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Fast Grid-Based Fluid Dynamics Simulation with Conservation of Momentum and Kinetic Energy on GPU

机译:基于快速的网格流体动力学仿真,通过GPU保护动量和动力量

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Since the computation of fluid animation is often too heavy to run in real-time simulation, we propose a fast grid-based method with parallel acceleration. In order to reduce the cost of computation keeping a balance between fluid stability and diversity, we consider the Navier-Stokes equation on the grid structure with momentum conservation, and introduce the kinetic energy for collision handling and boundary condition. Our algorithm avoids the mass loss during the energy transfer, and can be applied to the two-way coupling with a solid body. Importantly, we propose to use the forward-tracing-based motion and design for parallel computing on Graphics Processing Unit (GPU). In particular, these experiments illustrate the benefits of our method, both in conserving fluid density and momentum. They show that our method is suitable to solve the energy transfer when object interaction is considered during fluid simulation.
机译:由于流体动画的计算往往太重而无法在实时仿真中运行,因此我们提出了一种具有平行加速的基于快速的基于网格的方法。为了降低计算成本,在流体稳定性和多样性之间保持平衡,我们考虑具有动力保护的网格结构上的Navier-Stokes方程,并引入碰撞处理和边界条件的动能。我们的算法避免了能量转移过程中的质量损失,并且可以应用于具有固体体的双向耦合。重要的是,我们建议使用基于前进跟踪的运动和设计进行图形处理单元(GPU)并行计算。特别地,这些实验说明了我们的方法的益处,无论是节省流体密度和动量。他们表明,当在流体仿真期间考虑物体相互作用时,我们的方法适合解决能量传递。

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