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OCR for page 18

18
x
y
Figure 18. X-Y origin for aircraft undershoots.
length is adjusted for each type of aircraft according to
MTOW and the EMAS bed length, according to the follow-
ing steps:
y
1. The maximum runway exit speed to hold the aircraft
within the EMAS bed is calculated according to the
Figure 19. Y origin for aircraft veer-offs.
model presented below. The adjusted R2 for this model
is 89%.
For Table 5, the following are the parameters represented: v = 3.0057 - 6.8329 log (W ) + 31.1482 log ( S )
d = any given distance of interest; where:
x = the longitudinal distance from the runway end; v = the maximum exit speed in m/s;
P{d>x} = the probability the wreckage location exceeds dis- W = the maximum takeoff weight of the aircraft in kg; and
tance x from the runway end; S = the EMAS bed length in meters.
y = the transverse distance from the extended runway
centerline (overruns and undershoots) or from the 2. The maximum runway exit speed estimated using the pre-
runway border (veer-offs); and vious regression equation, along with the EMAS bed length
P{d>y} = the probability the wreckage location exceeds dis- (SEMAS), is input in the following equation to calculate the
tance y from the extended runway centerline (over- deceleration of the aircraft in the EMAS bed.
runs and undershoots) or from the runway border v2
(veer-offs). aEMAS =
2S
Figures 2229 illustrate the models presented in Table 5.
3. The runway length factor is then estimated as follows:
EMAS Deceleration Model aEMAS
RLF =
a RSA
The analysis tool developed in this research includes the
capability to evaluate RSAs with EMAS beds. The details of 4. The runway length factor is then estimated as follows:
the development are presented in Appendix E.
The same location models for overruns are used when aEMAS
RLF =
EMAS beds are available in the RSA. However, the bed a RSA
Probability location
Probability location
Exceeds y
Exceeds x
n m
P{ Location x } e ax P{ Location y} e by
P{Loc > x1} P{Loc > y1}
rwy end x1 Distance x from runway end X
rwy border
y1 Distance y from runway border y
Figure 20. Typical model for aircraft overruns. Figure 21. Typical model for aircraft veer-offs.

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Table 5. Summary of location models.
Type of Type of Model R2 # of
Accident Data Points
LDOR X 0.00321x 0.984941 99.8% 305
P{d x} e
Y 0.20983 y 0.4862 93.9% 225
P{d y} e
LDUS X 0.01481x 0.751499 98.7% 83
P{d x} e
Y 0.02159 y 0.773896 98.6% 86
P{d y} e
LDVO Y 0.02568y 0.803946 99.5% 126
P{d y} e
TOOR X 0.00109 x 1.06764 99.2% 89
P{d x} e
Y 0.04282y 0.659566 98.7% 90
P{d y} e
TOVO Y 0.01639 y 0.863461 94.2% 39
P{d y} e
Prob=exp((-.00321)*X**(.984941))
R2=99.8%
1.0
Probability of Stopping Beyond X
0.8
0.6
0.4
0.2
0.0
0 400 800 1200 1600 2000
Distance X from Runway End (ft)
Figure 22. Longitudinal location model for landing overruns.
Prob=exp((-.20983)*Y**(.486))
R2=93.9%
1.0
Probability of Stopping Beyond Y
0.8
0.6
0.4
0.2
0.0
0 200 400 600 800 1000 1200
Distance Y from Extended Runway Centerline (ft)
Figure 23. Transverse location model for landing overruns.

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Prob=exp((-.01481)*X**(.751499))
R2=98.7%
1.0
Probability of Touching Down Before X
0.8
0.6
0.4
0.2
0.0
0 400 800 1200 1600 2000
Distance X from Runway Arrival End (ft)
Figure 24. Longitudinal location model for landing
undershoots.
Prob=exp((-.02159)*Y**(.773896))
R2=98.6%
1.0
Probability of Touching Down Beyond Y
0.8
0.6
0.4
0.2
0.0
0 200 400 600 800 1000
Distance Y from Runway Extended Centerline (ft)
Figure 25. Transverse location model for landing undershoots.

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Prob=exp((-.02568)*Y**(.803946))
R2=99.5%
1.0
Probability of Stopping Beyond Y
0.8
0.6
0.4
0.2
0.0
0 200 400 600 800 1000
Distance Y from Runway Edge (ft)
Figure 26. Lateral location model for landing veer-offs.
Prob=exp((-.00109)*X**(1.06764))
R2=99.2%
1.0
Probability of Stopping Beyond X
0.8
0.6
0.4
0.2
0.0
0 400 800 1200 1600 2000
Distance X from Runway End (ft)
Figure 27. Longitudinal location model for takeoff overruns.