Defocusing digital particle image velocimetry and the three-dimensional characterization of two-phase flows

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

Pre-processing of integral images for 3-D displays

This paper seeks to explore a method to accurately correct geometric distortions caused during the capture of three dimensional (3-D) integral images. Such distortions are rotational and scaling errors which, if not corrected, will cause banding and moire effects on the replayed image. The method for calculating the angle of deviation in the 3-D Integral Images is based on Hough Transform. It allows detection of the angle necessary for correction of the rotational error. Experiments have been conducted on a number of 3-D integral image samples and it has been found that the proposed method produces results with accuracy of 0.05 deg

Fast, Scalable, and Interactive Software for Landau-de Gennes Numerical Modeling of Nematic Topological Defects

Numerical modeling of nematic liquid crystals using the tensorial Landau-de Gennes (LdG) theory provides detailed insights into the structure and energetics of the enormous variety of possible topological defect configurations that may arise when the liquid crystal is in contact with colloidal inclusions or structured boundaries. However, these methods can be computationally expensive, making it challenging to predict (meta)stable configurations involving several colloidal particles, and they are often restricted to system sizes well below the experimental scale. Here we present an open-source software package that exploits the embarrassingly parallel structure of the lattice discretization of the LdG approach. Our implementation, combining CUDA/C++ and OpenMPI, allows users to accelerate simulations using both CPU and GPU resources in either single- or multiple-core configurations. We make use of an efficient minimization algorithm, the Fast Inertial Relaxation Engine (FIRE) method, that is well-suited to large-scale parallelization, requiring little additional memory or computational cost while offering performance competitive with other commonly used methods. In multi-core operation we are able to scale simulations up to supra-micron length scales of experimental relevance, and in single-core operation the simulation package includes a user-friendly GUI environment for rapid prototyping of interfacial features and the multifarious defect states they can promote. To demonstrate this software package, we examine in detail the competition between curvilinear disclinations and point-like hedgehog defects as size scale, material properties, and geometric features are varied. We also study the effects of an interface patterned with an array of topological point-defects.Comment: 16 pages, 6 figures, 1 youtube link. The full catastroph