基于Euler-Lagrange方法的细粒煤脉动气流分选数值模拟

传统的欧拉模型和离散相模型难以准确模拟细粒煤气流分选过程,为此采用DDPM(Dense Discrete Phase Model)模型,引入相体积分数和软球碰撞模型,提出了一种基于离散相体积分数和颗粒间碰撞作用的新的细粒煤气流分选过程数值模拟方法。通过数值模拟与实验室连续分选实验,研究了分选机内流场分布和6~3 mm细粒煤脉动气流分选效果。结果表明:采用DDPM模型可有效模拟细粒煤气流分选过程中颗粒相对流场的扰动作用;分选柱内流场受被分选物料的影响,速度分布和压降值较加入颗粒前变化明显,且分选机处理量越高,压降变化越明显;实验条件范围内,DDPM模型模拟得到的各密度级重产物分配率均方根误差低于3%,且相同风量时,分选机处理量越大,分选密度越高。

Numerical studies of pulsing airflow separation of fine coal based on Euler-Lagrange method

It is difficult to simulate the pulsing airflow separation process of fine coal accurately using the conventional numerical model，such as Eulerian Model and Discrete Phase Model.The Dense Discrete Phase Model (DDPM) of the pulsing airflow separation process of fine coal was proposed based on the volume fraction of discrete phase and Soft sphere approach to account for the influence from the volume of particles and the forces that result from the collision of particles.The distribution of the flow field and the separation results of 6-3 mm coal particles in pulsing air classifier were simulated through numerical simulation and continuous separation experiments in laboratory.The results show that DDPM was suitable for the simulation of the pulsing airflow separation process of fine coal and it was effective to show the perturbation action on the distribution of the flow field from particle phases.The separated materials had a significant impact on the distribution of the flow field，particularly on the velocity distribution and the change of pressure drop.Moreover，the greater handling capacity of the pulsing air classifier，the more significantly change of pressure drop.Within the scope of experiment conditions，the root mean square error of partition coefficients of heavy product in different density fractions was less than 3% by the method of DDPM，and the greater handling capacity，the higher separation density when the blowing rate was constant.