Browsing by Subject "SPH"

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    A GPU Accelerated Smoothed Particle Hydrodynamics Capability For Houdini
    (2012-10-19) Sanford, Mathew
    Fluid simulations are computationally intensive and therefore time consuming and expensive. In the field of visual effects, it is imperative that artists be able to efficiently move through iterations of the simulation to quickly converge on the desired result. One common fluid simulation technique is the Smoothed Particle Hydrodynamics (SPH) method. This method is highly parellelizable. I have implemented a method to integrate a Graphics Processor Unit (GPU) accelerated SPH capability into the 3D software package Houdini. This helps increase the speed with which artists are able to move through these iterations. This approach is extendable to allow future accelerations of the algorithm with new SPH techniques. Emphasis is placed on the infrastructure design so it can also serve as a guideline for both GPU programming and integrating custom code with Houdini.
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    Testing Accuracy and Convergence of GPUSPH for Free-Surface Flows
    (2012-10-19) Rooney, Erin Ann
    The effect of vegetation on the dissipation of waves is important in understanding the vegetation's role in protecting coastal communities during extreme events such as hurricanes and tsunamis. Numerical modeling makes it possible to study the flow through vegetation fields, but it is important to understand the flow dynamics around one piece of vegetation and validate the numerical model used, before the dynamics of an entire vegetated patch can be modeled and understood. This project validated GPUSPH, a Lagrangian mesh-free numerical model, by determining the optimal characteristics to obtain accurate simulations for flow through a flume with and without an obstruction. The validation of GPUSPH and determination of optimal characteristics was accomplished by varying model particle spacing, sub-particle scale (SPS) turbulence inclusion in the conservation of momentum equation, and kernel weighting function for two test cases. The model particle spacing sets the initial distance between the moving grid points, known as particles, in the system. The SPS turbulence term is intended to account for turbulence generated at the sub-particle scale between the particles. The kernel weighting functions used are the quadratic kernel and the cubic spline kernel. These kernels determine how much influence surrounding particles have on the flow characteristics of an individual particle. The numerical results of these tests were compared with experimental results to obtain conclusions about the accuracy of these simulations. Based on comparisons with experimental velocities and forces, the optimal particle spacing was found to occur when the number of particles was in the high 100,000s for single precision calculations, or mid-range capabilities, for the hardware used in this project. The sub-particle scale turbulence term was only necessary when there was large-scale turbulence in the system and created less accurate results when there was no large-scale turbulence present. There was no definitive conclusion regarding the best kernel weighting function because neither kernel had overall more accurate results than the other. Based on these conclusions, GPUSPH was shown to be a viable option for modeling free-surface flows for certain conditions concerning the particle spacing and the inclusion of the subparticle scale turbulence term.