基于晶格-Boltzmann方法的纳米流体流动和传热模型

纳米流体是由流体与纳米粒子组成的悬浮体.悬浮在流体中的纳米粒子会受到运动阻力、布朗力、扩散力和重力等作用力的影响,因而其运动规律极其复杂.本文运用晶格-Boltzmann(LB)方法,建立纳米流体流动和传热模型模型,对纳米流体的流型结构和温度场进行了模拟和分析.     

纳米流体对流换热的实验研究

建立了测量纳米流体对流换热系数的实验系统,测量了不同粒子体积份额的水-Cu纳米流体在层流与湍流状态下的管内对流换热系数,实验结果表明,在液体中添加纳米粒子增大了液体的管内对流换热系数,粒子的体积份额是影响纳米流体对流换热系数的因素之一。综合考虑影响纳米流体对流换热的多种因素,提出了计算纳米流体对流换热系数的关联式。     

变物性参数对微通道内纳米流体强制对流换热的影响

对二维微通道内Al_2O_3-水纳米流体的强制对流换热进行了数值研究。主要研究纳米流体的变热物性参数、纳米粒子体积分数φ和Re数对纳米流体强制对流换热的影响。研究表明:在Re数和纳米颗粒体积分数φ一定时,变热物性参数纳米流体比定热物性参数纳米流体在微通道内的强制对流换热强。在Re数一定时,随着纳米粒子体积分数φ的增加,纳米流体换热性能增强。在纳米粒子体积分数φ一定时,随着Re数的增加,纳米流体的换热能力也随之增加。     

小通道扁管内纳米流体流动与传热特性

建立了测量小通道扁管内纳米流体流动与对流换热性能的实验系统,测量了不同粒子体积份额的水-Cu纳米 流体的管内对流换热系数和摩擦阻力系数,实验结果表明,在相同雷诺数条件下,小通道扁管内纳米流体的对流换热系数 大于纯液体,且随粒子的体积份额的增加而增大,而纳米流体的阻力系数并未明显增大。     

ZrO2纳米流体的对流换热系数测定及机理浅析

建立了测量圆管内纳米流体流动与传热性能的实验系统,测量了不同粒子浓度的ZrO2/水纳米流体在雷诺数为3 000～18 000范围内的管内对流换热系数以及不同位置处纳米流体对流换热系数的变化情况.实验结果显示,在液体中添加纳米粒子显著增大了液体的管内对流换热系数,例如,在相同雷诺数时,与纯水相比,如果纳米粒子的质量浓度从1.6%增大到4.1%,则纳米流体的对流换热系数增加的比例从1.09增大到1.2.此外,从颗粒的浓度、粒径两方面分析纳米流体强化传热的机理.     

封闭腔内纳米流体强化自然对流换热的数值模拟

采用F luen软件对封闭腔内Cu-H2O纳米流体强化自然对流换热进行了数值模拟,重点分析Cu纳米粒子添加量和Gr数对换热性能的影响,并解释其换热机理。研究结果表明:在水基液中加入Cu纳米粒子可以显著提高基液的自然对流换热特性。对于一给定的Gr数,随着纳米粒子质量分数的增加,纳米流体的速度组成部分增加,纳米流体质量分数越大,x方向和y方向的速度峰越大,因此加速了流体中能量传输。另一方面,随着Gr数的增加,流线图中旋涡逐渐变大,流线间强度增加,说明换热效果逐渐增强。当Gr数较小时,传热主要是由热壁和冷壁之间的热传导引起的,随着Gr数的增大,换热逐渐变为由对流换热占主导地位。     

黏弹性流体基铜纳米流体流动与传热实验研究

成功建立了流体流动阻力和换热性能测试实验台,在45℃的流体温度下,对不同铜粒子体积分数和基液浓度的纳米流体在湍流状态下的对流换热特性和流动阻力进行了实验测量。实验结果表明:黏弹性流体基液中添加纳米粒子后,在降低对应基液减阻率的同时能明显增强传热性能.例如,将1.0%体积分数的铜纳米粒子添加到质量分数为6×10~(-4)的基液中所形成的黏弹性流体基纳米流体其综合性能指数K=0.47,表现了很好的传热强化和减阻性能.     

纳米流体强化传热研究

本文通过在液体中添加纳米级金属或金属氧化物粒子,研制了一种新型传热冷却工质—纳米流体,并对纳米流体的悬浮稳定性和均匀性进行了研究,给出的纳米流体电镜照片显示了悬浮液具有较高的分散性、稳定性;同时,介绍了纳米流体导热系数的理论分析方法,运用瞬态热线法测定了不同种类、不同体积份额配比的纳米流体的导热系数,分析了纳米粒子属性、份额、形状和尺度等因素对纳米流体导热系数的影响。     

纳米流体射流冲击冷却技术的实验研究

将高传热性能的Cu-水纳米流体作为换热工质引入射流冲击冷却技术,设计并搭建了射流冲击冷却系统,测试了该系统的换热性能和系统压降,研究了纳米粒子体积份额、入口射流速度以及射流冲击高度对系统换热性能的影响。实验结果表明,在液体中添加纳米粒子、增加射流速度、选取合适的射流冲击高度可以有效提高射流冲击冷却效果,且少量纳米粒子的加入并未引起系统压降的明显变化。     

纳米流体对流换热系数增大机理

纳米流体流动换热能力优于传统流体介质.研究了纳米流体热物性的提升和热散射对其对流换热系数的影响.结果表明,纳米颗粒的加入,优化了介质的热物性,增大了导热系数,强化了纳米流体内颗粒、流体以及流道管壁碰撞和相互作用,同时加强了流体的混合脉动和湍流,从而增大了对流换热系数. 关键词： 纳米流体 换热系数 热散射     

Numerical simulation of Electrokinetically Driven Peristaltic Pumping of Silver-Water Nanofluids in an asymmetric microchannel

This article intends to focus on the theoretical and numerical investigation of the peristaltic pumping of water-based silver nanofluid in the presence of electroosmotic forces. The investigation is carried out in an asymmetric microchannel subject to the influence of mixed convection and viscous dissipation. No-slip boundary conditions for velocity, temperature, and nanoparticle volume fraction are imposed on channel walls. The lubrication approach is utilized to simplify the normalized constitutive equations. The distribution of electric potential in the electric double layer is characterized by Poisson-Boltzmann ionic distribution which is further linearized by Debye-Hückel approximation. Nanofluid properties are predicted by a combination of the Buongiorno two-phase mixture model and homogeneous flow model. Additionally, the effective thermal conductivity and dynamic viscosity of silver-water nanofluid are characterized by the Corcione model. Silver nanoparticles of 20nm diameter are utilized in this suspension. The transformed set of nonlinear and coupled equations is numerically executed for axial velocity, temperature, and nanoparticle volume fraction by employing the mathematical software Maple 17. Pumping and trapping phenomena are also investigated. A comparison between the thermal conductivity of nanofluid predicted by the Corcione model and the Maxwell model is further presented. The influence of various flow parameters is outlined through graphical results. It has been observed that the thermal conductivity of silver-water nanofluid enhances with increasing nanoparticle volume fraction and temperature but decreases for larger sized nanoparticles. Moreover, the heat transfer rate rises significantly when smaller silver nanoparticles are suspended in water. Furthermore, the temperature of nanofluid is directly related to the Debye length parameter and the Helmholtz- Smoluchowski velocity parameter.     

Natural Convection of Fe_3O_4-Ethylene Glycol Nanofluid under the Impact of Electric Field in a Porous Enclosure

Free convection of Fe_3O_4-Ethylene glycol nanofluid in existence of Coulomb forces is studied. Effect of thermal radiation is taken into account. Properties of nanofluid are varied with supplied voltage and shape of nanoparticles. The bottom wall is considered as positive electrode. Control Volume based Finite Element Method is used to obtain the results, which are the roles of Darcy number(Da), radiation parameter(Rd), Rayleigh number(Ra), nanofluid volume fraction(φ), and supplied voltage(?φ). Results indicate that Nusselt number is an enhancing function of supplied voltage and Darcy number. Maximum values for temperature gradient are occurred for platelet shape nanoparticles.     

方腔内Cu/Al2O3水混合纳米流体自然对流的格子Boltzmann模拟

纳米流体作为一种较高的导热介质, 广泛应用于各个传热领域. 鉴于纳米颗粒导热系数和成本之间的矛盾, 本文提出了一种混合纳米流体. 为了研究混合纳米流体颗粒间相互作用机理和自然对流换热特性, 在考虑颗粒间相互作用力的基础上, 利用多尺度技术推导了纳米流体流场和温度场的格子Boltzmann方程, 通过耦合流动和温度场的演化方程, 建立了Cu/Al₂O₃水混合纳米流体的格子Boltzmann模型, 研究了混合纳米流体颗粒间的相互作用机理和纳米颗粒在腔体内的分布. 发现在颗粒间相互作用力中, 布朗力远远大于其他作用力, 温差驱动力和布朗力对纳米颗粒的分布影响最大. 分析了纳米颗粒组分、瑞利数对自然对流换热的影响, 对比了混合纳米流体(Cu/Al₂O₃-水)与单一金属颗粒纳米流体(Al₂O₃-水)的自然对流换热特性, 发现混合纳米流体具有更强的换热特性.     

Particle agglomeration and properties of nanofluids

The present study demonstrates the importance of actual agglomerated particle size in the nanofluid and its effect on the fluid properties. The current work deals with 5 to 100 nm nanoparticles dispersed in fluids that resulted in 200 to 800 nm agglomerates. Particle size distributions for a range of nanofluids are measured by dynamic light scattering (DLS). Wet scanning electron microscopy method is used to visualize agglomerated particles in the dispersed state and to confirm particle size measurements by DLS. Our results show that a combination of base fluid chemistry and nanoparticle type is very important to create stable nanofluids. Several nanofluids resulted in stable state without any stabilizers, but in the long term had agglomerations of 250 % over a 2 month period. The effects of agglomeration on the thermal and rheological properties are presented for several types of nanoparticle and base fluid chemistries. Despite using nanodiamond particles with high thermal conductivity and a very sensitive laser flash thermal conductivity measurement technique, no anomalous increases of thermal conductivity was measured. The thermal conductivity increases of nanofluid with the particle concentration are as those predicted by Maxwell and Bruggeman models. The level of agglomeration of nanoparticles hardly influenced the thermal conductivity of the nanofluid. The viscosity of nanofluids increased strongly as the concentration of particle is increased; it displays shear thinning and is a strong function of the level of agglomeration. The viscosity increase is significantly above of that predicted by the Einstein model even for very small concentration of nanoparticles.     

纳米颗粒聚集形态对纳米流体导热系数的影响

纳米流体中悬浮的纳米颗粒可以增强其导热性能已经得到广泛认可,然而纳米流体颗粒增强传热的机理目前尚不清楚.研究表明,纳米颗粒的聚集是纳米流体导热系数增大的重要机制,而且纳米颗粒聚集的形态对纳米流体的导热系数有重要影响,但是目前的导热系数模型大多是建立在Maxwell有效介质理论的"静态"和"均匀分散"假设基础上.本文用平衡分子动力学模拟Cu-Ar纳米流体,采用Green-Kubo公式计算导热系数,采用Schmidt-Ott关系式计算不同聚集形态下的分形维数.对比导热系数与分形维数可以发现:在相同体积分数下,较低的分形维数会有更高的导热系数,分析了分形维数与导热系数的定量关系.此外,通过径向分布函数可以看出纳米颗粒紧密聚集与松散聚集的差异,基液分子在纳米颗粒附近的纳米薄层中处于动态平衡状态.研究结果有助于理解纳米颗粒聚集形态对导热系数的影响机理.     

Prediction of heat transfer of nanofluid on critical heat flux based on fractal geometry

Analytical expressions for nucleate pool boiling heat transfer of nanofluid in the critical heat flux (CHF) region are derived taking into account the effect of nanoparticles moving in liquid based on the fractal geometry theory. The proposed fractal model for the CHF of nanofluid is explicitly related to the average diameter of the nanoparticles, the volumetric nanoparticle concentration, the thermal conductivity of nanoparticles, the fractal dimension of nanoparticles, the fractal dimension of active cavities on the heated surfaces, the temperature, and the properties of the fluid. It is found that the CHF of nanofluid decreases with the increase of the average diameter of nanoparticles. Each parameter of the proposed formulas on CHF has a clear physical meaning. The model predictions are compared with the existing experimental data, and a good agreement between the model predictions and experimental data is found. The validity of the present model is thus verified. The proposed fractal model can reveal the mechanism of heat transfer in nanofluid.     

利用格子Boltzmann方法模拟矩形腔内纳米流体Raleigh-Benard对流

利用格 子 Boltzmann方法模拟矩形腔内纳米流体Rayleigh-Benard对流, 得到温度场和流线分布, 比较分析不同Ra数、体积分数、粒径下纳米流体对流换热的变化情况. 结果表明: 在相同的Ra 数和体积分数下, 纳米流体的对流换热随着粒径的增大而减弱; 在相同的Ra数和粒径下, 纳米流体的对流换热随着体积分数增大而增强. 关键词： 纳米流体 Raleigh-Benard 多相流 格子Boltzmann方法     

Physics and mechanics of heat exchange processes in nanofluid flows

Nanofluids present a new type of dispersed fluids consisting of a carrier fluid and solid nanoparticles. Unusual properties of nanofluids, particularly high thermal conductivity, make them eminently suitable for many thermophysical applications, e.g., for cooling of equipment, designing of new heat energy transportation and production systems and so on. This requires a systematic study of heat exchange properties of nanofluids. The present paper contains the measurement results for the heat transfer coefficient of the laminar and turbulent flow of nanofluids on the basis of distilled water with silica, alumina and copper oxide particles in a minichannel with circular cross section. The maximum volume concentration of particles did not exceed 2%. The dependence of the heat transfer coefficient on the concentration and size of nanoparticles was studied. It is shown that the use of nanofluids allows a significant increase in the heat transfer coefficient as compared to that for water. However, the obtained result strongly depends on the regime of flow. The excess of the heat transfer coefficient in the laminar flow is only due to an increase in the thermal conductivity coefficient of nanofluid, while in the turbulent flow the obtained effect is due to the ratio between the viscosity and thermal conductivity of nanofluid. The viscosity and thermal conductivity of nanofluids depend on the volume concentration of nanoparticles as well as on their size and material and are not described by classical theories. That is why the literature data are diverse and contradictory; they do not actually take into account the influence of the mentioned factors (size and material of nanoparticles). It has been shown experimentally and by a molecular dynamics method that the nanofluid viscosity increases while the thermal conductivity decreases with the decreasing dispersed particle size. It is found experimentally for the first time that the nanofluid viscosity coefficient depends on the particle material. The higher is the density of particles, the higher is the thermal conductivity coefficient of nanofluid.     

Modeling of nanoparticles’ aggregation and sedimentation in nanofluid

The aggregation and sedimentation of nanoparticles in nanofluid have significant influences on the stability and applicability of nanofluids. The objective of this study is to propose a model to predict the nanoparticles’ aggregation and sedimentation characteristics. The characteristics are evaluated by the concentration of nanoparticles in nanofluid at different time. The concentration of nanoparticles can be calculated according to the speed and location of each nanoparticle. Then, the speed and location of each nanoparticle can be yielded when the forces on each nanoparticle are determined. For the forces on nanoparticles are related to the space structure of nanoparticle clusters, the clusters’ space structures are simulated. Case study shows that the mean deviation of predicted nanoparticle concentration from experimental data for Fullerence + H₂O, Fullerence + Oil and CuO + Oil nanofluids are 25%, 16% and 13%, respectively. The model can provide quantitative prediction of the aggregation and sedimentation characteristics of nanoparticles in nanofluid.