TY - GEN
T1 - Application of optimization algorithms to scramjet inlet design
AU - Hasegawa, Susumu
AU - Knight, Doyle
PY - 2005
Y1 - 2005
N2 - An automated design optimization process is applied to both single and multi objective optimization problems of scramjet inlet design. This optimization process integrates together an optimizer with a mesh generator, a flow solver, and an objective analysis tool into an automated optimization loops because the flow simulation is required for every step along the line search and finding the feasible direction. This paper presents the implementation of these new design techniques by the gradient-based optimizer Sequential Quadratic Programming (SQP) and their application to scramjet inlet case in flight condition of Mach 8. The performance of scramjet inlets with uniform inflow is improved, and the optimized functions, that is, the total pressure recovery co-efficient increases by approximately 10%. The trade-off (also known as the ε-constraint) method is applied and implemented to find the Pareto optimal set formed by the non-dominated solutions of the feasible design. The objective functions are the total pressure loss and the drag, and some solutions are obtained to analyze the relations between the total pressure loss and the drag.
AB - An automated design optimization process is applied to both single and multi objective optimization problems of scramjet inlet design. This optimization process integrates together an optimizer with a mesh generator, a flow solver, and an objective analysis tool into an automated optimization loops because the flow simulation is required for every step along the line search and finding the feasible direction. This paper presents the implementation of these new design techniques by the gradient-based optimizer Sequential Quadratic Programming (SQP) and their application to scramjet inlet case in flight condition of Mach 8. The performance of scramjet inlets with uniform inflow is improved, and the optimized functions, that is, the total pressure recovery co-efficient increases by approximately 10%. The trade-off (also known as the ε-constraint) method is applied and implemented to find the Pareto optimal set formed by the non-dominated solutions of the feasible design. The objective functions are the total pressure loss and the drag, and some solutions are obtained to analyze the relations between the total pressure loss and the drag.
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U2 - https://doi.org/10.2514/6.2005-3207
DO - https://doi.org/10.2514/6.2005-3207
M3 - Conference contribution
SN - 1563477297
SN - 9781563477294
T3 - A Collection of Technical Papers - 13th AIAA/CIRA International Space Planes and Hypersonic Systems and Technologies Conference
SP - 74
EP - 85
BT - A Collection of Technical Papers - 13th AIAA/CIRA International Space Planes and Hypersonic Systems and Technologies Conference
PB - American Institute of Aeronautics and Astronautics Inc.
T2 - 13th AIAA/CIRA International Space Planes and Hypersonic Systems and Technologies Conference
Y2 - 16 May 2005 through 20 May 2005
ER -