气泡动力学
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研究气泡空化运动的方法-概述说明以及解释1.引言1.1 概述概述:气泡空化运动是一种在流体中液体脉动引起气泡形成和破裂的现象,也是流体力学中的重要研究课题之一。
气泡空化不仅在海洋工程、化工工艺、生物医学等领域有着重要的应用价值,同时也对流体运动的理解和控制具有重要的理论意义。
本文旨在探讨研究气泡空化运动的方法,通过深入分析气泡空化现象的基本概念并提出不同的研究方法,以期对气泡空化运动有更全面深入的理解。
通过本文的研究,我们希望能够为未来在气泡空化运动领域的研究提供一定的参考和启示,推动相关领域的发展和应用。
1.2 文章结构文章结构部分的内容可以描述整篇文章的组织结构和各部分的主要内容安排,以便读者了解整体内容流程。
具体内容可以包括:文章结构部分:本文共分为引言、正文和结论三个部分。
1. 引言部分介绍了本文的研究背景和意义,以及本文的目的和意义。
2. 正文部分主要包括气泡空化运动的基本概念、研究方法一和研究方法二三个子章节。
在正文部分中,将对气泡空化运动的相关概念进行介绍,并分别阐述两种不同的研究方法。
3. 结论部分对本文的研究方法进行总结,展望了这些方法的应用前景,最后给出结论。
通过引言、正文和结论三部分的结构布局,本文将全面系统地介绍研究气泡空化运动的方法,为读者提供清晰的研究框架和思路。
1.3 目的:研究气泡空化运动的目的主要包括以下几个方面:1.探索气泡在流体中的运动规律:通过深入研究气泡空化运动的方法,可以更好地理解气泡在流体中的运动规律,揭示气泡空化现象背后的物理机理。
2.提高气泡空化现象的控制和应用:通过研究气泡空化运动的方法,可以为气泡空化技术的发展提供有效的方法和手段,进一步提高气泡空化现象的控制性和应用性。
3.促进相关领域的学术交流和合作:通过开展气泡空化运动的研究,可以促进学术界和工业界在相关领域的交流与合作,推动气泡空化技术及其应用的发展。
2.正文2.1 气泡空化运动的基本概念气泡空化运动是指在液体中存在气泡时,由于液体的流动或外力作用,气泡不断变形、移动并最终破裂的过程。
汽水喷出的化学原理是什么汽水喷出的化学原理是通过碳酸饮料中溶解的二氧化碳气体的释放。
汽水是一种含有二氧化碳气泡的饮料,通常由水、糖或甜味剂、香料和二氧化碳组成。
当瓶子关闭时,二氧化碳气体被压缩在瓶内。
然而,当瓶子被打开时,气体压力的突然释放导致溶解在液体中的二氧化碳迅速释放,形成气泡并将液体带到口部,从而喷出。
汽水喷出现象的主要原理是物理溶解度和气体动力学的相互作用。
首先,二氧化碳在液体中以物理形式溶解,形成一种称为碳酸的弱酸。
这一过程是可逆的,即溶解和脱溶解之间存在平衡。
当瓶子关闭时,被压缩的气体以相对稳定的状态存在于液体中。
然而,当瓶子被打开,气体压力突然减小,导致平衡失调。
此时,相较于新的低压环境,液体中的二氧化碳具有较高的自由能,因此开始从溶液中逸出。
这一过程称为脱溶解。
从溶液中脱溶解的二氧化碳形成了微小的气泡,这些气泡会依附在瓶壁或悬浮在液体中。
由于液体中的二氧化碳过饱和,这些气泡会不断增大,并随着时间的推移成为稳定的气泡。
当瓶盖被解开时,瓶内压力骤然下降,这使液体中的二氧化碳气泡迅速增大。
这是由于气体动力学原理以及Henry定律的效应。
根据Henry定律,溶解度与气体的分压成正比。
换句话说,气体分压降低时,溶解度也会降低,导致溶解在液体中的气体迅速释放。
当瓶盖被解开时,由于压力的快速释放,液体中的二氧化碳气泡会迅速增大并上升到表面。
由于液体中溶解了大量的二氧化碳气体,气泡在上升过程中聚集成为更大的气泡。
在达到液体表面后,这些气泡脱离液体并快速升到瓶口。
此外,含有糖分的饮料还会促进喷射过程。
糖分在液体中形成了高黏度的糖浆,使液体粘稠度增加。
当瓶盖被解开时,瓶内压力快速减小,液体的黏稠度减小,从而使二氧化碳气泡更容易上升到液面。
总结起来,汽水喷出的化学原理是通过瓶内压力突然释放,导致溶解在液体中的二氧化碳气体迅速释放,形成气泡并将液体带到瓶口。
这一过程结合了物理溶解度和气体动力学原理,以及糖分在液体中形成的高黏稠度。
Er∶YAG激光SWEEPS双脉冲模式激活荡洗在自由水域中的气泡动力学观测何新宇;李依洲;聂铭远;于悦;陈浩天;潘翀;赵继志【期刊名称】《实用口腔医学杂志》【年(卷),期】2024(40)1【摘要】目的:探究Er∶YAG激光光子增强的光声流(SWEEPS)技术在不同脉冲间隔参数条件下的蒸汽气泡动力学效应。
方法:Er∶YAG激光手具连接工作尖放置于自由水域模型中,设置SWEEPS模式,150~600μs脉冲间隔激活。
高速摄像机(200 000 Hz)摄录Er∶YAG激光激活荡洗引起空穴效应的过程,matlab逐帧分析蒸汽气泡间的相互作用关系,及蒸汽气泡消失时刻气泡残余与激光工作尖之间的距离。
实验数据经SPSS 19.0统计软件进行统计分析。
结果:在自由水域中,Er∶YAG激光SWEEPS模式下,脉冲间隔设置的改变会引起两次脉冲激发的蒸汽气泡形成不同的相互作用关系,包括双气泡融合、双气泡撞击及双气泡脱离。
其中,脉冲间隔设置为360~440μs时,双气泡撞击现象会使蒸汽气泡消失时气泡残余与激光工作尖之间达到最远距离。
结论:在自由水域中,Er∶YAG激光双脉冲SWEEPS模式在不同的脉冲间隔设置下引起双气泡间形成不同的作用关系,该现象可能可以增强Er∶YAG激光空穴效应,强化激光激活荡洗的临床应用效果。
【总页数】7页(P64-70)【作者】何新宇;李依洲;聂铭远;于悦;陈浩天;潘翀;赵继志【作者单位】中国医学科学院北京协和医院口腔科;清华大学玉泉医院口腔科;北京航空航天大学流体力学教育部重点实验室【正文语种】中文【中图分类】R781.05【相关文献】1.不同脉冲宽度Er:YAG激光激活根管荡洗的研究2.Er:YAG激光辅助根管荡洗安全性的研究进展3.Er:YAG激光辅助根管荡洗对冲洗液根尖溢出影响的系统评价4.Er:YAG激光活化荡洗对桩道牙本质微观结构及纤维桩粘接强度的影响5.Er∶YAG激光激活荡洗辅助根管治疗对慢性根尖周炎临床效果及影响因素的回顾性研究因版权原因,仅展示原文概要,查看原文内容请购买。
纳米尺度下气泡核化生长的分子动力学研究佚名【摘要】采用分子动力学方法模拟纳米尺度下液体在固体壁面上发生核化沸腾的过程,主要研究壁面浸润性对气泡初始核化过程和气泡生长速率的影响以及固-液界面效应在液体核化沸腾的能量传递过程中所起到的作用.研究结果发现:壁面浸润性越强,气泡在固壁处越容易核化.该结果与经典核化理论中“疏水壁面易于产生气泡”的现象产生了明显的区别.其根本原因是在纳米尺度下,固-液界面热阻效应不能被忽略.一方面,在相同的壁温下,通过增强固-液相互作用,可以显著降低界面热阻,使得热量传递效率提高,导致靠近壁面处的流体温度升高,气泡核化等待时间缩短,有利于液体沸腾核化.另一方面,气泡的生长速率随着壁面浸润性的增强而明显升高.当气泡体积生长到一定程度时,会在壁面处形成气膜,从而导致壁面传热性能恶化.因此,通过壁面的热流密度呈现出先增大后减小的规律.【期刊名称】《物理学报》【年(卷),期】2018(067)023【总页数】11页(P159-169)【关键词】纳米尺度;气泡核化;浸润性;界面效应【正文语种】中文1 引言随着微纳米技术在不同领域中的广泛应用,微纳设备中因高热流密度的产生而导致各种微纳器件的热管理问题成为亟待解决的核心难题.工质核化相变原理因具有高效换热特性,而作为一种理想方案被应用于微纳制造领域[1−3].利用相变原理进行换热将导致气泡产生及两相流的形成.因此,对微纳尺度下流体的相变诱导气泡形核生长及脱离等现象的研究成为传热传质领域一项具有挑战性的研究课题.深入研究其物理机制并优化微系统内部的热质传递过程,是节约资源和提高能源利用效率的重要手段.众所周知,纳米尺度下固-液界面效应对于微纳系统传热传质及工质相变现象具有显著影响.已有研究[4−6]发现,在微米通道的单相流动中,壁面浸润性影响固-液界面结构及流体原子与固体原子的黏附情况,进而影响界面能量与动量的传递.同时,界面效应也会对纳米尺度相变过程产生影响.因此,有必要对微纳设备中涉及的异质核化的机理及影响因素进行深入的分析与探讨.壁面浸润性对于异质核化具有重要的影响,根据经典核化理论,表面沸腾中液体在光滑固体加热表面上形成气泡所需的活化能与过热度及表面接触角有关.当壁面接触角越大时,气泡核化所需的活化能越少,发生沸腾的极限过热度越低.此结论已被大量实验数据及理论分析证实.Bourdon等[7]通过实验研究固体表面浸润性对池沸腾起始核化点的影响规律,发现起始核化过热度随表面接触角的增大呈单调递减趋势.Jo 等[8]认为在低热流密度区域,虽然疏水壁面更加有利于核化的发生,但是临界热流密度(CHF)却很低.此外,异质浸润性壁面与均质浸润性壁面相比,更有利于核化沸腾.Quan等[9]对固壁上异质核化沸腾进行理论分析,发现当近壁区液体存在温度梯度时,在异质核化的初始核化阶段,其临界核化半径随着接触角的增大而减小,可以促进气泡核化.Xu和Qian[10]采用范德瓦耳斯理论分析单气泡异质成核过程,得到与之类似的结论:当壁面为均质浸润性时,增大接触角或者过热度将促使气泡在加热壁面处膨胀扩展,增大气泡脱离直径,易于产生膜态沸腾.在常规尺度范围,传热传质以连续介质力学为理论依据,而微观尺度则以纳米级微观粒子理论作为依据,界面特性影响尤为突出,使得微纳相变过程明显区别于常规尺度.目前,已有学者对微纳尺度的相变传热问题展开研究.由于尺寸限制,在纳米尺度下开展实验研究存在很大的困难,而分子动力学方法直接面向原子层面,是研究原子尺度物理现象的有效手段.在均质核化方面,Kinjo和Matsumoto[11]采用分子动力学方法研究负压情况下的气泡空化过程,发现核化速率比经典核化理论预测值大8个数量级.Kimura和Maruyama[12]研究平板上的异质核化规律,模拟结果与经典核化理论预测的一致.Kinjo等[13]采用分子动力学方法研究受限微通道内流体的核化过程,发现壁面浸润性导致流体出现3种不同的核化过程,即弱吸附力壁面处的气膜形成过程、中等吸附力通道内的异质核化过程以及强吸附力通道内的均质核化过程.Mao和Zhang[14]模拟气泡均质成核过程,结果显示气泡生长规律与用RaleighPlesset方程预测的结果不一致.研究发现采用经典核化理论预测的极限过热度、临界核化半径、核化速率及气泡生长速率等数据与纳米尺度下获取到的实验结果相比,在某些情况下会相差很大的数量级[15].目前学术界对于该问题产生的深层原因仍然没有统一的定论.在异质核化方面,Nagayama等[16]认为气泡核化位置受壁面浸润性影响,在亲水性微通道内发生均质核化,气泡在主流液体区域产生;在疏水性微通道内发生异质核化,气泡在固体壁面处产生;此外,对于超疏水壁面,则不会在壁面处产生气泡,而是在固-液之间形成一层气膜.Bai和Li[17]研究发现对于浸润性较强的壁面,近壁区中能量较高的分子向主流液体区的运动受到限制,能量传递效率较低,从而导致界面接触热阻增大,固体界面温差也大幅增加,因此不利于核化发生.Novak等[18]通过模拟流体氩在固体壁面处的异质核化过程,发现气泡在浸润性弱的壁面处发生异质核化的时间有所减少,其原因是随着固-液相互作用增强,流体在近壁区呈类固体的形式排列,从而导致气泡在类固体排列流体区域上产生.Carey和Wemhof f[19]修正了Redlich-Kwong流体状态方程,用于预测受固壁影响的近壁区流体物性.近壁区流体由于受固壁的作用,导致该区域内的流体压力增高,流体发生核化所需的临界过热度显著提高.因此,距离固体壁面有一定距离的液体反而先达到核化条件开始沸腾,进而发生均质核化.然而也有部分文献研究得出相反的结果,Hens等[20]认为在非浸润壁面上气泡难以形成,亲水性壁面为气泡核化提供有利场所并促进了气膜的形成.Yamamoto和Matsumoto[21]推断固-液相互作用影响界面能量传递,从而调控沸腾核化行为.当壁面浸润性越强时,流体吸收的能量越多,因而更加易于核化的发生.综上所述,微纳尺度界面效应影响突出,使得微纳相变具有显著区别于常规尺度的行为特点.尽管对于纳米尺度下核化相变的研究已经取得了一定成果,但是目前的研究手段多数都是在初始时刻给定系统一个过饱和状态,最终达到一个稳定型态,整个研究过程类似等温系统中的空化反应,对于由壁面传热产生热纳米气泡的核化生长过程,仍然缺乏完整深入的研究,未能全面揭示固-液界面效应在沸腾相变过程中所起的作用.此外,不同学者对壁面浸润性与气泡核化之间的内在联系经常会持有相反的意见.因此,关于壁面浸润性对液体核化沸腾的影响还有待进一步验证分析.本文利用分子动力学方法模拟了纳米尺度下液体在不同浸润性壁面发生异质核化沸腾的完整过程,并着重分析探讨了固体壁面浸润性对气泡核化生长的作用机制.分析两者之间的关系,有助于加强对纳米尺度下气泡核化机理的理解,同时能为实际应用提供可靠的理论支撑.本模拟采用开源分子动力学模拟软件LAMMPS实现,原子位型实现可视化采用VMD软件.2 物理模型及模拟细节图1为模拟系统分别在初始、核化以及终了状态的分子模型xz平面分布图,y方向与xz平面垂直.本文模拟的是二维气泡的核化过程,模拟体系尺寸为Lx× Ly×Lz=172.9σ×5.76σ×461.2σ(σ为流体氩原子之间的尺寸参数),x和z方向的尺度显著大于y方向.系统沿着x,y方向均采用周期性边界条件,z方向为固定边界条件.固体壁面原子按照面心立方(FCC)晶格排列,晶格常数为1.15σ,其(100)晶面与流体原子接触,共有29100个固体原子.壁面厚度d=4.61σ,纳米凹槽的深度h=17.29σ,宽度w=18.45σ.固体壁面最外两层原子固定不动,作为边界壁来维持系统的稳定.对其余固体原子施加弹簧力作用,使其在初始位置附近振动,本文中采用的弹簧系数为3249.1ε·σ−2(ε为流体氩原子之间的能量参数).沿着z方向,流体氩原子分为两部分被置于固壁间,在上下侧液膜之间有一段真空区域.靠近下壁面流体液膜的厚度为115.29σ,上侧液膜厚度为11.52σ.初始氩原子按照FCC晶格排列方式布置,晶格常数为1.72σ,共有95035个流体原子.图1 模拟系统在(a)初始、(b)核化和(c)终了状态的分子模型x-z平面图Fig.1 .Molecular distribution in x-z plan of system atthe(a)beginning,(b)nucleation,and(c)f i nal period.流体氩原子之间的相互作用采用Lennard-Jones(L-J)势能模型,表达式为式中r为原子间的距离;流体氩原子之间的尺寸参数σ=0.3405 nm,能量参数ε=1.67×10−21J;原子质量m=6.69×10−23g.固体原子之间的相互作用也采用L-J 势能模型,σs=0.2475 nm,εs=8.35× 10−20J.固-液之间的势能作用通过对L-J势能模型进行修正[22]:式中由Lorentz-Berthelot守则得到能量参数εsl=尺寸参数σsl=(σs+ σl)/2, 下标s表示固体,l表示流体.调节能量系数α与尺寸系数β的值可以得到不同的浸润性.本文算例参数设置分别为α=0.14,β=0.6,0.7,0.8,0.9,1.0及α=0.2,β=1.0,在模拟过程中势能截断半径为3.5σ.超过此距离的原子,其相互作用忽略不计.采用Velocity-Verlet算法求解运动方程,时间步长取为0.0023τ,其中为特征时间,m为质量.在模拟过程中首先对整个系统采用正则系综(NVT),维持其温度为恒定值kB为玻尔兹曼常数,运行100万步,使系统达到平衡后撤掉系统整体温度热浴,仅对壁面施加温度控制,将下壁面温度升高到上壁面温度降低至流体原子采用微正则系综(NVE).根据固-液壁面浸润性,算例运行时间在40—600万步范围内,观察流体的核化轨迹.本文为了直观展示流体被壁面加热发生核化的过程,忽略了控制初始温度阶段的时间步统计,直接从加热阶段开始记录时间.在本文中,为了观察气泡在核化过程中的密度以及温度变化,将流体核化区域沿着z 方向划分为n层,第k个切片层(1 6 k 6 n)在第JStart到第JEnd内时间段内的无量纲粒子密度为式中Nk为第k层的液体原子数目;z为各液体分层的厚度;A为液体计算区域在xy 平面的面积,A=Lx×Ly.第k个切片层(16 k 6 n)在第JStart到第JEnd内时间段内的温度为式中α代表x,y和z三个方向;为粒子沿着α方向的热运动速度.根据原子携带的能量和其具有的速度可获得通过流体的热流密度,热流密度的微观表达采用(5)式计算:式中V为系统的容积;N为流体原子数目;ei为每个原子的能量,包括动能和势能的总和;Fij为第i个原子受到来自与第j个原子之间的相互作用力;vi为第i个原子的速度;rij为第i个原子与第j个原子之间的距离.3 结果与讨论通过调节固-液势能参数来改变壁面浸润性,图2表示两个粒子间的无量纲势能与相互作用力随无量纲距离的变化关系,Φ为势能,F为相互作用力.图2(a)中势阱深度反映固体原子对流体原子的束缚强度,势阱越深流体原子越不容易挣脱固体原子的束缚.当吸收的热量不足以克服势能壁垒的限制时,流体原子将在其平衡位置附近振动,呈现出类固体排列方式.图2(b)中无量纲力为正值时,固-液原子之间相互排斥;无量纲力为负值时,固-液原子之间相互吸引.由图2可见,当α一定时,β越小,固-液之间的作用力越弱,壁面浸润性更趋向于疏水性;当β一定,α越大,固-液之间的作用力越强,壁面浸润性越趋向于亲水性.上述结论与文献[22]的模拟结果一致.本文研究对比不同浸润性壁面处气泡的核化生长过程,可以用纯物质T-ρ相图分布中的状态点来观察液体氩的核化状态.从气泡核化过程可知,气泡核化位置沿着z方向主要分布在0—90σ之间.因而,将此空间范围设置为成核区域,统计该区域内流体的平均数密度和温度.每1000步输出一次模拟结果.由图3得知,成核区域的原子数密度随着流体温度的升高逐渐减小,从初始气液饱和态逐渐过渡到稳定过热态,表明本文的成核条件符合核化动力学规律.此外,需要统计远离液体核化区域的蒸汽相空间内的温度与压力,以便确定沸腾发生的状态.监测沿着z方向250σ—300σ气相区域内的温度与压力,发现气相温度一直维持在左右,压力为其相应的饱和压力0.007654εσ−3.因此,本文着重研究过饱和沸腾.图2 两个粒子间的无量纲(a)势能与(b)相互作用力随无量纲距离的变化关系Fig.2 .Dimensionless(a)potential energy and(b)interaction force depends on the distance between two particles.图3 核化区域热力学状态点及饱和线与包络线相分布图Fig.3 .Thermodynamic state point and phase diagram with coexistence curve and spinodal curve in nucleation region.3.1 气泡核化过程图4 不同壁面浸润性下异质核化过程(a)α=0.14,β=0.6;(b)α=0.14,β=0.7;(c)α=0.14,β=0.8;(d)α=0.14,β=0.9;(e)α=0.1 4,β=1.0;(f)α=0.20,β=1.0Fig.4 .Heterogeneous nucleati on process with dif f erent wallwettability:(a)α=0.14,β=0.6;(b)α=0.14,β=0.7;(c)α=0.14,β=0.8;(d)α=0.14,β=0.9;(e)α=0.14,β=1.0;(f)α=0.20,β=1.0.图4(a)—(f)表示气泡在不同浸润性壁面处发生异质核化的过程.由图可见,给壁面加热一段时间后,气泡胚核首先在凹槽内部形成,其体积随着壁面传热量的增多而增大.当气泡足够大露出穴面后,开始向两个方向生长,一方面向上膨胀,气泡高度增大;另一方面气泡向侧面铺展扩张,三相接触线逐渐向外延伸.由于沿着x,y方向为周期性边界条件,当气泡生长到一定程度会引起边界聚合,在壁面处形成气膜,推动液膜向上运动.由图4可知,随着α与β的增大,固-液相互作用增强,达到气泡初始核化所需过热度的时间缩短,即核化等待时间减少.当固-液势能参数为α=0.14,β=0.6时,固-液相互作用最弱,气泡发生核化的等待时间约为7360τ;固-液势能参数取α=0.2,β=1.0时,壁面浸润性最强,核化等待时间仅276τ.根据图3不同浸润性壁面处核化区域过热状态的演化规律,体系进入包络线区域的快慢程度有所差异,即核化等待时间不同.当势能参数为α=0.14,β=0.6时,状态曲线在亚稳态过热区紧贴饱和线缓慢上升后才进入稳态过热区;当势能参数为α=0.14,β=1.0时,则迅速进入稳态过热区域,气泡发生核化更快.图5给出不同研究结果中气泡约化核化时间随壁面浸润性的变化关系,CA表示接触角.气泡核化时间包括核化等待时间与气泡生长时间.由于不同尺度下,气泡核化时间的数量级存在很大的差别,本文为方便比较不同尺度下气泡核化时间随壁面浸润性的变化趋势,均采用约化比值.Phan等[23]与Gong和Cheng[24]的研究结果分别以接触角为43.8o与28.1o时的气泡核化时间为参考值,对气泡核化时间进行约化.本文的模拟结果则将势能参数为α=0.14,β=0.6的气泡核化时间作为参考值,约化核化时间取为1.Phan等[23]采用实验方法研究水在100 mm×5 mm纳米涂层壁面上的沸腾核化,发现随着壁面浸润性的增强,气泡脱离直径增大,核化时间增长,而气泡脱离频率却降低.Gong和Cheng[24]使用格子玻尔兹曼方法探究介观尺度下固体表面浸润性对液体饱和沸腾传热特性的影响机制.综上可知,在常规尺度范围,壁面接触角越大,即壁面浸润性越弱,气泡核化时间越短,越容易核化.在纳米尺度下,α与β值越大,壁面浸润性越强,核化等待时间与气泡生长时间均缩短,核化周期减小,反而更有利于核化发生.这是由于尺度效应的存在,导致核化规律在不同尺度下呈现出截然相反的变化趋势.图5 气泡约化核化时间与壁面浸润性的关系Fig.5 .Relationship between reduced nucleation time and wall wettability.图6 流体沿着z方向的密度分布图 (a)势能参数为α=0.14,β=1.0;(b)势能参数为α=0.14,β=0.6Fig.6 .Density prof i le of argon along zcoordinate:(a)Potential energy parameters is α =0.14,β =1.0;(b)potential energy parameters is α =0.14,β =0.6.在统计流体密度分布时,将整个系统内流体区域沿着z方向均匀划分层,每层的高度是2.3σ.图6表示不同浸润条件下流体沿z方向的密度分布随加热时间的变化趋势.图中红色虚线表示固-液界面位置.不同浸润条件下,其流体数密度分布规律类似.在初始时刻,液体区域的密度ρσ3维持在0.78附近.随着加热时间增加,气泡胚核在近壁区核化生长,核化区域的流体数密度逐渐减小.直到气泡消失,在壁面处形成气膜且液体层脱离壁面后,靠近高温壁面处的流体数密度接近气相密度.对比图6(a)与图6(b)流体数密度变化规律,可以看出壁面浸润性越强,核化区域靠近密度减小越快,反映出气泡核化生长速率随壁面浸润性的增强而增大.为了对比不同浸润条件下的核化状态,选取同一个时刻的流体数密度分布.图7表示时间为690τ时流体沿着z方向的数密度分布.结合上述核化过程原子位型图,近壁核化区域的流体有3种状态,即过热液体态、气泡核化态、过热气体态.势能参数为α=0.14,β=0.6时核化区域流体氩的数密度最大.保持α=0.14不变,增大β值,当β=0.7和0.8时,紧贴壁面处流体数密度有轻微的减小,几乎维持不变;当β=0.9时,近壁处流体数密度呈大幅度下降趋势,由图4可知,此时气泡胚核露出穴面;当固-液势能参数为α=0.2,β=1.0时,流体的密度已经接近气相的密度值,液膜脱离壁面,在壁面附近形成气膜.综上所述,在浸润性强的壁面处液体核化时间短,气泡核化速率快,气泡胚核体积更大.因此,浸润性强的表面更有利于气泡成核.图7 时间为690τ时氩流体沿着z方向的数密度分布Fig.7 .Number density profi le of argon along z coordinate at 690τ.3.2 气泡生长规律通过计算核化气泡的等效半径来定量分析壁面浸润性对气泡核化生长的作用.由于本文模拟的是二维气泡,因此气泡体积相当于在xz平面上的面积,为了计算气核的等效半径,将液氩核化区域在xz平面内划分成二维小网格,每个网格的尺寸为2σ×2σ,每100步统计一次网格内的流体原子数密度.将液体数密度与蒸汽数密度之和的1/2作为判断网格是气态还是液态的阈值[25].当网格内的无量纲原子数密度小于0.39时,将此网格标记为气态;当网格内的无量纲原子数密度大于0.39时,则认为此网格为液体.然后将核化区域内所有气态网格叠加起来得到气泡的二维面积S∗,计算气泡的等效半径[26]:图8表示气泡等效半径随加热时间的变化关系.由图8可见,不同浸润性壁面处的气泡生长规律类似,在初始加热阶段,液体没有发生核化,气泡的等效半径为0;当流体吸收的热量聚集到一定程度时,近热壁区发生核化,气泡等效半径开始增大.从图8可以看出,当气泡核化进入稳定生长阶段,气泡等效半径几乎遵循线性增长规律,此过程中气泡等效半径的生长速率随着壁面浸润性的增强而显著提升,势能参数为α=0.20,β=1.0时的气泡等效半径约等于势能参数为α=0.14,β=0.6的3.27倍.值得注意的是,本文将气膜在壁面处形成的时间记录为气泡停止生长的时间,即气泡等效半径变化曲线的统计结束时间.由图8可知,图中每条曲线终止时刻的气泡等效半径值有所差异,其随着壁面浸润性的增强反而减小.结合图4(e)—(f)分析其原因:一方面是壁面浸润性越强,气泡胚核不止在凹槽产生,还会在平壁面处形成,进而多个气核迅速聚合形成气膜;另一方面,流体原子在浸润性强的壁面形成气泡后,蒸汽与固壁间的液体膜更容易蒸发相变,三相接触线沿着x方向迁移,气泡铺展直径增大.当壁面浸润性弱时,气泡反而更倾向于向上生长.因此,浸润性越强的壁面在液膜脱离壁面时气泡的体积与等效半径越小.图8 气泡等效半径随加热时间的变化关系Fig.8 .Relationship between bubble equivalent radius and heating time.3.3 核化传热机理为研究壁面浸润性对气泡核化生长的作用机理,需要从固-液能量传递方面来进行分析.图9表示靠近壁面处的流体沿着z方向的温度分布随时间的变化关系.热量通过固-液界面扩散到流体区域,近壁区的液温先升高,在液体区域形成温度梯度,直至流体内部的温度呈现线性分布.当固-液势能参数为α=0.14,β=1.0时,近壁区流体温度几乎在920τ就达到线性分布,固-液界面温度约为,固-液温度阶跃约为. 而固-液势能参数为α=0.14,β=0.6时,其需要约2760τ才达到线性分布,此时,固-液界面处的流体温度值约为,固-液温度阶跃约为. 据此推断,界面热阻随固-液势能作用的减弱而增大,导致通过固-液界面传递热量的效率降低,进而使得流体温度升高达到线性分布的时间越来越长,对气泡的核化生长时间产生了显著影响.需要说明的是,图9中在−20σ—0范围内流体温度随加热的进行出现减小现象,这是由于此范围为凹槽中的液体原子核化变为气体,粒子数大量减少,造成统计误差.根据核化动力学,当活化分子团能量积累到临界活化能后,才能形成稳定的气泡并开始生长.由图9可知,浸润性强的壁面传热效率高,流体温度快速升高,明显高于浸润性弱的情形,使得核化区域液体能量迅速累积达到临界活化能,满足核化条件.而且气泡在生长过程中周围过热液体温度越高,越容易蒸发相变.该结论也可从核化区域流体总势能变化规律得到验证.图10表示核化区域流体总势能随加热时间的变化规律.值得注意的是,图中势能值为负值.初始加热阶段,气泡尚未形成稳定的胚核,液体原子仍紧贴壁面.当势能参数为α=0.2,β=1.0时,固-液作用最强,核化区域的流体总势能值最小.与之相反,当势能参数为α=0.14,β=0.7时,其总势能值最大.随着加热进行,前者的势能值显著增大,反而高于后者,促进了气泡的核化生长.此外,壁面势能参数α与β越大,能垒越深,固-液相互作用越强,液体原子越难挣脱固体壁面束缚,导致气泡胚核的初始核化位置随浸润性变化而有所差异.如图4所示,气泡胚核在纳米凹槽内初始形成阶段,壁面浸润性越弱,越趋于在壁面处形成;而浸润性越强,则气核在偏离固体壁面的液体中央形成.在气泡生长后期,贴近壁面处的液膜受热蒸发.对于浸润性强的壁面,其热阻小,近壁面处液膜温度高,液体更容易相变成气体.综上所述,尽管能垒越深,紧贴壁面的液体原子越难以挣脱束缚,但是近壁区流体吸收能量增多,明显利于形成气泡胚核,只是紧贴壁面的流体原子受到固体壁面的束缚程度不同,导致初始形核位置有所差异.图9 核化区域氩流体沿着z方向的温度分布 (a)势能参数为α=0.14,β=1.0;(b)势能参数为α=0.14,β=0.6Fig.9 .Temperature prof i le of argon along zcoordinate in nuclear boiling region:(a)Potential energy parameters is α =0.14,β=1.0;(b)poten tial energy parameters is α =0.14,β =0.6.为进一步探究核化过程中热量传递的规律,图11给出气泡核化区域流体的温度随时间的变化规律.由图可知,壁面浸润性越强,通过界面传递的热量越多,流体温度升高越快.在气泡核化等待阶段,底板传递的热量直接加热近壁区液体,便于能量聚集使其发生核化.当液体发生核化,气泡生长到一定程度,部分底板与气体直接接触,气固直接传热效率较低,气泡生长核化的热量主要来源于周围高温液体.如图11温度曲线所示,当核化区域流体温度上升到一定程度开始下降,这是由于底板传给液体的热量不足以弥补气泡边界液体蒸发相变及气泡体积膨胀所需能量,核化区域温度反而降低.当势能参数为α=0.2,β=1.0时,核化区域温度几乎没有下降过程,在1023τ时刻温度又以不同速率迅速升高;而α=0.14,β=1.0,0.9,0.8,0.7时则分别在。
声空化与声致发光研究进展陈伟中(近代声学教育部重点实验室,南京大学声学研究所,南京 210093)1 引言声波在液体中传播,在时空上产生压力起伏,出现低于静态压力的负压现象。
在液体的负压区域,液体中的结构缺陷(空化核)会逐渐成长,形成肉眼可见的微米量级的气泡,这就是声空化(Acoustic cavitation)[1]。
声空化强度不仅与驱动声压有关,还与液体中的空化核数量有关。
由于表面张力的作用,空化泡的形状几乎是球形的。
描述它的动力学模型是著名的Rayleigh气泡动力学方程[2]。
空化泡的运动具有明显的非线性特征,具体表现为缓慢的膨胀和急剧的压缩。
通常声空化泡的半径压缩比可达102的量级,体积压缩比就是106量级,因此它具有很高的聚能能力。
在压缩至最小半径前后,空化泡内部有数千度的高温和数千个大气压的高压。
这是超声清洗、超声粉碎、声化学等一系列声空化应用的基础。
当继续增大驱动声压,空化泡内部的温度压力继续上升,会导致光的辐射,这就是上世纪30年代发现的声致发光(Sonoluminescence,SL)现象[3]。
由于当时的声致发光来自大量随机产生的空化泡的破裂发光,故也称多泡声致发光。
多泡声致发光的气泡动力学特征很难测量,直到1992年,Gaitan等人结合声悬浮在充分去气的水中,实现了空间上定位、时间上周期的单一气泡的声致发光,即单泡声致发光[4],相关的研究才取得重要进展。
和多泡声致发光的区别在于,它是一种稳态的振荡发光,不是破裂发光。
空间定位的稳态单泡发光为实验测量提供了必要的条件,人们可以测量气泡的动力学演化过程,可以测量光子的各种关联。
由于在早期的单泡声致发光实验中,没有测到多泡声致发光中的原子线状光谱,所以,人们认为多泡和单泡声致发光在机理上是不同的[5]。
直到2001年,人们在极暗的(Extreme dim)声致发光中开始观察到原子线谱[6]。
最近,人们在抖动的(Moving)声致发光中,也观察到了Ar原子特征谱线[7]。
非均匀润湿性表面的气泡动力学特性孙远志;邬智宇;张伟;姜家宗【摘要】为探究不同润湿性表面气泡动力学特性,本文采用FLUENT软件中VOF 模型对四种不同的微结构下气泡的成长、脱离进行了数值模拟,分析了气泡脱离频率、生长速度、体积、气泡最高点等,获得了不同接触角匹配特性及微结构对气泡动力学特性的影响规律.数据分析表明,对于具有微结构的非均匀润湿表面,凹穴出口外部的表面润湿特性对气泡脱离起主导作用,凹穴结构本身的几何结构和润湿性对气泡脱离的影响相对较弱.【期刊名称】《节能技术》【年(卷),期】2019(037)002【总页数】5页(P166-169,173)【关键词】气泡动力学;润湿性;微结构;亲水性;疏水性【作者】孙远志;邬智宇;张伟;姜家宗【作者单位】华北电力大学能源动力与机械工程学院,北京102206;华北电力大学能源动力与机械工程学院,北京102206;华北电力大学能源动力与机械工程学院,北京102206;低品位能源多相流动与传热北京市重点实验室,北京102206;华北电力大学能源动力与机械工程学院,北京102206【正文语种】中文【中图分类】TH703;TK114润湿现象广泛存在于自然界和人类的生产生活中,基于润湿性调控的热质输运过程强化技术已成为工程热物理领域的研究热点之一,如通过对石油管道进行疏水性处理,可减少管道内的流动阻力;沙漠中采用超疏水表面作为空间集水器的集水面;在相变传热系统中,采用疏水表面可降低沸腾起始温度,提高换热系数;采用亲水表面可提高临界热流密度等。
张震[1]对于换热管转子的数值模拟得出了转子可以强化传热。
吕吉锋[2]针对换热器流动不均匀进行了数值模拟,并优化了通道,改善了流动的不稳定性。
Xu[3]等使用VOF方法对气体微通道内液滴的动力学行为,做了系统的模拟研究。
杨燕[4]采用VOF模型,对微重力下矩形通道的池沸腾现象进行数值模拟。
Subrat Das[5]等人研究了倾斜表面上表面张力对气泡沿表面上升的影响。
核态池沸腾中气泡生长和脱离的动力学特征——气泡的脱离
直径与脱离频率
杨春信;吴玉庭;袁修干;马重芳
【期刊名称】《热能动力工程》
【年(卷),期】1999(14)5
【摘要】在前人工作的基础上提出了表征核态池沸腾中气泡脱离和生长过程的特征时间和特征尺度,并进而得到了气泡生长时间和气泡脱离直径的通用关系式,应用传热学类比方法建立了计算气泡脱离直径的一般公式。
本文的研究结果与前人的实验结果甚为相符。
【总页数】4页(P330-333)
【关键词】核态沸腾;气泡;脱离直径;脱离频率
【作者】杨春信;吴玉庭;袁修干;马重芳
【作者单位】北京航空航天大学;北京工业大学
【正文语种】中文
【中图分类】TK124
【相关文献】
1.微重力池沸腾过程中的气泡热动力学特征研究 [J], 吴克;赵建福;李会雄
2.乙烷池内核态沸腾气泡脱离直径 [J], 陈汉梽;姚远;公茂琼;陈高飞;邹鑫;董学强;沈俊
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5.核态池沸腾中气泡生长和脱离的动力学特征——气泡动力学研究回顾 [J], 杨春信;吴玉庭;袁修干;马重芳
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Computational Fluid Dynamics (CFD)Modeling of Bubble Dynamics in the Aluminum Smelting ProcessKaiyu Zhang,‡,†Yuqing Feng,*,†Phil Schwarz,†Zhaowen Wang,‡and Mark Cooksey §‡School of Metallurgical Engineering,Northeastern University,Shenyang,China†CSIRO Mathematics,Informatics and Statistics,Clayton,Victoria 3169,Australia§CSIRO Process Science and Engineering,Clayton,Victoria 3169,AustraliaThe Hall −He r oult process is the only commercial process for producing aluminum from alumina.1In an aluminum reduction cell,alumina is fed to,and dissolved in,a molten bath of cryolite at approximately 970°C in which several carbon anodes are submerged.Electric current is fed between the anodes and an underlying cathode to cause electrochemical reduction of the alumina reactant to aluminum which settles onto a pool lying over the cathode.CO 2gas bubbles aregenerated by the reaction at the anode,which causes recirculation flows as a result of the gas bubbles moving up through the molten cryolite (the bath)under the in fluence of buoyancy.Because cryolite will dissolve most potential wall materials,a layer of frozen cryolite must be formed on the walls of the vessel to contain the bath,and this requires the achievement of a delicate heat balance in the cell,over which the recirculatory flows in the bath have an important in fluence.The gases are generated at the bottom surface of the anodes in a continuous manner.Thus,the anode bottom surfaces are covered with a layer of bubbles right beneath the anode bottom surface.The bubble area coverage can vary from 30to 90%,2−4which leads to an extra voltage drop.According to Haupin,5the extra voltage drop in the electrolyte due to the presence of gas bubbles is in the range 0.15−0.35V.The bubble motion beneath the anodes also introduces waves into the bath −metal interface,voltage fluctuations,and high local current density,and indirectly results in instabilities of the magnetic field.Moreover,the global scale bath flow and alumina mixing are closely related to the bubble behavior.Therefore,a detailedunderstanding of the bubble dynamics and the resulting bath flow is important to quantitatively assess its e ffect on cell performance.molten salt bath)restricts direct observation of bubble behavior in industrial cells.Studies of bubble behavior in industrial cells,laboratory cells,and physical models have been reviewed by Cooksey et al.6There is good evidence that the bubble layer thickness is at least 5mm in industrial cells,5and similar in laboratory cells.6−8In order to observe the bubble dynamic behavior at a scale typical of industrial cell geometries,room temperature laboratory models have been used.9−28Trans-parent materials such as Plexiglas are used to construct the cell,and a room temperature liquid is used to replace the cryolite bath.As listed in Table 1,various gas −liquid systems have been used to represent the CO 2−cryolite system,such as NaOH solution,9CuSO4solution,10air −oil −water,11or simply air −water.12−28Since the bubble formation is quite complex andthe motion is controlled by many factors,such as surface tension,contact angle,anode shape,and even the roughness of the surface,none of those systems can closely match all the factors of the real system.The standpoint for using the air −water system is that the kinematic viscosity of water is verysimilar to that of cryolite (1.005×10−6m 2s −1for water and 1.43×10−6m 2s −1for cryolite).This will lead to a similar liquid flow dynamics as long as the same volume of gas is used but might not have relevance on the similarity of bubble dynamics.Special Issue:Multiscale Structures and Systems in Process EngineeringReceived:December 15,2012Revised:May 7,2013Accepted:May 7,2013Published:May 7,2013According to a mathematical simulation,22,23the bubble morphology mainly depends on the liquid’s Morton number (Mo),a dimensionless number defined as((gμl4(ρl−ρg))/ (ρl2σ3)),where g is the gravitational acceleration,μis the viscosity,ρis the density,andσis the surface tension.The subscripts g and l stand for the bubble gas and the surrounding liquid,respectively.As shown in Table2,the Morton number for the air−water system is very different from that for the CO2−cryolite system.The Eo t vo s number((g(ρl−ρg)L2)/σ) is often used together with the Morton number to characterize the shape of bubbles or drops moving in a surroundingfluid or continuous phase.L refers to the characteristic length,e.g., bubble size or diameter(d b),in this calculation.The Eo t vo s numbers are provided in Table2as well.Because the two systems have a similar ratio of the buoyancy force to the surface tension(i.e.,1.36×105for an air−water system and1.56×105 for a CO2−cryolite system),consequently,the Eo t vo s number of the air−water system is very similar to that of the CO2−cryolite system at a given bubble size.Over the last two decades,with advances in computing speed,parallelization technology,improved software,and multiphase algorithms,computationalfluid dynamics(CFD) has progressed substantially.The advantage of CFD modeling is not only that it provides a cost-effective way to gain a detailed understanding of the complex process but also that it is sometimes the only research tool due to measurement challenges in a real process,such as the high temperature and corrosive environment found in aluminum electrolytic cells. Depending on the application and information required, gas−liquidflows such as those encountered in aluminum reduction cells can be modeled at different length scales:at the micro or individual bubble scale or at the macro level by local averaging.The former approach tracks the interfaces around each bubble,and detailed transient bubbling behavior can be obtained.The micro model is very useful to the detailed elucidation of the governing mechanisms of these complex processes but requires large computing power,which means that it cannot presently be directly applied to industrial-scale simulations.The macro model represents theflowfield averaged over time,and hence,steady state equations are often solved.The model requires less computing power,but the accuracy of a macro model depends on the accuracy of constitutive correlations that describe the local averaging of the micro scale information,such as bubble-induced turbulence and the turbulent dispersion force.In the past,physical models have often been used to validate the CFD model either based on flow patterns29or detailed liquid velocity and turbulence30 obtained using particle image velocimetry(PIV)technology.31 The validated CFD model is then extended to simulate the exact scale,properties,and operating conditions of the real system.32,33The question lies in whether the CFD model, validated based on the air−water system,can be directly used for another system or ing a multiscale modeling approach,the detailed micro modeling information of a real system,such as the bubble dynamics in an aluminum reduction cell,can be used to build constitutive correlations to improve macro modeling accuracy.This multiscale modeling approach is believed to be promising and powerful,and has received increasing interest in the study of complex multiphaseflow systems.34−39The individual bubble model has recently been used to study an aluminum smelting system with different focuses. Einarsrud11studied the effect of detaching bubbles on aluminum−cryolite interfaces;Das et al.20investigated the principal characteristics of the detachment and sliding mechanism of gas bubbles under an inclined anode;Wang and Zhang40studied the effect of the anode edge on bubble release.In our own recent work,41the relationships between the air−water system and CO2−cryolite systems have been checked.The assessment was focused on the bubble dynamics during the bubble sliding process under the anode only. This paper aims to further evaluate the relative effect of bubble sizes and simulation systems(air−water vs CO2−cryolite)during the bubble releasing process at the anode edge and the bubble rising process in the side channels.In additionTable1.Analogous Systems to CO2−Cryolite Reported inthe Literaturebath liquid gas metal referencesNaOH solution oxygen none ref9Bluestone solution oxygen none ref10light mineral oil air water ref11water air none ref12ref13ref14ref15ref16ref17ref18refs24−27ref28oil air none ref14water−0.5pct butanol air none ref15propaneiol−water air none ref19isopropanol−water air none ref19glycerine−water air none ref19olive oil air none ref20water air organic ref21Table2.Physical Properties of the CO2−Cryolite and the Air−Water Systemsproperties CO2at960°C cryolite at960°C air at25°C water at25°C density(kg/m3)0.42100 1.225998.2 dynamic viscosity(kg/m·s) 1.37×10−5 3.0×10−3 1.789×10−5 1.003×10−3 kinematic viscosity(m2/s) 3.43×10−5 1.43×10−6 1.46×10−5 1.005×10−6 surface tension coefficient(N/m)0.1320.072contact angle(deg)120°60°Morton number 1.645×10−10 2.664×10−11Eo t vo s number at different bubble sizes0.0113m19.90417.2940.0226m79.62669.1750.0339m158.624137.820to the study of bubble dynamics,the bubble-induced liquid motion is quanti fied as well.The investigation is based on similar simulation conditions to those used in our previous study.41Also,we identi fied some errors in the data processing in our earlier work,41so we repeated the simulation in the present study with an optimized gas injection method.Hence,the present work amends and extends the research presented in our previous publication,41and provides updated information and further discussion.2.CFD MODELING METHOD 2.1.Model Description.Simulation of bubble flow phenomena requires accounting for the irregular deformation of the interfaces and free surfaces,which has been a challenging task in the numerical modeling of multiphase flow over the past few decades.42Generally,a free surface flow can be modeled by the interface-tracking method 43or interface-capturing meth-od.44The interface-tracking method uses interface-fittedmoving grids,while the interface-capturing method uses fixedgrids and solves an additional equation to locate the freesurface.Given that the free surface can change its topology due to bubble breakage,overturning,and splashing,the grid mightnot be able to deform to such an extent.The simulationdomain would need to be remeshed,which is computationallyintensive.The interface-capturing method is commonly used.There have been many kinds of interface-capturing methodsdeveloped,such as the level set,45height of liquid,46and volume of fluid (VOF)methods.47In addition to the traditional CFD approach,the lattice Boltzmann (LB)model has been increasingly used to study interface flow due to its capability to model interfaces.48Figure 1.Geometry and mesh information for the CFD model:(a)geometry;(b)initial meshes;(c)re fined meshes around the bubble (left)and air −liquid interfaces using the mesh adaption method.In this study,the VOF method in the CFD software (ANSYS/Fluent)was used.Details of this method are well documented in the literature.49Here,only the key governing equations are brie fly provided.The VOF method is based on the fact that two or more fluids are not interpenetrating.For each phase,a variable is introduced to record the volume fraction of the phase in each computational cell or control volume.The volume fractions of all phases sum to unity at each cell.The fields for all variables and properties are shared by the phases and represent volume-averaged values,as long as the volume fraction of each of the phases is known at each location.Thus,the variables and properties in any given cell are either purely representative of one of the phases or representative of a mixture of the phases,depending on the volume fraction values.Each phase agrees with the mass conservation equation,given by αα∂∂+∇·⇀=t v ()0(1)where αis the phase volume fraction and t and ⇀v represent the time and velocity,respectively.In Fluent,the equation will not be solved for the primary phase (the liquid phase in current model setting).The primary phase volume fraction will be computed on the basis of the following constraint:αα+=1g l (2)As all variables and properties are shared by the phases and represent volume-averaged values,a single momentum equation is solved,with the following formulation:ρρμρ∂⇀∂+∇·⇀⇀=−∇+∇·∇⇀+∇⇀+⇀+⇀v t v v P v v g F ()()(())T (3)where P is the pressure term and ⇀F represents the surface tension force.The superscript T denotes the matrix transpose operation.The mixture density and viscosity is based on the volume averaging,given by ραραρ=+g g l l (4)μαμαμ=+g g l l (5)The simulation accuracy is largely dependent on the method of interpolation near the interfaces,which a ffects the convection and di ffusion fluxes through the control volume faces in eqs 1and 3as well as the surface tension force (⇀F )that is included as a body force in eq 3.The geometric reconstruction scheme and a mesh adaption method are adopted to capture the detailed interface shapes.2.2.Simulation Conditions.While there are no technical di fficulties in simulating the three-dimensional (3D)motion of bubbles,the limitations of simulation time and computing cost mean that the investigations are conducted using a two-dimensional (2D)geometry.The 2D study may not fully represent the real bubble behavior,which is indeed three-dimensional,but will give a similar trend to the 3D study.The 2D geometry might be acceptable for comparison purposes as long as the air −water and CO 2−cryolite systems have the same simulation conditions.Figure 1a shows the simulation geometry that represents a slice of a typical commercial Hall −He r oult prebake cell;note that the geometry is not related to any speci fic cell design.The distance between anode and cathode is 50mm.The space or gap between the anode and cathode is conventionally called the anode −cathode distance (ACD)in the aluminum smelting industry.The space between the anode and the side vertical wall is called the “side channel ”,which is set at 240mm in width.An inclination of 1.5°(as might occur because of anode consumption)is set to help the release of bubbles.The formation of bubbles in an aluminum reduction cell is very complex,and the detailed bubble formation mechanism is not fully understood.It is believed that di fferent sized bubbles exist in the cell.The large bubbles move faster than the small bubbles.The bubbles will coalesce to form larger bubbles when the large bubbles catch up with the small bubbles.The bubbles will break up when the bubble size grows too large.To model the bubble generation more realistically,a CFD model fully coupled with thermal and electric models with chemical reactions is required.In this study,a simple gas generation method is used.The gas is injected through the inlet that is located at the anode bottom surface.The inlet is 5mm in length with the center 25mm from the left side.The inlet velocity is 0.25ms −1,and the injection time is set to 0.08,0.32,and 0.64s to form initial bubbles with equivalent diameters of 11.3,22.6,and 31.9mm,respectively.These three sizes are used on the basis of experimental observations.12,18,28The bubbles undergo various types of distortion under the anode and break up in the side channel.For convenience of discussion,the bubble size refers to the initial introduced bubble size,e.g.,the equivalent diameter of the 2D bubble.Following the injection of the speci fied amount of gas,the inlet boundary condition reverts to a nonslip wall boundary condition.The simulation cases are presented in Table 3.To capture the bubble surface,the mesh size should be substantially smaller than the bubble size.The solution-adaptive mesh re finement feature of ANSYS/Fluent allows the user to re fine and/or coarsen meshes based on geometric and numerical solution data.Figure 1b shows the initial mesh without re finement functions,which consists of 1624quadri-lateral cells.During the simulation,the hanging node adaption method 49is used,which allows more accurate capturing of the detailed interface between gas and liquid,and signi ficantly reduces computing time.The mesh is dynamically re fined at the interface,and coarsened back when the interface moves out of that region.The left part of Figure 1c shows the meshes over a bubble in the bath under the anode,and the right part shows the meshes at the gas −bath interface after mesh adaption at an instance of the simulation.The maximum cell surface is set as 5×10−6m 2,and the minimum cell surface is set as 6.0×10−9m 2.The initial time step is set to 5×10−5s.The ANSYS Fluent solver will re fine the time step based on the input for the maximum Courant number.The Courant number is a dimensionless number that expresses the ratio of the simulationTable 3.Simulation Cases with Di fferent Bubble Sizes system equivalent bubble diameter (m)case 1air −water 0.0113case 2CO 2−cryolite 0.0113case 3air −water 0.0226case 4CO 2−cryolite 0.0226case 5air −water 0.0339case 6CO 2−cryolite 0.0339time step to the characteristic time of transit of a fluid element across a control volume.The global Courant number is set as 0.15in the current simulations.The absolute convergence criteria for continuity and velocity are both set as 10−7.Given that the liquid flow driven by a single bubble is not strong and that the mesh size is fine enough to capture the local recirculation near the bubble region,the flow is treated as laminar flow.3.RESULTS AND DISCUSSION Bubbles demonstrate di fferent behavior in di fferent regions of the cell.In general,the bubble motion can be divided into three periods:bubble sliding under the anode,bubble releasing at the anode edge,and bubble rising in the side channel.The three periods are discussed separately.3.1.Bubble Sliding under the Anode.3.1.1.BubbleMorphology.Following gas injection through the inlet,a singlebubble starts to grow.Once the bubble is su fficiently large,it begins to move along the anode bottom surface toward the higher end of the anode.This sliding motion occurs for the three selected bubble sizes.The induced bubble rapidly reaches a dynamically stable state and moves toward the channel between the anode and the cell wall with various shapes which depend on the bubble size and system.Figure 2shows the bubble morphologies for each case,all of which are after the bubble reaches a dynamically stable state at three instants in time.To be comparable,all cases are plotted at the same scale and in the same location:the left edge is 0.136m from the left side of the full simulation domain,and the horizontal length is 0.445m.When the bubble size is very small,the speci fic surface area,de fined as the total surface area divided by the bubble volume,is large,which implies that a unit volume of gas experience larger surface tension for the smaller bubbles compared to larger bubbles.The bubble tends to a more circular form as the bubble size decreases.The formation of bubble shapes is actually a complex dynamic balance of surface tension,buoyancy force,viscosity friction between liquid and gas,solid wall friction,and contact angle.For all of the simulation cases,the bubble becomes flat where the thickness is less than its length.Thus,bubble shape is quite stable,as di fferent time frames show a similar shape.When the bubble size increases,the bubble simply becomes more flattened,and the bubble tends to form a nonregular shape with a thick head,and a long and thin tail.This trendbecomes more obvious as the bubble size increases.Suchbubbles with thicker head and thinner tail represent amidsection of a large bubble moving under a downward facingsurface and have been well observed in the past studies either in aluminum reduction cells 12,19,22,24−28or more broadly in gravity −current or density −current flow behavior.503.1.2.Bubble Layer Thickness.Figure 3shows the mean bubble thickness for all simulation cases.For both systems,theFigure 2.Bubble morphologies in ACD for simulation cases 1−6at three di fferent times after their dynamically stable states are reached.Case 1:air −watersystem,bubble size 11.3mm.Case 2:CO 2−cryolite system,bubble size 11.3mm.Case 3:air −water system,bubble size 22.6mm.Case 4:CO 2−cryolite system,bubble size 22.6mm.Case 5:air −water system,bubble size 33.9mm.Case 6:CO2−cryolite system,bubble size 33.9mm.All cases are plotted from the same location:the left edge is 0.136m from the left side of the full simulation domain,and the length is 0.445m.(Adapted from ref 41.Copyright 2012The Minerals,Metals &Materials ed withpermission.)Figure3.Mean bubble thickness as a function of bubble diameter and system.(Adapted from ref 41.Copyright 2012The Minerals,Metals &Materials ed with permission.)bubble thickness increases as the bubble diameter increases.At a given bubble diameter,the bubble thickness is larger in the air −water system (∼4−5mm)than that in the CO 2−cryolite system (∼3mm).It is interesting to see that the predicted bubble thickness based on the single bubble model is quite consistent with experimental work with continuous gas injection.5The bubble thickness below flat surfaces has been studied in the past.51−53For a bubble layer under a solid surface,its thickness increases with increasing bubble volume until it reaches a maximum value,then subsequently increases in the volume and slightly decreases the bubble depth until it reaches the limit height.The empirical formulas for the maximum and limiting heights of a stationary bubble under a downward surface were given as follows:51πθπθσρρ=−×−+×−−×−h g (0.19() 1.293()0.053)()max 2l g (6)πθσρρ=×−−×−h g 2(1cos())()lim l g (7)In the above equation,θis the contact angle.Given that the surface inclination angle in this work is very small,the work on flat surfaces is still valid for a comparison with the simulation results.The above equation has been actually used to compare the measured bubble thickness under a slightly inclined surface relevant to aluminum cells.18According to eqs 6and 7,the maximum and limiting heights of CO 2bubbles in molten cryolite are 2.8and 2.5mm,respectively,and the maximum and limiting height of air bubbles in water are 4.9and 4.7mm,respectively.As shown in Figure 3,the simulated bubble thicknesses are in a reasonable range of the empirical correlations developed for bubbles below a flat surface.Closer agreement is not possible,as the simulation demonstrates an e ffect of bubble size,while the empirical correlations do not consider the bubble size e ffect.The simulated bubble thickness from the air −water system is closer to the empirical correlations than the CO 2−cryolite system.Possibly,the empirical correlation is based on the air −water data,and is not directly applicable for the CO 2−cryolite system.In eqs 6and 7,the term (σ/((ρl −ρg )g ))1/2on the right-hand side (RHS)gives a similar value for the two systems,while the coe fficients of this term in each case are functions of the contact angle.This implies that the contact angle plays a dominant role in determining the di fference in bubble thickness between the two investigated systems.Figure 4shows the values of these coe fficients at a wide range of contact angles.As indicated by the slope of the curves,the e ffect of contact angle increases as the contact angle increases.3.1.3.Bubble Sliding Velocity and Drag Coe fficient.The motion of bubbles is quanti fied by their mean velocity at their dynamically stable state.Figure 5shows the mean bubble velocity as a function of the bubble size for both systems.The mean velocity increases as the bubble size increases for both systems.When the bubble size increases,the buoyancy force increases linearly with the bubble volume,while the bubble surface area does not increase proportionally.Thus,the bubble receives less skin friction per volume of gas for larger bubbles;consequently,larger bubbles slide faster than smaller bubbles.For a given bubble size,the bubble velocity is higher for the CO2−cryolite system compared to the air −water system.Thisappears consistent with the bubble shapes:as the bubble thickness is smaller in the CO2−cryolite system,consequentlythere is less resistance around the bubble head.The sliding velocity under an inclined channel has been measured experimentally in the past.18,24−28While quantitative comparison between the CFD simulation and the experimental measurement is not possible,as they are conducted at di fferent conditions,it is important to know if the CFD prediction is in the range of the physical modeling or not.The experimental data from two previous works involving air −water systems are used for this comparison.18,27As shown in Figure 5,the CFD simulation is within a reasonable range of the experimental data.The measurements from both Che et al.27and Perron et al.18were conducted at an inclination angle of 2.0°,while the 2D CFD simulation is at an angle of 1.5°.Further quantitative comparison is necessary by implementing a CFD model in 3D and at the same inclination angle as the experiment.The bubble-induced voltage drop is closely related to bubble coverage area and gas layer thickness.The bubble coverage area will have a much larger e ffect than the bubble thickness.6FigureFigure 4.E ffect of contact angle on the coe fficient of the term on theright-hand side of eqs 6and7.Figure5.Mean sliding velocity as a function of bubble diameter and system.(Adapted from ref 41.Copyright 2012The Minerals,Metals &Materials ed with permission.)3indicates that the bubble coverage area is larger in the CO 2−cryolite system than in the air −water system for the same size bubble.On the other hand,the larger bubble thicknesses in the air −water system often lead to lower bubble sliding velocity;thus,the bubble residence time under the anode is larger in the air −water system than in the CO 2−cryolite system for the same size bubble.Therefore,a combined consideration of bubble coverage area and bubble velocity is needed to compare the e ffect on the voltage drop between the two systems.A drag coe fficient is often used to quantify the drag or resistance of an object in a fluid environment,where a lower drag coe fficient indicates the object will have less hydrodynamic drag.The bubble is often treated as a 3D sphere in the empirical correlations.Thus,the drag coe fficient is calculated on the basis of a form for spherical bubbles,given as ρρρφ=−C dg v 43()sin()d l g l b 2(8)where C d is the bubble drag coe fficient and φis the inclination angle of the anode bottom surface.Figure 6shows the drag coe fficient of the bubble as a function of the bubble size for both systems.For a given bubble size,the drag coe fficient in the air −water system is larger than that in the CO 2−cryolite system.The drag coe fficient does not change much for the two large bubbles.It is interesting to observe that the drag coe fficient increases for the air −water system and reduces for the CO 2−cryolite system at the smallest bubble size.It is commonly accepted that the drag coe fficient will increase as the bubble size reduces due to the large volume-to-surface ratio.As shown in Figure 2,at small sizes (cases 1and 2),the bubble undergoes a lot more distortion in the CO 2−cryolite system than it does in the air −water system.This may explain why the drag coe fficient from the CO 2−cryolite at the small size (case 2)does not follow the trend of the air −water system (case 1).Further investigation,with more simulations of di fferent bubble sizes,is required to better explain this issue.According to Ishii and Zuber ’s correlation,54the drag coe fficient is about 2.67in the free rising bubbling region.The drag force coe fficient related to flow under an inclined surface is almost 10times less than that in free rising bubbling flow in the CO 2−cryolite system.A proper set of drag coe fficients is required in the local averaged model for process scale simulation,where the drag coe fficient determines the interface momentum exchange.In previous studies,using the local averaged model,the drag coe fficient under the anode is simply set the same as if it were vertical flow,55or arbitrarily set with a small value.29,32,33Present quanti fication of the drag coe fficient for bubbles under the anode indicates the capability of the current modeling as a useful approach to further evaluate the drag coe fficient in the region between the anode and cathode for improving the accuracy of process-scale simu-lations.3.1.4.Flow Dynamics around and within the Bubble.In an aluminum electrolytic cell,the alumina is mainly consumed in the region between the anode and cathode,and a good transfer of alumina from the surrounding bath into this region is required to ensure the cell operates with good performance.The bubble-induced liquid flow is believed to be the maindriver for alumina mixing within the ACD.It is interesting tocheck the bubble-induced liquid flow within this region by plotting the flow dynamics around the bubbles.While the single bubble model cannot fully represent the real condition,it provides an advantage to assess the contribution of each individual bubble.Figure 7plots the streamlines that show the liquid flow around the bubble.In this figure,all cases are located with the left edge 0.136m from the left side of the full simulation domain and with a length of 0.275m.The buoyancy component induced by the density di fference between the two phases,which runs parallel to the anode ’s bottom surface,is the main cause of the bubble sliding along the anode,while the perpendicular component of liquid flow flattens the shape of the bubble.The bubble head pushes the front liquid away,and the liquid flows backward under the bubble to fill the space where the bubble tail had been.Right beneath the bubble ’s bottom surface,the liquid flows forward driven by the skin friction at the gas −liquid interface.This leads to various local recirculations.The local recirculation increases as the bubble size increases due to the large momentum exchange between the liquid and the gas bubble.Figure 8plots the flow velocities and dynamic pressure distribution in the bubble region.To keep the same scale in all of the figures,only the bubble head region is plotted for cases 3−6.Note that the spatial positions are not the same in this figure.The velocity magnitude inside the bubble is much larger than that in the surrounding liquid.Thus,the forward motion of gas will be impeded by the front liquid.This will lead to a momentum exchange at the interface.Consequently,there is a high dynamic pressure gradient right in front of the bubble head.The pressure gradient partly drives the liquid forward and partly drives the liquid downward,leading to a thick head.As the bubble size increases,the gas bubble velocities increase,leading to a higher dynamic pressure gradient.At the gas −liquid interface,the skin friction leads to higher liquid flow to the front.This forward flow meets with the backward flow beneath the bubble head,resulting in the formation of a big bubble nose.Negative dynamic pressures are observed in the regions associated with local swirls.The detailed flow dynamics explain the formation of di fferent types of bubbles very well.3.2.Bubble Releasing at the Anode Edge.Figure 9shows the bubble behavior at the anode edge for all simulation cases.When the bubble approaches the edge of the anode,the horizontal momentum keeps the bubble moving along.OnceFigure 6.Bubble drag coe fficient as a function of bubble size for di fferent systems.(Adapted from ref 41.Copyright 2012The Minerals,Metals &Materials ed with permission.)。