A methodology for developing optimized designs for symmetric-centerbody ramjet powered missiles, using a genetic algorithm as the driver for the system optimization process, has been developed. The methodology described in this paper allows for a comprehensive but efficient exploration of the design space. This global optimization process is made possible by performance prediction codes, which can provide preliminary design-level accuracy very efficiently. This work demonstrates the first truly comprehensive design strategy for this type of device. The paper contains a discussion of the methodology and shows results for a typical design scenario.

1.
Anderson
,
M. B.
,
Burkhalter
,
J. E.
, and
Jenkins
,
R. M.
, 2001, “
Design of a Guided Missile Interceptor Using Genetic Algorithms
,”
J. Spacecr. Rockets
0022-4650,
38
(
1
) pp.
28
35
.
2.
Anderson
,
M. B.
,
Burkhalter
,
J. E.
, and
Jenkins
,
R. M.
, 2001, “
Intelligent Systems Approach to Designing an Interceptor to Defeat Highly Maneuverable Targets
,” 39th AIAA Aerospace Science Meeting, Reno, January 2001, AIAA Paper No. 2001-1123.
3.
Anderson
,
M. B.
,
Burkhalter
,
J. E.
, and
Jenkins
,
R. M.
, 1999, “
Missile Performance Optimization Using Pareto Genetic Algorithms
,” 37th AIAA Aerospace Sciences Conference, Reno, NV, January 1999, AIAA 99-0261.
4.
Krishnakumar
,
K.
, and
Goldberg
,
D. E.
, 1992, “
Control System Optimization Using Genetic Algorithms
,”
J. Guid. Control Dyn.
0731-5090,
15
(
3
), p.
735
.
5.
Schoonover
,
P. L.
,
Crossley
,
W. A.
, and
Heister
,
S. D.
, 1998, “
Application of Genetic Algorithms to the Optimization of Hybrid Rockets
,” 34th AIAA/ASME/SAE/ASEE Joint Propulsion Conference and Exhibit, Cleveland, OH, AIAA Paper No. 98-3349.
6.
Mondoloni
,
S.
, 1998, “
A Genetic Algorithm for Determining Optimal Flight Trajectories
,” AIAA Guidance, Navigation, and Control Conference and Exhibit, Boston, MA, AIAA Paper No. 98-4476.
7.
Tong
,
S. S.
, 1992, “
Turbine Preliminary Design Using Artificial Intelligence and Numerical Optimization Techniques
.”
ASME J. Turbomach.
0889-504X,
114
(
1
), pp.
277
286
.
8.
Oyama
,
A.
,
Obayashi
,
S.
, and
Nakahashi
,
K.
, 1997, “
Transonic Wing Optimization Using Genetic Algorithm
,” 13th Computational Fluid Dynamics Conference, Norfolk, VA, July 1997, AIAA Paper No. 97-1854.
9.
Selig
,
M. S.
, and
Coverstone-Carroll
,
V. L.
, 1996, “
Application of a Genetic Algorithm to Wind Turbine Design
,”
ASME J. Energy Resour. Technol.
0195-0738,
118
, pp.
22
28
.
10.
Torella
,
G.
, and
Blasi
,
L.
, 2000, “
The Optimization of Gas Turbine Engine Design by Genetic Algorithms
,” 36th AIAA/ASME/SAE/ASEE Joint Propulsion Conference and Exhibit, Huntsville, AL, AIAA Paper No. 2000-3710.
11.
Wollam
,
J. D.
,
Kramer
,
S.
,
Campbell
,
S.
, 2000, “
Reverse Engineering of Foreign Missiles Via Genetic Algorithms
,” 38th AIAA Aerospace Sciences Meeting and Exhibit, Reno, NV, January 2000, AIAA Paper No. 2000-0685.
12.
Nelson
,
A.
,
Nemec
,
M.
,
Aftosmis
,
M.
, and
Pulliam
,
T.
, 2005, “
Aerodynamic Optimization of Rocket Control Surfaces Using Cartesian Methods and CAD Geometry
,” 23rd AIAA Applied Aerodynamics Conference, Toronto, June 2005, AIAA Paper No. 2005-4836.
13.
Ahujz
,
V.
, and
Hosangadi
,
A.
, 2005, “
Design Optimization of Complex Flowfields Using Evolutionary Algorithms and Hybrid Unstructured CFD
,” 23rd AIAA Applied Aerodynamics Conference, Toronto, June 2005, AIAA Paper No. 2005-4984.
14.
Mattingly
,
J. D.
, 1996,
Elements of Gas Turbine Propulsion
,
McGraw-Hill
,
New York, NY
, pp.
820
822
.
15.
Flack
,
R. D.
, 2005,
Fundamentals of Jet Propulsion with Applications
,
Cambridge University Press
, Cambridge, England.
16.
Anderson
,
J. D.
, 1990,
Modern Compressible Flow
,
2nd ed.
,
McGraw-Hill
,
New York
, pp.
294
306
.
17.
NACA Report 1135, 1953, “
Equations, Tables and Charts for Compressible Flow
,” Ames Research Staff, Ames Aeronautical Laboratory, Moffett Field, CA.
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