A new temperature–thermal conductivity relationship for predicting saturated liquid thermal conductivity

Sastri, S. R. S.; Rao, K. K.

doi:10.1016/s1385-8947(99)00046-7

Cited by 65 publications

(45 citation statements)

References 32 publications

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“…No data at all were located for the thermal conductivity. The corresponding states coefficients in Table 3 were adjusted so that predictions are similar to those of the method of Sastri and Rao (Sastri & Rao, 1999). Parameters for the critical enhancement are presented in Table 4.…”

Section: Carbonyl Sulfidementioning

confidence: 99%

Models for viscosity, thermal conductivity, and surface tension of selected pure fluids as implemented in REFPROP v10.0

Huber¹

2018

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We describe models for the viscosity, thermal conductivity, and surface tension for selected fluids implemented in version 10.0 of the NIST computer program, NIST Standard Reference Database 23, also known as NIST Reference Fluid Thermodynamic and Transport Properties Database (REFPROP). These fluids do not presently have published reference fluid quality models in the open literature, so we provide preliminary models based on available data as an interim measure to allow calculations of these properties. Comparisons with available experimental data are given.

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Section: Carbonyl Sulfidementioning

confidence: 99%

Models for viscosity, thermal conductivity, and surface tension of selected pure fluids as implemented in REFPROP v10.0

Huber¹

2018

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“…Thus, in order to evaluate the proposed correlation, the new model was compared with other models at atmospheric pressure. The average values according to [12,13,27] were 8, 11.1, and 11.5%, respectively, whe reas for the suggested model AARE is equal to 4.82%. Conclusions.…”

Section: Resultsmentioning

confidence: 98%

A New Equation for the Thermal Conductivity of Liquid Refrigerants Over Wide Temperature and Pressure Ranges

Amooey

2017

J Eng Phys Thermophy

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This work presents a new simple equation for the thermal conductivity of liquid refrigerants as a function of the reduced temperature, molecular mass, reduced pressure, and the acentric factor. This model is applied for predicting the thermal conductivity of the refrigerants over the whole temperature and pressure ranges. A set of 915 data on the thermal conductivity for 30 refrigerants has been used. These refrigerants were divided into three categories on the basis of various chemical halogens forming the compounds and were investigated individually. For the data sets, the average error of the proposed model was 4.82%. The results show that the new equation can be used with confi dence in engineering calculations.Introduction. Thermal conductivity is evaluated primarily in terms of the Fourier law for heat conduction. It shows the capability of a substance to transfer heat by conduction. In fact, the higher the thermal conductivity, the higher the heat transfer coeffi cient. Knowledge of the thermal conductivity is required in numerous phenomena of scientifi c and practical interest, in particular, for refrigerants, though the values of their thermal conductivity are frequently not attainable with suffi cient reliability and are sometimes even unattainable.For computation of the thermal conductivity of liquids, a number of theories have been presented on the basis of the characteristic properties of materials, such as the heat capacity and/or density [1,2]. There are equations based on the theory of group contribution for calculating the thermal conductivity of liquids, such as those based on the intermolecular distances [3] or on the degree of association of liquids [4]. These equations are very often inappropriate for all compounds. Different correlations for the description of the thermal conductivity are proposed in [5][6][7][8][9][10][11][12][13].In the present research, the thermal conductivity is estimated from an empirical approach based on a number of fi xed physical parameters, and the results are tested on the large database for liquid refrigerants. The new equation is used for refrigerants over the whole ranges of temperatures and pressures, unlike previous equations that were applicable at atmospheric pressure. Description of the Simple Equation.In this research, an attempt is made to present an approach to calculating the thermal conductivity of refrigerants with a high accuracy over the whole range of temperatures and pressures. A total of 915 experimental points for the proposed correlation has been considered.The proposed equation presents a simple correlation for estimating the thermal conductivity of refrigerants as a function of the reduced pressure, reduced temperature, acentric factor, and the molecular weight. This new equation includes fi ve independent variables A i :

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“…The critical temperature (T c ), critical pressure (P c ), critical density (ρ c ), and critical compressibility factor (Z c ) of pure compounds are key properties in this regard as the critical constants are often necessary parameters in EoS calculations and in many thermophysical prediction models. [1][2][3][4][5][6] The n-alkane family is of particular importance due to the significant role it plays in the petrochemical field. However, due to thermal decomposition, experimental critical point data are scarce and potentially unreliable for n-alkanes larger than C 12 .…”

Section: Introductionmentioning

confidence: 99%

Uncertainty quantification and propagation of errors of the Lennard-Jones 12-6 parameters forn-alkanes

Messerly

Knotts

Wilding

2017

The Journal of Chemical Physics

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Molecular simulation has the ability to predict various physical properties that are difficult to obtain experimentally. For example, we implement molecular simulation to predict the critical constants (i.e., critical temperature, critical density, critical pressure, and critical compressibility factor) for large n-alkanes that thermally decompose experimentally (as large as C 48 ). Historically, molecular simulation has been viewed as a tool that is limited to providing qualitative insight. One key reason for this perceived weakness in molecular simulation is the difficulty to quantify the uncertainty in the results. This is because molecular simulations have many sources of uncertainty that propagate and are difficult to quantify. We investigate one of the most important sources of uncertainty, namely, the intermolecular force field parameters. Specifically, we quantify the uncertainty in the Lennard-Jones (LJ) 12-6 parameters for the CH 4 , CH 3 , and CH 2 united-atom interaction sites. We then demonstrate how the uncertainties in the parameters lead to uncertainties in the saturated liquid density and critical constant values obtained from Gibbs Ensemble Monte Carlo simulation. Our results suggest that the uncertainties attributed to the LJ 12-6 parameters are small enough that quantitatively useful estimates of the saturated liquid density and the critical constants can be obtained from molecular simulation. Published by AIP Publishing. [http://dx

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A new temperature–thermal conductivity relationship for predicting saturated liquid thermal conductivity

Cited by 65 publications

References 32 publications

Models for viscosity, thermal conductivity, and surface tension of selected pure fluids as implemented in REFPROP v10.0

Models for viscosity, thermal conductivity, and surface tension of selected pure fluids as implemented in REFPROP v10.0

A New Equation for the Thermal Conductivity of Liquid Refrigerants Over Wide Temperature and Pressure Ranges

Uncertainty quantification and propagation of errors of the Lennard-Jones 12-6 parameters forn-alkanes

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