Method for evaluating safety of molten pool in severe accident of reactor

Abstract

The application is a kind of reactor severe accident molten pool safety evaluation method, input core component mass, select component distribution model, determine the key parameters of component distribution, import a variety of extreme conditions as optimization target into genetic algorithm, determine the structure of each model and the physical property of each layer;Using the molten pool transient phase change model software to perform numerical operation, simulate the heat flux density distribution of the head wall surface under each extreme condition, take the maximum value of the heat flux density distribution of each condition to obtain the safety evaluation curve of the molten pool, and provide guidance for the molten pool cooling facility under severe safety accident.The application solves the problem of unknown molten pool component distribution through genetic algorithm, and determines the molten pool structure and components under extreme conditions, and then obtains the molten pool safety evaluation curve under extreme accident conditions, and provides guidance for the molten pool cooling measures under severe safety accident.

Description

Technical Field

[0001] This invention belongs to the field of severe nuclear reactor accidents, and relates to the structure and flow heat transfer of the molten pool. In particular, it relates to a method for assessing the safety of the molten pool under severe accidents by considering the composition, mass, and power density of the reactor core. Background Technology

[0002] Following a severe nuclear reactor accident, the decay heat released from the nuclear fuel causes the reactor core to gradually melt and deteriorate, transferring to the lower head of the pressure vessel to form a molten pool. During a severe accident, the reactor core continuously melts and may even collapse under the influence of decay heat, with the molten material accumulating in the lower head of the pressure vessel to form a molten pool. Simultaneously, the interactions between the main components of the molten material can lead to stratification within the molten pool, and different molten pool structures will affect the heat flux density distribution on the outer wall of the lower head of the reactor pressure vessel. To address these issues, a method is needed to assess the safety of the molten pool in order to take appropriate measures to reduce the thermal effects of the reactor molten pool and decrease the reliability of melt-through.

[0003] In recent years, some researchers have used the lumped parameter method to study the heat transfer of multilayer molten pools. However, they have studied specific cases of each layer composition to explore the safety of the lower head wall. However, the composition of the molten pool varies greatly in different accident sequences. Therefore, various components of the molten pool may exist, and each possible component may lead to the failure of the lower head. Analyzing the extreme component distribution to assess the safety of the lower head wall is of great significance. Summary of the Invention

[0004] To overcome the shortcomings of the prior art, the present invention aims to provide a method for assessing the safety of the molten pool under severe reactor accidents. The method uses a genetic algorithm to calculate the composition of the multi-layered molten pool, obtains the structure and properties of each layer under extreme conditions, and calculates the heat flux density curves of the head under each extreme condition using the finite volume method. These curves are then combined to form a safety assessment curve for the molten pool, thus realizing the assessment of the molten pool safety and the heat transfer characteristics.

[0005] To achieve the above objectives, the present invention adopts the following technical solution: A method for assessing the safety of the molten pool under severe reactor accidents includes the following steps: Step 1: Establish a multi-layer molten pool composition distribution model and determine the mass percentage of each component as the key parameter based on the composition distribution characteristics of each layer. Step 2: Determine various extreme operating conditions of the molten pool based on the thickness and power density distribution characteristics of each layer; Step 3: Optimize various extreme working conditions using a genetic algorithm to determine the values ​​of the key parameters, thereby obtaining the molten pool geometry and composition distribution. Based on the composition distribution, perform volume-weighted and mass-weighted averaging to obtain the physical properties of each layer. Step 4: Based on the geometry of the molten pool and the properties of each layer, the flow and heat transfer characteristics of the molten pool are calculated using the finite volume method. Then, based on the calculation results of the flow and heat transfer of the molten pool, the heat flux density distribution of the head wall under various extreme conditions is statistically analyzed. The maximum value of the heat flux density under various extreme conditions is collected to form a safety assessment curve. By comparing it with the critical heat flux density curve, the safety of the molten pool is determined.

[0006] In one embodiment, step one, establishing a multilayer molten pool composition distribution model, involves designing the composition distribution model as a calculation formula based on the mass percentage of each component. Here, "each component" refers to all components in all layers.

[0007] In one embodiment, step two, the process of determining the extreme operating conditions of the molten pool, is as follows: Based on the mass and density of each component in each layer, the volume of each component in each layer is determined, and then the volume of each layer is calculated, and the thickness of each layer can be calculated accordingly. Calculate the decay heat in the molten pool and the power distribution ratio of several decay heat layers; The extreme operating conditions identified in this invention include: the thickness of a certain layer of the molten pool reaches a minimum, and the power density of a certain layer reaches a maximum according to the aforementioned decay heat power distribution ratio.

[0008] In one embodiment, step three involves determining the mass and power density of each component in each layer based on the relationship between each key parameter and the volume and power density of each layer, and by introducing density and partial component content constraints, using the values ​​of each key parameter determined in step one. A genetic algorithm is used to optimize the component distribution model. A random initial population is generated, with each individual representing a potential solution. The solutions are represented using an encoding method, and key parameters are arranged in sequence to obtain a gene chain, which serves as the encoded population individuals. Various extreme operating conditions are defined as functions evaluating the fitness of the population individuals. Subsequent operations such as selection, crossover, and mutation are used to obtain the optimal value of the function, thereby obtaining the molten pool geometry and physical properties under various extreme conditions. These physical properties include density, coefficient of thermal expansion, and specific heat capacity. 、 Latent heat of fusion and thermal conductivity.

[0009] In one embodiment, step four, the flow and heat transfer characteristics of the molten pool are calculated as follows: First, the geometry of the molten pool is modeled and meshed using software. Then, the physical properties of each layer are determined by the mass percentage of each layer's components. Finally, the flow and heat transfer characteristics of the molten pool are calculated using the finite volume method.

[0010] Compared with the prior art, the present invention has the following advantages: 1. This invention establishes a molten pool composition distribution model based on the principle of multi-layer molten pool mass transfer, and uses a genetic algorithm to perform iterative calculations on near-end conditions in order to determine the composition and physical properties of each layer of the molten pool under extreme conditions, thereby enabling the determination of extreme molten pool conditions for different types of reactor cores.

[0011] 2. This invention compiles the heat flux density of the molten pool under extreme operating conditions into a safety assessment curve of the molten pool. With knowledge of relevant parameters such as the composition, mass, and power density of the reactor core, it can predict the thermal characteristics of the molten pool under severe accidents, so as to design corresponding methods to cool the hot spots.

[0012] In summary, this invention can predict the composition and structure of the molten pool under different severe accidents in reactor cores, improve the calculation efficiency of the thermal properties of the molten pool, and further improve the effectiveness of molten pool cooling measures. Attached Figure Description

[0013] Figure 1 This is a calculation diagram for extreme operating conditions of the molten pool composition model.

[0014] Figure 2 This is the safety assessment curve for the molten pool. Detailed Implementation

[0015] To more clearly illustrate the purpose, method, and advantages of this invention, the invention will be further explained in conjunction with the accompanying drawings.

[0016] The method for assessing the safety of the molten pool under severe reactor accidents according to this invention mainly includes the following steps: Step 1: Construct a multi-layer molten pool composition model.

[0017] This invention takes a typical three-layer molten pool consisting of a light metal layer, an oxide layer, and a heavy metal layer as an example. Each of the light metal layer, oxide layer, and heavy metal layer has its own composition and composition mass percentage. Due to the presence of eutectic reaction in the molten pool, there is a large uncertainty in the composition and composition mass percentage of each layer. Therefore, the composition and composition mass percentage of the molten pool are characterized by several key parameters.

[0018] The light metal layer consists of Zr and Fe, the oxide layer consists of ZrO2, UO2, and Fe, and the heavy metal layer consists of U, Zr, and Fe. The process of establishing the three-layer molten pool composition distribution model is as follows: The mass of U in the heavy metal layer is: (1) In the formula, This represents the mass of UO2 in the molten pool before the displacement reaction occurs. x This represents the mass percentage of UO2 in the oxide layer relative to the total mass of UO2 in the molten pool. The mass of Zr participating in the substitution reaction is: (2) In the formula, The mass of Zr replacing U; The mass of the heavy metal layer; The mass of Zr in the heavy metal layer is: (3) In the formula, y This represents the mass percentage of U in the heavy metal layer. The mass of the heavy metal layer; The mass of Fe in the heavy metal layer is: (4) In the formula, j This represents the mass percentage of Fe in the light metal layer relative to the total Fe in the molten pool. This represents the mass of Fe in the molten pool. k This represents the mass percentage of Fe in the oxide layer relative to the total Fe in the molten pool. The masses of UO2 and ZrO2 in the oxide layer are respectively: (5) (6) In the formula, This represents the mass of UO2 in the oxide layer. This represents the mass of ZrO2 in the oxide layer. z This represents the percentage of Zr oxidation. The mass of Zr in the molten pool; The mass of Fe in the oxide layer is: (7) In the formula, k This represents the mass percentage of Fe in the oxide layer relative to the total Fe in the molten pool. The masses of Fe and Zr in the light metal layer are: (8) (9) In the formula, The mass of Fe in the light metal layer; The mass of Zr in the light metal layer; This represents the total mass of Zr in the molten pool.

[0019] Among them, parameters x, y, z, j, k These are the key parameters described in this invention. By using these parameters, the mass of each component in each layer can be determined.

[0020] Step 2: Determine the extreme operating conditions of the multi-layer molten pool.

[0021] First, determine the volume of each layer based on the mass and density of each component: The volume of the light metal layer is: (10) (11) (12) In the formula, Let be the volume of Fe in the light metal layer; The density of Fe; Let Zr be the volume of the light metal layer; The density of Zr, The volume of the light metal layer.

[0022] The volume of the oxide layer is: (13) (14) (15) (16) In the formula, This represents the volume of UO2 in the oxide layer; The density of UO2; This represents the volume of ZrO2 in the oxide layer; The density of ZrO2; Let be the volume of Fe in the oxide layer. This represents the volume of the oxide layer.

[0023] The volume of the heavy metal layer is: (17) (18) (19) (20) In the formula, Let U be the volume of U in the heavy metal layer; The density of U; Let Zr be the volume of the heavy metal layer. Let be the volume of Fe in the heavy metal layer. The volume of the heavy metal layer.

[0024] The thickness of the heavy metal layer is calculated using the following formula: (twenty one) The thickness of the oxide layer is calculated as follows: (twenty two) The thickness of the heavy metal layer is calculated as follows: (twenty three) In the formula, The thickness of the heavy metal layer; The thickness of the oxide layer; The thickness of the light metal layer; R Let be the radius of the molten pool.

[0025] Decay heat in the molten pool Calculated by the following formula: (twenty four) In the formula, f d This is a correction factor for volatile fission products; P 0 represents the initial thermal power of the reactor core. t This is the time since the reactor was shut down.

[0026] In a three-layer molten pool structure, neglecting decay heat in the light metal layer, the power distribution ratio of decay heat between the heavy metal layer and the oxide layer, while keeping the total power constant, is calculated according to the following formula: (25) In the formula, For the thermal power of the oxide layer, This represents the thermal power of the heavy metal layer.

[0027] when At its minimum, the light metal layer is the thinnest; At its minimum, the heavy metal layer is the thinnest; At its minimum, the oxygen metal layer is the thinnest; At its maximum, the power density of the heavy metal layer is at its maximum. At its maximum, the oxide layer power density is at its highest; the above process determined five extreme operating conditions.

[0028] Step 3: Use a genetic algorithm to perform optimization calculations for various extreme working conditions.

[0029] Based on the relationship between each key parameter and the volume and power density of each layer, it can be seen that when x As the volume increases, the volume of the oxide layer increases, and the power density increases; when y As the power density of the heavy metal layer increases, the power density of the heavy metal layer also increases; when z As the volume increases, the volume of the oxide layer increases; when j As the volume increases, the volume of the light metal layer increases; when k As the volume increases, the volume of the oxide layer also increases.

[0030] Subsequently, two constraints were introduced into the composition distribution model of the molten pool: first, the density of the heavy metal layer must be greater than that of the oxide layer, and the density of the oxide layer must be greater than that of the light metal layer; second, the Zr content of the light metal layer cannot be negative. These constraints were then determined by defining key parameters. x , y , z, j, k The value of is used to determine the mass and power density of each layer component.

[0031] A genetic algorithm is used to optimize the component distribution model. A random initial population is generated, with each individual representing a potential solution. The solution is represented by an encoding method, specifically binary encoding. The five key parameters are arranged in order to obtain the gene chain, which is then converted to binary to obtain the encoded population individuals. The conditions of the five extreme working conditions are defined as functions to evaluate the fitness of the population individuals. Subsequently, selection, crossover, and mutation operations are used to obtain the optimal value of the function, thereby obtaining the geometric structure and physical property parameters of the molten pool under various extreme working conditions.

[0032] Step 4: Plot the safety assessment curve.

[0033] Once the physical model of the molten pool is determined, the geometry of the molten pool is first modeled and meshed using appropriate software. Then, the physical properties of each layer are determined by the mass percentage of each layer's composition. Finally, the flow and heat transfer characteristics of the molten pool are calculated using the finite volume method. The physical properties of each layer include density. ρ Coefficient of thermal expansion β Specific heat capacity c、 Latent heat of fusion Δ h and thermal conductivity λ Calculated by the following formula: Light metal layer: (26) (27) (28) (29) (30) In the formula, The density of the light metal layer; is the coefficient of thermal expansion of the light metal layer; Zr is the coefficient of thermal expansion. The coefficient of thermal expansion of Fe; The specific heat capacity of the light metal layer; The specific heat capacity of Zr; Let be the specific heat capacity of Fe; The latent heat of fusion of the light metal layer; The latent heat of fusion of Fe; The latent heat of fusion of Zr; The thermal conductivity of the light metal layer; Let Zr be the thermal conductivity. is the thermal conductivity of Fe; The volume ratio of Zr in the light metal layer; The volume ratio of Fe in the light metal layer; The mass ratio of Zr in the light metal layer; This represents the mass ratio of Fe in the light metal layer.

[0034] Oxide layer: (31) (32) (33) (34) (35) In the formula, The density of the oxide layer; The coefficient of thermal expansion of the oxide layer; The coefficient of thermal expansion of UO2; The coefficient of thermal expansion of ZrO2; The specific heat capacity of the oxide layer; The specific heat capacity of UO2; The specific heat capacity of ZrO2; The latent heat of fusion of the oxide layer; The latent heat of fusion of ZrO2; The latent heat of fusion of UO2; The thermal conductivity of the oxide layer; The thermal conductivity of ZrO2; The thermal conductivity of UO2; This represents the volume ratio of ZrO2 in the oxide layer; This represents the volume ratio of UO2 in the oxide layer; This refers to the mass ratio of ZrO2 in the oxide layer; The mass ratio of UO2 in the oxide layer; This represents the volume ratio of Fe in the oxide layer; This represents the mass ratio of Fe in the oxide layer.

[0035] Heavy metal layer: (36) (37) (38) (39) (40) In the formula, The density of the heavy metal layer; The coefficient of thermal expansion of the heavy metal layer; U is the coefficient of thermal expansion. The specific heat capacity of the heavy metal layer; Let U be the specific heat capacity. The latent heat of fusion of the heavy metal layer; The latent heat of fusion of U; The thermal conductivity of the heavy metal layer; Let U be the thermal conductivity. The volume ratio of Zr in the heavy metal layer; The volume ratio of U in the heavy metal layer; This represents the volume ratio of Fe in the heavy metal layer; This represents the mass ratio of Fe in the heavy metal layer. The mass ratio of U in the heavy metal layer; This represents the mass ratio of Zr in the heavy metal layer.

[0036] Based on the calculation results of heat transfer in the molten pool, the heat flux density distribution on the head wall under five extreme conditions was statistically analyzed. The maximum value of the heat flux density under the five extreme conditions was taken and combined to form a safety assessment curve. The safety of the molten pool was judged by comparing it with the critical heat flux density curve.

[0037] In summary, this invention establishes a molten pool composition model based on the three-layer molten pool mass transfer principle and uses a genetic algorithm to iteratively calculate extreme operating conditions in order to determine the composition and properties of each layer of the molten pool under extreme conditions. This enables the determination of extreme molten pool operating conditions for different types of reactor cores. Furthermore, this invention compiles the heat flux density of the molten pool under extreme operating conditions into a molten pool safety assessment curve. Given the composition, mass, power density, and other relevant parameters of the reactor core, it can predict the thermal characteristics of the molten pool under severe accidents, thereby enabling the design of corresponding methods to cool hotspot locations. This invention has broad application prospects.

[0038] In a further embodiment of the present invention, the radius of the molten pool is 2.2 m, the thickness of the lower head wall is 0.15 m, and the thickness of each layer is calculated based on the mass percentage of different components. The embodiment simplifies the component distribution, selecting a component distribution model where the light metal layer contains Fe and Zr, the oxide layer contains ZrO2 and UO2, and the heavy metal layer contains U and Fe.

[0039] Step 1: Establish a three-layer molten pool composition distribution model. Based on the composition distribution characteristics of the three-layer molten pool, determine the corresponding key parameters. The key parameters include the mass percentage of UO2 in the oxide layer to the mass percentage of UO2 in the molten pool, the mass percentage of U in the heavy metal layer to the mass percentage of Zr oxidation, the mass percentage of Fe in the light metal layer to the mass percentage of Fe in the molten pool, and the mass percentage of Fe in the oxide layer to the mass percentage of Fe in the molten pool.

[0040] Step 2: Based on the component distribution model in Step 1, determine the extreme operating conditions of the molten pool, including the thinnest light metal layer, the thinnest heavy metal layer, the thinnest oxide layer, the highest power density of the heavy metal layer, and the highest power density of the oxide layer.

[0041] Step 3: Based on the extreme conditions in Step 2, the genetic algorithm is used to calculate each condition. The component distribution of the five conditions is shown in Table 1.

[0042] Table 1. Quality Percentage for Five Operating Conditions Step four: Based on the physical properties and power density of each molten layer from step three, as shown in Table 2-6, the geometry of the molten pool is first modeled and meshed using appropriate software. Then, the physical properties of each layer are determined by the mass percentage of each layer's composition. Finally, the flow and heat transfer characteristics of the molten pool are calculated using the finite volume method.

[0043] Table 2. Properties and thickness of each layer in the thinnest molten pool with the light metal layer. parameter Heavy metal layer Oxide layer Light metal layer unit density 10519 7824 6952 kg·m⁻³ Isobaric specific heat capacity 478 569 813 J·kg-1·K-1 thermal conductivity 39 4.8 24 W·m-1·K-1 Latent heat of fusion 123 390 266 kJ·kg⁻¹ coefficient of thermal expansion 1.13×10-4 1.05×10-4 1.16×10-4 K-1 thickness 0.49 1.26 0.39 m Power density 1.72 1.50 / MW·m-3 Table 3. Physical properties and thickness of each layer in the molten pool with the thinnest heavy metal layer. density Heavy metal layer Oxide layer Light metal layer unit density 10671 7882 6928 kg·m⁻³ Specific heat capacity 468 563 805 J·kg-1·K-1 thermal conductivity 39 4.87 24 W·m-1·K-1 Latent heat of fusion 119 382 266 kJ·kg⁻¹ coefficient of thermal expansion 1.13×10-4 1.05×10-4 1.14×10-4 K-1 thickness 0.39 1.33 0.42 m Power density 1.80 1.56 / MW·m-3 Table 4. Properties and thickness of each layer in the molten pool with the thinnest oxide layer. parameter Heavy metal layer Oxide layer Light metal layer unit density 13254 7807 6841 kg·m⁻³ Isobaric specific heat capacity 331 571 776 J·kg-1·K-1 thermal conductivity 43 4.8 25 W·m-1·K-1 Latent heat of fusion 78 392 263 kJ·kg⁻¹ coefficient of thermal expansion 1.07×10-4 1.05×10-4 1.08×10-4 K-1 thickness 0.64 0.95 0.45 m Power density 3.08 1.50 / MW·m-3 Table 5. Physical properties and thickness of each layer in the molten pool with the highest power density of the heavy metal layer. density Heavy metal layer Oxide layer Light metal layer unit density 14310 7806 6851 kg·m⁻³ Specific heat capacity 289 571 780 J·kg-1·K-1 thermal conductivity 45 4.8 25 W·m-1·K-1 Latent heat of fusion 65 392 263 kJ·kg⁻¹ coefficient of thermal expansion 1.05×10-4 1.05×10-4 1.09×10-4 K-1 thickness 0.59 0.97 0.47 m Power density 3.60 1.50 / MW·m-3 Table 6. Properties and thickness of each layer in the molten pool with the highest oxide layer power density. density Heavy metal layer Oxide layer Light metal layer unit density 12734 8029 6780 kg·m⁻³ Specific heat capacity 354 548 756 J·kg-1·K-1 thermal conductivity 42 5 25 W·m-1·K-1 Latent heat of fusion 85 363 261 kJ·kg⁻¹ coefficient of thermal expansion 1.04×10-4 1.05×10-4 1.05×10-4 K-1 thickness 0.54 1.02 0.50 m Power density 2.82 1.68 / MW·m-3 Step 5: Based on the calculation results of molten pool flow and heat transfer in Step 4, statistically analyze the heat flux density distribution on the head wall under five extreme conditions. Take the maximum value of the heat flux density under each of the five extreme conditions and synthesize it into a safety assessment curve, such as... Figure 2 As shown, the molten pool is relatively safe compared to the critical heat flux density curve, but the heat flux density of its light metal layer is relatively high, which should be a key consideration when designing corresponding cooling measures.

Claims

1. A method for assessing the safety of the molten pool under a severe reactor accident, characterized in that, Includes the following steps: Step 1: Establish a multi-layer molten pool composition distribution model and determine the mass percentage of each component as the key parameter based on the composition distribution characteristics of each layer. Step 2: Determine various extreme operating conditions of the molten pool based on the thickness and power density distribution characteristics of each layer; Step 3: Optimize various extreme working conditions using a genetic algorithm to determine the values ​​of the key parameters, thereby obtaining the molten pool geometry and composition distribution. Based on the composition distribution, perform volume-weighted and mass-weighted averaging to obtain the physical properties of each layer. Step 4: Based on the geometry of the molten pool and the properties of each layer, the flow and heat transfer characteristics of the molten pool are calculated using the finite volume method. The heat flux density distribution on the head wall under various extreme conditions is statistically analyzed. The maximum values ​​of the heat flux densities under various extreme conditions are collected to form a safety assessment curve. The safety of the molten pool is determined by comparing the curve with the critical heat flux density curve.

2. The method for assessing the safety of the molten pool under a severe reactor accident according to claim 1, characterized in that, In step one, the component distribution model is designed as a calculation formula based on the mass percentage of each component.

3. The method for assessing the safety of the molten pool under a severe reactor accident according to claim 1, characterized in that, Step two, the process for determining the extreme operating conditions of the molten pool, is as follows: Based on the mass and density of each component in each layer, the volume of each component in each layer is determined, and then the volume and thickness of each layer are calculated. Calculate the decay heat in the molten pool and the power distribution ratio of several decay heat layers; Determine extreme operating conditions, including: the minimum thickness of a certain layer in the molten pool and the maximum power density of a certain layer.

4. The method for assessing the safety of the molten pool under a severe reactor accident according to claim 1, characterized in that, In step three, based on the relationship between each key parameter and the volume and power density of each layer, and by introducing density and partial component content constraints, the mass and power density of each component in each layer are determined by the values ​​of the key parameters. A genetic algorithm is used to optimize the component distribution model. A random initial population is generated, with each individual representing a potential solution. The solutions are represented using an encoding method, and key parameters are arranged in sequence to obtain a gene chain, which serves as the encoded population individuals. Various extreme operating conditions are defined as functions evaluating the fitness of the population individuals. Selection, crossover, and mutation operations are then used to obtain the optimal value of the function, thereby obtaining the molten pool geometry and physical properties under various extreme conditions. These physical properties include density, coefficient of thermal expansion, and specific heat capacity. 、 Latent heat of fusion and thermal conductivity.

5. A method for assessing the safety of the molten pool under a severe reactor accident as described in claim 1 or 4, characterized in that, In step four, the flow and heat transfer characteristics of the molten pool are calculated as follows: First, the geometry of the molten pool is modeled and meshed using software. Then, the physical properties of each layer are determined by the mass percentage of each layer's components. Finally, the flow and heat transfer characteristics of the molten pool are calculated using the finite volume method.

6. The method for assessing the safety of the molten pool under a severe reactor accident according to claim 1, characterized in that, The molten pool has three layers: a light metal layer, an oxide layer, and a heavy metal layer. The light metal layer consists of Zr and Fe, the oxide layer consists of ZrO2, UO2, and Fe, and the heavy metal layer consists of U, Zr, and Fe.

7. The method for assessing the safety of the molten pool under a severe reactor accident according to claim 6, characterized in that, The process of establishing the component distribution model is as follows: The mass of U in the heavy metal layer is: (1) In the formula, This represents the mass of UO2 in the molten pool before the displacement reaction occurs. x This represents the mass percentage of UO2 in the oxide layer relative to the total mass of UO2 in the molten pool. The mass of Zr participating in the substitution reaction is: (2) In the formula, The mass of Zr replacing U; The mass of Zr in the heavy metal layer is: (3) In the formula, y This represents the mass percentage of U in the heavy metal layer. The mass of the heavy metal layer; The mass of Fe in the heavy metal layer is: (4) In the formula, j This represents the mass percentage of Fe in the light metal layer relative to the total Fe in the molten pool. This represents the mass of Fe in the molten pool. k This represents the mass percentage of Fe in the oxide layer relative to the total Fe in the molten pool. The masses of UO2 and ZrO2 in the oxide layer are respectively: (5) (6) In the formula, This represents the mass of UO2 in the oxide layer. This represents the mass of ZrO2 in the oxide layer. z This represents the percentage of Zr oxidation. The mass of Zr in the molten pool; The mass of Fe in the oxide layer is: (7) The masses of Fe and Zr in the light metal layer are: (8) (9) In the formula, The mass of Fe in the light metal layer; The mass of Zr in the light metal layer; This represents the total mass of Zr in the molten pool. Among them, parameters x, y, z, j, k That is, the key parameters mentioned above.

8. The method for assessing the safety of the molten pool under a severe reactor accident according to claim 7, characterized in that, Step two, the process for determining the extreme operating conditions of the molten pool, is as follows: First, determine the volume of each layer, including the volume of the light metal layer. for: (10) (11) (12) In the formula, Let be the volume of Fe in the light metal layer; The density of Fe; Let Zr be the volume of the light metal layer; The density of Zr; Oxide layer volume for: (13) (14) (15) (16) In the formula, This represents the volume of UO2 in the oxide layer; The density of UO2; This represents the volume of ZrO2 in the oxide layer; The density of ZrO2; The volume of Fe in the oxide layer; Heavy metal layer volume for: (17) (18) (19) (20) In the formula, Let U be the volume of U in the heavy metal layer; The density of U; Let Zr be the volume of the heavy metal layer. Let be the volume of Fe in the heavy metal layer; First, determine the thickness of each layer, including the thickness of the heavy metal layer. Calculated using the following formula: (21) Oxide layer thickness Calculated using the following formula: (22) Thickness of heavy metal layer Calculated using the following formula: (23) In the formula, R The radius of the molten pool; Calculate the decay heat in the molten pool : (24) In the formula, f d This is a correction factor for volatile fission products; P 0 represents the initial thermal power of the reactor core. t This refers to the time since the reactor was shut down. In a three-layer molten pool structure, neglecting decay heat in the light metal layer, the power distribution ratio of decay heat between the heavy metal layer and the oxide layer, while keeping the total power constant, is calculated according to the following formula: (25) In the formula, For the thermal power of the oxide layer, The thermal power of the heavy metal layer; Five extreme operating conditions were identified: when At its minimum, the light metal layer is the thinnest; At its minimum, the heavy metal layer is the thinnest; At its minimum, the oxygen metal layer is the thinnest; At its maximum, the power density of the heavy metal layer is at its maximum. At its maximum, the oxide layer power density is at its maximum.

9. The method for assessing the safety of the molten pool under a severe reactor accident according to claim 8, characterized in that, In step three, the relationship between each key parameter and the volume and power density of each layer is as follows: when x As the volume increases, the volume of the oxide layer increases, and the power density increases; when y As the power density of the heavy metal layer increases, the power density of the heavy metal layer also increases; when z As the volume increases, the volume of the oxide layer increases; when j As the volume increases, the volume of the light metal layer increases; when k As the size increases, the volume of the oxide layer increases; The following two constraints are introduced to the component distribution model: Constraint 1: The density of the heavy metal layer is greater than that of the oxide layer, and the density of the oxide layer is greater than that of the light metal layer; Constraint 2: The Zr content of the light metal layer cannot be negative; By determining key parameters x , y , z, j, k The value of is used to determine the mass and power density of each layer component; Subsequently, a genetic algorithm was used to optimize the component distribution model. A random initial population was generated, with each individual representing a potential solution. The solution to the problem was represented using binary encoding. The five key parameters were arranged in order to obtain the gene chain, which was then converted to binary to obtain the encoded population individuals. The conditions of the five extreme working conditions were defined as functions to evaluate the fitness of the population individuals. Subsequently, selection, crossover, and mutation operations were used to obtain the optimal value of the function, thereby obtaining the geometric structure and physical property parameters of the molten pool under various extreme working conditions.

10. The method for assessing the safety of the molten pool under a severe reactor accident according to claim 9, characterized in that, Step four involves first modeling and meshing the molten pool geometry using software, then determining the properties of each layer based on the mass percentage of each layer's composition, and finally calculating the flow and heat transfer characteristics of the molten pool using the finite volume method. The properties of each layer include density. ρ Coefficient of thermal expansion β Specific heat capacity c、 Latent heat of fusion Δ h and thermal conductivity λ Calculated by the following formula: Light metal layer: (26) (27) (28) (29) (30) In the formula, The density of the light metal layer; is the coefficient of thermal expansion of the light metal layer; Zr is the coefficient of thermal expansion. The coefficient of thermal expansion of Fe; The specific heat capacity of the light metal layer; The specific heat capacity of Zr; Let be the specific heat capacity of Fe; The latent heat of fusion of the light metal layer; The latent heat of fusion of Fe; The latent heat of fusion of Zr; The thermal conductivity of the light metal layer; Let Zr be the thermal conductivity. is the thermal conductivity of Fe; The volume ratio of Zr in the light metal layer; The volume ratio of Fe in the light metal layer; The mass ratio of Zr in the light metal layer; This represents the mass ratio of Fe in the light metal layer; Oxide layer: (31) (32) (33) (34) (35) In the formula, The density of the oxide layer; The coefficient of thermal expansion of the oxide layer; The coefficient of thermal expansion of UO2; The coefficient of thermal expansion of ZrO2; The specific heat capacity of the oxide layer; The specific heat capacity of UO2; The specific heat capacity of ZrO2; The latent heat of fusion of the oxide layer; The latent heat of fusion of ZrO2; The latent heat of fusion of UO2; The thermal conductivity of the oxide layer; The thermal conductivity of ZrO2; The thermal conductivity of UO2; This represents the volume ratio of ZrO2 in the oxide layer; This represents the volume ratio of UO2 in the oxide layer; This refers to the mass ratio of ZrO2 in the oxide layer; The mass ratio of UO2 in the oxide layer; This represents the volume ratio of Fe in the oxide layer; This represents the mass ratio of Fe in the oxide layer; Heavy metal layer: (36) (37) (38) (39) (40) In the formula, The density of the heavy metal layer; The coefficient of thermal expansion of the heavy metal layer; U is the coefficient of thermal expansion. The specific heat capacity of the heavy metal layer; Let U be the specific heat capacity. The latent heat of fusion of the heavy metal layer; The latent heat of fusion of U; The thermal conductivity of the heavy metal layer; Let U be the thermal conductivity. The volume ratio of Zr in the heavy metal layer; The volume ratio of U in the heavy metal layer; This represents the volume ratio of Fe in the heavy metal layer; This represents the mass ratio of Fe in the heavy metal layer. The mass ratio of U in the heavy metal layer; This represents the mass ratio of Zr in the heavy metal layer.

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