Gas Turbine Blade Stress and Temperature Sensitivity to Turbine Inlet Profile and Cooling Flow

Author:

Kim Beom Soo1,Kim Bum Shin1,Choi Woosung1,Musgrove Grant O.2,McFarland John2,Fierro Frank2,Ransom David L.2

Affiliation:

1. Korea Electric Power Research Institute, Daejeon, South Korea

2. Southwest Research Institute, San Antonio, TX

Abstract

Actual operating conditions in the hot section of a gas turbine vary from the design condition due to factors such as geographic location, component wear, and fuel composition. Turbine design practices typically use a conservative approach that requires checking the sensitivity of operating parameters such as turbine inlet profiles, cooling flows, and heat transfer correlations on component temperatures and stresses. In most cases, a sensitivity check is limited to analyzing the bounds of a range of values for only a few input parameters, whereby the inputs that produce the most conservative results are carried through the remainder of the analysis. For flow path components, however, multiple inputs must be evaluated over a range of values due to the interaction of the hot gas flow field and internal cooling systems. The study presented in this paper uses a probabilistic approach to develop surrogate models to evaluate the sensitivity of a set of operating parameters on the predicted blade temperatures and stresses. Commercially available software is utilized to predict blade temperatures and stresses for the first two stages of an industrial gas turbine. The operating parameters define the blade cooling flow and the shape and values of the turbine inlet profiles of total temperature and total pressure. The results of the study show the spatially resolved sensitivity of the operating parameters on blade temperature and stress distributions.

Publisher

American Society of Mechanical Engineers

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3