Markov-Type Vector Field for endless surface animation of water stream

In this paper, we propose a hybrid (physical-stochastic) model of surface element (surfel) fluctuations for the visual simulation of an endlessly running water surface. This model comprises two main phases: preprocessing and endless animation phases. First, we simulate a physics-based method for a specific period of time during the preprocessing phase. We construct a stochastic vector field in the simulation, referred to as a Markov-Type Vector Field (MTVF), using only the surface values of the fluid flow. Next, we import the MTVF data into the main endless animation phase and create a surface fluctuation animation by surfels and temporary velocity field modeling of the MTVF using a random sample. In our approach, the surfel edges that cover the fluid flow domain are transferred simply via a temporary single velocity and the new flow surface is determined directly based on their positions. MTVF allows us to generate a water surface animation endlessly in real time without the time-consuming processes of solving the corresponding physical equations. We describe the MTVF construction method and the endless surface animation steps, as well as present the results of experiments that demonstrate the plausibility of our method.     

The Lattice-boltzmann method for simulating gaseous phenomena

We present a physically-based, yet fast and simple method to simulate gaseous phenomena. In our approach, the incompressible Navier-Stokes (NS) equations governing fluid motion have been modeled in a novel way to achieve a realistic animation. We introduce the lattice Boltzmann model (LBM), which simulates the microscopic movement of fluid particles by linear and local rules on a grid of cells so that the macroscopic averaged properties obey the desired NS equations. The LBM is defined on a 2D or 3D discrete lattice, which is used to solve fluid animation based on different boundary conditions. The LBM simulation generates, in real-time, an accurate velocity field and can incorporate an optional temperature field to account for the buoyancy force of hot gas. Because of the linear and regular operations in each local cell of the LBM grid, we implement the computation in commodity texture hardware, further improving the simulation speed. Finally, textured splats are used to add small scale turbulent details, achieving high-quality real-time rendering. Our method can also simulate the physically correct action of stationary or mobile obstacles on gaseous phenomena in real-time, while still maintaining highly plausible visual details.     

大规模流体场景的真实感与实时模拟

目的 基于物理的流体动画模拟是计算机图形学领域中的研究热点,针对实际应用中仍难以实现大规模流体场景的真实感与实时模拟,提出了基于shallow water方程的物理模拟方法。方法 首先,给出shallow water方程的稳定欧拉数值求解方法,解决模拟过程中存在的毛刺、陡坡水滴斑点等数值求解的不稳定性问题;其次,提出刚体和粒子系统与流体高度场的稳定耦合模型,实现双向固流耦合和流体表面细节的真实感模拟;最后,设计高度场的多精度网格算法以及粒子的隔点采样方法,加速大规模流体的物理模拟计算。结果 实验结果表明,本文方法解决了传统欧拉方法求解shallow water方程的流体模拟过程中存在的不稳定和计算复杂等问题,在300×300网格分辨率和2.2×10⁴粒子数的规模下,达到了20帧/s的实时模拟速度。结论 本文算法具有良好的高效性和稳定性,适用于电子游戏和视景仿真等实时应用领域中的大规模流体场景的真实感模拟。     

基于物理模型的烟雾实时模拟

本文提出了一种基于物理模型的烟雾的实时数值模拟方法.真实感和实时性是计算机图形学追求的两个目标.传统的动画技术生成的物体运动是虚拟的,并不能完全反映物体的真实运动.与传统的动画技术相比,基于物理的动画更能表现运动的真实性.在用非粘性不可压欧拉方程表示烟雾的物理模型的基础上,利用破开算子法将其分解成外力项、对流项和投影项分别进行求解,每一步都稳定,因而整个求解也就稳定.求解过程的稳定性保证了模拟可以用大时间步长,也就保证了模拟的实时性.与传统的方法相比,能同时满足计算机图形学的真实感和实时性要求.     

基于物理模型的火苗动画

本文提出了一种基于物理模型的火苗数值模拟方法。真实感和实时性是计算机图形学追求的两个目标。传统的动画技术生成的物体运动是虚拟的,并不能完全反映物体的真实运动。与传统的动画技术相比,基于物理的动画更能表现运动的真实性。本文在用非粘性不可压欧拉方程表示火苗物理模型的基础上,利用破开算予法将其分解成外力项、对流项和投影项分别进行求解,每一步都稳定,因而整个求解也就稳定。求解过程的稳定性保证了模拟可以用大时间步长,也就保证了模拟的实时性。与传统的方法相比,能同时满足计算机图形学的真实感和实时性要求。     

3D Hair sketching for real-time dynamic & key frame animations

Physically based simulation of human hair is a well studied and well known problem. But the “pure” physically based representation of hair (and other animation elements) is not the only concern of the animators, who want to “control” the creation and animation phases of the content. This paper describes a sketch-based tool, with which a user can both create hair models with different styling parameters and produce animations of these created hair models using physically and key frame-based techniques. The model creation and animation production tasks are all performed with direct manipulation techniques in real-time.     

具有真实感的三维人脸动画

具有真实感的三维人脸模型的构造和动画是计算机图形学领域中一个重要的研究课题.如何在三维人脸模型上实时地模拟人脸的运动,产生具有真实感的人脸表情和动作,是其中的一个难点.提出一种实时的三维人脸动画方法,该方法将人脸模型划分成若干个运动相对独立的功能区,然后使用提出的基于加权狄里克利自由变形DFFD(Dirichlet free-form deformation)和刚体运动模拟的混合技术模拟功能区的运动.同时,通过交叉的运动控制点模拟功能区之间运动的相互影响.在该方法中,人脸模型的运动通过移动控制点来驱动.为了简化人脸模型的驱动,提出了基于MPEG-4中脸部动画参数FAP(facial animation parameters)流和基于肌肉模型的两种高层驱动方法.这两种方法不但具有较高的真实感,而且具有良好的计算性能,能实时模拟真实人脸的表情和动作.     

基于物理的流体模拟动画综述

基于物理的流体模拟近年来成为计算机动画领域的一个研究热点.回顾了该领域中基于物理的流体模拟的发展情况,总结了该研究方向所采用的各类方法,并结合各种现象的特点分门别类地详细展开.其方法总体上可以分为欧拉法和拉格朗日法,涉及的现象包括烟雾、火焰、爆炸、波浪、气泡以及自由运动界面等.最后展望了未来发展的3个重点：细节策略、加速策略和控制策略,以使整个模拟能够更好地满足人们对真实感、实时性以及灵活性的需求.     

Real-time simulation of large-scale dynamic river water

The real-time modeling and rendering of large-scale dynamic river motion phenomenon is one of the most challenge problems in the research field of simulation, the river water is the most important component in the virtual flood routing process, the simulation should realistically represent its dynamic behavior. This paper embraces a number of techniques covering all the steps of water motion simulation and focuses on the dynamic river surface generation and animation, we describes a combination of modeling methods for flood routing process simulation: FFT-based (Fast Fourier Transform) large-scale water surface modeling and dynamic flood peak generation on water surface using a physically based approach. The real-time rendering techniques for the large-scale 3D scene rendering such as LOD and seamless tiling of LOD patches were discussed in detail, we have adapted them to the rendering of flowing river, new method called template culling for fast clipping were also developed. The methods allow the user to interactively fly over a virtual valley, and there are presented results of implementation of the 3D visualization for river flood routing simulation.     

Stable free surface flows with the lattice Boltzmann method on adaptively coarsened grids

In this paper we will present an algorithm to perform free surface flow simulations with the lattice Boltzmann method on adaptive grids. This reduces the required computational time by more than a factor of three for simulations with large volumes of fluid. To achieve this, the simulation of large fluid regions is performed with coarser grid resolutions. We have developed a set of rules to dynamically adapt the coarse regions to the movement of the free surface, while ensuring the consistency of all grids. Furthermore, the free surface treatment is combined with a Smagorinsky turbulence model and a technique for adaptive time steps to ensure stable simulations. The method is validated by comparing the position of the free surface with an uncoarsened simulation. It yields speedup factors of up to 3.85 for a simulation with a resolution of 480³ cells and three coarser grid levels, and thus enables efficient and stable simulations of free surface flows, e.g. for highly detailed physically based animations of fluids.     

Simulation and interaction of fluid dynamics

In the fluid simulation, the fluids and their surroundings may greatly change properties such as shape and temperature simultaneously, and different surroundings would characterize different interactions, which would change the shape and motion of the fluids in different ways. On the other hand, interactions among fluid mixtures of different kinds would generate more comprehensive behavior. To investigate the interaction behavior in physically based simulation of fluids, it is of importance to build physically correct models to represent the varying interactions between fluids and the environments, as well as interactions among the mixtures. In this paper, we will make a simple review of the interactions, and focus on those most interesting to us, and model them with various physical solutions. In particular, more detail will be given on the simulation of miscible and immiscible binary mixtures. In some of the methods, it is advantageous to be taken with the graphics processing unit (GPU) to achieve real-time computation for middle-scale simulation.     

Research problems in clothing simulation

Clothing simulation and animation are of great importance in computer animation. If cloth simulations could be improved to the point that they could generate realistic cloth motion in real-time, they would find uses in many aspects of daily life such as in fashion design and manufacturing. The area of cloth simulation and animation is full of technical challenges: creating more realistic results, achieving faster run-times, and developing methods capable of constructing and simulating more complex garments. This paper provides an overview of the key procedures involved in the creation of clothed characters, describes the current state-of-the-art techniques, and proposes the research problems that most require further study. Three technical aspects of cloth simulation are considered in this paper: garment construction, physically based simulation, and collision resolution.     

Physically Based Deformable Models in Computer Graphics

Physically based deformable models have been widely embraced by the Computer Graphics community. Many problems outlined in a previous survey by Gibson and Mirtich have been addressed, thereby making these models interesting and useful for both offline and real‐time applications, such as motion pictures and video games. In this paper, we present the most significant contributions of the past decade, which produce such impressive and perceivably realistic animations and simulations: finite element/difference/volume methods, mass‐spring systems, mesh‐free methods, coupled particle systems and reduced deformable models‐based on modal analysis. For completeness, we also make a connection to the simulation of other continua, such as fluids, gases and melting objects. Since time integration is inherent to all simulated phenomena, the general notion of time discretization is treated separately, while specifics are left to the respective models. Finally, we discuss areas of application, such as elastoplastic deformation and fracture, cloth and hair animation, virtual surgery simulation, interactive entertainment and fluid/smoke animation, and also suggest areas for future research.     

Higher-Order Time Integration for Deformable Solids

Visually appealing and vivid simulations of deformable solids represent an important aspect of physically based computer animation. For the temporal discretization, it is customary in computer animation to use first-order accurate integration methods, such as Backward Euler, due to their simplicity and robustness. Although there is notable research on second-order methods, their use is not widespread. Many of these well-known methods have significant drawbacks such as severe numerical damping or scene-dependent time step restrictions to ensure stability. In this paper, we discuss the most relevant requirements on such methods in computer animation and motivate the interest beyond first-order accuracy. Keeping these requirements in mind, we investigate several promising methods from the families of diagonally implicit Runge-Kutta (DIRK) and Rosenbrock methods which currently do not appear to have considerable popularity in this field. We show that the usage of such methods improves the visual quality of physical animations. In addition, we demonstrate that they allow distinctly more control over damping at lower computational cost than classical methods. As part of our theoretical contribution, we review aspects of simulations that are often considered more intricate with higher-order methods, such as contact handling. To this end, we derive an implicit linearized contact model based on a predictor-corrector approach that leads to consistent behavior with higher-order integrators as predictors. Our contact model is well suited for the simulation of stiff, nonlinear materials with the integration methods presented in this paper and more common methods such as Backward Euler alike.     

Stable and Fast Fluid–Solid Coupling for Incompressible SPH

The solid boundary handling has been a research focus in physically based fluid animation. In this paper, we propose a novel stable and fast particle method to couple predictive–corrective incompressible smoothed particle hydrodynamics and geometric lattice shape matching (LSM), which animates the visually realistic interaction of fluids and deformable solids allowing larger time steps or velocity differences. By combining the boundary particles sampled from solids with a momentum‐conserving velocity‐position correction scheme, our approach can alleviate the particle deficiency issues and prevent the penetration artefacts at the fluid–solid interfaces simultaneously. We further simulate the stable deformation and melting of solid objects coupled to smoothed particle hydrodynamics fluids based on a highly extended LSM model. In order to improve the time performance of each time step, we entirely implement the unified particle framework on GPUs using compute unified device architecture. The advantages of our two‐way fluid–solid coupling method in computer animation are demonstrated via several virtual scenarios.     

水流动画模拟方法探讨

目前,对于水流动画模拟的研究已经取得了相当丰富的成果。基于物理模型的流体动画模拟的研究,需要计算流体力学和计算机图形学的交叉融合,根据其研究的背景与内容的不同,可分为两种类型。基于物理模型的流体动画模拟中描述流体运动的方法主要有两种,一种是Euler方法,另一种是Lagrange方法。Euler方法的主要缺点是难以处理流体的细节,Lagrange方法的优点就是能很好地表现流体的细节。由于Euler方法和Lagrange方法的这些特点,如果发展这两种方法的综合方法,则可取长补短。     

Liquid Splash Modeling with Neural Networks

This paper proposes a new data‐driven approach to model detailed splashes for liquid simulations with neural networks. Our model learns to generate small‐scale splash detail for the fluid‐implicit‐particle method using training data acquired from physically parametrized, high resolution simulations. We use neural networks to model the regression of splash formation using a classifier together with a velocity modifier. For the velocity modification, we employ a heteroscedastic model. We evaluate our method for different spatial scales, simulation setups, and solvers. Our simulation results demonstrate that our model significantly improves visual fidelity with a large amount of realistic droplet formation and yields splash detail much more efficiently than finer discretizations.     

Accelerating Liquid Simulation With an Improved Data-Driven Method

In physics-based liquid simulation for graphics applications, pressure projection consumes a significant amount of computational time and is frequently the bottleneck of the computational efficiency. How to rapidly apply the pressure projection and at the same time how to accurately capture the liquid geometry are always among the most popular topics in the current research trend in liquid simulations. In this paper, we incorporate an artificial neural network into the simulation pipeline for handling the tricky projection step for liquid animation. Compared with the previous neural-network-based works for gas flows, this paper advocates new advances in the composition of representative features as well as the loss functions in order to facilitate fluid simulation with free-surface boundary. Specifically, we choose both the velocity and the level-set function as the additional representation of the fluid states, which allows not only the motion but also the boundary position to be considered in the neural network solver. Meanwhile, we use the divergence error in the loss function to further emulate the lifelike behaviours of liquid. With these arrangements, our method could greatly accelerate the pressure projection step in liquid simulation, while maintaining fairly convincing visual results. Additionally, our neutral network performs well when being applied to new scene synthesis even with varied boundaries or scales.     

A deformable surface model for real-time water drop animation

A water drop behaves differently from a large water body because of its strong viscosity and surface tension under the small scale. Surface tension causes the motion of a water drop to be largely determined by its boundary surface. Meanwhile, viscosity makes the interior of a water drop less relevant to its motion, as the smooth velocity field can be well approximated by an interpolation of the velocity on the boundary. Consequently, we propose a fast deformable surface model to realistically animate water drops and their flowing behaviors on solid surfaces. Our system efficiently simulates water drop motions in a Lagrangian fashion, by reducing 3D fluid dynamics over the whole liquid volume to a deformable surface model. In each time step, the model uses an implicit mean curvature flow operator to produce surface tension effects, a contact angle operator to change droplet shapes on solid surfaces, and a set of mesh connectivity updates to handle topological changes and improve mesh quality over time. Our numerical experiments demonstrate a variety of physically plausible water drop phenomena at a real-time rate, including capillary waves when water drops collide, pinch-off of water jets, and droplets flowing over solid materials. The whole system performs orders-of-magnitude faster than existing simulation approaches that generate comparable water drop effects.