液体导热系数的自由体积模型

本文用统一的自由体积模型描述温度，压力和组成对稠密流体，尤其是液体的导热系数的影响。首先，在低压下纯液体的导热系数提出了简单的三参数关联式，对４３种纯物质，４４３个数据点的总平均误差仅为０．２６％，在此基础上，提出了液体混合的模型，其参数可视与温度无关，对４３个二元体系，包括含水体系，计８６９个点的计算误差仅为２．３１％，优于被认为成功的Ｔｅｊａ－Ｒｉｃｅ模型，最后，提出了适用于高压下，包括气液两     

一步法制备铜导热油纳米流体的导热系数与黏度

为研究Cu纳米颗粒对VP-1导热油导热系数和黏度的影响,基于两相法一步制备十二烷基硫醇表面修饰的Cu/VP-1导热油纳米流体,研究30—130℃下不同质量分数纳米流体的导热系数和黏度变化规律。实验结果表明：添加分散剂可以改善纳米流体稳定性。在30—130℃纳米流体导热系数随温度、质量分数的增加而增大;黏度随温度升高呈指数降低,质量分数越高,黏度下降越缓慢。通过计算纳米流体在不同体积分数下的黏度和导热系数理论模型,对实验结果进行验证。Prasher模型能够准确预测纳米流体的导热系数,而现有的黏度模型不适用于Cu/VP-1导热油纳米流体,在修正现有的黏度模型基础上,提出新的黏度计算公式。     

氧化硅纳米流体的导热性能研究

采用瞬态热线法测量SiO2-水和SiO2-乙二醇两种纳米流体在不同体积分数和温度下的导热系数,分析研究纳米SiO2体积含量、温度及悬浮稳定性对纳米流体导热系数的影响。研究结果表明,纳米流体的导热系数显著高于基体液体的导热系数,且随着粒子体积分数的增大和温度的升高均有所提高;对于悬浮稳定性越好的纳米流体,它的导热系数增加量越大。     

气体流动条件下钴基催化剂固定床的传热

在气体流量4~8 Nm3/h、气体分布器进口温度190~210℃、加热管壁温约240℃的条件下,对气体流动时活性组分呈蛋壳型分布的钴基催化剂固定床的传热进行了实验研究,建立了二维拟均相传热模型,利用正交配置法和Levenberg-Marquardt法对其求解,得到了钴基催化剂床层径向有效导热系数及壁给热系数的关联式,并将传热参数与由气体处于静态时固定床的有效导热系数计算而得的固定床传热参数值进行了比较,在气体入口温度范围内考察了其对固定床传热参数的影响. 结果表明,实验所得传热参数与文献值的最大偏差绝对值均在15%以内.     

液体纯物质导热系数的预测

在估算导热系数的Weber方程和Sato—Riedel法的基础上,根据对液体导热系数影响因素的分析,提出了估算液体导热系数的计算模型。利用该模型计算了34种液体物质（包括27种有机物和7种无机物）100个数据点的导热系数,计算值与试验值的总平均相对偏差为3．00％,计算准确性优于文献方法,方法简单方便,利用被估算液体物质的摩尔质量、临界温度临界压缩因子和正常沸点温度数据,就可以直接预测这些液体在不同温度下的导热系数。     

用激光导热仪测定炭黑填充橡胶的导热系数

用激光导热仪测定了5种填充不同量炭黑N 220的胶料在30～140℃时的导热系数,分析了导热系数随温度和炭黑填充量变化的关系,发现胶料的导热系数均随着温度的升高呈线性增大趋势,随炭黑填充量的增加也逐渐增大.将导热系数与温度和炭黑填充量进行了关联,得到了线性回归方程式,进而确立了适合于计算不同温度和不同炭黑N 220填充量胶料导热系数的关联方程A=0.133 77 2.008 74×10-4t 0.001 64 X.将用该方程计算的结果与实验值进行比较,60个数据点的平均相对误差仪为0.93%.     

苄胺-乙腈-水体系导热系数的测量与计算

导热系数是流体的基础物理性质之一,苄胺-乙腈-水体系的导热系数对其相关反应的工业化开发具有重要意义。研究利用瞬态热线装置分别测定了苄胺-乙腈、苄胺-水、乙腈-水和苄胺-乙腈-水体系在288.15～318.15 K、常压条件下3种组分质量分数在0.1～0.9的导热系数。实验数据不确定度为±2.5%,覆盖因子k=2。运用二阶Scheffé多项式将二元体系导热系数拟合成关于温度和组成的方程,并与4种导热系数预测方程的预测结果进行了对比,多项式关联结果明显优于其他预测方程。因此用Scheffé多项式对苄胺-乙腈-水混合体系导热系数进行了预测,最大相对偏差和平均相对偏差分别为2.54%和0.68%。     

水泥熟料堆积体等效导热系数模型与实验研究

水泥熟料堆积体导热系数表征了水泥熟料颗粒传递热量的能力,在研究篦冷机内水泥熟料冷却换热机理方面具有重要意义.本文在多孔介质的两相导热模型的基础上,考虑到固气两相随机混合方式排列,建立了一种新的适用于水泥熟料堆积体的导热数学模型.为求解模型参数,应用圆球导热仪测量水泥熟料堆积体的导热系数,实验结果表明,水泥熟料堆积体的等效导热系数随温度的升高而增大,随孔隙率的增大而减小.     

低浓度Al_2O_3-水纳米流体制备及导热性能测试

采用两步法制备低浓度Al_2O_3(40 nm)-水纳米流体,其体积分数为0.1%～0.5%.制备过程中不加分散剂,采用超声振动,并对其进行Zeta电位、粒度和吸光度测试表征其悬浮稳定性,结果表明当超声时间为3 h时,Al_2O_3-水纳米流体悬浮稳定性最好.进一步测试其导热系数,结果表明Al_2O_3-水纳米流体的导热系数均高于水的导热系数;室温下(17 ℃)当体积分数从0.1%增加到0.5%时,其导热系数从5.40%增加到17.9%.对于体积分数为0.2%的Al_2O_3-水纳米流体,当温度从17 ℃增加到57 ℃时,相应的导热系数从7.23%增加到23%;实验还发现纳米流体导热系数与纳米粒子的体积分数和温度均呈非线性关系.     

硬脂酸修饰MoS_2纳米颗粒的制备及其强化传热性能

以硬脂酸为表面修饰剂,采用表面修饰法制备了硬脂酸修饰MoS_2(SA-MoS_2)纳米颗粒,并合成了导热油基MoS_2纳米流体,对产物进行了表征和测定了纳米流体的高温导热系数。结果表明,硬脂酸通过化学反应修饰在MoS_2纳米颗粒表面,SA-MoS_2纳米颗粒具有很好的亲油性,在导热油中具有良好的分散稳定性;SA-MoS_2纳米颗粒属于无定型非晶态,为不完全规则的球形纳米颗粒,尺寸约为30~90 nm;在40~120℃,纳米流体的导热系数随着温度的增大而略有减小,而温度大于120℃,导热系数与温度的变化呈正比;SA-MoS_2纳米颗粒对导热油的导热系数具有显著的强化作用,导热系数提高率与纳米颗粒的质量浓度呈正比,仅添加0.60 wt%的SA-MoS_2纳米颗粒时,纳米流体的导热系数比基础油提高了34.3%~51.2%。这种强化传热特点在高温传热工质和热能工程中具有重要的应用价值。     

有机物混合液导热系数的预测

文章根据液体物质的导热系数与密度的关系,导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53个体系369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1.434%,计算值与实验数据吻合较好,计算准确性优于文献方法;文章方法简单方便,只需要混合液各组分的临界温度、临界体积和导热系数数据,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。     

Thermal transport characteristics in diamond/SiC composites via molten Si infiltration

Heat dissipation remains a critical challenge in optical and electronic devices and diamond/SiC composite is the premiere material solution because of its outstanding thermal and mechanical properties. Si liquid infiltration is one of the most promising techniques to fabricate fully dense diamond/SiC composites with desired phase structures and exceptional properties. In this study, the thermal conductivity from room temperature to 1000 °C was investigated for the diamond/SiC composites fabricated by a liquid Si infiltration method. The experimental thermal measurement shows a good agreement with the computational solution obtained by solving the Boltzmann transport equation. The results suggest a strong correlation between the composite thermal conductivity and diamond volume percentage. A level-off of the thermal conductivity at high diamond content reflects increased thermal resistance. In addition, the annealing effect on the composite thermal conductivity as well as the thermal stability were evaluated.     

地埋管换热器热短路及其对热物性测试影响分析

为了更准确地建立垂直地埋管换热器钻孔内传热模型,采用模拟分析的方法探讨了不同钻孔、支管和布置形式的冷热支管热量回流情况,并拟合得到了热短路热阻的表达式。建立了三维数值模型,分析了管内流体流速、埋深对热短路的影响,流速越小,热短路损失率越大和单位管长换热量越小,然而流速过大,热短路损失率减少并不明显且能耗加大;增加埋深可以增大埋管进出口的温差,但冷热支管间的热损失也大大增加。对比了流体积分平均温度与几何平均温度的差别,由于忽略了热短路的影响,往往线性几何平均温度值偏大。借助于试验平台,分析了流速变化和埋深变化对土壤平均传热系数测试的影响,结果表明:流速越小,热短路损失率越大,土壤平均传热系数越小,即埋管的换热能力也越低;埋管的深度应综合换热量要求、热短路损失、投资而确定。     

液体有机物导热系数的估算

在计算液体导热系数的Weber方程和Sato关系式的基础上,根据对有机物液体导热系数影响因素的分析研究,提出了估算有机物导热系数的计算模型;利用该模型计算了22个体系74个数据点的有机物液体的导热系数,计算值与实验值的总平均相对偏差3.18%,计算准确性优于文献方法;计算结果表明,利用被估算物质的摩尔质量、临界温度、正...     

Models for fuel droplet heating and evaporation: Comparative analysis

The results of comparative analysis of liquid and gas phase models for fuel droplets heating and evaporation, suitable for implementation into computational fluid dynamics (CFD) codes, are presented. Among liquid phase models, the analysis is focused on the model based on the assumption that the liquid thermal conductivity is infinitely large, and the so-called effective thermal conductivity model. Seven gas phase models are compared. These are six semi-theoretical models based on various assumptions and a model based merely on the approximation of experimental data. It is pointed out that the gas phase model, taking into account the finite thickness of the thermal boundary layer around the droplet, predicts the evaporation time closest to the one based on the approximation of experimental data. In most cases, the droplet evaporation time depends strongly on the choice of the gas phase model. The droplet surface temperature at the initial stage of heating and evaporation does not practically depend on the choice of the gas phase model, while the dependence of this temperature on the choice of the liquid phase model is strong. The direct comparison of the predictions of various gas models, with available experimental data referring to droplet heating and evaporation without break-up, leads to inconclusive results. The comparison of predictions of various liquid and gas phase models with the experimentally observed total ignition delay of n-heptane droplets without break-up, has shown that this delay depends strongly on the choice of the liquid phase model, but practically does not depend on the choice of the gas phase model. In the presence of droplet break-up processes, the evaporation time and the total ignition delay depend strongly on the choice of both gas and liquid phase models.     

加压下液体物质导热系数的计算

根据液体物质的导热系数与其对比温度和对比压力的关系的文献数据,导出了估算加压下液体有机物导热系数的计算模型;利用该模型计算了9种液体物系223个数据点的导热系数数据,计算值与实验值的总平均相对误差为3.349%,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,只需要物质的临界温度、临界压力和低压下物...     

The use of drying experiments in the study of the effective thermal conductivity in a solid containing a multicomponent liquid mixture

The effective thermal conductivity of a porous solid containing multicomponent liquid mixtures has been studied. To achieve this, the liquid composition, liquid content and temperature distributions have been measured in a cylindrical sample dried by convection from the open upper side and heated by contact with a hot source at the bottom side. A quasi-steady state reached at high source temperatures permits to calculate the total heat flux from temperatures measured on the surface and the gas stream. The simulations performed and compared with experimental data made it possible to estimate the adjusting geometric parameter of Krischer's model for the effective thermal conductivity. The effective thermal conductivity has been widely studied for two-phase systems, mostly with regard to thermal insulation elements. The calculation of this transport parameter includes the contribution to heat transfer of the evaporation–diffusion–condensation mechanism undergone by the multicomponent mixture. The influence of liquid composition and temperature on the thermal conductivity due to the evaporation–diffusion–condensation mechanism and the effective thermal conductivity is described. The results reveal that in this case the resistance to heat transfer seems to correspond to a parallel arrangement between the phases.     

A local composition model for multicomponent liquid mixture thermal conductivities

A local composition model for multicomponent, liquid mixture thermal conductivity has been developed and tested. Only binary equilibrium thermodynamic information is used in the model to obtain local compositions. No mixture thermal conductivity data are required and no adjustable parameters are used. Predictions based on this model agreed, within experimental uncertainty, with the experimental results for eighteen different binary mixtures at 1 atm and various temperatures. An average absolute percent deviation from experiment of 1.0% was obtained over the entire composition range for the eighteen systems. The maximum deviation at any of the tested compositions was 3.5%. Thermal conductivities for ternary systems have also been computed.     

Correlating thermal conductivity of pure hydrocarbons and aromatics via perceptron artificial neural network (PANN) method

Accurate estimation of liquid thermal conductivity is highly necessary to appropriately design equipments in different industries. Respect to this necessity, in the current investigation a feed-forward artificial neural network(ANN) model is examined to correlate the liquid thermal conductivity of normal and aromatic hydrocarbons at the temperatures range of 257–338 K and atmospheric pressure. For this purpose, 956 experimental thermal conductivities for normal and aromatic hydrocarbons are collected from different previously published literature.During the modeling stage, to discriminate different substances, critical temperature(Tc), critical pressure(Pc)and acentric factor(ω) are utilized as the network inputs besides the temperature. During the examination, effects of different transfer functions and number of neurons in hidden layer are investigated to find the optimum network architecture. Besides, statistical error analysis considering the results obtained from available correlations and group contribution methods and proposed neural network is performed to reliably check the feasibility and accuracy of the proposed method. Respect to the obtained results, it can be concluded that the proposed neural network consisted of three layers namely, input, hidden and output layers with 22 neurons in hidden layer was the optimum ANN model. Generally, the proposed model enables to correlate the thermal conductivity of normal and aromatic hydrocarbons with absolute average relative deviation percent(AARD), mean square error(MSE), and correlation coefficient(R~2) of lower than 0.2%, 1.05 × 10~(-7) and 0.9994, respectively.