Zhiqiang Meng, S. Krishnababu, S. Jackson, B. Sjödin
{"title":"Probabilistic Assessment of Gas Turbine Compressor Blade HCF Life","authors":"Zhiqiang Meng, S. Krishnababu, S. Jackson, B. Sjödin","doi":"10.1115/gt2022-82323","DOIUrl":null,"url":null,"abstract":"\n This paper uses a novel and practical probabilistic approach to assess the risk of a compressor blade HCF failure in the gas turbine. For a specific design case, the tip timing tests for a newly designed gas turbine compressor blade successfully passed HCF design criteria during engine operation when operated over a wide speed range. However, on a later test high amplitude responses were seen under a VGV configuration which was different from that used during normal operation.\n Firstly, the gas turbine operational data and blade bench test data are used by the probabilistic assessment to identify the characteristics of the HCF problem. The resonance counting is carried out by the Monte Carlo simulations. The simulation indicates that the HCF endurance limit for the alternating stress is required to be satisfied for this blade.\n Secondly, the material test data, blade tip timing data and finite element (FE) results are used to build a HCF endurance stress probabilistic model, following which the probability of blade HCF failure was estimated. The Monte Carlo simulations are used for the probabilistic model. The simulation results show that the probability of HCF failure per blade and the risk of HCF failure for any blade of the stage are very small and acceptable.","PeriodicalId":171593,"journal":{"name":"Volume 8B: Structures and Dynamics — Probabilistic Methods; Rotordynamics; Structural Mechanics and Vibration","volume":"63 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Volume 8B: Structures and Dynamics — Probabilistic Methods; Rotordynamics; Structural Mechanics and Vibration","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1115/gt2022-82323","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This paper uses a novel and practical probabilistic approach to assess the risk of a compressor blade HCF failure in the gas turbine. For a specific design case, the tip timing tests for a newly designed gas turbine compressor blade successfully passed HCF design criteria during engine operation when operated over a wide speed range. However, on a later test high amplitude responses were seen under a VGV configuration which was different from that used during normal operation.
Firstly, the gas turbine operational data and blade bench test data are used by the probabilistic assessment to identify the characteristics of the HCF problem. The resonance counting is carried out by the Monte Carlo simulations. The simulation indicates that the HCF endurance limit for the alternating stress is required to be satisfied for this blade.
Secondly, the material test data, blade tip timing data and finite element (FE) results are used to build a HCF endurance stress probabilistic model, following which the probability of blade HCF failure was estimated. The Monte Carlo simulations are used for the probabilistic model. The simulation results show that the probability of HCF failure per blade and the risk of HCF failure for any blade of the stage are very small and acceptable.