Empirical Approach for Predicting Viscosities of Liquid Hydrocarbon Systems: Defined Compounds and Coal Liquids and Fractions

Abstract

A single-parameter empirical method, based on the effective carbon number concept, was developed to predict the viscosities of defined (alkanes, alkenes, aromatics, alicyclics, and hydrocarbon mixtures) and undefined (coal liquids and coal liquid fractions) hydrocarbon liquids at various temperatures and for pressures up to 700 bar. The only parameter required for estimating the viscosities of a hydrocarbon system is the effective carbon number, which can be obtained from a single liquid viscosity datum of the compound using one of two proposed correlations, that is, n-alkane correlation or aromatic correlation. Also, experimental data on the viscosities of laboratory-generated coal liquid oils were generated and used in the evaluation of the model. The new method, when tested on viscosity data of defined and undefined hydrocarbon liquid compounds at various pressures and temperatures, yielded an overall average absolute deviation (AAD) of 4.11% and 9.99%, respectively. The model was also found to compare favorably with other methods available in the literature.

Predicting the viscosity of liquid mixtures consisting of n-alkane, alkylbenzene and cycloalkane species based on molecular description

“…This state of affairs is particularly acute for liquid viscosity which exhibits a rapid increase as one approaches the solidification line, thus putting severe constraints on the accuracy with which the viscosity can be predicted, as any proposed prediction model will be very sensitive to the value of the input parameters, primarily temperature and density. The lack of underlying theory has led to a number of different approximate approaches that are based on kinetic theory [10][11][12][13][14], corresponding states theory [15][16][17][18][19][20][21][22], free-volume concept [23][24][25][26], friction theory [27][28][29][30][31], relationship with residual entropy [32][33][34][35], density scaling [36][37][38], effective carbon number approach [39,40] and the expanded fluid based approach [41][42][43] among others. The plethora of predictive models is useful for practitioners, but we are still lacking a comprehensive comparison against reliable experimental data in order to ascertain the accuracy and the range of validity of different models.…”

Surrogate Generation and Evaluation for Diesel Fuel

“…According to this approach, it is only necessary to define one viscosity value at a specified temperature to determine the values of the parameters. 40 For most of the pure components, the 16 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 dynamic viscosity was provided at 40 ℃, but due to the lack of experimental data for some components, data at a different, but similar, temperature were taken.…”

Surrogate Generation and Evaluation for Biodiesel and Its Mixtures with Fossil Diesel

“…where the empirical parameters A and B are determined with the ECN-method. 29 The pure component viscosity of the FAME is calculated with the Vogel equation…”