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| Content Provider | The American Society of Mechanical Engineers (ASME) Digital Collection |
|---|---|
| Author | Chen, Naixing Zhang, Hongwu Ning, Fangfei Xu, Yanji Huang, Weiguang |
| Copyright Year | 2006 |
| Abstract | This paper describes a procedure for a rapid and accurate 3D aerodynamic optimization of high performance turbine blades. This procedure has been developed to account for the complicated geometrical aspects and the complex nature of the associated fluid flow, while remaining simple, practical and demanding less computing power. The focus has been placed on the blade geometrical representation using a set of simple algebraic equations (blade parameterization) and on the aerodynamic optimization methodology based on the numerical computations by a N.S. solver. The turbine blade, including thickness distribution and camber line for each section of the blade span and radial stacking line, has been defined by polynomials, allowing investigation of the influence of any single-parameter change on blade performance. An improved response surface method, by incorporating a simulated annealing algorithm (RS-SAM), has been found to improve the accuracy and to strengthen the optimum-searching ability. A multi-objective response surface method (MORSM) has also been included for testing. One example is given here to demonstrate the effectiveness of the procedure. |
| Sponsorship | International Gas Turbine Institute |
| Starting Page | 1169 |
| Ending Page | 1180 |
| Page Count | 12 |
| File Format | |
| ISBN | 079184241X |
| DOI | 10.1115/GT2006-90104 |
| e-ISBN | 0791837742 |
| Volume Number | Volume 6: Turbomachinery, Parts A and B |
| Conference Proceedings | ASME Turbo Expo 2006: Power for Land, Sea, and Air |
| Language | English |
| Publisher Date | 2006-05-08 |
| Publisher Place | Barcelona, Spain |
| Access Restriction | Subscribed |
| Subject Keyword | Turbine blades Algebra Algorithms Blades Fluid dynamics Computation Simulated annealing Polynomials Response surface methodology Optimization Testing |
| Content Type | Text |
| Resource Type | Article |
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