Rodney O. Rogers1

Albert Boquet1

Cass Howell1

Charles DeJohn2

1

Embry-Riddle Aeronautical University

Daytona Beach, FL 32114

2

Civil Aerospace Medical Institute

Federal Aviation Administration

Oklahoma City, OK 73125

March 2009

Final Report

An Experiment to Evaluate Transfer of 

Low-Cost Simulator-Based 

Upset-Recovery Training

DOT/FAA/AM-09/5

Office of Aerospace Medicine

Washington, DC 20591

OK-09-0434-JAH

Federal Aviation

Administration
NOTICE

This document is disseminated under the sponsorship 

of the U.S. Department of Transportation in the interest 

of information exchange. The United States Government 

assumes no liability for the contents thereof.

___________

This publication and all Office of Aerospace Medicine 

technical reports are available in full-text from the Civil 

Aerospace Medical Institute’s publications Web site: 

www.faa.gov/library/reports/medical/oamtechreports


Technical Report Documentation Page 

1. Report No. 2. Government Accession No. 3. Recipient's Catalog No. 

DOT/FAA/AM-09/5 

4. Title and Subtitle 5. Report Date 

An experiment to evaluate transfer of low-cost simulator-based upset- March 2009 

recovery training 6. Performing Organization Code 

 

7. Author(s) 8. Performing Organization Report No. 

Rogers RO,1 Boquet A,1 Howell C,1 DeJohn C2 

9. Performing Organization Name and Address 10. Work Unit No. (TRAIS) 

 

11. Contract or Grant No. 

1

Embry-Riddle Aeronautical University 

Daytona Beach, FL 32114 

2

FAA Civil Aerospace Medical Institute 

P.O. Box 25082 

Oklahoma City, OK 73125 12. Sponsoring Agency name and Address 13. Type of Report and Period Covered 

Office of Aerospace Medicine 

Federal Aviation Administration 

800 Independence Ave., S.W. 

Washington, DC 20591 14. Sponsoring Agency Code 

15. Supplemental Notes 

 

16. Abstract 

Many air transport training programs provide simulator-based upset-recovery instruction for company pilots. 

However, apparently no prior research exists to demonstrate that such training transfers to an airplane in flight. 

We report on two-phase FAA-funded research experiment to evaluate upset-recovery training transfer. 

In two separate training/testing evolutions involving two different general aviation aircraft, participant pilots 

were trained using low-cost desktop flight simulation, then subjected to serious in-flight upsets in an aerobatic 

airplane. Their performance in upset-recovery maneuvering was compared with the performance of control 

group pilots who received no upset-recovery training. Data collected during both flight testing periods suggest 

that simulator-based training improves a pilot’s ability to recover an airplane from an upset. However, in the 

most important measure of upset maneuvering skills—minimizing altitude loss—trained pilots fell well short of 

the performance routinely achieveable by pilots experienced in all-attitude manuevering. 

We summarize prior related research, describe the experiments, present and analyze data collected during 

both flight testing periods, and advance recommendations for future upset maneuvering training. Although we 

conducted flight testing in a general aviation airplane, our research has important implications for heavy aircraft 

upset-recovery trainers. 

 

17. Key Words 18. Distribution Statement 

 

 

Airplane Upset-Recovery Training, Low-Cost

Flight Simulation, Training Transfer

Document is available to the public through the 

Defense Technical Information Center, Ft. Belvoir, VA 

22060; and the National Technical Information 

Service, Springfield, VA 22161 

19. Security Classif. (of this report) 20. Security Classif. (of this page) 21. No. of Pages 22. Price 

Unclassified Unclassified 18 

Form DOT F 1700.7 (8-72) Reproduction of completed page authorized 

iii

Contents

1. Prior Research. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

1.1 Calspan-Related Research. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

1.2 Centrifuge-Based Flight Simulation. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

1.3 Human Factors Considerations in Upset-recovery Training. . . . . . . . . . . . . . . . . . . . . . . . . . . 2

1.4 Low-Cost Simulation. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2

2. The Research Experiment. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2

3. Phase One Flight Testing. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

3.1 Upset Attitudes and Dependent Variables. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

3.2 Statistical Analysis. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

3.3. Interpretation. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

3.4 Potential for Improved Training. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5

4. Phase Two Testing. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5

4.1 Data Collection, Upset Attitudes, and Dependent Variables. . . . . . . . . . . . . . . . . . . . . . . . . . 5

4.2 Statistical Analysis. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6

4.3. Effect of Improved Training. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7

4.4. Possible Effect of Reduced Sample Size in the Nose-low Inverted Upset Results. . . . . . . . . . . 8

4.5. Limitations of Ground-Based Simulator Training. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10

5. Implications for Transport Type Airplanes. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11

6. Follow-On Research. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11

7. Endnotes. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12

8. List of Sources. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13

An Experiment to Evaluate Transfer of Low-Cost

Simulator-Based Upset-Recovery Training

An upset occurs when an airplane enters an unexpected attitude that threatens loss of control (LOC) and 

subsequent ground impact. For the years 1998 – 2007 

inclusive, LOC was the leading cause of hull losses and 

passenger fatalities in worldwide air transport operations, 

causing almost 25% of all crashes and nearly 40% of all 

fatalities.1

 During the years 1991 – 2000, statistics for 

general aviation (GA) accidents in the United States are 

similar, while in Australia LOC accounted for an even 

greater proportion of GA accidents and fatalities.2

Since LOC threatens both passengers and flight crews, 

as well as potential victims on the ground, many air 

transport training programs contain a module instructing 

pilots how to recover an airplane from an upset. However, 

the effectiveness of such training has not been demonstrated. We will report on a two-phase Federal Aviation 

Administration-funded research experiment designed to 

evaluate transfer of upset-recovery training conducted 

using low-cost flight simulation. We assess training effectiveness by means of in-flight upset-recovery testing 

in a general aviation airplane. In what follows, we:

Discuss prior research related to our experiment.

Describe the experiment.

Summarize previously reported results of Phase 

One flight testing.

Present and interpret results of Phase Two flight 

testing.

Construe the relevance of our results to air transport 

upset-recovery training.

Explain plans for future related research.

1. Prior Research3

We have found only a few research articles related to 

the transfer of simulator-based upset-recovery training. 

Several reports result from research at the Calspan In-Flight 

Upset Recovery Training Program in Roswell, N.M.4

 A 

second set of articles focuses on centrifuge-based flight 

simulators manufactured by the Environmental Tecton-

ics Corporation. A third group discusses human factors 

considerations in upset-recovery training. Finally, we are 

aware of just one article related to training transfer when 

upset maneuvering is taught using low-cost simulation.

1.

2.

3.

4.

5.

6.

1.1 Calspan-Related Research

Calspan provides in-flight simulator-based upsetrecovery training in a variable stability Learjet 25 modified 

to simulate the control characteristics of an air transport 

airplane. The Calspan Lear can simulate various accident 

scenarios that in the past have resulted in air transport 

upsets leading to uncontrolled crashes.

Gawron used Calspan’s Learjet to test five groups 

of airline pilots with varying degrees of upset-recovery 

training and/or aerobatics experience on a series of eight 

upsets, hypothesizing that pilots with more training 

and/or experience would outperform those with less. 

However, she found no significant difference among the 

performances of the five groups.5

Kochan used the Calspan Lear to examine the roles 

of domain knowledge and judgment in upset-recovery 

proficiency. Domain knowledge is specific knowledge 

about upset-recovery procedures. Judgment is the abil-

ity to analyze and learn from an in-flight upset-recovery 

experience. She tested four groups of participants on a 

series of three in-flight upsets. Statistical analyses revealed 

that judgment was a significant factor in successful upset 

recovery, especially when a pilot has low domain knowledge, i.e., when a pilot is not trained to proficiency in 

upset recovery.6

Kochan and Priest studied the effect of upset-recovery 

training in the Lear. They measured pre- and post-training 

pilot performance in recovering from a series of upsets. 

Statistical analysis indicated “a strong positive influence 

of the [Calspan program] on a pilot’s ability to respond 

to an in-flight upset.”7

Kochan, Breiter, Hilscher, and Priest surveyed retention of knowledge in Calspan-trained pilots. Although 

participants in retrospect “rated their ability to recover 

from loss-of-control situations as being greatly improved 

by the training,” most were unable to recall various specific 

details about upset-recovery maneuvering taught during 

their training.8

1.2 Centrifuge-Based Flight Simulation

The Calspan Learjet in-flight simulator allows pilots 

to experience upset maneuvering G forces that very 

few ground-based flight simulators can replicate. The 
Environmental Tectonics Corporation (ETC) of Southampton, Pennsylvania, manufactures centrifuge-based 

flight simulators capable of generating continuous G 

forces. Such simulators bring to ground-based upsetrecovery training a degree of realism unachievable even 

in Level- D simulators. Three ETC proprietary technical 

reports (available from Dick Leland at dletc@aol.com) 

detail the capabilities of the company’s current generation of centrifugal simulators.9,10,11 One drawback of 

such simulators, however, is that “if a pilot moves his 

head while under G in a centrifuge, strong feelings of 

disorientation (the Coriolis illusion) result because of 

the small rotation radius needed to create the G forces 

artificially.”12 In a related article on motion-based flight 

simulation, Szczepanski and Leland argue that “simulator 

data analysis suggests that motion cueing is necessary 

when training ab initio pilots or pilots who have lim-

ited or no experience in the particular flying task that 

is being trained.”13

Since upset maneuvering involves generating high G 

forces than many pilots have never experienced, it seems 

reasonable to wonder if a centrifuge-based simulator 

might not be more effective that low-cost or Level-D 

flight simulators for upset-recovery training. We return 

to this subject later.

1.3 Human Factors Considerations in Upsetrecovery Training

A number of papers examine the “surprise” or “startle” 

factor in aviation, an effect that can hinder a pilot’s ability 

to respond appropriately to an emergency situation such as 

an upset. Kochan, Breiter, and Jentsch (2004) found pilots 

often miss cues that might lead to avoiding an emergency 

that later arrives as a surprise.14 In a follow-on paper, the 

same researchers develop “a conceptual framework for 

the study of unexpected events in aviation.”15 Kochan, 

Priest, and Moskal use a model for the “cognitive process 

of surprise”16 to study “how an unexpected event can escalate to a loss-of-control situation.”They conclude that 

in-flight (as opposed to ground-based) simulator training 

may be necessary to teach pilots to deal adequately with 

their perceptual biases in processing information during 

a surprise upset.17,18 In a related paper, Kochan argues 

that a pilot’s response to unexpected events can be improved through cognitive flexibility training (to discourage 

formulaic and encourage flexible responses to surprise 

events), adaptive expertise training (to reinforce modified 

or new responses to surprise based on responses learned 

in previous expert training), and metacognitive training

(to teach pilots how to evaluate their mental processes 

in responding to surprise).19

1.4 Low-Cost Simulation

Roessingh (2005) studied training transfer from lowfidelity ground-based flight simulators to control of an 

actual airplane during aerobatic flight.20 Twoexperimental 

groups received ground-based instruction in aerobatic 

maneuvering using desktop flight simulators. The simulator syllabus was the same for both groups, but one 

experimental group’s simulator training was enhanced 

with a more “realistic layout of stick, rudder pedals, and 

throttle.” Then the two experimental groups and a control 

group received five hours of in-flight aerobatic training. 

Data collected during subsequent testing revealed no 

significant difference in the aerobatic maneuvering of 

experimental and control group pilots.

2. The Research Experiment

Our research seeks to determine if upset-recovery train-

ing in low-cost flight simulators develops flying skills that 

improve a pilot’s ability to recover from a serious upset 

in a real airplane. We hypothesize that pilots trained in 

upset recovery will outperform untrained pilots. To test 

this hypothesis, we train a group of participant pilots in 

upset-recovery maneuvering using Microsoft Flight Simulator (MFS),21 then subject both trained and untrained 

participants to a series of four upset situations in an actual 

airplane and collect data on their performance in recover-

ing the airplane to straight-and-level flight. Participants 

in our experiment are student pilots at Embry-Riddle 

Aeronautical University (ERAU) in Daytona Beach, 

Florida. All participants hold a current instrument rating 

and have completed an academic course in basic aerodynamics for pilots. None has prior aerobatic experience 

or upset-recovery training beyond that required for FAA 

flight certificates and ratings.

As reflected in Table 1, our experiment is a 2 x 4 repeated 

measures factorial. The first independent variable is degree 

of training and has two levels—trained and untrained. 

Trained participants receive ten hours of classroom upset 

training and ten hours of MFS upset-recovery training.22

Untrained participants—control group pilots—receive no 

classroom or simulator training. The second independent 

variable is upset attitude. It has four levels corresponding 

to the four upsets each participant is subjected to during 

flight testing. We categorize upset attitudes as nose-high 

or nose-low and as upright or inverted. An inverted attitude is one where the bank angle exceeds 90o

.

Flight testing subjects participants to upsets intended to 

simulate an airplane in cruise flight suddenly disturbed by 

an external force such as severe wind shear or very strong 

wake turbulence. Participants close their eyes while the 

safety pilot induces an upset, then—when instructed to 
do so—open their eyes and attempt to bring the airplane 

under control. If a participant pilot returns the aircraft 

to straight-and-level flight without verbal or physical 

assistance from the safety pilot, a recovery is successful; 

otherwise, it is unsuccessful.

We define a good upset recovery as one where a pilot 

respects aircraft operating limitations while returning the 

aircraft to straight-and-level flight with the minimum 

possible loss of altitude. Minimum altitude loss will 

result from:

Prompt and correct control and throttle inputs in 

response to an upset situation.

A high roll rate toward an upright attitude to orient 

the lift vector toward the sky.

Use of appropriate G forces (unloaded during low-speed 

or inverted rolls; high Gs in dive pullouts while avoid-

ing accelerated stalls) during upset maneuvering.

The dependent variables in our experiment are designed 

to measure these factors. Upset attitudes and dependent 

variables differ slightly between Phase One and Phase Two 

of our research because we used different test airplanes, 

with different instrumentation, in each of the two phases. 

This situation, however, does not constitute a design 

limitation: no data from Phase One testing were used in 

Phase Two analysis.

3. Phase One Flight Testing23

3.1 Upset Attitudes and Dependent Variables

We conducted Phase One flight testing in a Beech 

Bonanza airplane provided by the Calspan Flight Research 

Group. Table 2 indicates the initial attitudes and airspeeds 

associated with each of the four upsets. Nose-high upset 

airspeeds were set at 10 KIAS above VS

, the Bonanza 1 

G stall speed. Nose-low airspeeds were a maximum safe 

value taking into consideration the Bonanza never-exceed 

speed of 196 KIAS. Data values for dependent variables 

were derived from a flight data recorder and a video file 

produced from a camera focused on the Bonanza’s instrument panel. Table 3 shows dependent variables used in 

statistical analysis.

•

•

•

3.2 Statistical Analysis

During flight testing, we experienced difficulties with 

data collection hardware that resulted in lost or inaccurate 

data. In addition, we discarded data for upsets where the 

initial aircraft attitude and airspeed varied significantly 

from target values show in Table 2. Finally, we omitted 

data for 14 unsuccessful upset recoveries, six by trained 

participants and eight by control group participants. 

As a consequence, although we tested 28 trained and 

30 control group participants during 232 upsets, we 

produced reliable data for far fewer upsets, as shown 

in Table 4. Note that the table reflects the number of 

individual upsets with reliable data for each upset, not 

the number of participants with complete data sets for 

all four upsets.

Because unusable data resulted in too few complete data 

sets, a two-group repeated measures Multivariate Analyses 

of Covariance (MANCOVA) proved infeasible. Thus, we 

decided to analyze each upset separately to preserve a reasonable sample size. For each upset in order, we calculated 

the Wilks’ Lambda value. Since each analysis revealed a 

significant multivariate effect, we then used univariate 

ANOVAs employing the Bonferroni adjustment to assess 

the contribution of individual dependent measures. 

Table 5 records the mean and standard deviation (in 

italics) for each dependent measure. Bolding indicates 

a significant effect.

3.3. Interpretation

Statistical analysis implies a strong relationship between training in low-cost flight simulators and improved 

control responses during a serious upset situation in a 

real airplane. Trained pilots outperformed control group 

pilots in six of the nine dependent measures, reflecting 

a superior control of G forces during unloaded rolls and 

dive pullouts, an increased willingness to use large roll 

control inputs, and quicker throttle responses. The result 

was a tendency to return the aircraft to straight-and-level 

flight faster than control group pilots. In three dependent 

measures, however—seconds to first roll; rudder input; 

and, most notably, altitude loss—trained pilots never 

outperformed control group pilots.

Table 1. The 2 x 4 Factorial Design 

Upset Attitude (Repeated Measure) 

2 x 4 Factorial 

Nose-high 

Upright 

Nose-low 

Upright 

Nose-high 

Inverted 

Nose-low 

Inverted 

10 Hours Classroom / Simulator 

(Trained Group) Trained pilots Trained pilots Trained pilots Trained pilots 

Training

None (Control Group) Untrained pilots Untrained pilots Untrained pilots Untrained pilots
Table 5. Dependent Measures Means and Standard Deviations (Bolding = Significant Effect) 

Nose-Low Upright Nose-High Upright Nose-Low Inverted Nose-High Inverted Upset Trained Control Trained Control Trained Control Trained Control 

G Use in Dive 

Recovery 

3.13 

0.50 

2.50 

0.38 

1.88 

0.29 

1.36 

0.20 

3.49 

0.59 

2.92 

0.58 

2.56 

0.82 

2.00 

0.57 

Average G / 

Target G 

0.79 

0.13 

0.63 

0.09 

0.93 

0.14 

0.91 

0.12 

0.87 

0.15 

0.75 

0.20 

0.84 

0.15 

0.64 

0.16 

Unload G 1.37 

0.28

1.72 

0.34 

0.34 

0.26 

0.23 

0.20 

1.34 

0.52 

1.71 

0.63

0.52 

0.59 

0.66 

0.81 

Altitude Loss 918.26’ 

225.70’ 

1001.76’ 

223.53’ 

12.17’ 

188.39’ 

-119.38’ 

226.41’ 

1290.95’ 

371.82’ 

1243.68’ 

338.68’ 

563.18’ 

481.43’ 

538.95’ 

380.63’ 

Seconds to First 

Throttle 

2.13 

1.10 

3.12 

2.34 

1.91 

0.51

4.38 

5.25

1.57 

.51

2.74 

1.52 

2.45 

1.77 

4.79 

4.34 

Seconds to First 

Roll 

2.00 

0.85 

2.18 

1.01 

2.30 

1.11 

2.06 

0.99 

1.76 

0.94 

2.11 

1.56 

2.36 

0.85 

2.58 

1.68 

Seconds to 

Recover

5.96 

1.07 

8.18 

2.21 

11.08 

2.86 

12.31 

1.77 

7.43 

1.69 

8.32 

1.45 

9.14 

2.34 

12.00 

3.27 

Roll Input 24.22o

13.73o

17.18o

4.79o

63.30o

18.16o

46.38o

13.77o

25.67o

13.54 o

23.16o

9.60o

40.64o

20.44o

40.00o

18.46o

Rudder Input 0.18” 

0.12” 

.20”

0.15” 

0.91” 

0.28” 

.75”

0.58” 

0.33” 

0.24” 

0.23” 

0.20” 

1.05” 

0.58” 

0.79” 

0.76” 

Table 4. Group Size for Each Upset 

Upset 

Group Nose-High 

Upright 

Nose-Low 

Upright 

Nose-High 

Inverted 

Nose-Low 

Inverted 

Control 16 17 19 19 

Experimental 23 23 22 21 

Total 39 40 41 40 

Table 2. Levels of the Upset Attitude Independent Variable for Phase One Testing 

Upset Pitch Bank Airspeed Thrust

Nose-high Upright 60o Nose-high 15o Left Wing Down 70 KIAS Idle 

Nose-low Upright 30o Nose-low 75o Left Wing Down 120 KIAS Cruise 

Nose-high Inverted 60o Nose-high 135o Right Wing Down 70 KIAS Idle 

Nose-low Inverted 20o Nose-low 135o Left Wing Down 100 KIAS Cruise 

Table 3. Dependent Variables Used in Phase One Statistical Analysis 

Dependent Measures 

G Force in Dive Pullout 

Ratio of Available to Allowable G in Dive Pullout 

G Force Unloading during Rolls 

Recovery Altitude Loss in Feet† 

Time to First Throttle Response in Seconds 

Time to First Roll Response in Seconds 

Time to Recover in Seconds 

Use of Ailerons for Roll Authority in Degrees of Yoke Rotation 

Use of Rudder for Roll Authority in Inches of Rudder Pedal Displacement 

†Some nose-high upset recoveries resulted in small altitude gains, i.e., in negative altitude losses. 
While trained pilots applied larger roll imputs and 

controlled G forces better than untrained pilots, both 

groups used relatively small control inputs in comparison 

to those required for optimal recoveries. Minimum altitude 

loss results from high roll rates (achieved at low airspeeds 

by using both aileron and rudder) and from the prompt 

application of maximum available/allowable G during dive 

pullout. However, general aviation pilots are accustomed 

to the small control inputs required for straight-and-level 

flight or flight at small bank and pitch angles. Without 

prior aerobatic experience, pilots find it difficult to apply 

large control inputs during a high-stress upset situation. We 

term this tendency general aviation syndrome. An equally 

appropriate name for this hard-to-resist behavior would be 

straight-and-level syndrome, as it also appears to characterize 

professional pilots who lack aerobatic experience—most 

notably airline pilots undergoing upset-recovery training.24

This behavior was exhibited by trained participants to only a 

slightly lesser degree than untrained participants. We believe 

general aviation syndrome, which our training moderated 

but failed to overcome, explains why the superior control 

manipulations by trained pilots did not result in smaller 

altitude losses. The magnitude of trained pilot control 

inputs, though statistically significant in comparison to 

untrained pilot control input, was not close enough to 

optimal to result in an altitude loss difference. Moreover, 

as explained in Subsection 3.4, in some cases our train-

ing methods likely increased (rather than decreased) the 

altitude losses experienced by trained pilots.

3.4 Potential for Improved 

Training

During Phase One flight test-

ing, we identified areas where 

improved ground training might 

result in better pilot performance 

during flight testing. The first 

concerns the practice of leveling 

the wings before dive pullout, as 

opposed to performing a rolling 

pullout. If less than an optimal roll 

rate is employed to level the wings 

before applying high G, or if less 

than allowable G is applied dur-

ing pullout, a rolling pullout will 

decrease altitude loss. Second, the 

“standard” recovery technique for 

nose-high upsets, which involves 

inducing a steep bank angle to 

allow the nose to fall toward the 

horizon before leveling the wings, 

is not optimal for high thrust-toweight ratio airplanes. In high 

thrust-to-weight aerobatic airplanes, far less altitude loss 

results when a pilot rolls immediately toward a wings-level 

upright attitude while flying nose-high at full power “across 

the top” of a half-loop. This recovery technique mimics the 

final roll-out portion of an Immelman aerobatic maneuver. 

Third, more emphasis is required during training to help 

pilots overcome general aviation syndrome by using large 

control inputs. Simulator training should stress unloading 

fully during nose-low inverted rolls or when rolling at low 

airspeeds during nose-high upsets. It must also emphasize 

the use of large rudder as well as aileron inputs to increase 

roll rates at low airspeeds. Finally, it must stress the need to 

apply high G forces quickly during dive recovery once the 

lift vector is pointed toward the sky. In Phase One training, 

we were less than perfect in all four instructional areas.

4. Phase Two Testing

4.1 Data Collection, Upset Attitudes, and 

Dependent Variables

After repeated failed efforts to find a suitably instrumented contract aircraft, we decided to use the EmbryRiddle Super Decathlon aerobatic trainer for Phase Two 

flight testing. To collect data, we installed a battery-operated video camera focused on the Decathlon’s instrument 

panel. A high-resolution palm-size video recorder captured 

the camera’s output and cockpit voice communications. 

Figure 1 presents a screen capture of a video recorded 

during flight testing. We also installed an Appareo AHARS 

data recorder, an inexpensive battery-operated GPS-based 

Figure 1. Sample Decathlon Video Recorder Output 
system capable of recording aircraft position, altitude, 

airspeed, attitude (pitch and bank), G forces (x, y, and 

z), yaw angles (β), and similar parameters. However, this 

unit proved unreliable in aerobatic attitudes. As a consequence, we were able to obtain only G force data from it. 

Two factors prevented our installing a more sophisticated 

data recording system. One was the significant cost. The 

other is a prohibition against invasive instrumentation in 

an ERAU training aircraft.

Because we used the Decathlon rather than the Bonanza for Phase Two testing, we modified upset initial 

attitudes and airspeeds slightly from those used in Phase 

One. Table 6 reflects upset attitudes and airspeeds for 

Phase Two flight testing. Nose-high initial airspeeds 

were set 12 MPH above VS for the Decathlon, while 

nose-low airspeeds reflect a maximum safe value based 

on the Decathlon’s red line speed VNE of 200 mph. The 

principal change in attitudes is that we used 180o

 of bank 

(inverted wings-level attitude) for both of the inverted 

upsets. This change made it easier for the safety pilot 

to position the airplane in the prescribed attitudes, a 

challenging task significantly complicated by the fact 

that the Decathlon rear cockpit, where the safety pilot 

sits, has no flight instruments. The change was prudent, 

given the difficulty we experienced during Phase One in 

positioning the Bonanza accurately.

Table 7 details the six dependent measures we used to 

conduct Phase Two statistical analyses. Lacking a reliable 

flight data recorder, we were unable to collect data on 

rudder and aileron input that we obtained during Phase 

One.25 We consider the absence of these data points 

inconsequential, because rudder and aileron input are 

responsible for roll rate, and Phase One results established 

training transfer in using roll authority. In Phase Two, 

our main objective was to determine if improved training 

would result in significantly smaller altitude losses for 

trained pilots, compared with control group pilots.

4.2 Statistical Analysis

As a result of careful safety pilot training, we were able 

to position the Decathlon accurately for upsets and to 

collect complete data sets for 24 of 25 trained participants 

and for 25 of 26 control group participants. Average flight 

time for each group is shown in Table 8. Six trained pilots 

and eight control group pilots experienced unsuccessful 

recoveries during the nose-low inverted upset. In every 

case, the safety pilot took control in dive pullout to avoid 

exceeding the Decathlon’s red line speed. Data for these 

upsets are not included in our statistical analysis.

To compare trained and control group pilot performance, 

we conducted one-way MANOVAs for each of the four upsets using the dependent measures in Table 7. The resulting 

Table 7. Dependent Variables Used in Phase Two Statistical Analysis 

Dependent Measure

Maximum G Force in Dive Pullout

Minimum G Force Unloading during Rolls†

Recovery Altitude Loss in Feet: Negative Value = Altitude Gain 

Time to First Throttle Response in Seconds

Time to First Roll Response in Seconds

Time to Recover in Seconds

†Not applicable to the nose low upright upset, since trained pilots were taught to use rolling 

pullouts during dive recovery. 

Table 6. Levels of the Upset Attitude Independent Variable for Phase Two Testing 

Upset Pitch Bank Airspeed Thrust

Nose-high Upright 60o Nose-high 45o Left Wing Down 65 MPH Idle 

Nose-low Upright 45o Nose-low 70o Right Wing Down 130 MPH Full 

Nose-high Inverted 60o Nose-high 180o (Inverted, Wings Level) 65 MPH Idle 

Nose-low Inverted 20o Nose-low 180o (Inverted, Wings Level) 110 MPH Full 

Table 8. Flight Hour Data for 50 Flight-Tested Participants 

Group Group Size Mean Flight Hours Standard Deviation 

Control 26 160.5 54.0 

Experimental 25 201.2 85.9 

Combined 51 180.5 73.8 
Wilks’ Lambda values shown in Table 9 reflect a significant 

difference between the two groups in all four upsets. We 

then conducted ANOVAs with the Bonferroni adjustment 

for each of the dependent variables. Table 10 reports mean 

and standard deviation data for the post hoc analyses. Bolding in Table 10 indicates a significant difference. Figure 2 

presents information from Table 10 in graphical format. 

Table 12, which follows in Subsection 4.3, presents F values 

associated with significant effects in Table 10.

Two factors motivated our decisions to forego a more 

traditional 2 x 4 mixed-model analysis. First, because we 

eliminated data from unsuccessfully recoveries in the noselow inverted upset, a mixed-model analysis would have 

substantially reduced the sample size (cf. Table 9). This 

approach maintains consistency with our Phase One approach, where each upset was analyzed separately because 

data collection problems, as well as unsuccessfully recoveries, 

resulted in a small number of complete data sets (cf. Table 

4). Second, the nature of the upset data themselves argues 

against the direct comparisons that characterize a repeated 

measures MANOVA. For example, a nose-high recovery 

may lead to an altitude gain, whereas nose-low recoveries 

invariably result in significant altitude losses. Rather than 

compare “apples to oranges,” we opted for a more direct and 

operationally more relevant approach to data analysis.

4.3. Effect of Improved Training

As in Phase One, Phase Two statistical analysis confirms 

our hypothesis that low-cost simulator-based upset-recovery 

training improves pilot performance in recovering an airplane 

from a serious upset. However, Phase Two statistical results 

reflect a far more comprehensive training transfer than we 

detected in Phase One. Phase Two-trained pilots lost less 

altitude than control group pilots in all four upsets, and two 

of the four altitude differences were statistically significant. 

This result stands in vivid contrast to Phase One testing 

outcomes, where trained pilots actually lost more altitude than 

control group pilots in three of four upsets.26 We attribute 

this result to improved participant training, as described in 

Subsection 3.4 above.

The improved performance in altitude loss occurred 

because trained pilots initiated rolls toward a wings-level 

upright attitude sooner and applied more Gs in dive pullouts 

than untrained pilots, both critical factors in minimizing 

altitude loss. In addition, trained pilots also applied throttle 

more promptly than untrained pilots. These differences in 

turn resulted in a quicker return to straight-and-level flight. 

Excluding altitude loss, trained pilots were statistically 

superior to control group pilots in 14 of 19 categories, or 

73.7 % of the time. Including altitude loss, trained pilot 

performance exceeded untrained pilot performance in 16 of 

Table 9. Multivariate Wilks’ Lambda Values and Group Sizes for Each Upset 

Upset Nose-Low 

Upright 

Nose-High 

Upright 

Nose-Low 

Inverted 

Nose-High 

Inverted 

Trained Group Size n=25 n=25 n=19 n=24 

Control Group Size n=26 n=26 n=17 n=26 

Combined Group Size n=51 n=51 n=36 n=50 

Wilks Lambda Value 

F (5,45) =9.59

p = .0001 

Ș2 = .0.52 

F(6,44) = 4.47 

p = .001 

Ș2 = .38 

F (6,29) =9.11 

p = .0001 

Ș2 = .653 

F (6,43) =10.26

p = .0001 

Ș2 = .60 

Table 10. Dependent Measures Means and Standard Deviations (Bolding = Significant Difference) 

Nose-Low Upright Nose-High Upright Nose-Low Inverted Nose-High Inverted Upset Trained Control Trained Control Trained Control Trained Control 

Altitude Loss 

In Feet 

565.20 

75.28

728.46 

169.51

331.20 

225.56

340.38 

184.75

382.08 

200.65

464.62 

169.59

948.95 

167.03

1069.41 

139.08

Min Unload G 

in Rolls Not Applicable† 0.93 

0.14 

0.00 

0.12 

-0.47 

.28

-0.43 

.26

0.84 

0.15 

0.99 

0.86

Max G in Dive 

Pullout 

3.70 

0.64

2.90 

0.49

2.41 

0.90

1.82 

0.30

2.34 

0.45

2.34 

0.45

4.74 

0.62

3.98 

0.50

Seconds to 

First Throttle 

3.0 

1.66

5.19 

2.43

2.12 

1.62

3.27 

2.97

3.31 

3.21

3.31 

3.21

2.79 

1.78

4.41 

2.81

Seconds to 

First Roll 

1.28 

.46

1.85 

.68

2.28 

.89

3.15 

1.38

6.15 

2.98

6.15 

2.98

1.68 

.67

4.88 

3.30

Seconds to 

Recover

5.40 

1.38

7.04 

1.64

11.16 

1.43

12.88 

2.98

15.23 

2.27

15.23 

2.27

7.11 

1.29

7.88 

.99

† Not applicable to nose-low upright upset because trained pilots were taught to use rolling pullouts from dives. 
23 categories, or 69.6% of the time. This is in opposition 

to 16 out of 36 categories, or 44.4% of the time, in Phase 

One testing. These contrasts are presented in Tables 11 and 

12, where an “X” or an “F” value, respectively, indicates a 

significant effect.

4.4. Possible Effect of Reduced Sample Size in the 

Nose-low Inverted Upset Results

As previously explained, all 14 unsuccessful recoveries 

occurred during the nose-low inverted upset. Eliminating 

data from these unsuccessful upsets results in a sample size 

of 36, as opposed to a sample size of 50 when unsuccessful recoveries are included. Moreover, when data from 

the unsuccessful recoveries are included in an analysis 

of the nose-low inverted upset, the MANOVA and all 

six univariate Fs are significant. When it is excluded, the 

univariate differences for Minimum Unload G in Rolls and 

Seconds to Recover are no longer significant.

In Table 13, Ratio-A (All) is the ratio of a dependent 

measure control group average to the corresponding trained 

group average with data from all recoveries included. Ratio-S (Successful) is the same quotient computed for successful recoveries only. Eliminating data from unsuccessful 

recoveries has little effect on relative differences between the 

two groups, as reflected in the fact that Ratio-A divided by 

Ratio-S is in every case close to 1.0, and extremely close to 

1.0 in the two categories where loss of statistical significance 

occurs when unsuccessful recoveries are eliminated. We 

believe the information in Table 13 suggests that the loss 

of significance in Unload G and Time to Recover differences 

when unsuccessful recoveries are eliminated may be due 

primarily to the resulting reduced sample size.

Figure 2. Phase Two ANOVA Results in Graphical format (* = Significant Effect)
Table 11. Phase One Flight Testing Significant Effects (X) as Determined by 

Univariate Analysis (Rogers et al. [2007], p. 11) 

Upset Dependent 

Measure Nose-Low 

Upright 

Nose-High 

Upright 

Nose-Low 

Inverted 

Nose-High 

Inverted 

G Use in Dive Recovery X X X X 

Average G / Target G X X X 

Unload G X X 

Altitude Loss 

Seconds to First Throttle X X X 

Seconds to First Roll 

Seconds to Recover X X 

Roll Input X X 

Rudder Input 

Table 13. Comparison of Nose-low Inverted Upset Data with Unsuccessful Recoveries 

Included and Excluded (Bolding = Significant Difference) 

Dependent Successful + Unsuccessful Successful Recoveries Only 

Measure Trained Control Ratio-A Trained Control Ratio-S 

Ratio-A /

Ratio-S 

Altitude 

Loss

973.2 

158.9 

1088.1 

139.9 1.118 948.9 167.0 

1069.4 

139.1 1.127 0.992 

Minimum Unload 

G in Rolls†

0.86 

0.90 

1.33 

0.60 1.547 0.99 

0.86 

1.41 

0.63 1.424 1.086 

Maximum G Load 

in Dive Pullout 

4.20 

1.17 

3.40 

0.99 0.810 4.74 0.61 

3.98 

0.50 0.840 0.964 

Seconds to 

First Throttle 

3.08 

1.96 

4.76 

2.85 1.545 2.79 1.78 

4.41 

2.81 1.581 0.978 

Seconds to 

First Roll 

1.96 

1.40 

5.24 

3.29 2.673 1.68 0.67 

4.88 

3.30 2.905 0.920 

Seconds to 

Recover†

7.08 

1.15 

8.08 

0.95 1.141 7.11 

1.29 

7.88 

0.99 1.108 1.030 

†Indicates that the difference is significant when data from unsuccessful recoveries are included but loses 

significance when data from unsuccessful recoveries are eliminated. 

Table 12. Phase Two Flight Testing Significant Effect F Values as Determined by 

Univariate Analysis 

Upset Dependent 

Measure Nose-Low 

Upright 

Nose-High 

Upright 

Nose-Low 

Inverted 

Nose-High 

Inverted 

Altitude 

Loss

F(1,49) = 19.48

p = .0001 

F(1,34) = 5.45 

p = .03 

Minimum Unload 

G in Rolls 

Not 

Applicable†

Maximum G Load 

in Dive Pullout 

F(1,49) = 25.52

p = .0001 

F(1,49) = 10.11

p = .003 

F(1,34) = 16.02

p = .0001 

F (1, 48) = 8.912 

p = .004 

Seconds to 

First Throttle 

F(1,49) = 14.02

p = .0001 

F(1,34) = 4.38 

p = .04 

F(1,48) = 7.46 

p = .009 

Seconds to 

First Roll 

F(1,49) = 12.19

p = .001 

F(1,49) = 7.18 

p = .01 

F(1,34) = 17.16

p = .0001 

F(1,48) = 22.29 

p = .0001 

Seconds to 

Recover

F(1,49) = 14.82

p = .0001 

F(1,49) = 6.83 

p = .012 

F(1,48) = 10.90 

p = .002 

†Not applicable to nose-low upright upset because trained pilots were taught to use rolling pullouts 

from dives. 
10

If Unload G and Seconds to Recover were significant in 

the nose-low inverted upset recovery, then trained pilots 

would have been statistically superior to untrained pilots 

in 18 of 23 dependent measure categories, or 78.3% of 

the time.

4.5. Limitations of Ground-Based Simulator 

Training

Our research results also suggest the limitations of 

low-cost simulator training in developing upset-recovery 

maneuvering skills. MFS responses to control stick inputs 

are realistic near the middle of the Decathlon flight envelope (V-n diagram). Near the envelope’s available G line 

[αCRIT, (CL)

MAX], however, responses to control inputs tend 

to differ from the Decathlon’s behavior in actual flight 

situations. For example, if a Decathlon pilot inadvertently 

stalls the airplane with an aileron down, a departure from 

controlled flight may result. However, MFS does not 

simulate departures from controlled flight realistically. 

MFS also responds inaccurately during accelerated stalls 

in low-speed dive pullouts. To recover the actual airplane 

from such a stall, it suffices to momentarily relax back stick 

pressure a small amount, resulting in a slightly reduced G 

force. To recover the simulated Decathlon from the same 

accelerated stall situation, a pilot must unload completely 

to 0 Gs for a second or two. In such scenarios, the potential 

for negative training is significant.

During flight testing, imperfect participant pilot 

control inputs frequently resulted in a nose-high upset 

progressing into low-speed nose-low upset. Whenever 

this occurred, accelerated stalls and departures from 

controlled flight were common. MFS limitations may 

explain why these post-stall departures occurred so 

frequently and why there was a significant difference 

between trained and control group pilot altitude losses in 

nose-low upsets but not in nose-high upsets. Maneuver-

ing during high energy nose-low upsets occurs near the 

middle of the Decathlon flight envelope, where MFS 

control responses are reasonably accurate. By contrast, 

nose-high and low-speed nose-low maneuvering occurs 

near αCRIT and (CL)

MAX, where MFS control responses 

tend to be inaccurate. Moreover, required control inputs 

when maneuvering in high-speed nose-low upsets differ 

in degree, but not in kind, from control inputs general 

aviation pilots routinely use in non-aerobatic upright 

maneuvering. During nose-high upset maneuvering, by 

contrast, the proper control inputs differ radically from 

what general aviation pilots typically are accustomed 

to. As an example, efficient rolling in nose-high upsets 

requires a pilot to use large aileron and rudder inputs 

at maximum thrust while maintaining zero G at airspeeds approaching 0 mph. If any significant positive or 

negative G force is applied, a stall and departure from 

controlled flight may result. However, using elevator to 

maintain 0 G while applying large rudder and aileron 

inputs is something general aviation pilots never experience. As a second example, minimizing altitude loss 

in low-speed dive recovery by pulling out at the stall 

buffet (i.e., at or very slightly above αCRIT) is again an 

experience unfamiliar to general aviation pilots. Train-

ing in a flight simulator that responds inaccurately to 

control inputs in these and similar situations makes it 

difficult to prepare pilots to handle them adequately in 

a real airplane. It is conceivable that the pilot behaviors 

necessary to perform nose-high low airspeed precision 

aerobatic maneuvers can be rehearsed using MFS and 

similar low-cost flight simulators but can only be perfected in a real airplane.

Moreover, even when trained pilots significantly 

bettered control group pilots in altitude loss, their 

performance was far from optimal. For each of the four 

upsets, Table 14 presents Phase Two average altitude 

losses for trained and control group pilots. The bottom 

row of Table 14 reflects the minimum altitude losses 

that we observed for each upset during safety pilot 

training.27There is a large disparity between research 

participant altitude losses and the far smaller altitude 

losses achievable by experienced pilots. Low-cost flight 

simulator training clearly improves a pilot’s ability to 

recover an airplane from a serious upset. Just as clearly, 

however, it is prelude and complement to, not a substitute for, aerobatic experience in a real airplane. Whether 

a better flight simulator would produce a different result 

during flight-testing is an open question.

Table 14. Altitude Losses to Nearest Foot for the Four Upsets (Bolding = Significant Effect) 

Altitude Loss in Feet 

Data Source Nose-Low 

Upright 

Nose-High 

Upright 

Nose-Low 

Inverted 

Nose-High

Inverted 

Trained Pilot Average 565 331 949 382 

Control Group Pilot Average 728 340 1069 465 

Observed Minimums during Safety Pilot Training 220 -50 350 -30 
11

5. Implications for Transport Type

Airplanes28

Phase Two flight-test data reflect only a modest difference in performance between trained and untrained 

participants. It may well be the case that simulator-trained 

pilots need all-attitude flight experience in a real airplane 

to hone simulator-taught upset-recovery skills to an 

acceptably high level. It appears that during an initial 

upset-recovery experience, low-cost simulator training 

can help pilots overcome General Aviation Syndrome

only to a limited extent. Simulator shortcomings—for 

example, unrealistic control feedback, inaccurate accelerated stall responses, and the inability to replicate the 

positive and negative G forces that characterize all-attitude 

flight—limit a trainer’s ability to prepare a pilot mentally 

and emotionally for a real-world upset. As a result, any 

subsequent initial experience in a real upsets may appear 

strange and disquieting. In such a circumstance, a pilot 

easily loses situational awareness and instinctively resorts 

to old control input habits. Long-reinforced patterns of 

behavior and the significant stress of a serious upset tend 

to inhibit the application of new and relatively unfamiliar 

piloting skills developed during simulator training.

Our research findings seem to call in question the 

implicit assumption that airline simulator-based upsetrecovery training programs impart flying skills sufficient 

to make it probable that typical line pilots can recover 

an airliner from a serious upset. It is true that airline 

pilots, on average, are considerably more experienced 

than our research participants, hence may benefit more 

from upset-recovery training. However, air transport 

pilots' experience consists of hours of flying straight and 

level, punctuated by occasional excursions into very small 

bank and pitch angles. In addition, airline pilots typically receive only about four hours of classroom-based 

upset-recovery training and perhaps an hour of simulator training, in comparison to ten hours of each for our 

trained participants. Moreover, the primary advantage of a 

Level-D simulator over low-cost desktop flight simulation 

is limited to cockpit verisimilitude and realistic control 

forces. Typically, the motion of a Level-D simulator is 

disabled to avoid stressing the mechanism unnecessarily in 

upset-recovery maneuver. In any event, Level-D simulator 

motion is in no way realistic in all-attitude maneuvering, 

and neither Level-D nor low-cost desktop simulators can 

replicate the G forces that characterize upset-recovery 

maneuvering in a real airplane.

Thirty years ago, U.S. airline pilots typically came from 

military flight backgrounds where training afforded them 

extensive opportunity to perform aerobatic flight maneuvers. These pilots were routinely accustomed to all-attitude 

flight. For them, there were no unusual attitudes, only 

unexpected attitudes. By contrast, most air transport pilots 

flying today lack a military background and have never 

experienced the extreme pitch and bank angles and high 

G forces associated with severe airplane upsets. Indeed, 

most have never even been upside-down in an airplane. 

Informal conversations with current airline pilots suggest 

that while virtually all regard the upset training they receive 

as useful, a significant number also perceive it as a pro 

forma approach to a serious safety problem—better than 

nothing but far from what would be desirable if training 

costs were not a paramount consideration. In short, it 

seems unlikely that airline upset training is a completely 

acceptable substitute for all-altitude manuevering experience in a real airplane.

Upsets are known to be a primary cause of fatal commercial air transport accidents. Passenger and air crew 

safety considerations mandate that air transport pilots 

be able to recover from the infrequent but potentially 

catastrophic upsets, which inevitably will occur from 

time to time in air transport operations. Our research 

implies that aerobatic experience in a real airplane may 

be required to make recovery probable with minimum 

altitude loss. Since aerobatic experience cannot be obtained legally in transport type aircraft, perhaps the FAA 

should consider making aerobatic experience in a light 

airplane part of the requirement for a commercial pilot 

license and/or an ATP rating.

6. Follow-On Research

In August 2008, we commenced follow-on upset-recovery research in partnership with Dick Leland of ETC, 

lead researcher and financial sponsor of the project under 

an FAA grant. Twenty-five Embry-Riddle flight students 

received the same ten hours of classroom training that 

Phase Two trained-participants received. They received 

five hours of MFS training, then traveled in small groups 

to Pennsylvania to receive five hours of weekend upsetrecovery training in ETC’s proprietary centrifuge-based 

GyroLab-2000 flight simulator. ETC modified the 

GyroLab-2000 to give it the flight characteristics of a 

Super Decathlon airplane and to make its basic flight 

instruments replicate the layout on a Decathlon’s instrument panel.

When their GyroLab training was complete, in early 

November 2008, the 25 follow-on research participants 

underwent Decathlon flight testing identical to that 

received by Phase Two participants. Their performance 

in recovering from the four upsets will be compared with 

the performance of Phase Two-trained and control group 

pilots. The follow-on research is designed to determine 
12

the added value of upset training in a motion-based flight 

simulator capable of generating continuous G forces. We 

hypothesize that pilots trained in the sophisticated GyroLab-2000 simulator will outperform Phase Two-trained 

and untrained pilots in upset-recovery maneuvering. Table 

15 reflects the fact that the experimental design of the 

follow-on research is a 3x4 repeated measures factorial.

7. ENDNOTES

1. “Statistical Summary of Commercial Jet Airplane 

Accidents, World Wide Operations, 1959 – 2007.” 

Downloaded 20 July 2008 from www.boeing.

com/news/techissues/pdf/statsum.pdf. 

2. Rodney Rogers, Albert Boquet, Cass Howell, and 

Charles DeJohn (2007). “Preliminary Results of 

an Experiment to Evaluate Transfer of Low-Cost, 

Simulator-Based Airplane Upset-Recovery Train-

ing.” FAA Technical Report DOT/FAA/AM-07/27, 

Office of Aerospace Medicine, Washington, DC 

20591, p. 1.

3. This section reorganizes and condenses information 

presented in Rogers et al. (2007), pp. 2-4.

4. www.calspan.com/upset.htm.

5. Valerie Gawron (2004). Aircraft Upset Training 

Evaluation Report (revision 20). National Aeronautics and Space Administration (NASA): NAS2-

99070.

6. J.A. Kochan (2005). The Role of Domain Expertise 

and Judgment in Dealing with Unexpected Events.

Ph.D. Dissertation, Department of Psychology, 

University of Central Florida, Orlando FL, Summer 

Term 2005.

7. J.A. Kochan and J. E. Priest (2005). “Program 

Update and Prospects for In-Flight Upset Recovery Training.” Proceedings of the 13th International 

Symposium on Aviation Psychology, Oklahoma City, 

OK: Wright State University, 2005.

Table 15. The 3 x 4 Repeated Measures Factorial Design of the Follow-On Research Experiment 

Upset Attitude (Repeated Measure) 3 x 4 Factorial Nose-high 

Upright 

Nose-low 

Upright 

Nose-high 

Inverted 

Nose-low 

Inverted 

10 Hours Classroom / 5 Hours 

MFS +5 Hours GyroLab-2000 

GyroLab/MFS 

Trained Pilots

GyroLab/MFS 

Trained Pilots 

GyroLab/MFS 

Trained Pilots 

GyroLab/MFS 

Trained Pilots 

10 Hours Classroom / 10 Hours 

MFS Training

MFS Trained 

Pilots

MFS Trained 

Pilots

MFS Trained 

Pilots

MFS Trained 

Pilots

Training

None 

Control Group Pilots Untrained Pilots Untrained Pilots Untrained Pilots Untrained Pilots

8. J.A. Kochan, E. Breiter, M. Hilscher, and J. E. 

Priest (2005). “Pilots’ Perception and Retention 

of In-Flight Upset Recovery Training: Evidence 

for Review and Practice.” Proceedings of the Human 

Factors and Ergonomics Society 49th Annual Meeting, 

Orlando, FL: 26-30 September 2005.

9. Environmental Tectonics Corporation. “ATFS-400 

Authentic Tactical Flight Simulator Model 400 

Executive Summary.”

10. Dick Leland, Curt Spenney, Tammy Chelette, 

and Ernie Lewis (2003). “Opportunities in Flight 

Simulation: Tactical Flight Simulation.”

11. Zulkeffeli Mat Jusoh and Dick Leland (2006). 

“Tactical Flight Simulation in the Royal Malaysian 

Air Force: The ATFS-400 Authentic Tactical Flight 

Simulator.”

12. Ian W. Strachan (2001). “Motion Cueing in the Real 

World and in Simulators: Principles and Practice.” 

Janes Simulation and Training Systems 2000-2001, 

pp. 149-75.

13. Cezary Szczepanski and Dick Leland (2000). 

“Move or Not to Move? A Continuous Question.” 

Southampton, PA: Environmental Tectonics, 200l. 

2000 ETC, published by the American Institute 

of Aeronautics and Astronautics with permission 

(AIAA Paper 0161). Copy provided by the second 

author.

14. J.A. Kochan, E.G. Breiter, and F. Jentsch (2004). 

“Surprise and Unexpectedness in Flying: Database 

Reviews and Analysis.” Proceedings of the Human 

Factors and Ergonomics Society 48th Annual Meeting, 

New Orleans, LA: Human Factors and Ergonomic 

Society, 2004.

15. J.A. Kochan, E.G. Breiter, and F. Jentsch (2005). 

“Surprise and Unexpectedness in Flying: Database 

Factors and Features.” Proceedings of the 13th International Symposium on Aviation Psychology, Oklahoma 

City, OK: Wright State University, 2005.
13

16. Based on Kochan (2005).

17. J.A. Kochan, J.E. Priest, and M. Moskal (2005a). 

“The Application of Human Factors Principles to 

Upset Recovery Training.” 50th Annual Corporate 

Aviation Safety Seminar,” Orlando, FL: Flight Safety 

Foundation and National Business Association, 

26-28 April 2005.

18. J.A. Kochan, J.E. Priest, and M. Moskal (2005). 

“Human Factors Aspect of Upset Recovery Train-

ing.” 17th Annual European Aviation Safety Seminar,” Warsaw, Poland: Flight Safety Foundation 

and European Regions Airline Association, 14-16 

March 2005.

19. J.A. Kochan (2006). “Human Factors Aspects of 

Unexpected Events as Precursors to Unwanted 

Outcomes.” 18th Annual European Aviation Safety 

Seminar, Flight Safety Foundation and European 

Regions Airline Association: Athens, Greece, 13-15 

March 2006.

20. Jan J.M. Roessingh (2005). “Transfer of Manual 

Flying Skills from PC-Based Simulation to Actual 

Flight—Comparison of In-Flight Data and Instructor Ratings.” The International Journal of Aviation 

Psychology, 15 (1), 67-90.

21. The United States Navy uses Microsoft Flight 

Simulator in both basic and advanced flight train-

ing of student Naval aviators.

22. Training materials may be viewed at http://faculty.

erau.edu/rogersr/as471.

23. Rogers et al. (2007). pp. 8-14.

24. Two authors of this paper—Rogers and Howell—

have attended upset training at four legacy airline 

companies. At each, trainers remarked of the difficulties they experienced in persuading line pilots 

to use full-yoke deflection when rolling a Level-D 

simulator in an inverted upset to an upright, wingslevel attitude.

25. In addition, we did not compute use of available 

G in dive pullout, since this information indirectly reflects the maximum G force applied in 

the recovery.

26. Compare the altitude loss data in Table 10 with the 

altitude loss data in Table 5.

27. The values in the last row of Table 14 are not losses 

produced by optimal recoveries, a subject we have 

not pursued systematically. They merely reflect the 

minimum altitude losses we recorded during Phase 

Two safety pilot training with experienced pilots 

maneuvering the Decathlon out of an upset. 

28. Portions of this section are closely paraphrased or 

transcribed verbatim from Rogers et al. (2007), 

p. 16.

8. List of Sources

Boeing Aircraft Company. “Statistical Summary of 

Commercial Jet Airplane Accidents, World Wide 

Operations, 1955 – 2006.” www.boeing.com/news/

techissues/pdf/statsum.pdf.

Gawron, Valerie (2004). Aircraft Upset Training Evaluation Report (revision 20). National Aeronautics 

and Space Administration (NASA) NAS2-99070. 

(Airplane Upset Training Evaluation Report, February 25, 2002, National Aeronautics and Space 

Administration (NASA) NAS2-99070 is an earlier 

version of this research report.)

General Aviation Fatal Accidents: How Do They Happen? 

A Review of General Aviation Accidents 1991-2000

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