xacstrake = yM.A.C.strake tan LEstrake + 0.25 M.A.C.strake (subsonic)
= (0.33 ft) tan 80o + 0.25 ( 6.4 ft) = 3.5 ft
x acstrake = yM.A.C.strake tan LEstrake + 0.50 M.A.C.strake (supersonic)
= (0.33 ft) tan 80o + 0.50 ( 6.4 ft) = 5.1 ft
but these are defined relative to the leading edge of the strake root chord, not the wing root chord. From Table 6.3, the strake root is 8 ft forward of the wing root, so relative to the wing:
x acstrake = -4.5 ft (subsonic)
x acstrake = -2.9 ft (supersonic)
and:
= 6.5 ft (subsonic)
= 9.1 ft (supersonic)
Now, adding the effect of the fuselage, using Cl wing/strake = 0.068/o (predicted in Section 4.7) and the fact that the wing root leading edge is 20 ft aft of the fuselage nose, so that lacwing/strake = 20 ft + xacwing/strake :
= 6.4 (subsonic)
To perform the supersonic calculation, supersonic lift curve slope must be predicted. A specific Mach number must be chosen. For M = 1.5:
![](data:image/png;base64,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) = 0.051/o
= 9.0 ft (supersonic)
Next, the aerodynamic center of the F-16A stabilator is located:
stabilator = ctip / croot = 2 ft /10 ft = 0.2
= 6.9 ft
= 3.5 ft
xacstab = yM.A.C. stab tan LE stab + 0.25 M.A.C. stab (subsonic)
= (3.5 ft) tan 40o + 0.25 ( 6.9 ft) = 4.7 ft
xacstab = yM.A.C. stab tan LE stab + 0.4 M.A.C. stab (supersonic)
= (3.5 ft) tan 40o + 0.50 ( 6.9 ft) = 6.4 ft
These are defined relative to the leading edge of the stabilator root chord. From Table 6.3, the stabilator root is 17.5 ft aft of the wing root, so relative to the wing:
x ac stab = 22.2 ft (subsonic)
x ac stab = 23.9 ft (supersonic)
But the distance of interest for the stabilator is lt, the distance from the stabilator’s aerodynamic center to the aircraft center of gravity. Table 6.3 lists the center of gravity as 0.35 M.A.C., so relative to the wing root:
xcg = yM.A.C. tan LE + 0.35 M.A.C.
= (5.875 ft) tan 40o + 0.35 ( 11.4 ft) = 8.9 ft
and:
lt = x ac stab - xcg = 22.2 ft - 8.9 ft = 13.3 ft (subsonic)
= 23.9 ft -8.9 ft = 15 ft (supersonic)
It is now possible to calculate tail volume ratio:
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