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Research On Low Dimensional Prediction Method Of Sealing Efficiency Of Gas Turbine Disk Cavity

Posted on:2022-12-16Degree:MasterType:Thesis
Country:ChinaCandidate:L M DuFull Text:PDF
GTID:2532306488480124Subject:Aircraft airworthiness certification project
Abstract/Summary:
One of the most important problems that researchers need to face in the design of gas turbine is how to prevent the mainstream high temperature gas from entering the disk cavity.The high temperature gas that ingests the disk cavity will greatly reduce the service life of the turbine disk.The main causes of gas ingestion include the circumferential inhomogeneous pressure field of the annulus and the rotating effect of the rotor.Researchers defined the concept of sealing efficiency to represent the degree of gas ingestion.CCAR33.70 issued by Civil Aviation Administration of China(CAAC)has the following contents: the maximum allowable number of flight cycles for each life limited part of engine in use restriction must be specified through the procedure approved by CAAC.As a typical life limiting component of engine,the life prediction of turbine disk is needed.It has been proved that gas ingestion has a significant impact on the life of turbine disk.Therefore,it is necessary to accurately predict the sealing efficiency of gas ingestion.The reduce order model only needs to input the working condition and cavity size to predict the cavity sealing efficiency.However,the model also has the disadvantages of small scope of application and low prediction accuracy,which need to be optimized.In this paper,the reduced order model is analyzed and optimized from three aspects of guide vane potential field,disk cavity structure and rotor speed,to expand the application range of the model and improve the prediction accuracy of the model.Finally,the influence of conjugate heat transfer factors on the prediction results of the model is analyzed.Firstly,the prediction results of the reduced order model are preliminarily verified.It is proved that the reduced order model has certain advantages in predicting the sealing efficiency,and there is room for improvement.A numerical model including the annulus,the vane and the disk cavity is established,and then the calculation model is verified,which proves that it is effective to simulate the gas ingestion problem.Secondly,by changing the relative position between the stator and the sealing structure in the annulus,the potential field of the guide vane is changed,so as to change the pressure field of the annulus.Starting from the mechanism of gas ingestion,it is found that when the distance between the guide vane and the sealing structure is small,the greater the pressure extreme value of the annulus is,the greater the difference between the positive and negative pressure is,the stronger the inhomogeneous of the pressure field is,the more the invading gas is,and the higher the sealing pressure is,the efficiency is reduced.In order to optimize the model,the control parameters related to annulus Reynolds number are adjusted in the reduced order model.Thirdly,by changing the structure of the disk cavity,it is found that the accuracy of the reduced order model in predicting the simple axial seal is obviously better than that in predicting the radial seal.By adjusting the control parameters related to the seal Reynolds number,the accuracy of the model can be improved.Fourth,by changing the rotating speed of the rotor,the purpose of controlling the rotating Reynolds number is achieved.It is found that the faster the rotor speed,the more serious the gas ingress,the prediction accuracy of the model decreases and the goal of optimizing the model is achieved by adjusting the control parameters related to the rotating Reynolds number in the model.Fifth,set the temperature difference between mainstream gas and cooling gas in the coupled calculation,and analyze the influence of conjugate heat transfer factors on the prediction results of sealing efficiency.
Keywords/Search Tags:gas ingestion, sealing efficiency, reduced-order model, guide vane potential field, regression analysis method, numerical simulation
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