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arXiv 1303.2653physics.flu-dynphysics.comp-ph
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基于格子Boltzmann的气固流态化离散模拟

Lattice Boltzmann based discrete simulation for gas-solid fluidization

Limin Wang, Bo Zhang, Xiaowei Wang, Wei Ge, Jinghai Li

摘要:

离散粒子模拟是计算流体动力学与离散方法如离散元法(DEM)、直接模拟蒙特卡罗(DSMC)、光滑粒子流体动力学(SPH)、粒子模拟(PIC)等相结合的方法,随着并行计算技术的发展,气固两相流的数值模拟正逐渐成为研究实验室规模气固体系的一种实用工具。然而,气固耦合和相应的流体流动求解器仍然不成熟。在这项工作中,我们提出了一个修改的格子Boltzmann方法来考虑局部固体体积分数和颗粒与流体之间的局部相对速度的影响,这是不同于传统的体积平均的纳维-斯托克斯方程。结合时间驱动的硬球算法来模拟单个粒子的运动,粒子之间通过硬球碰撞相互作用,碰撞检测和粒子的运动以固定的时间间隔进行。将EMMS(能量最小化多尺度)阻力与基于格子Boltzmann的离散粒子模拟相结合,以提高计算精度。用该方法模拟了两种典型的流化过程,即初始流化时的单气泡喷射和快速流化床提升管中的颗粒聚团,模拟结果与已发表的关联式和实验数据吻合较好。该方法的能力,以捕捉更详细的和内在的特性的颗粒流体系统的证明。该方法也可以直接用于其他固相求解器。

英文摘要:

Discrete particle simulation, a combined approach of computational fluid dynamics and discrete methods such as DEM (Discrete Element Method), DSMC (Direct Simulation Monte Carlo), SPH (Smoothed Particle Hydrodynamics), PIC (Particle-In-Cell), etc., is becoming a practical tool for exploring lab-scale gas-solid systems owing to the fast development of parallel computation. However, gas-solid coupling and the corresponding fluid flow solver remain immature. In this work, we propose a modified lattice Boltzmann approach to consider the effect of both the local solid volume fraction and the local relative velocity between particles and fluid, which is different from the traditional volume-averaged Navier-Stokes equations. A time-driven hard sphere algorithm is combined to simulate the motion of individual particles, in which particles interact with each other via hard-sphere collisions, the collision detection and motion of particles are performed at constant time intervals. The EMMS (energy minimization multi-scale) drag is coupled with the lattice Boltzmann based discrete particle simulation to improve the accuracy. Two typical fluidization processes, namely, a single bubble injection at incipient fluidization and particle clustering in a fast fluidized bed riser, are simulated with this approach, with the results showing a good agreement with published correlations and experimental data. The capability of the approach to capture more detailed and intrinsic characteristics of particle-fluid systems is demonstrated. The method can also be used straightforward with other solid phase solvers.

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