We provide direct measurements of the boundary layer properties in highly turbulent Taylor-Couette flow up to Re=2×106) (Ta=6.2×10(12)) using high-resolution particle image velocimetry and particle tracking velocimetry. We find that the mean azimuthal velocity profile at the inner and outer cylinder can be fitted by the von Kármán log law u+=1/κ lny+ +B. The von Kármán constant κ is found to depend on the driving strength Ta and for large Ta asymptotically approaches κ≈0.40. The variance profiles of the local azimuthal velocity have a universal peak around y+≈12 and collapse when rescaled with the driving velocity (and not with the friction velocity), displaying a log dependence of y+ as also found for channel and pipe flows.

The reliable measurement of mean flow properties near walls and interfaces between different fluids or fluid and gas phases is a very important task, as well as a challenging problem, in many fields of science and technology. Due to the decreasing concentration of tracer particles and the strong flow gradients, these velocity measurements are usually biased. To investigate the reason and the effect of the bias errors systematically, a detailed theoretical analysis was performed using window-correlation, singe-pixel ensemble-correlation and particle tracking evaluation methods. The different findings were validated experimentally for microscopic, long-range microscopic and large field imaging conditions. It is shown that for constant flow gradients and homogeneous particle image density, the bias errors are usually averaged out. This legitimates the use of these techniques far away from walls or interfaces. However, for inhomogeneous seeding and/or nonconstant flow gradients, only PTV image analysis techniques give reliable results. This implies that for wall distances below half an interrogation window dimension, the singe-pixel ensemble-correlation or PTV evaluation should always be applied. For distances smaller than the particle image diameter, only PTV yields reliable results.

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This work analyzes the spatial resolution that can be achieved by digital particle image velocimetry (DPIV) as a function of the tracer particles and the imaging and recording system. As the in-plane resolution for window-correlation evaluation is related by the interrogation window size, it was assumed in the past that single-pixel ensemble-correlation increases the spatial resolution up to the pixel limit. However, it is shown that the determining factor limiting the resolution of single-pixel ensemblecorrelation are the size of the particle images, which is dependent on the size of the particles, the magnification, the f-number of the imaging system, and the optical aberrations. Furthermore, since the minimum detectable particle image size is determined by the pixel size of the camera sensor in DPIV, this quantity is also considered in this analysis. It is shown that the optimal magnification that results in the best possible spatial resolution can be estimated from the particle size, the lens properties, and the pixel size of the camera. Thus, the information provided in this paper allows for the optimization of the camera and objective lens choices as well as the working distance for a given setup. Furthermore, the possibility of increasing the spatial resolution by means of particle tracking velocimetry (PTV) is discussed in detail. It is shown that this technique allows to increase the spatial resolution to the subpixel limit for averaged flow fields. In addition, PTV evaluation methods do not show bias errors that are typical for correlation-based approaches. Therefore, this technique is best suited for the estimation of velocity profiles.

Astigmatism particle tracking velocimetry (APTV) is a method to determine three components (3C) of the velocity field in a volume (3D) using a single camera. The depth position of the particles is coded by optical distortions caused by a cylindrical lens in the optical setup. This technique is particularly suited for microfluidic applications as measurement errors due to spatial averaging and depth of correlation, typically encountered with μPIV approaches, are eliminated so that the measurement precision is enhanced. Unfortunately, the current state of the technique is limited by the small measurement region achievable with the current calibration procedures as well as by higher order image aberrations (Cierpka et al 2010 Meas. Sci. Technol. 21 045401). In order to extend the size of the measurement volume and to account for all image aberrations, a new intrinsic calibration procedure, based on the imaging function of the particles, is proposed in the paper at hand. It provides an extended measurement depth, taking into account all image aberrations. In this work, the calibration procedure was applied to a μPIV arrangement but could also be implemented on macroscopic experimental setups. The calibration procedure is qualified with synthetic data as well as Poiseuille flow in a straight rectangular micro-channel with a cross-sectional area of 200 ×  500 µm2. The three-dimensional velocity distribution of the whole channel was resolved via APTV with uncertainties of 0.9% and 3.7% of the centerline velocity, uc, for the in-plane and out-of-plane components, respectively. Further investigations using different cylindrical-lens focal lengths, magnifications and particle sizes provide information about achievable measurement depths and help to design and adapt the optimal system for the desired experiment.