A method of computational flow imaging applied to better comparison between theory and experiments

Computational flow imaging (CFI) is a prediction of transmission of optical waves through theoretical flow fields. In this paper, it is introduced to perform flow visualization for measurements of thermal parameters. A new method to achieve better plan of experiments and better comparison between theory and experiment was proposed. The influence of solved theoretical flow fields on quality of Computational Flow Imaging is also studied. It is found that the grid density of numerical analogue should satisfy the Nyquist-Shannon sampling principle to ensure the CFI can be correctly expressed.