Mesoscopic modeling of complex multiphase fluids: Dissipative particle dynamics (DPD) method and its applications
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摘要: 在悬浮液、乳液和泡沫等复杂多相流体中, 离散分布着大量的纳米至微米尺度的颗粒、液滴和气泡等, 在流动作用下这些离散相物质呈现出复杂的个体或群体运动行为, 进而显著影响这些复杂多相流体的宏观流变和流动行为. 针对这类流体, 开展介观尺度数值模拟成为一种有效且相对经济的研究手段. 其中, 耗散粒子动力学 (dissipative particle dynamics, DPD) 方法是一种具有代表性的介观尺度数值模拟方法, 由于其粒子方法的特质, DPD方法适合用于上述复杂多相流体内部结构的数值建模和数值模拟研究. 本文对近年来DPD方法在颗粒悬浮液、乳液和气泡等复杂多相流体模拟方面研究进展进行了系统的介绍, 深入探讨了DPD方法在复杂多相流体介观模拟方面的针对性改进以及当前存在的不足, 并对DPD方法的研究和应用进行了总结和展望.Abstract: Complex multiphase fluids, such as suspension, emulsion and foam, which contain large number of particles, droplets and bubbles, respectively, with characteristic scale ranges from nanometer to micron. For these kinds of dispersed materials, either individually or in clusters, complex kinematic behavior is exhibited under the imposed flow, affecting the bulk rheological properties of these multiphase fluids. Investigations of these complex fluids by using mesoscopic numerical methods are among the most effective and economic approaches. In particular, dissipative particle dynamics (DPD) is a typical mesoscopic numerical method. Due to its particle-based nature, it is especially suitable for the modeling and investigating of these types of complex fluids. In this review, we thoroughly introduce the applications of DPD methods in the modeling of suspension, emulsion and bubbles as well as the corresponding developments in DPD methods. Meanwhile, we also discuss relevant shortcomings and certain aspects that require further improvement. Finally, we provide a conclusion and outlook for DPD methods.
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图 2 冻结粒子模型示意图. (a)二维颗粒模型(Hoogerbrugge & Koelman 1992), (b)三维球形颗粒模型(Chen S et al. 2006)
图 3 DPD模拟得到的单颗粒阻力系数与流动Re关系图及其与实验和理论结果的对比验证. (a) Kim和Phillips(2004)的模拟结果与实验结果(Perry & Green 1999)以及渐进分析结果(Oseen 1910, Proudman & Pearson 1957)的对比, (b) Chen等(2006)的模拟结果与理论结果(Dennis & Walker 1971)的对比
图 4 基于DPD-DEM模拟得到的颗粒悬浮液内部颗粒团结构的演变过程, 上行为半浓相悬浮液, 下行为浓相悬浮液, 不同颜色颗粒表示不同数量悬浮颗粒组成的颗粒团结构(Boromand et al. 2018)
图 5 复杂颗粒的DPD方法建模. (a) 碟形颗粒模型(Jamali et al. 2017), (b) 低维红细胞模型(Pan W et al. 2010b), (c) 石墨烯片状颗粒模型(Min et al. 2012), (d) 颗粒表面粗糙度模型(Jamali & Brady 2019)
图 7 (a) 改进的DPD模拟液滴在剪切流作用下变形结果与实验和前人模拟的对比(Pan D et al. 2014), (b) 液滴在剪切作用下的瞬态变形结果与实验和前人模拟的对比(Zhao G et al. 2021)
图 8 (a) 平板泊肃叶流动中液滴变形以及横向平衡位置的DPD模拟与理论 (实线) 和VoF模拟 (虚线) 结果的验证(Pan D et al. 2016), (b) 液滴在泊肃叶流动中横向平衡位置随Oh数的变化规律(Marson et al. 2018)
图 9 (a) 剪切流作用下乳液液滴变形的DPD模拟(Pan D et al. 2014), (b) 乳液相对黏度随体积分数的变化情况(Pan D et al. 2014)及其与相关理论模型(Choi & Schowalter 1975, Phan-Thien & Pham 1997, Taylor 1932, Yaron & Gal-Or 1972)和实验结果(Pal 2001)的对比, (c) 振荡剪切作用下乳液的Lissajous曲线(赵庚尧 2023)
图 10 (a) 微尺度流道内气液两相流动模拟(Chen C et al. 2010), (b) 微纳尺度液柱模拟(Tiwari et al. 2008), (c) 壁面上液滴运动模拟(Li Z et al. 2013), (d) 平行壁面间的液桥模拟(Zhao J et al. 2020a)
图 12 传统DPD和many-body DPD相结合的气泡DPD模型. (a) 模型示意图(Lin C et al. 2021a), (b) 稳态气泡的DPD模拟结果(Pan D et al. 2018), (c) 气泡内外密度分布(Pan D et al. 2018), (d) 外场压力作用下的气泡振荡模拟结果与Rayleigh-Plesset方程对比(Pan D et al. 2018)
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