We present a new method to create and preserve the turbulent details generated around moving objects in SPH fluid. In our approach, a high-resolution overlapping grid is bounded to each object and translates with the object. The turbulence formation is modeled by resolving the local flow around objects using a hybrid SPH-FLIP method. Then these vortical details are carried on SPH particles flowing through the local region and preserved in the global field in a synthetic way. Our method provides a physically plausible way to model the turbulent details around both rigid and deformable objects in SPH fluid, and can efficiently produce animations of complex gaseous phenomena with rich visual details.
Category: Fluids
Creature Control in a Fluid Environment
In this paper, we propose a method designed to allow creatures to actively respond to a fluid environment. We explore various objective functions in order to determine ways to direct the behavior of our creatures. Our proposed method works in conjunction with generalized body forces as well as both one-way and two-way coupled fluid forces. As one might imagine, interesting behaviors can be derived from minimizing and maximizing both drag and lift as well as minimizing the effort that a creature’s internal actuators exert. A major application for our work is the automatic specification of secondary motions, for example, certain joints can be animated while others are automatically solved for in order to satisfy the objective function.
Reconstructing Surfaces of Particle-Based Fluids Using Anisotropic Kernels
In this paper we present a novel surface reconstruction method for particle-based fluid simulators such as Smoothed Particle Hydrodynamics. In particle-based simulations, fluid surfaces are usually defined as a level set of an implicit function. We formulate the implicit function as a sum of anisotropic smoothing kernels, and the direction of anisotropy at a particle is determined by performing Principal Component Analysis (PCA) over the neighboring particles. In addition, we perform a smoothing step that re-positions the centers of these smoothing kernels. Since these anisotropic smoothing kernels capture the local particle distributions more accurately, our method has advantages over existing methods in representing smooth surfaces, thin streams and sharp features of fluids. Our method is fast, easy to implement, and our results demonstrate a significant improvement in the quality of reconstructed surfaces as compared to existing methods.
Reconstructing Surface of Particle-Based Fluids Using Anisotropic Kernels
Practical Animation of Compressible Flow for Shockwaves and Related Phenomena
We propose a practical approach to integrating shock wave dynamics into traditional smoke simulations. Previous methods either simplify away the compressible component of the flow and are unable to capture shock fronts or use a prohibitively expensive explicit method that limits the time step of the simulation long after the relevant shock waves and rarefactions have left the domain. Instead, we employ a semi-implicit formulation of Euler’s equations, which allows us to take time steps on the order of the fluid velocity (ignoring the more stringent acoustic wave-speed restrictions) and avoids the expensive characteristic decomposition typically required of compressible flow solvers. We also propose an extension to Euler’s equations to model combustion of fuel in explosions. The flow is two-way coupled with rigid and deformable solid bodies, treating the solid-fluid interface effects implicitly in a projection step by enforcing a velocity boundary condition on the fluid and integrating pressure forces along the solid surface. As we handle the acoustic fluid effects implicitly, we can artificially drive the sound speed c of the fluid to infinity without going unstable or driving the time step to zero. This permits the fluid to transition from compressible flow to the far more tractable incompressible flow regime once the interesting compressible flow phenomena (such as shocks) have left the domain of interest, and allows the use of state-of-the-art smoke simulation techniques.
Practical Animation of Compressible Flow for Shockwaves and Related Phenomena
Real-Time Simulation of Large Bodies of Water with Small Scale Details
We present a hybrid water simulation method that combines grid based and particles based approaches. Our specialized shallow water solver can handle arbitrary underlying terrain slopes, arbitrary water depth and supports wet-dry regions tracking. To treat open water scenes we introduce a method for handling non-reflecting boundary conditions. Regions of liquid that cannot be represented by the height field including breaking waves, water falls and splashing due to rigid and soft bodies interaction are automatically turned into spray, splash and foam particles. The particles are treated as simple non-interacting point masses and they exchange mass and momentum with the height field fluid. We also present a method for procedurally adding small scale waves that are advected with the water flow. We demonstrate the effectiveness of our method in various test scene including a large flowing river along a valley with beaches, big rocks, steep cliffs and waterfalls. Both the grid and the particles simulations are implemented in CUDA. We achieve real-time performance on modern GPUs in all the examples.
Real-Time Simulation of Large Bodies of Water with Small Scale Details
A Novel Algorithm for Incompressible Flow Using Only A Coarse Grid Projection
Large scale fluid simulation can be difficult using existing techniques due to the high computational cost of using large grids. We present a novel technique for simulating detailed fluids quickly. Our technique coarsens the Eulerian fluid grid during the pressure solve, allowing for a fast implicit update but still maintaining the resolution obtained with a large grid. This allows our simulations to run at a fraction of the cost of existing techniques while still providing the fine scale structure and details obtained with a full projection. Our algorithm scales well to very large grids and large numbers of processors, allowing for high fidelity simulations that would otherwise be intractable.
A Novel Algorithm for Incompressible Flow Using Only A Coarse Grid Projection
A parallel multigrid Poisson solver for fluids simulation on large grids
We present a highly efficient numerical solver for the Poisson equation on irregular voxelized domains supporting an arbitrary mix of Neumann and Dirichlet boundary conditions. Our approach employs a multigrid cycle as a preconditioner for the conjugate gradient method, which enables the use of a lightweight, purely geometric multigrid scheme while drastically improving convergence and robustness on irregular domains. Our method is designed for parallel execution on shared-memory platforms and poses modest requirements in terms of bandwidth and memory footprint. Our solver will accommodate as many as 768X1152 voxels with a memory footprint less than 16GB, while a full smoke simulation at this resolution fits in 32GB of RAM. Our preconditioned conjugate gradient solver typically reduces the residual by one order of magnitude every 2 iterations, while each PCG iteration requires approximately 6.1 sec on a 16-core SMP at 768^3 resolution. We demonstrate the efficacy of our method on animations of smoke flow past solid objects and free surface water animations using Poisson pressure projection at unprecedented resolutions.
A parallel multigrid Poisson solver for fluids simulation on large grids
Discrete Viscous Threads
We present a continuum-based discrete model for thin threads of viscous fluid by drawing upon the Rayleigh analogy to elastic rods, demonstrating canonical coiling, folding, and breakup in dynamic simulations. Our derivation emphasizes space-time symmetry, which sheds light on the role of time-parallel transport in eliminating — without approximation — all but an O(n) band of entries of the physical system’s energy Hessian. The result is a fast, unified, implicit treatment of viscous threads and elastic rods that closely reproduces a variety of fascinating physical phenomena, including hysteretic transitions between coiling regimes, competition between surface tension and gravity, and the first numerical fluid-mechanical sewing machine. The novel implicit treatment also yields an order of magnitude speedup in our elastic rod dynamics.
Enhancing Fluid Animation with Adaptive, Controllable, and Intermittent Turbulence
This paper proposes a new scheme for enhancing fluid animation with controllable turbulence. An existing fluid simulation from ordinary fluid solvers is fluctuated by turbulent variation modeled as a random process of forcing. The variation is precomputed as a sequence of solenoidal noise vector fields directly in the spectral domain, which is fast and easy to implement. The spectral generation enables flexible vortex scale and spectrum control following a user prescribed energy spectrum, e.g. Kolmogorov’s cascade theory, so that the fields provide fluctuations in subgrid scales and/or in preferred large octaves. The vector fields are employed as turbulence forces to agitate the existing flow, where they act as a stimulus of turbulence inside the framework of the Navier-Stokes equations, leading to natural integration and temporal consistency. The scheme also facilitates adaptive turbulent enhancement steered by various physical or user-defined properties, such as strain rate, vorticity, distance to objects and scalar density, in critical local regions. Furthermore, an important feature of turbulent fluid, intermittency, is created by applying turbulence control during randomly selected temporal periods.
Enhancing Fluid Animation with Adaptive, Controllable, and Intermittent Turbulence
Underwater Cloth Simulation with Fractional Derivatives
We introduce the use of fractional differentiation for simulating cloth de formations underwater. The proposed approach is able to achieve realistic underwater deformations without simulating the Eulerian body of water in which the cloth is immersed. Instead, we propose a particle-based cloth model where half-derivative viscoelastic elements are included for describing both the internal and external dynamics of the cloth. These elements model the cloth responses to fluid stresses and are also able to emulate the memory-laden behavior of particles in a viscous fluid. As a result, we obtain fractional clothes, which are able to correctly depict the dynamics of the immersed cloth interacting with the fluid even though the fluid is not simulated. The proposed approach produces realistic underwater cloth deformations and has obvious advantages in simplicity and speed of computation in comparison to volumetric fluid simulation approaches.