气泡减阻

409
Annu. Rev. Fluid Mech. 2013.45:409-436. Downloaded from by Michigan State University Library on 01/03/14. For personal use only.
4 HWA
0 1960 1970 1980 1990 2000
Figure 1 The occurrence of the trigrams hot wire anemometry (HWA), laser Doppler velocimetry (LDV), and particle image velocimetry (PIV) in Google Books () between 1952 and 2008. We note that a previous review on PIV in this journal (Adrian 1991) appeared when there was no obvious prevalence for any of the three main measurement methods. In the two decades since, PIV has become the dominant approach in experimental fluid mechanics. Data taken from Google Ngrams.
Annu. Rev. Fluid Mech. 2013. 45:409–36
First published online as a Review in Advance on October 8, 2012
The Annual Review of Fluid Mechanics is online at fl
Annu. Rev. Fluid Mech. 2013.45:409-436. Downloaded from by Michigan State University Library on 01/03/14. For personal use only.
Abstract
Particle image velocimetry (PIV) has evolved to be the dominant method for velocimetry in experimental fluid mechanics and has contributed to many advances in our understanding of turbulent and complex flows. In this article we review the achievements of PIV and its latest implementations: time-resolved PIV for the rapid capture of sequences of vector fields; tomographic PIV for the capture of fully resolved volumetric data; and statistical PIV, designed to optimize measurements of mean statistical quantities rather than instantaneous fields. In each implementation, the accuracy and spatial resolution are limited. To advance the method to the next level, we need a completely new approach. We consider the fundamental limitations of twopulse PIV in terms of its dynamic ranges. We then discuss new paths and developments that hold the promise of achieving a fundamental reduction in uncertainty.
1. INTRODUCTION
In the past three decades, particle image velocimetry (PIV) has become a standard tool in experimental fluid mechanics. The principal characteristic that has made it so useful is its ability to measure the instantaneous velocity field simultaneously at many points, typically of the order of 103–105, with spatial resolution sufficient to permit the computation of the instantaneous fluid vorticity and rate of strain. To date, PIV is the only experimental method that provides such information in rapidly evolving flows. PIV measurements are most commonly snapshots of the two- or three-component velocity vector field on a planar cross section of the flow, but in recent years new developments have made it possible to measure the velocity over volumetric domains and to measure sequences of velocity in time at rates sufficient to resolve the temporal evolution. Undoubtedly, PIV has significantly advanced experimental fluid mechanics, especially the study of flows in complex geometries and turbulent flows, providing resolution and detail that can compete with modern numerical methods, such as direct numerical simulation (DNS) (Moin & Mahesh 1998). Applications of PIV range from creeping flows (Santiago et al. 1998) to detonations lasting only a few tens of microseconds (Murphy & Adrian 2011), from nanoscale flow phenomena (Stone et al. 2002, Zettner & Yoda 2003) to motion in the atmosphere of Jupiter (Tokumaru & Dimotakis 1995), and from the motion in the beating heart of vertebrate embryos (Hove et al. 2003, Vennemann et al. 2006) to the accidental release of oil at the bottom of the Gulf of Mexico (McNutt et al. 2011, 2012). The evolution of PIV into the currently dominant method for measuring velocity is illustrated in Figure 1. Since its invention, it has largely superseded the two most important methods of measuring point-wise velocity, hot-wire anemometry (HWA) and laser-Doppler velocimetry (LDV). These methods have strengths that PIV has not been able to duplicate thus far. HWA has a superb signal-to-noise ratio, which makes it ideally suited to study low-intensity turbulent flows and their spectra, whereas LDV is well suited to high-intensity fluctuations with respect to the mean and accurate measurements of long-time average, single-point statistics. But neither provides the spatial derivatives, flow visualization, and capability for the spatial correlation offered by PIV, and Figure 1 is perhaps best interpreted as an indicator of the importance of those capabilities in modern experimental fluid mechanics.