Dirt risk calculation method and device of reactor and storage medium

Abstract

The invention provides a fouling risk calculation method and equipment of a reactor and a storage medium, and relates to the technical field of nuclear reactors. The reactor fouling risk calculation method provided by the invention comprises the following steps: step S110, acquiring input parameters; s120, the mass evaporation rate is calculated based on the input parameters; step S130, calculating the dirt thickness of the reactor core based on the mass evaporation rate; step S140, calculating boron deposition mass based on the dirt thickness of the reactor core; step S150, judging whether a convergence condition is met or not, if the convergence condition is met, entering step S160, and otherwise, returning to step S110; and step S160, outputting a calculation result. According to a risk formation mechanism and important phenomena caused by reactor fouling, the fouling thickness and the boron deposition quality of the reactor core are calculated based on the input parameters, so that risks, including CILC risks and CIPS risks, caused by fouling are evaluated.

Description

Technical Field

[0001] The present application relates to the technical field of nuclear reactors, and in particular to a method, device and storage medium for calculating the fouling risk of a reactor. Background Art

[0002] Reactor core fouling-induced axial power deviation (CIPS) and local cladding corrosion (CILC) will affect the safety and economy of reactor operation, and is also one of the key challenges for improving the performance of pressurized water reactors, which has attracted increasing attention in the nuclear power industry. The phenomenon caused by reactor core fouling is an important factor affecting the safety and economy of reactor operation, and the risk assessment of reactor core fouling may become an important issue of concern to the industry in the future. Summary of the invention

[0003] In view of this, the present application provides a method, device and storage medium for calculating the fouling risk of a reactor to implement the fouling risk analysis of the reactor core.

[0004] In a first aspect, the present application provides a method for calculating the fouling risk of a reactor, comprising:

[0005] Step S110, obtaining input parameters;

[0006] Step S120, calculating the mass evaporation rate based on the input parameters;

[0007] Step S130, calculating the fouling thickness of the core based on the mass evaporation rate;

[0008] Step S140, calculating the boron deposition mass based on the fouling thickness of the core;

[0009] Step S150, determine whether the convergence condition is met, if the convergence condition is met, proceed to step S160, otherwise return to step S110;

[0010] Step S160: output the calculation result.

[0011] In a second aspect, the present application provides a computing device, including:

[0012] at least one processor; and

[0013] At least one memory having instructions stored thereon, which, when executed individually or collectively by the at least one processor, cause the computing device to perform the method according to the first aspect.

[0014] In a third aspect, the present application provides a computer storage medium having instructions stored thereon, which, when executed individually or collectively by at least one processor of a computing device, causes the computing device to execute the method described in the first aspect.

[0015] Compared with the prior art, this application has the following advantages:

[0016] The fouling risk calculation method of the reactor provided in the present application includes: step S110, obtaining input parameters; step S120, calculating the mass evaporation rate based on the input parameters; step S130, calculating the fouling thickness of the core based on the mass evaporation rate; step S140, calculating the boron deposition mass based on the fouling thickness of the core; step S150, judging whether the convergence condition is met, if the convergence condition is met, entering step S160, otherwise returning to step S110; step S160, outputting the calculation result. The present application calculates the fouling thickness and boron deposition mass of the core based on the input parameters through the risk formation mechanism and important phenomena caused by reactor fouling, thereby evaluating the risks brought by fouling, including CILC risk and CIPS risk. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] 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:

[0018] Figure 1 It is a flow chart of a method for calculating the fouling risk of a reactor provided in an embodiment of the present application;

[0019] Figure 2 It is a flow chart of a method for calculating mass evaporation rate provided in an embodiment of the present application;

[0020] Figure 3 It is a flow chart of a method for calculating the fouling thickness of a core provided in an embodiment of the present application;

[0021] Figure 4 It is a schematic flow chart of a method for calculating boron deposition quality provided in an embodiment of the present application;

[0022] Figure 5 is a schematic diagram of a dirt grid division provided in an embodiment of the present application;

[0023] Figure 6 It is a structural diagram of a computing device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0024] 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.

[0025] 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.

[0026] 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.

[0027] 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 present 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.

[0028] In addition, although the terms used in this application are selected from well-known and commonly used terms, some of the terms mentioned in this application specification 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.

[0029] Flowcharts are used in this application to illustrate the operations performed by the apparatus or equipment according to the embodiments of the application. It should be understood that the preceding or following operations are not necessarily performed precisely in order. On the contrary, the 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.

[0030] When the reactor is in operation, corrosion products (nickel, iron, etc.) on the coolant system pipes will be released into the coolant and deposited on the surface of the fuel assembly cladding to form scale. Boron and lithium hydroxide accumulate in the porous gaps of the scale. When boron accumulates to a certain extent, it will precipitate on the scale, resulting in a decrease in the power of the upper part of the fuel assembly, and the power peak will move downward, that is, the CIPS phenomenon occurs. If the scale deposition in a local position is thick, the coolant will not be able to flow through the scale and cool the surface of the fuel cladding, resulting in a high temperature of the fuel cladding. If the fuel cladding is at a very high temperature for a long time, it will accelerate the corrosion and failure of the fuel cladding, resulting in the CILC phenomenon. When the reactor power is increased, the average temperature of the reactor coolant increases, or the core power peak factor increases, the CIPS / CILC phenomenon is very easy to occur, and usually occurs in high-power fuel assemblies in the core.

[0031] In the embodiment of the present application, during the calculation of the fouling risk of the reactor, the space of the calculation objects (such as the core, steam generator, etc.) is relatively large. In order to ensure the accuracy of the calculation results, the calculation objects can be divided into multiple nodes, and calculations are performed for each node separately. Then, in the embodiment of the present application, calculations are performed for the calculation objects, which means calculations are performed for multiple nodes of the divided calculation objects.

[0032] Figure 1 Schematic diagram of a method for calculating the fouling risk of a reactor provided in an embodiment of the present application. Figure 1 As shown, the method for calculating the fouling risk of a reactor includes the following steps:

[0033] Step S110: Obtain input parameters.

[0034] Input parameters include some parameters required for subsequent calculations. In actual operation, the user can provide input parameters by providing input text files, calculation results of other modules (such as computational fluid dynamics software, etc.), restart file information, etc.

[0035] In some embodiments, certain parameter values ​​that require solutions may be iteratively updated during the iterative calculation process, such as dirt thickness, and their initial values ​​need to be set at each time step. For example, the initial values ​​of the input parameters of the current time step may be set based on the calculation results of the previous time step.

[0036] Step S120: Calculate the mass evaporation rate based on the input parameters.

[0037] The present application embodiment calculates the mass evaporation rate based on the input parameters, which can improve the calculation accuracy and thus improve the accuracy of the fouling risk analysis. Figure 2 , the calculation of mass evaporation rate based on input parameters includes the following steps:

[0038] Step S201, constructing a momentum equation.

[0039] The momentum equation is constructed based on the heat flux density transferred by heat conduction, the mass evaporation rate, the vapor phase enthalpy of the fouling surface, and the liquid phase enthalpy of the fouling surface. An example of the relationship of the momentum equation is as follows:

[0040] (1)

[0041] Where: Q is the heat flux density transferred by heat conduction, unit is W / m 2 ;

[0042] x is the coordinate axis perpendicular to the dirt surface;

[0043] G evap is the mass evaporation rate, in kg / m 2 ·s;

[0044] H l is the liquid phase enthalpy of the dirt surface, in J / kg;

[0045] H v It is the vapor phase enthalpy of dirt surface, in J / kg.

[0046] Among them, Q, H l , H v is the input parameter.

[0047] Step S202: construct an energy equation.

[0048] The energy equation is constructed based on the vapor pressure in the dirt, the liquid pressure in the dirt, the surface tension of the liquid inside the dirt, the dirt contact angle and the critical pore radius of the dirt. An example of the relationship of the energy equation is as follows:

[0049] (2)

[0050] Where: P v is the vapor phase pressure in the dirt, in Pa;

[0051] P l is the liquid phase pressure in the dirt, in Pa;

[0052] is the surface tension of the liquid inside the dirt, in N / m;

[0053] is the dirt contact angle, in degrees;

[0054] is the critical pore radius of dirt, in meters.

[0055] in, , is the input parameter.

[0056] Step S203: construct a heat transfer equation.

[0057] The heat transfer equation is constructed based on the internal temperature of the dirt, the saturated temperature of the liquid inside the dirt, the mass evaporation rate, and the latent heat of vaporization of the liquid inside the dirt. An example of the relationship of the heat transfer equation is as follows:

[0058] (3)

[0059] Where: h v is the volume heat transfer coefficient, in J / m 3 ·s·℃;

[0060] T crud is the internal temperature of the dirt, in °C;

[0061] T sat is the saturation temperature of the liquid inside the dirt, in °C;

[0062] G evap is the mass evaporation rate, in kg / m 2 ·s;

[0063] h fg It is the latent heat of vaporization of the liquid inside the dirt, in J / kg.

[0064] Among them, h v 、T crud 、T sat 、h fg is the input parameter.

[0065] Step S204: Calculate the mass evaporation rate based on the momentum equation, the energy equation and the heat transfer equation.

[0066] In actual operation, step S204 may include the following steps:

[0067] 1) Set the dirt side boundary value;

[0068] 2) Set the upper limit of the dirt layer, which should not exceed 500;

[0069] 3) Solve the momentum equation. When the solution of equation (1) converges, proceed to the next step of calculation;

[0070] 4) Solve the energy equation;

[0071] 5) Solve the heat transfer equation. When the solution of equation (3) converges, otherwise return to step 3);

[0072] 6) When the calculation reaches the target condition, such as the calculation has reached the evaporation position, it ends, otherwise it returns to step 2).

[0073] Step S130: Calculate the fouling thickness of the core based on the mass evaporation rate.

[0074] Calculating the fouling thickness of the core based on the mass evaporation rate includes: obtaining the mainstream nickel solubility and near-wall nickel solubility of the core; when the near-wall nickel solubility of the core is greater than the mainstream nickel solubility of the core, constructing a mass transfer model of the core based on the mass evaporation rate, the mainstream nickel solubility of the core, the total concentration of corrosion products in the coolant system, and the mass flow rate of fouling deposition transfer in the core; otherwise, constructing a mass transfer model of the core based on the mass evaporation rate, the near-wall nickel solubility of the core, the total concentration of corrosion products in the coolant system, and the mass flow rate of fouling deposition transfer in the core; constructing a mass balance model of the coolant system based on the total concentration of corrosion products in the coolant system, the mass flow rate of fouling deposition transfer in the core, and the total release rate of corrosion products in the coolant system; solving the mass flow rate of fouling deposition transfer in the core based on the mass transfer model of the core and the mass balance model of the coolant system; and calculating the fouling thickness of the core based on the mass flow rate of fouling deposition transfer in the core.

[0075] The embodiment of the present application constructs a mass transfer model and a mass balance model, calculates the dirt thickness based on the mass transfer model and the mass balance model, and comprehensively considers the factors affecting the dirt deposition thickness, so that the calculation result is more accurate and reasonable.

[0076] In some embodiments, a mass transfer model of the downflow system may also be constructed, specifically including: obtaining the nickel solubility of the downflow system; constructing the mass transfer model of the downflow system based on the nickel solubility of the downflow system and the mass flow rate of the fouling deposition transferred by the downflow system. The mass flow rate of the fouling deposition transferred by the downflow system may be calculated based on the mass transfer model of the downflow system, and when constructing the mass balance model, the fouling mass of the downflow system is also considered, that is, the mass balance model of the coolant system is also constructed based on the mass flow rate of the fouling deposition transferred by the downflow system, and the mass flow rate of the fouling deposition transferred by the core is also solved based on the mass transfer model of the downflow system.

[0077] In some embodiments, a mass transfer model of the steam generator may also be constructed. Specifically, it includes: obtaining the mainstream nickel solubility and near-wall nickel solubility of the steam generator; when the near-wall nickel solubility of the steam generator is greater than the mainstream nickel solubility of the steam generator, the mass transfer model of the steam generator is constructed based on the mass evaporation rate, the mainstream nickel solubility of the steam generator, the total concentration of corrosion products in the coolant system, and the mass flow rate of fouling deposition transfer of the steam generator; otherwise, the mass transfer model of the steam generator is constructed based on the mass evaporation rate, the near-wall nickel solubility of the steam generator, the total concentration of corrosion products in the coolant system, and the mass flow rate of fouling deposition transfer of the steam generator. When constructing the mass balance model, the fouling mass of the steam generator is also considered, that is, the mass balance model of the coolant system is also constructed based on the mass flow rate of fouling deposition transfer of the steam generator, and the mass flow rate of fouling deposition transfer of the core is also solved based on the mass transfer model of the steam generator.

[0078] In the embodiment of the present application, when constructing the mass balance model, the fouling mass inside the core, inside the steam generator and inside the downflow system is considered at the same time, and the location where the fouling is generated and disappears in the primary circuit is fully considered, so that the fouling distribution in the entire circuit is more reasonable and the calculated fouling thickness is more accurate. It is understandable that in some other embodiments, the arrangement in the reactor circuit may be different, and the steam generator and / or downflow system may not be considered, thereby omitting the corresponding calculation steps.

[0079] In some embodiments, calculating the thickness of the dirt in the core based on the mass flow of the dirt deposition in the core includes: calculating the mass per unit area of ​​the dirt in the core based on the mass flow of the dirt deposition in the core; and calculating the thickness of the dirt in the core based on the mass per unit area of ​​the dirt in the core and the dirt density. In the embodiments of the present application, the dirt thickness is directly solved by a given dirt density, without considering the dirt density at different positions separately, thereby reducing the amount of calculation.

[0080] In an exemplary embodiment, please refer to Figure 3 , the calculation method of dirt thickness includes the following steps:

[0081] Step S301, calculating the mainstream nickel solubility of the steam generator.

[0082] The nickel solubility can be obtained by solving a function based on the pH value of the fluid, and the pH value of the fluid can be obtained by a table lookup method. In some embodiments, the calculation relationship of the nickel solubility is as follows:

[0083] (4)

[0084] Where: Con Ni is the nickel solubility in ppb;

[0085] a1, a2 and a3 are coefficients, which can be obtained by fitting based on corrosion test data or nuclear power plant operation data, that is, a1, a2 and a3 are input parameters.

[0086] The mainstream nickel solubility of the steam generator can be calculated by the calculation relationship (4) of nickel solubility and the mainstream pH value of the steam generator. It should be noted that in the above embodiment, the nickel solubility is solved based on the calculation relationship related to the fluid pH value. In some other embodiments, the calculation can also be performed based on other calculation relationships of nickel solubility.

[0087] Step S302: Calculate the nickel solubility near the wall of the steam generator.

[0088] The nickel solubility near the wall of the steam generator can be calculated by using the calculation formula (4) of nickel solubility and the pH value of the fluid near the wall of the steam generator: wall .

[0089] In some embodiments, the pH value of the fluid near the wall of the steam generator may be calculated based on the externally input temperature, boron concentration, and lithium concentration of the fluid near the wall of the steam generator. The pH value may also be obtained by a table lookup method.

[0090] Step S303: construct a mass transfer model of the steam generator.

[0091] The mass transfer model of the steam generator is constructed based on the nickel solubility of the steam generator, the total concentration of corrosion products in the coolant system, and the mass flow rate of fouling deposition in the steam generator. In an exemplary embodiment, the mass transfer model of the steam generator considers the mass transfer from the mainstream to the near-wall layer caused by turbulence, the mass transfer from the near-wall layer to the wall caused by deposition, etc., and the relationship is as follows:

[0092] (5)

[0093] Where: Con is the total concentration of corrosion products in the coolant system, in ppb.

[0094] Con wall is the near-wall nickel solubility of the steam generator, in ppb. When the near-wall nickel solubility of the steam generator is greater than the mainstream nickel solubility, the near-wall nickel solubility of the steam generator in equation (5) is equal to the mainstream nickel solubility, that is, the mass transfer model of the steam generator is constructed based on the mainstream nickel solubility of the steam generator.

[0095] F is the factor converting nickel solubility into total concentration.

[0096] is the mass transfer coefficient caused by the mixing of the near-wall layer and the mainstream of the steam generator, in kg / s·m2 .

[0097] G sed The mass flow rate transferred for the fouling deposition of the steam generator, in kg / s·m 2 ;

[0098] Among them, F and is the input parameter.

[0099] Step S304: Calculate the mainstream nickel solubility in the core.

[0100] The pH value of the core mainstream fluid can be calculated based on the externally input core mainstream fluid temperature, boron concentration, and lithium concentration. Combined with the calculation relationship (4) of nickel solubility, the core mainstream nickel solubility can be calculated.

[0101] Step S305, calculating the nickel solubility near the core wall.

[0102] Based on the external input of the fluid temperature, boron concentration, and lithium concentration near the core wall, the pH value of the fluid near the core wall can be calculated. Combined with the calculation relationship of nickel solubility (4), the nickel solubility near the core wall Con can be calculated. wnode .

[0103] Step S306: construct a mass transfer model of the core.

[0104] The mass transfer model of the core is constructed based on the nickel solubility of the core, the total concentration of corrosion products in the coolant system, and the mass flow rate of fouling deposition in the core. In an exemplary embodiment, the mass transfer model of the core considers 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, etc. The relationship is as follows:

[0105] (6)

[0106] Where: is the mass transfer efficiency due to boiling;

[0107] G evap is the mass evaporation rate, in kg / s·m 2 ;

[0108] Con is the total concentration of corrosion products in the coolant system, in ppb;

[0109] Con wnodeis the near-wall nickel solubility of the core, in ppb. When the near-wall nickel solubility of the core is greater than the mainstream nickel solubility, the near-wall nickel solubility of the core in equation (6) is equal to the mainstream nickel solubility, that is, the mass transfer model of the core is constructed based on the mainstream nickel solubility of the core.

[0110] F is the factor converting nickel solubility into total concentration.

[0111] is the mass transfer coefficient caused by the mixing of the core near wall layer and the mainstream, in kg / s·m 2 ;

[0112] G node The mass flow rate of fouling deposition in the core, in kg / s·m 2 .

[0113] in, , G evap , and F are input parameters.

[0114] Step S307: construct a mass transfer model of the downstream system.

[0115] First, the nickel solubility of the downstream system is obtained. Then, a mass transfer model of the downstream system is constructed based on the nickel solubility of the downstream system and the mass flow rate of the fouling deposition transferred by the downstream system. In an exemplary embodiment, the fluid pH value of the downstream system can be calculated based on the external input of the fluid temperature, boron concentration, and lithium concentration of the downstream system. Combined with the calculation relationship (4) of the nickel solubility, the nickel solubility of the downstream system can be calculated. ld The mass transfer model of the downflow system is expressed as follows:

[0116] (7)

[0117] Where: G ld The mass flow rate of dirt deposits in the downstream system, in kg / s·m 2 ;

[0118] G sld is the discharge flow rate, in kg / s·m 2 ;

[0119] Con ld is the nickel solubility in the downstream system, in ppb;

[0120] F p is the particle removal rate;

[0121] F s is the solute removal rate.

[0122] Among them, Gsld 、F p and F s is the input parameter.

[0123] Step S308: construct a mass balance model of the coolant system.

[0124] A mass balance model of the coolant system is constructed based on the total concentration of corrosion products in the coolant system, the mass flow rate of fouling deposits transferred by the steam generator, the mass flow rate of fouling deposits transferred by the core, the mass flow rate of fouling deposits transferred by the downflow system, and the total release rate of corrosion products in the coolant system. In an exemplary embodiment, the mass balance model of the coolant system considers the fouling mass removal of the downflow system, the total release of corrosion products in the coolant system, the fouling mass in the steam generator, and the fouling mass inside the core, and the relationship is as follows:

[0125] (8)

[0126] Where: m total is the mass of coolant in the coolant system, in kg / m 2 ;

[0127] Con is the total concentration of corrosion products in the coolant system, in ppb;

[0128] t is time, in seconds;

[0129] G node The mass flow rate of fouling deposition in the core, in kg / s·m 2 ;

[0130] G sed The mass flow rate transferred for the fouling deposition of the steam generator, in kg / s·m 2 ;

[0131] G ld The mass flow rate of dirt deposits in the downstream system, in kg / s·m 2 ;

[0132] G dis is the total release rate of corrosion products in the coolant system, in kg / s·m 2 .

[0133] Among them, m total and G dis It should be noted that, without considering the steam generator, the parameter G in formula (8) can be sed Similarly, without considering the downflow system, the parameter G in formula (8) can be ld Remove.

[0134] In some embodiments, the total release rate G of the corrosion products in the coolant system can be calculated based on the mainstream pH value in the coolant system. dis The following is an example of a calculation relationship for the total release rate of corrosion products in a coolant system:

[0135] G dis =f 1 (PH dis ) (9)

[0136] Where: G dis is the total release rate of corrosion products in the coolant system, in kg / m 2 ·s;

[0137] f 1 is the calculation function of the total release rate of corrosion products in the coolant system;

[0138] PH dis is the mainstream pH value in the coolant system. This parameter is an input parameter.

[0139] It should be noted that, in the above embodiment, the total release rate of corrosion products in the coolant system is calculated based on the mainstream pH value in the coolant system. In other embodiments, the total release rate of corrosion products in the coolant system may also be calculated based on other calculation formulas.

[0140] Step S309: Calculate the mass flow rate of dirt deposition transfer.

[0141] Based on the mass transfer model of the steam generator, the mass transfer model of the core, the mass transfer model of the downflow system and the mass balance model of the coolant system, the mass flow rate of the fouling deposition transfer of the steam generator and the mass flow rate of the fouling deposition transfer of the core are solved. That is, the combined relationship (5), (6), (7) and (8) can be solved to obtain G node In some embodiments, G can also be solved sed and Con.

[0142] Step S310: Calculate the dirt thickness.

[0143] The fouling thickness can be calculated based on the mass flow of fouling deposition transfer calculated in step S309. In some embodiments, the fouling mass per unit area can be calculated based on the mass flow of fouling deposition transfer, and then the fouling thickness can be calculated based on the fouling mass per unit area and the fouling density. For example, the fouling thickness of the core can be calculated using equations (10) and (11). Similarly, G sed The fouling thickness of the steam generator is calculated.

[0144] (10)

[0145] (11)

[0146] Where: m node is the mass per unit area of ​​core dirt, in kg / m 2 ;

[0147] G node The mass flow rate of fouling deposition in the core, in kg / s·m 2 ;

[0148] t is time, in seconds;

[0149] THC node is the thickness of the core fouling, in m;

[0150] is the dirt density, in kg / m 3 .

[0151] in, is the input parameter.

[0152] When constructing the mass transfer model, the embodiments of the present application take into account the inflow and outflow of coolant and corrosion products in the near-wall coolant layer; the effects of turbulent mixing and boiling circulation, which cause mass transfer; the dissolution and deposition of dirt on the wall; and the increase or decrease of corrosion products in the coolant. These processes make the process of dirt deposition from the mainstream coolant to the wall more detailed and the mass transfer process more accurate.

[0153] Step S140: Calculate the boron deposition mass based on the fouling thickness of the core.

[0154] The embodiment of the present application considers two boron deposition mechanisms, namely boron-lithium compound deposition and boron adsorption, and combines these two deposition mechanisms to calculate the total boron deposition mass, thereby realizing the boron deposition mass calculation of the reactor, making the calculation result more accurate.

[0155] Please refer to Figure 4 , the calculation method of boron deposition quality includes the following steps:

[0156] Step S401, calculating the deposited mass of boron-lithium compounds inside the dirt.

[0157] The mass of boron-lithium compound deposition inside the dirt, that is, the mass of boron-lithium compound deposition inside the dirt, can be calculated through a certain relationship, such as the mass of boron-lithium compound deposition inside the dirt can be calculated based on the thickness of the boron deposition layer, the boron concentration in the coolant, and the concentration factor. The thickness of the boron deposition layer can be calculated based on the dirt thickness, such as based on the relationship between the boron deposition layer thickness inside the dirt and the dirt thickness fitted according to the test data, or based on the concentration of the target substance (lithium, boron, etc.) inside the dirt and the dirt thickness. That is, the mass of boron-lithium compound deposition inside the dirt can be calculated based on the concentration of the target substance inside the dirt, the dirt thickness of the core, the boron concentration in the coolant, and the concentration factor.

[0158] In some embodiments, obtaining the thickness of the boron deposition layer inside the dirt includes: obtaining the concentration of the target substance inside the dirt; when the concentration of the target substance exceeds the solubility of the deposited boron lithium compound, obtaining the thickness of the boron deposition layer based on the dirt thickness. Wherein, obtaining the concentration of the target substance inside the dirt includes: dividing the dirt into multiple layers of grids based on the dirt thickness; calculating the concentration of the target substance at the grid. Then, when the concentration of the target substance at the grid exceeds the solubility of the deposited boron lithium compound, the thickness of the boron deposition layer is obtained based on the dirt thickness and the position of the grid. The embodiment of the present application divides the dirt into multiple layers of grids and performs calculations based on the grid units, so that the calculation results are more accurate.

[0159] Since the microstructure of dirt is a capillary porous body, the porous body is considered to be a group of interconnected pipes, the larger vertical pores are filled with steam, and the smaller pores are filled with liquid. Considering the diffusion of the target substance i (lithium, boron, etc.) inside the dirt and the convection caused by the mass flow in the dirt, the mass flow convection equations are constructed for the liquid phase and the vapor phase in the dirt respectively, and then the concentration of the target substance inside the dirt is obtained by solving it, making the calculation results more accurate. In detail, calculating the concentration of the target substance at the grid includes: constructing a mass flow convection equation for the liquid phase in the dirt based on the diffusion coefficient of the target substance in the liquid phase in the dirt, the total mass flow rate of the target substance at the grid in the liquid phase in the dirt, and the mass concentration of the target substance at the grid in the liquid phase in the dirt; constructing a mass flow convection equation for the vapor phase in the dirt based on the diffusion coefficient of the target substance in the vapor phase in the dirt, the total mass flow rate of the target substance at the grid in the vapor phase in the dirt, and the mass concentration of the target substance at the grid in the vapor phase in the dirt; solving the mass concentration of the target substance at the grid in the liquid phase in the dirt based on the mass flow convection equation for the liquid phase in the dirt, the mass flow convection equation for the vapor phase in the dirt, the total mass flow rate of the target substance at the grid in the liquid phase in the dirt and the total mass flow rate of the target substance at the grid in the vapor phase in the dirt, and the relationship between the mass concentration of the target substance at the grid in the liquid phase in the dirt and the mass concentration of the target substance at the grid in the vapor phase in the dirt, and using the solved mass concentration of the target substance at the grid in the liquid phase in the dirt as the concentration of the target substance at the grid.

[0160] In an exemplary embodiment, obtaining the thickness of the boron deposition layer inside the dirt includes the following steps:

[0161] Step S1111, dividing the grid.

[0162] Please refer to Figure 5 , dirt is deposited on the surface of the fuel assembly cladding, in the figure, q w is the heat flux density on the shell surface, in W / m 2 ;q surf is the heat flux density on the dirt surface, in W / m 2 . The grid is evenly divided based on the given dirt thickness, and the thickness of each grid layer is dx. The grid is divided from the dirt surface (close to the fluid side) to the cladding surface in sequence and the parameters at each grid layer are determined. For example, if the dirt is evenly divided into N-1 layers of grids, the N-1 layers of grids share N surfaces, namely surfaces x(1), x(2), ..., x(n), x(n+1), ..., x(N). The thickness of the nth grid layer is dx(n). It can be understood that, considering the large surface size of the fuel assembly cladding, each layer of grid can also be divided into multiple grids in a direction perpendicular to the dirt deposition direction, and calculations are performed cyclically for each grid.

[0163] In the above embodiment, the grid is divided sequentially from the dirt surface to the cladding surface. In some other embodiments, the grid may also be divided sequentially from the cladding surface to the dirt surface, which is not limited in the embodiments of the present application.

[0164] Step S1112: Calculate the concentration of the target substance at the grid, wherein the target substance may include lithium, or boron, or lithium and boron.

[0165] Considering the diffusion of the target substance i (lithium, boron, etc.) inside the dirt and the convection caused by the mass flow inside the dirt, the mass flow convection equations are constructed for the liquid phase and the vapor phase inside the dirt. Among them, at the kth grid layer, the mass flow convection equations for the liquid phase inside the dirt and the mass flow convection equations for the vapor phase inside the dirt are respectively as follows:

[0166] (12)

[0167] (13)

[0168] (14)

[0169] Where: G i,l,k is the total mass flow rate of target substance i at the k-layer grid in the liquid phase of the dirt, in kg / s·m 2 ;

[0170] D i,lis the diffusion coefficient of target substance i in the liquid phase of the dirt, in m 2 / s;

[0171] is the density of the liquid phase in the dirt, in kg / m 3 ;

[0172] A l The flow area of ​​the dirt filled with liquid phase, in m 2 ;

[0173] C i,l,k is the mass concentration of the target substance at the k-layer grid in the liquid phase in the dirt, in ppb;

[0174] G l is the mass flow rate of the liquid phase in the dirt, in kg / s·m 2 ;

[0175] G i,v,k is the total mass flow rate of target substance i at the k-layer grid in the vapor phase of the dirt, in kg / s·m 2 ;

[0176] D i,v is the diffusion coefficient of target substance i in the vapor phase of the dirt, in m 2 / s;

[0177] is the vapor phase density in the dirt, in kg / m 3 ;

[0178] A v The flow area of ​​the dirt filled with vapor phase, in m 2 ;

[0179] C i,v,k is the mass concentration of the target substance at the k-layer grid in the vapor phase in the dirt, in ppb;

[0180] G v is the mass flow rate of the vapor phase in the dirt, in kg / s·m 2 ;

[0181] B is the coefficient.

[0182] Among them, D i,l , , A l , G l , D i,v , , G v , A v , B are input parameters.

[0183] In steady state, the net flow of target substance i at any position in the dirt is 0, and the following relationship exists at the k-layer grid:

[0184] G i,l,k + G i,v,k = 0 (15)

[0185] By combining equations (12)-(15), we can obtain C i,l,k , the solved C i,l,k as the concentration of target substance i at the grid.

[0186] Step S1113, calculating the thickness of the boron deposition layer.

[0187] Based on the concentration distribution of the target substance i inside the dirt, it is determined whether the target substance i at the grid has reached the critical concentration, that is, whether it exceeds the solubility of the deposited boron-lithium compound, thereby obtaining the thickness d of the boron deposition layer. B . Boron deposition layer thickness d B The calculation formula example is as follows:

[0188] (16)

[0189] Where, d B is the thickness of the boron deposition layer, in m;

[0190] THC node is the thickness of the core fouling, in m;

[0191] x(j) is the thickness from the dirt surface to the jth grid layer, assuming that the concentration of target substance i at the jth grid layer exceeds the solubility of the deposited boron-lithium compound. If the thickness of each grid layer is dx, then the thickness from the dirt surface to the jth grid layer is j·dx, in meters.

[0192] The solubility of the deposited boron-lithium compound can be used as an input parameter or obtained based on the internal temperature of the dirt. For example, the solubility of the deposited boron-lithium compound is obtained based on an empirical relationship related to temperature:

[0193] (17)

[0194] Where SI is the solubility of the deposited boron-lithium compound, in ppb;

[0195] T crud is the internal temperature of the dirt, in °C.

[0196] Among them, T crud is the input parameter.

[0197] The mass of boron-lithium compound deposition is calculated based on the thickness of the boron deposition layer, the boron concentration in the coolant, and the concentration factor. In some embodiments, the calculation formula for the mass of boron-lithium compound deposition is as follows:

[0198] (18)

[0199] Where M b,1 is the mass of boron-lithium compound deposition, in kg;

[0200] k B is the concentration factor;

[0201] C coolant B is the boron concentration in the coolant, in ppb;

[0202] is the coolant density, in kg / m 3 ;

[0203] A is the calculated area of ​​the cladding surface, in m 2 .

[0204] Among them, k B , C coolant B , , A is the input parameter.

[0205] Step S402: Calculate the boron adsorption mass on the dirt surface.

[0206] The boron adsorption mass on the fouling surface, i.e., the boron mass adsorbed on the fouling surface, can be calculated by a certain relationship, such as the boron adsorption mass can be calculated based on the boron concentration on the cladding surface and the fouling mass in the core. In some embodiments, calculating the boron adsorption mass on the fouling surface includes the following steps:

[0207] Step S1201, obtaining the boron concentration on the surface of the cladding.

[0208] The boron concentration on the cladding surface can be an input parameter or calculated based on a related calculation formula. In an exemplary embodiment, the boron concentration on the cladding surface is calculated based on the concentration factor and the boron concentration in the coolant. The calculation relationship is as follows:

[0209] (19)

[0210] (20)

[0211] In the formula, C clad B is the boron concentration on the cladding surface, in ppb;

[0212] C coolant B is the boron concentration in the coolant, in ppb;

[0213] CF B is the concentration factor;

[0214] G evap is the mass evaporation rate, in kg / s·m 2 ;

[0215] THC node is the thickness of the core fouling, in m;

[0216] is the coolant density, in kg / m 3 ;

[0217] D B is the diffusion coefficient of boron in the coolant, in m 2 / s;

[0218] P is the dirt porosity.

[0219] Among them, C coolant B , , D B , P is the input parameter.

[0220] Step S1202: Calculate the boron adsorption mass based on the boron concentration and the dirt mass on the cladding surface.

[0221] In actual operation, the mass of boron adsorbed on the fouling surface can be obtained based on the relationship between the boron adsorption mass, the boron concentration on the cladding surface and the fouling mass fitted according to the experimental data. The relationship is shown below:

[0222] (twenty one)

[0223] Among them, b 1 , b 2 and b 3 is a constant, is an input parameter;

[0224] M crud is the dirt mass, in kg, which can be based on the dirt mass per unit area of ​​the core m node Calculated;

[0225] C clad B is the boron concentration on the cladding surface, in ppb.

[0226] Step S403: Calculate the boron deposition mass.

[0227] The boron deposition mass M is obtained by summing the boron-lithium compound deposition mass and the boron adsorption mass. b , the relationship example is as follows:

[0228] (twenty two)

[0229] Step S150: determine whether the convergence condition is met. If the convergence condition is met, proceed to step S160; otherwise, return to step S110.

[0230] Judging whether the convergence condition is met may include judging whether the target parameter meets the convergence condition, and may also include judging whether the time point reaches the end time, or may include both the judgment of the target parameter and the judgment of the time point. If the target parameter does not meet the convergence condition, the input parameter is updated for iterative calculation, otherwise proceed to the next step. If the time point reaches the end time, it ends, otherwise the value of the input parameter is set for subsequent calculation. After each time step is calculated, the time point of the current calculation is updated. It should be noted that the values ​​of some input parameters are related to time, and these input parameters can be interpolated in time, such as the concentration of boron and lithium in the coolant.

[0231] The target parameter may include one or more parameters obtained during the calculation process. In an exemplary embodiment, the target parameter includes the calculated mass evaporation rate and the total concentration of corrosion products in the coolant system, so that the solution process is more accurate. Specifically, judging whether the target parameter meets the convergence condition includes: judging whether the error between the calculated mass evaporation rate and the first preset value is less than the first threshold; judging whether the error between the calculated total concentration of corrosion products in the coolant system and the second preset value is less than the second threshold. When the error between the calculated mass evaporation rate and the first preset value is less than the first threshold, the convergence condition is met. When the error between the calculated total concentration of corrosion products in the coolant system and the second preset value is less than the second threshold, the convergence condition is met. When both the mass evaporation rate and the total concentration of corrosion products in the coolant system meet the convergence condition, the current time step calculation is completed, otherwise the input parameters are updated to perform iterative calculation of the current time step.

[0232] Step S160: output the calculation result.

[0233] In some embodiments, the calculation result of the current time step may be output after each time step calculation is completed. In other embodiments, the calculation result may be output after the end time is reached at the time point and the calculation of all time steps is completed. The form of outputting the calculation result may be set as required.

[0234] Figure 6 Schematic diagram of a computing device provided in an embodiment of the present application. Figure 6 As shown, computing device 600 includes one or more processors 610 , one or more memories 620 coupled to processor 610 , and one or more communication modules 640 coupled to processor 610 .

[0235] The communication module 640 is used for two-way communication. The communication module 640 has at least one antenna to facilitate communication. The communication interface may represent any interface necessary for communicating with other network elements.

[0236] Processor 610 may be of any type suitable for the local technology network, and may include, as non-limiting examples, one or more of: a general purpose computer, a special purpose computer, a microprocessor, a digital signal processor (DSP), and a processor based on a multi-core processor architecture. Computing device 600 may have multiple processors, such as application specific integrated circuit chips, which are driven in time to a clock that synchronizes a master processor.

[0237] The memory 620 may include one or more non-volatile memories and one or more volatile memories. Examples of non-volatile memories include, but are not limited to, read-only memory (ROM) 624, electrically programmable read-only memory (EPROM), flash memory, hard disk, compact disk (CD), digital video disk (DVD), and other magnetic and / or optical memories. Examples of volatile memories include, but are not limited to, random access memory (RAM) 622 and other volatile memories that do not persist during the duration of a power outage.

[0238] The computer program 630 includes computer executable instructions that are executed by the associated processor 610. The computer program 630 may be stored in the ROM 624. The processor 610 may perform any suitable actions and processes by loading the computer program 630 into the RAM 622.

[0239] The embodiments of the present application can be implemented by a computer program 630, so that the computing device 600 can execute the reference Figure 1-Figure 4 Any process disclosed in the discussion. The embodiments of the present application may also be implemented by hardware or by a combination of software and hardware.

[0240] In some embodiments, the computer program 630 may be tangibly embodied in a computer-readable medium, which may be contained in the computing device 600 (e.g., memory 620) or other storage device accessible to the computing device 600. The computing device 600 may load the computer program 630 from the computer-readable medium to the RAM 622 for execution. The computer-readable medium may include any type of tangible non-volatile memory, such as ROM, EPROM, flash memory, hard disk, CD, DVD, etc. The computer-readable medium has the computer program 630 stored thereon.

[0241] Generally, various embodiments of the present application may be implemented in hardware or dedicated circuits, software, logic, or any combination thereof. Certain aspects may be implemented in hardware, while other aspects may be implemented in firmware or software, which may be performed by a controller, microprocessor, or other computing device. Although various aspects of the embodiments of the present application are shown and described as block diagrams, flow charts, or using some other graphical representations, it should be understood that, as non-limiting examples, the blocks, devices, systems, techniques, or methods described herein may be implemented in hardware, software, firmware, dedicated circuits or logic, general hardware or controllers or other computing devices, or some combination thereof.

[0242] The present application also provides at least one computer program product tangibly stored on a non-transitory computer readable storage medium. The computer program product includes computer executable instructions, such as instructions included in program modules, which are executed in a device on a target real or virtual processor to perform the above-mentioned reference Figure 1-Figure 4 The method described. Typically, program modules include routines, programs, libraries, objects, classes, components, data structures, etc. that perform specific tasks or implement specific abstract data types. In various embodiments, the functions of program modules can be combined or separated between program modules as needed. Machine executable instructions for program modules can be executed in local or distributed devices. In distributed devices, program modules can be located in local and remote storage media.

[0243] The program code for executing the method of the present application can be written in any combination of one or more programming languages. These program codes can be provided to a processor or controller of a general-purpose computer, a special-purpose computer or other programmable data processing equipment so that when the program code is executed by the processor or controller, the function / operation specified in the flow chart and / or the block diagram is realized. The program code can be executed completely on the machine as an independent software package, partially on the machine, partially on the machine, partially on a remote machine, partially on a remote machine, or all on a remote machine or server.

[0244] In the context of this application, computer program codes or related data may be carried by any appropriate carrier to enable a device, apparatus or processor to perform various processes and operations as described above. Examples of carriers include signals, computer readable media, etc.

[0245] The computer readable medium may be a computer readable signal medium or a computer readable storage medium. The computer readable medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared or semiconductor systems, devices or apparatuses, or any suitable combination of the foregoing. More specific examples of computer readable storage media include an electrical connection having one or more conductors, a portable computer floppy disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0246] In addition, although the operations are described in a specific order, this should not be construed as requiring to perform these operations in the specific order or sequence shown, or to perform all the operations shown, to obtain the desired result. In some cases, multitasking and parallel processing may be advantageous. Similarly, although several specific implementation details are included in the above discussion, these details should not be interpreted as limiting the scope of the application, but can be interpreted as a description of the specific features of a particular embodiment. Some of the features described in the context of a separate embodiment may also be implemented in combination in a single embodiment. On the contrary, the various features described in the context of a single embodiment may also be implemented in multiple embodiments individually or in any suitable sub-combination.

[0247] Although the present application has been described in language specific to structural features and / or methodological acts, it should be understood that the present application defined in the appended claims is not necessarily limited to the specific features or acts described above. Instead, the specific features and acts described above are disclosed as example forms of implementing the claims.

Claims

1. A method for calculating the fouling risk of a reactor, characterized in that: include: Step S110, obtaining input parameters; Step S120, calculating the mass evaporation rate based on the input parameters; Step S130, calculating the fouling thickness of the core based on the mass evaporation rate; Step S140, calculating the boron deposition mass based on the fouling thickness of the core; Step S150, determine whether the convergence condition is met, if the convergence condition is met, proceed to step S160, otherwise return to step S110; Step S160: output the calculation result.

2. The method according to claim 1, characterized in that The calculating of the mass evaporation rate based on the input parameters comprises: The momentum equation is constructed based on the heat flux density transferred by heat conduction, the mass evaporation rate, the vapor phase enthalpy of the fouling surface, and the liquid phase enthalpy of the fouling surface; An energy equation is constructed based on the vapor pressure in the dirt, the liquid pressure in the dirt, the surface tension of the liquid inside the dirt, the dirt contact angle and the critical pore radius of the dirt; The heat transfer equation is constructed based on the internal temperature of the dirt, the saturated temperature of the liquid inside the dirt, the mass evaporation rate and the latent heat of vaporization of the liquid inside the dirt; A mass evaporation rate is calculated based on the momentum equation, the energy equation, and the heat transfer equation.

3. The method according to claim 1, characterized in that The calculating the fouling thickness of the core based on the mass evaporation rate comprises: Obtain the mainstream nickel solubility in the core and the nickel solubility near the wall; In the case where the nickel solubility near the core wall is greater than the mainstream nickel solubility of the core, a mass transfer model of the core is constructed based on the mass evaporation rate, the mainstream nickel solubility of the core, the total concentration of corrosion products in the coolant system, and the mass flow rate of fouling deposition transfer in the core; otherwise, a mass transfer model of the core is constructed based on the mass evaporation rate, the nickel solubility near the core wall, the total concentration of corrosion products in the coolant system, and the mass flow rate of fouling deposition transfer in the core; Constructing a mass balance model of the coolant system based on the total concentration of corrosion products in the coolant system, the mass flow rate of fouling deposits transferred by the core, and the total release rate of corrosion products in the coolant system; Solving the mass flow rate of fouling deposition transfer in the core based on the mass transfer model of the core and the mass balance model of the coolant system; The fouling thickness of the core is calculated based on the mass flow rate delivered by the fouling deposition of the core.

4. The method according to claim 3, characterized in that The calculating the fouling thickness of the core based on the mass evaporation rate further comprises: Obtain nickel solubility in the downflow system; A mass transfer model of the downflow system is constructed based on the nickel solubility of the downflow system and the mass flow rate of the fouling deposition transferred by the downflow system; A mass balance model of the coolant system is also constructed based on the mass flow rate of fouling deposits transferred by the downcomer system, and the mass flow rate of fouling deposits transferred by the core is solved based on the mass transfer model of the downcomer system.

5. The method according to claim 3, characterized in that The calculating the fouling thickness of the core based on the mass evaporation rate further comprises: Obtain the mainstream nickel solubility and near-wall nickel solubility of the steam generator; In the case where the nickel solubility near the wall of the steam generator is greater than the mainstream nickel solubility of the steam generator, a mass transfer model of the steam generator is constructed based on the mass evaporation rate, the mainstream nickel solubility of the steam generator, the total concentration of corrosion products in the coolant system, and the mass flow rate of fouling deposition transfer of the steam generator; otherwise, a mass transfer model of the steam generator is constructed based on the mass evaporation rate, the nickel solubility near the wall of the steam generator, the total concentration of corrosion products in the coolant system, and the mass flow rate of fouling deposition transfer of the steam generator; A mass balance model of a coolant system is also constructed based on the mass flow rate transferred by the fouling deposits of the steam generator, and the mass flow rate transferred by the fouling deposits of the core is solved based on the mass transfer model of the steam generator.

6. The method according to claim 3, characterized in that The calculating the fouling thickness of the core based on the mass evaporation rate further comprises: The total release rate of corrosion products in the coolant system is calculated based on the mainstream pH value in the coolant system.

7. The method according to claim 3, characterized in that The calculating the fouling thickness of the core based on the mass flow rate of the fouling deposition transfer of the core comprises: Calculating the fouling mass per unit area of ​​the core based on the mass flow rate of fouling deposition transfer of the core; The fouling thickness of the core is calculated based on the fouling mass per unit area and the fouling density of the core.

8. The method according to claim 7, characterized in that The calculation of the boron deposition mass based on the fouling thickness of the core includes: Calculating the mass of boron-lithium compound deposition inside the fouling based on the concentration of the target substance inside the fouling, the fouling thickness of the core, the boron concentration in the coolant, and the concentration factor; The boron adsorption mass on the fouling surface is calculated based on the boron concentration on the cladding surface and the mass per unit area of ​​the fouling in the core; The boron deposition mass is obtained by summing the boron lithium compound deposition mass and the boron adsorption mass.

9. A computing device, characterized in that: include: at least one processor; as well as At least one memory having instructions stored thereon, which, when executed individually or collectively by the at least one processor, cause the computing device to perform the method according to any one of claims 1 to 8.

10. A computer storage medium, characterized in that: The computer storage medium stores instructions, which, when executed individually or collectively by at least one processor of a computing device, cause the computing device to perform the method according to any one of claims 1 to 8.

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