High-temperature gas cooled reactor micro-scale TRISO particle temperature prediction method and system

Abstract

The invention discloses a high-temperature gas cooled reactor micro-scale TRISO particle temperature prediction method and system, and relates to the technical field of high-temperature gas cooled reactor micro-scale TRISO particle temperature prediction, and the method comprises the steps: taking the temperature of the TRISO particle at the corresponding position in a fuel ball as a first-class boundary condition of the TRISO particle; and solving a heat conduction differential equation to obtain the temperature distribution of the micro-scale TRISO particles. According to the method disclosed by the invention, through the decomposition calculation process, compared with the calculation time which takes day as a unit for directly calculating the TRISO particles, the method disclosed by the invention can finish the calculation only by dozens of minutes, so that the calculation amount can be effectively reduced, and the calculation efficiency is improved.

Description

Technical Field

[0001] The present invention relates to the technical field, and in particular to a method and system for predicting the temperature of micro-scale TRISO particles in a high-temperature gas-cooled reactor. Background Art

[0002] The pebble bed reactor (PBR) is an advanced nuclear reactor design. Unlike traditional water-cooled reactors, the pebble bed reactor uses gas (usually helium) as a coolant. This design allows the pebble bed reactor to operate at very high temperatures, improving thermal efficiency. Its core structure uses spherical fuel elements, and each fuel ball is composed of tens of thousands of TRISO (spherical fuel particle encapsulation structure) particles. Therefore, the entire high-temperature gas-cooled reactor core can be defined as three scales, namely the macroscopic pebble bed scale, the mesoscopic fuel ball scale, and the microscopic TRISO particle scale. The specific schematic diagram is shown below. Figure 1 shown.

[0003] TRISO particles are specially designed nuclear fuel particles that contain nuclear fuel, cladding, heat conduction layer and outer cladding layer, which can withstand high temperature and radiation environment. They undertake the key tasks of protecting nuclear fuel, maintaining safe packaging of radioactive materials and providing heat transfer. Therefore, the temperature inside the TRISO particles directly affects the performance of nuclear fuel and the operational safety of the reactor. The maximum temperature of TRISO particles during operation can help evaluate their stability, durability and fuel performance. If overheating occurs, it may cause damage to the fuel cladding structure, thereby triggering the release of radioactive materials. Therefore, accurately evaluating the maximum temperature inside the TRISO particles is crucial to ensuring the safety of the pebble bed high temperature gas-cooled reactor.

[0004] At present, although the pebble bed high temperature gas-cooled reactor technology has received extensive attention and research, there is still a clear lack of research on the maximum temperature inside the TRISO particles. Most of the existing research focuses on the overall fuel performance, while detailed research on the internal temperature of TRISO particles is relatively scarce. The main difficulty is that since the entire pebble bed high temperature gas-cooled reactor core contains hundreds of thousands of fuel balls and each fuel ball contains tens of thousands of TRISO particles, the amount of calculation required for direct simulation is very large and cannot meet the actual rapid analysis requirements of the reactor. Therefore, it is very necessary to develop a corresponding solution method for the temperature prediction of microscopic TRISO particles. Summary of the invention

[0005] The purpose of this section is to summarize some aspects of embodiments of the present invention and briefly introduce some preferred embodiments. Some simplifications or omissions may be made in this section and the specification abstract and the invention title of this application to avoid blurring the purpose of this section, the specification abstract and the invention title, and such simplifications or omissions cannot be used to limit the scope of the present invention.

[0006] In view of the above problems or problems existing in the prior art, the present invention is proposed.

[0007] Therefore, the technical problem solved by the present invention is that the amount of calculation required for direct simulation is very large and cannot meet the actual rapid analysis requirements of the reactor.

[0008] In order to solve the above technical problems, the present invention provides the following technical solutions: a method for predicting the temperature of TRISO particles in a high-temperature gas-cooled reactor at a microscopic scale, which comprises simulating and solving the temperature field of a core of a macroscopic pebble-bed high-temperature gas-cooled reactor to obtain the temperature distribution at the macroscopic pebble-bed scale;

[0009] Set the temperature and convection heat transfer coefficient of the third type boundary condition at the macroscopic ball bed scale coordinate point;

[0010] The uniform temperature distribution of a single fuel ball in the mesoscopic fuel ball scale is obtained by solving the heat conduction differential equation;

[0011] Based on the fuel ball scale, the positions of all TRISO particles in a randomly distributed single fuel ball are given by a random distribution algorithm, and the positions of the TRISO particles are stored;

[0012] According to the position of TRISO particles in the fuel sphere, the heat source of microscopic TRISO particles is obtained from the corresponding coefficient of radial distribution and the proportion of a single TRISO particle in the fuel sphere.

[0013] The temperature of the TRISO particle at the corresponding position in the fuel ball is used as the first type boundary condition of the TRISO particle;

[0014] The temperature distribution of microscopic TRISO particles is obtained by solving the heat conduction differential equation.

[0015] As a preferred embodiment of the method for predicting the temperature of TRISO particles at a microscopic scale in a high temperature gas-cooled reactor of the present invention, the method for obtaining the temperature distribution at a macroscopic pebble bed scale includes:

[0016] Simulation calculations on a macroscopic scale through simulation equations;

[0017] Based on the fact that the object to be simulated is a pebble bed core, according to the thermal-hydraulic characteristics of the high-temperature gas-cooled reactor core, this part is simplified into a porous medium model;

[0018] In the simulation of the core of the macro-scale pebble bed high temperature gas-cooled reactor, a simplified treatment of the NS equations is used, that is, the porous medium friction dominant equations, and the specific equations are:

[0019]

[0020]

[0021]

[0022]

[0023] Where t is time, ρ is density, V is coolant flow rate, P is pressure, ε is porosity, c p is the specific heat at constant pressure, T is the temperature, k is the thermal conductivity, α is the volume convection heat transfer coefficient, q is the heat source term, g is the gravitational acceleration, and the subscripts f and s represent fluid and solid, respectively.

[0024] As a preferred scheme of the method for predicting the temperature of micro-scale TRISO particles in a high-temperature gas-cooled reactor described in the present invention, wherein: the temperature and convection heat transfer coefficient of the third-type boundary conditions for setting the macro-scale ball bed coordinate points include: the core of the macro-scale ball bed gas-cooled reactor contains hundreds of thousands of fuel balls. In order to simplify the data transmission from macro to meso, including the transmission of temperature and coordinate data, it is assumed that the fuel balls in the core are arranged in an orderly manner, and the macro-scale coolant fluid temperature and convection heat transfer coefficient at the location are used as the third-type boundary conditions of the fuel balls at the location coordinates, and the energy density at the location is used as the heat source size of the meso-scale fuel balls.

[0025] As a preferred solution of the method for predicting the temperature of TRISO particles at a microscopic scale in a high-temperature gas-cooled reactor of the present invention, the method of obtaining the uniform temperature distribution of a single fuel ball at a mesoscopic fuel ball scale by solving the heat conduction differential equation includes:

[0026] According to the obtained heat source and boundary conditions, the temperature distribution in a single fuel ball is calculated by solving the heat conduction differential equation, which is expressed as:

[0027]

[0028] Among them, q meso represents the heat source term, t represents time, ρ meso represents the density of the fuel ball being solved, c p,meso represents the constant pressure specific heat of the fuel ball to be solved, T meso represents the temperature of the fuel ball being solved, k meso represents the thermal conductivity of the fuel ball being solved.

[0029] As a preferred solution of the method for predicting the temperature of micro-scale TRISO particles in a high-temperature gas-cooled reactor of the present invention, the positions of all TRISO particles in a randomly distributed single fuel ball given by the random distribution algorithm include:

[0030] The TRISO particles are considered to be uniformly distributed in the fuel sphere;

[0031] Use Mersenne Twister as random number generation algorithm;

[0032] The inverse transform sampling method is used to generate the uniformly distributed TRISO particle positions in the fuel ball. The specific calculation formula is:

[0033] r=R·U 1 / 3

[0034] θ=arccos(1-2U)

[0035] φ=2πU

[0036] Among them, U represents a random number uniformly generated using the Mersenne Twister algorithm, and then the corresponding radial distance r, azimuth angle θ and polar angle φ are obtained using the inverse function set according to the characteristics of the fuel ball, which ensures that the generated TRISO particles are uniformly distributed in the fuel ball;

[0037] In the fuel ball, a certain minimum distance needs to be maintained between TRISO particles to prevent heat conduction and physical loss caused by mutual contact. After the generation of TRISO particles is completed, the minimum distance detection is performed, that is, the distance between any two TRISO particles needs to be calculated, which is required to ensure that it is greater than 2 times the TRISO particle radius to ensure that there is no overlap between any TRISO particles, which is expressed as:

[0038]

[0039] Among them, p1 and p2 represent any two randomly generated TRISO particles, and x, y, and z represent their Cartesian coordinates;

[0040] If a TRISO particle does not satisfy the above formula, it is necessary to regenerate the TRISO particle. The coordinates of a new TRISO particle are obtained by repeating the Mersenne rotation algorithm and the inverse transformation sampling method, and then substituted into the above formula for calculation until the generated TRISO particle satisfies the formula.

[0041] The positions of these TRISO particles are stored for subsequent calculation of the microscopic TRISO particle temperature;

[0042] Different areas are identified by using different numbers. The white area labeled 1 represents the TRISO particles, the blue area labeled 3 represents the remaining components in the shell of the fuel ball except the TRISO particles, and the red area labeled 2 represents the shell of the fuel ball.

[0043] As a preferred solution of the method for predicting the temperature of micro-scale TRISO particles in a high-temperature gas-cooled reactor of the present invention, wherein: the heat source of the micro-scale TRISO particles is obtained according to the position of the TRISO particles in the fuel ball, the corresponding coefficient of radial distribution, and the proportion of a single TRISO particle in the fuel ball, including:

[0044] Divide the fuel ball into seven equal layers according to the length in the radial direction;

[0045] Since the neutron self-shielding effect in the fuel ball will cause the energy to be absorbed by the TRISO particles, and the strength of this effect is related to the distribution position of the TRISO particles, the energy density of the TRISO particles needs to be multiplied by different coefficients at different levels for correction. The specific correction coefficient size is:

[0046]

[0047] Among them, ε1 is the correction coefficient, the innermost layer of the fuel ball is the first layer, and the outermost layer is the second layer, the third layer, and so on, until the outermost layer is the seventh layer;

[0048] The calculation of the energy density of TRISO particles needs to be recalculated based on the ratio of the fuel ball to the core of the TRISO particle, that is, multiplying a coefficient on the basis of the energy density of the fuel ball. The calculation formula of the coefficient is:

[0049]

[0050] Where n represents the number of TRISO particles in the fuel sphere, and R represents the radius of the fuel sphere and TRISO particles;

[0051] The energy density of TRISO particles is given by q micro =q 燃料球 ε1ε2 is calculated;

[0052] Taking the distribution of TRISO particles in the fuel sphere into comprehensive consideration and calculating the volume of TRISO particles and the proportion they occupy, the size of the heat source of TRISO particles in the fuel sphere is obtained.

[0053] As a preferred embodiment of the method for predicting the temperature of micro-scale TRISO particles in a high-temperature gas-cooled reactor of the present invention, the temperature distribution of micro-scale TRISO particles obtained by solving the heat conduction differential equation includes:

[0054] Since the distribution of components in TRISO particles is completely uniform, the simulation calculation is simplified to a one-dimensional model;

[0055] The two sides of the TRISO particle are the first type of boundary conditions obtained, and then the heat source is assigned to the UO2 core of the TRISO particle according to the size of the heat source at the core of the TRISO particle obtained;

[0056] By solving the heat conduction differential equation, the corrected temperature inside the microscopic TRISO particles is obtained. The specific calculation equation is:

[0057]

[0058] Among them, ρ mi cro represents the density of TRISO particles, c p,micro represents the constant pressure specific heat of TRISO particles, k micro represents the thermal conductivity of TRISO particles, q micro represents the heat source distribution within the TRISO particle, T micro is the TRISO particle temperature distribution within the unit.

[0059] Another object of the present invention is to provide a system for predicting the temperature of micro-scale TRISO particles in a high-temperature gas-cooled reactor, which can obtain the temperature distribution of micro-scale TRISO particles by solving the heat conduction differential equation, thereby solving the current problem of complex temperature calculation of micro-scale TRISO particles in a high-temperature gas-cooled reactor.

[0060] As a preferred solution of the system for predicting the temperature of micro-scale TRISO particles in a high-temperature gas-cooled reactor of the present invention, it includes: a simulation solution module, a setting module, an acquisition module, a position module, a heat source module, a condition module, and a distribution module;

[0061] The simulation and solution module is used to simulate and solve the temperature field of the core of the macroscopic pebble bed high temperature gas-cooled reactor to obtain the temperature distribution at the macroscopic pebble bed scale;

[0062] The setting module is used to set the temperature and convection heat transfer coefficient of the third type boundary condition of the macroscopic ball bed scale coordinate point;

[0063] The acquisition module is used to obtain the uniform temperature distribution of a single fuel ball in the mesoscopic fuel ball scale by solving the heat conduction differential equation;

[0064] The position module is used to provide the positions of all TRISO particles in a randomly distributed single fuel ball based on the fuel ball scale through a random distribution algorithm, and store the positions of the TRISO particles;

[0065] The heat source module is used to obtain the heat source of microscopic TRISO particles according to the position of the TRISO particles in the fuel sphere, the corresponding coefficient of radial distribution, and the proportion of a single TRISO particle in the fuel sphere;

[0066] The condition module is used to use the temperature of the TRISO particle at the corresponding position in the fuel ball as the first type of boundary condition of the TRISO particle;

[0067] The distribution module is used to obtain the temperature distribution of microscopic TRISO particles by solving the heat conduction differential equation.

[0068] A computer device comprises a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement a method for predicting the temperature of micro-scale TRISO particles in a high-temperature gas-cooled reactor.

[0069] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps of a method for predicting the temperature of micro-scale TRISO particles in a high-temperature gas-cooled reactor.

[0070] Beneficial effects of the present invention: In view of the huge amount of calculation required to directly calculate microscopic TRISO particles, the process is decomposed into three scales in the present invention, namely, from the macroscopic pebble bed core scale to the mesoscopic fuel ball scale, and then to the microscopic TRISO particle scale, and gradually advances to obtain a more accurate microscopic TRISO particle internal temperature. The gas-cooled reactor microscopic TRISO particle temperature prediction method of the present invention expands the channels for calculating the temperature inside microscopic TRISO particles. By decomposing the calculation process, compared to the calculation time required in days for directly calculating TRISO particles, this method only takes a dozen minutes to complete the calculation, which can not only effectively reduce the amount of calculation and improve the calculation efficiency, but also more accurately predict the internal temperature distribution of TRISO particles. This method can ensure the safety of the gas-cooled reactor operation process to a greater extent while meeting the engineering operation time. BRIEF DESCRIPTION OF THE DRAWINGS

[0071] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative labor. Among them:

[0072] Figure 1 Schematic diagram of representative objects at macro-meso-micro scales in the core of a high-temperature gas-cooled reactor.

[0073] Figure 2 This is a schematic diagram of the components in the fuel ball.

[0074] Figure 3 Schematic diagram of the internal components of TRISO particles at the microscopic scale.

[0075] Figure 4 This is the overall flow chart of the micro-scale TRISO particle temperature prediction method for high-temperature gas-cooled reactors. DETAILED DESCRIPTION

[0076] In order to make the above-mentioned objects, 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 accompanying drawings.

[0077] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0078] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive with other embodiments.

[0079] Example 1

[0080] Reference Figures 1 to 4 , which is an embodiment of the present invention, provides a method for predicting the temperature of micro-scale TRISO particles in a high-temperature gas-cooled reactor, comprising:

[0081] S1. The temperature field of the core of a macroscopic pebble bed high temperature gas-cooled reactor is simulated and solved, and the temperature distribution at the macroscopic pebble bed scale is preliminarily calculated.

[0082] Specifically, according to the thermal-hydraulic characteristics of the gas-cooled reactor core, in the simulation of the macro-scale pebble bed high-temperature gas-cooled reactor core, the simplified treatment of the NS equations is used in this method, that is, the porous medium friction dominant equations, specifically:

[0083]

[0084]

[0085]

[0086]

[0087] Where: t is time, ρ is density, V is coolant flow rate, P is pressure, ε is porosity, c p is the specific heat at constant pressure, T is the temperature, k is the thermal conductivity, α is the volume convection heat transfer coefficient, q is the heat source term, g is the gravitational acceleration, and the subscripts f and s represent fluid and solid, respectively.

[0088] S2. Assuming that in the core of the pebble bed gas-cooled reactor, the fuel spheres are in an orderly stacked form, the temperature and convective heat transfer coefficient of the macroscopic pebble bed scale at all positions are taken as the temperature and convective heat transfer coefficient of the third type boundary condition of the coordinate point.

[0089] Specifically, in the core of a macroscopic pebble bed high temperature gas-cooled reactor, there are hundreds of thousands of fuel spheres. In order to simplify the data transfer process from macroscopic to mesoscopic, including the transfer of temperature and coordinate data, it is assumed that the fuel spheres in the core are arranged in order. Under this assumption, the macroscopic coolant fluid temperature and convection heat transfer coefficient at each position in the core are regarded as the third-class boundary conditions of the fuel sphere at that position. At the same time, the energy density at that position is regarded as the heat source size of the mesoscopic fuel sphere.

[0090] In this setting, data transfer can be simplified because there is no need to transfer the temperature and coordinate information of each fuel ball. Instead, only the macroscopic fluid temperature, convection heat transfer coefficient and the mesoscopic fuel ball energy density need to be transferred.

[0091] S3. The uniform temperature distribution of a single fuel ball at the mesoscopic fuel ball scale is obtained by solving the heat conduction differential equation.

[0092] Specifically, according to the size of the heat source obtained in step S2 and the processing method of the third type of boundary conditions, the temperature distribution in a single fuel ball is calculated by solving the heat conduction differential equation. The specific calculation formula is:

[0093]

[0094] Among them, q meso represents the heat source term, t represents time, ρ meso represents the density of the fuel ball being solved, c p,meso represents the constant pressure specific heat of the fuel ball to be solved, T meso represents the temperature of the fuel ball being solved, k meso represents the thermal conductivity of the fuel ball being solved.

[0095] S4. Based on the scale of the fuel ball, a random distribution algorithm is used to give the positions of all TRISO particles in a randomly distributed single fuel ball while ensuring that the TRISO particles are reasonably distributed, and the positions are stored.

[0096] Specifically, since it is necessary to generate the positions of TRISO particles in the fuel sphere, first, this method regards the TRISO particles as being uniformly distributed in the fuel sphere. In this method, the Mersenne rotation algorithm is used as a random number generation algorithm. This method has the characteristics of high quality and high efficiency, so that a high-quality random number source can be obtained. Then, the inverse transform sampling method is used to generate the positions of TRISO particles uniformly distributed in the fuel sphere. This method can convert the uniformly distributed random numbers into the positions of TRISO particles suitable for uniform distribution in the fuel sphere. The specific calculation formula is:

[0097] r=R·U 1 / 3

[0098] θ=arccos(1-2U)

[0099] φ=2πU

[0100] Among them, U represents a random number uniformly generated using the Mersenne twister algorithm, and then the corresponding radial distance r, azimuth angle θ and polar angle φ are obtained using the inverse function set according to the characteristics of the fuel ball, which ensures that the generated TRISO particles are uniformly distributed in the fuel ball.

[0101] In the fuel ball, it is necessary to keep a certain minimum distance between TRISO particles to prevent heat conduction and physical loss caused by mutual contact. Therefore, after the generation of TRISO particles is completed, it is necessary to pass the minimum distance detection, that is, it is necessary to calculate the distance between any two TRISO particles, and ensure that it is greater than 2 times the radius of the TRISO particles to ensure that there is no overlap between any TRISO particles, that is

[0102]

[0103] Among them, p1 and p2 represent any two randomly generated TRISO particles, and x, y, and z represent their Cartesian coordinates. If it is found that a TRISO particle does not satisfy the above formula, it is necessary to regenerate the TRISO particle. The coordinates of the new TRISO particle are obtained by repeating the above-mentioned Mersenne rotation algorithm and inverse transformation sampling method, and then substituted into the above formula for calculation until the generated TRISO particle satisfies the formula. In this way, the position of the TRISO particles in the fuel ball is reasonably generated by the above-mentioned random generation method, thereby realizing a simple and efficient random position generation algorithm. After the generation of the TRISO particles is completed, it is also necessary to store them. This information is stored by using different labels to represent different areas. The label 1 represents the TRISO particle, the label 2 represents the fuel ball shell, and the label 3 represents the remaining components in the fuel ball shell except the TRISO particle. These data are saved and subsequently extracted through the structure.

[0104] S5. According to the position of the TRISO particles in the fuel sphere, the heat source of the microscopic TRISO particles is obtained from the corresponding coefficient of radial distribution.

[0105] Specifically, according to existing studies, the size of the heat source contained in the TRISO particles in the fuel sphere is related to the radial length of the fuel sphere. Therefore, in this method, the heat source of the TRISO particles at the microscopic scale is derived based on the TRISO particle position obtained in step S4 and the size of the heat source of the fuel sphere, combined with the volume ratio of the core containing the heat source in the TRISO particles to the fuel sphere.

[0106] In this derivation process, first, the fuel ball is divided into seven layers according to the length in the radial direction. Since the neutron self-shielding effect in the fuel ball will cause the energy to be absorbed by the TRISO particles, and the strength of this effect is related to the distribution position of the TRISO particles, the energy density of the TRISO particles at different levels needs to be multiplied by different coefficients for correction. The specific correction coefficient size is:

[0107]

[0108] Among them, ε1 is the correction coefficient, the innermost layer of the fuel ball is the first layer, and the outermost layer is the second layer until the seventh layer.

[0109] In addition, since the heat source used in the fuel ball actually only exists in the core of the TRISO particle, and there is no heat source in other locations, but the average heat source is used when calculating the energy density of the fuel ball, the calculation of the energy density of the TRISO particle needs to be recalculated based on the proportion of the fuel ball and the core of the TRISO particle, that is, multiplying a coefficient on the basis of the energy density of the fuel ball. The calculation formula of the coefficient is:

[0110]

[0111] Where n represents the number of TRISO particles in the fuel sphere, R represents the radius of the fuel sphere and TRISO particles, then the energy density of the TRISO particles can be calculated by q micro =q 燃料球 ε1ε2 is calculated. In this way, the distribution of TRISO particles in the fuel ball is comprehensively considered, and the heat source size of TRISO particles in the fuel ball can be obtained by calculating the volume of TRISO particles and the proportion they occupy.

[0112] S6. The temperature of the TRISO particle at the corresponding position in the fuel ball is used as the first type of boundary condition for the TRISO particle.

[0113] Since the inside of the fuel ball is solid and there is no fluid flow, the energy transfer is only heat conduction between solids, and there is no heat convection and heat radiation. Therefore, temperature is the first choice for information transmission from the fuel ball to the TRISO particle. According to the position of the TRISO particle in the fuel ball stored in step S4, the temperature of the fuel ball at the corresponding position is found, and this temperature is used as the first type of boundary condition for the calculated TRISO particle, that is, the constant temperature boundary, for the calculation of the subsequent steps.

[0114] S7. The temperature distribution of TRISO particles at the microscopic scale is obtained by solving the heat conduction differential equation.

[0115] Specifically, since the distribution of components in the TRISO particles is completely uniform, the simulation calculation can be simplified to a one-dimensional model. Set the two sides of the TRISO particles as the first-class boundary conditions obtained in step S6, and then according to the size of the heat source at the core of the TRISO particles obtained in step S5, by solving the heat conduction differential equation, the corrected temperature in the microscopic TRISO particles can be obtained. The specific calculation equation is:

[0116]

[0117] Among them, ρ micro Indicates the density of TRISO particles, c p,micro represents the constant pressure specific heat of TRISO particles, k micro represents the thermal conductivity of TRISO particles, q micro represents the heat source distribution within the TRISO particle, T micro is the temperature distribution of TRISO particles in the unit. In this way, the temperature distribution of TRISO particles at the microscopic scale is solved, and the maximum predicted temperature of TRISO particles is also obtained accordingly, which can be applied to engineering practice and play a theoretical guiding role in the selection of actual engineering materials and safety assessment.

[0118] In summary, in view of the huge amount of calculation required to directly calculate microscopic TRISO particles, the process is decomposed into three scales in the present invention, namely, from the macroscopic pebble bed core scale to the mesoscopic fuel ball scale, and then to the microscopic TRISO particle scale, and gradually advances to obtain a more accurate microscopic TRISO particle internal temperature. The gas-cooled reactor microscale TRISO particle temperature prediction method of the present invention expands the channel for calculating the temperature inside microscopic TRISO particles. By decomposing the calculation process, compared to the calculation time required in days for directly calculating TRISO particles, this method only takes more than ten minutes to complete the calculation, which can not only effectively reduce the amount of calculation and improve the calculation efficiency, but also can more accurately predict the internal temperature distribution of TRISO particles. This method can ensure the safety of the gas-cooled reactor operation process to a greater extent while meeting the engineering operation time.

[0119] The above is a schematic scheme of a method for predicting the temperature of micro-scale TRISO particles in a high-temperature gas-cooled reactor in this embodiment. It should be noted that the technical scheme of the system for predicting the temperature of micro-scale TRISO particles in a high-temperature gas-cooled reactor and the technical scheme of the method for predicting the temperature of micro-scale TRISO particles in a high-temperature gas-cooled reactor described above belong to the same concept. For details not described in detail in the technical scheme of the system for predicting the temperature of micro-scale TRISO particles in a high-temperature gas-cooled reactor in this embodiment, please refer to the description of the technical scheme of the method for predicting the temperature of micro-scale TRISO particles in a high-temperature gas-cooled reactor described above.

[0120] This embodiment also proposes a high temperature gas-cooled reactor microscale TRISO particle temperature prediction system, including:

[0121] It includes simulation solution module, setting module, acquisition module, position module, heat source module, condition module and distribution module;

[0122] The simulation and solution module is used to simulate and solve the temperature field of the core of the macroscopic pebble bed high temperature gas-cooled reactor to obtain the temperature distribution at the macroscopic pebble bed scale;

[0123] The setting module is used to set the temperature and convection heat transfer coefficient of the third type boundary condition of the macroscopic ball bed scale coordinate point;

[0124] The acquisition module is used to obtain the uniform temperature distribution of a single fuel ball in the mesoscopic fuel ball scale by solving the heat conduction differential equation;

[0125] The position module is used to provide the positions of all TRISO particles in a randomly distributed single fuel ball based on the fuel ball scale through a random distribution algorithm, and store the positions of the TRISO particles;

[0126] The heat source module is used to obtain the heat source of microscopic TRISO particles according to the position of the TRISO particles in the fuel sphere, the corresponding coefficient of radial distribution, and the proportion of a single TRISO particle in the fuel sphere;

[0127] The condition module is used to use the temperature of the TRISO particle at the corresponding position in the fuel ball as the first type of boundary condition of the TRISO particle;

[0128] The distribution module is used to obtain the temperature distribution of microscopic TRISO particles by solving the heat conduction differential equation.

[0129] This embodiment also provides a computing device, which is applicable to the prediction of the temperature of TRISO particles at a microscopic scale in a high temperature gas-cooled reactor, and includes:

[0130] A memory and a processor; the memory is used to store computer executable instructions, and the processor is used to execute computer executable instructions to implement the method for predicting the temperature of micro-scale TRISO particles in a high-temperature gas-cooled reactor as proposed in the above embodiment.

[0131] This embodiment also provides a storage medium on which a computer program is stored. When the program is executed by a processor, the method for predicting the temperature of micro-scale TRISO particles in a high-temperature gas-cooled reactor as proposed in the above embodiment is implemented.

[0132] The storage medium proposed in this embodiment and the method for realizing the micro-scale TRISO particle temperature prediction of a high-temperature gas-cooled reactor proposed in the above embodiment belong to the same inventive concept. The technical details not described in detail in this embodiment can be referred to the above embodiment, and this embodiment has the same beneficial effects as the above embodiment.

[0133] Through the above description of the implementation methods, the technicians in the relevant field can clearly understand that the present invention can be implemented by means of software and necessary general hardware, and of course can also be implemented by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as a computer floppy disk, read-only memory (ReadOnly, Memory, ROM), random access memory (RandomAccess Memory, RAM), flash memory (FLASH), hard disk or optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, server, or network device, etc.) to perform the methods of various embodiments of the present invention.

[0134] 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 method for predicting the temperature of microscale TRISO particles in a high temperature gas-cooled reactor, characterized in that: include, The temperature field of the core of a macroscopic pebble bed high temperature gas-cooled reactor is simulated and solved to obtain the temperature distribution at the macroscopic pebble bed scale. Set the temperature and convection heat transfer coefficient of the third type boundary condition at the macroscopic ball bed scale coordinate point; The uniform temperature distribution of a single fuel ball in the mesoscopic fuel ball scale is obtained by solving the heat conduction differential equation; Based on the fuel ball scale, the positions of all TRISO particles in a randomly distributed single fuel ball are given by a random distribution algorithm, and the positions of the TRISO particles are stored; According to the position of TRISO particles in the fuel sphere, the heat source of microscopic TRISO particles is obtained from the corresponding coefficient of radial distribution and the proportion of a single TRISO particle in the fuel sphere. The temperature of the TRISO particle at the corresponding position in the fuel ball is used as the first type boundary condition of the TRISO particle; The temperature distribution of microscopic TRISO particles is obtained by solving the heat conduction differential equation.

2. The method for predicting the temperature of micro-scale TRISO particles in a high temperature gas-cooled reactor according to claim 1, characterized in that: The method of obtaining the temperature distribution at the macroscopic pebble bed scale includes: Simulation calculations on a macroscopic scale through simulation equations; Based on the fact that the object to be simulated is a pebble bed core, according to the thermal-hydraulic characteristics of the high-temperature gas-cooled reactor core, this part is simplified into a porous medium model; In the simulation of the core of the macro-scale pebble bed high temperature gas-cooled reactor, a simplified treatment of the NS equations is used, that is, the porous medium friction dominant equations, and the specific equations are: Where t is time, ρ is density, V is coolant flow rate, P is pressure, ε is porosity, c p is the specific heat at constant pressure, T is the temperature, k is the thermal conductivity, α is the volume convection heat transfer coefficient, q is the heat source term, g is the gravitational acceleration, and the subscripts f and s represent fluid and solid, respectively.

3. The method for predicting the temperature of micro-scale TRISO particles in a high temperature gas-cooled reactor according to claim 2, characterized in that: The temperature and convection heat transfer coefficient of the third-type boundary conditions for setting the macroscopic pebble bed scale coordinate points include: the core of the macroscopic pebble bed gas-cooled reactor contains hundreds of thousands of fuel balls. In order to simplify the data transmission from macroscopic to mesoscopic, including the transmission of temperature and coordinate data, it is assumed that the fuel balls in the core are arranged in an orderly manner. The macroscopic scale coolant fluid temperature and convection heat transfer coefficient at the location are used as the third-type boundary conditions of the fuel balls at the location coordinates, and the energy density at the location is used as the heat source size of the mesoscopic scale fuel balls.

4. The method for predicting the temperature of micro-scale TRISO particles in a high temperature gas-cooled reactor according to claim 3, characterized in that: The method of obtaining the uniform temperature distribution of a single fuel ball in the mesoscopic fuel ball scale by solving the heat conduction differential equation includes: According to the obtained heat source and boundary conditions, the temperature distribution in a single fuel ball is calculated by solving the heat conduction differential equation, which is expressed as: Among them, q meso represents the heat source term, t represents time, ρ meso represents the density of the fuel ball being solved, c p,meso represents the constant pressure specific heat of the fuel ball to be solved, T meso represents the temperature of the fuel ball being solved, k meso represents the thermal conductivity of the fuel ball being solved.

5. The method for predicting the temperature of micro-scale TRISO particles in a high temperature gas-cooled reactor according to claim 4, characterized in that: The random distribution algorithm is used to give the positions of all TRISO particles in a single fuel ball in a random distribution, including: The TRISO particles are considered to be uniformly distributed in the fuel sphere; Use Mersenne Twister as random number generation algorithm; The inverse transform sampling method is used to generate the uniformly distributed TRISO particle positions in the fuel ball. The specific calculation formula is: r=R·U 1 / 3 θ=arccos(1-2U) φ=2πU Among them, U represents a random number uniformly generated using the Mersenne Twister algorithm, and then the corresponding radial distance r, azimuth angle θ and polar angle φ are obtained using the inverse function set according to the characteristics of the fuel ball, which ensures that the generated TRISO particles are uniformly distributed in the fuel ball; In the fuel ball, a certain minimum distance needs to be maintained between TRISO particles to prevent heat conduction and physical loss caused by mutual contact. After the generation of TRISO particles is completed, the minimum distance detection is performed, that is, the distance between any two TRISO particles needs to be calculated, which is required to ensure that it is greater than 2 times the TRISO particle radius to ensure that there is no overlap between any TRISO particles, which is expressed as: Among them, p1 and p2 represent any two randomly generated TRISO particles, and x, y, and z represent their Cartesian coordinates; If a TRISO particle does not satisfy the above formula, it is necessary to regenerate the TRISO particle. The coordinates of a new TRISO particle are obtained by repeating the Mersenne rotation algorithm and the inverse transformation sampling method, and then substituted into the above formula for calculation until the generated TRISO particle satisfies the formula. The positions of these TRISO particles are stored for subsequent calculation of the microscopic TRISO particle temperature; Different areas are identified by using different numbers. The white area labeled 1 represents the TRISO particles, the blue area labeled 3 represents the remaining components in the shell of the fuel ball except the TRISO particles, and the red area labeled 2 represents the shell of the fuel ball.

6. The method for predicting the temperature of micro-scale TRISO particles in a high temperature gas-cooled reactor according to claim 5, characterized in that: According to the position of the TRISO particles in the fuel sphere, the heat source of the microscopic TRISO particles is obtained by the corresponding coefficient of radial distribution and the proportion of a single TRISO particle in the fuel sphere, including: Divide the fuel ball into seven equal layers according to the length in the radial direction; Since the neutron self-shielding effect in the fuel ball will cause the energy to be absorbed by the TRISO particles, and the strength of this effect is related to the distribution position of the TRISO particles, the energy density of the TRISO particles needs to be multiplied by different coefficients at different levels for correction. The specific correction coefficient size is: Among them, ε1 is the correction coefficient, the innermost layer of the fuel ball is the first layer, and the outermost layer is the second layer, the third layer, and so on, until the outermost layer is the seventh layer; The calculation of the energy density of TRISO particles needs to be recalculated based on the ratio of the fuel ball to the core of the TRISO particle, that is, multiplying a coefficient on the basis of the energy density of the fuel ball. The calculation formula of the coefficient is: Where n represents the number of TRISO particles in the fuel sphere, and R represents the radius of the fuel sphere and TRISO particles; The energy density of TRISO particles is given by q micro =q 燃料球 ε1ε2 is calculated; Taking the distribution of TRISO particles in the fuel sphere into comprehensive consideration and calculating the volume of TRISO particles and the proportion they occupy, the size of the heat source of TRISO particles in the fuel sphere is obtained.

7. The method for predicting the temperature of micro-scale TRISO particles in a high temperature gas-cooled reactor according to claim 6, characterized in that: The method of obtaining the temperature distribution of microscopic TRISO particles by solving the heat conduction differential equation includes: Since the distribution of components in TRISO particles is completely uniform, the simulation calculation is simplified to a one-dimensional model; The two sides of the TRISO particle are the first type of boundary conditions obtained, and then the heat source is assigned to the UO2 core of the TRISO particle according to the size of the heat source at the core of the TRISO particle obtained; By solving the heat conduction differential equation, the corrected temperature inside the microscopic TRISO particles is obtained. The specific calculation equation is: Among them, ρ micro Indicates the density of TRISO particles, c p,micro represents the constant pressure specific heat of TRISO particles, k micro represents the thermal conductivity of TRISO particles, q micro represents the heat source distribution within the TRISO particle, T micro is the temperature distribution of TRISO particles in the unit.

8. A system using the high temperature gas-cooled reactor microscale TRISO particle temperature prediction method according to any one of claims 1 to 7, characterized in that: It includes simulation solution module, setting module, acquisition module, position module, heat source module, condition module and distribution module; The simulation and solution module is used to simulate and solve the temperature field of the core of the macroscopic pebble bed high temperature gas-cooled reactor to obtain the temperature distribution at the macroscopic pebble bed scale; The setting module is used to set the temperature and convection heat transfer coefficient of the third type boundary condition of the macroscopic ball bed scale coordinate point; The acquisition module is used to obtain the uniform temperature distribution of a single fuel ball in the mesoscopic fuel ball scale by solving the heat conduction differential equation; The position module is used to provide the positions of all TRISO particles in a randomly distributed single fuel ball based on the fuel ball scale through a random distribution algorithm, and store the positions of the TRISO particles; The heat source module is used to obtain the heat source of microscopic TRISO particles according to the position of the TRISO particles in the fuel sphere, the corresponding coefficient of radial distribution, and the proportion of a single TRISO particle in the fuel sphere; The condition module is used to use the temperature of the TRISO particle at the corresponding position in the fuel ball as the first type of boundary condition of the TRISO particle; The distribution module is used to obtain the temperature distribution of microscopic TRISO particles by solving the heat conduction differential equation.

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 for predicting the temperature of micro-scale TRISO particles in a high temperature gas-cooled reactor 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 for predicting the temperature of micro-scale TRISO particles in a high temperature gas-cooled reactor according to any one of claims 1 to 7 are implemented.

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