Particle Image Velocimetry(PIV)is a well-developed and contactless technique in experimental fluid mechanics,but the strong velocity gradient and streamline curvature near the wall substantially limits its accuracy im...Particle Image Velocimetry(PIV)is a well-developed and contactless technique in experimental fluid mechanics,but the strong velocity gradient and streamline curvature near the wall substantially limits its accuracy improvement.This paper presents a data processing procedure combining conventional PIV and newly developed Mirror Interchange(MI)based Interface-PIV for the measurement of the boundary layer parameter development in the blade leading edge region.The synthetic particle images are used to analyze the measurement errors in the entire procedure.Overall,three types of errors,namely the errors caused by the Window Deformation Iterative Multigrid(WIDIM)algorithm,the discrete data interpolation and integration,and the wall offset uncertainty,comprise the main measurement error.Specifically,the errors due to the discrete data interpolation and integration and the WIDIM algorithm comprise the mean bias,which can be corrected through the error analysis method proposed in the present work.Meanwhile,the errors due to the WIDIM algorithm and the wall offset uncertainty contribute to the measurement uncertainty.Computational fluid dynamics-based synthetic particle flows were generated to verify the newly developed PIV data processing procedure and the corresponding error analysis method.Results showed that the data processing method could improve the accuracy of PIV measurements for boundary layer flows with high curvature and acceleration and even with significant flow separation bubbles.Finally,the data processing method is also applied in a PIV experiment to investigate the boundary layer flows around a compressor blade leading edge,and several credible boundary flow parameters were obtained.展开更多
基金funded by the National Natural Science Foundation of China(Nos.51790511 and 51806004)the National Science and Technology Major Project,China(No.2017-II-0001-0013).
文摘Particle Image Velocimetry(PIV)is a well-developed and contactless technique in experimental fluid mechanics,but the strong velocity gradient and streamline curvature near the wall substantially limits its accuracy improvement.This paper presents a data processing procedure combining conventional PIV and newly developed Mirror Interchange(MI)based Interface-PIV for the measurement of the boundary layer parameter development in the blade leading edge region.The synthetic particle images are used to analyze the measurement errors in the entire procedure.Overall,three types of errors,namely the errors caused by the Window Deformation Iterative Multigrid(WIDIM)algorithm,the discrete data interpolation and integration,and the wall offset uncertainty,comprise the main measurement error.Specifically,the errors due to the discrete data interpolation and integration and the WIDIM algorithm comprise the mean bias,which can be corrected through the error analysis method proposed in the present work.Meanwhile,the errors due to the WIDIM algorithm and the wall offset uncertainty contribute to the measurement uncertainty.Computational fluid dynamics-based synthetic particle flows were generated to verify the newly developed PIV data processing procedure and the corresponding error analysis method.Results showed that the data processing method could improve the accuracy of PIV measurements for boundary layer flows with high curvature and acceleration and even with significant flow separation bubbles.Finally,the data processing method is also applied in a PIV experiment to investigate the boundary layer flows around a compressor blade leading edge,and several credible boundary flow parameters were obtained.
