Shape Design Optimization
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[[Direct design]] can be further classified into [[gradient-based methods]] and [[global search methods]]. | [[Direct design]] can be further classified into [[gradient-based methods]] and [[global search methods]]. | ||
Gradient-based methods will reach a local optimum design, while global search methods can in theory reach a global optimum. But the cost of global search methods is prohibitively huge with a large number of design variables. | Gradient-based methods will reach a local optimum design, while global search methods can in theory reach a global optimum. But the cost of global search methods is prohibitively huge with a large number of design variables. | ||
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| + | '''ISSUES in Direct Design Shape Optimization for CFD''' | ||
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| + | 1) Huge Processing power is pre-requisite. This factor is becoming less an obstacle as computing power is going cheaper as we speak. | ||
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| + | 2) Automatic surface or shell modification in unison with automatic volumesh adjustment. As the surface changes and develops according to a preset lower bound and upper bound in an optimization code, the volumesh domain is affected unprecedentedly. Refinement in the volumesh and quality aspects of the volumesh have to built into the CFD solver to ensure smooth flow in the auto-optimization process. | ||
Revision as of 09:35, 19 June 2007
Aerodynamic shape design optimization can be classified as two categories: inverse design and direct design. Inverse design requires specification of target pressure or velocity distribution on the surface of an body, of which the success highly depends on the experience of the designer. Direct design can be further classified into gradient-based methods and global search methods. Gradient-based methods will reach a local optimum design, while global search methods can in theory reach a global optimum. But the cost of global search methods is prohibitively huge with a large number of design variables.
ISSUES in Direct Design Shape Optimization for CFD
1) Huge Processing power is pre-requisite. This factor is becoming less an obstacle as computing power is going cheaper as we speak.
2) Automatic surface or shell modification in unison with automatic volumesh adjustment. As the surface changes and develops according to a preset lower bound and upper bound in an optimization code, the volumesh domain is affected unprecedentedly. Refinement in the volumesh and quality aspects of the volumesh have to built into the CFD solver to ensure smooth flow in the auto-optimization process.
