• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文学位 >An adaptive sampling approach to incompressible particle-based fluid.
【24h】

An adaptive sampling approach to incompressible particle-based fluid.

机译：不可压缩的基于粒子的流体的自适应采样方法。

获取原文
获取原文并翻译 | 示例
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

I 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, neghboring 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, I 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. In addition, the particle sampling technique is extended to a fully adaptive approach, supporting adaptive splitting and merging of fluid particles and adaptive spatial sampling for the reconstruction of the velocity and pressure fields. Particle splitting allows a detailed sampling of fluid momentum in regions of complex flow. Particle merging, in regions of smooth flow, reduces memory and computational overhead. An octree structure is used to compute inter-particle interactions and to compute the pressure field. The octree supporting field-based calculations is adapted to provide a fine spatial reconstruction where particles are small and a coarse reconstruction where particles are large. This scheme places computational resources where they are most needed, to handle both flow and surface complexity. Thus, incompressibility can be enforced even in very small, but highly turbulent areas. Simultaneously, the level of detail is very high in these areas, allowing the direct support of tiny splashes and small-scale surface tension effects. This produces a finely detailed and realistic representation of surface motion.
机译：我提出了一种基于粒子的模拟不可压缩流体的技术，其中包括对粒子采样的自适应改进。每个粒子代表其局部区域中的大量流体。颗粒被分成几个颗粒，以便在复杂流动的区域中进行更精细的采样。在平稳流动的区域，可以合并附近的粒子。表面以下的深度和雷诺数被用作我们确定是否应该进行分裂或合并的标准。对于流体动力学计算，我使用混合FLIP方法，该方法计算简单且有效。由于流体不可压缩，因此每个粒子的体积均与其质量成比例。有效范围基于此体积的核函数用于传递和更新粒子的物理特性（例如质量和速度）。此外，粒子采样技术已扩展到完全自适应的方法，支持流体粒子的自适应拆分和合并以及用于重建速度和压力场的自适应空间采样。颗粒分裂允许对复杂流动区域中的流体动量进行详细采样。在平滑流动区域中的粒子合并减少了内存和计算开销。八叉树结构用于计算粒子间的相互作用并计算压力场。基于八叉树的基于场的计算适用于在粒子较小的情况下提供精细的空间重建，在粒子较大的情况下提供粗略的重建。该方案将计算资源放在最需要的地方，以处理流量和表面复杂性。因此，即使在很小但高度动荡的区域中也可以增强不可压缩性。同时，这些区域的细节水平很高，可以直接支持微小的飞溅和小范围的表面张力效应。这样可以产生精细而逼真的表面运动表示。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号