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.     

二氧化铈/水基纳米流体核沸腾传热特性

对CeO₂纳米流体进行了池沸腾传热特性研究,考察了CeO₂/水基纳米流体的热导率,静态接触角以及沸腾后表面沉积情况对沸腾传热的影响。结果表明,CeO₂纳米流体可提高沸腾传热系数,且纳米流体最佳质量分数为0.05%,其沸腾传热系数较去离子水提高36%。热导率以及接触角随纳米流体质量分数的增加而增加,在本实验范围内,热导率最大增加1%;而纳米流体接触角从50.5°增加到92.9°;表面沉积随纳米流体的质量分数增加越来越明显,去离子水在沉积表面的接触角发生较大变化(51.4°～134.4°)。纳米流体的热导率影响可忽略不计;而接触角和沸腾表面颗粒沉积对纳米流体的强化传热作用影响较大。     

Experimental investigation of the thermal transport properties of a carbon nanohybrid dispersed nanofluid

A hybrid nanostructure consisting of 1D carbon nanotubes and 2D graphene was successfully synthesized. Nanofluids were made by dispersing the hybrid nanostructure in deionized (DI) water and ethylene glycol (EG) separately, without any surfactant. Later the thermal conductivity and heat transfer coefficient of the nanofluids were experimentally measured. Meanwhile, multiwalled carbon nanotubes (MWNT) were prepared by catalytic chemical vapor deposition (CCVD), and hydrogen exfoliated graphene (HEG) was synthesized by exfoliating graphite oxide in a hydrogen atmosphere. The hybrid nanostructure (f-MWNT+f-HEG) of functionalized MWNT (f-MWNT) and functionalized HEG (f-HEG) was prepared by a post mixing technique, and the sample was characterized by powder X-ray diffraction, Raman spectroscopy, field emission scanning electron microscopy and transmission electron microscopy. Thermal conductivity of the nanofluids was measured for different volume fractions of f-MWNT+f-HEG at different temperatures. The hybrid nanostructure dispersed in the DI water based nanofluid shows a thermal conductivity enhancement of 20% for a volume fraction of 0.05%. Similarly, for a Reynolds number of 15,500, the enhancement of the heat transfer coefficient is about 289% for a 0.01% volume fraction of f-MWNT+f-HEG.     

Thermal Conductivity of Multiwalled Carbon Nanotubes-Kapok Seed Oil-Based Nanofluid

The synthesis of a nanofluid from multiwalled carbon nanotubes (MWCNTs) and Kapok seed oil by a one-step method is reported. The nanofluid showed excellent stability of nanoparticle dispersion in the base fluid. Furthermore, this study deals with the prediction of the thermal conductivity of the MWCNTs-kapok seed oil nanofluid. To improve the prediction of the thermal conductivity of the nanofluid, the artificial neural network (ANN) computing approach was used with different algorithms including the back-propagation, Levenberg-Marquardt, and genetic algorithm (GA). Finally, the ANN-GA model is recommended for the prediction of thermal conductivity with higher accuracy.     

三元混合纳米流体稳定性及热性能

采用两步法制备体积分数为0.005%～1%的Al₂O₃-TiO₂-Cu/水三元混合纳米流体,粒子体积比为40∶40∶20。为了提高其稳定性,添加少量的PVP（0.005%）表面活性剂,并用XRD、TEM、紫外分光光度计和沉淀观察法共同表征纳米流体的稳定特性。测量温度为20～60℃的黏度和热导率,并与相对应的单一纳米流体作对比。试验结果表明,三元混合纳米流体由于各种粒子的粒径和表面能不同,小粒径的Al₂O₃颗粒填充在大粒径TiO₂和Cu颗粒形成的间隙里,可形成致密的固液界面层。三元混合纳米流体由于粒子的特殊排布,使其热导率明显高于相同体积分数下对应的单一纳米流体,黏度却无明显增大。当体积分数和温度分别为1%和60℃时,与Al₂O₃/水纳米流体对比,其热导率增大了5.5%,黏度下降了2.6%。热导率随温度和浓度的升高而升高;而黏度随浓度的升高而升高,随温度的升高而下降,这与单一纳米流体的性质一致。最后,基于试验数据,对热导率和黏度分别进行与温度的拟合,R²分别为0.9835和0.9820,能较精确地预测Al₂O₃-TiO₂-Cu/水三元混合纳米流体的热导率和黏度。     

Statistical mechanics and artificial intelligence to model the thermodynamic properties of pure and mixture of ionic liquids

In this paper, the volumetric properties of pure and mixture of ionic liquids are predicted using the developed statistical mechanical equation of state in different temperatures, pressures and mole fractions. The temperature dependent parameters of the equation of state have been calculated using corresponding state correlation based on only the density at 298.15 K as scaling constants. The obtained mean of deviations of modified equation of state for density of al pure ionic liquids for 1662 data points was 0.25%. In addition, the performance of the arti-ficial neural network (ANN) with principle component analysis (PCA) based on back propagation training with 28 neurons in hidden layer for predicting of behavior of binary mixtures of ionic liquids was investigated. The AADs of a col ection of 568 data points for al binary systems using the EOS and the ANN at various temperatures and mole fractions are 1.03%and 0.68%, respectively. Moreover, the excess molar volume of all binary mixtures is predicted using obtained densities of EOS and ANN, and the results show that these properties have good agree-ment with literature.     

Effect of Heat Treatment on the Microstructure and Properties of Dense AIN Sintered with Y2O3 Additions

The secondary phase constitution in two sintered AIN ceramics (1.8% and 4.2% Y₂O₃ additions) was studied as a function of heat treatment temperatures between 1750° and 1900°C under pure nitrogen atmosphere. The effect of the phase constitution on the physical properties, such as density, thermal conductivity ( K ), and lattice constants, and on the mechanical properties in three-point bending, was also investigated. Y₃Al₅O₁₂ was found to getter dissolved oxygen from the AIN lattice below 1850°C, but evaporated at 1850°C and above. Y₄Al₂O₉ appeared to sublimate below 1850°C in the atmosphere used in this study. Depending on the secondary phase constitution, heat treatment affected thermal conductivity favorably or adversely. Occasionally, samples with similar lattice oxygen contents were found to have different thermal conductivities, suggesting that factors besides dissolved oxygen can also influence K . Lattice parameter measurements indicated that, within the small range of lattice oxygen concentrations in the AIN samples studied, the c-axis was more sensitive than the a -axis to oxygen content.     

表面活性剂对水基纳米流体固液相变特性的影响

引言蓄冷是利用谷电生产冷能并储存起来以满足峰电时空调负荷需求的一种节能技术,能达到移峰填谷、稳定电力需求的目的。冰蓄冷是一种常用蓄冷技术,即利用具有较大凝固潜热水作为相变材料工质。     

纳米冷冻机油热导率的实验研究

采用两步法,以聚乙烯吡咯烷酮(PVP)为表面活性剂,制备了不同种类的纳米冷冻机油并对其分散稳定性进行了实验研究。采用Hot Disk热常数分析仪,测量了40℃下纳米冷冻机油(纳米材料为TiO₂、Al₂O₃、Fe₂O₃、石墨和碳纳米管,体积分数为0.05%、0.1%、0.2%、0.5%、1%和2%)的热导率,分析研究了颗粒体积分数、粒径、材质以及表面活性剂等因素的影响。结果表明:纳米冷冻机油的热导率随着颗粒体积分数的提高而增大;相同体积分数下随着颗粒粒径的增大而减小,而相同粒径下又随着颗粒材质热导率的提高而增大;同时分散稳定性优的纳米冷冻机油热导率较高。基于纳米粒子的体积分数、粒径、团聚理论和布朗运动开发了纳米冷冻机油热导率预测模型,并与实验数据进行比较,发现预测值与90%的实验数据偏差在±3%以内,平均偏差1.6%。     

聚苯乙烯-二氧化硅@十四烷复合纳米相变胶囊的表征及其乳液性能

采用细乳液原位聚合法,研制了以正十四烷(Tet)为芯材、高热导率二氧化硅(SiO₂)改性的聚苯乙烯(PS)为壳层的新型复合纳米相变胶囊蓄冷材料;对复合胶囊形貌、组成以及热物性进行纳米粒度、透射电镜(TEM)、X射线光电子能谱(XPS)、差示扫描量热(DSC)以及热失重(TG)等表征,并测试其乳液的热导率、比热容、黏度及机械稳定性。结果显示:复合相变胶囊平均粒径为64.90 nm,具有规整的球形核壳结构,表面硅含量(质量分数)为3.27%,相变潜热达83.38 J·g^-1,复合壳材对芯材有很好的保护作用;其乳液的热导率及比热容峰值均优于未用SiO₂改性的纳米胶囊乳液,且乳液具有较高机械稳定性和较低黏度,可作为潜在的蓄冷用功能热流体。     

Densification, Structure, and Thermophysical Properties of Ytterbium–Gadolinium Zirconate Ceramics

(Yb _x Gd_{1− x} )₂Zr₂O₇ (0≤ x ≤1.0) ceramic powders synthesized with the chemical-coprecipitation and calcination method were pressureless-sintered at 1550–1700°C to develop new thermal barrier oxides with a lower thermal conductivity than yttria-stabilized zirconia ceramics. (Yb _x Gd_{1− x} )₂Zr₂O₇ ceramics exhibit a defective fluorite-type structure. The linear thermal expansion coefficients of (Yb _x Gd_{1− x} )₂Zr₂O₇ ceramics increase with increasing temperature from room temperature to 1400°C. The measured thermal conductivity of (Yb _x Gd_{1− x} )₂Zr₂O₇ ceramics first gradually decrease with increasing temperature and then slightly increase above 800°C because of the increased radiation contribution. YbGdZr₂O₇ ceramics have the lowest thermal conductivity among all the composition combinations studied.     

Y2O3对高热导率Si3N4陶瓷显微结构和性能的影响

以氧含量相对较高的“平价”Si₃N₄粉体(氧含量1.85%(质量分数))为原料,Y₂O₃-MgO作为烧结助剂,制备低成本高热导率Si₃N₄陶瓷,研究Y₂O₃含量对Si₃N₄陶瓷致密化、显微结构、力学性能及热导率的影响。结果表明,适当增加Y₂O₃的加入量不仅可以促进Si₃N₄陶瓷的致密化和显微结构的细化,还有助于晶格氧含量的降低和热导率的提升。Y₂O₃含量为7%(质量分数)的样品在1 900 ℃烧结后的综合性能最佳,其相对密度、抗弯强度、断裂韧性和热导率分别为99.5%、(726±46) MPa、(6.9±0.2) MPa·m^1/2和95 W·m^-1·K^-1。     

空调用纳米有机复合相变蓄冷材料制备与热物性

针对目前空调用有机相变蓄冷材料热导率低的问题,将具有高导热性的纳米材料(MWNTs、Al₂O₃、Fe₂O₃)添加到所开发制备的二元复合有机蓄冷材料(质量比73.7:26.3的辛酸/肉豆蔻醇)中,从纳米材料的种类和浓度两方面,研究其对复合有机蓄冷材料热物性的影响。实验发现:对于MWNTs、Al₂O₃、Fe₂O₃ 3种纳米材料,当其质量分数分别小于0.3%、0.4%、0.8%时,对应纳米复合材料热导率随纳米材料浓度的增加幅度较为明显;与原二元复合有机相变蓄冷材料相比,添加0.3%的MWNTs,热导率提高26.3%;添加0.4%的Al₂O₃,热导率提高13.1%;添加0.8%的Fe₂O₃,热导率提高32.1%;当在一定纳米材料质量分数(如0.7%)下,加入纳米颗粒的复合材料导热性能效果依次为Fe₂O₃>MWNTs>Al₂O₃。不同纳米粒子的添加对原蓄冷材料的相变温度和相变潜热影响很小,相变温度变化波动最大为0.4℃,相变潜热变化波动范围最大为1.4%。     

The effect of functionalisation method on the stability and the thermal conductivity of nanofluid hybrids of carbon nanotubes/gamma alumina

Based on our previous studies that focused on the synthesis of a nanohybrid of multi-walled carbon nanotubes (MWCNTs) and gamma alumina (γ-Al₂O₃) particles, this paper reports the heat transfer properties and dispersion behaviour of the hybrid. In this study, functionalised CNTs were synthesised via a solvothermal process with various concentrations of carboxylic acid groups (–COOH). The microstructure of the synthesised nanohybrids was characterised via high-resolution transmission electron microscopy (HRTEM), transmission electron microscopy (TEM), and energy-dispersive X-ray spectroscopy (EDX). The MWCNT/γ-Al₂O₃ nanofluid was prepared using a two-step method. The thermal conductivities of different nanohybrids were measured with a KD2 probe using a modified transient hot wire method. The zeta potential and particle size distribution were determined to investigate the stability of the nanofluid.The results showed that the functional groups had a significant influence on the thermal conductivity of the hybrid nanofluid. The data showed that the enhancement in thermal conductivity reached up to 20.68% at a 0.1% volume fraction of hybrid, for a gum arabic (GA) based nanofluid.     

Thermal Conductivity: XIV, Conductivity of Multicomponent Systems

The thermal conductivity of a number of multi-component systems has been determined as a function of composition and temperature. These were silicate glasses, MgO-NiO, Al₂O₃-Cr₂O₃, UO₂-UO_2+x-ThO_2, ZrO₂-HfO₂-CaO, MgO-Mg₂-SiO₄, MgO-BeO, Al₂O₃-mullite, MgO-MgAl₂O₄, Al₂O₃-ZrO₂, Al₂O₃-glass, and Si-Sic. Analyses of these results indicate that a second component in solid solution markedly lowers the thermal conductivity. The second-component scattering mean free path is inversely proportional to concentration at low concentrations and independent of temperature at the temperatures studied (above room temperature). The conductivity of polyphase ceramics can be predicted if the conductivity of each phase, amount of each phase, and phase distribution (including pore phase) are known.     

纳米粒子对CO2水合物导热性能的影响

试验研究了不同种类（Al₂O₃、Cu、SiO₂）、不同质量分数（0.05%、0.1%、0.15%）及不同粒径（10、30、50 nm）的纳米粒子对CO₂水合物热导率的影响。结果表明温度为-5~5℃时,纯CO₂水合物热导率为0.553~0.5861 W·m^-1·K^-1,具有玻璃体的变化特性。分散剂SDBS的加入,可改善CO₂水合物-纳米粒子体系的导热性能。在相同的质量分数和粒径下,纳米Cu粒子对CO₂水合物热导率的增强作用最好,但综合考虑水合物生成特性和溶液悬浮稳定性,选用纳米Al₂O₃粒子较合适。Al₂O₃粒子粒径越小,水合物热导率越大,15 nm比50 nm纳米粒子体系中CO₂水合物热导率的增长率平均提高了12.7%。此外,CO₂水合物热导率随Al₂O₃粒子质量分数的增大而增大,质量分数由0.05%增加到0.15%时,水合物热导率的增长率由4.2%提高到8.2%。     

掺镁碳酸熔盐液体导热特性

为克服碳酸熔盐热导率较低的不足,提出通过向三元碳酸熔盐（Li₂CO₃-Na₂CO₃-K₂CO₃）掺杂金属镁粉来改善导热性能的新思路,采用静态熔融法制备了掺杂1%、2%掺镁碳酸熔盐复合材料。采用扫描电镜-X射线能谱、阿基米德法、差示扫描量热法（DIN比热测试标准）和激光闪光法,分别观察了掺镁碳酸熔盐形貌结构,测量了熔盐和复合熔盐液体的密度、比热容、热扩散系数,最后计算获得复合熔盐液体的热导率。研究结果表明,镁粉的加入改变了纯盐（三元碳酸熔盐）的形貌结构,熔体内形成大量的2~5 μm球体颗粒,与纯盐相比,1%掺镁碳酸熔盐液体密度、热扩散系数和热导率都得到增强,液体比热容减小,复合熔盐液体的平均热导率增加了21.67%;2%掺镁碳酸熔盐液体密度、热扩散系数和热导率同样得到增强,虽然复合熔盐液体的比热容减小,但其平均热导率仍然增加了19.07%。1%掺镁碳酸熔盐具有更高的液体密度、热扩散系数和热导率,可作为传热介质在太阳能热发电传蓄热系统推广。     

CuO/H2O纳米流体的池沸腾传热及预测

通过络合-沉淀法合成氧化铜纳米颗粒,制备铜颗粒的直径在40～100 nm,晶型为正六面体。利用“两步法”制备水基氧化铜纳米流体。考察了不同质量分数纳米流体的热导率、接触角变化和加热表面颗粒沉积对核沸腾传热性能的影响,并利用可视化记录沸腾过程气泡行为。结果表明：在测试质量分数范围内,传热系数随热通量增加而增大,当质量分数达到0.1%时,强化率最大为146.1%。经过分析可知纳米流体的接触角度、热导率、颗粒沉积以及颗粒扰动对水基氧化铜纳米流体强化传热作用均有影响。通过高速摄像采集质量分数0.07%纳米流体沸腾过程验证结论的可靠性。并对纳米流体核沸腾传热过程建立气泡动力学经验模型,模型计算结果与实测值相对偏差在±10%以内。     

Preparation, Electrical Conductivity, and Thermal Expansion Behavior of Dense Nd1−xCaxCrO3 Solid Solutions

Nd_{1− x} Ca _x CrO₃ (0≤ x ≤0.25) solid solutions are synthesized using a two-step calcination solid-state reaction method and can potentially be used as interconnect applications in solid oxide fuel cells (SOFCs). The lattice parameters and unit cell volume decrease with an increase of the Ca²⁺ dopant concentration at the A-site. On the other hand, the relative density, electrical conductivity, and thermal expansion coefficient (TEC) increase with an increase of Ca²⁺ contents. Calcium doping significantly depresses the chromium vaporization of NdCrO₃, thus accelerating the sintering and densification of the oxides. Nd_{1− x} Ca _x CrO₃ with x =0.25 shows the best electrical conductivity of 28.8 and 1.1 S/cm at 850°C in air and hydrogen, respectively, with a high relative density of 98.0% and a good TEC of 9.19 × 10⁻⁶ K⁻¹ in the temperature range from 30° to 1000°C in air. This indicates that Nd_0.75Ca_0.25CrO₃ is a promising candidate as an interconnect material for application in SOFCs.     

Proton-Conductive Membranes Doped with Orthophosphoric Acid Based on Inorganic–Organic Hybrid Materials

A series of proton-conductive inorganic–organic hybrid membranes doped with phosphoric acid (H₃PO₄) have been prepared by the sol–gel process with 3-glycidoxypropyltrimethoxysilane (GPTMS), 3-aminopropyltriethoxysilane (APTES), and tetraethoxysilane (TEOS) as precursors. High proton conductivity of 3.0 × 10⁻³ S/cm with a composition of 50TEOS–30GPTMS–20APTES–50H₃PO₄ was obtained at 120°C under 50% relative humidity (RH). The differential thermal analysis curve showed that thermal stability of membrane is significantly enhanced by the presence of an SiO₂ framework up to 250°C. X-ray ray diffraction revealed that the gels were amorphous. Infrared spectra showed a good complexation of H₃PO₄ in the matrix. The porous hybrid membrane, characterized by scanning electron microscopy, shows humidity-dependent conduction, and the conductivity under 75% relative humidity was significantly improved by addition of APTES due to the increase in the concentration of the defective site in the hybrid matrix.