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An Efficient Adaptive Vortex Particle Method for Real-Time Smoke Simulation
Abstract
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.
... 또한 물리 기반 시뮬레이션 분야에서는 시뮬레이션 정확도를 개선하 기 위해 고차 수치 보간법을 사용한다 [9]. 연기 시뮬레이션의 이류항에 활용되는 선형보간 기반의 세미 라그랑주 방식을 [10] 개선하기 위해 BFECC(Back and forth error compensation and correction) [11], CIP(Constrained interpolation profile) [12], US-CIP(Unsplit semi-Lagrangian CIP) [13], 스트림 기반 연기 [14], 주 파스 기반 연기 [15], 적응형 와류 기법 [16], Polynomial PIC [17] 등 기법들이 제안되었다. [19,20,10]. ...
... 세미 라그랑주 기법은 안정적인 유체를 시뮬레이션하 기 위해 제안되었으며 [10], 와류 제한 기법(Vorticity confinement method)은 격자기반에서 난류를 표현하기 위한 와류 힘을 추정했 으며 [21], 향후 라그랑지안 입자를 와류 운반체로 활용하여 와류 입자 방법(Vortex particle method)으로 개선되었다 [22]. 그 외에 도 BFECC [11], CIP [12], USCIP [13], 스트림 기반 연기 [14], 주 파스 기반 연기 [15], 적응형 와류 기법 [16] ...
... [17][18][19] These methods solve Navier-Stokes' equation. Some simulation methods using "vortex particles" 20,21 or simulation methods called "vortex particle method" [22][23][24] are used for real-time simulations of smoke, water, and explosions. In fact, these methods are closer to the VIC method than the VPM, according to the classification mentioned above. ...
... Satoh 26 developed a higher-order semi-Lagrangian method combined with the constrained interpolation profile (CIP) method 27 to trace vortices in the atmosphere. The method simultaneously solves the vorticity and Navier-Stokes' equations as similar to the methods used in the field of CG. [22][23][24] Therefore, there are no comprehensive researches on the properties including the accuracy, conservativity, and execution speed of the semi-Lagrangian methods for solving the vorticity equation. ...
This study focuses on the convection scheme in the vortex particle method. The usual two-step convection procedure for vortex elements, which comprises the convection of vortex elements on each grid point and redistribution of vorticity into each grid point, is extremely difficult to parallelize because of unavoidable memory-write conflictions in the redistribution step, thereby limiting the computational speed. We apply a semi-Lagrangian method called the cubic semi-Lagrangian method, as the convection scheme in the vortex particle method to improve space–time accuracy and accelerate computations. Two test problems, namely the Taylor–Green vortex and double shear flow, are simulated using the semi-Lagrangian vortex particle method proposed in this study to confirm its suitability. The results show that the accuracy of capturing standing vortices and the total amount of kinetic energy conservation are significantly improved. The performance measurements show that the average execution time for the convection of vortex elements is reduced to one-half, thus verifying the semi-Lagrangian method as a suitable convection scheme for the vortex particle method.
... However, particle methods based on momentum equations cannot describe the vortex details of the smoke vortex. He et al. used an adaptive vortex particle model to realize realtime smoke simulation [16] ; the particle method based on a vorticity equation is able to show the details of the smoke vortex. Hu et al. used the GPU acceleration method to simulate smoke based on a vortex particle model [17] . ...
Background and Objective
A realistic virtual surgery simulation needs to simulate smoke as electrical cutting causes thermal tissue damage. The vortex particle method of simulating smoke can realistically present the vortex details and motion trajectory of the smoke, but there is high computational cost.
Methods
To address this problem, we propose the 3D Vortex Particles in Cube Algorithm (3D-VPICA). 3D-VPICA can realistically show the visual effect of smoke and reduce the computational cost. In addition, in order to enhance the reality of the smoke, we propose the Auxiliary Particles Algorithm (APA) method to deal with the collision problem of smoke.
Results
The 3D-VPICA can calculate the velocity of the vortex particles speedily with the help of cube grids and with the complexity decreasing from O(N²) to O(N) + O(Mlog 2M). The APA can ensure that boundary conditions are satisfied when the smoke collides with irregular surfaces. Experimental results show that 3D-VPICA is faster than traditional methods of smoke simulation and that APA is successful in simulating smoke colliding with moving objects with irregular surfaces.
Conclusions
The proposed 3D smoke simulation method was applied to a virtual surgery system using a high frequency electric knife. The cutting and coagulate operations were fluent and the smoke flowed with fidelity.
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.
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.
This article presents a simple, fast and stable method for the animation and visualisation of turbulent gaseous fluids in two dimensions. We draw on well known methods from computational fluid dynamics to model the fluid using vorticity and velocity fields. While the vorticity is transported by a particle system, we use a uniform grid to compute velocities and displacements for each particle. This mixed approach where free particles move on a fixed grid requires little computational power, making it suitable for computer animation. The method simulates the behaviour of fluids in situations where the contact between fluid masses with different velocities generates an intermediate mixing layer which can give rise to turbulence phenomena. Unlike previous algorithms, it is possible to generate quasiturbulent patterns, where large scale coherent vortex structures are still discernible in the flow.
We describe an interactive system featuring fluid-driven animation that responds to moving objects. Our system includes a GPU-accelerated Eulerian fluid solver that is suited for real-time use because it is unconditionally stable, takes constant calculation time per frame, and provides good visual fidelity. We dynamically translate the fluid simulation domain to track a user-controlled object. The fluid motion is visualized via its effects on particles which respond to the calculated fluid velocity field, but which are not constrained to stay within the bounds of the simulation domain. As particles leave the simulation domain, they seamlessly transition to purely particle-based motion, obscuring the point at which the fluid simulation ends. We additionally describe a hardware-accelerated volume rendering system that treats the particles as participating media and can render effects such as smoke, dust, or mist. Taken together, these components can be used to add fluid-driven effects to an interactive system without enforcing constraints on user motion, and without visual artifacts resulting from the finite extents of Eulerian fluid simulation methods.
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 article presents a simple, fast and stable method for the animation and visualisation of turbulent gaseous fluids in two dimensions. We draw on well known methods from computational fluid dynamics to model the fluid using vorticity and velocity fields. While the vorticity is transported by a particle system, we use a uniform grid to compute velocities and displacements for each particle. This mixed approach where free particles move on a fixed grid requires little computational power, making it suitable for computer animation. The method simulates the behaviour of fluids in situations where the contact between fluid masses with different velocities generates an intermediate mixing layer which can give rise to turbulence phenomena. Unlike previous algorithms, it is possible to generate quasi-turbulent patterns, where large scale coherent vortex structures are still discernible in the flow.
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
A practical introduction, the second edition of Fluid Simulation for Computer Graphics shows you how to animate fully three-dimensional incompressible flow. It covers all the aspects of fluid simulation, from the mathematics and algorithms to implementation, while making revisions and updates to reflect changes in the field since the first edition. Highlights of the Second Edition • New chapters on level sets and vortex methods • Emphasizes hybrid particle–voxel methods, now the industry standard approach • Covers the latest algorithms and techniques, including: fluid surface reconstruction from particles; accurate, viscous free surfaces for buckling, coiling, and rotating liquids; and enhanced turbulence for smoke animation • Adds new discussions on meshing, particles, and vortex methods The book changes the order of topics as they appeared in the first edition to make more sense when reading the first time through. It also contains several updates by distilling author Robert Bridson’s experience in the visual effects industry to highlight the most important points in fluid simulation. It gives you an understanding of how the components of fluid simulation work as well as the tools for creating your own animations.
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.
Abstract We develop a new Lagrangian primitive, named Langevin particle, to incorporate turbulent flow details in fluid simulation. A group of the particles are distributed inside the simulation domain based on a turbulence energy model with turbulence viscosity. A particle in particular moves obeying the generalized Langevin equation, a well known stochastic differential equation that describes the particle's motion as a random Markov process. The resultant particle trajectory shows self-adapted fluctuation in accordance to the turbulence energy, while following the global flow dynamics. We then feed back Langevin forces to the simulation based on the stochastic trajectory, which drive the flow with necessary turbulence. The new hybrid flow simulation method features nonrestricted particle evolution requiring minimal extra manipulation after initiation. The flow turbulence is easily controlled and the total computational overhead of enhancement is minimal based on typical fluid solvers.
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.
A variety of animation effects such as herds and fluids contain detailed motion fields characterized by repetitive structures. Such detailed motion fields are often visually important, but tedious to specify manually or expensive to simulate computationally. Due to the repetitive nature, some of these motion fields (e.g. turbulence in fluids) could be synthesized by procedural texturing, but procedural texturing is known for its limited generality.
We apply example-based texture synthesis for motion fields. Our technique is general and can take on a variety of user inputs, including captured data, manual art, and physical/procedural simulation. This data-driven approach enables artistic effects that are difficult to achieve via previous methods, such as heart shaped swirls in fluid animation. Due to the use of texture synthesis, our method is able to populate a large output field from a small input exemplar, imposing minimum user workload. Our algorithm also allows the synthesis of output motion fields not only with the same dimension as the input (e.g. 2D to 2D) but also of higher dimension, such as 3D volumetric outputs from 2D planar inputs. This cross-dimension capability supports a convenient usage scenario, i.e. the user could simply supply 2D images and our method produces a 3D motion field with similar characteristics. The motion fields produced by our method are generic, and could be combined with a variety of large-scale low-resolution motions that are easy to specify either manually or computationally but lack the repetitive structures to be characterized as textures. We apply our technique to a variety of animation phenomena, including smoke, liquid, and group motion.
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.