"rrt"l*;s - Port City International University

port cin' Intentationar [Jnit,ersio Joumar, vor-7( I &2 _{): 55 _62}

.{ .\E\\-APPROXI}IATION _METHOD

FOR THE ESTIMATION _OF VISCOSITIES OF LIQUID _{MIXTURES USING}

UNIFAC-USCO MODEL

M. Mehedi Hasan Rockyl, Iqbal Hossen,, M. Kamrul Hassan2, Syeda Rahimon _Naher3and *Shamim _Akhtar2

Deparrment of chernistry, university _of chittagong, chittagong, Bangladesh.

lDepartment

of Natural slien.e, port

city rrt"r*tiorrul

University, chittagong.

2Depaftment

of chemistry, chittagong university of Science

&

Technology, chittagong.

sDepartment

of Science

&

Humanitier, technology, Cumilla.Bangladesh Army International University of Science

&

ABSTRACT

viscosity

is

considered as one

of

the most significant transport properties

in

the scientific point

of

_view and i-or.various chemical applications.

with

an increased popurarity of process _and reservoir simulators, there

is

always

an

acute need

for

consistent, reliable as

well

as accurate predictive _methods for viscosity calculations- The present study reports the viscosities

of 14

binary liquid systems involving various

tlpes of

alcohors, aromatics, and ketones predicted

in

the entire range of composition and' at different temperatures. computations _were performed by employing _the

LNIFAC-\ISCO

model' To investigate _its predictiue cupubility, _the

INIFAC-\TSC.

_{model has also} been tested

critically by

considerirg group interaction pa.amete.s belonging

to two

different categories:

o*

fiom original LNIFAC-\'ISCO _and

B,- from ^the

UNIFAC-WE.

Consideration of _B,n parameters in line with Q,,, has further led to easier predictions of both the dynamic _{and the} kinematic r iscosities ofvarious organic liquids in a wider range.

Kelnvords: LNIFAC-vlsco, liquid

_parameter. mixtures, viscosity,

predictive model, group

interaction

INTRODUCTION

From theoretical points

of

view, transpofi properlies have rong been used

to

understand molecular interactions

in

liquids'

A

prior knowledge

of

thermodynamics _and transport properties

of

multi-component mixtures

is

extremely important-",

"rrt"l*;s ^of

^{designing chemicar processes}

(Sohrevardi _et

al',

2017'I

with

the increased popularity _or

"nemi.at process and reservoir simulators, there is always an acute need for some consistent, reliable _as well as accurate predictive _methods for i'iscosity which is considered _as one of the most significant transporl properlies for scientific _studies and their subsequent chemical applications (Hossain et

al., 2076;wu,

1gg6; Zhao andJacquemin, 2011)' Models used

for

estimatin! viscosity

of

liquid mixtures may be classified as correrative or predictive in type' In correlative methods' the experimental _data for mixtures _{are used} for evaluation of model parameters (Kijevdanin _et

al',

2oo8). whereas,

p.op"rtio

_of pure components _are ut,ized in thepredictivemodels(Billah

etal',2}l8:Kijevdanin

"iot.,zoots;Zhangetal.,207g).

Inpredictive approach-based group contribution method mixture viscosities _are calculated using data of only pure components and the relevant functional group parameters. Moreover, group contribution _{models are}

trJ#ffi::#"""r0.,,1,,:,Jr: a faster

evatuation

of

thermo_physical properries

under

_different

In

this work' estimation of viscosities is made for various binary liquid systems employing predictive model known as

uNIFAC-usco

(Chevalier _et al.,79gg;Gaston-Bonhomme _et a..,7994).

To improve the prediction results, _a new approximate technique has been developed to overcome _the

*Correspondin

55