有机物混合液导热系数的估算

通过对液体导热系数与密度关系的分析研究,提出了估算有机物混合液导热系数的计算模型;利用该模型计算了55个体系377个数据点的二元有机物混合液导热系数,计算值与实验值的总平均相对偏差为1.48%,计算值与实验数据吻合很好,计算准确性优于文献方法;本文方法简单方便,只需要混合液各组分的导热系数数据,就可以直接预测各种温度和组成的有机物混合液的导热系数。     

BN填充PA6基导热绝缘复合材料导热性能研究

以聚酰胺6（PA6）为基体, 氮化硼（BN）作为导热填料,经双螺杆挤出机熔融共混,模压成型制得导热绝缘复合材料。研究了BN含量、粒径、形状和不同BN粒径复配对复合材料导热性能的影响,并研究了BN含量和粒径对复合材料绝缘性能的影响。结果表明,在各种粒径下,复合材料热导率均随BN填充量的增加而增大;在BN粒径为5 μm、填充量为25 %（体积分数,下同）时,复合材料热导率达到1.2187 W/(m·K);在BN填充量相同时,填料粒径对复合材料热导率的影响不是简单的单调规律,呈现50、100 μm时较小,1、5、15 μm时较大,150 μm时最大的规律;片状BN填料比球状BN填料更有利于提高复合材料的热导率;2种不同粒径填料复配所填充的复合材料的热导率大于单一粒径填充的复合材料;5 μm与150 μm粒径BN复配,在填充量为20 %,配比为1:3时,复合材料的热导率最大,达到1.3753 W/(m·K),为纯PA6的4.9倍;在不同BN含量和粒径下,复合材料体积电阻率均能达到10000000000000 Ω·cm以上,满足绝缘性能。     

稳态平板法测导热系数的补充实验研究

以建陶坯体为研究对象,针对目前平板法测量圆饼状固体材料导热系数的常见问题,采用蜡封方法避免水分沿圆周方向的逸出,分析湿度对导热系数的影响。试验结果表明:坯体导热系数随温度和含水率的升高而升高,并首次针对不符合尺寸要求的实验样品采用简化的实验方法,推导出其导热系数的计算公式。     

WALL AND PARTICLE-SHAPE EFFECTS ON HEAT TRANSFER IN PACKED BEDS

The effective radial thermal conductivity and apparent heat transfer coefficient for a packed bed were experimentally determined for beds of spheres, full cylinders and hollow cylinders, for flow rates giving particle Reynolds numbers in the range 100-1000, and for tube to particle diameter ratios of 5-12. Over these ranges the radial Peclet number Pe_r showed significant dependence on solid conductivity, gas flow rate and particle shape, while the wall Biot number Bi showed significant dependence on tube to particle diameter ratio, gas flow rate and particle shape. These dependencies were predicted well by equations incorporating the effects of these variables into individual gas and solid phase parameters, which were then combined to give the effective or lumped parameters     

Numerical simulation of local and global mixing/segregation characteristics in a gas–solid fluidized bed

Researches on solids mixing and segregation are of great significance for the operation and design of fluidized bed reactors. In this paper, the local and global mixing and segregation characteristics of binary mixtures were investigated in a gas–solid fluidized bed by computational fluid dynamics-discrete element method (CFD-DEM) coupled approach. A methodology based on solids mixing entropy was developed to quantitatively calculate the mixing degree and time of the bed. The mixing curves of global mixing entropy were acquired, and the distribution maps of local mixing entropy and mixing time were also obtained. By comparing different operating conditions, the effects of superficial gas velocity, particle density ratio and size ratio on mixing/segregation behavior were discussed. Results showed that for the partial mixing state, the fluidized bed can be divided into three parts along the bed height: complete segregation area, transition area and stable mixing area. These areas showed different mixing/segregation processes. Increasing gas velocity promoted the local and global mixing of binary mixtures. The increase in particle density ratio and size ratio enlarged the complete segregation area, reduced the mixing degree and increased the mixing time in the stable mixing area.     

醇+1,2-二氯乙烷、醇+环己酮二元体系热导率的测定和推算

采用瞬态热丝法液体热导率测量装置测定 10种醇 (甲醇、乙醇、正丙醇、异丙醇、正丁醇、异丁醇、仲丁醇、叔丁醇、正戊醇和异戊醇 )分别与 1,2 -二氯乙烷、环己酮组成的 2 0个二元体系在常压、 30℃和不同组成时的热导率 ,测量误差± 0 .7% .用文献中 5种热导率方程对所测液体的热导率做了推算 ,将计算值与实测结果做了比较 ,并进行了讨论     

Modelling the Effective Thermal Conductivity in Polydispersed Bed Systems: A Unified Approach using the Linear Packing Theory and Unit Cell Model

A comprehensive, unified approach, using the Linear Packing Theory and Unit Cell Model, is proposed for calculating of the effective thermal conductivity of polydispersed packed beds. In this new approach, the effect of packing density is incorporated by the use of (i) an initial porosity to take into account the packing of mono‐sized particles, and (ii) the packing size ratio as a measure of the particle‐particle interaction. The proposed approach was validated with the experimental measurements of binary and ternary beds. This new approach demonstrates that the effective thermal conductivity of beds composed of polydispersed particles can be simulated for any composition without the need to measure the in situ porosity.     

The thermal,electrical and mechanical properties of porous α-SiC ceramics bonded with Ti3SiC2 and β-SiC via low temperature in-situ reaction sintering

Porous SiC ceramics have recently attracted wide attention for their applications in the electrically heatable filter. Further improvement of the thermal and electrical conductivity without sacrificing permeability is a critical parameter for such applications. In the present work, porous SiC/Ti₃SiC₂ ceramic composites with Ti₃SiC₂ and micro/nano SiC have been prepared from TiC/Si/α-SiC mixtures at a low sintering temperature (1400 °C). Nano-laminated Ti₃SiC₂ enhanced the electrical conductivity, while the good thermal conductivity was achieved through in-situ formed nano β-SiC and raw coarse α-SiC in the porous ceramics. Along with the increase of initial α-SiC particle size from 0.76 to 16.13 μm, the permeability, thermal and electrical conductivity improved due to the decreased porosity and increased pore size in porous SiC/Ti₃SiC₂ ceramics. The results suggested that the decoupling of the electrical conductivity from the thermal conductivity could be tuned by adjusting the initial α-SiC particle size.     

氧化铝纳米粉体悬浮液强化导热研究

利用非稳态热丝法测定了2种纳米氧化铝粉分别分散于水和乙二醇（EG）中制备在悬浮液的导热系数，分析研究了悬浮液pH值，分散剂、纳米氧化铝粉体积含量，基体液体导热系数以及纳米氧化铝粉体团聚状态对悬浮液导热系数的影响，结果表明：悬浮液的导热系数随粉体加入量的增加而增加，相同体积含量的同一粉体悬浮液，基体液体为乙二醇的导热系数相对增加量明显比基体液体为水的大；团聚较多的粉体悬浮液的导热系数大于团聚较少粉体的悬浮液，pH值对悬浮液的导热系数无明显影响，分散剂的加入，增大了粉体和基体液体间的界面热阻，降低了悬浮液的有效导热系数。     

基于Lattice-Boltzmann方法的纳米颗粒多孔介质导热特性

为研究气凝胶纳米颗粒的导热特性,提出了一种基于随机统计原理的构造气凝胶多孔介质介观尺度三维物理模型的方法。模型中颗粒空间分布、粒径分布及孔隙率可以根据实际气凝胶微尺度结构数据调整。基于所构造的物理模型,采用D3Q15LBM进行了数值模拟。分析了颗粒尺寸、孔隙率等因素对气凝胶导热性能的影响规律,即在既定孔隙率下,热导率随粒径增大而减小;既定粒径下,随孔隙率的递增热导率先下降后上升;颗粒尺寸不均匀性对热导率的影响甚大。模拟与实验结果相吻合。研究工作对优化气凝胶导热性能,提高其有效热导率的预测精度具有参考价值。     

固液相变数学模型中有效热导率

在一维固液相变数学模型中有效热导率计算公式的研究基础上,根据理论分析和实验数据,对一维有效热导率进行了修正,并把有效热导率计算公式应用到二维相变问题中.通过对等热通量和等壁温边界条件的仿真计算结果与实验数据相比较,说明了本文的有效热导率计算方法的合理性.     

EXPERIMENTAL INVESTIGATION OF PARAMETERS AFFECTING NANOFLUID EFFECTIVE THERMAL CONDUCTIVITY

The present research reports nanofluid effective thermal conductivity enhancements (ETCE) using an accurate transient short hot wire method system. Preparation of nanofluids was carried out through a two-step method with highly powered pulses similar to that for nanoparticle dispersion in base fluids. Parameters affecting nanofluid heat conductivity such as concentration, sizes, and material of nanoparticle? type of base fluid, temperature, ultrasonic mixing time, and elapsed time after preparation were studied. In the present study, nanoparticles of Al, Al₂O₃, CuO, SnO₂, TiO₂, and SiO₂ with base fluids of water and ethylene glycol were used. Parameters like concentration, size, temperature, and the type of base fluid showed more noticeable effect on the effective thermal conductivity than the others, and mixing time had the least effect. The results showed that any increase in concentration and temperature, and also any decrease in size of nanoparticles and time elapsed after nanofluid preparation, leads to the ETCE of the nanofluid. However, the effects of nanoparticle material, base fluid, and mixing time on thermal conductivity of the nanofluid showed varying trends. Last, a number of mathematical models for prediction of thermal conductivity of nanofluids were applied.     

聚合物基复合材料导热模型及其研究进展

本文对聚合物基复合材料的各种导热模型进行了归纳和总结,包括理论性和经验性的模型。模型描述是多方面的,包括粒子填充型、纤维填充型、纤维布增强型等,并做出评价,提出应用过程中的一些建议。     

Heat transfer in nanoparticle suspensions: Modeling the thermal conductivity of nanofluids

This work reviews experimental data and models for the thermal conductivity of nanoparticle suspensions and examines the effect of the properties of the two phases on the effective thermal conductivity of the heterogeneous system. A model is presented for the effective thermal conductivity of nanofluids that takes into account the temperature dependence of the thermal conductivities of the individual phases, as well as the size dependence of the thermal conductivity of the dispersed phase. We demonstrate that this model can be used to calculate the thermal conductivity of nanofluids over a wide range of particle sizes, particle volume fractions, and temperatures. The model can also be used to validate experimental thermal conductivity data for nanofluids containing semiconductor or insulator particles and confirm the size dependence of the thermal conductivity of nanoparticles. © 2010 American Institute of Chemical Engineers AIChE J, 2010     

Discrete element method study on hopper discharge behaviors of binary mixtures of nonspherical particles

This study is aimed at unveiling the influence of binary mixtures of nonspherical particles on hopper discharge behavior, which remains poorly understood. The discrete element method (DEM) is employed to simulate seven particle types with aspect ratios between 0 and 2 (namely, a sphere, two ellipsoids, two cylinders, and two cuboids) with the same volume. Seven monodisperse systems and twelve binary-shape mixtures are assessed. For the monodisperse systems, particle shape is the dominant factor dictating discharge rate, compared to other factors like aspect ratio, preferential orientation, and packing. Regarding the binary-shape mixtures, the discharge rates are similar for all twelve mixtures, reflecting a surprising lack of shape effects, which in turn means the negligible impact of solid volume fraction, aspect ratio, and segregation extent. Moreover, collision force is generally negatively correlated with discharge rate.     

喷动流化床最大喷动压降的多因素影响与关联

基于截面200 mm×20 mm,高1600 mm,锥角60°的矩形喷动流化床,以二组分混合颗粒、单一组分球形颗粒及非球形颗粒为物料进行最大喷动压降的实验研究。结果表明,最大喷动压降随静止床高、颗粒密度、颗粒球形度及二组分混合颗粒体系中沉积组分分率增加而增大,随流化气速增大而减小;增大颗粒粒径或喷口宽度,呈现先减小后增大趋势,存在极小值;对于非球形颗粒及混合颗粒,其床层总压降随表观喷动气速变化的规律与单一组分球形颗粒相同,但相同条件下的前者压降波动幅度大于后者。以实验测量的854组数据为基础,结合量纲分析法建立了最大喷动压降预测关联式,与测量值及文献实验数据吻合较好。     

MOLECULAR PRINCIPLE OF CORRESPONDING STATES FOR VISCOSITY AND THERMAL CONDUCTIVITY OF FLUID MIXTURES

Conformal solution theory is developed for the viscosity and thermal conductivity of fluid mixtures. The procedure involves expanding the transport coefficient for the mixture about the value for an ideal solution, using groupings of the potential parameters and molecular mass as expansion coefficients. The parameters for the ideal solution are chosen so as to annul the first-order term in this expansion, thus encouraging rapid convergence. This yields mixing rules (similar to those of the van der Waals 1 theory for thermodynamic properties) for the potential parameters and molecular mass of the reference fluid. Reference fluid properties are obtained from pure fluid corresponding states correlations

By making calculations for dilute gas mixtures and comparing with Chapman-Enskog theory, it is found that the first-order theory works well for mixtures of quite widely different energy parameters (ε) and molecular masses; it is more sensitive to the size difference of the molecular components, however. For cryogenic liquid mixtures composed of simple liquids good results are obtained using two-parameter corresponding states for the reference fluid. For polyatomic fluids it is necessary to use a three-parameter corresponding states approach for the pure fluids. A method of introducing a third parameter, while retaining the simplicity of having only two independent variables, is used for such fluids. Good results are obtained for a variety of binary mixtures. The method is of particular value for multicomponent fluids. Thus, without fitting any parameters from ternary data the theory predicts viscosities for the system carbon tetrachloride/n-hexane/benzene over the full composition range with a standard deviation of only 1.69%.     

MOLECULAR PRINCIPLE OF CORRESPONDING STATES FOR VISCOSITY AND THERMAL CONDUCTIVITY OF FLUID MIXTURES

Conformal solution theory is developed for the viscosity and thermal conductivity of fluid mixtures. The procedure involves expanding the transport coefficient for the mixture about the value for an ideal solution, using groupings of the potential parameters and molecular mass as expansion coefficients. The parameters for the ideal solution are chosen so as to annul the first-order term in this expansion, thus encouraging rapid convergence. This yields mixing rules (similar to those of the van der Waals 1 theory for thermodynamic properties) for the potential parameters and molecular mass of the reference fluid. Reference fluid properties are obtained from pure fluid corresponding states correlations

By making calculations for dilute gas mixtures and comparing with Chapman-Enskog theory, it is found that the first-order theory works well for mixtures of quite widely different energy parameters (ε) and molecular masses; it is more sensitive to the size difference of the molecular components, however. For cryogenic liquid mixtures composed of simple liquids good results are obtained using two-parameter corresponding states for the reference fluid. For polyatomic fluids it is necessary to use a three-parameter corresponding states approach for the pure fluids. A method of introducing a third parameter, while retaining the simplicity of having only two independent variables, is used for such fluids. Good results are obtained for a variety of binary mixtures. The method is of particular value for multicomponent fluids. Thus, without fitting any parameters from ternary data the theory predicts viscosities for the system carbon tetrachloride/n-hexane/benzene over the full composition range with a standard deviation of only 1.69%.     

二氧化硅气凝胶的气相热导率模型分析

气凝胶是一种超级隔热材料,具有极低的整体热导率。气凝胶的纳米多孔网络结构极大限制了气体分子热运动,使得气凝胶中的气相热导率低于自由气体的气相热导率。本文介绍并讨论了气凝胶气相热导率的基本理论和模型,考察了孔径尺度和气凝胶固相骨架对气相热导率的影响。结果表明,气凝胶气相热导率随气压和孔径的减小而迅速降低,随气凝胶密度的增大而降低。当压力极低时,气凝胶的气相热导率远低于常压下大空间的静止空气。气凝胶纳米固体网格对气相热导率存在重要影响,在(0.01～100)×10⁵ Pa的压力范围内影响尤其显著。     

Minimum Fluidization Velocities of Binary Solid Mixtures: Empirical Correlation and Genetic Algorithm-Artificial Neural Network Modeling

Experimental investigation of the fluidization behavior in single and binary solid-liquid fluidized beds of nonspherical particles as solid phase and water as liquid phase was performed in a Perspex column. Different particle sizes were used to prepare single and binary mixtures with different weight ratios for fluidization. Minimum fluidization velocity increased with increasing average particle size and decreasing sphericity for the binary mixture. An empirical correlation was developed to predict the minimum fluidization velocity. Genetic algorithm-artificial neural network (GA-ANN) modeling was applied to predict the minimum fluidization velocity for single and binary solid-liquid fluidized beds. The application of GA-ANN analysis leads to designing binary solid-liquid fluidization systems without experimentation.