搜索

x

留言板

尊敬的读者、作者、审稿人, 关于本刊的投稿、审稿、编辑和出版的任何问题, 您可以本页添加留言。我们将尽快给您答复。谢谢您的支持!

姓名
邮箱
手机号码
标题
留言内容
验证码

eXtended Pom-Pom黏弹性流体的改进光滑粒子动力学模拟

许晓阳 周亚丽 余鹏

引用本文:
Citation:

eXtended Pom-Pom黏弹性流体的改进光滑粒子动力学模拟

许晓阳, 周亚丽, 余鹏

Improved smoothed particle dynamics simulation of eXtended Pom-Pom viscoelastic fluid

Xu Xiao-Yang, Zhou Ya-Li, Yu Peng
PDF
HTML
导出引用
  • 黏弹性流体广泛存在于自然界和工业生产中, 对其复杂流变特性的研究具有重要的学术价值和应用意义. 本文提出一种改进的光滑粒子动力学方法, 对基于eXtended Pom-Pom模型的黏弹性流动进行了数值模拟. 为了提高计算精度, 采用一种不含核导数计算的核梯度修正离散格式. 为了防止粒子穿透固壁, 提出一种增强型的边界处理技术. 为了消除张力不稳定性, 将人工应力耦合到动量守恒方程中. 运用改进光滑粒子动力学方法数值模拟了基于eXtended Pom-Pom模型的黏弹性Poiseuille流和黏弹性液滴撞击固壁问题, 通过与解析解或有限差分方法解的比较以及对数值收敛性的评价, 验证了改进光滑粒子动力学方法的有效性和优势, 并在此基础上, 深入分析了Reyonlds数、Weissenberg数、溶剂黏度比、各向异性参数、松弛时间比和分子链臂数等流变参数对流动过程的影响.
    Viscoelastic fluids widely exist in nature and industrial production, and the study of their complex rheological properties has important academic value and application significance. In this work, an improved smoothed particle hydrodynamics (SPH) method is proposed to numerically simulate the viscoelastic flow based on the eXtended Pom-Pom (XPP) model. In order to improve the accuracy of the calculation, a kernel gradient correction discrete format without kernel derivative calculation is adopted. In order to prevent fluid particles from penetrating the solid wall, an enhanced boundary processing technology is proposed. To eliminate the tensile instability, an artificial stress is coupled into the momentum equation of conservation. Based on the XPP model, the viscoelastic Poiseuille flow and the viscoelastic droplet impacting solid wall problem are simulated by using the improved SPH method. The effectiveness and advantages of the improved SPH method are verified by comparing the SPH solutions with the solutions from the analytical method or finite difference method. The convergence of the improved SPH method is further evaluated by using several different particle sizes. On this basis, the influences of rheological parameters such as Reyonlds number Re, Weissenberg number Wi, solvent viscosity ratio β, anisotropy parameter α, relaxation time ratio γ and molecular chain arm number Q on the flow process are analyzed in depth. For the viscoelastic Poiseuille flow, the bigger the value of Re, Wi, and α, the larger the steady-state velocity is; the larger the value of γ and Q, the smaller the steady-state velocity is; the larger the value of β, the weaker the velocity overshoot is, but it does not affect the steady-state velocity. For the viscoelastic droplet problem, the larger the value of Re and Wi, the faster the droplet spreads; the larger the value of β, the weaker the droplet shrinkage behavior is, but it does not affect the final spreading width of droplet; the larger the value of α, the larger the droplet’s spreading width is; the larger the value of γ is, the stronger the droplet shrinkage behavior is; the larger the value of Q, the weaker its influence on the droplet’s spread width is. The improved SPH method in this paper can effectively describe the complex rheological properties and the free surface variation characteristics of viscoelastic fluid based on XPP model.
      通信作者: 许晓阳, xiaoyang.xu@xust.edu.cn ; 余鹏, yup6@sustech.edu.cn
    • 基金项目: 国家自然科学基金(批准号: 12071367, 12172163)和陕西省“特支计划”青年拔尖人才项目(批准号: 289890259)资助的课题.
      Corresponding author: Xu Xiao-Yang, xiaoyang.xu@xust.edu.cn ; Yu Peng, yup6@sustech.edu.cn
    • Funds: Project supported by the National Natural Science Foundation of China (Grant Nos. 12071367, 12172163) and the Shaanxi Youth Top-notch Talent Program of China (Grant No. 289890259).
    [1]

    Viezel C, Tomé M F, Pinho F T, McKee S 2020 J. Non-newton Fluid Mech. 285 104338Google Scholar

    [2]

    Li B, Chen L, Joo S 2021 Case Stud. Therm. Eng. 26 101109Google Scholar

    [3]

    Li S, Liu W K 2007 Meshfree Particle Methods (Springer Science & Business Media) p68

    [4]

    Gingold R A, Monaghan J J 1977 Mon. Not. R. Astron. Soc. 181 375Google Scholar

    [5]

    Lucy L B 1977 Astron. J. 82 1013Google Scholar

    [6]

    马理强, 刘谋斌, 常建忠, 苏铁熊, 刘汉涛 2012 物理学报 61 244701Google Scholar

    Ma L Q, Liu M B, Chang J Z, Su T X, Liu H T 2012 Acta Phys. Sin. 61 244701Google Scholar

    [7]

    邵绪强, 梅鹏, 陈文新 2021 物理学报 70 234701Google Scholar

    Shao X Q, Mei P, Chen W X 2021 Acta Phys. Sin. 70 234701Google Scholar

    [8]

    Macià F, Merino-Alonso P E, Souto-Iglesias A 2022 Comput. Methods Appl. Mech. Eng. 397 115045Google Scholar

    [9]

    Xu X, Dey M, Qiu M, Feng J J 2020 Appl. Math. Model. 83 719Google Scholar

    [10]

    Liu M B, Zhang Z L, Feng D L 2017 Comput. Mech. 60 513Google Scholar

    [11]

    Zhang C, Rezavand M, Hu X 2021 J. Comput. Phys. 429 110028Google Scholar

    [12]

    Liu W K, Jun S, Zhang Y F 1995 Int. J. Numer. Methods Fluid 20 1081Google Scholar

    [13]

    Liu M B, Liu G R 2006 Appl. Numer. Math. 56 19Google Scholar

    [14]

    Fang J, Parriaux A, Rentschler M, Ancey C 2009 Appl. Numer. Math. 59 251Google Scholar

    [15]

    Yang X, Liu M, Peng S 2014 Comput. Fluids 92 199Google Scholar

    [16]

    Antuono M, Sun P N, Marrone S, Colagrossi A 2021 Comput. Fluids 216 104806Google Scholar

    [17]

    Lyu H G, Sun P N 2022 Appl. Math. Model 101 214Google Scholar

    [18]

    Monaghan J J, Kajtar J B 2009 Comput. Phys. Commun. 180 1811Google Scholar

    [19]

    Morris J P, Fox P J, Zhu Y 1997 J. Comput. Phys. 136 214Google Scholar

    [20]

    Liu M B, Shao J R, Chang J Z 2012 Sci. China Technol. Sci. 55 244Google Scholar

    [21]

    Fang J, Owens R G, Tacher L, Parriaux A 2006 J. Non-newton Fluid Mech. 139 68Google Scholar

    [22]

    Hashemi M R, Fatehi R, Manzari M T 2011 J. Non-newton Fluid Mech. 166 1239Google Scholar

    [23]

    Xu X, Deng X L 2016 Comput. Phys. Commun. 201 43Google Scholar

    [24]

    Ozgen O, Kallmann M, Brown E 2019 Comput. Animat. Virtual Worlds 30 e1870Google Scholar

    [25]

    Vahabi M, Kamkari B 2019 Eur. J. Mech. B. Fluids 75 1

    [26]

    King J R C, Lind S J 2021 J. Non-newton Fluid Mech. 293 104556Google Scholar

    [27]

    Verbeeten W M H, Peters G W M, Baaijens F P T 2001 J. Rheol. 45 823Google Scholar

    [28]

    O'connor J, Domínguez J M, Rogers B D, Lind S J, Stansby P K 2022 Comput. Phys. Commun. 273 108263Google Scholar

    [29]

    Jiang T, Ouyang J, Ren J L, Yang B, Xu X 2012 Comput. Phys. Commun. 183 50Google Scholar

    [30]

    Xu X, Yu P 2018 Comput. Mech. 62 963Google Scholar

    [31]

    Monaghan J J 2000 J. Comput. Phys. 159 290Google Scholar

    [32]

    Gray J P, Monaghan J J, Swift R P 2001 Comput. Methods Appl. Mech. Eng. 190 6641Google Scholar

    [33]

    Waters N D, King M J 1970 Rheol. Acta 9 345Google Scholar

    [34]

    Oishi C M, Martins F P, Tomé M F, Alves M A 2012 J. Non-newton Fluid Mech. 169 91Google Scholar

  • 图 1  黏弹性Poiseuille流的几何区域

    Fig. 1.  Geometric region of viscoelastic Poiseuille flow.

    图 2  基于XPP模型的黏弹性Poiseuille流的SPH模拟 (Re = 2, Wi = 1, β = 0.1, α = 0.01, γ = 0.9, Q = 4) (a) 速度分布图; (b) 空间点1—3速度u随时间的变化; (c) 空间点1—3弹性剪切应力τxy随时间的变化

    Fig. 2.  SPH simulation of viscoelastic Poiseuille flow based on XPP model (Re = 2, Wi = 1, β = 0.1, α = 0.01, γ = 0.9, Q = 4): (a) Velocity profile; (b) time change of velocity u at points 1 to 3; (c) time change of elastic shear stress τxy at points 1 to 3.

    图 3  本文改进SPH数值解与传统SPH数值解和解析解的比较

    Fig. 3.  Comparison of improved SPH solutions with original SPH solutions and analytical solutions.

    图 4  利用传统SPH和改进SPH方法得到的u数值解与解析解的L-2范数误差随时间变化的比较

    Fig. 4.  Comparison of the time change of L-2 norm error obtained based on original SPH solutions and improved SPH solutions.

    图 5  利用不同粒子初始间距Δx得到的SPH数值解 (a) 空间点2处速度u随时间的变化; (b) 空间点1处弹性剪切应力τxy随时间的变化

    Fig. 5.  SPH solutions obtained by different initial particle spacings Δx : (a) Time change of velocity u at point 2; (b) time change of elastic shear stress τxy at point 1.

    图 6  不同流变参数下空间点2处速度u随时间的变化情况 (a) Re; (b) Wi; (c) β; (d) α; (e) γ; (f) Q

    Fig. 6.  Time change of velocity u at point 2 under different rheological parameters: (a) Re; (b) Wi; (c) β; (d) α; (e) γ; (f) Q

    图 7  不同流变参数下空间点1处弹性剪切应力τxy随时间的变化情况 (a) Re; (b) Wi; (c) β; (d) α; (e) γ; (f) Q

    Fig. 7.  Time change of elastic shear stress τxy at point 1 under different rheological parameters: (a) Re; (b) Wi; (c) β; (d) α; (e) γ; (f) Q.

    图 8  XPP黏弹性液滴产生张力不稳定性的SPH结果

    Fig. 8.  SPH results of a XPP viscoelastic droplet with tensile instability.

    图 9  液滴撞击固壁问题的计算模型

    Fig. 9.  Computational model of droplet impacting solid wall problem.

    图 10  基于XPP模型的液滴撞击固壁问题的SPH模拟(Re = 5, Wi = 1, β = 0.1, α = 0.01, γ = 0.9, Q = 4) (a) T = 1.55; (b) T = 1.85; (c) T = 2.35; (d) T = 2.85; (e) T = 3.45; (f) T = 5.00

    Fig. 10.  SPH simulation of droplet impacting solid wall problem based on XPP model (Re = 5, Wi = 1, β = 0.1, α = 0.01, γ = 0.9, Q = 4): (a) T = 1.55; (b) T = 1.85; (c) T = 2.35; (d) T = 2.85; (e) T = 3.45; (f) T = 5.00.

    图 11  不同粒子间距下液滴铺展宽度随时间的变化以及SPH解和FDM解[34]的比较

    Fig. 11.  Time changes of droplet spread width obtained by different initial particle spacings and comparison between SPH and FDM[34] solutions.

    图 12  不同流变参数下液滴铺展宽度d(T)/d0随时间的变化 (a) Re; (b) Wi; (c) β; (d) α; (e) γ; (f) Q

    Fig. 12.  Time change of droplet spread width d(T)/d0 under different rheological parameters: (a) Re; (b) Wi; (c) β; (d) α; (e) γ; (f) Q

  • [1]

    Viezel C, Tomé M F, Pinho F T, McKee S 2020 J. Non-newton Fluid Mech. 285 104338Google Scholar

    [2]

    Li B, Chen L, Joo S 2021 Case Stud. Therm. Eng. 26 101109Google Scholar

    [3]

    Li S, Liu W K 2007 Meshfree Particle Methods (Springer Science & Business Media) p68

    [4]

    Gingold R A, Monaghan J J 1977 Mon. Not. R. Astron. Soc. 181 375Google Scholar

    [5]

    Lucy L B 1977 Astron. J. 82 1013Google Scholar

    [6]

    马理强, 刘谋斌, 常建忠, 苏铁熊, 刘汉涛 2012 物理学报 61 244701Google Scholar

    Ma L Q, Liu M B, Chang J Z, Su T X, Liu H T 2012 Acta Phys. Sin. 61 244701Google Scholar

    [7]

    邵绪强, 梅鹏, 陈文新 2021 物理学报 70 234701Google Scholar

    Shao X Q, Mei P, Chen W X 2021 Acta Phys. Sin. 70 234701Google Scholar

    [8]

    Macià F, Merino-Alonso P E, Souto-Iglesias A 2022 Comput. Methods Appl. Mech. Eng. 397 115045Google Scholar

    [9]

    Xu X, Dey M, Qiu M, Feng J J 2020 Appl. Math. Model. 83 719Google Scholar

    [10]

    Liu M B, Zhang Z L, Feng D L 2017 Comput. Mech. 60 513Google Scholar

    [11]

    Zhang C, Rezavand M, Hu X 2021 J. Comput. Phys. 429 110028Google Scholar

    [12]

    Liu W K, Jun S, Zhang Y F 1995 Int. J. Numer. Methods Fluid 20 1081Google Scholar

    [13]

    Liu M B, Liu G R 2006 Appl. Numer. Math. 56 19Google Scholar

    [14]

    Fang J, Parriaux A, Rentschler M, Ancey C 2009 Appl. Numer. Math. 59 251Google Scholar

    [15]

    Yang X, Liu M, Peng S 2014 Comput. Fluids 92 199Google Scholar

    [16]

    Antuono M, Sun P N, Marrone S, Colagrossi A 2021 Comput. Fluids 216 104806Google Scholar

    [17]

    Lyu H G, Sun P N 2022 Appl. Math. Model 101 214Google Scholar

    [18]

    Monaghan J J, Kajtar J B 2009 Comput. Phys. Commun. 180 1811Google Scholar

    [19]

    Morris J P, Fox P J, Zhu Y 1997 J. Comput. Phys. 136 214Google Scholar

    [20]

    Liu M B, Shao J R, Chang J Z 2012 Sci. China Technol. Sci. 55 244Google Scholar

    [21]

    Fang J, Owens R G, Tacher L, Parriaux A 2006 J. Non-newton Fluid Mech. 139 68Google Scholar

    [22]

    Hashemi M R, Fatehi R, Manzari M T 2011 J. Non-newton Fluid Mech. 166 1239Google Scholar

    [23]

    Xu X, Deng X L 2016 Comput. Phys. Commun. 201 43Google Scholar

    [24]

    Ozgen O, Kallmann M, Brown E 2019 Comput. Animat. Virtual Worlds 30 e1870Google Scholar

    [25]

    Vahabi M, Kamkari B 2019 Eur. J. Mech. B. Fluids 75 1

    [26]

    King J R C, Lind S J 2021 J. Non-newton Fluid Mech. 293 104556Google Scholar

    [27]

    Verbeeten W M H, Peters G W M, Baaijens F P T 2001 J. Rheol. 45 823Google Scholar

    [28]

    O'connor J, Domínguez J M, Rogers B D, Lind S J, Stansby P K 2022 Comput. Phys. Commun. 273 108263Google Scholar

    [29]

    Jiang T, Ouyang J, Ren J L, Yang B, Xu X 2012 Comput. Phys. Commun. 183 50Google Scholar

    [30]

    Xu X, Yu P 2018 Comput. Mech. 62 963Google Scholar

    [31]

    Monaghan J J 2000 J. Comput. Phys. 159 290Google Scholar

    [32]

    Gray J P, Monaghan J J, Swift R P 2001 Comput. Methods Appl. Mech. Eng. 190 6641Google Scholar

    [33]

    Waters N D, King M J 1970 Rheol. Acta 9 345Google Scholar

    [34]

    Oishi C M, Martins F P, Tomé M F, Alves M A 2012 J. Non-newton Fluid Mech. 169 91Google Scholar

  • [1] 冯山青, 龚路远, 权生林, 郭亚丽, 沈胜强. 纳米液滴撞击高温平板壁的分子动力学模拟. 物理学报, 2024, 73(10): 103106. doi: 10.7498/aps.73.20240034
    [2] 刘贺, 杨亚晶, 唐玉凝, 魏衍举. 声致液滴失稳动力学研究. 物理学报, 2024, 73(20): 204204. doi: 10.7498/aps.73.20240965
    [3] 秦威广, 王进, 纪文杰, 赵文景, 陈聪, 蓝鼎, 王育人. 液-液驱替动力学研究. 物理学报, 2022, 71(6): 064701. doi: 10.7498/aps.71.20211682
    [4] 蒋涛, 黄金晶, 陆林广, 任金莲. 非线性薛定谔方程的高阶分裂改进光滑粒子动力学算法. 物理学报, 2019, 68(9): 090203. doi: 10.7498/aps.68.20190169
    [5] 李蕾, 张程宾. 电场对协流式微流控装置中乳液液滴生成行为的调控机理. 物理学报, 2018, 67(17): 176801. doi: 10.7498/aps.67.20180616
    [6] 叶学民, 张湘珊, 李明兰, 李春曦. 液滴在不同润湿性表面上蒸发时的动力学特性. 物理学报, 2018, 67(11): 114702. doi: 10.7498/aps.67.20180159
    [7] 蒋涛, 陈振超, 任金莲, 李刚. 基于修正并行光滑粒子动力学方法三维变系数瞬态热传导问题的模拟. 物理学报, 2017, 66(13): 130201. doi: 10.7498/aps.66.130201
    [8] 梁宏, 柴振华, 施保昌. 分叉微通道内液滴动力学行为的格子Boltzmann方法模拟. 物理学报, 2016, 65(20): 204701. doi: 10.7498/aps.65.204701
    [9] 林林, 袁儒强, 张欣欣, 王晓东. 液滴在梯度微结构表面上的铺展动力学分析. 物理学报, 2015, 64(15): 154705. doi: 10.7498/aps.64.154705
    [10] 刘虎, 强洪夫, 陈福振, 韩亚伟, 范树佳. 一种新型光滑粒子动力学固壁边界施加模型. 物理学报, 2015, 64(9): 094701. doi: 10.7498/aps.64.094701
    [11] 马理强, 苏铁熊, 刘汉涛, 孟青. 微液滴振荡过程的光滑粒子动力学方法数值模拟. 物理学报, 2015, 64(13): 134702. doi: 10.7498/aps.64.134702
    [12] 蒋涛, 任金莲, 徐磊, 陆林广. 非等温非牛顿黏性流体流动问题的修正光滑粒子动力学方法模拟. 物理学报, 2014, 63(21): 210203. doi: 10.7498/aps.63.210203
    [13] 蒋涛, 陆林广, 陆伟刚. 等直径微液滴碰撞过程的改进光滑粒子动力学模拟. 物理学报, 2013, 62(22): 224701. doi: 10.7498/aps.62.224701
    [14] 苏铁熊, 马理强, 刘谋斌, 常建忠. 基于光滑粒子动力学方法的液滴冲击固壁面问题数值模拟. 物理学报, 2013, 62(6): 064702. doi: 10.7498/aps.62.064702
    [15] 杨秀峰, 刘谋斌. 光滑粒子动力学SPH方法应力不稳定性的一种改进方案. 物理学报, 2012, 61(22): 224701. doi: 10.7498/aps.61.224701
    [16] 马理强, 刘谋斌, 常建忠, 苏铁熊, 刘汉涛. 液滴冲击液膜问题的光滑粒子动力学模拟. 物理学报, 2012, 61(24): 244701. doi: 10.7498/aps.61.244701
    [17] 马理强, 常建忠, 刘汉涛, 刘谋斌. 液滴溅落问题的光滑粒子动力学模拟. 物理学报, 2012, 61(5): 054701. doi: 10.7498/aps.61.054701
    [18] 蒋涛, 欧阳洁, 赵晓凯, 任金莲. 黏性液滴变形过程的核梯度修正光滑粒子动力学模拟. 物理学报, 2011, 60(5): 054701. doi: 10.7498/aps.60.054701
    [19] 刘谋斌, 常建忠. 光滑粒子动力学方法中粒子分布与数值稳定性分析. 物理学报, 2010, 59(6): 3654-3662. doi: 10.7498/aps.59.3654
    [20] 王晓亮, 陈硕. 液气共存的耗散粒子动力学模拟. 物理学报, 2010, 59(10): 6778-6785. doi: 10.7498/aps.59.6778
计量
  • 文章访问数:  4027
  • PDF下载量:  68
  • 被引次数: 0
出版历程
  • 收稿日期:  2022-10-07
  • 修回日期:  2022-11-17
  • 上网日期:  2022-11-28
  • 刊出日期:  2023-02-05

/

返回文章
返回