Distortion Mapping Correction of In-Cylinder Flow Field Measurements through Optical Liner Using Gaussian Optics Model 2017-01-0615
Combustion efficiency of internal combustion engine is closely influenced by the air flow pattern in the engine cylinder. Some researchers use high-speed particle image velocimetry to visualize and measure the temporally and spatially resolved in-cylinder velocity flow fields in the optically assessable engine. However, the transparent cylindrical liner makes it difficult to accurately determine the particle displacements inside the cylinder due to the optically distorted path of scattering light from seeding particles through the curved liner. To correct for the distortion-induced error in the seeding particle positions through the optical liner, the distortion mapping function is modeled using the Gaussian optics theory. Two artificial flow patterns with 5 by 5 vectors were made to illustrate the mapping correction. Distortion-induced error of velocity vectors was precisely mapped in six different planes inside the cylinder. In addition, the in-cylinder PIV measurements in these six planes were applied to illustrate the distortion-induced error. Results show that velocity fields in the center plane did not exhibit much distortion-induced effect. However, the relative distortion-induced error percentage of ensemble velocity magnitude near the cylinder liner could reach as much as 2.1%, indicating that it is necessary to correct for optical distortion in this location. The distortion mapping function used in this study can provide an effective way to correct the distortion-induced error in the planar in-cylinder flow field measured through the transparent liner.
Citation: Ge, P., Zhao, F., Hung, D., Pan, H. et al., "Distortion Mapping Correction of In-Cylinder Flow Field Measurements through Optical Liner Using Gaussian Optics Model," SAE Technical Paper 2017-01-0615, 2017, https://doi.org/10.4271/2017-01-0615. Download Citation
Penghui Ge, Fengnian Zhao, David Hung, Hujie Pan, Min Xu
University of Michigan - SJTU Joint Institute, Shanghai Jiao Tong University