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Journal of Central South University

, Volume 24, Issue 5, pp 1183–1189 | Cite as

Data mining optimization of laidback fan-shaped hole to improve film cooling performance

  • Chun-hua Wang (王春华)
  • Jing-zhou Zhang (张靖周)
  • Jun-hui Zhou (周君辉)
Article

Abstract

To improve the cooling performance, shape optimization of a laidback fan-shaped film cooling hole was performed. Three geometric parameters, including hole length, lateral expansion angle and forward expansion angle, were selected as the design parameters. Numerical model of the film cooling system was established, validated, and used to generate 32 groups of training samples. Least square support vector machine (LS-SVM) was applied for surrogate model, and the optimal design parameters were determined by a kind of chaotic optimization algorithm. As hole length, lateral expansion angle and forward expansion angle are 90 mm, 20° and 5°, the area-averaged film cooling effectiveness can reach its maximum value in the design space. LS-SVM coupled with chaotic optimization algorithm is a promising scheme for the optimization of shaped film cooling holes.

Key words

gas turbine laidback fan-shaped film cooling holes optimization support vector machine (SVM) chaotic optimization algorithm 

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Copyright information

© Central South University Press and Springer-Verlag GmbH Germany 2017

Authors and Affiliations

  • Chun-hua Wang (王春华)
    • 1
  • Jing-zhou Zhang (张靖周)
    • 1
    • 2
  • Jun-hui Zhou (周君辉)
    • 1
  1. 1.College of Energy and Power EngineeringNanjing University of Aeronautics and AstronauticsNanjingChina
  2. 2.Collaborative Innovation Center of Advanced Aero-EngineBeijingChina

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