November 1982
A Combat Aircraft Availability
Assessment Technique VECHNISCHE HOGESCHOOL DELFT LUCHTVAART- EN RUIMTEVAARTTECHNJHC
B I B L I O T H E E K by C D . Burieigh and J.P. Fielding »<«"Vverweg 1 - DELFT
CoUege of Aeronautics Cranfield Institute of Technology
Cranfield. Bedford, UK
College of Aeronautics Report 8228 November 1982
A Combat Aircraft Availability Assessment Technique
by CD. Burleigh and J.P. Fielding
College of Aeronautics Cranfield Institute of Technology
Cranfield, Bedford, UK
Paper accepted for the 4th Euredata Conference Spring 1983
VENICE
ISBN 0 902937 80 4 £7.50
'The views expressed herein are those of the authors alone and do not necessarily represent those of the Institute."
on their equipment being available to them during a conflict. Some recent published figures, however, showed that two modern fighter aircraft were only available for missions for 47% or 56% of the time. These figures prompted a study of the causes of unavailability
and the development of an availability assessment technique.
Initial studies concentrated on determining probability distributions of reliability, maintainability, battle damage repair and attrition.
A simple operation simulation model was then derived to show an aircraft's sensitivity to the main availability parameters. This model can be applied to any aircraft type provided that the necessary
inputs can be calculated. The simulated operations were as realistic as possible, although many assumptions had to be made.
For reasons of national security it was not possible to relate this study directly to any current service aircraft, so a design project study has been used as the baseline aircraft in the simulation model. This aircraft was the 1980 Mini-CAS, developed at Cranfield Institute of Technology. This was used because all the necessary data were available or could be estimated with reasonable confidence and also the operating conditions are comparable to a number of current service types employed in the Close-Air-Support role. Thus the simulation was kept realistic and the results and conclusions are directly applicable to real and projected designs.
The Operation Simulation Model proved to be a satisfactory means of assessing the effectiveness of a force of aircraft under war time conditions. It was far more flexible than the Availability and Mission Readiness equations commonly used to compare the in-service performance of aircraft and highlighted areas where resources could best be concentrated to improve availability.
INDEX Page Number 1. 2. 3. 4. 5. 6. 7. 8. 9. Introduction
The Operation Simulation Model R e l i a b i l i t y Data Maintainability Data Turn-Round Times Vulnerability Estimation Simulation Results Discussion of Results Conclusions References
Table 1 - Average System Mean Times to Repair Table 2 - Mini-CAS Operation Simulation Results Fig. 1 - Mini-CAS Layout Equipment
Fig. 2 - Operation Simulation Model
Fig. 3 - Mini-CAS Defect Rate Distribution Fig. 4 - A i r c r a f t Turnround Checks
Fig. 5 - Vulnerability
Fig. 6 - Mini-CAS Operation Simulations: P^ = 0.01
1 3 7 9
n
12 14 16 17 19 21 21 22 23 24 25 26 27worked example throughout. I t was not possible to directly relate the work to any current service a i r c r a f t for reasons of suitable security, but the Cranfield Mini-CAS project was chosen as the base-line a i r c r a f t . This a i r c r a f t was designed as part of a post-graduate student exercise and is described in reference 3. I t i s a single-engined anti-tank a i r c r a f t , artned with a 27 mm cannon and Maverick and Sidewinder missiles (Figure 1). I t ' s role is to attack targets at speeds up to Mach 0.8 at low-level and i t
incorporates many s u r v i v a b i l i t y features. The design was
performed i n some detail i n terms of structure and equipment and thus there was a considerable amount of information available for input into an a v a i l a b i l i t y model. Any s h o r t f a l l i n data could be estimated with reasonable confidence from comparable a i r c r a f t . Use of this approach thus had the potential of making a r e a l i s t i c simulation of a v a i l a b i l i t y with results d i r e c t l y applicable to current operational and projected designs. I f the model could be kept r e l a t i v e l y simple i t could be used for educational purposes to show the effect of changing an a i r c r a f t ' s configuration or operating methods.
3
-The Operation Simulation Model
The usual d e f i n i t i o n o f a v a i l a b i l i t y i s :
-Inherent a v a i l a b i l i t y A- = MTB^fKTTR
where MTBM = Mean time between maintenance actions
MTTR = Mean time to r e p a i r or complete maintenance
This d e f i n i t i o n assumes t h a t the equipment i s constantly r e q u i r e d , but many combat a i r c r a f t cannot operate successfully at night and therefore a more useful d e f i n i t i o n i s Mission
Readiness:-M-!oo-;«„ D^^Ai^^^c- MD actual number of s o r t i e s flown Mission Readiness MR = sm
where NSI = SD x NO x NAC and
SD = no. of s o r t i e s possible per day ND = no. of days
NAC = no. of a i r c r a f t
I t was decided to i n v e s t i g a t e the above d e f i n i t i o n s together with any others t h a t might emerge to obtain the most r e a l i s t i c
simulation possible w i t h i n the constraints of the study.
The Operation Simulation Model (OSM) was developed to be used to c a l c u l a t e the number of s o r t i e s generated and the number of serviceable a i r c r a f t throughout a deployment or b a t t l e . The input data consist of a series of e x t e r n a l l y c a l c u l a t e d
p r o b a b i l i t i e s to cover defect a r i s i n g s , a t t r i t i o n rate e t c . , and the basic operating parameters such as the number of days to run and the f l e e t s i z e . The output can be provided i n several forms but the most convenient was found to be a table g i v i n g the end of day values of s e r v i c e a b i l i t y and tuinu'ldtive s o r t i e generation, w i t h a d d i t i o n a l output o f the number of a i r c r a f t t h a t would be a v a i l a b l e f o r use on the day a f t e r the deployment i s terminated.
The program is written in "Commodore BASIC" for use on the CBM "Pet" micro-computer. This machine was found to be adequate for the job but was slow in operation, this limited the number of runs that could be completed in the available time. However, a fairly comprehensive set of results was produced, tracing the impact of changes to all the main input parameters.
Input
The Operation Simulation Model contains the variables listed below, which can be pre-set or input by the operator to determine the effects of changing the aircraft's operating parameters.
i) Initial Fleet Size (nacj: This acts as a scaling factor and does not affect the relationships between the other parameters. Large fleet sizes will have more precise results than small ones owing to the rounding operations used in the program.
ii) Number of Days to Run (nd): This defines the length of the operation to be simulated.
iii) Number of Sorties per Day (sd): This is set at its maximum value by the mission duration and the turnround time but may also be set arbitrarily at any other value.
iv) Mean Time to Repair Defect (m): This parameter is a function of the maintainability of the aircraft but may also be influenced by conditions in the field. An exponential distribution of the "probability of repair" has been assumed as described in paragraph 4 for which only the mean time value is required.
v) Mean Time to Repair Battle Damage (n): This again requires only a mean time input, as an exponential distribution
has been assumed. The estimation of MTTR for battle damage is described in paragraph 6.
vi) Probability of Abort (pi): This is the probability of a serious defect causing an "operational effect" arising during the time between the aircraft being called upon
to fly and its arrival at the forward edge of the battle area (FEBA). This value can be estimated from the aircraft's defect data, (see paragraph 3 ) .
vii) Probability of Attrition (p2): The loss rate for the aircraft will depend on the type of defensive equipment employed by the enemy, the aircraft's vulnerability to attack and its ability to survive a hit (see paragraph 6 ) .
viii) Probability of Sustaining Battle Damage (p3): This is directly linked to p2 and will be made up of those aircraft which sustain a hit but are still able to
return to base.
ix) Probability of Defect Arising (p5): This depends upon reliability, some defects may have repair deferred under certain conditions (see paragraph 3 ) .
2.2 Program Description
A flow chart depicting the significant steps through a mission cycle is shown in Figure 2. Each cycle covers all aspects of the operation except scheduled maintenance, which would not be carried out in a war situation. The program proceeds down the main "trunk" of the flow chart, assigning aircraft to the various
branches depending on the fixed probability of occurrence at each branch. As aircraft pass into the side branches the number of serviceable aircraft is reduced. Before the cycle is indexed to the next mission, a proportion of the aircraft in the side
branches are returned to the serviceable state. This operation is controlled by the particular probability of repair and the final number of serviceable aircraft at the end of each mission cycle becomes the number of aircraft despatched on the following mission.
The program indexes, through the full number of missions scheduled to be flown each day (input sd). It assumes a 12 hour flying day and a 24 hour maintenance day, so on the last cycle of each day an extra 12 hours is allocated to maintenance in order to give the correct number of serviceable aircraft on the first
mission of the following day. The number of serviceable aircraft on each mission (the output value) is the number scheduled to fly minus those aircraft which abort.
Full listing of the program is contained in reference 4, on which this paper is based,
Development of the input parameters used in the Mini-CAS
simulation are described in paragraphs 3 to 6 below, whilst the results are discussed in paragraphs 7 and 8.
7
-Reliability Data
The reliability of an aircraft is a fundamental input into the simulation model. It was necessary to determine realistic values for the various aircraft systems. This was done by making
comparisons with those of similar existing aircraft and making allowances for improvements in technology. Ten system groups were studied, yielding the defect rate distribution shown in figure 3. These systems account for some 80% of all aircraft defects. The contributions made by the remaining systems were estimated on an empirical basis. The total defect rate amounted to 892.3 for 1000 flying hours or a figure of 1.12 mean flying hours between defects.
The probability of a defect arising (P5) can be determined
from:-D(- „-t X 0.8923 P5 = e
Where t is the mission duration in hours.
A small proportion of defects that occur have significant effects on the operation of the aircraft. These were estimated for each system and amounted to 92.7 per 1000 flying hours. This figure was used to calculate the probability of abort, PI, for input into the simulation model. The time used in this case was that from aircraft call-out to it's appearance at the Forward Edge of the Battle Area (FEBA).
At a later stage in the study it was decided to examine the effects of maximum deferral of defects. This is a philosophy used in the heat of battle whereby the aircraft is dispatched even if it is shown to have operational defects. This obviously leads to a degradation of the aircraft's effectiveness, but this would have to be accepted providing that it is maintained within certain limits. To quantify this degradation, every major component was given an importance rating between 1 and 3. Less important sysLöTiS, such as external lights, would have a rating of 3. An
intermediate rating of 2 would he applied to, say, the failure of an artificial horizon, providing that the head-up display was serviceable. An essential system, such as roll control would have a rating of 1. These ratings were applied to the
operational defect rates for each system to give an overall battle effect defect rate of 54.9 per 1000 hours. This was then used to calculate new values of PI and P5 to study the effect of maximum defect deferral.
9
-Maintainability Data
The elapsed time for the repair of defective systems was used in the simulation model to give the probability of the aircraft
returning to service by the time the next sortie is to be launched. The distribution of repair time was assumed to follow an
exponential curve and therefore the only input required was the Mean Time To Repair (MTTR).
The maintenance downtime was estimated by finding a mean time for the rectification or replacement of faulty items in each system, based on historical data and then weighting the times by the proportion of the total aircraft defects that are expected to occur in each system. The weighting was based on the defect rate distribution as described in paragraph 3. The maintenance times were derived for each of the systems considered to be a major contributor to the maintenance workload. Some systems could not be treated owing to the lack of data.
A typical example for the estimation of MTTR is shown for the
undercarriage:-Reference 5 gives the following figures for the Hawk trainer undercarriage component replacement
times:-UNIT ELAPSED TIME (min)
Main Wheel 11.0 Brake Pads 23.0 Undercarriage Door 12,0
These times do not include allowances for diagnosis or spares
positioning and could therefore be larger in practice. Reference 6 gives the following
figures:-UNIT ELAPSED TIME (min)
F-15 Main landing gear 320 F-4E Main landing gear 920
F-15 Main Wheel 16.0 F-4E Main Wheel 51.0
It can be seen that there is some consistency between the F-15 and Hawk main-wheel replacement figures. Both aircraft are modern designs in which great emphasis was placed on design for
maintainability. Reference 6 also quotes MTTR's for the complete undercarriage systems of the F-15 and F-4E fighters. These figures are 0.77 and 2.8 hours respectively and, as the Mini-CAS system is somewhere between the two in terms of complexity and maintainability, a mean MTTR of 1.8 hours was taken.
The MTTR's for the systems examined were entered into table 1 and weighted according to the total defects attributable to each
system. This analysis accounted for only 71% of all defects, but this fact was catered for in the determination of the overall weighted MTTR of 1.53 hours for the aircraft. This part of the
study suffered from a lack of more suitable data but gave a good "ballpark" figure which was suitable for use in this relatively simple model.
11
-Turn-Round Times
The maximum number of sorties that can be flown by an aircraft within a given time is controlled by the mission duration and the
turnround time on the ground. The time taken to complete the turnround operations will depend upon the number and type of tasks to be performed and the organisation of the maintenance manpower.
The principal tasks that must he performed when an aircraft returns from a sortie are:
i) Inspection of the aircraft for damage and serviceability. This was estimated from the figures of the generally similar Hawk aircraft.
ii) Refuelling times were estimated from study of the operation of Cranfield Institute of Technology aircraft and
comparison with published information.
iii) Rearming
Reloading the cannon and on-loading missiles were determined from Hawk statistics.
iV) Brake Parachute Re-Packing
This was determined from reference 6.
Figure 4 was derived from the above i n f o r m a t i o n , together w i t h allowances f o r safety precautions suggested by Engineering O f f i c e r s .
6. Vulnerability Estimation
The estimation of attrition losses and battle damage inflicted upon a fleet of aircraft in any combat scenario is based on historical data that has been built up during past conflicts. Many aircraft have been lost due to their vulnerability while on
the ground when the base comes under eneiny attack. The location of airfields would be of great importance to the sortie generation capability of a close support aircraft such as the Mini-CAS but the whole subject of airfield survival and defence is beyond the scope of this present study. The vulnerability of an aircraft to enemy defences during its mission can be estimated if information is available on the nature of the defences, the mission profile and tactics to be employed by the pilot and the vulnerability of the aircraft to enemy weapons. This subject has been covered by J.R.Wojcik in reference 7.
Reference 8 contains an assessment of the expected attrition and battle damage rates for the Fairchild A-IO aircraft which
operates under conditions similar to those of the Mini-CAS and this has been used as a basis for setting attrition and battle damage rates in the simulation model. Mini-CAS, like the A-IO can be expected to suffer high attrition when it performs close support operations in the face of an extensive air defence system.
For the purposes of the operation simulation model the probability of attrition on each flight was input as arbitrary values up to a maximum of 3%. The level of battle damage sustained by the force will be related to the attrition rate via the vulnerability of the aircraft.
Fiyp views of the Mini-CAS were drawn for u^e in the vulnerability analysis, one of which is shown in figure 5. The two side views were assumed to be the same, so only the Left Hand Side was drawn. Each view was divided by a grid of scaled 18" squares and the
13
-aircraft was assumed to take a hit in the centre of each square.
Reference 8 indicates that a 23mm HEI shell which is the main threat, will have an area of effect about 18" across and shrapnel will penetrate deeply into the structure. All exposed systems in each square were assumed to have been destroyed and the number of squares containing a "kill" counted. The proportion of
squares in each view that contain a kill were summed to give the vulnerability fraction (Vf).
This was used in the method of reference 8 to give the following kill and battle damage probabilities for input values of attrition rate into the
model:-Probability of kill (attrition) Pa 0.01 0.02 0.03 Probability of kill by missile Pkm 0.004 0.008 0,012 Probability of kill by shell Pks 0.006 0,012 0.018 Probability of battle damage Pd 0,02 0,041 0.061
7. Simulation Results
7.1 Peacetime Operations
Some preliminary program runs were performed to determine the best combination of input parameters. It was decided to use an
initial fleet quantity of 24 aircraft and to model their operations over a five day period.
Twenty four runs were conducted under peacetime operating ground rules to produce generalised curves of sorties flown and aircraft available for a range of MTTR's and probabilities of defects. These curves could be used to compare different aircraft types or the effect of changes in Mini-CAS reliability and maintainability performance. The latter process was carried out for the Mini-CAS for the next 9 runs to check the effect of maintainability changes and a further set of runs with varying reliability figures.
These showed that improvements in reliability had a more powerful effect in improving sortie generation for this aircraft. The datum aircraft with reliability and maintainability inputs as described in paragraphs 3 and 4 produced 845 sorties over the five day period, with no aircraft losses. This gave an average
Mission-Readiness of 59% whereas classical availability theory would give 42.3%.
7.2 Wartime Operations
The first series of runs looked at the effect of introducing attrition and battle damage. These were related by the vulnerability of the aircraft to attack, as described in
paragraph 6. The other parameters were kept at their peacetime levels. Attrition rate was input as the probability of attrition at ,01, .02 and .03 with their respective probabilities of
15
-Subsequent runs investtgated the effects
of:-i) Reduced turn-round times by reducing safety standards ii) Maximum deferral of defect rectification
iii) The use of rapid battle damage repair techniques
iv) Reduced vulnerability due to improved aircraft component protection
Figure 6 shows the effect of these measures with an attrition probability of 1% in terms of cumulative sorties flown. Table 2 shows the overall results of this exercise.
Discussion of Results
Reducing the turn-round time allowed one extra sortie to be flown each day, but as 12 were already being flown the number of
aircraft available for the extra sortie were limited because of attrition losses and aircraft grounded for maintenance or repair.
Deferring maintenance on the less serious defects had the greatest beneficial effect. This allowed aircraft to continue flying for longer during the 12 hour flying day and enabled the maintenance crews to "catch up" during the night. Figure 6
shows that for a 1% attrition rate this action gave considerably more sorties than even the peacetime datum condition.
The use of rapid battle damage repairs had a small beneficial effect, but this action, together with maximum deferral of defects must produce some detrimental effects on the aircraft's combat capabilities. It was impossible to quantify this effect, however, on such a simple model.
The effect of vulnerability reduction, based on a 3% attrition rate was to increase the sorties from 646 to 724 and to increase the remaining aircraft at the end of the period from 5 to 7. This shows that careful attention to this aspect would be worthwhile.
Recent work by another student (reference 9) showed that the simulation model could be used for another close-air support
aircraft of a different configuration than Mini-CAS. Meaningful comparisons were then made between the two design solutions.
17
-Conclusions
The Operation Siitiulatton Model proved to be a satisfactory; simple means of assessing the effectiveness of a force of aircraft
under wartime conditions. It was far more flexible than the Availability and MissTon Readiness equations commonly used to compare the in-service performance of aircraft.
It was found during the study that once attrition is introduced into the operations even the Mission Readiness values derived from the total number of sorties flown were inadequate for the comparison of operations. A much simpler parameter was used for comparing the wartime operations, this is the Cumulative Sortie Generation. It remains valid under all circumstances except when different missions or aircraft are being compared, when different input information will be needed.
The Mini-CAS aircraft used throughout the simulation study made the results relevant to a number of current service aircraft and used operating procedures that are still being developed among Western air forces. The study has enabled some areas on which effort should be concentrated to be identified but the results are specific to the Mini-CAS and cannot be directly applied to other aircraft because the relationships between the parameters will be different. It has shown how the relationships between
the parameters can be determined in any battle situation.
For the Mini-CAS the simulation study has shown that the greatest benefit to the force, in terms of sortie generation will come
from reducing the number of aircraft grounded for the rectification of defects. The most effective means of doing this under wartime cond'tions ic to defer the rectification of the less serious
defects until a more convenient time. The proportion of defects that can be treated in this way will depend on the aircraft and the type of mission being flown. For the Mini-CAS a Go/Cancel list
of essential equipment was developed and this was used to assess the rate at which serious defects can be expected to occur.
The use of rapid battle damage repairs and reduced turn-round times had small beneficial effects on the Mini-CAS's availability.
Vulnerability reduction had a more marked effect and should be investigated further.
The use of this simple model based on a cheap micro-computer, has the potential of being a useful tool for demonstrating the effects of various parameters on availability. This would be useful in the training of designers, engineers and aircrew.
19
REFERENCES
1. General Dynamics Corp. Fort Worth Div.
"Maintenance and Support
Alternatives and Their Impact on Aircraft Design and Support
Planning".
3rd Annual Logistics Education Conf. Washington DC. Nov.1980
2. News Article Flight INternational Magazine
14th June 1980, p.1244.
3. Fielding J.P. "1980 Design Awareness Course: The
Design of a Miniature Close Air Support Aircraft". College of Aeronautics Memo 8102. Cranfield
Institute of Technology UK. 1981
4. Burliegh CD. "Mission Readiness of Combat A i r c r a f t " . MSc Research Thesis Cranfield I n s t i t u t e of Technology 1981
B r i t i s h Aerospace Kingston-Brough Div.
"Hawk T. Mk.I - Maintainability Demonstrations". HSK.237 April 1977
6. McDonnell A i r c r a f t Co. "Minimum Maintenance". P.S.838. October 1974.
Paper
7. Wojcik J.R. "Aircraft Combat Survivability Design Considerations and Vulnerability Analysis". MSc. Research Thesis, Cranfield
8. Johnson S.E.
9. Hussein A.M.
"The Impact of Battle Damage on A-10 Availability and Sortie Rate" Institute for Defence Analyses -System Evaluation Division. Paper P-1205, May 1976
"Project Design of a Miniature Close-Air Support Aircraft". MSc Research Thesis, Cranfield
21
-TABLE 1
AVERAGE SYSTEM MEAN TIMES TO REPAIR
SYSTEM Nav/Attack Avionics Undercarriage Fuel System Flying Controls Hydraulic Power Electrical Power Communication Instruments Propulsion AIRCRAFT TOTAL M.T.T.R.(HRS) 1.5 1.8 .48 .70 3.84 .73 .16 .34 6.0 1.53 TABLE 2
MINI-CAS OPERATION SIMULATION RESULTS
No. — 1 2 3 4 6 7 8 9 10 11 12 CONDITION
Peacetime, normal maint. and repair 1% Attrition, 2% Damage, 4hr BDR 2% Att. 4.1% Dam. 4hr BDR
3% Att. 6.1% Dam. 4hr BDR
Reduced turnround, SD=13, 1% Att. As No,4, 3% Att. 6.1% Dam.4hr BDR Deferral. SD=13, P2=.01, P3=.02 As No.7, P2=.03, P3=.061
As No.7 but with Op Effects only Rapid BDR (N=2.6hrs) 1% Att. As No.10 but 3% Att. 6.1% Damage Reduced Vulnerability P2=.024 TOTAL SORTIES 845 692 579 499 732 516 1029 619 607 1051 646 724 AIRCRAFT REMAINING 20 14 8 8 14 6 12 5 5 12 5 7
Whpre*-BDR = mean battle damage repair time Att = a t t r i t i o n
SD = sorties per day
AVfONiCS BAY
CONTROL ROOS
' P A M J N ' *
S A ' - f O r : * r T ^ / ï j i > ' / AHMO / ƒ - BOX
MAUSEP BK J7 CANNON r n i ' i i p n o ' . F U E L CEIL 3 (STB O SIDE I ^^^^ ^ELL I ( POOT
ANO 7 I S T B D I « A K ' N C C K T E r u s QATU»» ^,-4-"4^>...-M -r ' F U E l C E U T (COUECTOR TANK I
PRATT ANO « H I T N E T ; S 7 tKrIte ENGINE A C C E S S O R I E S
•fUSELACE 80X1
BALI-SCREW FLAP CTUATOP
FLAP ORIVE MOTOR
•J-^J j\,-\rj^f
•/%•>.'•; ; = : i £
CANOPr DETONATING CORDIMOCI
: >
LAYOUT OF EQUiP^E-S" . D.-a-n by CD BURLEIGH 15m AUG.'61
TOBOUE TUBES TROL CCARI ACTUATOR INKAGE SPOILERS FOR ROLL CONTROL >>>*< PC J - S T B C k'tt c , c ' - S T i -.'f- P C ' . i A > < P i v j T . p c a : PLAKC P ' . U - P C P T • PIECE
FOLL SPAN SINGLE -SLOTTED FOwLER FLAPS
23
OPERATION SIMULATION MODEL
C
STARTI
OPERATION DATA I N FLT. SCHEDULE T i \ SORTIE N? AIRCRAFT OUTPUT F I G . 2-CAS DEFECT RATE DISTRIBUTION
25-1FLIGHT/NAV-ATTACK
_J
o ^
LU £
^ ^-z ^
LU <
LU er
CL " i :
<2 0
-10^
n / /UNDERCARRIAGE
/ /STRUCTURES
// FUEL SYSTEM
y
/
A FLYING/OP CON
^ ^ ^' l ' 2 ' 3 ' 1 ' 5 ' 6 ' 7 ' 8 ' 9 ' m '
s^
r'ST
EM
F I G . 3- 25
AIRCRAFT TURNROUND CHECKS. REFUEL & REARM TIME SCALED NETWORK
(WARTIME )
5 10
ELAPSED TIME (MINUTES)
Key to Time-Scaled Network
Task No. 1. Positioning of bowser and personnel prior to refuelling operation: | min.
2. Cockpit and safety checks prior to turnround operations: I min.
3. Connect fuel hose and earthing leads: J min.
4. Fuel a i r c r a f t , 1959 kg: 4 min.
5. Disconnect fuel hose and earthing leads: IJ mins.
6. Safety check prior to rearming; power supplies OFF, safety pins i n place, gun safety break disconnected e t c . : IJ mins. 7. A i r c r a f t turnround servicing actions: 8 mins.
8. Gun rear;:iing operation: 4J mins.
9. Rearm stb'd "Sidewinder" launcber: 3 mins.
10. Rearm and load braking parachute: 5 mins.
11. Rearm stb'd inboard (No.2) weapon pylon with "Maverick" missile: 5 mins.
12. Rearm port "Sidewinder" launcher: 3 mins.
13. Rearm stb'd outboard (No.l) weapon pylon with "Maverick" missile: 5 mins.
14. Rearm port inboard (No.3) weapon pylon with "Maverick" missile: 5 mins.
15. Rearm port outboard (No,4) weapon pylon with "Maverick" missile: 5 mins.
16. Final safety checks and inspections: I min.
2 J _ 2 — 2 - l 7 r - 1 - r l - r ^
VULNERABILITY 1. DIRECT KILL
2. INDIRECT OR CONDITIONAL KILL
MAIN U/C ENGINE BRAKING CHU"^' FUEL TANK ^/P»-ANE RC.U.(PORT) (COLLECTOR )
27
-Mini-CAS OPERATION SIMULATIONS : Pa=-01
1 l U U -1
