Frictional drag reduction due to the presence of small bubbles is investigated experimentally using a Couette–Taylor flow system; i.e., shear flow between concentric cylinders. Torque and bubble behavior are measured as a function of Reynolds number up to Re=5000 while air bubbles are injected constantly and rise through an array of vortical cells. Silicone oil is used to avoid the uncertain interfacial property of bubbles and to produce nearly monosized bubble distributions. The effect of drag reduction on sensitivity and power gain are assessed. The sensitivity exceeds unity at Re<2000, proving that the effect of the reduction in drag is greater than that of the reduction in mixture density. This is due to the accumulation of bubbles toward the rotating inner cylinder, which is little affected by turbulence. The power gain, which is defined by the power saving from the drag reduction per the pumping power of bubble injection, has a maximum value of O(10) at higher Re numbers around 2500. An image processing measurement shows this is because of the disappearance of azimuthal waves when the organized bubble distribution transforms from toroidal to spiral modes. Moreover, the axial spacing of bubble clouds expands during the transition, which results in an effective reduction in the momentum exchange.

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Particle tracking velocimetry (PTV) is applied to flows around a Savonius turbine. The velocity vector field measured with PTV is utilized to estimate the pressure field around the turbine, as well as to evaluate the torque performance. The main objective of the work is the establishment of the pressure estimation scheme required to discuss the turbine performance. First, the PTV data are interpolated on a regular grid with a fourth-order ellipsoidal differential equation to generate velocity vectors satisfying the third-order spatio-temporal continuity both in time and space. Second, the phase-averaged velocity vector information with respect to the turbine angle is substituted into three different types of pressure-estimating equations, i.e. the Poisson equation, the Navier–Stokes equation and the sub-grid scale model of turbulence. The results obtained based on the Navier–Stokes equation are compared with those based on the Poisson equation, and have shown several merits in employing the Navier–Stokes-based method for the PTV measurement. The method is applied to a rotating turbine with the tip-speed ratio of 0.5 to find the relationship between torque behaviour and flow structure in a phase-averaged sense. We have found that a flow attached to the convex surface of the blades induces low-pressure regions to drive the turbine, namely, the lift force helps the turbine blades to rotate even when the drag force is insufficient. Secondary mechanisms of torque generation are also discussed.

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