A Group Contribution Method for the Prediction of Thermal Conductivity of Liquids and Its Application to the Prandtl Number for Vegetable Oils

Abstract

Data on thermal conductivity of liquids, as a function of temperature, are essential in the design of heat- and mass-transfer equipment. A number of correlations have been developed to predict thermal conductivity of liquids with limited success. Among the correlations proposed so far, only the correlation due to Nagvekar and Daubert (Ind. Eng. Chem. Res. 1987, 26, 1362) is based on group contributions. In this paper, a new group contribution method is developed based on the Klaas and Viswanath (Ind. Eng. Chem. Res. 1998, 37, 2064) method for prediction of thermal conductivity of liquids and the results are compared to the method of Nagvekar and Daubert and other existing correlations. The present method predicts thermal conductivity of some 228 liquids that encompass 1487 experimental data points with an average absolute deviation of 2.5%. The group contribution method is used to examine the temperature dependence of Prandtl number for vegetable oils.

Research on the Influencing Factors of China Apple Juice Trade

“…If a country has a product with large international market share, the product is likely to have a great deal of competitiveness in the international market (Cheng et al, 1994;Rodenbush et al, 1999;Tan, 2007;Ying-Ying et al, 2010). Since China joined in the WTO, the share of China's apple juice has been increasing steadily in the international market, up to the peak (49%, almost half of the whole quantity) in 2007, but it dropped to 42% in 2009 because the international financial crisis (Table 1) Market share has been living the first in the world, which shows apple juice export of China has strong competitive in the world.…”

“…To extend the industrial chain by building brand and strengthen the construction of circulation, reduce circulation cost. To improve the production technology, strengthen the research and development, the technology and the world synchronicity (Rodenbush et al, 1999).…”

Non-isothermal dynamic model of a supercritical fluid extraction packed column

“…The carbon dioxide heat capacity and thermal conductivity pure data [9,10] were used to compute the gas phase heat capacity and thermal conductivity, assuming the influence of the solutes to be negligible. The thermophysical properties of liquid methyl oleate and squalene were estimated with the help of the original methods of Rowlinson [11] and Rodenbush and Viswanath [12]. The properties of the ternary liquid phase were assumed to be the weighted average of the pure-component data.…”

General method for prediction of thermal conductivity for well-characterized hydrocarbon mixtures and fuels up to extreme conditions using entropy scaling

“…For extreme conditions, limited experimental thermal conductivity data are available for well-characterized hydrocarbon mixtures, and there is a greater lack of thermal conductivity data available for complex mixtures, such as rocket propellant (RP), jet, and diesel fuels. Various correlations and theories have been developed for the prediction of thermal conductivity for pure hydrocarbons and their mixtures [13, 21-23, 30, 33-37] including structure-based group-contribution methods [38][39][40][41][42][43][44].…”