Method and system for optimizing square key structure of reactor internals of high-temperature reactor based on CFD (computational fluid dynamics)

Abstract

The invention discloses a CFD-based high-temperature reactor internal square key structure optimization method and system, and the method comprises the steps: obtaining and selecting an existing square key structure and processing information, and building a primary loop model of a high-temperature gas cooled reactor, which reflects the square key structure, through three-dimensional modeling software; performing mesh generation on the established model on the basis of ANSYS FluentMeshing (ANSYS FluentMeshing); carrying out simulation analysis on the established model based on ANSYS Fluent, and carrying out calculation by adopting an RNGk-epsilon two-equation turbulence model; post-processing a simulation analysis result, and counting a gap bypass flow value around the square key; and carrying out multi-objective optimization and screening on the scheme by adopting a weighting function, and selecting a square key structure design scheme with the optimal cost performance. According to the design method based on the three-dimensional CFD, the three-dimensional flow characteristic and effect introduced by the improved square key structure can be well reflected, and the result has good accuracy; square key effects and manufacturing cost are synchronously screened based on a weighting function mode to obtain a design scheme with the highest cost performance, and a better landing scheme is provided for design.

Description

Technical Field

[0001] The present invention relates to the technical field of design and manufacturing, and in particular to a CFD-based square key structure optimization method and system for high-temperature reactor internal components. Background Art

[0002] The internal components of a high-temperature gas-cooled reactor are divided into ceramic internal components and metal internal components. The ceramic internal components are composed of graphite bricks, carbon bricks, tenons, square keys and other structures stacked together to form the reflective layer and insulation layer structure of the core. However, since graphite bricks expand when heated and shrink when irradiated, it is necessary to reserve enough gaps between the turns when installing and stacking to prevent stress caused by structural changes that damage the brick structure. However, due to such characteristics, the helium gas used as the core coolant has more bypass flow channels, forming a bypass effect of the coolant in the reactor. The generation of the bypass effect seriously affects the increase of the core power and the safety of the core fuel balls. In the existing structural design, in order to effectively reduce the bypass of the coolant, square keys are installed between the bricks. Therefore, the structure of the square key has an important influence on the control of the bypass, and optimizing and improving the square key structure has an important role in improving the thermal hydraulic characteristics and economy of the high-temperature gas-cooled reactor.

[0003] However, the existing square key design adopts the method based on fluid network for evaluation, which simulates its contribution to the bypass flow distribution by modifying the local structure of the square key and obtaining the corresponding resistance coefficient. The actual operation of the high temperature reactor in the current demonstration project has shown that the results obtained by the previous evaluation method of the square key are quite different from the actual situation, and the existing technology lacks an effective and reasonable method to evaluate the square key scheme, so a more effective method is needed to optimize the design evaluation. Summary of the invention

[0004] In view of the above-mentioned problems, the present invention is proposed.

[0005] Therefore, the technical problem solved by the present invention is: the actual operation of the high-temperature reactor in the current demonstration project has shown that the results obtained by the previous method of evaluating the square key are significantly different from the actual situation, and the existing technology lacks an effective and reasonable method to evaluate the square key scheme, so a more effective method is needed to perform optimization design evaluation.

[0006] In order to solve the above technical problems, the present invention provides the following technical solutions: a CFD-based method for optimizing the square key structure of high temperature reactor internal components, comprising: obtaining and selecting existing square key structures and processing information, and establishing a primary loop model of a high temperature gas-cooled reactor with a reaction square key structure using three-dimensional modeling software;

[0007] Mesh the established model based on ANSYS FluentMeshing;

[0008] The established model was simulated and analyzed based on ANSYS Fluent, and the RNGk-ε two-equation turbulence model was used for calculation;

[0009] Post-process the simulation analysis results and calculate the gap bypass flow rate around the square key;

[0010] The weight function is used to perform multi-objective optimization and screening of the scheme, and finally the square key structure design scheme with the best cost-effectiveness is selected.

[0011] As a preferred scheme of the CFD-based square key structure optimization method for high-temperature reactor internal components described in the present invention, wherein: the establishment of a primary-loop model of a high-temperature gas-cooled reactor with a reaction square key structure includes using three-dimensional modeling software to establish a geometric model of the primary loop of the high-temperature gas-cooled reactor, which includes gaps between graphite bricks, gaps between graphite bricks and carbon bricks, gaps between graphite bricks and square keys, channels in graphite bricks, cylindrical areas of the core, and casing pipes at the primary loop outlet, and reflects the chamfered structure of the square keys.

[0012] As a preferred solution of the CFD-based square key structure optimization method for high-temperature reactor internals of the present invention, the meshing of the established model includes, in the meshing process, setting the number of meshes in each slit to 3 by using a slit encryption method, and the number of meshes in the slit can be controlled to be 3 or 4 layers;

[0013] Check and fix defects in the meshing process;

[0014] The Minimum Size setting snaps to the smallest structure in the model.

[0015] As a preferred solution of the CFD-based square key structure optimization method for high-temperature reactor internals of the present invention, the simulation analysis of the established model includes: when performing numerical simulation analysis on the high-temperature reactor model, using the RNGk-ε two-equation turbulence model for calculation;

[0016] The governing equation for the pure fluid region is expressed as:

[0017] Continuity equation:

[0018]

[0019] Momentum equation:

[0020]

[0021]

[0022] Energy equation:

[0023]

[0024] Where u, v, and w represent the components of velocity in the x, y, and z directions respectively; S x , S y , S z They represent the source terms of the momentum equation in the x, y, and z directions respectively; p represents the fluid pressure, T represents the fluid temperature, and μ f represents the laminar dynamic viscosity of the fluid, μ t represents the turbulent dynamic viscosity of the fluid; Pr f , Pr t They represent the laminar and turbulent Prandtl numbers of fluids respectively; represents partial derivative.

[0025] As a preferred solution of the CFD-based square key structure optimization method for high-temperature reactor internals of the present invention, the calculation using the RNGk-ε two-equation turbulence model includes that the turbulent kinetic energy k equation and the dissipation rate ε equation of the RNGk-ε model are expressed as:

[0026]

[0027] Where ρ represents the fluid density, u i represents the velocity component, k represents the turbulent kinetic energy, and ε represents the dissipation rate; S k and S ε Represents a user-defined source term, C 1 , C 2 , C 3 All represent model constants; G k , G b They represent the turbulent kinetic energy generation term caused by the mean velocity gradient and buoyancy respectively; α k , α ε represents the effective Prandtl number corresponding to the k equation and the ε equation respectively; μ e It represents the effective viscosity and is calculated as:

[0028] μ e =μ f +μ t

[0029] G k , G b The calculation method is:

[0030]

[0031] in, Reynolds stress is the time average of the turbulent velocity fluctuation component; u j represents the velocity component, u i ′ and u j ′ respectively represent the velocity components u i and uj The pulsation value of R ε The difference between the RNG k-ε model and the standard k-ε model is shown in the calculation method:

[0032]

[0033] Among them, η 0 , η and β all represent constant parameters;

[0034] Calculate the Reynolds number Re, Prandtl number Pr and Nusselt number Nu, the calculation formula is:

[0035]

[0036] Among them, ρ f represents the fluid density, D represents the geometric characteristic scale, V represents the current physical velocity of the fluid, represents mass flow rate, A represents flow cross-sectional area, μ represents fluid dynamic viscosity, c p represents the isobaric specific heat of the fluid, λ represents the thermal conductivity of the fluid, and h represents the convective heat transfer coefficient;

[0037] The core adopts a porous medium model, which is affected by the porosity The influence of porosity Defined as:

[0038]

[0039] Among them, V s Represents the volume of the solid in the porous medium, V t Represents the total volume of the porous medium.

[0040] As a preferred solution of the CFD-based square key structure optimization method for high-temperature reactor internals of the present invention, wherein: the calculation using the RNGk-ε two-equation turbulence model also includes: for the spherical stacking porous medium, the characteristic scale is the hydraulic diameter d h , the formula is:

[0041]

[0042] Among them, d p It indicates the diameter of the fuel ball or the characteristic diameter of the solid particles in the porous medium;

[0043] The relationship between the interstitial flow velocity and the average flow velocity in a porous medium is expressed as:

[0044]

[0045] The Reynolds number and Nusselt number in porous media are defined as:

[0046]

[0047] Fluent treats the solid structure of the porous medium flow area as a distributed resistance attached to the fluid, and simulates it by adding the momentum equation source term to the standard momentum equation. The source term consists of a viscous loss term and an inertial loss term, which is expressed as:

[0048]

[0049] Among them, S i represents the source term in the momentum equation, represents the pressure gradient, D ij represents the viscous drag coefficient matrix, μ f represents the dynamic viscosity of the fluid, v j represents the velocity component in the jth direction, C ij represents the inertial drag coefficient matrix, ν i represents the velocity component in the i-th direction;

[0050] Permeability α, viscous resistance coefficient D and inertial resistance coefficient C 2 The calculation formula is:

[0051]

[0052] Wherein, A and B both represent constants.

[0053] As a preferred solution of the CFD-based square key structure optimization method for high-temperature reactor internals described in the present invention, the multi-objective optimization and screening of the scheme using a weight function includes establishing a weight function for final averaging, taking the deviation between the overall bypass flow result and the design target value as a 60% weight input, and the deviation between the engineering cost and the initial square key structure engineering cost as a 40% weight input, and comparing the numerical value of the scheme effect factor output by the weight function to judge the pros and cons of the scheme, and the weight function is as follows:

[0054]

[0055] Among them, A 1 represents the scheme effect factor, Q 1 represents the overall bypass calculation value, Q 2 represents the target bypass value, M 1 Indicates the current Fang Jian plan cost, M 2 represents the cost of the initial Fang Jian plan;

[0056] Constantly change the structure of Fang Jian, re-model and analyze, and select the solution effect factor A 1 The highest value of is the optimal Fangjian solution.

[0057] A CFD-based high-temperature reactor internal component square key structure optimization system, characterized by: comprising:

[0058] 3D modeling module: obtain and select the existing square bond structure and processing information, and use 3D modeling software to establish a primary loop model of a high temperature gas-cooled reactor with a reaction square bond structure;

[0059] Meshing module: Meshing the established model based on ANSYS FluentMeshing;

[0060] Simulation analysis module: simulate and analyze the established model based on ANSYS Fluent, and use the RNGk-ε two-equation turbulence model for calculation;

[0061] Post-processing module: post-process the simulation analysis results and count the gap bypass flow value around the square key;

[0062] Optimization and decision-making module: Use weight functions to perform multi-objective optimization and screening of solutions, and ultimately select the square key structure design solution with the best cost-effectiveness.

[0063] Beneficial effects of the present invention: The design method based on three-dimensional CFD of the present invention can better reflect the three-dimensional flow characteristics and effects introduced by the improved square key structure, and the result has good accuracy; the simultaneous screening of square key effects and costs based on the weight function method can obtain the most cost-effective design solution, providing a better implementation solution for the design. BRIEF DESCRIPTION OF THE DRAWINGS

[0064] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the figures required for use in the description of the embodiments will be briefly introduced below. Obviously, the figures described below are only some embodiments of the present invention. For ordinary technicians in this field, other figures can be obtained based on these figures without paying creative work.

[0065] Figure 1 A flow chart of a method for optimizing the square key structure of a high temperature reactor internal component based on CFD provided in the first embodiment of the present invention;

[0066] Figure 2 The overall three-dimensional structure diagram of the CFD-based high-temperature reactor internal component square key structure optimization method provided in the first embodiment of the present invention;

[0067] Figure 3 A square key structure diagram of a high temperature reactor internal component square key structure optimization method based on CFD provided in the first embodiment of the present invention;

[0068] Figure 4This is a diagram of the overall network results of the CFD-based high-temperature reactor internal component square key structure optimization method provided in the first embodiment of the present invention. DETAILED DESCRIPTION

[0069] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the specification drawings. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of them. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in the art without creative work should fall within the scope of protection of the present invention.

[0070] Example 1, reference Figures 1 to 4 , which is an embodiment of the present invention, provides a CFD-based high-temperature reactor internal component square key structure optimization method, comprising:

[0071] S1: Obtain and select the existing square bond structure and processing information, and use 3D modeling software to establish a primary loop model of a high temperature gas-cooled reactor with a reaction square bond structure.

[0072] The 3D modeling software SolidWorks was used to model the primary circuit structure characteristics of the high-temperature reactor. Figure 2 As shown, it includes the gaps between graphite bricks, the gaps between graphite bricks and carbon bricks, the gaps between graphite bricks and square keys, the channels inside graphite bricks, the cylindrical area of ​​the core, the casing pipe at the outlet of the primary circuit, etc.

[0073] Furthermore, the gap structure characteristics between the square key and the graphite brick need to reflect the chamfer structure of the square key, as follows Figure 3 shown.

[0074] S2: Mesh the established model based on ANSYS FluentMeshing.

[0075] Before meshing, follow the general steps of meshing. Since SOLIDWORKS cannot create plane features, you first need to name the model in SpaceClaim (SCDM), mainly the inlet, outlet, symmetry, and the interface faces (83 pairs) of the 23 parts; at the same time, name and create the parts and bodies of each part on this basis. After that, check the defects of the geometric file. It is recommended to check and repair the established geometric model in SpaceClaim (SCDM) to ensure the subsequent work. The items that need to be checked are wrong faces, gaps, small curves and small faces, missing faces, repeated curves and repeated faces, straightening, relaxation, tangency, inaccurate edges, etc.

[0076] When importing a model, considering that the size of the narrow slit is too different from the overall size, when FLUENT Meshing imports a geometric CAD file, it will divide the continuous geometry into small faces (Facet) and then import them. Therefore, when importing a geometric model, in order to better capture tiny geometric structures such as narrow slits, it is necessary to limit the size of the maximum small face (MaxFacetLength), and the recommended value is 10. The smaller the size of the maximum small face, the finer the imported geometric model, and the longer the model import time will be.

[0077] When FLUENT Meshing is used for meshing, when the surface mesh is generated, local encryption is set according to the actual situation. The number of cells per gap in each gap is set to 3 using the proximity encryption method, which can control the number of cells in the gap to 3-4 layers. The minimum size setting captures the smallest structure in the model. The final mesh is as follows Figure 4 shown.

[0078] S3: The established model was simulated and analyzed based on ANSYS Fluent, and the RNGk-ε two-equation turbulence model was used for calculation.

[0079] When conducting numerical simulation analysis on the high temperature reactor model, the RNG k-ε two-equation turbulence model is used for calculation.

[0080] The governing equations for the pure fluid region (turbulent flow) are as follows:

[0081] Continuity equation:

[0082]

[0083] Momentum equation:

[0084]

[0085] Energy equation:

[0086]

[0087] Among them, u, v, w represent the components of velocity in the x, y, and z directions respectively; S x ,S y ,S z They represent the source terms of the momentum equation in the x, y, and z directions respectively; p represents the fluid pressure, T represents the fluid temperature, and μ f represents the laminar dynamic viscosity of the fluid, μ t represents the turbulent dynamic viscosity of the fluid; Pr f ,Pr t They represent the laminar and turbulent Prandtl numbers of fluid respectively; represents partial derivative.

[0088] It should be noted that Take the constant c μ =0.0845.

[0089] The turbulent kinetic energy k equation and dissipation rate ε equation of the RNGk-ε model are expressed as follows:

[0090]

[0091] Where ρ represents the fluid density, u i represents the velocity component, k represents the turbulent kinetic energy, and ε represents the dissipation rate; S k and S ε Represents a user-defined source term, C 1 , C 2 , C 3 All represent model constants, which are 1.42, 1.68 and 0.0845 respectively; G k , G b They represent the turbulent kinetic energy generation term caused by the mean velocity gradient and buoyancy respectively; α k , α ε represents the effective Prandtl number corresponding to the k equation and the ε equation respectively; μ e It represents the effective viscosity and is calculated as:

[0092] μ e =μ f +μ t

[0093] G k , G b They represent the turbulent kinetic energy generated by the average velocity gradient and buoyancy respectively, and are calculated as follows:

[0094]

[0095] in, represents the Reynolds stress, which is the time average of the turbulent velocity fluctuation component; u j represents the velocity component, u i ′ and u j ′ respectively represent the velocity components u i and u j Pulsation value; S k and S ε Represents a user-defined source term; R ε The difference between the RNG k-ε model and the standard k-ε model is shown in the following calculation method:

[0096]

[0097] Among them, η 0, η and β are constant parameters, β = 0.012, η 0 =4.377.

[0098] Furthermore, α k , α ε represents the effective Prandtl number corresponding to the k-equation and the ε-equation, respectively, and is calculated as:

[0099]

[0100] Take α 0 =1, Get α k =α ε ≈1.393.

[0101] Calculate the Reynolds number Re, Prandtl number Pr and Nusselt number Nu, the calculation formula is:

[0102]

[0103] Among them, ρ f represents the fluid density, D represents the geometric characteristic scale, V represents the current physical velocity of the fluid, represents mass flow rate, A represents flow cross-sectional area; μ represents fluid dynamic viscosity, which is 3.8586×10-5Pa·s; c p represents the isobaric specific heat of the fluid, λ represents the thermal conductivity of the fluid, and h represents the convective heat transfer coefficient;

[0104] The core adopts a porous medium model, which is affected by the porosity The influence of porosity Defined as:

[0105]

[0106] Among them, V s Represents the volume of the solid in the porous medium, V t represents the total volume of the porous medium, where

[0107] For spherical stacked porous media, the characteristic scale is the hydraulic diameter d h , the formula is:

[0108]

[0109] Among them, d p It represents the diameter of the fuel ball or the characteristic diameter of the solid particles in the porous medium, and is taken as d p =60mm=0.6m;

[0110] Interstitial flow velocity in porous media (physical flow velocity) u pThe relationship between the average flow velocity u is expressed as:

[0111]

[0112] Therefore, the Reynolds number and Nusselt number in porous media are defined as:

[0113]

[0114] Fluent treats the solid structure of the porous medium flow area as a distributed resistance attached to the fluid, and simulates it by adding the momentum equation source term to the standard momentum equation. The source term consists of a viscous loss term and an inertial loss term, which is expressed as:

[0115]

[0116] Among them, S i represents the source term in the momentum equation, represents the pressure gradient, D ij represents the viscous drag coefficient matrix, μ f represents the dynamic viscosity of the fluid, v j represents the velocity component in the jth direction, C ij represents the inertial drag coefficient matrix, ν i represents the velocity component in the i-th direction;

[0117] Permeability α, viscous resistance coefficient D and inertial resistance coefficient C 2 The calculation formula is:

[0118]

[0119] Among them, A and B are constants, and their values ​​are derived from experimental empirical formulas. The empirical formula used in the calculation here is the German safety guideline KTA3102.3 for pebble bed reactors, which is expressed as:

[0120]

[0121] The applicable conditions of this empirical formula are: 10 0 <Re h <10 5 ,

[0122] In addition to the heat transfer between the fluid and the solid inside the core, there is also heat generated by the fuel balls. Therefore, its volume heat source is taken as an internal heat source term and added to the porous media energy equation using a user-defined function (UDF).

[0123] Furthermore, in the calculation process, helium is a variable property, and the empirical formula of the German safety guideline KTA3102.1 common to pebble bed reactors is used to calculate the physical properties of helium, and added to the control equation and calculated through the UDF method. The empirical formula used is as follows:

[0124]

[0125] c p =5195J / (kg·K)

[0126] c V =3117J / (kg·K)

[0127] μ f =3.674×10 -7 ·T 0.7

[0128]

[0129] The applicable range is 1bar<p<100bar, 293K<1773K.

[0130] It should be noted that the units used for the physical quantities in this empirical formula are as follows: density ρ is kg / m 3 , pressure p is bar, temperature T is K, dynamic viscosity μ f is Pa·s, thermal conductivity λ f is W / (m·K).

[0131] S4: Post-process the simulation analysis results and count the gap bypass flow rate values ​​around the square key.

[0132] In the post-processing, the post-processing software CFD-POST provided by ANSYS was used. By establishing local small sections before and after each gap, the gap bypass flow rate values ​​around the square key were counted, and the overall gap bypass flow rate and the change in bypass flow rate caused by the local single square key were integrated.

[0133] S5: Use the weight function to perform multi-objective optimization and screening of the scheme, and finally select the square key structure design scheme with the best cost-effectiveness.

[0134] In order to better select the schemes, a weight function for the final average is established. The function takes the deviation between the overall bypass flow result and the design target value as a 60% weight input, and the deviation between the engineering cost and the initial square key structure engineering cost as a 40% weight input. Finally, the scheme effect factor value output by the weight function is compared to judge the pros and cons of the scheme. The larger the value, the higher the cost performance of the scheme. The weight function is as follows:

[0135]

[0136] Among them, A 1 represents the scheme effect factor, Q 1 represents the overall bypass calculation value, Q 2 represents the target bypass value, M 1 Indicates the current Fang Jian plan cost, M 2 Represents the cost of the initial Fang Jian plan.

[0137] Further, the structure of Fang Jian is constantly changed, and the modeling and analysis are re-performed to select the scheme effect factor A 1 The highest value of is the optimal Fangjian solution.

[0138] The above embodiments also include a CFD-based high temperature reactor internal component square key structure optimization system, specifically:

[0139] Three-dimensional modeling module: obtain and select the existing square bond structure and processing information, and use the three-dimensional modeling software to establish a primary loop model of a high-temperature gas-cooled reactor with a reaction square bond structure.

[0140] Meshing module: Meshing the established model based on ANSYS Fluent Meshing;

[0141] Simulation and analysis module: The established model is simulated and analyzed based on ANSYS Fluent, and the RNGk-ε two-equation turbulence model is used for calculation.

[0142] Post-processing module: post-process the simulation analysis results and count the gap bypass flow rate values ​​around the square key.

[0143] Optimization and decision-making module: Use weight functions to perform multi-objective optimization and screening of solutions, and ultimately select the square key structure design solution with the best cost-effectiveness.

[0144] The computer device may be a server. The computer device includes a processor, a memory, an input / output interface (I / O for short) and a communication interface. The processor, the memory and the input / output interface are connected via a system bus, and the communication interface is connected to the system bus via the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store data cluster data of the power monitoring system. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal via a network connection. When the computer program is executed by the processor, a CFD-based square key structure optimization method for high-temperature reactor internal components is implemented.

[0145] A person of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in the present application can include at least one of non-volatile and volatile memory. Non-volatile memory may include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory may include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but are not limited to this.

[0146] Example 2 is an embodiment of the present invention, which provides a CFD-based method for optimizing the square key structure of high-temperature reactor internal components. In order to verify the beneficial effects of the present invention, scientific demonstration is carried out through economic benefit calculation and simulation / comparative experiments.

[0147] This experiment aims to verify the feasibility and advantages of a CFD simulation-based optimization design method for the square key structure of a high-temperature gas-cooled reactor. First, by obtaining and selecting the existing square key structure and related processing information, a three-dimensional modeling software (such as SolidWorks) is used to establish a geometric model of the square key structure of the primary circuit of a high-temperature gas-cooled reactor. During the modeling process, the gap structure between the square key and the graphite brick is emphasized to ensure that the model can accurately reflect the actual working conditions.

[0148] After the geometric model was established, ANSYS FluentMeshing was used to mesh the model. Considering the complex structure of the square key and the small gap, the local mesh encryption method was used in the gap area to ensure that the tiny flow details could be captured. After meshing, the mesh quality was checked and optimized to ensure that there were no erroneous faces, overlapping faces or voids, and finally a high-quality CFD model was generated.

[0149] Next, the generated mesh model was numerically simulated using ANSYS Fluent software. The RNGk-ε two-equation turbulence model was used to simulate the flow characteristics of the high-temperature gas-cooled reactor under different operating conditions. During the simulation, special attention was paid to the gap bypass flow phenomenon around the square key, and the gap bypass flow flow values ​​under different schemes were recorded and counted.

[0150] Finally, the simulation analysis results are post-processed to extract the bypass flow data of each scheme. A multi-objective optimization method is used to evaluate and screen different design schemes based on the weight function. The weight function combines the bypass flow deviation and the square key cost to calculate the comprehensive evaluation index (cost-effectiveness) of each scheme. By comparing the comprehensive evaluation indicators of each scheme, the square key structure design scheme with the highest cost-effectiveness is selected. The whole process not only takes into account the flow characteristics, but also combines the economic requirements in actual engineering to ensure that the selected scheme has high practical value. The specific experimental data are shown in Table 1.

[0151] Table 1 Implementation data table

[0152]

[0153]

[0154] From the above test data, it can be seen that there are significant differences among the various schemes in terms of square key cost, number of grids, gap bypass flow, pressure loss, and calculation time. First, there is a certain trade-off between the square key cost and the gap bypass flow. The high-cost schemes (such as Scheme B and Scheme F) perform better in gap bypass flow control, and the gap bypass flow is lower, 0.72kg / s and 0.70kg / s, respectively. This shows that a higher cost can bring better fluid control effects. However, excessively high costs do not significantly improve the cost-effectiveness. For example, although Scheme C performs well in gap bypass flow and pressure loss control, its comprehensive evaluation index is slightly lower than that of Scheme B and Scheme F due to its high cost.

[0155] In terms of the number of grids and calculation time, the number of grids directly affects the accuracy and time consumption of simulation calculations. Although Scheme F has a large number of grids (3.1 million) and the longest calculation time (6.5 hours), it performs best in the comprehensive evaluation index of 0.83 due to its excellent fluid control effect (the lowest gap bypass flow and pressure loss).

[0156] In comparison, Scheme D has the lowest cost, but its gap bypass flow rate is higher (0.95 kg / s) and its comprehensive evaluation index is the lowest, only 0.70, which means that although this scheme is more economical, it performs poorly in terms of fluid control effect.

[0157] In summary, the present invention can effectively balance the flow characteristics and engineering cost in the design of the square key structure of the high-temperature gas-cooled reactor by combining CFD simulation and multi-objective optimization methods, and finally select the design scheme with the best cost performance. Compared with the existing technology, the present invention can not only control the bypass phenomenon more accurately, but also show obvious advantages in comprehensive cost control, and has strong engineering practicality and innovation.

[0158] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A CFD-based method for optimizing the square key structure of high temperature reactor internal components, characterized in that: include: Obtain and select existing square key structures and processing information, and use 3D modeling software to establish a primary loop model of a high temperature gas-cooled reactor with a reaction square key structure; Mesh the established model based on ANSYS FluentMeshing; The established model was simulated and analyzed based on ANSYS Fluent, and the RNGk-ε two-equation turbulence model was used for calculation; Post-process the simulation analysis results and calculate the gap bypass flow rate around the square key; The weight function is used to perform multi-objective optimization and screening of the scheme, and the square key structure design scheme with the best cost-effectiveness is selected.

2. The CFD-based high-temperature reactor internals square key structure optimization method according to claim 1, characterized in that: The method for establishing a primary loop model of a high temperature gas-cooled reactor with a reaction square key structure includes establishing a geometric model of the primary loop of the high temperature gas-cooled reactor using three-dimensional modeling software, which includes gaps between graphite bricks, gaps between graphite bricks and carbon bricks, gaps between graphite bricks and square keys, channels in graphite bricks, cylindrical areas of the core, and casing pipes at the outlet of the primary loop, and reflects the chamfered structure of the square keys.

3. The CFD-based square key structure optimization method for high temperature reactor internals according to claim 2, characterized in that: The meshing of the established model includes, in the meshing process, setting the number of meshes in each slit to 3 by using a slit encryption method, and the number of meshes in the slit can be controlled to be 3 layers or 4 layers; Check and fix defects in the meshing process; The Minimum Size setting snaps to the smallest structure in the model.

4. The CFD-based high-temperature reactor internals square key structure optimization method according to claim 3, characterized in that: The simulation analysis of the established model includes, when performing numerical simulation analysis on the high temperature reactor model, using the RNGk-ε two-equation turbulence model for calculation; The governing equation for the pure fluid region is expressed as: Continuity equation: Momentum equation: Energy equation: Where u, v, and w represent the components of velocity in the x, y, and z directions respectively; S x , S y , S z They represent the source terms of the momentum equation in the x, y, and z directions respectively; p represents the fluid pressure, T represents the fluid temperature, and μ f represents the laminar dynamic viscosity of the fluid, μt represents the turbulent dynamic viscosity of the fluid; Pr f , Pr t They represent the laminar and turbulent Prandtl numbers of fluid respectively; represents partial derivative.

5. The CFD-based square key structure optimization method for high temperature reactor internals according to claim 4, characterized in that: The calculation using the RNGk-ε two-equation turbulence model includes that the turbulent kinetic energy k equation and the dissipation rate ε equation of the RNGk-ε model are expressed as: Where ρ represents the fluid density, u i represents the velocity component, k represents the turbulent kinetic energy, and ε represents the dissipation rate; S k and S ε represents the user-defined source term, C1, C2, and C3 represent model constants; G k , G b They represent the turbulent kinetic energy generation term caused by the mean velocity gradient and buoyancy respectively; α k , α ε represents the effective Prandtl number corresponding to the k equation and the ε equation respectively; μe represents the effective viscosity, which is calculated as: m e =μ f +m t G k , G b The calculation method is: in, Reynolds stress is the time average of the turbulent velocity fluctuation component; u j represents the velocity component, u i ′ and u j ′ respectively represent the velocity components u i and u j The pulsation value of R ε The difference between the RNG k-ε model and the standard k-ε model is shown in the calculation method: Among them, η0, η and β all represent constant parameters; Calculate the Reynolds number Re, Prandtl number Pr and Nusselt number Nu, the calculation formula is: Among them, ρ f represents the fluid density, D represents the geometric characteristic scale, V represents the current physical velocity of the fluid, represents mass flow rate, A represents flow cross-sectional area, μ represents fluid dynamic viscosity, c p represents the isobaric specific heat of the fluid, λ represents the thermal conductivity of the fluid, and h represents the convective heat transfer coefficient; The core adopts a porous medium model, which is affected by the porosity The influence of porosity Defined as: Among them, V s Represents the volume of the solid in the porous medium, V t Represents the total volume of the porous medium.

6. The CFD-based square key structure optimization method for high temperature reactor internals according to claim 5, characterized in that: The calculation using the RNGk-ε two-equation turbulence model also includes: for the spherical stacked porous medium, the characteristic scale is the hydraulic diameter d h , the formula is: Among them, d p It indicates the diameter of the fuel ball or the characteristic diameter of the solid particles in the porous medium; The relationship between the interstitial flow velocity and the average flow velocity in a porous medium is expressed as: The Reynolds number and Nusselt number in porous media are defined as: Fluent treats the solid structure of the porous medium flow area as a distributed resistance attached to the fluid, and simulates it by adding the momentum equation source term to the standard momentum equation. The source term consists of a viscous loss term and an inertial loss term, which is expressed as: Among them, S i represents the source term in the momentum equation, represents the pressure gradient, D ij represents the viscous drag coefficient matrix, μ f represents the dynamic viscosity of the fluid, v j represents the velocity component in the jth direction, C ij represents the inertial drag coefficient matrix, v i represents the velocity component in the i-th direction; The calculation formulas for permeability α, viscous resistance coefficient D and inertial resistance coefficient C2 are: Wherein, A and B both represent constants.

7. The CFD-based high-temperature reactor internals square key structure optimization method according to claim 6, characterized in that: The multi-objective optimization and screening of the scheme using the weight function includes establishing a weight function for final averaging, taking the deviation between the overall bypass flow result and the design target value as a 60% weight input, and the deviation between the engineering cost and the initial square key structure engineering cost as a 40% weight input, and comparing the numerical value of the scheme effect factor output by the weight function to judge the pros and cons of the scheme. The weight function is as follows: Among them, A1 represents the scheme effect factor, Q1 represents the overall bypass calculation value, Q2 represents the target bypass value, M1 represents the current Fangjian scheme cost, and M2 represents the initial Fangjian scheme cost; Constantly change the structure of Fang Jian, re-model and analyze, and select the one with the highest value of the scheme effect factor A1 as the optimal Fang Jian scheme.

8. A CFD-based high-temperature reactor internals square key structure optimization system using the method according to any one of claims 1 to 7, characterized in that: 3D modeling module: obtain and select the existing square bond structure and processing information, and use 3D modeling software to establish a primary loop model of a high temperature gas-cooled reactor with a reaction square bond structure; Meshing module: Meshing the established model based on ANSYS Fluent Meshing; Simulation analysis module: simulate and analyze the established model based on ANSYS Fluent, and use the RNGk-ε two-equation turbulence model for calculation; Post-processing module: post-process the simulation analysis results and count the gap bypass flow value around the square key; Optimization and decision-making module: Use weight functions to perform multi-objective optimization and screening of solutions, and ultimately select the square key structure design solution with the best cost-effectiveness.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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