Membrane separation process design system for modeling optimal membrane separation process

Abstract

The present disclosure relates to a membrane separation process design system and, more particularly, to a design system capable of designing an optimal continuous membrane separation process.

Description

A membrane separation process design system that models the optimal membrane separation process.

[0001] The present disclosure relates to a membrane separation process design system, and more particularly, to a design system capable of designing an optimal continuous membrane separation process.

[0002]

[0003] Traditionally, centrifugation has been used to separate microbial cells by density differences using high gravitational acceleration (g-force). However, this centrifugation method is difficult to completely separate the microbial cells from the fermentation broth, and it is a batch process that cannot continuously process the process liquid, making it difficult to apply to production processes that require large volumes of material to be processed quickly. Therefore, continuous membrane separation methods have been introduced to the industry to effectively separate microbial cells. Compared to centrifugation methods, continuous membrane separation methods have the advantages of high separation efficiency and low energy consumption, and can be operated continuously, making them suitable for application in mass production processes.

[0004] When removing cells from a fermentation solution, the rate of membrane fouling, in which cells accumulate on the membrane surface, varies depending on the condition of the fermentation solution and process operating conditions (operating pressure, operating time, dilution factor, etc.). This, in turn, affects the permeation rate.

[0005] Additionally, the cell separation efficiency and the state of the final product (i.e., target product) may vary depending on the number of membranes and operating conditions.

[0006] Meanwhile, the number of the above-mentioned membranes is calculated by including the equipment investment cost, and the operating conditions and cleaning cycle are included in the operating cost, so the manufacturing cost of the final product can be derived through this.

[0007]

[0008] Accordingly, the present disclosure aims to provide a system for modeling a continuous membrane separation process, which is capable of modeling by taking into account the permeation rate.

[0009] In addition, the present disclosure aims to provide a system capable of modeling a manufacturing cost model that varies depending on the number of membranes and operating conditions.

[0010] In addition, the present disclosure aims to provide a system capable of modeling by taking into account situations in which the permeation rate of a fermentation solution changes.

[0011] The problems to be solved by the present invention are not limited to the problems mentioned above, and other problems not mentioned will be clearly understood by those skilled in the art from the description below.

[0012]

[0013] According to one embodiment of the present disclosure, there is provided a method for calculating optimal design conditions of a continuous membrane separation process including a plurality of sections, each section including one or more skids, wherein (A) a permeation rate model generation unit generates a permeation rate of each section. The present invention provides a method comprising: (A) a step of generating a permeation velocity model that models a mass balance in each section; (B) a step of generating a skid model that models a mass balance in each section using the permeation velocity model by a skid model generating unit; (C) a step of generating a manufacturing cost model that models a manufacturing cost required to manufacture a target product using the skid model by a manufacturing cost generating unit; and (D) a step of calculating an optimal design condition by an optimal condition calculating unit using at least one of the permeation velocity model, the skid model, and the manufacturing cost model.

[0014] In addition, preferably, the plurality of sections according to one embodiment of the present disclosure includes a first section which is a permeate zone, a second section which is a permeate recycle zone, and a third section which is a diafiltration zone, and the optimal condition calculation unit calculates a transmembrane pressure (TMP) and the number of skids (N) arranged in the first section. Z1 ), the number of skids (N) arranged in the second section Z2 ), the number of skids (N) placed in the third section Z3 ) and the DF ratio are changed to calculate the optimal design conditions, and the DF ratio is the mass ratio of the fermentation liquid to the water injected into the above-mentioned filtration section.

[0015] Also, preferably, the penetration rate in the first section according to one embodiment of the present disclosure is the concentration factor (F C ) and the transmembrane pressure (TMP), and the permeation rate in the second section and the penetration rate in the third section is the above concentration factor (F C ), the transmembrane pressure (TMP) and the dilution factor (F D ) is determined by, and the step (A) is, (a1) the data collection module of the transmission speed model generation unit determines the transmission speed in the first section , concentration factor (F C ) and transmembrane pressure (TMP), the permeation rate in the second section , concentration factor (F C ), dilution factor (F D ) and transmembrane pressure (TMP), and the permeation velocity in the third section. , concentration factor (F C ), dilution factor (F D) and a step of receiving experimental results including transmembrane pressure (TMP); and (a2) a parameter fitting module of the permeation velocity model generation unit; and (a3) ​​a step of receiving experimental results including transmembrane pressure (TMP); and (a4) a step of receiving experimental results including transmembrane pressure (TMP); and (a5) a step of receiving experimental results including experimental results including experimental results including experimental results including experimental results; and (a6) a step of receiving experimental results including experimental results including experimental results; and (a7) a step of receiving experimental results including experimental results including experimental results; and (a8) a step of receiving experimental results including experimental results including experimental results; and (a9) a step of receiving experimental results including experimental results including experimental results; and (a10) a step of receiving experimental results including experimental results including experimental results; and (a11) a step of receiving experimental results including experimental results; and (a12) a step of receiving experimental results including experimental results; and (a13) a step of receiving experimental results including experimental results; and (a14) a step of and concentration factor (F C ) A permeation velocity model representing the relationship between the second section and the third section, and the permeation velocity in the second section and the third section and concentration factor (F C ) and the dilution factor (F D ) includes a step of modeling a penetration velocity model representing the relationship between the two.

[0016] In addition, preferably, step (B) according to one embodiment of the present disclosure, (b1) the initial condition input module of the skid model generation unit inputs the volume flow rate of the input liquid of the first skid of the first section. , target product mass flow rate and cell mass flow rate A step of receiving initial conditions including; (b2) a step of the material balance calculation module of the skid model generation unit calculating the material balance of the first section using the permeation velocity model of the first section and the initial conditions in a preset manner; (b3) a step of the material balance calculation module of the skid model generation unit calculating the material balance of the second section using the permeation velocity model of the second section and the material balance of the first section in a preset manner; and (b4) a step of the material balance calculation module of the skid model generation unit calculating the material balance of the third section using the permeation velocity model of the third section and the material balance of the second section in a preset manner.

[0017] In addition, preferably, the step (C) according to an embodiment of the present disclosure includes: (c1) a step in which a fixed cost input module of the manufacturing cost model generation unit receives a fixed cost; (c2) a step in which a variable cost calculation module of the manufacturing cost model generation unit calculates a target product cost; (c3) a step in which a variable cost calculation module of the manufacturing cost model generation unit calculates a steam cost; and (c4) a step in which the manufacturing cost model generation unit generates a manufacturing cost model using the costs calculated by steps (c1) to (c3); wherein the fixed cost includes an installation cost, depreciation, and labor cost, the variable cost includes a target product cost and a steam cost, the target product cost is calculated using a preset method using an input flow rate of a first skid of the first section and a flow rate of a permeate of a last skid of the third section, and the steam cost is calculated using a preset method using the DF ratio.

[0018] In addition, preferably, the step (D) according to one embodiment of the present disclosure includes: (d1) a step in which the optimal TMP calculation module of the optimal condition calculation unit calculates an optimal TMP that minimizes the manufacturing cost using the skid model and the manufacturing cost model; (d2) a step in which the optimal skid number calculation module of the optimal condition calculation unit calculates an optimal skid number that minimizes the manufacturing cost using the skid model and the manufacturing cost model; and (d3) a step in which the optimal DF ratio calculation module of the optimal condition calculation unit calculates an optimal DF ratio that minimizes the manufacturing cost using the skid model and the manufacturing cost model.

[0019] According to another embodiment of the present disclosure, a system for calculating optimal design conditions of a continuous membrane separation process including a plurality of sections, each section including one or more skids, is provided, the system including: a permeation rate model generation unit that models a permeation rate of each section; a skid model generation unit that calculates a mass balance of the continuous membrane separation process using the permeation rate model modeled by the permeation rate model generation unit, thereby generating a skid model; a manufacturing cost model generation unit that calculates a manufacturing cost required to manufacture a target product using the skid model, thereby generating a manufacturing cost model; and an optimal condition calculation unit that calculates optimal conditions using the permeation rate model, the skid model, and the manufacturing cost model.

[0020] In addition, preferably, the plurality of sections according to another embodiment includes a first section which is a permeate zone, a second section which is a permeate recycle zone, and a third section which is a diafiltration zone, and the optimal condition calculation unit calculates the transmembrane pressure (TMP), the number of skids (N) arranged in the first section Z1 ), the number of skids (N) arranged in the second section Z2 ), the number of skids (N) placed in the third section Z3 ) and the DF ratio are changed to calculate the optimal design conditions, and the DF ratio is the mass ratio of the fermentation liquid to the water injected into the above-mentioned filtration section.

[0021] Also, preferably, the penetration rate in the first section according to another embodiment is the concentration factor (F C ) and the transmembrane pressure (TMP), and the permeation rate in the second section and the penetration rate in the third section is the above concentration factor (F C), the transmembrane pressure (TMP) and the dilution factor (F D ) is determined by the transmission velocity model generation unit, and the transmission velocity in the first section , concentration factor (F C ) and transmembrane pressure (TMP), the permeation rate in the second section , concentration factor (F C ), dilution factor (F D ) and transmembrane pressure (TMP), and the permeation velocity in the third section. , concentration factor (F C ), dilution factor (F D ) and a data collection module that receives experimental results including transmembrane pressure (TMP); and the permeation velocity in the first section. and concentration factor (F C ) and model the penetration velocity model representing the relationship between the second section and the third section. and concentration factor (F C ), dilution factor (F D ) and a parameter fitting module that models a penetration velocity model representing the relationship between the two.

[0022] In addition, preferably, the skid model generation unit according to another embodiment is configured to generate a volume flow rate of the input liquid of the first skid of the first section. , target product mass flow rate and cell mass flow rate An initial condition input module for receiving initial conditions including; and a material balance calculation module for calculating a material balance of the first section using a permeation rate model and the initial conditions in the first section in a preset manner, calculating a material balance of the second section using a permeation rate model in the second section and the material balance of the first section in a preset manner, and calculating a material balance of the third section using a permeation rate model in the third section and the material balance of the second section in a preset manner.

[0023] In addition, preferably, the manufacturing cost model generation unit according to another embodiment includes a fixed cost input module for receiving a fixed cost; and a variable cost calculation module for calculating a variable cost, wherein the fixed cost includes installation cost, depreciation, and labor cost, the variable cost includes a target product cost and a steam cost, and the target product cost is calculated using a preset method using the input flow rate of the first skid of the first section and the flow rate of the permeate of the last skid of the third section, and the steam cost is calculated using a preset method using the DF ratio.

[0024] According to another embodiment of the present disclosure, there is provided a permeate zone, N Z1 A first section comprising a dog skid; a permeate recycle zone, and N Z2 A second section comprising a dog skid; and a diafiltration zone, N Z3 A system for modeling a continuous membrane separation process including a third section including a dog skid, wherein the material balance of the first section is calculated, wherein the material balance of the first section is a solution of [Mathematical Equations 1] to [Mathematical Equations 9], 1≤i≤N z1 It provides a system that is computed by repeatedly computing for i.

[0025] Also, preferably, the system according to another embodiment calculates the material balance of the second section, wherein the material balance of the second section is a solution of [Mathematical Formula 4], [Mathematical Formula 5] and [Mathematical Formula 10] to [Mathematical Formula 16], 1≤i≤N z2 It is calculated by repeating the operation for i.

[0026] Also, preferably, the system according to another embodiment calculates the material balance of the third section, wherein the material balance of the third section is a solution of [Mathematical Formula 4] and [Mathematical Formula 13] to [Mathematical Formula 19], 1≤i≤N z3It is calculated by repeating the operation for i.

[0027]

[0028] As described above, according to one embodiment of the present disclosure, the material balance in each section is used, and the type of fermentation liquid, membrane area, and concentration factor (VCF, F C ), dilution factor (F D ), TMP, etc. can be considered, and it has the effect of being able to derive modeling close to actual results.

[0029] In addition, by using a penetration velocity model, a skid model, and a manufacturing cost model modeled using the same, the manufacturing cost of the target product is calculated more accurately.

[0030] In addition, the optimal condition calculation unit calculates the optimal number of skids by varying the weights of the penetration rate model, which has the effect of being able to reconstruct a situation in which the penetration rate of the fermentation liquid changes.

[0031]

[0032] Figure 1 is an example of a conceptual diagram of a continuous membrane separation process having a 4-2-2 configuration for treating a microbial fermentation solution.

[0033] FIG. 2 is a flowchart of a membrane separation process design method according to one embodiment of the present disclosure.

[0034] FIG. 3 is a block diagram of a membrane separation process design system according to one embodiment of the present disclosure.

[0035] FIG. 4 is a detailed flowchart of a penetration velocity model generation step according to one embodiment of the present disclosure.

[0036] Figure 5 shows the result of fitting parameters by a penetration velocity model generation unit according to one embodiment of the present disclosure.

[0037] FIG. 6 is a detailed flowchart of a skid model generation step according to one embodiment of the present disclosure.

[0038] FIG. 7 is a flowchart showing a skid model generation unit calculating material balance according to one embodiment of the present disclosure.

[0039] Figures 8 to 10 are conceptual diagrams for explaining the equation described in Figure 7.

[0040] FIG. 11 is a detailed flowchart of a manufacturing cost model generation step according to one embodiment of the present disclosure.

[0041] Figure 12 is a detailed flowchart of an optimal design condition calculation step according to one embodiment of the present disclosure.

[0042] Figures 13 and 14 are calculation results of an optimal condition calculation unit according to one embodiment of the present disclosure.

[0043]

[0044] Hereinafter, some embodiments of the present disclosure will be described in detail with reference to exemplary drawings. When designating components in each drawing, it should be noted that, where possible, identical components are given identical reference numerals, even if they appear in different drawings. Furthermore, in describing the present disclosure, detailed descriptions of related known structures or functions will be omitted if they are deemed to obscure the gist of the present disclosure.

[0045] In describing components of embodiments according to the present disclosure, symbols such as first, second, i), ii), a), b) may be used. These symbols are only for distinguishing the components from other components, and the nature, order, or sequence of the components are not limited by the symbols. When a part in the specification is said to "include" or "have" a component, this does not mean that other components are excluded, but rather that other components may be included, unless explicitly stated otherwise.

[0046]

[0047] In the present disclosure, “permeation rate” means the linear velocity of a solution (fermentation liquid) passing through one skid.

[0048] Additionally, in this disclosure, the term "skid model" refers to a model that includes all skids in each section. Therefore, the skid model in this disclosure should be viewed as referring to the configuration of a continuous membrane separation process, rather than a single skid.

[0049] Also, in the present disclosure, the "initial condition" is the volume flow rate of the input liquid of the first skid of zone 1. , target product mass flow rate and cell mass flow rate Includes.

[0050] In addition, in the present disclosure, "optimal" means a condition in which the cost used to obtain the desired product through a continuous membrane separation process by fermenting a fermentation liquid containing microorganisms is minimized. In the present disclosure, the decision variables determined through optimization are TMP, the number of skids in each section (N Z1 ,N Z2 ,N Z3 ) and DF ratio, but it should be noted that the variables may change depending on the case.

[0051]

[0052] 1. Configuration of continuous membrane separation process

[0053] Figure 1 is an example of a conceptual diagram of a continuous membrane separation process having a 4-2-2 configuration for treating a microbial fermentation solution.

[0054] Referring to FIG. 1, a continuous membrane separation process that a membrane separation process design system (1) according to one embodiment of the present disclosure seeks to model is described.

[0055] Referring to FIG. 1, the continuous membrane separation process includes zone 1, zone 2, and zone 3.

[0056] Zone 1 is conventionally referred to as the permeate zone, where the desired product (hereinafter referred to as the "target product") is recovered as permeate and transferred to a subsequent process for manufacturing the product. In zone 1, the cells are concentrated in the retentate and mixed with the feed of zone 2.

[0057] Zone 2 is commonly referred to as the permeate recycle zone, and the feed from zone 1 is mixed with the recycle permeate from zone 3 as a buffer, and then re-separated. Like the permeate from zone 1, the permeate from zone 2 is transferred to a downstream process to manufacture a product. In addition, the cells are concentrated in the retentate and mixed with the feed from zone 3.

[0058] Zone 3 is conventionally referred to as the diafiltration zone, and the feed from zone 2 is mixed with water as a buffer, re-separated, and diafiltration is performed. The recycle permeate from zone 3 is circulated to be used as a buffer for zone 2, and the residual solution containing the cells is passed to a subsequent process for treating the cells.

[0059]

[0060] One or more skids are arranged in a section. A skid is a structure that combines a process device (e.g., a membrane) and a frame.

[0061] One or more skids are connected in series. A solution containing solutes (cells, target product) and a solvent is fed into the skids as feed, which is then separated into permeate and retentate via membrane separation. The retentate from one skid becomes the feed for the next skid. Furthermore, the retentate from one skid is either transferred to the next process or becomes the feed for another skid.

[0062]

[0063] Although the present disclosure illustrates that four skids are arranged in zone 1 and two skids are arranged in zones 2 and 3, this is merely an example, and the present disclosure describes a mathematical modeling method that can determine how many skids should be arranged in each zone (zone 1, 2, 3) to be most economical.

[0064] Hereinafter, a method for modeling a membrane separation process is described, which is formed of a plurality of sections as disclosed in FIG. 1, and in which one or more skids are arranged in each section (zone 1, 2, 3).

[0065]

[0066] 2. Description of the membrane separation process design system

[0067] FIG. 2 is a flowchart of a membrane separation process design method according to one embodiment of the present disclosure. FIG. 3 is a block diagram of a membrane separation process design system according to one embodiment of the present disclosure.

[0068] Referring to FIGS. 2 and 3, a membrane separation process design system (1) according to one embodiment of the present disclosure simulates a membrane separation process and can determine a scenario with optimal economic feasibility by calculating the cost for each scenario.

[0069] To this end, a membrane separation process design system (1) according to one embodiment of the present disclosure includes all or part of a permeation velocity model generation unit (10), a skid model generation unit (12), a manufacturing cost model generation unit (14), and an optimal condition calculation unit (16).

[0070] The general order in which the membrane separation process is designed by each part is as follows.

[0071] First, the penetration velocity model generation unit (10) generates a penetration velocity model (S200).

[0072] Then, the skid model generation unit (12) generates a skid model using the penetration velocity model (S210).

[0073] Then, the manufacturing cost model generation unit (14) generates a manufacturing cost model using the skid model (S220).

[0074] Finally, the optimal condition calculation unit (16) calculates the optimal design conditions using the manufacturing cost model (S230).

[0075] At this time, the optimal condition calculation unit (16) can further utilize the penetration speed model and skid model when calculating the optimal design conditions.

[0076] Below, each part is explained in detail.

[0077]

[0078] 2.1. Description of the penetration velocity model generation section

[0079] (1) Necessity of a penetration velocity model generation unit

[0080] The membrane separation process can be described by fluid flow. Therefore, if the permeation rate and membrane area in each zone (zones 1, 2, and 3) can be calculated, the mass balance in each zone (zones 1, 2, and 3) can be determined. Therefore, modeling the permeation rate is necessary. Here, the permeation rate is the linear velocity.

[0081] The penetration velocity model generation unit (10) generates the penetration velocity in each section (zone 1, 2, 3). It is configured to model. Meanwhile, the penetration velocity It will be modeled differently depending on the type of solution, more specifically, the type of solvent and solute, and the concentration factor (VCF; F) that represents the properties of the solute in the solution C ) Contrast penetration rate Wow, the dilution factor (F) that indicates the properties of the solvent D ) Contrast penetration rate It is desirable to model it by taking into account .

[0082]

[0083] (2) Steps for creating a penetration velocity model

[0084] The penetration velocity model generation unit (10) may include a data collection module (100) and a parameter fitting module (102). Referring to Fig. 4, the penetration velocity model generation step will be described.

[0085] The data collection module (100) receives experimental results (S400).

[0086] Afterwards, the parameter fitting module (102) models the penetration velocity model in each section (zone 1, 2, 3) using the experimental results received (S410).

[0087] Below, each module and steps S400 and S410 are described in more detail.

[0088]

[0089] (3) Description of data collection module and S400

[0090] Fig. 5 illustrates the results of parameter fitting by a penetration velocity model generation unit according to one embodiment of the present disclosure. Referring to Figs. 3 to 5, the detailed configuration of the penetration velocity model generation unit (10) will be described.

[0091] Penetration rate according to the present disclosure is modeled by a method derived from an empirical formula. For this purpose, the penetration velocity model generation unit (10) may include a data collection module (100) and a parameter fitting module (102).

[0092] The data collection module (100) is configured to receive experimental results in order to model the penetration rate. Meanwhile, the experimental conditions according to the present disclosure are as follows. Here, the experimental results include the penetration rate and the concentration factor (F) in each section (zone 1, 2, and 3). C ) and transmembrane pressure (TMP).

[0093]

[0094] - The target product is lysine or arginine.

[0095] - Contains lysine concentration of 200 g / L and solid content of 2 wt% in fermentation solution containing lysine

[0096] - The ceramic membrane used to measure the permeation rate of the fermentation solution containing lysine is Kerasep BXTM manufactured by Novasep, and the cut-off size is 0.1 μm.

[0097] - Has a 7-channel configuration with a diameter of 6 mm per membrane

[0098] - Arginine concentration of fermented liquid containing arginine 120 g / L, solid content 2 wt%

[0099] - The ceramic membrane used to measure the permeation rate of the fermentation solution containing arginine is INSIDE CeRAMTM manufactured by Tami, and the cut-off size is 0.25 μm.

[0100] - Has a 19-channel configuration with a diameter of 3.5 mm per membrane

[0101] - Initial transmembrane pressure (TMP) is measured in the range of 0.5 bar to 2.0 bar.

[0102]

[0103] (3) Description of parameter meeting module and S410

[0104] The parameter fitting module (102) uses the experimental results collected by the data collection module (100) to create a penetration velocity model for each section. Modeling.

[0105] Meanwhile, the penetration velocity model in zone 1 Silver concentration factor (F C ), can be expressed as a formula according to transmembrane pressure (TMP) and time (t), and the permeation velocity model in zone 2 and zone 3 Silver concentration factor (F C ), transmembrane pressure (TMP) and time (t) and dilution factor (F D ) can be expressed as a formula.

[0106] At this time, the parameter fitting module (102) is F C and F D It is configured to fit other parameters.

[0107]

[0108] (4) Example of the results of the penetration velocity model

[0109] The experimental results of the VCF penetration velocity model under the above conditions are as shown in Fig. 3.

[0110] Specifically, Fig. 3 (a) shows the change in permeation rate according to the VCF of the fermentation solution containing lysine and the fermentation solution containing arginine. Referring to Fig. 3 (a), it is confirmed that the experimental value (labeled exp. in Fig. 3 (a)) and the trend line (labeled calc. in Fig. 3 (a)) when the VCF of the fermentation solution is 3.5 are closest.

[0111] Figure 3 (b) shows the dilution factor (F) when the VCF of the fermentation solution containing lysine and the fermentation solution containing arginine are both 3.5. D) shows the change in relative penetration rate.

[0112]

[0113] Meanwhile, the formulas of the trend lines according to (a) and (b) of Fig. 3, i.e., the mathematical modeling of the regression model, are summarized in [Table 1].

[0114] At this time, the parameters of each regression model are calculated by the parameter fitting module (102). Preferably, parameter fitting can be performed using the least squares method.

[0115] Material target unit penetration rate model Lysine VCF(F C ) Permeation rate change L·m-2·hr-1 Dilution factor (F D ) changes in relative penetration rate - Arginine VCF(F C ) Permeation rate change L·m-2·hr-1 Dilution factor (F D ) changes in relative penetration rate -

[0116] In summary, the penetration velocity model in Table 1 is the result of fitting parameters using the collected experimental data of the penetration velocity model generation unit (10). A skid model can be generated using the above-described penetration velocity model.

[0117] Below, the skid model is described.

[0118]

[0119] 2.2. Description of the skid model generation section

[0120] (1) Necessity of skid model generation unit

[0121] If the permeation velocity model for each skid is modeled by the permeation velocity model generation unit (10), the material balance for the skid can be modeled using this. Meanwhile, since the manufacturing cost can be determined by knowing the number of skids in each section, it is necessary to model the number of skids in each section.

[0122] The skid model generation unit (12) is configured to calculate the number of skids in each section (zone 1, 2, 3) using the permeation velocity model modeled by the permeation velocity model generation unit (10). At this time, modeling is possible using the material balance between skids within each section (zone 1, 2, 3) and the material balance relationship between each section (zone 1, 2, 3). Meanwhile, the process of calculating the material balance includes the process of calculating numerical solutions to a number of equations.

[0123]

[0124] (2) Steps for creating a skid model

[0125] The skid model generation unit (12) may include an initial condition input module (120) and a material balance calculation module (122). Referring to Fig. 6, the skid model generation step is described.

[0126] Initial conditions are input into the initial condition input module (120) (S600). At this time, the initial conditions are the volume flow rate of the input liquid of the first skid of the first section. , target product mass flow rate and cell mass flow rate may include.

[0127] Afterwards, the material balance calculation module (122) calculates the material balance of section 1 (S610).

[0128] Additionally, the material balance calculation module (122) calculates the material balance of section 2 (S620).

[0129] Additionally, the material balance calculation module (122) calculates the material balance of section 3 (S630).

[0130] Below, each module and steps S600 to S630 are described in more detail.

[0131]

[0132] (3) Description of initial condition input module and S600

[0133] As previously explained, the skid modeling process can be performed through material balance calculations, which can be performed by numerically solving multiple equations. Therefore, initial conditions must be input.

[0134] The initial condition input module (120) is configured to receive the above-mentioned initial conditions.

[0135]

[0136] (4) Description of the material balance calculation module

[0137] Fig. 7 is a flowchart illustrating a skid model generation unit calculating a material balance according to one embodiment of the present disclosure. Figs. 8 to 10 are conceptual diagrams illustrating the equations described in Fig. 7.

[0138] Using FIGS. 7 to 10, the method by which the material balance calculation module (122) calculates the material balance is described.

[0139]

[0140] (5) Description of the material balance calculation method (S610) for section 1

[0141] First, referring to FIGS. 7 and 8, a method for calculating the material balance of zone 1 is described.

[0142] To calculate the material balance, the number of skids (N) in each section (zone 1, 2, 3) Z1 ,N Z2 ,N Z3 ) and the membrane area of ​​the skid (A i ) must be defined. In addition, the volume flow rate for the initial input (i.e., the input of the first skid in zone 1) , target product mass flow rate and mass flow rate of the cells This should be defined. Meanwhile, in the present disclosure, the volume flow rate, the mass flow rate of the target product, and the mass flow rate of the cells are collectively referred to as 'flow rate'.

[0143] The above-mentioned number, membrane area, volume flow rate, and mass flow rate are input into the initial condition input module (120).

[0144] The flow rate of the input liquid of the first skid of zone 1, i.e., the permeate zone, is the initial condition input into the initial condition input module (120). . Meanwhile, the second skid or N z1 The flow rate of the feed of the i-th skid is equal to the retentate of the previous skid, and satisfies [Mathematical Formula 1] to [Mathematical Formula 3]. Meanwhile, the subscript i denotes the i-th skid.

[0145]

[0146]

[0147]

[0148]

[0149]

[0150]

[0151]

[0152]

[0153]

[0154]

[0155] By repeatedly calculating the material balance in the above-mentioned zones 1 to 3, each flow rate converges to a certain value, and the flow of fluid in the desired arrangement and configuration of the skid is modeled.

[0156] As described above, the skid configuration and arrangement are modeled using the material balance in each section (zone 1, 2, 3), including the type of fermentation liquid (more precisely, the type of target product), membrane area, and concentration factor (VCF, F C ), dilution factor (F D), TMP, etc. can be considered, and it has the effect of being able to derive modeling close to actual results.

[0157]

[0158] 2.3. Description of the Manufacturing Cost Model Generation Section

[0159] (1) Steps for creating a manufacturing cost model

[0160] The manufacturing cost model generation unit (14) is configured to calculate the manufacturing cost using the skid model generated by the skid model generation unit (12).

[0161] The manufacturing cost model generation unit (14) may include a fixed cost input module (140) and a variable cost calculation module (142) (see FIG. 3). The manufacturing cost model generation steps will be described with reference to FIG. 11.

[0162] Fixed costs are input into the fixed cost input module (140) (S1100).

[0163] The variable cost calculation module (142) calculates the cost of the target product using the skid model (S1110).

[0164] The variable cost calculation module (142) calculates the steam cost using the skid model and DF ratio (S1120).

[0165] The manufacturing cost model generation unit generates a manufacturing cost model by adding up the costs calculated by steps S1100 to S1120 (S1130).

[0166] Below, each module and steps S1100 to S1130 are described in more detail.

[0167]

[0168] (2) Description of fixed cost input module and S1100

[0169] The fixed cost input module (140) is configured to receive fixed costs. Fixed costs may include installation costs, depreciation, labor costs, and other expenses. It should be noted that fixed costs may include other costs in addition to the listed costs.

[0170]

[0171] (3) Description of variable cost calculation module and S1110 to S1130

[0172] The variable cost calculation module (142) is configured to calculate variable costs. Variable costs are composed of the sum of the target product cost, steam cost, and equipment cleaning cost.

[0173] The target product cost is calculated by multiplying the mass of the target material by its unit price and dividing by the target material recovery rate. The target material recovery rate can be calculated from the input flow rate of the first skid in zone 1 and the permeate flow rate of the last skid in zone 3. In other words, the target product cost can be determined from the skid model.

[0174] Steam cost is calculated by dividing the mass of the filtration buffer by the steam economy (the mass of water that can be evaporated with a unit mass of steam) and multiplying by the unit price of steam. The mass of the filtration buffer can be calculated from the DF ratio.

[0175] In summary, the variable cost calculation module (142) calculates variable costs using a skid model, and the manufacturing cost model generation unit (14) can obtain a total manufacturing cost model by combining the fixed costs input into the fixed cost input module (140) and the variable costs calculated by the variable cost calculation module (142).

[0176] Due to the above configuration, according to one embodiment of the present disclosure, there is an effect that the manufacturing cost of the target product can be calculated more accurately.

[0177]

[0178] 2.4. Description of the optimal condition calculation unit

[0179] (1) Composition of the optimal condition calculation unit

[0180] Referring to FIG. 3, the optimal condition calculation unit (16) is configured to calculate optimal conditions using the skid model generated by the skid model generation unit (12) and the manufacturing cost model generated by the manufacturing cost model generation unit (14). At this time, in order to determine the optimal conditions, an optimal TMP calculation module (160), an optimal skid number calculation module (162), and an optimal DF ratio calculation module (164) may be included.

[0181]

[0182] (2) Optimal condition calculation step

[0183] Referring to Figure 12, the optimal condition calculation step is described.

[0184] The optimal TMP calculation module (160) calculates the optimal TMP using at least one of a skid model and a manufacturing cost model (S1210).

[0185] The optimal skid number calculation module (162) calculates the optimal skid number using at least one of the skid model and the manufacturing cost model (S1220).

[0186] The optimal DF ratio calculation module (164) calculates the optimal DF ratio using at least one of the skid model and the manufacturing cost model (S1230).

[0187] Below, each module and steps S1210 to S1230 are described in more detail.

[0188]

[0189] (3) Description of the optimal TMP operation module and S1210

[0190] As explained above, the permeation rate in all sections (zones 1, 2, and 3) is dependent on the transmembrane pressure (TMP). Therefore, by changing the transmembrane pressure, the permeation rate model can be changed, and accordingly, the skid model and manufacturing cost can be changed. In this case, the number of skids (N) in each section (zones 1, 2, and 3) Z1 ,N Z2 ,NZ3 ), and the DF ratio is fixed.

[0191] The optimal TMP calculation module (160) is configured to calculate the optimal TMP. To this end, the optimal TMP calculation module (160) uses the minimum value (e.g., 0.5 bar), maximum value (e.g., 2 bar), and number of divisions (e.g., 5) of the TMP. The manufacturing cost is calculated for the case where the TMP increases from the minimum value to the maximum value by the value (maximum value - minimum value) / number of divisions.

[0192] When applied to the above example, the optimal TMP calculation module (160) is configured to calculate the values ​​of the changing TMP (i.e., 0.5 bar, 0.8 bar, 1.1 bar, 1.4 bar, 1.7 bar and 2.0 bar), the number of predetermined skids (N Z1 ,N Z2 ,N Z3 ) and DF ratio into the skid model generation unit (12) and the manufacturing cost model generation unit (14), so that the manufacturing cost at each TMP value can be calculated.

[0193]

[0194] (4) Description of the optimal skid count calculation module and S1220

[0195] Number of skids (N) in each section (zone 1, 2, 3) Z1 ,N Z2 ,N Z3 ) the skid model is different. Therefore, the number of skids (N) in each section (zone 1, 2, 3) Z1 ,N Z2 ,N Z3 ) changes the skid model, and the manufacturing cost changes accordingly. In this case, the TMP and DF ratios are fixed.

[0196] The optimal skid number calculation module (162) calculates the optimal number of skids (N Z1 ,N Z2 ,N Z3) is configured to calculate. To this end, the optimal skid count calculation module (162) calculates the number of skids (N) in zone 1. Z1 ) and set the minimum and maximum values, and the number of skids in zone 1 (N Z1 ) Calculate the manufacturing cost for the case where the number increases by 1 from the minimum to the maximum.

[0197] In addition, the optimal skid count calculation module (162) calculates the number of skids (N) in zone 2. Z2 ) and set the minimum and maximum values, and the number of skids (N) in zone 2 Z2 ) Calculate the manufacturing cost for the case where the number increases by 1 from the minimum to the maximum.

[0198] In addition, the optimal skid count calculation module (162) calculates the number of skids (N) in zone 3. Z3 ) and set the minimum and maximum values, and the number of skids in zone 3 (N Z3 ) Calculate the manufacturing cost for the case where the number increases by 1 from the minimum to the maximum.

[0199] Meanwhile, N Z1 + N Z2 + N Z3 The value of is constant. That is, the number of skids in each section (zone 1, 2, 3) is fixed while the total number of skids is fixed (N Z1 ,N Z2 ,N Z3 ) to find the optimal manufacturing cost.

[0200]

[0201] An optimal skid count calculation module (162) according to one embodiment of the present disclosure calculates the optimal number of skids (N Z1 ,N Z2 ,N Z3 ) is shown in Fig. 13. Specifically, Fig. 8 shows the manufacturing cost in a skid model modeling the membrane separation process of a fermentation liquid containing lysine.

[0202] At this time, the conditions considered are as follows:

[0203] - The volume flow rate of the initial input is 40 kl / hr, the unit price of lysine is 1000 USD / ton, and the unit price of steam is 30 USD / ton.

[0204] - The total number of skids is fixed at 8.

[0205] - The membrane area of ​​all skids is 200 m 2

[0206] - Concentration factor (VCF, F) C ) for the cases where the weights of the regression model of the change in penetration rate (i.e., penetration rate model) are 125%, 100%, 75%, and 50%, respectively, and the manufacturing cost is calculated.

[0207]

[0208] Meanwhile, the reason for differentiating the weights of the permeation velocity model among the considered conditions is that even when producing the same product, cases such as changes in the properties of the fermented liquid depending on the results of the fermentation process, changes in the product being produced, changes in raw materials, and changes in the membrane can occur in real situations, and all of these cases are to be considered.

[0209] Figure 13 (a) shows the number of skids (N) in each section (zone 1, 2, 3) when the weight of the penetration velocity model is 125%. Z1 ,N Z2 ,N Z3 ) is the manufacturing cost.

[0210] (b) of Fig. 13 shows the number of skids (N) in each section (zone 1, 2, 3) when the weight of the penetration velocity model is 100%, (c) shows the number of skids (N) in each section (zone 1, 2, 3) when the weight of the penetration velocity model is 75%, and (d) shows the number of skids (N) in each section (zone 1, 2, 3) when the weight of the penetration velocity model is 50%. Z1 ,N Z2 ,N Z3 ) is the manufacturing cost.

[0211] Referring to the figure, the optimal number of skids (N) is obtained when the weights of the penetration velocity model are 125%, 100%, 75%, and 50%, respectively. Z1 ,N Z2 ,N Z3 ) were 2-2-3, 3-3-2, 2-4-2, and 1-6-1. The respective costs at this time were USD 1019 / ton, USD 1028 / ton, USD 1062 / ton, and USD 1184 / ton. This shows that the membrane separation process, which can reconstruct the situation in which the permeation rate of the fermentation liquid changes, has an economic effect.

[0212]

[0213] (5) Description of the optimal DF ratio calculation module and S1230

[0214] The DF ratio refers to the dilution factor (DF), which is the mass ratio of water used to dilute the fermentation solution to the fermentation solution. As explained above, the permeation rate of the permeate in zone 2 and zone 3 ( ) is the concentration factor and the dilution factor (F D ) are all affected. Accordingly, the skid model may be different depending on the ratio of the dilution factor. Therefore, the skid model changes as the DF ratio changes, and the manufacturing cost changes accordingly. In this case, the TMP and the number of skids (N) in each section (zone 1, 2, 3) Z1 ,N Z2 ,N Z3 ) is fixed.

[0215] The optimal DF ratio calculation module (164) is configured to calculate the optimal DF ratio. To this end, the optimal DF ratio calculation module (164) uses the minimum value (e.g., 10%), maximum value (e.g., 60%), and number of divisions (e.g., 6) of the DF ratio. The manufacturing cost is calculated for the case where the DF ratio increases from the minimum value to the maximum value by the value (maximum value - minimum value) / number of divisions.

[0216] When applied to the above example, the optimal DF ratio calculation module (164) calculates the values ​​of the changing DF ratio (i.e., 10%, 20%, 30%, 40%, 50%, and 60%), the number of predetermined skids (N Z1 ,N Z2 ,N Z3 ) and TMP can be input into the skid model generation unit (12) and the manufacturing cost model generation unit (14) to calculate the manufacturing cost at each DF ratio.

[0217]

[0218] The result of calculating the optimal DF ratio by the optimal DF ratio calculation module (164) according to one embodiment of the present disclosure is shown in FIG. 14.

[0219] Specifically, (a) of Fig. 14 shows the manufacturing cost in a skid model that models the membrane separation process of a fermentation liquid containing lysine.

[0220] At this time, the conditions considered are as follows:

[0221] - Number of skids in zone 1 (N) Z1 ) is 4, the number of skids in zone 2 (N) Z2 ) is 2, the number of skids in zone 3 (N) Z3 ) is 2

[0222] - The membrane area of ​​all skids is 200 m 2

[0223] - The unit price of lysine was 1000 USD / ton, the unit price of steam was 30 USD / ton, the steam economy was 5, and the maximum allowable VCF was 8.

[0224] - Calculate the manufacturing cost when the volume flow rate of the fermentation liquid containing lysine is 30, 34, 38, and 42 kl / hr.

[0225] Referring to (a) of Fig. 14, the optimal DF ratios were 31, 35, 38, and 41% when the initial volume flow rates were 30, 34, 38, and 42 kl / hr, respectively. The manufacturing costs at these times were 1018 USD / ton, 1022 USD / ton, 1027 USD / ton, and 1033 USD / ton, respectively.

[0226]

[0227] Figure 14 (b) shows the manufacturing cost in a skid model that models the membrane separation process of a fermentation liquid containing arginine.

[0228] At this time, the conditions considered are as follows:

[0229] - Number of skids in zone 1 (N) Z1 ) is the number of skids in zone 2 (N) Z2 ) is 6, the number of skids in zone 3 (N) Z3 ) is 1

[0230] - The membrane area of ​​all skids is 200 m 2

[0231] - The unit price of arginine is 2000 USD / ton, the unit price of steam is 30 USD / ton, the steam economy is 5, and the maximum allowable VCF is 15.

[0232] - Calculation of manufacturing cost for cases where the volume flow rate of the fermentation solution containing arginine is 84, 88, 92, and 96 kl / hr, respectively.

[0233] Referring to Figure 14(b), it can be seen that, unlike the skid model using the fermentation broth containing lysine, the fermentation broth containing arginine does not have an optimal cost at a specific DF ratio. As can be seen in Figure 5, the permeation rate of the fermentation broth containing arginine is greater than that of the fermentation broth containing lysine. Consequently, it can be interpreted that the optimal method is to minimize the DF ratio and operate the membrane separation process until the pipeline becomes clogged.

[0234] The optimal DF ratios were 22%, 3.4%, 0%, and 0% when the initial input volume flow rates were 84, 88, 92, and 96 kl / hr, respectively. The manufacturing costs at these times were 2030 USD / ton, 2074 USD / ton, 2116 USD / ton, and 2177 USD / ton, respectively.

[0235]

[0236] As described above, the membrane separation process design system (1) according to one embodiment of the present disclosure collects data to model a permeation rate model representing the permeation rate in each section, creates a skid model using the permeation rate model, and calculates the manufacturing cost using the created skid model. At this time, the transmembrane pressure (TMP) affecting the skid model and the number of skids (N) in each section (zone 1, 2, 3) are Z1 ,N Z2 ,N Z3 ) and DF ratio, the lowest manufacturing cost can be found by calculating the optimal conditions (optimal TMP, optimal number of skids, optimal DF ratio).

[0237]

[0238] The above description is merely an example of the technical idea of ​​the present embodiment, and those skilled in the art will appreciate that various modifications and variations can be made without departing from the essential characteristics of the present embodiment. Therefore, the present embodiments are not intended to limit the technical idea of ​​the present embodiment, but rather to explain it, and the scope of the technical idea of ​​the present embodiment is not limited by these embodiments. The scope of protection of the present embodiment should be interpreted by the claims below, and all technical ideas within a scope equivalent thereto should be interpreted as being included in the scope of rights of the present embodiment.

[0239]

[0240] (Explanation of symbols)

[0241] 1: Membrane separation process design system

[0242] 10: Transmission velocity model generation section

[0243] 100: Data Collection Module

[0244] 102: Parameter Fitting Module

[0245] 12: Skid model generation section

[0246] 120: Initial condition input section

[0247] 122: Material Balance Calculation Module

[0248] 14: Manufacturing cost model generation section

[0249] 140: Fixed cost input module

[0250] 142: Variable Cost Calculation Module

[0251] 16: Optimal Condition Operation Section

[0252] 160: Optimal TMP operation module

[0253] 162: Optimal skid count calculation module

[0254] 164: Optimal DF ratio calculation module

Claims

1. A method for calculating optimal design conditions for a continuous membrane separation process including multiple sections, each section including one or more skids, (A) The penetration velocity model generation unit generates the penetration velocity of each section. A step for generating a penetration velocity model that models; (B) A step of generating a skid model by a skid model generation unit that models mass balance in each section using the above penetration velocity model; (C) a manufacturing cost model generation unit generating a manufacturing cost model that models the manufacturing cost required to manufacture the target product using the skid model; and (D) A step for calculating optimal design conditions using at least one of the penetration velocity model, the skid model, and the manufacturing cost model, by the optimal condition calculation unit; method.

2. In paragraph 1, The above multiple sections include a first section which is a permeate zone, a second section which is a permeate recycle zone, and a third section which is a diafiltration zone. The above optimal condition calculation section calculates the transmembrane pressure difference (TMP) and the number of skids (N) arranged in the first section. Z1 ), the number of skids (N) arranged in the second section Z2 ), the number of skids (N) arranged in the third section Z3 ) and calculate the optimal design conditions by changing the DF ratio. The above DF ratio is the mass ratio of the fermented liquid to the water injected into the above-mentioned filtration section. method.

3. In paragraph 2, Penetration rate in the above first section is the concentration factor (F C ) and is determined by the transmembrane pressure (TMP), Penetration rate in the above second section and the penetration speed in the third section is the above concentration factor (F C ), the transmembrane pressure (TMP) and the dilution factor (F D ) is determined by, Step (A) above, (a1) The data collection module of the above penetration velocity model generation unit determines the penetration velocity in the first section. , concentration factor (F C ) and transmembrane pressure (TMP), the permeation rate in the second section. , concentration factor (F C ), dilution factor (F D ) and transmembrane pressure (TMP), and the permeation rate in the third section. , concentration factor (F C ), dilution factor (F D ) and a step of receiving experimental results including transmembrane pressure (TMP); and (a2) The parameter fitting module of the above penetration velocity model generation unit calculates the penetration velocity in the first section. And the concentration factor (F C ) A permeation velocity model representing the relationship between the second section and the third section. And the concentration factor (F C ) and the dilution factor (F D ) comprising a step of modeling a penetration velocity model representing the relationship between; method.

4. In paragraph 3, Step (B) above, (b1) The initial condition input module of the above skid model generation section is the volume flow rate of the input liquid of the first skid of the above first section. , target product mass flow rate and cell mass flow rate A step for receiving initial conditions including; (b2) a step in which the material balance calculation module of the skid model generation unit calculates the material balance of the first section using the penetration velocity model and the initial conditions of the first section in a preset manner; (b3) a step in which the material balance calculation module of the skid model generation unit calculates the material balance of the second section using a pre-set method by using the permeation velocity model of the second section and the material balance of the first section; and (b4) a step of calculating the material balance of the third section using the material balance calculation module of the skid model generation unit and the material balance of the second section using a preset method; method.

5. In paragraph 4, Step (C) above, (c1) A step in which the fixed cost input module of the manufacturing cost model generation section receives fixed costs; (c2) A step in which the variable cost calculation module of the manufacturing cost model generation unit calculates the cost of the target product; (c3) a step in which the variable cost calculation module of the manufacturing cost model generation unit calculates the steam cost; and (c4) a step of generating a manufacturing cost model by using the cost calculated by steps (c1) to (c3) above; including, The above fixed costs include installation costs, depreciation and labor costs. The above variable costs include the cost of target products and steam costs. The above target product cost is calculated in a preset manner using the input flow rate of the first skid of the first section and the flow rate of the permeate of the last skid of the third section. The above steam cost is calculated in a preset manner using the above DF ratio. method.

6. In paragraph 2, Step (D) above (d1) a step in which the optimal TMP calculation module of the optimal condition calculation unit calculates the optimal TMP that minimizes the manufacturing cost using the skid model and the manufacturing cost model; (d2) a step in which the optimal skid number calculation module of the optimal condition calculation unit calculates the optimal skid number that minimizes the manufacturing cost using the skid model and the manufacturing cost model; and (d3) a step in which the optimal DF ratio calculation module of the optimal condition calculation unit calculates the optimal DF ratio that minimizes the manufacturing cost using the skid model and the manufacturing cost model; method.

7. A system for calculating optimal design conditions of a continuous membrane separation process including multiple sections, each section including one or more skids, A penetration velocity model generation unit that models the penetration velocity of each section above; A skid model generation unit that generates a skid model by calculating the mass balance of the continuous membrane separation process using the permeation rate model modeled by the permeation rate model generation unit; A manufacturing cost model generation unit that generates a manufacturing cost model by calculating the manufacturing cost required to manufacture the target product using the above skid model; and Including an optimal condition calculation unit that calculates optimal conditions using the above penetration speed model, the skid model, and the manufacturing cost model. System.

8. In paragraph 7, The above multiple sections include a first section which is a permeate zone, a second section which is a permeate recycle zone, and a third section which is a diafiltration zone. The above optimal condition calculation section calculates the transmembrane pressure difference (TMP) and the number of skids (N) arranged in the first section. Z1 ), the number of skids (N) arranged in the second section Z2 ), the number of skids (N) arranged in the third section Z3 ) and calculate the optimal design conditions by changing the DF ratio. The above DF ratio is the mass ratio of the fermented liquid to the water injected into the above-mentioned filtration section. System.

9. In paragraph 8, Penetration rate in the above first section is the concentration factor (F C ) and is determined by the transmembrane pressure (TMP), Penetration rate in the above second section and the penetration speed in the third section is the above concentration factor (F C ), the transmembrane pressure (TMP) and the dilution factor (F D ) is determined by, The above penetration velocity model generation unit is, Penetration rate in the above first section , concentration factor (F C ) and transmembrane pressure (TMP), the permeation rate in the second section. , concentration factor (F C ), dilution factor (F D ) and transmembrane pressure (TMP), and the permeation rate in the third section. , concentration factor (F C ), dilution factor (F D ) and a data collection module that receives experimental results including transmembrane pressure (TMP); and Penetration rate in the above first section And the concentration factor (F C ) and model the penetration velocity model representing the relationship between the second section and the third section. And the concentration factor (F C ), dilution factor (F D ), including a parameter fitting module that models a penetration velocity model representing the relationship between System.

10. In paragraph 8, The above skid model generation unit, Volume flow rate of the input liquid of the first skid of the above first section , target product mass flow rate and cell mass flow rate An initial condition input module that receives initial conditions including; and A material balance calculation module comprising: a material balance calculation module that calculates the material balance of the first section using a pre-set method by using the permeation rate model and the initial conditions of the first section; a material balance calculation module that calculates the material balance of the second section using a pre-set method by using the permeation rate model of the second section and the material balance of the first section; and a material balance calculation module that calculates the material balance of the third section using a pre-set method by using the permeation rate model of the third section and the material balance of the second section. System.

11. In paragraph 8, The above manufacturing cost model generation unit, A fixed cost input module for receiving fixed costs; and a variable cost calculation module for calculating variable costs, The above fixed costs include installation costs, depreciation and labor costs. The above variable costs include the cost of target products and steam costs. The above target product cost is calculated in a preset manner using the input flow rate of the first skid of the first section and the flow rate of the permeate of the last skid of the third section. The above steam cost is calculated in a preset manner using the above DF ratio. System.

12. Permeate zone, N Z1 A first section comprising a dog skid; a permeate recycle zone, and N Z2 A second section comprising a dog skid; and a diafiltration zone, N Z3 A system for modeling a continuous membrane separation process comprising a third section comprising a dog skid, Calculate the material balance of the first section, and the material balance of the first section is the solution of [Mathematical Formula 1] to [Mathematical Formula 9], 1≤i≤N z1 It is computed by repeatedly computing for i, [Mathematical Formula 1] [Mathematical formula 2] [Mathematical Formula 3] [Mathematical Formula 4] [Mathematical Formula 5] [Mathematical Formula 6] [Mathematical formula 7] [Mathematical formula 8] [Mathematical formula 9] - At this time, is the feed volume flow rate of the i-th skid, is the volume flow rate of the retentate of the ith skid, is the volume flow rate of the permeate of the ith skid, is the target product mass flow rate of the input of the i-th skid, is the target product mass flow of the residue of the i-th skid, is the target product mass flow rate of the i-th permeate, is the mass flow rate of the cells in the input solution of the i-th skid, is the mass flow rate of the cells in the residual solution of the i-th skid, is the mass flow rate of the cells in the permeate of the i-th skid, is the concentration factor of the i-th skid, is the permeation rate of the permeate of the i-th skid, is the membrane surface area of ​​the i-th skid - System.

13. In paragraph 12, The material balance of the second section is calculated, and the material balance of the second section is the solution of [Mathematical Formula 4], [Mathematical Formula 5], and [Mathematical Formula 10] to [Mathematical Formula 16], 1≤i≤N z2 It is calculated by repeating the operation for i. [Mathematical Formula 10] [Mathematical Formula 11] [Mathematical formula 12] [Mathematical formula 13] [Mathematical formula 14] [Mathematical Formula 15] [Mathematical formula 16] - At this time, is the volume flow rate of the recycled permeate in the third section, is the mass flow rate of the target product contained in the circulating permeate mixed with the input liquid of the second section, is the dilution factor of the i-th skid - System.

14. In paragraph 13, The material balance of the third section is calculated, and the material balance of the third section is the solution of [Mathematical Formula 4] and [Mathematical Formula 13] to [Mathematical Formula 19], 1≤i≤N z3 It is calculated by repeating the operation for i. [Mathematical formula 17] [Mathematical expression 18] [Mathematical Formula 19] - At this time, is the volume flow rate of the buffer in the third section - System.

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