Method, system and computer storage medium for determining operating parameters of a pool-type sodium-cooled fast reactor

Abstract

Embodiments of the present application relate to the technical field of computer-aided design, and particularly relate to a method and system for determining operating parameters of a pool-type sodium-cooled fast reactor and a computer storage medium. The method mainly comprises: determining physical property parameters of a full-core geometry model; dividing the full-core geometry model into different regions according to the physical property parameters, and dividing the calculation tasks of the different regions from the calculation level; using a distributed calculation manner, setting different nodes, and processing the calculation tasks in the different nodes, and setting to ensure continuous calculation; the calculation tasks of the different nodes are set to be synchronously processed in parallel, so that the neutron transport of the pool-type sodium-cooled fast reactor and the thermal-hydraulic multi-physics field are coupled and determined. Using the method can realize the collaborative parallel solution of the multi-physics field, is conducive to accurately simulating the coupling relationship between the devices in the reactor, realizes the accurate determination of the actual operating parameters of the fast reactor, and further improves the full-core simulation accuracy of the fast reactor.

Description

Technical Field

[0001] The embodiments of this application relate to the technical field of computer-aided design, specifically to a method, system, and computer storage medium for determining the operating parameters of a pool-type sodium-cooled fast neutron reactor. Background Technology

[0002] The statements herein are provided merely as background information in connection with this application and do not necessarily constitute prior art.

[0003] Pool-type sodium-cooled fast neutron reactors are one of the important reactor types in fourth-generation advanced nuclear energy systems. Before designing and building a fast reactor, it is necessary to conduct high-fidelity simulations of its physical processes, complex internal spatial flows, and heat transfer characteristics to achieve simulation of the pool-type sodium-cooled fast neutron reactor, thereby providing data support for the safety assessment and design optimization of the fast reactor.

[0004] To achieve high-precision simulation of pool-type sodium-cooled fast neutron reactors, it is necessary to accurately determine their operating parameters. However, the internal structure of pool-type sodium-cooled fast neutron reactors is complex, and existing simulation technologies are difficult to apply to them, resulting in a deficiency in meeting their high-fidelity simulation requirements. Summary of the Invention

[0005] A brief overview of this application is provided below to offer a basic understanding of certain aspects thereof. It should be understood that this overview is not an exhaustive summary of the application. It is not intended to identify key or essential parts of the application, nor is it intended to limit its scope. Its purpose is merely to present certain concepts in a simplified form as a prelude to the more detailed description that follows.

[0006] In a first aspect, embodiments of this application provide a method for determining the operating parameters of a pool-type sodium-cooled fast neutron reactor, comprising the following steps: S10: determining the structural parameters of the pool-type sodium-cooled fast neutron reactor; determining the full-core geometric model of the pool-type sodium-cooled fast neutron reactor based on the structural parameters; and determining the physical property parameters of the full-core geometric model based on the full-core geometric model; S20: dividing the full-core geometric model into different regions based on the physical property parameters, and dividing the computational tasks of different regions from a computational perspective; S30: adopting a distributed computing approach, setting up different nodes, with computational tasks processed on different nodes respectively, and setting up to ensure continuous computation; S40: setting the computational tasks of different nodes to be processed synchronously and in parallel, so that the neutron transport and thermal-hydraulic multiphysics fields of the pool-type sodium-cooled fast neutron reactor are coupled and determined; S50: determining the operating parameters of the pool-type sodium-cooled fast neutron reactor based on the processing results of step S40.

[0007] The method for determining the operating parameters of a pool-type sodium-cooled fast neutron reactor provided in this application determines the physical property parameters of the full-core geometric model of the pool-type sodium-cooled fast neutron reactor, and divides the full-core geometric model into different regions based on the physical property parameters. This first physically layers the core of the pool-type sodium-cooled fast neutron reactor, and then divides the computational tasks of different regions at the computational level. The computational tasks within each region are then divided into blocks, thereby decomposing the simulation computational task into multiple subtasks that can be executed in parallel. Furthermore, by setting different nodes, the computational tasks are processed on different nodes, and the computational tasks on different nodes are set to the same... Parallel processing is employed to couple and determine the neutron transport and thermal-hydraulic multiphysics fields of the pool-type sodium-cooled fast neutron reactor, thereby achieving collaborative parallel solution of the multiphysics fields. This facilitates accurate simulation of the coupling relationships between various devices within the pool-type sodium-cooled fast neutron reactor, enabling accurate determination of the actual operating parameters of the pool-type sodium-cooled fast neutron reactor, and ultimately improving the accuracy of the full-core simulation of the pool-type sodium-cooled fast neutron reactor. Compared to traditional simulation calculation techniques, this method transforms the full-core simulation of the fast reactor from a single-threaded sequential execution mode to a multi-task parallel mode, achieving efficient utilization of computing resources and effectively improving the efficiency of the full-core simulation of the pool-type sodium-cooled fast neutron reactor.

[0008] Secondly, embodiments of this application provide a system for determining the operating parameters of a pool-type sodium-cooled fast neutron reactor, comprising: a parameter determination module and a processor. The parameter determination module is configured to determine the structural parameters of the pool-type sodium-cooled fast neutron reactor, determine the full-core geometric model of the pool-type sodium-cooled fast neutron reactor based on the structural parameters, and determine the physical property parameters of the full-core geometric model based on the full-core geometric model. The processor is configured to divide the full-core geometric model into different regions based on the physical property parameters, and to divide the computational tasks of different regions from a computational perspective; it adopts a distributed computing approach, setting up different nodes, with computational tasks processed on different nodes, and is configured to ensure continuous computation; the computational tasks of different nodes are configured to be processed synchronously and in parallel, so that the neutron transport and thermo-hydraulic multiphysics fields of the pool-type sodium-cooled fast neutron reactor are coupled and determined; and the operating parameters of the pool-type sodium-cooled fast neutron reactor are determined based on the processing results.

[0009] Thirdly, embodiments of this application provide a computer storage medium having a computer program stored thereon, the computer program being executed by a processor to implement the method provided in any embodiment of the first aspect of this application. Attached Figure Description

[0010] Other objects and advantages of this application will become apparent from the following description of embodiments of this application with reference to the accompanying drawings, and will help to provide a comprehensive understanding of this application.

[0011] Figure 1This is a temperature distribution diagram of the fuel element at different axial positions in a pool-type sodium-cooled fast neutron reactor according to an embodiment of this application; Figure 2 This is a graph showing the time variation of the highest fuel element pellet temperature, the highest cladding temperature, and the highest outlet sodium temperature of a pool-type sodium-cooled fast neutron reactor under an unspecified displacement accident of the control rods, according to an embodiment of this application. Figure 3 This is a graph showing the changes in reactor relative power and relative flow rate over time for a pool-type sodium-cooled fast neutron reactor under an unspecified displacement accident of the control rods, according to an embodiment of this application. Figure 4 This is a graph showing the changes in the reactor relative power and relative flow rate over time for a pool-type sodium-cooled fast neutron reactor under a primary main pump shutdown accident, according to an embodiment of this application. Figure 5 This is a graph showing the time-varying maximum temperature of fuel element pellets, maximum cladding temperature, and maximum outlet sodium temperature of a pool-type sodium-cooled fast neutron reactor according to an embodiment of this application under a primary main pump shutdown accident.

[0012] It should be noted that the accompanying drawings are not necessarily drawn to scale, but are shown only in a schematic manner without affecting the reader's understanding. Detailed Implementation

[0013] Exemplary embodiments of this application will be described below with reference to the accompanying drawings. For clarity and brevity, not all features of actual implementations are described in the specification. However, it should be understood that many implementation-specific decisions must be made in the development of any such actual embodiment to achieve the developer's specific goals, such as complying with constraints related to the system and business, and these constraints may vary depending on the implementation. Furthermore, it should be understood that while development work can be very complex and time-consuming, such development work is merely a routine task for those skilled in the art who benefit from the content of this application.

[0014] It should also be noted that, in order to avoid obscuring this application with unnecessary details, only the equipment structure and / or processing steps closely related to the solution according to this application are shown in the accompanying drawings, while other details that are not closely related to this application are omitted.

[0015] Due to the complex internal structure of pool-type sodium-cooled fast neutron reactors (LCCs) and the large number of in-reactor components (including the core, internal shielding structure, main pumps, and intermediate heat exchangers), the structural asymmetry is significant, resulting in a massive simulation computation scale. Furthermore, because the various in-reactor components are interconnected, traditional simulation computations typically establish coupling relationships between the various algorithm modules to determine the actual operating parameters of the fast reactor. These modules are then executed sequentially in a single-threaded manner, meaning the next task only begins after the previous one has completely finished. This leads to low efficiency and low utilization of computational resources in fast reactor simulations, making it difficult to meet the high-precision simulation requirements of pool-type LCCs.

[0016] Based on this, embodiments of this application provide a method for determining the operating parameters of a pool-type sodium-cooled fast neutron reactor, which includes the following steps: S10: Determine the structural parameters of the pool-type sodium-cooled fast neutron reactor. Based on the structural parameters, determine the full-core geometric model of the pool-type sodium-cooled fast neutron reactor. Based on the full-core geometric model, determine the physical property parameters of the full-core geometric model.

[0017] S20: Based on physical property parameters, divide the entire core geometric model into different regions, and from a computational perspective, divide the computational tasks into different regions.

[0018] S30: It adopts a distributed computing approach, setting up different nodes, with computing tasks being processed on different nodes, and is configured to ensure continuous computing.

[0019] S40: The computational tasks of different nodes are set to be processed synchronously and in parallel, so that the neutron transport, thermal-hydraulic multiphysics fields of the pool-type sodium-cooled fast neutron reactor are coupled and determined.

[0020] S50: Based on the processing results of step S40, determine the operating parameters of the pool-type sodium-cooled fast neutron reactor.

[0021] The method for determining the operating parameters of a pool-type sodium-cooled fast neutron reactor provided in this application determines the physical property parameters of the full-core geometric model of the pool-type sodium-cooled fast neutron reactor, and divides the full-core geometric model into different regions based on the physical property parameters. This first physically layers the core of the pool-type sodium-cooled fast neutron reactor, and then divides the computational tasks of different regions at the computational level. The computational tasks within each region are then divided into blocks, thereby decomposing the simulation computational task into multiple subtasks that can be executed in parallel. Furthermore, by setting different nodes, the computational tasks are processed on different nodes, and the computational tasks on different nodes are set to the same... Parallel processing is employed to couple and determine the neutron transport and thermal-hydraulic multiphysics fields of the pool-type sodium-cooled fast neutron reactor, thereby achieving collaborative parallel solution of the multiphysics fields. This facilitates accurate simulation of the coupling relationships between various devices within the pool-type sodium-cooled fast neutron reactor, enabling accurate determination of the actual operating parameters of the pool-type sodium-cooled fast neutron reactor, and ultimately improving the accuracy of the full-core simulation of the pool-type sodium-cooled fast neutron reactor. Compared to traditional simulation calculation techniques, this method transforms the full-core simulation of the fast reactor from a single-threaded sequential execution mode to a multi-task parallel mode, achieving efficient utilization of computing resources and effectively improving the efficiency of the full-core simulation of the pool-type sodium-cooled fast neutron reactor.

[0022] In some embodiments, in step S10, the full-core geometric model of the pool-type sodium-cooled fast neutron reactor can be determined based on the material parameters and operating condition parameters of the pool-type sodium-cooled fast neutron reactor, so that by taking into account its materials and operating conditions, the determined full-core geometric model can accurately simulate the actual situation of the pool-type sodium-cooled fast neutron reactor.

[0023] In some embodiments, step S10 specifically includes the following steps: S11: Divide the full core geometry model. Use fine mesh for the critical core regions of the full core geometry model and coarse mesh for the non-critical core regions.

[0024] S12: Determine the correspondence between the mesh after division in step S11 and the physical regions of the reactor core.

[0025] S13: Determine the physical property parameters of the full core geometry model based on the correspondence.

[0026] In this embodiment, a hybrid meshing strategy of fine mesh in critical core regions and coarse mesh in non-critical regions is adopted to divide the entire core geometric model. This reduces the number of meshes while ensuring the accuracy of key parameters. Traditional 3D CFD numerical simulations typically involve tens of millions of meshes, while this embodiment reduces the number to thousands (approximately 8,000). This effectively reduces the scale of the simulation and the consumption of computing resources, decreases the burden on subsequent synchronous parallel processing tasks, and improves computational efficiency. Furthermore, by determining the correspondence between the divided meshes and the physical regions of the core, the physical property parameters of the entire core geometric model are determined. This allows the geometric model to be divided into different regions according to the physical property parameters, improving the consistency between the divided regions and the actual pool-type sodium-cooled fast neutron reactor.

[0027] In some embodiments, in step S11, the full core geometry model includes all core components such as the core fuel assemblies, internal shielding structure, main pumps, intermediate heat exchangers, independent heat exchangers, and refueling elevators. The critical core regions mainly include the fuel rod bundle region and the coolant channel region, while the non-critical core regions mainly include the outer shielding structure region of the reactor pool. The fine mesh size can be 0.1m, and the coarse mesh size can be 0.5m.

[0028] In some embodiments, in step S12, when determining the correspondence between the divided grid and the core physical region, the grid can be partitioned and numbered according to the core physical region, and the grids belonging to the same core physical region can be numbered with the same number.

[0029] In some embodiments, the physical property parameters of the determined full-core geometry model in step S13 may include geometric dimensions, material properties, and thermal parameters.

[0030] In some embodiments, step S20 specifically includes the following steps: S21: Based on the physical property parameters, the full core geometric model is divided into the core area, shielding area, coolant circulation area, and residual heat removal area, and each of the core area, shielding area, coolant circulation area, and residual heat removal area includes a calculation task.

[0031] S22: Divide the computational tasks into different regions and make the computational load in different regions tend to be balanced.

[0032] In this embodiment, the entire core geometry model is divided according to physical property parameters. First, the core of the pool-type sodium-cooled fast neutron reactor is divided into physical regions, with each region corresponding to a set of computational tasks. Then, the computational tasks within each physical region are further divided into blocks, resulting in a dual division of physical region layering and computational task block partitioning. This facilitates the decomposition of the core simulation task into multiple subtasks that can be executed independently and in parallel, and makes the computational load in different regions tend to be balanced, thereby balancing the allocation of computational tasks and improving the utilization rate of computing resources.

[0033] In some embodiments, in step S22, the computational task of each region can be divided into several computational sub-blocks according to the number of grids in each region of the divided core region, shielding region, coolant circulation region, and residual heat removal region, as well as the computational complexity, so as to balance the computational task of each region and achieve a more balanced computational load in different regions.

[0034] In some embodiments, during step S22, when dividing the computational tasks into different regions, the computational tasks in the core region can be divided according to the fuel assembly array, and the computational tasks in the coolant circulation region can be divided according to the flow path. This embodiment, considering the structural characteristics of a pool-type sodium-cooled fast neutron reactor, adopts a strategy of dividing the computational tasks in the core region and the coolant circulation region according to the fuel assembly array and flow path, respectively. This ensures that the resulting sub-blocks are spatially decoupled, reduces data exchange between sub-blocks, allows for independent parallel processing, and ensures clear computational logic and consistent solvers for each sub-block. This facilitates a balanced allocation of computational tasks and ensures efficient utilization of computational resources.

[0035] For example, in step S22, the calculation task of the core area is divided into 16 calculation sub-blocks according to the fuel assembly array, each sub-block containing 75 fuel assemblies; the calculation task of the coolant circulation area is divided into 8 calculation sub-blocks according to the flow path; the calculation task of the shielding area is divided into 4 calculation sub-blocks; and the calculation task of the residual heat removal area is divided into 4 calculation sub-blocks, for a total of 32 calculation sub-blocks decomposed into the core simulation task.

[0036] In some embodiments, step S30 specifically includes the following steps: S31: A distributed computing approach is adopted, with one master node and multiple slave nodes. The master node is configured to perform task scheduling and data management, while the slave nodes are configured to perform computing tasks.

[0037] S32: The master node and slave nodes are configured for load balancing calculation.

[0038] S33: The master node is configured to monitor the status of the slave nodes and collect the slave nodes' computing progress, resource utilization, and fault information in real time.

[0039] S34: When a slave node fails, its computing tasks are redistributed to other slave nodes to ensure the continuity of computing.

[0040] In this embodiment, the computational tasks of different regions of the core are processed through the above steps to build a distributed computing architecture. A load balancing computing method is adopted to achieve reasonable allocation of computational tasks in different regions. Furthermore, by setting the master node to monitor the status of slave nodes, the computational progress, resource utilization, and fault information of slave nodes are collected in real time. When a slave node fails, the computational tasks are redistributed to other slave nodes. This enables the master node to establish a node status monitoring mechanism, realize reasonable scheduling of computing resources, improve fault tolerance, avoid the risk of interruption of the entire simulation computation process due to the failure of a single node, and help ensure that the synchronous parallel computation of computing tasks can be carried out stably and continuously.

[0041] In some embodiments, in step S31, the number of slave nodes can be determined based on the total number of computational sub-blocks obtained from dividing the computational tasks of different regions in step S22. Specifically, the total number of computational sub-blocks is equal to the number of slave nodes.

[0042] For example, when the core simulation task is decomposed into 32 computational sub-blocks, one master node and 32 slave nodes are set up. Since the computational task in the core area is divided into 16 computational sub-blocks, which involves a large amount of computation, these 16 computational sub-blocks are assigned to slave nodes with stronger computing power.

[0043] In some embodiments, step S32 specifically includes the following steps: S321: Based on the computational sub-blocks obtained by dividing the computational tasks of different regions in step S22, determine the computational scope, dependencies, and data interaction requirements of each computational sub-block; S322: Based on the computational scope, dependencies, and data interaction requirements of each computational sub-block, determine the parallel task dependency graph; S323: Based on the parallel task dependency graph and the real-time load status of each slave node, allocate the computational sub-blocks to slave nodes to avoid slave nodes being overloaded or idle.

[0044] In some embodiments, step S323 further includes the steps of: determining the computational load, data volume, and node computing power of each computational sub-block; and using a dynamic load balancing algorithm to adjust the allocation of computational sub-blocks in real time based on the computational load, data volume, and node computing power of each computational sub-block; thereby achieving a reasonable allocation of computational tasks and avoiding overload or idleness of any slave node.

[0045] In some embodiments, step S40 specifically includes the following steps: S41: Each slave node is configured to receive and execute assigned computing tasks.

[0046] S42: For the core region, neutron transport is determined by using partitioned neutron transport equations for different regions.

[0047] S43: For the core area, coolant circulation area, and waste heat removal area, the thermal hydraulics are determined using one-dimensional fluid control equations.

[0048] S44: The master node and slave node are set to data interaction and data synchronization, so that the neutron transport, thermal-hydraulic multiphysics field of the pool-type sodium-cooled fast neutron reactor are coupled and determined.

[0049] In this embodiment, neutron transport is determined by using a partitioned neutron transport equation for the core region, and thermal hydraulics are determined by a one-dimensional fluid control equation for the thermal zone consisting of the core region, coolant circulation region, and residual heat removal region. This allows the three-dimensional structure to be expanded into one dimension, facilitating accurate simulation of the complex spatial flow and heat transfer characteristics of the core and effectively reducing computational complexity. Furthermore, by setting the master and slave nodes to interact and synchronize data, multiphysics can be solved collaboratively and in parallel on different nodes, enabling accurate simulation of the coupling relationships between various devices within the pool-type sodium-cooled fast neutron reactor. At the same time, key data synchronization between different slave nodes ensures the consistency of multiphysics coupling, which is beneficial for accurately determining the actual operating parameters of the pool-type sodium-cooled fast neutron reactor.

[0050] In some embodiments, step S42 specifically includes the following steps: each slave node assigned to the computational sub-block of the core region uses the partitioned neutron transport equation to solve each computational sub-block of the core region in parallel to obtain neutron flux and power distribution parameters; and determines neutron transport based on the neutron flux and power distribution parameters. For example, the partitioned neutron transport equation can be a partitioned point reactor equation.

[0051] In some embodiments, in step S42, a coarse-grid method can be used to reduce the computational load during the determination of neutron transport, while an interpolation algorithm can be used to ensure computational accuracy.

[0052] In some embodiments, step S43 specifically includes the following steps: each slave node assigned to the core region, coolant circulation region, and residual heat removal region uses a one-dimensional fluid control equation to solve the computational sub-blocks of the core region, coolant circulation region, and residual heat removal region in parallel to obtain thermal hydraulic parameters.

[0053] In some embodiments, in step S43, during the process of determining the thermal hydraulics, a multi-path unfolding method can be used to simulate the multi-path flow, pressure, temperature distribution and heat transfer characteristics of the coolant, which is beneficial to balance computational efficiency and accuracy.

[0054] In some embodiments, in step S44, the master node and slave nodes share a memory to enable data interaction for neutron transport and burnup calculations; the master node and slave nodes synchronize core data (e.g., core temperature, neutron flux) at predetermined time intervals via a high-speed communication protocol to achieve data synchronization. For example, the predetermined time interval is 0.5 seconds.

[0055] In some embodiments, step S50 specifically includes the following steps: S51: After each slave node completes the calculation, it uploads the calculation results to the master node.

[0056] S52: The master node performs data fusion on the calculation results of each slave node, and performs mesh stitching, parameter correction, and boundary condition consistency verification.

[0057] S53: Process the fused calculation results to determine the operating parameters of the pool-type sodium-cooled fast neutron reactor.

[0058] In this embodiment, the master node is used to unify and verify the calculation results of each slave node to eliminate numerical deviations that may occur at the boundaries during parallel computing. This ensures the integrity and consistency of the core simulation results. Furthermore, by processing the fused calculation results, more accurate actual operating parameters of the pool-type sodium-cooled fast neutron reactor are generated, thereby improving the full core simulation accuracy of the pool-type sodium-cooled fast neutron reactor.

[0059] In some embodiments, step S53 specifically includes the following steps: processing the fused calculation results to obtain simulation results of neutron flux distribution, temperature field distribution, coolant flow path, and flow rate distribution; outputting the simulation results in a visual form; and determining the operating parameters of the pool-type sodium-cooled fast neutron reactor based on the output results. In this embodiment, by outputting the processed simulation results in a visual form, the simulation results are transformed into intuitive images, providing direct and accurate data support for reactor design optimization and safety assessment, facilitating user analysis and decision-making.

[0060] The results of the operating parameters of the pool-type sodium-cooled fast neutron reactor determined by the method provided in the embodiments of this application are as follows: Figures 1-5 As shown. Figure 1 This paper illustrates temperature distribution diagrams at different axial positions of fuel elements in a pool-type sodium-cooled fast neutron reactor according to an embodiment of this application. Figure 1 In the diagram, the horizontal axis represents the location number of the active area of ​​the fuel element, where 1 is the outlet position and 10 is the inlet position. Figure 2 The diagram shows the time-varying maximum temperature of fuel element pellets, maximum cladding temperature, and maximum outlet sodium temperature of a pool-type sodium-cooled fast neutron reactor according to an embodiment of this application under an unspecified displacement accident of the control rod. Figure 3The diagram illustrates the time-varying relative power and relative flow rate of a pool-type sodium-cooled fast neutron reactor according to an embodiment of this application under an unspecified displacement accident of the control rods. Figure 4 The diagram illustrates the time-varying relative power and relative flow rate of a pool-type sodium-cooled fast neutron reactor according to an embodiment of this application under a primary main pump outage. Figure 5 The diagram illustrates the time-varying maximum fuel element pellet temperature, maximum cladding temperature, and maximum outlet sodium temperature of a pool-type sodium-cooled fast neutron reactor according to an embodiment of this application under a primary main pump outage. The operating parameters of the pool-type sodium-cooled fast neutron reactor determined using the method provided in the embodiments of this application are consistent with actual fast reactor conditions, demonstrating the effectiveness of this method in improving the accuracy of full-core simulation of pool-type sodium-cooled fast neutron reactors.

[0061] The method for determining the operating parameters of a pool-type sodium-cooled fast neutron reactor provided in the embodiments of this application can improve the computational efficiency by more than ten times compared with the traditional single-threaded sequential execution mode. The time consumption of fine simulation of the entire fast reactor core can be realized in real time, which fully meets the need for efficient updating of simulation results in the design and construction process of pool-type sodium-cooled fast neutron reactors.

[0062] Embodiments of this application also provide a system for determining the operating parameters of a pool-type sodium-cooled fast neutron reactor, comprising: a parameter determination module and a processor. The parameter determination module is configured to determine the structural parameters of the pool-type sodium-cooled fast neutron reactor, determine the full-core geometric model of the pool-type sodium-cooled fast neutron reactor based on the structural parameters, and determine the physical property parameters of the full-core geometric model based on the full-core geometric model. The processor is configured to divide the full-core geometric model into different regions based on the physical property parameters, and to divide the computational tasks of different regions from a computational perspective; it adopts a distributed computing approach, setting up different nodes, with computational tasks processed on different nodes, and is configured to ensure continuous computation; the computational tasks of different nodes are configured to be processed synchronously and in parallel, so that the neutron transport and thermo-hydraulic multiphysics fields of the pool-type sodium-cooled fast neutron reactor are coupled and determined; and the operating parameters of the pool-type sodium-cooled fast neutron reactor are determined based on the processing results.

[0063] The system for determining the operating parameters of a pool-type sodium-cooled fast neutron reactor provided in this application determines the physical property parameters of the full-core geometric model of the pool-type sodium-cooled fast neutron reactor. Based on these physical property parameters, the full-core geometric model is divided into different regions. This first physically layers the core of the pool-type sodium-cooled fast neutron reactor, and then, from a computational perspective, the computational tasks for different regions are divided into blocks. The computational tasks within each region are then partitioned, thereby decomposing the simulation computational task into multiple subtasks that can be executed in parallel. Furthermore, by setting different nodes, the computational tasks are processed on different nodes, and the computational tasks on different nodes are configured to perform the same tasks. Parallel processing is employed to couple and determine the neutron transport and thermal-hydraulic multiphysics fields of the pool-type sodium-cooled fast neutron reactor, thereby achieving collaborative parallel solution of the multiphysics fields. This facilitates accurate simulation of the coupling relationships between various devices within the pool-type sodium-cooled fast neutron reactor, enabling accurate determination of the actual operating parameters of the pool-type sodium-cooled fast neutron reactor, and ultimately improving the accuracy of the full-core simulation of the pool-type sodium-cooled fast neutron reactor. Compared to traditional simulation calculation techniques, this method transforms the full-core simulation of the fast reactor from a single-threaded sequential execution mode to a multi-task parallel mode, achieving efficient utilization of computing resources and effectively improving the efficiency of the full-core simulation of the pool-type sodium-cooled fast neutron reactor.

[0064] In some embodiments, the parameter determination module may also be configured to: divide the full core geometric model; use fine meshing for the critical core region of the full core geometric model and coarse meshing for the non-critical core region; determine the correspondence between the divided mesh and the core physical region; and determine the physical property parameters of the full core geometric model based on the correspondence.

[0065] Embodiments of this application also provide a computer storage medium having a computer program stored thereon, the computer program being executed by a processor to implement the method provided in any embodiment of the first aspect of this application.

[0066] Regarding the embodiments of this application, it should also be noted that, without conflict, the embodiments of this application and the features in the embodiments can be combined with each other to obtain new embodiments.

[0067] The above are merely specific embodiments of this application, but the scope of protection of this application is not limited thereto. The scope of protection of this application shall be determined by the scope of the claims.

Claims

1. A method for determining the operating parameters of a pool-type sodium-cooled fast neutron reactor, characterized in that, It includes the following steps: S10: Determine the structural parameters of the pool-type sodium-cooled fast neutron reactor, determine the full-core geometric model of the pool-type sodium-cooled fast neutron reactor based on the structural parameters, and determine the physical property parameters of the full-core geometric model based on the full-core geometric model. S20: Based on the physical property parameters, divide the full core geometric model into different regions, and from a computational perspective, divide the computational tasks of the different regions; S30: A distributed computing approach is adopted, with different nodes set up. The computing tasks are processed on different nodes, and the setup is configured to ensure continuous computing. S40: The computational tasks of the different nodes are set to be processed synchronously and in parallel, so that the neutron transport and thermal-hydraulic multiphysics fields of the pool-type sodium-cooled fast neutron reactor are coupled and determined. S50: Based on the processing results of step S40, determine the operating parameters of the pool-type sodium-cooled fast neutron reactor.

2. The method according to claim 1, characterized in that, Step S10 specifically includes the following steps: S11: Divide the full core geometric model, and use fine mesh for the critical core region of the full core geometric model and coarse mesh for the non-critical core region; S12: Determine the correspondence between the mesh generated in step S11 and the physical regions of the core; S13: Determine the physical property parameters of the full-core geometric model according to the correspondence.

3. The method according to claim 1, characterized in that, Step S20 specifically includes the following steps: S21: Based on the physical property parameters, the full core geometric model is divided into a core area, a shielding area, a coolant circulation area, and a residual heat removal area, and each of the core area, the shielding area, the coolant circulation area, and the residual heat removal area includes a calculation task; S22: Divide the computational tasks into different regions and make the computational load in different regions tend to be balanced.

4. The method according to claim 3, characterized in that, The computational tasks for the core region are divided according to the fuel assembly array. The computational tasks for the coolant circulation zone are divided according to the flow path.

5. The method according to claim 1, characterized in that, Step S30 specifically includes the following steps: S31: A distributed computing approach is adopted, with one master node and multiple slave nodes, wherein the master node is configured to perform task scheduling and data management, and the slave nodes are configured to execute the computing tasks; S32: The master node and the slave node are configured for load balancing calculation; S33: The master node is configured to monitor the status of the slave node and collect the slave node's computing progress, resource utilization, and fault information in real time; S34: When a slave node fails, its computing tasks are redistributed to other slave nodes to ensure the continuity of computing.

6. The method according to claim 1, characterized in that, Step S40 specifically includes the following steps: S41: Each slave node is configured to receive and execute the assigned computing task; S42: For the core region, neutron transport is determined by using partitioned neutron transport equations for different regions; S43: For the core area, coolant circulation area, and waste heat removal area, the thermal hydraulics are determined using one-dimensional fluid control equations; S44: The master node and slave node are set to interact and synchronize data, so that the neutron transport, thermal-hydraulic multiphysics field of the pool-type sodium-cooled fast neutron reactor are coupled and determined.

7. The method according to claim 1, characterized in that, The S50 step specifically includes the following steps: S51: After each slave node completes the calculation, it uploads the calculation results to the master node; S52: The master node performs data fusion on the calculation results of each slave node, and performs mesh stitching, parameter correction, and boundary condition consistency verification. S53: Process the fused calculation results to determine the operating parameters of the pool-type sodium-cooled fast neutron reactor.

8. A system for determining the operating parameters of a pool-type sodium-cooled fast neutron reactor, characterized in that, It includes: The parameter determination module is configured to determine the structural parameters of the pool-type sodium-cooled fast neutron reactor, determine the full-core geometric model of the pool-type sodium-cooled fast neutron reactor based on the structural parameters, and determine the physical property parameters of the full-core geometric model based on the full-core geometric model. The processor is configured to divide the full core geometry model into different regions based on the physical property parameters, and to perform computational tasks that divide the different regions from a computational perspective. A distributed computing approach is adopted, with different nodes set up, and the computing tasks are processed on different nodes to ensure continuous computing. The computational tasks of the different nodes are set to be processed synchronously and in parallel, so that the neutron transport, thermal-hydraulic multiphysics field of the pool-type sodium-cooled fast neutron reactor is coupled and determined. Based on the processing results, the operating parameters of the pool-type sodium-cooled fast neutron reactor were determined.

9. The system according to claim 8, characterized in that, The parameter determination module is set to, The full core geometry model is divided, and a fine mesh is used for the critical core region of the full core geometry model, while a coarse mesh is used for the non-critical core region. Determine the correspondence between the divided grid and the physical regions of the reactor core; Based on the correspondence, the physical property parameters of the full-core geometric model are determined.

10. A computer storage medium, characterized in that, It stores a computer program thereon, which is executed by a processor to implement the method as described in any one of claims 1-7.

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