Abstract
Flow reconstruction techniques are a crucial element for feedback flow control. In particular, when we try to install a feedback loop for a drag reduction system using bubble injection, it is necessary to estimate two-phase flow features using a limited number of sensors. In this study, we introduce the stochastic estimation in order to reconstruct unsteady bubbly flows based on point-wise shear stress measurement. We develop a simultaneous measurement system combining four shear-stress sensors and a high-speed camera in a horizontal channel, and reconstruct two-dimensional bubble distribution in the course of time. We investigate the signal processing for the reconstruction algorithm and discuss the capabilities of the stochastic estimation applying to two-phase flows. The results show that the recovered images agree with the two-dimensional bubble distribution in a reasonable degree during the sampling time period at which the linear coefficients are determined. On the other hand, when we apply the algorithm beyond the sampling time period, the reconstructed images agree only for limited time intervals.
