Compaction of powders and granular materials is an important process used to manufacture products including pharmaceuticals, ceramics, metals and explosives. In order to ensure mechanical integrity of the final product, an understanding of the compaction process, with particular reference to the homogeneity of the compacted bed, is required. In particular, it is necessary to have an improved understanding of the physics of the process, which can only be achieved through appropriate experimental measurements. X-ray tomography offers the opportunity to make full-field measurements of displacements in-situ: without removing the specimens from the die. This allows researchers to better understand the processes that take place at different stages in the compaction, and to more rigorously test numerical models.In this paper, we present data obtained using Digital Volume Correlation (DVC) to measure displacements in a compacted bed of sugar, with data obtained using X-ray microtomograpy. Instead of adding tracer particles, the natural, random, microstructure of the bed is used as the pattern for the volume correlation. The displacement data obtained are then used to calculate strain fields in the bed. A novel Finite Element (FE) based smoothing technique is applied to robustly smooth the data, allowing accurate and continuous strains to be calculated. These strains are compared to those calculated from the unsmoothed data. The paper presents details of both the DVC and FE smoothing routines.

The performance of seven different correlation functions applied in Digital Image Correlation has been investigated using simulated and experimentally acquired laser speckle patterns. The correlation functions were constructed as combinations of the pure intensity correlation function, the gradient correlation function and the Hessian correlation function, respectively. It was found that the correlation function that was constructed as the product of all three pure correlation functions performed best for the small speckle sizes and large correlation values, respectively. The difference between the different functions disappeared as the speckle size increased and the correlation value dropped. On average, the random error of the combined correlation function was half that of the traditional intensity correlation function within the optimum region.

Side scattered light from micrometer-sized particles is recorded using an off-axis digital holographic setup. From holograms, a volume is reconstructed with information about both intensity and phase. Finding particle positions is non-trivial, since poor axial resolution elongates particles in the reconstruction. To overcome this problem, the reconstructed wavefront around a particle is used to find the axial position. The method is based on the change in the sign of the curvature around the true particle position plane. The wavefront curvature is directly linked to the phase response in the reconstruction. In this paper we propose a new method of estimating the curvature based on a parametric model. The model is based on Chebyshev polynomials and is fit to the phase anomaly and compared to a plane wave in the reconstructed volume. From the model coefficients, it is possible to find particle locations. Simulated results show increased performance in the presence of noise, compared to the use of finite difference methods. The standard deviation is decreased from 3–39 μm to 6–10 μm for varying noise levels. Experimental results show a corresponding improvement where the standard deviation is decreased from 18 μm to 13 μm.

A novel dual-view polarization-resolved pulsed holographic system for particle measurements is presented. Both dual-view configuration and polarization-resolved registration are well suited for particle holography. Dual-view registration improves the accuracy in the detection of 3D position and velocities, and polarization-resolved registration provides polarization information about individual particles. The necessary calibrations are presented, and aberrations are compensated for by mapping the positions in the two views to positions in a global coordinate system. The system is demonstrated on a sample consisting of 7 μm spherical polystyrene particles dissolved in water in a cuvette. The system is tested with different polarizations of the illumination. It is found that the dual view improves the accuracy significantly in particle tracking. It is also found that by having polarization-resolved holograms, it is possible to separate naturally occurring sub-micrometer particles from the larger, 7 μm seeding particles.

This study describes a multi-camera photogrammetric approach to measure the 3D velocity of free surface flow. The properties of the camera system and particle tracking velocimetry (PTV) algorithm were first investigated in a measurement of a laboratory open channel flow to prepare for field measurements. The in situ camera calibration methods corresponding to the two measurement situations were applied to mitigate the instability of the camera mechanism and camera geometry. There are two photogrammetry-based PTV algorithms presented in this study regarding different types of surface particles employed on the water flow. While the first algorithm uses the particle tracking method applied for individual particles, the second algorithm is based on correlation-based particle clustering tracking applied for clusters of small size particles. In the laboratory, reference data are provided by particle image velocimetry (PIV) and laser Doppler velocimetry (LDV). The differences in velocities measured by photogrammetry and PIV, photogrammetry and LDV are 0.1% and 3.6%, respectively. At a natural river, the change of discharges between two measurement times is found to be 15%, and the corresponding value reported regarding mass flow through a nearby hydropower plant is 20%. The outcomes reveal that the method can provide a reliable estimation of 3D surface velocity with sufficient accuracy.