Wear dust generation and flow analysis method, apparatus, device, and storage medium

Abstract

This application discloses a method, apparatus, equipment, and storage medium for analyzing wear dust generation and flow, relating to the field of nuclear energy technology. The method includes: establishing a discrete element model of fuel elements and completing parameter calibration, defining it as a unit cell; constructing a local unit cell model of a cubic reactor core, with the unit cells arranged according to a classical grain configuration, and simultaneously establishing a CFD model; setting corresponding boundary conditions and thermal parameters, and completing the initialization of DEM and CFD simulations respectively; simulating the continuous cyclic motion of fuel elements, employing a bidirectional coupling method with multiple DEM substeps embedded within a large CFD time step, iteratively completing the calculation of wear dust generation and the solution of flow heat transfer, achieving dynamic coupling between dust generation and dust transport. This method can accurately reproduce the dynamic process of wear dust generation of fuel elements within the reactor core and dust migration with coolant, improving the accuracy of dust source term assessment in pebble bed reactors.

Description

Technical Field

[0001] This application relates to the field of nuclear energy technology, and in particular to a method, apparatus, equipment and storage medium for analyzing the generation and flow of abrasive dust. Background Technology

[0002] The pebble bed type high-temperature gas-cooled reactor uses spherical fuel elements, which are randomly stacked in the active zone of the reactor core to form a pebble bed. During long-term operation of the reactor, the fuel elements undergo surface wear due to mechanical actions such as gravity, collision, and compression, generating micron to sub-millimeter-sized graphite dust. This type of dust is carried by the coolant and migrates and deposits in the primary circuit, which may affect the heat exchange of the equipment and cause the release of radioactive source terms. This is one of the key issues in reactor safety analysis.

[0003] Current research on graphite dust in pebble bed reactors mainly includes two categories: experiments and numerical simulations. Experiments struggle to recreate the coupled environment of collisions between spheres and between spheres and the reactor wall, as well as coolant scouring within the core. Existing numerical simulations often decouple dust generation from the transport process. Discrete element methods only estimate dust generation through collision parameters without coupling with coolant flow. Dust source terms in multi-behavior coupling analysis remain preset values, failing to achieve dynamic feedback. Furthermore, existing simulations often employ equivalent porous media or random packing models, making it difficult to accurately reflect the impact of pebble bed grain configuration on wear and flow field. They also frequently use the fixed-bed assumption, failing to simulate the long-term effects of continuous fuel sphere circulation on wear and dust accumulation, thus hindering the acquisition of accurate results regarding graphite dust generation and flow distribution. Summary of the Invention

[0004] This application provides a method, apparatus, equipment, and storage medium for analyzing wear dust generation and flow. It can solve the problems of insufficient accuracy in simulating dust generation and flow distribution caused by the decoupling of dust generation and transport processes, distortion of the geometry of the pellet bed, and the inability to simulate the circulating motion of fuel pellets in related technologies.

[0005] According to a first aspect of this application, a method for analyzing the generation and flow of wear dust is provided, comprising:

[0006] S1: Establish a discrete element model of the fuel element, calibrate the parameters of the fuel element according to the macroscopic physical property parameters of the actual fuel element, determine the contact model parameter combination that conforms to the macroscopic physical property parameters of the fuel element as the parameter setting of the discrete element model of the fuel element, and set the discrete element model of the fuel element as a unit cell. S2: Establish a local unit cell model of the reactor core. Its geometric dimensions are determined by the number of discrete element models of the fuel elements and the volume fraction of the fuel elements in the active region of the reactor core. The shape is a cube. The multiple discrete element models of the fuel elements in the local unit cell model of the reactor core are arranged according to the classical grain configuration. A computational fluid dynamics (CFD) model is established synchronously according to the geometric parameters and distribution positions. S3: Set the cubic surface boundary conditions for the local unit cell model of the core, set the front and back, left and right boundaries as periodic boundary conditions, the upper boundary as free and unconstrained, and the lower boundary as wall. Set the gravity, initial temperature, heat source of the unit cell, and boundary temperature of the local unit cell model of the core. S4: The local unit cell model of the reactor core is filled with unit cells that meet the quantity requirements, and the contact model parameters between unit cells are set. The initialization of the local unit cell model of the reactor core is completed, that is, the simulation settings and calculation initialization of the Digital Elevation Model (DEM) are completed. S5: Set up CFD simulation of cooling flow in the local unit cell model of the core: Based on the actual operating parameters of the specified location in the active region of the core, set the temperature, flow rate and pressure boundary conditions of the coolant on the upper and lower surfaces of the local unit cell model of the core, and keep the temperature, flow rate and pressure of the other surfaces the same as the lower surface to complete the initialization of the flow simulation of the local unit cell model of the core. S6: Set a unit cell at the upper boundary of the local unit cell model of the core to enter the local unit cell model of the core with acceleration. The acceleration is calculated from the total force of gravity superimposed on the buoyancy of the coolant. When any unit cell moves away from the boundary of the local unit cell model of the core, the unit cell that satisfies the given state re-enters the model from the corresponding boundary to simulate the continuous cyclic motion of the fuel elements in the reactor. S7: A CFD time step is used as a large time step. Each large time step contains multiple DEM time steps. In the DEM sub-loop of a large time step, the total force, movement speed, position of each unit cell, and discrete dust particles generated by collision and wear are simulated. Discrete dust particles include particle size and position. The size of the generated discrete particles and the particle position at the end of the sub-loop are determined according to the wear model, and the first result file is output. S8: Within the current CFD time step, based on the cell position and stress conditions in the first result file, as well as the size and position of discrete particles, set the geometric configuration and particle source terms for the CFD simulation to complete the heat transfer and flow CFD simulation of the model under the current state. S9: After the CFD simulation completes the current time step, it outputs the fluid drag force and heat flux at each integration point on the surface of each unit cell, as well as the fluid velocity, pressure, temperature, lift and drag coefficient parameters at the location of each dust particle to the second result file. S10: For the DEM sub-cycle within the next large CFD time step, update the boundary conditions in the local unit cell model of the core according to the fluid drag force and the fluid parameters of the particles in the second result file. S11: Repeat S7 to S10 until the preset total simulation time is reached, then the calculation ends.

[0007] According to a second aspect of this application, an apparatus for analyzing the generation and flow of abrasive dust is provided, comprising: The first module is configured to establish a discrete element model of the fuel element. Based on the macroscopic physical property parameters of the actual fuel element, the parameters of the fuel element are calibrated. The contact model parameter combination that conforms to the macroscopic physical property parameters of the fuel element is determined as the parameter setting of the discrete element model of the fuel element. The discrete element model of the fuel element is set as a unit cell. The second module is configured to build a local unit cell model of the reactor core. Its geometric dimensions are determined by the number of discrete element models of the fuel elements and the volume fraction of the fuel elements in the active region of the reactor core. The shape is a cube. The multiple discrete element models of the fuel elements in the local unit cell model of the reactor core are arranged according to the classical grain configuration. The CFD model is built synchronously according to the geometric parameters and distribution positions. The first setting module is configured to set the cubic surface boundary conditions of the local unit cell model of the core, set the front and back, left and right boundaries as periodic boundary conditions, the upper boundary as free and unconstrained, the lower boundary as wall, and set the gravity, initial temperature, heat source of the unit cell, and the boundary temperature of the local unit cell model of the core. The initialization module is configured to fill the local unit cell model of the reactor core with the required number of unit cells and complete the parameter settings for the contact model between unit cells, thus completing the initialization of the local unit cell model of the reactor core, which is to say, completing the DEM simulation settings and calculation initialization. The setting module is configured to set the CFD simulation of cooling flow within the local unit cell model of the core: based on the actual operating parameters at a specified location in the active region of the core, the temperature, flow rate and pressure boundary conditions of the coolant are set on the upper and lower surfaces of the local unit cell model of the core, while the other surfaces maintain the same temperature, flow rate and pressure as the lower surface, thus completing the initialization of the flow simulation of the local unit cell model of the core. The second setting module is configured to set a unit cell at the upper boundary of the local unit cell model of the core to enter the local unit cell model of the core with acceleration. The acceleration is calculated from the total force of gravity superimposed on the buoyancy of the coolant. When any unit cell moves away from the boundary of the local unit cell model of the core, the unit cell that satisfies the given state re-enters the model from the corresponding boundary to simulate the continuous cyclic motion of the fuel elements in the reactor. The first simulation module is configured to use a CFD time step as a large time step, with multiple DEM time steps embedded within each large time step. In a DEM sub-loop of a large time step, the module simulates the total force, movement speed, position, and discrete dust particles generated by collision and wear for each cell. The discrete dust particles include particle size and position. The module determines the size of the generated discrete particles and the particle position at the end of the sub-loop based on the wear model, and outputs the first result file. The second simulation module is configured to, within the current large CFD time step, set the geometric configuration and particle source terms of the CFD simulation based on the cell position and force conditions in the first result file, as well as the size and position of the discrete particles, and complete the heat transfer and flow CFD simulation of the model under the current state. The output module is configured to output the fluid drag force and heat flux at each integration point on the surface of each cell, as well as the fluid velocity, pressure, temperature, lift and drag coefficient parameters at the location of each dust particle, to the second result file after the CFD simulation completes the current time step. The update module is configured to update the boundary conditions in the local unit cell model of the core based on the fluid drag and fluid parameters of the particles in the second result file for the DEM sub-cycle within the next large CFD time step. The repeat module is configured to repeatedly run the first simulation module, the second simulation module, the output module, and the update module until the preset total simulation time is reached, at which point the calculation ends.

[0008] According to a third aspect of this application, an electronic device is provided, comprising: At least one processor; and memory that is communicatively connected to at least one processor; The memory stores instructions that can be executed by at least one processor, which enables the at least one processor to perform the aforementioned method for analyzing wear dust generation and flow in the first aspect.

[0009] According to a fourth aspect of this application, a non-transitory computer-readable storage medium storing computer instructions is provided, wherein the computer instructions are used to cause a computer to perform the wear dust generation and flow analysis method of the first aspect described above.

[0010] According to a fifth aspect of this application, a computer program product is provided, comprising a computer program that, when executed by a processor, implements the wear dust generation and flow analysis method as described in the first aspect above.

[0011] This application achieves a bidirectional coupling calculation of wear dust generation and coolant flow field by simultaneously constructing discrete element and CFD models using local unit cells of the reactor core with a classic grain configuration, setting continuous cyclic motion boundaries for fuel elements, and embedding DEM substeps within a large CFD time step. Therefore, it can solve the problems of insufficient simulation accuracy of dust generation and flow distribution caused by the decoupling of dust generation and transport processes, distortion of pebble bed geometry, and inability to simulate the cyclic motion of fuel spheres in related technologies. This achieves the technical effect of accurately restoring the dynamic process of wear dust generation of fuel elements and dust migration with coolant flow in the reactor core, and improving the accuracy of dust source term assessment in pebble bed reactors.

[0012] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of this application, nor is it intended to limit the scope of this application. Other features of this application will become readily apparent from the following description. Attached Figure Description

[0013] To more clearly illustrate the embodiments of this application, the accompanying drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0014] Figure 1 A schematic flowchart illustrating a method for analyzing the generation and flow of wear dust provided in an embodiment of this application; Figure 2 This is a schematic diagram of the structure of an abrasion dust generation and flow analysis device provided in an embodiment of this application. Detailed Implementation

[0015] The following description, in conjunction with the accompanying drawings, illustrates exemplary embodiments of this application, including various details to aid understanding. These should be considered merely exemplary. Therefore, those skilled in the art will recognize that various changes and modifications can be made to the embodiments described herein without departing from the scope and spirit of this application. Similarly, for clarity and brevity, descriptions of well-known functions and structures are omitted in the following description.

[0016] The following description, with reference to the accompanying drawings, describes a method, apparatus, device, and storage medium for analyzing the generation and flow of wear dust according to embodiments of this application.

[0017] Figure 1This is a schematic flowchart of a method for analyzing the generation and flow of wear dust provided in an embodiment of this application.

[0018] like Figure 1 As shown, the method includes the following steps: S1. Establish a discrete element model of the fuel element. Based on the macroscopic physical property parameters of the actual fuel element, calibrate the parameters of the fuel element. Determine the contact model parameter combination that conforms to the macroscopic physical property parameters of the fuel element as the parameter setting of the discrete element model of the fuel element. Set the discrete element model of the fuel element as a unit cell.

[0019] In some embodiments, a discrete element model of the fuel element is established, using a real spherical fuel element as the simulation prototype, and parameter calibration is performed based on the macroscopic physical properties of the fuel element. Parameter calibration involves iteratively adjusting the input parameters of the discrete element contact model to match the simulated macroscopic mechanical and heat transfer characteristics with the measured physical properties of the actual fuel element, thereby ensuring the physical authenticity of the simulation results. The specific macroscopic physical properties of the fuel element include a density of 1.75 g / cm³, an elastic modulus of 10 GPa, a Poisson's ratio of 0.2, and a thermal conductivity of 50 W / (m²). K).

[0020] Discrete element simulations (DEMs) employed the Hertz-Mindlin no-slip contact model to describe the contact mechanics between fuel elements. After multiple rounds of calibration simulations, the final combination of contact model parameters conforming to the aforementioned macroscopic properties was determined, with a coefficient of restitution of 0.85, a static friction coefficient of 0.3, and a rolling friction coefficient of 0.05. The DEM model of a single fuel element, after parameter calibration, was set as a unit cell, serving as the basic computational unit for subsequent wear and flow coupling analysis.

[0021] By obtaining discrete element units with properties consistent with real fuel elements through precise parameter calibration, the contact and collision characteristics of fuel elements can be accurately reproduced, providing a reliable model basis for subsequent high-precision simulation of wear and dust generation.

[0022] S2. Establish a local unit cell model of the reactor core. Its geometric dimensions are determined by the number of discrete element models of the fuel elements and the volume fraction of the fuel elements in the active region of the reactor core. The shape is a cube. Multiple discrete element models of fuel elements in the local unit cell model of the reactor core are arranged according to the classical grain configuration. A CFD model is established synchronously based on the geometric parameters and distribution positions.

[0023] In some embodiments, a local unit cell model of the reactor core is established. The model as a whole adopts a cubic structure, and its geometric dimensions are determined by reverse calculation based on the total number of discrete element models of fuel elements filled within the unit cell, combined with the 60% volume share of fuel elements in the active region of the reactor core. Taking a body-centered cubic grain configuration as an example, a single unit cell contains 9 discrete element models of fuel elements, and the total volume of fuel elements is 1.01787 × 10⁻⁶.- Based on the 60% volume fraction, the side length of the cubic unit is calculated to be 11.92 cm.

[0024] The discrete element models of multiple fuel elements within the unit cell are arranged in an ordered manner according to a classic grain configuration, which can be either body-centered cubic (BCC) or face-centered cubic (FCC). When using a BCC configuration, the centers of the nine fuel elements are located at the body center and eight corner points of the cube, respectively. During the arrangement, the distance between any two center points is ensured to be no less than 6 cm to avoid geometric overlap. Calculations show that an offset of 3.1 cm for the corner point centers ensures that the corner points do not exceed the unit cell boundary while maintaining a sufficient safety distance from the body-centered sphere.

[0025] Based on the geometric arrangement of discrete elements, a corresponding CFD calculation model is constructed simultaneously according to the geometric parameters of the unit and the distribution position of the fuel elements, so that the geometric shape and element position of the fluid calculation domain and the discrete element solid domain are completely corresponding, ensuring the spatial consistency of subsequent coupled calculations.

[0026] By replacing the traditional random stacking or equivalent porous media model with the ordered arrangement of classical grain configurations, the influence of the periodic arrangement structure in the ball bed on wear behavior and coolant flow field can be accurately reflected. The CFD model established simultaneously ensures the consistency of geometric boundaries, providing a real and reliable geometric carrier for the coupled analysis of wear and flow.

[0027] S3, set the cubic surface boundary conditions for the local unit cell model of the core, set the front and back, left and right boundaries as periodic boundary conditions, the upper boundary as free and unconstrained, and the lower boundary as wall. Set the gravity, initial temperature, heat source of the unit cell, and boundary temperature of the local unit cell model of the core.

[0028] In some embodiments, the local unit cell model of the reactor core adopts a cubic computational domain containing six spatial surfaces. The front and rear surfaces, as well as the left and right surfaces, are all set as periodic boundary conditions. The physical parameters of the computational domain on both sides of these boundaries remain continuous, enabling the simulation of the distribution characteristics of a large-scale continuous pebble bed within the active region of the reactor core under finite unit cell size, effectively reducing boundary interference caused by the finite computational domain. The upper boundary is set as a free and unconstrained state, imposing no restrictions on the displacement of the fuel element unit cell. The lower boundary is set as a rigid wall, providing stable mechanical support for the unit cell and restricting its downward displacement.

[0029] After setting the boundary conditions, the basic mechanical and thermal parameters of the unit cell were configured. The gravitational acceleration was set to 9.8 m / s², acting vertically downwards. The initial temperature of the entire unit cell model was set to 900 K, matching the typical operating temperature level of a high-temperature gas-cooled reactor core. An internal volume heat source was set for each fuel element unit cell, with an intensity of 3.22 W / m³, to equivalently characterize the decay heat or fission heat production of the fuel element. Simultaneously, the temperature of all walls of the local unit cell model in the core was uniformly set to 900 K to ensure a uniform and stable initial thermal environment in the computational domain.

[0030] By matching the boundary conditions and thermal parameters of actual operating conditions, the mechanical constraint environment and thermal field conditions of the active region of the reactor core can be realistically reproduced, providing an accurate boundary basis for subsequent discrete element calculations and fluid calculations, and ensuring the authenticity and reliability of the simulation results.

[0031] S4: Fill the local unit cell model of the reactor core with the required number of unit cells, and complete the parameter settings for the contact model between unit cells. This completes the initialization of the local unit cell model of the reactor core, which means completing the DEM simulation settings and calculation initialization.

[0032] In some embodiments, the core local unit cell model is filled with a required number of unit cells. The arrangement of the unit cells corresponds one-to-one with a preset classical grain configuration. During the arrangement process, the center-to-center spacing of each unit cell is strictly verified to ensure that there is no geometric overlap between unit cells, and the overall filling state matches the volume fraction requirements of the core active region. Taking the body-centered cubic configuration as an example, the unit cell model is filled with a total of 9 unit cells, corresponding to the body center position and 8 corner positions of the unit cell, respectively.

[0033] After the unit cell filling is completed, pre-calibrated contact model parameters are configured for all unit cells. The Hertz-Mindlin no-slip contact model is used to describe the contact interaction between unit cells, with corresponding settings of a restitution coefficient of 0.85, a static friction coefficient of 0.3, and a rolling friction coefficient of 0.05, so that the collision and tribomechanical behavior between unit cells matches the macroscopic physical properties of real fuel elements.

[0034] After completing the above configuration, the initialization of the local unit cell model of the reactor core is carried out, and the time step of the discrete element calculation is set to 1×10. -5 The preset total simulation time is 100 seconds, corresponding to 100 hours of actual reactor core operation. At the same time, the initial velocity, spatial position, and temperature field of all unit cells are assigned, so that the model enters the initial state for executable calculation. This completes the parameter setting and calculation initialization of all DEM simulations.

[0035] By precisely arranging the unit cells and configuring the contact parameters, the mechanical properties of the discrete element model are ensured to be consistent with those of the real fuel element. The standardized initialization settings provide stable and accurate initial conditions for the subsequent dynamic calculation of collision wear, ensuring the reliability of the wear dust generation calculation results.

[0036] S5, Set up CFD simulation of cooling flow in the local unit cell model of the core: Based on the actual operating parameters of the specified location in the active region of the core, set the temperature, flow rate and pressure boundary conditions of the coolant on the upper and lower surfaces of the local unit cell model of the core, and keep the temperature, flow rate and pressure of the other surfaces the same as the lower surface to complete the initialization of the flow simulation of the local unit cell model of the core.

[0037] In some embodiments, a CFD simulation of coolant flow within a local unit model of the reactor core is set up. The working fluid used in the simulation is helium coolant in the primary loop of a high-temperature gas-cooled reactor. All parameters are determined based on the actual operating conditions at a specified location in the active region of the reactor core. The physical properties of helium at 900K and 7MPa are: density 0.067kg / m³, dynamic viscosity 4.2×10⁻⁶. -5 Pa s, thermal conductivity 0.3 W / (m K), specific heat capacity 5190 J / (kg) K).

[0038] Temperature, flow rate, and pressure boundary conditions for the coolant are set on the upper and lower surfaces of the local unit model of the reactor core. The upper surface is set as the velocity inlet, with the coolant flowing vertically downwards at an inlet velocity of 5 m / s, an inlet temperature of 900 K, and an inlet pressure of 7.0 MPa. The lower surface is set as the pressure outlet, with an outlet pressure of 6.98 MPa, used to simulate the flow pressure drop generated by the coolant flowing through the pebble bed region, and the outlet temperature is set to 900 K.

[0039] The front, back, left, and right surfaces of the unit cell model are kept at the same temperature (900K) as the bottom surface. Flow rate and pressure are set to symmetric conditions with zero gradients from neighboring grids, zero wall normal velocity, and zero tangential physical quantity gradients to accommodate the flow characteristics of the periodically arranged spherical bed. CFD calculations use the k-ωSST turbulence model with a 1mm grid size and a time step of 1×10⁻⁶. -4 After completing the configuration of all boundary and model parameters, the initial flow field calculation is carried out to complete the initialization of the flow simulation of the local unit cell model of the reactor core.

[0040] By matching the coolant properties and boundary conditions to real-world operating conditions, the coolant flow and heat transfer environment within the reactor core spheres can be accurately reproduced. The standardized initialization settings provide a stable and accurate initial state for flow and heat transfer simulations, ensuring the reliability of fluid calculation results.

[0041] S6, set a unit cell at the upper boundary of the local unit cell model of the core to enter the local unit cell model of the core with acceleration. The acceleration is calculated from the total force of gravity superimposed with coolant buoyancy. When any unit cell moves away from the boundary of the local unit cell model of the core, the unit cell that satisfies the given state re-enters the model from the corresponding boundary to simulate the continuous cyclic motion of fuel elements in the reactor.

[0042] In some embodiments, a fuel element circulation mechanism is set up for the local unit cell model of the reactor core. A virtual injection surface is set 0.1 mm above the upper boundary of the unit cell model, and the unit cells are configured to enter the computational domain with a set acceleration. This acceleration is calculated from the total force of gravity and coolant buoyancy. Taking into account both the weight of the fuel element itself and the buoyancy exerted by the helium coolant, the corresponding calculation relationship is as follows:

[0043] Where g is the acceleration due to gravity. For coolant buoyancy, This refers to the mass of the fuel element unit cell.

[0044] The buoyancy of the coolant is calculated from the helium density, the volume of the unit cell, and the acceleration due to gravity, using the following formula: ,in The density of helium gas. Let g be the volume of the unit cell and g be the acceleration due to gravity. The mass of the unit cell is calculated from the density of the fuel element and the volume of the unit cell, using the following formula: ,in, For fuel element density, Let be the volume of the unit cell. Substituting the corresponding physical property parameters, the cyclic acceleration of the unit cell is approximately 9.762 m / s². When any unit cell completely leaves the boundary of the unit cell model due to motion, the unit cell satisfying the given state will re-enter the computational domain from the relative boundary of the corresponding departure surface, with the velocity component remaining consistent with that at departure. The given state of the unit cell can be either an intact, unworn state or a state with the same degree of wear as the departing unit cell. To ensure the stability of the cyclic process, an average of one unit cell leaves the upper boundary and re-enters the model every 0.1 s, thereby simulating the dynamic operating characteristics of the continuous cyclic operation of fuel elements within the reactor core. By using the cyclic acceleration calculated through the coupling of gravity and buoyancy with the boundary entry and exit mechanism, the continuous cyclic motion of fuel elements within the reactor core can be realistically simulated, restoring the long-term impact of dynamic cycling on wear behavior and dust accumulation, effectively improving the fit between the simulation results and actual reactor core operating conditions.

[0045] S7 uses a CFD time step as a large time step, with multiple DEM time steps embedded within each large time step. In a DEM sub-loop of a large time step, it simulates the total force, movement speed, position, and discrete dust particles generated by collision and wear for each unit cell. Discrete dust particles include particle size and position. Based on the wear model, it determines the size of the generated discrete particles and the particle position at the end of the sub-loop, and outputs the first result file.

[0046] In some embodiments, a CFD time step is defined as a large time step, and multiple DEM time steps are embedded within each large time step. This multi-time-scale nesting approach adapts to the different accuracy requirements of fluid dynamics computation and discrete element collision computation. In this scheme, the CFD time step is set to 1×10⁻⁶. -4 s, a single CFD time step contains 10 nested DEM time steps, and the time step for DEM calculation is 1×10. -5 s.

[0047] Within a DEM sub-loop with a large time step, the total force, velocity, and spatial position of each cell are simulated step-by-step. The total force on each cell includes gravity, contact force, coolant drag, and damping force. The contact force between cells is calculated using the Hertz-Mindlin model, and the coolant drag is calculated using the Ergun equation, thereby accurately reproducing the motion evolution of the cell under multiple mechanical forces.

[0048] During the sub-cycle, the collision force, relative sliding velocity, and contact stress between unit cells are calculated simultaneously. Based on the wear model, the size of discrete dust particles generated by collision and wear is determined. The diameter of the dust particles ranges from micrometers to sub-millimeters and can be generated according to a normal distribution or a random distribution. After completing all DEM sub-step calculations, the position, velocity, and angular velocity of all unit cells are updated. At the same time, the spatial position of each discrete dust particle at the end of the sub-cycle is determined, and the mechanical motion parameters of the unit cells, the size and position data of the dust particles are integrated and output as the first result file.

[0049] By adopting a computational architecture with large time steps nested substeps, a refined transient simulation of the wear and dust generation process can be achieved while ensuring the efficiency of coupled computation. This accurately captures the dynamic characteristics of unit cell collision wear and the initial distribution state of dust particles, providing precise source term data support for subsequent fluid-structure interaction heat transfer calculations.

[0050] S8. Within the current large CFD time step, based on the cell position and stress conditions in the first result file, as well as the size and position of discrete particles, set the geometric configuration and particle source terms for the CFD simulation, and complete the heat transfer and flow CFD simulation of the model under the current state.

[0051] In some embodiments, within the current large time step of the CFD calculation cycle, the cell position and force data in the first result file are read to update the solid geometry configuration within the CFD computation domain. Combined with a pre-constructed dynamic mesh system, the shape and distribution of the fluid computation mesh are adjusted according to the real-time spatial position of the cell, ensuring that the solid boundary of the fuel element in the CFD model perfectly matches the element position obtained from the discrete element calculation, thus guaranteeing the spatial consistency of the fluid-structure interaction calculation.

[0052] The size and spatial location data of discrete dust particles in the first result file are read synchronously and set as the particle phase source term in the CFD simulation. Based on the particle size parameters and initial generation position of each dust particle, discrete phase particles are added at the corresponding grid nodes in the flow field to replace the pre-set dust source term in the traditional simulation, thereby realizing the dynamic connection between the wear dust generation process and the dust transport process.

[0053] After completing the geometry update and particle source term settings, perform CFD calculations at the current time step to simulate the flow state and heat transfer process of coolant in the gap between the ball bed elements. At the same time, calculate the force and motion characteristics of dust particles under the coolant carrier to complete the flow and heat transfer coupling solution of the model at this time step.

[0054] By updating the CFD geometric boundary and dust source terms in real time based on the discrete element calculation results, dynamic coupling of wear dust generation and fluid transport is realized, which solves the problem of pre-set distortion of dust source terms in traditional decoupled simulation. It can truly reflect the physical process of dust being affected by the flow field immediately after dust generation, and effectively improve the accuracy of flow and heat transfer simulation in the ball bed.

[0055] S9, after the CFD simulation completes the current time step, outputs the fluid drag force and heat flux at each integration point on the surface of each unit cell, as well as the fluid velocity, pressure, temperature, lift, and drag coefficient parameters at the location of each dust particle to the second result file.

[0056] In some embodiments, after the CFD simulation completes the flow and heat transfer solution for the current time step, the calculation results are extracted and output. For each fuel element unit cell, fluid interaction parameters are collected at various integration points on its surface. The integration points are numerical sampling nodes distributed along the solid wall, which can accurately reflect the spatial distribution characteristics of the physical quantities on the wall. The collected parameters include fluid drag force and wall heat flux, which respectively characterize the magnitude of the force exerted by the coolant on the surface of the unit cell and the heat transfer intensity between the unit cell and the coolant.

[0057] For all discrete dust particles in the computational domain, based on the real-time spatial position of each particle, the coolant flow field parameters at the corresponding position are extracted, covering fluid velocity, pressure and temperature. At the same time, the lift force and corresponding drag coefficient of the dust particles are calculated and output, which fully characterizes the physical state and fluid interaction characteristics of the flow field environment in which the dust particles are located.

[0058] The surface mechanics and heat transfer parameters of the aforementioned unit cells and the flow field parameters corresponding to dust particles are standardized and integrated, and then uniformly output to the second result file to form a coupled dataset that is transferred from the CFD side to the DEM side.

[0059] By accurately extracting multi-dimensional flow field parameters from the cell wall and dust particle locations, accurate fluid force boundary data can be provided for discrete element calculations, ensuring the accuracy of data transmission in the bidirectional coupling process and providing a reliable data foundation for iterative simulation of wear dust generation and flow transport.

[0060] S10, for the DEM sub-cycle within the next large CFD time step, update the boundary conditions in the local unit cell model of the core based on the fluid drag force and the fluid parameters of the particles in the second result file.

[0061] In some embodiments, before entering the DEM sub-cycle calculation within the next large CFD time step, the flow field coupling data in the second result file is read to update the boundary conditions of the discrete element model of the local unit cell in the reactor core. For each fuel element unit cell, the fluid drag force data corresponding to each integration point on the surface of the unit cell in the file is synchronously loaded into the discrete element force calculation module, replacing the drag force parameters of the previous calculation cycle, so that the total force calculation of the unit cell is performed based on the latest coolant flow effect results.

[0062] For all discrete dust particles within the computational domain, the flow field boundary conditions for each particle are updated based on the fluid velocity, pressure, temperature, lift, and drag coefficient parameters at each particle's location in the second results file. This incorporates the fluid's force on the particles into the discrete element particle dynamics calculation system, ensuring that the dust particle's motion evolution matches the current flow field state. After updating the boundary conditions for both the unit cell and dust particles, the discrete element model can then enter the sub-loop calculation process within the current large time step.

[0063] By feeding back the flow field data obtained from CFD solutions to the discrete element calculation system, bidirectional data interaction between the fluid field and the solid particle system is achieved, ensuring the physical consistency of the coupled calculation and enabling a more realistic reflection of the dynamic impact of the flow field on fuel element wear and dust movement.

[0064] S11, repeat S7 to S10 until the preset total simulation time is reached, then the calculation ends.

[0065] In some embodiments, after completing a single round of CFD calculations with a large time step, the complete steps of wear dust generation calculation, flow heat transfer solution, parameter output, and boundary update are executed cyclically according to a predetermined process, forming a bidirectional coupled iterative mechanism of discrete element mechanics calculation and computational fluid dynamics solution. In each round, the geometry and source terms of the CFD calculation domain are updated with the component positions and dust distribution output by the DEM sub-loop, and the discrete element calculation boundary is corrected with the flow field force feedback obtained from the CFD solution, realizing real-time data interaction and state synchronization between the two types of numerical simulations.

[0066] The preset total simulation duration is 100 seconds, corresponding to 100 hours of actual reactor core operation. During the cycle, the motion position, stress state, and wear degree of the fuel element unit cells are continuously updated. Simultaneously, the generation, migration, and spatial distribution changes of discrete dust particles are recorded. The flow velocity, pressure, and temperature distribution of the coolant field, as well as its interaction parameters with solid particles, are dynamically corrected. The dynamic connection between the wear-induced dust generation process and the dust transport process is maintained throughout the entire process, recreating the real physical processes of wear and flow interaction within the reactor core. When the cumulative simulation duration reaches the preset total simulation duration, the cycle calculation terminates, completing all simulation analyses.

[0067] Through long-cycle bidirectional coupling iteration, the cumulative effect and dynamic feedback of wear dust generation and flow field changes during core operation can be accurately reflected. This solves the problem that traditional decoupling simulation cannot reflect the process coupling effect, and can provide accurate numerical analysis support for the long-term safety assessment of graphite dust source terms in pebble bed reactors.

[0068] Compared with related technologies, in this embodiment, the following steps are taken: S1: Establish a discrete element model of the fuel element, calibrate the fuel element parameters based on the macroscopic physical property parameters of the actual fuel element, determine the contact model parameter combination that conforms to the macroscopic physical property parameters of the fuel element as the parameter setting of the discrete element model of the fuel element, and set the discrete element model of the fuel element as a unit cell; S2: Establish a local unit cell model of the core, the geometric dimensions of which are determined by the number of fuel element discrete element models filled and the volume fraction of the fuel element in the active region of the core, and the shape is cubic. Multiple fuel element discrete element models in the local unit cell model of the core are arranged according to the classical grain configuration, and a CFD model is established synchronously based on the geometric parameters and distribution position; S3: Set the local unit cell model of the core. The cube surface boundary conditions are set as follows: the front and rear, left and right boundaries are set as periodic boundary conditions, the upper boundary is free and unconstrained, and the lower boundary is set as a wall. The gravity, initial temperature, heat source, and boundary temperature of the unit cell are set, as well as the boundary temperature of the local unit cell model in the core are set. S4: The local unit cell model in the core is filled with unit cells that meet the required quantity, and the contact model parameters between the unit cells are set. This completes the initialization of the local unit cell model in the core, i.e., the DEM simulation setup and calculation initialization are completed. S5: The CFD simulation of the cooling flow within the local unit cell model in the core is set: based on the actual operating parameters at a specified location in the active region of the core, the temperature, flow rate, and pressure boundary conditions of the coolant are set on the upper and lower surfaces of the local unit cell model in the core, while the remaining surfaces remain unchanged. Initialize the flow simulation of the local unit cell model of the reactor core under the same temperature, flow rate, and pressure on the lower surface; S6: Set a unit cell to enter the local unit cell model of the reactor core at the upper boundary with acceleration. The acceleration is calculated from the total force of gravity plus coolant buoyancy. When any unit cell moves away from the boundary of the local unit cell model of the reactor core, the unit cell satisfying the given state re-enters the model from the corresponding boundary to simulate the continuous cyclic motion of fuel elements in the reactor; S7: Use one CFD time step as a large time step. Each large time step embeds multiple DEM time steps. In the DEM sub-loop of a large time step, simulate the total force, movement speed, position, and other parameters of each unit cell. Discrete dust particles generated by collision and wear, including particle size and position, are generated. The size of the discrete particles and the position of the particles at the end of the sub-cycle are determined according to the wear model, and the first result file is output; S8: Within the current CFD time step, based on the cell position and force conditions in the first result file, as well as the size and position of the discrete particles, the geometric configuration and particle source terms of the CFD simulation are set to complete the heat transfer and flow CFD simulation of the model under the current state; S9: After the CFD simulation completes the current time step, the fluid drag force and heat flux at each integration point on the surface of each cell, as well as the fluid velocity, pressure, temperature, lift and drag coefficient parameters at the location of each dust particle are output to the second result file;S10: For the DEM sub-cycle within the next large CFD time step, update the boundary conditions in the local unit cell model of the reactor core based on the fluid drag force and fluid parameters acting on the particles in the second result file; S11: Repeat S7 to S10 until the preset total simulation time is reached, and the calculation ends. This can solve the problems of insufficient simulation accuracy of dust generation and flow distribution caused by the decoupling of dust generation and transport processes, distortion of pebble bed geometry, and inability to simulate fuel sphere circulation motion in related technologies. It achieves the technical effect of accurately restoring the dynamic process of dust generation from fuel element wear and migration with coolant flow within the reactor core, and improving the accuracy of dust source term assessment in pebble bed reactors.

[0069] As a specific implementation of this application, based on the basic scheme, the macroscopic physical property parameters in S1 are further defined as density, elastic modulus, Poisson's ratio and thermal conductivity, and the contact model parameters include coefficient of restitution, static friction coefficient and rolling friction coefficient.

[0070] Specifically, as one embodiment of this application, the macroscopic physical properties selected in the parameter calibration process for establishing the discrete element model of the fuel element include density, elastic modulus, Poisson's ratio, and thermal conductivity. These four parameters jointly determine the macroscopic mechanical and heat transfer physical properties of the fuel element. The density of the fuel element is set to 1.75 g / cm³, directly determining the mass and inertial mechanical properties of the unit cell; the elastic modulus is set to 10 GPa, and the Poisson's ratio is set to 0.2, both characterizing the elastic deformation behavior of the fuel element under contact load; the thermal conductivity is set to 50 W / (m²). K) is used to describe the heat transfer capacity inside and between fuel elements.

[0071] The contact model parameters matched during parameter calibration specifically include the coefficient of restitution, static friction coefficient, and rolling friction coefficient. These three types of parameters correspond to the core input terms of the Hertz-Mindlin no-slip contact model and are used to describe the mechanical response of contact collisions between unit cells. The coefficient of restitution is set to 0.85 to characterize the degree of energy loss during unit cell collisions; the static friction coefficient is set to 0.3 to limit the critical resistance to tangential sliding at the unit cell contact interface; and the rolling friction coefficient is set to 0.05 to describe the resistance attenuation characteristics when the unit cell undergoes rolling motion. By calibrating and adjusting the above contact model parameters, the macroscopic mechanical response obtained from discrete element simulation can be made to perfectly match the measured physical properties of real fuel elements.

[0072] By clearly defining the specific composition and values ​​of macroscopic physical property parameters and contact model parameters, the discrete element model can be accurately calibrated, ensuring that the simulated collision, friction, and deformation behaviors are highly consistent with those of real fuel elements, thus providing a reliable mechanical model basis for subsequent wear and dust generation calculations.

[0073] As a specific implementation of this application, based on the basic scheme, the classic grain configuration in S2 is further defined as body-centered cubic or face-centered cubic.

[0074] Specifically, as one embodiment of this application, the classic grain configuration in the local unit cell model of the reactor core can be either body-centered cubic or face-centered cubic. Both configurations are typical periodic ordered stacking structures that can accurately characterize the spatial arrangement of fuel elements in the pebble bed.

[0075] In a body-centered cubic (BCC) configuration, a single cubic unit contains nine fuel element cells, with one cell located at the body center and the remaining eight at the eight corners. Based on the 60% fuel element volume share in the core active region, the side length of the cubic unit is calculated to be 11.92 cm. During the arrangement, the distance between any two sphere centers is controlled to be no less than 6 cm, and the offset of the corner sphere centers is set to 3.1 cm, ensuring that all cell types have no geometric overlap and do not exceed the unit boundaries. The packing characteristics of this configuration closely match the actual packing state of the core's main active region, making it suitable for wear and flow analysis in the conventional areas of the core.

[0076] When using a face-centered cubic (FCC) configuration, a single cubic unit contains 14 fuel element cells. Eight cells are located at the vertices of the cube, and six cells are located at the centers of the six faces. The geometric dimensions of the cells are calculated based on the volume fraction of the active region in the core, ensuring that the cells do not overlap. This configuration has a higher packing density and can be used to simulate the wear behavior and flow field distribution characteristics of locally densely packed regions within a pebble bed.

[0077] Regardless of the grain configuration chosen, a CFD model is established synchronously based on the corresponding geometric parameters and the distribution position of the unit cell, so that the geometric structure and spatial position of the components in the fluid computation domain and the discrete element solid domain are completely corresponding, ensuring the spatial consistency of subsequent coupled calculations.

[0078] By providing two classic grain configuration options, it can adapt to the pebble bed stacking characteristics of different regions of the reactor core, accurately reproduce the influence of periodic arrangement structure on component wear and coolant flow field, and effectively improve the applicability and analysis accuracy of the simulation scheme to different reactor core regions.

[0079] As a specific implementation of this application, based on the basic scheme, the given state in S6 is further defined as either an intact and unworn state or a state with the same degree of wear as the departing unit cell.

[0080] Specifically, as one embodiment of this application, during the simulation of the continuous cyclic motion of the fuel element, the unit cell re-entering the model can be selected from two given states: an intact and unworn state and a state in which the departing unit cell has the same degree of wear. The selection can be flexibly made according to the target of the simulation analysis.

[0081] When the undamaged state is selected, the surface of the unit cell re-entering the unit cell model shows no wear marks, and the mechanical and geometric parameters are completely consistent with the initially calibrated brand-new fuel elements. This corresponds to the operating condition in which brand-new fuel elements are continuously replenished in the core fuel cycle system. This state setting can be used to analyze the dust generation characteristics during the initial impact wear stage after new fuel elements are introduced into the core, as well as the differences in wear behavior under mixed accumulation of new and worn elements.

[0082] When a unit cell with the same wear level as the departing unit cell is selected, the re-entering unit cell inherits the surface wear state and related physical properties of the departing unit cell, corresponding to the steady-state operating condition of repeated fuel element circulation and continuous wear accumulation within the reactor core. This state setting can reproduce the wear evolution law of fuel elements in the long-term circulation process within the reactor core and is suitable for analyzing dust accumulation and distribution characteristics under long-term operation. During the circulation process, an average of one unit cell completes the replacement of departure and entry every 0.1 seconds to ensure a stable and continuous circulation process.

[0083] By setting two selectable cell entry states, two typical operating conditions—core fuel replenishment and steady-state circulation—can be simulated respectively, flexibly adapting to different analysis needs. This more realistically restores the impact of the fuel element circulation process in the reactor on wear, dust generation, and dust accumulation, improving the consistency between simulation results and actual operating scenarios.

[0084] As a specific implementation of this application, based on the basic scheme, the acceleration in S6 is further defined to satisfy the following relationship:

[0085] Where g is the acceleration due to gravity. For coolant buoyancy, This refers to the mass of a unit cell.

[0086] Specifically, as one embodiment of this application, the cyclic acceleration of the fuel element unit cell entering the reactor core local unit cell model satisfies the following relationship: Where g is the acceleration due to gravity. For coolant buoyancy, This refers to the mass of a unit cell.

[0087] The buoyancy of the coolant is calculated from the helium density, the volume of the unit cell, and the acceleration due to gravity, using the following formula: ,in The density of helium gas. Let g be the volume of the unit cell and g be the acceleration due to gravity. The mass of the unit cell is calculated from the density of the fuel element and the volume of the unit cell, using the following formula: ,in, For fuel element density, This refers to the volume of a single cell.

[0088] By using the acceleration calculation formula that couples gravity and buoyancy, the actual stress state of fuel elements in the coolant environment can be accurately reproduced, ensuring that the motion characteristics of the circulating unit cells are consistent with the actual core operating conditions, and effectively improving the physical realism and calculation accuracy of the fuel element cyclic motion simulation.

[0089] As a specific implementation of this application, based on the basic scheme, the wear model in S7 is further defined to determine the size of the generated discrete particles according to the collision force, relative sliding speed and contact stress between unit cells.

[0090] Specifically, as one embodiment of this application, in the calculation of wear and dust generation in the DEM sub-cycle, the wear model used takes the collision force, relative sliding velocity, and contact stress between unit cells as the core judgment parameters to determine the discrete dust particle size generated by a single collision wear. The collision force is obtained by solving the Hertz-Mindlin contact model, which can simultaneously output the normal and tangential loads of the contact interface, intuitively reflecting the intensity of the contact action between unit cells; the relative sliding velocity characterizes the tangential relative motion rate of the two contacting unit cells at the contact interface and is the core driving factor for friction and wear; the contact stress is the load borne per unit area of ​​the contact interface, and combined with the wear characteristics of graphite materials, the wear volume of the contact area can be quantitatively calculated.

[0091] The wear model, based on the three types of parameters mentioned above and combined with the material wear coefficient of the graphite fuel element, calculates the total wear volume of the unit cell contact area within a single DEM time step. This wear volume is then discretized into discrete dust particles ranging from micrometers to sub-millimeters in size. The particle diameter can be generated according to a normal or random distribution rule. Simultaneously, the generation location and initial motion state of each dust particle are recorded. After completing the wear calculation for all DEM time steps within the sub-loop, the size and spatial location information of all discrete dust particles are summarized and output to the first results file.

[0092] By using a wear calculation method that couples multiple parameters such as collision force, sliding velocity, and contact stress, the amount of dust and particle size distribution generated by the collision and friction of unit cells can be accurately quantified, restoring the wear dust generation characteristics under real contact conditions. This effectively improves the accuracy of dust source term calculation and provides a reliable initial data foundation for subsequent dust transport and deposition simulation.

[0093] As a specific implementation of this application, based on the basic scheme, the total force on each unit cell in S7 is further defined to include gravity, contact force, coolant drag force and damping force. The contact force is calculated using the Hertz-Mindlin model and the coolant drag force is calculated using the Ergun equation.

[0094] Specifically, as a particular embodiment of this application, in the mechanical calculation process of the DEM sub-cycle, the total force on each fuel element unit cell consists of four parts: gravity, contact force, coolant drag force, and damping force. These four types of forces jointly determine the unit cell's motion acceleration, running speed, and spatial position evolution process.

[0095] Gravity, determined by the mass of the unit cell and gravitational acceleration, acts vertically downwards and is the fundamental mechanical driving force for the formation of the unit cell's stacked structure and the resulting collision and compression. Contact force refers to the interaction forces generated when unit cells contact each other and when a unit cell contacts the wall, calculated using the Hertz-Mindlin model. This model can simultaneously solve for the normal elastic contact force and tangential friction force at the contact interface, matching the elastic contact characteristics of graphite fuel elements. The calculation process, combined with pre-calibrated parameters such as the coefficient of restitution, static friction coefficient, and rolling friction coefficient, accurately recreates the energy loss and frictional dynamics during collisions. Coolant drag is the fluid force exerted by the flowing coolant on the surface of the unit cell, calculated using the Ergun equation. This equation is applicable to solving fluid resistance within a particle-packed bed and, by combining coolant density, dynamic viscosity, and local velocity parameters, accurately determines the magnitude and direction of the drag force acting on the unit cell. Damping force is used to suppress vibration during numerical calculations, ensuring the numerical stability of the discrete element solution process.

[0096] By clearly defining the constituent components of the total force of the unit cell and the corresponding calculation model, the motion state and contact characteristics of the unit cell under multiple mechanical actions can be accurately quantified. The Hertz-Mindlin model ensures the mechanical accuracy of the collision contact calculation, and the Ergun equation is adapted to solve the fluid drag force under the ball bed stacking structure. The combination of the two provides a reliable mechanical analysis basis for the accurate calculation of wear dust generation.

[0097] Figure 2 This is a schematic diagram of the structure of an abrasion dust generation and flow analysis device provided in an embodiment of this application, as shown below. Figure 2 As shown, it includes: The first module 1 is configured to establish a discrete element model of the fuel element, calibrate the parameters of the fuel element according to the macroscopic physical property parameters of the actual fuel element, determine the contact model parameter combination that conforms to the macroscopic physical property parameters of the fuel element as the parameter setting of the discrete element model of the fuel element, and set the discrete element model of the fuel element as a unit cell. The second module 2 is configured to establish a local unit cell model of the reactor core. Its geometric dimensions are determined by the number of discrete element models of the fuel elements and the volume fraction of the fuel elements in the active region of the reactor core. The shape is a cube. The multiple discrete element models of the fuel elements in the local unit cell model of the reactor core are arranged according to the classical grain configuration. The CFD model is established synchronously according to the geometric parameters and distribution positions. The first setting module 3 is configured to set the cubic surface boundary conditions of the local unit cell model of the core, set the front and back boundaries and the left and right boundaries as periodic boundary conditions, set the upper boundary as free and unconstrained, set the lower boundary as wall, and set the gravity, initial temperature, heat source of the unit cell, and the boundary temperature of the local unit cell model of the core. Initialization module 4 is configured to fill the local unit cell model of the reactor core with a number of unit cells that meet the requirements, and to complete the parameter settings of the contact model between unit cells, thereby completing the initialization of the local unit cell model of the reactor core, that is, completing the DEM simulation settings and calculation initialization. Setting module 5 is configured to set the CFD simulation of cooling flow within the local unit cell model of the core: based on the actual operating parameters at a specified location in the active region of the core, the temperature, flow rate and pressure boundary conditions of the coolant are set on the upper and lower surfaces of the local unit cell model of the core, while the other surfaces maintain the same temperature, flow rate and pressure as the lower surface, thus completing the initialization of the flow simulation of the local unit cell model of the core. The second setting module 6 is configured to set a unit cell at the upper boundary of the local unit cell model of the core to enter the local unit cell model of the core with acceleration. The acceleration is calculated from the total force of gravity superimposed on the buoyancy of the coolant. When any unit cell moves away from the boundary of the local unit cell model of the core, the unit cell that satisfies the given state re-enters the model from the corresponding boundary to simulate the continuous cyclic motion of the fuel elements in the reactor. The first simulation module 7 is configured to use one CFD time step as a large time step, with multiple DEM time steps embedded in each large time step. In the DEM sub-loop of a large time step, the total force, movement speed, position of each unit cell, and discrete dust particles generated due to collision and wear are simulated. Discrete dust particles include particle size and position. The size of the generated discrete particles and the particle position at the end of the sub-loop are determined according to the wear model, and the first result file is output. The second simulation module 8 is configured to, within the current large CFD time step, set the geometric configuration and particle source terms of the CFD simulation based on the cell position and force conditions in the first result file, as well as the size and position of the discrete particles, and complete the heat transfer and flow CFD simulation of the model under the current state. Output module 9 is configured to output the fluid drag force and heat flux at each integration point on the surface of each cell, as well as the fluid velocity, pressure, temperature, lift and drag coefficient parameters at the location of each dust particle, to the second result file after the CFD simulation completes the current time step. Update module 10 is configured to update the boundary conditions in the local unit cell model of the core based on the fluid drag and fluid parameters of the particles in the second result file for the DEM sub-cycle within the next large CFD time step. The repeat module 11 is configured to repeatedly run the first simulation module, the second simulation module, the output module, and the update module until the preset total simulation time is reached and the calculation ends.

[0098] It should be noted that other corresponding descriptions of the functional units involved in the wear dust generation and flow analysis device provided in this embodiment can be found in [reference]. Figure 1 The corresponding description in [the document] will not be repeated here.

[0099] Based on the above, Figure 1 The method for analyzing the generation and flow of wear dust is illustrated. Correspondingly, this embodiment also provides a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the above-described method. Figure 1 This paper presents a method for analyzing the generation and flow of wear dust.

[0100] Based on the above, Figure 1 The embodiment illustrates a method for analyzing the generation and flow of wear dust. Correspondingly, this embodiment also provides a computer program product storing a computer program that, when executed by a processor, implements the above-described method. Figure 1 This paper presents a method for analyzing the generation and flow of wear dust.

[0101] Based on this understanding, the technical solution of this application can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (such as CD-ROM, USB flash drive, mobile hard drive, etc.) and includes several instructions to cause a computer device (such as personal computer, server, or network device, etc.) to execute the methods of various implementation scenarios of this application.

[0102] Based on the above, Figure 1 The method shown is for analyzing the generation and flow of wear dust, and Figure 2 To achieve the above objectives, the present application also provides an electronic device, such as a personal computer or a server, in the illustrated virtual device embodiment. This device includes a storage medium and a processor; the storage medium stores a computer program; the processor executes the computer program to implement the above-described virtual device. Figure 1This paper presents a method for analyzing the generation and flow of wear dust.

[0103] In some embodiments, the aforementioned physical device may further include a user interface, a network interface, a camera, radio frequency (RF) circuitry, sensors, audio circuitry, a Wi-Fi module, etc. The user interface may include a display screen, an input unit such as a keyboard, etc., and optionally, a USB interface, a card reader interface, etc. In some embodiments, the network interface may include a standard wired interface, a wireless interface (such as a Wi-Fi interface), etc.

[0104] The storage medium may also include an operating system and a network communication module. The operating system is a program that manages the hardware and software resources of the aforementioned physical device, supporting the operation of information processing programs and other software and / or programs. The network communication module is used to enable communication between the various components within the storage medium, as well as communication with other hardware and software in the information processing physical device.

[0105] It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes the element.

[0106] The above are merely specific embodiments of this application, enabling those skilled in the art to understand or implement this application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this application. Therefore, this application is not to be limited to these embodiments, but is to be accorded the widest scope consistent with the principles and novel features claimed herein.

Claims

1. A method for analyzing the generation and flow of abrasive dust, characterized in that, include: S1: Establish a discrete element model of the fuel element, calibrate the parameters of the fuel element according to the macroscopic physical property parameters of the actual fuel element, determine the contact model parameter combination that conforms to the macroscopic physical property parameters of the fuel element as the parameter setting of the discrete element model of the fuel element, and set the discrete element model of the fuel element as a unit cell. S2: Establish a local unit cell model of the core. Its geometric dimensions are determined by the number of fuel element discrete element models filled with the core and the volume fraction of the fuel element in the active region of the core. The shape is a cube. The multiple fuel element discrete element models in the local unit cell model of the core are arranged according to the classical grain configuration. A CFD model is established synchronously according to the geometric parameters and distribution positions. S3: The core local unit cell model is set with cubic surface boundary conditions, front and back, left and right boundaries are set with periodic boundary conditions, upper boundary is free and unconstrained, lower boundary is set as wall, and the gravity, initial temperature, heat source, and boundary temperature of the core local unit cell model are set. S4: The local unit cell model of the reactor core is filled with the required number of unit cells, and the contact model parameters between the unit cells are set. The initialization of the local unit cell model of the reactor core is completed, that is, the DEM simulation setting and calculation initialization are completed. S5: Set the CFD simulation of cooling flow in the local unit model of the core: According to the actual operating parameters of the specified location of the active region of the core, set the temperature, flow rate and pressure boundary conditions of the coolant on the upper and lower surfaces of the local unit model of the core, and keep the temperature, flow rate and pressure of the other surfaces the same as the lower surface to complete the initialization of the flow simulation of the local unit model of the core. S6: Set a unit cell at the upper boundary of the local unit cell model of the core to enter the local unit cell model of the core with acceleration. The acceleration is calculated from the total force of gravity superimposed on the buoyancy of the coolant. When any unit cell moves away from the boundary of the local unit cell model of the core, the unit cell that satisfies the given state re-enters the model from the corresponding boundary to simulate the continuous cyclic motion of the fuel elements in the reactor. S7: A CFD time step is used as a large time step. Each large time step contains multiple DEM time steps. In the DEM sub-loop of a large time step, the total force, movement speed, position of each unit cell, and discrete dust particles generated by collision and wear are simulated. The discrete dust particles include particle size and position. The size of the generated discrete particles and the particle position at the end of the sub-loop are determined according to the wear model, and the first result file is output. S8: Within the current large CFD time step, based on the cell position and force conditions in the first result file, as well as the size and position of discrete particles, set the geometric configuration and particle source terms for the CFD simulation to complete the heat transfer and flow CFD simulation of the model under the current state. S9: After the CFD simulation completes the current time step, output the fluid drag force and heat flux at each integration point on the surface of each unit cell, as well as the fluid velocity, pressure, temperature, lift and drag coefficient parameters at the location of each dust particle to the second result file; S10: For the DEM sub-cycle within the next large CFD time step, update the boundary conditions in the local unit cell model of the core according to the fluid drag force and the fluid parameters of the particles in the second result file. S11: Repeat S7 to S10 until the preset total simulation time is reached, then the calculation ends.

2. The wear dust generation and flow analysis method according to claim 1, characterized in that, The macroscopic physical property parameters mentioned in S1 include density, elastic modulus, Poisson's ratio, and thermal conductivity, and the contact model parameters include coefficient of restitution, static friction coefficient, and rolling friction coefficient.

3. The wear dust generation and flow analysis method of claim 1, wherein, The classic grain configuration described in S2 is either body-centered cubic or face-centered cubic.

4. The wear dust generation and flow analysis method of claim 1, wherein, The given state described in S6 is either an intact, unworn state or a state with the same degree of wear as the departing unit cell.

5. The wear dust generation and flow analysis method of claim 1, wherein, The acceleration described in S6 satisfies the following relationship: where g is the acceleration of gravity, is the coolant buoyancy, is the mass of the unit cell.

6. The wear dust generation and flow analysis method of claim 1, wherein, The wear model described in S7 determines the size of the generated discrete particles based on the collision force, relative sliding velocity, and contact stress between the unit cells.

7. The wear dust generation and flow analysis method of claim 1, wherein, The total force on each unit cell in S7 includes gravity, contact force, coolant drag force and damping force. The contact force is calculated using the Hertz-Mindlin model and the coolant drag force is calculated using the Ergun equation.

8. A wear dust generation and flow analysis apparatus characterized by, include: The first module is configured to establish a discrete element model of the fuel element, calibrate the parameters of the fuel element according to the macroscopic physical property parameters of the actual fuel element, determine the contact model parameter combination that conforms to the macroscopic physical property parameters of the fuel element as the parameter setting of the discrete element model of the fuel element, and set the discrete element model of the fuel element as a unit cell. The second module is configured to establish a local unit cell model of the reactor core. Its geometric dimensions are determined by the number of fuel element discrete element models filled with the fuel element volume fraction in the active region of the reactor core. The shape is a cube. The multiple fuel element discrete element models in the local unit cell model of the reactor core are arranged according to the classical grain configuration. A CFD model is established synchronously based on the geometric parameters and distribution positions. The first setting module is configured to set the cubic surface boundary conditions of the local unit cell model of the core, set the front and back, left and right boundaries as periodic boundary conditions, set the upper boundary as free and unconstrained, set the lower boundary as wall, and set the gravity, initial temperature, heat source of the unit cell, and boundary temperature of the local unit cell model of the core. The initialization module is configured to fill the local unit cell model of the reactor core with the required number of unit cells, and to complete the parameter settings of the contact model between the unit cells, thereby completing the initialization of the local unit cell model of the reactor core, that is, completing the DEM simulation settings and calculation initialization. The setting module is configured to set the CFD simulation of cooling flow within the local unit cell model of the reactor core: based on the actual operating parameters at a specified location in the active region of the reactor core, the temperature, flow rate and pressure boundary conditions of the coolant are set on the upper and lower surfaces of the local unit cell model of the reactor core, while the other surfaces maintain the same temperature, flow rate and pressure as the lower surface, thus completing the initialization of the flow simulation of the local unit cell model of the reactor core. The second setting module is configured to set a unit cell at the upper boundary of the local unit cell model of the core to enter the local unit cell model of the core with acceleration. The acceleration is calculated from the total force of gravity plus coolant buoyancy. When any unit cell moves away from the boundary of the local unit cell model of the core, the unit cell that satisfies the given state re-enters the model from the corresponding boundary to simulate the continuous cyclic movement of fuel elements in the reactor. The first simulation module is configured to use a CFD time step as a large time step, with multiple DEM time steps embedded within each large time step. In a DEM sub-loop of a large time step, the module simulates the total force, movement speed, position, and discrete dust particles generated by collision and wear on each unit cell. The discrete dust particles include particle size and position. The module determines the size of the generated discrete particles and the particle position at the end of the sub-loop based on the wear model and outputs a first result file. The second simulation module is configured to, within the current large CFD time step, set the geometric configuration and particle source terms of the CFD simulation based on the cell position and force conditions in the first result file, as well as the size and position of the discrete particles, and complete the heat transfer and flow CFD simulation of the model under the current state. The output module is configured to output the fluid drag force and heat flux at each integration point on the surface of each unit cell, as well as the fluid velocity, pressure, temperature, lift and drag coefficient parameters at the location of each dust particle, to the second result file after the CFD simulation completes the current time step. The update module is configured to update the boundary conditions in the local unit cell model of the core based on the fluid drag and fluid parameters of the particles in the second result file for the DEM sub-cycle within the next large CFD time step. The repeat module is configured to repeatedly run the first simulation module, the second simulation module, the output module, and the update module until the preset total simulation time is reached, at which point the calculation ends.

9. An electronic device, comprising: include: At least one processor; and a memory communicatively connected to the at least one processor; The memory stores instructions that can be executed by the at least one processor, which, when executed by the at least one processor, enables the at least one processor to perform the wear dust generation and flow analysis method according to any one of claims 1-7.

10. A non-transitory computer-readable storage medium having stored thereon computer instructions, wherein, The computer instructions are used to cause the computer to execute the wear dust generation and flow analysis method according to any one of claims 1-7.

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