Ind. Eng. Chem. Res. 1995,34, 3059-3067
3059
Knowledge-Based System for the Preliminary Design of Mixing Equipment Tuomas Koiranen, Andrzej Kraslawski,"and Lars Nystrtim Lappeenranta University of Technology, Department of Chemical Technology, P.O. Box 20, FIN-53851 Lappeenranta, Finland
The paper presents a methodology of mixing system design and a n expert system that is built according to the proposed principles. The knowledge-based system for the predesign of stirred vessels is strongly user-oriented. The presented program selects and designs impeller, tank, and auxiliary equipment (baMes, entering). There are performed mixing power and mechanical calculations, too. The system is constructed as an object-oriented database in MS-Windows environment. The Excel tables are used, as the databases, for the selection of stirred vessel components. The stirred vessel components are objects in Nexpert Object (by Neuron Data Inc.) knowledge bases. A user interface is developed with ToolBook (by Asymetrix Inc). The knowledge bases are activated from the user interface to get the possible selection candidates in ranked order for the problems under consideration. Part of the user interface is an explanation system. The main features of the system are flexibility and good imitation of the design activity.
Introduction The need for the more effective design of equipment is postulated at many industrial and scientific meetings. It is a common opinion that knowledge-based systems can improve the design process. Stephanopoulos and Han (1994) have stated in their survey of expert systems applications that the successful use of knowledge-based programs in design requires three conditions: specific, narrow field of application; flexible architecture of knowledge bases enabling easy expansion; and integration of the diverse sources of knowledge. They conclude that equipment selection would be a good example for the application of the principles mentioned above. The mixing process is a very old and very popular unit operation but the problem of its automatic design is still unresolved. Papers addressing computerized mixing equipment selection are rare. We think that the main reason is a lack of balance between general methodology of design and design of the particular elements of a mixing system. There is a great amount of dispersed data about the specific aspects of design, e.g., selection of the tank shape or the impeller type, and nearly nonexistent information about the sequence of design steps and interactions between the elements of a mixing system. The problems encountered in the automation of the mixing system design have been presented by Bakker et al. (1994). They have developed a system (AgDesign) to design turbine agitators. The system allows reduction of the time needed for selection from 1.5 h to 10 min. Usually better-optimized and less-expensive solutions are proposed than those proposed by a human expert. Computational fluid dynamics (CFD) simulations have been proposed as a supportive tool for knowledge-based systems. An example of the knowledge-based system designed for the narrow application field is the expert system for the configuration of the agitators in food processing (Knoch and Bottlinger, 1993). The first phase of the preliminary design of a mixing system consists in the selection of mixing type, e.g.,
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mixing in stirred vessel, pneumatic mixing, and static mixing. In the next step, a more detailed description of the selected mixing type is performed. In the case of mixing in a stirred vessel, it consists in determination of tank diameter, tank bottom, impeller type, impeller number, impeller entering, baffles, impeller supports, and power consumption calculations. This article is third in a series on the construction of the knowledge-based tools for the preliminary design of mixing systems. The first publication concentrated on the initial phase of the preliminary design of mixing system, e.g., mixing type selection (Koiranen et al., 1994a). In the next publication (Koiranen et al., 1994b), some aspects of the second phase of the preliminary design, e.g., impeller selection, have been described in more detail. In this paper a second stage of preliminary design of mixing equipment is described in more detail. The paper presents a methodology of mixing system design and gives a proposal for the organization of the objectoriented tool for mixing equipment selection. There are three hierarchical levels of knowledge in the presented system: user interface, inference machine, and object database levels. There is control knowledge at the user interface level. The control knowledge is used to organize the tasks to be executed during the stage of preliminary design. The interrelations of the tasks require a specific order of their realization. The knowledge about the control of the information flow is stored in the inference machine. This knowledge imitates the actions of the designer during the solving of the particular selection problem. The knowledge about the selection of the stirred vessel components is constructed in a table form. The tables are selection objects with their attributes. Tables can be simultaneously opened in function of the selection task. The tables are stored in Excel in the symbolic link format. The knowledge, dynamically retrieved from the Excel tables, is treated as objects in Nexpert Object knowledge bases. The presented system is constructed as an objectoriented database. The Excel tables are used as the databases for the selection of stirred vessel components.
0 1995 American Chemical Society
3060 Ind. Eng. Chem. Res., Vol. 34, No. 9, 1995 Stirred vessel components are objects in Nexpert Object knowledge bases. The pattern-matching techniques are used for classes to test the suitability of the candidates. A user interface is developed with ToolBook. The knowledge bases are activated from the user interface to get possible selection candidates in ranked order for the problems under consideration. One of the parts of the user interface is an explanation system. The explanations are presented as the values of attributes that are used in the selection process. The help functions are included in the system to explain the meaning of the different terms related to mixing. Those functions are also used for the presentation of charts and tables utilized in the design process. The help functions are presented in hypertext form. The calculations of mixing power and the different geometric arrangements of the tank are executed in MS-Excel spreadsheets. The spreadsheets are linked t o the ToolBook user interface. The flexibility of the system consists in the possibilities of changing the knowledge from the databases. The user-friendly interface enables the designer to make the decisions at every stage of design. The optimal design alternative is worked out in an iterative manner. The article is divided into five sections. In the section Engineering Factors in the Selection of Mixing System in Stirred Vessel, the literature is presented devoted t o the detailed description of the important elements of the mixing systems. There are discussed main elements of the system, e.g., impeller selection, tank design, and mixing power calculations, in the section Selection Concept. The system configuration, knowledge representation, database description, and user interface are presented in the section System Description. Two examples are given in the Examples section, and next some general remarks are presented in the Summary.
Engineering Factors in the Selection of Mixing System in Stirred Vessel The important factors influencing the selection have been presented in the basic textbooks and papers Liquid Agitation (19751, McDonough (1992), Nagata (1975), Oldshue (19831, Uhl and Gray (1986), and Tatterson (1991). They have been briefly presented by Koiranen et al. (1994a). The straightforward remark resulting from the survey of the above-mentioned sources is a lack of transparent information about the design steps, their order, and interrelations. The dispersed knowledge extracted from the basic books and papers as well as the discussions with experts resulted in the design methodology implemented in this system (Figure 1).Its main feature is user-controlled selection of the elements of the mixing system. This property is realized by the possibility of return t o the previous selection tasks at any stage of design process. The system does not select automatically any element of the system and every decision must be confirmed. The flexible structure of the program enables exhaustive studies of the different variants of the mixing system. Case studies could be performed starting from any stage of the design process. Such structure guarantees the maximum insight into the different aspects of design. Another advantage is easy management of data compared to manual design, especially when several alternatives are possible. The broad field of application is another feature distinguishing this system from the other knowledgebased programs in mixing. The presented expert system is applicable for Newtonian and non-Newtonian liquids, liquid-liquid problems, and liquid-solid prob-
~
lnputdata \,
Impeller mounting selection (top or side entering)
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Fpeller entering selection
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I -~ Decision of using baffles
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Impeller numbr selection I
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+A ,
i
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Checking of mixing power
Impeller placement (clearance) seleqion-
Figure 1. Methodology of design of mixing system.
lems, and can handle the cases where the mixed volume is thousands of cubic meters.
Selection Concept Main Entering Selection. The selection is made between top entering or side-entering mounting. The input information required is fluid volume, fluid viscosity, mixing process (blending, solid suspension, mass transfer, etc.), and particle property (abrasive, nonabrasive). The output information obtained is top-entering and side-entering mounting with the appropriate values of certainty factors. Impeller Selection. The possible impellers are selected on the basis of the following input information: fluid volume, fluid viscosity, rheology type (Newtonian, Non-Newtonian),mixing process (blending, solid suspension, mass transfer, etc.) and main entering type. The output information obtained is name of the impeller (marine propeller, Rushton turbine, pitched blade turbine, etc.), impeller class (propeller, turbine, etc.), impeller flow direction (axial, radial), and impeller type (open, close-clearance). Tank Design. Tank diameter (27, height (H)liquid , height (21, and Z/Tratio are selected. All dimensions (Z, H, T ) can be introduced manually. The input information is tank type (DIN 28136, normal tanks), fluid volume, and the way of tank design (manual, based on ZIT ratio, based on the maximum tank diameter or height). In the normal tanks, the user should also determine the form of the tank (cylindrical, square), tank bottom (plate, ellipsoidal, conical, flanged plate, dished, and flanged) and tank top (open, plate, ellipsoidal, conical, flanged plate, dished, and flanged). Moreover units (m, mm, inch) and fluid volume are used as input information. The output information is tank diameter (27, tank height (H), liquid height (Z),ZIT ratio, ZIH ratio, and total vessel height. Entering Selection. The selection is made between top-on-center, portable, and side-entering mountings. The input information is tank diameter (27, impeller class (propeller, turbine, high-efficiency, etc.), tank
Ind. Eng. Chem. Res., Vol. 34, No. 9, 1995 3061 pressure (atmospheric, pressure), and main entering (top entering, side-entering). The output information is top-on-center mounting, portable mixer, and sideentering mounting. Main entering, impeller class, tank pressure, and tank diameter ranges are matched with the entering selection. Baffles Selection, The decision is made whether to use the baMes or not. The input information is fluid viscosity, impeller entering (top-on-center,side-entering, portable mixer), and impeller type (open, close-clearance). The output information is “yes baffles” and “no baffles”. The selected impeller type is matched with impeller types (open, close-clearance) of baffle decision possibilities. The selected impeller entering is matched with impeller entering of baffle decision possibilities. The ranges of the fluid viscosity determining the use of the baffles are checked with the value of the design fluid viscosity. Impeller Number Selection. The number of impellers is selected. The maximum number of impellers in this system is five. It is possible to select ”standardn or “nonstandard” installation. Input information is installation (standard, nonstandard), fluid viscosity, tank ZIT ratio, fluid phases (liquid-liquid, solid-liquid, gas-liquid), and impeller type (open, close-clearance). Output information is given as the number of impellers. Suitable Impeller Size Selection. The possible impeller diameter to tank diameter (DIT)ratio range is selected. The correct impeller DIT ratio will be selected together with mixing power calculations because the impeller DIT ratio depends on mixing power.The input information is given as the name of the impeller (marine propeller, hydrofoil, Rushton turbine, etc.). The output information is presented as the possible impeller DIT ratio range. Mixing Power Calculation. Mixing power, impeller speed, impeller diameter, and mixing parameters are calculated. The calculations are based on the agitation scales (Liquid Agitation by Chemineer, 1975, 1976). Their values are given by the system. The input information is impeller power number, impeller flow number (discharge coefficient, pumping number), loading for the motor or power loss factor, number of impellers, agitation scale, fluid volume tank diameter (T),impeller DIT ratio, and fluid density, fluid viscosity. The power and the flow numbers, the agitation scale, the impeller DIT ratio, and impeller speed can be changed t o obtain suitable mixing power conditions. Selection of the Method for the Verification of Mixing Power. The calculated mixing power is verified according to the impeller Reynolds number region, the impeller tip speed region, and the mixing process (blending, solids suspension, etc.) P N region. The industrial application PN regions are not verified according to the calculated mixing power due to the lack of the knowledge of the industrial application P N regions. Mixing power verification selection results should be considered only as advice. The input information is: impeller tip speed, impeller Reynolds number, and mixing process (blending, etc.). The output information is given as suitability value of the calculated impeller tip speed compared to the specific impeller tip speed region, suitability value of the calculated impeller Reynolds number compared t o the specific impeller Reynolds number region, and suitability value of the calculated mixing P N ratio compared to the specific mixing process PN region. Impeller Clearance Selection. The distance between impeller and tank bottom is determined based on the input information of impeller installation (stan-
-activate knowledge bases and calculations -show results with explanations -navigation in the system
KNOWLEDGE BASE -consists of the rules how to use
’DATABASE (EXCEL) -consists of knowledge about the application
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dard, nonstandard), mixing process (solid suspension etc.), impeller entering, fluid phases, tank ZIT ratio, tank diameter (T), liquid height, impeller number, impeller type (open, close-clearance),and fluid viscosity. The output information is given as impeller clearance (C)from the bottom; upper impeller clearance from the bottom (optional for two impellers), and clearance between multiple impellers (optional for several impellers). Baffle Design. BaMe design means the determination of the blade width, the distance from the tank wall, the distance from the bottom, and the number of baffle blades. The input information is impeller Reynolds number, tank diameter (T), and number of impeller blades. The output information is blade width of the baffle, the distance from the tank wall, the distance from the bottom, and the number of baMe blades.
System Description A knowledge-based system MIXES has been developed as an aid in preliminary design work. The results of a consultation are proposals for impeller, impeller entering, impeller number, installation, and mixing intensity. Tank and baffle design and power calculations are also included in the system. The selection method is based on an idea that the selection can be divided into smaller decision-making tasks with common parameters, which affect a particular selection task. A small selection task often gives more than one possible variant. The possible answers have suitability (certainty factors) from 0 (unsuitable) to 1 (the most suitable) to help the user to make a final decision. “What if’ designs can be performed with the system by checking several possible answers through. The system includes explanations about the proposed solutions. The general structure of the program is presented in Figure 2. The program is an object-oriented system where classes represent the different aspects that have t o be investigated during the design process. The example is an examination of the suitability of the different elements of stirred tanks as a function of viscosity. The classes do not contain any physical object but the calculation procedures. An example of class used for the examination of the applicability of different impellers from the point of view of viscosity is given in Figure 3. Fuzzy sets are applied in the system for description of the applicability ranges and the linguistic expressions. An example of the applicability range is the viscosity interval adequate for the operation of the given impeller. The linguistic expressions are used to describe the impeller capability to produce the adequate shear and flow. Matching is realized by calculation of the
3062 Ind. Eng. Chem. Res., Vol. 34, No. 9, 1995 CUSS' € Q U I AllRIEUTES: difference calculated in viscosity-object t c q u l >.maxparop- Cequl >.maxparac difference calculated in viscosih/-object t e q u l > . m i n p a r a p - t e q u l Xminparac certainty lactor of operating viscosity lor impeller viscosity range difference calculated in v i s c o s i t y - o b j e c l t e q u l > . m a x p a r a c v i s c o s i ~ , v a l u e MPXP difference calculated in v i s c o s i i y - o b j e c t < e q u l >.maxparapYiscosity.value MlNC difference caiculatcd in viscosih/-objectviscosity.value..minparap MAXPARPIC the highest certain V I S C ~ S I ~ ~ , MAXPARAP the highest possible viscosity MINPARAC the lowest certain viscosity MINPARAP the lowest possible viscosity NAME n a m e of an impeller
AREA-H AREA-L
CFV MAX
METHODS: H-UNCERTAIN : SELF.CVF = O-[O-l]/SELF.ARE~_H'SELF.MPXP L-UNCERTAIN : SELF.CVF = OyO-l]/SELF.AREA_L'SELF.MINP CERTAIN1 : S E L F . C N 1 .O
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RETRlEVhL F90M DATABASE
OBJECT: I M P E L L E R 1
OBJECT: I M P E L L E R 2
METHODS:
METHODS:
OBJECT: I M P E L L E R N
METHODS:
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Figure 3. Class and object hierarchy for checking candidate applicability. Procedure based on the examination of fluid viscosity and operational viscosities of the selected candidates.
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CALCULATION OF CF FROM FUZZY MATCH FOR SHEAR NEEDED BY THE MIXING PROCESS AND SHEAR CAPABILIlY O F THE IMPELLER
DB
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d atab as e MF=membership function CFScertaintyfactor
IT--of MF for Retrieve linguistic values of shear for mixing process DB and mixing impellers
Retrieve
flow and $hear from
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Identify the fuzzy match between the MF:s
(the mixing process considered&
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Figure 4. Calculations of the certainty factor. The case of the fuzzy match of shear needed by the given process and shear produced by the given impeller.
intersection point of the overlappingfuzzy sets according to the formula degree of match = max(pA(x)r\pu,(x)) where ~ A ( x and ) ~ B ( xare ) the membership functions of the fuzzy sets A and B. An illustration is given in Figure 4. System Configuration. The system consists of a user interface, an inference machine, calculation programs, and databases. The user controls the stirred vessel selection through an interface. The inference machine is hidden under the user interface. Its function is to generate possible selection candidates from the knowledge that is stored in the database. There are calculation programs included in the system that are implemented in Excel spreadsheets. They are activated through a user interface. The knowledge is stored as
decision tables in databases to be allowed for knowledge modification. The decision tables are the sets of the selection rules, and they are interpreted in table form as shown in Figure 5. The data types in the databases are numerical, fuzzy, linguistic, or string values. Knowledge €&presentation. The parts of the inference machine are programmed with the Nexpert Object Development Package (by Neuron Data Inc.). The rules of the inference machine are used to handle information flow and actions between objects of specified classes. A scheme of an information flow is described in Figures 4 and 6. The example of a knowledge base structure for the selection of impeller types is presented in Figure 6. A more detailed description of the first task (first box in Figure 6) is described in Figure 4. The objects are dynamically retrieved pieces of knowledge stored in databases (Figure 3). The classes have
Ind. Eng. Chem. Res., Vol. 34, No. 9, 1995 3063 FORM OF RULE :
IF shear is very low AND flow is wry high AND impeller lype is olose-cleuance AND flow direction it {axial.radirl) AND entering is topentering AND fluid phase is {liq/liq.sol/liq) AND fluid viscosity > aboul3OOO mPas AND fluid viscosity .c about 75OOO mPar THEN impeller is GATE ANCHOR
DATABASE FORM: IMPELLER
NAME
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Figure 5. Rule interpretation of the selection candidate. The case of anchor impeller. CALCULATIONOF CF FROM FUZZY MATCH FOR SHEAR NEEDED THE MIXING
IMPELLER SELECTION
PROCESS AND SHEAR CAPABILW OF THE IMPELLER F U Z N MATCH FOR FLOW NEEDED BVTHE PROCESS AND FLOW CAPABILITY OF THE TAKE THE MINIMUM OF C F S FOR IMPELLER CANDIDATES A N 0 PANKTHEM INDESCENDING ORDER
CALCULATION OF CF FOR OPERATING VISCOSITY RANGE OF IMPELLERS
CF= CERTAINTY FACTOR IFLUlD PHASE
I
Figure 6. Information flow in impeller selection.
the calculation algorithms which are common for all objects belonging to the class. For example, class EQUl in Figure 3 has the calculation algorithms for estimating the suitability of the operating viscosity range of impellers compared to the given fluid viscosity. The function of the inference machine is to check the knowledge from a database to get possible answers for a specified problem. The calculations of fuzzy variables are included in the inference machine. Databases. Databases consist of the selection rules and are developed with Excel. It ensures an easy modification of knowledge. It is possible to change any parameter values that are stored in a database. Also it is possible to add more selection candidates (impellers, new industrial applications for agitation intensity determination, etc.). It is not possible t o add new parameters. Related Calculation Programs. The calculation programs are implemented in spreadsheets with Excel. There are calculation programs included for mixing power calculations and for baffle design. There is a DDE (dynamic data exchange) link between the user interface and Excel so that the Excel program can be executed directly from the user interface. It is also possible to start Excel to see the calculation equations or to scroll intermediate calculation results. The calculations of the shaft diameter and critical speed are implemented in the system. A report is generated into the Excel datasheet. The results of the selection can be used in the detailed mechanical or cost calculation programs. User Interface. The interface is programmed with ToolBook (by Asymetrix Inc.). There are two screens for input data where a selection problem is formulated
and there are selection tasks in the next five screens in the user interface. A user can either browse through any of the screens or approve the data in a screen by pressing the OK button. The results can be seen in the result fields with the values of certainty factors. The user should make the final decision from the alternatives generated by the system by pressing one of the alternatives. Examples of a few user interface screens are given in Figure 7. The explanations can be displayed by pressing the ‘WHS”’button. The explanations of a selection are the values of parameters affecting a particular selection. On the top of the page there is a menu bar that consists of “State” and “Report” menus. A current state of a design can be shown under the “State” button from any screen. The system generates a report into the Excel spreadsheet. The size of the interface (Toolbook application) is 570.5 kB. It consists of the control of subselection problems, hypertext based help system, charts, and tables. The size of the knowledge bases to handle information flow (Nexpert Object) is 320 kB and the databases in symbolic link format is 75 kB. The calculation programs realized in Excel occupy 60 kB. It has taken 10 months to organize and to implement the collected knowledge.
Examples An example of an application of this system has been published by Koiranen et al. (1994~).The following case studies are presented to illustrate the capabilities of the constructed knowledge-based system. Example 1. The problem consists in dilution of 10 m3 of 76 wt % sucrose solution to the final concentration of 10 wt %. Water is added first to the tank. The density and the viscosity of the 76 wt % sucrose solution are 1380 kg/m3and 1700 cP, respectively. The viscosity of the final solution is ‘5cP. The mixing tank has a flat bottom. The liquid height t o tank diameter ratio is 1.4, as shown in Figure 7a. The detailed input information and results of reasoning are generated by the system in the report presented in Figure 8. There are the following comments to the results obtained. Top entering mixer has been selected because the fluid volume is small. Marine propeller has been selected because the process is blending (very high flow and very low shear are needed in mixing, and axial flow is ideal for blending), the fluid viscosity is small (5 cP), the fluid is Newtonian, and the fluid phases to be mixed are liquids. Marine propeller is an open impeller, and open impeller is adequate for this kind of mixing process because the fluid viscosity is small and the fluid is Newtonian. Marine propeller also produces very high flow and very low shear. Top-on-centerinstallation has been suggested because the tank diameter is greater than about 2 m, a top entering mixer has been selected, and an axial flow impeller has been applied. Baffles have been selected because the fluid viscosity is less than about 15 000 cP, the impeller entering is top-on-center, and the impeller is of open type. One impeller element is used because the fluid viscosity is less than about 25 000 CP and the liquid height to tank diameter ratio (ZIT) is less than about 1.45 when only liquids are present. The explanations concerning impeller mounting direction, baffle decision, and impeller number selection are displayed on the screen, as shown in Figure 7b. It
3064 Ind. Eng. Chem. Res., Vol. 34,No. 9, 1995
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MIXER SELECTION
Ed11 State
Beport
Z HC
H
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Normal design (@
Space Restrictio
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Tank is sclcctcd hascd on liquid height to tank diameter pm -ratio. Y o u can input yoursclfZ/r -ratio. Normally, Qis l 1 . 0 . 11 Z l l is not given the system calculates -ratio accordinq to viscosity. based on the
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cllcr
tntcring sc,cc(lnn
n low viscosity blending most often used impeller. In small anks the installation is top-on-center or fixed-mounted and in big tanks the installation is side-enter. Propeller can also sed in small vessels for emulsificating and other liquld disperslon processes due to Its shearing actlon at high speed.
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Figure 7. Examples of the user's interface screens: (a, top) example of the help information in the form of hypertext; (b, middle) outline of the mixing tank geometry; (c, bottom) example of the selection tasks in one of the five screens.
should be noted that all kinds of tank tops are possible for top-on-center installation, but not all kinds of tank tops are possible for portable mixers. This is the reason why vessel top is a selection parameter for impeller mounting selection. Agitation scale index between 3 and 4 has been selected because the density difference between the liquids is greater than 100 kg/m3 and less than 600 kg/ m3 and the viscosity ratio between the liquids is greater than 100 and less than 10 000. In mixing power calculations the suitable drive (420 rpm) has been selected so that the impeller diameter
to tank diameter ratio (DIT)is between 0.05 and 0.4 for marine propellers, the impeller Reynolds number is in the turbulent flow region, the tip speed for the marine propeller is between about 3 m / s and about 15 m / s , and the specific power input (PN)for blending processes is between about 0.01 kW/m3 and about 0.4 kW/m3. The impeller is placed 1 m from the tank bottom because one-third of the liquid height is a recommended distance from the tank bottom for liquid mixing when one impeller is used. The standard baffle sizing for water-like fluids is 4 baffles, baffle width 1/12 of the tank diameter, and baffle setout 1/72 of the tank diameter. The shaft diameter is suggested to be 95 mm because the impeller speed should be less than 80% of the first lateral natural frequency. Example 2. An industrial example of ore refining is studied. The volume of the solid suspension is 4000 m3. The mass fraction of nonabrasive mineral particles is 70 w t %. The density of the fluid is 2300 kg/m3. The slurry is non-Newtonian and fluid viscosity is estimated to be 1000 cP. The best process result is obtained when the agitation scale index is 3.7. Thus, the non-Newtonian viscous slurry will be suspended uniformly to 95% of the liquid level. The slurry draw-off has a minor importance because low exit nozzle locations are adequate in this application. The cylindrical mixing tank has a flat bottom. The tank diameter is 18 m and the tank height is 17.5 m. The filling rate of the fluid is 90% of the tank height. The details of the problem and the solution are given in Figure 9. There are the following comments to the results. Top entering mixer has been selected because fluid viscosity is quite high although the fluid volume is large and the mass fraction of particles is very high. Hydrofoil mixer has been selected because the process is solid suspension (very high flow and very low shear are needed in mixing, and axial flow is ideal for suspension), the fluid viscosity is moderate (1000 cP), the fluid is non-Newtonian, and fluid phases to be mixed are solids and liquids. Hydrofoil is an open impeller, and open impellers are adequate for solid suspension because the fluid volume is very large and the fluid viscosity is not very high although the rheology is non-Newtonian. Flow and shear requirements are met from a process standpoint with hydrofoil impellers. Top-on-center installation and baffles have been selected from the same reasons as in the first example. One impeller element has been used because the fluid viscosity is not very high and the Z/Tratio is less than about 1.2 when solids are present. In mixing power calculations the agitation scale index was set to 3.7. The impeller DIT ratio has been selected to 0.28 because the specific power input PN ratio is between 0.02 and 0.05 kW/m3 for this application and the tip speed for the hydrofoil impeller is between 2 and 9 m/s. Impeller is placed 3 m from the tank bottom because one-fourth to one-fifth of the liquid height is a recommended distance from the tank bottom for solid-liquid mixing when one impeller is used. Summary The presented system is a final version of the MSWindows based program for the preliminary design of mixing equipment.
Ind. Eng. Chem. Res., Vol. 34, No. 9, 1995 3065 Comments Dilution of a sugar solution. Water is added first, concentrated sugar
Volume Rheology Virroritv ..- - -. ., Liquid viscosity ratio Density Liquid density difference Phases Application Solid-Liquid: Suspension criteria Draw off: Particle property Solids type Particle content Gas-liquid:
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INewtonian fluid I 51 1700 1040 kglm'3 kglm 3 380 Iliquid-liquid I [blending CP
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Liquid height
M i . shaft diameter for shear stress __ Min. shaft diameter for tensile stress Suggested shaft diameter based on allowable stresses Use~~'ven-sh~diameter Actual shaft diameter Equivalent weight of the impeller First lateral natural frequency (critical speed) Impeller speed lnormally 80 % o f the first natural frequency) Impellerspeed of the first natural frequency 1361
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Setout, m :
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Mass transfer Industry: Branch Application Pressure in tank Fluid temperature OUTPUT INFORMATION
Form factor I IZIT~limoellernumber I Knuckle radius Cone angle Baffles: Decision:
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mm mm mm mm kg 1Is 1/s ~
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I 10 ._ 95 (Increase dia to increase crit speed) 95 51,376 10.05975 7 69.58424
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Figure 8. Report generated for the problem of the dilution of the sucrose solution.
The Toolbook program used in the system is a powerfiil tool for the development of user interfaces with hypertext characteristics. It allows illustration of the
design task in a flexible way. Nexpert Object allows definition of the design actions during the solving of the particular selection problem. It creates strong informa-
3066 Ind. Eng. Chem. Res., Vol. 34, No. 9, 1995
Figure 9. Report obkained for the ore-refining problem.
tion links to the databases and the user interface. An easy modification and enrichment of the knowledge are
possible thanks to the application of the databases for the information storage.
Ind. Eng. Chem. Res., Vol. 34,No. 9, 1995 3067 The requirement for the control of the selection process by the user and not by the system was one of the most important demands presented by engineers. This is why the design process is organized to be controlled via the user interface. The proposed architecture of the system ensures the maximal flexibility in the design process. A report generated in a spreadsheet form creates a platform for further, detailed design. It is also possible to perform the case studies by changing the selected values of the input data. The program can be used in very different fields of applications, e.g., wastewater treatment, chemical and petrochemical industries, food industry, etc. It has been applied by the designers to solve the difficult real-world problems. An important feature of this system is its compactness. The different design tasks such as selection, calculations, reporting, etc. are realized in one program. The information obtained from the system is complete and forms a firm basis for further design steps. Acknowledgment This research has been financially supported by the Finnish Technology Development Centre (TEKES). The engineers from the companies Vaahto Machinery Ltd. and Neste Oy are also gratefully acknowledged for their cooperation.
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Received for review August 22, 1994 Revised manuscript received April 13, 1995 Accepted April 26, 1995@ IE9405060
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Abstract published in Advance A C S Abstracts, J u n e 1, 1995. @
