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作 者:潘定一[1] 胡国辉[2] 陈硕[3] PHAN-THIEN Nhan PAN Dingyi;HU Guohui;CHEN Shuo;PHAN-THIEN Nhan(State key Laboratory of Fluid Power and Mechatronic Systems and Department of Engineering Mechanics,Zhejiang University,Hangzhou 310027,China;College of Mechanics and Engineering Science,Shanghai University,Shanghai Institute of Applied Mathematics and Mechanics,Shanghai 20072,China;College of Aerospace and Mechanics,Tongji University,Shanghai 200092,China;Department of Mechanical Engineering,National University of Singapore,Singapore 117575,Singapore)
机构地区:[1]浙江大学工程力学系,流体动力基础件与机电系统全国重点实验室,杭州310027 [2]上海大学力学与工程科学学院,上海市应用数学和力学研究所,上海200072 [3]同济大学航空航天与力学学院,上海200092 [4]Department of Mechanical Engineering,National University of Singapore,Singapore 117575
出 处:《力学进展》2024年第1期173-201,共29页Advances in Mechanics
基 金:国家自然科学基金(12222211,11972322)资助项目.
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.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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