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Multi-Objective Optimization of Convective Heat Transfer for a Composite Internal and Film Cooling Structure

Zhang, Guohua LU ; Zhu, Huaitao ; Xie, Gongnan LU and Sunden, Bengt LU (2023) In Journal of Heat Transfer 145(3).
Abstract

This paper conducted a multi-objective optimization work for a composite internal and film cooling structure. The pitch-To-height ratio of the ribs, the inclination angle of the ribs, and the inclination angle of the film hole are chosen as the three design variables to enhance the heat transfer performance, improve the film cooling effectiveness and reduce the pressure loss of the internal channel flow. During the optimization process, the Latin hypercube sampling method is adopted to select 26 sample points from the design space. The response values with higher fidelity at the sample points are calculated using computational fluid dynamics (CFD) simulations. Among the 26 sample points, 21 are used to construct a surrogate model of... (More)

This paper conducted a multi-objective optimization work for a composite internal and film cooling structure. The pitch-To-height ratio of the ribs, the inclination angle of the ribs, and the inclination angle of the film hole are chosen as the three design variables to enhance the heat transfer performance, improve the film cooling effectiveness and reduce the pressure loss of the internal channel flow. During the optimization process, the Latin hypercube sampling method is adopted to select 26 sample points from the design space. The response values with higher fidelity at the sample points are calculated using computational fluid dynamics (CFD) simulations. Among the 26 sample points, 21 are used to construct a surrogate model of each objective function while the rest of them are adopted to validate the correctness of the established surrogate model. By combining the Kriging surrogate model with a nondominated sorting genetic algorithm, the Pareto optimal front is obtained after the optimization process. Finally, comparison and analysis are conducted with respect to the cooling performance and mechanisms between the reference model and the selected three representative optimized models. Results show that the optimized three models can not only improve the film cooling effectiveness but also reduce the pressure loss of the channel flow and enhance the heat transfer. In addition, it is found that the optimized model induces an anticlockwise rotating vortex, which entrains more coolant near the target surface. The inclined ribs of the optimized models induce a secondary flow along the inclined ribs, which enhances the flow mixing and augments the heat transfer performance.

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Please use this url to cite or link to this publication:
author
; ; and
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Flow characteristics, Gas turbine cooling, Multi-objective optimization, Nondominated sorting genetic algorithm, Surrogate model
in
Journal of Heat Transfer
volume
145
issue
3
article number
031802
publisher
American Society Of Mechanical Engineers (ASME)
external identifiers
  • scopus:85148073832
ISSN
0022-1481
DOI
10.1115/1.4055676
language
English
LU publication?
yes
id
d709abf2-40e7-4f90-9525-af8659eb5137
date added to LUP
2023-03-03 13:25:10
date last changed
2023-11-21 16:44:25
@article{d709abf2-40e7-4f90-9525-af8659eb5137,
  abstract     = {{<p>This paper conducted a multi-objective optimization work for a composite internal and film cooling structure. The pitch-To-height ratio of the ribs, the inclination angle of the ribs, and the inclination angle of the film hole are chosen as the three design variables to enhance the heat transfer performance, improve the film cooling effectiveness and reduce the pressure loss of the internal channel flow. During the optimization process, the Latin hypercube sampling method is adopted to select 26 sample points from the design space. The response values with higher fidelity at the sample points are calculated using computational fluid dynamics (CFD) simulations. Among the 26 sample points, 21 are used to construct a surrogate model of each objective function while the rest of them are adopted to validate the correctness of the established surrogate model. By combining the Kriging surrogate model with a nondominated sorting genetic algorithm, the Pareto optimal front is obtained after the optimization process. Finally, comparison and analysis are conducted with respect to the cooling performance and mechanisms between the reference model and the selected three representative optimized models. Results show that the optimized three models can not only improve the film cooling effectiveness but also reduce the pressure loss of the channel flow and enhance the heat transfer. In addition, it is found that the optimized model induces an anticlockwise rotating vortex, which entrains more coolant near the target surface. The inclined ribs of the optimized models induce a secondary flow along the inclined ribs, which enhances the flow mixing and augments the heat transfer performance.</p>}},
  author       = {{Zhang, Guohua and Zhu, Huaitao and Xie, Gongnan and Sunden, Bengt}},
  issn         = {{0022-1481}},
  keywords     = {{Flow characteristics; Gas turbine cooling; Multi-objective optimization; Nondominated sorting genetic algorithm; Surrogate model}},
  language     = {{eng}},
  number       = {{3}},
  publisher    = {{American Society Of Mechanical Engineers (ASME)}},
  series       = {{Journal of Heat Transfer}},
  title        = {{Multi-Objective Optimization of Convective Heat Transfer for a Composite Internal and Film Cooling Structure}},
  url          = {{http://dx.doi.org/10.1115/1.4055676}},
  doi          = {{10.1115/1.4055676}},
  volume       = {{145}},
  year         = {{2023}},
}