Unformatted text preview: profile of an airfoil. The moment coefficients for the two airfoils are the same they have the same angle of attack
and the same camber. PROBLEM 3a
NACA 0012
0.3
0.2
0.1 y 0
0.1
0.2
0.3
0.2 0.4 0.6 0.8 1 x Fig.1. Airfoil Geometry.
PROBLEM 3b
The pressure coefficient plots based on different compressibility rules are shown in figures 25. M=0.4
1 Cp__PG
Cp__KT
Cp__L 0.8
0.6
0.4 Cp 0.2
0
0.2
0.4
0.6
0.8
1
0 0.2 0.4 0.6 0.8 1 x
Fig.2. Pressure coefficient variation along the length of the airfoil at M=0.4. M=0.6
1 Cp__PG
Cp__KT
Cp__L 0.8
0.6
0.4 Cp 0.2
0
0.2
0.4
0.6
0.8
1
0 0.2 0.4 0.6 0.8 1 x
Fig.3. Pressure coefficient variation along the length of the airfoil at M=0.6. M=0.7
1 Cp__PG
Cp__KT
Cp__L 0.8
0.6
0.4 Cp 0.2
0
0.2
0.4
0.6
0.8
1
0 0.2 0.4 0.6 0.8 1 x
Fig.4. Pressure coefficient variation along the length of the airfoil at M=0.7. M=0.75
1 Cp__PG
Cp__KT
Cp__L 0.8
0.6
0.4 Cp 0.2
0
0.2
0.4
0.6
0.8
1
0 0.2 0.4 0.6 0.8 1 x
Fig.5. Pressure coefficient variation along the length of the airfoil at M=0.75.
PROBLEM 3c
From figures 25 we see that at a low subsonic Mach number of 0.4, all three methods do a good job in
predicting the compressible pressure coefficient and the plots match well with the experimental data
given in the lecture notes. As the Mach number is increased, the Laitone method gives the highest peak
value for the pressure coefficient. The PrandtlGlauert rule is the least sensitive to Mach number
variation compared to the other two methods which account for nonlinear effects in the compressible
potential equation. Overall, the KarmanTsien rule gave the best representation of the compressible
coefficient values. It must be pointed out that all three rules give the same vale for Cp over the airfoil
surface where local Mach numbers are well below sonic conditions.
PROBLEM 3d
The expression for...
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 Spring '09
 COLLICOTT

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