Spreadsheet use in Conceptual Design ofChemical Processes*

OMAR A. IGLESIAS, J. PASTOR, A. HENSELER, R. BERTOLINI, J. D. SOTO ANDC. N. PANIAGUAUniversidad Nacional de la Plata, Dpto. de IngenierõÂa QuõÂmica, Fac. De IngenierõÂa, 1 esq. 47,1900 La Plata, Argentina. E-mail: oaiglesi@volta.ing.unlp.edu.ar

The main purpose of the following work is to present an elemental simulator of chemical processesdeveloped on an Excel1 spreadsheet. The simulator consists basically of three main modules:Property Prediction Block: different physicochemical and thermodynamic properties for purecompounds and mixtures can be calculated; Equipment Block: the main dimensions and outputstreams of typical process equipment are calculated by means of approximate methods; CostCalculation Block: the investment required by the different equipments is estimated through genericcorrelations. Several application examples are introduced, as well as the general structure of theprogram.

INTRODUCTION

DURING THE TEACHING of elemental prin-ciples of process design in chemical engineering, aspecial emphasis should be made on what Douglascalls Conceptual Design of Processes [1]. This basicconcept implies a systematic search, throughsucceeding refinements hierarchically ordered,which starts from the simplest solutions and goeson up to the concretion of an entire processdiagram.

Douglas proposes the following hierarchy ofdecisions:

1. Batch vs. continuous processing.2. Input-Output structure of the flowsheet.3. Recycle structure of the flowsheet.4. General structure of the separation system:

± vapor recovery system,± liquid recovery system.

To fulfill these steps, it is necessary to make use ofboth calculation and economic estimation methodsin accordance with the increasing complexity levelsimplied by the procedure.

In the early stages, it is possible to eliminatedesign alternatives that are clearly disadvanta-geous by means of very simple assumptions, afew economic data and unsophisticated computa-tion schemes. Farther on, the search will require agreater volume of information and calculationschemes of higher complexity.

Of course, the final purpose is the simulation ofthe process, using a program that establishesexactly the stream properties and performanceconditions of the different units. This program isclearly oriented to the professional practice, and its

use requires a specific training, whose extentdepends on the particular characteristics of thecommercial product.

Before running process simulators, the engineerpossesses powerful calculation tools that make theanalysis easier, using approximate values of thecompound and mixture properties as well assimplified methods for equipment calculation.

Among those software tools, it is worthmentioning:

. ASCEND, from Carnegie Mellon University,http://www-2.cs.cmu.edu/-ascend/

. GAMS, from GAMS Development Corpora-tion, Washington DC, http://www.gams.com

. spreadsheet.

ASCEND and GAMS are modeling systems whichare appropriate for engineering problems, in parti-cular, for chemical engineering ones. They haveseveral developments and facilities (prebuilt units,organization routines, etc) that help the user tomodel the analyzed systems.

The spreadsheet is the most used computationtool in the engineering field, not only in profes-sional practice but also during undergraduatestudy. Because of this, all the developments forengineering teaching based on spreadsheets implyan environment and techniques well-known to thestudent, as well as a reinforcement of the requiredskills for the future professional performance.

Thereby, at the Faculty of Engineering of theUniversidad Nacional de La Plata (UNLP), in theProcess Engineering course, we have decided todevelop a simplified process simulator, SimPro, inExcel1 and its associated VBA programminglanguage. Technical and economic analysis oftypical systems of the chemical industry is feasiblewith SimPro, as well as eventual mass and energyrecycling and the search for optimal design and* Accepted 11 June 2004.

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Int. J. Engng Ed. Vol. 20, No. 6, pp. 999±1004, 2004 0949-149X/91 $3.00+0.00Printed in Great Britain. # 2004 TEMPUS Publications.

performance conditions. The basic structure ofdata entry and property calculation has beentaken from Partin [2], the most direct antecedentfor the present work.

BASIC REQUIREMENTS FOR A PROCESSSIMULATOR IN SPREADSHEETS

The development of a simulator requires:

. routines for thermodynamic and physichochem-ical properties of pure compounds and mixtures;

. routines for the design of typical process equip-ment, with the corresponding calculation proce-dures;

. routines for the estimation of equipment costs.

To achieve bigger pedagogic effectiveness, the typeof simulation problem considered with SimPro willbe of reduced complexity: four to ten process units,two to six decision variables and one or two recyclematerial streams, as it is shown in Fig. 1 [3].

To find the optimal values for the decisionvariables, Excel1 has a specific add-in calledSolver that turns out to be sufficient for themagnitude of the analyzable cases. Besides,though it is possible to solve an iteration problemdirectly with the spreadsheet (`circular reference',

using the Excel1 jargon), it is recommended [4] tomake that calculation explicit and also to solve itwith Solver.

Due to the preliminary approach in which thesimulator will be used, the design of the equipmentwill be made through simplified (shortcut) methods.Nevertheless, it requires a multiplicity of argumentsas data and its result will be a set of values. Itincludes not only composition, pressure, tempera-ture, etc, of each equipment's output stream, butalso the main dimensions of the equipment. In thiscase, matrix functions, which are not familiar to thestudent, must be used. Thereby, it was decided toimplement their handling through a specific menu.

Property prediction and cost estimation routinesare of scalar nature, with multiple input argumentsand a single output value. In the case of theseroutines, even though it is possible to use theclassical function structure and to handle themthrough Function Wizard, it was decided toaccess them from SimPro menu in order to unifythe handling of the add-in.

The obtained product, SimPro.xla, is faultlesslyadapted to the demands of the final stages of acourse on Conceptual Design, in order to make apreliminary analysis of the behavior of a particularequipment structure or the characteristics ofsome compound mixtures. Also, SimPro can be

Fig. 1. Typical problem to be solved with SimPro.

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extremely useful for other academic activities suchas elementary material and energy balances, singleprocess calculations, among others.

MAIN CHARACTERISTICS OF THESIMPRO ADD-IN

SimPro is an add-in (SimPro.xla) for Excel1 97and subsequent programs. When it is incorpo-rated, a modification in the menu bar takesplace, where the SimPro option appears. Also,two sheets are created, `DatosProp' and `Datos-Serv', both destined for data entry of compoundsand auxiliary services that will be present duringthe simulation. In these sheets, several propertiesand parameters for each compound in the system(name, formula, molecular weight, fusion andboiling temperatures, critical properties, etc.) canbe entered using SimPro menu. Those data arenecessary to estimate different properties (enthal-pies, VLE constants, etc.) of the pure compoundsand their mixtures. SimPro has a database withinformation on 168 typical compounds of chemicaland petrochemical process plants. In addition, theuser can enter this kind of information forcompounds that are not found in the databasefrom the data available in classical bibliographicalsources [5, 6]. Figure 2 shows part of the `Datos-Prop' sheet.

The add-in assigns a number to each compoundat the top of the corresponding column. During thesimulation, this number will work as the identifica-tion code of that compound. The prediction of

properties requires the compound identificationcode or the mixture composition (it depends onthe case) to be entered as arguments, as well as thepressure values and temperature to which theproperty is to be calculated.

As we have said, the SimPro add-in has severalscalar functions in order to predict properties ofpure compounds and mixtures. Also, from theSimPro menu it is possible to access severalmatrix functions that perform the calculation ofprocess equipment and the auxiliary units availablein the simulator. These functions are listed inTables 1, 2 and 3.

Figure 3 shows the sequence of alternatives ofthe corresponding entry in the SimPro menu. Formatrix functions, Excel1 requires the user toselect a priori the range of results. In the case ofequipment, this is troublesome since the dimen-sions of that range change according to the chosenone. The function cannot perform the selectionbecause this is a forbidden operation to functions,but procedures are allowed to do it.

In this way, the solution to the problem beginswith the use of procedures, but only if it is possible tokeep the automatic updating of results in order tocarry out eventual iterative calculations or optimumsearches. Then, the procedure must select the rangeand fill it with the corresponding function.

The Cost of Equipment block includes thefollowing functions: Absorption and DistillationTower, Heat Exchanger, Compressor and Pump,Reactor Vessel and Flash Tank.

The cost estimations for the installment equip-ment are made using the correlations given by

Fig. 2. `DatosProp' sheet.

Spreadsheet use in Conceptual Dseign of Chemical Processes 1001

Guthrie [7], updated by Marshall Swift's index(M&S) [7].

In addition to the three mentioned modules, thereare some edition tools that allow, for instance,extracting the bottom or top conditions of acolumn from the corresponding range that containsthe results of the unit. These functions, as theequipment calculation ones, are of matrix natureand they are accessed from the SimPro menu.

APPLICATION EXAMPLES

SimPro system has been used in severalproblems of Conceptual Design, complementingthe activities of design and cost calculation incomplex systems.

Figure 4 partially shows the sheet with theresults of one of the five possible schemes for theseparation train of a 4-hydrocarbon mixture,which were obtained in the analysis made withSimPro. For clarity's sake, the correspondingprocess diagram has been added to the sheet. Inthis case, SimPro is being used as a tool for theanalysis of the separation sector of liquid streams.Before using SimPro system, students have alreadyperformed a selection of the most promisingschemes, taking into account the total annualcost that is associated to each scheme.

To carry out this previous selection, evaluationrates are used, such as Porter and Momoh's ROTEequation [9] or Jobson's boiling capacity variable[10]. In this example, the previous study hasreduced the analysis to two schemes: the directsequence (the lightest compound entering the feedis isolated in each column), and the one that isshown in Fig. 4. For both of them, the student hasto carry out a series of activities which, in thecommercial simulators, are made by the executiveprogram in a transparent way to the user.

The simulation of every process scheme usingSimPro requires:

. The preparation of a flow diagram which showsthe data that come in and out from each simu-lation unit. This diagram must consider theinterrelations among units. For instance, thevariables that are calculated in one unit andwhich are data in another unit, represent infor-mation flowing from the first unit to the secondone. It is also necessary to detect the iterationcycles produced by the typical structural stiff-ness of the modular simulators, usually whenthere are variables that appear as results in morethan one block.

. About the flow diagram: if there are recyclestructures, tearing sets allowing sequential cal-culation must be selected. Also, it is necessary toadd control equations that allow performing theadjustment of the guessed values.

. If the previous analysis indicates the existenceof independent variables, iteration schemes withguessed variables, or mixed situations with both

Table 1. Pure compounds properties functions

Liquid heat capacityGas heat capacityLiquid densityGas densityLiquid enthalpyGas enthalpyVapor pressureViscosity

Table 2. Mixtures properties functions

Heat capacityVle constantLiquid densityGas densityLiquid enthalpyGas enthalpyMolecular weightBubble point pressureCritical pressureDew point pressureBubble point temperatureCritical temperatureDew point temperature

Table 3. Units functions

Absorption columnDistillation columnCompressorCondenserAdiabatic flashIsothermal flashHeat exchangerMixerPumpConversion reactorContinuous stirred tank reactorPlug flow reactorReboilerSplitter

Fig. 3. SimPro menu.

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types, the Solver add-in has to be used to solvethe simulation problem.

Concerning the separation train analysis, there areno iterative schemes in the problem, though thereare independent variables such as reflux ratio andtop refrigerant temperatures. Figure 5 showsanother part of the sheet in which the simulationis carried out. The results of the third tower of thescheme can be observed as well as the total annualcost calculation table. Besides identification labels,the results show the values of the process variablesand those ones related to the equipment size.

The user should enter the data for the differentunits by following the information flow that cor-

responds to the flowsheet. In this way, the infor-mation used for the third column is taken from therow corresponding to the distillate of the secondone. In turn, the second column is calculated fromthe bottom of the first one, until the feed is reached.

The results obtained in the example are inaccordance with the estimations carried out bythe evaluation functions, following Jobson'scriteria, being the direct sequence the one thathas the lowest total annual cost.

This example allows us to value the possibilitiesof SimPro, including the analysis of differentprocess alternatives and the selection of the mostappropriate one from a technical and economicpoint of view.

Fig. 4. Flow summaries for a train distillation simulated with SimPro.

Fig. 5. SimPro results for a distillation column and cost estimations for the train.

Spreadsheet use in Conceptual Dseign of Chemical Processes 1003

The availability of a cost expression for eachprocess unit allows us to use SimPro in order tocarry out the variable significance analysis accord-ing to the methodology proposed by Douglas et al.[11], detecting the process units and variables thathave a bigger influence on the production cost.

In this case, the use of Solver has to be carriedout in several steps:

. First, suitable values for the decision variablesmust be set.

. Second, values for the guessed variables in theiterative schemes will be found. Of course, thisstep is not necessary if there are no iterationschemes.

. Then, the decision variables will be disturbedone by one, and the entire calculation processwill be repeated.

. After that, estimation of the partial derivativesof the total annual cost function componentswill be carried out.

Finally, the significance of each independent

variable is determined and the optimization prob-lem is reformulated taking into account only thosevariables that are relevant due to their influence onthe objective function.

It is really easy to perform the whole processonce the problem has been posed on the spread-sheet, using the SimPro add-in.

CONCLUSIONS

The developed SimPro add-in allows us to carryout approximate calculations (mass and energybalances, equipment dimensions and cost estima-tion) for chemical processes of medium complex-ity. The use of this add-in is not different from theusual uses in the handling of functions and proce-dures in spreadsheet. With SimPro, we can effi-ciently deal with basic questions of ConceptualDesign of Processes such as alternative analysis,specific modifications to a scheme and designvariable significance analysis, among others.

REFERENCES

1. J. M. Douglas, Conceptual Design of Chemical Processes, McGraw-Hill (1988).2. L. R. Partin, Opportunities in PC and Mac numerical software for process engineering, AIChE

Symposium Series, 91, 1995, pp. 340±343.3. L. T. Biegler, R. R. Hughes, Infeasible path optimization with sequential modular simulators,

AIChE Journal, 28(6), 1982, pp. 994±1002.4. O. A. Iglesias, C. N. Paniagua, Use of spreadsheets in optimization problems involving iterations,

Computer Appl. Engng. Educ., 7, 1999, pp. 227±234.5. Reid, et al., The Properties of Gases and Liquids, McGraw-Hill.6. Perry, Chemical Engineers' Handbook, McGraw-Hill.7. K. M. Guthrie, Capital cost estimating, Chem. Eng., 76(6), 1969, p. 114.8. Chemical Engineering, McGraw-Hill, ISSN 0009-2460.9. K. E. Porter, S. O. Momoh, Finding the optimum sequence of distillation columnsÐan equation to

replace the `rules of thumb' (heuristics), The Chemical Engineering Journal, 46, 1991, pp. 97±108.10. M. Jobson, Short-cut evaluation of distillation sequences, Computers Chem. Engng., 21, Suppl,

1997, pp. S553±S557.11. W. R. Fischer, M. F. Doherty, J. M. Douglas, Evaluating significant economic trade-off for

process design and steady-state control optimization problems, AIChEJ, 31, 1985, p. 1538.

Omar A. Iglesias received his chemical engineering degree from the Universidad Nacionalde La Plata (UNLP). He is currently a professor in the Department of ChemicalEngineering at UNLP, where he teaches graduate and undergraduate courses and conductsrelated research on plant simulation and process optimization. He is also enveloped indeveloping educational software for engineering courses.

Carmen N. Paniagua received her chemical engineering degree from the UniversidadNacional de La Plata (UNLP). Her former research area was in petrochemical industry.She is currently in the Department of Chemical Engineering at UNLP, where she teachesundergraduate courses in process engineering. Her area of research is plant simulation andprocess optimization. She is also involved in developing educational software forengineering courses.

Juan D. Soto received his chemical engineering degree from the Universidad Nacional de LaPlata (UNLP). He is currently in the Department of Chemical Engineering at UNLP, wherehe teaches undergraduate courses in process engineering. He also works on technical andeconomic formulation of investment projects.

Javier Pastor, Alejandro Henseler and Rosina Bertolini were undergraduate students in theDepartment of Chemical Engineering at UNLP at the time they helped to developing thebasic structure of SimPro. They are currently working in professional activities.

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