Method and device for predicting corrosion product content in pressurized water reactor primary circuit, and electronic equipment

Abstract

The present application provides a method and device for predicting the content of corrosion products in the primary loop of a pressurized water reactor, and electronic equipment, wherein the primary loop of the pressurized water reactor is equivalent to a first node representing the reactor core, a second node representing soluble corrosion products in the coolant, a third node representing the steam generator, and a fourth node representing corrosion product particles in the coolant; the method comprises: obtaining calculation parameters of the corrosion products, and inputting the calculation parameters into a pre-constructed prediction model to make the prediction model output content information of the corrosion products according to the calculation parameters. The above prediction method can obtain the content of corrosion products at each node in the primary loop of the pressurized water reactor, so as to restore the distribution and migration process of the corrosion products in the primary loop of the pressurized water reactor according to the content of the corrosion products at each node, thereby improving the safety of the fuel rod and the reactor core, ensuring the integrity of the cladding during long-term use, preventing the leakage of radioactive substances, and ensuring the safety of the reactor.

Description

Technical Field

[0001] This invention relates to the field of reactor technology, and in particular to a method, apparatus and electronic equipment for predicting the content of corrosion products in the primary loop of a pressurized water reactor. Background Technology

[0002] During pressurized water reactor operation, as the metal surfaces around the primary cooling loop corrode, corrosion products of iron, nickel, chromium, and cobalt—the main constituent elements of metals such as stainless steel and nickel-based alloys (as well as trace impurities like cobalt)—are released into the coolant and permeate the entire primary loop with the coolant flow. Due to the low solubility of corrosion products in the reactor core, the resulting water-soluble (ionic) or insoluble particulate corrosion products may deposit on the fuel surfaces of the reactor core, forming a loose Chalk River Unidentified Deposit (CRUD). Some of this deposit is eroded by the shearing action of the coolant flow and released back into the coolant, eventually accumulating in the coolant or redepositing on other surfaces of the reactor core.

[0003] However, due to the loose structure of this fouling layer and the resulting deterioration in heat transfer, boron enrichment occurs on the fuel rod surface, significantly impacting core boron concentration distribution and fuel performance, leading to fouling-induced axial power shift (CIPS). Simultaneously, the inherent thermal resistance causes further deterioration in heat transfer, triggering fouling-induced localized corrosion (CILC), further threatening fuel rod safety. Therefore, predicting the distribution and migration of corrosion products in the primary circuit to improve fuel rod and core safety is a pressing issue that needs to be addressed. Summary of the Invention

[0004] In view of this, the purpose of this invention is to provide a method, apparatus and electronic equipment for predicting the content of corrosion products in the primary loop of a pressurized water reactor, so as to alleviate the above-mentioned problems, and to reconstruct the distribution and migration of corrosion products in the primary loop of a pressurized water reactor based on the content of corrosion products at each node, thereby improving the safety of fuel rods and reactor core, ensuring the integrity of the cladding during long-term use, preventing the leakage of radioactive materials and ensuring reactor safety.

[0005] In a first aspect, embodiments of the present invention provide a method for predicting the content of corrosion products in the primary loop of a pressurized water reactor (PWR). The corrosion products include soluble corrosion products and corrosion product particles. The PWR primary loop is equivalent to multiple nodes. These multiple nodes include: a first node, a second node, a third node, and a fourth node. The first node characterizes the core of the PWR primary loop, the second node characterizes the soluble corrosion products in the coolant, the third node characterizes the steam generator of the PWR primary loop, and the fourth node characterizes the corrosion product particles in the coolant. The method includes:

[0006] Obtain the calculation parameters of the corrosion products; wherein the calculation parameters include at least one of the following: crystallization rate of soluble corrosion products, deposition rate of soluble corrosion products, ion release rate of corrosion products, corrosion rate of steam generator, particle deposition fraction of the first node and particle deposition fraction of the third node.

[0007] The calculation parameters are input into the pre-built prediction model so that the prediction model outputs the content information of corrosion products based on the calculation parameters. The content information includes the content of corrosion products at each node. The prediction model includes: the first prediction sub-model corresponding to the first node, the second prediction sub-model corresponding to the second node, the third prediction sub-model corresponding to the third node, and the fourth prediction sub-model corresponding to the fourth node.

[0008] Preferably, the step of inputting calculation parameters into a pre-built prediction model so that the prediction model outputs information on the content of corrosion products based on the calculation parameters includes:

[0009] The expression for the first predictive sub-model is as follows:

[0010]

[0011] Where dI1 represents the increase in the amount of corrosion products at the first node within the time increment dt, J dp f represents the deposition rate of soluble corrosion products. p1 J represents the particle deposition fraction of the first node. cr This indicates the crystallization rate of soluble corrosion products.

[0012] Preferably, the step of inputting calculation parameters into a pre-built prediction model so that the prediction model outputs information on the content of corrosion products based on the calculation parameters includes:

[0013] The expression for the third predictive sub-model is as follows:

[0014]

[0015] Where dI3 represents the increase in the amount of corrosion products at the third node within the time increment dt, CR represents the corrosion rate of the steam generator, and J rlf represents the ion release rate of corrosion products. p3 J represents the particle deposition fraction at the third node. cr This indicates the crystallization rate of soluble corrosion products.

[0016] Preferably, the step of inputting calculation parameters into a pre-built prediction model so that the prediction model outputs information on the content of corrosion products based on the calculation parameters includes:

[0017] The expressions for the second and fourth prediction sub-models are as follows:

[0018]

[0019] Where dI2 represents the increase in the amount of corrosion products at the second node within the time increment dt, and dI4 represents the increase in the amount of corrosion products at the fourth node within the time increment dt.

[0020] Preferably, the step of obtaining calculation parameters for corrosion products includes: obtaining concentration parameters of soluble corrosion products; wherein, the concentration parameters include: saturation concentration of soluble corrosion products, concentration of soluble corrosion products at the interface between the coolant and the metal surface, and concentration of soluble corrosion products in the mainstream area; calculating the crystallization rate, deposition rate, and ion release rate of soluble corrosion products based on the concentration parameters and preset mass transfer coefficients; wherein, the mass transfer coefficients include: crystallization mass transfer coefficient, deposition mass transfer coefficient, and release mass transfer coefficient.

[0021] Preferably, the step of calculating the crystallization rate, deposition rate, and ion release rate of soluble corrosion products based on concentration parameters and preset mass transfer coefficients includes: calculating the crystallization rate of soluble corrosion products based on the saturation concentration of soluble corrosion products, the concentration of soluble corrosion products at the interface, and the crystallization mass transfer coefficient; calculating the deposition rate of soluble corrosion products based on the saturation concentration of soluble corrosion products, the concentration of soluble corrosion products in the mainstream area, and the deposition mass transfer coefficient; and calculating the ion release rate of corrosion products based on the saturation concentration of soluble corrosion products, the concentration of soluble corrosion products in the mainstream area, and the release mass transfer coefficient.

[0022] Preferably, the elements in the corrosion products include at least one of the following: iron, chromium, and nickel. The method further includes: obtaining basic parameters of the corrosion products; wherein the basic parameters include: solid stoichiometry, hydrogen partial pressure, activity coefficient of neutral substances, activity coefficient of monovalent ions, hydrogen ion concentration, and reaction constants of the hydrolysis-related reactions of the corrosion products; calculating the solubility information of the corrosion products based on the basic parameters; wherein the solubility information includes: saturation concentration of iron, saturation concentration of chromium, and saturation concentration of nickel.

[0023] Secondly, embodiments of the present invention also provide a device for predicting the content of corrosion products in the primary loop of a pressurized water reactor (PWR). The corrosion products include soluble corrosion products and corrosion product particles. The PWR primary loop is equivalent to multiple nodes. These multiple nodes include a first node, a second node, a third node, and a fourth node. The first node is used to characterize the core of the PWR primary loop, the second node is used to characterize the soluble corrosion products in the coolant, the third node is used to characterize the steam generator of the PWR primary loop, and the fourth node is used to characterize the corrosion product particles in the coolant. The device includes:

[0024] The acquisition module is used to acquire calculation parameters of corrosion products; wherein the calculation parameters include at least one of the following: crystallization rate of soluble corrosion products, deposition rate of soluble corrosion products, ion release rate of corrosion products, corrosion rate of steam generator, particle deposition fraction of the first node and particle deposition fraction of the third node.

[0025] The calculation module is used to input calculation parameters into a pre-built prediction model so that the prediction model outputs corrosion product content information based on the calculation parameters. The content information includes the corrosion product content at each node. The prediction model includes: a first prediction sub-model corresponding to the first node, a second prediction sub-model corresponding to the second node, a third prediction sub-model corresponding to the third node, and a fourth prediction sub-model corresponding to the fourth node.

[0026] Thirdly, embodiments of the present invention also provide an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the method described in the first aspect.

[0027] Fourthly, embodiments of the present invention also provide a computer-readable storage medium storing a computer program, which, when executed by a processor, performs the steps of the method described in the first aspect.

[0028] The embodiments of the present invention bring the following beneficial effects:

[0029] This invention provides a method, apparatus, and electronic equipment for predicting the content of corrosion products in the primary loop of a pressurized water reactor (PWR). First, the PWR primary loop is equivalent to a first node representing the reactor core, a second node representing soluble corrosion products in the coolant, a third node representing the steam generator, and a fourth node representing corrosion product particles in the coolant. Then, calculation parameters for the corrosion products are obtained, including at least one of the following: soluble corrosion product crystallization rate, soluble corrosion product deposition rate, corrosion product ion release rate, steam generator corrosion rate, particle deposition fraction at the first node, and particle deposition fraction at the third node. Finally, the calculation parameters are input into a pre-constructed prediction model, which outputs corrosion product content information based on the calculation parameters. The content information includes the corrosion product content at each node. This prediction method can obtain the corrosion product content at each node in the PWR primary loop, allowing for the reconstruction of the distribution and migration processes of corrosion products in the PWR primary loop based on the corrosion product content at each node. This improves the safety of fuel rods and the reactor core, ensures the integrity of the cladding during long-term use, prevents radioactive material leakage, and ensures reactor safety.

[0030] Other features and advantages of the invention will be set forth in the following description, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention are realized and obtained through the structures particularly pointed out in the description and the drawings.

[0031] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, preferred embodiments are described below in detail with reference to the accompanying drawings. Attached Figure Description

[0032] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0033] Figure 1 A flowchart illustrating a method for predicting the content of corrosion products in the primary loop of a pressurized water reactor, provided in an embodiment of the present invention;

[0034] Figure 2 This is an equivalent schematic diagram of the primary loop of a pressurized water reactor provided in an embodiment of the present invention;

[0035] Figure 3 A schematic diagram illustrating the configuration of the oxide film on the surface of a chromium-nickel-iron 600 barrel for a steam generator, provided in an embodiment of the present invention;

[0036] Figure 4 A schematic diagram of a corrosion product content prediction device in the primary loop of a pressurized water reactor provided in an embodiment of the present invention;

[0037] Figure 5 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0038] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0039] To facilitate understanding of this embodiment, the embodiments of the present invention will be described in detail below.

[0040] Example 1:

[0041] This invention provides a method for predicting the content of corrosion products in the primary loop of a pressurized water reactor (PWR). The corrosion products include soluble corrosion products and corrosion product particles. The PWR primary loop is equivalent to multiple nodes; these nodes include a first node, a second node, a third node, and a fourth node. The first node characterizes the core of the PWR primary loop, the second node characterizes the soluble corrosion products in the coolant, the third node characterizes the steam generator of the PWR primary loop, and the fourth node characterizes the corrosion product particles in the coolant. Figure 1 As shown, the method includes the following steps:

[0042] Step S102: Obtain the calculation parameters of the corrosion products;

[0043] The calculation parameters include at least one of the following: soluble corrosion product crystallization rate, soluble corrosion product deposition rate, corrosion product ion release rate, steam generator corrosion rate, particle deposition fraction of the first node, and particle deposition fraction of the third node; the specific number of calculation parameters can be set according to the actual situation, and the embodiments of the present invention do not limit this description.

[0044] Step S104: Input the calculation parameters into the pre-built prediction model so that the prediction model outputs the content information of corrosion products based on the calculation parameters.

[0045] The content information includes the corrosion product content at each node. The prediction model includes: the first prediction sub-model corresponding to the first node, the second prediction sub-model corresponding to the second node, the third prediction sub-model corresponding to the third node, and the fourth prediction sub-model corresponding to the fourth node. Based on the calculation parameters and the prediction sub-model corresponding to each node, the corrosion product content at each node can be calculated. Based on the changes in the corrosion product content at each node, the entire process of corrosion product generation, migration, deposition, and growth is simulated, thus providing an important reference for predicting CRUD growth thickness, corrosion product content in coolant, and corrosion status of steam generators.

[0046] Therefore, the corrosion product content prediction method in the primary loop of a pressurized water reactor provided in this embodiment of the invention can calculate the corrosion product content at each node in the primary loop of a pressurized water reactor by using the prediction sub-model and calculation parameters corresponding to each node. This allows for the reconstruction of the distribution and migration of corrosion products in the primary loop of the pressurized water reactor based on the corrosion product content at each node, thereby improving the safety of fuel rods and reactor core, ensuring the integrity of the cladding during long-term use, preventing the leakage of radioactive materials, and ensuring reactor safety.

[0047] For pressurized water reactors, existing methods mainly focus on analyzing the thickness and trend of CRUD growth, while the generation, distribution, and migration processes of corrosion products remain unclear. Predicting the migration process of corrosion products in the primary circuit, their content and distribution at different locations, and assessing the impact of water chemistry and thermal parameters are crucial for safety protection and core parameter design.

[0048] In practical applications, the migration process of corrosion products involves the complex loop structure and temperature changes of the primary loop. The morphology of the corrosion products themselves is also diverse, involving chemical and physical transformations of the corrosion products themselves. Furthermore, it is controlled by temperature distribution and flow field information, making it difficult to directly predict the migration and distribution of corrosion products in the primary loop of pressurized water reactors.

[0049] Based on this, in order to model the complex corrosion product migration process in the primary loop and to statistically analyze the content and distribution of corrosion products at different locations in the primary loop, this embodiment of the invention equates the pressurized water reactor primary loop to multiple nodes. Here, the number of nodes is four: a first node, a second node, a third node, and a fourth node, as follows: Figure 2 As shown, the first node (i.e., node 1) is used to characterize the core of the pressurized water reactor primary loop, the second node (i.e., node 2) is used to characterize soluble corrosion products in the coolant, the third node (i.e., node 3) is used to characterize the steam generator of the pressurized water reactor primary loop, and the fourth node (i.e., node 4) is used to characterize corrosion product particles in the coolant.

[0050] Furthermore, based on mass transfer kinetics, chemical reaction equilibrium, and hydrochemistry theories, mass transfer balance equations for corrosion products (i.e., prediction sub-models corresponding to each node) were established for the four nodes. Correlation coefficients for the migration process of corrosion products were calculated based on experimental conclusions and mass transfer theory. Finally, by solving the mass transfer balance equations, information such as the content and solubility of corrosion products at the four nodes in the primary loop can be obtained, laying the foundation for assessing the impact of reactor fouling and improving the safety of pressurized water reactor operation.

[0051] For ease of explanation, this section is divided into two parts: (1) calculation of key parameters for the migration process of corrosion products, and (2) prediction sub-models corresponding to the four nodes of corrosion products. In (1), the key parameters include, but are not limited to, the calculation parameters, as well as the mass transfer coefficient, crystallization rate, solubility rate, and diffusion coefficient of corrosion products. This provides basic data support for the subsequent establishment of the four-node model and provides reliable data support for reactor safety assessment. In (2), the modeling process of the prediction sub-models of the four nodes is described based on the key links of corrosion product migration.

[0052] Specifically, the two parts mentioned above are described below:

[0053] (1) Calculation of key parameters for the migration process of corrosion products;

[0054] ① Calculate the diffusion coefficients of soluble corrosion products and corrosion product particles;

[0055] To calculate the mass transfer of corrosion products (soluble and particulate matter) in the primary coolant of a PWR (Pressurized Water Reactor), the diffusion coefficient is necessary. This study focuses primarily on the precipitated forms of soluble ions of transition metals such as iron, nickel, and cobalt, and their oxides in high-temperature water.

[0056] Specifically, ions of soluble corrosion products exist in aqueous solutions in various forms, such as Fe. 2+ Fe(OH) + Fe(OH)3 － At low temperatures, Fe 2+ Ions are predominant, with Fe(OH)₂ being dominant at high temperatures. Since all iron ions exist in aqueous solution in an hydrated form, their particle sizes are very similar. Therefore, based on the Stokes-Einstein equation, it can be assumed that the diffusion coefficient of each ionic form is approximately the same, and the diffusion coefficient of an infinitely dilute electrolyte solution can be calculated using the Nernst-Einstein equation.

[0057] The diffusion coefficient of soluble corrosion products is calculated using the following formula:

[0058]

[0059] Among them, D ab The diffusion coefficient of soluble corrosion products is represented by F, F represents the Faraday constant, R represents the ideal gas constant, T represents the temperature, and n represents the diffusion coefficient of soluble corrosion products. + Indicates the valence state of the cation, n － Indicates the valence state of anion. The limiting conductivity of cations in a solution. It represents the limiting conductivity of anions in the solution.

[0060] Furthermore, the Stokes-Einstein equation is used for the diffusion coefficient of corrosion product particles. The absolute movement of a single particle (considered a rigid sphere) is determined by hydrodynamic friction, and this value is related to the viscosity of the electrolyte solution and the particle radius. The specific calculation formula is as follows:

[0061]

[0062] Among them, D p The value represents the diffusion coefficient of corrosion product particles, k represents the Boltzmann constant, μ represents the viscosity, and r represents the viscosity. p Let T represent the particle radius and T represent the temperature. For example, for a particle with a radius of 0.01 μm, the diffusion coefficient is 6.9e-6 (cm²). 2 / s).

[0063] ② Calculate the mass transfer coefficient of soluble corrosion products;

[0064] In practical applications, corrosion products are transferred from the supersaturated coolant region to the core surface. The driving force for this mass transfer is that the soluble corrosion products in the coolant become supersaturated due to the rise in core temperature. Because the temperature rises rapidly, the dissolved substances in the coolant become supersaturated. The controlling factors for the deposition of soluble corrosion products on the core surface are mass transfer through the boundary layer and the crystallization and growth of soluble corrosion products on the core surface. On the other hand, the coolant temperature in the steam generator tubes decreases, and the soluble corrosion products in the coolant quickly become unsaturated. There is also a driving force for the release of soluble corrosion products from the steam generator tube surface through the flow boundary layer into the unsaturated coolant. To estimate mass transfer, an analogy between heat transfer and mass transfer is often used. Since heat transfer is more thoroughly studied than mass transfer, based on existing experiments and calculations, the analogy between heat transfer and mass transfer has a smaller error under the following conditions: (a1) dilute solution, (a2) constant surface nuclide concentration, and (a3) ​​no anisotropic, homogeneous chemical reaction. These conditions can be well satisfied for the transfer of corrosion products (soluble corrosion products and corrosion product particles) in the core.

[0065] Furthermore, the uncertainty of eddy diffusion in the turbulent lower boundary layer makes theoretical estimation of the mass transfer coefficient difficult, and the mass transfer factor can only be calculated using experimentally obtained correlations. Since there is no explicit mass transfer formula for the transport of soluble corrosion products in PWRs, analogies for heat and mass transfer are used. The flow inside the tubes (steam generator) and outside the tubes (core) of the PWR have very high Reynolds numbers (Re > 10⁵). For fully developed turbulent flow inside the tubes under adiabatic conditions, the Dittus-Boelter heat transfer relation is used as follows:

[0066] Nu = 0.023Re 0.8 Pr 1 / 3 (3)

[0067] Where Nu represents the Nusselt number, Re represents the Reynolds number, and Pr represents the Prandtl number.

[0068] In the analogy of mass transfer relations, the Prandtl number is the ratio of momentum diffusion to thermal diffusion, and is replaced by the Schmidt number (Sc), while the Nusselt number is replaced by the Sherwood number (Sh). Thus, the mass transfer relation for the same flow conditions is:

[0069] Sh = 0.0165Re 0.86 Sc 1 / 3 (4)

[0070] The mass transfer coefficient of the soluble corrosion products can be obtained according to formula (4), and the calculation formula is as follows:

[0071]

[0072] Where h represents the mass transfer coefficient of the soluble corrosion products, and D ab D represents the diffusion coefficient of soluble corrosion products. e Re represents the equivalent hydraulic diameter, and Re represents the Reynolds number.

[0073] ③ Calculate the crystallization rate and solubility rate of soluble corrosion products;

[0074] (A1) Calculate the crystallization rate of soluble corrosion products. In practical applications, the deposition of soluble corrosion products involves two steps: mass transfer of traditional ionic corrosion products from the solution to the nearby metal surface; and crystallization of soluble corrosion products between the metal surface and the coolant. Electron microscopic analysis shows that the oxide layer formed on the surface of the fuel element under PWR operating conditions is mainly composed of small, loose nickel-ferrite crystals with a density ranging from 0.1 to 0.4 times the theoretical density of oxide crystals. It can be assumed that the solution at the interface between the metal surface and the coolant is saturated. In this case, when the soluble corrosion products in the coolant are supersaturated, the soluble corrosion products in the coolant are transferred to the coolant through the boundary layer, and then the ionic corrosion products crystallize or precipitate at the interface and deposit on the metal surface. The crystallization rate of soluble corrosion products can be expressed by the crystallization constant and the degree of supersaturation, as shown in the following formula:

[0075] J cr =k cr (C i -C sat ) n (6)

[0076] Among them, J cr C represents the crystallization rate of soluble corrosion products. i C represents the concentration of soluble corrosion products at the interface between the coolant and the metal surface. sat The saturation concentration of soluble corrosion products is represented by n, which represents the order of the crystallization reaction, and k is the number of soluble corrosion products. cr This represents the crystallization constant. It should be noted that k... cr It depends on temperature, impurities, surface tension, and the activation barrier of ion diffusion across the interface and stripping.

[0077] The order n of the crystallization reaction is determined experimentally. We can assume that the crystallization of the soluble corrosion product is a first-order reaction, i.e., n = 1. In this case, the formula for calculating the crystallization rate of the soluble corrosion product is as follows:

[0078] J cr =h cr (C i -C sat (7)

[0079] Among them, h cr The mass transfer coefficient for crystallization is a constant that can be obtained through experimental measurement under corresponding conditions. For details, please refer to the existing technology. The embodiments of the present invention will not be described in detail here.

[0080] Furthermore, the deposition rate of soluble corrosion products can be obtained as follows. The formula for calculating the deposition mass transfer rate of soluble corrosion products is as follows:

[0081] J mt =h mt (Cbulk -C i (8)

[0082] Among them, J mt h represents the deposition mass transfer rate of soluble corrosion products. mt C represents the diffusion mass transfer coefficient, which is a constant; bulk This indicates the concentration of soluble corrosion products in the mainstream region. It should be noted that the mainstream region here can be understood as a part near the center of the flow channel; it is a technical term in fluid mechanics. The concentration C of soluble corrosion products in the mainstream region mentioned above... bulk It can also be understood as the concentration of soluble corrosion products inside the fluid.

[0083] Under steady state, the deposition mass transfer rate and crystallization rate of soluble corrosion products are both related to the deposition rate of soluble corrosion products, J. dp Equal means satisfying the following relationship:

[0084] J dp =J mt =J cr (9)

[0085] The concentration of soluble corrosion products at the interface between the coolant and the metal surface is reduced by C. i , deposition rate of soluble corrosion products J dp The calculation formula is as follows:

[0086]

[0087] Among them, J dp h represents the deposition rate of soluble corrosion products. dp C represents the sedimentation mass transfer coefficient. bulk C represents the concentration of soluble corrosion products in the mainstream area. sat This indicates the saturation concentration of soluble corrosion products.

[0088] (A2) Calculate the solubility of soluble corrosion products; In practical applications, the ions of soluble corrosion products are released into the coolant in two steps, that is, the soluble corrosion products dissolve at the interface between the oxide layer surface and the coolant; the mass transfer of soluble corrosion products through the boundary layer.

[0089] The dissolution of soluble corrosion products is the reverse process of their crystallization. It can be assumed that the interface between the oxide layer and the coolant is saturated with soluble corrosion products. In this case, when the coolant is not saturated with soluble corrosion products, the soluble corrosion products at the interface are transferred through the boundary layer into the coolant, and the soluble corrosion products in the oxide layer dissolve, restoring saturation at the coolant interface.

[0090] The dissolution of soluble corrosion products is a chemical reaction. Because soluble corrosion products can exist in various forms at the oxide layer interface, such as Fe, FeO, Fe₂O₃, Fe₃O₄, and Fe, they are a chemical reaction that can occur at the oxide layer interface. 3-x Ni x To estimate the dissolution mechanism of soluble corrosion products, it is necessary to consider various possible chemical reactions. Specifically, the solubility at the metal-coolant interface can be simply expressed as follows:

[0091] J ds =k ds (C sat -C i ) n (11)

[0092] Among them, J ds C represents the solubility of soluble corrosion products. i C represents the concentration of soluble corrosion products at the interface between the coolant and the metal surface. sat The saturation concentration of soluble corrosion products is represented by n, which represents the order of the dissolution reaction, and k is the number of soluble corrosion products. ds This represents the solubility constant. It should be noted that k... ds It depends on temperature, the activation barrier of dissolution, and the physicochemical conditions of the interface.

[0093] Assuming the dissolution of soluble corrosion products is a first-order reaction, i.e., n=1, the formula for calculating the solubility rate of soluble corrosion products is as follows:

[0094] J ds =h ds (C sat -C i (12)

[0095] Among them, h ds It represents the solubility-mass transfer coefficient, which can be obtained through experimental measurement under specific conditions.

[0096] Under steady-state conditions, the ion release rate of corrosion products J rl Solubility of soluble corrosion products J ds Deposition mass transfer rate of soluble corrosion products J mt Equal means satisfying the following relationship:

[0097] J rl =J mt =J ds (13)

[0098] In this way, the concentration C of soluble corrosion products at the interface between the coolant and the metal surface is reduced. i ion release rate of corrosion products J rl The calculation formula is as follows:

[0099]

[0100] Among them, J rl h represents the ion release rate of corrosion products. rl C represents the release mass transfer coefficient. bulk C represents the concentration of soluble corrosion products in the mainstream area. sat This indicates the saturation concentration of soluble corrosion products. For example, if the experimentally measured ion release rate of corrosion products is 1.15e-10 (gm / cm³). 2 The corresponding release mass transfer coefficient is 8.2e-2 (cm / s). From this corrosion product ion release rate, the dissolution mass transfer coefficient h of soluble iron can be obtained. rl = 8.2e-2 (cm / s), which is exactly the same as h mt The fact that they are equal means that the solubility constant is close to infinity and much larger than the mass transfer coefficient. Therefore, in the release of soluble corrosion products, the resistance to dissolution is negligible for the mass transfer process across the boundary layer.

[0101] Therefore, in one embodiment, the process of obtaining the calculation parameters of the corrosion products further includes: obtaining the concentration parameters of the soluble corrosion products; wherein the concentration parameters include: the saturation concentration C of the soluble corrosion products. sat Concentration C of soluble corrosion products at the interface between coolant and metal surface i Concentration C of soluble corrosion products in the mainstream area bulk The crystallization rate J of the soluble corrosion products was calculated based on the concentration parameters and the preset mass transfer coefficient. cr , Deposition rate of soluble corrosion products J dp and corrosion product ion release rate J rl .

[0102] The mass transfer coefficient includes: the crystallization mass transfer coefficient h. cr Deposition mass transfer coefficient h dp Release mass transfer coefficient h rl The specific calculation process is as follows: Based on the saturation concentration C of soluble corrosion products... sat Concentration C of soluble corrosion products at the interface i Crystallization mass transfer coefficient h cr The crystallization rate J of the soluble corrosion products was calculated. cr That is, the crystallization rate J of the soluble corrosion product is calculated according to formula (7). cr Based on the saturation concentration C of soluble corrosion products sat Concentration C of soluble corrosion products in the mainstream area bulk Deposition mass transfer coefficient h dp The deposition rate of soluble corrosion products J was calculated. dp That is, the deposition rate J of soluble corrosion products is calculated according to formula (10). dpBased on the saturation concentration C of soluble corrosion products sat Concentration C of soluble corrosion products in the mainstream area bulk Release mass transfer coefficient h rl The corrosion product ion release rate J was calculated. rl That is, the corrosion product ion release rate J is calculated according to formula (14). rl .

[0103] It should be noted that in the above calculation process, the crystallization rate J of the soluble corrosion products... cr , Deposition rate of soluble corrosion products J dp and corrosion product ion release rate J rl Calculations can be performed simultaneously or in the order they occur, depending on the specific circumstances.

[0104] ④ Calculate the corrosion rate of the corrosion products;

[0105] Specifically, under PWR operating conditions, the oxide layer forms a deposited layer with a complex structure on chromium-nickel-iron alloys and stainless steel, such as... Figure 3 As shown, the composition of the oxide layer depends on the base metal and the exposed chemical environment, such as temperature, pH, and oxygen concentration. The inner layer is composed of (Cr,Ni,Fe)₂O₃, and in particular, the Cr₂O₃ forms a dense oxide layer that protects the base metal from corrosion. Furthermore, the outer layer consists of relatively non-oxidizing substances, such as (Fe,Ni)₂O₃ or (Fe,Ni)₃O₄, the specific composition of which depends on the oxygen concentration in the coolant. Therefore, the corrosion rate of the base metal is passively controlled by the inner layer.

[0106] For chromium-nickel-iron alloys and stainless steel in aqueous environments, the point defect model (PDM) agrees well with experimental results, predicting logarithmic growth of the oxide layer over time. Under the logarithmic growth rate of the PDM, after an initial high corrosion rate reaching a transition value, the corrosion rate becomes proportional to time. During this corrosion process, oxygen, as anion, is transported across the passive oxide layer and forms stable oxides at the interface between the oxide layer and the base metal. Among Fe, Ni, and Cr, the latter has the strongest oxide form. Thus, the oxide (Fe,Ni)₂O₃ may tend to migrate towards the neutral chromium in the base metal, forming more stable chromium oxides. Cations in the inner oxide layer lose oxygen to Cr and, through diffusion via point defects, penetrate the passive oxide layer to reach the solution oxide interface and approach the solution or precipitate as loose oxides such as (Fe,Ni)₃O₄. The thickness of the outer oxide layer depends on the net solubility of Fe and Ni in the coolant and the corrosion and deposition effects of the coolant and boron particles.

[0107] Furthermore, electron microscopy analysis of chromium-nickel-iron alloys and stainless steel oxides revealed that chromium oxides were more abundant in the inner layer compared to the base metal, while Fe and Ni were more abundant in the outer layer. In the outer layer, more oxygen was transferred from the coolant to the base metal, and the driving force for the movement of charged oxygen ions, Fe, and Ni created a potential gradient between the base metal and the solution. Therefore, the amount of Fe and Ni diffusion mass transfer from the inner to the outer layer is defined as the "corrosion rate." This value can be measured experimentally, as exemplified in Table 1.

[0108] Table 1

[0109]

[0110] The table above shows the total corrosion rates of Cr-Nickel 600 and 304 stainless steel under nominal pressurized water reactor conditions. Therefore, the steam generator corrosion rate (CR) can be obtained based on the material of the steam generator.

[0111] ⑤ Calculate the solubility of the corrosion products;

[0112] The corrosion products formed on the chromium-nickel-iron alloy tubes and stainless steel surfaces of the steam generator, under normal PWR coolant chemical environment (i.e., low oxygen concentration, high hydrogen partial pressure environment), are mainly composed of nickel-ferrite (NiFe). x Fe 3-x O4) or nickel-cobalt ferrite (Ni x Co y Fe 3-x-y O4), where x or x+y ranges from 0.45 to 0.75.

[0113] Based on the aforementioned composition of nickel-ferrite, the solubility of iron can be calculated through the chemical separation reaction of nickel-ferrite. In practical applications, the dissolution of iron mainly involves four ionic forms, such as Fe2+. 2+ Fe(OH) + Fe(OH)2 The solubility of iron is the sum of the saturation (or equilibrium) concentrations of these ions. However, the saturation concentrations and solubilities of these ions vary with temperature and pH. For example, nickel ferrite and Ni... x Fe 3-x The chemical reactions and reaction constants of O4 are as follows:

[0114] For Fe 2+ :

[0115]

[0116] Similarly, for Fe(OH) + :

[0117]

[0118] For Fe(OH)2:

[0119]

[0120] for

[0121]

[0122] In formulas (15) to (18) above, H 2(g) This refers to hydrogen gas in the coolant. This indicates hydrogen ions in the coolant.

[0123] At this point, the solubility S of iron is:

[0124]

[0125] Where x represents the concentration of the corresponding element, K i These represent the equilibrium constants for reactions in various ionic forms, and are their respective free energy changes ΔG. i The function. Here K i The calculation formula is as follows:

[0126]

[0127] Where R represents the ideal gas constant and T represents temperature. It should be noted that the free energy change ΔG of a chemical reaction... i It varies with temperature, and the variation differs for each reaction, as do the reaction constant and the resulting iron solubility.

[0128] The saturation concentration S of corrosion products at node i i It can be expressed by its chemical dissociation reaction equilibrium constant. In practical applications, since the corrosion products are mainly nickel-iron oxide or nickel-cobalt-iron oxide, the saturation concentration of iron can be calculated by formula (21) and corrected by the solubility measurement values ​​of nickel and iron. The saturation concentrations of nickel and chromium are obtained by converting formulas (22) and (23). The specific expressions of (21) to (23) are as follows:

[0129]

[0130] S Ni =0.25S Fe (twenty two)

[0131] S Cr =0.1S Fe (twenty three)

[0132] Among them, S Fe S represents the saturation concentration of iron. Ni S represents the saturation concentration of nickel. Cr A represents the saturation concentration of chromium, A represents the stoichiometric ratio of the solid, and P represents the saturation concentration of chromium. H2 The partial pressure of hydrogen gas is represented by γ0, the reactivity coefficient of neutral substances is represented by γ1, the reactivity coefficient of monovalent ions is represented by z, and K represents the hydrogen ion concentration. i The reaction constant representing the hydrolysis-related reactions of corrosion products is a function of temperature.

[0133] In addition, the partial pressure of hydrogen P H2 It can be determined using Henry's Law, and the specific calculation formula is as follows:

[0134]

[0135] Among them, c H2 M represents the hydrogen concentration. f k represents the molar mass of water. hcc This represents the Henry's constant.

[0136] Since the concentration of corrosion products in the coolant is saturated during long-term corrosion in actual conditions, the concentration C in part (1) can be replaced by the saturated concentration at the corresponding position. The solubility of corrosion products at different nodes can be calculated using formulas (21) to (23), thus providing guidance for safety protection and core parameter design.

[0137] Therefore, in one embodiment, the elements of the corrosion products include at least one of the following: iron, chromium, and nickel. The method further includes: obtaining basic parameters of the corrosion products; wherein the basic parameters include: solid stoichiometry, hydrogen partial pressure, activity coefficient of neutral substances, activity coefficient of monovalent ions, hydrogen ion concentration, and reaction constants of the hydrolysis-related reactions of the corrosion products; calculating the solubility information of the corrosion products based on the basic parameters; wherein the solubility information includes: saturation concentration of iron, saturation concentration of chromium, and saturation concentration of nickel. For the specific calculation process, please refer to the above formulas (21) to (24), which will not be described in detail in this embodiment of the invention.

[0138] (2) Prediction sub-models corresponding to the four nodes of corrosion products;

[0139] Specifically, the transfer of corrosion products, including particles, can be modeled by considering factors such as the corrosion generation rate, release rate, deposition rate, and precipitation rate of these products. Figure 2 As shown, the corrosion product balance equation for each node can be expressed by the following formula:

[0140]

[0141]

[0142]

[0143]

[0144] Where, dI i J represents the increase in the amount of corrosion products at node i within the time increment dt; CR represents the corrosion rate of the steam generator; RS represents the release rate of soluble corrosion products in the steam generator, i.e., J rl DS represents the deposition rate of soluble corrosion products in the reactor core, i.e., J dp PR represents the precipitation rate of soluble corrosion products in the coolant, i.e., the crystallization rate of soluble corrosion products J. cr ;DP i This indicates the deposition rate of corrosion product particles in node i. Subscript 1 represents the core, subscript 2 represents soluble corrosion products, subscript 3 represents the steam generator, and subscript 4 represents corrosion product particles. For example, DP3 represents the deposition rate of corrosion product particles in the steam generator.

[0145] In addition, DP i The calculation formula is as follows:

[0146] DP i =f pi ·PR (29)

[0147] Among them, f pi This represents the particle deposition fraction of node i, such as based on the particle deposition fraction f of the first node. p1 And the particle deposition fraction f of the third node p3 And the crystallization rate of soluble corrosion products J cr DP1 and DP3 can be calculated.

[0148] In one implementation, under steady state, the amounts of soluble corrosion products and corrosion product particles in the coolant corrosion products are both constant. In this case, the expressions for the second and fourth prediction sub-models can be obtained as follows:

[0149]

[0150] Where dI2 represents the increase in corrosion product stock at the second node within the time increment dt, and dI4 represents the increase in corrosion product stock at the fourth node within the time increment dt. It should be noted that the stock of iron ions in the coolant is assumed to be a time-invariant constant, and the particle precipitation in the coolant is always equal to the total particle deposition rate on the core surface. This relationship is also independent of the particle size distribution in the coolant.

[0151] In one implementation, for the first node, its corrosion product transfer equilibrium equation, i.e., the expression of the corresponding first prediction sub-model, is as follows:

[0152]

[0153] Where dI1 represents the increase in the amount of corrosion products at the first node within the time increment dt, J dp f represents the deposition rate of soluble corrosion products. p1 J represents the particle deposition fraction of the first node. cr This indicates the crystallization rate of soluble corrosion products.

[0154] Similarly, for the third node, its corrosion product transfer equilibrium equation, i.e., the expression of the corresponding third predictive sub-model, is as follows:

[0155]

[0156] Where dI3 represents the increase in the amount of corrosion products at the third node within the time increment dt, CR represents the corrosion rate of the steam generator, and J rl f represents the ion release rate of corrosion products. p3 J represents the particle deposition fraction at the third node. cr This indicates the crystallization rate of soluble corrosion products.

[0157] Therefore, once the calculation parameters of the corrosion products are obtained, the amount of corrosion products at each node can be calculated using formulas (30) to (32), that is, the content of corrosion products at each node can be obtained, and the migration and distribution of corrosion products can be predicted based on the changes in the amount of corrosion products at each node. For example, the process of generation, corrosion, release, migration, deposition, precipitation and growth of corrosion products in the primary circuit can be fully simulated, and the migration route of corrosion products from generation to deposition in the primary circuit can be restored. This improves the safety of pressurized water reactor operation, provides a scientific basis for reactor management and maintenance, and has good practical value.

[0158] In summary, the method for predicting the content of corrosion products in the primary loop of a pressurized water reactor provided in this invention, by modeling the water chemistry conditions of a given reactor and based on reaction kinetics, reaction equilibrium theory, and mass transfer theory, constructs a four-node model for predicting the migration and distribution of corrosion products in the primary loop. This simplifies the corrosion products in the primary loop into four key nodes. By constructing and solving the corrosion product content conservation equation, the entire process of generation, migration, deposition, and growth of corrosion products in the primary loop is simulated, reconstructing the migration path of corrosion products from generation to deposition in the primary loop. This provides an important reference for predicting CRUD growth thickness, corrosion product content in the coolant, and corrosion status of the steam generator. Furthermore, considering the complex loop structure and temperature changes in the primary loop, the design of the prediction sub-models corresponding to the four nodes can more realistically reflect the corrosion product migration process, while also addressing the diverse morphologies of corrosion products and their temperature and flow field control characteristics. Finally, it improves the safety attributes of the reactor, provides important support for predicting CIPS and CILC, and is of great value for protecting the integrity of fuel rods, preventing the leakage of radioactive materials, and ensuring reactor safety.

[0159] Example 2:

[0160] Corresponding to the above method embodiments, this invention also provides a device for predicting the content of corrosion products in the primary loop of a pressurized water reactor. The corrosion products include soluble corrosion products and corrosion product particles. The primary loop of the pressurized water reactor is equivalent to multiple nodes. The multiple nodes include: a first node, a second node, a third node, and a fourth node. The first node is used to characterize the core of the pressurized water reactor primary loop, the second node is used to characterize the soluble corrosion products in the coolant, the third node is used to characterize the steam generator of the pressurized water reactor primary loop, and the fourth node is used to characterize the corrosion product particles in the coolant.

[0161] like Figure 4 As shown, the device includes: an acquisition module 41 and a calculation module 42; wherein the functions of each module are as follows:

[0162] The acquisition module 41 is used to acquire the calculation parameters of the corrosion products; wherein the calculation parameters include at least one of the following: crystallization rate of soluble corrosion products, deposition rate of soluble corrosion products, ion release rate of corrosion products, corrosion rate of steam generator, particle deposition fraction of the first node and particle deposition fraction of the third node.

[0163] The calculation module 42 is used to input the calculation parameters into the pre-built prediction model so that the prediction model outputs the content information of corrosion products according to the calculation parameters; wherein, the content information includes the content of corrosion products at each node, and the prediction model includes: a first prediction sub-model corresponding to the first node, a second prediction sub-model corresponding to the second node, a third prediction sub-model corresponding to the third node, and a fourth prediction sub-model corresponding to the fourth node.

[0164] The corrosion product content prediction device for the primary loop of a pressurized water reactor (PWR) provided in this invention first equates the PWR to a first node representing the reactor core, a second node representing soluble corrosion products in the coolant, a third node representing the steam generator, and a fourth node representing corrosion product particles in the coolant. Then, it acquires calculation parameters for the corrosion products and inputs these parameters into a pre-built prediction model, allowing the model to output corrosion product content information based on the calculation parameters. This content information includes the corrosion product content at each node. This prediction method can obtain the corrosion product content at each node in the PWR primary loop, enabling the reconstruction of the distribution and migration of corrosion products within the PWR primary loop based on the corrosion product content at each node. This improves the safety of the fuel rods and reactor core, ensures the integrity of the cladding during long-term use, prevents radioactive material leakage, and ensures reactor safety.

[0165] Preferably, the calculation module 42 further includes:

[0166] The expression for the first predictive sub-model is as follows:

[0167]

[0168] Where dI1 represents the increase in the amount of corrosion products at the first node within the time increment dt, J dp f represents the deposition rate of soluble corrosion products. p1 J represents the particle deposition fraction of the first node. cr This indicates the crystallization rate of soluble corrosion products.

[0169] Preferably, the calculation module 42 further includes:

[0170] The expression for the third predictive sub-model is as follows:

[0171]

[0172] Where dI3 represents the increase in the amount of corrosion products at the third node within the time increment dt, CR represents the corrosion rate of the steam generator, and J rl f represents the ion release rate of corrosion products. p3 J represents the particle deposition fraction at the third node. cr This indicates the crystallization rate of soluble corrosion products.

[0173] Preferably, the calculation module 42 further includes:

[0174] The expressions for the second and fourth prediction sub-models are as follows:

[0175]

[0176] Where dI2 represents the increase in the amount of corrosion products at the second node within the time increment dt, and dI4 represents the increase in the amount of corrosion products at the fourth node within the time increment dt.

[0177] Preferably, the acquisition module 41 further includes: acquiring concentration parameters of soluble corrosion products; wherein the concentration parameters include: saturation concentration of soluble corrosion products, concentration of soluble corrosion products at the interface between the coolant and the metal surface, and concentration of soluble corrosion products in the mainstream area; calculating the crystallization rate, deposition rate, and ion release rate of soluble corrosion products based on the concentration parameters and preset mass transfer coefficients; wherein the mass transfer coefficients include: crystallization mass transfer coefficient, deposition mass transfer coefficient, and release mass transfer coefficient.

[0178] Preferably, the crystallization rate, deposition rate, and ion release rate of soluble corrosion products are calculated based on concentration parameters and preset mass transfer coefficients, including: calculating the crystallization rate of soluble corrosion products based on the saturation concentration of soluble corrosion products, the concentration of soluble corrosion products at the interface, and the crystallization mass transfer coefficient; calculating the deposition rate of soluble corrosion products based on the saturation concentration of soluble corrosion products, the concentration of soluble corrosion products in the mainstream area, and the deposition mass transfer coefficient; and calculating the ion release rate of corrosion products based on the saturation concentration of soluble corrosion products, the concentration of soluble corrosion products in the mainstream area, and the release mass transfer coefficient.

[0179] Preferably, the elements in the corrosion products include at least one of the following: iron, chromium, and nickel. The apparatus further includes: acquiring basic parameters of the corrosion products; wherein the basic parameters include: solid stoichiometry, hydrogen partial pressure, activity coefficient of neutral substances, activity coefficient of monovalent ions, hydrogen ion concentration, and reaction constants of the hydrolysis-related reactions of the corrosion products; and calculating solubility information of the corrosion products based on the basic parameters; wherein the solubility information includes: saturation concentration of iron, saturation concentration of chromium, and saturation concentration of nickel.

[0180] The corrosion product content prediction device in the primary loop of a pressurized water reactor provided in this embodiment of the invention has the same technical features as the corrosion product content prediction method in the primary loop of a pressurized water reactor provided in the above embodiment, so it can also solve the same technical problems and achieve the same technical effects.

[0181] This invention also provides an electronic device, including a processor and a memory. The memory stores machine-executable instructions that can be executed by the processor. The processor executes the machine-executable instructions to implement the above-described method for predicting the content of corrosion products in the primary loop of a pressurized water reactor.

[0182] See Figure 5As shown, the electronic device includes a processor 100 and a memory 101. The memory 101 stores machine-executable instructions that can be executed by the processor 100. The processor 100 executes the machine-executable instructions to implement the above-described method for predicting the content of corrosion products in the primary loop of a pressurized water reactor.

[0183] Furthermore, Figure 5 The electronic device shown also includes a bus 102 and a communication interface 103, with the processor 100, the communication interface 103 and the memory 101 connected via the bus 102.

[0184] The memory 101 may include high-speed random access memory (RAM) or non-volatile memory, such as at least one disk storage device. Communication between this system network element and at least one other network element is achieved through at least one communication interface 103 (which can be wired or wireless), such as the Internet, wide area network, local area network, or metropolitan area network. The bus 102 may be an ISA (Industrial Standard Architecture) bus, a PCI (Peripheral Component Interconnect) bus, or an EISA (Enhanced Industry Standard Architecture) bus. These buses can be categorized as address buses, data buses, and control buses. For ease of representation, Figure 5 The symbol is represented by a single double-headed arrow, but this does not mean that there is only one bus or one type of bus.

[0185] Processor 100 may be an integrated circuit chip with signal processing capabilities. In implementation, each step of the above method can be completed by the integrated logic circuitry in the hardware of processor 100 or by instructions in software form. Processor 100 may be a general-purpose processor, including a Central Processing Unit (CPU), a Network Processor (NP), etc.; it may also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field-Programmable Gate Array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. It can implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of this invention. The general-purpose processor may be a microprocessor or any conventional processor. The steps of the methods disclosed in the embodiments of this invention can be directly manifested as execution by a hardware decoding processor, or execution by a combination of hardware and software modules in the decoding processor. The software module can reside in a readily available storage medium in the art, such as random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, or registers. This storage medium is located in memory 101, and the processor 100 reads the information from memory 101 and, in conjunction with its hardware, completes the steps of the method described in the foregoing embodiments.

[0186] This embodiment also provides a machine-readable storage medium storing machine-executable instructions. When the machine-executable instructions are called and executed by a processor, the machine-executable instructions cause the processor to implement the above-mentioned method for predicting the content of corrosion products in the primary loop of a pressurized water reactor.

[0187] The computer program product of the method, apparatus and electronic device for predicting the content of corrosion products in the primary loop of a pressurized water reactor provided in the embodiments of the present invention includes a computer-readable storage medium storing program code. The instructions included in the program code can be used to execute the methods described in the preceding method embodiments. For specific implementation, please refer to the method embodiments, which will not be repeated here.

[0188] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working process of the system and apparatus described above can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0189] Furthermore, in the description of the embodiments of the present invention, unless otherwise explicitly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in the present invention based on the specific circumstances.

[0190] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a processor-executable, non-volatile, computer-readable storage medium. Based on this understanding, the technical solution of this invention, essentially, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0191] In the description of this invention, it should be noted that the terms "center," "upper," "lower," "left," "right," "vertical," "horizontal," "inner," and "outer," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are used only for the convenience of describing the invention and for simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on the invention. Furthermore, the terms "first," "second," and "third" are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0192] Finally, it should be noted that the above-described embodiments are merely specific implementations of the present invention, used to illustrate the technical solutions of the present invention, and not to limit it. The scope of protection of the present invention is not limited thereto. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that any person skilled in the art can still modify or easily conceive of changes to the technical solutions described in the foregoing embodiments within the technical scope disclosed in the present invention, or make equivalent substitutions for some of the technical features; and these modifications, changes, or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be covered within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A method for predicting the corrosion product content in a pressurized water reactor primary circuit, the corrosion product including soluble corrosion products and corrosion product particles, the pressurized water reactor primary circuit being equivalent to a plurality of nodes; wherein, The plurality of nodes comprise: a first node for representing a reactor core of the pressurized water reactor primary loop, a second node for representing the soluble corrosion product in the coolant, a third node for representing a steam generator of the pressurized water reactor primary loop, and a fourth node for representing the corrosion product particles in the coolant; and the method comprises: obtaining a calculation parameter of the corrosion product, wherein the calculation parameter comprises at least one of a soluble corrosion product crystallization rate, a soluble corrosion product deposition rate, a corrosion product ion release rate, a steam generator corrosion rate, a particle deposition fraction of the first node, and a particle deposition fraction of the third node; inputting the calculation parameter into a pre-constructed prediction model, so that the prediction model outputs content information of the corrosion product according to the calculation parameter, wherein the content information comprises corrosion product contents at each of the nodes, and the prediction model comprises a first prediction sub-model corresponding to the first node, a second prediction sub-model corresponding to the second node, a third prediction sub-model corresponding to the third node, and a fourth prediction sub-model corresponding to the fourth node.

2. The method of claim 1, wherein, The step of inputting the calculation parameter into a pre-constructed prediction model, so that the prediction model outputs content information of the corrosion product according to the calculation parameter, comprises: The expression of the first prediction sub-model is as follows: wherein dI1 represents the increment of the inventory of corrosion products of the first node in the increment of time dt, J dp represents the rate of dissolution of the corrosion products, f p1 represents the fraction of particles deposited in the first node, J cr represents the rate of crystallization of the soluble corrosion products.

3. The method of claim 1, wherein, The step of inputting the calculation parameter into a pre-constructed prediction model, so that the prediction model outputs content information of the corrosion product according to the calculation parameter, comprises: The expression of the third prediction sub-model is as follows: wherein dl3 represents the increment of the inventory of corrosion products of the third node in the increment of time dt, CR represents the corrosion rate of the steam generator, J rl represents the release rate of the corrosion product ions, f p3 represents the fraction of the deposition of the particles of the third node, J cr represents the crystallization rate of the soluble corrosion products.

4. The method of claim 1, wherein, The step of inputting the calculation parameter into a pre-constructed prediction model, so that the prediction model outputs content information of the corrosion product according to the calculation parameter, comprises: The expressions of the second prediction sub-model and the fourth prediction sub-model are as follows: wherein dI2 represents a corrosion product stock increment of the second node within a time increment dt, and dI4 represents a corrosion product stock increment of the fourth node within the time increment dt.

5. The method of claim 1, wherein, The step of obtaining the calculation parameter of the corrosion product comprises: obtaining a concentration parameter of the soluble corrosion product, wherein the concentration parameter comprises a soluble corrosion product saturation concentration, a soluble corrosion product concentration at an interface between the coolant and a metal surface, and a soluble corrosion product concentration in a main flow region; calculating the soluble corrosion product crystallization rate, the soluble corrosion product deposition rate, and the corrosion product ion release rate according to the concentration parameter and preset mass transfer coefficients, wherein the mass transfer coefficients comprise a crystallization mass transfer coefficient, a deposition mass transfer coefficient, and a release mass transfer coefficient.

6. The method of claim 5, wherein, The step of calculating the soluble corrosion product crystallization rate, the soluble corrosion product deposition rate, and the corrosion product ion release rate according to the concentration parameter and preset mass transfer coefficients comprises: calculating the soluble corrosion product crystallization rate according to the soluble corrosion product saturation concentration, the interface soluble corrosion product concentration, and the crystallization mass transfer coefficient; calculating the soluble corrosion product deposition rate according to the soluble corrosion product saturation concentration, the main flow region soluble corrosion product concentration, and the deposition mass transfer coefficient; and calculating the corrosion product ion release rate according to the soluble corrosion product saturation concentration, the interface soluble corrosion product concentration, and the release mass transfer coefficient. The soluble corrosion product deposition rate is calculated according to the soluble corrosion product saturation concentration, the soluble corrosion product concentration in the main flow area and the deposition mass transfer coefficient; The corrosion product ion release rate is calculated according to the soluble corrosion product saturation concentration, the soluble corrosion product concentration in the main flow area and the release mass transfer coefficient.

7. The method of claim 1, wherein, The elements of the corrosion product include at least one of iron, chromium and nickel, and the method further comprises: Basic parameters of the corrosion product are obtained; wherein the basic parameters include solid stoichiometric ratio, hydrogen partial pressure, activity coefficient of neutral substance, activity coefficient of monovalent ion, hydrogen ion concentration and reaction constant of corrosion product hydrolysis related reaction; Solubility information of the corrosion product is calculated according to the basic parameters; wherein the solubility information includes saturation concentration of iron, saturation concentration of chromium and saturation concentration of nickel.

8. An apparatus for predicting a corrosion product content in a pressurized water reactor primary loop, the corrosion product including soluble corrosion products and corrosion product particles, the pressurized water reactor primary loop being equivalent to a plurality of nodes; wherein, The plurality of nodes include a first node, a second node, a third node and a fourth node, the first node is used to represent a reactor core of a pressurized water reactor primary loop, the second node is used to represent the soluble corrosion product in the coolant, the third node is used to represent a steam generator of the pressurized water reactor primary loop, and the fourth node is used to represent the corrosion product particles in the coolant; characterized in that the device comprises: A calculation parameter of the corrosion product is obtained by the obtaining module; wherein the calculation parameter includes at least one of soluble corrosion product crystallization rate, soluble corrosion product deposition rate, corrosion product ion release rate, steam generator corrosion rate, particle deposition fraction of the first node and particle deposition fraction of the third node; The calculation module inputs the calculation parameter into a pre-constructed prediction model, so that the prediction model outputs content information of the corrosion product according to the calculation parameter; wherein the content information includes corrosion product content at each node, and the prediction model includes a first prediction sub-model corresponding to the first node, a second prediction sub-model corresponding to the second node, a third prediction sub-model corresponding to the third node and a fourth prediction sub-model corresponding to the fourth node.

9. An electronic device comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that, The processor executes the computer program to implement the steps of the method of any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The computer readable storage medium stores a computer program, and the computer program is run by the processor to execute the steps of the method of any one of claims 1-7.

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