高压涡轮叶片尖部薄膜冷却孔位置的气热优化

IF 1.6 4区 工程技术 Q3 ENGINEERING, MECHANICAL
Faruk Yildiz, E. Alpman, L. Kavurmacioğlu, Cengiz Camci
{"title":"高压涡轮叶片尖部薄膜冷却孔位置的气热优化","authors":"Faruk Yildiz, E. Alpman, L. Kavurmacioğlu, Cengiz Camci","doi":"10.1115/1.4064431","DOIUrl":null,"url":null,"abstract":"\n This paper presents a time-efficient method to optimize the positions of film cooling holes on a gas turbine blade's squealer tip for cooling and aerodynamic performance. A computational approach is employed for the optimization, including validations against experiments. Five discrete film cooling holes are considered, and two different blowing ratios of 0.4 and 1.0 are studied. The positions of cooling holes on the tip along the tangential direction are varied as the input parameters of optimization. The multi-objective optimization uses an algorithm with an artificial neural network for fast fitness function predictions. The best cooling configuration found by the optimization achieves a 13.43% reduction in total heat flux and a 0.4% increase in aerodynamic loss when the blowing rate is 1.0. Including the casing relative motion in the computations results in a total pressure loss coefficient increase of about 8 % for both blowing ratios. For M=1.0, imposing the casing's motion results in a 10.2% reduction in total heat transfer to the tip compared to the stationary casing. For the lower blowing rate of 0.4, the total heat flux reduction to the tip is 12.0% because of imposed casing motion. Hence, the cooling effectiveness can be improved by employing the particular position optimization method presented in this study. The results suggest that experimental and computational heat transfer studies on cooled turbine blade tips, especially in cascade arrangements, need to consider the relative motion of the blade tip.","PeriodicalId":17404,"journal":{"name":"Journal of Thermal Science and Engineering Applications","volume":"17 14","pages":""},"PeriodicalIF":1.6000,"publicationDate":"2024-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Aerothermal Optimization of Film Cooling Hole Locations on the Squealer Tip of an HP Turbine Blade\",\"authors\":\"Faruk Yildiz, E. Alpman, L. Kavurmacioğlu, Cengiz Camci\",\"doi\":\"10.1115/1.4064431\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\\n This paper presents a time-efficient method to optimize the positions of film cooling holes on a gas turbine blade's squealer tip for cooling and aerodynamic performance. A computational approach is employed for the optimization, including validations against experiments. Five discrete film cooling holes are considered, and two different blowing ratios of 0.4 and 1.0 are studied. The positions of cooling holes on the tip along the tangential direction are varied as the input parameters of optimization. The multi-objective optimization uses an algorithm with an artificial neural network for fast fitness function predictions. The best cooling configuration found by the optimization achieves a 13.43% reduction in total heat flux and a 0.4% increase in aerodynamic loss when the blowing rate is 1.0. Including the casing relative motion in the computations results in a total pressure loss coefficient increase of about 8 % for both blowing ratios. For M=1.0, imposing the casing's motion results in a 10.2% reduction in total heat transfer to the tip compared to the stationary casing. For the lower blowing rate of 0.4, the total heat flux reduction to the tip is 12.0% because of imposed casing motion. Hence, the cooling effectiveness can be improved by employing the particular position optimization method presented in this study. The results suggest that experimental and computational heat transfer studies on cooled turbine blade tips, especially in cascade arrangements, need to consider the relative motion of the blade tip.\",\"PeriodicalId\":17404,\"journal\":{\"name\":\"Journal of Thermal Science and Engineering Applications\",\"volume\":\"17 14\",\"pages\":\"\"},\"PeriodicalIF\":1.6000,\"publicationDate\":\"2024-01-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Thermal Science and Engineering Applications\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://doi.org/10.1115/1.4064431\",\"RegionNum\":4,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ENGINEERING, MECHANICAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Thermal Science and Engineering Applications","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1115/1.4064431","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, MECHANICAL","Score":null,"Total":0}
引用次数: 0

摘要

本文提出了一种省时高效的方法,用于优化燃气轮机叶片尖部薄膜冷却孔的位置,以提高冷却和空气动力性能。该方法采用计算方法进行优化,包括根据实验进行验证。考虑了五个离散的薄膜冷却孔,并研究了 0.4 和 1.0 两种不同的吹气比。冷却孔在尖端沿切线方向的位置作为优化的输入参数而变化。多目标优化采用人工神经网络算法,可快速预测拟合函数。当吹气速率为 1.0 时,优化找到的最佳冷却配置可使总热流量减少 13.43%,空气动力损失增加 0.4%。在计算中加入套管相对运动会导致两种吹气速率下的总压力损失系数增加约 8%。在 M=1.0 时,与静止套管相比,套管的运动导致向喷嘴的总传热减少 10.2%。对于 0.4 的较低吹气速率,由于施加了套管运动,喷嘴的总热流量减少了 12.0%。因此,采用本研究提出的特定位置优化方法可以提高冷却效果。结果表明,对冷却涡轮叶尖的实验和计算传热研究,特别是在级联布置中,需要考虑叶尖的相对运动。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Aerothermal Optimization of Film Cooling Hole Locations on the Squealer Tip of an HP Turbine Blade
This paper presents a time-efficient method to optimize the positions of film cooling holes on a gas turbine blade's squealer tip for cooling and aerodynamic performance. A computational approach is employed for the optimization, including validations against experiments. Five discrete film cooling holes are considered, and two different blowing ratios of 0.4 and 1.0 are studied. The positions of cooling holes on the tip along the tangential direction are varied as the input parameters of optimization. The multi-objective optimization uses an algorithm with an artificial neural network for fast fitness function predictions. The best cooling configuration found by the optimization achieves a 13.43% reduction in total heat flux and a 0.4% increase in aerodynamic loss when the blowing rate is 1.0. Including the casing relative motion in the computations results in a total pressure loss coefficient increase of about 8 % for both blowing ratios. For M=1.0, imposing the casing's motion results in a 10.2% reduction in total heat transfer to the tip compared to the stationary casing. For the lower blowing rate of 0.4, the total heat flux reduction to the tip is 12.0% because of imposed casing motion. Hence, the cooling effectiveness can be improved by employing the particular position optimization method presented in this study. The results suggest that experimental and computational heat transfer studies on cooled turbine blade tips, especially in cascade arrangements, need to consider the relative motion of the blade tip.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Journal of Thermal Science and Engineering Applications
Journal of Thermal Science and Engineering Applications THERMODYNAMICSENGINEERING, MECHANICAL -ENGINEERING, MECHANICAL
CiteScore
3.60
自引率
9.50%
发文量
120
期刊介绍: Applications in: Aerospace systems; Gas turbines; Biotechnology; Defense systems; Electronic and photonic equipment; Energy systems; Manufacturing; Refrigeration and air conditioning; Homeland security systems; Micro- and nanoscale devices; Petrochemical processing; Medical systems; Energy efficiency; Sustainability; Solar systems; Combustion systems
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信