M. R. Beierl, Damian M. Vogt, Magnus Fischer, Tobias R. Müller, Kwok Kai So
{"title":"Numerical Investigation of the Excitation Characteristics of Contaminated Nozzle Rings","authors":"M. R. Beierl, Damian M. Vogt, Magnus Fischer, Tobias R. Müller, Kwok Kai So","doi":"10.3390/ijtpp9020021","DOIUrl":null,"url":null,"abstract":"The deposition of combustion residues in the nozzle ring (NR) of a turbocharger turbine stage changes the NR geometry significantly in a random manner. The resultant complex and highly asymmetric geometry induces low engine order (LEO) excitation, which may lead to resonance excitation of rotor blades and high cycle fatigue (HCF) failure. Therefore, a suitable prediction workflow is of great importance for the design and validation phases. The prediction of LEO excitation is, however, computationally expensive as high-fidelity, full annulus CFD models are required. Previous investigations showed that a steady-state computational model consisting of the volute, the NR, and a radial extension is suitable to reduce the computational costs massively and to qualitatively predict the level of LEO forced response. In the current paper, the aerodynamic excitation of 69 real contaminated NRs is analyzed using this simplified approach. The results obtained by the simplified simulation model are used to select 13 contaminated NR geometries, which are then simulated with a model of the entire turbine stage, including the rotor, in a transient time-marching manner to provide high-fidelity simulation results for the verification of the simplified approach. Furthermore, two contamination patterns are analyzed in a more detailed manner regarding their aerodynamic excitation. It is found that the simplified model can be used to identify and classify contamination patterns that lead to high blade vibration amplitudes. In cases where transient effects occurring in the rotor alter the harmonic pressure field significantly, the ability of the simplified approach to predict the LEO excitation is not sufficient.","PeriodicalId":36626,"journal":{"name":"International Journal of Turbomachinery, Propulsion and Power","volume":null,"pages":null},"PeriodicalIF":1.3000,"publicationDate":"2024-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Turbomachinery, Propulsion and Power","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3390/ijtpp9020021","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, AEROSPACE","Score":null,"Total":0}
引用次数: 0
Abstract
The deposition of combustion residues in the nozzle ring (NR) of a turbocharger turbine stage changes the NR geometry significantly in a random manner. The resultant complex and highly asymmetric geometry induces low engine order (LEO) excitation, which may lead to resonance excitation of rotor blades and high cycle fatigue (HCF) failure. Therefore, a suitable prediction workflow is of great importance for the design and validation phases. The prediction of LEO excitation is, however, computationally expensive as high-fidelity, full annulus CFD models are required. Previous investigations showed that a steady-state computational model consisting of the volute, the NR, and a radial extension is suitable to reduce the computational costs massively and to qualitatively predict the level of LEO forced response. In the current paper, the aerodynamic excitation of 69 real contaminated NRs is analyzed using this simplified approach. The results obtained by the simplified simulation model are used to select 13 contaminated NR geometries, which are then simulated with a model of the entire turbine stage, including the rotor, in a transient time-marching manner to provide high-fidelity simulation results for the verification of the simplified approach. Furthermore, two contamination patterns are analyzed in a more detailed manner regarding their aerodynamic excitation. It is found that the simplified model can be used to identify and classify contamination patterns that lead to high blade vibration amplitudes. In cases where transient effects occurring in the rotor alter the harmonic pressure field significantly, the ability of the simplified approach to predict the LEO excitation is not sufficient.
燃烧残留物在涡轮增压器涡轮级喷嘴环(NR)中的沉积会以随机方式显著改变 NR 的几何形状。由此产生的复杂且高度不对称的几何形状会诱发发动机低阶(LEO)激励,从而可能导致转子叶片的共振激励和高循环疲劳(HCF)故障。因此,合适的预测工作流程对于设计和验证阶段非常重要。然而,低地轨道激振预测的计算成本很高,因为需要高保真的全环 CFD 模型。之前的研究表明,由涡壳、NR 和径向延伸部分组成的稳态计算模型可大幅降低计算成本,并可定性预测低地轨道强迫响应水平。本文采用这种简化方法分析了 69 个实际污染 NR 的气动激励。简化仿真模型得到的结果被用于选择 13 种污染 NR 几何形状,然后用包括转子在内的整个涡轮级模型以瞬态时间进行仿真,从而为验证简化方法提供高保真仿真结果。此外,还对两种污染模式的空气动力激励进行了更详细的分析。结果发现,简化模型可用于识别和分类导致高叶片振动幅度的污染模式。在转子中发生的瞬态效应显著改变谐波压力场的情况下,简化方法不足以预测低地轨道激励。