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Safe and efficient training using flight simulation training devices (FSTD) is one of the fundamental components of training in the commercial, military, and general aviation. When compared with the live training, the most significant benefits of ground trainers include improved safety and the reduced cost of a pilot training process. Flight simulation is a multidisciplinary subject that relies on several research disciplines which have a tendency to be investigated separately and in parallel with each other. This paper presents a comprehensive overview of the research within the FSTD domain with a motivation to highlight contributions from separate research topics from a general aspect, which is necessary as FSTD is a complex man–machine system. Application areas of FSTD usage are addressed, and the terminology used in the literature is discussed. Identification, classification, and overview of major research fields in the FSTD domain are presented. Specific characteristics of FSTD for fighter aircraft are discussed separately.
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International Journal of Aeronautical and Space Sciences
Flight Simulation Training Devices: Application, Classification,
JelenaVidakovic1 · MihailoLazarevic2 · VladimirKvrgic3 · IvanaVasovicMaksimovic1 · AleksandarRakic1
Received: 12 May 2020 / Revised: 5 January 2021 / Accepted: 18 January 2021
© The Korean Society for Aeronautical & Space Sciences 2021
Safe and efficient training using flight simulation training devices (FSTD) is one of the fundamental components of training
in the commercial, military, and general aviation. When compared with the live training, the most significant benefits of
ground trainers include improved safety and the reduced cost of a pilot training process. Flight simulation is a multidisci-
plinary subject that relies on several research disciplines which have a tendency to be investigated separately and in parallel
with each other. This paper presents a comprehensive overview of the research within the FSTD domain with a motivation
to highlight contributions from separate research topics from a general aspect, which is necessary as FSTD is a complex
man–machine system. Application areas of FSTD usage are addressed, and the terminology used in the literature is discussed.
Identification, classification, and overview of major research fields in the FSTD domain are presented. Specific characteristics
of FSTD for fighter aircraft are discussed separately.
Keywords Flight simulation· Training devices· Ground trainers· Fighter aircraft
1 Introduction
A pilot training process generally relies on a number of
learning methodologies and training aids used within three
learning concepts: (1) theoretical studies; (2) training in
flight simulation training devices (FSTD); (3) live train-
ing. The purpose of flight simulation is to reproduce (on
the ground) the behavior of an aircraft in flight as sensed
by the cockpit crew members, so that they can, by flying
the simulator, develop, and maintain the skills necessary to
safely and efficiently operate the real aircraft and prove their
proficiency to examiner [1].
Over the last forty years, flight simulation has made a
major contribution to flight safety and became essential for
the operation of civil airlines and military organizations
[24]. Training with FSTD reduces the number of training
hours needed in the air for a student to reach a defined pro-
ficiency level; thus, reducing high costs of operating and
maintenance of a fleet of aircraft [5]. Flying a real aircraft
require coordination with numerous other services (e.g., air
traffic control and maintenance), and need of appropriate
weather and visibility conditions, which is avoided with
the use of FSTD [2]. In this sense, FSTDs contribute to the
reduction of time of the making-ready-pilot process. From
an environmental point of view, ground trainers represent a
much favorable alternative to training in aircraft [2].
Even though the first commercially built pilot ground
trainers emerged at the beginning of the last century [2], the
real use of flight simulation started in the military during
World War II [1, 2, 6]. After World War II through the late
1950s, flight simulation branched out from the military into
commercial aviation [6]. The significant number of different
aircraft in service and under development in commercial
aviation prompted the design and deployment of flight simu-
lation training devices that attempted to replicate the char-
acteristics of specific aircraft. The breakthrough in the flight
simulation industry came with computer development in the
1980s [2, 7], and since then, a significant transition has been
made from live training to ground trainers-based training.
Improvements in flight simulation technology and the data
acquired from flight tests provided by aircraft manufacturers
* Jelena Vidakovic
1 Lola Institute, Kneza Viseslava 70a, Belgrade, Serbia
2 Faculty ofMechanical Engineering, University ofBelgrade,
Kraljice Marije 16, Belgrade, Serbia
3 Institute Mihajlo Pupin (IMP), University ofBelgrade,
Volgina 15, Belgrade, Serbia
International Journal of Aeronautical and Space Sciences
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(with detailed aerodynamic and engine models for different
regimes within the flight envelope), together with some reg-
ulations and practices established by the regulatory authori-
ties, were instrumental for the mentioned advancement [2].
They contributed to the broader acceptance of flight simula-
tion in the military, which in many countries happened only
in the last decade of the twentieth century [8].
Flight simulation training devices are currently used for
the training of a cockpit crew, maintenance personnel, and
command and supervisory staff [1, 9, 10]. Flight simulation
has made a significant impact in the systems engineering
field including human factors research [3, 11, 12]. FSTDs
are used for flight training program design and development
[13], and accident investigations [1, 14].
Flight simulation is a multidisciplinary subject that relies
on several research disciplines, such as sensory perceptions,
motion actuation, visual image generation, human factors,
etc. This research tends to be investigated separately and in
parallel with each other. Overview studies and meta-analysis
on a certain aspect of FSTDs, for example on the value of
motion cueing, can be found in the literature; however, there
are no recent general-point-of-view overviews. Furthermore,
an inquiry of the literature shows that there is inconsistency
regarding the applied terminology for flight simulation train-
ing devices, which may add to the confusion during analysis
and application of the available research, and that there is
very little published material on classification and general
application of FSTDs.
This paper provides a comprehensive overview of the
research within FSTD domain with a motivation to con-
nect and highlight contributions from separate research
topics from a general aspect, which is necessary as FSTD
is a complex man–machine system. To perform general
research overview, it is important to establish clear termi-
nology which has been found to depend on the application of
FSTDs. Two main areas of usage of FSTDs have been identi-
fied, and the terminology used in the literature is discussed.
An overview of research is presented, classified into two
major research topics. Identification, classification, and over-
view of major research fields in the FSTD domain are pre-
sented. Herein, we consider ground trainers for fixed-wing
aircraft. Specific characteristics of FSTD for fighter aircraft
are discussed separately. Visual presentation describing the
structure of the paper is given in Fig.1.
2 Application, Terminology,
2.1 FSTD Application
Herein, we consider two main application areas of FSTD: (1)
training; and (2) system engineering (research). Graphical
representation of the major FSTD applications categories is
given in Fig.2, while the literature used in this Section is
systematically listed in Table1 according to areas of FSTD
Fig. 1 Visual layout of the paper structure
Fig. 2 FSTD application categories
Table 1 Application of FSTDs literature
Application References
General training and licensing
[13, 5, 9, 10, 13, 21, 22]
System engineering
Control research
Avionics design and validation
Aircraft stability
Human factors
Accident investigations
[1, 2325]
[2, 23, 27]
[1, 26]
[5, 9, 1113, 21, 2832]
[1, 14]
International Journal of Aeronautical and Space Sciences
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2.1.1 Training
Training is the basic purpose of FSTDs. FSTDs are used for
the training of a cockpit crew, maintenance personnel, [13,
15], and command and supervisory staff [1, 9, 10]. FSTDs
that provide duplication of actual equipment or systems are
employed for purposes like familiarization, acquiring proce-
dural and continuous control skills, learning part or whole-
task performance, and the practice of complete or segments
of missions [1, 5]. Simulators can recreate various locations,
weather (e.g., wind, turbulence, and visibility), equipment
failure [13], and provide training in extended flight enve-
lopes [1620]. FSTDs are particularly suitable for skill
decay-preventing recurrent training [21]. Flight simulators
are used for the purposes of personnel selection and licens-
ing [1, 22]. Multi-crew pilot license training recommenda-
tions for FSTD-based training for four different phases of
pilot training according to ICAO are described in [22].
2.1.2 System Engineering (Research)
Flight simulator training devices have been used for system
engineering research in aviation for more than 30years [23].
An overview of research shows that the usage of FSTDs in
the system engineering field can be classified into two major
groups: (1) aircraft and equipment design and validation and
(2) human factors in aviation.
Usage of FSTDs for aircraft and equipment design and
validation involves control research [1, 2325], aircraft
stability [1, 26], and avionics design and validation (e.g.
research prototypes of hazard sensors, weather condition
information processing systems, display concepts, etc.) [2,
23, 27].
Most of the human factor research in aviation is con-
ducted in FSTDs due to requirements for sophisticated
experimental designs and instrumentation, and high cost of
flights. Much of the research deals with cockpit or display
variables, which may not require actual flight [13]. Human
factors studies performed in FSTDs are given in [5, 9,
1113, 21, 2832].
2.2 Classification andTerminology
The term flight simulator (FS) is often used amongst the
researchers, various engineering and software specialist,
and enthusiasts. Survey of the literature shows that there
is inconsistency in the use of the term “flight simulator”,
as it may indicate a device that provides equipment, and
both visual and motion cues [33, 34], or a device that pro-
vides equipment and visual cues [2, 13, 32, 3537], or a
device that provides only equipment cues [1]. Significant
software on the verge of games is labeled as a flight simula-
tor, and even though many of this software is marketed as
entertainment, they are useful within some aspects of abini-
tio training [38, 39]. Inconsistency regarding the applied
terminology for FSTDs may add to the confusion during
analysis and application of the available research on the
flight simulation technology. In this section we address this
important issue.
When considering applied terminology within flight
simulation domain in the literature, it has to be taken into
consideration that, according to their main purpose there are
two categories of devices that simulate flight conditions on
the ground: (1) FSTDs used in training and (2) FSTDs used
in research, including high-end, advanced FSTDs [1, 40].
As a result of the wide acceptance of flight simulation
in training, classifications and terminology of FSTDs used
in training are strictly defined by regulatory authorities to
be used by certification bodies responsible for evaluation,
and qualification of FSTDs. International and national agen-
cies and association bodies, such as ICAO (international),
EASA (Europe), FAA (USA) [41], and others [42] define
strict guidance on how to qualify FSTDs. European Avia-
tion Safety Agency (EASA) defines flight simulation train-
ing device as any type of device in which flight conditions
are simulated on the ground, including (1) flight simulators
(FS); (2) flight training devices (FTD); (3) flight and naviga-
tion procedures trainers (FNPT); and (4) basic instrument
training devices (BITD) [43]. Other training device (OTD) is
defined as a training aid other than an FSTD which provides
for training where a complete flight deck/cockpit environ-
ment is not necessary [43]. In Table2, the interpretation of
FSTDs approved by EASA is given. An FFS does not have
to replicate all the physical aspects of flight but only com-
ply with minimum requirements approved by the qualifying
authority. In [43], the levels of FFS are A, B, C, D (from
lowest to the highest level, respectively), with defined mini-
mum requirements for visual, sound, and motion simulation
systems that also include flight controls (response to control
inputs), buffet simulation effects, wind shear, etc. The cur-
rent commercial FFS is mostly based on Stewart platform
presented in Fig.3. Upset prevention and recovery training
(UPRT) are required for 6DoF C and D levels of FFS in [43].
Presented classifications are not obligatory for FSTDs
used in research, and potentially may not be applicable for
a new type of FSTD. Some studies acknowledge three types
of FSTDs used in research: FFS, personal computer aviation
training devices (PCATD), and part-task trainers [1, 13].
Some motion platforms, such as high-end centrifuge-based
motion simulators, dedicated spatial disorientation trainers,
etc. that do not imply pilot control feedback would likely be
classified within FNPT category of [43]. However, FSTDs
categories [4143] are created primarily having in mind the
devices to train pilot handling skills or pilot and crew aircraft
system operations, and are not intrinsic for the mentioned
FSTDs that do not involve pilot control feedback.
International Journal of Aeronautical and Space Sciences
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3 An Overview ofResearch inFlight
Underlying technologies of flight simulation include math-
ematical modeling, real-time computing, motion actuation,
visual image generation systems, projection systems for vis-
ual cueing, etc. [2]. The correct mathematical model and/or
data on the characteristic features of the aircraft that together
describe the aircraft behavior in response to pilot inputs and
external disturbances may be obtained from theoretical anal-
ysis, wind tunnel measurements, and flight tests [1].
Research problems in FSTDs are usually investigated
separately, and there are few older date general point of view
studies. From an inquiry of the literature, we notice that
most of the research regarding flight simulation achievement
can be classified into two categories: (1) effective usage of
flight simulation technology; and (2) improvements in cue-
ing fidelity. Identified major research categories are graphi-
cally described in Fig.4 with a motivation to highlight and
connect contributions from separate research topics from a
general aspect. Literature used in this section is presented in
Table3, according to identified research areas.
3.1 Effective Usage ofFlight Simulation Technology
Despite the recent advances in flight simulation technology,
when considering the practical implications of integrating
simulation-based training, positive outcomes for time and
cost-effectiveness, factors that influence the overall justifica-
tion of FSTD use, are not always guaranteed [45]. Optimiz-
ing flight curricula to capitalize on the strengths of the avail-
able FSTDs of lower and higher fidelity is critical to flight
training [10]. There is considerable debate regarding the
influence of simulator fidelity on the effectiveness of FSTD
usage, particularly regarding the impact of motion [34, 40].
Table 2 Interpretation of FSTD classification requirements according to EASA [43]
FSTD type Flight deck/cockpit environment Simulation capabilities Equipment and software specifications Visual system Force cue-
ing motion
FFS A full-size replica of a flight deck/
cockpit of a specific type or make,
model and series of aircraft
Represents the airplane in ground and flight
Includes assemblage of all equipment.
Includes computer software programs
Required to provide an out
of the flight deck/cockpit
FTD A full-size replica of a specific
aircraft type’s instruments, equip-
ment, panels and controls
Represents the aircraft in ground and flight
conditions to the extent of the systems
installed in the device
Includes assemblage of equipment. Includes
computer software programs
Not required Not required
FNPT The flight deck/cockpit environment Represents an aircraft or class of aeroplane in
flight operations to the extent that the sys-
tems appear to function as in an aircraft
Includes assemblage of equipment. Includes
computer software programs
Not required Not required
BITD The student pilot’s station Provides at least the procedural aspects of
instrument flight for a class of aeroplanes
Not specified, likely use of screen-based
instrument panels and spring loaded flight
Not required Not required
Fig. 3 Stewart platform [44] with universal and spherical joints
International Journal of Aeronautical and Space Sciences
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Studies regarding simulator fidelity are inconclusive and, at
times, seemingly contradictory, with many asserting fidelity
does not affect training transfer while others affirm impacts
[34]. From a literature overview, it can be concluded that
the value of fidelity for pilot training depends on the level
of pilot proficiency [10, 34, 39, 4547].
There is a discrepancy in the nature of skills being
learned during abinitio compared to more advanced phases
of pilot training [39, 45]. It is said that the usage of high-
fidelity FSTD is cost-effective for advanced stages of com-
mercial and military pilot training, but to a lesser extent for
early abinitio phases [45]. Furthermore, it is argued that the
fidelity of a real-world flight environment may even detract
from, rather than enhance, the performance of a novice pilot
[48]. Determination of performance variables through iden-
tification and examination of aspects of the set task that are
critical for improving skills is necessary to establish efficient
training programs [49]. The inclusion of learning theories
is of great importance within general efforts to increase the
effectiveness of flight training programs, including FSTD-
based training, some of this research is presented in [5, 13,
21, 31, 36, 47, 48, 50]. The extent to which trained behav-
ior transfers between different environments (e.g., an FSTD
or an aircraft) is mostly influenced by the environmental
dependency of the applied skills [36]. Determination and
understanding of the nature of these environmental depend-
encies are essential for the effective use of flight simulation
technology. For this purpose, transfer-of-training experi-
ments (ToT) can be used. ToT is one of the few available
methods for direct evaluation of the effectiveness of simula-
tor-based training [36, 51]. To evaluate simulator effective-
ness, i.e., to calculate the amount of transfer, several formu-
las for transfer effectiveness ratio (TER) are developed [50,
52]. The variables that can be used to quantify the transfer
of training are for example the number of training sessions,
the total time necessary for training to criterion, the cost of
using a simulator versus the cost of actual flight, counts of
errors made while performing a task, etc. [52]. It is said that
the use of flight simulators is cost-effective if the TER is 0.2
or greater [15]. The incremental transfer effectiveness ratio
(ITER) is used as the indicator of the transfer effectiveness
of successive increments of training in the ground trainer
Besides the training purpose of FSTD, fidelity is an
important concept to be taken into account for the system
engineering applications of FSTD described in Sect.2.2,
Fig. 4 FSTD research classification
Table 3 Research on the topic
of flight simulation Research topic References
General review papers [1, 2, 5, 7]
The influence of cueing fidelity to effectiveness of training
[7, 10, 34, 39, 49]
[7, 3437, 46, 49, 5158]
Integration of flight simulation into training [10, 35, 39, 45]
Sensory perception
Role of human factors on integration of cues in FSTD
[1, 25, 63, 6572]
[60, 73]
Objective motion cueing fidelity analysis
Motion cueing for UPRT
Cybernetic approach
[64, 66, 86, 87, 89, 90]
[91, 93]
[1620, 8285]
[20, 25, 62, 88]
International Journal of Aeronautical and Space Sciences
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where it is necessary to select the right level of simulation
fidelity. Using high-fidelity FSTDs, the costs increase expo-
nentially, whereas the level of flexibility, i.e., the ease of
changing, integrating, and testing a prototype decreases [32].
3.1.1 Evaluation ofMotion Cueing Effectiveness
Motion cueing effectiveness is a major research interest
within investigations in the domain of effective usage of
flight simulation technology. Importance of platform motion
in FSTDs has been debated in the literature for more than
half of the century [3537, 46, 49, 51, 5358]. The main
drive for the studies regarding motion effectiveness in flight
simulation is the need for reduction of cost. Also, the use
of a motion platform with poor motion cues can produce
simulator sickness, and produce negative transfer of training
[59]. Some researchers argue that there are still no compre-
hensive guidelines for determining where and why motion
simulation is cost or time effective in pilot training [45, 49].
Nevertheless, regulatory training and civil licensing authori-
ties require motion (FFS) to be used for the advanced phases
of training [22]. Research shows that the presence of motion
cues adds to pilot acceptance and subjective preference for
motion, even while lacking the concomitant objective evi-
dence [46]. Motion is valuable for some aspects of system
engineering application of FSTDs, and for pilot licensing
using FSTDs [35, 60].
The value of motion cueing in training is said to be appli-
cation specific, and the meta-analytic approach proved to be
essential for determining the value of platform motion [35].
In motion simulators, two types of motion are differenti-
ated: motion related to pilot maneuvering (associated with
control actions, i.e., motion feedback), and motion related to
environmental changes or disturbance (cues associated with
motion due to wind shears, turbulence, or engine failure)
[35, 56]. The presence of disturbance cues is found impor-
tant for the transfer of training in [35, 49, 54, 56, 58]. The
bulk of studies [37, 49, 51, 53, 5557] found that maneuver-
ing motion does not necessarily contribute to the transfer of
training for fixed-wing aircraft. In other research, it is found
that motion feedback achieves the positive or bigger transfer
of training for novices [35, 51, 54], and that is required for
effective initial simulator-based training of skill-based man-
ual control [36]. In [46], it is found that for high-altitude stall
recovery and overbank recovery, motion improved results. In
[61], it is found that physical motion cues are immediately
useful for the disambiguation of the visual signal.
It is argued that one of the reasons for the continuing
controversy regarding platform motion value is the issue of
collecting convincing and generalizable evidence regarding
training effectiveness, which requires reliable and quantita-
tive data regarding trainees’ developing skills [62]. Besides,
numerous variables might influence the effectiveness of
motion cueing and impact on the observed effects, includ-
ing the presence and quality of the visual display, temporal
synchronization between motion and visuals, the quality
of auditory cues, the dynamic model and type of aircraft,
degrees of freedom of the motion system, duration and type
of training, measurement equipment used, calibration set-
tings and the motion cueing algorithm (MCA) [35, 59, 63,
3.2 Improvements inCueing Fidelity
Regarding improvements in cueing fidelity, two major
research fields can be identified: (1) sensory perceptions
and (2) improvement of motion cueing systems. Besides
advanced high-end FSTDs development, a survey of recent
research in the field of improvement of motion cueing sys-
tems points to the two current research interests: achieve-
ment of UPRT, and MCA development and evaluation.
1. Sensory perceptions
In piloted flight, vision is the primary sense used
within perception of motion. The non-visual (inertial)
human sensors that enable the simulation of motion in a
limited space of flight simulators are (1) the vestibular
system (semi-circular canals and the otoliths); (2) pres-
sure sensors (surface tactile receptors and deep pressure
sensors); and (3) proprioceptive and kinesthetic sensors
[1]. Auditory signals, such as engine sound or wind
noise also provide important indirect information on
self-motion that pilots use, especially during simulation
based on the vection [65]. The visual system of a flight
simulator is particularly effective in simulating motion
patterns that are relatively constant [63, 66]. Changing
motion patterns are the best perceived by vestibular
inner ear system and other proprioceptors that are spe-
cifically tuned to acceleration [67].
Flight simulators try to simulate motion trajectories
which are considerably larger than the actual range of
the physical simulator device [63, 66]. Larger range of
movement allows for more accurate acceleration cue-
ing; however, increasing the number of degrees of free-
dom and enlarging the movement range of the simula-
tor raises the costs of the device considerably [1, 66].
By using the investigations of the perception of self-
motion, researchers are oriented to the development of
techniques (e.g. acceleration onset cueing and angular
displacement of the platform to trade the gravity vector
for a perception of acceleration) to mimic the accelera-
tions that act on the body during self-motion in limited
motion space of ground trainers using human vestibular,
tactile, and visual systems combined to provide a con-
vincing perceptual illusion of motion [1, 35, 66, 67].
The quality of the motion cueing algorithm is directly
International Journal of Aeronautical and Space Sciences
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dependent on the implemented perception models for
self-motion, some of these models can be find in [25,
65, 66, 6870]. To avoid visual-motion cueing conflicts,
investigation of the perception of coherence zones in
flight simulation is performed, [71] and the influence of
motion perception thresholds is investigated [71, 72].
The effects of platform motion on the pilots’ perception
of specific aircraft maneuvers are investigated [69]. The
recent research on the role of human factors on the suc-
cess of integration of visual and inertial cues in FSTDs
is given in [60, 73]. The modeling of skill-based pilot
control behavior, a so called cybernetic approach [20,
25, 62] received attention lately.
2. Improvement of motion cueing systems
Conventional flight simulators are designed as a 6 DoF
parallel manipulator, also known as hexapod, or Stewart
platform [35, 44, 74]. Hexapods make up to 80% in training
devices that the FAA qualifies [46]. Besides Stewart plat-
form, FSTD with motion platforms of different kinematic
configurations have been developed. Notable examples
include: (1) centrifuge motion simulator (CMS), also known
as human centrifuge, which provides planetary motion [75,
76]; (2) Vertical motion simulator, which is uncoupled 6DoF
mechanism that consists of 4DoF platform mounted on a
2DoF large-amplitude platform [46, 77]; (3) Desdemona
simulator, a device that combines a centrifuge design with
six serial DoFs, and has the capability to translate along the
centrifuge radius, and capability to move up and down in
heave [78, 79]. These devices are capable of overcoming
some of the limitations of the hexapod motion platform;
however, the costs to procure and maintain such systems are
high so that the hexapods are still the most common choice
for training and evaluation of airline pilots requiring “full”
motion simulation [37, 80].
One of the significant factors that lead to loss of con-
trol (LOC) in flight, which has and continues to remain the
number one cause of passenger fatalities [18, 81], is the
entry of an aircraft into an upset, a situation in which an
aircraft unintentionally exceeds the parameters normally
experienced in line operations or training [18]. Generally,
it includes inappropriate pitch attitudes (greater than 25°
nose up or 10° nose down), bank angles (greater than 45°),
by flying in airspeed inappropriate for the flight conditions
[18]. One of the most important upsets to be recovered from
is stall. When exercising UPRT using the commercially
operated FFS-conventional hexapod type motion platform,
it has to be taken into account that (1) the motion envelope
of hexapod platforms is limited so that they are unable to
replicate the certain motion cues that occur during upsets
[16, 17] and sustained G-loads that accompany certain upset
recoveries [18]; (2) majority of the upsets and consequent
recovery events exceed the normal flight envelope, where
the aerodynamic model has not been developed or validated
[16, 18, 82]. Recent efforts to attain expanded aerodynamic
envelope for flight simulation in the realm of UPRT for air-
line pilots are presented in [8284]. Motion cueing strategies
for stall recovery training in commercial transport simula-
tors are presented in [17, 18, 20, 82, 85]. The study from
2013 [19] identified training tasks involved in UPRT which
require an upgrade of, or addition to existing FSTD, or an
extension of the FSTD’s aerodynamic model, whereas it is
suggested that some tasks that involve spatial disorientation
and G-load management should be performed on an air-
plane, or, alternatively, using special ground trainers.
MCA, commonly called the washout, is employed to
provide the best possible motion cues within the capabil-
ity of the simulator throughout the flight envelope [59, 86].
MCA modifies the simulated aircraft’s motion into simu-
lator motions that fit inside the simulator’s motion space,
and it incorporates filtering necessary to overcome the lim-
ited motion envelope of the motion base [86, 87], such as
frequency-independent scaling to reduce the overall mag-
nitude of the cued simulator motion, and high-pass filter-
ing to attenuate the low-frequency motion that is especially
difficult to replicate [88]. Within the design of a simulator
motion filter, human motion perception and control models
play crucial role [69]. On the other hand, pilots’ percep-
tion of the motion cues depends significantly on how well
MCA has been adjusted [59]. Different control strategies
have been employed within washout design, such as clas-
sical washout (still widely used in commercial simulators
[18]), optimal control, coordinated adaptive, model predic-
tive control, etc. [64, 78, 80, 86, 87, 89, 90]. MCA tuning
and evaluation [80, 87], up until recently, has been primarily
based on the subjective judgment of experienced pilots [59,
80]. Objective motion cueing test (OMCT), which compares
simulator response (including MCA, transport delays, and
motion platform dynamics) to the aircraft input signal, is
proposed recently and adopted as a part of the latest ICAO
criteria for qualification of FSTD [9193]. The OMCT was
recentlyadopted by the FAA, albeit without the fidelity cri-
teria for the OMCT [93]. Recent use of cybernetic approach
in validation of motion cueing algorithms developed for stall
recovery training is presented in [20], and for the purpose
of objective evaluation of flight simulator motion cueing
fidelity is given in [88].
4 Flight Simulation Training Devices
forFighter Aircraft
The expensive process of military pilot training is pre-
ceded by medical examinations, aptitude testing, and flight
screening [94]. The main goal of the fighter pilot training
process is to produce a combat-ready pilot at an affordable
International Journal of Aeronautical and Space Sciences
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cost within the shortest possible period. Owing to the high
cost of combat aircraft procurement and maintenance, air
forces worldwide struggle to preserve the combat readi-
ness of their pilots. Maintaining a high level of readiness
with smaller numbers of aircraft requires the efficient use
of alternative means of training, such as FSTDs [95]. In the
military, FSTDs are used for aircrewtraining andtesting,
and for airplane maintenance tasks [1, 96, 97]. Regarding
training, FSTD serves several functions: it provides cost-
effective training aid with reduced risk to flight crews, lesser
environmental impact, and better preservation of strategic
and tactical secrecy.
Military use of FSTD starts as a part of abinitio pilot
training and continues with advanced training, including
type conversion, and training for specific tasks like air-to-
air refueling, airborne surveillance, landing on a ship, land-
ing in woods/mountain, air-to-air combat [1, 9, 97]. Besides
avoiding high costs of operating and maintenance of aircraft,
the cost of deployment of expensive weapons on training
ranges is reduced. Today, the smallest unit that performs
air combat missions is the two-ship section (two aircraft),
which makes team coordination to be an essential part of
air combat [95]. For fighter aircraft pilots, FSTDs provides
an effective training aid for crew cooperation [2]. A mis-
sion rehearsal capability is introduced within FSTD, with
the flight crews enabled to operate in multi-aircraft forma-
tions [2, 98]. FSTDs have been used for the development
of aircraft avionics, including displays, flight management
systems (FMS), radars, warning systems and monitoring
systems [2].
While the commercial pilot’s job is to minimize turbu-
lence, overcome visual distractions and system failures, and
limit the effects on passengers and cargo, the combat-ready
fighter or strike fighter pilot has an entirely different mission:
to outlast his/her opponent in an often hostile and foreign
environment [81]. Defending and employing an aircraft,
especially in combat, requires high pilot skill levels [49].
Modern combat aircraft pilots are exposed to extreme flight
conditions in which the pilot’s ability to control the aircraft
is reduced. The scope of the EASA civilian FSTD is rela-
tively limited as it includes take off, land and cruise [99].
The technology of civil flight training is not appropriate for
all military training programmers [7]. In particular, (1) the
pilot of a fighter aircraft is not constrained to a forward-
looking windscreen, and (2) the sustained acceleration levels
that occur during turning maneuvers cannot be replicated in
hexapods [7, 74].
Hexapod devices cannot achieve sustained high-G load
that fighter aircraft pilots are subjected to (accelerations dur-
ing flight go up to 9g [76, 81]); however they are particularly
suitable for simulation of flight conditions with low G-load
values such as landing simulation where pilot response is
critically dependent on the fidelity of the visual and motion
cues provided by the simulator [100]. High G-load effects on
pilots include G-LOC (G-force induced Loss Of Conscious-
ness), neck injuries, vibration effects, reach envelope reduc-
tion, vestibular illusions, etc. [101]. Combat aircraft are lim-
ited in terms of the maximum level of G-load that they may
be exposed to for a specified period and must be returned for
maintenance if this maximum level is exceeded [75]. CMS
is a motion platform typically employed in the military for
simulation of high-G accelerations (transient and sustained).
It has one or more DoFs, and if it’s qualified by certification
bodies, it can fall into the category of FFS [108] or FNPT
[99], depending on the flight deck/cockpit environment. The
drawbacks regarding CMS usage are related to the high cost
of the procurement, usage and maintenance of the device
due to its large size. CMS requires very powerful motors to
achieve fast variation in acceleration in the gondola [100,
102104]. For any large FSTD, particular attention has to
be given to match the lags of the motion platform and the
visual system (including projection), to avoid the occurrence
of simulator sickness [7], and for this reason, visual cues are
often minimal within CMS.
Many military organizations in the past have opted to
use fixed-base simulators with a wide field of view visual
displays (e.g., hemispherical domes) [7, 49, 79]. Various
militaries make use of G-seats, or dynamic seats [55, 58],
where a pilot is subject to haptic pressure applied by mov-
ing the seat pan and sides to simulate forces on the body
during high-G maneuvers [7, 74, 105, 106]. These cues are
often combined with visual cues, and also with vibrations
to simulate high-frequency accelerations [7].
Dynamic flight simulator (DFS) is defined to be a cen-
trifuge operated as a flight simulator, i.e. driven by pilot
commands in the cabin in response to a perceived flight con-
dition [74, 100]. The critical problem in the achievement of
dynamic flight simulation is to obtain a required response
time of the simulator to a given change in control by the pilot
with a massive device and to avoid degrading the pilot’s per-
ception of flight caused by fast acceleration change artifacts
and vestibular Coriolis cross-coupling effect in centrifuges
[100, 107]. Flight simulation training devices that, through
the integration of a high-performance planetary motion cen-
trifuge with a gimbaled, flyable, cockpit module, are capable
of replicating G forces experienced in flight and achieving
flight simulation are also called continuous G devices (CGD)
in the literature [79]. Besides the potential for fully recreat-
ing flight environment for fighter aircraft, CGD can provide
UPRT training for civil FSTD operators. In the study [79],
existing examples of CGD are identified to be Desdemona
simulator [78, 79], GYROLAB series of spatial disorien-
tation trainers [79, 108], and Authentic Tactical Fighting
System (ATFS)-400 [79, 108].
Besides high values of sustained and transient G-load,
another major issue for fighter pilots is spatial disorientation
International Journal of Aeronautical and Space Sciences
1 3
(SD). SD is one of the main causes of fatal accidents in the
military (it accounts for 6–32% of major and 15–69% of fatal
military accidents [109]). As a measure of preventive against
the SD, research and regulatory bodies suggest training of
flight crew in aircraft, as well as in motion simulators to
procedures and techniques that enable them to recognize and
solve problems related to SD during the flight in civil and
military aircraft [4, 110112]. Training in motion simula-
tors is dedicated to teaching the pilot to recognize unusual
flight orientations, to train the pilot to adapt to them and to
persuade the pilot to believe in the aircraft instruments for
orientation, and not into his senses [111]. SD training for
fighter pilots is regularly used in military organizations [113]
however, there are very few standardized training procedures
for SD simulation and training [113]. The reason for this is
perhaps due to the fact that the environment in which SD is
likely to occur is difficult to define [113]. FSTD used for SD
training in military and civil aviation vary considerably from
small to large, from pure SD demonstrators, to full-flight
simulators [4, 79, 113].
Transfer-of-training studies are rare in the military
domain [53, 96, 97, 114116]. Research on the effective-
ness of the flight simulation for fighter aircraft pilots is pre-
sented in [6, 9, 15, 49, 96, 97]. Recent efforts to provide
pilot behavior models is given in [107]. Research into the
relative training benefits of fixed-base platforms, synergis-
tic platforms, and G-seats is given in [37, 53, 55, 58, 105],
however, a little research is presented lately [7]. Literature
used in this section is presented in Table4.
5 Conclusion
Over the last forty years, flight simulation has made a major
contribution to flight safety and became critical to the opera-
tion of civil airlines and military organizations for provid-
ing a cost-reduced pilot training process. Inthis paper, a
comprehensive overview of the available research within the
FSTD domainis presented. Training, and system engineer-
ing (research), recognized within this study as two major
application areas of FSTDs, are addressed. Terminology and
classification regarding FSTDs used for training and FSTDs
used for research are discussed. An overview of research
is given, classified into two categories: effective usage of
flight simulation technology, and improvements in cueing
fidelity. Motion cueing effectiveness is discussed sepa-
rately. Regarding improvements in cueing fidelity, a survey
of research identified two major research domains: sensory
perceptions, and improvement of motion cueing systems. An
investigation on the literature in the field of improvement of
motion cueing systems, besides advanced high-end FSTDs
development, points to the two current research interests:
achievement of upset prevention and recovery training, and
motion cueing algorithms development and evaluation. The
specificities of flight simulation for fighter aircraft are dis-
cussed separately, with benefits and drawbacks of typically
used motion platforms addressed. To achieve effective flight
simulation, simulation designers have to determine how
much and what kind of simulation fidelity is needed taking
training context into account, along with establishing and
implementing an optimized training syllabus to capitalize
on the strengths of the available FSTDs of lower and higher
Acknowledgements This research has been supported by the research
Grants of the Serbian Ministry of Education, Science and Technologi-
cal Development.
Funding This research has been supported by the research grants
of the Serbian Ministry of Education, Science and Technological
Availability of data and material Not applicable.
Code availability Not applicable.
Compliance with ethical standards
Conflict of interest The authors declare that they have no conflict of
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... Like some flight simulators [8,9,10] medical virtual environments provide a well-monitored and safe method of surgical staff training. Students and surgeons can learn new skills and training difficult and complex surgical procedures. ...
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Laparoscopic surgery is very popular medical intervention for diagnoses and treatment of same abdominal diseases. The procedures are performed using long thin tools that are inserted through a trocar in the human body. The surgeon orients the instruments by laparoscopic images displayed on a monitor. Environment is uncertain (highly dynamic) with limited work space. The surgeon must adapt to the instruments' specifics. Guiding such an instrument is difficult and requires a lot of training and practice. This article is related to early design of a mechatronic device prototype, which main target is training of surgical skills in medical students using concepts of Medical Mechatronics and Robotics, thus will be preparing future surgeons and advanced technologies will be introduced in Surgical area.
... Active G-training has the potential to provide a realistic platform where pilots can safely practice dangerous scenarios at a much lower cost [8,10]; G-suits or G-seats are an alternative [11,12]. Ref. [13] provides a comprehensive review of research carried out in Dynamic Flight Simulators (DFS) and its usefulness in various simulation scenarios. ...
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When coupled with additional degrees of freedom, centrifuge-based motion platforms can combine the agility of hexapod-based platforms with the ability to sustain higher G-levels and an extended motion space, required for simulating extreme maneuvers. However, the false and often nauseating sensations of rotation, by Coriolis effects induced by the centrifuge rotation in combination with rotations of the centrifuge cabin or the pilot's head, are a major disadvantage. This paper discusses the development of a motion filter, the Coherent Alignment Method (COHAM), which aims at reducing Coriolis effects by allowing small mismatches in the G-vector alignment, reducing cabin rotations. Simulations show that as long as these mismatches remain within a region where humans perceive the G-vector as 'coherent', the Coherent Alignment Zone (CAZ), the cabin angular accelerations can indeed be reduced. COHAM was tested in a high G-maneuver task with a fixed CAZ threshold obtained in a previous study. It was experimentally compared to an existing motion filter, using metrics such as sickness, comfort and false cues. Results show that sickness, dizziness and discomfort are reduced, making the centrifuge sessions more bearable. It is recommended to further improve the filter design and tuning, and test it with more fighter pilots.
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Goal: The purpose of the research is to apply a method of decision support to prioritize flight simulators of the Air Force Command in view of the country”s budget constraints in the defense sector. Methodology: The research was performed with the Analytic Hierarchy Process (AHP), associated with hypothesis tests to define the preference or equivalence relationships between the simulators. Data collection involved the support of 32 Air Force specialists with extensive experience in the chosen simulators. Results: The T-27 Tucano simulator was preferred, followed by the C-95M Bandeirantes and the C-105 Amazonas, which obtained statistical similarity to each other. In fourth place was the A-29 Super Tucano simulator. The two simulators that had the least preference were the F-5M Tiger II and the A-1 AMX, which achieved results that were statistically close to each other. Limitations: Any multicriteria decision aid technique embeds its features and limitations. This is not exclusive to AHP, although the consistency ratio is a differential in relation to other methods. The expert sample also reflects the preferences of a group, with reservations to the generalization of the results. Practical implications: The findings of this research can be used in practice, by assisting the Brazilian Air Force in applying its scarce financial resources to prioritize flight simulators. Originality / Value: The research is unique to the Brazilian Air Force, in particular to the Center that oversees flight simulators, and is also relevant in including hypothesis testing to AHP results.
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When coupled with additional degrees of freedom, centrifuge-based motion platforms can combine the agility of an hexapod-based motion platform with the ability of sustaining higher G- levels and an extended motion space. This combination of motion characteristics is required for realistic simulation of extreme flight scenarios. However, a false and often nauseating sensation of rotation, the so-called Coriolis effect, induced by the central yaw rotation, combined with the simultaneous rotation of the centrifuge cabin (passive Coriolis effect), or pilot’s head (active Coriolis effect), is the main disadvantage of any centrifuge-based motion platform. For this reason, the majority of human centrifuges are used solely as passive G-trainers in relatively short sessions. This paper discusses the development of a novel motion filter which aims to minimize the undesired Coriolis effects, by allowing for small mismatches in the alignment of pitch or roll coordination. Numerical studies showed that this Coherent Alignment Method (COHAM), is capable of reducing the angular accelerations, while constrained to operate within a region of coherent alignment, the Coherent Alignment Zone. In order to obtain data to construct the CAZ region, i.e., establish body tilt thresholds in pitch and roll, an experiment was carried out in the Desdemona motion simulator. Results show higher thresholds in pitch and also higher ambiguity in pitch perception. A follow-up study is planned to further develop and experimentally validate our novel, predictive motion filter, based on the established CAZ region.
Professionals such as medical doctors, aeroplane pilots, lawyers, and technical specialists find that some of their peers have reached high levels of achievement that are difficult to measure objectively. In order to understand to what extent it is possible to learn from these expert performers for the purpose of helping others improve their performance, we first need to reproduce and measure this performance. This book is designed to provide the first comprehensive overview of research on the acquisition and training of professional performance as measured by objective methods rather than by subjective ratings by supervisors. In this collection of articles, the world's foremost experts discuss methods for assessing the experts' knowledge and review our knowledge on how we can measure professional performance and design training environments that permit beginning and experienced professionals to develop and maintain their high levels of performance, using examples from a wide range of professional domains.
A development of a robot control system is a highly complex task due to nonlinear dynamic coupling between the robot links. Advanced robot control strategies often entail difficulties in implementation, and prospective benefits of their application need to be analyzed using simulation techniques. Computed torque control (CTC) is a feedforward control method used for tracking of robot’s time-varying trajectories in the presence of varying loads. For the implementation of CTC, the inverse dynamics model of the robot manipulator has to be developed. In this paper, the addition of CTC compensator to the feedback controller is considered for a Spatial disorientation trainer (SDT). This pilot training system is modeled as a 4DoF robot manipulator with revolute joints. For the designed mechanical structure, chosen actuators and considered motion of the SDT, CTC-based control system performance is compared with the traditional speed PI controller using the realistic simulation model. The simulation results, which showed significant improvement in the trajectory tracking for the designed SDT, can be used for the control system design purpose as well as within mechanical design verification.
BACKGROUND: Spatial disorientation (SD) remains a significant cause of accidents and near accidents. A variety of training methods have been used to assist pilots to anticipate the SD problem. The value of such training in the prevention of disorientation has been difficult to assess.METHODS: To study transfer of SD awareness training, we related reported incidents to the content and frequency of SD awareness training received. The questionnaire was completed by 368 out of 495 pilots; 189 currently flying fixed-wing, and 150 flying rotary-wing aircraft. On average, their age was 38, and they had 2466 flight hours on-type.RESULTS: Respondents gave high ratings for the importance of SD training and their awareness of SD, the latter being one of the training objectives. The amount of SD training received by respondents was positively correlated with ratings for appreciation and importance. Self-rated awareness was positively correlated with the number of reported SD experiences. Although the correlations were below 0.50, the results provide an indication that SD training is effective. In total, respondents reported 5773 SD experiences, 195 of them resulting in a serious risk for flight safety. Narratives of these serious events show that, in many cases, pilots managed their SD by carefully checking the flight instruments, and also by good crew coordination.DISCUSSION: The results of the survey provide some evidence, although based on subjective reports, for transfer of SD training. The results of the SD experiences can be used to improve the SD training in terms of content and frequency.Pennings HJM, Oprins EAPB, Wittenberg H, Houben MMJ, Groen EL. Spatial disorientation survey among military pilots. Aerosp Med Hum Perform. 2020; 91(1):4-10.
This article describes a flight simulator study to validate a new command control system for longitudinal load factor $n_x$ . The system is called nxControl and actuates thrust, speedbrakes, and wheel brakes that directly influence the total energy state of the aircraft. It aims at manually flying with higher precision and lower workload. After a brief overview of the functionality of nxControl and its cockpit interfaces, the key results of earlier proof-of-concept simulator studies are summarized. The focus lies on the comprehensive flight simulator study with 24 airline pilots to conclusively evaluate the complete system. The task was a highly demanding approach trajectory containing segmented-continuous-descent in gusty wind conditions, touch-down, deceleration, and taxi as well as engine failure at low altitude. With nxControl, the pilots achieved higher precision in airspeed and energy control with lower workload compared to conventional manual thrust control. In addition, nxControl achieved safety benefits in case of an engine failure.
The principles of aerodynamic modeling in the extended flight envelope, which is characterized by the development of separated flow, are outlined and illustrated for a generic transport airplane. The importance of different test techniques for generating wind-tunnel data and the procedure for blending the obtained experimental data for aerodynamic modeling are discussed. Complementary use of computational fluid dynamics simulations reveals a substantial effect of the Reynolds number on the intensity of aerodynamic autorotation, which is later reflected in the aerodynamic model. Validation criteria for an extended envelope aerodynamic model are discussed, and the important role of professional test pilots with poststall flying experience in tuning aerodynamic model parameters is emphasized. The paper presents an approach to aerodynamic modeling that was implemented in the project titled “Simulation of Upset Recovery in Aviation” (2009–2012), funded by the European Union under the Seventh Framework Programme. The developed poststall aerodynamic model of a generic airliner configuration for a wide range of angles of attack, sideslip, and angular rate was successfully validated by a number of professional test pilots on hexapod- and centrifuge-based flight simulator platforms.