Defocusing digital particle image velocimetry (DDPIV) is the natural extension of planar PIV techniques to the third spatial dimension. In this paper we give details of the defocusing optical concept by which scalar and vector information can be retrieved within large volumes. The optical model and computational procedures are presented with the specific purpose of mapping the number density, the size distribution, the associated local void fraction and the velocity of bubbles or particles in two-phase flows. Every particle or bubble is characterized in terms of size and of spatial coordinates, used to compute a true three-component velocity field by spatial three-dimensional cross-correlation. The spatial resolution and uncertainty limits are established through numerical simulations. The performance of the DDPIV technique is established in terms of number density and void fraction. Finally, the velocity evaluation methodology, using the spatial cross-correlation technique, is described and discussed in terms of velocity accuracy.

A whole-field three-dimensional (3D) particle tracking velocimetry (PTV) tool for diagnostics in fluid mechanics is presented. Specifically, it is demonstrated why and when PTV is the natural choice in 3D applications compared to particle image velocimetry (PIV). Three different tracking methods are investigated, namely the nearest neighbour, the neural network and the relaxation method. In order to demonstrate the use of PTV for 3D applications, the selected tracking schemes are implemented for use with the defocusing digital particle image velocimetry (DDPIV) technique. The performance of the tracking algorithms is evaluated based on synthetic 3D information. Furthermore, the potential benefit of a merging between the PIV and PTV approaches is explored within the DDPIV framework. The results show that the relaxation tracking method is the most robust and efficient, while the combined PIV/PTV analysis brings significant improvements solely with the neural network scheme. In terms of errors, PTV is found to be more sensitive to particle reconstruction errors than the DDPIV cross-correlation analysis.

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Effect of ractopamine and the methods of diet formulation on the performance and carcass characteristics of finishing barrowsABSTRACT -An experiment was conduced with the objective of evaluating the effects of diet formulation methods and supplementation of ractopamine (RAC) on the performance and carcass characteristics of finishing barrows. Sixty commercial hybrid swines were used, distributed in a randomized experimental block design, in a 2 x 3 factorial arrangment, with two levels of RAC and three methods of diet formulation. Supplementation with RAC improved the final weight, daily weight gain (DWG) and feed conversion (FC) of the finishing barrows. Addition of RAC improved also the carcass characteristics by reducing the backfat thickness in point P 1 and increase daily lean meat deposition rate. Diets formulated based in the concept of ideal protein or by the increase of soybean meal provided better results on FC, but did not influence significantly daily feed intake, DWG and carcass characteristics. Finishing barrows supplemented with RAC during 21 or 28 days showed better performance and carcass quality. Diets formulated to attend the levels of digestible lysine by the inclusion of L-lysine HCL with the adjustment of other amino acids for ideal protein relation (ideal protein) or by the greater inclusion of soybean meal (increase of CP)provided better results of feed conversion in finishing borrows supplemented with RAC during 28 days.

This work describes an experimental study of the flow field and wall pressure fluctuations induced by quasi-two-dimensional incompressible turbulent boundary layers overflowing a forward-facing step (FFS). Pressure fluctuations are measured upstream and downstream of an instrumented FFS step model installed inside a large scale recirculation water tunnel, while two-dimensional (2D) velocity fields are measured close to the step via 2D particle image velocimetry (PIV). The overall flow physics is studied in terms of averaged velocity and vorticity fields for different Reynolds numbers based on the step's height. The wall pressure statistics are analyzed in terms of several indicators, including the root mean squares and probability density functions of the pressure fluctuations, demonstrating that the most relevant flow structure is the unsteady recirculation bubble formed at the reattachment region downstream of the step. Pressure spectra and cross correlations are computed as well, and the convection velocity characterizing the propagation of hydrodynamic perturbations is determined as a function of the distance to the vertical side of the step. The simultaneous measurement of time-resolved PIV fields and wall pressure signals enabled us to compute the pressure/velocity cross correlations in the region downstream of the step and substantiated the relevant role played by the recirculation bubble. (C) 2008 American Institute of Physics