Correlation and Prediction of Thermal Conductivity Using the Redlich–Kwong Cubic Equation of State and the Geometric Similitude Concept for Pure Substances and Mixtures

Abstract

In this work, a model for the thermal conductivity of nonpolar and polar substances is developed based on the geometric similitude concept between the P−v (molar volume)−-T and T−k (thermal conductivity)−-P plots. The Redlich−Kwong equation of state is used to perform the geometric similitude. The parameters of the model are estimated by fitting experimental data of saturated liquid and saturated vapor. Generalized expressions in terms of the normal boiling point are proposed for the parameters of n-alkanes and n-alcohols. The calculated average absolute deviations are 7.63 and 8.55%, respectively, for the n-alkanes and the n-alcohols used to develop the generalized expressions. Also, some predictive calculations are performed, and deviations below 10.62 and 9.42% are obtained for n-alkanes and n-alcohols, respectively. In total, 2412 experimental data (952 correlated data and 1460 predicted data) in the temperature range of 95− to 645.5 K and pressures below 906.4 bar have been considered. The empirical model has been extended to binary and ternary mixtures using several approaches. In total, 16 mixtures in the temperature range between 287.55 and 345.48 K at 1.01 bar are evaluated. The deviations are below 4.63% when one binary interaction parameter is used. In general, the results indicate that the empirical model is simpler than the other models reported in the literature and generates adequate results.

Extension of a Group Contribution Method to Predict Viscosity Based on Momentum Transport Theory Using a Modified Peng–Robinson EoS

“…In eq 12, AADμ is the average absolute relative deviation between the calculated values (μ cal ) and pseudoexperimental values (μ exp ), 79 N is the number of experimental data, and μ is the viscosity at Pa•s. The objective function has been used to estimate the parameters associated with transport properties such as viscosity 17−20 and thermal conductivity 82 in the literature. The optimum parameters in terms of the number of carbon atoms are presented in Figure 1 and the following facts can be noticed:…”

“…The exception is related to the first substance of the homologous series, due to the different experimental behaviors when it is compared to the rest of the substances. 37,38,82,87,88 The literature review showed that these substances can be modeled as a separate functional group.…”

Friction Theory Model for Thermal Conductivity

“…Besides the empirical methods, correlations based on popular equations of state, such as the Peng and Robinson 31 (PR EoS), have also been developed. 32,33 To these equations the theorem of corresponding states has been applied, that is, similarity between p-v-T and T-λ-p behavior (Geometric Similitude Concept). 34 Teja and Tarlneu 35 introduced an effective carbon number concept to calculate the thermal conductivity of pure liquids and liquid mixtures.…”

“…Besides the empirical methods, correlations based on popular equations of state, such as the Peng and Robinson (PR EoS), have also been developed. , To these equations the theorem of corresponding states has been applied, that is, similarity between p-v-T and T-λ-p behavior (Geometric Similitude Concept) …”

Modelo simple y generalizado para estimar la conductividad térmica de líquidos iónicos

“…Cuando se carece de datos experimentales, esta importante propiedad debe ser estimada utilizando modelos empíricos, teóricos o semi-teóricos (Bonyadi y Rostami, 2017) y los basados en redes neuronales e inteligencia artificial (Hezave et al, 2012). Ejemplo de estos modelos son los desarrollados por Hopp y Gross (2019), Cardona et al (2019), Tomassetti et al (2020), Chen et al (2020). No obstante, estos modelos han sido utilizados para predecir sustancias orgánicas y no se han extendido a líquidos iónicos.…”