dc.contributor.author | Xing, X.Q. | |
dc.contributor.author | Damodaran, Murali | |
dc.date.accessioned | 2003-12-23T03:23:59Z | |
dc.date.available | 2003-12-23T03:23:59Z | |
dc.date.issued | 2002-01 | |
dc.identifier.uri | http://hdl.handle.net/1721.1/4019 | |
dc.description.abstract | 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 | en |
dc.description.sponsorship | Singapore-MIT Alliance (SMA) | en |
dc.format.extent | 265864 bytes | |
dc.format.mimetype | application/pdf | |
dc.language.iso | en_US | |
dc.relation.ispartofseries | High Performance Computation for Engineered Systems (HPCES); | |
dc.subject | global optimization | en |
dc.subject | simultaneous perturbation stochastic approximation method | en |
dc.subject | simulated annealing | en |
dc.subject | transonic fan design | en |
dc.title | Optimal Design of Transonic Fan Blade Leading Edge Shape Using CFD and Simultaneous Perturbation Stochastic Approximation Method | en |
dc.type | Article | en |