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Computational Fluid Dynamics Simulation of Gas–Solid Hydrodynamics in a Bubbling Fluidized-Bed Reactor: Effects of Air Distributor, Viscous and Drag Models

机译:鼓泡流化床反应器中气固流体动力学的计算流体动力学模拟:空气分布器,粘性和阻力模型的影响

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In this work, we employed a computational fluid dynamics (CFD)-based model with a Eulerian multiphase approach to simulate the fluidization hydrodynamics in biomass gasification processes. Air was used as the gasifying/fluidizing agent and entered the gasifier at the bottom which subsequently fluidized the solid particles inside the reactor column. The momentum exchange related to the gas-phase was simulated by considering various viscous models (i.e., laminar and turbulence models of the re-normalisation group (RNG), k-ε and k-ω). The pressure drop gradient obtained by employing each viscous model was plotted for different superficial velocities and compared with the experimental data for validation. The turbulent model of RNG k-? was found to best represent the actual process. We also studied the effect of air distributor plates with different pore diameters (2, 3 and 5 mm) on the momentum of the fluidizing fluid. The plate with 3-mm pores showed larger turbulent viscosities above the surface. The effects of drag models (Syamlal–O’Brien, Gidaspow and energy minimum multi-scale method (EMMS) on the bed’s pressure drop as well as on the volume fractions of the solid particles were investigated. The Syamlal–O’Brien model was found to forecast bed pressure drops most consistently, with the pressure drops recorded throughout the experimental process. The formation of bubbles and their motion along the gasifier height in the presence of the turbulent flow was seen to follow a different pattern from with the laminar flow.
机译:在这项工作中,我们采用了基于计算流体动力学(CFD)的模型,并采用欧拉多相方法来模拟生物质气化过程中的流化流体动力学。空气用作气化/流化剂,并在底部进入气化炉,随后使反应器塔内的固体颗粒流化。通过考虑各种粘性模型(即重新归一化组(RNG),k-ε和k-ω的层流和湍流模型)模拟与气相有关的动量交换。通过绘制每个粘性模型获得的压降梯度来绘制不同的表观速度,并与实验数据进行比较以进行验证。 RNG k-?的湍流模型被发现最能代表实际过程。我们还研究了不同孔径(2、3和5 mm)的空气分配器板对流化流体动量的影响。具有3mm孔的板在表面上方显示出较大的湍流粘度。研究了阻力模型(Syamlal-O'Brien模型,Gidaspow和最小能量最小尺度方法(EMMS))对床压降以及固体颗粒体积分数的影响。研究发现,在整个实验过程中记录的压降可以最一致地预测床压下降,在湍流存在的情况下,气泡的形成及其沿气化炉高度的运动与层流遵循的模式不同。

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