Journal•ISSN: 0723-4864
Experiments in Fluids
Springer Science+Business Media
About: Experiments in Fluids is an academic journal published by Springer Science+Business Media. The journal publishes majorly in the area(s): Turbulence & Particle image velocimetry. It has an ISSN identifier of 0723-4864. Over the lifetime, 6127 publications have been published receiving 207946 citations.
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TL;DR: In this article, the directional ambiguity associated with PIV and LSV is resolved by implementing local spatial cross-correlations between two sequential single-exposed particle images, and the recovered velocity data are used to compute the spatial and temporal vorticity distribution and the circulation of the vortex ring.
Abstract: Digital particle image velocimetry (DPIV) is the digital counterpart of conventional laser speckle velocitmetry (LSV) and particle image velocimetry (PIV) techniques. In this novel, two-dimensional technique, digitally recorded video images are analyzed computationally, removing both the photographic and opto-mechanical processing steps inherent to PIV and LSV. The directional ambiguity generally associated with PIV and LSV is resolved by implementing local spatial cross-correlations between two sequential single-exposed particle images. The images are recorded at video rate (30 Hz or slower) which currently limits the application of the technique to low speed flows until digital, high resolution video systems with higher framing rates become more economically feasible. Sequential imaging makes it possible to study unsteady phenomena like the temporal evolution of a vortex ring described in this paper. The spatial velocity measurements are compared with data obtained by direct measurement of the separation of individual particle pairs. Recovered velocity data are used to compute the spatial and temporal vorticity distribution and the circulation of the vortex ring.
1,976 citations
TL;DR: The development of the method of particle image velocimetry (PIV) is traced by describing some of the milestones that have enabled new and/or better measurements to be made.
Abstract: The development of the method of particle image velocimetry (PIV) is traced by describing some of the milestones that have enabled new and/or better measurements to be made. The current status of PIV is summarized, and some goals for future advances are addressed.
1,284 citations
TL;DR: In this article, a micro-resolution particle image velocimetry (micro-PIV) system was developed to measure instantaneous and ensemble-averaged flow fields in micron-scale fluidic devices.
Abstract: A micron-resolution particle image velocimetry (micro-PIV) system has been developed to measure instantaneous and ensemble-averaged flow fields in micron-scale fluidic devices. The system utilizes an epifluorescent microscope, 100–300 nm diameter seed particles, and an intensified CCD camera to record high-resolution particle-image fields. Velocity vector fields can be measured with spatial resolutions down to 6.9×6.9×1.5 μm. The vector fields are analyzed using a double-frame cross-correlation algorithm. In this technique, the spatial resolution and the accuracy of the velocity measurements is limited by the diffraction limit of the recording optics, noise in the particle image field, and the interaction of the fluid with the finite-sized seed particles. The stochastic influence of Brownian motion plays a significant role in the accuracy of instantaneous velocity measurements. The micro-PIV technique is applied to measure velocities in a Hele–Shaw flow around a 30 μm (major diameter) elliptical cylinder, with a bulk velocity of approximately 50 μm s-1.
1,187 citations
TL;DR: In this paper, a tomographic particle image velocimetry (tomographic-PIV) system based on the illumination, recording and reconstruction of tracer particles within a 3D measurement volume is described.
Abstract: This paper describes the principles of a novel 3D PIV system based on the illumination, recording and reconstruction of tracer particles within a 3D measurement volume The technique makes use of several simultaneous views of the illuminated particles and their 3D reconstruction as a light intensity distribution by means of optical tomography The technique is therefore referred to as tomographic particle image velocimetry (tomographic-PIV) The reconstruction is performed with the MART algorithm, yielding a 3D array of light intensity discretized over voxels The reconstructed tomogram pair is then analyzed by means of 3D cross-correlation with an iterative multigrid volume deformation technique, returning the three-component velocity vector distribution over the measurement volume The principles and details of the tomographic algorithm are discussed and a parametric study is carried out by means of a computer-simulated tomographic-PIV procedure The study focuses on the accuracy of the light intensity field reconstruction process The simulation also identifies the most important parameters governing the experimental method and the tomographic algorithm parameters, showing their effect on the reconstruction accuracy A computer simulated experiment of a 3D particle motion field describing a vortex ring demonstrates the capability and potential of the proposed system with four cameras The capability of the technique in real experimental conditions is assessed with the measurement of the turbulent flow in the near wake of a circular cylinder at Reynolds 2,700
1,159 citations
TL;DR: In this article, an adaptation of the original median test for the detection of spurious PIV data is proposed that normalizes the median residual with respect to a robust estimate of the local variation of the velocity.
Abstract: An adaptation of the original median test for the detection of spurious PIV data is proposed that normalizes the median residual with respect to a robust estimate of the local variation of the velocity. It is demonstrated that the normalized median test yields a more or less ‘universal’ probability density function for the residual and that a single threshold value can be applied to effectively detect spurious vectors. The generality of the proposed method is verified by the application to a large variety of documented flow cases with values of the Reynolds number ranging from 10−1 to 107.
1,121 citations