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چكيده انگليسي :

Abstract In this work the group contribution approach has been used in combination with the linear isothermregularity LIR equation of state to estimate pvT properties of primary secondary and tertiary alcohols ketonesand 1 carboxylic acid We assume each of these organic compounds as a hypothetical mixture of methyl methylene and a functional group in which the interaction potential of each pair is assumed to be the averageeffective pair potential Then the LIR equation of state EOS has been extended to such a hypothetical mixture Three basic compounds namely propane n butane and cyclohexane are used to obtain the contribution ofmethyl and methylene groups in the EOS parameters and also other appropriate compounds are used to obtain thecontribution of the functional groups such as 1 pentanol for the contribution of CH2OH 2 pentanol for thecontribution of CHOH 2 methyl 2 propanol t BuOH for the contribution of COH 2 pentanon for thecontribution of C O and 1 pentanoic acid for the contribution of COOH groups The calculated EOSparameters along with the modified EOS are then used to calculate the density of different compounds atdifferent pressures and temperatures with the average percentage error less than 1 2 Also the isothermalcompressibility T and thermal pressure coefficient at different pressures and the thermal expansioncoefficient p at different temperatures are calculated for some hydrocarbons with absolute percent deviationless than 1 0 Then a new method based on the modified Enskog theory MET is presented for calculation oftransport properties at high densities c We have substituted b0 from hard sphere HS theory and zerodensity transport properties from the kinetic theory of gases for HS in the MET expression As a result a simplelinear expression for self diffusion D and quadratic expressions for viscosity and thermal conductivity coefficients have been obtained in terms of Y at high densities c where Y T p T RT 1 Usingexperimental values of densities and the transport properties and calculated Y from the reported accurate equationof state EOS for Ar and Xe we found that the quadratic fits for viscosity and thermal conductivity and thelinear fit when T Tc for self diffusion hold quiet well with the correlation coefficient R2 0 9994 when c Also we have found that the curves for different isotherms of a fluid superimposed to each other at high densitiesover entire temperature range for which experimental data exist but the curves depend on the nature of fluid Wehave used the calculated values of density and thermal pressure coefficient from the MLIR along with thisapproach to predict viscosity of n alkanes from propane to n octane and cyclohexane at different densities c and temperatures and their viscosities have been predicted with the average percentage error less than 1 6 Tomake the approach more general we have used principle of corresponding states to give viscosity expressionindependent of fluid in terms of reduced variables Therefore one may use experimental data for one isotherm ofan arbitrary fluid to find the coefficients of reduced viscosity expression Then these coefficients may be used forother fluids at the same reduced temperature Tr to calculate the reduced viscosity Here we have selected n butane as a reference compound because of abundance of experimental data We have used the coefficients of theexpression for n butane and density and Y are calculated from the MLIR this approach gives viscosity ofhydrocarbons with average percentage error less than 1 7 Similar approach has been used to calculate the selfdiffusion coefficient and thermal conductivity of dense fluids In next section a wavelet neural network WNN has been used to predict density of 35 organic fluids suchas n alkanes cycloalkanes primary secondary and tertiary alcohols ketones and 1 carboxylic acids for witch thenumber of carbon atoms varying from 2 to 10 over wide ranges of temperature and pressure The WNN modelhas been constructed using 11

كلانتر، زهرا

پيش بيني خواص ترموديناميكي و انتقالي سيالات آلي چگال با استفاده از روش سهم گروه ها و شبكه ي عصبي موجك