronautics, Inc.; 

Emily Lewis, Luong Nguyen, Northrop Grumman IT

Summary

The Civil ADS experiment was the first of a series 

of experiments intended to improve civilian flight for 

helicopters operating under Instrument Flight Rules 

(IFR). The goal of this inaugural simulation was to 

develop the necessary tools and gather preliminary 

data to gain insights into these topics.

Introduction

The Civil ADS simulation series supports the “Civil 

Helicopter IFR” program, a sub-task of the NASA 

“Safe All-Weather Flight for Rotorcraft” program. 

Studies show that helicopter accident rates are much 

higher than those of commercial airliners, probably 

because most helicopters are not certified for IFR 

flight. The “Civil Helicopter IFR” program will identify 

ways to advance IFR operations in civil helicopters 

and consequently increase their safety. To that end, 

the Civil ADS simulation series will quantify what is 

safe for helicopter IFR by defining a standardized set 

of IFR tasks--including Stability Augmentation System 

(SAS) failures--and defining criteria that will result in 

an acceptable workload for civilian IFR tasks. 

Simulation 

For this experiment, a MD-500 helicopter was used 

as the model, and four vehicle configurations of varying stabilities were simulated. Three SAS types were 

developed: a series SAS (10% authority), a parallel 

SAS (full authority), and a rate SAS (for both the 

series and parallel systems). The parallel SAS was 

expanded to two versions, each optimized for different vehicle configurations. An autopilot with attitude hold, altitude hold, glideslope capture, heading 

hold, and navigation modes was designed and implemented for this simulation.

Engineers developed a civil IFR visual database, 

which included many airports in the San Francisco 

Bay area, Very High Frequency Omni-Directional 

Ranges (VOR), and intersections, such that VOR 

and Instrument Landing System (ILS) precision 

approaches could be performed using IFR charts and 

procedures. Two displays, an instrument display and 

a moving map/navigation display, were developed for 

viewing in the cab. Displays developed for observation in the lab were: an aircraft position trace display; 

a repeater of the mechanical instruments, buttons, 

and lights in the cab; and a real-time data display. 

Four task scenarios, representative of realistic, 

high workload, single-pilot IFR situations, were used 

in this experiment. The scenarios were broken into 

three segments: 1) an IFR departure starting at 40 

knots, with a 50-foot flight altitude, and including navigation to final approach; 2) execution of an ILS, 

Localizer, or Localizer-Type Directional Aid (LDA) 

approach, with weather below minimums and execution of the initial portion of a missed approach, culminating in a holding pattern; and 3) a missed approach 

procedure with a holding pattern assigned in climb 

and the execution of a non-precision approach.

Results

During this experiment, four pilots flew 47 half-hour 

data runs to evaluate the simulation. All pilots agreed 

that the simulation was a valid tool for the stated 

objectives. Turbulence and winds were found to be 

major contributors to IFR pilot workload. The autopilot 

resulted in satisfactory pilot workload. Pilots liked the 

parallel SAS configuration; however, they had to keep 

their hands off the stick when performing non-control 

tasks. SAS-off runs resulted in unacceptably high 

pilot workload, even for the configuration that meets 

FAA requirements for helicopter IFR. The highest 

tendency for serious errors occurred late in the run 

during the missed approach, probably due to a combination of light stick forces, divided attention, and 

fatigue.

Investigative Team

Aeroflightdynamics Directorate

Hoh Aeronautics, Inc.

Northrop Grumman IT

The establishment of IFR for civil helicopters should 

decrease the number of accidents and fatalities for this 

type of aircraft.
21 Aviation Systems Division

AutoCue II

Munro Dearing, NASA ARC; Norm Bengford, Northrop Grumman IT

Summary

The AutoCue II simulation investigated the impact 

of appropriate visual and motion cues on pilot performance during a helicopter autorotation maneuver 

simulation. This was accomplished by varying the 

texturing and resolution content of simulated runways 

and by varying the motion cueing environment. The 

experiment also researched the ability of a pilot to 

recognize relative rates of descent visually in a nonmotion simulation environment.

Introduction

The helicopter autorotation maneuver is employed 

when flight conditions warrant a minimum or nopower descent and landing. The maneuver allows the 

pilot to execute a safe, survivable landing depending 

on the availability of appropriate terrain. Because 

practice autorotations are expensive and carry high 

risk, there is a need for a helicopter autorotation 

simulator. Such simulators require the establishment 

of minimum cueing specifications for both visual 

and motion systems. The AutoCue II simulation was 

designed to determine the tradeoff between pilotvehicle performance and workload versus visual and 

motion cues.

Simulation

The first AutoCue experiment demonstrated the 

need for enhanced visual cues during the helicopter 

autorotation maneuver. In support of this goal, six 

wickets were placed across the runway at different 

longitudinal and vertical positions. These wickets 

helped the pilot stay on glideslope and assisted the 

pilot in determining when to begin descent arrest. 

The wickets were used for practice runs and were 

removed during rated runs.

For each run, the pilot autorotated the helicopter 

from an initial altitude of 1000 ft and an initial airspeed of 80 kts to land at a designated spot on 

the runway. The runs were done using two different 

runway visual cue environments: one with no texture 

and little scene content, and one with high scene 

density. The motion cueing environment included 

the full VMS motion system, no motion, and limited 

motion to emulate a hexapod simulator with a 15-in 

actuator stroke. For each run, the pilot performed an 

autorotation to touchdown with a maximum airspeed 

of less than 25 knots and a maximum rate of descent 

of less than five ft/sec. Pilots rated each autorotation 

according to the speed, rate of descent, and touchdown position. 

A secondary goal of the simulation was to develop 

an R-22 helicopter model. An R-22 is more representative of the civilian helicopters that this research is 

intended to benefit. SimLabs personnel developed 

the model from documentation supplied by the 

researcher, information obtained from the library, and 

computer archive files from simulations run in 1983 

and 1985.

The computer code was converted to the proper 

format and syntax to run on the current Alpha host 

computers and built into a running simulation model. 

This model was tested with static trim checks, stability derivative checks, and time history dynamic 

checks. After comparing the new check data with the 

old, the models matched very well. The R-22 math 

model and checks were then thoroughly documented 

to assist future development and use. 

Results

During the two weeks of this simulation, 11 subjects (six pilots and five non-pilots) participated. 167 

data runs and 112 non-data runs were collected. The 

objectives of the simulation were met. Data analysis 

was in progress during publication of this report.

Investigative Team

U.S. Army

NASA ARC

Northrop Grumman IT

A UH-60A Black Hawk helicopter model was used to 

examine visual and motion cues during an autorotation 

maneuver.
22 Aviation Systems Division

Joint Shipboard Helicopter Integration Process (JSHIP) II

Mike Roscoe, Colin Wilkinson, Bob Nicholson, Denver Sheriff, Gary VanderVliet, Information 

Spectrum, Inc.; Chuck Perry, Jeff Homan, Christopher Sweeney, Northrop Grumman IT

Summary

As part of JSHIP, the DIMSS project was formed 

to develop a process to establish WOD launch and 

recovery flight envelopes for helicopter/ship combinations using simulation. In this study, shipboard landings and take-offs were simulated to define WOD 

envelopes for the UH-60A helicopter/LHA ship combination. 

Introduction

The primary goal of the JSHIP process is to 

increase the interoperability of joint shipboard helicopter operations for helicopter units that are not specifically designed to go aboard Navy ships. An important issue of shipboard helicopter integration is the 

definition of WOD launch and recovery flight envelopes to ensure safe and consistent operations. For 

the Navy, WOD flight envelopes have been established for specific ship and aircraft combinations 

using at-sea flight tests. For each new helicopter/ship 

combination, WOD flight envelopes must be developed before operations commence. This flight testing 

involves taking an aircraft to the ship and conducting 

numerous (50 to 100) launches and recoveries from 

and to the ship while incrementally varying the WOD 

conditions (5 knots or 15 degree azimuth changes). 

For ships with multiple landing spots, flight envelopes 

must be developed for each spot. This process must 

be repeated for each aircraft configuration, ship class, 

landing spot, and approach style. DIMSS is therefore 

investigating the use of ground-based flight simulation as a cost-effective and controlled alternative for 

WOD flight envelope determination.

Simulation

The specific goals of the simulations were:

• To evaluate simulated shipboard landings and 

take-offs using the LHA/UH-60A combination for a 

range of subsystem fidelity levels; 

• To record pilot ratings, comments, and aircraft 

data to validate the simulation against real-life data; 

• To identify the configuration with the minimum 

fidelity required to predict the WOD envelope; and

• To conduct a General Utility Assessment and 

determine if the simulator can be used to extend/

modify Field Deck Landing Practice/Deck Landing 

Qualification requirements.

The simulation was based on the development and 

evaluations of previous JSHIP simulations (see report 

for JSHIP, p. 17). Changes made involved: replacement of the dynamic seat with a single-axis shaker, 

enhancement of the ESIG 4530 visual system to 

include a person providing landing signals, updating 

the math model to include a modification to the helicopter off-axis responses, and modification of the 

ship-airwake code to more accurately model the airflow around the LHA.

The central task for this simulation was to conduct 

landings and take-offs to define the WOD envelopes. 

Three configurations were tested for four landing 

spots on an LHA ship. The simulation was also demonstrated to various military training organizations.

Results

During the first three weeks of simulation, four 

pilots completed 1245 WOD runs to define the launch 

and recovery envelopes. During the final week, 11 

pilots flew 68 runs to assess the value of DIMSS 

technologies for training purposes.

Preliminary comparisons indicate envelopes developed with the highest simulation fidelity level and the 

envelopes developed at sea are very close. One pilot 

commented that the airwake was “very representative of actual airwake on a ship under the same 

conditions.” The lowest fidelity configuration tested 

(fixed base with seat shaker and PC-based visuals) 

was found to be unsatisfactory for envelope development and frequently induced simulator sickness. The 

simulation has good potential for training pilots. Pilots 

indicated that the simulation would be a valuable tool 

to help pilots meet current requirements.

Investigative Team

JSHIP Joint Test and Evaluation Office

Information Spectrum, Inc.

NASA ARC

Northrop Grumman IT

This image depicts wind turbulence over the deck of an 

LHA ship.
23 Aviation Systems Division

Civil Tiltrotor-10 (CTR-10)

Bill Decker, Dan Dugan, NASA ARC; Robert Fortenbaugh, BHT; Dan Bugajski, 

Mike Jackson, Honeywell; Gordon Hardy, Steve Belsley, Ron Gerdes, 

Emily Lewis, Phil Tung, Northrop Grumman IT

Summary

CTR-10 was a continuation of the CTR series of 

simulations that investigated handling qualities and 

flight operational issues related to operating a tiltrotor 

aircraft at a vertiport. During this experiment, a “full 

mission simulation” of tiltrotor terminal area operations was conducted.

Introduction

Research requirements will arise in the near future 

to integrate the civil tiltrotor-class aircraft into the 

common airspace. To this end, the CTR series of 

simulation experiments have investigated certification 

and operational issues affecting terminal operations 

of a civil tiltrotor transport. This CTR experiment was 

the last scheduled activity of the NASA Short Haul 

Civil Tiltrotor (SHCT) Program. For the SHCT program, CTR-10 fulfilled the requirements of a Level 1 

Milestone: demonstration of Civil Tiltrotor operability 

in an ATC environment. This simulation also studied 

operational issues under normal airspace management procedures.

Simulation

This experiment was conducted in a “full-mission” 

environment, including air traffic, controlled air space, 

low visibility, and winds. Specifically, the simulation 

studied:

• TOGA strategies and guidance; 

• OEI recoveries before and after landing decision; 

• Approach profile limitations (turn radii, winds, and 

other air traffic); 

• Testing of Ames flight path vector guidance; and 

• Implications of a “fixed configuration” Instrument 

Landing System approach to a runway.

To achieve these objectives, many software 

improvements were made to the CTR mathematical 

model. Modern aircraft features such as AutoPilot 

functions, an MCP, and a Flight Management System 

(FMS) were used or improved upon from previous 

CTR simulations. BHT improved the yaw axis of 

the CTR-9-developed BHT SCAS, added a height 

damper, and enabled the control system to switch 

modes upon pilot request. Honeywell developed the 

VNav system (core structure of the future FMS). The 

MCP was modified from a version which was previously used for High Speed Civil Transport (HSCT) 

research. A modern navigation display based on the 

Boeing 777 version (with a Traffic Collision Avoidance System) was upgraded. The ATC/PAS interface 

and graphics drivers (navigation display and ESIG 

3000 visual system) were developed and integrated 

into the simulation. SimLabs also developed a new 

communication infrastructure to support future joint 

simulation operations.

The Quickened Inverse (QI) flight director and 

TOGA profiles were designed by Ames researchers 

and used during the simulation. The QI flight director 

was the focus of the fixed-base study that followed 

the simulation. The flight director gains were finetuned. During the fixed-base period, stability derivative data were generated in support of future flight 

control system development.

Results

During the CTR-10 simulation, 560 pilot-in-theloop VMS data runs and 433 fixed-base data runs 

were generated. The researchers and project office 

involved in the SHCT program were extremely 

pleased to have completed the Level 1 milestone 

during the fiscal year. Modifications to the Bell 

SCAS, the Honeywell vertical guidance algorithms, 

the approach profiles, and the flight director were 

completed in time for pilot evaluation and were well 

received by the pilot community.

Investigative Team

NASA ARC

Northrop Grumman IT

Bell Helicopter Textron

Honeywell

FAA

A simulated tiltrotor lands at a vertiport in San Francisco, 

CA.
24 Aviation Systems Division

Space Shuttle Vehicle 2001-2

Howard Law, Greg Johnson, Ken Ham, Chris Ferguson, Alan Poindexter, NASA JSC; Ed Digon, 

Boeing; Peter Dailey, Lockheed Martin; Jim Harder, United Space Alliance; 

Estela Hernandez, Jeff Homan, Northrop Grumman IT

Summary

Simulations of the Space Shuttle orbiter were performed at the VMS to fine-tune the Shuttle’s landing 

systems and provide landing and rollout training for 

the astronaut corps. Upgrades to the math model 

were made to increase its fidelity.

Introduction

The Space Shuttle orbiter landing and rollout 

is simulated at the VMS twice each year. Researchers have examined modifications to the flight-control 

system, guidance and navigation systems, Head-Up 

Displays (HUD), flight rules, and the basic simulation 

model. The simulations also provide astronaut training with realistic landing and rollout scenarios. 

Although there were no engineering studies during 

this simulation, upgrades to the math model were 

made to increase the fidelity of the orbiter model.

Simulation 

The primary objective of SSV-2001-2 was to train 

upcoming mission crews and astronaut candidates 

through a series of flights. During this simulation, various runways, visibility conditions, and wind conditions 

(including the profiles recorded during the 104th and 

105th Shuttle flights) were simulated, and system failures were periodically introduced. One system failure 

duplicated an actual problem that occurred during a 

flight, when the HUD was misaligned by 0.5 degrees.

Additions to the math model included: the spiral 

heading alignment cone (HAC) data on the Horizontal Situation Indicator (HSI) instrument, wind estimation on a Head-Down Display, the ability to induce 

HUD symbology misalignment, a wet runway model 

at Kennedy Space Center (KSC), and flight wind 

profiles.

The astronaut office requested the implementation 

of a spiral HAC on the HSI instrument. Prior to landing, the orbiter loops around a theoretical inverted 

cone (the HAC) for proper landing alignment. While 

looping around this cone, it is important that the 

astronauts have an accurate indication of their position with respect to a defined flight profile. Hence, 

computer guidance systems run algorithms during 

the approach which continually display error indications. Two of the Shuttle’s displays which indicate 

errors are based upon the inverted cone algorithm, 

but a third display--the HSI--uses a cylinder in its 

calculations, making the HSI readout less accurate. 

The spiral HAC was implemented and tested.

The second math model change involved the onboard wind estimator. This estimator displays rough 

wind magnitude and direction during the guidance, 

approach, and landing phases. Winds during the final 

phase of entry directly affect energy conditions while 

flying around the HAC and at touchdown; however, 

there is currently no onboard wind information available. The new wind estimator uses two methods to 

calculate the wind direction and magnitude, each with 

a different reference frame.

Preparation was made for potential engineering 

research involving wet-weather landings at KSC. 

Shuttle Flight Rules limit wet-weather landings to 

grooved runways, to provide the necessary “grip” for 

the orbiter’s tires. KSC’s runway poses a unique challenge, since it is part smooth and part grooved. The 

two sections were modeled and tested by SimLabs 

for future studies.

Results

During the simulation, 39 pilots and two Flight 

Directors flew 576 training runs. Thirteen mission 

specialists also received training in the jump seat 

position. The researchers met their objectives for the 

three weeks of training.

Based upon pilot comments, the crew familiarization phase of the simulation reinforced the importance 

of the VMS in preparing upcoming crews for the 

landing and rollout phase of Shuttle missions and for 

possible failures during that phase.

Investigative Team

NASA JSC

Boeing North American

Lockheed Engineering and Services Corp.

United Space Alliance

Northrop Grumman IT

Space Shuttle landings and rollouts are simulated at the 

VMS twice each year.
25 Aviation Systems Division

Crew Vehicle Systems

Research Facility

The Crew Vehicle Systems Research Facility, a 

unique national research resource, was designed for the 

study of human factors in aviation safety. The facility analyzes performance characteristics of flight crews, formulates 

principles and design criteria for future aviation environments, 

evaluates new and contemporary air traffic control procedures, and 

develops new training and simulation techniques required by the continued technical evolution of flight 

systems.

Studies have shown that human error plays a part in 60 to 80 percent of all aviation accidents. The 

Crew Vehicle Systems Research Facility allows scientists to study how errors are made, as well as the 

effects of automation, advanced instrumentation, and other factors, such as fatigue, on human performance in 

aircraft. The facility includes two flight simulators, an FAA certified Level D Boeing 747-400 and an Advanced 

Concepts Flight Simulator, as well as a simulated Air Traffic Control System. Both flight simulators are capable 

of full-mission simulation.

CVSRF

PROJECT

SUMMARIES
26 Aviation Systems Division

Integrated Neural Flight Propulsion Control System (INFPCS) I

John Kaneshige, Karen Gundy-Burlet, Don Soloway, NASA; Don Bryant, Dave Brown, George 

Mitchell, Northrop Grumman IT; Ian MacLure, Anna Dabrowski, ManTech

Summary

This experiment examined the effectiveness of an 

INFPCS as a means of controlling a damaged aircraft. Experimental results indicated that the system 

operated successfully.

Introduction

This experiment is a follow-up experiment to the 

Neural Flight Control System Experiment conducted 

in May 2000. Neural networks are processing systems that do not require explicitly defined characteristics relating input to output; rather, they are capable 

of learning the relationship between input to a system 

and the resulting output by analysis of desired system 

behavior. Neural nets can be composed of hardware 

or software and consist of large numbers of relatively 

simple processing elements connected in multiple 

ways.

The purpose of this experiment was to examine 

the effectiveness of an INFPCS as a means of providing higher levels of adaptability and autonomy 

than current state-of-the-art systems. The goal was 

to develop a system capable of automatically compensating for aircraft damage or failures and further 

reduce the costs associated with flight control 

law development. The approach was to evaluate 

second generation neural flight control architectures, 

apply these to generic transport aircraft applications, 

and utilize alternate sources of control power for 

increased control authority and redundancy. This was 

accomplished by applying direct adaptive inverse 

control architecture, incorporating Propulsion Control 

Aircraft (PCA) technologies, and utilizing a daisychain approach for applying alternate control sources 

while simulating a broad range of damage or failure 

conditions.

Simulation

The AFCS was used as the test platform. The 

ACFS simulates a Boeing 757-class generic commercial air transport, having a wide body, a T-tail, low 

wings, and twin turbo-fan engines located beneath 

the wings. 

Tests consisted of select flight maneuvers as well 

as approach and landing scenarios under different 

flight conditions. The performance of different controllers was evaluated under nominal and simulated failure conditions. Additional control authority was developed using symmetric ailerons (for pitch), symmetric 

thrust (for pitch), yaw-based roll control (for roll), 

and differential thrust (for yaw). Simulated failures 

included frozen flight control surfaces, offset flight 

control surfaces, and shifts in center of gravity (longitudinal and lateral).

Evaluation criteria used included handling quality 

maneuvers based on gross acquisition tasks, fine 

tracking tests, and approach and landing tasks. Audio 

and video recordings were made of the test runs, 

and a specified set of data was collected using the 

simulator’s built-in data collection system.

Results

Experiment runs were conducted by test pilots 

from NASA and by three crews from commercial airlines. Each airline crew flew two full-mission scenarios and was confronted with en route cascading 

failures. Handling qualities, pilot workload, and task 

performance of the fully functional aircraft and of the 

aircraft under a variety of control failure conditions 

were assessed. Results indicate that the INFPCS 

controller was able to stabilize the aircraft without 

significant pilot compensation under simulated failure 

conditions. All pilots were able to land safely using 

the INFPCS controller. The Investigative Team has 

been awarded a NASA Group Achievement award, 

and this work has received attention from NASA 

Headquarters, Congress, and the national media.

Investigative Team

NASA ARC

Northrop Grumman IT

ManTech

ACFS Surface Position Indicator Cockpit Display showing 

a tail failure.
27 Aviation Systems Division

Air Traffic Control Simulation Fidelity

Alfred T. Lee, Ph.D., Beta Research, Inc.; Barbara Kanki, Ph.D., Terry Rager, NASA ARC; 

Diane Carpenter, Eric Gardner, Carlos Gomez, Jerry Jones, Rod Ketchum, David Brown, 

George Mitchell, Tom Prehm, Dan Renfroe, Gary Uyehara, ManTech

Summary

This simulation evaluated the efficacy of ATC simulation in providing airline aircrews with a training 

and evaluation environment comparable to actual line 

operations. Crews operating in a typical training environment responded to emergency scenarios more 

quickly than crews operating under simulated actual 

operations.

Introduction

The level of ATC fidelity achieved in simulation 

training and evaluation affects the workload experienced by the human participants, particularly in crew 

coordination and communication exercises. The goal 

is to present simulation workloads comparable to 

real-life operational levels. Reduced simulation fidelity may engender unrealistic crew behaviors and 

expectations in training and evaluation that would not 

be consistent with line operations.

This study investigated a Line-Oriented Flight 

Training scenario for a flight between LAX and 

San Francisco International Airport (SFO). Comparisons were made between the “experimental condition” using the ATC simulation environment and the 

“control condition” using standard line training procedures.

Simulation 

The B747 simulator was configured to set 

aircraft and environmental conditions and to activate 

requested malfunctions. A separate voice scenario 

was created to maintain repeatability, and this was 

used by ATC personnel to create the ATC chatter for 

the “control condition” group.

Twelve crews participated. Six crews were 

assigned to a low radio communications simulation 

(RCS) which was comparable to the level provided in 

training environments, and six crews were assigned 

to a high RCS condition comparable to actual line 

operations. The two groups were matched for flying 

experience. The crews received a briefing package 

necessary to complete a flight from LAX to SFO. 

They boarded the aircraft at the gate and began 

necessary procedures to make the flight.

Upon taxi out to the active runway, visual ground 

traffic was programmed to increase crew interaction 

and radio chatter. As the flight proceeded, destination 

weather was changed and the Automated Terminal 

Information Service (ATIS) was updated; both events 

required additional crew interaction. When the flight 

neared approach, a nose gear malfunction was activated, necessitating a missed approach procedure 

and eventual routing to a holding fix to resolve the 

problem. This required additional input to the FMS 

and increased crew workload. After solving the nose 

gear problem and advising ATC, revised runway visibility and breaking actions were issued, requiring further crew coordination. Subsequent approach, landing, and taxi to the gate were conducted under standard conditions.

Data collection commenced when the aircraft 

descended below 10,000 ft on arrival. Video and 

audio data were collected for the entire session, 

beginning as the crew entered the cockpit.

Results

The crew’s planning activity was reduced significantly in the high RCS fidelity condition, with smaller 

increases shown in situation awareness and workload management. Crews also initiated ATC communications more often in the high RCS fidelity condition. In the high RCS condition, there was a significant increase in the reliability, and hence validity, 

of instructor evaluations. Crew-system performance 

was affected, as well, by RCS fidelity. High RCS fidelity led to substantially increased time for execution of 

a missed approach, possibly due to increased time 

spent on crew-ATC communication. These findings 

suggest that there is a marked influence of RCS fidelity on crew workload, on the reliability of instructor 

evaluations, and on the crew coordination processes.

All research goals for this simulation were met. 

Possible follow-on studies will depend on future funding and interest from the aviation community.

Investigative Team

Beta Research, Inc.

NASA ARC

ManTech

Air traffic system in use at the CVSRF.
28 Aviation Systems Division

Boeing Noise I

Kevin Elmer, Daniel McGregor, Joseph Wat, Belur Shivshankar, The Boeing Company; Terry Rager,

NASA ARC; Jerry Jones, Rod Ketchum, George Mitchell, Fritz Renema, Diane Carpenter, Ghislain 

Saillant, David Lambert, Northrop Grumman IT

Summary

The Boeing Noise Experiment is a joint effort 

between Boeing and NASA Ames Research Center 

to demonstrate the use of noise analysis tools integrated with the Boeing 747-400 flight simulator to 

measure noise under the flight path. The goal is to 

demonstrate that noise issues can be successfully 

studied in a simulation environment. This capability 

would serve as a useful tool for researchers, airports, 

and communities studying ways of minimizing noise 

impact on communities adjacent to airports. 

Introduction

The impact of aircraft noise on communities has 

become an important element of consideration in airport operation. Some airports near noise-sensitive 

communities have established special noise abatement protocols that modify existing instrument flight 

procedures to minimize noise impact. This project 

investigated a methodology for developing additional 

tools to minimize noise impact by examining the 

noise differences generated by varying approach and 

departure procedures of the Boeing 747-400.

Simulation

Using NASA’s B747-400 simulator, 90 runs were 

conducted consisting of four types of Standard 

Instrument Departures and two types of Instrument 

Approach Procedures. Aircraft flight path data and 

the resulting noise levels were collected at a rate 

of 3.3 Hertz. The parameters collected were the distance from initial position, ground distance under the 

flight path, lateral offset relative to the flight path, 

altitude, equivalent airspeed, net thrust, net-corrected 

high pressure rotor speed, scenario time, engine 

pressure ratio, and pitch euler angle. The resulting 

flight path data files were read into a program called 

“Integrated Noise Model” which then generated the 

noise contour footprint illustrated here. The noise 

contours were continuously displayed in the cockpit. 

Results

In addition to the 90 runs originally planned, the 

Boeing team collected 18 extra runs to enhance the 

test matrix under different approach procedures. Representatives from United Airlines, the Coalition for 

San Francisco Neighborhoods, and the SFO Aircraft 

Noise Abatement office attended noise demonstration 

runs. 

This simulation leaves a valuable legacy for 

future noise abatement and Air Traffic Management 

research. By using the noise analysis tools integrated 

in the simulator, researchers can study the noise 

impact of a large number of flights in a very short 

time. Also, by immediately observing the results of 

operating procedures via the noise contour in the 

cockpit and lab, it will be possible to fine-tune procedures in real-time.

Boeing and NASA have planned to continue noise 

studies in this program. Phase II was completed this 

year; its description is included on p. 31. These further studies will elucidate human factor issues related 

to current and proposed Noise Abatement Procedures (NAP), as well as examine their feasibility. 

Investigative Team

The Boeing Company

NASA ARC

Northrop Grumman IT

This noise footprint displays results of Noise Abatement 

Departure Procedures from SFO runway 28R. The dark 

gray shows climb thrust initiation at 1500 ft, while the light 

gray shows climb thrust initiation at 1000 ft reflecting less 

noise.
29 Aviation Systems Division

Boeing 747 Neural Flight Control System

Joe Totah, Karen Gundy-Burlet, John Kaneshige, Don Soloway, NASA; 

Jerry Jones, George Mitchell, Rod Ketchum, Diane Carpenter, David Lambert, David Brown, ManTech 

Summary

This study determined if the Neural Flight Control 

System (NFCS) developed by NASA earlier this 

year could successfully drive a cable-driven aircraft 

system and provide damage-adaptive capability to 

such an aircraft.

Introduction

The test platform selected for the NFCS retrofit 

study was the B747-400 flight simulator. Previous 

PCA studies conducted on the B747 simulator demonstrated that an automated full-authority propulsion 

control system retrofit is not economically viable for 

this aircraft. Therefore, this experiment’s objective 

was to evaluate the feasibility of implementing the 

NFCS (which has no propulsion control element) in 

assisting pilots with controlling the airplane in a failure 

situation.

Two retrofit systems that provided rate command 

attitude hold with auto-trim capabilities and varying 

levels of damage adaptation were investigated. The 

first system involved a simple cable retrofit in which 

the roll, pitch, and yaw axes were decoupled from 

each other. The second system entailed coupling 

between the roll and yaw axes with a daisy-chain 

approach for moving control authority for pitch to 

the ailerons as needed. This second approach may 

require fly-by-wire system implementation with central computational capability overlaid on the existing 

cable-driven system. 

Simulation

The resulting two retrofit options were evaluated 

by NASA test pilots in a series of handling qualities 

tests consisting of fine-tracking maneuvers as well 

as approach and landing scenarios under different 

flight conditions. The objective was to compare the 

performance of the NFCS with that of conventional 

aircraft systems. The evaluation criteria were based 

upon performance measurements, Cooper-Harper 

handling qualities ratings, and pilot comments. The 

simulated failure conditions consisted of flight control 

surface failures and aircraft damage affecting aerodynamic stability and control characteristics. These failures included a full-tail failure, a failure of two engines 

on one side of the aircraft, and a stabilizer/rudder 

failure. Approach and landing scenarios were incorporated under runway incursion and non-incursion 

conditions. Weather scenarios consisted of no turbulence, light turbulence, and moderate turbulence 

under clear visibility conditions. Audio and video 

recordings were made of the test runs, and a specified set of real-time digital data was collected.

Results

It was determined that both retrofit options could 

adapt for the two-engine-out and stabilizer/rudder failures. However, the second retrofit option was necessary for successful damage adaptation for full-tail 

failure scenarios, and both inboard and outboard ailerons were necessary for sufficient pitch control (in the 

absence of the integrated propulsion control). Three 

test pilots from NASA Ames Research Center and 

one test pilot from NASA Dryden evaluated the NFCS 

systems. Under nominal flight conditions, the pilots 

determined the NFCS controller to be on par with 

the handling qualities of the normal aircraft. The 

NFCS controllers received favorable comments in the 

damage scenarios. The most critical phase of flight 

was from the transition into ground effect and roll out. 

Ground effect reduced control authority, and rudder 

cable breakage scenarios made nose-wheel steering 

difficult on roll out.

Investigative Team

NASA ARC

NASA Dryden

ManTech

Control Surfaces Display during tail failure.
30 Aviation Systems Division

Airborne Information for Lateral Separation (AILS)

Vernol Battiste, Walter Johnson, Terry Rager, NASA ARC; David Brown, Diane Carpenter, 

Eric Gardner, Nabil Hanania, Jerry Jones, Rod Ketchum, Dave Lambert, Ian Maclure, George Mitchell, 

Craig Pires, Tom Prehm, Fritz Renema, Ghislain Saillant, Gary Uyehara, ManTech

Summary

This study examined the operational implementation of an airborne system that would support Closely 

Spaced Parallel Approach (CSPA) operations at airports with parallel runways during Instrument Meteorological Conditions (IMC). Data analyses are in progress.

Introduction

Several major airports in the United States have 

parallel runways that are in close proximity. When 

visual contact between aircraft is possible, capacity is 

greatly increased by having aircraft fly closely spaced 

parallel visual approaches. Under IMC, airports with 

runways closer than 4300 ft are required to revert 

to a single runway operation or to run dependent 

approaches, each greatly reducing the number of 

landing aircraft.

This study investigated the utility and viability of 

a flight-deck-based display and alerting system that 

supports flight crews’ situational and traffic awareness during all phases of an ILS approach. The 

study also examined flight deck and ATC final controller roles and responses during dual independent parallel approach operations at Seattle-Tacoma Airport 

(SEATAC). 

Simulation

This simulation was conducted with scenarios 

using the airspace in and around SEATAC. This site 

was selected to evaluate the Airborne Information 

for Lateral Separation (AILS) concept because the 

airport is undergoing a new runway addition which 

will give the primary runways approximately 2500 ft 

centerline separation. This configuration lends itself 

to use of the AILS and CSPA technologies. Additionally, the FAA and managers at SEATAC were interested in supporting and implementing the results of 

this study.

The CVSRF’s B747 full-mission simulator was 

adapted to accept AILS symbology on the PFD and to 

present CSPA information on the navigation display. 

Initial positions were created to allow the B747 simulator to enter the scenario at desired points. The 

SEATAC runway scene depicted in the B747 simulator’s visual system was modified to represent the 

new runway. Additionally, a custom FMS navigation 

database was designed and loaded into the FMS for 

use with the new approaches.

PAS was heavily modified to incorporate changes 

required to support traffic flow realism into SEATAC. 

The CVSRF’s ATC Lab was configured to represent 

the SEATAC feeder sectors, departure sectors, a 

tower position, and adjacent airspace positions; all 

used PAS. A separate final approach controller position was created in an isolated area of the lab for 

controller evaluation. Based on controller estimates 

of normal traffic flow to dual parallel runways, a single 

controller handled 48 aircraft per hour.

Additional video cameras, video splitters, routers, 

and other hardware were installed to collect audio 

and video data for both the B747 flight deck crew and 

the isolated ATC position.

Scenarios began with air traffic routed to runways 

17 L/R. The B747 simulator was released into this 

traffic flow via automated software programs that also 

“paired” conflict traffic for a subsequent “blunder” or 

breakout maneuver.

Results

The flight crew’s assessment of the AILS concept 

was of primary interest for this experiment. This 

included all aspects of the AILS concept from system 

initialization and display status through the responses 

of the flight crew and the aircraft systems to an intruding or “blundering” aircraft.

Flight crew workload and performance data were 

collected using both objective and subjective assessment methodologies. Data analyses are in progress.

Investigative Team

NASA ARC

ManTech

SEATAC

PFD depicting an armed AILS approach.
31 Aviation Systems Division

Boeing Noise II

Kevin Elmer, Gary Gershzohn, Joseph Wat, Belur Shivshankar, Jack Dwyer, Daniel McGregor, The 

Boeing Company; Len Tobias, NASA ARC; J. P. Clark, Nhut Tan Ho, MIT; Jerry Jones, Dan Renfroe, 

Rod Ketchum, George Mitchell, Diane Carpenter, Ghislain Saillant, 

Estela Hernandez, David Lambert, Northrop Grumman IT

Summary

The purpose of the Boeing Noise Phase II experiment was to conduct a pilot-in-the-loop simulation 

to evaluate the feasibility and human factors issues 

of current and proposed NAPs in noise-sensitive airports. The flight crew’s performance in the NAPs, as 

well as the impact of the NAPs on noise reduction, 

was examined. 

Introduction

In the past, researchers used computer simulation 

and actual airport operations to study the feasibility of 

different NAPs. It was determined that only selected 

NAPs were useable in the Air Traffic Management 

(ATM) and FMS’s of the time. Modern ATM and FMS 

systems will increase the feasibility of utilizing additional NAPs, but the new NAPs must be evaluated 

before they can be implemented. The controlled environment of the CVSRF was ideal for studying the 

results of different NAPs on crew performance and on 

noise reduction. 

Simulation

Using the B747-400 flight simulator, three departure and four arrival NAPs were evaluated for the 

London Heathrow airport. Heathrow was chosen for 

the experiment because it has a stringent noise 

impact policy and monitoring plan. Aircraft flight path 

data and the resulting noise levels were recorded 

for each run. Sixty-nine additional variables were collected, including aircraft performance variables, controls movement, and autopilot events. Statistical data 

were also recorded for specific aircrew activities, 

such as when turns were made, when climbs and 

descents were initiated, and when systems were activated.

Results

A total of 318 data runs were completed for three 

departure NAPs on two separate routes, and for 

four arrival NAPs flown in both “auto” and “manual” 

modes. Collected data are being analyzed. Of the 

NAPs tested, those that have the most noise reduction benefit and least impact on the flight crew will 

be selected for further study. Human factors results 

will be provided to the Massachusetts Institute of 

Technology (MIT) for inclusion in a statistical model to 

study aircraft separation in a “noise flight procedure” 

and in heavy workload situations. Information from 

this study will benefit NASA by providing critical data 

for its Quiet Aircraft Technology Program.

Investigative Team

The Boeing Company

Massachusetts Institute of Technology 

NASA ARC

Northrop Grumman IT

A noise graph depicting decreasing noise levels as the 747 

departs London Heathrow. As the altitude increases and 

net thrust decreases, the resultant noise level decreases.
32 Aviation Systems Division

Distributed Air-Ground Demonstration

Sandy Lozito, Vernol Battiste, Walter Johnson, Nancy Smith, Terry Rager, NASA ARC; 

Thomas Prevot, San Jose State University; 

Don Bryant, David Brown, Ramesh Panda, Gary Uyehara, Northrop Grumman IT

Summary

This simulation demonstrated technologies and 

procedures related to the Distributed Air-Ground 

(DAG) concepts in the ACFS. DAG research pertains 

to interactions between the airborne flight crew and 

ground-based air traffic controllers. 

Introduction

Distributed Air-Ground research is a part of NASA’s 

Advanced Air Transportation Technologies (AATT) 

Program. It is intended to explore the triad for the 

National Airspace System: the flight deck, the ATC 

environment, and the dispatch system. This research 

specifically focuses on human factors issues.

As part of the DAG research, a demonstration was 

conducted in September of 2001. The goal of the 

demonstration was to construct and accomplish the 

initial testing of the air and ground simulation environments, using the Airspace Operations Laboratory 

(AOL) and the ACFS. Emphasis was placed upon 

the ability to configure and collect data necessary 

to test human performance parameters of pilots and 

controllers. 

Simulation Description

Several researchers and developers were involved 

in the overall planning and development of the various components in the DAG architecture. The participating organizations were NASA Ames Research 

Center, San Jose State University, and Northrop 

Grumman IT. 

For SimLabs, the development was focused on the 

ACFS. Cockpit Display of Traffic Information (CDTI), 

a key component of the DAG research, was integrated into the ACFS. The CDTI, developed separately by the DAG research team, consisted of display graphics and both self-separation and conflict 

detection logic. All elements were hosted on a Windows PC environment. Two PCs were used to drive 

the captain’s and first officer’s displays. The CDTI 

display graphics were video switched into the Navigation Display (ND) locations in the ACFS cockpit. The 

CDTI computers were interfaced with the ACFS simulation host via the Aeronautical Datalink and Radar 

System (ADRS). The ADRS, in turn, acted as a gateway to the simulated air traffic and to the Center and 

Terminal Radar Approach Control (TRACON) environments located in the AOL.

Several additional modifications were made to the 

ACFS in support of this study, including the automation of the self-spacing speed mode. This mode helps 

maintain safe separation distances between aircraft 

without pilot intervention. The Crew Activity Tracking 

System (CATS) was also integrated with the simulator to collect additional data during demonstration 

runs.

The ACFS was linked to the AOL for the demonstration runs. The AOL provided the simulated air 

traffic and the Center and TRACON environments. 

Two flight crews participated in experiment runs in 

the ACFS. The flight scenario commenced from the 

Dallas/Ft. Worth (DFW) Center airspace, continued 

through the approach environment, and concluded 

with a landing back at DFW. The CDTI and airborne 

logic to self-separate in a scenario with a few conflicts 

was used in the Center environment. Self-spacing 

algorithms developed by NASA Langley Research 

Center were used in the approach environment. 

Results

The goals of the demonstration were accomplished. Test results indicate that the integration of 

air and ground simulation environments, using the 

AOL and the ACFS, was quite successful. Data collection capability was also validated, and some new 

data requirements were identified. The integrated 

system will serve as a valuable resource for NASA’s 

air transportation system research.

Investigative Team

NASA ARC

San Jose State University

Northrop Grumman IT

CDTI with control interface in the ACFS.
33 Aviation Systems Division

 FFC is operated and managed by NASA personnel, 

including experts in Air Traffic Control, computer 

graphics, human factors, and large-scale simulations. 

The two-story facility offers a 360-degree, full-scale, 

real-time simulation of an airport, where controllers, 

pilots, and airport personnel can interact to optimize 

operating procedures and test new technologies.

FutureFlight Central

Research Facility

NASA FutureFlight Central is a national Air Traffic 

Control/Air Traffic Management test facility dedicated to 

solving the present and emerging capacity problems of 

the nation’s airports. The facility was designed in collaboration with the Air Transportation Association, the Federal Aviation Administration, the National Air Traffic Controllers Association, and the Supervisors' Committee.
34 Aviation Systems Division

AGI Ramp Controller Training

Mike Madson, Marlene Hooten, NASA ARC; Marc Kenyon, AGI; 

Farid Haddad, Jim McClenahen, Ron Miller, Christine Wong, Raytheon

ing more complex coordination skills during two days 

of training. To aid in the controllers’ training, two SFO 

Tower air traffic controllers were present to critique 

the trainees’ performance. Although ramp controllers 

typically receive a printed schedule of the prospective 

arrivals and departures into their area, the controllertrainees made use of such a schedule only on the 

first day of training. On the second day, to better 

focus the training, the trainees just managed traffic. 

Results

Using FFC simulation capabilities, AGI was better 

able to understand the required staffing levels and 

knowledge for running the new ramp facility. Based 

on their training, AGI convinced senior management 

that greater staffing levels and experience were 

required to successfully operate the ramp tower 

facility. “[NASA’s FutureFlight Central provided] the 

very best training environment possible,” said Robert 

Peterson, Ramp Tower Manager for AGI, “We would 

like to spend more time in the facility.”

Post-simulation responses on an evaluation survey 

showed that controller-trainees were highly satisfied 

with their training experience, which included typical 

pilot-controller communications. The realism of the 

OTW scene also received high marks.

Investigative Team

NASA ARC

FAA

Airport Group International

Raytheon

Summary

The simulation objective was to train Airport Group 

International (AGI) ramp controllers for the new International Terminal at San Francisco International Airport.

Introduction

SFO is the seventh-busiest airport in the world. It 

has recently added two new international terminals as 

part of a major construction effort.

AGI was contracted to operate Ramp Tower A, 

located on top of the new International Terminal, “Terminal A.” Efficient ramp operations are crucial to the 

overall operating efficiency of the airport. The goal 

of this simulation, therefore, was to train AGI’s ramp 

controllers for the operation of Terminal A.

Simulation 

Utilizing the SFO visual database at FFC, the controller-trainees were provided a 360° visual representation of the view from the ramp tower in different 

weather conditions. The capability of FFC’s software 

includes moving the tower eye point to the OTW 

scene appropriate to the user (in this case, the ramp 

controller-trainees).

FFC staffed the tower, directing arriving aircraft 

to appropriate locations when controller-trainees took 

over. A team of “pseudo-pilots” taxied aircraft into and 

out of the 26-gate ramp area. The pilots were in twoway radio communication with the controller-trainees, 

who directed the aircraft into and out of the ramp area 

in real-life traffic flow situations. 

Each trainee was put in charge of an hour-long 

scenario that varied from a slow tempo to one requir120° View of the Ramp Area from Ramp Tower “A."

The indicated area is Ramp Tower A’s responsibility.
35 Aviation Systems Division

LAX Phase I

Boris Rabin, Richard Haines, Cedric Walker, Michael Madson, Marlene Hooten, Betty Silva, 

Ken Christensen, NASA ARC; Elliot Brann, FAA; Jim McClenahen, Farid Haddad, 

Ron Miller, Christine Wong, Raytheon

Summary

The primary objective of the LAX Phase I Baseline 

simulation was to assess whether FFC could represent the LAX operational environment with sufficient 

realism to study alternative runway incursion solutions proposed in Phase II. This simulation was the 

first time a major hub airport has been successfully 

modeled.

Introduction

The FAA defines a runway incursion as “any occurrence at an airport involving an aircraft, vehicle, 

person, or object on the ground that creates a collision hazard or results in loss of separation with an 

aircraft taking off, intending to take off, landing, or 

intending to land.” Although relatively rare, runway 

incursions can lead to catastrophic runway collisions, 

putting many lives at risk. Consequently, the FAA has 

declared runway incursion problems at U.S. airports 

a top priority.

Out of 779,000 takeoffs and landings in 1999, 

LAX experienced 10 runway incursions, almost all of 

which were attributed to pilot deviation or air traffic 

controller error. To address this issue, Los Angeles 

World Airports (LAWA), the FAA, United Airlines, and 

NASA entered into an agreement to study changes at 

LAX that would help reduce runway incursions, thus 

making their runways safer. 

FFC proposed a two-phase study. The primary 

objective in Phase I was to evaluate the realism of an 

FFC simulation before proceeding to Phase II. 

Simulation 

In Phase I, FFC designed three types of scenarios: 

a peak arrival rush operating under visual flight conditions, with 92 arrivals per hour and 78 departures; 

a peak departure rush operating under visual flight 

conditions, with 62 arrivals and 107 departures; and 

a peak arrival/departure rush operating under instrument conditions with 88 arrivals at minimum separation and 107 departures.

Both the north and south runways of LAX were 

simulated, with a complement of 22 airlines and an 

aircraft mix representative of LAX in the summer 

of 2000, for which NASA obtained actual LAX operational statistics. Some aspects of airport operations 

(e.g., ramp control, ground vehicle traffic, and maintenance operations) were omitted. 

Two groups of four LAX controllers worked each of 

the four tower positions over a two-day period, for a 

total of four simulation days. Controllers were rotated 

to ensure that there was no response bias produced 

by such human factors as over-familiarity with a particular scenario, fatigue, or particular expertise in a 

position by any individual.

Results

FFC achieved notable success in its replication 

of realistic LAX operations. Three types of measurements were used to validate the facility: controller ratings, aircraft data, and voice communication recordings. After each run, controllers rated their experience in terms of workload and realism. They judged 

workload in terms of the amount of coordination and 

communication required in comparison with the same 

task at LAX. Controllers rated virtual LAX workload as 

“about the same as LAX.” Controllers rated realism 

in terms of the operational efficiency, complexity, aircraft movements, radio communications, and sound 

effects. For all categories, controllers judged the simulation overall as “about the same as LAX.” Aircraft 

surface data --including arrival and departure rates, 

departure taxi times, and runway occupancy times--

also helped to validate the simulation. 

Investigative Team

NASA ARC

Raytheon

Los Angeles World Airports

FAA

VOLPE National Transportation Systems Center

United Airlines

Alaska Airlines

Southwest Airlines

American Airlines

Photograph of Local 1 Controller Position at FutureFlight 

Central, showing the LAX visual scene.
36 Aviation Systems Division

LAX Phase II

Boris Rabin, Cedric Walker, Betty Silva, Michael Madson, Marlene Hooten, NASA 

ARC; Elliot Brann, FAA; Jim McClenahen, Raytheon

Summary

The objective of the Phase II simulation was to 

evaluate six alternative changes to the airport surface, airport operations, or both, which could reduce 

the possibility of runway incursions at LAX. Two 

favorable alternatives were found during the course 

of the simulation.

Introduction

This study was the second in a series of 

runway incursion studies. In the Phase I Baseline 

Simulation, FFC demonstrated that its simulation 

was sufficiently representative of LAX operations and 

thus ready for further studies. The Phase II simulation evaluated several candidate airport changes 

designed to reduce runway incursion incidents, thus 

increasing airport safety. 

The objective of this study was to assess the 

impact of each candidate change on surface traffic, 

overall capacity, and controller workload. Tested conditions concentrated on redistributing surface traffic 

away from the congested South Complex “hot spots” 

associated with many runway incursions at LAX.

Simulation

Controllers were presented with a realistic environment to operate in the FFC tower the same way 

they would in the LAX tower. All operation alternatives 

were tested for two traffic conditions and under Visual 

Flight Rules: peak arrivals scenario, consisting of 92 

programmed arrivals and 78 departures; and peak 

departures scenario, consisting of 62 programmed 

arrivals and 107 departures.

Two groups of four LAX controllers worked several 

45-minute sessions over a three-day period for a 

total of six simulation days. Controllers were rotated 

by tower position to eliminate response bias produced by over-familiarity with any scenario, fatigue, 

boredom, or particular expertise in a position by any 

individual. 

Alternatives tested included swapping runways 

used for arrivals and departures, adding an additional 

local controller to help manage the south side of 

the airport, and variations utilizing the proposed B-16 

Taxiway Extension under different sets of procedural 

rules with or without an additional controller.

Results

Data from Phase I were compared with data from 

the alternatives of Phase II. These comparisons highlighted the strengths and weaknesses of the different 

alternatives as measured by airport efficiency, capacity, traffic flow, and controller workload.

The most favored two alternatives utilized the proposed B-16 extension. Controllers rated these alternatives as having the least potential for a runway 

incursion and as being safer in comparison with 

today’s LAX operations. Controllers gave the alternatives high marks for traffic management ease and 

efficiency. Departure rates (another measure of efficiency) were the highest of any of the alternatives.

It was equally important to discover which alternatives wouldn’t work. Adding a second controller to 

south side operations created workload and coordination problems between the local controllers. It 

was also regarded as unsafe. Although the alternative that involved swapping the runways for arrivals 

and departures reduced runway crossings, it also 

increased taxiway congestion. Consequently, this 

alternative could contribute to a different type of 

incursion in which landing aircraft occupy the runway 

longer due to congestion in the exit area. 

Frank Sweeney, Support Manager for the LAX 

tower, summed up the value of the simulation for the 

airport: “The NASA simulation was remarkably similar 

to LAX in real life.... Simply put: If we could not get it 

to work in the simplified NASA version of LAX airport, 

then it was clearly not going to work at real LAX. This 

saved the airport a lot of time (and money) in eliminating those untenable procedures and/or options.”

Investigative Team

NASA ARC

Los Angeles World Airports

FAA

Raytheon

United Airlines

Alaska Airlines

Southwest Airlines

American Airlines

This FFC view of LAX depicts the airport’s south side 

terminal area overlooking Terminals 6, 7 and 8. It is a 

heavy-traffic area for LAX’s major carrier, United Airlines. 
37 Aviation Systems Division

Surface Management System: First Simulation

Chris Brinton, Metron; Susan Lockwood, Seagull Technologies; Jim Hitt, Booz-Allen Hamilton; 

Deborah Walton, Mike Madson, Marlene Hooten, Boris Rabin, Ken Christensen, NASA ARC; Farid 

Haddad, Jim McClenahen, Christine Wong, Raytheon

Summary

The Surface Management System (SMS) is a decision support tool that will help controllers and air 

carriers manage airport surface traffic at busy airports. The goal of the first simulation was to evaluate 

the effectiveness of the SMS system at a simulated 

Dallas-Fort Worth airport.

Introduction

NASA Ames Research Center’s AATT Project, in 

cooperation with the FAA, is studying automation for 

aiding surface traffic management at major airport 

facilities. The Surface Management System is a decision support tool that will help controllers and airlines 

manage aircraft surface traffic at busy airports, thus 

improving safety, capacity, efficiency and flexibility. 

SMS will also interoperate with the airborne management of arrivals and departures to provide additional 

benefits.

NASA’s ultimate goal is to develop SMS to the 

point that it can be transferred to the FAA’s Free 

Flight Phase 2 program, the second phase of the 

FAA’s program to modernize the National Air Space 

through the introduction of new technologies and procedures.

FFC was designed as a test environment for the 

introduction of new technologies for air traffic control. 

The SMS display system utilized Dallas-Fort Worth’s 

East Tower operations to try out this new system 

within a realistic, working environment.

Two simulations of the SMS were planned. The 

first simulation, which is provisionally completed, 

utilized the SMS system integrated into the FFC 

facility; the second simulation will evaluate the next 

version of SMS, including Traffic Management Advisor’s (TMA) interoperation with SMS. (TMA assists 

TRACON and Center traffic management coordinators in flow management planning.)

Simulation 

Simulation conditions for Phase I included daytime 

operations in visual conditions with a south traffic 

flow and no ground vehicles. Each of the 45-minute 

scenarios was modeled from scheduled operations at 

8:00 a.m., 11:30 a.m., and 1:00 p.m. at DFW.

The FutureFlight tower cab was configured to 

match DFW’s East Tower layout with two local and 

two ground controller stations and hanging radar 

screens. Three SMS workstations were installed at 

the controller workstations, with an additional workstation at the center console for observers.

During the simulation, the tower was staffed with 

four controllers from DFW. The controllers’ positions 

were rotated for each scenario so as to avoid any 

response bias. During the simulation runs, a staff of 

18 “pseudo-pilots” controlled the aircraft traffic, as 

directed by controllers.

On the technical side, FFC’s simulation software 

delivered real-time aircraft updates (including aircraft 

ID, aircraft type, latitude, longitude, altitude, climb 

rate, on-ground/airborne status, heading, ground 

speed, and simulation time) to the SMS. The High 

Level Architecture interface, a feature developed by 

FFC, was the means for transferring the necessary 

data to the SMS software.

Results

The first simulation of the SMS was completed in 

September 2001. Each of three test conditions was 

run once. Input from controllers who utilized the SMS 

will influence the prototype to be tested in the second 

simulation. Stephen Atkins, NASA’s project lead for 

SMS, was “very satisfied” with the simulation.

“FFC allows the eventual users to experience SMS 

in a realistic environment. It’s not until controllers try 

using a [decision support tool] that they can provide 

the feedback needed to design a usable and useful 

product,” explained Atkins. Complete data analysis is 

pending.

Investigative Team

NASA ARC

Metron 

Seagull Technology

Booz-Allen Hamilton

Raytheon

FFC's depiction of the view from the East Tower at DFW 

with the SMS display at a controller workstation. 
38 Aviation Systems Division
39 Aviation Systems Division

 State-of-the-Art

Simulation Facilities

Providing advanced flight simulation capabilities 

requires continual modernization. To keep pace 

with evolving customer needs, SimLabs strives to 

optimize the simulation systems, from cockpits to 

computers to technology for real-time networking with 

flight simulators and laboratories in remote locations.
40 Aviation Systems Division

Rapid Integration Test Environment III

Summary

The vision of the RITE program is to merge 

advanced ITs in such a way as to make flight simulation an integral part of the design process when 

developing new systems. RITE III compared newer 

designs for a Crew Transfer Vehicle with the previously designed HL-20 vehicle and the Space Shuttle 

orbiter.

Introduction

The objective of the RITE program is to produce 

systems and infrastructure to facilitate the use of 

aerodynamics data developed using CFD technology 

in a real-time, piloted flight simulation. The subjective 

and objective flight simulation data will allow the 

design team to apply “return knowledge” from simulation to improve vehicle design and performance.

RITE is a multi-phase program. The first phase 

united separate aerodynamic disciplines to establish 

the infrastructure for rapid integration of CFD data 

into flight simulation. The second phase of RITE was 

an exercise to redesign the Space Shuttle’s nose. 

RITE application included increased data integration 

and fidelity, simulation flights of back-to-back cases 

with different geometries, the application of “return 

knowledge” by the design team, the development of 

system analysis data displays, and the enhanced use 

of VLAB to allow real-time system analysis between 

the multiple disciplines at different sites.

The goal of RITE III was to apply the process 

developed during the first two RITE phases to the 

preliminary design of a Slender Hypersonic Aerodynamic Research Probe (SHARP) Crew Transfer 

Vehicle (CTV). Specifically, RITE III compared newer 

designs for a CTV with the previously designed HL-20 

vehicle and the Space Shuttle orbiter. Additions to 

this phase included tool integration (for vehicle optimization) and control system optimization (to improve 

handling qualities of successive designs).

Project Description

A SHARP CTV geometry was designed, and a 

baseline aerodynamic model was developed using 

wind tunnel and CFD methods. A flight control system 

for the baseline SHARP CTV was designed using 

the HL-20 control system architecture and optimized 

using CONDUIT software.

After the baseline version of the CTV was finalized, 

geometries for other CTVs were developed to improve 

approach and landing performance. Improvements 

included using wing optimization techniques, control 

surface modifications/additions, and modifications to 

the wing sweep, dihedral, and camber. 

The baseline SHARP CTV’s stability, control and 

handling qualities were evaluated through real-time 

piloted simulations. Pilots’ comments were “returned” 

to the design team for rapid redesign of the aerodynamic model and control system. The revised designs 

were subjected to further pilot evaluations.

During the simulation, seven vehicles (five CTV 

versions, the HL-20, and the Space Shuttle) 

were flown. The pilots flew three tasks: straight-in 

approach, offset approach, and a 20-kt wind scenario.

Results

The RITE III simulation’s objectives of generating 

vehicle designs, aerodynamics, and flight control systems for a SHARP CTV were met. The designers 

increased their knowledge of which points and parameters were critical to generate a lifting body aircraft 

with satisfactory handling qualities. This first use of 

CONDUIT for RITE resulted in greater understanding 

of the control system design process and the tool 

itself. Pilots gave valuable feedback to both the aerodynamic design and control system groups for further 

study areas. VLAB use was extended beyond ARC 

to both Johnson Space Center and Marshall Space 

Flight Center; this will assist in future collaboration 

efforts between centers.

Development Team

Fanny Zuniga, Julie Mikula, Jorge Bardina, Susan 

Cliff, John Bunnell, Dave Kinney, Mary Livingston, 

NASA ARC; Chun Tang, Veronica Hawke, ELORET 

Corp; Joe Ogwell, John Bunnell, Dan Wilkins, Russ 

Sansom, Northrop Grumman IT

The SHARP CTV was modeled for RITE III.
41 Aviation Systems Division

Virtual Laboratory (VLAB)

Summary

VLAB is a suite of tools that extend the real-time 

flight simulation engineering and research capabilities of the VMS beyond the physical boundaries of 

the laboratory and onto the remote user’s desktop. 

With a VLAB client system, remote users receive and 

interact with live, real-time flight simulation experiments at the VMS. Currently, VLAB clients are supported at Ames Research Center, Johnson Space 

Center, and Marshall Space Flight Center.

Introduction

The VLAB client system features a fully-navigable 

3D replica of the VMS laboratory and includes the 

capability to move beyond the physical walls and ceiling to obtain a full-scale view of both the VMS and 

a mock-up of an interchangeable cockpit. Navigation 

in the 3D virtual space is accomplished via keyboard 

commands or a joystick. 

VLAB data displays include real-time strip chart 

displays, an end-of-run data monitor, data plots, and 

two-way white board text communication. Visual displays include the 3D laboratory environment (with 

either a full or orthogonal view of the VMS motion 

system), graphic representations of the OTW display, 

the chase-plane view, project and simulation engineer control panels, and a real-time Heads-Up Display. VLAB also provides stereo ambient sound and 

two-way voice intercom between the VMS lab and 

the remote client. Additional component systems are 

available for video conferencing, post-run data analysis, and multi-channel voice communication. 

Project Description

Initial development and implementation of the 

VLAB system was accomplished on a mid-range 

performance workstation. Today’s client systems are 

quickly progressing to desktop and laptop platforms. 

In addition to live client systems, a stand-alone demonstration version of the VLAB client system has 

been developed. Recently, both the client and server 

elements have been ported to laptop platforms. Wireless networking has been implemented on the Apple 

client platforms. This provides a truly “portable” client 

system. The server runs on a laptop PC under a 

Linux Operating System (OS). 

A number of client configurations have been developed and deployed for various research teams. The 

Space Shuttle client configuration is currently used by 

JSC researchers to participate in live experiments at 

the VMS lab twice annually. The RITE research team 

uses multiple VLAB clients at multiple remote locations to participate in the development of the RITE 

process. Currently, clients are supported at ARC, 

JSC, and Marshall Space Flight Center. The 2001 

implementation of RITE client systems will utilize multicast networking technologies to implement up to five 

remote clients at separate locations simultaneously. 

Future Plans

Future plans for the VLAB client suite include: 

further development of real-time plotting capability; 

extended use of multicast network transmission; continued investigation of wireless Local Area Network 

(LAN) technologies; enhancements to existing display elements; and multi-platform, multi-OS, PCbased client systems. The VLAB project will be investigating technologies that allow migration of the video 

conferencing, OTW visuals, and post-data reduction 

tools into the VLAB client interface. The goal is 

to integrate all four functional components into a 

single hardware platform controlled and operated 

from within the VLAB interface. 

Development Team

Russell Sansom, Chuck Gregory, Rachel Wang-Yeh, 

T. Martin Pethtel, Christopher Sweeney, Thomas 

Crawford, Kelly Carter, Dan Wilkins, Northrop Grumman IT; Thomas Alderete, Steven Cowart, Julie 

Mikula, John Griffin, NASA ARC

A typical VLAB display used by researchers.
42 Aviation Systems Division

VMS Modernization

Summary

The VMS Modernization project will upgrade all 

electrical and control elements of the VMS with stateof-the-art components. The upgrade will increase 

performance and reliability while decreasing maintenance and support efforts, contributing to continued 

cost-effective simulations for the aerospace community. The project is currently in the design phase, 

which is expected to be completed in winter 2001.

Introduction

The VMS is the largest amplitude flight simulator 

in the world and provides unparalleled high-fidelity 

motion. As the country’s premier motion-base flight 

simulator, it has been used extensively to support 

major national aeronautical research programs. Until 

recently, modern digital control technology was inferior to the analog control systems used on the VMS. 

However, recent advancements in technology have 

made replacing the original VMS system with “state 

of the art” digital systems beneficial, as these systems will reduce costs and enhance performance.

The primary objectives of the modernization effort 

are to reduce maintenance and operating costs and 

to improve motion performance. Completion of this 

project will keep the VMS at the forefront of flight 

simulation and contribute to continued cost-effective 

simulations for aerospace research and design.

Project Description

The project is divided into the following phases:

• Management Planning;

• Studies;

• Maintenance Requirements Documentation;

• Design;

• Procurement;

• Construction;

• Installation; and

• Testing and Verification.

The first four phases are complete, and team 

members are awaiting further funding. The image 

in this write-up depicts a computer rendering of 

the mechanical changes to the VMS, which include 

replacing the existing rack and pinion-driven gimbaled carriage system with a light-weight, tape-driven 

hexapod carriage. The project also plans to increase 

the number of vertical motors from eight to 

twelve. System performance, maintainability, reliability, safety, and cost are key factors being applied in 

the design process. This phase will be completed in 

winter 2001.

Future Plans

Purchase and fabrication of the new systems will 

begin in fall 2002, and installation of the equipment 

will begin in spring 2004. All new systems will be verified and proven operational on a test bed before final 

installation in the VMS. The thorough off-line testing 

will drastically reduce system integration and validation time; consequently, minimizing the unavailability 

of the motion system for active simulation use.

Development Team

Tim Gafney, Jeff Brown, Dean Giovannetti, Gary 

French, Khoa Nguyen, Steve Beard, Joel Baldovino, 

Paul Brown, Doug Greaves, George Wong, Rodger 

Mueller, Doug Smith, Bob Surratt, Charlie Ady, NASA 

ARC; Julie Murphy, Bechtel; Bill Manning, Dave 

Lawrence, Khalid Aram, Sverdrup; Ted Miller, Mike 

Blum, Johnny Chang, E&C Engineering; Bill Chung, 

Northrop Grumman IT

An extensive project at the VMS will modernize the motion 

simulator to increase reliability and maintainability.
43 Aviation Systems Division

Air Traffic Control for the VMS

Summary

This project’s objective was to support an SHCT 

program milestone of demonstrating the operability 

of a CTR in an ATC environment. The project integrated the ATC simulation elements with the VMS. 

This enabled full-mission studies of CTR operation in 

air traffic around the airport terminal area and assessment of tiltrotor impact on flight procedures and traffic 

capacity. The link developed by this project will allow 

the VMS and CVSRF simulators to jointly participate 

in large networked simulations.

Introduction

The ATC simulator, which currently resides in the 

CVSRF, has the capability to generate air traffic as 

well as control air space. The upcoming and current 

CTR simulations in the VMS require that the tiltrotor 

operate in an air traffic environment. Because ATC 

capability was not originally available to the VMS 

simulations, this project sought to integrate the ATC 

simulation elements with the VMS. This addition now 

provides a full mission environment/capability to the 

VMS.

The CTR researcher requested development of air 

space operations to demonstrate the tiltrotor’s operability under FAA normal approach and departure 

procedures. The request was phased: 1) demonstration of air space operations for the CTR 9 simulation 

(October 2000); and 2) full air space operations for 

the CTR 10 simulation (July-August 2001).

Project Description

The integration was completed in two phases: 

Phase I of the project developed the ATC environment capability for the VMS complex, which includes 

ICAB, RSIS, and the VMS labs. Integration of the 

ATC environment included real-time communications 

between the host computers and the PAS workstations, as well as voice communications with the controllers and other air traffic. For host communications, 

the High Level Architecture (HLA) protocol was used. 

The VMS host computer received data from PAS 

and displayed the traffic on the out-the-window visual 

system. Phase II completed the pilot’s interaction with 

the ATC environment, including communications and 

navigation.

Audio communication was provided by the 

Advanced Systems Technology, Inc. (ASTi), digital 

audio system. The audio system hardware was 

upgraded to the latest version to allow the use of 

Voicenet in all of the laboratories. Along with controller communications in the CVSRF, a simulation of 

ATIS was also provided.

The testing of the ATC for VMS project was accomplished in a two-week fixed-base simulation following 

the CTR-9 simulation in the year 2000. During the 

test, data from PAS generated in the CVSRF facility 

was transmitted using HLA to the Alpha host computer in the RSIS lab of the VMS complex. This 

data was graphically displayed by the ESIG 3000 

Image Generator as aircraft approaching and departing SFO. The data was also graphically represented 

in the cab on the navigation display as other aircraft 

in the area of the tiltrotor.

Results

A controlled airspace simulation was developed 

around SFO to demonstrate the tiltrotor’s operability 

in an ATC environment. Simulated traffic was generated by PAS from the CVSRF and sent to the 

VMS via a digital link. Real-time data communications between the host computers and PAS was 

established as well as driving and displaying aircraft 

on the out-the-window displays and navigation displays. ASTi audio voice communications and a running ATIS were established with the CVSRF. Integration between the PAS ATC lab in the CVSRF and the 

VMS lab was completed. 

Development Team

Ernie Inn, Marty Pethtel, Rachel Wang-Yeh, Emily 

Lewis, Phil Tung, Tom Crawford, Mike Izrailov, Joel 

Rosado, Dave Darling, Cary Wales, Northrop Grumman IT; Craig Pires, Tom Prehm, Joe King, ManTech; 

Dave Astill, John Griffin, NASA ARC

ATC simulation in progress.
44 Aviation Systems Division

Kaiser HMD and Head Tracker

Summary 

The purpose of this project is to integrate a commercial off-the-shelf Helmet-Mounted Display (HMD) 

and head-tracking system to support simulation of 

Forward-Looking Infrared (FLIR) sensor and a HUD 

for a Comanche helicopter visual display experiment 

at the VMS laboratory. Future use may include HUD 

symbology projected on the HMD with look-through 

capability onto the existing cockpit display systems. 

Introduction

The Kaiser “Proview 50 ST” HMD features stateof-the-art Liquid Crystal Displays (LCD) coupled with 

lightweight optical projection technology to deliver full 

color visual imagery to the pilot. Two LCD displays 

project high-resolution images through an overlapping optical package to deliver a continuous 29 ̊ (V) 

x 50 ̊ (H) Field-of-View (FOV) visual scene. Each 

LCD generates a full color, progressive scan with 

640 x 480 pixel resolution to create a 29 ̊ (V) x 38 ̊ 

(H) monocular display for each eye. The optical package then forms a bi-ocular virtual display with 50% 

overlap to create the continuous FOV. The pilot’s 

head movement is tracked by a Polhemus “Fastrack 

12” magnetic head tracking system. Feedback from 

the Polhemus head tracker is then used to move the 

imagery projected on the HMD. Integration of HMD 

and head tracking technology into the ICAB systems 

at VMS will add an important new dimension to the 

overall simulation capabilities of the VMS. 

Project Description

The project’s first challenge was to determine if the 

Polhemus magnetic tracking system would operate in 

an ICAB environment. A two axes jig was created 

and placed at the pilot’s eye point in FCAB. The 

magnetic transmitter/receiver pair was manually positioned to known angles in yaw and azimuth, while 

the serial feedback from the Polhemus system was 

monitored on a laptop computer. The transmitter was 

then manually rotated and pitched while monitoring 

the serial data stream. Initial testing indicated that the 

Polhemus tracking system would work in a fixed base 

ICAB. 

The next challenge was to merge the separate 

OTW scene and the HUD graphics into a single 

image on the HMD. [The OTW and HUD images 

have different formats since they are generated by 

different image generators (IG).] This was accomplished using a variety of video post-processing techniques. Once the images were successfully merged, 

the team set about the process of scaling the merged 

images to affect conformal image tracking between 

the HUD and OTW images. 

The final step involves static image tracking, and 

then dynamically driving the HUD and OTW images 

based on feedback from the head-tracking system. 

This element involves graphics, systems, network 

and simulation engineering support. 

Integration of the Kaiser HMD and Polhemus tracking system required support from all technical disciplines at SimLabs. The graphics team created the 

HUD display symbology and additional displays to 

support alignment and calibration of the HMD system. 

The network team integrated a serial communication 

link between the HUD IG and the head tracking 

system. Graphics programmers integrated the serial 

feedback to drive the HUD display symbology. Simulation engineers are taking the serial feedback from 

the HUD IG and using it to drive the OTW IG system. 

Project Status

The project is in the final stages of development. 

Once the displays can be driven satisfactorily from 

the head-tracking system, performance data will be 

gathered and documented to baseline the entire HMD 

system for current and future use. Completion is 

anticipated in the first quarter of 2002.

Development Team 

Dan Wilkins, Jeff Dewey, Tuan Truong, Shelley 

Larocca, Russ Sansom, Ed Rogers, Tom Crawford. 

Chris Murphy, Marty Pethtel, Kevin Jackson, Robert 

Morrison, Northrop Grumman IT

An off-the-shelf HMD will be used to support Comanche 

helicopter display experiments.
45 Aviation Systems Division

navigation facilities database, the navigation displays, 

and a portion of FMS was completed in the first 

phase of this project. Remaining database files and 

associated access routines involved in the latter three 

systems were addressed in the current development.

Project Description

FMS airport and runway databases not previously 

addressed in Phase I were modified to accept automated Jeppesen updates. The FMS software was 

also altered to support non-unique waypoints typically 

present in the navigation database. A special Control 

Display Unit (CDU) page was created to allow the 

pilot to select the desired waypoint when more than 

one waypoint with the same name is present. 

The EOS Graphic User Interface uses a database 

to reposition the aircraft to various airports. This database was previously hand-edited and is now generated by the new software.

The Flight Safety, Inc., Vital 8 visual system has 

the capability of building a generic airport if the 

runway length, width, type of lighting, and other 

parameters are provided. New software was written 

to incorporate the runway information for all of the 

airports in the continental United States and generate 

the desired airport with a runway that meets the 

criteria mentioned above.

Results

Greater efficiency has been achieved with the current upgrade. Previously, hours of tedious manual 

labor were required to identify, input, and verify 

changes made to the navigation aids and airports. 

Now, when the Jeppesen update is processed, the 

identification and entering of changes is done automatically, and verification usually shows no errors.

Development Team

David Brown, Northrop Grumman IT

Navigation Database: Automation

Summary

The purpose of the Navigation Database Automation Project was to automate the process of updating 

the airport and runway record database files for use 

by the Flight Management System in the ACFS.

Introduction

The navigation databases of the ACFS require 

periodic updates to reflect the changes in real-world 

operations. Jeppesen is the source for all the navigation data that is processed via CVSRF’s Navigation Database utilities. In the past, these files were 

manually updated, and the updates were localized to 

the specific area of interest for a given experiment. 

Recently, a phased development effort was undertaken to automate the processing of Jeppesen source 

data.

In the ACFS, there are separate databases for 

the following systems: navigation facilities, navigation 

displays, the FMS, the Experimenter Operator Station (EOS), and the visual system. Automation of the 

The ACFS navigation display.
46 Aviation Systems Division

FFC has a proprietary digital audio system for modeling communications for the controllers and pseudopilots, and it lacks an external network interface. 

The project team implemented an analog bridge 

solution between the ASTi systems and the FFC 

system. An ASTi sound system is now located in FFC 

and is interfaced with CVSRF’s ASTi systems via the 

second VLAN over a dedicated fiber link. The analog 

audio from the ASTi is patched into one of the communications stations in the FFC, and this provides 

basic audio connectivity between the two facilities.

The proof-of-concept experiment consisted of the 

747-400 and ACFS simulators in the CVSRF joining 

the existing FFC HLA Federation. Performance was 

determined by observation of aircraft behavior in the 

visual system of each simulator.

Results

All of the simulators used their respective LAX airport databases for the proof-of-concept experiment. 

Although there were minor alignment issues due to 

differences in the database origin points, the position 

of aircraft was acceptable. The motion of aircraft in 

simulations was more problematic. The CVSRF simulators have smoothing algorithms that limit discontinuities in aircraft appearance when HLA data is 

updated at 1 Hz; however, the FFC simulator does 

not have such a feature. This led to significant jumping in FFC aircraft position when the data was only 

updated once per second. At the end of the demonstration period, it was determined that the internal 

update of aircraft positions in the FFC simulator is 

done at 5 Hz. If the CVSRF simulators had been 

configured to send HLA data at the higher rate, the 

FFC performance may have been more acceptable.

Further investigation of interoperability issues will 

be undertaken, pending an upgrade to FFC’s simulation software. Additionally, a project has been initiated 

to evaluate the audio communications in all three 

SimLabs’ facilities and to investigate how the audio 

systems can be upgraded to improve the integrated 

simulation environment.

Development Team

Ronald Lehmer, T. Martin Pethtel, Thomas Prehm, 

David M. Brown, Diane Carpenter, Ghislain Saillant, 

Northrop Grumman IT; Fritz Renema, Jason Binstock, ManTech; Greg Pisanich, QSS Group Inc.; Ron 

Miller, Farid Haddad, Raytheon STX; Stefan Beaubien, Adacel Canada, Debbi Ballinger, Cedric Walker, 

NASA ARC; Claudine Herbelin, De Anza College

High Level Architecture to FFC

Summary

The physical network and software infrastructure 

were developed to interconnect the flight simulators 

in CVSRF with the airport surface operations simulator in FFC. The value of connecting the facilities for 

integrated simulations was demonstrated, and shortcomings of the current interface were exhibited.

Introduction

Integration of a high-fidelity flight simulation facility 

with simulations in the FFC, requires both facilities 

to exchange digital data about aircraft positions and 

behavior, as well as voice communications. This project provided the first opportunity to interface FFC with 

another simulation facility, the CVSRF, using the HLA 

interface.

Project Description

To facilitate the connectivity between FFC and 

CVSRF, the CVSRF fiber optic network was physically extended. Two Virtual LANs (VLAN) were established over the fiber optics link to logically separate 

HLA traffic from voice communications. Additionally, 

FFC implemented a gateway system that isolated the 

internal FFC network from external network traffic. 

The HLA gateway provided data to the CVSRF in 

multicast packets with an update rate of 1 Hz. A 

significant amount of effort was devoted to integrating 

and testing the HLA interface.

For the proof-of-concept experiment, two incompatible radio/intercom systems were bridged to integrate audio communications. CVSRF has a radio 

communications system patterned after ASTi sound 

modeling systems and can provide remote audio 

communications with Cisco Voice-over-IP routers. 

Virtual representation of the interaction between the FFC 

and CVSRF simulators.
47 Aviation Systems Division

Integrated Vehicle Modeling Environment Development

Summary

The Integrated Vehicle Modeling Environment 

(IVME) will provide a flexible simulation architecture 

in the ACFS to simulate and conduct experiments 

with various aircraft models. Currently, the ACFS is 

capable of simulating one type of aircraft: a generic 

B757-class transport.

Introduction

The IVME is a major effort to support Intelligent 

Flight Control (IFC) research goals. A primary requirement of the IFC researchers is the capability of integrating various aircraft models into a full-mission simulation environment. This would allow the researchers to develop and evaluate neural flight control strategies on a wide range of civil and military aircraft.

Project Description

The ACFS is currently a full-mission simulator representative of a generic B757-class of passenger 

transport aircraft. It has state-of-the-art avionics, 

including simulated flight displays and a Flight Management System.

The current aircraft model architecture utilized by 

the ACFS is functionally distributed. However, the 

IVME project required a further restructuring of model 

sub-systems into airframe-specific and generic subsystems. This was necessary in order to eliminate 

duplication of software while providing the multiple 

vehicle model implementation. The data interfaces 

between the airframe-specific subsystems and the 

remainder of the simulation components were generalized, thereby ensuring that the simulation provided 

by the new models would be compatible with all the 

other subsystems in the simulator.

There are three airframe models which will be 

initially supported for this project. They include the 

default ACFS 757-type airframe model, a C-17 

model, and a Vortex-Lattice-generated model. SimLabs has an existing C-17 model, and the Vortex-Lattice software will be provided by NASA Code IC. Both 

of these simulations will be modified to conform to 

the IVME generalized data interface definition. Within 

the airframe-specific model subsystems, each of the 

three airframe models will be allowed to preserve the 

structural differences of their native implementation. 

This approach will minimize the implementation effort 

by making use of a well-established code set.

At the end of the IVME development, basic aerodynamics, flight controls, engines, and ground handling 

systems will be fully integrated with the rest of the 

ACFS simulation systems. This will allow researchers 

to develop adaptive neural controllers to provide both 

the inner and outer loop control functions. This software will possibly provide the interface to the FMS 

and other higher level automation available in the 

default ACFS. The classic autoflight and autothrottle 

systems, therefore, will not be developed and integrated as part of the IVME effort. The existing C-17 

model software includes Fly-by-Wire flight controls 

with stability augmentation. These systems will be 

integrated only to serve as a reference for comparative studies of the neural flight controllers.

Results

The complex architectural restructuring of the 

IVME project is currently underway at the CVSRF. 

The flexible IVME architecture will greatly enhance 

the capabilities of the ACFS to simulate various aircraft models to support intelligent flight control and 

handling qualities research in the near term. With 

fully developed adaptive automation, the full-mission 

capabilities can be extended to the other types of 

airframes in order to support intermediate to longterm research goals.

Development Team

Ramesh Panda, Carla Ingram, Northrop Grumman IT

Neural Flight Control/IVME block diagram.
48 Aviation Systems Division
49 Aviation Systems Division

Acronyms

AATT ...................................................... Advanced Air Transportation Technologies

ACFS...................................................... Advanced Concepts Flight Simulator

ADRS ..................................................... Aeronautical Datalink and Radar System

ADS........................................................ Army Design Specification

AGI ......................................................... Airport Group International

AIAA ....................................................... American Institute of Aeronautics and Astronautics

AILS........................................................ Airborne Information for Lateral Separation

AOL ........................................................ Airspace Operations Laboratory

ARC........................................................ Ames Research Center

ASTi........................................................ Advanced Systems Technology Incorporated

ATC ........................................................ Air Traffic Control

ATM ........................................................ Air Traffic Management

ATIS........................................................ Automatic Terminal Information Service

AvSTAR.................................................. Aviation System Technology Advanced Research Program

B747....................................................... Boeing 747

BHT ........................................................ Bell Helicopter Textron

CATS...................................................... Crew Activity Tracking System

CDTI....................................................... Cockpit Display of Traffic Information

CDU........................................................ Control Display Unit

CFD........................................................ Computational Fluid Dynamics

CICT....................................................... Computing, Information, and Communications Technology

CRT........................................................ Cathode Ray Tubes

CSPA...................................................... Closely Spaced Parallel Approaches

CTR........................................................ Civil Tiltrotor

CTV ........................................................ Crew Transfer Vehicle

CVSRF ................................................... Crew Vehicle Systems Research Facility

DAG........................................................ Distributed Air-Ground

DFW ....................................................... Dallas-Fort Worth Airport

DI............................................................ Dynamic Inverse

DIMSS.................................................... Dynamic Interface Modeling and Simulation System

EFIS ....................................................... Electronic Flight Information System

EGPWS.................................................. Enhanced Ground Proximity Warning System

EOS........................................................ Experimenter Operator Station

ESIG....................................................... Evans and Sutherland Image Generator

FAA......................................................... Federal Aviation Administration

FB........................................................... Fixed-Base

FFC ........................................................ FutureFlight Central

FLIR........................................................ Forward-Looking Infrared

FMS........................................................ Flight Management System

FOV........................................................ Field-of-View

FY 01...................................................... Fiscal Year 2001

FY 02...................................................... Fiscal Year 2002

GPS........................................................ Global Positioning System

GPWS .................................................... Ground Proximity Warning System

Continued next page...
50 Aviation Systems Division

HAC........................................................ Heading Alignment Cone

HLA ........................................................ High Level Architecture

HMD ....................................................... Helmet-Mounted Display

HSCT...................................................... High Speed Civil Transport

HSI ......................................................... Horizontal Situation Indicator

HUD........................................................ Head-Up Display

ICAB....................................................... Interchangeable Cab

IFC.......................................................... Intelligent Flight Control

IFR.......................................................... Instrument Flight Rules

IG............................................................ Image Generator

ILS.......................................................... Instrument Landing System

IMC......................................................... Instrument Meteorological Conditions

INFPCS .................................................. Integrated Neural Flight and Propulsion Control System

IT ............................................................ Information Technology

IVME....................................................... Integrated Vehicle Modeling Environment

JSC......................................................... Johnson Space Center

JSHIP ..................................................... Joint Shipboard Helicopter Integration Process

KSC........................................................ Kennedy Space Center

LAN ........................................................ Local Area Network

LAWA ..................................................... Los Angeles World Airports

LAX......................................................... Los Angeles International Airport

LCD ........................................................ Liquid Crystal Display

LDA ........................................................ Localizer-Type Directional Aid

LNav ....................................................... Lateral Navigation System

MCP ....................................................... Mode Control Panel

MIT ......................................................... Massachusetts Institute of Technology

MTE........................................................ Mission Task Elements

NAP........................................................ Noise Abatement Procedure

NASA...................................................... National Aeronautics and Space Administration

NASA ARC ............................................. NASA Ames Research Center

NASA JSC.............................................. NASA Johnson Space Center

ND .......................................................... Navigation Display

NFCS...................................................... Neural Flight Control System

OEI ......................................................... One-Engine-Inoperative

OS .......................................................... Operating System

OSD........................................................ Office of Secretary of Defense

OTW....................................................... Out-The-Window

PAS ........................................................ Pseudo-Aircraft System

PC .......................................................... Personal Computer

PCA........................................................ Propulsion Control Aircraft

PFD ........................................................ Primary Flight Display

QI............................................................ Quickened Inverse

RCS........................................................ Radio Communications Simulation

RITE ....................................................... Rapid Integration Test Environment

Continued next page...
51 Aviation Systems Division

SAS ........................................................ Stability Augmentation System

SCAS...................................................... Stability and Control Augmentation System

SEATAC ................................................. Seattle-Tacoma International Airport

SFO........................................................ San Francisco International Airport

SGI ......................................................... Silicon Graphics, Inc.

SHARP................................................... Slender Hypersonic Aerodynamic Research Probe

SHCT...................................................... Short Haul Civil Tiltrotor

SimLabs ................................................. Simulation Laboratories

SMS........................................................ Surface Management System

SSV ........................................................ Space Shuttle Vehicle

STOVL.................................................... Short Take Off/Vertical Landing

TCL......................................................... Thrust Control Lever

TMA........................................................ Traffic Management Advisor

TOGA ..................................................... Take Off/Go Around

TRACON ................................................ Terminal Radar Approach Control

UCE........................................................ Useable Cue Environment

VAST ...................................................... Virtual Airspace Simulation Technology

VLAB ...................................................... Virtual Laboratory

VLAN...................................................... Virtual Local Area Network

VMS........................................................ Vertical Motion Simulator

VNav....................................................... Vertical Navigation

VOR........................................................ Very High Frequency Onmi-Directional Range

WOD....................................................... Wind-Over-Deck
52 Aviation Systems Division

A very brief description of the Aviation Systems Division facilities follows. More detailed 

information can be found on the world wide web 

at: http://www.simlabs.arc.nasa.gov

Boeing 747-400 Simulator

This simulator represents a cockpit of one 

of the most sophisticated airplanes flying today. 

The simulator is equipped with programmable 

flight displays that can be easily modified to 

create displays aimed at enhancing flight crew 

situational awareness and thus improving systems safety. The simulator also has a fully digital 

control loading system, a six degree-of-freedom 

motion system, a digital sound and aural cues 

system, and a fully integrated autoflight system 

that provides aircraft guidance and control. It is 

also equipped with a weather radar system. The 

visual display system is a Flight Safety International driven by a VITAL VIIIi. The host computer 

driving the simulator is the IBM 6000 series of 

computer utilizing IBM’s reduced instruction set 

computer technology.

The 747-400 simulator provides all modes of 

airplane operation from cockpit preflight to parking and shutdown at destination. The simulator 

flight crew compartment is a fully detailed replica 

of a current airline cockpit. All instruments, controls, and switches operate as they do in the 

aircraft. All functional systems of the aircraft are 

simulated in accordance with aircraft data. To 

ensure simulator fidelity, the 747-400 simulator 

is maintained to the highest possible level of certification for airplane simulators as established 

by the FAA. This ensures credibility of the results 

of research programs conducted in the simulator.

Advanced Concepts Flight Simulator

This unique research tool simulates a generic 

commercial transport aircraft employing many 

advanced flight systems as well as features 

existing in the newest aircraft being built today. 

The ACFS generic aircraft was formulated and 

sized on the basis of projected user needs 

beyond the year 2000. Among its advanced 

flight systems, the ACFS includes touch sensitive electronic checklists, advanced graphical 

flight displays, aircraft systems schematics, a 

flight management system, and a spatialized 

aural warning and communications system. In 

addition, the ACFS utilizes side stick controllers 

for aircraft control in the pitch and roll axes. 

ACFS is mounted atop a six degree-of-freedom 

motion system. 

The ACFS utilizes Silicon Graphics, Inc. (SGI), 

computers for the host system as well as graphical flight displays. The ACFS uses visual generation and presentation systems that are the 

same as the 747-400 simulator’s. These scenes 

depict specific airports and their surroundings 

as viewed at dusk, twilight, or night from the 

cockpit. 

ATC Laboratory

The Air Traffic Control environment is a significant contributor to pilot workload and, therefore, to the performance of crews in flight. Fullmission simulation is greatly affected by the realism with which the ATC environment is modeled. 

From the crew’s standpoint, this environment 

consists of dynamically changing verbal or datalink messages, some addressed to or generated 

by other aircraft flying in the immediate vicinity.

The CVSRF ATC Laboratory is capable of 

operating in three modes: stand-alone, without 

participation by the rest of the facility; single-cab 

mode, with either advanced or conventional cab 

participating in the study; and dual-cab mode, 

with both cabs participating.

Appendix

Simulation Facilities
53 Aviation Systems Division

Vertical Motion Simulator Complex

The VMS is a critical national resource supporting the country’s most sophisticated aerospace Research & Development programs. The 

VMS complex offers three laboratories fully 

capable of supporting research. The dynamic 

and flexible research environment lends itself 

readily to simulation studies involving controls, 

guidance, displays, automation, handling qualities, flight deck systems, accident/incident investigations, and training. Other areas of research 

include the development of new techniques and 

technologies for simulation and the definition of 

requirements for training and research simulators.

The VMS’ large amplitude motion system is 

capable of 60 feet of vertical travel and 40 

feet of lateral or longitudinal travel. It has six 

independent degrees of freedom and is capable 

of maximum performance in all axes simultaneously. Motion base operational efficiency is 

enhanced by the Interchangeable Cab (ICAB) 

system which consists of five different interchangeable cabs. These five customizable cabs 

simulate ASTOVL vehicles, helicopters, transports, the Space Shuttle orbiter, and other 

designs of the future. Each ICAB is customized, 

configured, and tested at a fixed-base development station and then either used in place for a 

fixed-base simulation or moved on to the motion 

platform.

Digital image generators provide full color 

daylight scenes and include six channels, multiple eye points, and a chase plane point of 

view. The VMS simulation lab maintains a large 

inventory of customizable visual scenes with a 

unique in-house capability to design, develop 

and modify these databases. Real-time aircraft 

status information can be displayed to both pilot 

and researcher through a wide variety of analog 

instruments, and head-up, head-down or helmet-mounted displays.

FutureFlight Central Research Facility

FFC is a full-scale airport operations simulator 

that has the look and “feel” of an actual air 

traffic control tower. It supports cost-benefit studies; provides a stable platform from which new 

requirements can be derived; enables information sharing among multiple users; and tests 

software performance, safety, and reliability 

under realistic conditions.

FFC can be configured to support subsystems 

that may exist in some airport facilities but not in 

others. The various operational uses of FFC are 

enabled by the flexibility of its modular design 

and adherence to open systems architecture. 

Using an open architecture allows technology 

insertion during design iterations and throughout 

lifecycle upgrades. 

The FFC ATC Tower Cab has full-scale consoles and functionally accurate computer displays that replicate controller position-specific 

equipment. FFC’s controller positions are interchangeable to accommodate any air traffic control tower configuration.
For additional information, please contact:

Tom Alderete

Chief, Simulation Planning Office

Aviation Systems Division

(650) 604-3271

E-mail: talderete@mail.arc.nasa.gov

or

Barry Sullivan

Chief, Aerospace Simulation Operations Branch

Aviation Systems Division

(650) 604-6756

E-mail: bsullivan@mail.arc.nasa.gov