基于LBM的自由表面流体真实感绘制

针对自由表面流体的模拟,提出一种基于Lattice Boltzmann(LBM)的高效建模和绘制的方法.首先基于浅水方程的LBM模型进行流体建模及表面高度场计算,并提出一种基于Marching Cubes和自由表面算法结合的方法来抽取流体的表面,随后采用考虑移动障碍物的外力叠加机制和自适应加密算法来进行流体交互及表面的网格重构.最后采用硬件加速技术实现了不同自由表面流体的绘制,如溪流、水池浅水流、洪水水淹等真实感效果.     

基于Double Marching Cubes的表面重建算法

为克服基于Marching Cubes的表面重建算法在绘制三维表面时因二义性面的存在而使生成的表面网格易出现错误连接而形成层间空洞的不足,提出了基于Double Marching Cubes的表面重建算法.该算法采用双立方体体素作为生成表面网格的基本单元,以双立方体的12个特征点的标记情况为依据,建立一个双立方体体素索引表,通过查找索引表的方法绘制三维表面.该算法在建立双立方体索引表时就排除掉了二义性面的所有错误连接方式,因而生成的表面网格不会出现层间空洞,避免了为消除二义性面所进行的复杂计算,加快了表面重建的速度.     

基于CUDA的弱可压SPH流体建模与仿真

为了实现小尺度范围流体场景的实时、真实感模拟,采用弱可压SPH方法对水体进行建模,提出了流体计算的CPU GPU混合架构计算方法。针对邻域粒子查找算法影响流体计算效率的问题,采用三维空间网格对整个模拟区域进行均匀网格划分,利用并行前缀求和和并行计数排序实现邻域粒子的查找。最后,采用基于CUDA并行加速的Marching Cubes算法实现流体表面提取,利用环境贴图表现流体的反射和折射效果,实现流体表面着色。实验结果表明,所提出的流体建模和模拟算法能实现小尺度范围流体的实时计算和渲染,绘制出水的波动、翻卷和木块在水中晃动的动态效果,当粒子数达到1 048 576个时,GPU并行计算方法相较CPU方法的加速比为60.7。     

一种基于半拉格朗日的液体实时仿真方法

近些年,在计算机图形学与虚拟现实技术领域中,自然现象的模拟得到了广泛的关注和研究.如何快速且逼真地模拟自然现象,是此类研究的目的.以液体表面作为研究对象,总结了关于液体模拟近年来的部分研究成果;针对三维液体的复杂流体状态,提出了一种基于半拉格朗日的液体实时仿真方法,并对仿真结果进行了表面构建.该方法首先将Navier-Stokes 方程离散化,并通过求解构造的Poisson 方程得到每一时间步长的数值解,进而精确驱动粒子运动以构建真实液体表面;之后,利用液体表面追踪及Marching Cubes 表面重建,生成了真实的液体表面模型.实验结果表明,该仿真方法不但在运算过程中遵循经典的流体力学方程,从而保证了结果的真实性,并且运算速度快且能取得较好的视觉效果.在计算机游戏、电影制作以及医学等领域的仿真,均有广泛的应用前景.     

基于图像分割的三维重构

三维重构方法是医学图像可视化系统、治疗计划系统的重要技术。基于图像分割的三维重构方法结合了图像分割、等值面抽取、网格简化三种技术,是不同于传统Marching Cubes算法的一种三维重构方法。它首先将医学图像分割为二值图,然后利用Marching Cubes方法进行等值面抽取,最后对得到的网格模型进行简化。实验结果表明,基于图像分割的三维重构方法加快了Marching Cubes的运算速度,改善了重构的效果,有利于实现对基于三维重构的大型几何模型的实时绘制和交互。     

一种面向三维点集的快速表面重构算法

在对目前比较流行的空间三角化算法进行对比研究的基础上 ,对 Hugues Hoppe提出的算法进行了改进 ,即借鉴 Marching Cubes算法的基本思想 ,首先通过自动选取适当的参数 ,用包围盒方法将三维散乱点划分为数据区域 ;然后求取点的切平面及法向 ,同时采用广度优先算法遍历数据点来调整法向和快速地求取 Marching Cubes的等势函数 ;最后用基于查表法的 Marching Cubes来输出三角面片 ,即得到表面模型 .实验结果表明 ,改进后的算法效率有较大的提高 .新算法不仅适用于表面三维散乱点数据 ,也可以对体数据进行重构 ,具有一定的通用性 .     

剖面数据场中的三维表面建模

在三维表面建模技术中,Marching Cubes算法是应用最为广泛的方法之一。该算法简单高效,但与此同时,研究人员也发现它存在一些不足。在构造等值面时,Marching Cubes算法要把所有体素全部检测一遍,即使有些体素没有和等值面相交,这影响了算法效率;此外在这个过程中,Marching Cubes算法还会忽略掉一些本来在等值面上的点,降低了表面重建的精度。针对这些问题,本文对算法进行了改进。在构造等值面时,不检测空的体素以提高算法的速度,并且把一些被忽略的等值点添加进来以提高算法的精度。     

基于气象雷达回波3D重建的Marching Cubes改进算法

根据气象雷达回波数据的三维极坐标分布特点,提出一种改进的Marching Cubes三维重建算法.该算法将Marching Cubes常规算法中的单位正立方体构建转换为直接对回波极坐标数据的拟柱体构建,生成相应的等值三角面,并对三角面的顶点数据进行地曲订正,供OpenGL显示.为进一步提高重建算法的效率,该算法避免了对高仰角远距离无回波区的重建.实验表明,该算法有效实现了雷达回波的三维重建.     

MC算法与MT算法的比较

三维医学图像表面重建算法是近来的一个研究热点,目前已有多种算法,其中最具代表性的是Marching Cubes(MC)算法和Marching Tetrahedra(MT)算法.本文对这两种算法的实现原理进行了分析比较,给出了实现这两种算法的数据结构,分析了两者的实现过程,并针对具体的实验结果比较了两者的优劣.     

一种由轮廓线重建物体表面的方法

针对基于轮廓线拼接重建物体表面所出现的轮廓对应和分叉问题,提出了一种通过体数据转换由轮廓线实现重建物体表面的方法。在分析体数据构造中出现逼近精度问题的前提下,通过提高轮廓线上点的密度,生成精确度较高的体数据。该方法通过对相邻层轮廓线区域的集合运算,只对处于集合运算解中的像素点进行距离函数值的计算。采用MC（Marching Cubes）算法生成等值面,完成物体的表面重建。实验结果表明,该方法能顺利解决基于轮廓线拼接重建物体表面中出现的轮廓对应问题和分叉问题,既提高重建表面精确度,又加快整个表面的重建速度,是一种可行的方法。     

GPU通用计算平台上的SPH流体模拟

针对流体模拟需要大量计算资源从而很难达到实时模拟的问题,提出一种完全在GPU上实现的基于平滑粒子流体动力学的流体模拟方法.首先通过在GPU上构造基于哈希函数的空间均匀网格来实现任意大小场景的快速邻近粒子查找,并在GPU上并行求解SPH流体方程来实现流体模拟;渲染流体时,通过在顶点着色器中进行纹理采样,利用粒子坐标缓存数据直接更新流体粒子系统的顶点缓存,从而避免了CPU—GPU之间的数据传输,充分利用了GPU的并行性.实验对比表明,与纯CPU实现以及CPU和GPU混合实现的模拟结果相比,采用该方法能显著地减少单个时间片的计算时间,大幅度提高流体模拟和渲染的整体性能.     

Adaptive particles for incompressible fluid simulation

We propose a particle-based technique for simulating incompressible fluid that includes adaptive refinement of particle sampling. Each particle represents a mass of fluid in its local region. Particles are split into several particles for finer sampling in regions of complex flow. In regions of smooth flow, neighboring particles can be merged. Depth below the surface and Reynolds number are exploited as our criteria for determining whether splitting or merging should take place. For the fluid dynamics calculations, we use the hybrid FLIP method, which is computationally simple and efficient. Since the fluid is incompressible, each particle has a volume proportional to its mass. A kernel function, whose effective range is based on this volume, is used for transferring and updating the particle’s physical properties such as mass and velocity. Our adaptive particle-based simulation is demonstrated in several scenarios that show its effectiveness in capturing fine detail of the flow, where needed, while efficiently sampling regions where less detail is required.     

Solving the Shallow Water equations using 2D SPH particles for interactive applications

In this paper, we introduce a 2D particle-based approach to achieve realistic water surface behaviors for interactive applications. We formulate 2D particle-based Shallow Water equations using the Smoothed Particle Hydrodynamics. Particles defined with specific amount of water volume interplay with each other, which generates the horizon flow and the water surface motion. By the application of the particle-based Lagrangian framework to the 2D Shallow Water simulation, our method allows the water particles to move freely without being confined to a grid. The motion of the particles can represent global flow with dynamic waves covering a large area while avoiding extensive 3D fluid dynamics computation. The 2D particle-based Shallow Water equations are straightforward and computed fast with the GPU-based implementation. Experiments on a standard hardware demonstrate the performance of our approach which is running on the GPU, and the results show a realistic motion of the water surface at interactive rates.     

GPU-based rendering of point-sampled water surfaces

Particle-based simulations are widely used to simulate fluids. We present a real-time rendering method for the results of particle-based simulations of water. Traditional approaches to visualize the results of particle-based simulations construct water surfaces that are usually represented by polygons. To construct water surfaces from the results of particle-based simulations, a density function is assigned to each particle and a density field is computed by accumulating the values of the density functions of all particles. However, the computation of the density field is time consuming. To address this problem, we propose an efficient calculation of density field using a graphics processing unit (GPU). We present a rendering method for water surfaces sampled by points. The use of the GPU permits efficient simulation of optical effects, such as refraction, reflection, and caustics.     

Monolithic Friction and Contact Handling for Rigid Bodies and Fluids Using SPH

We propose a novel monolithic pure SPH formulation to simulate fluids strongly coupled with rigid bodies. This includes fluid incompressibility, fluid–rigid interface handling and rigid–rigid contact handling with a viable implicit particle-based dry friction formulation. The resulting global system is solved using a new accelerated solver implementation that outperforms existing fluid and coupled rigid–fluid simulation approaches. We compare results of our simulation method to analytical solutions, show performance evaluations of our solver and present a variety of new and challenging simulation scenarios.     

基于透视网格的自适应窄带表面粒子提取方法

为了提升基于粒子的流体表面重建效率,提出了一种基于透视网格的自适应窄带表面粒子提取方法。与基于物体空间的方法相比,该方案根据粒子密度、离散系数等信息自适应提取视锥范围内最靠近视点的表面粒子,使表面粒子数、内存消耗仅与可见的表面区域相关,而不是整个流体表面或模拟域。此外,利用透视网格沿视线排布的优势,提出了基于粒子密度的自适应厚度估计方法。实验结果表明,该方案有效减少了40%～76%的表面粒子和30%～50%的内存开销,解决了表面粒子冗余和空洞问题,并以较低的代价获取了厚度信息。该方案为后续的表面重建和渲染带来了明显的性能提升,可以更好地处理大规模粒子集的重建和渲染。     

Direct raytracing of a closed-form fluid meniscus

We present a direct raytracing method for implicitly described fluid surfaces that takes into account the effects of capillary solid coupling at the boundaries. The method is independent of the underlying fluid simulation method and solely based on distance fields. We make use of the closed-form solution of the meniscus shape at the fluid interface to achieve the effect of surface tension exerted by the solid object. The shape of the liquid at these boundaries is influenced by various physical properties such as the force of gravity and the affinity between the liquid and the solid material. We generate contact angles at the boundaries without the need for computationally intensive small-scale simulation. At render time, we combine the closed-form solution for a small-scale effect with the numerical solution of a large-scale simulation. Our method is applicable for any implicit representation of the fluid surface and does not require an explicit extraction of the surface geometry. Therefore, it is especially useful for particle-based simulations. Furthermore, the solution is guaranteed to yield the correct contact angle and, for certain scenarios, it delivers the entirely correct solution throughout the interface; even in general scenarios, it yields plausible results. As for an example, we implemented and tested the proposed method in the setting of a smoothed particle hydrodynamics (SPH) fluid simulation.     

Volume preserving viscoelastic fluids with large deformations using position-based velocity corrections

We propose a particle-based hybrid method for simulating volume preserving viscoelastic fluids with large deformations. Our method combines smoothed particle hydrodynamics (SPH) and position-based dynamics (PBD) to approximate the dynamics of viscoelastic fluids. While preserving their volumes using SPH, we exploit an idea of PBD and correct particle velocities for viscoelastic effects not to negatively affect volume preservation of materials. To correct particle velocities and simulate viscoelastic fluids, we use connections between particles which are adaptively generated and deleted based on the positional relations of the particles. Additionally, we weaken the effect of velocity corrections to address plastic deformations of materials. For one-way and two-way fluid-solid coupling, we incorporate solid boundary particles into our algorithm. Several examples demonstrate that our hybrid method can sufficiently preserve fluid volumes and robustly and plausibly generate a variety of viscoelastic behaviors, such as splitting and merging, large deformations, and Barus effect.     

基于多重网格法的实时流体模拟

在GPU上实现了多重网格法,并用该方法改进了二维的实时流体模拟,更充分地利用GPU的并行计算能力.使用4层网格,依靠渲染到纹理的计算方式、帧缓存扩展的纹理管理方法,提高了图形硬件的利用率.实验对比表明,在同样的帧数下该方法能提高GPU实时流体模拟的精度.尤其在较大规模的问题上,与同等精度的基于一般迭代方法的GPU实时流体模拟相比,该方法在速度上可有成倍地提高.     

基于CPU-GPU混合加速的SPH流体仿真方法

基于光滑粒子流体力学SPH的流体仿真是虚拟现实技术的重要研究内容,但SPH流体仿真需要大量的计算资源,采用一般计算方法难以实现流体仿真的实时性。流体仿真通常由物理计算、碰撞检测和渲染等部分组成,借助GPU并行加速粒子的物理属性计算和碰撞过程使SPH方法的实时流体仿真成为可能。为了满足流体仿真应用中的真实性和实时性需求,提出一种基于CPU GPU混合加速的SPH流体仿真方法,流体计算部分采用GPU并行加速,流体渲染部分采用基于CPU的OpenMP加速。实验结果表明,基于CPU GPU混合加速的SPH流体仿真方法与CPU实现相比,能显著地减少流体仿真单帧计算时间且能更快速地完成渲染任务。