Month: October 2014

Windy Trees: Computing Stress Response for Developmental Tree Models

Sören Pirk, Till Niese, Torsten Hädrich, Bedrich Benes, Oliver Deussen

We present a novel method for combining developmental tree models with turbulent wind fields. The tree geometry is created from internal growth functions of the developmental model and its response to external stress is induced by a physically-plausible wind field that is simulated by Smoothed Particle Hydrodynamics (SPH). Our tree models are dynamically evolving complex systems that (1) react in real-time to high-frequent changes of the wind simulation; and (2) adapt to long-term wind stress. We extend this process by wind-related effects such as branch breaking as well as bud abrasion and drying. In our interactive system the user can adjust the parameters of the growth model, modify wind properties and resulting forces, and define the tree’s long-term response to wind. By using graphics hardware, our implementation runs at interactive rates for moderately large scenes composed of up to 20 tree models.

Windy Trees: Computing Stress Response for Developmental Tree Models

SPGrid: A Sparse Paged Grid structure applied to adaptive smoke simulation

Rajsekhar Setaluri, Mridul Aanjaneya, Sean Bauer, and Eftychios Sifakis

We introduce a new method for fluid simulation on high-resolution adaptive grids which rivals the throughput and parallelism potential of methods based on uniform grids. Our enabling contribution is SPGrid, a new data structure for compact storage and efficient stream processing of sparsely populated uniform Cartesian grids.SPGrid leverages the extensive hardware acceleration mechanisms inherent in the x86 Virtual Memory Management system to deliver sequential and stencil access bandwidth comparable to dense uniform grids. Second, we eschew tree-based adaptive data structures in favor of storing simulation variables in a pyramid of sparsely populated uniform grids, thus avoiding the cost of indirect memory access associated with pointer-based representations. We show how the costliest algorithmic kernels of fluid simulation can be implemented as a composition of two kernel types: (a) stencil operations on a single sparse uniform grid, and (b) structured data transfers between adjacent levels of resolution, even when modeling non-graded octrees. Finally, we demonstrate an adaptive multigridpreconditioned Conjugate Gradient solver that achieves resolutionindependent convergence rates while admitting a lightweight implementation with a modest memory footprint. Our method is complemented by a new interpolation scheme that reduces dissipative effects and simplifies dynamic grid adaptation. We demonstrate the efficacy of our method in end-to-end simulations of smoke flow.

SPGrid: A Sparse Paged Grid structure applied to adaptive smoke simulation

Coupling Hair with Smoothed Particle Hydrodynamics Fluids

Wei-Chin Lin

We present a two-way coupling technique for simulating the complex interaction between hair and fluids. In our approach, the motion of hair and fluids is simulated by evaluating the hydrodynamic forces among them based on boundary handling techniques used in SPH (Smoothed Particle Hydrodynamics) fluids. When hair makes contact with fluids, water absorption inside the hair volume can be simulated with a diffusion process by treating the hair volume as porous media with anisotropic permeability. The saturation of each hair strand is then used to derive the adhesive force between wet hair strands. This enables us to simulate the formation of hair clumps dynamically without the need to employ post clumping processes. The proposed method can be easily applied to any SPH fluid solvers as well as various hair models.

Coupling Hair with Smoothed Particle Hydrodynamics Fluids