JP4716684B2 - Wastewater treatment simulation system - Google Patents

Description

  The present invention relates to a wastewater treatment simulation system used for processing behavior prediction, analysis, control, facility design, and operation plan formulation of a wastewater treatment facility.

  In recent years, drainage standards have become stricter to prevent environmental enrichment in closed areas. As a method for removing BOD in wastewater at a low cost, there is an activated sludge method. Further, as a method for biologically removing nitrogen and phosphorus, AO and A2O methods for changing the flora in sludge by anaerobic aerobic circulation Is well known.

  Regarding nitrogen removal, the mechanism of nitrification of ammonia by absolute aerobic nitrifying bacteria in an aerobic environment and denitrification by denitrifying bacteria in an anaerobic environment is different and the mechanism is clear. There is no major problem other than cost.

  However, with regard to phosphorus removal, the mechanism of action of the phosphorus-accumulating bacteria responsible for phosphorus removal is complicated, so that much effort is required for the device design, operation condition determination, and stable operation. In general, phosphorus-accumulating bacteria preferentially ingest nutrients to other bacteria in anaerobic environments using energy that decomposes polyphosphate in the anaerobic environment, and grow in the aerobic environment using organic matter in the body as an energy source It is said that it absorbs activity and ortholine in the fluid and stores it in the body as polyphosphoric acid, but its action has not been fully elucidated.

  In order to quantify biological denitrification and dephosphorization, the “Activated Sludge Model” ASM1, which expresses microbial activity in activated sludge as a mathematical model, has been published by the International Society for Water Environment. Thereafter, version upgrades are repeated, and at present, ASM3 (see, for example, Non-Patent Document 1) is the latest mathematical model. Of these, however, biological phosphorus removal can be calculated in ASM2 (see, for example, Non-Patent Document 2) and ASM2d (see, for example, Non-Patent Document 3), and biological phosphorus removal in the latest ASM3. In order to calculate, a phosphorus accumulating bacteria model option such as Bio-P module published by EAWAG (for example, see Non-Patent Document 4) must be used.

With the popularization of activated sludge models, the quantification of biological wastewater treatment has made great progress, and the movement to perform operation management and equipment design using it has become active. However, since the activated sludge model itself includes a large number of parameters and differential equations, it has a drawback that it is difficult to handle unless it is thoroughly used. Therefore, even if there is no specialized knowledge, as a means to perform quantitative prediction / analysis of treatment equipment using activated sludge model, the specialized part is being made into simulation software as a black box (for example, WEST: registered trademark) , AQUASIM: registered trademark, GPS-X: registered trademark, AquaNavi: registered trademark), and the use opportunities thereof are rapidly increasing.
W. Gujar Wat. Sci. Tech. 39 (1) 183-193 (1999) Wat. Sci. Tech. 31 (2), 1-11 (1995) Henze Wat. Sci. Tech. Vol 39, No. 1, pp165-182 (1999) L. RIEGER Wat. Res. Vol. 35, no. 16, pp 3887-3903 (2001) Tokyo Metropolitan Sewerage Bureau 40th sewer research presentation lecture p192 Hitachi Plant Construction 37th Sewerage Research Presentation Lecture 431 Furuya Journal of Japan Society on Water Environment Vol.23 No. 5 (2000)

  However, the above-described simulation system according to the prior art has a problem that a mixture distribution peculiar to the device structure cannot be expressed. It is known that the mixing distribution in the apparatus is particularly prominent in the dissolved oxygen concentration distribution, whereby the behavior of denitrification and dephosphorization utilizing an anaerobic / aerobic environment is greatly different (Japanese Patent Application No. 2002-298603, Application 2004-021246; applicant Mitsubishi Rayon). Avoiding calculation errors due to the influence by adjusting the parameters of the microbial reaction rate is not an essential measure, and the simulation model is not versatile unless physical factors are modeled.

  As a method of simply expressing the mixture distribution, a method of setting a predetermined ratio of anaerobic regions in the aerobic tank (for example, refer to Non-Patent Document 5), a method of performing enormous calculation by directly connecting to CFD or the like (for example, However, the former is not essential, and the latter has to calculate a gas-liquid two-phase flow. Therefore, the calculation load is enormous and rapid output is impossible.

  As a method of expressing the distribution in the tank without using the above technique, the user can only express the mixed state in the tank by modeling the tank row (see Non-Patent Document 7), but the substance between the tank rows The problem is that it is difficult to guess the movement.

  Further, the second problem is that the specialized part is too black-boxed, and the versatility is lowered. In particular, when using the activated sludge method, it is mainly assumed that a completely mixed state is used, so dissolved and suspended components are handled as being transported uniformly. When expressed, dissolved and suspended components must be configurable so that they can be transferred in any proportion.

  The present invention has been made to solve the above problems, and its purpose is to achieve wastewater treatment behavior considering the mixed distribution state in the apparatus without requiring specialized knowledge, enormous computational load and physical testing. It is to provide a wastewater treatment simulation system that can be predicted.

As a result of intensive investigations, the present inventors have quickly made the airlift swirl flow in the treated water tank by combining two of the many bubble column correlation equations in the chemical engineering field and obtaining the solution by the Monte Carlo method. By finding that a flow rate comparable to the actual swirling flow rate can be estimated, and by constructing a method that optionally uses that method in the wastewater treatment simulation system, the versatility of the wastewater treatment simulation system is improved, leading to the present invention. It was.
That is, the wastewater treatment simulation system according to the present invention inputs the dimensions and aeration conditions of the treatment tank and the upward flow generation portion in the treatment tank, thereby converting the swirling flow rate generated in the tank to the bubble slip speed and the pressure balance. Subroutine (1) where two equations are solved by the Monte Carlo method and the average value of the obtained solution is a swirl flow rate, and a partial tank in which the inside of the tank is virtually divided into several regions and circulation is performed by the swirl flow The subroutine (2) for calculating the composition change in the tank using the column model is provided, and the user can select whether to perform the complete mixing calculation or the air lift swirl flow calculation for an arbitrary processing tank. When the calculation is performed, the outflow composition of the treatment tank is calculated by executing subroutines (1) and (2).

  In addition, it is preferable to gradually reduce the error determination value e for recognizing the assumed swirling flow rate value as a solution during the random number search in the swirling flow calculation. As a result, a highly accurate solution with reduced dispersion can be obtained.

  Furthermore, with respect to the processing tank for executing the airlift swirl flow calculation, it is possible to select the inflow position to the tank and the outflow position from the tank by using the GUI, and each region in the partial tank row model in the subroutine (2) is selected. It is preferable to add a coefficient obtained by multiplying an inflow term from another tank and an outflow term to another tank by a coefficient into the differential equation obtained by formulating the mass balance, and change the coefficient value according to the selected connection position. Thereby, it becomes possible to make it possible to cope with any connection position.

  Furthermore, in these wastewater treatment simulation systems, any one of the IWA activated sludge models ASM1, ASM2, ASM2d, ASM3 and their own activated sludge models in which these phosphorus accumulating bacterial action processes and organic matter accumulating processes are changed for the calculation of the microbial reaction rate. It is preferable to use these.

  Furthermore, in these wastewater treatment simulation systems, when setting that the fluid moves between the treatment tank A and the treatment tank B, in addition to the flow rate, the transfer ratio of the solid content and the dissolved component can be set. It is preferable to keep it. Thereby, when using an activated sludge method, the simulation which does not presuppose a perfect mixing state is attained.

  According to the present invention, the wastewater treatment simulation in the form of the present invention can be applied to the inside of the apparatus with the airlift swirl flow without requiring specialized knowledge in chemical engineering, enormous computational load such as flow analysis, and physical test. It is possible to easily predict the wastewater treatment behavior in consideration of the mixed distribution state, and on the other hand, the user can model various apparatus configurations. Furthermore, even in complex equipment configuration modeling, the calculated values are unlikely to become abnormal values (such as negative values), so the reliability of the calculated values is higher, and the plant operating conditions without trial and error to meet the desired wastewater quality standards The change policy becomes clear and adverse environmental impacts (eutrophication) can be reduced.

  Hereinafter, a wastewater treatment simulation system according to an embodiment of the present invention will be described with reference to the drawings.

FIG. 1 is a schematic block diagram showing a wastewater treatment simulation system according to this embodiment. In the figure, the input unit 1 is the dimensions of the treatment tank and the upflow generation part in the treatment tank (the bottom area of the treatment tank, the liquid depth of the treatment tank, the bottom area of the treatment tank internal upflow region (riser), the treatment tank Enter the distance from the bottom to the lower end of the riser, the distance from the liquid level to the upper end of the riser, the circumference of the lower part of the riser, the installation position of the air diffuser and the aeration condition (aeration air volume).
Note that the treatment tank internal upward flow region (riser) does not necessarily have to be partitioned by a physical partition with the downward flow region. When no partition is provided, for the distance from the bottom of the treatment tank to the lower end of the riser and the distance from the liquid level to the upper end of the riser, the corresponding values are obtained by calculation based on the installation position of the aeration tube and the aeration conditions. .

The bubble slip speed calculation unit 2 calculates the bubble slip speed from the gas / liquid ratio. The gas holdup calculation unit 3 calculates the gas holdup of the riser from the bubble slip speed. The flow path resistance calculation unit 4 calculates the flow path resistance of the swirl flow in the tank from the geometric ratio between the treatment tank and the riser. The in-tank swirling flow rate calculation unit 5 solves two equations of the bubble slip velocity and the pressure balance by the Monte Carlo method, and calculates the average value of the obtained solutions as the swirling flow rate. More specifically, the in-tank swirling flow rate Q1 by the air lift is calculated using random number generation means based on the set value. Then, the bubble slip velocity is calculated from the gas / liquid ratio, and the gas holdup of the riser is calculated. Subsequently, the in-tank swirl flow Q2 is calculated and stored from the flow resistance of the in-tank swirl flow calculated from the gas hold-up of the riser and the geometric ratio between the treatment tank and the riser based on the set value. Then, the preset error e is compared with | Q1-Q2 |, and if e> | Q1-Q2 |, at least one of Q1 and Q2 is stored. The average value of at least one in-tank swirling flow stored by repeating the above assumption of the in-tank swirling flow rate Q1, calculation of the in-tank swirling flow rate Q2, and the magnitude comparison result is used as a representative value. Further, in the process of calculating the representative swirling flow, by gradually subtracting the setting error range, it may be to improve the accuracy of the turning rate value stored.

The composition change calculation unit 6 in the tank has several pieces in the tank when the mixing state selected from at least two types of the complete mixing type and the airlift swirl flow generation type is the airlift swirl flow generation type or the like. And a partial tank array model (differential equation: differential equation group q: dS _{i, j} / dt =) in which the internal liquid circulates in the swirl flow by virtually dividing the region into at least two regions of the aerated portion and the non-aerated portion. {Σ (F _{k, j} * S _{i, k} ) −S _{i, j} * ΣF _{j, m} + R _{i, j} * V _j } / V _j : Si, j: region j i-th component concentration, Fk, j: The flow rate from the region k to the region j, Ri, j: the region j i-th component reaction rate calculated by the microbial mathematical model, Vj: the region j volume), and the inflow composition to the treatment tank and the inflow amount are arguments By substituting as follows, q is solved and the composition change in the tank is calculated. The outflow composition calculation part 7 calculates the outflow composition of this processing tank based on the inflow composition and inflow amount to a processing tank as a part of the composition change calculation part 6 in a tank. The storage unit 8 stores the dimensions and aeration conditions of the treatment tank and the upward flow generation part in the treatment tank, the tank turning flow rate Q1, the tank turning flow rate Q2, the tank turning flow average value, and the like. The display unit 9 displays various menu screens, data input screens, and the like.

  Each unit described above is realized by computer software, and may be a modification of commercially available wastewater treatment simulation software, or newly created simulation software. Here, the wastewater treatment simulation software created using general-purpose programming software will be described as an example.

  Next, the operation of the above-described wastewater treatment simulation system will be described. 2 to 5 are flowcharts for explaining the operation of the wastewater treatment simulation system. 6 to 15 are schematic diagrams showing examples of screens of the wastewater treatment simulation system.

  First, the main screen shown in FIG. 6 is displayed (S1). When “tank setting” is selected from the main menu A on the main screen shown in FIG. 6 (“tank setting” in S2), the tank setting form shown in FIG. 7 is developed (S3). The tank setting form shown in FIG. 7 includes a button B for setting the tank form in addition to setting the tank volume, the liquid temperature, and the aeration condition (S4). On button B, the current tank form is displayed. By default, the tank configuration is “complete mixing tank”.

  Next, when the button B is pressed, the tank-shaped detailed setting form shown in FIG. 8 is developed (S5). In the detailed setting form, in addition to the number of the currently selected tank, the tank form can be selected from the list C. When “MBR with draft tube” is selected in the list C (S6), a panel D shown in FIG. 9 is displayed (S7).

  In panel D, input items necessary for calculating the airlift swirl flow are set (S8). More specifically, in the field D1 shown in FIG. 9, the geometric shape of the aeration tank is input. In the field D2 shown in FIG. 10, an aeration condition is input. Further, in the field D3 shown in FIG. 11, it is possible to select whether the swirling flow rate is manually input or calculated. And in the field D4 shown in FIG. 12, the inflow / outflow position is set by the list E for selecting the inflow position from the other tank and the outflow position to the other tank.

  In this way, the GUI allows the inflow position to the tank and the outflow position from the tank to be selected, and when calculating the swirling flow rate to be described later, the material balance of each region in the partial tank row model is mathematically expressed. In the differential equation, the inflow term from other tanks and the outflow term to other tanks multiplied by a coefficient are added, and the coefficient value is changed according to the selected connection position, so that it can be applied to any connection position. It can be made possible.

  More specifically, the inflow term from the other tank and the outflow term to the other tank are described for the differential equation, and the processing tank divided in terms of calculation is multiplied by the coefficient a in the inflow term and the outflow term. An identification number n is given to the combination of the inflow position from the other tank and the outflow position to the other tank, and the processing tank in which the inflow position and the outflow position corresponding to the recognition number are entered by selecting the identification number n As shown in FIG. Then, the quotient n1 and the remainder n2 obtained by dividing the recognition number n by the division number N in the tank are calculated, and when n1 and n2 are equal to the q-internal differential equation recognition number n representing the region n, a = 1, not equal By returning a = 0 and turning on / off the inflow term and the outflow term of each differential equation in q based on the value of n, it is possible to deal with any inflow position and outflow position.

  Next, after these settings are completed, when the button F shown in FIG. 12 is pressed, it is determined whether or not manual input is selected in the field D3 (S9). When manual input is selected in the field D3, the input value is directly used as the turning flow rate (S10), and a partial tank row is generated inside (S12). On the other hand, when it is selected to calculate in the field D3, a swirl flow calculation subroutine is activated to calculate a swirl flow rate (S11), and a partial tank row is generated inside (S12).

Here, the swirl flow calculation subroutine will be described in detail. In the swirl flow calculation subroutine, first, the liquidus flow velocity u1 of the downcomer portion is assumed using a random number (S20). Next, the gas hold-up ε _GR of the riser portion is calculated from the liquidus flow velocity u1 of the downcomer portion using the Rouhani equation (Chemical Engineering Handbook Revised 5th Edition p.275) (S21).

Next, the obtained gas hold-up ε _GR and the flow resistance of the swirling flow in the tank are used to calculate the liquidus flow velocity u2 of the downcomer section using the Chisti equation (the following equation) as the pressure balance equation inside and outside the draft tube. Calculate (S22).

Here, U _LR : Ascending line flow velocity, g: Gravity acceleration, Z: Liquid depth, ε _GR : Upflow part gas holdup, _εGD : Downflow part gas holdup, K _T : Tower top resistance, K _B : Tower bottom resistance, A _R : rising part area, A _D : falling part area.

  Next, when the deviation between the liquidus flow velocity u1 and the liquidus flow velocity u2 is smaller than the internally set value, the liquidus flow velocity u1 is accumulated in the memory (S23). Next, when the number of the obtained liquidus flow velocities u1 is equal to or larger than a predetermined amount, the swirling flow rate is calculated using the average value of all the obtained liquidus flow velocities u1 as the downcomer descending line velocities (S24). ). At this time, the text property of the button B of the tank setting form shown in FIG. 7 is changed to “MBR with draft tube” which is a type of air lift swirl flow generation type (S25). Thereafter, it is recognized as an MBR with a draft tube on the program (FIG. 13).

  Next, returning to FIG. 2, when “setting of flow” is selected from the main menu A of the main screen shown in FIG. 6 (“setting of flow” in S2), the hydraulic conditions shown in FIG. The form for inputting "is expanded (S30 in FIG. 4). Here, in addition to the raw water inflow rate, filtered water flow rate, surplus sludge amount, flocculant injection amount, and circulation flow rate setting (S31), it is possible to input the solid content transport block rate α of circulation (including overflow). Yes (S32). Specifically, when each tank on the suction side and the discharge side of the circulation is selected from the lists G and H, the flow rate of the currently selected circulation path is displayed in the text box I, and the solid content block rate α setting button J is displayed. When button J is pressed, α can be input. α is multiplied only by the solid component transfer term in actual calculation.

  Further, when “integral calculation” (not shown) is selected from “calculation control” in the main menu A of the main screen shown in FIG. 6 (“integral calculation” in S2), as shown in FIG. In addition to the maximum and minimum increments of integration, a form having a portion K for inputting the maximum change width dΦ / Φ of the variable to be calculated Φ is developed (S40). Here, in addition to the maximum and minimum increments of integration, the maximum change width dΦ / Φ of the calculation target variable Φ is set (S41). The input value is stored in the memory and used when executing the simulation (described later).

  Then, after setting the microorganism model, setting the initial value, setting the calculation, and setting the output, when the button L on the main screen is pressed ("Simulation execution" in S2), the necessary input items are input. It is determined whether it has been completed (S15). If all necessary input items have been input, a simulation is started (S16). In the calculation process, the processing tank registered as “MBR with draft tube” does not normally go through the integration routine (complete mixing tank tank calculation), but through the partial tank row calculation subroutine that performs circulation by swirling flow, An operation of returning the composition of the outflow position set in the field D4 to the normal integration routine is performed.

  Further, in these integration processes, an integral step width dh is calculated for all tanks (all areas when registered as MBR with a draft tube) where dΦ / Φ of all calculation target parameters Φ are set values. The smallest value among all dh is adopted as the integration width, and the integration proceeds.

  More specifically, when integrating the differential equation representing the microbial reaction in each tank, the maximum change width dXmax of variables and the maximum integration step Δmax are set, and the reaction rate of the i-th tank and j-th component Sj, i Rj, i is stored, Δij = dXmax × Sj, i / Rj, i is compared with Δmax, and when Δmax> Δij, Δmax = Δij is performed for all i, j, and a series of operations By performing the integration using Δmax obtained from the above as an integration step size, an abnormal change of the variable value, that is, a negative value or divergence is avoided.

  As described above, in the wastewater treatment simulation system, calculation is performed and the composition in the treatment tank is calculated. The wastewater treatment simulation system can also be applied to an operation support system for wastewater treatment.

  The above-described wastewater treatment simulation system has a computer system inside. The process of the wastewater treatment simulation system described above is stored in a computer-readable recording medium in the form of a program, and the above process is performed by the computer reading and executing this program. Here, the computer-readable recording medium means a magnetic disk, a magneto-optical disk, a CD-ROM, a DVD-ROM, a semiconductor memory, or the like. Alternatively, the computer program may be distributed to the computer via a communication line, and the computer that has received the distribution may execute the program.

  The embodiment of the present invention has been described in detail with reference to the drawings. However, the specific configuration is not limited to this embodiment, and includes design and the like within a scope not departing from the gist of the present invention.

It is a schematic block diagram which shows the waste water treatment simulation system by this embodiment. It is a flowchart for demonstrating operation | movement of the waste water treatment simulation system in the embodiment. It is a flowchart for demonstrating operation | movement of the waste water treatment simulation system in the embodiment. It is a flowchart for demonstrating operation | movement of the waste water treatment simulation system in the embodiment. It is a flowchart for demonstrating operation | movement of the waste water treatment simulation system in the embodiment. It is a schematic diagram which shows the example of a screen of the waste water treatment simulation system in the embodiment. It is a schematic diagram which shows the example of a screen of the waste water treatment simulation system in the embodiment. It is a schematic diagram which shows the example of a screen of the waste water treatment simulation system in the embodiment. It is a schematic diagram which shows the example of a screen of the waste water treatment simulation system in the embodiment. It is a schematic diagram which shows the example of a screen of the waste water treatment simulation system in the embodiment. It is a schematic diagram which shows the example of a screen of the waste water treatment simulation system in the embodiment. It is a schematic diagram which shows the example of a screen of the waste water treatment simulation system in the embodiment. It is a schematic diagram which shows the example of a screen of the waste water treatment simulation system in the embodiment. It is a schematic diagram which shows the example of a screen of the waste water treatment simulation system in the embodiment. It is a schematic diagram which shows the example of a screen of the waste water treatment simulation system in the embodiment.

Explanation of symbols

DESCRIPTION OF SYMBOLS 1 Input part 2 Bubble slip speed calculation part 3 Gas holdup calculation part 4 Flow path resistance calculation part 5 In-tank swirl flow rate calculation part 6 In-tank composition change calculation part 7 Outflow composition calculation part 8 Storage part 9 Display part

Claims (6)

In the wastewater treatment simulation system that calculates the composition in the treatment tank using the hydraulic operation conditions and the microbial mathematical model,
The bottom area of the treatment tank, the liquid depth of the treatment tank, the bottom area of the upflow region in the treatment tank, the distance from the bottom of the treatment tank to the lower end of the upflow region, and the liquid level in the treatment tank An input means for inputting the distance to the upper end of the upflow region, the circumference of the lower portion of the upflow region, the installation position of the air diffuser, and the amount of aeration air;
Based on the value input by the input means, the in-tank flow rate assumption means for calculating the in-tank swirling flow rate Q1 by the air lift using a random number generation means,
A gas hold-up calculating means for calculating a gas hold-up in the upflow region using the in-tank swirling flow rate Q1,
In-tank swirl flow rate calculating means for calculating the in-tank swirl flow rate Q2 from the flow path resistance of the in-tank swirl flow calculated from the gas hold-up in the upflow region and the value input by the input unit;
Comparing the magnitude of a preset error e with | Q1-Q2 |, if e> | Q1-Q2 |, store at least one of Q1 and Q2, and assume the swirling flow rate Q1 in the tank. Calculation of the swirling flow rate Q2 in the tank, and a swirling flow determination means that sets the average value of at least one swirling flow rate in the tank stored by repeating the magnitude comparison result as a swirling flow rate,
Dividing the inside of the tank into several areas, and assuming that circulation is performed by the swirling flow determined by the swirling flow determining means, calculate the composition change in the tank using the partial tank row model indicated by the differential equation group A wastewater treatment simulation system comprising: a tank composition change calculating means. The wastewater treatment simulation system includes:
The apparatus further comprises a processing tank selection means for selecting that the user performs the airlift swirl flow calculation for an arbitrary processing tank,
The swirling flow rate determining means, when air lift swirling flow calculation is selected by the processing tank selecting means , the bottom area of the processing tank , the liquid depth, the bottom of the upflow region in the processing tank, which is input by the input means. Area, distance from the bottom of the treatment tank to the lower end of the upflow region, distance from the liquid level in the treatment tank to the upper end of the upflow region, the peripheral length of the lower part of the upflow region, the diffusion tube The wastewater treatment according to claim 1, wherein the outflow composition of the treatment tank is calculated based on an installation position , an aeration area, an aeration amount, an inflow position from another treatment tank, and an outflow position to the other treatment tank. Simulation system. The waste water treatment simulation system according to claim 1, wherein the turning flow rate determining unit gradually subtracts an error e when calculating the turning flow rate. The model representing the microbial reaction in the treatment tank is IWA ASM1, ASM2, ASM2d, ASM3, and a model obtained by modifying the organic substance accumulation process and the phosphorus accumulation bacteria action process. The wastewater treatment simulation system according to any one of claims 3 to 4. In the wastewater treatment simulation method that calculates the composition in the treatment tank using the hydraulic operating conditions and the microbial mathematical model using a computer,
The bottom area of the treatment tank, the liquid depth of the treatment tank, the bottom area of the upflow region in the treatment tank, the distance from the bottom of the treatment tank to the lower end of the upflow region, and the liquid level in the treatment tank Enter the distance to the upper end of the upflow region, the circumference of the lower part of the upflow region, the installation position of the diffuser, and the aeration air volume,
Based on the input value, the turning flow rate Q1 in the tank by the air lift is calculated using a random number generating means,
Using the in-tank swirling flow rate Q1, calculate the gas holdup in the upflow region,
The in-tank swirling flow rate Q2 is calculated from the flow resistance of the in-tank swirling flow calculated from the gas hold-up in the upflow region and the input value,
Comparing the magnitude of a preset error e with | Q1-Q2 |, if e> | Q1-Q2 |, store at least one of Q1 and Q2, and assume the swirling flow rate Q1 in the tank. The average value of at least one or more in-tank swirling flow stored by repeating the calculation of the in-tank swirling flow rate Q2 and the size comparison result is calculated, and the calculated average value is defined as the swirling flow rate.
Dividing the inside of the tank into several regions, the circulation is performed by the calculated swirling flow rate, and the composition change in the tank is calculated using the partial tank row model indicated by the differential equation. Wastewater treatment simulation method. To calculate the composition in the treatment tank using hydraulic operating conditions and microbial mathematical model using a computer,
The bottom area of the treatment tank, the liquid depth of the treatment tank, the bottom area of the upflow region in the treatment tank, the distance from the bottom of the treatment tank to the lower end of the upflow region, and the liquid level in the treatment tank Enter the distance to the upper end of the upflow region, the circumference of the lower part of the upflow region, the installation position of the diffuser, and the aeration air volume,
Based on the input value, the turning flow rate Q1 in the tank by the air lift is calculated using a random number generating means,
Using the in-tank swirling flow rate Q1, calculate the gas holdup in the upflow region,
The in-tank swirling flow rate Q2 is calculated from the flow resistance of the in-tank swirling flow calculated from the gas hold-up in the upflow region and the input value,
Comparing the magnitude of a preset error e with | Q1-Q2 |, if e> | Q1-Q2 |, store at least one of Q1 and Q2, and assume the swirling flow rate Q1 in the tank. The average value of at least one or more in-tank swirling flow stored by repeating the calculation of the in-tank swirling flow rate Q2 and the size comparison result is calculated, and the calculated average value is defined as the swirling flow rate.
Dividing the inside of the tank into several areas, and assuming that circulation is performed with the calculated swirl flow rate, execute a computer to calculate the composition change in the tank using the partial tank row model indicated by the differential equation Program to make.

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