高级检索

  • ISSN 1006-3080
  • CN 31-1691/TQ

工业聚乙烯流化床的气固流动特性数值模拟

刘信瑀 张海涛 马宏方 李涛

刘信瑀, 张海涛, 马宏方, 李涛. 工业聚乙烯流化床的气固流动特性数值模拟[J]. 华东理工大学学报(自然科学版). doi: 10.14135/j.cnki.1006-3080.20210731001
引用本文: 刘信瑀, 张海涛, 马宏方, 李涛. 工业聚乙烯流化床的气固流动特性数值模拟[J]. 华东理工大学学报(自然科学版). doi: 10.14135/j.cnki.1006-3080.20210731001
LIU Xinyu, ZHANG Haitao, MA Hongfang, LI Tao. Numerical simulation of gas-solid flow in industrial polyethylene fluidized bed[J]. Journal of East China University of Science and Technology. doi: 10.14135/j.cnki.1006-3080.20210731001
Citation: LIU Xinyu, ZHANG Haitao, MA Hongfang, LI Tao. Numerical simulation of gas-solid flow in industrial polyethylene fluidized bed[J]. Journal of East China University of Science and Technology. doi: 10.14135/j.cnki.1006-3080.20210731001

工业聚乙烯流化床的气固流动特性数值模拟

doi: 10.14135/j.cnki.1006-3080.20210731001
详细信息
    作者简介:

    刘信瑀(1998—),男,浙江台州人,硕士生,主要研究方向:多相流模拟。E-mail:798588739@qq.com

    通讯作者:

    李 涛, E-mail:tli@ecust.edu.cn

  • 中图分类号: TQ021.1

Numerical simulation of gas-solid flow in industrial polyethylene fluidized bed

  • 摘要: 采用计算颗粒流体力学(CPFD)的数值模拟方法,对工业级聚乙烯流化床内的气固流动特性进行了冷态模拟,并利用Matlab的图像处理功能将图像的像素点与模拟的网格对应来计算流化床内的气泡大小。从 流化床流动结构 、颗粒、气泡三个角度,研究了不同气速、不同初始物料量对工业级聚乙烯流化床的气固流动特性的影响。结果表明:不同于中试和实验阶段设备,工业流化床内部的边壁效应明显较弱,密相区整体呈现较为均匀的颗粒分布。气速对于流化床气固流动的影响较大,当气速=0.46 m/s时,流化床内密相区的颗粒分布最为均匀,整体的流动较好。初始床层高度主要影响流化后密相区的高度,对于床层膨胀率的影响较小。

     

  • 图  1  流化床几何结构

    Figure  1.  Geometry of a fluidized bed

    图  2  流化床的网格划分

    Figure  2.  Meshing of fluidized bed

    图  3  不同网格尺度的轴向固含率分布情况

    Figure  3.  Distribution of axial solid holdup at different grid scales

    图  4  图像数字化

    Figure  4.  Image digitization

    图  5  针对气泡的Matlab图像处理过程

    Figure  5.  Process of Matlab image processing for bubbles

    图  6  流化床内部颗粒随时间分布情况

    Figure  6.  Process of Matlab image processing for bubbles

    图  7  各气速下流化床内的流线图

    Figure  7.  Flow diagram in fluidized bed at various gas velocities

    图  8  气速对聚乙烯颗粒轴向分布的影响

    Figure  8.  Effect of gas velocity on polyethylene particle axial distribution

    图  9  气速对聚乙烯颗粒径向分布的影响

    Figure  9.  Effect of gas velocity on polyethylene particle radial distribution

    图  10  气速对气泡平均直径轴向分布的影响

    Figure  10.  Effect of gas velocity on axial distribution of average diameter of bubbles

    图  11  初始床层高度对轴向固含率的影响

    Figure  11.  Effect of initial bed height on axial solid holdup

    表  1  气相和聚乙烯颗粒的组成

    Table  1.   1 Composition of gas phase and polyethylene particles

    Gas compsitonMole fractionParticle size
    distribution/mesh
    Mass fraction,%Average diameter,μmTotal mean particle
    diameter/μm
    H20.0652040.2831580
    C2H40.3520~4031.5600
    1-C4H8200.1440~6012.3322
    N240.20.44560~1006.5190
    100~1403.8120
    140~2001.889
    下载: 导出CSV

    表  2  模拟参数及计算条件

    Table  2.   2 Simulation parameters and calculation conditions

    Operating temperature/KOperating pressure/MPaMean particle diameter/μmGrain density/(kg·m−3)Maximum allowable volume fraction of particlesInitial apparent density of bed particles/(kg·m−3)Initial bed height/mNormal recovery coefficient of particle-wall collision
    3612.35809200.648080.9
    Gas density/
    (kg·m−3)
    Gas viscosity/
    (pa·s)
    Gas velocity/
    (m·s−3)
    Drag force
    model
    Turbulence
    model
    Time step/sTime average calculation start time/sSimulated time/s
    221.527×10−50.46GidaspowLES0.0012040
    下载: 导出CSV

    表  3  不同初始床层高度的膨胀率

    Table  3.   3 Expansion rates at different initial bed heights

    Initial bed height/mHeight of dense zone/mBed expansion rate
    4 6.5391.635
    610.4121.735
    813.86 1.733
    下载: 导出CSV
  • [1] MULHAUPT R. Catalytic polymerization and post polymerization catalysis fifty years after the discovery of Ziegler's catalysts[J]. Macromolecular Chemistry and Physics, 2003, 204(2): 289-327. doi: 10.1002/macp.200290085
    [2] SCHNEIDERBAUER S, PUTTINGER S, PIRKER S, et al. CFD modeling and simulation of industrial scale olefin polymerization fluidized bed reactors[J]. Chemical Engineering Journal, 2015, 264(2015): 99-112.
    [3] 李延頔, 何雪莲, 黄宇, 等. 单链聚乙烯在石墨烯二维表面结晶的分子模拟[J]. 华东理工大学学报(自然科学版), 2016, 42(5): 594-600.
    [4] SOARES J B P, MCKENNA T F. Polyolefin Reaction Engineering[J]. Focus on Catalysts, 2013, 2012(11): 8.
    [5] 车煜. 基于计算流体力学气相法聚乙烯流化床反应器的多尺度模型化研究[D]. 上海: 华东理工大学, 2016.
    [6] NING Y, TAO J, LI Z. Progress of gas-phase polyethylene technique and catalyst[J]. Petrochemical Technology & Application, 2008, 26(05): 480-485.
    [7] 郭宜祜, 王喜忠. 流化床基本原理及其工业应用[M]. 北京: 化学工业出版社, 1980.
    [8] CHE Y, TIAN Z, LIU Z, et al. CFD prediction of scale-up effect on the hydrodynamic behaviors of a pilot-plant fluidized bed reactor and preliminary exploration of its application for non-pelletizing polyethylene process[J]. Powder Technology, 2015, 278: 94-110. doi: 10.1016/j.powtec.2015.02.022
    [9] UPENDER H, KISHORE K A. Effect of materials on hydrodynamics of cone-shaped inverse fluidized bed by experimental and CFD simulations[J]. Materials Today:Proceedings, 2020, 21(3): 1502-1512.
    [10] KARIMI S, MANSOURPOUR Z, MOSTOUFI N, et al. CFD-DEM Study of Temperature and Concentration Distribution in a Polyethylene Fluidized Bed Reactor[J]. Part. Sci. Technol, 2011, 29(2): 163-178. doi: 10.1080/02726351003758451
    [11] DEEN N G, ANNALAND M V, HPEF M A V D, et al. Review of discrete particle modeling of fluidized beds[J]. Chemical Engineering Science, 2007, 62(1-2): 28-44. doi: 10.1016/j.ces.2006.08.014
    [12] 曾佳, 黄婷, 刘斌斌, 等. 基于计算流体力学的中药流化床制粒工艺数值模拟与实验验证[J]. 中国新药杂志, 2021, 30(01): 62-72.
    [13] 马华庆, 赵永志. 喷动流化床中杆状颗粒混合特性的CFD-DEM模拟[J]. 浙江大学学报(工学版), 2020, 54(7): 1347-1354.
    [14] 任安星, 唐天琪, 王天宇, 等. 脉动流化床内球柱形颗粒流动行为研究[J]. 工程热物理学报, 2021, 42(3): 651-656.
    [15] ANDREWS M. J, O'ROURKE P J. The multiphase particle-in-cell (MP-PIC) method for dense particulate flows[J]. International Journal of Multiphase Flow, 1996, 22(2): 379-402. doi: 10.1016/0301-9322(95)00072-0
    [16] 王坤, 朱丽云, 李安俊, 等. 湍动流化床颗粒流动特性的数值模拟[J]. 石油化工设备技术, 2021, 42(1): 5-10. doi: 10.3969/j.issn.1006-8805.2021.01.002
    [17] 张贤, 葛荣存, 张守玉, 等. CFB密相区大颗粒横向扩散系数的CPFD模拟[J]. 化工学报, 2017, 68(10): 3725-3732.
    [18] 任喜熙, 陈祁, 杨海平, 等. 基于CPFD方法的流化床生物质气化数值模拟[J]. 化工学报, 2020, 71(12): 5763-5773.
    [19] ROKKAM R G, FOX R O, MUHLE M E. Computational fluid dynamics and electrostatic modeling of polymerization fluidized-bed reactors[J]. Powder Technology, 2010, 203(2): 109-124. doi: 10.1016/j.powtec.2010.04.002
    [20] VERMA V, PADDING J T, DEEN N G, et al. Effect of bed size on hydrodynamics in 3-D gas-solid fluidized beds[J]. Aiche Journal, 2015, 61(5): 1492-1506. doi: 10.1002/aic.14738
    [21] GOBIN A, NEAU H, SIMONIN O, et al. Fluid dynamic numerical simulation of a gas phase polymerization reactor[J]. International Journal for Numerical Methods in Fluids, 2003, 43(10‐11): 1199-1220.
    [22] GIDASPOW D. Multiphase flow and fluidization: Continuum and kinetic theory description[J]. Journal of Non-Newtonian Fluid Mechanics, 1994, 55(2): 207-208. doi: 10.1016/0377-0257(94)80007-3
    [23] 陈巨辉, 王帅, 于广滨. 流化床技术模拟方法研究[M]. 北京: 科学出版社, 2016.
    [24] 韩颖. 基于计算流体力学的烯烃聚合反应器模型化与模拟研究[D]. 浙江: 浙江大学, 2013.
    [25] DEHNAVI M A, SHAHHOSSEINI S, HASHEMABADi S H, et al. CFD simulation of hydrodynamics and heat transfer in gas phase ethylene polymerization reactors[J]. Int. Commun. Heat Mass Transfer, 2010, 37(4): 437-442. doi: 10.1016/j.icheatmasstransfer.2009.12.005
    [26] 兰斌, 徐骥, 刘志成, 等. 连续操作密相流化床颗粒停留时间分布特性模拟放大研究[J]. 化工学报, 2021, 72(01): 521-533.
    [27] 王铁峰, 王金福, 杨卫国, 等. 三相循环流化床中气泡大小及其分布的实验研究[J]. 化工学报, 2001, 52(3): 197-203. doi: 10.3321/j.issn:0438-1157.2001.03.004
    [28] SHAFFER F, GOPALAN B, BREAULT R W, et al. High speed imaging of particle flow fields in CFB risers[J]. Powder Technol, 2013, 242: 86-99. doi: 10.1016/j.powtec.2013.01.012
    [29] 陆时杰, 陈彩霞, 夏梓洪, 等. 多晶硅流化床反应器内气固两相流场与气泡尺寸分布的TFM-KTGF模拟[J]. 华东理工大学学报(自然科学版), 2015, 41: 758-764. doi: 10.3969/j.issn.1006-3080.2015.06.005
    [30] YAN H, JIANG P, CHEN B. Digital image processing technique based on MATLAB toolbox[J]. Microcomputer Information, 2010, 26: 214-216.
    [31] BAI D, SHIBUYA E, MASUDA Y, et al. Flow structure in a fast fluidized bed[J]. Chemical Engineering Science, 1996, 51(6): 957-966. doi: 10.1016/0009-2509(95)00331-2
    [32] ZHAO J, LV Y, ZHOU Z, et al. A novel deep learning algorithm for incomplete face recognition: Low-rank-recovery network[J]. Neural Networks, 2017, 94: 115-124. doi: 10.1016/j.neunet.2017.06.013
    [33] 秦霁光. 聚式流化床的膨胀[J]. 化学工程, 1979(5): 70-73.
  • 加载中
图(11) / 表(3)
计量
  • 文章访问数:  30
  • HTML全文浏览量:  17
  • PDF下载量:  12
  • 被引次数: 0
出版历程
  • 收稿日期:  2021-07-31
  • 网络出版日期:  2021-11-09

目录

    /

    返回文章
    返回