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Aspen Gamble

Apr 07, 2018

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    Don't Gamble WithP yscal PropertiesFor Simula ionsF in din g g oo d va lu es

    fo r in a de qu ateo r m issin g p hy sic alp ro p er ty p a rame te rs

    is the key to asuccessful

    simu la tio n. A n dth is depen ds u ponch oosin g th e righ te stima tion me thods .

    E ric C . C a rls on ,Aspen Techno logy .nc .

    Chemica len gin eers use pro ces sS imU la .ti o n t o p er fo rm a . varietyo f impo rtan t wo rk. This workran ges from ca lcu la tio n s o fmass- and energy ba lan ces o f la rge flow-sheets to predic tio n o f the perfo rm ance o fp ro ces s a ltern atives tha t c an s av e m illio nso f dollars, An engin eer very quickly candefin e a complex flowsheet and an [hepro cess co nditio n s. Desk top computersnow allow ra ting. s izing. optim izatio n ,an d dyn am ic ca lcula tio ns tha t p revio uslyrequired la rge ma in frame computers . Inthe pa st, these simula tio n s were o ftenbuilt by a group o f experts , in c luding aphys ic al pro perty expert. N ow , s im ula to rssuch a s ASPEN PLUS. C hemCAD Ill,HYSIM , PRO 11, and SPEEDUP are eas i-er to use and mo re powerful. than thestanda lo ne program s o f the pas t. To day, asingleengineer can set up the ba s ic s imu-la tio n s pec ific atio ns , in cludin g th e phys i-c a l properties, in very little time.

    M iss ing o r in adequa te physic a l prop-erties , however, can underm ine the accu-racy o f a model o r even preven t you f romperfo rm in g the sim ula tio n .. Tha t so me re-quired in fo rm a tio n is m iss ing is no t ano versight in the s imula to r. A fter a ll, fo rmos t compounds. phys ica l property pa~rameters a re n ot known fo r every thermo -dynam ic mode! o r fo r aU tempera ture o rpres sure ranges. M odels have built-in a s-sum ptio ns an d pra c tic a l lim its tha t sho uldapply.

    [0 this a r tic le we will provide prac ti-c a l tips and techn iques to help you accu-

    - ra rely desc ribe the physic a l propertiesn eeded in a simula tio n . As an eng in eer.

    you alw ays w ill have to make a ssump-tio n s in term s o f physic a l properties ,however. The goa l o f this a rtic le is to out-lin e the appropr ia te as sumptio n s and topro vide techn iques when properties a remissing.The five important tasks

    Success fully desc ribing the phys ica lproperties to be used in a s im u la ti o n in -v olv es fiv e ta sk s:1. selec tin g the appropria te phys ica l

    p ro pe rty m eth od s;2. v alid atin g th e p hy sic al p ro perties ;3. desc rib in g nondarabank compo -

    nen ts (chem ica l spec ies o r compound)a nd m is sin g p ar am eters ;

    4. obta in in g and us in g phys ica l prop-er ty data ; an d

    5. estim ating an y m issing propertyparameters .

    It c an be a rgued tha t these ta sks a reno t sequen tia l and, to some degree, theya re co ncurren t. Durin g sim ula tio n devel-opmen t, however, you will n eed to vis itea ch a rea to be co nfiden t [ha t yo ur sim u-la t ion is a s ac cura te a s po ss ib le - sotha t impo rtan t dec is io n s c an be madeba sed o n the results o f yo ur s im ula tio ns .Se lecti n9 thea.ppropriatephysical property methods

    This es sen tia l firs t s tep will affec t a llsubsequen t ta sks in developing accura tephys ica l propen ies in yo ur s imula tio n .In deed. the cho ice o f the physic a l pro per-ty models fo r a simula tio n can be one o fthe mo st impo rtan t dec is io n s fo r an engi-n eer . Severa l fac to rs n eed to be con s id-

    C H E M IC A L E N G IN E E R IN G P R O G R .E .S S O C T O B E R 1 9 9 6 35

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    SUCCEEDING AT SIMULATION

    ered, and no single method can han -dle a ll sys tems. Table I lis ts so methermodynam ic models ava ilable insimula tors .

    The four fac to rs that you shouldcon sider when choo sing propertymethods are:

    [he n ature o f the properties o finterest;

    the co mpos itio n o f the mixture; the pressure a nd tem pera ture

    range; and th e a va ila bility o f p ara meters .To ea se the selec tio n o f the right

    physica l property methods, we sug-gest usin g the dec is io n trees shown inFigures L-3. These trees a re based onthe fo ur fa c to rs fo r selec ting propertymethods, and can be used when thechemica l componen ts and approxi-m ate tempera ture an d pressure ran gesa re known . W hile these diagrams ares implific a tio n s , they do show theba sic s teps o f the dec is io n -makingpro cess , while the no tes in the s ideba ramplify some o f the key po in ts .The nature of (he properties of in-terest. A question tha t you may askyourself when starting a simula tio n is"Do es the cho ice o f physica l pro pertymethods matter?" The an swer is anempha tic YES. The cho ice canstro ngly a ffec t the predic tio n of thesimula tio n . You should be selec ting acol lec t ion of methods that w ill bestpredict th e properties o r results o f in -terest to you.

    Because many chem ica l pro ces ss im ula tio ns in clu de distillation ..strip-ping, o r evapora tio n , one impo rtan tpo ten tia l co nsidera tio n fo r the cho iceof phys ic a l property models isvapo r/liquid equilibrium (V LE ). Thisis the a rea in w hic h the m ost physica lproperty wo rk is fo cused in chemica lengineering. L iq ui d/l iq ui d e qu il ib ri -um (LLE ) a lso becomes impo rtan t inpro cesses such a s so lven t extra c tiona n d e xtr ac ti ve d is ti ll ati o n.

    Ano ther critic a l con sidera tio n ispure-C omponen t and mixture en-tha lpy. E nrha lpies an d hea t c apac itiesa re im portan t fo r un it o pera tion s sucha s hea t exchangers , c ondensers , dis -tilla tio n c olu mn s, a nd rea cto rs .

    Table 1.Thermodynamic property modelsavailable in a simulator.E qua ti on -o l- Sl al e M il de isBenedic t-Webb-RubinlBWR.I-Lee-Star t ingHayden-O 'Conne l l *H yd ro ge nflu orid e e qu atio n o f s ta te fo rhexarner izat ion"Id ea l g as la w*L ee -K e sle r I LK ]Lee-Kes le r -P lockerPengRobinson IP .R)Per turbed-Herd-ChainP re dic tiv e S R KR ed lic h-K wo ng I R KIR e dlic h Kw on gS oa ve I RK SIRKSor PR with Wo ng "S an dl er m ix in g r ul eR KS o r P R w rth m od in ed -H llro nV id al-Z m ix -i n g r u leS an ch ez -L a c om be fo r p oly m er s* N ot us ed fo r the liq uid p has e

    Act iv ity C o ef fi ci en t M o de lsE le c tro ly te N R TLAory-Hugg insNRTLS catchard-H i ldebrandUN IQUACUN IFACV an L aa rWi lsonSpecial ModelsA P I s ou r-w ate r m e th odB ra un K -IOChao -Seade rG re ys o n - S tr a e dKent-EisenbergS te am T ab le s

    Ncn-elsctolvte S ee F ig ure 2

    Polar

    ElectolyteReal?

    Electol 'yte N R T Lo r P itz er

    A ll Nonpo l a r

    Pe ng , Rob i n son ,Be dlich-Kwong-Scave,L e e K e s l e r- P l oc k e r

    Polarity

    Rea lorP s e u d c c o rn p o n e n ts

    Chac-Seade r ,G ravs on -S tra ed o rB rau n K -IO

    P?

    Vacuum Braun K -IO o r Id ea l

    36 O CTO BER 1 99 6. C HEM IC AL E NG INE ERIN G PR OGR ESS

    < ! > Elec to ly tes< ! ! > Pressure Figure 1. The first steps for selecting physical property methods.

    Sou r ce : (7 )

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    Navigating the decision treesH ere a re s om e p oin te rs to he lp yo u n av ig ate the d ec is io n tre es tha t a p-p ea r a s F ig ure s 1-3.

    Wha t a r e pseuaocomoonen ts ? In m an y a pp lic atio ns w he re o nly n on -p ola r m ole cu le s a re p re se nt (s uc h a s in hyd ro ca rb on p roc es sin g a nd re -fin in g) . the m ix tu re is s o c om p le x tha t in ste ad o f re pre se ntin g it b y a ll thek no wn c on stitu en ts , it is e as ie r to g ro up the c on stitu en ts b y s om e u se fu lp ro pe rty s uc h a s b oilin g p oin t. In this w ay , a m ix tu re o f h un dre ds o f c on -s titu en ts c an b e re du ce d to 30 o r fe we r. T he p ro pe rtie s a t t he se g ro up edc on stitu en ts , c alle d p se ud oc om p on en ts , a re re pre se nte d b y a n a ve ra gebo ilin g p o in t, s p ec ific g ra v rty , a n d m ole c u la r w eight I f yo u do n ot us ep se ud o-c om p on en ts , the c on stitu en ts s ho uld b e d es crib ed b y a m o le cu -la r fo rm ula a nd a re re fe rre d to a s re al c om p on en ts .

    Wh y a re e le ctr oly te m ix tu re s d iffe re nt? E le c tr oly te m i xtu re s in c lu d ec om pon en ts tha t a re c ha rg ed m ole cu le s (io ns l o r tha t fo rm s alts . S om es im ula to rs a llo w c alc ula tio n o f e le ctro ly te re ac tion e qu ilib rium w ithp has e e qu ilib r iu m. T his is a ve ry p ow erfu l m ethod a nd its us ag e c ove rsmany a pp lic atio ns s uc h a s c au stic s cru bb in g, n eu tra liz atio n. a cid p ro -d uc tio n, a nd s alt p re cip ita tio n. T he n on id ea lity o f e le ctro ly te s olu tio ns ,u su ally c on ta in in g w ate r, c an b e o bs erv ed in b oil in g p oin t e le va tio n, s alt-in g o ut o f g as es ltha t is , a dd in g s alts to the s olu tio n to c ha ng e the s olu bil-ity o f g as es ), a nd s alt p re c i p ita tio n, T he m os t c om m on e le ctro ly te m ath-o ds a re the P itze r m od el, a nd the m od ifie dN RT L a ctiv ity c oe ffic ie ntm od el o f C he n a nd c ow orke rs . S om e e le ctro ly te s, like fo rm ic ac id a nda ce tic a cid , a re v ery w ea k a nd a n e le ctro ly te m e tho d is n ot re qu ire d.

    W hich type of me/hod should be chosen for mouses conta iningpo la r c omponen ts tm l no e lect ro ly tes? T he re a re tw o g ro up s o f m e tho ds- b as ed o n a ctiv ity c oe ffic ie nts o r e qu atio ns o f s ta te . U s e a ctiv ity -c oe f-fic ie ntb as ed m e tho ds w he n p re ss ure s a re lo w to m e diu m [ty pic ally le sstha n 1 0 b ar o r 150 p sia ) a nd if n o c om p on en ts a re n ea r c ritic al p oin t. A c-tiv ity c oe ffic ie nt m od els a ls o o fte n a re u se d to a cc ura te ly p re dic t n on -id

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