NETWORK PINCH ANALYSIS PART II

NETWORK PINCH ANALYSIS PART II
PROCESS OPTIMIZATION Introducing Process Integration for Environmental Control in Engineering Curricula NETWORK PINCH ANALYSIS PART II Created by: Ana Carolina Hortua Texas A&M University College Station, TX.

PURPOSE The purpose of this module is to describe basic concepts and techniques necessary in the application of direct recycle as a strategy for the optimization of a process performance. Direct recycle is considered a low-cost strategy since the companies are not required to invest a large amount of capital into equipment or technologies in order to reduce significantly their fresh resource consumption and/or waste production.

MODULE STRUCTURE This module is made up of three tiers:
Tier I: Basic Concepts Tier II: Application of Direct Recycle Concepts (Case Study) Tier III: Open-Ended Problem

TIER I BASIC CONCEPTS

DEFINITIONS PROCESS INTEGRATION:
It is a holistic approach to process design and operation that emphasizes the unity of the process and optimizes its design and operation. Refers to the identification of performance benchmarks ahead of detailed design. In other words, targeting determines how far we can push the process performance without specifying how it may be reached. TARGETING:

DEFINITIONS RECYCLE: Refers to the utilization of a process stream (e.g. a waste or a low-value stream) in a process unit. SEGREGATION: Refers to avoiding mixing of streams. Segregation of streams with different compositions avoids unnecessary loss of driving force streams. Thus, improving the performance of process units and may allow the streams to be recycle directly into the units.

DEFINITIONS (F) (T) FRESH LOAD (F):
Correspond to the quantity of the targeted species in streams entering the process. Whole Plant (F) TERMINAL LOAD (T): Correspond to the load of the targeted species in streams designated as waste streams or point sources of pollution. Whole Plant (T)

DEFINITIONS SOURCE: A stream which contains the targeted species.
SINK: An existing process unit/equipment such as reactors, separators, etc., which can accept a source.

RECYCLE STRATEGY This is an important strategy in the optimization of a process because through this technique we can determine the target for minimum usage of fresh resource (Fmin), maximum material reuse and minimum discharge to waste (Tmin); as a result of the reutilization of process streams. Total Fresh Load (F) Process Streams Total Terminal Load (T) Recovery Network Whole Plant OUT IN Maximum Recycle (R) Fmin = F - R Tmin = T - R

DIRECT RECYCLE

DIRECT RECYCLE This technique is based on the rerouting of process streams directly to process units without the addition of new equipment. Direct recycle must respect the constrains such as feed flowrate, composition, etc., for each process units involved in the recycle analysis in order to keep the same level of product quality as well as the safety process operation. Therefore, in order to fulfill with these constrains the process streams can be segregated, mixed and/or distributed in several ways depending on the specific case.

DIRECT RECYCLE REPRESENTATION
Sources Segregated Sources Sinks Constrains on feed flowrate and composition SINK ? SINK SINK

DIRECT RECYCLE The next design questions should be answered in order to apply direct recycle strategy successfully : Should a stream (source) be segregated and split? To how many fractions? What should be the flow rate of each split? Should streams or splits of streams be mixed? To what extent? What should be the optimum feed entering each sink? What should be its composition? What is the minimum amount of fresh resource used? What is the minimum discharge of unused process sources?

DIRECT RECYCLE HOW TO IDENTIFY BOUNDS ON SINKS
The previous design questions can be solved by the application of a graphical procedure called Source-Sink Mapping Diagram and Level-Arm Rules. However, before describing the methods mentioned above, it is necessary to identify the bounds (limits) on flowrate and composition for the sink(s) that is/are going to accept the recycle stream(s). HOW TO IDENTIFY BOUNDS ON SINKS The flow rate and composition bounds on sinks can be determined based on several considerations such as: From physical limitations (e.g. flooding flowrate, weeping flowrate, channeling flowrate, saturation composition, etc.). From manufacturer’s design data. From technical constrains (e.g., to avoid scaling, corrosion, explosion, buildup, etc.) From historical data.

HOW TO IDENTIFY BOUNDS ON SINKS (continued)
Example: By taking into account a process with a number of process sources that can be considered for possible recycle and replacement of the fresh material and/or reduction of waste discharge. Each source, i, has a given flowrate, Wi, and a given composition of a targeted species, yi. Available for services is a fresh (external) resource that can be purchased to supplement the use of process sources in sinks. Each sink, j, requires a feed whose flowrate, Ginj, and an inlet composition of a targeted species, zinj, that must satisfy certain bounds. Feed Ginj zinj Unit j Source i Wi yi

HOW TO IDENTIFY BOUNDS ON SINKS (continued)
As mentioned in the previous problem statement, there are bounds on flowrate and composition entering each sink. In this example, the bounds were set using historical data and they are described as follows : Flow Rate Bounds: Gminj Gmaxj Time Gminj < Ginj < Gmaxj Where: j=1,2,…,Nsinks Gminj and Gmaxj are the lower and upper bounds on admissible flowrate to unit j Composition Bounds: zminj < zinj < zmaxj Where: j=1,2,…,Nsinks zminj and zmaxj are the lower and upper bounds on admissible composition to unit j zmaxj zminj Time

zinj zinj +1 HOW TO IDENTIFY BOUNDS ON SINKS (continued)
Constrain propagation: In some cases, the constrains on a sink j are based on critical constrains for another unit (j+1). Therefore, to determine the constrains for unit j, it is necessary to use a process model that relates the inlets for both sinks. Example: Unknown Constraints Known Constraints zminj+1 < zinj+1 < zmaxj+1 zminj < zinj < zmaxj zminj < zinj < zmaxj Unit j Unit j+1 zinj zinj +1 From process model: zinj = 3zinj+1 0.03 < zinj < 0.04 0.09 < zinj < 0.012

Source-Sink Mapping Diagram
In order to determine if process streams can be direct recycle to a specific process unit or sink a graphic technique called Source-Sink Mapping Diagram was developed. This diagram is constructed by plotting the flowrate versus composition for each targeted species. On the source-sink mapping diagram the sources are represented by shaded circles and sinks are represented by unshaded circles. The constrains on flowrate and composition are respectively represented by horizontal and vertical bands and the intersection of this two bands provides a zone of acceptable load and composition for recycle. As shown in Fig. 1.

Source-Sink Mapping Diagram
Figure 1: Source-Sink Mapping Diagram Range of acceptable composition on sink “S” sink source S b a Composition c Flowrate Source “a” can be directly recycle to sink “S” Range of acceptable flowrates on sink “S” El-Halwagi, 1997

Lever-Arm Rules Flowrate Wa+Wb Wb Wa ya ys yb Composition
As we can see from Fig. 1, just source “a” can be directly recycle to the sink (s) but we still have two more sources “b” and “c”, which contain the targeted specie. Therefore, to create a mixed stream that fulfills with the flowrate and composition constrains for sink (s), the sources “a” and “b” will be mixed using the Lever-Arm Rules as follows in Fig. 2: Figure 2: Mixing of sources “a” and “b” Flowrate Resulting Mixture Source b Wa+Wb Source a Wb Wa ya ys yb El-Halwagi, 1997 Composition

Lever-Arm Rules As seen in Fig. 2, the result of mixing the source “a” and “b”, which have a flowrate Wa and Wb and a composition ya and yb respectively, is a mixture with a flowrate Wa + Wb and a targeted composition ys. This resulting mixture fulfills with the constrains for sink (s). Applying a material balance for the targeted species around the mixing operation we get the following equation: ys(Wa + Wb) = yaWa + ybWb (1) From equation (1), we obtained: Similarly: Wa yb - ys arm for a Wb ys - ya arm for b = Wa arm for a Wa + Wb Total arm = Arm for a = yb - ys Arm for b = ys - ya Total Arm = yb - ya

Lever-Arm Rules Flowrate Wa Wa+Wb Wb Composition ya ys yb Arm for b
The lever-arm for the sources and resulting mixture are represented in Fig. 3. Figure 3: Lever-Arm Rules for mixing Flowrate Source a b Resulting Mixture Wa Wa+Wb Wb Composition ya ys yb Arm for b Arm for a Total Arm El-Halwagi, 1997

Lever-Arm Rules Applications
Lever-Arm rules for fresh resource: One effective method to reduce fresh resource consumption is by mixing the fresh resource stream with a process stream. But to determine what should be the appropriate composition of the feed entering the sink (s), the lever-arm rules should be applied as shown in Fig. 4: Figure 4: Lever-Arm Rules for fresh resource Flowrate Source a Fresh Feed to Sink j Fresh Arm Total Arm yf ya Z feed to sink Composition

Based on the equations showed in the previous slide, we can see that the flowrate of fresh resource is minimized when the feed composition (zfeed to sink) entering the sink (s) is maximized. This analysis leads us to the following rule: Sink Composition Rule: When a fresh source is mixed with process sources (s), the composition of the mixture entering the sink should be set to a value that minimizes the fresh arm. Example: To reduce the fresh resource consumption in sink (s), the fresh resource stream is mixed with a process stream “a” to obtain a mixture, which satisfies the composition and flowrate requirements for sink (s). The composition constrains for the sink (s) are zmin < zin < zmax. What should be the composition of the feed entering the sink?

Figure 6: Sink Composition Rule Sink S Source a What should be the composition of the feed entering the sink? Zmin, Zavg or Zmax? ? ? ? Flowrate Fresh Z min Z max Z avg Z max Flowrate Source a Fresh Minimum fresh arm Sink S Applying the sink composition rule, the composition of the inlet feed should be Zmax because with that value we have the shortest fresh arm.

When there are two or more process sources that can be recycle to reduce the fresh usage, it is necessary to determine the order in which they should be used. Example: Supposed we have three process sources (a, b and c) that can be mixed with the fresh source. Which source should be recycled first in order to minimize the use of fresh resource? Source a Source b Source c Sink S ? ? ? Fresh Flowrate yF Z smax ya yb yc

In order to solve the problem previously mentioned, a prioritization rule was developed using the concept of fresh arm as follows: Source Prioritization Rule: To minimize the usage of the fresh resource, recycle of the process sources should be prioritized in order of their fresh arms starting with the source having the shortest fresh arm. According with the source prioritization rule, the source a should be used first until it is completely recycled before using source b. Source a (1st) Source B (2nd) Source C(3rd) Sink S Fresh Flowrate Shortest Fresh Arm yF Z smax ya yb yc

Process Before Recycle
Recycle Alternatives Using the concepts explained in direct recycle strategies, we can set the target performance of a process. However, depending on the process this target may be attain for more than one recycle alternative, as shown in the next example: Example: To minimize the terminal load discharged of the process shown below, two different recycle alternatives could be applied. Alternative 1 Process Before Recycle Fk,1 Tk,1 1 2 Tk,1 Tk,2 2 3 1 Fk,1 Fk,2 Fk,2 Tk,2 3 Alternative 2 Note: To generate an effective recycle strategy all the recycle streams should be rerouted to units process that employ fresh resources (In our case: S1 and S3). Tk,1 2 3 1 Fk,1 Fk,2 Tk,2

Material Recycle Pinch Diagram

Reference: El-Halwagi, M. M., F. Gabriel, and D. Harell, “Rigorous Graphical Targeting for Resource Conservation via Material Recycle/Reuse Networks”, Ind. Eng. Chem. Res., 42, (2003) Material Recycle Pinch Diagram is a method use to determine the target performance of a process as a result of direct recycle without detailing the recycle strategies. Before describing the targeting procedure the following considerations should be taken into account: Composition Constrain for Sink j: zminj < zinj < zmaxj Where: j=1,2,…,Nsinks Impurities Entering the Sink j: Where Gj is the feed flowrate entering to the sink j Msinkj = Gj zinj Constrain on Load: 0 < Msinkj < Mmaxj Where: j=1,2,…,Nsinks

In order to apply the Material Recycle Pinch Diagram the next procedure should be follow: Rank the sinks in ascending order of maximum admissible composition of impurities. zmax1 < zmax2 < …. < zmaxj.... < zmaxNSINKS Rank sources in ascending order of impurities composition y1 < y2 < …. < yi.... < yNSINKS Plot the sink composite curve. In order to generate this curve each sink is represented as an arrow by plotting the maximum load of impurities for each sink (Msinkj = Gj zinj ) versus its flowrate, as shown in Fig. 7.

Figure 7: Sink Representation Load Msink,max3 S3 Msink,max2 S2 Msink,max1 S1 G1 G3 G2 Flowrate Reference: El-Halwagi, M. M., F. Gabriel, and D. Harell, “Rigorous Graphical Targeting for Resource Conservation via Material Recycle/Reuse Networks”, Ind. Eng. Chem. Res., 42, (2003)

Sink Composite Curve (Fig. 8) - is the outcome of superposing the sink arrows in ascending order starting with the sink, which has the lowest composition of impurities (zmaxj). Figure 8: Sink Composite curve G1 + G1 G3 S2 S1 S3 Msink,max1 Msink,max2 Msink,max3 G2 + G1 + G2 Load Flowrate Source Composite Curve

Generate the source composition curve by plotting the load of each source (Msourcei = Wj yi ) versus its flowrate. This curve starts with the source that has the least composition and the rest of the sources will be plotted in ascending order using superposition, as shown in Fig.9: Figure 9: Source Composite Curve Load Msource3 M source2 Msource1 W1 W2 W3 Flowrate

Locating the pinch point. The pinch point is found by placing both composite curves in the same diagram (Fig. 10a), then the source composite stream is moved horizontally until it touches the sink composite stream. The point where both curves unite is called the pinch point (Fig. 10b). Figure 10 a : Sink and Source Composite Curves Load Sink Composite Curve Source Composite Curve Flowrate

Figure 10 b : Material Recycle Pinch Diagram Load Material Recycle Pinch Point Source Composite Curve Sink Composite Curve Flowrate Minimum Fresh Maximum Recycle Minimum Waste Reference: El-Halwagi, M. M., F. Gabriel, and D. Harell, “Rigorous Graphical Targeting for Resource Conservation via Material Recycle/Reuse Networks”, Ind. Eng. Chem. Res., 42, (2003)

Identify the targets for Minimum Fresh Usage, Maximum Direct Recycle and Minimum Waste Discharge. Those targets are determined using the Material Recycle Pinch Diagram as follows: The target for Minimum Fresh Usage is the flowrate of sink below, which there are not sources (fig. 10b). The target for Maximum Direct Recycle is the overlapped area region of process and sources (fig. 10b). The target for Minimum Waste Discharge is the flowrate above the sources, which there are not sinks. (fig. 10b)

Design Rules In order to attain the optimum target for minimum fresh usage and minimum waste discharge, the following three design rules are required: 1. No flowrate should be passed through the pinch. Figure 11: Passing Flow through the Pinch. Load Sink Composite Curve Source Composite Curve Fresh Recycle Waste Flowrate Minimum Fresh Minimum Waste Reference: El-Halwagi, M. M., F. Gabriel, and D. Harell, “Rigorous Graphical Targeting for Resource Conservation via Material Recycle/Reuse Networks”, Ind. Eng. Chem. Res., 42, (2003)

Design Rules As we can see in Fig. 11, the sink stream is not touching the source stream; this fact allows a flowrate (α) to pass through the pinch point, which will cause an increase in the consumption of fresh resource as well as in the waste discharge in the amount equal to the (α). Therefore, it will increase the cost operation twice since we are consuming more resource and producing more waste. No waste should be discharged from sources below the pinch. 3. No fresh resource should be used in any sink above the pinch.

Targeting for Impure Fresh
In the case where the fresh resource is not pure, the same targeting procedure explained previously applies. However, the main difference now is that the source composite curve will not be locus on the horizontal axis as was shown before, instead it will be locus on a straight line emanating from the origin. The slope of this line is the composition of impurities in the fresh (yfresh ) Fig.12. Figure 12: Material pinch Diagram when fresh resources is Impure Flowrate Material Recycle Pinch Point Sink Composite Curve Source Composite Curve Minimum Fresh Maximum Recycle Waste Load Locus Reference: El-Halwagi et al., 2003

Material Recycle Pinch Diagram Based on Properties
Reference: Kazantzi, V. and M. M. El-Halwagi, “Targeting Material Reuse via Property Integration”, Chem. Eng. Prog., 101(8) 28-37(2005)

As we have seen so far, we have just considered the composition and flowrate constrains to evaluate the sink performance; however, there are many process units, specially those that work with solvents, which their performance are based in properties such as viscosity, solubility, density, volatility, etc. Therefore, in order to apply direct recycle as a process optimization strategy, a graphic property integration method was developed to track properties instead of compositions as was study previously.

Before describing the targeting procedure, consider the following process with: A number of sinks Nsinks, which require a feed with a given flowrate Gj and an inlet property, pinj. The feed entering to each sink should satisfy the following constrain: A number of sources Nsources, which have a given flowrate i, and a given property, pi. They can be considered for recycle to reduce fresh usage. A fresh resource whose property value is pfresh, and it can supplement the use of process sources in sinks. Property constrain: pminj < pinj < pmaxj Where: j=1,2,…,Nsinks (1)

In order to develop a procedure that allows us to determine the optimum target performance of the process stated before, the following rules should be taken into account. The resulting property of mixing two or more source streams will be evaluated according to the next equation: F * Ψ ( p ) = ΣFi * Ψ( pi ) (2) i Where F is the total flowrate of the mixture, which is given by: F = ΣFi (3) And, Ψ( pi ) is the property-mixing operator, which can be evaluated from first principles or estimated through empirical or semi-empirical methods. 1. Mixing Rule:

Example: Consider the mixing of two liquid sources whose flowrates are F1 and F2, volumetric flowrates are V1 and V2, and densities are ρ1 and ρ2. Suppose that the volumetric flowrate of the mixture is given by V = V1 + V2 (4). Applying the definition of density and designating the total flowrate of the mixture by F, we obtain: F = F1 + F2 (5) comparing with equation (2) ρ ρ1 ρ2 We can define the density-mixing operator as: Ψ( pi ) = 1 (6) ρ i

After the mixing operator is defined, the sink property constrain (eq. 1) can be restated as follows: And considering the special case where the fresh source has a property operator larger than all other streams, the sink constrain is rewritten as: The equations shown above gives us the basis to derive optimality rules for maximum recycle of process to sinks, as explained in the following slide. Ψminj < Ψinj < Ψmaxj (7) Ψfresh < Ψinj < Ψmaxj (8) Where: Ψfresh = Ψ( pfresh) (9)

Reference: Kazantzi, V. and M. M. El-Halwagi, “Targeting Material Reuse via Property Integration”, Chem. Eng. Prog., 101(8) 28-37(2005) 2. Sink Optimality Condition: When a fresh source is mixed with a reused material, the inlet property operator to the sink should be assigned to its maximum feasible value, that is described in Fig. 13 using the lever-arm rules: Figure 12: Sink Optimality Condition Flowrate To minimize the consumption of fresh resource Ψin = Ψ max. Appling the lever-arm rule: Ffresh = Ψi - Ψ maxj Gj Ψi - Ψ fresh Ffresh = Fresh arm for 1 Gj Total arm from i to fresh Source i Sink j Gj Fresh Minimum fresh arm Ψ fresh Ψ max Property Operator

Reference: Kazantzi, V. and M. M. El-Halwagi, “Targeting Material Reuse via Property Integration”, Chem. Eng. Prog., 101(8) 28-37(2005) 3. Source Prioritization Rule: The use of the process sources should be prioritized starting with the source having the last value of property operator and sequenced in increasing order of the property operator of the sources (Fig.13). Figure 13: Source Prioritization Rule Flowrate Source i +1 Sink j Source i Gj Fresh Fresh arm for i Fresh arm for i+1 Ψ fresh Ψ max Ψi Ψi +1 Property Operator

Based on the optimality conditions for sources and sinks, the next graphical targeting procedure is developed: Targeting Procedure: Rank the sinks in ascending order of Ψmaxj, Ψ max1 < Ψ max2 < …. < Ψ maxj.... <Ψ maxNSINKS (10) and calculate the maximum admissible property load (Uj), for each sink using the following equation: Uj= Gj* Ψmaxj (11) Where Gj is the required flowrate for each sink.

Creating a sink composite curve using the required flowrate for each sink (Gj) and the calculated values of the maximum admissible loads (Uj), as shown in Fig.14. Figure 14: Fresh Locus G1 G2 Flowrate G3 U1 Load U1 + U2 U1 + U2 + U3 Sink Composite Curve Sink3 S3 S2 Sink2 Source Composite Curve Sink1 Reference: Kazantzi, V. and M. M. El-Halwagi, “Targeting Material Reuse via Property Integration”, Chem. Eng. Prog., 101(8) 28-37(2005)

Evaluating the property operator of fresh (Ψfresh) using equation 9, then a locus of the fresh line is drawn starting from the origin with a slope of Ψfresh Fig.15. Figure 15: Sink Composite Curve Based on Properties. G1 G2 Flowrate G3 U1 Load U1 + U2 U1 + U2 + U3 Sink Composite Curve Fresh Line Reference: Kazantzi, V. and M. M. El-Halwagi, “Targeting Material Reuse via Property Integration”, Chem. Eng. Prog., 101(8) 28-37(2005)

Calculating the value of the property operator for each source (Ψi) and then ranking the sources in ascending order of (Ψi). Ψ 1 <Ψ2 < …. < Ψ3.... <Ψi …. <Ψi NSources (12) In addition, the property load of each source (Mi) is calculated using the next equation. Mi = Fi * Ψ( pi ) (13) Where Fi is the flowrate and Ψ( pi ) is the property operator for each source .

Generating the source composite curve using the flowrate of each source and the calculated values of the property operator Ψi,, as seen in Fig. 16. Figure 16: Sink Composite Curve Based on Properties M1 + M2 This curve starts with the source, which has the lowest property operator and the rest of the sources will be plotted in ascending order using superposition. Source2 Load Source Composite Curve M1 Source1 F1 F2 Flowrate Reference: Kazantzi, V. and M. M. El-Halwagi, “Targeting Material Reuse via Property Integration”, Chem. Eng. Prog., 101(8) 28-37(2005)

Placing both composite curves in the same diagram Fig. 17: Figure 17: Sink and Source Composite Curves G1 G2 Flowrate G3 U1 Load U1 + U2 U1 + U2 + U3 Sink Composite Curve Fresh Line Source Composite Reference: Kazantzi, V. and M. M. El-Halwagi, “Targeting Material Reuse via Property Integration”, Chem. Eng. Prog., 101(8) 28-37(2005)

Locating the pinch point. The pinch point is found by placing the source composite curve onto the fresh line and then sliding it to the left until the source composite stream touches the sink composite stream. The point where both curves unite, is called the pinch point (Fig. 18). Figure 18: Pinch Diagram Flowrate Load Property-Based Material Reuse Pinch Point Sink Composite Curve Source Composite Fresh Line Reference: Kazantzi, V. and M. M. El-Halwagi, “Targeting Material Reuse via Property Integration”, Chem. Eng. Prog., 101(8) 28-37(2005)

Identifying the targets for Minimum Fresh Usage, Maximum Direct Recycle and Minimum Waste Discharge. Those targets are determined using the Material Recycle Pinch Diagram, as shown in Fig.19: Figure 19: Pinch Diagram (Targeting) Load Property-Based Material Reuse Pinch Point Source Composite Curve Sink Composite Curve Fresh Line Flowrate Minimum Fresh Usage Maximum Recycle Minimum Waste Reference: Kazantzi, V. and M. M. El-Halwagi, “Targeting Material Reuse via Property Integration”, Chem. Eng. Prog., 101(8) 28-37(2005)

Design Rules: The same three design rules explained in the Material Recycle Pinch Diagram directly apply to the Material Recycle Pinch Diagram Based on Properties, which are as follows: No flowrate should be passed through the pinch. 2. No waste should be discharged from sources below the pinch. No fresh resource should be used in any sink above the pinch. Reference: Kazantzi, V. and M. M. El-Halwagi, “Targeting Material Reuse via Property Integration”, Chem. Eng. Prog., 101(8) 28-37(2005)

TIER II Case Study Suvit

Case Study Tapioca Starch Manufacturing
Reference: Tia., Thongchai Srinophakun Water-Waste Management of Tapioca Starch Manufacturing Using Optimization Technique. Science Asia, pp 57-67, February (2000) Tapioca Starch Manufacturing Tapioca Starch is obtained from the processing of tuberous roots of the manioc or cassava plant. This process can be divided in four stages, which are: Washing and peeling of the roots, rasping them and straining the pulp with addition of water. Rapid removal of the fruit water and its soluble and replacing them with pure water to prevent deterioration of the pulp. This stage includes sedimentation and washing of the starch in tanks or settling tables. The removal of water by draining, centrifuging and drying. Grinding, bolting and other finishing operations. Tapioca starch process is described in detailed in the following flowsheet Fig. 20.

Figure 20: Flowsheet for the Manufacturing of Tapioca Starch Plant.
Fresh Roots 32 ton/hr. (S=20.) Wastewater 75 ton/hr. (S=0.2%, COD=40) Water 72 ton/hr. (S=0.06%, COD=29) Wash & Rasp Clean Roots 28 ton/hr. (S=22%) Peels 1.19 ton/hr. (S=7.8%) Water 86 ton/hr. (S=13%, COD=196) Grind Pulp 100 ton/hr. (S=15%) Fiber 21ton/hr. (S=15%) Fresh Water 15 Ton/hr Screen 1 Final Screen Starch Milk 114 ton/hr. (S=8%) Fiber 21ton/hr. (S=15%) Fiber 28 ton/hr. (S=18%) Fresh Water 25 Ton/hr Water 38 ton/hr. Screen 2 Press Starch Milk 130 ton/hr. (S=7%) Water 160 ton/hr. (S=15%, COD=29) Fresh Water 72 Ton/hr Separator 1 Starch Milk 130 ton/hr. (S=7%) Fiber 41 ton/hr. (S=10% COD=205 ) Wastewater 87 ton/hr. Fresh Water 8 Ton/hr Screen 3 Starch Milk 16 ton/hr. (S=33%) Wastewater 30 ton/hr. (S=0.07, COD=8) Fresh Water 42 Ton/hr Separator 2 Evaporated Water 4 ton/hr. Starch Milk 15 ton/hr. (S=34%) Wastewater 5 ton/hr. (S=0.75%, COD=6.5) Drying Dewater Dry Starch 7.43 ton/hr. (S=67%) Water loss 0.31 ton/hr. (S=67%)

Case Study As seen in Fig. 20, the processes of washing, rasping and grinding do not required the use of fresh water to operate because the water is used to wash the adhering dirt to the roots as they go through the mentioned processes. After that, the slurry is sent to the screening process in order to separate the fiber and other insoluble particles such as protein, fat, etc. Then the soluble particles are removed with water in the separating process. On the other hand, the discharged water from screening and separating processes contain a high value of starch. Therefore, in order to recover this important component those streams are sent to the ‘final screen’. The stream resulting from the final screen process is rich with starch and is returned to the grinding process while the fiber is sent to the press process to recover water. Fresh pulp is sold as a cattle food. Taking into account the information given for tapioca starch manufacturing process, determine the recycle strategies that minimize the usage of fresh water.

Case Study Solution: In order to solve the previously stated problem the next procedure is followed: Identifying the sinks/process units which consume fresh water, and as we can see in Fig. 20 they are: Screen 1, Screen 2, Separator 1, Screen 3 and Separator 2. Identifying the bounds in composition and flowrate for each one of the process units mentioned above. To determine these bounds a mathematical model was developed using the following assumptions: There are two main components in the manioc roots: starch and water. Only one single contaminant is considered: COD (Chemical Oxygen Demand) The composition of starch loss in drying is the same as they dry starch product.

Composition Constrains (Based on COD mg/l)
Case Study As a result of the application of the mathematical model the following process constrains were determined (Table 1): Table 1: Process Constrains Process Units Flowrate Constrains (Tons/hr) Composition Constrains (Based on COD mg/l) Screen 1 15≤ Flowrate of Feed to Screen 1 ≤ 20 0≤ Composition of COD in Feed to Screen 1 ≤ 5 Screen 2 25≤ Flowrate of Feed to Screen 2 ≤ 33 0≤ Composition of COD in Feed to Screen 2 ≤ 4 Separator 1 80≤ Flowrate of Feed to Separator 1 ≤ 72 0≤ Composition of COD in Feed to Separator 1 ≤ 0.00 Screen 3 8≤ Flowrate of Feed to Separator 1 ≤ 10 0≤ Composition of COD in Feed to Screen 3 ≤ 3.5 Separator 2 42≤ Flowrate of Feed to Separator 2 ≤ 50 0≤ Composition of COD in Feed to Separator 2 ≤ 0.00

Case Study Selecting the process streams (sources) that can be recycle to the chosen process units. The criteria used to select the streams is based on the COD value, amount of starch and amount of protein. This criteria is applied to the four wastewater streams that are leaving the process as follows: The stream leaving the washing and rasping units can not be reused in any unit due to its high content of COD. The discharged water from Separator 1 can not be reused in any unit except in washing process since this water contains high protein. The streams leaving the dewater and Separator 2 units can be consider for recycle.

Case Study Generating the Source-Sink Mapping Diagram Fig. 21:
Figure 21: Source-Sink Mapping Diagram for the Tapioca Starch Case Study 80 Separator 1 (S3) 72 70 60 50 Separator 2 (S4) 42 Flowrate, tons/hr 40 Separator 1 wastewater 1(R2) 33 30 Screen 2 (S2) 25 20 Screen 1 (S1) 15 10 Screen 3 (S4) 8.0 Dewater wastewater (R1) 5.0 3.5 Concentration of Contaminant, mg/lt

Case Study Applying Lever-Arm Rules. Flowrate, tons/hr
Calculations for Screen 1 For S1, R1 has the shortest water fresh arm 80 Separator 1 (S3) 72 70 Fresh Water Used in S1 = tons/hr 60 Flowrate to be recycled from R1 to S1 should be: 50 15 – 3.46 = tons/hr Separator 2 (S4) 42 Flowrate, tons/hr 40  All of R1 is used in S1 (5 tons/hr) 33 Screen 2 (S2) 30 Separator 1 wastewater 1(R2) 25 20 Screen 1 (S1) 15 10 Screen 3 (S4) 8.0 Dewater wastewater (R1) 5.0 3.5 Concentration of Contaminant, mg/lt

Case Study Applying Lever-Arm Rules. Flowrate, tons/hr
Calculations for Screen 1 (continued) For S2, After using all R1, R2 has the next shortest arm 80 Separator 1 (S3) Applying a water balance: 72 70 5* *8 + Fresh Water in S1* = 15*5 60 5.312 tons/hr 50 Separator 2 (S4) 42 Fresh water in S1 = 15 – 5 – 5,312 = 4,68 ton/hr Flowrate, tons/hr 40 33 30 Screen 2 (S2) Separator 1 wastewater 1(R2) 25 20 Screen 1 (S1) 15 10 Screen 3 (S4) 8.0 Dewater wastewater (R1) 5.0 3.5 Concentration of Contaminant, mg/lt

Case Study Applying Lever Arm Rules. Flowrate, tons/hr
Calculations for Screen 2 80 Separator 1 (S3) 72 70 Fresh Water Used in S2 = tons/hr 60 Flowrate to be recycled from R2 to S2 should be: 50 Separator 2 (S4) 25 – 12.5 = 12.5 tons/hr 42 Flowrate, tons/hr 40  tons/hr of R2 are used in S2 33 Screen 2 (S2) 30 Separator 1 wastewater 1(R2) 25 20 Screen 1 (S1) 15 10 Screen 3 (S4) 8.0 Dewater wastewater (R1) 5.0 3.5 Concentration of Contaminant, mg/lt

Case Study Applying Lever Arm Rules. Flowrate, tons/hr
Calculations for Screen 3 80 Separator 1 (S3) 72 70 Fresh Water Used in S3 = 4.5 tons/hr Flowrate to be recycled from R2 to S3 should be: 60 8 – 4.5 = 3.5 tons/hr 50  3.5 tons/hr of R2 are used in S3 Separator 2 (S4)  8.7 tons/hr of R2 will go to waste since they can not be used in other sink, 42 Flowrate, tons/hr 40 33 30 Screen 2 (S2) Separator 1 wastewater 1(R2) 25 20 Screen 1 (S1) 15 10 Screen 3 (S4) 8.0 Dewater wastewater (R1) 5.0 3.5 Concentration of Contaminant, mg/lt

Case Study Case Study R1 R2 Fresh Water Waste
Applying Lever Arm Rules. For the process units Separator 1 and Separator 2 nothing can be done to reduce their consumption of fresh water since those sinks are not allowed to accept a feed flowrate with any concentration of contaminant. Solution to the minimization of fresh water consumption R1 5 tons/hr Screen 1 R2 5.312 tons/hr 30 tons/hr 12.5 tons/hr Screen 2 3.5 tons/hr Fresh Water 12.5 tons/hr Screen 3 4.68 tons/hr 21.7 tons/hr 4.5 tons/hr Waste 8.7 tons/hr Total Fresh Water Consumption = = tons/hr

Case Study Case Study R1 R2 Fresh Water Waste
Applying Lever Arm Rules. Alternate Solution: R1 5 tons/hr 3 tons/hr Screen 1 6.937 tons/hr 5.063 tons/hr R2 30 tons/hr 12.5 tons/hr Screen 2 2 tons/hr 12.5 tons/hr Fresh Water 1.875 tons/hr 21.7 tons/hr 4.125 tons/hr Screen 3 Waste 8.7 tons/hr The same target for minimum fresh usage is reached using a different recycle strategy.

Inlet Composition (Based on COD mass fraction)
Case Study Case Study Applying Lever Arm Rules. The same problem is now solve using the Material-Recycle Pinch Diagram. The important data for sources and sinks are summarized in Tables 2 and 3. Table 2 : Sources Data for the Tapioca Starch Case Study Source Flowrate (Tons/hr) Inlet Composition (Based on COD mass fraction) Inlet Load (Tons/hr) R1 (Dewater 1) 5 0.065 0.325 R2 (Separator 1) 30 0.08 2.4

Maximum Inlet Composition (Based on COD mass fraction)
Case Study Case Study Applying Lever Arm Rules. Table 3 : Sink Data for the Tapioca Starch Case Study Sinks Flowrate (Tons/hr) Maximum Inlet Composition (Based on COD mass fraction) Maximum Inlet Load Separator 1 72 Separator 2 42 Screen 3 8 0.035 0.28 Screen 2 25 0.04 1.0 Screen1 15 0.05 0.75

Case Study Case Study Applying Lever Arm Rules.
Using the data given in the Tables 2 and 3, the sink and source composite curve are constructed as shown in Figures 22 and 23: Figure 22: Source Composite Curve for the Tapioca Starch Case Study 3.0 2.725 2.5 2.0 Separator 1 Load, tons/hr 1.5 Source Composite Curve 1 0.5 0.325 Dewater Dewater 10 20 30 35 40 50 60 70 80 90 100 120 130 140 150 160 170 5 Flowrate, tons/hr

Case Study Case Study Applying Lever Arm Rules. Load, tons/hr
Figure 23: Sink Composite Curve for the Tapioca Starch Case Study 3.0 2.5 2.03 2.0 Load, tons/hr Sink Composite Curve Screen 1 1.5 1.28 1 Screen 2 0.5 Screen 3 Separator 2 Separator 1 0.28 10 20 30 40 50 60 70 80 90 100 120 130 140 150 160 170 42 114 122 147 162 Flowrate, tons/hr

Case Study Case Study Applying Lever Arm Rules. Next, both curves are placed in the same diagram and the source composite curve is slid horizontally to the right until it touches the sink composite curve as shown in Fig. 24: Figure 24: Material Recycle Pinch Diagram for the Tapioca Starch Case Study Waste = 8.7 3.0 2.5 Material Recycle Pinch Point 2.0 Load, tons/hr 1.5 Sink Composite Curve 1 Source Composite Curve 0.5 Fresh Water = 135.7 10 20 30 40 50 60 70 80 90 100 120 130 140 150 160 170 180 Flowrate, tons/hr 135.7 162 170.7

Case Study Case Study Applying Lever Arm Rules.
As demonstrated by applying Direct Recycle Strategy, the maximum consumption of fresh water reduction that can be reached without the use of new equipment is from 162 tons/hr to tons/hr. The same targeted value was reached by using the Material Recycle Pinch Diagram and Direct Recycle Strategy.

Case Study TIER III Open Ended Problem
Applying Lever Arm Rules. TIER III Open Ended Problem

Case Study Open Ended Problem Applying Lever Arm Rules.
Problem Statement: Consider the metal degreasing process shown in Fig.25: Figure 25: Microelectronics Manufacturing Flowsheet Reference: Kazantzi, V. and M. M. El-Halwagi, “Targeting Material Reuse via Property Integration”, Chem. Eng. Prog., 101(8) 28-37(2005)

Case Study Open Ended Problem Applying Lever Arm Rules.
In this process, a fresh organic solvent is used in the degreaser and the absorber. A reactive thermal processing and solvent regeneration system is used to decompose the grease and the organic additives and regenerate the solvent from the degreaser. The liquid product of the solvent regeneration system is reused in the degreaser, while the gaseous product is passed through a condenser, an absorber and a flare. The process produces two condensate streams: Condensate I from the solvent regeneration unit and Condensate II from degreaser. The two streams are currently sent to hazardous waste disposal. Since these two streams have many desirable properties that enable their possible use in the process, it is recommended their recycle/reuse to be considered. The absorber and the degreaser are the two process sinks. The two process sources satisfy many properties required for the feed of two sinks. An additional property should be examined; namely Reid Vapor Pressure (RVP), which is important in characterizing the volatility, makeup and regeneration of the solvent.

Lower Bound on RVP (atm) Upper Bound on RVP (atm)
Case Study Open Ended Problem Applying Lever Arm Rules. The mixing rule for vapor pressure (RVP) is giving by the following expression: The pertinent information regarding the sinks in study can be seen in Table 5. Table 5 : Flow Rates and Bounds on Properties of Sinks Sink Flowrate (kg/s) Lower Bound on RVP (atm) Upper Bound on RVP (atm) Degreaser 5.0 2.0 3.0 Absorber 4.0

Open Ended Problem Applying Lever Arm Rules.
The RVP for Condensate I is a function of the thermal regeneration temperature as follows: RVPCondensate I = Where RVP Condensate I is the RVP of Condensate I in atm and T is the temperature of thermal processing system in K. The acceptable range of this temperature is 430 to 520 K. At present, the thermal processing system operates at 515 K leading to an RVP of 6.0. The data for Condensate I and Condensate II are given in Table 6.

Open Ended Problem Applying Lever Arm Rules.
Table 6 : Properties of Process Sources and Fresh Sources Flowrate (kg/s) RVP (atm) Process Condensate I 4.0 6.0 Process Condensate II 3.0 2.5 Fresh Solvent To be determined 2.0 Using Direct Recycle Strategies, identify the target for minimum usage of fresh solvent and minimum waste discharge for this case study.

END OF TIER III CONGRATULATIONS This is the end of Module 18.
Applying Lever Arm Rules. CONGRATULATIONS This is the end of Module 18. Please submit your report to your professor for grading.

REFERENCES Applying Lever Arm Rules.
El-Halwagi, M.M. Pollution Prevention through Process Integration. Acadamic Press. 1997 El-Halwagi, M. M., F. Gabriel, and D. Harell, “Rigorous Graphical Targeting for Resource Conservation via Material Recycle/Reuse Networks”, Ind. Eng. Chem. Res., 42, (2003) Kazantzi, V. and M. M. El-Halwagi, “Targeting Material Reuse via Property Integration”, Chem. Eng. Prog., 101(8) 28-37(2005) Suvit Tia., Thongchai Srinophakun Water-Waste Management of Tapioca Starch Manufacturing Using Optimization Technique. Science Asia, pp 57-67, February (2000)

NETWORK PINCH ANALYSIS PART II

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