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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.

Air–water two-phase flow in a helically coiled tube is investigated using backlight imaging tomography to elucidate the effect of centrifugal acceleration on phase distribution and interfacial structure. Superficial velocities up to 6 m s−1 in 20 mm diameter tube are tested. We focused on a slug flow regime in which centrifugal acceleration dominates the flow. The interfacial structure is visualized in six directions using a set of originally designed mirror-mounted water jackets. A temporal expansion image is made from line-sampled images and is used to reconstruct phase distribution through a linear backward projection algorithm. The present topography measurement showed various new features of gas–liquid two-phase flow in a helically coiled tube, such as a wall-covering effect in the case of high superficial velocity.

The method of direct measurement of vorticity (DMV) is used for extracting vorticity directly from digital particle images. It is the analogue of cross-correlation in particle image velocimetry (PIV) evaluation. There are two main purposes behind the present study: one is to compare the implementation of DMV with PIV in order to clarify the characteristics of the DMV technique; the other is to investigate the influence of the experimental parameters such as particle image size, the size of the sample pattern and the particle density on the precision of DMV. The investigation is performed by applying the DMV method to two kinds of pairs of synthetic digital particle recordings, which respectively represent a solid rotational and a parallel shearing flow. The statistical uncertainty errors are obtained by varying a single parameter at a time. The DMV method shows good measurement results for the stronger rotational flow. Limitations of the DMV technique with regard to the measurable intensity of the shear flow are discussed. The optimum experimental parameters for both flows are given.

Particle tracking velocimetry (PTV) has recently been recognized as quite an effective engineering research tool for understanding multi-dimensional fluid flow structures. There are, however, still a number of unsettled problems in the practical use of PTV, i.e. the lack of generality of the PTV algorithm for various types of flows and the measurement uncertainty with respect to spatial resolution. The authors have developed a generalized PTV algorithm named the velocity gradient tensor (VGT) method in order to accurately track the tracer particles in a flow field with strong local deformation rates. The performance of the VGT method has already been examined for several simple flow fields, such as linear shearing and Taylor-Green vortex flows. In this paper, the applicability of the VGT method for complicated flows, which include a wide dynamic range in wavenumber, is quantitatively examined by simulation of Rankine vortex flows, Karman vortex-shedding flows around a rectangular cylinder and homogeneous turbulent flows, which are numerically solved by using the unsteady Navier-Stokes equations. The results show that the VGT technique, using only two frames to estimate velocity, performs better than does the four-frame PTV technique and has a remarkably higher tracking performance than those of typical conventional PTV algorithms.

Data-assimilation capabilities of hybrid-type simulations integrating time-resolved particle image velocimetry with unsteady computational fluid dynamics (CFD) are characterized, and a series of algorithms developed previously are evaluated in terms of four criteria: (i) compatibility with the governing equations; (ii) completeness of a set of flow quantities; (iii) temporal and spatial filtering functions; and (iv) spatial resolution. This study specifically introduces a hierarchy of three hybrid simulations combining time-resolved particle tracking velocimetry (PTV) and direct numerical simulation (DNS) from low to high fidelities: the proper orthogonal decomposition–Galerkin-projection approach with proportional feedback of PTV data, the DNS solver with similar feedback, and the DNS solver with the extended Kalman filter. By solving a planar-jet problem at , we demonstrate that the resultant hybrid flow fields essentially (i) satisfy the governing equations spatially and approximately temporally, and (ii) can provide instantaneous pressure fields (iii) with the noise levels substantially lower than those of the original PTV data and (iv) the resolution comparable to CFD. The results show that increasing the feedback gain improves replicability, i.e. the agreement between the simulation and the data; however, it degrades temporal compatibility and filtering functions. On the other hand, the fidelity enhances both replicability and spatial filtering, but increases computational cost.

Bubble-injection methods are considered to be a prospective approach to reduce skin-frictional drag for ships. To apply this technique for unsteady flows, we attempt to introduce a feedback loop of air injection in future applications. Hence, we wish to establish reduced-order models of unsteady bubbly flows from the information at the bottom of the ship, but this must be achieved with a limited number of sensors in practice. This motivates us to develop a reconstruction technique that recovers instantaneous phase information of gas–liquid flows. This study introduces the so-called stochastic estimation and reconstructs bubble distribution based on electrical impedance. We simulate the flow at the bottom of a ship using a horizontal channel and install a 16-channel electrode array on the upper wall to acquire time histories of electrical impedance. The relation between the bubble distribution and the electrical impedance is determined by simultaneous image measurement using a high-speed video camera. Once the coefficients of the linear relation between the electrical impedance and the local void fraction are calculated, two-dimensional bubble distribution can be estimated from only voltages at the 16 electrodes. The proposed technique is examined over a range of void fractions and flow velocities, and the capabilities of the stochastic estimation applied to bubbly flow reconstruction are demonstrated by comparing the reconstructed/predicted images with the original ones.

The particle image velocimetry (PIV) technique was used to investigate the N2-air convection caused by the application of magnetic field gradients. When the magnetic field was applied (1.5 T at the center of an electromagnet) and N2 gas was injected into air toward a weaker magnetic field, the surrounding air was found to be drawn toward a stronger magnetic field forming a vortex, while the N2 gas was pushed out. The maximum velocity of the N2 gas with the field was about five times larger than that without the field. These results agree well with the results of numerical simulations.