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

适用复杂几何壁面的耗散粒子动力学边界条件

林晨森 陈硕 肖兰兰

引用本文:
Citation:

适用复杂几何壁面的耗散粒子动力学边界条件

林晨森, 陈硕, 肖兰兰

New dissipative particle dynamics boundary condition for complex geometry

Lin Chen-Sen, Chen Shuo, Xiao Lan-Lan
PDF
HTML
导出引用
  • 耗散粒子动力学(DPD)是一种针对介观流体的高效的粒子模拟方法, 经过二十多年发展已经在诸如聚合物、红细胞、液滴浸润性等方面有了很多研究应用. 但是因为其边界处理手段的不完善, 耗散粒子动力学模拟仍局限于相对简单的几何边界问题中. 本文提出一种能自适应各种复杂几何边界的处理方法, 并能同时满足三大边界要求:流体粒子不穿透壁面、边界处速度无滑移、边界处密度和温度波动小. 具体地, 通过给每个壁面粒子赋予一个新的矢量属性—局部壁面法向量, 该属性通过加权计算周围壁面粒子的位置得到;然后通过定义周围固体占比概念, 仅提取固体壁面的表层粒子参与模拟计算, 减少了模拟中无效的粒子;最后在运行中, 实时计算每个流体粒子周围固体粒子占比, 判断是否进入固体壁面内, 如果进入则修正速度和位置. 我们将这种方法应用于Poiseuille流动, 验证了该方法符合各项要求, 随后还在复杂血管网络和结构化固体壁面上展示了该边界处理方法的应用. 这种方法使得DPD模拟不再局限于简单函数描述的壁面曲线, 而是可以直接从各种设计图纸和实验扫描影像中提取壁面, 极大地拓展了DPD的应用范围.
    Dissipative particle dynamics (DPD) is a thriving particle-based simulation method of modeling mesoscale fluids. After two decades of evolution, DPD has shown unique advantages in researches about polymer, red blood cell, droplets wetting, etc. However, DPD is limited to relatively simple geometries due to the lack of a satisfactory boundary method. In this paper, we propose an adaptive boundary method for complex geometry, which fulfills the three basic requirements of boundary method: no penetration into the solid, no-slip near boundary, negligible fluctuation of density or temperature near boundary. Specifically, first, a new vector attribution is added to each solid particle, the attribution is named local wall normal (LWN) attribution and it is a function of its neighbor solid particle’s position, the LWN attribution is used to correct the penetrating fluid particles’ velocity and position and is computed only once if the wall is stationary. Second the surface wall particles are identified by neighbor solid fraction (φ), which indicates the percentage of surrounding space occupied by solid particles, then the wall is reconstructed by only the surface particles instead of all solid particles. By doing so, the redundant bulk particles are removed from the simulation. Third, it is detected on-the-fly whether the moving fluid particle penetrates the wall by computing its φ, the fluid particles with φ greater than 0.5 are considered to enter into the solid wall, their position and velocity will be corrected based on the local wall normal attribution. We verify that the method causes negligible density and temperature fluctuation in Poiseuille flow. Then, we illustrate the implementation of LWNM in the cases of complex blood vessel network and micro-structured surface. With this method, the obstacles in flow are no longer restricted to shapes described by functions but can be generated by CAD software, and blood vessels can also be generated by CT scan images or other experimental data. Moreover, we show a case with a bent tube and droplets inside, demonstrating the practicability of constructing complex geometry and the effectiveness of LWNM. This new boundary approach empowered DPD to simulate more realistic problems.
      通信作者: 陈硕, schen_tju@tongji.edu.cn
    • 基金项目: 国家自然科学基金(批准号:11872283)和上海市科技人才计划(批准号:19YF1417400)资助的课题.
      Corresponding author: Chen Shuo, schen_tju@tongji.edu.cn
    • Funds: Project supported by the National Natural Science Foundation of China (Grant No. 11872283) and the Shanghai Science and Technology Talent Program, China (Grant No. 19YF1417400).
    [1]

    Hoogerbrugge P J, Koelman J 1992 Europhys. Lett. 19 155Google Scholar

    [2]

    Español P, Warren P 1995 Europhys. Lett. 30 191Google Scholar

    [3]

    Groot R D, Warren P B 1997 J. Chem. Phys. 107 4423Google Scholar

    [4]

    Xiao L L, Chen S, Lin C S, Liu Y 2014 Mol. Cell. Biomech. 11 67

    [5]

    Xiao L L, Liu Y, Chen S, Fu B M 2017 Int. J. Comput. Methods Exp. Meas. 6 303

    [6]

    Arienti M, Pan W, Li X J, Karniadakis G E 2011 J. Chem. Phys. 134 204114Google Scholar

    [7]

    Lin C S, Chen S, Xiao L L, Liu Y 2018 Langmuir 34 2708Google Scholar

    [8]

    Wang Y X, Chen S 2015 Appl. Surf. Sci. 327 159Google Scholar

    [9]

    林晨森, 陈硕, 李启良, 杨志刚 2014 物理学报 63 104702Google Scholar

    Lin C S, Chen S, Li Q L, Yang Z G 2014 Acta Phys. Sin. 63 104702Google Scholar

    [10]

    Reddy H, Abraham 2009 J. Phys. Fluids 21 053303Google Scholar

    [11]

    陈硕, 金亚斌, 张明焜, 尚智 2012 同济大学学报 01 137Google Scholar

    Chen S, Jin Y B, Zhang M K, Shang Z 2012 J. Tongji Univ. 01 137Google Scholar

    [12]

    Kang S H, Hwang W S, Lin Z, Kwon S H, Hong S W 2015 Nano Lett. 15 7913Google Scholar

    [13]

    Liu M B, Liu G R, Zhou L W, Chang J Z 2014 Arch. Comp. Meth. Eng. 22 529

    [14]

    Kreder M J, Alvarenga J, Kim P, Aizenberg J 2016 J. Nat. Rev. Mater. 1 20153

    [15]

    Revenga M, Zúñiga I, Español P 1999 Comput. Phys. Commun. 121 309

    [16]

    许少锋, 汪久根 2013 浙江大学学报 47 1603Google Scholar

    Xu S F, Wang J G 2013 J. Zhejiang Univ. 47 1603Google Scholar

    [17]

    Mehboudi A, Saidi M S 2011 Scientia Iranica 18 6

    [18]

    刘谋斌, 常建忠 2010 物理学报 59 7556Google Scholar

    Liu M B, Chang J Z 2010 Acta Phys. Sin. 59 7556Google Scholar

    [19]

    Li Z, Bian X, Tang Y H, Karniadakis G E 2018 J. Comput. Phys. 355 534Google Scholar

    [20]

    Pivkin I V, Karniadakis G E 2005 J. Comput. Phys. 207 114Google Scholar

    [21]

    Duong-Hong D, Phan-Thien N, Fan X J 2004 Comput. Mech. 35 24Google Scholar

    [22]

    Lei H, Fedosov D A, Karniadakis G E 2011 J. Comput. Phys. 230 3765Google Scholar

    [23]

    Ranjith S K, Patnaik B S V, Vedantam S 2013 J. Comput. Phys. 232 174Google Scholar

    [24]

    Sigalotti L D, Klapp J, Sira E, Meleán Y, Hasmy A 2003 J. Comput. Phys. 191 622Google Scholar

    [25]

    Liu T, Kim C J 2014 Science 346 1096

    [26]

    Malouin B A, Koratkar N A, Hirsa A H, Wang Z 2010 Appl. Phys. Lett. 96 234103Google Scholar

    [27]

    Fedosov D A, Caswell B, Karniadakis G E 2010 Comput. Meth. Appl. Mech. Eng. 199 1937

    [28]

    Xiao L L, Liu Y, Chen S, Fu B M 2016 Cell Biochem. Biophys. 74 513Google Scholar

    [29]

    Ye T, Phan-Thien N, Khoo B C, Lim C T 2014 J. Appl. Phys. 116 124703Google Scholar

  • 图 1  计算计算壁面粒子i的法向量lwni

    Fig. 1.  Computing the local wall normal vector lwni of wall particle i.

    图 2  流体粒子固体体积分数(φ)的四种情况(φ = 0远离壁面, 0 < φ < 0.5未穿透壁面, 0.5 < φ < 1.0已穿透壁面, φ = 1.0完全浸入壁面)

    Fig. 2.  Four scenarios for solidfraction (φ): φ = 0 particle away from wall; 0 < φ < 0.5 particle near the wall; 0.5 < φ < 1.0 particle penetrating the wall; φ = 1.0 particle submerged in wall.

    图 3  选用一定范围内固体粒子的lwni计算修正流体粒子时的法向量en

    Fig. 3.  Computing en from nearby lwni for correcting penetrating fluid particle.

    图 4  LWNM边界条件的实施过程图 (a) 固体粒子构造壁面; (b) 提取表面层固体粒子; (c)计算LWN; (d)模拟时效果

    Fig. 4.  Workflow of LWNM: (a) Constructing wall with frozen particles; (b) identifying surface wall particles; (c) com-puting LWN; (d) snapshot during simulation.

    图 5  LWNM边界方法统计结果和理论解的对比(Vx)

    Fig. 5.  Comparison of LWNM and theoretical results (Vx).

    图 6  LWNM边界方法统计结果和理论解的对比(温度和密度)

    Fig. 6.  Comparison of LWNM and theoretical results (temperature and density).

    图 7  (a)微结构表面对液滴亲疏水性的影响[26]; (b)粒子模拟中微结构表面的LWN

    Fig. 7.  (a) Microstructures on surface affect the hydrophilicity; (b) LWNs (grey arrows) of surface with microstructures.

    图 8  复杂血管的局部法向量的生成

    Fig. 8.  LWN generation in complex blood vessel.

    图 9  应用LWNM实现液滴在TJU(同济大学)形状的复杂管道中运动

    Fig. 9.  Droplets in TJU (Tongji University) shape tube with LWNM.

  • [1]

    Hoogerbrugge P J, Koelman J 1992 Europhys. Lett. 19 155Google Scholar

    [2]

    Español P, Warren P 1995 Europhys. Lett. 30 191Google Scholar

    [3]

    Groot R D, Warren P B 1997 J. Chem. Phys. 107 4423Google Scholar

    [4]

    Xiao L L, Chen S, Lin C S, Liu Y 2014 Mol. Cell. Biomech. 11 67

    [5]

    Xiao L L, Liu Y, Chen S, Fu B M 2017 Int. J. Comput. Methods Exp. Meas. 6 303

    [6]

    Arienti M, Pan W, Li X J, Karniadakis G E 2011 J. Chem. Phys. 134 204114Google Scholar

    [7]

    Lin C S, Chen S, Xiao L L, Liu Y 2018 Langmuir 34 2708Google Scholar

    [8]

    Wang Y X, Chen S 2015 Appl. Surf. Sci. 327 159Google Scholar

    [9]

    林晨森, 陈硕, 李启良, 杨志刚 2014 物理学报 63 104702Google Scholar

    Lin C S, Chen S, Li Q L, Yang Z G 2014 Acta Phys. Sin. 63 104702Google Scholar

    [10]

    Reddy H, Abraham 2009 J. Phys. Fluids 21 053303Google Scholar

    [11]

    陈硕, 金亚斌, 张明焜, 尚智 2012 同济大学学报 01 137Google Scholar

    Chen S, Jin Y B, Zhang M K, Shang Z 2012 J. Tongji Univ. 01 137Google Scholar

    [12]

    Kang S H, Hwang W S, Lin Z, Kwon S H, Hong S W 2015 Nano Lett. 15 7913Google Scholar

    [13]

    Liu M B, Liu G R, Zhou L W, Chang J Z 2014 Arch. Comp. Meth. Eng. 22 529

    [14]

    Kreder M J, Alvarenga J, Kim P, Aizenberg J 2016 J. Nat. Rev. Mater. 1 20153

    [15]

    Revenga M, Zúñiga I, Español P 1999 Comput. Phys. Commun. 121 309

    [16]

    许少锋, 汪久根 2013 浙江大学学报 47 1603Google Scholar

    Xu S F, Wang J G 2013 J. Zhejiang Univ. 47 1603Google Scholar

    [17]

    Mehboudi A, Saidi M S 2011 Scientia Iranica 18 6

    [18]

    刘谋斌, 常建忠 2010 物理学报 59 7556Google Scholar

    Liu M B, Chang J Z 2010 Acta Phys. Sin. 59 7556Google Scholar

    [19]

    Li Z, Bian X, Tang Y H, Karniadakis G E 2018 J. Comput. Phys. 355 534Google Scholar

    [20]

    Pivkin I V, Karniadakis G E 2005 J. Comput. Phys. 207 114Google Scholar

    [21]

    Duong-Hong D, Phan-Thien N, Fan X J 2004 Comput. Mech. 35 24Google Scholar

    [22]

    Lei H, Fedosov D A, Karniadakis G E 2011 J. Comput. Phys. 230 3765Google Scholar

    [23]

    Ranjith S K, Patnaik B S V, Vedantam S 2013 J. Comput. Phys. 232 174Google Scholar

    [24]

    Sigalotti L D, Klapp J, Sira E, Meleán Y, Hasmy A 2003 J. Comput. Phys. 191 622Google Scholar

    [25]

    Liu T, Kim C J 2014 Science 346 1096

    [26]

    Malouin B A, Koratkar N A, Hirsa A H, Wang Z 2010 Appl. Phys. Lett. 96 234103Google Scholar

    [27]

    Fedosov D A, Caswell B, Karniadakis G E 2010 Comput. Meth. Appl. Mech. Eng. 199 1937

    [28]

    Xiao L L, Liu Y, Chen S, Fu B M 2016 Cell Biochem. Biophys. 74 513Google Scholar

    [29]

    Ye T, Phan-Thien N, Khoo B C, Lim C T 2014 J. Appl. Phys. 116 124703Google Scholar

  • [1] 马奥杰, 陈颂佳, 李玉秀, 陈颖. 纳米颗粒布朗扩散边界条件的分子动力学模拟. 物理学报, 2021, 70(14): 148201. doi: 10.7498/aps.70.20202240
    [2] 赖煜成, 陈苏琪, 牟兰雅, 王兆娜. 基于麦克斯韦方程组的纳米尺度电磁边界条件. 物理学报, 2021, 70(23): 230301. doi: 10.7498/aps.70.20211025
    [3] 杨颖, 宋俊杰, 万明威, 高靓辉, 方维海. 分子层次的金纳米棒-表面活性剂-磷脂自组装复合体形貌. 物理学报, 2020, 69(24): 248701. doi: 10.7498/aps.69.20200979
    [4] 谭志中, 谭震. 一类任意m×n阶矩形网络的电特性. 物理学报, 2020, 69(2): 020502. doi: 10.7498/aps.69.20191303
    [5] 许少锋, 楼应侯, 吴尧锋, 王向垟, 何平. 微通道疏水表面滑移的耗散粒子动力学研究. 物理学报, 2019, 68(10): 104701. doi: 10.7498/aps.68.20182002
    [6] 刘波, 王青, 李永明, 隆正文. 有限空间中经典场的正则量子化. 物理学报, 2015, 64(10): 100301. doi: 10.7498/aps.64.100301
    [7] 林晨森, 陈硕, 李启良, 杨志刚. 耗散粒子动力学GPU并行计算研究. 物理学报, 2014, 63(10): 104702. doi: 10.7498/aps.63.104702
    [8] 姚祎, 周哲玮, 胡国辉. 有结构壁面上液滴运动特征的耗散粒子动力学模拟. 物理学报, 2013, 62(13): 134701. doi: 10.7498/aps.62.134701
    [9] 王青, 隆正文, 罗翠柏. 有限空间中Dirac场的正则量子化. 物理学报, 2013, 62(10): 100305. doi: 10.7498/aps.62.100305
    [10] 刘汉涛, 刘谋斌, 常建忠, 苏铁熊. 介观尺度通道内多相流动的耗散粒子动力学模拟. 物理学报, 2013, 62(6): 064705. doi: 10.7498/aps.62.064705
    [11] 许少锋, 汪久根. 微通道中高分子溶液Poiseuille流的耗散粒子动力学模拟. 物理学报, 2013, 62(12): 124701. doi: 10.7498/aps.62.124701
    [12] 刘汉涛, 常建忠. 直接模拟中不同边界条件的实施及对沉降规律的影响. 物理学报, 2013, 62(8): 084401. doi: 10.7498/aps.62.084401
    [13] 常建忠, 刘汉涛, 刘谋斌, 苏铁熊. 介观尺度流体绕流球体的耗散粒子动力学模拟. 物理学报, 2012, 61(6): 064704. doi: 10.7498/aps.61.064704
    [14] 吴兆春. 导热几何形状反演的变分原理及边界条件的确立. 物理学报, 2010, 59(9): 6326-6330. doi: 10.7498/aps.59.6326
    [15] 李树玲, 张劭光. 双凹盘形解开口膜泡形状的解析法研究. 物理学报, 2010, 59(8): 5202-5208. doi: 10.7498/aps.59.5202
    [16] 张旭, 周玉泽, 闭强, 杨兴华, 俎云霄. 有边界条件的忆阻元件模型及其性质. 物理学报, 2010, 59(9): 6673-6680. doi: 10.7498/aps.59.6673
    [17] 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
    [18] 刘谋斌, 常建忠. 耗散粒子动力学处理复杂固体壁面的一种有效方法. 物理学报, 2010, 59(11): 7556-7563. doi: 10.7498/aps.59.7556
    [19] 董丽芳, 谢伟霞, 赵海涛, 范伟丽, 贺亚峰, 肖红. 氩气/空气介质阻挡放电自组织超六边形斑图实验研究. 物理学报, 2009, 58(7): 4806-4811. doi: 10.7498/aps.58.4806
    [20] 韩一平, 吴振森. 椭球粒子电磁散射的边界条件的讨论. 物理学报, 2000, 49(1): 57-60. doi: 10.7498/aps.49.57
计量
  • 文章访问数:  8872
  • PDF下载量:  100
  • 被引次数: 0
出版历程
  • 收稿日期:  2019-04-11
  • 修回日期:  2019-05-05
  • 上网日期:  2019-07-01
  • 刊出日期:  2019-07-20

/

返回文章
返回