Calculation method and calculation device for dirt behavior under influence of zinc injection and readable medium

Abstract

The invention provides a method and a device for calculating a dirt behavior under the influence of zinc injection, and a readable medium. The fouling behavior calculation method comprises the following steps: carrying out node division on a reactor coolant system; the mass evaporation rate of each node and the corrosion product release rate after zinc injection are calculated; and inputting the corrosion product release rate after zinc injection and the mass evaporation rate into a mass transmission and mass balance model, and calculating to obtain the dirt mass of each node after zinc injection. According to the method, the corrosion product release rate after zinc injection is calculated based on the influence mechanism of zinc injection on corrosion product release, and parameters such as the dirt mass and the reactor core boron deposition mass of each part of the reactor core under the influence of zinc injection are calculated based on the corrosion product release rate after zinc injection, mass transmission and a mass balance model; the method can be used for judging the risk of axial power offset (CIPS) caused by dirt and local cladding corrosion (CILC) caused by dirt.

Description

Technical Field

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

[0002] When the reactor is in operation, the corrosion products (nickel, iron, etc.) on the primary loop pipes will be released into the coolant and deposited on the upper part of the high heat flux density fuel assembly where supercooled nucleate boiling occurs to form scale (Chalk Rivers Unidentified Deposit, CRUD). Boron and lithium hydroxides accumulate in the porous gaps of the scale. When boron accumulates to a certain extent, it will precipitate on the scale, which will cause the power of the upper part of the fuel assembly to decrease, and the power peak will move downward, that is, the axial power shift (Crud Induced Power Shift, CIPS) caused by scale will occur. If the scale deposition in the local position is thick, the coolant will not be able to flow through the scale and cool the surface of the fuel cladding, which will cause the temperature of the fuel cladding to be too high. If the fuel cladding is at a very high temperature for a long time, the corrosion and failure of the fuel cladding will be accelerated, resulting in the localized cladding corrosion (Crud-Induced Localized Corrosion, CILC) caused by scale.

[0003] By injecting zinc into the primary coolant, the composition of the oxide film on the surface of the primary structural material can be improved, thereby reducing corrosion and further reducing the release of corrosion products, activation and the radiation field outside the core. At present, there are few quantitative analyses of the impact of zinc injection on CIPS in pressurized water reactors. Therefore, it is necessary to establish a calculation method for fouling behavior under the influence of zinc injection to evaluate the risk of core CIPS and CILC under zinc injection conditions. Summary of the invention

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

[0005] In order to solve the above technical problems, the present invention provides a method for calculating fouling behavior under the influence of zinc injection, including: dividing the reactor coolant system into nodes; 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 to calculate the fouling mass of each node after zinc injection.

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

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

[0008]

[0009] in, 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 release rate of the second corrosion product.

[0010] Optionally, calculating the corrosion product release rate 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 a 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 ​​and corrosion product release rates.

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

[0013] Optionally, it also includes constructing a mass transfer model and a mass balance model, including: constructing a mass transfer model for a steam generator, the mass transfer model for 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 for the core, the mass transfer model for 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, 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 transferred by steam generator deposition, and the mass flow rate transferred by core node deposition.

[0014] Optionally, 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 flow rate of core node deposition transfer and the mass flow rate of steam generator deposition transfer by the mass transfer model of the steam generator, the mass transfer model of the core and the mass balance model; 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.

[0015] Optionally, the method further includes: calculating the boron concentration distribution inside the scale after zinc injection, and calculating the boron deposition mass after zinc injection 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.

[0016] Optionally, the boron concentration distribution inside the scale after zinc injection is calculated: mass flow relationship equations are established for the liquid phase and gas phase of the boron substance inside the scale respectively; the net flow rate of the substance at any position inside the scale under steady state is 0 as a constraint condition of the mass flow relationship equation, and the boron concentration distribution inside the scale after zinc injection is obtained by solving the equation.

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

[0018] To solve the above technical problems, the present invention provides a device for calculating fouling behavior under the influence of zinc injection, comprising: at least one processor; and at least one memory on which instructions are stored, and when the instructions are executed individually or collectively by the at least one processor, the computing device executes the method as described above.

[0019] To solve the above technical problems, the present invention provides a computer-readable medium for scale behavior under the influence of zinc injection, on which instructions are stored. When the instructions are executed individually or collectively by at least one processor of a computing device, the computing device executes the method described above.

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

[0021] The fouling behavior calculation method, calculation device and readable medium under the influence of zinc injection of the present invention calculate the corrosion product release rate after zinc injection based on the influence mechanism of zinc injection on the release of corrosion products, and calculate the fouling mass of each part of the core under the influence of zinc injection, the core boron deposition mass and other parameters based on the corrosion product release rate after zinc injection, mass transfer and mass balance model, which can be used to judge CIPS and CILC risks. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] The accompanying drawings are included to provide a further understanding of the present application. They are included and constitute a part of the present application. The accompanying drawings illustrate embodiments of the present application and together with the present specification serve to explain the principles of the present application. In the accompanying drawings:

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

[0024] Figure 2 yes Figure 1 Step S3 is a flow chart of an embodiment.

[0025] Figure 3 yes Figure 1 Step S4 is a flow chart of an embodiment.

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

[0027] Figure 5 Schematic diagram of boron deposition quality before and after zinc injection according to an embodiment of the present disclosure.

[0028] Figure 6 4 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 DESCRIPTION

[0029] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following is a brief introduction to the drawings required for the description of the embodiments. Obviously, the drawings described below are only some examples or embodiments of the present application. For ordinary technicians in this field, the present application can also be applied to other similar scenarios based on these drawings without creative work. Unless it is obvious from the language environment or otherwise explained, the same reference numerals in the figures represent the same structure or operation.

[0030] According to operating experience, zinc injection in the primary circuit of a pressurized water reactor can reduce the risk of CIPS. Currently, there are few quantitative analyses of the impact 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 risk of CIPS and CILC in the core under zinc injection conditions.

[0031] The present invention provides a method for calculating fouling behavior under the influence of zinc injection. The 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 the fouling mass of each part of the core under the influence of zinc injection, the core boron deposition mass and other parameters 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 FIG. 1 is a flow chart of a method for calculating fouling behavior under the influence of zinc injection according to an embodiment of the present disclosure. Figure 1 As shown, the method 100 for calculating the fouling behavior under the influence of zinc injection includes:

[0033] Step S1: dividing the reactor coolant system into nodes.

[0034] The reactor coolant system in a nuclear power plant is also called the primary circuit system. The coolant system consists of a reactor coolant pump, a reactor and a steam generator, and corresponding pipelines. For the reactor coolant system, the core and steam generator are divided into model calculation nodes 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 area per unit time. Optionally, the mass evaporation rate can be calculated by the following formula:

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

[0038] The accumulation of fouling will reduce the mass transfer coefficient, thereby reducing the mass evaporation rate, which is one of the important indicators for assessing the risk of fouling in the reactor core. Optionally, calculating the mass evaporation rate of each node includes: obtaining the fouling thickness of the current node, determining whether the fouling thickness of the current node is greater than a critical value, and if so, calculating the mass evaporation rate of the node based on the porous sediment boiling module; wherein the porous sediment boiling module sets the interior of the fouling to a capillary porous 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, the mass evaporation rate of the node is calculated based on the boiling heat flux and mass evaporation module. The boiling heat flux and mass evaporation module sets the current node to a clean cladding surface, calculates the heat flux density component through the heat flux density relationship, and calculates the mass evaporation rate of the node based on the heat flux density component and the latent heat of vaporization.

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

[0040] The present invention considers two aspects of the impact of zinc injection on the release-deposition process in the PWR loop:

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

[0042] Zinc ions (Zn²⁺) react with metal surfaces (such as stainless steel and 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, thereby reducing the release rate of corrosion products.

[0043] 2) Zinc replaces nickel or iron in the oxide layer, resulting in an increase in the source of corrosion products.

[0044] Due to the 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, and Co), forming a zinc-iron composite oxide layer (such as ), replacing the original oxides (such as ).

[0045] Figure 2 yes Figure 1 Step S3 is a flow chart of an embodiment. Figure 2 As shown, the calculation of the total release rate of corrosion products after zinc injection includes:

[0046] Step S31: Calculate the corrosion product release rate before zinc injection, which is recorded as the first corrosion product release rate.

[0047] Optionally, calculation of the corrosion product release rate before zinc injection includes:

[0048] The pH value of each node is calculated according to the fluid parameters of each node, and the pH value of the node is input 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, the pH value of the fluid near the wall of the steam generator is calculated by the fluid temperature, boron concentration and lithium concentration near the wall of the steam generator, and the pH value can be obtained by looking up the table. For another example, the pH value of the mainstream of each node in the core is calculated by the fluid temperature, boron concentration and lithium concentration of the mainstream of each node in the core, and the pH value can be obtained by looking up the table.

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

[0051]

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

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

[0054] Optionally, the corrosion product release model is obtained by fitting historical pH values ​​and corrosion product release rates.

[0055] Step S32: Calculate the corrosion product release rate caused by zinc substitution, which is recorded as the second corrosion product release rate.

[0056] The mass of the corrosion product caused by zinc substitution is obtained, and the mass of the corrosion product is divided 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, zinc preferentially occupies the active sites on the metal surface due to its high reducibility, preventing the release of other corrosion products. The present application uses the corrosion product release rate reduction factor to indicate the degree of reduction in the corrosion product release rate after zinc injection. Optionally, the corrosion product release rate after zinc injection is calculated by the following formula:

[0059]

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

[0061] Step S4: The corrosion product release rate and mass evaporation rate after zinc injection are input into the mass transfer model and the mass balance model to calculate the scale 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. Wherein, constructing the mass transfer model and the mass balance model includes:

[0063] 1) Construct a mass transfer model of the steam generator. 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. 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, in ppb;

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

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

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

[0069] in, is the input parameter, It can be calculated from the pH value near the wall of the steam generator.

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

[0071]

[0072] in, is the mass transfer efficiency due to 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 nickel solubility near the core wall, in ppb.

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

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

[0078] in, is the input parameter, It 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 the steam generator fouling deposition 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 steam generator deposition transfer , the total concentration Con of corrosion products in the coolant system.

[0093] Step S43: obtaining the fouling mass of the core node according to the mass flow rate transmitted by the core node deposition, and obtaining the fouling mass of the steam generator node according to the mass flow rate transmitted by the steam generator deposition.

[0094] Optionally, the core node fouling mass and the steam generator node fouling mass are calculated by the following formulas.

[0095]

[0096] in, is the mass of dirt in the core, in kg / m 2 ;

[0097] The mass of dirt in the steam generator, in kg / m 2 ;

[0098] t is time, unit is s.

[0099] Figure 4 Schematic diagram of the fouling mass of the core nodes before and after zinc injection according to an embodiment of the present disclosure. Figure 4 As shown in the figure, the quality of core node fouling is significantly reduced after zinc injection.

[0100] Optionally, the present invention also considers the effect of zinc injection on the quality of boron precipitation. The degree of boron enrichment can be expressed as a concentration factor express:

[0101]

[0102] in, is the mass evaporation rate, in kg / (m 2 s);

[0103] is the dirt thickness, in m;

[0104] is the liquid density, in kg / m 2 ;

[0105] P is the sediment porosity;

[0106] Enter parameters for the user.

[0107] The reduction of dirt mass will lead to a decrease in dirt thickness. From formula (8), it can be seen that after zinc injection, the change of dirt thickness will change the enrichment degree of boron, and then change the quality of boron deposition.

[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 by the following formula:

[0109]

[0110]

[0111]

[0112] in, is the mass of boron-lithium compound precipitation, is the boron adsorption mass, is the thickness of the boron layer, A is the node area, in m 2 ; Input parameters for users respectively. is the boron concentration on the cladding surface, It is the dirt mass after zinc injection.

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

[0114] Optionally, calculating the boron concentration distribution inside the scale after zinc injection includes: establishing mass flow relationship equations for the liquid phase and gas phase of the boron substance inside the scale respectively; taking the net flow of the substance at any position inside the scale under steady state as 0 as a constraint condition of the mass flow relationship equation, and solving the boron concentration distribution inside the scale after zinc injection.

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

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

[0117] The mass of boron-lithium compound precipitation is calculated based on the boron concentration distribution inside the scale after zinc injection;

[0118] The boron adsorption mass is calculated based on the boron concentration on the cladding surface and the dirt mass after zinc injection;

[0119] The boron deposition mass after zinc injection was calculated based on the boron-lithium compound precipitation mass and the boron adsorption mass.

[0120] Figure 5 FIG. 1 is a schematic diagram of the boron deposition quality before and after zinc injection according to an embodiment of the present disclosure. Figure 5As shown in the figure, this experiment started to inject zinc at a low concentration from the 10th cycle, and obtained the trend of boron precipitation in the continuous cycle. Before zinc injection, the maximum boron precipitation continued to increase in the first three cycles, reaching a maximum value in the third cycle, slightly lower than 110 g, and then gradually decreased to a lower level. This is because there are more corrosion products and a larger amount of dirt in the first three cycles, which ultimately leads to a larger amount of boron precipitation. After zinc injection, the amount of boron precipitation in the pile decreased. In the long run, the amount of boron precipitation after zinc injection decreased by about 40%, reducing the risk of CIPS.

[0121] The present application also includes a device for calculating fouling behavior under the influence of zinc injection, comprising a memory and a processor, wherein the memory is used to store instructions executable by the processor; and the processor is used to execute the instructions to implement the above method for calculating fouling behavior under the influence of zinc injection.

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

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

[0124] The present application also includes a computer-readable medium storing a computer program code, which, when executed by a processor, implements the above-mentioned method for calculating fouling behavior under the influence of zinc injection.

[0125] When the method for calculating the fouling behavior under the influence of zinc injection is implemented as a computer program, it can also be stored in a computer-readable storage medium as a product. For example, a computer-readable storage medium may include, but is not limited to, a magnetic storage device (e.g., a hard disk, a floppy disk, a magnetic strip), an optical disk (e.g., a compact disk (CD), a digital versatile disk (DVD)), a smart card, and a flash memory device (e.g., an electrically erasable programmable read-only memory (EPROM), a card, a stick, a key drive). 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 the present application to illustrate the operations performed by the system according to the embodiments of the present application. It should be understood that the preceding or following operations are not necessarily performed accurately in order. On the contrary, various steps may be processed in reverse order or simultaneously. At the same time, other operations may be added to these processes, or one or more operations may be removed from these processes.

[0127] In addition, it should be noted that the use of words such as "first" and "second" to define components is only for the convenience of distinguishing the corresponding components. If not otherwise stated, the above words have no special meaning and cannot be understood 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 terms mentioned in the specification of this application may be selected by the applicant at his or her discretion, and their detailed meanings are explained in the relevant parts of the description of this article. In addition, it is required to understand this application not only by the actual terms used, but also by the meaning implied by each term.

[0128] As shown in this application, unless the context clearly indicates an exception, the words "a", "an", "a kind" and / or "the" do not refer to the singular, but also include the plural. Generally speaking, the terms "include" and "comprise" 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 arrangement, numerical expressions and numerical values ​​of the parts and steps set forth in these embodiments do not limit the scope of the application. Meanwhile, it should be understood that, for ease of description, the sizes of the various parts shown in the accompanying drawings are not drawn according to actual proportional relationships. The technology, methods and equipment known to those of ordinary skill in the relevant art may not be discussed in detail, but in appropriate cases, the technology, methods and equipment should be considered as a part of the specification. In all examples shown and discussed here, any specific value should be interpreted as being merely exemplary, rather than as a limitation. Therefore, other examples of exemplary embodiments may have different values. It should be noted that similar reference numerals and letters represent similar items in the following drawings, and therefore, once a certain item is defined in an accompanying drawing, it does not need to be further discussed in subsequent drawings.

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

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

[0132] Some aspects of the present application may be performed entirely by hardware, entirely by software (including firmware, resident software, microcode, etc.), or by a combination of hardware and software. The above hardware or software may be referred to as "data blocks", "modules", "engines", "units", "components" or "systems". The processor may 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, various aspects of the present application may be represented as computer products located in one or more computer-readable media, which include computer-readable program codes. For example, computer-readable media may include, but are not limited to, magnetic storage devices (e.g., hard disks, floppy disks, tapes ...), optical disks (e.g., compact disks CDs, digital versatile disks DVDs ...), smart cards, and flash memory devices (e.g., cards, sticks, key drives ...).

[0133] A computer-readable medium may include a propagated data signal containing computer program code, such as in baseband or as part of a carrier wave. The propagated signal may have a variety of manifestations, including electromagnetic, optical, etc., or a suitable combination. A computer-readable medium may be any computer-readable medium other than a computer-readable storage medium, which may be connected to an instruction execution system, device or apparatus to communicate, propagate or transmit a program for use. The program code on the computer-readable medium may be propagated via any suitable medium, including radio, cable, fiber optic cable, radio frequency signal, or similar medium, or any combination of the above mediums.

[0134] Similarly, it should be noted that in order to simplify the description of the disclosure of this application and thus help understand one or more embodiments of the invention, in the above description of the embodiments of the present application, multiple features are sometimes combined into one embodiment, figure or description thereof. However, this disclosure method does not mean that the subject of the present application requires more features 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 describing the number of components and attributes are used. It should be understood that such numbers used for the description of the embodiments are modified by the modifiers "about", "approximately" or "substantially" in some examples. Unless otherwise specified, "about", "approximately" or "substantially" indicate that the numbers are allowed to vary by ±20%. Accordingly, in some embodiments, the numerical parameters used in the specification are approximate values, which can be changed according to the required characteristics of individual embodiments. In some embodiments, the numerical parameters should take into account the specified significant digits and adopt the method of general digit retention. Although the numerical domains and parameters used to confirm the breadth of the range in some embodiments of the present application are approximate values, in specific embodiments, the setting of such numerical values ​​is as accurate as possible within the feasible range.

[0136] Although the present application has been described with reference to the current specific embodiments, ordinary technicians in this technical field should recognize that the above embodiments are only used to illustrate the present application, and various equivalent changes or substitutions may be made without departing from the spirit of the present application. Therefore, as long as the changes and modifications to the above embodiments are within the essential 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.

2. The method for calculating fouling behavior under the influence of zinc injection as claimed in 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 as claimed in claim 2, characterized in that: The corrosion product release rate after zinc injection is calculated by the following formula: in, 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 release rate of the second corrosion product.

4. The method for calculating fouling behavior under the influence of zinc injection as claimed in claim 2, characterized in that: 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 as claimed in 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 as claimed in claim 4, characterized in that: The fluid parameters include fluid temperature, boron concentration, and lithium concentration.

7. The method for calculating fouling behavior under the influence of zinc injection as claimed in claim 1, characterized in that: It also includes building mass transfer models and mass balance models, including: Constructing a mass transfer model of a steam generator, wherein the mass transfer model of the steam generator includes mass transfer from a mainstream to a near-wall layer caused by turbulence, and mass transfer from a near-wall layer to a wall caused by deposition; Constructing a core mass transfer model, wherein the core mass transfer model includes mass transfer from the mainstream to the near-wall layer due to boiling at the core, mass transfer from the mainstream to the near-wall layer due to turbulence, and mass transfer from the near-wall layer to the wall due to deposition; A mass balance model is constructed, 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 transferred by the steam generator deposition, and the mass flow rate transferred by the core node deposition.

8. The method for calculating fouling behavior under the influence of zinc injection as claimed in claim 7, characterized in that: Calculation of the fouling mass after zinc injection at 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; 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 core node deposition transfer and the mass flow rate of steam generator deposition transfer; The core node fouling mass is obtained according to the mass flow rate transmitted by the core node deposition, and the steam generator node fouling mass is obtained according to the mass flow rate transmitted by the steam generator deposition.

9. The method for calculating fouling behavior under the influence of zinc injection as claimed in 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.

10. The method for calculating fouling behavior under the influence of zinc injection as claimed in claim 9, 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.

11. The method for calculating fouling behavior under the influence of zinc injection as claimed in claim 9, wherein calculating the boron deposition quality after zinc injection comprises: Calculating the mass of boron-lithium compound precipitation according to the boron concentration distribution inside the dirt after zinc injection; Calculating the boron adsorption mass according to the boron concentration on the surface of the cladding layer and the dirt mass after the zinc injection; The boron deposition mass after the zinc injection is calculated according to the boron-lithium compound precipitation mass and the boron adsorption mass.

12. A device for calculating fouling behavior under the influence of zinc injection, characterized in that: include: at least one processor; as well as At least one memory having instructions stored thereon, wherein when the instructions are executed individually or collectively by the at least one processor, the computing device executes the method as claimed in any one of claims 1 to 11.

13. A computer readable medium for describing fouling behavior under the influence of zinc injection, characterized in that: The computer-readable medium stores instructions, which, when executed individually or collectively by at least one processor of a computing device, cause the computing device to execute the method as claimed in any one of claims 1 to 11.

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