Brush seal design and secondary air system modification of a heavy-duty gas turbine to improve the output power

涡轮机 刷子 计算流体力学 海洋工程 机械工程 气流 汽车工程 质量流 燃料效率 流量(数学) 印章(徽章) 工程类 模拟 环境科学 机械 航空航天工程 物理 艺术 视觉艺术
作者
Ali Amini,Ali Khavari,Mohammad Reza Alizadeh
出处
期刊:Proceedings of the Institution of Mechanical Engineers, Part A: Journal of Power and Energy [SAGE]
卷期号:236 (8): 1660-1679 被引量:2
标识
DOI:10.1177/09576509221096923
摘要

The overall performance of heavy-duty gas turbines is strongly affected by the mass flow distribution of the secondary air system. Reducing the mass flow of the secondary air is a remarkable method to improve the performance of a gas turbine. The aim of this article is to implement a brush seal as an alternative to labyrinth seal. Based on the experiences gained from the integrity of brush seals into a gas turbine, installing a brush seal would not necessarily improve turbine performance. This is because of SAS mass flow redistribution, which may not lead to overall SAS mass flow reduction. Therefore, some other components in the SAS arrangement should be modified as controlling variables to overcome this problem. The effect of these modifications on the airflow distribution is investigated using an in-house network analysis code. To establish an optimum solution (optimized brush seal geometry and controlling variables), the network analysis code is coupled with an in-house optimization code that benefits from the Genetic Algorithms and Artificial Neural Networks. Some constraints including upstream and downstream cavity purge flow and vane cooling air are considered in the optimization process. The final network results show a 33.27% reduction in overall SAS mass flow. To ensure an improvement in the performance of the new three-stage turbine, a CFD analysis is conducted, which indicates 1.0% more power with respect to the original turbine. In the end, the aerodynamic and mechanical behavior of the brush seal is analyzed using CFD and FEM.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
刚刚
魔幻灯泡完成签到,获得积分10
刚刚
小陈完成签到,获得积分10
1秒前
科研通AI6应助谢生婷采纳,获得10
1秒前
1秒前
2秒前
九月完成签到 ,获得积分10
2秒前
2秒前
汤圆完成签到,获得积分10
3秒前
多看文献完成签到,获得积分10
3秒前
科研通AI6应助北北北采纳,获得10
3秒前
念安完成签到 ,获得积分10
3秒前
李爱国应助英勇羿采纳,获得10
3秒前
4秒前
duo完成签到,获得积分10
4秒前
不明发布了新的文献求助10
5秒前
5秒前
5秒前
6秒前
冷艳水壶完成签到 ,获得积分10
7秒前
JuntaoWang发布了新的文献求助20
7秒前
小胖胖完成签到,获得积分10
7秒前
wxyshare举报阿哲求助涉嫌违规
8秒前
8秒前
9秒前
李健应助缥缈的机器猫采纳,获得10
9秒前
ding应助努力的学采纳,获得10
9秒前
科目三应助dingmeijia采纳,获得10
9秒前
bodao发布了新的文献求助10
10秒前
yyjw完成签到,获得积分10
10秒前
10秒前
所所应助隐形小熊猫采纳,获得10
12秒前
mimiya完成签到,获得积分20
12秒前
purple发布了新的文献求助10
13秒前
lalala完成签到,获得积分10
13秒前
可爱的函函应助凛冬采纳,获得10
13秒前
LUCK发布了新的文献求助10
13秒前
烟花应助科研通管家采纳,获得10
14秒前
打打应助科研通管家采纳,获得10
14秒前
脑洞疼应助猪猪hero采纳,获得20
14秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
List of 1,091 Public Pension Profiles by Region 1001
The Antibodies, Vol. 2,3,4,5,6 1000
Clinical Microbiology Procedures Handbook, Multi-Volume, 5th Edition 1000
On the application of advanced modeling tools to the SLB analysis in NuScale. Part I: TRACE/PARCS, TRACE/PANTHER and ATHLET/DYN3D 500
L-Arginine Encapsulated Mesoporous MCM-41 Nanoparticles: A Study on In Vitro Release as Well as Kinetics 500
Virus-like particles empower RNAi for effective control of a Coleopteran pest 400
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 生物化学 物理 纳米技术 计算机科学 内科学 化学工程 复合材料 物理化学 基因 遗传学 催化作用 冶金 量子力学 光电子学
热门帖子
关注 科研通微信公众号,转发送积分 5461138
求助须知:如何正确求助?哪些是违规求助? 4566175
关于积分的说明 14303831
捐赠科研通 4491884
什么是DOI,文献DOI怎么找? 2460490
邀请新用户注册赠送积分活动 1449811
关于科研通互助平台的介绍 1425582