Abstract
In order to obtain the aerodynamic loads of the vibrating blades efficiently, the eXterme Gradient Boosting (XGBoost) algorithm in machine learning was adopted to establish a three-dimensional unsteady aerodynamic force reduction model. First, the database for the unsteady aerodynamic response during the blade vibration was acquired through the numerical simulation of flow field. Then the obtained data set was trained by the XGBoost algorithm to set up the intelligent model of unsteady aerodynamic force for the three-dimensional blade. Afterwards, the aerodynamic load could be gained at any spatial location during blade vibration. To evaluate and verify the reliability of the intelligent model for the blade aerodynamic load, the prediction results of the machine learning model were compared with the results of Computation Fluid Dynamics (CFD). The determination coefficient R2 and the Root Mean Square Error (RMSE) were introduced as the model evaluation indicators. The results show that the prediction results based on the machine learning model are in good agreement with the CFD results, and the calculation efficiency is significantly improved. The results also indicate that the aerodynamic intelligent model based on the machine learning method is worthy of further study in evaluating the blade vibration stability.
Highlights
IntroductionPublisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations
In order to achieve an unsteady aerodynamic load on the blade, a reduced-order intelligent model of the three-dimensional blade in compressor was established in this paper based on a machine learning algorithm for the first time
Technology, the modeling for the aerodynamic force can be performed for a threedimensional blade of compressor in vibration
Summary
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. With the development of high load and high efficiency in compressors, the centrifugal load and aerodynamic load are endured by the blade due to the strong unsteady flow in the field. The problem of blade vibration has become increasingly prominent. The accurate prediction of the internal flow and blade aerodynamic force in the compressor is of great significance for evaluating the reliability of blade vibration in the design stage
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