Modelling reactive distillation
Modelling reactive distillation Modelling reactive distillation
5198 R. Taylor, R. Krishna / Chemical Engineering Science 55 (2000) 5183}5229of Seader (1985) for background and original literaturecitations. Brief reviews of early RD algorithms are byHolland (1981) and by Hunek, Foldes and Sawinsky (1979).Short-cut methods involve a number of simplifyingassumptions that are made in order to derive simpleapproximate equations that can be used for rapid computations.It is quite di$cult to derive generic short-cutprocedures for RD because of the many ways in whichchemical reactions in#uence the process (see, however,Ciric & Spencer, 1995). Bock and Wozny (1997) showthat the assumption of chemical equilibrium, often madein developing short cut methods, is inappropriate formany RD processes.Tearing methods involve dividing the model equationsinto groups to be solved separately. A brief description ofcomputer based tray-to-tray calculations for the RD ofethylene oxide and water was given by Corrigan andMiller (1968). Tray-to-tray calculations and parametricstudies for the simulation and optimisation of an RDcolumn for trioxane synthesis are described by Hu, Zhou& Yuan (1999). The bubble-point method of Wang andHenke (1966) was extended by Suzuki, Yagi, Komatsuand Hirata (1971) to be able to deal with chemical reactions.Suzuki's method was used by Babcock and Clump(1978). The so-called θ method developed for conventionaldistillation columns by Holland and his manycollaborators (see, Holland, 1963, 1981) was extended toRD operations by Komatsu and Holland (1977) andnamed the multi-θ}η method. The method is applied tothe esteri"cation of acetic acid. Other papers from thisgroup are Izarraz, Bentzen, Anthony and Holland (1980)and Mommessin, Bentzen, Anthony and Holland (1980).Mommessin and Holland (1983) discuss the computationalproblems associated with multiple columns. Savkovic-Stevanovic,Mis\ ic-Vukovic, Boncic-Caricic, Tris\ ovicand Jezdic (1992) used the θ method to model an esteri"-cation of acetic acid and ethanol carried out in a glasscolumn that was 33 mm in diameter and 1000 mmtall. The calculated temperature pro"le and productcompositions are in good agreement with the measuredquantities.Solving all of the independent equations simultaneouslyusing Newton's method (or a variant thereof)nowadays is an approach used very widely by authors ofmany of the more recent papers in this "eld (see, forexample, Pilavachi, Schenk, Perez-Cisneros and Gani,1997; Lee & Dudukovic, 1998). Holland (1981) providesa cursory description of this approach to RD simulation.More details and illustrative examples are to be found inthe works of Block (1977); Block and Hegner (1977);Kaibel, Mayer and Seid (1979) and Simandl and Svrcek(1991).Relaxation methods involve writing the MESH equationsin unsteady-state form and integrating numericallyuntil the steady-state solution has been found (Komatsu,1977; Jelinek & Hlavacek, 1976). Komatsu compares hisEQ stage model calculations to his own experimentaldata for one experiment showing that the EQ modelcomposition pro"les are qualitatively correct. Theauthors from Prague provide three numerical examplesinvolving esteri"cation processes. Relaxation methodsare not often used because they are considered to betoo demanding of computer time. They are, of course,closely related to dynamic models. Bogacki, Alejski& Szymanowski (1989) used the Adams}Moultonnumerical integration method to integrate a simpli"eddynamic model that neglects the enthalpy balance toa steady-state solution. Numerical results for a singleexample are compared to numerical results obtained byKomatsu (1977).There also exists a class of algorithm that really isa combination of equation tearing and simultaneoussolution in that Newton's method is used to solve a subsetof the MESH equations, but in which other methodsare used to solve the remaining equations. Papers byNelson (1971), Kinoshita, Hashimoto and Takamatsu(1983), and by Tierney and Riquelme (1982) fall into thiscategory. Very few RD examples accompany these papers.Takamatsu, Hashimoto and Kinoshita (1984) andKinoshita (1985) used a similar approach to model columnsfor an unusual application: heavy water enrichmentusing hydrophobic catalysts.Isla and Irazoqui (1996) use Newton's method to solvethe equations that model what they refer to as a `partialequilibriuma stage. However, despite the new name,theirs is essentially the same EQ model employed byalmost everyone else in that the exiting streams are inphase equilibrium, but not in chemical equilibrium witheach other. Parametric studies involving the e!ects ofcatalyst load and distribution, operating pressure andre#ux ratio are reported.Homotopy-continuation methods are employed mostoften for solving problems that are considered very di$cultto solve with other methods (e.g. Newton's). Formore details about this method, the reader is referred toWayburn and Seader (1987). Homotopy-continuationwas "rst applied to RD operations by Chang and Seader(1988). Their paper is illustrated by a number of casestudies involving the esteri"cation of acetic acid andethanol to ethyl acetate and water. Bondy (1991) describesphysical continuation approaches to solving RDproblems. Lee and Dudukovic (1998) have also usedhomotopy continuation to solve both EQ and NEQmodels of RD operations. Continuation methods are alsouseful for studying parametric sensitivity (see, forexample, Sneesby, TadeH and Smith, 1997c) and for locatingmultiple steady-states (Pisarenko, Anokhina& Sera"mov, 1993).Alejski, Szymanowski and Bogacki (1988) used a minimisationmethod due to Powell (1965) to solve theMESH equations. This approach is, however, rather slowto converge. Numerical results for the esteri"cation of
R. Taylor, R. Krishna / Chemical Engineering Science 55 (2000) 5183}5229 5199acetic acid with ethanol were compared with data fromKomatsu (1977). Komatsu carried out experiments onthe esteri"cation system of acetic acid and ethanol. Theexperiments were carried out in a column of 7 trays eachwith a single bubble cap. The trays had an inside diameterand spacing of 140 mm. Liquid-phase compositionpro"les are provided for "ve experiments. There are also3 sets of data for a #ash RD. Alejski et al. (1988), as wellas Simandl and Svrcek (1991), show that the shape of thepro"les obtained by the EQ model is largely in agreementwith the shape of the pro"les measured byKomatsu, although there are some signi"cant quantitativedi!erences. Alejski and Szymanowski (1988, 1989)provide a brief (in Polish) review of RD algorithms.In a later paper Alejski (1991a) models the liquid #owacross a tray by a sequence of mixing cells, each of whichis considered to be a non-equilibrium cell. Departuresfrom equilibrium were handled through the calculation(in the usual way) of the point e$ciency. The modelequations were solved using a relaxation method combinedwith Newton's method for computing the variablesat each time step. A comparison between the numericalresults of Alejski (1991a) obtained with an equilibriumcells-in-seriesmodel and the experimental data of Marek(1956) shows that the assumption of complete mixing onthe tray is much less successful than the multi-cell modelat predicting the actual composition pro"les. Marek(1956) had described a plant for the production of aceticanhydride. Experimental composition pro"les are providedfor a single set of operating conditions.Alejski (1991b) investigated the steady-state propertiesof an RD column in which parallel reactions take place.It was assumed that reactions occur in the liquid-phaseand the reactions are rate controlling. Each stage wasassumed to be perfectly mixed, and the interstage #owswere equimolar. The vapor leaving any stage was inphysical equilibrium with the liquid in this stage. Alejksilooked at the in#uence of reactants' volatilities, reactionequilibrium constants, reaction rates, re#ux ratio, locationof feed inlets, number of theoretical stages and distillaterate upon the yield, selectivity and productdistribution. As has been reported elsewhere, the columnpressure is an important factor that strongly a!ects reactionrates by changing the column temperature pro"le.Venkataraman, Chan and Boston (1990) describe theinside-out algorithm known as RADFRAC that is part ofthe commercial program Aspen Plus. Inside-out methodsinvolve the introduction of new parameters into themodel equations to be used as primary iteration variables.Four examples demonstrate that RADFRAC canbe applied to a wide variety of reactive separation processes.RADFRAC is able to handle both equilibriumreactions as well as kinetically limited reactions. Simandland Svrcek (1991) provide more details of their ownimplementation of an inside-out method for RDsimulation.RADFRAC has been used by many other authors.Quitain, Itoh & Goto (1999a) modelled a small-scalecolumn used to produce ETBE from bioethanol. Simulationresults are compared to experimental data. A secondpaper (Quitain, Itoh & Goto, 1999b) used RADRAC tomodel an industrial-scale version of the same process.Bezzo et al. (1999) used RADFRAC to study the steadystatebehaviour of an actual industrial RD column producingpropylene oxide from propylene chlorohydrinand calcium hydroxide. The thermodynamic propertiesof this system are complicated by the presence of electrolytesin the liquid-phase and by salting out e!ects.Reaction kinetics were modelled using the expressionsreported by Carra, Santacesaria, Morbidelli and Cavalli(1979b). By adjusting the Murphree e$ciency the authorswere able to obtain the best possible agreement betweenthe plant data and the simulations.Davies, Jenkins and Dilfanian (1979) describe a variationon the standard EQ stage model that is depicted inFig. 19. The vapor/liquid contacting section is modelledas a conventional vapor}liquid equilibrium stage (withoutreaction). The outgoing liquid stream passes to a reactorwhere chemical equilibrium is established. Thestream leaving this reactor passes on to the next equilibriumstage. The disadvantage of this approach is that itfails to properly account for the in#uence that chemicalequilibrium has on vapor}liquid equilibrium (and viceversa). The model is used to predict the temperature andcomposition pro"les in a 76 mm diameter column inwhich formaldehyde is reacting with water and methanol.Good agreement between predicted and measured valuesFig. 19. Equilibrium stage model used by Davies et al. (1979).
- Page 7 and 8: R. Taylor, R. Krishna / Chemical En
- Page 9 and 10: R. Taylor, R. Krishna / Chemical En
- Page 12 and 13: 5194 R. Taylor, R. Krishna / Chemic
- Page 14 and 15: 5196 R. Taylor, R. Krishna / Chemic
- Page 18 and 19: 5200 R. Taylor, R. Krishna / Chemic
- Page 20 and 21: 5202 R. Taylor, R. Krishna / Chemic
- Page 22 and 23: 5204 R. Taylor, R. Krishna / Chemic
- Page 24 and 25: 5206 R. Taylor, R. Krishna / Chemic
- Page 26 and 27: 5208 R. Taylor, R. Krishna / Chemic
- Page 28 and 29: 5210 R. Taylor, R. Krishna / Chemic
- Page 30 and 31: 5212 R. Taylor, R. Krishna / Chemic
- Page 32 and 33: 5214 R. Taylor, R. Krishna / Chemic
- Page 34 and 35: 5216 R. Taylor, R. Krishna / Chemic
- Page 36 and 37: 5218 R. Taylor, R. Krishna / Chemic
- Page 38 and 39: 5220 R. Taylor, R. Krishna / Chemic
- Page 40 and 41: 5222 R. Taylor, R. Krishna / Chemic
- Page 42 and 43: 5224 R. Taylor, R. Krishna / Chemic
- Page 44 and 45: 5226 R. Taylor, R. Krishna / Chemic
- Page 47: R. Taylor, R. Krishna / Chemical En
R. Taylor, R. Krishna / Chemical Engineering Science 55 (2000) 5183}5229 5199acetic acid with ethanol were compared with data fromKomatsu (1977). Komatsu carried out experiments onthe esteri"cation system of acetic acid and ethanol. Theexperiments were carried out in a column of 7 trays eachwith a single bubble cap. The trays had an inside diameterand spacing of 140 mm. Liquid-phase compositionpro"les are provided for "ve experiments. There are also3 sets of data for a #ash RD. Alejski et al. (1988), as wellas Simandl and Svrcek (1991), show that the shape of thepro"les obtained by the EQ model is largely in agreementwith the shape of the pro"les measured byKomatsu, although there are some signi"cant quantitativedi!erences. Alejski and Szymanowski (1988, 1989)provide a brief (in Polish) review of RD algorithms.In a later paper Alejski (1991a) models the liquid #owacross a tray by a sequence of mixing cells, each of whichis considered to be a non-equilibrium cell. Departuresfrom equilibrium were handled through the calculation(in the usual way) of the point e$ciency. The modelequations were solved using a relaxation method combinedwith Newton's method for computing the variablesat each time step. A comparison between the numericalresults of Alejski (1991a) obtained with an equilibriumcells-in-seriesmodel and the experimental data of Marek(1956) shows that the assumption of complete mixing onthe tray is much less successful than the multi-cell modelat predicting the actual composition pro"les. Marek(1956) had described a plant for the production of aceticanhydride. Experimental composition pro"les are providedfor a single set of operating conditions.Alejski (1991b) investigated the steady-state propertiesof an RD column in which parallel reactions take place.It was assumed that reactions occur in the liquid-phaseand the reactions are rate controlling. Each stage wasassumed to be perfectly mixed, and the interstage #owswere equimolar. The vapor leaving any stage was inphysical equilibrium with the liquid in this stage. Alejksilooked at the in#uence of reactants' volatilities, reactionequilibrium constants, reaction rates, re#ux ratio, locationof feed inlets, number of theoretical stages and distillaterate upon the yield, selectivity and productdistribution. As has been reported elsewhere, the columnpressure is an important factor that strongly a!ects reactionrates by changing the column temperature pro"le.Venkataraman, Chan and Boston (1990) describe theinside-out algorithm known as RADFRAC that is part ofthe commercial program Aspen Plus. Inside-out methodsinvolve the introduction of new parameters into themodel equations to be used as primary iteration variables.Four examples demonstrate that RADFRAC canbe applied to a wide variety of <strong>reactive</strong> separation processes.RADFRAC is able to handle both equilibriumreactions as well as kinetically limited reactions. Simandland Svrcek (1991) provide more details of their ownimplementation of an inside-out method for RDsimulation.RADFRAC has been used by many other authors.Quitain, Itoh & Goto (1999a) modelled a small-scalecolumn used to produce ETBE from bioethanol. Simulationresults are compared to experimental data. A secondpaper (Quitain, Itoh & Goto, 1999b) used RADRAC tomodel an industrial-scale version of the same process.Bezzo et al. (1999) used RADFRAC to study the steadystatebehaviour of an actual industrial RD column producingpropylene oxide from propylene chlorohydrinand calcium hydroxide. The thermodynamic propertiesof this system are complicated by the presence of electrolytesin the liquid-phase and by salting out e!ects.Reaction kinetics were modelled using the expressionsreported by Carra, Santacesaria, Morbidelli and Cavalli(1979b). By adjusting the Murphree e$ciency the authorswere able to obtain the best possible agreement betweenthe plant data and the simulations.Davies, Jenkins and Dilfanian (1979) describe a variationon the standard EQ stage model that is depicted inFig. 19. The vapor/liquid contacting section is modelledas a conventional vapor}liquid equilibrium stage (withoutreaction). The outgoing liquid stream passes to a reactorwhere chemical equilibrium is established. Thestream leaving this reactor passes on to the next equilibriumstage. The disadvantage of this approach is that itfails to properly account for the in#uence that chemicalequilibrium has on vapor}liquid equilibrium (and viceversa). The model is used to predict the temperature andcomposition pro"les in a 76 mm diameter column inwhich formaldehyde is reacting with water and methanol.Good agreement between predicted and measured valuesFig. 19. Equilibrium stage model used by Davies et al. (1979).
Change language