Method and device for analyzing serious accident of nuclear reactor

Abstract

The invention provides a nuclear reactor serious accident analysis method and device, and relates to the field of nuclear control, the method is applied to electronic equipment, the electronic equipment comprises a plurality of calculation threads, and the method comprises the following steps: obtaining a plurality of simulation steps, each simulation step is used for simulating a simulation result of a nuclear reactor under the condition that the nuclear reactor is in an accident occurrence state; a physico-chemical reaction occurring in at least one component of the nuclear reactor; the multiple simulation steps are processed in parallel through the multiple calculation threads, multiple simulation results are obtained, each calculation thread is used for processing one simulation step, and each simulation result is used for representing the reaction result of the physical and chemical reaction occurring in the corresponding part. Therefore, the total calculation time required by accident simulation is shortened, and the calculation efficiency of nuclear reactor accident simulation is improved.

Description

Technical Field

[0001] This invention relates to the field of nuclear control, and more specifically to a method and apparatus for analyzing severe accidents in nuclear reactors. Background Technology

[0002] Severe accident prevention and mitigation measures are crucial considerations in nuclear reactor design, and severe accident analysis data serves as an important reference for designing these measures. Technicians can utilize severe accident analysis software to simulate and analyze the phenomena and processes of severe accidents, encompassing complex physicochemical behaviors such as pressurized water reactor thermal-hydraulic processes, core oxidation, degradation, molten material resetting, molten pool stratification, molten pool heat transfer, containment thermal-hydraulic processes, hydrogen combustion, molten material-concrete interactions, and fission product behavior.

[0003] However, the computational workload involved in simulating complex severe accident phenomena using severe accident analysis software is substantial. Therefore, improving the computational efficiency in nuclear reactor accident simulation is an urgent problem to be solved. Summary of the Invention

[0004] The purpose of this application is to provide a method and apparatus for analyzing severe nuclear reactor accidents, aiming to improve the computational efficiency during nuclear reactor accident simulation.

[0005] In a first aspect, embodiments of this application provide a method for analyzing severe accidents in nuclear reactors. The method is applied to an electronic device, which includes multiple computing threads. The method includes:

[0006] Multiple simulation steps are obtained, each of which is used to simulate the physicochemical reactions that occur in at least one component of the nuclear reactor under accident conditions.

[0007] Multiple simulation steps are processed in parallel using multiple computing threads to obtain multiple simulation results, wherein each computing thread is used to process one simulation step, and each simulation result is used to characterize the reaction result of the physicochemical reaction that occurs in the corresponding component.

[0008] In some implementations, the parallel processing of the multiple simulation steps using the multiple computing threads includes:

[0009] For each simulation step, a computing thread is used for processing. After processing for M preset time intervals, the processing result is determined as the simulation result of the simulation step, where M is a positive integer.

[0010] During the processing of the M preset time intervals in the simulation step, every preset time interval, the processing result obtained by the calculation thread is stored in the shared memory of the electronic device, and the processing result stored in other simulation steps is retrieved from the shared memory for updating the processing result of the next preset time interval.

[0011] In some implementations, for each simulation step, the sum of N processing cycles of the simulation step is equal to the preset time interval, where N is a positive integer and the processing cycle is the time interval between each update of the processing result of the simulation step.

[0012] In some implementations, the processing result includes sub-results with multiple dimensions;

[0013] The computing thread stores the processing results into the shared memory of the electronic device, including:

[0014] For each sub-result in the processing result, the calculation thread determines whether the sub-result is within a preset range of the corresponding dimension of the sub-result;

[0015] If the sub-result is within a preset range of the dimension corresponding to the sub-result, the sub-result is stored in the shared memory of the electronic device.

[0016] In some implementations, the plurality of simulation steps include a first simulation step, the first simulation step includes a plurality of first sub-steps, and the computation thread that processes the first simulation step is a first computation thread, the first computation thread including a plurality of first sub-threads;

[0017] The method of using multiple computing threads to process multiple simulation steps in parallel to obtain multiple simulation results includes:

[0018] During the first simulation step, multiple first sub-threads are used to process multiple first sub-steps in parallel to obtain multiple first sub-simulation results, and the multiple first sub-simulation results are used as the simulation results of the first simulation step, wherein each first sub-thread is used to process one first sub-step.

[0019] In some implementations, after obtaining multiple simulation results, the method further includes:

[0020] The annual average occurrence rate of the accident is obtained, and the probability that the nuclear reactor will experience at least one accident within a preset time period is determined using the Poisson model based on the annual average occurrence rate.

[0021] The severity level of the accident's consequences is determined based on the results of the multiple simulations.

[0022] The risk level of the accident is determined based on the probability and the severity level of the consequences, and recommended preventive measures for the accident are output based on the risk level.

[0023] In some implementations, after obtaining multiple simulation results, the method further includes:

[0024] The simulation results are visualized to obtain simulation images, which include images of the nuclear reactor under accident conditions.

[0025] Secondly, embodiments of this application provide a nuclear reactor severe accident analysis device, the device being applied to an electronic device, the electronic device including multiple computing threads, the device comprising:

[0026] An acquisition module is used to acquire multiple simulation steps, each of which is used to simulate the physicochemical reactions that occur in at least one component of the nuclear reactor under accident conditions.

[0027] The calculation module is used to process multiple simulation steps in parallel using multiple calculation threads to obtain multiple simulation results, wherein each calculation thread is used to process one simulation step, and each simulation result is used to characterize the reaction result of the physicochemical reaction that occurs in the corresponding component.

[0028] In some implementations, the computing module includes:

[0029] The first computing unit is used to process each simulation step using one computing thread, and after processing for M preset time intervals, the processing result is determined as the simulation result of the simulation step, where M is a positive integer.

[0030] The second calculation unit is used to, during the processing of the M preset time intervals of the simulation step, store the obtained processing results into the shared memory of the electronic device through the calculation thread at each preset time interval, and retrieve the stored processing results of other simulation steps from the shared memory for updating the processing results of the next preset time interval.

[0031] In some embodiments, the apparatus further includes:

[0032] An occurrence rate acquisition module is used to acquire the annual average occurrence rate of the accident, and to determine the probability that the nuclear reactor will experience at least one accident within a preset time period based on the annual average occurrence rate using a Poisson model.

[0033] The severity level determination module is used to determine the severity level of the consequences of the accident based on the multiple simulation results;

[0034] The risk level determination module is used to determine the risk level of the accident based on the probability and the severity level of the consequences, and output recommended prevention steps for the accident based on the risk level.

[0035] In this embodiment, by utilizing multiple computing threads in the electronic device to process multiple simulation steps in parallel, the physicochemical reactions occurring in various components of the nuclear reactor under accident conditions can be calculated in parallel to obtain multiple simulation results. This shortens the total computation time required for accident simulation, improves the computational efficiency of nuclear reactor accident simulation, and solves the problem of large computational load and low computational efficiency faced by electronic devices used for handling accident analysis processes when dealing with complex physicochemical phenomena such as pressurized water reactor thermal-hydraulics, core oxidation, degradation, molten material reset, molten pool stratification, molten pool heat transfer, containment thermal-hydraulics, hydrogen combustion, molten material-concrete interaction, and fission product behavior. It also provides fast and reliable accident simulation data for the design of severe accident prevention and mitigation measures. Attached Figure Description

[0036] Figure 1 This is a schematic flowchart of the nuclear reactor severe accident analysis method provided in the embodiments of this application;

[0037] Figure 2 This is another schematic flowchart of the nuclear reactor severe accident analysis method provided in the embodiments of this application;

[0038] Figure 3 This is another schematic flowchart of the nuclear reactor severe accident analysis method provided in the embodiments of this application;

[0039] Figure 4 This is a schematic diagram illustrating the relationship between the preset time interval and the processing cycle of the simulation steps provided in the embodiments of this application;

[0040] Figure 5 This is a schematic diagram of the structure of the nuclear reactor severe accident analysis device provided in the embodiments of this application;

[0041] Figure 6 This is a schematic diagram of the structure of the electronic device provided in the embodiments of this application. Detailed Implementation

[0042] The technical solutions of the embodiments of this application will be clearly described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application are within the scope of protection of this application.

[0043] The terms "first," "second," etc., used in the specification and claims of this application are used to distinguish similar objects and not to describe a specific order or sequence. It should be understood that such terms can be used interchangeably where appropriate so that embodiments of this application can be implemented in orders other than those illustrated or described herein, and the objects distinguished by "first," "second," etc., are generally of the same class and the number of objects is not limited; for example, a first object can be one or more. Furthermore, in the specification and claims, "and / or" indicates at least one of the connected objects, and the character " / " generally indicates that the preceding and following objects are in an "or" relationship.

[0044] Severe accident prevention and mitigation measures are crucial considerations in nuclear reactor design, and severe accident analysis data serves as an important reference for designing these measures. Technicians can utilize severe accident analysis software to simulate the phenomena and processes of severe accidents, encompassing complex physicochemical behaviors such as pressurized water reactor thermal-hydraulic processes, core oxidation, degradation, molten material resetting, molten pool stratification, molten pool heat transfer, containment thermal-hydraulic processes, hydrogen combustion, molten material-concrete interactions, and fission product behavior.

[0045] Currently, commonly used severe accident analysis software in this field includes ASTEC, MAAP, and MELCOR. These software programs involve the simulation of complex severe accident phenomena, have a large computational load, and use serial methods for calculation, resulting in low efficiency.

[0046] Therefore, improving the computational efficiency in nuclear reactor accident simulation is an urgent problem to be solved.

[0047] Based on this, the embodiments of this application provide a method and apparatus for analyzing severe nuclear reactor accidents, aiming to improve the computational efficiency during nuclear reactor accident simulation.

[0048] The method and apparatus for analyzing severe nuclear reactor accidents provided in this application will be described in detail below with reference to the accompanying drawings, through specific embodiments and application scenarios.

[0049] Please see Figure 1 This is a flowchart illustrating a severe nuclear reactor accident analysis method provided in an embodiment of this application. The method is applied to an electronic device, which includes multiple computing threads. Figure 1 As shown, the method for analyzing severe accidents in a nuclear reactor includes the following steps S100 to S200.

[0050] Step S100: Obtain multiple simulation steps, each simulation step being used to simulate the physicochemical reactions occurring in at least one component of the nuclear reactor under accident conditions.

[0051] In this step, the electronic equipment first acquires several simulation steps for accident simulation. Each simulation step corresponds to at least one component of the nuclear reactor that needs to be simulated under accident conditions, aiming to independently simulate the physicochemical reactions in that component or phenomenon. Specifically, each acquired simulation step may include:

[0052] Thermal-hydraulic simulation steps: These steps are used to simulate the thermal-hydraulic behavior within the main loop and containment of a nuclear reactor, such as flow distribution, two-phase heat transfer, wall heat transfer, core flow blockage, and the evolution of gas temperature, pressure, and composition within the containment (i.e., this simulation step is used to simulate the physicochemical reactions within the main loop and containment of a nuclear reactor).

[0053] Core melting simulation steps: used to simulate the degradation and melting process of the reactor core under severe accident conditions, including core heat exchange, zirconium cladding oxidation, chemical reactions and phase transitions, molten material migration and stratification, etc. (that is, this simulation step is used to simulate the physicochemical reactions of the reactor core).

[0054] Lower head simulation step: used to simulate the behavior of the molten pool in the lower head region of the pressure vessel, such as the repositioning of the molten material at the lower head position, the reaction and stratification of the molten material with the metal, heat transfer, and damage and failure of the lower head (i.e., this simulation step is used to simulate the physicochemical reactions in the lower head region of the pressure vessel of a nuclear reactor).

[0055] Containment Phenomenon Simulation Steps: These steps simulate the generation and combustion of hydrogen within the containment, the elimination of hydrogen by the hydrogen recombination device, the interaction between the molten material and the containment concrete, and direct heating of the containment (i.e., these simulation steps simulate the physicochemical reactions within the containment of a nuclear reactor).

[0056] Source term simulation step: used to simulate the behavior of radioactive source terms, including the migration process of fission products (such as iodine, cesium, strontium, etc.) from the reactor core into the coolant, water pool and aerosol after the fuel cladding is damaged, as well as the changes in chemical speciation in water and aerosol condensation and leaching (that is, this simulation step is used to simulate the physicochemical reactions of fuel rods or fuel assemblies and their cladding in the reactor core).

[0057] Each simulation step can independently define the type of physicochemical reaction to be simulated for the corresponding nuclear reactor components (such as the core, containment vessel, and main loop, etc.) (e.g., two-phase flow heat transfer, oxidation reaction, phase change melting, hydrogen generation and combustion, aerosol migration, etc.), the type of boundary conditions (e.g., flow rate, temperature, pressure input, or chemical component concentration), and the content of the output simulation results (e.g., temperature profile, molten pool size, hydrogen concentration, radioactive emissions, etc.).

[0058] For example, suppose one of the simulation steps acquired by the electronic equipment is a "thermal-hydraulic simulation step". This simulation step is used to simulate the two-phase flow heat transfer and wall heat transfer processes in the nuclear reactor main loop and containment during a reactor power outage accident. Specifically, the components involved in this simulation step are the reactor main loop and the containment; the simulation content includes calculating the coolant flow rate change, two-phase flow heat transfer, core perimeter wall heat transfer, and pressure-temperature evolution within the containment after the accident; the output simulation results are as follows: "At 2000s, the main loop outlet temperature reaches 1200K; at 5000s, the pressure within the containment rises to 0.5MPa".

[0059] Step S200: Multiple simulation steps are processed in parallel using multiple computing threads to obtain multiple simulation results. Each computing thread is used to process one simulation step, and each simulation result is used to characterize the reaction results of the physicochemical reactions that occur in the corresponding component.

[0060] After completing the acquisition of the simulation steps in step S100, the electronic device will allocate a computing thread for each simulation step. All computing threads will execute their respective simulation steps in parallel, and finally produce their respective simulation results.

[0061] Figure 2 This is another schematic flowchart of the nuclear reactor severe accident analysis method provided in the embodiments of this application, please refer to it as well. Figures 1-2 Specifically, the electronic equipment can map the thermal-hydraulic simulation steps, core melting simulation steps, lower head simulation steps, containment phenomenon simulation steps, and source term simulation steps obtained in step S100 to threads 1 to 5 respectively, and process their respective simulation tasks in parallel:

[0062] Thread 1 independently executes the thermal-hydraulic simulation steps and outputs simulation results such as "core outlet temperature of 1200K at 2000s and containment pressure of 0.5MPa at 5000s".

[0063] Thread 2 independently executes the core melting simulation step and outputs simulation results such as "core melting begins at 4800s and melt pool size and temperature distribution (diameter 0.8m, height 0.5m, temperature 2900K) at 5500s".

[0064] Thread 3 independently executes the lower head simulation step and outputs simulation results such as "layering information of the molten pool at the lower head at 6100s (bottom layer is a zirconium-uranium mixture at 3100K, top layer is an oxide with a thickness of 0.1m)".

[0065] Thread 4 independently executes the containment phenomenon simulation step and outputs simulation results such as "average hydrogen concentration of 8% between 6200s and 7000s, and concrete erosion depth of 0.15m at 7000s".

[0066] Thread 5 independently executes the source term simulation step, outputting simulation results such as "Iodine-131 escape start point at 5500s, 30% of the total core escape at 7000s, and environmental release at 9000s is only 5% of the escaped amount".

[0067] Each computation thread can exchange boundary data in shared memory (e.g., pressure and temperature output from thermal-hydraulic systems for the containment phenomenon simulation step or core meltdown simulation step to read), ensuring consistent boundary conditions for each simulation step during parallel execution. Through the above parallel computation, each thread simultaneously completes the physicochemical reaction simulation of its respective simulation step, significantly shortening the overall computation time and outputting complete and detailed accident simulation results data.

[0068] Those skilled in the art will understand that the simulation results output by each computing thread are not limited to numerical form. The simulation results can be line graphs, heat maps, point cloud maps, dynamic animations representing visually perceptible phenomena of components, and other forms.

[0069] Through steps S100-S200, the electronic equipment utilizes multiple computing threads to process multiple simulation steps in parallel, enabling parallel calculation of the physicochemical reactions occurring in various components of the nuclear reactor under accident conditions to obtain multiple simulation results. This significantly shortens the total computation time required for accident simulation, improves the computational efficiency of nuclear reactor accident simulation, and solves the problems of large computational load and low computational efficiency faced by electronic equipment used for handling accident analysis processes when dealing with complex physicochemical phenomena such as pressurized water reactor thermal-hydraulic processes, core oxidation, degradation, molten material reset, molten pool stratification, molten pool heat transfer, containment thermal-hydraulic processes, hydrogen combustion, molten material-concrete interaction, and fission product behavior. It also provides fast and reliable accident simulation data for the design of severe accident prevention and mitigation measures.

[0070] Figure 3 This is another schematic flowchart of the nuclear reactor severe accident analysis method provided in the embodiments of this application, please refer to it as well. Figures 1-3 In some implementations, multiple computational threads are used to process multiple simulation steps in parallel, including:

[0071] For each simulation step, a computing thread is used for processing. After processing for M preset time intervals, the processing result is determined as the simulation result of the simulation step, where M is a positive integer.

[0072] During the processing of the M preset time intervals in the simulation steps, at each preset time interval, the processing result obtained is stored in the shared memory of the electronic device through the calculation thread, and the processing result stored in other simulation steps is retrieved from the shared memory for updating the processing result of the next preset time interval.

[0073] In this embodiment, when multiple simulation steps are processed in parallel using multiple computing threads, a computing thread is allocated to each simulation step for independent computation, and the process iterates cyclically within multiple preset time intervals. Specifically, each computing thread starts from the first preset time interval, calculates the state evolution of the component within that time interval based on the initial boundary conditions and physicochemical equations defined in the corresponding simulation step, and stores the calculated processing results (such as key physical quantities like temperature, pressure, melting rate, hydrogen concentration, and radioactive release rate) into the shared memory of the electronic device at the end of the preset time interval.

[0074] Simultaneously, this computation thread also reads the processing results stored by other simulation step threads from shared memory at the end of the same preset time interval. It uses this boundary data from other modules as input for its own calculations in the next preset time interval to update the boundary conditions of this module and continue the simulation. This cycle repeats until, after M preset time intervals, each computation thread has accumulated M external iterations, simulating the physicochemical reactions at each stage of the entire accident time evolution.

[0075] Those skilled in the art will understand that the value of M for each computation thread, i.e., each simulation step, may be consistent or inconsistent, and can be adaptively set according to the processing accuracy requirements of each simulation step or the overall processing accuracy requirements.

[0076] In this way, by processing each simulation step in parallel in multiple computing threads and exchanging boundary data through shared memory at each preset time interval, the co-simulation of the physicochemical reactions of each component during the accident was realized, thereby improving computational efficiency and ensuring the consistency and accuracy of simulation results.

[0077] For example, assume that the parallel simulation steps include thermal-hydraulic simulation, core meltdown simulation, and containment phenomenon simulation, and set M = 3 preset time intervals, corresponding to three global synchronization times T0→T1, T1→T2, and T2→T3 (T n →T n+1 );

[0078] Within the first preset time interval (T0→T1):

[0079] The calculation thread of the thermal-hydraulic simulation step solves the coupling equation between the two-phase flow in the main loop and the pressure-temperature in the containment based on the boundary conditions at time T0 (e.g., initial coolant flow rate of 5000 kg / s and core inlet temperature of 300 °C). The calculation results at time T1 are obtained as core outlet temperature of 800 K and pressure of 10 MPa. This result is then written to shared memory.

[0080] The calculation thread for the core melting simulation step also calculates the local oxidation rate of the core and whether melting has started within this interval based on the boundary conditions at time T0. It finds that no melting has occurred at time T1, but the cladding temperature has reached 1200K. The processing results are then written to shared memory.

[0081] The calculation thread in the containment phenomenon simulation step also calculates the hydrogen generation rate and the pressure change inside the containment at time T1 based on the boundary conditions at time T0, obtaining a hydrogen concentration of 1% and a pressure of 0.15 MPa at time T1, and writes the processing results into shared memory.

[0082] During the second preset time interval (T1→T2):

[0083] The calculation thread of the thermal-hydraulic simulation step reads the cladding temperature of 1200K at time T1 written in the core melting simulation step and the containment internal pressure of 0.15MPa at time T1 written in the containment phenomenon simulation step from the shared memory. Using these boundary data, the two-phase flow heat transfer boundary conditions are adjusted, and the core outlet temperature at time T2 is calculated to increase to 1200K and the pressure decreases to 8MPa. The results are then written to the shared memory.

[0084] The calculation thread for the core melting simulation step reads the newly written core outlet temperature (800 K) and pressure (10 MPa) at time T1 from the thermal-hydraulic simulation step, as well as the heat transfer coefficient between the cladding and coolant (210 W / cm·℃). Based on this, it calculates the local melting area of ​​0.2 m² at time T2. 2 1. Form the initial melt; 2. Write the result of this process to shared memory;

[0085] The calculation thread for the containment phenomenon simulation step reads the temperature of 350K and pressure of 0.15MPa inside the containment at time T1 written in the thermal-hydraulic simulation step, as well as the heat flux of the molten material generated during T1→T2 written in the core melting simulation step. It calculates that at time T2, the hydrogen concentration rises to 3% and the molten material initially contacts the concrete but has not yet penetrated, and writes it into shared memory.

[0086] During the third preset time interval (T2→T3):

[0087] The calculation thread of the thermal-hydraulic simulation step extracts the local melt information (temperature about 2400K, mass about 50kg) output from the core melting simulation step at time T2 and the containment pressure of 0.2MPa output from the containment phenomenon simulation step from the shared memory, updates the boundary conditions of the thermal-hydraulic equation, and calculates until the core outlet temperature rises to 1500K and the pressure continues to drop to 5MPa at time T3, and writes the results back to the shared memory;

[0088] The calculation thread for the core meltdown simulation step uses the main loop temperature drop and containment pressure of 0.2 MPa during the T2→T3 period written in the thermal-hydraulic simulation step, as well as the hydrogen concentration of 3% at time T2 written in the containment phenomenon simulation step, to calculate the large-area core meltdown within this interval. The result is a melt pool diameter of 0.8 m, a height of 0.5 m, and a temperature of 2900 K at time T3. The processing results are then written to shared memory.

[0089] The calculation thread of the containment phenomenon simulation step reads the containment internal temperature of 450K and pressure of 0.2MPa updated by the thermal-hydraulic simulation step during T2→T3, as well as the heat flux of the molten material output by the core melting simulation step. It calculates that at time T3, the hydrogen concentration reaches 8%, a brief oxygen enrichment risk occurs, the concrete erosion depth reaches 0.15m, and the local pressure of the containment reaches 0.35MPa. The processing results are then written to shared memory.

[0090] Thus, after cyclic processing for M=3 preset time intervals, each computation thread has completed iterative calculations within three time periods, and its final processing result at time T3 is uniformly determined as the simulation result of that simulation step. For example, the simulation result of the thermal-hydraulic simulation step is a core outlet temperature of 1500K and a pressure of 5MPa at time T3; the simulation result of the core melting simulation step is a melt pool diameter of 0.8m, a height of 0.5m, and a temperature of 2900K at time T3; and the simulation result of the containment phenomenon simulation step is a hydrogen concentration of 8% and a concrete erosion depth of 0.15m at time T3. By continuously storing intermediate processing results into shared memory at each preset time interval and reading the results of other simulation steps in real time, dynamic updates of boundary conditions and collaborative simulation are achieved between simulation steps. This ensures both the efficiency of parallel computing and the coupling and temporal consistency of the simulation results of the physicochemical reactions of each component.

[0091] Figure 4 This is a schematic diagram illustrating the relationship between the preset time interval and the processing cycle of the simulation steps provided in the embodiments of this application, as shown below. Figure 4 As shown, in some implementations, for each simulation step, the sum of N processing cycles of the simulation step is equal to a preset time interval, where N is a positive integer and the processing cycle is the time interval between each update of the processing result of the simulation step.

[0092] In this embodiment, each simulation step may have a different internal processing cycle, and the processing result of the simulation step is updated once every processing cycle.

[0093] To ensure consistent boundary condition exchange and synchronous updates across all simulation steps on the global timeline, for each simulation step, assuming a preset time interval has been set, the sum of the N processing cycles of that simulation step—that is, the total duration of the N processing cycles—must equal the aforementioned preset time interval. The lengths of the N processing cycles can vary. In other words, the preset time interval must be set such that the sum of the N processing cycles equals the preset time interval.

[0094] Those skilled in the art will understand that the value of N for each computation thread, i.e. each simulation step, may be inconsistent and can be adaptively set according to the processing accuracy requirements of each simulation step or the overall processing accuracy requirements.

[0095] Specifically, the electronic device first determines the preset time interval (T0→T1) for data exchange. Then, each simulation step (computation thread) performs iterative calculations according to its own calculation logic, accumulating the processing cycles advanced in each iteration. For example, for the first simulation step, it advances by a1 s in the first processing cycle (the first processing cycle is a1 s), by a2 s in the second processing cycle (the second processing cycle is a2 s), and by an s in the Nth processing cycle (the Nth processing cycle is an s). a1+a2+…an=T1-T0, and a1, a2,…an can be different. Thus, this simulation step completes the calculation of a preset time interval (T0→T1) through N processing cycles (i.e., N processing result updates). The processing result obtained from the Nth update is stored in the shared memory mentioned above, and the latest result written by other threads at time T1 is read from the shared memory to update the boundary conditions for the next round. This ensures that each simulation step can periodically synchronize and coordinate simulation when running at different clock cycles.

[0096] For example, in an accident simulation scenario:

[0097] The state of the nuclear reactor at time 0s is obtained, and a preset time interval of 10s is set. In each simulation step (computation thread), iterative calculations are performed according to their respective calculation logic, and data exchange occurs at time 10s.

[0098] The thermal-hydraulic simulation step involves 20 processing cycles of calculation, completing a 10-second calculation, which is used to calculate the main loop flow rate, core temperature, and containment pressure.

[0099] The core melting simulation step involves 15 processing cycles of calculation, completing a 10-second calculation, to simulate the core oxidation and melting process.

[0100] The lower head simulation step involves 10 processing cycles of calculation, completing a 10-second calculation to simulate the resetting and stratification of the molten material in the lower head region.

[0101] The containment phenomenon simulation, through 12 processing cycles, completes a 10-second calculation, used to calculate hydrogen generation, combustion, and the interaction with concrete.

[0102] The source term simulation step involves 16 processing cycles to complete a 10-second calculation, used to simulate the escape of fission products from the fuel cladding and the migration of aerosols.

[0103] The calculation thread of each simulation step writes its calculation results at time 10s (e.g., core outlet temperature of 1250K and containment pressure of 0.6MPa in the thermal-hydraulic simulation step, molten pool size of 0.7m×0.4m in the core melting simulation step, hydrogen concentration of 5% and concrete erosion depth of 0.1m in the containment phenomenon simulation step, and cumulative iodine-131 escape of 20% in the source term simulation step, etc.) into shared memory.

[0104] At the same time, each computing thread reads the latest boundary data written by other computing threads at the 10th second from the shared memory, and uses this data as the input boundary for their new round of computing in the next stage (10s→20s);

[0105] In the next 10-second interval, the thermal-hydraulic simulation step will iterate 20 times, the core melting simulation step will iterate 15 times, the lower head simulation step will iterate 10 times, the containment phenomenon simulation step will iterate 12 times, and the source term simulation step will iterate 18 times, and so on until the simulation ends.

[0106] In some implementations, the processing results include sub-results with multiple dimensions;

[0107] The computation thread stores the processing results into the shared memory of the electronic device, including:

[0108] For each sub-result in the processing result, the calculation thread determines whether the sub-result is within the preset range of the corresponding dimension of the sub-result;

[0109] If the sub-result is within a preset range of the corresponding dimension of the sub-result, the sub-result is stored in the shared memory of the electronic device.

[0110] In this implementation, each computation thread, after completing the calculations for its corresponding simulation step, obtains a multi-dimensional processing result. Each dimension's sub-result can correspond to a specific physical quantity (e.g., temperature, pressure, flow rate, hydrogen concentration, molten pool size, radionuclide emission rate, etc.). Before writing these processing results into the shared memory of the electronic device, the computation thread verifies each sub-result one by one—that is, compares the sub-result with its corresponding preset range. If a sub-result is within (or falls within) the preset range of that dimension, it is written into the shared memory; otherwise, the computation thread skips the sub-result and does not store it. The purpose of this is twofold: firstly, to filter out outliers that exceed reasonable or safe ranges, preventing erroneous data from interfering with the boundary conditions of other simulation steps; and secondly, to only pass the key indicators of interest to other threads for the next step of collaborative simulation.

[0111] For example, taking the calculation of a preset time interval in the thermal-hydraulic simulation step as an example, the processing result of this thread includes three sub-results: core outlet temperature (unit: K), main loop pressure (unit: MPa), and coolant flow rate (unit: kg / s). Assume the preset ranges for each dimension are as follows:

[0112] Temperature range: [300K, 3000K];

[0113] Pressure range: [0.1MPa, 20MPa];

[0114] Flow rate range: [0 kg / s, 10000 kg / s];

[0115] At the end of a certain preset time interval, the sub-results calculated by the thermal-hydraulic simulation step are as follows:

[0116] Core outlet temperature = 1200K;

[0117] Main circuit pressure = 25 MPa;

[0118] Coolant flow rate = 6000 kg / s;

[0119] The calculation thread first checks whether the core outlet temperature of 1200K is within the range of [300K, 3000K]. The result is "within the range", so the temperature of 1200K is stored in shared memory.

[0120] Then, the system checks whether the main circuit pressure of 25MPa is within the range of [0.1MPa, 20MPa], and the result is "out of range". Therefore, this sub-result is skipped and 25MPa is not written to the shared memory.

[0121] Finally, the check was performed to see if the "coolant flow rate of 6000 kg / s is within the range of [0 kg / s, 10000 kg / s]", and the result was "within the range". Therefore, the flow rate of 6000 kg / s was written to the shared memory.

[0122] Through the above filtering, when other computing threads read shared memory in the next time interval, they can only obtain the two key boundary parameters within the preset range: core outlet temperature of 1200K and coolant flow rate of 6000kg / s, without being affected by obvious numerical anomalies such as 25MPa.

[0123] In some implementations, the multiple simulation steps include a first simulation step, the first simulation step includes multiple first sub-steps, and the computation thread that processes the first simulation step is a first computation thread, which includes multiple first sub-threads.

[0124] Multiple simulation steps are processed in parallel using multiple computation threads to obtain multiple simulation results, including:

[0125] During the first simulation step, multiple first sub-threads are used to process multiple first sub-steps in parallel to obtain multiple first sub-simulation results, and these multiple first sub-simulation results are used as the simulation results of the first simulation step. Each first sub-thread is used to process one first sub-step.

[0126] In this embodiment, all simulation steps include a simulation step referred to as the first simulation step, and there can be multiple first simulation steps. Each first simulation step is further subdivided into multiple first sub-steps, and is handled entirely by a first computation thread. During execution, the first computation thread does not perform serial computation in a single thread like other simulation steps; instead, it further creates multiple first sub-threads and assigns the first sub-steps to these sub-threads for parallel processing.

[0127] Specifically, after receiving its corresponding first simulation step, the first computation thread first divides the step into several predefined first sub-steps. Each first sub-step corresponds to an independent computational task within the simulation step (e.g., solving for the state of a set of control volumes or mesh elements). Then, the first computation thread starts several first sub-threads (the number of which can be determined based on the number of cores in the electronic device or the OpenMP configuration), allowing each first sub-thread to independently process one first sub-step and generate the corresponding first sub-simulation result after its respective computation is completed. When all first sub-threads have completed their respective tasks, the first computation thread aggregates these first sub-simulation results to obtain the final simulation result of the entire first simulation step.

[0128] For example, the thermal-hydraulic simulation step is the first simulation step, which requires solving the thermal-hydraulic equations for hundreds of control volumes (including coolant channels for each fuel assembly around the reactor core and control volume regions inside the containment). The thermal-hydraulic simulation step is divided into three first sub-steps, each responsible for solving the hydrodynamic and energy conservation equations for a set of control volumes:

[0129] First sub-step A: Solve the mass conservation, momentum conservation, and energy conservation equations for the 1st to 50th control volumes in the thermal-hydraulic simulation domain;

[0130] First sub-step B: Solve the equations for control volumes 51 to 100 in the thermal-hydraulic simulation domain;

[0131] First sub-step C: Solve the equations for the 101st to 150th control volumes in the thermal-hydraulic simulation domain;

[0132] At this point, the first computing thread will activate three first sub-threads on the electronic device to perform parallel calculations for the three control groups A, B, and C respectively:

[0133] First sub-thread 1.1: Independently obtain the boundary conditions given in the current global time step (such as the inlet flow rate, cladding temperature, upstream pressure, etc. of the previous time step), use the convective heat transfer and two-phase flow model to calculate the pressure, temperature, and mass flow rate distribution of the 1st to 50th control volumes in this time step, and output the first sub-simulation result A;

[0134] First sub-thread 1.2: Simultaneously reads the boundary conditions of the same global time step from shared memory, solves the same mass-momentum-energy equation for control volumes 51 to 100, and outputs the first sub-simulation result B;

[0135] First sub-thread 1.3: Within the same preset time interval, independently complete the simulation of control bodies 101 to 150, and output the first sub-simulation result C;

[0136] Once the three first sub-threads have completed their respective calculations, the first calculation thread will collect the results of the three first sub-simulations (A, B, and C), summarize and integrate the confirmed pressure, temperature, and flow distributions of the control bodies, and form the final simulation results of the complete thermal-hydraulic simulation step (e.g., at time 2000s, the entire core outlet temperature segment, the main loop inlet pressure segment, and the pressure-temperature field distribution inside the containment). Through this first calculation thread + multiple first sub-thread nested parallel strategy, the thermal-hydraulic simulation step can efficiently solve numerical equations in parallel across multiple control bodies, significantly reducing the computation time of a single simulation step, while ensuring the consistency of boundary conditions between sub-steps.

[0137] In some implementations, after obtaining multiple simulation results, the method further includes:

[0138] Obtain the annual average occurrence rate of accidents, and use the Poisson model based on the annual average occurrence rate to determine the probability that a nuclear reactor will experience at least one accident within a preset time period.

[0139] The severity level of the accident's consequences was determined based on multiple simulation results;

[0140] The risk level of an accident is determined based on the probability and severity of its consequences, and recommended preventative measures are then output based on the risk level.

[0141] In this embodiment, after the simulation steps are performed in parallel and multiple simulation results are obtained, the electronic equipment first obtains the annual average occurrence rate λ of the simulated accident, and then uses the Poisson model to calculate the probability P = 1 - e^(-λ / t) of the nuclear reactor occurring at least once within a preset time period t based on the annual average occurrence rate. -λt Subsequently, the electronic equipment compares multiple simulation results (such as the degree of core meltdown, the size of the molten pool, the hydrogen concentration in the containment, and the amount of radioactive material released) with pre-set consequence thresholds to determine the severity level of the accident (e.g., "minor," "moderate," "severe," "catastrophic," etc.). Next, the probability P and the severity level are mapped to a pre-set risk matrix or risk coordinate system to ultimately derive the risk level of the accident (e.g., "low risk," "moderate risk," "high risk," "extremely high risk"). Finally, based on the calculated risk level, corresponding recommended preventative measures are automatically output to the user. For example, in a high-risk situation, it is recommended to "prioritize starting the backup diesel generator and activating the passive cooling system," and in a moderate-risk situation, it is recommended to "enhance the efficiency of the hydrogen recombiner and add a radioactive filtration device."

[0142] For example, assuming the simulated accident involves a complete loss of power within the reactor core, the simulation results obtained after parallel computation are as follows: maximum core meltdown rate of 35%, melt pool diameter of 0.8 m, height of 0.5 m, peak hydrogen concentration in the containment of 8%, and 30% of the total iodine-131 escaping from the core by 7000 s. The annual average incidence rate of this accident, λ, obtained from electronic equipment, is 1.2 × 10⁻¹⁰. -5 / year, and with t=10 years as the preset time period, then according to the Poisson model, P=1–e^(–1.2×10 -5 (×10)≈1.20×10 -4(Approximately 0.012%), mapped to "very unlikely". Combined with the simulation results showing a hydrogen concentration as high as 8%, containment concrete erosion of 0.15m, and a significant amount of iodine-131 escaping, the accident consequence can be determined as "serious consequence". After locating "very unlikely" and "serious consequence" in the risk matrix, the accident is classified as "medium risk". For the "medium risk" level, the electronic equipment automatically recommends the following preventative measures: activating the backup diesel generator, improving the operating efficiency of the hydrogen recombiner, installing a high-efficiency radioactive aerosol filter at the containment vent, and regularly checking the emergency cooling water supply capacity of the control system.

[0143] In some implementations, after obtaining multiple simulation results, the method further includes:

[0144] Multiple simulation results are visualized to obtain simulation images, including images of the nuclear reactor under accident conditions.

[0145] In this embodiment, after each parallel computing thread obtains multiple simulation results such as thermal-hydraulic, core melting, lower head, containment phenomena, and source terms, the system will convert these numerical data into visual images to intuitively show the evolution of key physical fields and structural responses of the nuclear reactor under accident conditions. These simulated images may include, but are not limited to: contour maps or chromatograms of temperature, pressure, and flow rate in the core and main loop, used to show the spatial distribution of core outlet temperature (e.g., 1200K at 2000s, reaching 1500K at 5000s) and main loop pressure at various time points; three-dimensional reconstructed core melt pool topography maps, used to show the 0.8m diameter and 0.5m height melt pool formed at 5500s and its internal temperature distribution (up to approximately 2900K); two-dimensional profile thermal maps of hydrogen concentration and pressure inside the containment, such as the concentration cloud map corresponding to a hydrogen concentration reaching 8% at a certain location during 6200s–7000s, and a local melting profile map when the concrete melting depth reaches 0.15m; and the distribution map of the cumulative emission of radioactive source terms in the radial direction at different times (e.g., 7000s, 9000s) or the concentration contour surface in the pool and aerosol. All these visualization results originate from the simulation results output by each parallel thread. Through a unified rendering engine or visualization simulation steps, electronic devices project or reconstruct multi-dimensional sub-results such as temperature, pressure, concentration, and molten pool size into color graphics, forming a simulation image that can intuitively reflect the spatiotemporal evolution of each physical quantity during the entire accident process.

[0146] Please see Figure 5This is a schematic diagram of the structure of a nuclear reactor severe accident analysis device provided in an embodiment of this application. A second aspect of this application provides a nuclear reactor severe accident analysis device 10. The device 10 is applied to an electronic device, which includes multiple computing threads. The device 10 includes:

[0147] The acquisition module 11 is used to acquire multiple simulation steps, each simulation step being used to simulate the physicochemical reactions that occur in at least one component of the nuclear reactor under the condition that the nuclear reactor is in an accident state;

[0148] The calculation module 12 is used to process multiple simulation steps in parallel using multiple calculation threads to obtain multiple simulation results. Each calculation thread is used to process one simulation step, and each simulation result is used to characterize the reaction result of the physicochemical reaction that occurs in the corresponding component.

[0149] In some implementations, the computing module 12 includes:

[0150] The first computing unit is used to process each simulation step using a computing thread. After processing for M preset time intervals, the processing result is determined as the simulation result of the simulation step, where M is a positive integer.

[0151] The second calculation unit is used to store the processing results obtained in the simulation steps into the shared memory of the electronic device through the calculation thread at every preset time interval during the processing of M preset time intervals, and to retrieve the processing results stored in other simulation steps from the shared memory for updating the processing results of the next preset time interval.

[0152] In some embodiments, the device 10 further includes:

[0153] The occurrence rate acquisition module is used to obtain the annual average occurrence rate of accidents, and to determine the probability that a nuclear reactor will experience at least one accident within a preset time period based on the annual average occurrence rate using the Poisson model.

[0154] The severity level determination module is used to determine the severity level of the consequences of an accident based on multiple simulation results;

[0155] The risk level determination module is used to determine the risk level of an accident based on the probability and severity of the consequences, and output recommended preventive measures based on the risk level.

[0156] The nuclear reactor severe accident analysis apparatus 10 provided in the second aspect of the present application can realize the various processes implemented in the above method embodiments and achieve the same beneficial effects. To avoid repetition, it will not be described again here.

[0157] Please see Figure 6This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. A third aspect of this application provides an electronic device 1000, including a processor 1100 and a memory 1200. The memory 1200 stores machine-executable instructions that can be executed by the processor 1100. The processor 1100 can execute the machine-executable instructions to implement the above-mentioned nuclear reactor severe accident analysis method.

[0158] A fourth aspect of this application provides a machine-readable storage medium storing instructions that, when executed by a processor, cause the processor to implement the aforementioned method for analyzing severe nuclear reactor accidents.

[0159] In some embodiments, this application also provides a computer program product, including a computer program that, when executed by a processor, implements the nuclear reactor severe accident analysis method according to the above embodiments.

[0160] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0161] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 The computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to operate in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1The functions specified in one or more boxes. These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable apparatus for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0162] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0163] Memory may include non-persistent memory in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. Memory is an example of computer-readable media.

[0164] Computer-readable media include both permanent and non-permanent, removable and non-removable media that can store information by any method or technology. Information can be computer-readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, magnetic magnetic disk storage or other magnetic storage devices, or any other non-transfer medium that can be used to store information accessible by a computing device. As defined herein, computer-readable media does not include temporary computer-readable media (transistor silicon switching devices), such as modulated data signals and carrier waves.

[0165] It should also be noted that 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 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 that element.

[0166] The above are merely embodiments of this application and are not intended to limit the scope of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of the claims of this application.

[0167] Furthermore, various different embodiments of the present invention can be combined in any way, as long as they do not violate the spirit of the present invention, they should also be regarded as the content disclosed by the present invention.

Claims

1. A method for analyzing severe accidents in nuclear reactors, characterized in that, The method is applied to an electronic device, the electronic device including multiple computing threads, the method comprising: Multiple simulation steps are obtained, each of which is used to simulate the physicochemical reactions that occur in at least one component of the nuclear reactor under accident conditions. Multiple simulation steps are processed in parallel using multiple computing threads to obtain multiple simulation results, wherein each computing thread is used to process one simulation step, and each simulation result is used to characterize the reaction result of the physicochemical reaction that occurs in the corresponding component.

2. The method according to claim 1, characterized in that, The method of using the multiple computing threads to process the multiple simulation steps in parallel includes: For each simulation step, a computing thread is used for processing. After processing for M preset time intervals, the processing result is determined as the simulation result of the simulation step, where M is a positive integer. During the processing of the M preset time intervals in the simulation step, every preset time interval, the processing result obtained by the calculation thread is stored in the shared memory of the electronic device, and the processing result stored in other simulation steps is retrieved from the shared memory for updating the processing result of the next preset time interval.

3. The method according to claim 2, characterized in that, For each of the simulation steps, the sum of the N processing cycles of the simulation step is equal to the preset time interval, where N is a positive integer, and the processing cycle is the time interval between each update of the processing result of the simulation step.

4. The method according to claim 2, characterized in that, The processing results include sub-results in multiple dimensions; The computing thread stores the processing results into the shared memory of the electronic device, including: For each sub-result in the processing result, the calculation thread determines whether the sub-result is within a preset range of the corresponding dimension of the sub-result; If the sub-result is within a preset range of the dimension corresponding to the sub-result, the sub-result is stored in the shared memory of the electronic device.

5. The method according to claim 1, characterized in that, The plurality of simulation steps include a first simulation step, the first simulation step includes a plurality of first sub-steps, the computation thread that processes the first simulation step is a first computation thread, and the first computation thread includes a plurality of first sub-threads; The method of using multiple computing threads to process multiple simulation steps in parallel to obtain multiple simulation results includes: During the first simulation step, multiple first sub-threads are used to process multiple first sub-steps in parallel to obtain multiple first sub-simulation results, and the multiple first sub-simulation results are used as the simulation results of the first simulation step, wherein each first sub-thread is used to process one first sub-step.

6. The method according to claim 1, characterized in that, After obtaining multiple simulation results, the method further includes: The annual average occurrence rate of the accident is obtained, and the probability that the nuclear reactor will experience at least one accident within a preset time period is determined using the Poisson model based on the annual average occurrence rate. The severity level of the accident's consequences is determined based on the results of the multiple simulations. The risk level of the accident is determined based on the probability and the severity level of the consequences, and recommended preventive measures for the accident are output based on the risk level.

7. The method according to claim 1, characterized in that, After obtaining multiple simulation results, the method further includes: The simulation results are visualized to obtain simulation images, which include images of the nuclear reactor under accident conditions.

8. A nuclear reactor severe accident analysis device, characterized in that, The device is applied to an electronic device, the electronic device including multiple computing threads, and the device includes: An acquisition module is used to acquire multiple simulation steps, each of which is used to simulate the physicochemical reactions that occur in at least one component of the nuclear reactor under accident conditions. The calculation module is used to process multiple simulation steps in parallel using multiple calculation threads to obtain multiple simulation results, wherein each calculation thread is used to process one simulation step, and each simulation result is used to characterize the reaction result of the physicochemical reaction that occurs in the corresponding component.

9. The apparatus according to claim 8, characterized in that, The computing module includes: The first computing unit is used to process each simulation step using one computing thread, and after processing for M preset time intervals, the processing result is determined as the simulation result of the simulation step, where M is a positive integer. The second calculation unit is used to, during the processing of the M preset time intervals of the simulation step, store the obtained processing results into the shared memory of the electronic device through the calculation thread at each preset time interval, and retrieve the stored processing results of other simulation steps from the shared memory for updating the processing results of the next preset time interval.

10. The apparatus according to claim 8, characterized in that, The device further includes: An occurrence rate acquisition module is used to acquire the annual average occurrence rate of the accident, and to determine the probability that the nuclear reactor will experience at least one accident within a preset time period based on the annual average occurrence rate using a Poisson model. The severity level determination module is used to determine the severity level of the consequences of the accident based on the multiple simulation results; The risk level determination module is used to determine the risk level of the accident based on the probability and the severity level of the consequences, and output recommended prevention steps for the accident based on the risk level.

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