

Type of Document Dissertation Author Knill, Duane L. Author's Email Address knill@aoe.vt.edu URN etd-111097-15623 Title Implementing Aerodynamic Predictions from Computational Fluid Dynamics in Multidisciplinary Design Optimization of a High-Speed Civil Transport Degree Doctor of Philosophy Department Aerospace and Ocean Engineering Advisory Committee
Advisor Name Title Bernard Grossman Committee Chair Joseph A. Schetz Committee Member Layne T. Watson Committee Member Raphael T. Haftka Committee Member Robert W. Walters Committee Member William H. Mason Committee Member Keywords
- MDO CFD HSCT
Date of Defense 1997-12-01 Availability restricted Abstract A method to efficiently introduce supersonic drag predictions fromcomputational fluid dynamics (CFD) calculations in a
combined aerodynamic-structural optimization of a High-Speed Civil
Transport (HSCT) is presented.
To achieve this goal, the method must alleviate the large computational
burden associated with performing CFD analyses and reduce the
numerical noise present in the analyses.
This is accomplished through the use of response surface (RS)
methodologies, a variation of the variable-complexity modeling (VCM)
technique, and coarse grained parallel computing.
Variable-complexity modeling allows one to take advantage of the information
gained from inexpensive lower fidelity models while maintaining the
accuracy of the more expensive high fidelity methods.
The utility of the method is demonstrated on HSCT design problems
of five, ten, fifteen, and twenty design variables.
Motivation for including CFD predictions into the HSCT optimization
comes from studies detailing the differences in supersonic aerodynamic
predictions from linear theory, Euler, and parabolized Navier-Stokes (PNS)
calculations for HSCT configurations.
The effects of these differences in integrated forces and distributed loads
on the aircraft performance and structural weight are investigated.
These studies indicate that CFD drag solutions are required for accurate
HSCT performance and weight estimates.
Response surface models are also used to provide useful information to the
designer with minimal computational effort.
Investigations into design trade-offs and sensitivities to certain design
variables, available at the cost of evaluating a simple quadratic polynomial,
are presented.
In addition, a novel and effective approach to visualizing high dimensional,
highly constrained design spaces is enabled through the use of RS models.
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