State-of-the-Art Review of Pinch Analysis Techniques for Water

Ind. Eng. Chem. Res. 2009, 48, 5125–5159

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REVIEWS State-of-the-Art Review of Pinch Analysis Techniques for Water Network Synthesis Dominic Chwan Yee Foo*

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Department of Chemical and EnVironmental Engineering, UniVersity of Nottingham Malaysia, Broga Road, 43500 Semenyih, Selangor, Malaysia

Water network synthesis has been an active area of research for the past one and a half decades. Many think that the technology reached a mature stage in the late 1990s, especially for the insight-based technique based on pinch analysis. The only review for the field dates back to 2000. However, many new papers published in this century reveal that new research gaps are found and more works were carried out to address the limitations of the “old” techniques. The main objective of this review is to provide a state-of-the-art overview of the insight-based techniques developed in the 21st century, particularly those developed for single impurity network of the fixed flow rate problems. Comparisons were also made between these recent techniques and those developed for the fixed load problems in the past century. Various flow rate targeting techniques developed for water reuse/recycle, regeneration, and wastewater treatment are reviewed in detail, along with the network design techniques that achieve the established targets. Finally, future research directions are outlined at the end of the review. Introduction The term process synthesis was first defined by Rudd in the late 1960s.1 The definition of the term has evolved over the years, and one commonly acceptable definition takes the form of “the discrete decision-making activities of conjecturing (1) which of the many available component parts one should use, and (2) how they should be interconnected to structure the optimal solution to a given design problem”.2 Since its early establishment, process synthesis has been an active research area, and reviews on its development can now be found in many papers.2-16 Manousiouthakis and Allen10 broadly classified process synthesis into seven major areas: i. Material synthesis ii. Reaction path synthesis iii. Reactor network synthesis iv. Separation network synthesis v. Heat exchanger network synthesis vi. Mass exchanger network synthesis vii. Total flowsheet network synthesis Among these many process synthesis areas, the most welldeveloped area is perhaps the synthesis of heat exchanger network (which later evolved into other heat integration areas,9 e.g. distillation integration, utility system design, etc.), with over 460 related works in the past century.14 The analogy between heat and mass transfer led to the evolution of mass exchanger network synthesis in the late 1980s17-19 (and other mass integration topics subsequently11,12,15). Within the framework of mass integration, water network synthesis (often known as water minimization) emerges as a special case for the area. Considerably amount of work has been presented for water network synthesis using both the insightbased pinch analysis technique (or water pinch analysis in short) and the mathematical-based optimization approach. This review paper focuses on the former, in which the success of the insight* To whom correspondence should be addressed. Tel.: +60-3-8924-8130. Fax: +60-3-8924-8017. E-mail: [email protected].

based approach has been mainly reported for single impurity systems. Professor Robin Smith and his co-workers at UMIST (now the University of Manchester) initiated the insight-based approach on pinch analysis technique in the mid-1990s.20-22 In their later works, the approach was extended into wastewater treatment network synthesis.23-25 With the publication of the first review for the research area26 as well as the publication of a dedicated textbook27 at the end of the last century, many consider the technology to have reached a mature stage. However, this is not the case, with the evidence of many recent published papers to address the limitation of the “old” techniques in the 20th century, the technology appears to be once again reborn. It is also worth mentioning that, unlike the case in the 20th century, recent works of the field are no longer limited to one group of researchers but are widely spread to groups in other parts of the world. Furthermore, water pinch analysis techniques are no longer limited to one kind. With the existence of a vast variety of new techniques and approaches, this makes the field more diverge and dynamic. This justifies why a second review paper is needed to analyze the advantages and limitations in each technique. Apart from making fundamental changes for the process operations (e.g., replacing cooling water towers by fin fan coolers, etc.), options for reducing the water demand of a process may be done via water reuse, recycle, and regeneration.20,21 In the context of process integration, reuse means that the effluent from a water-using operation is sent to other operations and does not re-enter operations where it was emitted (Figure 1a). On the other hand, a recycle scheme permits the effluent to reenter the operations where it is generated (Figure 1b). In regeneration schemes, effluent is partially treated by water purification unit (e.g., filter, adsorption, stripper, etc.) before reuse (Figure 1c) or recycle (Figure 1d) takes place. Similar to other typical applications of pinch analysis techniques (e.g., heat or mass exchange network synthesis), water network synthesis tasks are also subdivided into two stages

10.1021/ie801264c CCC: $40.75  2009 American Chemical Society Published on Web 05/07/2009

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Ind. Eng. Chem. Res., Vol. 48, No. 11, 2009

Figure 1. Various schemes for water reduction:20,21 (a) reuse, (b) recycle, (c) regeneration-reuse, and (d) regeneration-recycling.

involving flow rate targeting and network design. Flow rate targeting aims to set the minimum fresh water and wastewater flow rates for a network merely based on first principles (concentration and flow rate restrictions), without having to sort out the detailed matching between the individual waterproducing and water-using processes. These processes are matched in the network design stage to achieve minimum flow rates obtained in the targeting stage. The review is structured as follow. Two main categories of water network synthesis cases, i.e. fixed load and fixed flow rate problems. are first outlined. The several sections that follow provide a state-of-the-art review on the various flow rate targeting techniques developed for water reuse/recycle, regeneration, and wastewater treatment. This is followed by the review of the various water network design techniques. For each problem, the developed techniques are categorized into fixed load and fixed flow rate problems, where comparison may be easily made. An overall comparison among the various published works (e.g., origin, publication year, etc.) is then followed. The last section suggests future research direction, before the review is finally concluded. A few important remarks are worth mentioning here. First, the review focuses on single impurity problems where the insight-based approaches achieve significant results. Second, the review covers papers that were published in publicly available journals as well as important international conferences (conference papers that have their approach published in the journals are omitted). Third, only papers published in English media is included. Fourth, the review only covers water network synthesis in continuous processes, i.e. techniques developed for batch and semibatch processes are excluded. Finally, note that the review focuses on newly developed targeting and design tools. Hence, papers that report the application of these tools are excluded. Fixed Load Versus Fixed Flow Rate Problems Historically, two periods of time can be distinguished in the development of insight-based techniques for water network synthesis: phase 1 being the initiation of water pinch analysis technique since 1994 and phase 2 being the new approaches developed after 2000. There is in fact some overlap between the two phases of work, as techniques that fall in phase 2 were actually initiated in 1996 but only gained significant attention after 2000 (see descriptions in sections Targeting Techniques for Fixed Flow Rate Problems and Overall Analysis). Approaches developed in phase 1 mainly focused on mass transfer-based water-using processes and were developed based

on the more generalized approach of mass exchange network synthesis problems.17 In these processes, water is mainly used as a mass separating agent (as the lean stream) to remove a certain amount of impurity load from the rich stream (Figure 2a). Typical examples of these processes include vessel cleaning, solvent extraction, gas absorption, etc. The main concern for the phase 1 techniques is the impurity load removal from the rich stream, with the water flow rate requirement of the process being a secondary concern. Hence, the problem is more commonly known as the fixed load problem, with the following problem statement: • Given a number of water-using processes, designated as PROCESS, or P ) {p ) 1, 2, 3, ..., NP}, each with an inlet (CPR,in) and outlet (CPR,out) impurity concentrations of a targeted species, each process requires an impurity removal load of ∆mp. • In each process, the water source may enter at the maximum inlet concentration (Cin) and leave at the maximum outlet concentration (Cout) of the targeted species. • External fresh water source(s) are to be purchased to satisfy the impurity removal requirement of the process. It is worth mentioning some unique characteristics of the fixed load problem. Since water is used as a mass separating agent in the mass transfer processes, water loss and gain are always assumed to be negligible, and hence, the inlet and outlet flow rates of the process are assumed to be uniform. In the event where water losses/gains are significant, modifications are needed for the model.21,27 Note also that, since water of better quality (lower than Cin and/or Cout) may enter or leave the waterusing processes, the inlet and outlet flow rates (Fp) may vary and are given by eq 1: Fp )

∆mp (Cout - Cin)

(1)

On the other hand, the method developed in phase 2 sees the deviation from the mass transfer-based models. Synthesis tools developed in this phase addressed the problem from the water sink and source perspective (Figure 3). Instead of focusing on the impurity load removal, the flow rate is the main constraint in these works. One typical characteristic for this model is that the inlet and outlet flow rates of the water-using processes may not be uniform, which is totally different from that of the fixed load problems. This model is generally known as the fixed flow rate problem, with the following problem statement:28 • Given a number of water-consuming units, designated as SINK, or SK ) {j ) 1, 2, 3, ..., NSK} that each require a feed with a given flow rate, Fj, and a concentration of a targeted impurity, Cj, that satisfies the following constraint: C min e Cj e C max j j where Cmin and Cmax are the lowest and highest concentraj j tion limits of the targeted impurity. • Given a number of water-generating units/streams designated as SOURCES, or SR ) {i ) 1, 2, 3, ..., NSR}, each can be reused/recycled to process sinks. Each source has a given flow rate, Fi, and an impurity concentration of Ci. • External fresh water source(s) is also available to be purchased to satisfy the requirement of sinks. However, the objective for both kinds of problems remains the same, i.e. to minimize the flow rate of the external water source(s), FFW. As will be shown in the later sections, that both models yield exactly same flow rate targets, so long as the limiting water data for both models are converted


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Figure 2. (a) Mass transfer process where water is used as the mass separating agent to remove impurity load from process rich stream. (b) Conversion between a fixed load problem into a fixed flow rate problem. (c) Limiting water profile defined by maximizing the water inlet and outlet concentrations of the process. Table 1. Limiting Water Data for Example 1 (Fixed Load Problem) process, Pp

∆mp (kg/h)

Cin (ppm)

Cout (ppm)

Fp (ton/h)

1 2 3 4

2 5 30 4

0 50 50 400

100 100 800 800

20 100 40 10

Table 2. Transformation of Limiting Water Data of Example 1 into Fixed Flow Rate Problem

Figure 3. Sink/source representation of a water network for the fixed flow rate problem.

correctly. In principle, the water inlet and outlet of a waterusing process of the fixed load problem are taken as water sink and source in the fixed flow rate problem, respectively (see Figure 2b), assuming there is no interaction between the sink and source. For a water-using process in the fixed load problem, its maximum inlet concentration (Cin) corresponds to the highest concentration limit of the water sink (Cmax ) in the fixed flow rate problem; while its outlet j concentration (Cout) corresponds to the source concentration (Ci). As shown in the driving force plot in Figure 2c, in order to achieve maximum water recovery among water-using processes, inlet concentration of a process should be set at the maximum value (Cin). This allows lower quality outlet

SKj

Fj (ton/h)

Cj (ppm)

SRi

Fi (ton/h)

Ci (ppm)

SK1 SK2 SK3 SK4

20 100 40 10

0 50 50 400

SR1 SR2 SR3 SR4

20 100 40 10

100 100 800 800

stream from other water-using processes to be reused/ recycled. In other words, Cin will always take the value of (please also see the discussion on the optimality Cmax j condition in the last review paper26). Hence, if the flow rate of the process is to be minimized, the water supply line will always take the steepest slope, with the outlet concentration being limited by Cout. In this case, the water supply line is known as the limiting water profile, i.e. minimum water supply flow rate for a given set of Cin and Cout. However, please note that the above-described situation is only applicable for single impurity problems. To convert the fixed load problem into the fixed flow rate problem, the minimum water supply flow rate of the waterusing processes is extracted along with its Cin and Cout for each water sink and source, respectively. Data transformation between the two problems may be shown using examples 1 and 2. Table 1 shows the limiting water data for example 1. This is the classical fixed load problem with four water-using processes, each with an equal inlet and outlet flow rates.20 Column 2 of the table shows the impurity load (∆mp) to be removed from each water-using process p. The maximum

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Table 3. Limiting Water Data for Example 2 (Fixed Flow Rate Problem) SKj

SRi

j

unit

Fj (ton/h)

Cj (ppm)

i

unit

Fi (ton/h)

Ci (ppm)

1 2 3 4 5

reactor cyclone filtration steam system cooling system

80 50 10 10 15

100 200 0 0 10

1 2 3 4 5

reactor cyclone filtration steam system cooling system

20 50 40 10 5

1000 700 100 10 100

Table 4. Transformation of Limiting Water Data of Example 2 into Fixed Load Problem process, Pp 1a 1b 2 3a 3b 4 5a 5b

∆mp (kg/h) 18 25 1 0.1 0.45

Cin (ppm)

Cout (ppm)

Fp (ton/h)

100 100 200 0

1000

20 -60 50 10 30 10 5 -10

0 10 10

700 100 100 10 100

inlet (Cin) and outlet concentrations (Cout) for each process are shown in columns 3 and 4, respectively. The final column of the table lists the minimum water flow rate for each process p (Fp) dictated by the limiting water profile and is calculated using equation 1. To transform this problem into an equivalent fixed flow rate problem, inlet and outlet streams of each water-using process are regarded as separate entities, i.e. with the inlet flow rate taken as the water sink and the outlet as the water source, given as in Table 2. As shown, the sink and source flow rates (columns 2 and 5) are essentially equal to the minimum water flow rate dictated by the limiting water profile of the fixed load problem in Table 1 (column 5). Similarly, transformation steps are necessary to convert the limiting data for a fixed flow rate problem into a fixed load problem, with necessary adjustment to cater for water losses and gains.21 This is shown using example 2, with data given in Table 3.21 As shown, only cyclone and steam system are having uniform inlet and outlet flow rates, which may be treated as mass transfer processes (though strictly speaking, a steam system may be argued for not being a mass transfer process). On the other hand, reactor, filtration, and cooling systems that encounter water losses and gains are each segregated into two individual processes, i.e. one with a constant flow rate (take the lower value between the water sink and source flow rates) and the other with water loss (given as a negative flow rate value) or gain. For instance, a reactor system (P1) is represented by two subprocesses, i.e. P1a of constant inlet and outlet flow rates (20 ton/h) and P1b that represents water losses of 60 ton/h. Similar conversions were also carried out for filtration (P3) and cooling systems (P5), as shown in Table 4. Note that impurity load is also calculated for the constant flow rate subprocesses using equation 1. This variable is essential during flow rate targeting stage (to be discussed in a later section). From the above illustrations, it is clear that limiting water data for both fixed load and fixed flow rate problems are interchangeable. Hence, one may use any of the water targeting tools to locate the minimum water flow rates, so long as the water limiting data is converted correctly. However, an additional point to be noted here is that, when numerous water sinks and sources exist for a complex fixed flow rate problem (e.g., a highly integrated process), analyzing the case with a fixed load model may be cumbersome, as effort is needed to pair the water sinks and sources into water-using processes, with

water losses and gains taken into consideration simultaneously. In this case, the fixed flow rate problem is more convenient to use. This will be discussed in the next section when targeting techniques for the both problems are reviewed. In the following section, each flow rate targeting technique is reviewed according to their respective aim of reuse, recycling, regeneration, and waste treatment. Targeting Techniques for Water Reuse/Recycle Various graphical and numerical targeting techniques were proposed since the initialization of the water pinch analysis technique. In this section, these techniques will be reviewed according to the model to which they belong, i.e. fixed load and fixed flow rate problems. (A) Targeting Techniques for Fixed Load Problems. (a) Limiting Composite Curve. (i) Targeting for Networks without Water Losses and Gains.20 The limiting composite curVe presented in the seminal work of Wang and Smith20 is perhaps the most well-known targeting technique for water pinch analysis. On the basis of the mass transfer model, water is used as a mass separating agent in removing impurity loads from water-using processes, as explained in an earlier section (Figure 2). To construct the limiting composite curve, limiting water profiles of individual processes are plotted on an impurity concentration vs load diagram. As shown in Figure 4a, the limiting water profiles are plotted according to their limiting inlet and outlet concentrations which define the concentration intervals. The impurity load is then added within each concentration interval to form the limiting composite curve (Figure 4b). The limiting composite curve may be viewed as the representation of the overall water network system. The minimum flow rate for a pure fresh water feed to the entire water system may then be targeted by drawing a water supply line from the origin and rotated counter-clockwise until it touches the limiting composite curve, where a pinch is formed. The inverse slope of the water supply line defines the minimum flow rate of the fresh water feed. For example 1, this corresponds to 90 kg/h of fresh water. Since this network does not encounter water losses, the wastewater flow rate is equal to the targeted minimum fresh water flow rate, i.e. 90 kg/h.20 The pinch concentration at 100 ppm can be viewed as the bottleneck of the overall network where maximum water recovery may be achieved. Additional information that could be obtained from the limiting composite curves is that the end point of the water supply line in Figure 4b actually corresponds to the final impurity concentration of the terminal wastewater from the water network. For the case of example 1, the outlet concentration is determined to be 455.5 ppm. (ii) Targeting for Networks with Water Losses and Gains.21,27 When a water network consists of water-using processes that experience water losses or gains, the water supply line will have to be adjusted to reflect this. However, note that the construction of the limiting composite curve for this case is identical to cases without flow rate losses (e.g., example 1).


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Figure 4. Construction of a limiting composite curve from the limiting water profile of individual processes (example 1). Table 5. Limiting Water Data for Example 3 (Fixed Load Problem with Water Loss) process, Pp

∆mp (kg/h)

Cin (ppm)

Cout (ppm)

Fp (ton/h)

1 2 3

2 5 30

0 50 50

100 100 800

20 100 40

Targeting for systems with water loss/gain will be illustrated using example 3 (adapted from the work of Wang and Smith21), which is a modified case from example 1. As shown by the limiting water data in Table 5, example 3 consists of the first three water-using processes of example 1. Hence, the limiting composite curve (Figure 5a) looks similar to that in example 1. The minimum water flow rates before considering water losses/ gains is given by the water supply line as 90 ton/h (dashed line in Figure 5a), with a pinch concentration identified at 100 ppm. Knowing the pinch concentration is essential in considering water losses/gains, as different adjustment is needed for the water supply line for different cases when water losses/gains occurs in a region lower or higher than the pinch concentration. We first consider 40 ton/h water losses at 80 ppm, i.e. in the region lower than the pinch concentration (termed as the lower concentration region). Figure 5a shows that a steeper water supply line is drawn above the concentration of 80 ppm. Hence, the slope below 80 ppm defines the fresh water flow rate (termed as the fresh water segment), while the slope above it defines the wastewater flow rate (termed as the wastewater segment). However, the water supply line is observed to intercept with the limiting composite curves in Figure 5a. This means that a higher fresh water flow rate is needed to supplement the losses of the water network. Hence, the slope of both segments is decreased simultaneously (increased flow rate), with the wastewater segment connected to that of the fresh water at 80 ppm, until the pinch concentration is re-established at 100 ppm (Figure 5b). The revised fresh water and wastewater flow rates are determined as 98 and 58 ton/h, respectively. On the other hand, less fresh water will be needed when water gain is introduced in the lower concentration region. For instance, when 60 ton/h of water gain is introduced at 80 ppm for example 1, an increased wastewater flow rate of 150 ton/h is emitted from the network, represented by the wastewater segment of the water supply line (dashed line in Figure 5c). However, as shown in Figure 5c, the water supply line is no longer touching the limiting composite curve. This means that

the earlier targeted fresh water flow rate of 90 ton/h is in excess and is to be reduced. This may be done by reducing the slope of both the segments of the water supply line simultaneously, with the wastewater segment connected to the fresh water segment at 80 ppm, until the pinch concentration is reestablished at 100 ppm (solid line in Figure 5c). The minimum fresh water and wastewater flow rates for this case are determined from the slope of these segments as 78 and 138 ton/h, respectively. For regions higher than the pinch concentration (higher concentration regions), analysis of water losses and gains is relatively easier. Water gains as well as small water losses in this region will only increase/decrease the wastewater flow rate; they do not effect the fresh water flow rate of the network. However, for larger water loss in the higher concentration region, the water supply line will have to be adjusted by increasing the fresh water flow rate, similar to the case of water losses in the lower concentration region (Figure 5a). An example is shown in the Supporting Information for illustration (Figure S1-S3). (iii) Targeting for Fixed Flow Rate Problems.21 To target the minimum water flow rates for a fixed flow rate problem, the above-described technique in handling water losses and gains is utilized. Example 221 is used for illustration. Figure 6a shows the limiting composite curve that is constructed for processes 2 and 4, as well as subprocesses 1a, 3a, and 5a (see limiting water data in Table 4). A water supply line is drawn to locate the minimum flow rate before considering water losses and gains. As shown in Figure 6a, this corresponds to 55 ton/h of fresh water and wastewater, respectively. When water losses and gains (subprocesses 1b, 3b, and 5b) are included, the water supply line is adjusted using the earlier described technique, as shown in Figure 6b. The fresh water and wastewater flow rates are determined as 90.64 and 50.64 ton/h, respectively. At this end, it is worth noting that a targeting tool of the fixed load problem is equally accurate in determining the flow rate targets for a fixed flow rate problem. However, when there are more water sinks and sources in the problem, converting all of them into sink/source pairs as mass transfer water-using processes will be a complicated and cumbersome task. Example 4 serves as a good case to illustrate this situation. Figure 7 shows the process flow diagram of example 4, a Kraft pulping process18 where a large amount of fresh water is consumed, which in turn generates a large amount of waste-

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Figure 6. Limiting composite curve for example 2: (a) without water losses and gains; (b) with water losses and gains.

Figure 5. Limiting composite curve for example 3: (a) water supply line that intercepts with the limiting composite curve due to water loss in the lower concentration region; (b) increased fresh water flow rate to supplement for water loss; (c) reduced fresh water flow rate to adjust for water gain in the lower concentration region.

water. Impurity in concern for water recovery in this case is methanol. By following appropriate data extraction strategies (e.g., source segregation, etc.),18,29 the case may be treated as a fixed flow rate problem, with the limiting water data given in Table 6 (see also its sink/source representation in Figure S4 in the Supporting Information).29 As shown, there are three water sinks and nine water sources in the process. If one were to treat this case as a fixed load problem, these water sinks and sources are to be paired as mass transfer processes (with water losses and gains), as has been demonstrated in example 2 earlier. However, doing a transformation for this case will not be as straightforward as in example 2, as not many mass transfer processes are found for this example. Following the transformation step of example 2, the direct contact condenser may be treated as a mass transfer process with flow rate gain (inlet and


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Figure 7. Example 4: a Kraft pulping process (basis 1 h; T refers to tons). Table 6. Limiting Water Data for Example 4 (Fixed Flow Rate Problem) SKj j

unit

1 pulp washing 2 chemical recovery 3 condenser

SRi Fj (ton/h) Cj (ppm) i unit Fi (ton/h) Ci (ppm) 467 165 8.2

20 20 10

1 2 3 4 5 6 7 8 9

W3 W5 W7 W8 W9 W10 W11 W13 W14

12.98 9.7 10.78 116.5 48 52 52.2 300 140

419 16248 9900 20 233 311 20 30 15

outlet flows of 8.2 and 10.78 T, respectively). Besides, the countercurrent multistage washing, concentration unit, and paper finishing may be treated as a single operation with water loss. However, due to different concentration of the two outlet streams W13 and W14, two subprocesses of constant flow rates, as well as a water loss subprocess are needed. In addition, there still remain six water sources (with different impurity concentration) that need to be treated as water gains if the approach of the fixed load problem is to be adopted. Although one may argue that the conversion steps may be done effectively using computer software, but the transformation of data for plotting the limiting composite curve is indeed an added complexity. This is also the main reason why many other new targeting tools were developed for the fixed flow rate problems. These tools will be discussed in next section of the review. (iv) Targeting for Multiple Fresh Water Sources.21 There are cases when fresh water sources of different quality are available for a water network. The main assumption of this work

Figure 8. Targeting for multiple fresh water sources (example 3).

is that, the cost of the lower quality impure fresh water source is much lower or virtually free as compared to the pure fresh water source. Flow rate targeting for both fresh water sources is next presented using example 3, with the assumption that an impure fresh water source is available at 80 ppm, apart from the pure water source (0 ppm). The limiting composite curve for example 3 is shown in Figure 8. The flow rate for the impure fresh water source is first determined by drawing a water supply segment that starts from the intercept point between the 80 ppm

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Figure 9. (a) Water-source and water-sink33,34 composites. (b) Mixing of water sources at 100 and 700 ppm.

locus and the limiting composite curve. In order to minimize its flow rate, the water supply segment is set to have the steepest slope until it touches the limiting composite curve. Next, a segment for the pure fresh water source is added to connect the origin with the impure water supply segment and forms the complete water supply line. The inverse slope of the individual segments determines the flow rate of the pure and impure fresh water sources to be 72.5 and 160 ton/h, respectively. Note that this targeting approach will only locate the minimum flow rates for both fresh water sources. It does not necessarily lead to optimum solution when water costs are taken into consideration, as different water costs may lead to different optimum ratio between the pure and impure fresh water sources. Finally, note also that the use of limiting composite curve for flow rate targeting for multiple sources in the fixed flow rate problem is very cumbersome. Not only will the water supply line have to be modified to include water gains/losses of the water-using processes, flow rate targeting has to be carried out for the multiple water sources simultaneously. Hence, this involves an iterative procedure in bending and replotting the water supply line. (b) Mass Problem Table.30 The mass problem table (MPT) is an algebraic targeting tool to locate the minimum fresh water flow rate for a fixed load problem.30 It is conceptually similar to the concentration interval table of the mass integration problem.17,18 The use of the MPT is shown next using example 1. As shown in Table 7, the concentration levels (Ck, k ) 1,2,..., n) are arranged in an ascending order in column 1. Next, each water-using process is located in their respective concentration intervals (columns 2 and 3). Water flow rates in each concentration level k (Fk) are next summed in column 4. The interval impurity load (∆mk) is calculated from the product of interval flow rate and concentration difference across the interval, given in column 5. Next, the interval impurity load is cascaded down the concentration interval to yield the cumulative load at each concentration level k (cum ∆mk) in column 6. The interval fresh water flow rate (FFW,k, column 7) is calculated by dividing cum

∆mk by the concentration difference of the fresh water (CFW) and that at level k, i.e., FFW,k )

cum ∆mk Ck - CFW

(2)

The minimum fresh water flow rate (FFW) for a problem is identified by the largest FFW,k value. For example 1, this corresponds to 90 ton/h of fresh water, found at the pinch concentration of 100 ppm in the MPT (Table 7). Since this is a fixed load problem, an equal wastewater flow rate of 90 ton/h is emitted from the water network. Later works31,32 showed that the approach may be readily extended into the fixed flow rate problem, given the necessary transformation of the limiting water data (such as that shown in example 2). (B) Targeting Techniques for Fixed Flow Rate Problems. As mentioned in the earlier section, the insight-based techniques developed in the phase 2 period focus mainly on the fixed flow rate problems. The development of this phase was actually initiated back in 1996, with the work reported by a group of consultants at Linnhoff March.33,34 However, the fixed flow rate problems did not attract much attention from the research community until a much later stage (after 2000). It is also worth noting that, unlike the case in fixed load problems, a vast variety of targeting techniques were developed for fixed flow rate problems, yet by different research groups. These techniques are reviewed in the following subsections. (a) Water-Source and Water-Sink Composites33,34and Evolutionary Tables.35 The first version of the targeting technique for the fixed flow rate problems is the water-source and water-sink composites, plotted on a concentration versus flow rate diagram.33,34 Flow rate targeting using this tool is shown using example 2 (data in Table 3). As shown in Figure 9a, water sources and sinks of different impurity levels in Table 3 are grouped together to form the water-source and watersink composites, respectively. The two composites are arranged in a way so that the sinks-composite lies to the right of the sources-composites, and both composites touch at the pinch (200 ppm). Unlike the limiting composite curve in the fixed load

Ind. Eng. Chem. Res., Vol. 48, No. 11, 2009 Table 7. Mass Problem Table for Example 1

problem, this version of composite curves takes a step change at each concentration level. Note also that the concentration levels (y-axis) increase downward. The overlapped area between the two composites represents water recovery for the problem. For the case in Figure 9a, water sources at 10 (SR4) and 100 ppm (SR3 and SR5) may be recovered to water sinks at 100 (SK1) and 200 ppm (SK2). The fresh water (FFW ) 110 ton/h) and wastewater (FWW ) 70 ton/ h) flow rate targets are obtained from the overhang of the watersource and water-sink composites, respectively. However, these water flow rates are not the true minimum targets, as mixing of water sources of different concentration levels will lead to reduced water flow rates. One example is given in Figure 9b, where water sources at 100 and 700 ppm are mixed to produce a water source at 200 ppm. This removes the water recovery bottleneck at the original pinch concentration of 200 ppm. Hence, the water-source composite is moved further to the left until it touches the water-sink composite at a new pinch concentration of 100 ppm (Figure 9b). This results in the reduction of 5 ton/h for both water flow rates as compared to Figure 9a. Instead of relying on graphical approach, one may also utilize the equivalent algebraic technique called the eVolutionary table35 (not shown) to ease the flow rate targeting steps. Note that at this stage, it is worth mentioning that water sources of different quality may be mixed to form the new water source. For instance, instead of mixing water sources of 100 and 700 ppm (Figure 9b), one may also consider mixing water sources at 10 and 700 ppm, or even a mixture of 10, 100, and 700 ppm. A better source mixing strategy has been proposed to facilitate the search of better water targets.36 However, as pointed out by later work,37 the detailed water source mixing actually belongs to the second stage of water pinch analysis, i.e. network design. Unless the correct source mixing patents are identified, the resulted flow rates are hardly guaranteed to be the minimum targets. For the case of Figure 9, numerous trial-and-error exercises have to be performed before the true minimum flow rate targets are identified (90.64 ton/h of fresh water and 50.64 ton/h of wastewater, as reported in the earlier section on the limiting composite curve). In general, as long as there exist gaps between the two composite curves, the solution is not optimum and may subject for further improvement. Another pitfall of the above two targeting tools is the failure to identify the limiting pinch in a multiple pinch problem, which eventually leads to suboptimum solution in regeneration unit placement.37 (b) Water Surplus Diagram.37 This is the first promising tool in locating the true minimum water flow rates in the fixed flow rate problem. However, to plot the water surplus diagram, another diagram of water-sink and -source composites is needed. This will be demonstrated using example 5, with the limiting water data given in Table 8. If we follow the problem characteristic mentioned in the earlier section, this classical

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Table 8. Limiting Water Data for Example 5 SKj

Fj (ton/h)

Cj (ppm)

SRi

Fi (ton/h)

Ci (ppm)

SK1 SK2 SK3 SK4

50 100 80 70

20 50 100 200

SR1 SR2 SR3 SR4

50 100 70 60

50 100 150 250

literature example comprises a combination of mass transfer and nonmass transfer processes. Water sink SK1 and source SR1 may be treated as the inlet and outlet flow rates of the mass transfer operation of process 1, respectively. The same goes for SK2 and SR2 for process 2. On the other hand, one may treat the remaining limiting water data as individual water sinks and sources. The water-sink and -source composites for example 5 are shown in Figure 10a, plotted on a concentration versus flow rate diagram similar to the water-source and water-sink composites in Figure 9.33,34 However, this version of composites is plotted in such a way that sink/source of the lowest concentration level are placed on the most left. Note that for the source composite, an assumed fresh water flow rate is also included in the plot. In Figure 10a, the fresh water flow rate is assumed as 70 ton/h. Note also that in Figure 10a, impurity concentration is used rather than water purity as in the original work,37 for better illustration. It would be beneficial to understand the characteristic for each composite plot. For the water sink composite, the area below the concentration versus flow rate plot represents the total pure water (water content excluding impurity) required by all water sinks. On the other hand, the area below the source composite indicates pure water possessed by all water sources. When the source composite lies above the sink composite, water sinks in this region are supplied with cleaner water sources. The area between the two composites corresponds to the excess impurity capacity of the sinks in receiving additional impurity load. On the other hand, when the sink composite lies above the source composite, the water sink receive lower quality water from the source. Hence the area between the two composites represents the additional impurity load that can be accepted by the sinks. To construct the water surplus diagram, the area between the water-sink and -source composites is calculated. The excess impurity capacity and additional impurity load is next summed to form the water surplus diagram, Figure 10b. For instance, an excess capacity of 2.0 kg/h impurity load is found at 0 ppm (given as positive value); while 1.5 and 0.5 kg/h of additional impurity load (negative value) are found at 50 and 100 ppm, respectively. The cumulative for these values lead to the pinch concentration that forms at 150 ppm at the water surplus diagram (Figure 10b). When the whole water surplus diagram lies on the positive side of the diagram (with the formation of pinch concentration(s)), the earlier assumed fresh water flow rate is the true minimum fresh water flow rate for the water network. One may then calculate the wastewater flow rate by summing/ deducting any water gain/loss among all the water sinks and sources. For the case of example 5, this corresponds to the wastewater flow rate of 50 ton/h. Although the method is promising in locating the minimum water flow rate targets, even for multiple pinch problems,37 its main limitation is its iterative calculation steps. In the earlier step when the water-sink and -source composites are constructed, an assumed fresh water flow rate is needed. This value is normally unknown and can only be determined via trial-anderror effort, with the construction of the water surplus diagram. Hence, in order to adjust the assumed fresh water flow rate, both the water-sink and -source composites as well as the water

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Figure 10. (a) Water-sink and -source composites. (b) Water surplus diagram.

research groups in the US28 and India.39 The new targeting tool is not iterative, and it also includes the dual analysis of water flow rate and impurity load simultaneously. The targeting step will now be illustrated. (i) Targeting for a Single and Pure Fresh Water Source.28,39 In the material recovery pinch diagram, the sink and source composite curves are plotted on a cumulative impurity load versus cumulative water flow rate diagram, such that the slopes of the individual segments that correspond to the sink/source impurity concentrations are arranged in an ascending order (Figure 12a). The impurity load of each source (mi) and the maximum permissible load of each sink (mj) are determined using equation 2:

Figure 11. Procedure to construct the water surplus diagram.

surplus diagram are to be plotted. This iterative nature of the algorithm makes the targeting procedure cumbersome and unattractive. The detailed targeting procedure may be summarized in Figure 11.38 In spite of its iterative nature, the water surplus diagram did actually contribute to several in-depth analyses of the fixed flow rate problem. First, it is the first work that reported that the pinch concentration of the fixed flow rate problem will always fall at one of the source concentrations. Second, the need for two graphical plots indicates that two constraints need to be taken care of for the problem, i.e. water flow rate and impurity load balances. The former is analyzed by the water-sink and -source composites; while the latter, by the water surplus diagram. This important finding inspires many new targeting tools to be developed at a later stage. This will be discussed as follows. (c) Material Recovery Pinch Diagram.28,39 The first reported graphical tool in response to overcome the iterative steps of the water surplus diagram is the material recoVery pinch diagram.28,39 It is interesting to note that this new form of composite curve was independently developed by two different

mi ) FiCi

(3a)

mj ) FjCmax j

(3b)

Next, the source composite curve is moved horizontally until it touches the sink composite curve at the pinch, with the source composite curve being below and to the right of the sink composite curve. Minimum flow rate targets are obtained from the overhang of the sink and source composite curves, respectively. As shown in Figure 12a, flow rate targeting for example 5 with single pure fresh water yields the same water flow rates as with the water surplus diagram (Figure 10), i.e. 70 ton/h of fresh water and 50 ton/h of wastewater. It is also worth mentioning a unique characteristic of the fixed flow rate problem, where the pinch will always coincide with the concentration level of the water source. This is a characteristic that was first reported in the water surplus diagram37 and is more apparently shown using the material recovery pinch diagram. For the case of example 5, the pinch corresponds to the concentration level of source SR3, i.e. 150 ppm (Figure 12a). (ii) Targeting for Single28 and Multiple Impure Fresh Water Sources.40 When the water network is serviced by a single impure fresh water source, with its impurity concentration being the lowest among all water sources, the targeting procedure shall follow the previous targeting step with pure fresh


5135

Figure 12. Material recovery pinch diagram for example 5: (a) single pure fresh water feed; (b) impure fresh water feed of 10 ppm; (c) targeting for pure fresh in multiple fresh water feed case; (d) targeting for impure fresh in multiple fresh water feed case.

water feed.28 However, note that a new locus that corresponds to the impurity concentration of the impure fresh feed is added in the material recovery pinch diagram, where the source composite curve is slide until it touches the sink composite curve in order to locate the water flow rates. A typical example for this case is to supply the water network in example 5 with an impure fresh water feed of 10 ppm. As shown in Figure 12b, targeting with the material recovery pinch diagram yields a fresh water and wastewater flow rates of 75 and 55 ton/h respectively, i.e. relatively higher as compared to the case when pure fresh water feed is used (Figure 12a).40 Note that, in this case, pure fresh water is completely eliminated. When there are more than one fresh water sources, or an impure fresh water source that is not the lowest among all

impurity concentration levels of the sources, a revised algorithm is needed.40 The minimum flow rate of the pure fresh water source will first be located prior to the impure fresh water source. Consider the case when example 5 is served by an impure fresh water source of 80 ppm, apart from the pure fresh water source. Since the impure fresh source has an impurity concentration higher than the water source SR1 (50 ppm), the locus of this fresh water source will be connected to the end of the SR1 segment without having to connect other sources of higher concentration levels. As shown in Figure 12c, the SK1 segment together with the impure fresh water locus is slide horizontally until they touch the sink composite curve at the pinch. The overhang of the sink composite curve gives the minimum flow rate of the pure (primary) fresh water source, i.e. FFW,1 ) 56.25

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Table 9. WCT for Water Flow Rate Targeting k

Ck

∑jFj

∑iFi

∑iFi - ∑jFj

k

Ck

(∑jFj)1

(∑iFi)1

(∑iFi - ∑jFj)1

k+1

Ck+1

(∑jFj)k+1

(∑iFi)k+1

(∑iFi - ∑jFj)k+1

l l l n-2 n-1 n

l l l Cn-2

l l l (∑jFj)n-2

l l l (∑iFi)n-2

l l l (∑iFi - ∑jFj)n-2

Cn-1

(∑jFj)n-1

(∑iFi)n-1

(∑iFi - ∑jFj)n-1

Cn

ton/h. Next, the remaining of the water sources are connected and slide along the locus of the impure fresh water source until another pinch point is formed, and the horizontal distance of the impure fresh locus gives the minimum flow rate of the impure fresh water source. For this case, the minimum flow rate of the impure (secondary) fresh water source (FFW,2) is located as 43.75 ton/h, as shown in Figure 12d. Note that the impure fresh locus eventually forms part of the source composite curve once its flow rate is located. Note also that in this kind of multiple pinch cases, the pinch of the lowest concentration is known as the limiting pinch,37,38 in which it controls the overall fresh water flow rate. The main assumption for the case of multiple fresh water sources shall follow that in the fixed load problem (discussed earlier in the limiting composite curve section), i.e. the cost of the secondary fresh water is virtually free as compared to the primary pure fresh water source. Note that, however, for cases where the assumption does not hold, (e.g. partial treatment is needed to purify the fresh source which leads to purification cost), optimization needs to be carry out in order to identify the optimum flow rate for both of the fresh water sources. Finally, it is worth mentioning that the main limitation of this targeting tool is the visual resolution of its graphical representation. It is particularly cumbersome to use when the slopes of the composite curve segments are having similar values (particularly those segments that are close to the pinch), such as that shown in Figure 12d. In these cases, it is difficult to pinpoint exactly where the pinch point(s) lies, unless the pinch diagram is magnified, or the composite curves are generated using computer software. (d) Water Cascade Analysis.38,41 Inspired by the problem table algorithm in heat integration,42 the water cascade analysis (WCA)38,41 technique was developed to overcome the iterative procedure in the water surplus diagram.37 (i) Targeting for a Single Pure Fresh Water Source.38,41 The procedure of carrying out the WCA for flow rate targeting may be summarized in the water cascade table (WCT) in Table 9. As shown in the first two columns of Table 9, the concentration levels (Ck) are arranged in an ascending order (k ) 1, 2, ..., n), and the flow rates of water sink (Fj) and source (Fi) are summed at their respective concentration level k in columns 3 and 4. Column 5 represents the net flow rate, (∑iFi - ∑jFj) between water sources and sinks at each concentration level k; with positive indicating surplus and negative indicating deficit. Next, the net water flow rate surplus/deficit is cascaded down the concentration levels to yield the cumulative surplus/deficit flow rate (FC,k) in column 6 with an assumed zero fresh water flow rate (FFW ) 0). This assumed flow rate will be revised once the fresh water flow rate is determined. Next, impurity load in column 7

FC,k

∆mk

cum ∆mk

FFW,k

cum ∆mk+1

FFW,k+1

l l l

l l l

cum ∆mn-1

FFW,n-1

cum ∆mn

FFW,n

FFW FC,k

∆mk

FC,k+1

∆mk+1 l l l

l l l

FC,n-2

∆mn-2

FC,n-1 ) FWW

∆mn-1

(∆mk) is obtained via the product of cumulative flow rate (FC,k) and the concentration difference across two subsequent concentration levels (Ck+1 - Ck). Cascading the impurity load down the concentration levels in column 8 yields the cumulative load (cum ∆mk), which is numerically equivalent to the water surplus diagram37 (i.e., by plotting values in columns 2 and 8 in Table 9). A feasible water network is characterized by the presence of only positive values of cum ∆m in column 8. A negative cum ∆mk means the water surplus diagram is located on the negative side of the x-axis, which is infeasible. In such cases, an interval fresh water flow rate (FFW, k, column 9) is determined using the same eq 2 that was previously used in the mass problem table.30 The absolute value of the largest negative value of FFW,k will then replace the earlier assumed zero fresh water flow rate in the flow rate targeting (column 6) to obtain a feasible WCT. This new fresh water flow rate represents the minimum fresh water flow rate (FFW) of the network, while the final row in column 6 represents the wastewater flow rate (FWW) generated from the network. The network pinch concentration is the impurity concentration with zero cum. ∆mk, while the water source that exists at the pinch is called the pinch-causing source. Once the flow rate and impurity load cascading are carried out using the minimum fresh water flow rate, the column to determine the interval fresh water flow rate (column 9 in Table 9) is omitted. Following the outlined procedure, the WCT for example 5 is shown in Table 10. As shown, the minimum water flow rates are exactly the same as the previous reported values, i.e. 70 ton/h of fresh water and 50 ton/h of wastewater, with a pinch located at 150 ppm. An additional target that was reported in this technique is the water allocation targets, i.e. the flow rate allocation of the pinch-causing source to the higher and lower concentration regions.38,41 For the case of example 5, 10 ton/h of the pinch causing source (SR3) is allocated to the higher concentration region, while 60 ton/h to the lower concentration region. These flow rate targets are found in the FC,k column just above and below the pinch concentration. Note that the water allocation targets may also be found using the material recover pinch diagram,28,39 by inspecting the pinch-causing source segment that lies in both the higher and lower concentration regions. (ii) Targeting for Impure Fresh Water Source(s).43 Flow rate targeting for a water network that is served by impure fresh water source(s) is now shown using the WCA. For a fresh water source that has an impurity concentration that is lowest or equal to the most stringent water sink, the impure fresh water source will substitute the use of a pure source in the network. The targeting procedure is similar to the case of pure fresh source targeting in the previous subsection. This is shown using example 5 with an impure fresh water feed of 10 ppm. The


5137

Table 10. WCT for Example 5 (Pure Fresh) k

Ck (ppm)

1

0

2

20

∑jFj (ton/h)

∑iFi (ton/h)

∑iFi - ∑jFj (ton/h)

FC,k (ton/h)

∆mk (kg/h)

cum ∆mk (kg/h)

FFW ) 70 -50

50

3

50

100

50

-50

4

100

80

100

20

5

150

70

70

6

200

7

250

8

60

1.4

20

0.6

-30

-1.5

-10

-0.5

60

3.0

-10

-0.5

1.4

-70

70

70

60

FWW ) 50

2.0 0.5 0.0 (PINCH) 3.0 2.5

49987.5

1000000

49990.0

Table 11. WCA Targeting for an Impure Fresh Source of 10 ppm for Example 5 k

Ck (ppm)

1

10

2

20

∑jFj (ton/h)

∑iFi (ton/h)


FC,k (ton/h)

∆mk (kg/h)

cum ∆mk (kg/h)

FFW ) 75 -50

50

3

50

100

50

-50

4

100

80

100

20

5

150

70

70

6

200

7

250

8

60

0.8

25

0.8

-25

-1.3

-5

-0.3

65

3.3

-5

-0.3

0.8

-70

70

75

60

FWW ) 55

1.5 0.3 0.0 (PINCH) 3.3 3.0

54986.3

1000000

54989.3

Table 12. WCA Targeting for an Impure Fresh Source of 20 and 50 ppm for Example 5 ∑jFj (ton/h)

k

Ck (ppm)

1

20

50

2

50

100

3

100

4

150

5

200

6 7

250

80

∑iFi (ton/h)

∑iFi - ∑jFj (ton/h) -50

50 + FFW2 ) 50

20

70

70 -70

60

1000000

WCT in Table 11 shows the that fresh water and wastewater flow rates are targeted as 75 and 55 ton/h respectively, identical to the flow rate targets that were targeted using the material recovery pinch diagram in Figure 12b. On the other hand, when the water network is served by more than one fresh water source, a three-step approach is needed to locate the minimum flow rate for all fresh water sources, i.e.:43 i. Flow rate targeting for a lower quality source ii. Flow rate targeting for a higher quality source iii. Flow rate adjustment of a lower quality source Flow rate targeting/adjustment for each step is determined by eq 2 as before. Targeting for this case is shown using example 5 that is served with two impure fresh water sources of 20 (FW1) and 50 ppm (FW2), respectively. Due to space limitation, all WCTs are found in the Supporting Information (Tables S1-S3). The minimum water flow rate is first located for the lower

∆mk (kg/h)

60

cum ∆mk (kg/h)

FFW1 ) 50 0

0

0

0.00

20

1.00

90

4.50

20

1.00

0

100

70

FC,k (ton/h)

0.00 (PINCH) 0.00 (PINCH) 1.00 5.50

FWW ) 80

6.50 79980.00 79986.50

quality fresh water source of 50 ppm (FFW2 ) 130 ton/h, Table S1). The minimum flow rate for the higher quality source is determined in Table S2 (FFW1 ) 50 ton/h, 20 ppm). However, the use of this targeted FW1 flow rate leads to an excess flow rate of FW2, with the removal of the original pinch concentration of 100 ppm (when FW1 is used, Table S2). Hence, the excess flow rate of FW2 at each concentration level is determined by eq 2, (final column in Table S3). Deducting the smallest excess flow rates of FW2 (80 ton/h) from the earlier targeted FW2 flow rate (in step i) yields the actual flow rate needed for FW2 (130 - 80 ) 50 ton/h). The final WCT for the case is shown in Table 12, with two pinches formed at 50 and 100 ppm.43 (iii) Targeting for the Threshold Problem.44 Threshold problems may be regarded as special cases of the water network synthesis problem. While flow rate targeting using other methods

5138


Table 13. Limiting Water Data for Example 644 SKj

Fj (ton/h)

Cj (ppm)

SRi

Fi (ton/h)

Ci (ppm)

1 2 3

50 20 100

20 50 400

1 2 3

20 50 40

20 100 250

(e.g., material recovery pinch diagram28,39) remains the same,44 special treatment is needed to extend the WCA targeting techniques into this problem.44 Two cases of threshold problems are commonly encountered, i.e. zero fresh water intake and zero discharge. For the former, the above-described WCA technique is used, without having to determine the interval fresh water flow rates in each concentration level using eq 2 (since no fresh water is needed). For the zero discharge case, Example 644 is use for illustration, with limiting data given as in Table 13. Carrying out the WCA targeting procedure38,41 results in a negative flow rate of wastewater (Table S4 in the Supporting Information). Hence, a flow rate adjustment is needed for a positive wastewater flow rate. The absolute value of the negative wastewater flow rate is added to the targeted fresh water flow rate to obtain the true minimum flow rates for the threshold problem. As shown in Table 14, a zero discharge network is resulted, with a slightly higher fresh water flow rate. The pinch concentration before the flow rate adjustment is known as the threshold concentration. (e) Algebraic Targeting Approach.45,46 Apart from WCA,38,41 another flow rate targeting tool that is tabulated in nature is the algebraic targeting approach.45,46 However the underlying principles between these tools are totally different. While WCA is built based on the concept of material surplus, the algebraic targeting approach is constructed based on the material recovery pinch diagram.28,39 (i) Targeting for a Pure Fresh Water Source.45 The procedure for carrying out the algebraic targeting approach is illustrated using the generic load interVal diagram in Figure 13.45,46 In order to construct the load interval diagram, the concentrations of the water sinks and sources are first arranged in an increasing order. The maximum permissible load of sink (mj) and impurity load of each source (mi) are next determined using eq 2. The cumulative values of these loads are next arranged in ascending order in column 2 of Table 15, while the load difference in each interval (∆mk) is calculated in column 3. In columns 4 and 6, the sources and sinks are located in their respective load intervals as an arrow, with the tail corresponds to its starting load and head corresponds to the ending load. The interval flow rates of each source (Fi,k) and sink (Fj,k) are next calculated in columns 5 and 7 respectively, using a revised form of eq 2, i.e.: ∆mk Fi,k ) Ci Fj,k )

∆mk Cmax j

(4a)

(4b)

The minimum water flow rate is next determined by performing a flow rate cascade in a cascade diagram, similar to flow rate cascading in the WCA.38,41 Example 5 is revisited using this targeting method, with the load interval diagram shown in Figure 14, and its cascade diagram in Figure 15. As shown, zero fresh water is first assumed, which result in negative wastewater flow rate and, hence, an infeasible cascade in Figure 15a. The absolute value of the largest negative cumulative flow rate is then used as fresh water flow rate (FFW) in the feasible cascade in Figure

15b, which eventually yields a positive wastewater flow rate (FWW). As shown, the fresh water and wastewater flow rates are targeted as 70 and 50 ton/h, respectively, matching the targets obtained by other targeting tools, e.g. water surplus diagram (Figure 10), material recovery pinch diagram (Figure 12a), and WCA (Table 10). Pinch concentration is identified from the zero cumulative flow rate in the feasible cascade, i.e. between intervals 5 and 6 (see Figure 15b). From Figure 15, it is observed that water source SR3 lies within these intervals and, hence, its concentration of 150 ppm corresponds to the pinch concentration for the problem. (ii) Targeting for an Impure Fresh Water Source.46 The targeting procedure for impure fresh is similar to that in targeting pure fresh water source,45 with some necessary adjustments. The concentration of the water sources and sinks are to be deducted from the fresh water concentration before the impurity loads of the source (mi) and the sink (mj) are determined using eq 2. The remaining of the targeting procedure remains the same as that for the pure fresh water source.45 Example 5 is revisited with a fresh water source of 10 ppm. The targeting procedure yields the minimum fresh water and wastewater flow rates as 75 and 55 ton/h, respectively (see Figure S4 in the Supporting Information), which match the flow rate targets obtained by other targeting techniques (e.g., Figure 12b and Table 11). (f) Source Composite Curve.47,48 Among the various targeting approaches, this is the only tool that is a hybrid between algebraic and graphical steps. While the majority of the targeting steps are carried out in tabulated form, the final result may be displayed as a graphical plot called the source composite curVe.47,48 (i) Targeting for a Single Fresh Water Source.47,48 Table 15 shows the algebraic steps of the source composite curve approach. Unlike other targeting tool, the concentration levels (Ck) for the source composite curve are arranged in a descending order (k ) 1, 2, ..., n), located in column 1. The different between the total water sink and source flow rates (∑iFi - ∑jFj) are next calculated at each concentration level k in column 2. Next, the net water flow rate surplus/deficit is cascaded down the concentration levels to yield the cumulative flow rate (cum ∑k FC,k) in column 3. Next, impurity load in column 4 (∆mk) is obtained via the product of cumulative flow rate (cum ∑k FC,k) and the concentration difference across two subsequent concentration levels (Ck - Ck+1), i.e. ∆mk ) cum (ΣiFi - ΣjFj)k(Ck - Ck+1)

(5)

Cascading the impurity load down the concentration levels in column 5 yields the cumulative load (cum ∆mk). The interval wastewater flow rate (FWW,k) in column 6 is given by the ratio of the cumulative load difference (between the total and level k) to the concentration difference (between level k and the fresh water source concentration), i.e. FWW,k )

cum ∆mn - cum ∆mk Ck - CFW

(6)

The minimum wastewater flow rate of the network (FWW) is identified from the largest interval flow rate in column 6 of Table 15. The minimum fresh water (FFW) is then calculated from the gains/losses between the total sink and source flow rates (given by the final value in the cumulative flow rate in column 3). This is the main difference between the source composite curve with other targeting tools. While other targeting tools locate the minimum fresh water and waste-


5139

Figure 13. Generic load interval diagram. Table 14. WCA Targeting for Example 6 (Zero Discharge Network) k

Ck (ppm)

1

0

2

20

∑jFj (ton/h)

∑iFi (ton/h)


FC,k (ton/h)

∆mk (kg/h)

cum ∆mk (kg/h)

FFW ) 60.00

3

50

4

-20

20 50

250

6

400

-30

20

100

5

7

50

40

Ck

(∑iFi - ∑jFj)k

Ck+1 (∑iFi - ∑jFj)k+1 l l

l l

Cn-1 (∑iFi - ∑jFj)n-1 Cn

(∑iFi - ∑jFj)n

30.00

0.90

10.00

0.50

60.00

9.00

100.00

15.00

1.20 2.10 2.60

40 -100

100

11.60 FWW ) 0.00

1000000

∑iFi - ∑jFj

1.20

50

26.60 0.00 26.60 (THRESHOLD)

Table 15. Algebraic Steps for Water Source Diagram Ck

60.00

cum ∑kFC,k (∑iFi - ∑jFj)k

∆mk

cum ∆mk

FWW,k

∆mk

cum (∑iFi - ∑jFj)k+1 ∆mk+1 l l l l cum (∑iFi - ∑jFj)n-1 ∆mn-1

cum ∆Mk+1 FWW,k+1 l l l l cum ∆mn-1 FWW,n-1 cum ∆mn

FWW,n

water simultaneously (except the water surplus diagram37), the source composite curve locates the minimum wastewater flow rate prior to the fresh water flow rate. The source composite curve is next obtained by plotting the concentration level (column 1) versus the cumulative load (column 5). It is also worth mentioning some analogous and dissimilarities in terms of the targeting philosophy between the source composite curve and the previous described WCA technique.38,41 Since both targeting techniques are essentially algebraic-based procedure in nature, the determination of flow rate targets hence involve the use of flow rate and impurity load cascades. If one observes carefully, one will easily notice that the targeting steps for both techniques are very similar. In particular, the first 5 columns of Tables 15 (algebraic steps of the source composite curve) are essentially the same as the first 8 columns in Table 9 (WCA technique). However, the main dissimilarity between the two is the direction in performing the cascading steps. For the WCA (and also the algebraic targeting approach45,46), the cascading steps are carried out from the lowest to the highest concentration levels, which is totally in reverse for the source composite curve. Besides, the former requires the cascading steps to be carried out twice in order to locate the water flow rates as well as the pinch concentration(s), while the latter

only requires a single cascading step, which reduces the computation effort slightly. Example 5 is again used for illustrating the targeting procedure for the source composite curve. The algebraic step for this example is shown in Table 16a (columns 1-7 only), with the source composite curve in Figure 16. Apart from locating the minimum water flow rates from the algebraic step, one may also locate the minimum wastewater flow rate from the source composite curve. As shown in Figure 16, by drawing a wastewater line that starts at the bottom end of the source composite curve. This end point is then used as the pivot where the wastewater line is rotated until it touches the source composite curve at the pinch concentration. The minimum wastewater flow rate is given by the absolute value of the inverse slope of the wastewater line. Fresh water flow rate is then determined from the overall water loss/gain throughout the network. It is worth mentioning that the main advantage of the source composite curve over other fixed flow rate targeting techniques (e.g., water surplus diagram, material recovery pinch diagram, WCA, etc.) is that the average concentration of the wastewater stream emitting from the water network is indicated by the wastewater line. For the case of example 5, Figure 16 shows that the outlet concentration of the network effluent is determined as 200 ppm. This insight is also available in the graphical targeting tool for fixed flow rate problem, i.e. the limiting composite curve.20,21 In a later work, the authors also proposed an analytical procedure for the source composite curve based on mathematical proof.49 Since the procedure was derived from a mathematical proof, it takes a much simpler form as compared to the original source composite curve technique, but yet retains the same characteristics of the latter. In the targeting procedure, one first assumes each concentration

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Figure 14. Load interval diagram for example 5 (pure fresh water source; water flow rate given in tons per hour; impurity in kilograms per hour).

Figure 16. Source composite curve for example 5 (single pure water source).

Figure 15. Cascade diagram for example 5 (pure fresh water source; water flow rate given in tons per hour; impurity in kilograms per hour).

level k as the pinch concentration (i.e., Ck ) CPINCH); eq 7 is then applied to determine the lowest wastewater flow rate emits from each concentration level k (FWW,k): FWW,k )

∑F

i

Ci>Ck

CieCk

∑F

j

+

Cj>Ck

Ci - CFW k - CFW

∑ FC i

-

Ci - CFW k - CFW

∑ FC j

CjeCk

(7)

Since earlier work reported that the pinch concentration of the fixed flow rate problem will always be located among one of the source concentrations,37only source concentrations need to be evaluated using eq 7. Next, the lowest fresh water flow rate needed in each concentration level k is determined from the gains/losses between the total sink and source flow rates at each level k, similar to that in the source composite curve.47,48 Finally, the biggest fresh water and wastewater flow rates among all levels are identified as the minimum flow rate targets for the network. Applying the above-mentioned targeting procedure on example 5 yields the same minimum fresh water (70) and

wastewater flow rates (50 ton/h) as before, with the pinch concentration at 150 ppm (see Table S5 in the Supporting Information for detailed calculation). (ii) Targeting for Impure Fresh Water Source(s).50 The above-described procedure for targeting pure water source is readily incorporated for the targeting of single impure water source, as the concentration of the impure water source is included in eq 6. For a water network with multiple fresh water sources of different quality, a modified procedure is needed. The targeting procedure proposed by these authors possesses additional advantage over previous works,21,40,43 where cost of the various fresh water sources is included to achieve minimum total water cost. This is done by incorporating an index known as prioritized cost, given as a ratio of the cost of fth water source (COSTf) to the difference between the pinch (CPINCH, when the network is served by a pure fresh water source alone) and fresh water concentration (CFWf):50 PCf )

COSTf CPINCH - CFWf

(8)

An impure water source will be used for a water network only when its prioritized cost is lower than that of other purer source(s). This is shown using example 5. Example 5 is revisited with three fresh water sources, where their impurity concentrations and unit costs are given


5141

Table 16. Algebraic Steps for Water Source Diagram for Example 5: (a) with a single pure fresh water source; (b) with impure fresh water sources at 20 and 50 ppm (a) ∑iFi - ∑jFj (kg/h)

k

Ck (ppm)

1

250

60

2

200

-70

3

150

70

4

100

5

(b)

cum ∑kFC,k (kg/h)

∆mk (kg/h)

60

3.0

-10

-0.5

60

3.0

80

4.0

30

0.9

-20

-0.4

20 -50

50

6

20

-50

7

0

0

Table 17. Targeting for Example 5 using the Analytic Targeting Method Cj (ppm)

∑jFj (ton/h)

cum ∆mj,k (kg/h)

Ci (ppm)

∑iFi (ton/h)

cum ∆mi,k (kg/h)

20 50 100 200

50 100 80 70

1 6 14 28

50 100 150 250

50 100 70 60

2.5 12.5 23.0 38.0

as 20, 50, and 100 ppm and 1.3, 0.8, and 0.6 $/ton, respectively. From Figure 16, the pinch concentration is observed at 150 ppm. Hence, the prioritized cost for the three fresh water sources are calculated as 0.010, 0.008, and 0.012 $/ton. Hence, the 100 ppm fresh water source will not be considered due to its high prioritized cost. In order to determine the flow rate for both the water sources, the generated wastewater flow rate corresponding to each fresh water source (FWf) is to be determined, using equation 9:50 FWf )

cum ∆mf - cum ∆mk Ck - CFWf

(9)

where cum ∆mk and cum ∆mf are cumulative load at level k and level where fresh water source f is fed, respectively; while CFWf corresponds to the impurity concentration of the water source f. Columns 8 and 9 in Table 16 show the wastewater flow rate generated due to the feed of the 20 and 50 ppm fresh water sources, respectively. As shown, 30 and 80 ton/h of wastewater is generated with these fresh water sources. The authors50 further determined that the flow rate for the purest fresh water is determined as before, i.e. from the gains/losses between the total sink and source flow rates. Since 30 ton/h of wastewater (FW1) is generated by the 20 ppm fresh water source, the 20 ton/h of water losses between the total sink and source flow rates determine the flow rate of this fresh water source as 50 ton/h. For other fresh water sources, their flow rates are determined from the difference between the corresponding wastewater generated by the various fresh water sources (FWf). Hence, the flow rate for the 50 ppm fresh water source is also determined as 50 ton/h () 80 - 30 ton/h). (g) Analytical Method.51 [Author’s note: The name of the approach is arbitrarily assigned, as the authors did not provide the name for the approach]. This targeting method is mainly analytical-based. It is based on the underlying principle of the graphical technique of a material recovery pinch diagram.28,39 Unlike other targeting tools, the main objective of this analytical technique is first to locate the pinch concentration prior to the minimum water flow rates.

cum ∆mk (kg/h)

FWW,k (ton/h)

FW1,k (ton/h)

FW2,k (ton/h)

3.0

35

43.33

2.5

50

70.00

5.5

45

80.00

9.5

10

10.4

-20

10.0

0

30

The principle of the targeting tool is now explained. As described in an earlier section, the pinch concentration always occurs at the concentration of a water source (the pinch-causing source), where the network is divided into lower and higher concentration regions. The main aim of the targeting procedure is to locate the pinch-causing source, followed by the identification of the water sinks and sources that belong to each region. The minimum water flow rates can then be calculated from the water balance in each region. A water source can only be a pinch-causing source once it fulfils the following two criteria: 1. The concentration of the source is higher than all sink concentrations in the lower concentration region and lower than those in the higher concentration region. 2. The cumulative load of the source composite curve (including the pinch-causing source) until the pinch is always higher than that of the sink composite curve. The water sinks and sources are to be arranged in an ascending order of concentration before they may be analyzed using the both criteria. Note that only the first water source that fulfils both the criteria is the pinch-causing source. Note also that both of these criteria may be verified using the material recovery pinch diagram in Figure 12. The procedure is illustrated using example 5. As shown in Table 17, water sinks and sources are each arranged in an ascending order of concentration; while their cumulative impurity loads (cum ∆mk) are calculated in columns 3 and 6, respectively. The 50 ppm source is first analyzed. In order to be a pinch-causing source, this source has to be placed between the 50 and 100 ppm sinks, with its cumulative load being higher than that of the 50 ppm sink. However, this is not the case as the source cumulative load is lower than that of the 50 ppm sink. Next, the 100 and 150 ppm sources are analyzed. Both of these sources are placed between the 100 and 200 ppm sinks. However, only the 150 ppm source fulfils the second criteria and, hence, is identified as the pinch-causing source. This also means that all water sinks (20, 50, and 100 ppm) and sources (50 and 100 ppm) lower than 150 ppm are located in the lower concentration region, while the rest are in the higher concentration region. One may then identify the 100 ppm sink as the last segment of the sink composite curve in the lower concentration region, while the 200 ppm sink is the first segment in the higher concentration region. The minimum water flow rates are next calculated. From Table 17, the impurity load is accumulated to 14 kg/h at the 100 ppm sink (see also Figure 12a for the cumulative load of the sink composite curve). On the other hand, Table 17 also shows that the cumulative load of the 100 ppm source is 12.5 kg/h. This means that 1.5 kg/h of impurity load is

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Figure 17. Overall framework of automated targeting for water reuse/recycle.

contributed by the pinch-causing source (SR3) in the lower concentration region. Dividing this load by the source concentration (150 ppm) yields the allocated flow rate of 10 ton/h in the lower concentration region. Performing a flow rate balance between the total water sinks (50 + 100 + 80) and sources (50 + 100 + 10) for the lower concentration yields the fresh water flow rate of 70 ton/h. Finally, taking into account the overall flow rate lost (20 ton/h) between the total sources and sinks (excluding fresh water) yields the wastewater flow rate of 50 ton/h. (h) Automated Targeting Technique.52 One of the latest targeting techniques for the fixed flow rate problem is developed using the mathematical optimization technique based on the framework of WCA technique38,41 described earlier. It may be arguable that this targeting tool should not be classified as a pinch analysis technique, as it does not take the conventional graphical or algebraic forms of the latter, but rather built on a mathematical optimization framework. However, since its fundamental principle is based on the pinch targeting concept, it is included in the review. Note that the approach was actually inspired by a similar targeting technique for mass exchange network synthesis,53 which takes the form of linear programming model and guarantees a global optimum solution. The targeting procedure is described as follow, using the generic cascade diagram in Figure 17 (similar to that of the WCA techniques38,41). Flow rate difference between the total water sinks and sources (∑iFi - ∑jFj) is first determined at each concentration level k. The net water flow rate cascaded from the earlier level k - 1 (δk-1) is added with the flow rate balance at concentration level k to form the net water flow rate at level k (δk), as given in eq 10: δk ) δk-1 + (ΣiFi - ΣjFj)k

(10)

Impurity load cascade is next performed. Within each concentration interval, the impurity load is given by the product of δk with the difference between two adjacent concentration levels. The impurity load residue from concentration level k (εk) is then cascaded down to the next

concentration level. Hence, load balance at concentration level k is determined by eq 11: εk ) εk-1 + δk(Ck+1 - Ck)

(11)

where εk-1 is the residue impurity load cascaded from concentration level k - 1. Note that ε0 will always take a value of zero. Note also that the net water flow rate (δk) can either take positive or negative value (indicating water that flows from the lower to higher concentration level or vice versa), while the residue impurity load (ε) must take a positive value. Hence, eq 2 is added as a constraint in the mathematical model. εk g 0

(12)

Since the model is built on the WCA techniques,38,41 it locates the same network targets as the latter. As shown in Figure 17, the first δk in the flow rate cascade corresponds to the minimum fresh water flow rate (δ0 ) FFW), while that of the last corresponds to wastewater (δn-1 ) FWW). The pinch concentration is observed when the εk value is determined as zero by the optimization model. Besides, the flow rate allocation targets are observed from the net water flow rates (δk) entering and leaving the pinch concentration level. To apply the automated targeting technique for example 5, one would solve the linear model by minimizing the fresh water flow rate (FFW), subject to the constraints in eqs 10-12. The same results are obtained as before, i.e. 70 ton/h of fresh water, 50 ton/h of wastewater flow rates, and CPINCH ) 150 ppm (cascade diagram is shown in Figure S6 in the Supporting Information). The main advantage of the automated targeting technique is its flexibility in changing the objective function (e.g., to minimize costssee the extended work in the regeneration targeting section), rather than being restricted to minimizing water flow rates in almost all the conventional pinch analysis targeting techniques described earlier. This is particularly important for cases with multiple fresh water sources of different quality and/or cost (even though this has not been shown in the original work52). In addition, it allows the water source flow rate to vary with a particular sink (for water-using operations that allow flow rate variationssee the example in the original


5143

52

work ). Note that this feature is not eligible in most targeting approaches in the fixed flow rate problems, where the limiting flow rates of the sinks and sources are always treated as independent. However, since the approach is relatively new, it has yet to be extended to cases such as multiple fresh resources and threshold problems. Targeting Techniques for Water Regeneration Water regeneration involves partial or total removal of water impurity using any purification technique(s). The regenerated water can then be reused (in other water-using processes) or recycled (to its original process). This leads to a further reduction of both fresh water and wastewater flow rates. In general, water regeneration units may be broadly categorized as the fixed outlet concentration (CRout) and removal ratio (RR) type.20,22 For the latter, RR of a treatment unit is given as the ratio of the impurity load removed by the treatment process to the total impurity load in the inlet wastewater, as shown in eq 13: RR )

FT(CRout - CRin) FTCRin

(13)

where FT and CRin are the treatment/regenerated flow rate and the inlet concentration of the regeneration unit, respectively. For regeneration units without water loss, eq 14 may be simplified as CRout - CRin CRin

(14)

Figure 18. Targeting using the limiting composite curve for fixed load problem: (a) regeneration-reuse; (b) regeneration-recycle.

Discussion for this section shall be separated into fixed load and fixed flow rate problems. (A) Early Works on Regeneration Targeting for Fixed Load Problems. Early developments on water regeneration targeting for the fixed load problem were mainly contributed by Smith and his co-workers.20-22 The first generation of the regeneration targeting technique was based on the limiting composite curve for water reuse/recycle.20 This is illustrated using Figure 18, with the dotted line representing the individual segments of the fresh and regenerated water, while the composite water supply line is shown by the solid line. As shown, fresh water is first used in some water-using processes until it reaches the pinch concentration (CPINCH). It is then purified in a regeneration unit to the outlet concentration (CRout) before being reused/recycled in the water network again. In this early work for regeneration targeting, the optimum inlet concentration for regeneration (CRin) is assumed to be equal to the pinch concentration. The targeting procedure further differentiates between the options for the regenerated water, i.e. either to be sent for reuse in other processes (Figure 18a) or being recycled to processes where the original effluent is being generated (Figure 18b). For a regeneration-reuse system (Figure 18a), note that the segments for both fresh and regenerated water possess the same slope. This is due to the restriction where water recycle is not permitted. Hence a water stream(s) that reaches the pinch concentration is fully generated before it may be further reused. In contrast, for the regeneration-recycle system (Figure 18b), since water recycling is permitted, the flow rate of the regenerated water is less than that of fresh water. This is indicated by the higher slope of the fresh water segment than that of the regenerated water segment. Furthermore, a lower fresh water flow rate is observed for the regeneration-recycle system, as compared to the regeneration-reuse system, as

observed from the steeper slope of the fresh water segment in the former case. However, as observed by later works,22,27 in some cases the pinch may be reallocated to new concentration after regeneration took place in the water network. In other words, approach of drawing water sources at the pinch concentration for regeneration may fail to locate the minimum water targets for these cases. This observation indicates that the targeting procedure is not generic enough in handle all cases in the water networks. To overcome the drawback of pinch reallocation, an alternative targeting procedure was proposed where water-using processes are decomposed into two subgroups, in which targeting were performed separately.22 The first group consists of processes which are fed by fresh and reuse/recycle water, while the second group consists of processes which are only fed by regenerated water after it has been reused/recycled from the first group. Flow rate targets for both groups are located using two different limiting composite curves. Next, water targets were further reduced by migrating different water-using processes between the two subgroups.22 The migration of the water-using processes makes the approach being cumbersome and time-consuming. Despite the above-mentioned limitations these early targeting tools, the research area basically stayed stagnant for almost a decade before some important breakthroughs were reported by a group of Chinese researchers.54-56 Better insights on the problem were reported, and improved targeting steps using a sequential approach were proposed. Apart from locating the minimum regeneration flow rate, the improved targeting technique also showed that the optimum inlet concentration to a regeneration unit does not always correspond to the pinch concentration of the reuse/recycle network. The improved targeting technique is illustrated next, for both regenerationreuse and regeneration-recycle systems.

RR )

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Figure 19. Cases presented by Feng et al.54

Figure 20. Revised targeting technique for regeneration-reuse using a limiting composite curve.54

(a) Revised Targeting Procedure for Regeneration-Reuse.54 Feng et al.54 showed that apart from the regeneration system in Figure 18, there are two other cases where modification is needed on the original regeneration targeting procedure.20 These cases are shown in Figure 19. Comparing the limiting composite curves in Figure 19 with that in Figure 18, one observes that those in Figure 19 have a turning point near to the water supply line, either being higher (Figure 19a) or lower (Figure 19b) than the pinch concentration. However, this does not occur in Figure 18 (or its similar kind as in Figure 4). The turning points in those limiting composite curves in Figure 19 dictate the optimum inlet concentration for the regeneration process to take place, which eventually leads to the minimum regeneration flow rate. The solid water supply line in Figure 19 shows the flow rate targeting when fresh water is used alone (without regeneration), while the dotted lines show the fresh and regeneration water segment when regeneration take place (composite water supply line is omitted to avoid complication). Note that, in this case, the targeting approach of Wang and Smith20 is used where the pinch concentration is taken as the regeneration inlet concentration. For the case in Figure 19a, one can easily determine that the resulting composite supply line will not touch at the original pinch point, but rather at a new pinch which is of higher concentration (at the turning point on the limiting composite curve) than the original pinch. The migration of pinch concentration indicates that the regeneration flow rate is not optimum. To restore the original pinch, Feng et al.54 showed that water to be regenerated should be drawn from a higher inlet concentration (than the pinch). Figure 20a shows the result for

such a case. As shown, the resulting composite water supply line touches on the original pinch, as well as at the new pinch of higher concentration, results in a network of multiple pinches. For the case in Figure 19b, following the approach of Wang and Smith,20 i.e. drawing water from the pinch concentration for regeneration, will migrate the original pinch to a lower concentration (touching at the turning point on the limiting composite curve). This may be verified by drawing the composite water supply line for Figure 19b (now shown). This indicates that the regeneration flow rate is not optimum. Following the approach of Feng et al.54 to draw the regenerated water than a lower concentration (from the pinch), the original pinch concentration is restored and, hence, a multiple pinch case results, as shown in Figure 20b. Note that the authors also explored the effect of inlet and outlet concentrations on the regeneration flow rate, but they are not included here. Finally, note also that only the total regeneration process is discussed, as a partial regeneration targeting procedure for a regenerationreuse system is similar to that in the regeneration-recycle system, which will be discussed next. (b) Revised Targeting Procedure for Regeneration-Recycle.55 For a given quality of regenerated water, the regeneration-recycle (and partial regeneration for a regenerationreuse system) targeting procedure follows a sequential optimization approach that consists of the following steps:55 i. Targeting for minimum fresh water flow rate ii. Targeting for minimum regeneration flow rate iii. Determination of optimum inlet concentration for regeneration


5145

Figure 22. Zero discharge case with a regeneration-recycle scheme.56

Figure 21. Revised targeting technique for regeneration-recycle using a limiting composite curve.55

For cases such as those in Figure 18b, where no turning point on the limiting composite curve is near to the water supply line, the approach of Wang and Smith20 works well. One observes that water is drawn from the pinch concentration for regeneration without affecting the original pinch concentration. However, for the case in Figure 19a, one easily determines that the pinch is migrated to the turning point, which is of higher concentration than the original pinch. This means that the targeting technique20 does not lead to optimum flow rate targets (either the fresh or regenerated water). Applying the approach of Feng et al.,55 the minimum fresh water flow rate is first located by minimizing the slope of the fresh water segment below the regeneration outlet concentration (CRout). The segment of the fresh water is then extended to an arbitrary regeneration inlet concentration (CRin, which will be optimized at the later step), before the regenerated water segment is connected. An inlet concentration higher than the pinch is good for a start, as the optimum CRin value for this kind of network will have higher concentration than the original pinch.55 A final segment of the composite water supply line is then added to represent the final discharge from the water network, touching at the turning point of the limiting composite curve. This final discharge segment is set to have the same slope (and hence the same flow rate) as the fresh water segment, assuming no water is lost from the network. On the basis of the given inlet and outlet concentrations, the minimum regeneration flow rate is next determined. This is given by the steepest segment that connects between the regeneration outlet concentration (which in turn connects vertically from the fresh water segment) with the intercept of the final discharge segment, in such a way that

the resulting composite water supply line will touch at the original pinch concentration. In the final step, the CRin of the regeneration process that was taken arbitrarily earlier is minimized in order to reduce the regeneration load. The minimum CRin value will ensure that the composite water supply line to touch at the limiting composite curve at two pinches, i.e. the original pinch as well as the turning point. The resulting composite curves for the system is shown in Figure 21a. For the case in Figure 19b, the pinch will migrate to the turning point with lower concentration than the original pinch by applying the targeting technique of Wang and Smith.20 Applying the regeneration targeting procedure of Feng et al.55 results in the limiting composite curve as shown in Figure 21b. For this case, the final discharge segment touches at the original pinch, while the composite water supply line touches the turning point. Hence, a multiple pinch network results. The optimum inlet concentration for regeneration is determined to be lower than the original pinch concentration.55 For cases where the most stringent inlet concentration (Cin) among all water-using processes is nonzero, a zero discharge network may be achievable when a regeneration unit is employed for water purification. The necessary condition to achieve zero discharge is that the regeneration outlet concentration is less than the most stringent inlet concentration among all water-using processes.56 For a network without water loss, the whole wastewater stream is regenerated and recycled within the water network. This also leads to zero fresh water intake. In order to reduce regeneration flow rate, the water supply line is rotated at the regeneration outlet concentration (at the y-axis) as the pivot until it touches the limiting composite curve, as shown in Figure 22. For water network with flow rate loss, the fixed load problem is converted into fixed flow rate problem before the minimum flow rates are determined.56 Note that both the targeting approach for regenerationreuse and regeneration-recycle are applicable for regeneration of the fixed CRout type. Even though it is claimed that the developed approach will equally work for regeneration processes of fixed RR type,20 it has not been shown explicitly in the revised targeting procedure.54,55 Finally, note also that the mass problem table were extended to locate the flow rate targets in the regeneration system, based on the insights gained from the revised graphical targeting approach.54-56 (B) Regeneration Targeting Techniques for Fixed Flow Rate Problems. Some works have reported the extension of the targeting technique in fixed load problems into the fixed flow rate problems.32 However, due to the approach that was

5146


Table 18. Ultimate Flow Rate Targeting for Example 5 (CRout ) 10 ppm) k

Ck (ppm)

∑jFj (ton/h)

∑iFi (ton/h)


FC,k (ton/h)

∆mk (kg/h)

cum ∆mk (kg/h)

(a) flow rate targeting in the fresh water region FFW ) 20 1

0

0

2

10

0

3

20

4

50

5

100

6

1000000 total

-25

25

0 5

5

20

0.2

20

0.2

-5

-0.2

-5

-0.3

0.2

FWW ) 0

0.3 0.0

0.0

0 25

0.4

0.0

5 (b) flow rate targeting in the regenerated water region

1

CRout ) 10

2

20

FRW ) 53.57 0 -25

25

3

50

100

50

-50

4

100

80

95

15

5

150

70

70

6

200

7

250

8

1000000 total

-70

70 60

60 0

275

53.57

-4.3

28.57

0.9

-4.3

-21.43

-1.1

-6.43

-0.3

63.57

3.2

-6.43

-0.3

-3.4 -4.5 -4.8 -1.6 -2.0

FRW ) 53.57

53558.0 53556.1

275

based on the conventional targeting techniques of Wang and Smith,20 i.e. pinch concentration is taken as the regeneration inlet concentration, the approach suffers from the same limitations as described earlier in the fixed load problems. In particular, when the limiting composite curve has a turning point that is near to the fresh water supply line, higher fresh water flow rate is needed for the water network.57,58 However, it is believe that the improved approaches by Feng et al.54-56 may be used to overcome this limitation. On the other hand, recent works showed that more researchers prefer to directly address the regeneration targeting problem from the fixed flow rate perspective. Hallale37 first presented a guideline in placing regeneration units for the fixed flow rate problems. In order to reduce the overall water flow rates of the network, regeneration units should be placed across the pinch concentration, where water is drawn from higher concentration region (with an excess of water) to lower concentration region (with a flow rate deficit).37 Later works mainly follow the same guideline.19,38,41 However, none of these approaches guarantees the determination of the minimum regeneration flow rate along with the minimum fresh water and wastewater flow rates for the network. (a) Ultimate Flow Rate Targeting.59,60 The first approach that locates the minimum regenerated water, along with the minimum fresh water and wastewater flow rates (termed as ultimate water flow rates) in the fixed flow rate problems is reported by an algebraic targeting technique,59,60 which is based on the flow rate allocation concept of Kuo and Smith.22 The targeting technique first allocate the water sinks and sources into two subregions, i.e. fresh water region (FWR, supplied by fresh and regenerated water) and regenerated water region (RWR, only supplied by regenerated water), before the minimum flow rates are identified for each region separately. The work also showed that, for a network with total sink flow rates

that are higher than that of the sources, it is possible to achieve a zero discharge network with the use of a regeneration unit (with CRout lower than the most stringent inlet concentration among all water sinks). This is shown using example 5 with a regeneration unit of CRout of 10 ppm (Table 18), following the targeting steps outlined in Figure 23.59,60 As shown, a zero discharge network (FWW ) 0 ton/h; Table 18a) is achieved when 53.57 ton/h of regenerated flow rate (FRW) of 10 ppm is used (Table 18b). Due to lengthy description, the targeting procedure will not be described here. Readers may refer to the original source for a detailed description. The main assumption (and also the main limitation) of this work is that the targeting approach is only applicable for regeneration unit of the fixed CRout type. Hence, similar to the case in the fixed load problem, the targeting procedure is not applicable when a regeneration unit of the RR type is used. (b) Source Composite Curve.61 Another work that approached the problem using a source composite curve has been reported,61 where regeneration of both fixed CRout and RR type models may be used. Example 5 is used to illustrate this targeting technique. The source composite curve is first generated using the earlier described procedure (given in Figure 16). The algebraic step of the targeting procedure also determines the impurity load to be removed from the network when a regeneration unit is used. For example 5, this corresponds to 10 kg/h, given in the last value in the sixth column in Table 16. A vertical line is then drawn at 10 kg/h on the source composite curve to form an impurity recovery pocket. The pocket is then removed, and the actiVe source composite curVe is formed (see Figure 24). When a regeneration unit of fixed CRout ) 20 ppm is used, the point (10, 20) is used as a pivot where the treatment line is rotated and touches the active source composite curve at the treatment


5147

Figure 23. Regeneration targeting procedure of Ng et al.59,60

pinch. The regenerated flow rate is given by the inverse slope of the treatment line, given as 53.57 ton/h for example 5 (Figure 24a). On the other hand, when a regeneration unit of RR ) 0.95 is used, the impurity load of the treatment feed stream (∆mT) is first determined. Equation 10 is rearranged to relate mT () FTCRin) with the impurity load for removal ∆mR, () FT(CRin CRout)), given as in eq 15: ∆mT )

∆mR RR

(15)

Since the RR value is smaller than unity, higher load of impurity (∆mT) is always sent for regeneration in order to obtain the impurity load for removal ∆mR. For example 5, ∆mT is determined as 10.53 kg/h () 10/0.95). Next, the point (10.53, 0) is used as a pivot where the treatment line is rotated clockwise until it touches the active source composite curve (Figure 24b). Similar to the earlier cases, the regenerated flow rate is also determined as 53.57 ton/h. As mentioned earlier, that this regenerated flow rate leads to a zero discharge network for the problem (see Table 18). One advantage of the source composite curve in locating the regeneration targeting is that the inlet concentration of the regenerated water (CRin) may be located at the interception of the treatment line with the y-axis. Hence, it allows the maximum inlet concentration to be set for the regeneration unit. This is not available directly with other targeting techniques of the fixed flow rate problems.19,37,38,41,59,60 However, it is worth mentioning that the regeneration targeting procedure of the source composite curve61 was originally developed for total water network (see discussion in a later section); hence, it only locates minimum regenerated flow rate for zero discharge cases (after regeneration has taken place).

Figure 24. Regeneration targeting using source composite curve for Example 5: (a) unit with CRout ) 20 ppm; (b) unit with RR ) 0.95.

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Figure 25. Automated targeting for regeneration placement.62

For other more general cases (with wastewater discharge), the treated flow rate (FT) includes both regeneration (for reuse/recycle) and wastewater treatment (for final discharge). Hence, one would not be able to obtain the regenerated flow rate alone without considering the waste treatment. (c) Automated Targeting Technique.62 Apart from the conventional graphical and algebraic targeting techniques, the earlier-described automated targeting technique52 has also been extended into the regeneration targeting for the fixed flow rate problem. As shown in the generic cascade diagram in Figure 25, the regeneration unit of the fixed CRout type draws water (treated as sinks) from all concentration levels that contain a water source and sends the better quality water (as source) to the CRout level. Hence, a flow rate balance at the Ck (> CRout) level will take the modified form of eq 10, as follows: δk ) δk-1 + (ΣiFi - ΣjFj)k - FRWr

(16)

where FRWr is the flow rate of the rth regenerated water source. On the other hand, the flow rate balance at the CRout level will take the form in eq 17: δk ) δk-1 + (ΣiFi - ΣjFj)k + ΣrFRWr

(17)

The last term in eq 17 dictates the minimum regenerated flow rate of the network, which is the result of the optimization stage. Similar to the case of reuse/recycle, the δ0 and δn-1 values corresponds to the minimum fresh water (FFW) and wastewater flow rates (FWW) of the water network, while the zero value of εk indicates the pinch. Apart from locating the minimum flow rates for the network, the main advantage of the work is the incorporation of minimum cost solution in the targeting stage (which is usually done during detailed network design), as well as the simultaneous synthesis of a mass exchange network that is used as the regeneration system. These features are not commonly available in the conventional graphical and algebraic targeting techniques. However, the targeting approach is yet to be developed to handle cases with RR-type water regeneration unit. Targeting Techniques for Wastewater Treatment It is noticeable that the work reported for waste treatment targeting is relatively less as compared to that in water reuse/

recycle as well as regeneration. To date, only three groups of researchers have reported their work based on pinch-based targeting approach, where the basic underlying principles are based on the fixed load23,24 and fixed flow rate problems.61,63,64 These targeting approaches will be briefly reviewed. Note that the waste treatment units may also be rated according to fixed outlet concentration (CTout) and RR types, similar to the case of the regeneration units. (A) Wastewater Treatment Targeting for Fixed Load Problems. Since this first generation of the waste targeting tool is based on the fixed load problem,23 it is hence constructed on an impurity concentration vs load diagram, similar to the limiting composite curve for water reuse/recycle (Figure 26). As shown in Figure 26a, four individual wastewater streams (WW1-WW4, with concentrations CWW1-CWW4) are to be treated to meet the environmental discharge limit (CD). In order to represent the overall waste treatment system, the impurity load is then added within each concentration interval to form the wastewater composite curVe (Figure 26b). For a treatment unit of the fixed CTout type, the minimum treatment flow rate may be located by drawing a treatment line from CTout and rotated counterclockwise until it touches the wastewater composite curve, where a pinch is formed. The minimum treatment flow rate is given by the inverse slope of the treatment line. For a treatment unit with a fixed RR model, the treatment line is rotated at point O in Figure 26c. Similar to the case of the fixed CTout type treatment system, the minimum flow rate for this case is also given by the inverse slope of the treatment line. The main limitation of this earliest targeting approach is that, when multiple units are needed, the approach fails to locate the minimum flow rates for the system. This pitfall is later overcome by the revised procedure proposed by their later work (omitted here due to space limitations).24 (B) Wastewater Treatment Targeting for a Fixed Flow Rate Problem. Two wastewater targeting techniques have been reported for the fixed flow rate problems, which are based on a material recovery pinch diagram64 and source composite curve,61 respectively. (a) Targeting Procedure of Ng et al.64 This technique takes a two-stage approach. In the first stage, the individual wastewater streams that emerge from a water network are first identified, via graphical (material recovery pinch diagram28,39) or algebraic


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Figure 27. Targeting for the distributed waste treatment of Ng et al.64

Figure 26. Targeting for distributed waste treatment for fixed load problem:23,24 (a) individual wastewater streams; (b) flow rate targeting with fixed CTout type treatment unit; (c) flow rate targeting with fixed RR type treatment unit.

(WCA38,41) techniques.63 Note that the wastewater streams may also be identified using the source composite curve.47 The wastewater composite curve is then constructed on a load vs flow rate diagram, with the individual wastewater streams being arranged in an increasing order of impurity concentration, and connected from head to tail (Figure 27).64 A discharge locus is next added on the load vs flow rate diagram, with its slope corresponding to the maximum allowable concentration for effluent discharge (CD) that complies with the environmental regulation. The maximum allowable impurity load for discharge (∆mD) is represented by the height of the waste discharge locus. Hence, the height difference between the wastewater composite and the waste discharge locus gives the total impurity load to

be removed (∆mT) from the wastewater streams before they may be discharged to the environment. For a single waste treatment unit with fixed outlet concentration (CTout), a treatment line is added from the origin, with its slope being the outlet concentration. In most cases, the treatment unit will produce effluent clearer than the maximum allowable concentration for effluent discharge (CTout < CD). Hence, to reduce the operation cost (with smallest treatment flow rate and impurity load), the treatment line is moved vertically up until its final end (the discharge point) touches the discharge locus. The horizontal length of the treatment line between discharge point and the wastewater composite curve indicates the minimum treatment flow rate (FT) needed for the overall wastewater streams, while other portions of the wastewater streams will by pass the treatment system (with a flow rate of FBP). This is shown in Figure 27a. On the other hand, for a treatment unit of the RR type, flow rate targeting for this kind of treatment unit is shown in Figure 27b. Similar to the case where regeneration unit of RR type is used for partial treatment of water source (for reuse/recycle), the impurity loads of the treatment feed stream (∆mT) is first determined using eq 15. This higher load of impurity (∆mT) is sent for wastewater treatment in order to comply with environmental regulation for discharge. This is showed in Figure 27b, where the impurity load sent for treatment (∆mT) is larger than the impurity load being actually removed (∆mR) from the treatment unit. The minimum treatment flow rate (FT) is given

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Ind. Eng. Chem. Res., Vol. 48, No. 11, 2009 Table 19. Wastewater Stream Data for Example 7 wastewater stream

Fi (ton/h)

CWWi (ppm)

1 2 3

40 30 20

400 100 30

minimum wastewater treatment flow rate for the network. As mentioned earlier, the targeting techniques were developed for a total water network; hence, they do not cater to cases where water regeneration is omitted, as well as when wastewater treatment is considered separately. Example 7 is used to illustrate the earlier two wastewater treatment targeting techniques,23,64 with the stream data shown in Table 19. The source composite curve is omitted here since it does not cater to cases where wastewater treatment is considered separately. Composite curves for both techniques are shown in Figure 28. For simplicity, only a single treatment unit with RR ) 0.99 is shown. When the minimum discharge concentration (CD) is set at 20 ppm, both approaches yield a treatment flow rate (FT) of 59.8 ton/h and a treatment load (∆mT) of 17.8 kg/h () 17.6 - (-0.2) for Figure 28a). Targeting for a Total Water Network

Figure 28. Wastewater treatment targeting for Example 7: (a) fixed load problem;23 (b) fixed flow rate problem.64

by the corresponding horizontal distance of the composite curve segments associated with the impurity load for treatment (see Figure 27b). Apart from the minimum treatment flow rate, the targeting approach also ensures that the minimum impurity load is removed by the wastewater treatment system. One should note that even though the minimum treatment flow rate is easily located for both fixed CTout and RR type treatment units, the approach is yet to be able to locate the minimum treatment flow rate when multiple units are used (for both similar and different treatment types), as well as for cases where the wastewater treatment units are restricted with the regeneration inlet concentration. These are the research gaps to be filled in the future. (b) Targeting Procedure of Bandyopadhyay and Cormos.61 For source composite curve, the targeting procedure to locate the minimum treatment flow rate is exactly the same as that with regeneration targeting (as outlined for Figure 24).61 For a given fresh water flow rate (to be added at the respective concentration level of its algebraic steps), one can locate the

In the previous sections, various targeting techniques were reviewed for water reuse/recycle, regeneration, and wastewater treatment. From a broader perspective, these three individual elements form the overall framework called the total water network. Within the overall framework, the individual elements interact among each other, as shown in Figure 29. (A) Targeting for Fixed Load Problems. In order to ensure an optimum total water network, the targeting techniques for the individual elements (reuse/recycle, regeneration, and wastewater treatment) are brought together for the fixed load problems. This is particularly true for the earliest work in this area that was reported by Kuo and Smith,25 who studied the interaction among the individual elements for the fixed load problem. Strictly speaking, no guideline has been given on how to ensure an optimum water network that features minimum flow rates and impurity load removal for the overall network. On the other hand, several approaches were proposed for the fixed flow rate problem, which were mainly extended based on the works done by the same group of researchers on regeneration and wastewater treatment targeting.61,63,64 They are briefly reviewed next. (B) Targeting for Fixed Flow Rate Problems. (a) Targeting Procedure of Ng et al.63,64 This is the first work

Figure 29. Overall framework of a total water network.25


Figure 30. Overall targeting procedure for total water network of Ng et al.63,64

that reported the targeting for the fixed flow rate problem. Similar to the earlier case on the fixed load problems,25 the procedure calls for the individual targeting techniques developed for each individual element of the total water network. As shown in Figure 30, targeting for water reuse/recycle is first carried out. This is followed by the wastewater identification techniques. Water regeneration is next considered if further water reduction is required (true for most cases). Individual wastewater streams that were identified earlier are sent for regeneration. New wastewater streams from the water network are next identified, since the use of regenerated water in the water network will produce new wastewater streams. Finally, targeting for wastewater treatment is carried out. Being an insight-based approach, one notices that the targeting procedure is carried out step by step, in order to ensure that the minimum flow rates are achieved at each stage. Note that even though the targeting procedure is developed based on the material recovery pinch diagram and WCA techniques,63,64 in principle it is possible to utilize any of the earlier reviewed techniques for each of the targeting steps (e.g., algebraic targeting approach45,46 for targeting water reuse/recycle, source composite curve61 for targeting water regeneration, etc.), so long as they achieve rigorous flow rate targets. Besides, the targeting procedure also ensures that the minimum impurity load is removed from the total water network, to secure the lowest possible operating cost associated with the regeneration/treatment systems. In principle, the total impurity load removed from the overall network (by regeneration and treatment units) may be calculated from eq 18: ∆mR + ∆mT ) ΣiFiCi - ΣjFjCj - FWWCD

(18)

Despite its advantage of ensuring minimum flow rate targets at each stage, the approach is, nevertheless, limited to the following assumptions: • The water regeneration unit is limited to the fixed CRout type, since no work has been reported for the regeneration unit of the RR type. • The minimum water flow rate is only guaranteed for a single wastewater treatment unit, as the targeting technique

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does not locate the minimum treatment flow rate when multiple treatment units are used. • The regeneration/treatment unit(s) used in the targeting procedure must have outlet concentrations (CRout and CTout) lower than the discharge limit (CD). In other words, one cannot utilize the procedure if the regeneration/treatment units of higher CRout and CTout are to be used, even though there is a minimum flow rate solution for the network (see the discussion and example in next subsections). Hence, further works are needed to address the above limitation. Finally, note that even though no work has been reported for the overall targeting procedure for the total water network of the fixed load problems, it is believe that similar steps following that of the fixed flow rate problem in Figure 30 are envisaged. (b) Source Composite Curve.61 As explained in the regeneration targeting section (Figure 24), the targeting technique is developed based on the assumption that a single interception unit is used as both regeneration (for reuse/recycle), as well as for waste treatment (for environmental discharge). Hence, it should remove the total amount of impurity load as calculated by eq 18. The main advantage of this technique is that the targeting steps may be carried out in a single targeting tool (source composite curve), unlike the previous approaches where multiple targeting techniques are required for each element in the total water network.25,63,64 This means that the targeting procedure is much simpler. Second, unlike previous works,63,64 the targeting procedure will locate the minimum flow rate solution even for cases where regeneration/treatment with outlet concentration higher than the discharge limit (CRout and CTout > CD) is used. However, the approach is unable to target for networks with different units in the regeneration and wastewater treatment sections (each with different CRout or RR values). (c) Automated Targeting Technique.65 The basic framework of the automated targeting technique is similar to that of the regeneration schemes, given as in the generic cascade diagram in Figure 31. For a network with water regeneration and effluent treatment of the fixed outlet concentration types (CTout), water sources in all levels higher than these concentrations are subjected for regeneration/treatment (treated as water sinks). The treated flow rate of higher quality are then sent for further recovery in the water network (as source). Hence, flow rate balance at level Ck (higher than CRout or CTout) will take the modified form of eq 16, given as follows: δk ) δk-1 + (ΣiFi - ΣjFj)k - FRWr - FTt

(19)

where FTt is the flow rate of the tth treated water source. On the other hand, the flow rate balance at CRout and CTout will take the form in eq 20: δk ) δk-1 + (ΣiFi - ΣjFj)k + ΣrFRWr + ΣtFTt

(20)

The last two terms in eq 20 dictate the minimum regeneration and effluent treatment flow rates for the network, which is the result of the optimization stage. Finally, the discharge flow rate (FWW) is added as a new sink at the concentration level of the final discharge limit (CD). This allows the wastewater to be discharged from the network at its maximum discharge limit. Subsequently, net water flow rate from the last level is set to zero to forbid wastewater discharge from this level: δn-1 ) 0

(21)

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Figure 31. Automated targeting for total water network.65

The minimum fresh water flow rate (FFW) is determined as before from the δ0 value; while εk ) 0 indicates the pinch. The common strength and disadvantage of the approach are the same as discussed in the earlier sections, i.e. incorporation of different objective functions (e.g., minimum cost, minimum impurity load removal) in the targeting stage; while it is limited to network with regeneration and treatment units of fixed CRout or CTout types. Hence, effort is needed to extend the approach into this direction. Beside, it is worth mentioning that some cases that are unsolvable in other approaches may be solved using the automated targeting techniques, which indicate its generic nature. This will be shown by revisiting examples 1 and 2 for the total water network scenario. In example 1, the regeneration unit and the final treatment system are both fixed outlet concentration types, with CRout ) 5 ppm and CTout ) 10 ppm, respectively, while CD is set as 20 ppm.63,64 Solving the objective function to minimize fresh water flow rate (FFW) subject to the constraints in eqs 12 and 19-21 yields minimum fresh water and wastewater (FWW) flow rates of 20 ton/h, respectively (see Figure S7 in the Supporting Information for the cascade diagram), which is inconsistent with the result obtained using the targeting procedure of Ng et al.63,64 A second objective function may be set to minimize the total impurity removal from the network (∆mR + ∆mT) by imposing the earlier determined fresh water flow rate as a new constraint. Hence, the minimum impurity removal is determined as 40.6 kg/h, similar to the result obtained by Ng et al.,63,64 which can be verified using eq 18. It is also worth noting that the minimum impurity load solution may be achieved with different regeneration and wastewater treatment flow rates. For the automated targeting technique, these values correspond to 71.58 and 20 ton/h, respectively, while the values determined by Ng et al.63,64 are reported as 73.68 and 17.79 ton/h, respectively. Note that one may also include the unit water cost to obtain for a cost optimum solution (not shown here). Note further that the solution for this case is not possible by using the source composite curve technique,61 as it is limited to cases that

consider regeneration and treatment units of the same outlet concentrations. In example 2, a single treatment unit with CTout ) 60 ppm is used, while CD is set as 50 ppm.61 In this case, the treated flow rate may be sent for reuse/recycle (i.e., water regeneration), as well as for environmental discharge. Note that one will not be able to solve this case using the approach of Ng et al.,63,64 since it requires the outlet concentration of the treatment unit to be lower than the environmental discharge limit (CTout < CD for this case). Solving the objective function to minimize the fresh water flow rate (FFW) subject to the constraints in eqs 12 and 19-21 yields a zero discharge (FWW ) 0 ton/h) network with minimum fresh water of 40 t/h. Solving a second objective function to minimize the total impurity load removal (by adding fresh water as a new constraint) yields the minimum regeneration flow rate of 97.58 ton/h, with the minimum impurity load removal of 41.45 kg/h (see Figure S8 in the Supporting Information for the cascade diagram). In another scenario, one may set to minimize the regeneration flow rate by imposing a higher flow rate of fresh water, i.e. FFW ) 90.46 ton/h (minimum fresh flow rate for reuse/recycle case without regeneration), a minimum treatment flow rate for final discharge of 51.43 ton/h is obtained, with an impurity load removal of 38.92 kg/h (see Figure S9 in the Supporting Information for the cascade diagram). Both above scenarios are inconsistent with the results obtained using the source composite curve.61 In conclusion, these examples show that the automated targeting technique is more generic than both targeting techniques of Ng et al.63,64 and the source composite curve,61 despite its earlier mentioned limitation (limited to fixed CRout or CTout types water regeneration and wastewater treatment units). Overall Comparison of Different Targeting Techniques Earlier sections of this review reported that the limiting water data for both fixed load and fixed flow rate problems are

NR NR NR 63, 64 63, 64 NR 61 NR 65

NR NR

NR NR NR 63 63 NR 47 NR 65

NR NR NR 64 NR NR 47, 61 NR NR

23-25 NR

NR NR NR 44 44 NR NR NR NR NR NR NR 28, 39 38 45 47 51 NR

fixed flow rate problem

NR NR NR 28, 40 43 46 50 NR NR

NR NR NR 40 43 NR 50 NR NR

NR NR NR 63 38, 41 NR NR NR 52

NR NR 37 19 59, 60 NR 61 NR 62

20, 22, 32, 54-58 32, 54-56 21 NR 20 NR

33,34,36 35 37 28, 39 38, 41 45 47, 48 51 52 water-source and water-sink composites evolutionary table water surplus diagram material recovery pinch diagram water cascade analysis algebraic targeting approach source composite curve analytical method automated targeting technique

fixed load problem

NR NR NR NR 21,23 31,32 21,27 31 20 30

As mentioned in the earlier section, that network design is always regarded as the second stage of any conventional pinch analysis techniques. Once the minimum flow rate targets are determined, a water network may be designed to achieve the established flow rate targets. Note that network design is a degenerated problem, i.e. different network alternatives may exist for a given minimum water flow rates. A simple case such as example 1 with four water-using processes has been shown to exhibit 10 different alternative designs, each with significantly different network structures.66 Throughout the past one-and-a-half decades, various pinchbased network design techniques have been developed for both fixed load and fixed flow rate problems. These are summarized in Table 21 and mapped according to their applications in various water network elements. A further classification in Table 21 shows that approximately half of these techniques are actually dependent on the minimum flow rates established in the targeting stage. In most cases, the design of the water network proceeds in subsequent steps following the guidance of the targeting tools. In other words, these techniques cannot be used without prior location of the water flow rate targets. In contrast, the other half of the network design techniques in Table 21 are independent from the minimum flow rate targets, and hence, they can be used independently, i.e. without having

Table 20. Comparison of Various Flow Rate Targeting Techniques

Various Design Techniques for Water Networks

limiting composite curve mass problem table

interchangeable. Hence, the minimum flow rate targets for a water network may be determined using any of the presented targeting tools. However, not all cases in water network synthesis were being analyzed extensively, as most targeting tools were developed for general cases that are commonly encountered. Also, not all targeting tools were extended to cover for regeneration and treatment targeting. Table 20 shows a comparison among these techniques, where the various targeting tools are mapped according to their contribution in the water network synthesis problem. The numbers in the columns indicate the cited reference(s) associated with their respective contributions. Those cells without a citation indicate the irrelevancy of the work (e.g., water losses/gains are irrelevant to fixed flow rate problem, etc.). Besides, there are also possible developments for each of the targeting tools which were not reported (labeled as “NR”). One interesting fact to be noted from Table 20 is that, many more targeting techniques were proposed by researchers for the fixed flow rate problem, as compared to the fixed load problem. Among these techniques, the three most well developed techniques that cover those contributions listed in Table 20 are limiting composite curve, material recovery pinch diagram, and water cascade analysis. The former two techniques are graphicalbased, while the latter is an algebraic technique. Also, it is also worth mentioning that a common limitation associated with most of the graphical targeting techniques in the fixed flow rate problem, as compared to that in the fixed load problem. Note that, for the fixed load problem, the graphical tool of a limiting composite curve allows the user to easily locate the concentration of the final wastewater discharge for a water network (with/without regeneration and/or wastewater treatment), given by the arrowhead of the water supply line (see Figures 4-6, 8, and 18-22). However, this is not the case for the various targeting tools in the fixed flow rate problem (except for the source composite curve47-50,61), as the impurity concentration of the effluent stream is always an unknown in the graphical representation and additional calculation is needed to determine the value.

minimum reuse/recycle fixed multiple single impure multiple impure targeting for identification wastewater targeting for flow rates with a single water flow rate pinch threshold fresh water fresh water water regeneration flow of wastewater treatment total water pure fresh water source losses/gains problems problem problem source sources allocation targets rate streams targeting network


5153

5154


Table 21. Camparison of Various Network Design Techniques dependent on minimum flow rate targets design techniques

yes

water grid diagram load table water main method mass content diagram design rulesa CIA based heuristic design rules water source diagram

no

water reuse/recycle

water regeneration

wastewater treatment/total water network

fixed load problem

20 67 25,68 27

20 NR 69 27

31 71

NR 71

23, 24 NR 27 27 70 NR NR

18 36 72 39 73

18 NR NR 32 NR

NR NR NR 64 NR

fixed flow rate problem source sink mapping diagram source demand approach load problem table nearest neighbor algorithm network allocation diagram a

Only applicable for a wastewater treatment network.

to determine the flow rate targets a priori. Obviously, the latter group is much more versatile than the former, and many of them have proven their results in achieving the minimum flow rate targets, e.g. load table,67 source sink mapping diagram,18 etc. However, since many researchers are used to carrying out the two subsequent targeting and design steps since the introduction of pinch analysis techniques (and often ask questions like “Is there a better design?”), the targeting stage has become a standard practice in most pinch analysis studies, even though this may not be necessary if one were to use the design techniques that are independent of the minimum flow rate targets. It is also worth noting that most network design techniques were originally developed for water reuse/recycle networks, which were then extended to cater to cases with regeneration and wastewater treatment, such as the water grid diagram20,23,24 and nearest neighbor algorithm.32,39,64 In constrast, there is also a design technique that is solely developed for wastewater treatment networks.70 Finally, once a network is synthesized, the preliminary network is evolved to yield a simplified network using an evolution technique. Network evolution techniques were developed for both fixed load20 and fixed flow rate problems.73-75 Due to space limitation, the detailed procedure for each design techniques will not be described here; readers may look to the original sources for better understanding.

Figure 32. Number of publications according to journals/magazines.

Overall Analysis This section analyses the numerous published works in water pinch analysis techniques based on their origin and year of publication, for both fixed load and fixed flow rate problems. The source of data comes from the cited water network references in this review, i.e. refs18-75 (except 42 and 53). However, note that the papers without fundamental contribution on either flow rate targeting or network design techniques26,66 have been excluded. Figure 32 summarizes the journals/magazines where these works were published. Note that textbooks (refs 18, 19, and 27) and conference papers (refs 52, 62, and 65) are excluded from the analysis of this figure. From Figure 32, it is easily observed that Chemical Engineering Research and Design (ChERD), Industrial and Engineering Chemistry Research (I&ECR), and Chemical Engineering Science (CES) have the top three highest numbers of publication, with the former two each dominating the fixed load and fixed flow rate problems, respectively (not shown here).

Figure 33. Number of publications according to region.

Next, Figure 33 shows the regions where the works were originally conducted (catogorized based on the authors’ affiliations), while Figure 34 maps the publications according to the year of publication (textbook and conference papers are included here). As shown in Figure 33, a majority of the works in the fixed load problems were dominated by the Europeans and Asians. For the former, a large portion of papers20-25 were contributed by one research group, i.e. the Centre for Process Integration of the University of Manchester. Note also that these works date back to the last century (see Figure 34). The remaining works were contributed by Asian31,54-56,68-70 and American27,71 groups (including North


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Figure 34. Number of publications according to year.

and Latin America); however, these only occurred in the past decade (see Figures 33 and 34). On the other hand, it is interesting to note that the dominant role of the European researchers was much reduced for the fixed flow rate problems (Figure 33). Asian researchers dominated this area (with 70% contribution), which was then followed by American, European, and finally African researchers. In the author’s opinion, several reasons may explain this situation: • Many European researchers consider pinch targeting techniques to be well established; hence, little effort was made to improve the earlier proposed techniques. Furthermore, research funding in Europe have been dedicated to many other new research areas in recent years, with relatively less funding opportunities for resource conservation research. • The general pinch targeting techniques and their application (especially on heat integration) are now widespread to the many parts of the world, after about three decades of its establishment. The well established concept of heat pinch analysis techniques is virtually found in all process design textbooks.18,19,76-81 This, in a way, helps the global chemical engineering community to understand the underlying principles of pinch analysis, which then encourages the development of the many new research groups away from the Europe. • Rapid industrialization in the Asia Pacific region has encouraged the development of new water minimization techniques to address the various pollution prevention problems. Figure 34 also shows another interesting point on the development of the water pinch analysis. The fixed load problem was the main focus during the first decade when the pinch analysis technique was introduced (termed as phase 1 development as mentioned in the earlier part of this review). In contrast, the fixed flow rate problem which was initiated in 1996 (phase 2 development) has only attracted the attention of the researchers after several years since its introduction, with most papers contributed in the last half decade. Future Research Directions The final section of this review suggests several areas of work to be further developed for water pinch research.

(A) Extension to Other Resource Conservation Problems. Being both the special cases of mass integration, water network synthesis receives significantly more attention from the research community than its counterpart of gas integration problems.32,82-88 For the latter, attention was paid mainly to the integration of refinery hydrogen networks.82-86 It is observed that targeting and design techniques developed in both water and gas networks have been interchangeable, e.g. the water surplus diagram37 was originated from hydrogen surplus diagram,83 while the limiting composite curve and nearest neighbor algorithm of the water network39 was later utilized for the hydrogen network.32 Besides, techniques established for regeneration targeting for water networks have yet to be extended into hydrogen network synthesis. It is worth noting that unlike the regeneration units in water networks with uniform inlet and outlet flow rates, the interception units in hydrogen networks have two effluent streams of different flow rates and quality.84 Hence, modifications are needed to convert the techniques between the two areas of work. The same situation was also observed in property integration, a new area dedicated for material recovery based on property and functionality tracking rather than impurity concentration.89 Techniques developed for a water network have seen their application in property integration, particularly in the property-based reuse/recycle,90,91 as well as regeneration92,93 and treatment problems.94,95 It is believed that further extensions among these material conservation areas will remain active in the near future. (B) Multiple Impurity Problems. While pinch analysis techniques for the single impurity problem have been rather well established, the multiple impurity problem, on the other hand, has yet to receive equal attention from the research community. In particular, most pinch targeting papers were reported for the fixed load problem, ranging from reuse/recyce,20,96 regeneration,20 and wastewater treatment.23,24 On the other hand, the fixed flow rate problem has only seen one reported work on flow rate targeting for the water reuse/recycle case,97 and yet, the targeting technique only locates approximate rather than truly minimum flow rates. It is also worth noting that the recent reported work on a multiple impurity hydrogen

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network85,86 may be easily extended into water network synthesis. In conclusion, further works are needed for the fixed flow rate problem, as well as to extend the targeting work for water regeneration and wastewater treatment. Nevertheless, it is worth nothing that several works on network design techniques have been reported for both fixed load and fixed flow rate problems. This includes the water grid diagram,20 water main method,98 heuristic procedures,70,99 and water source diagram100 for the fixed load problem, as well as the analytical procedure101,102 for the fixed flow rate problem. (C) Simultaneous Targeting and Design of Water Networks. Some recent efforts have also seen the development of new targeting procedures for the simultaneous targeting and design of water networks. In principle, the conventional two-stage approach of sequential targeting and design steps are brought together as a single network synthesis step that ensures minimum water flow rates. To date, only one work has been reported in this direction, in which new insights are imposed into the limiting composite curve for the simultaneous targeting and design of a water network with regeneration-recycle.103 It is foreseen that the approach will soon be extended for other elements of water networks, e.g. water reuse/recycle and wastewater treatment. Note that the network allocation diagram73 that has also claimed to be a simultaneous targeting and design procedure for reuse/recycle network synthesis is actually extended from the material recovery pinch diagram.28,39 However, its sequential targeting and design steps that follow the conventional practice of pinch analysis techniques render its extension into a truly simultaneous targeting and design procedure. (D) Simultaneous Heat and Water Recovery. The discussion thus far has focused on water networks without the consideration of an energy aspect. In the past decade, significant research work has also been reported for a special case of water network synthesis, i.e. heat integration water networks.104-108 However, most reported works are based on the fixed load problems, with little reported work on the fixed flow rate case.109 Furthermore, only reuse/recycle cases have been considered. Hence, further works need to be developed for the fixed flow rate case, as well as to incorporate regeneration and wastewater treatment in the water network. Besides, the synthesis of cooling110-113 and chilled114,115 water networks may be considered as a subset of heat integrated water networks. It is worth mentioning that, in this case, the segregation of fixed flow rate problems may not be necessary, since all water-using processes consume and emit the same flow rate of cooling and chilled water. (E) Water Network Retrofit. A vast majority of the reported pinch analysis works for water network synthesis are developed for grassroots design. In contrast, very little work was dedicated to retrofit cases, except the few papers that are based on the fixed flow rate problems, working on reuse/recycle,116 as well as with regeneration placement117,118 For the latter, the overall concept is similar to that of heat exchanger network retrofit,119 where a parameter called the fresh water efficiency (analogous to constant area efficiency for heat exchanger network retrofit) was introduced to identify the cost optimum retrofit option. It should also be noted that the development of a systematic retrofit procedure for water network is not as straightforward as that in heat exchanger network,119 since capital cost target for a water network can only be established for the fixed load problem,120 but not

for the fixed flow rate problem. Hence, a different retrofit approach may have to be adopted. A good example will be the use of an evaluation tool for various retrofit options.121 However, the main challenge remains on how to locate the retrofit targets without having to evaluate all individual retrofit schmes, which is yet to be established. (F) Interplant Water Integration. After the water recovery potential is exhausted in a single water networks, water recovery between different networks may be considered for the reduction of the overall fresh water and wastewater flow rates. Some earlier attempts based on pinch analysis principle have been reported, focusing on water reuse and recycle.44,122-125 New targeting techniques are expected when regeneration and wastewater treatment are incorporated into the analysis. The earlier reviewed techniques developed for single water networks are expected to extend their role into this new area. Concluding Remarks It may be concluded that water pinch analysis techniques has reached another maturity stage after its establishment oneand-a-half decades ago. Many new targeting techniques have been developed in the past decade to address various research gaps, especially for the fixed flow rate problems. It is foreseen that this area will remain active, at least for the near future, since there are still some research gaps to be filled. Acknowledgment The financial support from the University of Nottingham (New Researcher Fund NRF 3822) and the Ministry of Science, Technology, and Innovation Malaysia (Science Fund 03-02-12-SF0018) is gratefully acknowledged. The feedback of the three anonymous reviewers is highly appreciated. Supporting Information Available: Figures S1-S9 and Tables S1-S5. This material is available free of charge via the Internet at http://pubs.acs.org. Literature Cited (1) Rudd, D. F. The Synthesis of System Designs, I. Elementary Decomposition Theory. AIChE J. 1968, 14 (2), 343–349. (2) Westerberg, A. W. Process Synthesis: A Morphology Review. In Recent DeVelopments in Chemical Process and Plant Design; Liu, Y. A., McGee, H. A., Epperly, W. R., Eds.; John Wiley and Sons: New York, 1987. (3) Hendry, J. E.; Rudd, D. F.; Seader, J. D. Synthesis in the Design of Chemical Processes. AIChE J. 1973, 19 (1), 1–15. (4) Hlava´c˘ek, V. Synthesis in the Design of Chemical Processes. Comput. Chem. Eng. 1973, 2, 67–75. (5) Westerberg, A. W. A Review of Process Synthesis. In Computer Applications to Chemical Engineering: Process Design and Simulation; Squires, R. G., Reklaitis, G. V., Eds.; American Chemical Society: Washington D. C., 1980. (6) Stephanopoulos, G. Synthesis of Process Flowsheet: An Adventure in Heuristic Design or a Utopia of Mathematical Programming? In Foundations of Computer-Aided Chemical Process Design; Mah, R. S. H., Seider, W. D., Eds.; Engineering Foundation: New York, 1981; Vol. II. (7) Nishida, N.; Stephanopoulos, G.; Westerberg, A. W. A Review of Process Synthesis. AIChE J. 1981, 27 (3), 321–351. (8) Gundersen, T.; Naess, L. The Synthesis of Cost Optimal Heat Exchange Networks-An Industrial Review of the State of the Art. Comput. Chem. Eng. 1988, 6, 503–530. (9) Linnhoff, B. Pinch Analysis: A State-of-Art Overview. Trans Inst. Chem. Eng. (Part A) 1993, 71, 503–522. (10) Manousiouthakis, A.; Allen, D. Process Synthesis for Waste Minimization. In Fourth International Conference on Foundations of Computer-Aided Process Design; Biegler, L. T., Doherty, M. F., Eds.; AIChE Symposium Series; AIChe: New York, 1995; Vol. 91, pp 256259.

Ind. Eng. Chem. Res., Vol. 48, No. 11, 2009 (11) El-Halwagi, M. M. Pollution Prevention through Process Integration. Clean Prod. Process. 1998, 1, 5–19. (12) El-Halwagi, M. M.; Spriggs, H. D. Solve Design Puzzle with Mass Integration. Chem. Eng. Prog. 1998, 94 (8), 25–44. (13) Johns, W. R. Process Synthesis: Poised for a Wider Role. Chem. Eng. Prog. 2001, 100 (8), 59–65. (14) Furman, K. C.; Sahinidis, N. V. A Critical Review and Annotated Bibliography for Heat Exchanger Network Synthesis in the 20th Century. Ind. Eng. Chem. Res. 2002, 41 (10), 2335–2370. (15) Dunn, R. F.; El-Halwagi, M. M. Process Integration Technology Review: Background and Applications in the Chemical Process Industry. J. Chem. Technol. Biotechnol. 2003, 78, 1011–1021. (16) Li, X.; Kraslawski, A. Conceptual Process Synthesis: Pass and Current Trend. Chem. Eng. Process. 2004, 43, 589–600. (17) El-Halwagi, M. M.; Manousiouthakis, V. Synthesis of Mass Exchange Networks. AIChE J. 1989, 35 (8), 1233–1244. (18) El-Halwagi, M. M. Pollution PreVention through Process Integration: Systematic Design Tools; Academic Press: San Diego, 1997. (19) El-Halwagi, M. M. Process Integration; Elsevier Inc.: San Diego, 2006. (20) Wang, Y. P.; Smith, R. Wastewater Minimisation. Chem. Eng. Sci. 1994, 49, 981–1006. (21) Wang, Y. P.; Smith, R. Wastewater Minimization with Flowrate Constraints. Chem. Eng. Res. Des. 1995, 73, 889–904. (22) Kuo, W. C. J.; Smith, R. Design of Water-Using Systems Involving Regeneration. Process Safety EnViron. Prot. 1998, 76, 94–114. (23) Wang, Y. P.; Smith, R. Design of Distributed Effluent Treatment Systems. Chem. Eng. Sci. 1994, 49 (18), 3127–3145. (24) Kuo, W. -C. J.; Smith, R. Effluent Treatment System Design. Chem. Eng. Sci. 1997, 52 (23), 4273–4290. (25) Kuo, W. C. J.; Smith, R. Designing for the Interactions between Water-Use and Effluent Treatment. Chem. Eng. Res. Des. 1998, 76, 287– 301. (26) Bagajewicz, M. A Review of Recent Design Procedures for Water Networks in Refineries and Process Plants. Comput. Chem. Eng. 2000, 24, 2093–2113. (27) Mann, J. G.; Liu, Y. A. Industrial Water Reuse and Wastewater Minimization; McGraw Hill: New York, 1999. (28) El-Halwagi, M. M.; Gabriel, F.; Harell, D. Rigorous Graphical Targeting for Resource Conservation via Material Recycle/Reuse Networks. Ind. Eng. Chem. Res. 2003, 42, 4319–4328. (29) Foo, D. C. Y.; Manan, Z. A.; El-Halwagi, M. M. Correct Identification of Limiting Water Data for Water Network Synthesis. Clean Technol. EnViron. Policy 2006, 8 (2), 96–104. (30) Castro, P.; Matos, H.; Fernandes, M. C.; Nunes, C. P. Improvements for Mass-exchange Networks Design. Chem. Eng. Sci. 1999, 54, 1649– 1665. (31) Liu, Y; Yuan, X.; Luo, Y. Synthesis of Water Utilization System Using Concentration Interval Analysis Method (I) Non-Mass-Transfer-Based Operation. Chin. J. Chem. Eng. 2007, 15 (3), 361–368. (32) Agrawal, V.; Shenoy, U. V. Unified Conceptual Approach to Targeting and Design of Water and Hydrogen Networks. AIChE J. 2006, 52 (3), 1071–1081. (33) Dhole, V. R.; Ramchandani, N.; Tainsh, R. A.; Wasilewski, M. Make Your Process Water Pay for Itself. Chem. Eng. 1996, 103, 100–103. (34) Buehner, F. W.; Rossiter, A. Minimize Waste by Managing Process Design. CHEMTECH 1996, April, 64-72. (35) Sorin, M.; Be´dard, S. The Global Pinch Point in Water Reuse Networks. Process Safety EnViron. Prot. 1999, 77, 305–308. (36) Polley, G. T.; Polley, H. L. Design Better Water Networks. Chem. Eng. Progress 2000, 96 (2), 47–52. (37) Hallale, N. A New Graphical Targeting Method for Water Minimisation. AdV. EnViron. Res. 2002, 6 (3), 377–390. (38) Manan, Z. A.; Tan, Y. L.; Foo, D. C. Y. Targeting the Minimum Water Flowrate Using Water Cascade Analysis Technique. AIChE J. 2004, 50 (12), 3169–3183. (39) Prakash, R.; Shenoy, U. V. Targeting and Design of Water Networks for Fixed Flowrate and Fixed Contaminant Load Operations. Chem. Eng. Sci. 2005, 60 (1), 255–268. (40) Wan Alwi, S. R.; Manan, Z. A. Targeting Multiple Water Utilities Using Composite Curves. Ind. Eng. Chem. Res. 2007, 46, 5968–5976. (41) Foo, D. C. Y.; Manan, Z. A.; Tan, Y. L. Use Cascade Analysis to Optimize Water Networks. Chem. Eng. Progress 2006, 102 (7), 45–52. (42) Linnhoff, B.; Townsend, D. W.; Boland, D.; Hewitt, G. F.; Thomas, B. E. A.; Guy, A. R.; Marshall, R. H. A User Guide on Process Integration for the Efficient Use of Energy; Institute of Chemical Engineers: Rugby, 1982.

5157

(43) Foo, D. C. Y. Water Cascade Analysis for Single and Multiple Impure Fresh Water Feed. Chem. Eng. Res. Des. 2007, 85 (A8), 1169– 1177. (44) Foo, D. C. Y. Flowrate Targeting for Threshold Problems and PlantWide Integration for Water Network Synthesis. J. EnViron. Manage. 2007, 88 (2), 253–274. (45) Almutlaq, A. M.; El-Halwagi, M. M. An Algebraic Targeting Approach to Resource Conservation via Material Recycle/Reuse. Int. J. EnViron. Pollut. 2007, 29 (1/2/3), 4–18. (46) Almutlaq, A. M.; Kazantzi, V.; El-Halwagi, M. M. An Algebraic Approach to Targeting Waste Discharge and Impure Fresh Usage via Material Recycle/Reuse Networks. Clean Technol. EnViron. Policy 2005, 7 (4), 294–305. (47) Bandyopadhyay, S.; Ghanekar, M. D.; Pillai, H. K. Process Water Management. Ind. Eng. Chem. Res. 2006, 45, 5287–5297. (48) Bandyopadhyay, S. Source Composite Curve for Waste Reduction. Chem. Eng. J. 2006, 125, 99–110. (49) Pillai, H. K.; Bandyopadhyay, S. A rigorous targeting algorithm for resource allocation networks. Chem. Eng. Sci. 2007, 62, 6212–6221. (50) Shenoy, U. V.; Bandyopadhyay, S. Targeting for Multiple Resources. Ind. Eng. Chem. Res. 2007, 46, 3698–3708. (51) Liu, Z.-Y.; Yang, Y.-Z.; Zhang, Y. Determining the Pinch Point and Calculating the Freshwater Target for Water-Using Systems with Single Contaminant. Chem. Eng. Res. Des. 2007, 85 (A11), 1485–1490. (52) Ng, D. K. S.; Foo, D. C. Y.; Tan, R. R. Automated Targeting Technique for Resource Conservation Networks. Presented at ASIA WATER, Kuala Lumpur, Malaysia, Apr 1-3, 2008. (53) El-Halwagi, M. M.; Manousiothakis, V. Automatic Synthesis of Mass-Exchange Networks with Single Component Targets. Chem. Eng. Sci. 1990, 45 (9), 2813–2831. (54) Bai, J.; Feng, X.; Deng, C. Graphical Based Optimization of SingleContaminant Regeneration Reuse Water Systems. Chem. Eng. Res. Des. 2007, 85 (A8), 1178–1187. (55) Feng, X; Bai, J.; Zheng, X. On the use of graphical method to determine the targets of single-contaminant regeneration recycling water systems. Chem. Eng. Sci. 2007, 62, 2127–2138. (56) Deng, C.; Feng, X.; Bai, J. Graphical Based analysis of water system with zeroliquid discharge. Chem. Eng. Res. Des. 2008, 86, 165–171. (57) Liao, Z.; Wang, J.; Yang, Y. Letter to the editors. AIChE J. 2007, 53 (7), 1898–1899. (58) Agrawal, V.; Shenoy, U. V. Letter to the editors. AIChE J. 2007, 53 (11), 3017. (59) Ng, D. K. S.; Foo, D. C. Y.; Tan, R. R.; Tan, Y. L. Ultimate Flowrate Targeting with Regeneration Placement. Chem. Eng. Res. Des. 2007, 85 (A9), 1253–1267. (60) Ng, D. K. S.; Foo, D. C. Y.; Tan, R. R.; Tan, Y. L. Extension of Targeting Procedure for “Ulltmate Flowrate Targeting with Regeneration Placement” by Ng, et al. Che. Eng. Res. Des. 85 (A9) 1253-1267. Chem. Eng. Res. Des. 2008, 86 (10), 1182–1186. (61) Bandyopadhyay, S.; Cormos, C. C. Water Management in Process Industries Incorporating Regeneration and Recycle through a Single Treatment Unit. Ind. Eng. Chem. Res. 2008, 47, 1111–1119. (62) Ng, D. K. S.; Foo, D. C. Y.; Tan, R. R. Automated Targeting for Resource Conservation Network with Interception Placement. Presented at the 12th Conference on Process Integration, Modeling and Optimisation for Energy Saving and Pollution Reduction (PRES 2009), Rome, May 1013, 2009. (63) Ng, D. K. S.; Foo, D. C. Y.; Tan, R. R. Targeting for Total Water NetworksPart 1: Waste Stream Identification. Ind. Eng. Chem. Res. 2007, 46, 9107–9113. (64) Ng, D. K. S.; Foo, D. C. Y.; Tan, R. R. Targeting for Total Water NetworksPart 2: Waste Treatment Targeting and Interactions with Water System Elements. Ind. Eng. Chem. Res. 2007, 46, 9114–9125. (65) Ng, D. K. S.; Foo, D. C. Y.; Tan, R. R. Automated Targeting Technique for Total Water Network. Presented an the 15th Regional Symposium on Chemical Engineering (RSCE 2008), Kuala Lumpur, Malaysia, Dec 2-3, 2008. (66) Dunn, R. F.; Wenzel, H. Process Integration Design Methods For Water Conservation And Wastewater Reduction In Industry. Part 1: Design for Single Contaminants. Clean Prod. Process. 2001, 3, 307–318. (67) Olesen, S. G.; Polley, G. T. A Simple Methodology for the Design of Water Networks Handling Single Contaminants. Chem. Eng. Res. Des. 1997, 75, 420–426. (68) Feng, X.; Seider, W. D. New Structure and Design Method for Water Networks. Ind. Eng. Chem. Res. 2001, 40, 6140–6146. (69) Cao, D.; Feng, X.; Duan, X. Design of Water Network with Internal Mains for Multi-containment Wastewater Regeneration Recycle. Chem. Eng. Res. Des. 2004, 82 (A10), 1331–1336.

5158


(70) Li, B.; Fan, X.; Yao, P. A New Method for Effluent Treatment System Design. Chin. J. Chem. Eng. 2002, 10 (3), 273–280. (71) Gomes, J. F. S.; Queiroz, E. M.; Pessoa, F. L. P. Design Procedure for Water/Wastewater Minimization: Single Contaminant. J. Cleaner Prod. 2006, 15, 474–485. (72) Aly, S.; Abeer, S.; Awad, M. A New Systematic Approach for Water Network Design. Clean Technol. EnViron. Policy 2005, 7 (3), 154– 161. (73) Wan Alwi, S. R.; Manan, Z. A. Generic Graphical Technique for Simultaneous Targeting and Design of Water Networks. Ind. Eng. Chem. Res. 2008, 47, 2762–2777. (74) Prakash, R.; Shenoy, U. V. Design and Evolution of Water Networks by Source Shifts. Chem. Eng. Sci. 2005b, 60 (7), 2089–2093. (75) Ng, D. K. S.; Foo, D. C. Y. Evolution of Water Network with Improved Source Shift Algorithm and Water Path Analysis. Ind. Eng. Chem. Res. 2006, 45, 8095–8104. (76) Douglas, J. Conceptual Design of Chemical Processes; McGrawHill: New York, 1988. (77) Smith, R. Chemical Process Design; McGraw-Hill: New York, 1995. (78) Biegler, L. T.; Grossman, E. I.; Westerberg, A. W. Systematic Methods of Chemical Engineering and Process Design; Prentice Hall: New Jersey, 1997. (79) Turton, R.; Bailie, R. C.; Whiting, W. B.; Shaeiwitz, J. A. Analysis, Synthesis and Design of Chemical Processes; Prentice Hall: New Jersey, 1998. (80) Seider, W. D.; Seader, J. D.; Lewin, D. R. Product and Process Design Principles: Synthesis, Analysis, and EValuation; John Wiley: New York, 2003. (81) Smith, R. Chemical Process Design and Integration; John Wiley & Sons: New York, 2005. (82) Towler, G. P.; Mann, R.; Serriere, A. J-L.; Gabaude, C. M. D. Refinery Hydrogen Management: Cost Analysis of Chemically Integrated Facilities. Ind. Eng. Chem. Res. 1996, 35 (7), 2378–2388. (83) Alves, J. J.; Towler, G. P. Analysis of Refinery Hydrogen Distribution Systems. Ind. Eng. Chem. Res. 2002, 41, 5759–5769. (84) Foo, D. C. Y.; Manan, Z. A. Setting the Minimum Utility Gas Flowrate Targets Using Cascade Analysis Technique. Ind. Eng. Chem. Res. 2006, 45, 5986–5995. (85) Zhao, Z.; Liu, G.; Feng, X. New Graphical Method for the Integration of Hydrogen Distribution Systems. Ind. Eng. Chem. Res. 2006, 45, 6512–6517. (86) Zhao, Z.; Liu, G.; Feng, X. The Integration of the Hydrogen Distribution System with Multiple Impurities. Chem. Eng. Res. Des. 2007, 85 (A9), 1295–1304. (87) Zhelev, T. K.; Ntlhakana, J. L. Energy-environment Closed-loop through Oxygen Pinch. Comput. Chem. Eng. 1999, 23, S79-S83. (88) Zhelev, T. K.; Bhaw, N. Combined Water-oxigen Pinch Analysis for Better Wastewater Treatment Management. Waste Manage. 2000, 20, 665–670. (89) Shelley, M. D.; El-Halwagi, M. M. Componentless design of recovery and allocation systems: a functionality-based clustering approach. Comput. Chem. Eng. 2000, 24, 2081–2091. (90) Kazantzi, V.; El-Halwagi, M. M. Targeting material reuse via property integration. Chem. Eng. Progress. 2005, 101 (8), 28–37. (91) Foo, D. C. Y.; Kazantzi, V.; El-Halwagi, M. M.; Manan, Z. A. Surplus diagram and cascade analysis techniques for targeting propertybased material reuse network. Chem. Eng. Sci. 2006, 61, 2626–2642. (92) Ng, D. K. S.; Foo, D. C. Y.; Kazantzi, V.; El-Halwagi, M. M. Cascade Analysis Technique for Targeting Property-Based Material Reuse/ Recycle Network. Presented at the AIChE Annual Meeting 2006, San Francisco, Nov 12-17, 2006. (93) Ng, D. K. S.; Foo, D. C. Y.; Tan, R. R.; Pau, C. H.; Tan, Y. L. Automated Targeting for Conventional and Bilateral Property-Based Resource Conservation Network. Chem. Eng. J. 2009, 149, 87-101. (94) Ng, D. K. S.; Foo, D. C. Y.; Tan, R. R. Automated targeting for total property network with Bilateral Constraints. To be presented at the Seventh International Conference on the Foundations of Computer-Aided Process Design (FOCAPD 2009), Colorado, US, June 7-12, 2009. (95) Ng, D. K. S.; Foo, D. C. Y.; Tan, R. R.; El-Halwagi, M. M. Automated Targeting for Total Property-based Network. To be presented at the European Symposium on Computer Aided Process Engineering (ESCAPE-19), Krako´w, Poland, June 14–17, 2009. (96) Doyle, S. J.; Smith, R. Targeting Water Reuse with Multiple Contaminants. Trans. Inst. Chem. Eng. (Part B) 1997, 75, 181–189. (97) Tan, Y. L.; Foo, D. C. Y.; Tan, R. R.; Ng, D. K. S. Approximate Graphical Targeting for Water Network with Two Contaminants. Presented

at the 10th Conference on Process Integration, Modeling and Optimisation for Energy Saving and Pollution Reduction (PRES 2007), Ischia, Italy, June 24-27, 2007. (98) Wang, B.; Feng, X.; Zhang, Z. A Design Methodology for MultipleContaminant Water Networks with Single Internal Water Main. Comput. Chem. Eng. 2003, 27, 903–911. (99) Liu, Z. -Y.; Zhang, J. Z.; Hu, L.; Wu, Z. Wastewater Minimisation Using a Heuristic Procedure. Int. J. Chem. Reactor Eng. 2004, 2 (A25), 1–10. (100) Ulson de Souza, A. A.; Forgiarini, E.; Branda˜o, H. L.; Xavier, M. F.; Pessoa, F. L. P.; Guelli, U.; Souza, S. M. A. Application of Water Source Diagram (WSD) Method for the Reduction of Water Consumption in Petroleum Refineries. Resour., ConserV. Recycling 2009, 53, 149–154. (101) Liu, Z.-Y.; Yang, Y.; Wan, L.-Z.; Wang, X.; Hou, K.-H. A Heuristic Design Procedure for Water-Using Networks with Multiple Contaminants. AIChE J. 2009, 55, 374-382. (102) Liu, Z.-Y.; Li, Y.-M.; Liu, Z.-H.; Wang, Y.-J. Design of WaterUsing Networks with Multi-Contaminant Involving Regeneration. AIChE J., in press. (doi:10.1002/aic.11748). (103) Deng, C.; Feng, X.; Ng, D. K. S.; Foo, D. C. Y. Process-based Graphical Approach (PGA) for Simultaneous Targeting and Design of Regeneration Recycling Water Networks. Proceedings of the 12th Asia Pacific Confederation of Chemical Engineers (APCChE 2008), Dalian, China, Aug 3–6, 2008. (104) Savulescu, L. E.; Sorin, M.; Smith, R. Direct and indirect heat transfer in water network systems. Appl. Therm. Eng. 2002, 22, 981–988. (105) Savulescu, L.; Kim, J.-K.; Smith, R. Studies on Simultaneous Energy and Water Minimisation - Part I: Systems with No Water Re-use. Chem. Eng. Sci. 2005, 60, 3279–3290. (106) Savulescu, L.; Kim, J.-K.; Smith, R. Studies on Simultaneous Energy and Water Minimisation - Part II: Systems with Maximum Re-use. Chem. Eng. Sci. 2005, 60, 3291–3308. (107) Polley, G. T.; Picon Nunez, M.; Canzales Davados, L. Design of Water and Heat Recovery Networks for the Simultanenous Minimisation of Water and Energy Consumption. Presented at the 12th Conference on Process Integration, Modeling and Optimisation for Energy Saving and Pollution Reduction (PRES 2009), Rome, May 10–13, 2009. (108) Leewongtanawit, B.; Kim, J.-K. Improving Energy Recovery for Water Minimisation. Energy, in press. (109) Savulescu, L. E.; Alva-Argaez, A. Direct Heat Transfer Considerations for Improving Energy Efficiency in Pulp and Paper Kraft Mills. Energy 2008, 33, 1562–1571. (110) Kim, J. -K.; Smith, R. Cooling Water System Design. Chem. Eng. Sci. 2001, 56, 3641–3658. (111) Kim, J. -K.; Savulescu, L.; Smith, R. Design of Cooling Systems For Effluent Temperature Reduction. Chem. Eng. Sci. 2001, 56, 1811–1830. (112) Kim, J. -K.; Smith, R. Cooling System Design for Water and Wastewater Minimization. Ind. Eng. Chem. Res. 2004, 43, 608–613. (113) Panjeshahi, M. H.; Ataei, A.; Gharaie, M.; Parand, R. Optimum design of cooling water systems for energy and water conservation. Chem. Eng. Res. Des. 2009, 87, 200–209. (114) Chew, I. M. L.; Ng, D. K. S.; Foo, D. C. Y.; Subramaniam, M. Simultaneous Reduction of Energy and Water-A Special Case on Chilled Water Network Synthesis. Presented at the 1st Engineering Conference: Energy & Environment (EnCon07), 2007. (115) Leong, M, K. Y.; Ng, D. K. S.; Foo, D. C. Y. Targeting for Hybrid Chilled and Cooling Water System. Presented in the 15th Regional Symposium on Chemical Engineering (RSCE 2008), Kuala Lumpur, Malaysia, Dec 2–3, 2008. (116) Tan, Y. L.; Manan, Z. A. A new systematic technique for retrofit of water network. Int. J. EnViron. Pollut. 2008, 32 (4), 519–526. (117) Tan, Y. L.; Manan, Z. A. Retrofit of Water Network with Optimization of Existing Regeneration Units. Ind. Eng. Chem. Res. 2006, 45, 7592–7602. (118) Tan, Y. L.; Manan, Z. A.; Foo, D. C. Y. Retrofit of Water Network with Regeneration Using Water Pinch Analysis. Process Safety EnViron. Prot. 2007, 85 (B4), 305–317. (119) Tjoe, T. N.; Linnhoff, B. Using Pinch Technology for Process Retrofit. Chem. Eng. 1986, (April 28), 47–60. (120) Hallale, N.; Fraser, D. M. Capital Cost Targets for Mass Exchange Networks. A Special Case: Water Minimisation. Chem. Eng. Sci. 1998, 52 (2), 293–313. (121) Wan Alwi, S. R.; Manan, Z. A. SHARPS: A New Cost-Screening Technique to Attain Cost-Effective Minimum Water Network. AIChE J. 2006, 52 (11), 3981–3988. (122) Olesen, S. G.; Polley, G. T. Dealing with plant geography and piping constraints in water network design. Process Safety EnViron. Prot. 1996, 74, 273–276.

Ind. Eng. Chem. Res., Vol. 48, No. 11, 2009 (123) Spriggs, D.; Lowe, E. A.; Watz, J.; El-Halwagi, M. M.; Lovelady, E. M. Design and development of eco-industrial parks. AIChE Spring Meeting, New Orleans, Nov 7–12, 2004. (124) Chew, I. M. L.; Ng, D. K. S.; Foo, D. C. Y. Graphical Targeting for Plant-Wide Water Integration. Presented at the Joint Symposium for Chemical and Metallurgical Engineering, South Africa, Aug 2–3, 2007. (125) Chew, I. M. L.; Foo, D. C. Y.; Ng, D. K. S.; Raymond Tan, R. R.; Saw, S. Y.; Lee, L.; Lim, M. H.; Klemes˘, J.; El-Halwagi, M. M. Flowrate

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Targeting for Inter-Plant Water Network. To be presented at the 8th World Congress of Chemical Engineering, Canada, Aug 23–27, 2009.

ReceiVed for reView August 19, 2008 ReVised manuscript receiVed February 18, 2009 Accepted March 11, 2009 IE801264C

State-of-the-Art Review of Pinch Analysis Techniques for Water

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