| dc.creator |
Xing, X.Q. |
|
| dc.creator |
Damodaran, Murali |
|
| dc.date |
2003-12-23T03:23:59Z |
|
| dc.date |
2003-12-23T03:23:59Z |
|
| dc.date |
2002-01 |
|
| dc.date.accessioned |
2013-10-09T02:33:40Z |
|
| dc.date.available |
2013-10-09T02:33:40Z |
|
| dc.date.issued |
2013-10-09 |
|
| dc.identifier |
http://hdl.handle.net/1721.1/4019 |
|
| dc.identifier.uri |
http://koha.mediu.edu.my:8181/xmlui/handle/1721 |
|
| dc.description |
Simultaneous Perturbation Stochastic Approximation method has attracted considerable application in many different areas such as statistical parameter estimation, feedback control, simulation-based optimization, signal & image processing, and experimental design. In this paper, its performance as a viable optimization tool is demonstrated by applying it first to a simple wing geometry design problem for which the objective function is described by an empirical formula from aircraft design practice and then it is used in a transonic fan blade design problem in which the objective function is not represented by any explicit function but is estimated at each design iteration by a computational fluid dynamics algorithm for solving the Navier-Stokes equations |
|
| dc.description |
Singapore-MIT Alliance (SMA) |
|
| dc.format |
265864 bytes |
|
| dc.format |
application/pdf |
|
| dc.language |
en_US |
|
| dc.relation |
High Performance Computation for Engineered Systems (HPCES); |
|
| dc.subject |
global optimization |
|
| dc.subject |
simultaneous perturbation stochastic approximation method |
|
| dc.subject |
simulated annealing |
|
| dc.subject |
transonic fan design |
|
| dc.title |
Optimal Design of Transonic Fan Blade Leading Edge Shape Using CFD and Simultaneous Perturbation Stochastic Approximation Method |
|
| dc.type |
Article |
|