Effect of dust on Kelvin-Helmholtz instabilities

Dust is present in a large variety of astrophysical fluids, from tori around supermassive black holes to molecular clouds, protoplanetary discs, and cometary outflows. In many such fluids, shearing flows are present, leading to the formation of Kelvin-Helmholtz instabilities (KHI) and changing the properties and structures of the fluid through processes such as mixing and clumping of dust. We investigate how dust changes the growth rates of the KHI in 2D and 3D and how the it redistributes and clumps dust. We investigate if similarities can be found between the structures in 3D KHI and those seen in observations of molecular clouds. We do this by performing numerical hydrodynamical dust+gas simulations with in addition to gas a number of dust fluids. Each dust fluid represents a portion of the particle size-distribution. We study how dust-to-gas mass density ratios between 0.01 and 1 alter the growth rate in the linear phase of the KHI. We do this for a wide range of perturbation wavelengths, and compare these values to the analytical gas-only growth rates. As the formation of high-density dust structures is of interest in many astrophysical environments, we scale our simulations with physical quantities similar to values in molecular clouds. Large differences in dynamics are seen for different grain sizes. We demonstrate that high dust-to-gas ratios significantly reduce the growth rate of the KHI, especially for short wavelengths. We compare the dynamics in 2D and 3D simulations, where the latter demonstrates additional full 3D instabilities during the non-linear phase, leading to increased dust densities. We compare the structures formed by the KHI in 3D simulations with those in molecular clouds and see how the column density distribution of the simulation shares similarities with log-normal distributions with power-law tails sometimes seen in observations of molecular clouds.Comment: 14 pages, 20 figure

Real-time simulation and visualisation of cloth using edge-based adaptive meshes

Real-time rendering and the animation of realistic virtual environments and characters has progressed at a great pace, following advances in computer graphics hardware in the last decade. The role of cloth simulation is becoming ever more important in the quest to improve the realism of virtual environments. The real-time simulation of cloth and clothing is important for many applications such as virtual reality, crowd simulation, games and software for online clothes shopping. A large number of polygons are necessary to depict the highly exible nature of cloth with wrinkling and frequent changes in its curvature. In combination with the physical calculations which model the deformations, the effort required to simulate cloth in detail is very computationally expensive resulting in much diffculty for its realistic simulation at interactive frame rates. Real-time cloth simulations can lack quality and realism compared to their offline counterparts, since coarse meshes must often be employed for performance reasons. The focus of this thesis is to develop techniques to allow the real-time simulation of realistic cloth and clothing. Adaptive meshes have previously been developed to act as a bridge between low and high polygon meshes, aiming to adaptively exploit variations in the shape of the cloth. The mesh complexity is dynamically increased or refined to balance quality against computational cost during a simulation. A limitation of many approaches is they do not often consider the decimation or coarsening of previously refined areas, or otherwise are not fast enough for real-time applications. A novel edge-based adaptive mesh is developed for the fast incremental refinement and coarsening of a triangular mesh. A mass-spring network is integrated into the mesh permitting the real-time adaptive simulation of cloth, and techniques are developed for the simulation of clothing on an animated character

Split-screen single-camera stereoscopic PIV application to a turbulent confined swirling layer with free surface

An annular liquid wall jet, or vortex tube, generated by helical injection inside a tube is studied experimentally as a possible means of fusion reactor shielding. The hollow confined vortex/swirling layer exhibits simultaneously all the complexities of swirling turbulence, free surface, droplet formation, bubble entrapment; all posing challenging diagnostic issues. The construction of flow apparatus and the choice of working liquid and seeding particles facilitate unimpeded optical access to the flow field. A split-screen, single-camera stereoscopic particle image velocimetry (SPIV) scheme is employed for flow field characterization. Image calibration and free surface identification issues are discussed. The interference in measurements of laser beam reflection at the interface are identified and discussed. Selected velocity measurements and turbulence statistics are presented at Re_λ = 70 (Re = 3500 based on mean layer thickness)

Real-time hybrid cutting with dynamic fluid visualization for virtual surgery

It is widely accepted that a reform in medical teaching must be made to meet today's high volume training requirements. Virtual simulation offers a potential method of providing such trainings and some current medical training simulations integrate haptic and visual feedback to enhance procedure learning. The purpose of this project is to explore the capability of Virtual Reality (VR) technology to develop a training simulator for surgical cutting and bleeding in a general surgery

Blue Noise Sampling using an SPH-based Method

We propose a novel algorithm for blue noise sampling inspired by the Smoothed Particle Hydrodynamics (SPH) method. SPH is a well-known method in fluid simulation -- it computes particle distributions to minimize the internal pressure variance. We found that this results in sample points (i.e., particles) with a high quality blue-noise spectrum. Inspired by this, we tailor the SPH method for blue noise sampling. Our method achieves fast sampling in general dimensions for both surfaces and volumes. By varying a single parameter our method can generate a variety of blue noise samples with different distribution properties, ranging from Lloyd's relaxation to Capacity Constrained Voronoi Tessellations ({CCVT}). Our method is fast and supports adaptive sampling and multi-class sampling. We have also performed experimental studies of the SPH kernel and its influence on the distribution properties of samples. We demonstrate with examples that our method can generate a variety of controllable blue noise sample patterns, suitable for applications such as image stippling and re-meshing