pilot performance and heat stress assessment...

PILOT PERFORMANCE AND HEAT STRESS ASSESSMENTSUPPORT USING A COCKPIT THERMOREGULATORY

SIMULATION MODEL

Jörg Schminder∗ , Robert Hällqvist∗∗ , Magnus Eek∗∗ , Roland Gårdhagen∗∗Applied Thermodynamics and Fluid Mechanics, Linköping University, Linköping, Sweden

, ∗∗Systems Simulation and Concept Design, Saab Aeronautics, Linköping, Sweden

Keywords: Thermal Comfort, Heat Stress, Thermoregulatory Model, Modeling and Simulation

Abstract

Flights with high thermal loads inside the cock-pit can have a considerable impact on pilot phys-iological and psychological performance result-ing in thermal discomfort, dehydration and fa-tigue. In this work, a Functional Mock-up Inter-face (FMI) based aircraft system simulator is uti-lized with intent to compute and predict thermalcomfort. The simulator can for example serve pi-lots as a tool for heat stress and flight risk assess-ment, supporting their pre-flight planning or beused by engineers to design and optimize coolingefficiency during an early aircraft design phase.Furthermore, the presented simulator offers sev-eral advantages such as map based thermal com-fort analysis for a complete flight envelop, timeresolved mental performance prediction, and aflexible composability of the included models.

1 Introduction

Thermal comfort describes a state in whichhumans sense a pleasant and satisfying environ-mental temperature [1]. A deviation from thisstate leads in hot environments to a feeling ofbeing febrile, which goes gradually along withsweating, dehydration and lapse of concentration[2] [3]. Pilots of small aircraft with limited cool-ing performance as well as high performanceaircraft with large transparent canopies are, dur-ing ground and low altitude flights, more oftenexposed to high heat loads when the weather

conditions are hot and sun radiation is high. Thesignificant increase of cockpit air temperaturein helicopters and fixed wing airplanes, plus theresulting decline of thermal comfort under suchhot conditions, is documented in several studies[4] [5]. The feeling of thermal discomfort, alongwith the awareness of potential heat illnesses,arises relatively distinctly in hot environments.However, physiological and mental performancemay also decrease during long flight missions inmoderate temperatures, easily underestimated bythe pilot.

The objective of this study is to demonstrate howan Aircraft System Simulator (ASS) can supportengineers, pilots, and ground crews to predictpossible heat stress related hazards before a flightso that error awareness is increased, sufficientand energy efficient cooling is provided, and hu-man health is not endangered. This is done by ap-plying the Functional Mock-up Interface (FMI)standard [6] in order to enable a flexible integra-tion of relevant sub-systems.

2 Method

One purpose of the ASS, schematically describedin Fig.1, is to enable studies of thermal com-fort coupled to Environmental Control System(ECS) overall performance. Interoperability be-tween the modeled sub-systems is established viathe FMI standard. Three novel models jointly de-scribing the aggregated cockpit thermal comfort

1

SCHMINDER J , HÄLLQVIST R , EEK M , GÅRDHAGEN R

conditions are connected to the ASS [7] [8]. TheASS is not aligned to a specific aircraft type butintended to be of research and industrial com-plexity in terms of range of application, non-linearities, and level of detail. The extensionsand refinements of the ASS, relevant for detailedanalyses of pilot thermal comfort, are describedin this section. Available atmospheric boundaryconditions are presented in section 2.1. The mod-eled sub-systems that together explicitly describethe provision of conditioned cockpit comfort airare described in section 2.2. Sub-systems mod-eling thermal comfort are over viewed in section2.3.

2.1 Atmosphere

The atmosphere model (Fig.1c) provides all sub-models within the ASS with atmosphere data.The model includes to date three atmosphericrepresentations: the International Standard At-mosphere (ISA) [9], the (suggested) InternationalTropical Atmosphere (ITRA) [10], and the Mili-tary Standard MIL-STD-210 [11].

2.2 Environmental Control

The environmental control related sub-systemmodels (Fig.1b) described here are developed inDymola and OpenModelica [12] [13], applyingthe object-oriented and equation based Modelicalanguage. The aircraft engine model is intendedto provide bleed air, extracted from the rearstages of the jet engine’s compressor to the ECSmodel. The bleed air temperature and pressureare modeled as functions of Mach number,altitude, and prevailing ambient conditions.

The applied environmental control system modelis a virtual representation of an ECS typically in-stalled in a fighter aircraft [14] [15]. The ECSprovides pressurized air at the needed mass flow,pressure, and temperature, to the cockpit, avion-ics, and pilot’s garment. The engine bleed airsupplied to the ECS is decreased in temperatureby the primary heat exchanger. A bootstrap cool-ing system, the cooling pack, is used to furthercondition the air. This is achieved by means of a

compressor, a turbine, a series of heat exchang-ers, and a water separator. The implemented heatexchangers utilize ram air for refrigeration. Thetemperature and pressure of the ECS output airare controlled to specification by means of anincorporated controlling software, denoted ECSControl in Fig.1b. The implemented softwarecontrols the motorized valves, which in turn reg-ulate the flow through two different cooling packby-pass branches. [7] and [8] provide more de-tailed information about the model.

Avionic

Defroster

Occu-

pant

Cockpit Air

Window /

Hood

Interior

Heating Cooling

Convection

Radiation

Turbine TurbineCondenserRe-Heater

Second. Heat

Exchanger

Prime. Heat

Exchanger

Compressor

(b)

(a)

ECS Control

Ram AirEnvironmental Control

System (ECS)

JetEngine

(c)

Conduction

Atmosphere

Fig. 1 : Concept diagram of the presented aircraft sys-tem simulator. Links between models illustrate schemat-ically FMI interfaces. (a) cockpit thermal climate modeland heat exchange mechanism, (b) environmental controlmodel and its sub-systems, (c) the atmosphere model.

2

PILOT PERFORMANCE AND HEAT STRESS ASSESSMENT SUPPORT USING A COCKPITTHERMOREGULATORY SIMULATION MODEL

2.3 Cockpit Comfort

The Cockpit Thermal Climate/Comfort (CTC)model (Fig.1a) is an enhanced version of theoriginal model [16] implemented in Matlab R©.The model is currently running in a Simulink R©

environment and consists of three major sub-models: the cockpit model, the thermal comfortmodel, and the occupant model.

The cockpit model computes the temporal ther-mal conditions within the cockpit compartmentwith boundary conditions defined both by theECS and the atmosphere model. The modelconsists of three smaller sub-models: the win-dow/hood, the interior and the compartment airmodel. The hood model utilizes an energy bal-ance, which in its general form reads

Enet = Econd + Econv + Erad . (1)

Eq.(1) is then discretized using an explicit finitedifference approach to compute the heat transferthrough the transparent cockpit canopy. Whileconduction (Econd), convection (Econv), sun radi-ation, and other radiation (Erad) only occur at thesurface nodes, internal nodes are only effected byconduction and sun radiation. Hence, for internalnodes Eq.(1) can be expressed as

∂T∂t

ρcp =∂

∂x

(k

∂T∂x

)+ Esun . (2)

Both the interior and the cockpit air sub-modelalso make use of energy balances,

Qint = Qintrad + Qequip + Qoccu

−Qintconv − Qcool(3)

Qair = Qequip + Qoccu + Qintconv + Qde f

+Qwconv − Qvent ,(4)

to compute their respective change in tempera-ture and use for time advancement

T t+dt = T t + Qdt

mcp. (5)

The interior, which includes all solid material(e.g. seats and panels), exchanges heat viaradiation Qintrad and convection Qintconv with thesurrounding cockpit air plus the cockpit’s hood,Eq.(3). Major sources of heat to the interior canbe the heat generated by the incident sun radi-ation, the equipment (instruments, computers)Qequip and the aircrew’s body heat Qoccu. Toregulate the temperature of the interior coolingair Qcool , provided by the ECS, is implementedas a heat sink. The cockpit air, Eq.(4), is mainlyheated-up by convection between the air andinterior Qintconv . Additional heat sources are theequipment Qequip, the occupants Qoccu, as wellas the defroster air Qde f if activated. Cockpit airtemperature can be controlled by ventilation airQvent coming from the ECS entering directly tothe cockpit.

Thermal comfort prediction is enabled by model-ing the cockpit wet-bulb and black-globe temper-atures which together form, with cockpit dry-airtemperature the input for several heat stress in-dices e.g. Wet Bulb Globe Temperature (WBGT)[17], Fighter Index of Thermal Stress (FITS) [18]or the Predicted Mean Vote (PMV) [19]. Thanother indices like the Predicted Percentage ofDissatisfied (PPD) occupants can be deduce [20].As previously presented for the interior and thecockpit air, wet-bulb and black-globe tempera-tures are computed applying energy balances

Qbg = Qrad + Qconv (6)

Qnwb = Qrad + Qconv − Qevap , (7)

which consider the radiative Qrad as well as con-vective Qconv heat exchange at the thermometers.Since the surface of the wet bulb thermometeris humid, an additional term had to be addedincluding the heat loss due to evaporation Qevap.The temperature of both thermometers weresubsequently advanced in time just as presentedin Eq.(5). A more detailed description of howthe models are implemented can be found in [16].

The physiological and psychological parameters

3


in this work are based on empirical regressionmodels, found in the literature, utilizing cockpitenvironmental parameters and/or thermal com-fort indices. Equilibrium rectal temperature (Trec)is based on experimental data published by Lind[21] and is estimated by means of

Trec = 0.000001Te f f5 −0.0001Te f f

4

+0.004Te f f3 −0.06Te f f

2

+0.46Te f f +36.22

(8)

describing rectal temperature as a function ofEffective Temperature (Te f f ).

Mean Skin Temperature (Tskin) is computed as

Tskin = 0.1263Tos +30.03 (9)

at which Tos is the temperature of the cockpit airclose to the pilot’s body [22] calculated as

Tos = 0.8367Tc +5.8 . (10)

In addition, Song [22] published a linear regres-sion to estimate the sweat rate (SR) of cockpitoccupants,

SR = 12.13Tos −149.96 . (11)

Mean Metabolic Rate (MR) and Heart Rate (HR)are estimated as

MR = 0.04Tc2 −1.96Tc +86.42 (12)

HR = 0.05Tc2 −2.2Tc +103.42 (13)

at which only regressions, presented by Lou [23],for a clothing insulation of 0.9 clo are applied,since fighter cockpit pilots normally are almostcompletely covered by clothes.

Relative Task Performance (TP) Eq.(14) is com-puted by

TP = 0.0000623Tc3 −0.0058274Tc

2

+0.1647524Tc −0.4685328(14)

employing a curve fit, presented by Seppänen[24], setting task productivity in relation toindoor ambient temperature (Tc).

To get a notion of human error risk due to sub-optimal thermal conditions, the Unsafe BehaviorIndex (UBI) for light workload was chosen. Theindex is calculated as

UBI = 0.0008Twbgt2 −0.0341Twbgt

+0.5829(15)

and indicate the detrimental effect on the safety-related behavior in relation to WBGT [25].

2.4 Model Intercommunication

The models included in the presented simulatorare exported as compressed model executables,according to the FMI standard format, wherethey are referred to as Functional Mock-up Units(FMUs). The environmental control sub-models,explained in section 2.2, are exported as FMUsfrom the commercially available Modelica toolDymola R© [12] [13]. The models comprisingthe CTC sub-models are ported from Matlab R©

to Simulink R© via the ”User-Defined Functionblock”. The Dassault developed toolbox ”FMIKit For Simulink” [26] is subsequently usedto generate FMUs from the resulting Simulinkmodels.

The ASS is then implemented in two differ-ent integrating tools, Dymola R© and the OM-Simulator. For the presented steady state sim-ulations, the CTC models are incorporated asFMUs in the Dymola implementation; however,the Modelica models are kept in their origi-nal format. Transient simulations were exe-cuted in the open-source tool OMSimulator. TheOMSimulator is a simulation environment sup-porting the FMI standard under development inthe research collaboration Open Cyber Physi-cal System Model-Driven Certified Development(OpenCPS) project [27]. In contrast to the steadystate simulation, all of the modeled sub-systems

4


are incorporated as FMUs in this second imple-mentation.

3 Results

The presented results are obtained by applyingthe ASS to compute the thermal conditions insidethe cockpit. This is then used to estimate thephysiological as well as psychological impact onthe pilot. The simulated aircraft is a single-seatergeneric fighter comparable to a AJ37 (Viggen)or F-18 (Hornet). First, 40 steady state casesimulations, each 800 s long, at different flightspeeds and altitudes were simulated covering theentire flight envelope typical for an aircraft inthis class [28] [29]. The atmospheric boundaryconditions during the simulations correspondto a standard day defined by the internationalstandard atmosphere (ISA).

Cockpit temperature (Fig.2a), computed by theCTC model, shows a variation of 40◦C withinthe flight envelop and rises up to 125◦C inregions with high Mach numbers. Cockpit aircondition, provided by the ECS, offers the pilot aminimum air temperature (Fig.2b) of 0◦C over awide rage of the flight envelope, but rises easilyup to 95◦C during fast flights at low altitudes.The thermal comfort a pilot would experiencewithin the flight envelope is assessed by fourdifferent indices. WBGT (Fig.2c) varies between15◦C and 30◦C but reaches highly critical valuesabove 33◦C [17] outside the flight envelopes.FITS (Fig.2d) is below 33◦C in a large part ofthe flight domain indicating no significant heatstress risk for the pilot. PMV (Fig.2e) of thepresent thermal situation varies from cold (-3) tohot (+3) resulting in PPD values (Fig.2f) fromthermal neutral (0%) up to distinct dissatisfaction(100%).

The pilot’s skin temperature (Fig.3a) is directlyaffected by the climatic in the the cockpit andvaries between 32◦C and 36◦C inside the flightenvelope, but exceeds 36◦C rapidly beyond theborders. A Sweat rate (Fig.3b) of 100 g/m2h-200 g/m2h is dominating within the flight

envelop, but reaches considerably higher valuesin areas with high cockpit temperatures. Themetabolic rate of the pilot (Fig.3c) is estimatedas 60 W/m2 in the operational area of the aircraft.However, higher rates are predicted outside theflight domain. The computed heart rate (Fig.3d)is, with some exceptions at high speed and highaltitude flights, relatively constant at 70-80 BPMwithin the reference borders. The relative taskperformance (Fig.3e) is 100% in large parts ofthe flight envelop but falls quickly below 50%where the ECS has difficulties to provide thenecessary cooling. The effect of the cockpittemperature on the pilot’s safe work behavior(Fig.3f) shows with 16%-40% a low to moderaterisk for unsafe actions within the assumed flightlimits.

In addition to the steady state case simulation,a transient mission was simulated with theaim to demonstrate the bidirectional dynamicinteraction of the FMI combined ECS and CTCmodel setup. The simulated mission includesfour flight phases: take off, landing, and twocruise segments. The results focus on the 11 minlong stepped-cruise part of the mission (Fig.4a)with both changes in altitude and flight speed.

To ensure thermal comfort during flight theECS uses FITS (Fig.4b) as feedback input toregulate air-condition temperature. The ECS wasprogramed to hold FITS constant at 20◦C, whichwas accomplished most of the time with excep-tion during the fast, high speed decent where27◦C is exceeded. At the beginning of the cruisephase cockpit temperature lies around 22◦C butincreases temporally up to 38◦C when quicklydescending to lower altitudes. Subsequently,when level flight is established again, cockpit airtemperature is stabilizing around 26◦C. Coolingair supplied by the ECS is initially maintainedat 20◦C; however, a deviation from the set pointis observed during the descent. After reachinglevel flight and reduced speed, cooling air dropsdown to an average value of 15◦C to restore theanticipated value of 20◦C FITS.

5


0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8

Mach Number [-]

0

2

4

6

8

10

12

14

16

18

20

Altitu

de

[km

]

15

15

15

20 20

20

20

20

25

25 25

25

25

30

30

30

30

35

35

35

35

35

40

40

40

40

40

40

45

45

45

45

45

45

50

50

50

50

50

50

50

55

55

55

55 55

55

55

60

60

60 60

60

65

65

65

65

70

70

70

75

75

80

80

85

85

90

90

95

95

100

100

105

105

110

110

115

120

125

TCockpit air

[oC]

F-18 Ref. Flight envelope

AJ37 Ref. Flight envelope

(a)

0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8

Mach Number [-]

0

2

4

6

8

10

12

14

16

18

20

Altitu

de

[km

]

0

0

0

0

0

0

55

5

5

5

5

55

10

10

10

10

10

10

15

15

15

15

15

1515

20

20

20

20 20

20

20

25

25

25

25

30

30

30

35

35

35

40

40

45

45

50

50

55

60

65

70

758085

90

T [oC]

Cockpit cooling air



(b)

0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8

Mach Number [-]

0

2

4

6

8

10

12

14

16

18

20

Altitu

de

[km

]

1015

20

20

20

20

20

25

25

25

25

30

30

30

30

3030

35

3535

35

35

35

40

40

40

40

45

45

45

50

50

50

55

55

60 65

70

WBGT [oC]



(c)

0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8

Mach Number [-]

0

2

4

6

8

10

12

14

16

18

20

Altitu

de

[km

]

15

15

15

15

20

20

20

20

20

20

25

25

25

25

25

30

30

30

30

30

30

35

35

35

35

35

35

40

40

40

45

45

45

50

50

55

55

60

60

65

70

75

80

FITS [oC]



(d)

0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8

Mach Number [-]

0

2

4

6

8

10

12

14

16

18

20

Altitu

de

[km

]

-3

-2

-2

-2

-1

-1

-1 -1

-1

-1

0

0

0

0

0

1

1

1

1

1

2

2

2

2

2

2

3

3

3

3

3

3

PMV [-]



(e)

0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8

Mach Number [-]

0

2

4

6

8

10

12

14

16

18

20

Altitu

de

[km

]

00

10

10

10

10

10

20

20

20

20

20

20

20

30

30

30

3030

30

30

30

40

40

40

40

40

40

40

50

50

50

50

50

50

505060

60

60

60

60

60

60

70

70

70

70

70

70

70

80

80

80

80

80

80

90

90 90

90

90

100 100

100

100

100

PPD [%]


AJ37 Ref. Flight emvelope

(f)

Fig. 2 : Steady state case simulation of cockpit temperatures and resulting thermal comfort within a poten-tial flight envelope. (a), cockpit air temperature inside the flight envelope is in average below 30◦C. (b), ECSprovided cooling air temperature increase significantly at higher Mach numbers. (c), WBGT shows low to moder-ate heat stress risk within the envelope. (d), FITS indicates no thermal risk inside the flight limits. (e), PMV assessthe thermal comfort as slightly chilly within the envelope. (f), PPD varies considerably inside the borders.

6


0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8

Mach Number [-]

0

2

4

6

8

10

12

14

16

18

20

Altitu

de

[km

]

32

32.5

32.5

32.5

33

33

33

33

3333

33.5

33.5

33.5

33.5

34

34

34

34

34

34.5

34.5

34.5

34.5

34.5

35

35

35

35

35

35

35.5

35.5

35.5

35.5

35.5

36

36

36

36

36

36

36.5

36.5

36.5

36.5

36.536.5

37

37

37

37

37

37.5

37.5

37.5

38

38

38

38

38.5

38.5

39

39

39.5

39.5

40

40

40.5

40.5

41

41

41.5

41.5

42

42

42.5

43

43

43.5

44

TSkin

[oC]



(a)

0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8

Mach Number [-]

0

2

4

6

8

10

12

14

16

18

20

Altitu

de

[km

]

50100

100

100

150

150

150

150

15015

0

200

200

200

200250

250

250

250

250

300

300

300

300

300

300

350

350

350

350

350

350

400

400

400

400400

400450

450

450

450

450450

500

500

500 500

500

550

550

550

550

600 6

00

600

600

650

650

700

700

750

750

800

800

850

850

900

900

950

950

1000

Sweat rate [g/m2h]



(b)

0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8

Mach Number [-]

0

2

4

6

8

10

12

14

16

18

20

Altitude [km

]

40

60

60

60

60

60

60

60

60

60

60

80

80

80

80

80

80

80

100

100100

100 100

100

120

120120

120 120

120

140140

140

140

160

160

160

180

180

200

200

220

220

240

240

260

260

280

280

300

300

320

320

340

340

360

360

380

400

Metabolic rate [W/m2]



(c)

0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8

Mach Number [-]

0

2

4

6

8

10

12

14

16

18

20

Altitu

de

[km

]

40

60

60

60

80

80

80

80

80

80

80

80100

100

100

100

100

100

120

120

120

120120

12012

0

140

140

140

140 140

140

160

160

160

160 160

160

180

180

180

180

180

200

200

200

220

220

240

240

260

260

280

280

300

300

320

320

340

340

360

360

380

380

400

400

420

420

440

440

460

460

480

500

520

540

560

580

600

Heart rate [BPM]



(d)

0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8

Mach Number [-]

0

2

4

6

8

10

12

14

16

18

20

Altitu

de

[km

]

10

10

10

20

20

20

20

20

30

30

30

30

30

40

40

40

40

40

40 5

0

50

50

50

50

60

60

60

60

60

60

70

70

70

70

70

70

80

80

80

80

80

90

90

90

90

90

100

100

100

100 100

100

100

100

Relative task performance [%]



(e)

0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8

Mach Number [-]

0

2

4

6

8

10

12

14

16

18

20

Altitu

de

[km

]

16

20

20

20

20

20

20

20

24

24

24

24

24

28

28

2828

28

28

32

32

32

32

32

3232

32

36

36

36

36

36

3636

36

40

40

40

40

40

40

44

44

44

44

44

48

48

48

48

48

52

52

52

52

52

56

56

56

56

60

60

60

64

64

64

68

68

68

72

72

72

76

76

76

80

80

80

84

84

84

88

88

88

92

92

92

96

96

100

100

UBI [%]



(f)

Fig. 3 : Steady state case simulation of pilot physiological and psychological parameters within a potentialflight envelope. (a), skin temperature inside flight envelope ≈34◦C. (b), sweat-rate is with 450 g/m2h clearlyincreased at high altitudes and Mach numbers. (c), metabolic-rate within the envelope mostly ≈60 W/m2. (d),heart-rate ≈80 BPM mostly constant inside the limits. (e), relative task performance is 100% inside the envelops.(f), risk for unsafe work behavior increases rapidly outside the flight limits.

7


The computed rectal temperature (Fig.4c) re-mains constant at around 37◦C during the flight,while skin temperature varies with ca. 2◦Cleading to an average of 33.2◦C.

The change in estimated heart rate (Fig.4d) dueto increased cockpit temperature amounts to12.6 BPM between its maximum and minimum.The predicted relative task performance of the pi-lot does not fall below 97% when cockpit tem-perature is close to the defined comfort set-point,however it drops significantly (75%) when thecockpit temperature is increased.

4 Discussion

Ensuring thermal comfort during flight alsomeans an increase in safety. To put this aspectinto the focus of pilots and engineers, a simu-lation tool was presented providing importantenvironmental, physiological and psychologicalinformation to support their flight planning,risk management and decision making. Inaddition, the study presents the potential ofapplying the FMI standard for interdisciplinaryand cross-program-linguistic model-exchangeand co-simulation.

Mapping vital aircraft system and aircrew param-eters over the entire flight envelope, as presentedin Fig.2 and Fig.3, facilitates a heliocentric viewof man and machine performance and helps toidentify potential hazards. The presented steadystate simulations show (within the presumed per-formance limits illustrated by the reference flightenvelops) good and reasonable results. Beyondthe borderlines, where ECS works off design,performance decreases rapidly (Fig.2b) leadingto an increase of cockpit air temperature (Fig.2a).This goes along with a significant decline inthermal comfort (Fig.2c-Fig.2f) where WBGTexceeds its maximum [17], FITS recommendto cancel planned flights [18], PMV indicates atoo hot environment, and PPD shows a signifi-cant dissatisfaction with the prevailing cockpitclimate [20]. Though all indices asses a cleardiscomfort for the occupants outside the envelop,

the PPD indicates also a moderate dissatisfactionwith the prevailing thermal comfort inside theflight limits. One reason for this could be thatPMV asses the cockpit climate as somewhatchilly.

The thermal conditions have a direct impacton the aircrews’ physiology and mental per-formance (Fig.3). Within the reference flightenvelope, human body parameters like skin tem-perature (Fig.3a), sweat rate (Fig.3b), metabolicrate (Fig.3c), and heart rate (Fig.3d) indicate noremarkable health risk. The picture looks ratherdifferent outside the envelopes where the cockpittemperature is high. The body tries to maintain aconstant core temperature by utilizing sweat andvasodilation, which is supported by the increasedsweat and heart rate [30]. In addition to thephysiological impact concentration and attentionis decreasing. The relative task performance(Fig.3e) is in large areas within the flight enveloppredicted as high leading to a low risk for unsafework behavior (Fig.3f). Outside the performancelimits of the aircraft relative task performancedrops significantly resulting in an increased riskfor unsafe work behavior which in turn couldlead to an enhanced probability for pilot error.

Regulating cockpit comfort can be done manu-ally (by the pilot) or fully automatic. In the sec-ond scenario cockpit air temperature is typicallymeasured and used as reference input for the ECSto adjust the cockpit climate if necessary. Con-trolling thermal comfort only by dry air temper-ature; however, this is not enough if the goal isto achieve pilot thermal comfort. The computedFITS was for this reason applied to regulate theECS. The advantage of using a thermal comfortindex as a control input is that these indices usu-ally consider additional factors like humidity, ra-diation, air speed, etc. For the dynamic case(Fig.4) cockpit comfort is over the entire flightensured since FITS stays below the suggestedcaution zone of 32◦C (Fig.4b).The physiology of the pilot is directly affectedby the climate of the cockpit whereby predictedrectal and skin temperature (Fig.4c) as well as

8


4 6 8 10 12 14 16

Time [min]

2

3

4

5

6

7

8

9

10

11

12

Altitude [km

]

0.8

0.9

1

1.1

1.2

1.3

1.4

1.5

1.6

Mach N

um

uber

[-]

Altitude

Mach

(a)

4 6 8 10 12 14 16

Time [min]

5

10

15

20

25

30

35

40

45

50

55

60

Te

mp

era

ture

[°C

]

5

10

15

20

25

30

35

40

45

50

55

60

FIT

S [°C

]

FITSFlight cancelation

Danger zone

Caution zone

Cockpit cooling air

Cockpit air

(b)

4 6 8 10 12 14 16

Time [min]

37.7

37.75

37.8

37.85

Recta

l T

em

pera

ture

[°C

]

32

32.5

33

33.5

34

34.5

35

Skin

Tem

pera

ture

[°C

]

Rectal

Skin

(c)

4 6 8 10 12 14 16

Time [min]

78

80

82

84

86

88

90

92

He

art

Ra

te [

BP

M]

75

80

85

90

95

100

Re

lative

Ta

sk P

erf

orm

an

ce

[%

]

Heart rate

Task performance

(d)

Fig. 4 : Transient simulation of cockpit air temperature and the impact on pilots physiological and psycho-logical performance. (a), generic flight with changing Mach number and altitude. (b), impact of cooling andcockpit air temperature on FITS with Stribley [18] suggested FITS limits illustrating different flight risks whichare not exceeded. (c), predicted pilot skin temperature show larger changes compared to rectal temperature whichmaintains nearly constant. (d), heard-rate and relative task performance behave contrary at increased cockpittemperatures.

heart rate (Fig.4d) respond with increased am-plitudes when cockpit temperature is reaching itsmaximum. The skin temperature and heart rateshow more distinct changes while rectal tempera-ture only rises minimally. This result is expectedsince the skin has more direct contact with thecockpit air, while the stressed heart rate is a invivo reaction attempting to remove heat from thebody to maintain a constant core temperature thatis close to rectal temperature [30]. Furthermore,mental performance drops with increased body

heat load, and as a consequence so does the rela-tive task performance of the pilot (Fig.4d).The results also demonstrate that the modelingapproach to connect smaller, one dimensional,independently running models via the FMIstandard into a larger aircraft system simulatoris very beneficial. On the one hand it provides ahigh compatibility of various simulation modelsand on the other hand a more heliocentric pictureof the aircraft systems and their interactions. Inaddition, the FMI standard provides engineers

9


with the freedom to choose the optimal simu-lation tool for their particular problem withoutrunning into danger not being able to collaborate.

In summary, it can be said that the presented ASSseems to be functional for thermal comfort stud-ies and shows reasonable results, yet refinementsof the simulator and its sub-models continues andvalidation will follow.

5 Conclusion

Based on the presented results it can be con-cluded that the demonstrated aircraft system sim-ulator has the potential to determinate variousheat stress parameters supporting pilots in theirflight preparation, increasing error awareness andthereby minimizing in-flight incidents. More-over, it enables engineers to incorporate cock-pit thermal comfort into the development of in-terfacing sub-systems in early design phases.Thereby design errors caused by possible sub-optimizations can be minimized.

6 Acknowledgements

The authors would like to show their gratitude tothe associated funding bodies and all contributingOpenCPS project members. Special thanks to Dr.Robert Braun and Dr. Lennart Ochel for their de-velopment and aid during the implementation ofthe ASS in the OMSimulator.

7 Contact Author Email Address

Mail to: [email protected]

Copyright Statement

The authors confirm that they, and/or their companyor organization, hold copyright on all of the origi-nal material included in this paper. The authors alsoconfirm that they have obtained permission, from thecopyright holder of any third party material includedin this paper, to publish it as part of their paper. Theauthors confirm that they give permission, or have ob-tained permission from the copyright holder of this

paper, for the publication and distribution of this pa-per as part of the ICAS proceedings or as individualoff-prints from the proceedings.

References

[1] Standard. ASHRAE 55 - Thermal Environmen-tal Conditions for Human Occupancy . Tech.rep., American Society of Heating, Refrigerat-ing and Air Conditioning Engineers, Atlanta,US, 2017.

[2] Jessen C. Temperature regulation in humansand other mammals. Berlin : Springer, cop.2001, 2001.

[3] Gaoua N. Cognitive function in hot environ-ments: A question of methodology. Scandina-vian Journal of Medicine & Science in Sports,vol. 20, no. Suppl 3, pp. 60 – 70, 2010.

[4] Nunneley S A, Stribley R F and Allan J R. Heatstress in front and rear cockpits of F-4 aircraft.Aviation Space and Environmental Medicine,vol. 52, no. 5, pp. 287–290, 1981.

[5] Reardon M, Fraser B and Omer J. Physiologi-cal Effects of Thermal Stress on Aviators Fly-ing a UH-60 Helicopter Simulator. MilitaryMedicine, vol. 163, no. 5, pp. 298–303, 1998.

[6] FMI development group. Functional Mock-up Interface for Model Exchange and Co-Simulation. Report 2.0, Modelica Association,2014.

[7] Hällqvist R, Braun R and Krus P. Early Insightson FMI-based Co-Simulation of Aircraft Vehi-cle Systems. Proceedings of 15:th Scandina-vian International Conference on Fluid Power,pp. 262–270. Linköping, 2017.

[8] Hällqvist R, Schminder J, Eek M, Braun R,Gårdhagen R and Krus P. A Novel FMIand TML-Based Desktop Simulator for De-tailed Studies of Thermal Pilot Comfort. 31stCongress of the International Council of theAeronautical Sciences. Belo Horizonte, Brazil,2018.

[9] Standard. ISO 2533:1975 - Standard Atmo-sphere. Tech. rep., International Organizationfor Standardization, Geneva, CH, 1975.

[10] Ananthasayanam M R and Narasimha R. A pro-posed International Tropical Reference Atmo-sphere up to 80 km. Advances in Space Re-

10


search, vol. 5, no. 7, pp. 145–154, 1985.[11] Zuppardo J C. Graphical comparison of U.S.

tandrd atmosphere and military standard cli-matic extremes. Tech. rep., Aeronautical Sys-tems Center, 1993.

[12] Dymola Systems Engineering. https://www.3ds.com/products-services/catia/products/dymola/. Accessed:2018-06-21.

[13] Fritzson P, Aronsson P, Lundvall H, Nyström K,Pop A, Saldamli L and Broman D. The Open-Modelica Modeling, Simulation, and SoftwareDevelopment Environment. Simulation NewsEurope, vol. 44, pp. 8–16, 2005.

[14] Shetty J, Lawson C and Shahneh A. Simula-tion for temperature control of a military aircraftcockpit to avoid pilot’s thermal stress. CEASAeronautical Journal, vol. 6, no. 2, pp. 319–333, 2015.

[15] Jordan P and Schmitz G. A Modelica Libraryfor Scalable Modelling of Aircraft Environmen-tal Control Systems. Proceedings of the 10thInternational Modelica Conference. Lund, Swe-den, 2014.

[16] Schminder J and Gårdhagen R. A generic sim-ulation model for prediction of thermal con-ditions and human performance in cockpits.Building and Environment, vol. 143, pp. 120 –129, 2018.

[17] Standard. ISO 7243:2017 - Ergonomics of thethermal environment - Assessment of heat stressusing the WBGT (wet bulb globe temperature)index. Tech. rep., International Organization forStandardization, Geneva, CH, 2017.

[18] Stribley R F and Nunneley S A. Fighter In-dex of Thermal Stress: Development of In-terim Guidance for Hot-Weather USAF Oper-ation. Tech. rep., USAF School of AerospaceMedicine, Aerospace Medical Division, 1978.

[19] ASHRAE Handbook Fundamentals. 1st ed.American Society of Heating, Refrigerating,and Air-Conditioning Engineers, 1993.

[20] Standard. ISO 7730:2005 - Ergonomics ofthe thermal environment - Analytical determi-nation and interpretation of thermal comfort us-ing calculation of the PMV and PPD indicesand local thermal comfort criteria. Tech. rep.,International Organization for Standardization,

Geneva, CH, 2005.[21] Lind A R. A physiological criterion for set-

ting thermal environmental limits for everydaywork. Journal of Applied Physiology (0021-8987), vol. 18, no. 1, p. 51, 1963.

[22] Song B, Cao X and Mitsui Y. A study of effectof Cockpit Heat Stress on Pilot Thermal Strain.Japan Society for Aeronautical and Space Sci-ences, vol. 38, no. 119, pp. 57–65, 1995.

[23] Luo M, Zhou X, Zhu Y and Sundell J. Revisit-ing an overlooked parameter in thermal comfortstudies, the metabolic rate. Energy and Build-ings, vol. 118, pp. 152 – 159, 2016.

[24] Seppänen O, Fisk W J and Lei Q. Effect of tem-perature on task performance in office environ-ment. Tech. rep., Helsinki University of Tech-nology, Laboratory for Heating Ventilating andAir-conditioning, 2006.

[25] Ramsey J, Burford C, Beshir M and Jensen R.Effects of Workplace Thermal Conditions onSafe Work Behavior. Safety Research, vol. 14,pp. 105 – 114, 1983.

[26] FMI tools for Simulink - FMI Kit. https://www.3ds.com/products-services/catia/products/dymola/fmi/. Ac-cessed: 2018-06-28.

[27] Open Cyber-Physical System Model-DrivenCertified Development (OpenCPS). https://opencps.eu/. Accessed: 2018-06-28.

[28] Kuhta S F, Clark J W, Gillies W J, ClimpsonC R, Dandridge L A and Slodkowski L I. F/A-18E/F will Provide Marginal Operational Im-provement at High Cost . Tech. rep., UnitedStates General Accounting Office, WashingtonD.C., US, 1996.

[29] SAAB-Scania. Fpl AJ 37 Speciell Förarinstruk-tion (SFI) Komplement Del 3 (M7780-400173).Tech. rep., Försvarets Materielverk, Stockholm,Sweden, 1979.

[30] Wyss C, Brengelmann G, Johnson J, Rowell Land Niederberger M. Control of skin blood flow,sweating, and heart rate: role of skin vs. coretemperature. Applied Physiology, vol. 36, no. 6,pp. 726–733, 1974.

11

https://www.3ds.com/products-services/catia/products/dymola/



https://www.3ds.com/products-services/catia/products/dymola/fmi/



https://opencps.eu/

https://opencps.eu/

pilot performance and heat stress assessment...

Documents