An investigation on implementation of generating adversarial network-based surrogate models for prediction of turbine endwall film cooling effectiveness-Reference-Cited by-同舟云学术

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An investigation on implementation of generating adversarial network-based surrogate models for prediction of turbine endwall film cooling effectiveness

Published:2024-07 Issue: Volume:133 Page:108268
ISSN:0952-1976
Container-title:Engineering Applications of Artificial Intelligence
language:en
Short-container-title:Engineering Applications of Artificial Intelligence

Author:

Zhang Weixin,Liu Zhao^ORCID,Song Yu,Lu Yixuan,Feng Zhenping^ORCID

Funder

National Major Science and Technology Projects of China

Publisher

Elsevier BV

Reference39 articles.

1. Irregular shape optimization for the film cooling Nozzle of gas turbines using numerical optimization tool;Alshehaby,2019

2. Numerical optimization of geometry parameters for shaped film cooling holes;Alshehaby,2017

3. Effects of freestream Mach number, Reynolds number, and boundary layer thickness on film cooling effectiveness of shaped holes;Anderson,2016

4. Correlation of film-cooling effectiveness from thermographic measurements at engine like conditions;Baldauf,2002

5. StarGAN: unified generative adversarial networks for multi-domain image-to-image translation;Choi,2018

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