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Coupled Aero-Thermodynamics Optimization for the Cooling System of a Turbine Vane

[+] Author Affiliations
Zhongran Chi, Jing Ren, Hongde Jiang

Tsinghua University, Beijing, China

Paper No. GT2013-94528, pp. V03BT11A010; 12 pages
doi:10.1115/GT2013-94528
From:
  • ASME Turbo Expo 2013: Turbine Technical Conference and Exposition
  • Volume 3B: Heat Transfer
  • San Antonio, Texas, USA, June 3–7, 2013
  • Conference Sponsors: International Gas Turbine Institute
  • ISBN: 978-0-7918-5515-7
  • Copyright © 2013 by ASME

abstract

Cooling system design for the air-cooled turbine is a critical issue in modern gas turbine engineering. Advances in CFD technology and optimization methodology is providing new prospects for turbine cooling system design, that the optimum cooling system of the vanes and blades could be designed automatically by the optimization search coupled with the Conjugate Heat Transfer (CHT) analysis.

An optimization platform consists of the Generic Algorithms (GA), a mesh generation tool (Coolmesh), and the CHT solver (ANSYS CFX) is presented in this paper. The optimization study was aimed at finding the optimum cooling structure for the 2nd stage vane of the E3 engine, with acceptable metal temperature distribution and limited coolant amount simultaneously. The vane was installed with impingement and pin-fin cooling structure. The optimization search involved the design of critical parameters of the cooling system, including the size of impingement tube, diameter and distribution of impingement holes, and the size and distribution of pin-fin near trailing edge.

The optimization design was carried under two engine operating conditions to explore the affect of different boundary conditions. A constant pressure drop was assumed within the cooling system during each optimization. To make the problem computationally faster, the simulations were approached for the interior only (solid and coolant). A weighed function of temperature distribution and coolant mass flow was used as the objective of the Single Objective Generic Algorithms (SOGA). The result showed that the optimal cooling system configuration with considerable cooling performance could be designed through SOGA optimization without human interference.

Copyright © 2013 by ASME

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