Calculation Method, Calculation Device and Readable Medium for Fouling Behavior under Zinc Injection Influence

Abstract

The present invention provides a method, a computing device and a readable medium for calculating fouling behavior under the influence of zinc injection. The fouling behavior calculation method includes: dividing nodes of a reactor coolant system; calculating the mass evaporation rate of each node and the corrosion product release rate after zinc injection; inputting the corrosion product release rate after zinc injection and the mass evaporation rate into a mass transfer and mass balance model to calculate the fouling mass after zinc injection for each node. Based on the influence mechanism of zinc injection on the release of corrosion products, the present invention calculates the corrosion product release rate after zinc injection, and calculates parameters such as the fouling mass of each part of the reactor core and the boron deposition mass in the reactor core under the influence of zinc injection based on the corrosion product release rate after zinc injection, mass transfer and mass balance model, which can be used to judge the risk of axial power shift caused by fouling (CIPS) and local cladding corrosion caused by fouling (CILC).

Description

Technical Field

[0001] The present invention mainly relates to the technical field of nuclear reactors, and particularly relates to a method, a device, and a readable medium for calculating fouling behavior under the influence of zinc injection. Background Art

[0002] During the operation of a reactor, corrosion products (such as nickel and iron) on the primary loop pipes will be released into the coolant and deposit on the upper part of the high heat flux density fuel assemblies where subcooled nucleate boiling occurs to form fouling (Chalk Rivers Unidentified Deposit, CRUD). Boron and lithium hydroxide accumulate in the pore-like gaps of the fouling. When the boron accumulates to a certain extent, it will precipitate onto the fouling, which will lead to a decrease in the power of the upper part of the fuel assembly. As a result, the power peak will shift downward, that is, the axial power shift (Crud Induced Power Shift, CIPS) caused by fouling occurs. If the fouling deposition is thick at a local position, the coolant will not be able to flow through the fouling and cool the surface of the fuel cladding, which will lead to a relatively high temperature of the fuel cladding. If the fuel cladding is at a high temperature for a long time, it will accelerate the corrosion and failure of the fuel cladding, resulting in local cladding corrosion (Crud-Induced Localized Corrosion, CILC) caused by fouling.

[0003] By injecting zinc into the primary coolant, the composition of the oxide film on the surface of the primary loop structural materials can be improved, thereby reducing corrosion and further reducing the release, activation, and external radiation field of the core of corrosion products. At present, there is little quantitative analysis of the influence of zinc injection on CIPS in pressurized water reactors. Therefore, it is necessary to establish a method for calculating fouling behavior under the influence of zinc injection to evaluate the risks of CIPS and CILC in the core under zinc injection conditions. Summary of the Invention

[0004] The technical problem to be solved by the present invention is to provide a method, a device, and a readable medium for calculating fouling behavior under the influence of zinc injection, and solve the problem of the current lack of a method for calculating fouling behavior under the influence of zinc injection.

[0005] To solve the above technical problem, the present invention provides a method for calculating fouling behavior under the influence of zinc injection, including: dividing nodes of the reactor coolant system; calculating the mass evaporation rate of each node and the corrosion product release rate after zinc injection; inputting the corrosion product release rate after zinc injection and the mass evaporation rate into a mass transfer model and a mass balance model, and calculating the fouling mass after zinc injection of each node.

[0006] Optionally, calculating the total release rate of corrosion products after zinc injection includes: calculating the release rate of corrosion products before zinc injection, denoted as the first corrosion product release rate; calculating the release rate of corrosion products caused by zinc participation in replacement, denoted as the second corrosion product release rate; calculating the release rate of corrosion products after zinc injection based on the first corrosion product release rate and the second corrosion product release rate.

[0007] Optionally, the release rate of corrosion products after zinc injection is calculated by the following formula:

[0008]

[0009] where, is the total release rate of corrosion products after zinc injection, is the corrosion product release rate reduction factor, is the first corrosion product release rate, is the second corrosion product release rate.

[0010] Optionally, calculating the release rate of corrosion products before zinc injection includes: calculating the pH value of each node according to the fluid parameters of each node; inputting the pH value of the node into the corrosion product release model to obtain the first corrosion product release rate.

[0011] Optionally, the corrosion product release model is obtained by fitting historical pH values with the corrosion product release rate.

[0012] Optionally, the fluid parameters include fluid temperature, boron concentration, and lithium concentration.

[0013] Optionally, it further includes constructing a mass transfer model and a mass balance model, including: constructing a mass transfer model of the steam generator, the mass transfer model of the steam generator includes mass transfer from the main flow to the near-wall layer caused by turbulence, and mass transfer from the near-wall layer to the wall caused by deposition; constructing a mass transfer model of the core, the mass transfer model of the core includes mass transfer from the main flow to the near-wall layer caused by boiling at the core, mass transfer from the main flow to the near-wall layer caused by turbulence, and mass transfer from the near-wall layer to the wall caused by deposition; constructing a mass balance model, the mass balance model includes dirt mass removal in the letdown system, corrosion product release rate in the coolant system, mass flow rate transferred by deposition in the steam generator, and mass flow rate transferred by deposition at the core nodes.

[0014] Optionally, calculating the fouling mass after zinc injection for each node includes: inputting the corrosion product release rate after zinc injection into the mass balance model, and inputting the mass evaporation rate into the mass transfer model of the core; simultaneously solving the mass transfer model of the steam generator, the mass transfer model of the core, and the mass balance model to calculate the mass flow rate of deposition transfer at the core nodes and the mass flow rate of deposition transfer at the steam generator nodes; obtaining the fouling mass at the core nodes based on the mass flow rate of deposition transfer at the core nodes, and obtaining the fouling mass at the steam generator nodes based on the mass flow rate of deposition transfer at the steam generator nodes.

[0015] Optionally, it further includes: calculating the boron concentration distribution inside the fouling after zinc injection, and calculating the boron deposition mass after zinc injection based on the boron concentration distribution inside the fouling after zinc injection, the boron concentration on the surface of the cladding layer, and the fouling mass after zinc injection.

[0016] Optionally, calculating the boron concentration distribution inside the fouling after zinc injection: establishing mass flow rate relationships for the liquid phase and gas phase of boron substances inside the fouling respectively; using the condition that the net flow rate of substances at any position inside the fouling is 0 under steady state as the constraint condition for the mass flow rate relationships, and solving to obtain the boron concentration distribution inside the fouling after zinc injection.

[0017] Optionally, calculating the boron deposition mass after zinc injection includes: calculating the precipitation mass of boron-lithium compounds based on the boron concentration distribution inside the fouling after zinc injection; calculating the boron adsorption mass based on the boron concentration on the surface of the cladding layer and the fouling mass after zinc injection; calculating the boron deposition mass after zinc injection based on the precipitation mass of boron-lithium compounds and the boron adsorption mass.

[0018] To solve the above technical problems, the present invention provides a fouling behavior calculation device under the influence of zinc injection, including: at least one processor; and at least one memory storing instructions, which when executed alone or jointly by the at least one processor, cause the computing device to execute the method as described above.

[0019] To solve the above technical problems, the present invention provides a computer-readable medium for fouling behavior under the influence of zinc injection, on which instructions are stored, and when the instructions are executed alone or jointly by at least one processor of a computing device, the computing device is caused to execute the method as described above.

[0020] Compared with the prior art, the present invention has the following advantages:

[0021] The method, device and readable medium for calculating fouling behavior under the influence of zinc injection according to the present invention calculate the release rate of corrosion products after zinc injection based on the influence mechanism of zinc injection on the release of corrosion products, and calculate parameters such as the fouling mass of each part of the reactor core and the boron deposition mass in the reactor core under the influence of zinc injection based on the release rate of corrosion products after zinc injection, mass transfer and mass balance models, which can be used to judge CIPS and CILC risks. Description of the Drawings

[0022] The inclusion of the drawings is to provide a further understanding of the present application. They are incorporated and constitute a part of the present application. The drawings illustrate embodiments of the present application and, together with the description herein, serve to explain the principles of the present application. In the drawings:

[0023] Figure 1 is a flowchart of a method for calculating fouling behavior under the influence of zinc injection according to an embodiment of the present disclosure.

[0024] Figure 2 is Figure 1 a flowchart of an embodiment of step S3.

[0025] Figure 3 is Figure 1 a flowchart of an embodiment of step S4.

[0026] Figure 4 is a schematic diagram of the fouling mass of reactor core nodes before and after zinc injection according to an embodiment of the present disclosure.

[0027] Figure 5 is a schematic diagram of the boron deposition mass before and after zinc injection according to an embodiment of the present disclosure.

[0028] Figure 6 is a system block diagram of a device for calculating fouling behavior under the influence of zinc injection according to an embodiment of the present disclosure. Detailed Embodiments

[0029] To more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings in the following description are only some examples or embodiments of the present application. For those of ordinary skill in the art, without creative efforts, the present application can also be applied to other similar scenarios based on these drawings. Unless obvious from the language context or otherwise stated, the same reference numerals in the figures represent the same structure or operation.

[0030] According to operating experience, the zinc addition technology in the primary circuit of a pressurized water reactor can reduce the risk of CIPS. Currently, there is little quantitative analysis of the influence of zinc injection on CIPS in pressurized water reactors. Therefore, it is necessary to establish a method for calculating fouling behavior under the influence of zinc injection to evaluate the CIPS and CILC risks in the reactor core under zinc injection conditions.

[0031] The present invention provides a method for calculating fouling behavior under the influence of zinc injection. This method calculates the corrosion product release rate after zinc injection based on the influence mechanism of zinc injection on the release of corrosion products, and calculates parameters such as the fouling mass of each part of the core and the boron deposition mass in the core under the influence of zinc injection based on the corrosion product release rate, mass evaporation rate, mass transfer, and mass balance model after zinc injection, which can be used to judge CIPS and CILC risks.

[0032] Figure 1 is a flowchart of the method for calculating fouling behavior under the influence of zinc injection according to an embodiment of the present disclosure. As Figure 1 shown, the method for calculating fouling behavior under the influence of zinc injection 100 includes:

[0033] Step S1: Divide the nodes of the reactor coolant system.

[0034] In the nuclear power plant system, the reactor coolant system is also called the primary loop system. The coolant system consists of a reactor coolant pump, a reactor, a steam generator, and corresponding pipelines. For the reactor coolant system, model calculation nodes are divided for the core and the steam generator according to the calculation requirements.

[0035] Step S2: Calculate the mass evaporation rate of each node.

[0036] The mass evaporation rate refers to the mass evaporated per unit time per unit area. Optionally, the mass evaporation rate can be calculated by the following formula:

[0037] Mass evaporation rate = (latent heat of vaporization of the liquid evaporation area mass transfer coefficient) / (molar mass of the liquid total heat transfer coefficient).

[0038] Fouling accumulation will reduce the mass transfer coefficient, thereby reducing the mass evaporation rate. The mass evaporation rate is one of the important indicators for evaluating the fouling risk of the reactor core. Optionally, calculating the mass evaporation rate of each node includes: obtaining the fouling thickness of the current node, judging whether the fouling thickness of the current node is greater than the critical value. If so, calculating the mass evaporation rate of the node based on the porous deposit boiling module; wherein, the porous deposit boiling module sets the inside of the fouling as a capillary porous body structure and calculates the mass evaporation rate of the node based on the momentum equation, energy equation, and heat transfer equation of the fouling. If not, calculating the mass evaporation rate of the node based on the boiling heat flux and mass evaporation module. The boiling heat flux and mass evaporation module sets the current node as a clean cladding surface, calculates the heat flux density component through the heat flux density relation, and calculates the mass evaporation rate of the node according to the heat flux density component and the latent heat of vaporization.

[0039] Step S3: Calculate the corrosion product release rate after zinc injection for each node.

[0040] The present invention considers the two - fold effects of zinc injection on the release - deposition process in the pressurized water reactor (PWR) loop:

[0041] 1) The reduction in the corrosion rate caused by zinc injection in the PWR loop, which leads to a decrease in the release rate of corrosion products.

[0042] Zinc ions (Zn²⁺) react with the metal surface (such as stainless steel, nickel - based alloys) in a high - temperature and high - pressure water environment to form a dense oxide film. This new oxide film is more stable and can effectively slow down the corrosion rate of the metal matrix, thus resulting in a decrease in the release rate of corrosion products.

[0043] 2) Zinc displaces nickel or iron in the oxide layer, leading to an increase in the source term of corrosion products.

[0044] Due to the relatively high reducibility of zinc, zinc preferentially occupies the active sites on the metal surface, preventing the release of other corrosion products (such as Fe, Ni, Co), and forming a zinc - iron composite oxide layer (such as ), replacing the original oxide (such as ).

[0045] Figure 2 Yes Figure 1 It is a flowchart of an embodiment of step S3. As Figure 2 shown, calculating the total release rate of corrosion products after zinc injection includes:

[0046] Step S31: Calculate the release rate of corrosion products before zinc injection, denoted as the first corrosion product release rate.

[0047] Optionally, calculating the release rate of corrosion products before zinc injection includes:

[0048] Calculate the pH value of each node according to the fluid parameters of each node, and input the pH value of the node into the corrosion product release model to obtain the first corrosion product release rate.

[0049] Among them, the fluid parameters include but are not limited to fluid temperature, boron concentration, and lithium concentration. For example, calculate the pH value of the fluid near the wall of the steam generator through the fluid temperature, boron concentration, and lithium concentration near the wall of the steam generator, and this pH value can be obtained by looking up a table. Another example is to calculate the pH value of the mainstream of each node in the core through the fluid temperature, boron concentration, and lithium concentration of the mainstream of each node in the core, and this pH value can be obtained by looking up a table.

[0050] Optionally, the corrosion product release model is:

[0051]

[0052] In the formula: is the corrosion product release rate, kg / s;

[0053] The pH is the pH value, which is obtained by looking up a table.

[0054] Optionally, the corrosion product release model is obtained by fitting the historical pH value with the corrosion product release rate.

[0055] Step S32: Calculate the corrosion product release rate caused by the replacement of zinc, denoted as the second corrosion product release rate.

[0056] Obtain the mass of the corrosion product caused by the replacement of zinc, and divide the mass of the corrosion product by the reaction time to obtain the second corrosion product release rate.

[0057] Step S33: Calculate the corrosion product release rate after zinc injection according to the first corrosion product release rate and the second corrosion product release rate.

[0058] After zinc injection, due to the high reducibility of zinc, zinc preferentially occupies the active sites on the metal surface, preventing the release of other corrosion products. In this application, the reduction degree of the corrosion product release rate after zinc injection is represented by the corrosion product release rate reduction factor. Optionally, the corrosion product release rate after zinc injection is calculated by the following formula:

[0059]

[0060] Where, is the corrosion product release rate after zinc injection, is the corrosion product release rate reduction factor, which can be measured through multiple experiments; is the first corrosion product release rate, is the second corrosion product release rate.

[0061] Step S4: Input the corrosion product release rate and the mass evaporation rate after zinc injection into the mass transfer model and the mass balance model, and calculate the fouling mass after zinc injection at each node.

[0062] Optionally, before entering step S4, it also includes constructing a mass transfer model and a mass balance model. Among them, constructing a mass transfer model and a mass balance model includes:

[0063] 1) Construct a mass transfer model of the steam generator. The mass transfer model of the steam generator includes the mass transfer from the main flow to the near-wall layer caused by turbulence and the mass transfer from the near-wall layer to the wall caused by deposition. Optionally, the mass transfer model of the steam generator is:

[0064]

[0065] Where, Con is the total concentration of corrosion products in the coolant system, with the unit of ppb;

[0066] is the near-wall nickel solubility of the steam generator, in kg / kg;

[0067] is the mass flow rate of deposition transfer in the steam generator, in kg / (m 2 ·s);

[0068] is the mass transfer coefficient caused by the mixing of the near-wall layer and the mainstream in the steam generator, in kg / (m 2 ·s).

[0069] Among them, is an input parameter, which can be calculated from the near-wall pH value of the steam generator.

[0070] 2) Construct a mass transfer model for the core. The mass transfer model for the core includes the mass transfer from the mainstream to the near-wall layer caused by boiling in the core, the mass transfer from the mainstream to the near-wall layer caused by turbulence, and the mass transfer from the near-wall layer to the wall caused by deposition. Optionally, the mass transfer model for the core is:

[0071]

[0072] Among them, is the mass transfer efficiency caused by boiling;

[0073] is the mass evaporation rate, in kg / (m 2 ·s);

[0074] Con is the total concentration of corrosion products in the coolant system, in ppb;

[0075] is the near-wall nickel solubility of the core, in ppb.

[0076] is the mass transfer coefficient caused by the mixing of the near-wall layer and the mainstream at the core node, in kg / (m 2 ·s);

[0077] is the mass flow rate of deposition transfer at the core node, in kg / (m 2 ·s).

[0078] Among them, is an input parameter, which can be calculated from the pH value of the core node.

[0079] 3) Construct a mass balance model, which includes the fouling mass removal of the downflow system, the corrosion product release rate in the coolant system, the mass flow rate of steam generator deposition transfer, and the mass flow rate of core node deposition transfer. Optionally, the mass balance model is:

[0080]

[0081] Where: is the mass of coolant in the coolant system, in kg / m 2 ;

[0082] Con is the total concentration of corrosion products in the coolant system, in ppb;

[0083] t is time, in seconds;

[0084] The mass flow rate of fouling deposition in the core, in kg / (m 2 s);

[0085] The mass flow rate of fouling deposits in the steam generator is kg / (m 2 s);

[0086] The mass flow rate of dirt deposition in the downflow system, in kg / (m 2 s);

[0087] is the corrosion product release rate after zinc injection, in kg / (m 2 ·s).

[0088] in, is the input parameter.

[0089] Figure 3 yes Figure 1 Step S4 is a flow chart of an embodiment. Figure 3 As shown, optionally, calculating the fouling mass of each node after zinc injection includes:

[0090] Step S41: inputting the corrosion product release rate after zinc injection into the mass balance model, and inputting the mass evaporation rate into the mass transfer model of the core.

[0091] Step S42: The mass transfer model of the steam generator, the mass transfer model of the core and the mass balance model are combined to calculate the mass flow rate of the core node deposition transfer and the mass flow rate of the steam generator deposition transfer.

[0092] That is, by combining equations (3) to (5), we can obtain the mass flow rate of core node deposition transfer: , the mass flow rate of deposition transfer in the steam generator , the total concentration Con of corrosion products in the coolant system.

[0093] Step S43: Obtain the fouling mass at the core node based on the mass flow rate of deposition transfer at the core node, and obtain the fouling mass at the steam generator node based on the mass flow rate of deposition transfer in the steam generator.

[0094] Optionally, calculate the fouling mass at the core node and the fouling mass at the steam generator node through the following formula.

[0095]

[0096] Wherein, is the fouling mass in the core, with the unit of kg / m 2 ;

[0097] the fouling mass in the steam generator, with the unit of kg / m 2 ;

[0098] t is time, with the unit of s.

[0099] Figure 4 is a schematic diagram of the fouling mass at the core node before and after zinc injection according to an embodiment of the present disclosure. As Figure 4 shown, the fouling mass at the core node decreases significantly after zinc injection.

[0100] Optionally, the present invention also considers the influence of zinc injection on the boron precipitation mass. The enrichment degree of boron can be represented by the concentration factor as follows:

[0101]

[0102] Wherein, is the mass evaporation rate, with the unit of kg / (m 2 ·s);

[0103] is the fouling thickness, with the unit of m;

[0104] is the liquid phase density, with the unit of kg / m 2 ;

[0105] P is the sediment porosity;

[0106] is a user input parameter.

[0107] The reduction of the fouling mass will lead to a decrease in the fouling thickness. It can be seen from formula (8) that after zinc injection, the change in the fouling thickness will change the enrichment degree of boron, and thus change the boron deposition mass.

[0108] The present invention considers two boron deposition mechanisms, namely boron-lithium compound precipitation and boron hiding, and calculates the boron deposition mass m after zinc injection through the following formula:

[0109]

[0110]

[0111]

[0112] wherein, is the mass of boron-lithium compound precipitation, is the mass of boron adsorption, is the thickness of the boron layer, A is the node area, with the unit of m 2 ; are respectively user input parameters, is the boron concentration on the surface of the cladding layer, is the mass of dirt after zinc injection.

[0113] Optionally, the value of the boron layer thickness is calculated from the boron concentration distribution inside the dirt after zinc injection.

[0114] Optionally, calculating the boron concentration distribution inside the dirt after zinc injection includes: establishing mass flow relationships for the liquid phase and gas phase of boron substances inside the dirt respectively; using the condition that the net flow of substances at any position inside the dirt is 0 under steady state as the constraint condition of the mass flow relationship, and solving to obtain the boron concentration distribution inside the dirt after zinc injection.

[0115] Based on the boron concentration distribution inside the dirt after zinc injection, determine whether the boron concentration at the grid reaches the critical concentration. If so, the boron concentration at the current grid exceeds the solubility limit of the deposited boron-lithium compound, and the position of the current grid is the thickness of the boron deposition layer .

[0116] In summary, the present disclosure calculates the boron deposition mass after zinc injection including:

[0117] Calculating the mass of boron-lithium compound precipitation according to the boron concentration distribution inside the dirt after zinc injection;

[0118] Calculating the mass of boron adsorption according to the boron concentration on the surface of the cladding layer and the mass of dirt after zinc injection;

[0119] Calculating the boron deposition mass after zinc injection according to the mass of boron-lithium compound precipitation and the mass of boron adsorption.

[0120] Figure 5 is a schematic diagram of the boron deposition mass before and after zinc injection according to an embodiment of the present disclosure. As Figure 5As shown, in this experiment, zinc injection started at a low concentration continuously from the 10th cycle, and the changing trend of boron precipitation in consecutive cycles was obtained. Before zinc injection, the maximum boron precipitation increased continuously in the first three cycles, reached the maximum value in the third cycle, slightly lower than 110 g, and then gradually decreased to a lower level. This is because there were more corrosion products and a larger total amount of dirt in the first three cycles, which ultimately resulted in a larger amount of boron precipitation. After zinc injection, the boron precipitation in the reactor decreased. In the long term, the boron precipitation after zinc injection decreased by about 40%, reducing the CIPS risk.

[0121] This application also includes a fouling behavior calculation device under the influence of zinc injection, including a memory and a processor. Among them, the memory is used to store instructions executable by the processor; the processor is used to execute the instructions to implement the fouling behavior calculation method under the influence of zinc injection as described above.

[0122] Figure 6 It is a system block diagram of a fouling behavior calculation device under the influence of zinc injection according to an embodiment of the present disclosure. Refer to Figure 6 As shown, the fouling behavior calculation device 600 (hereinafter referred to as "calculation device 600") under the influence of zinc injection may include an internal communication bus 601, a processor 602, a read-only memory (ROM) 603, a random access memory (RAM) 604, and a communication port 605. When applied to a personal computer, the calculation device 600 may further include a hard disk 606. The internal communication bus 601 can enable data communication between components of the calculation device 600. The processor 602 can make judgments and issue prompts. In some embodiments, the processor 602 may be composed of one or more processors. The communication port 605 can enable data communication between the calculation device 600 and the outside. In some embodiments, the calculation device 600 can send and receive information and data from a network through the communication port 605. The calculation device 600 may also include different forms of program storage units and data storage units, such as the hard disk 606, the read-only memory (ROM) 603, and the random access memory (RAM) 604, which can store various data files used for computer processing and / or communication, as well as possible program instructions executed by the processor 602. The processor executes these instructions to implement the main part of the method. The results processed by the processor are transmitted to the user device through the communication port and displayed on the user interface.

[0123] The above operation method can be implemented as a computer program, stored in the hard disk 606, and loaded into the processor 602 for execution to implement the fouling behavior calculation method under the influence of zinc injection of this application.

[0124] This application also includes a computer-readable medium storing computer program code, which implements the fouling behavior calculation method under the influence of zinc injection as described above when executed by a processor.

[0125] When the method for calculating fouling behavior under zinc injection is implemented as a computer program, it can also be stored in a computer-readable storage medium as an article of manufacture. For example, the computer-readable storage medium may include, but is not limited to, magnetic storage devices (e.g., hard disks, floppy disks, magnetic strips), optical disks (e.g., compact disks (CDs), digital versatile disks (DVDs)), smart cards, and flash memory devices (e.g., electrically erasable programmable read-only memories (EPROMs), cards, sticks, key drives). In addition, the various storage media described herein can represent one or more devices and / or other machine-readable media for storing information. The term "machine-readable medium" may include, but is not limited to, wireless channels and various other media (and / or storage media) that can store, contain, and / or carry code and / or instructions and / or data.

[0126] Flowcharts are used in this application to illustrate the operations performed by the systems according to the embodiments of this application. It should be understood that the operations before or below do not necessarily have to be executed precisely in order. On the contrary, various steps can be processed in reverse order or simultaneously. Also, other operations can be added to these processes, or one or more steps can be removed from these processes.

[0127] In addition, it should be noted that the use of terms such as "first" and "second" to limit components is only for the convenience of differentiating the corresponding components. Without additional statements, the above terms have no special meanings, and thus should not be construed as limiting the scope of protection of this application. In addition, although the terms used in this application are selected from well-known and commonly used terms, some of the terms mentioned in the specification of this application may be selected by the applicant according to his or her judgment, and their detailed meanings are described in the relevant parts of this description. In addition, it is required to understand this application not only through the actual terms used, but also through the meanings implied by each term.

[0128] As shown in this application, unless the context clearly indicates an exceptional situation, words such as "a", "an", "one", and / or "the" are not specifically singular and may also include the plural. Generally speaking, the terms "comprising" and "including" only indicate the inclusion of the steps and elements that have been clearly identified, and these steps and elements do not constitute an exclusive list. The method or device may also include other steps or elements.

[0129] Unless otherwise specifically stated, the relative arrangements of components and steps, numerical expressions, and numerical values set forth in these embodiments do not limit the scope of the present application. At the same time, it should be understood that, for the sake of convenience of description, the dimensions of the various parts shown in the drawings are not drawn in actual proportional relationship. Technologies, methods, and devices known to those of ordinary skill in the relevant art may not be discussed in detail, but where appropriate, the said technologies, methods, and devices should be regarded as part of the specification. In all the examples shown and discussed here, any specific value should be construed as merely exemplary and not as a limitation. Therefore, other examples of the exemplary embodiments may have different values. It should be noted that like reference numerals and letters denote like items in the following figures, and thus, once an item is defined in one figure, further discussion thereof is not required in subsequent figures.

[0130] The basic concepts have been described above. Obviously, for those skilled in the art, the above invention disclosure is only an example and does not constitute a limitation to the present application. Although not explicitly stated herein, those skilled in the art may make various modifications, improvements, and corrections to the present application. Such modifications, improvements, and corrections are proposed in the present application, so such modifications, improvements, and corrections still fall within the spirit and scope of the exemplary embodiments of the present application.

[0131] At the same time, the present application uses specific terms to describe the embodiments of the present application. Such as "one embodiment", "an embodiment", and / or "some embodiments" mean a certain feature, structure, or characteristic related to at least one embodiment of the present application. Therefore, it should be emphasized and noted that the "one embodiment" or "an embodiment" or "an alternative embodiment" mentioned twice or more at different positions in this specification does not necessarily refer to the same embodiment. In addition, certain features, structures, or characteristics in one or more embodiments of the present application may be appropriately combined.

[0132] Some aspects of the present application can be executed entirely by hardware, entirely by software (including firmware, resident software, microcode, etc.), or by a combination of hardware and software. The above-mentioned hardware or software can all be referred to as "data blocks", "modules", "engines", "units", "components" or "systems". The processor can be one or more application specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DAPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), processors, controllers, microcontrollers, microprocessors, or combinations thereof. In addition, aspects of the present application may be embodied as a computer product located in one or more computer-readable media, which includes computer-readable program code. For example, the computer-readable media may include, but is not limited to, magnetic storage devices (such as hard disks, floppy disks, magnetic tapes...), optical disks (such as compact disks CD, digital versatile disks DVD...), smart cards, and flash memory devices (such as cards, sticks, key drives...).

[0133] The computer-readable media may contain a propagated data signal having computer program code embodied therein, for example, on a baseband or as part of a carrier wave. The propagated signal may take many forms, including electromagnetic, optical, or the like, or any suitable combination thereof. The computer-readable media can be any computer-readable media other than a computer-readable storage medium, which can be connected to an instruction execution system, apparatus, or device to effect communication, propagation, or transmission for use of the program. The program code located on the computer-readable media can be propagated through any suitable medium, including radio, cable, fiber optic cable, radio frequency signal, or similar media, or any combination of the above media.

[0134] Similarly, it should be noted that, in order to simplify the presentation of the disclosure of the present application and thus help the understanding of one or more embodiments of the invention, in the foregoing description of the embodiments of the present application, sometimes multiple features are combined into one embodiment, drawing, or description thereof. However, this disclosure method does not mean that the features required by the subject matter of the present application are more than the features mentioned. In fact, the features of the embodiment are less than all the features of the single embodiment disclosed above.

[0135] In some embodiments, numbers are used to describe components and the quantity of attributes. It should be understood that such numbers used in the description of embodiments are modified by the modifiers "about", "approximately" or "substantially" in some examples. Unless otherwise stated, "about", "approximately" or "substantially" indicate that the said numbers allow a variation of ±20%. Accordingly, in some embodiments, the numerical parameters used in the specification are approximate values, which may vary according to the characteristics required by individual embodiments. In some embodiments, the numerical parameters should consider the specified significant digits and adopt the method of retaining the general number of digits. Although the numerical ranges and parameters used in some embodiments of the present application to confirm the breadth of their scope are approximate values, in specific embodiments, such numerical settings are as precise as possible within the feasible range.

[0136] Although the present application has been described with reference to the current specific embodiments, those of ordinary skill in the art should recognize that the above embodiments are only used to illustrate the present application, and various equivalent changes or substitutions can be made without departing from the spirit of the present application. Therefore, as long as the changes and modifications of the above embodiments are within the scope of the spirit of the present application, they will fall within the scope of the present application.

Claims

1. A method for calculating fouling behavior under the influence of zinc injection, characterized in that, include: Node partitioning of the reactor coolant system; Calculate the mass evaporation rate of each node and the corrosion product release rate after zinc injection; The corrosion product release rate after zinc injection and the mass evaporation rate are input into a mass transfer model and a mass balance model to calculate the scale mass after zinc injection at each node; The mass transfer model and the mass balance model are constructed in the following manner: constructing a mass transfer model of a steam generator, wherein the mass transfer model of the steam generator includes mass transfer from the mainstream to the near-wall layer caused by turbulence, and mass transfer from the near-wall layer to the wall caused by deposition; constructing a mass transfer model of the core, wherein the mass transfer model of the core includes mass transfer from the mainstream to the near-wall layer caused by boiling at the core, mass transfer from the mainstream to the near-wall layer caused by turbulence, and mass transfer from the near-wall layer to the wall caused by deposition; constructing a mass balance model, wherein the mass balance model includes the fouling mass removal of the downflow system, the corrosion product release rate in the coolant system, the mass flow rate of the steam generator deposition transfer, and the mass flow rate of the core node deposition transfer; Among them, calculating the fouling mass of each node after zinc injection includes: inputting the corrosion product release rate after zinc injection into the mass balance model, and inputting the mass evaporation rate into the mass transfer model of the core; jointly calculating the mass transfer model of the steam generator, the mass transfer model of the core and the mass balance model to obtain the mass flow rate of core node deposition transfer and the mass flow rate of steam generator deposition transfer; obtaining the core node fouling mass according to the mass flow rate of core node deposition transfer, and obtaining the steam generator node fouling mass according to the mass flow rate of steam generator deposition transfer.

2. The method for calculating fouling behavior under the influence of zinc injection according to claim 1, characterized in that Calculating the total release rate of corrosion products after zinc injection includes: Calculate the corrosion product release rate before zinc injection, recorded as the first corrosion product release rate; Calculate the corrosion product release rate caused by zinc substitution, which is recorded as the second corrosion product release rate; The corrosion product release rate after zinc injection is calculated according to the first corrosion product release rate and the second corrosion product release rate.

3. The method for calculating fouling behavior under the influence of zinc injection according to claim 2, wherein, The corrosion product release rate after zinc injection is calculated by the following formula: Among them, is the total release rate of the corrosion products after zinc injection, is the corrosion product release rate reduction factor, is the first corrosion product release rate, is the second corrosion product release rate.

4. The method for calculating fouling behavior under the influence of zinc injection according to claim 2, wherein, Calculating the corrosion product release rate before zinc injection includes: Calculate the pH value of each node based on the fluid parameters of each node; The pH value of the node is input into a corrosion product release model to obtain the first corrosion product release rate.

5. The method for calculating fouling behavior under the influence of zinc injection according to claim 4, characterized in that The corrosion product release model is obtained by fitting the historical pH value and the corrosion product release rate.

6. The method for calculating fouling behavior under the influence of zinc injection according to claim 4, wherein, The fluid parameters include fluid temperature, boron concentration, and lithium concentration.

7. The method for calculating fouling behavior under the influence of zinc injection according to claim 1, characterized in that Also includes: The boron concentration distribution inside the scale after zinc injection is calculated, and the boron deposition mass after zinc injection is calculated according to the boron concentration distribution inside the scale after zinc injection, the boron concentration on the surface of the cladding layer and the scale mass after zinc injection.

8. The method for calculating fouling behavior under the influence of zinc injection according to claim 7, characterized in that, Calculate the boron concentration distribution inside the scale after zinc injection: The mass flow relationship is established for the liquid phase and gas phase of the boron substance inside the dirt; The net flow of substances at any position inside the scale in a steady state is set to 0 as a constraint condition of the mass flow relationship, and the boron concentration distribution inside the scale after zinc injection is obtained by solving the problem.

9. The method for calculating the fouling behavior under the influence of zinc injection according to claim 7, wherein calculating the boron deposition mass after zinc injection includes: Calculating the precipitation mass of boron-lithium compounds according to the boron concentration distribution inside the fouling after zinc injection; Calculating the boron adsorption mass according to the boron concentration on the surface of the cladding layer and the fouling mass after zinc injection; Calculating the boron deposition mass after zinc injection according to the precipitation mass of boron-lithium compounds and the boron adsorption mass.

10. A fouling behavior calculation device under the influence of zinc injection, characterized in that, Including: At least one processor; And At least one memory storing instructions, which when executed alone or jointly by the at least one processor, cause the fouling behavior calculation device to execute the method according to any one of claims 1 to 9.

11. A computer-readable medium for fouling behavior under zinc injection, characterized in that, Instructions are stored on the computer-readable medium, which when executed alone or jointly by at least one processor of the computing device, cause the computing device to execute the method according to any one of claims 1 to 9.

Images