Steve Wereley

Volume illumination for two-dimensional particle image velocimetry

In particle image velocimetry experiments where optical access is limited or in microscale geometries, it may be desirable to illuminate the entire test section with a volume of light, as opposed to a two-dimensional sheet of light. With volume illumination, the depth of the measurement plane must be defined by the focusing characteristics of the recording optics. A theoretical expression for the depth of the two-dimensional measurement plane is derived and it is shown to agree well with experimental observations. Unfocused particle images, which lie outside the measurement plane, create background noise that decreases the signal-to-noise ratio of the particle-image fields. Results show that the particle concentration must be chosen judiciously in order to balance the desired spatial resolution and signal-to-noise ratio of the particle-image field.

A PIV Algorithm for Estimating Time-Averaged Velocity Fields

A PIV algorithm is presented for estimating time-averaged or phase-averaged velocity fields. The algorithm can be applied to situations where signal strength is not sufficient for standard cross correlation techniques, such as a low number of particle images in an interrogation spot, or poor image quality. The algorithm can also be used to increase the spatial resolution of measurements by allowing smaller interrogation spots than those required for standard cross correlation techniques. The quality of the velocity measurements can be dramatically increased by averaging a series of instantaneous corelation functions, before determining the location of the signal peak, as opposed to the commonly used technique of estimating instantaneous velocity fields first and then averaging the velocity fields. The algorithm is applied to a 30 μm×300 μm microchannel flow

Advanced Algorithms for Microscale Particle Image Velocimetry

The recent explosive increase in the use of e uidic microelectromechanical systems (MEMS) has subsequently driven the development of e uidic measurement techniques capable of measuring velocities at length scales small enough to be of use in characterizing and optimizing these new devices. Recently, several techniques have demonstrated spatialresolutions smallerthan 100 πm but largerthan 10 πm. Thesetechniquesincludex-ray microimaging, molecular tagging velocimetry, and microlaser Doppler velocimetry. However, measurements with spatial resolutionssmallerthan 10 πm arenecessary formaking measurementsin many MEMS applications.Only microparticle image velocimetry has demonstrated this high spatial resolution. By the use of a combination of advanced imaging and processing techniques that are described here, spatial resolutions on the order of single micrometers can be achieved. These techniques are used to investigate the e ow though a microfabricated thruster geometry.

Image Evaluation Methods for PIV

This chapter covers extensively the methods used to determine the flow velocity starting from the recordings of particle images. After an introduction to the concept of spatial correlation and Fourier methods, an overview of the different PIV evaluation methods is given. Ample discussions devoted to explain the details of the discrete spatial correlation operator in use for PIV interrogation. The main features associated to the FFT implementation (aliasing, displacement range limit and bias error) are discussed. Methods that enhance the correlation signal either in terms of robustness or of accuracy are surveyed. The discussion of ensemble correlation techniques and the use of single-pixel correlation in micro-PIV and macroscopic experiments is a novel addition to the present edition. A detailed description is given of the standard image interrogation based on multigrid image deformation, where the advantages in the treatment of complex flows are discussed as well as the issues in terms of resolution and numerical stability. Another new feature introduced in this chapter is the discussion of the recent developments of algorithms in use for PIV time series as obtained by high-speed PIV systems. Namely, the algorithms to perform Multi frame-PIV, Pyramid Correlation and Fluid Trajectory Correlation and Ensemble Evaluation are treated. Furthermore, a new section that discusses the methods used for individual particle tracking is introduced. The discussion describes the working principles of PTV for planar PIV. The potential of the latter techniques in terms of spatial resolution as well as their limits of applicability in terms of image density are presented.

A MICROFLUIDIC-BASED NANOSCOPE

A novel technique for noninvasively measuring the shapes of walls with resolution approaching tens of nanometers is presented. The nanoscope measures local wall position by measuring the velocity of a fluid with micron-scale spatial resolution as it flows over a surface. The location of the wall is estimated by assuming the no-slip velocity condition at the wall and extrapolating the velocity profile to zero. Nanoscope measurements were obtained in a 30 × 300-μm channel. The wall shape of the glass microchannel was determined to be flat to within a root mean square uncertainty of 62 nm. Numerical simulations show that noise in the velocity measurements contributes significantly to uncertainty in wall position. The technique can be used to measure surfaces that are immersed in liquids and in geometries that do not provide exposed surfaces, where traditional nanoscope techniques such as scanning probe microscopes (SPM) are not applicable.

Advances and applications of the digital mask technique in particle image velocimetry experiments

Some advancements of the digital mask technique, which was first described by Gui and Merzkirch (1996a ERCOFTAC Bull. 30 45–8) for a phase-separated evaluation of two-phase flow particle image velocimetry (PIV) recordings, are presented in this paper. The originally minimum-quadratic-difference- (MQD-) based mask technique is accelerated by using the fast Fourier transformation algorithm. In order to further increase the evaluation speed and the measurement accuracy, the digital mask technique is modified so that it can be combined with the correlation-based central difference image correction (CDIC) method, which is proved to be a more accurate and less peak-locked evaluation algorithm than both the MQD tracking method and the correlation-based tracking method. An ellipse-shaped interrogation window is constructed with the digital mask technique to improve the spatial resolution of the evaluation without loss of the evaluation accuracy. Applications in PIV measurements of solid/water two-phase flow, bubbly water flow, flow around a human blood cell and airflow near the tip of a vibrating cantilever demonstrate that the combination of the digital mask technique, the CDIC algorithm and the ellipse interrogation window makes a powerful tool for evaluating digital PIV recordings of complex flows.

Brownian Particle Distribution in Tube Flows

A rigid spherical particle translating at small tube Reynolds number in a shearing flow experiences lateral migration due to small inertia and wall effect. In a suspension flow of sufficiently small particles, Brownian motion is another factor. In this work, we investigate this migration phenomenon of Brownian particles in a pressure-driven flow for a range of particle volume fractions (φ) much less than 0.01. The flow velocity is varied, which results in bulk Peclet number (Pe) ranging over four orders of magnitude. Both the velocity and the particle distributions were measured. It has been found that when Pe is smaller than 1000, particles migrate away from the channel wall, and that the particle concentration in regions remote from the wall (more than 10 particle diameters) is nearly uniform; When Pe increases beyond 1000, particles move toward a preferred position with the migration effect becoming progressively stronger as Pe increases.Copyright

Optical Diffusometry Techniques and Applications in Biological Agent Detection

Optical diffusometry is a technique used for measuring diffusion. This work explores the possibility of directly measuring diffusion coefficients of submicron particles for pathogen detection. The diffusion coefficient of these particles is a function of the drag coefficient of the particle at constant temperatures. Particles introduced into a sample containing an analyte bind with the analyte if functionalized with the appropriate antibodies. This leads to an increase in the hydrodynamic drag of the particles and hence a decrease in their diffusion coefficient. This study uses the above principle to effectively measure the diffusion coefficient of the particles using two different experimental approaches. The measured reduction in the diffusion coefficient can be correlated to the amount of analyte present and thus forms the basis of biological agent detection. Sensitivity to experimental conditions is analyzed. It is observed that alternative techniques such as optical trapping hold promise: the diffusive behavior of particles in optical traps is found to be quantitatively different from that of a free particle. Hence preconditions are identified to make optical trapping appropriate for agent detection. DOI: 10.1115/1.2969430

Post-processing of PIV data

While the previous chapter have dealt with recording and evaluation of PIV images, the extracted data require further post-processing in the context of data validation and further data reduction to retrieve fluid mechanical relevant information. This chapter introduces a variety of validation schemes that operate either globally or locally on the data along with methods of data interpolation to fill in data gaps in both space and time. The validated data can then be subjected to differentiation to, for instance, extract gradient information such as vorticity fields. Issues and errors arising through applying differentials to the finitely-spaced data grid are discussed and illustrated. Alternatively, the velocity data can be integrated to retrieve streamlines, body forces or even pressure fields.

Single Pixel Evaluation of Microchannel Flows

Recently a new μPIV interrogation algorithm has been proposed in which the interrogation window size is reduced to a single pixel. Such small interrogation window sizes are possible using correlation averaging to increase the effective particle concentration to levels required for correlation analysis to succeed. The random error exhibits the expected behavior of decreasing roughly in proportion to N−1/2 while the bias error exhibits unexpected peak-locking behavior with zero bias error at integer and half integer pixel displacements and maximal errors at one-quarter and three-quarter pixel displacements. Accompanying experiments show the potential of this technique but have not yet been sufficiently refined to confirm this unexpected bias error behavior.Copyright