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Real-time smoke simulation with improved turbulence by spatial adaptive vorticity confinement
Abstract
Turbulence modeling has recently drawn many attentions in fluid animation to generate small-scale rolling features. Being one of the widely adopted approaches, vorticity confinement method re-injects lost energy dissipation back to the flow. However, previous works suffer from deficiency when large vorticity coefficient ε is used, due to the fact that constant ε is applied all over the simulated domain. In this paper, we propose a novel approach to enhance the visual effect by employing an adaptive vorticity confinement which varies the strength with respect to the helicity instead of a user-defined constant. To further improve fine details in turbulent flows, we are not only applying our proposed vorticity confinement to low-resolution grid, but also on a finer grid to generate sub-grid level turbulence. Since the incompressible Navier–Stokes equations are solved only in low-resolution grid, this saves a significant amount of computation. Several experiments demonstrate that our method can produce realistic smoke animation with enhanced turbulence effects in real-time. Copyright © 2011 John Wiley & Sons, Ltd.
... This method applies the same on the whole region, and the value of is non-physical and has to be turned manually. There are adaptive methods, such as [17,18], which apply different confinement forces on different positions. These methods use current velocity and vorticity fields to generate the confinement force, which neglects the real vorticity dynamics. ...
... This makes our method produce less noise. Furthermore, unlike other adaptive vorticity confinement methods [17,18], our method uses a tracked vorticity which is less probable to be affected by numerical dissipation. This is because motion of vorticity distribution function is weakly dependent on the momentum distribution function. ...
... We can see that GPU-based methods are much more efficient than CPU-based methods. Our implementation of TLBM costs similar computation to other methods [17,18,57]. Compared to TLBM, VPLBM has 36% extra computation (by extending two distribution functions to three) and brings the advantage of preserving details. ...
It is crucial to achieve high efficiency and to preserve fine-grid details in 3D interactive smoke simulation. In this paper, we present a vorticity preserving lattice Boltzmann method (VPLBM) to simulate high-resolution motion of smoke in real time. We design the method based on lattice Boltzmann method (LBM), which is parallelism-friendly, to ensure the efficiency on parallel computing devices such as graphic processing units (GPUs). To resolve the vorticity dissipation issue in LBM, we further propose an LBM-based vorticity transport method which tracks the magnitude of vorticity during the simulation. We apply vorticity confinement according to the tracked vorticity, and therefore, our method can preserve the detailed motion of smoke. Our method is forward-iterative and contains three weakly dependent distribution functions: two for thermal LBM and one for vorticity tracking. Finally, we show an implementation of a parallel smoke simulator integrating VPLBM method on a dual-GPU platform. Using a fast ray marching method, the simulator shows realistic visual effect and achieves 157.3 frames per second on a fine grid.
... 1. A parallel nested grid method that groups the vortex particles to decrease the number of vortex particles traversed during the velocity computation, thus reducing the computational cost; [16], and vorticity confinement [17][18][19] approaches. A common feature of the Eulerian method is that the fluid domain should be discretized in advance. ...
... We set a uniform grid inside the ink and place the vortex particles in the center of every grid. Except for the normal, the vorticity distribution of the two inks is the same, which is calculated by applying Eq (18). We observe that the vortex re-connection phenomenon can be obtained after the collision of rings in all cases, which is consistent with the result reported in [37]. ...
The Lagrangian vortex method has the advantage of producing highly detailed simulations of fluids such as turbulent smoke. However, this method has two problems: the construction of the velocity field from the vorticity field is inefficient, and handling the boundary condition is difficult. We present a pure Lagrangian vortex method, including a nested grid to accelerate the construction of the velocity field, and a novel boundary treatment method for the vorticity field. Based on a tree structure, the nested grid algorithm considerably improves the efficiency of the velocity computation while producing visual results that are comparable with the original flow. Based on the vortex-generating method, the least square method is used to compute the vorticity strength of the new vortex elements. Further, we consider the mutual influence between the generated vortex particles. We demonstrate our method’s benefits by using a vortex ring and various examples of interaction between the smoke and obstacles.
... Fedkiw et al. [24] introduced a physically consistent vorticity confinement term to simulate the small-scale rolling features of smoke. He et al. [25] proposed an adaptive vorticity confinement method, where the vorticity coefficient is determined by the variation in helicity rather than being a user-defined constant. Since the semi-Lagrangian advection and vorticity confinement models do not conserve momentum, Lentine et al. [26] proposed a correction strategy that can enable momentum conservation even with large time steps. ...
Smoke simulation is a crucial yet challenging aspect of constructing ship fire scenarios. For the Eulerian smoke simulation method, the low-resolution grid results in a loss of smoke detail, while the high-resolution grid faces significant computational costs. To address this issue, a detail enhancement approach is proposed for smoke simulation in ship fire scenarios based on vortex particles, aiming at high-realism smoke simulation on a low-resolution grid. The simulation domain is first discretized using a low-resolution grid to compute the basic flow. Next, the vortex particles are sampled within the grid, and the loss of vorticity is measured before and after vortex stretching to compensate for the missing smoke details. In our approach, a geometric method is employed to efficiently capture the stretching of vortex structures. The computational results demonstrate that turbulence details can be effectively captured in a low-resolution grid while maintaining the real-time performance of the simulation. The practical application value of our approach is demonstrated in improving the realism of ship fire scenarios.
... HWPW11] proposed an adaptive vorticity coefficient method and obtained more turbulent details in smoke simulations. Later work improved this method[HL13] and further guaranteed the numeri-cal stability. ...
Eulerian‐based smoke simulations are sensitive to the initial parameters and grid resolutions. Due to the numerical dissipation on different levels of the grid and the nonlinearity of the governing equations, the differences in simulation resolutions will result in different results. This makes it challenging for artists to preview the animation results based on low‐resolution simulations. In this paper, we propose a learning‐based flow correction method for fast previewing based on low‐resolution smoke simulations. The main components of our approach lie in a deep convolutional neural network, a grid‐layer feature vector and a special loss function. We provide a novel matching model to represent the relationship between low‐resolution and high‐resolution smoke simulations and correct the overall shape of a low‐resolution simulation to closely follow the shape of a high‐resolution down‐sampled version. We introduce the grid‐layer concept to effectively represent the 3D fluid shape, which can also reduce the input and output dimensions. We design a special loss function for the fluid divergence‐free constraint in the neural network training process. We have demonstrated the efficacy and the generality of our approach by simulating a diversity of animations deviating from the original training set. In addition, we have integrated our approach into an existing fluid simulation framework to showcase its wide applications.
... However, it cannot calculate the amount of confinement force to be injected without causing instability. To ensure the stability, He et al. [26] proposed the adaptive vorticity confinement method by adjusting the coefficients for vorticity according to the vorticity magnitude. ...
When we perform particle-based water simulation, water particles are often increased dramatically because of particle splitting around breaking holes to maintain the thin fluid sheets. Because most of the existing approaches do not consider the volume of the water particles, the water particles must have a very low mass to satisfy the law of the conservation of mass. This phenomenon smears the motion of the water, which would otherwise result in splashing, thereby resulting in artifacts such as numerical dissipation. Thus, we propose a new fluid-implicit, particle-based framework for maintaining and representing the thin sheets and turbulent flows of water. After splitting the water particles, the proposed method uses the ghost density and ghost mass to redistribute the difference in mass based on the volume of the water particles. Next, small-scale turbulent flows are formed in local regions and transferred in a smooth manner to the global flow field. Our results show us the turbulence details as well as the thin sheets of water, thereby obtaining an aesthetically pleasing improvement compared with existing methods.
... However, this method cannot determine how much confinement force should be injected back into the system without causing instability. He et al. [8] proposed an adaptive vorticity confinement method to adjust the vorticity coefficients according to the vorticity magnitude and to ensure its stability. The vortex particle method is also widely used to represent the turbulent details in smoke simulations. ...
We propose an efficient and physics-inspired method for producing water spray effects by modeling air particles within a narrowband of the water surface in particle-based water simulation. In the real world, water and air continuously interact with each other around free surfaces, and this phenomenon is commonly observed in waterfalls or in rough sea waves. Due to the small volume of water spray, the interfaces between water and air become vague, and the interactions between water and air lead to strong vortex phenomena. To express these phenomena, we propose the generation of narrowband air cells in particle-based water simulations and the expression of water spray effects by creating and evolving air particles in narrowband air cells. We guarantee the robustness of the simulation by solving the drifting problem that occurs when the number of adjacent air particles is insufficient. Experiments convincingly demonstrate that the proposed approach is efficient and easy to use while delivering high-quality results. We produce efficient water spray effects from coarse simulation as an independent post-process that can be applied to most particle-based fluid solvers.
We propose a pure Lagrangian vortex particle dynamics framework to simulate the various phenomena of turbulent smoke and two-way coupling between fluid and solid. In the framework, we model the fluid using vorticity and velocity fields that are discretized on the vortex particles. We extend a segment-based vortex stretching strategy with the subdivision of long segments to capture the fine details of smoke while maintaining good numerical stability. In addition, a vorticity field correction mechanism based on the merging and splitting of particles is proposed to avoid excessive particle counts and reduce the associated unnecessary computational overhead. We also present a fast and approximate two-way coupling method for simulating the interaction between solid and fluid. Our method can be used to solve various fluid phenomena, including Kármán vortex streets, jets, and some examples of two-way fluid–solid coupling.
The advection step in grid‐based fluid simulation is prone to numerical dissipation, which results in loss of detail. How to improve the advection accuracy to preserve more fluid details is still challenging. On the other hand, a common way to enhance smoke details is to use vorticity confinement. However, most of the previous methods simply used a fine‐tuned scale factor ε to adjust the strength of the confinement force, which can only amplify existing vortex details and is easy to cause instability when ε is large. In this article, we proposed an adaptive vorticity confinement method, which does not suffer from the above problems, to compensate the vorticity loss during advection with little extra cost. The main idea is to first calculate a scale factor whose value depends on the vorticity loss during advection, and then use it to adaptively control the vorticity confinement force for vorticity compensation with high stability. The experiment results show the effectiveness and efficiency of our method.
Real-time fluid control is indispensable in computer animation, games, virtual reality, etc. In the field of Smoothed Particle Hydrodynamics (SPH) fluid control, the strategy of control force is often employed to control fluid particles; however, the artificial viscosity introduced by the control force would frequently lead to the loss of fine-scale details. Although the introduction of the low-pass filter can add back details, it may easily destroy the control target, and the control force method itself cannot make SPH fluid follow the fast-moving control target. Meanwhile, this type of method is computation intensive and time consuming. To remedy the above problems, this paper proposed a novel, interactive SPH fluid control framework with turbulent details. We run SPH fluid simulation on Compute Unified Device Architecture (CUDA) and greatly improve the efficiency of fluid control. The control particle with curvature framework was adapted in this paper. We specially designed spring forces to make the fluid match a fast-moving control target. Moreover, fine fluid details were preserved separately by calculating the fluid turbulence under control and the free fluid turbulence. This improved SPH fluid control can run in real time, which can enhance the visual quality of fluid animation as well. Our novel method can be applied in fluid animation with special control effects to guide fluid to form a target shape while greatly preserving the dynamic details of fluid. Various experiment results demonstrated the ability of our novel method.
Simulation of explosive smoke generation and interaction between smoke and military targets in real time rendering of battlefield scene are studied. Numerical solution of Navier-Stokes equation of impressible gas is used to solve smoke field. Appropriate way of adding vortex particles is exploded to makes the smoke effect more realistic. Three dimensional Gaussian filter is used to density field of smoke in order to avoid scattered smoke flow. The reasonable parameters of the Gaussian filter are tried out for better smoke effect. The interaction effect between smoke and mobile military targets are simulated. Octree structure based voxelization is adopted to interactive computing for high computational efficiency. Proxy geometry is gained after a set of planes vertical to sight line intersecting with the edges of the smoke field cube. And then smoke and battlefield scene are synthesized. Research results of this paper can be applied to battlefield simulation and game scene rendering.
Enhancing the details of the smoke rendering is a major direction in virtual reality. One common solution is enhancing turbulence by adding vorticity confinement force. The traditional methods mostly add it on the global grid which would lead to expensive cost. To address this problem, we propose an adaptive two-scale vorticity confinement method. With a new scheme of computational grid, our method can determine the region with rich detail adaptively. First, the Navier-Stokes equations are solved on the coarse grid by the semi-Lagrangian method. Then, we divide the coarse grid using the defined threshold of vorticity. Finally, we obtain the velocity field of coarse grid by sampling from the fine grid, and advect density by it. In addition, we combine the helicity method which can avoid "blow up" when calculating vorticity confinement force. Various experiments validated our method.
Fluid animation has always been one of the most interesting and challenging projects. Fluid simulation based on physical methods can get vivid result. With its unparallel advantage of simulating incompressible fluid, vortex method is one of the most efficient methods. This paper mainly introduces the classification of vortex methods, draws a conclusion of previous study of vortex methods and makes a comparison between them.
We present an up-to-date survey on physically-based smoke simulation. Physically-based method becomes predominant in smoke simulation in computer graphics community. It prevails over traditional methods for its plausible visual effect. Significant results have been carried out over past two decades. We give a latest overview of state-of-the-art of smoke simulation and also compare various techniques according to their characteristics. We discuss several issues in terms of computational efficiency, numerical stability, numerical dissipation, and runtime performance. A number of open challenging problems are also addressed for further exploration.
Numerical dissipation acts as artificial viscosity to make smoke viscous. Reducing numerical dissipation is able to recover visual details smeared out by the numerical dissipation. Great efforts have been devoted to suppress the numerical dissipation in smoke simulation in the past few years. In this paper we investigate methods of combating the numerical dissipation. We describe visual consequences of the numerical dissipation and explore sources that introduce the numerical dissipation into course of smoke simulation. Methods are investigated from various aspects including grid variation, high-order advection, sub-grid compensation, invariant conservation, and particle-based improvement, followed by discussion and comparison in terms of visual quality, computational overhead, ease of implementation, adaptivity, and scalability, which leads to their different applicability to various application scenarios.
We propose an octree-based presentation of vortex particles to simulate smoke and gaseous phenomena in a physical way. Vortex particle method prevails over grid-based method in terms of less numerical dissipation and more detail features, but it suffers from heavy computational overhead due to per-particle Biot–Savart integration over the entire simulation space. To alleviate this problem, we employ an octree background grid to separate the vortex particles into individual groups. Particles in groups are aggregated as a single super vortex particle to reduce computational cost. The proposed method produces comparable visual result as previous methods with much less computational overhead. Copyright © 2014 John Wiley & Sons, Ltd.
Capturing fine details of turbulence on a coarse grid is one of the main tasks in real‐time fluid simulation. Existing methods for doing this have various limitations. In this paper, we propose a new turbulence method that uses a refined second vorticity confinement method, referred to as robust second vorticity confinement, and a synthesis scheme to create highly turbulent effects from coarse grid. The new technique is sufficiently stable to efficiently produce highly turbulent flows, while allowing intuitive control of vortical structures. Second vorticity confinement captures and defines the vortical features of turbulence on a coarse grid. However, due to the stability problem, it cannot be used to produce highly turbulent flows. In this work, we propose a robust formulation to improve the stability problem by making the positive diffusion term to vary with helicity adaptively. In addition, we also employ our new method to procedurally synthesize the high‐resolution flow fields. As shown in our results, this approach produces stable high‐resolution turbulence very efficiently.
While small-scale fluid details are crucial elements for the creation of visually pleasing fluid animations, their synthesis often requires heavy computation with traditional grid-based fluid simulation methods. This paper proposes a novel method for enhancing the appearance of small-scale details through frequency-domain analysis. Different from previous work, our method detects and improves fluid details in the frequency-domain via lifting wavelet decomposition. Based on a coarse-to-fine mechanism, the lifting wavelet composition first transforms the velocity in a fine grid into the frequency domain. Next, the velocity field is enhanced separately for different frequency bands. A novel velocity fusion method is developed for the enhancement of low-frequency parts. On the other hand, high-frequency parts are enhanced using a specially designed vorticity confinement method. Finally, the application of the inverse lifting wavelet transform determines the final velocity field with increased fine details. Our method can generate perceptually interesting fluid details, matching human visual perception theory. The results of various experiments validate the effectiveness and efficiency of our method. Copyright © 2014 John Wiley & Sons, Ltd.
Smoke simulation is one of the interesting topics in computer animation and it usually involves turbulence generation. Efficient generation of realistic turbulent flows becomes one of the challenges in smoke simulation. Vortex particle method, which is a hybrid method that combines grid-based and particle-based approaches, is often used for generating turbulent details. However, it may cause irrational artifacts due to its initial condition and vorticity forcing approach used. In this paper, a new vorticity forcing approach based on the spatial adaptive vorticity confinement is proposed to address this problem. In this approach, the spatial adaptive vorticity confinement force varies with helicity, leading to the fact that the grid-based simulation driven by the vortex particle is now based on the velocity field. Furthermore, we introduce an adaptive vortex particle approach to improve the computational efficiency of the simulation by making the influencing region adapt with the velocity and eliminating those particles with zero velocity in the vorticity forcing method. A parallel smoke simulator integrating our approaches has been implemented using GPUs with CUDA. Experimental results demonstrate that our proposed methods are efficient and effective for real-time smoke simulation.
A new ‘‘vorticity confinement’’ method is described which involves adding a term to the momentum conservation equations of fluid dynamics. This term depends only on local variables and is zero outside vortical regions. The partial differential equations with this extra term admit solutions that consist of Lagrangian-like confined vortical regions, or covons, in the shape of two-dimensional (2-D) vortex ‘‘blobs’’ and three-dimensional (3-D) vortex filaments, which convect in a constant external velocity field with a fixed internal structure, without spreading, even if the equations contain diffusive terms. Solutions of the discretized equations on a fixed Eulerian grid show the same behavior, in spite of numerical diffusion. Effectively, the new term, together with diffusive terms, constitute a new type of regularization of the inviscid equations which appears to be very useful in the numerical solution of flow problems involving thin vortical regions. The discretized Euler equations with the extra term can be solved on fairly coarse, Eulerian computational grids with simple low-order (first- or second-) accurate numerical methods, but will still yield concentrated vortices which convect without spreading due to numerical diffusion. Since only a fixed grid is used with local variables, the vorticity confinement method is quite general and can automatically accommodate changes in vortex topology, such as merging. Applications are presented for incompressible flow in 3D, where pairs of thin vortex rings interact and, in some cases, merge.
A general theoretical review of helicity in flows that are laminar or turbulent is presented with references to corresponding experimental investigations. The topological nature of the helicity invariant is examined, and the turbulent dynamo mechanism is discussed in relation to the phenomenon of helicity. Helicity is also discussed in terms of being a topological constraint in relaxation to equilibrium, and attention is given to the structure of turbulence and the suppression of nonlinearity. Observational and experimental data related to helical structures are reviewed including the generation of helicity in helicity-free flows, quantitative measurements of helicity, and the application of of helicity density as a pseudoscalar quantity for characterizing complex 3D flows. Other topics of significance are addressed including skew diffusion, the AKA effect, and relaxation under modified Euler equation evolution.
This is in no way intended as a review of turbulence-the subject is far too big for adequate treatment within a reasonably finite number of pages; the monumental treatise of Monin & Yaglom (1971, 1975) bears witness to this statement. It is rather a discourse on those aspects of the problem of turbulence with which I have myself had contact over the last twenty years or so. My choice of topics therefore has a very personal bias - but that is perhaps consistent with the style and objectives of this rather unusual issue of JFM.
Let u(x) be the velocity field in a fluid of infinite extent due to a vorticity distribution w(x) which is zero except in two closed vortex filaments of strengths K1, K2. It is first shown that the integral
\[
I=\int{\bf u}.{\boldmath \omega}\,dV
\]
is equal to αK1K2 where α is an integer representing the degree of linkage of the two filaments; α = 0 if they are unlinked, ± 1 if they are singly linked. The invariance of I for a continuous localized vorticity distribution is then established for barotropic inviscid flow under conservative body forces. The result is interpreted in terms of the conservation of linkages of vortex lines which move with the fluid.
We introduce a simple turbulence model for smoke animation, qualitatively capturing the transport, diffusion, and spectral cascade of turbulent energy unresolved on a typical simulation grid. We track the mean kinetic energy per octave of turbulence in each grid cell, and a novel "net rotation" variable for modeling the self-advection of turbulent eddies. These additions to a standard fluid solver drive a procedural post-process, layering plausible dynamically evolving turbulent details on top of the large-scale simulated motion. Finally, to make the most of the simulation grid before jumping to procedural sub-grid models, we propose a new multistep predictor to alleviate the nonphysical dissipation of angular momentum in standard graphics fluid solvers.
We propose a novel approach to guiding of Eulerian-based smoke animations through coupling of simulations at different grid resolutions. Specifically we present a variational formulation that allows smoke animations to adopt the low-frequency features from a lower resolution simulation (or non-physical synthesis), while simultaneously developing higher frequencies. The overall motivation for this work is to address the fact that art-direction of smoke animations is notoriously tedious. Particularly a change in grid resolution can result in dramatic changes in the behavior of smoke animations, and existing methods for guiding either significantly lack high frequency detail or may result in undesired features developing over time. Provided that the bulk movement can be represented satisfactorily at low resolution, our technique effectively allows artists to prototype simulations at low resolution (where computations are fast) and subsequently add extra details without altering the overall "look and feel". Our implementation is based on a customized multi-grid solver with memory-efficient data structures.
The back and forth error compensation and correction (BFECC) method advects the solution forward and then backward in time. The result is compared to the original data to estimate the error. Although inappropriate for parabolic and other non-reversible par- tial differential equations, it is useful for often troublesome advec- tion terms. The error estimate is used to correct the data before advection raising the method to second order accuracy, even though each individual step is only first order accurate. In this paper, we rewrite the MacCormack method to illustrate that it estimates the error in the same exact fashion as BFECC. The difference is that the MacCormack method uses this error estimate to correct the already computed forward advected data. Thus, it does not require the third advection step in BFECC reducing the cost of the method while still obtaining second order accuracy in space and time. Recent work re- placed each of the three BFECC advection steps with a simple first order accurate unconditionally stable semi-Lagrangian method yield- ing a second order accurate unconditionally stable BFECC scheme. We use a similar approach to create a second order accurate uncon- ditionally stable MacCormack method.
We present a novel technique for the animation of turbulent fluids by coupling a procedural turbulence model with a numerical fluid solver to introduce subgrid-scale flow detail. From the large-scale flow simulated by the solver, we model the production and behav- ior of turbulent energy using a physically motivated energy model. This energy distribution is used to synthesize an incompressible tur- bulent velocity field, whose features show plausible temporal be- havior through a novel Lagrangian approach for advected noise. The synthesized turbulent flow has a dynamical effect on the large- scale flow, and produces visually plausible detailed features on both gaseous and free-surface liquid flows. Our method is an order of magnitude faster than full numerical simulation of equivalent reso- lution, and requires no manual direction.
Vorticity confinement reintroduces the small scale detail lost when using efficient semi-Lagrangian schemes for simulating smoke and fire. However, it only amplifies the existing vorticity, and thus can be insufficient for highly turbulent effects such as explosions or rough water. We introduce a new hybrid technique that makes synergistic use of Lagrangian vortex particle methods and Eulerian grid based methods to overcome the weaknesses of both. Our approach uses vorticity confinement itself to couple these two methods together. We demonstrate that this approach can generate highly turbulent effects unachievable by standard grid based methods, and show applications to smoke, water and explosion simulations.
Physically based animation of fluids such as smoke, water, and fire provides some of the most stunning visuals in computer graphics, but it has historically been the domain of high-quality offline rendering due to great computational cost. In this chapter we show not only how these effects can be simulated and rendered in real time, as Figure 30-1 demonstrates, but also how they can be seamlessly integrated into real-time applications. Physically based effects have already changed the way interactive environments are designed. But fluids open the doors to an even larger world of design possibilities. In the past, artists have relied on particle systems to emulate 3D fluid effects in real-time applications. Although particle systems can produce attractive results, they cannot match the realistic appearance and behavior of fluid simulation. Real time fluids remain a challenge not only because they are more expensive to simulate, but also because the volumet-ric data produced by simulation does not fit easily into the standard rasterization-based rendering paradigm.
This paper describes a new animation technique for modeling the turbulent rotational motion that occurs when a hot gas interacts with solid objects and the surrounding medium. The method is especially useful for scenes involving swirling steam, rolling or billowing smoke, and gusting wind. It can also model gas motion due to fans and heat convection. The method combines specialized forms of the equations of motion of a hot gas with an efficient method for solving volumetric differential equations at low resolutions. Particular emphasis is given to issues of computational efficiency and ease-of-use of the method by an animator. We present the details of our model, together with examples illustrating its use. Keywords: Animation, Convection, Gaseous Phenomena, Gas Simulations, Physics-Based Modeling, Steam, Smoke, Turbulent Flow. 1 Introduction The turbulent motion of smoke and steam has always inspired interest amongst graphics researchers. The problem of modeling the complex inter-r...
Building animation tools for fluid-like motions is an important and challenging problem with many applications in computer graphics. The use of physics-based models for fluid flow can greatly assist in creating such tools. Physical models, unlike key frame or procedural based techniques, permit an animator to almost effortlessly create interesting, swirling fluid-like behaviors. Also, the interaction of flows with objects and virtual forces is handled elegantly. Until recently, it was believed that physical fluid models were too expensive to allow real-time interaction. This was largely due to the fact that previous models used unstable schemes to solve the physical equations governing a fluid. In this paper, for the first time, we propose an unconditionally stable model which still produces complex fluid-like flows. As well, our method is very easy to implement. The stability of our model allows us to take larger time steps and therefore achieve faster simulations. We have used our model in conjuction with advecting solid textures to create many fluid-like animations interactively in two- and three-dimensions.
In this paper, we propose a new approach to numerical smoke simulation for computer graphics applications. The method proposed here exploits physics unique to smoke in order to design a numerical method that is both fast and efficient on the relatively coarse grids traditionally used in computer graphics applications (as compared to the much finer grids used in the computational fluid dynamics literature). We use the inviscid Euler equations in our model, since they are usually more appropriate for gas modeling and less computationally intensive than the viscous NavierStokes equations used by others. In addition, we introduce a physically consistent vorticity confinement term to model the small scale rolling features characteristic of smoke that are absent on most coarse grid simulations. Our model also correctly handles the interaction of smoke with moving objects. Keywords: Smoke, computational fluid dynamics, Navier-Stokes equations, Euler equations, Semi-Lagrangian methods, stable fluids, vorticity confinement, participating media 1
The use of vorticity confinement techniques to predict missile forces and moments more accurately is demonstrated. An inviscid Cartesian grid CFD code was modified to include both field and surface vorticity confinement. The code was used to compute the forces and moments on missile geometries with and without vorticity confinement. Vorticity field confinement is shown to allow convection of discrete vortices without degradation due to numerical diffusion. Vorticity surface confinement is shown to soften the inviscid pressure field on the missile surface, allowing a viscous-like calculation for little more than the cost of an Euler calculation. Results are presented to show that these techniques can allow more accurate force and moment predictions from an Euler CFD code without resorting to a more expensive calculation.
This chapter describes a method for fast, stable fluid simulation that runs entirely on the GPU. It introduces fluid dynamics and the associated mathematics, and it describes in detail the techniques to perform the simulation on the GPU. After reading this chapter, you should have a basic understanding of fluid dynamics and know how to simulate fluids using the GPU. The source code accompanying this book demonstrates the techniques described in this chapter.
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.
Abstract We propose a fast and effective technique to improve sub-grid visual details of the grid based fluid simulation. Our method procedurally synthesizes the flow fields coming from the incompressible Navier-Stokes solver and the vorticity fields generated by vortex particle method for sub-grid turbulence. We are able to efficiently animate smoke which is highly turbulent and swirling with small scale details. Since this technique does not solve the linear system in high-resolution grids, it can perform fluid simulation more rapidly. We can easily estimate the influence of turbulent and swirling effect to the fluid flow.
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.
We present a novel wavelet method for the simulation of fluids at high spatial resolution. The algorithm enables large- and small-scale detail to be edited separately, allowing high-resolution detail to be added as a post-processing step. Instead of solving the Navier-Stokes equations over a highly refined mesh, we use the wavelet decomposition of a low-resolution simulation to determine the location and energy characteristics of missing high-frequency components. We then synthesize these missing components using a novel incompressible turbulence function, and provide a method to maintain the temporal coherence of the resulting structures. There is no linear system to solve, so the method parallelizes trivially and requires only a few auxiliary arrays. The method guarantees that the new frequencies will not interfere with existing frequencies, allowing animators to set up a low resolution simulation quickly and later add details without changing the overall fluid motion.
Visual simulation of smoke
- Jensenhw Fedkiwr Stamj
Real time simulation and rendering of 3d fluids
- Llamasi Cranek Tariqs
Evolving sub-grid turbulence for smoke animation. InProc
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Enhancing fluid animation with adaptive controllable and intermittent turbulence
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Fast third-order texture filtering
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Fast fluid dynamics simulation on the gpu. InGPU Gems
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