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Aerodynamic Design of Unmanned and Scaled Supersonic ...

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K. Yoshida <strong>and</strong> Y. Makino<br />

drag under the limitation <strong>of</strong> design condition <strong>and</strong> planform constraints.<br />

The key point <strong>of</strong> warp design is to suppress theoretical infinite load at leading edge. This<br />

usually leads to a certain leading edge droop to achieve an attached flow condition, because<br />

leading edge separation vortex is induced by local high angle <strong>of</strong> attack due to highly swept<br />

leading edge. This is the second principle for reducing supersonic drag.<br />

3) Area-Ruled Body<br />

According to the supersonic slender body theory [5], wave drag due to volume <strong>of</strong> a<br />

complete aircraft is generally related to so-called supersonic cross sectional area distribution.<br />

This area means the projection <strong>of</strong> oblique cross sectional area <strong>of</strong> airplane cut by Mach cone<br />

on a plane vertical to streamwise direction. The optimum axisymmetric body with the lowest<br />

wave drag due to volume was already derived using this formulation. It was called “Sears-<br />

Haack body”. If a wing <strong>and</strong> tails <strong>of</strong> a complete aircraft are specified, we suppose that fuselage<br />

geometry should be improved to adjust total supersonic area distribution to that <strong>of</strong> Sears-<br />

Haack body. It is very effective to reduce the wave drag due to total volume <strong>of</strong> the aircraft.<br />

This improved fuselage is generally called area-ruled body. This rule is the third principle <strong>of</strong><br />

reducing supersonic drag, especially interference drag between wings, tails <strong>and</strong> fuselage [5].<br />

4) Natural Laminar Flow Wing<br />

It is well expected that an aerodynamic optimum combination <strong>of</strong> the pressure drag<br />

reduction concepts mentioned above has large effect in reducing supersonic cruise drag.<br />

However, it is not easy to obtain the maximum gain <strong>of</strong> drag reduction effect, because we must<br />

consider several constraints that are not included in linear theory. Therefore, any other drag<br />

reduction concept is necessary to improve the L/D <strong>of</strong> a future advanced SST.<br />

Reducing friction drag is one <strong>of</strong> the c<strong>and</strong>idates. A laminar airfoil design concept is usually<br />

based on suppressing Tollmien-Schlichting (T-S) wave instability. For a low aspect ratio wing<br />

with highly swept leading edge, transition due to cross-flow (C-F) instability is dominant at<br />

forward part <strong>of</strong> the wing. First <strong>of</strong> all, an optimum pressure distribution must be found for<br />

suppressing the C-F instability. The key point is to reduce the region generating cross-flow.<br />

Cross-flow is produced by chordwise pressure gradient. At the front part <strong>of</strong> the wing, there is<br />

always severe acceleration. Therefore, it is very effective to set narrow acceleration region.<br />

This leads to a pressure distribution with steep gradient at front.<br />

Since the T-S instability becomes dominant after mid-chord <strong>of</strong> the wing, gradual<br />

acceleration is effective to suppress the T-S instability. Fortunately, most <strong>of</strong> SST planforms<br />

have supersonic trailing edge <strong>and</strong> require no recovery <strong>of</strong> trailing edge pressure. As a result, it<br />

was found that pressure distribution <strong>of</strong> the NLF wing had to have steep acceleration at front<br />

<strong>and</strong> gradual acceleration from the front to the trailing edge. At the first step <strong>of</strong> the NLF wing<br />

design, we already found an optimum pressure distribution to delay transition [6], using a<br />

practical transition prediction method (SALLY code [7]) based on e N method [8].<br />

As the next step, we must solve a so-called inverse design problem to achieve this pressure<br />

distribution. Therefore, we developed an original CFD-based inverse method [9]. This inverse<br />

method consists <strong>of</strong> iteration loop for the following two routines: i) flow estimation using a<br />

CFD code, <strong>and</strong> ii) modifying the geometry based on the difference between target <strong>and</strong> each<br />

5

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