Integrated reactor phenomenon identification and grading analysis method and device and storage medium

Abstract

The invention provides an integrated reactor phenomenon identification and grading analysis method and equipment and a storage medium, and relates to the technical field of nuclear reactors. According to the method, the safety-related phenomena of the integrated reactor under transient operation and hypothetical accident conditions can be identified, the identified phenomena are graded, and a phenomenon identification and grading report of the whole-range accidents of the integrated reactor is obtained and used for identifying important phenomena related to heat transfer of the integrated reactor, so that the safety of the integrated reactor is improved. And research, development and design of the integrated reactor are guided.

Description

Technical Field

[0001] The present application relates to the field of nuclear reactor technology, and in particular to an integrated reactor phenomenon identification and classification analysis method, device and storage medium. Background Art

[0002] The integrated reactor places the pressure vessel, pressurizer, volume control system and safety-related equipment inside the containment. The integrated reactor usually includes a primary circuit system and a secondary circuit system. The coolant in the primary circuit system is in direct contact with the nuclear reactor, taking away the heat generated by the nuclear reactor and transferring the heat to the secondary circuit system through a heat exchange device. The integrated reactor does not require a reactor coolant pump, and the control rod drive mechanism adopts a built-in structure, which will not cause a rod ejection accident due to the rupture of the pressure shell of the control rod mechanism. During normal operation, the driving force generated by the height difference and density difference between the reactor core and the primary and secondary circuit heat exchange components is used to establish a natural circulation to ensure the normal heat extraction of the reactor. Compared with large commercial pressurized water reactors, the integrated reactor has a compact design, high inherent safety, and low linear power, with a large thermal safety margin.

[0003] During the R&D phase of an integrated reactor, a phenomenon identification and ranking (PIRT) analysis is required. PIRT is used to identify important safety phenomena related to safety and to assess their importance and recognition by ranking these phenomena. PIRT is the starting point for the development of new reactor types and an important reference for the development of analysis programs, program suitability evaluation, transient and accident analysis.

[0004] At present, there is no phenomenon identification and classification analysis method for integrated reactors in the existing technology, and the only way to analyze it is to refer to the phenomenon identification and classification analysis method for large pressurized water reactors. However, due to the differences in system layout and initiating events, the phenomenon identification and classification analysis method and results of large pressurized water reactor power plants are not applicable to integrated reactors. Summary of the invention

[0005] In order to alleviate, mitigate or eliminate the above-mentioned technical problems, the present application provides a method, device and storage medium for integrated reactor phenomenon identification and graded analysis, which solves the problem of lack of phenomenon identification and graded analysis of integrated reactors in the prior art.

[0006] In a first aspect, the present application provides an integrated reactor phenomenon identification and classification analysis method, comprising:

[0007] Determine an accident list for the integrated reactor, the accident list including the following five types of accidents: increase in heat output of the primary system, decrease in heat removal capacity of the secondary system, abnormal reactivity and probability distribution, increase in reactor coolant charge, and decrease in reactor coolant charge;

[0008] Determine the objects of concern and their criteria related to the safety of the integrated reactor, including the fuel cladding temperature, system pressure and system water loading, and the criteria include the integrity of the fuel elements, the system pressure not exceeding the design pressure and the pressurizer not overflowing;

[0009] Identify phenomena related to the safety of the integrated reactor under each accident in the accident list, and classify the identified phenomena to form a list of phenomena of the integrated reactor, wherein the phenomena are phenomena that affect the object of concern and its criteria;

[0010] Determine whether the phenomenon list is complete. If not, repeat the above phenomenon identification and phenomenon classification until the phenomenon list is complete, and output a phenomenon identification and classification report.

[0011] In a possible implementation, the grading of the identified phenomena includes:

[0012] The phenomenon recognition and grading model is used to analyze the impact of the identified phenomenon on the object of interest and its criteria, and the phenomenon is graded according to the impact.

[0013] In a possible implementation, the use of the phenomenon identification hierarchical model to analyze the impact of the identified phenomenon on the object of interest and its criteria includes:

[0014] modifying input parameters in an integrated reactor system analysis program associated with the identified phenomenon using a phenomenon identification hierarchical model;

[0015] Extracting and outputting the results related to the object of interest and its criteria calculated by the integrated reactor system analysis program through the phenomenon identification classification model;

[0016] The degree of influence of the identified phenomenon on the object of interest and its criteria is determined according to the output result.

[0017] In a possible implementation, the use of the phenomenon identification hierarchical model to analyze the impact of the identified phenomenon on the object of interest and its criteria includes:

[0018] simulating, by an integrated reactor system analysis program, different parameter combinations associated with the identified phenomena and the objects of interest and their criteria;

[0019] Using the parameter combination to train a neural network model to obtain a trained phenomenon recognition and classification model;

[0020] The trained phenomenon recognition and grading model is used to perform parameter sensitivity analysis, and the degree of influence of the identified phenomenon on the object of interest and its criteria is determined based on the result of the sensitivity analysis.

[0021] In a possible implementation, the determining whether the phenomenon list is complete includes:

[0022] Build an expert database;

[0023] Selecting consulting experts for the integrated reactor phenomenon identification and classification analysis from the expert database;

[0024] Determine whether the list of phenomena is complete based on the opinions of the consulting experts.

[0025] In a possible implementation, the building of an expert database includes:

[0026] Gathering expert information related to the field of integrated reactors;

[0027] Carry out data cleaning and preprocessing on the collected expert information;

[0028] Extract relevant information of experts from the text data after data cleaning and preprocessing, and associate various types of information of experts to form a structured knowledge network.

[0029] In a possible implementation, the collecting of expert information related to the integrated reactor field includes:

[0030] Expert information related to the field of integrated reactors is collected based on scientific research paper databases, reports and speeches at professional conferences and seminars, news reports and interviews within the industry, and membership directories of professional associations and academic institutions.

[0031] In a possible implementation, the selecting of consulting experts from the expert database for the integrated reactor phenomenon identification and classification analysis includes:

[0032] Build an expert recommendation system;

[0033] The expert recommendation system is used to select consulting experts from the expert database for the integrated reactor phenomenon identification and classification analysis.

[0034] In a second aspect, the present application provides a computing device, including:

[0035] at least one processor; and

[0036] At least one memory having instructions stored thereon, which, when executed individually or collectively by the at least one processor, cause the computing device to perform the method according to the first aspect.

[0037] In a third aspect, the present application provides a computer storage medium having instructions stored thereon, which, when executed individually or collectively by at least one processor of a computing device, causes the computing device to execute the method described in the first aspect.

[0038] Compared with the prior art, this application has the following advantages:

[0039] The present application provides a method for identifying and grading integrated reactor phenomena, which can identify safety-related phenomena of an integrated reactor under transient operation and hypothetical accident conditions, and grade the identified phenomena to obtain a phenomenon identification and grading report for the full range of accidents in an integrated reactor, which is used to identify important phenomena related to heat transfer in an integrated reactor and guide the research, development and design of an integrated reactor. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] The accompanying drawings are included to provide a further understanding of the present application. They are included and constitute a part of the present application. The accompanying drawings illustrate embodiments of the present application and together with the present specification serve to explain the principles of the present application. In the accompanying drawings:

[0041] Figure 1 It is a flow chart of an integrated reactor phenomenon identification and classification analysis method provided in an embodiment of the present application;

[0042] Figure 2 It is a structural diagram of a computing device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0043] The principle of the present application will now be described with reference to some embodiments. It should be understood that the description of these embodiments is only for illustrative purposes, and helps those skilled in the art to understand and implement the present application, without any limitation to the scope of the present application. The disclosure described herein can be implemented in a manner different from that described below.

[0044] In the following description, unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.

[0045] References in this application to "one embodiment," "an embodiment," "an exemplary embodiment," etc. indicate that the described embodiment may include a particular feature, structure, or characteristic, but not every embodiment necessarily includes the particular feature, structure, or characteristic. Moreover, such phrases do not necessarily refer to the same embodiment. In addition, when a particular feature, structure, or characteristic is described in conjunction with an exemplary embodiment, whether or not explicitly described, those skilled in the art will recognize that such feature, structure, or characteristic may affect incorporation into other embodiments.

[0046] The terms used herein are only for describing specific embodiments, rather than for limiting exemplary embodiments. The singular forms "one", "an", and "the" used herein also include plural forms, unless the context clearly indicates otherwise. "A group of elements" or "element set" used herein is intended to include one or more elements. It should also be understood that the terms "include", "comprise", "have", "have", "include" and / or "include", when used herein, specify the presence of the features, elements and / or parts, etc., but do not exclude the presence or addition of one or more other features, elements, parts and / or combinations thereof.

[0047] In addition, it should be noted that the use of words such as "first" and "second" to limit objects is only to facilitate the distinction between corresponding objects. Unless otherwise stated, the above words have no special meaning and therefore cannot be understood as limiting the scope of protection of the present invention.

[0048] Flowcharts are used in the present application to illustrate the operations performed by the system according to the embodiments of the present application. It should be understood that the preceding or following operations are not necessarily performed accurately in order. On the contrary, various steps may be processed in reverse order or simultaneously. At the same time, other operations may be added to these processes, or one or more operations may be removed from these processes.

[0049] Figure 1 Schematic diagram of a flow chart of an integrated reactor phenomenon identification and classification analysis method provided in an embodiment of the present application. Figure 1 As shown in the figure, the integrated reactor phenomenon identification and classification analysis method includes the following contents:

[0050] Step 110: Determine the accident list of the integrated reactor.

[0051] Integrated reactors usually have three operating states: normal operation, transient operation, and accident conditions. Transient operation refers to a deviation with minor consequences, which can be resumed after appropriate adjustments. Accident conditions refer to a deviation with relatively serious consequences, which requires measures such as shutdown, safety facility activation, or operator intervention and manual operation to mitigate.

[0052] When determining the accident list of an integrated reactor, we can target the integrated reactor, based on the overall design plan of the integrated reactor, combined with the integrated reactor operation mode, system design, accident process and thermal-hydraulic phenomena, and draw on the existing pressurized water reactor nuclear power plant operating condition classification method to form a transient and full-range initial accident list for the integrated reactor, and then evaluate the envelope between accidents to form an accident list for subsequent phenomenon identification and phenomenon classification.

[0053] For example, the accident list for subsequent phenomenon identification and phenomenon classification formed in step 110 is shown in Table 1 below. The accident list includes five types of accidents: increased heat output of the primary loop system, reduced heat removal capacity of the secondary loop system, abnormal reactivity and probability distribution, increased reactor coolant loading, and reduced reactor coolant loading.

[0054] Table 1

[0055]

[0056]

[0057] Step 120: Determine the objects of concern and their criteria related to the safety of the integrated reactor.

[0058] The safety of an integrated reactor depends on whether the fuel elements are intact, whether the system pressure exceeds the design pressure, whether the pressurizer is overflowing, etc. Combined with the potential consequences of the above accident list, there are two ways for an integrated reactor to break thermal safety: first, due to the reduction of reactor coolant loading, the increase of heat output of the primary system, the abnormal heat removal capacity and reactivity and probability distribution of the secondary system, the core heat cannot be removed in time, the core temperature rises and the fuel elements are damaged, or the core heat is too large to cause the system pressure to rise and exceed the system design pressure; second, due to the increase of reactor coolant loading, the system is loaded too much, which eventually leads to the pressurizer overflowing. Therefore, from the perspective of thermal accident analysis, the objects of concern related to the safety of the integrated reactor include the temperature of the fuel cladding, the system pressure and the water loading of the system. Accordingly, the criteria for the objects of concern related to the safety of the integrated reactor include the integrity of the fuel elements, the system pressure does not exceed the design pressure and the pressurizer does not overflow.

[0059] Step 130, identifying phenomena related to the safety of the integrated reactor under each accident in the accident list, and classifying the identified phenomena to form a phenomenon list of the integrated reactor, wherein the phenomena are phenomena that affect the object of concern and its criteria.

[0060] Phenomenon identification under transient and hypothetical accidents is a decisive factor affecting the outcome of events. In the process of phenomenon identification, based on the overall design plan of the integrated reactor, combined with the operation mode of the integrated reactor, and drawing on the existing accident phenomena of pressurized water reactor nuclear power plants, the accident phenomena can be identified and then classified.

[0061] In some embodiments, artificial intelligence can be used to perform sensitivity analysis on parameters related to the identified phenomenon, and the degree of influence of the phenomenon on the criteria can be determined based on the sensitivity analysis results, and then the phenomenon can be graded based on the degree of influence. For example, a phenomenon identification and grading model can be used to analyze the degree of influence of the identified phenomenon on the object of interest and its criteria, and the phenomenon can be graded based on the degree of influence. Among them, using the phenomenon identification and grading model to analyze the degree of influence of the identified phenomenon on the object of interest and its criteria includes but is not limited to the following two implementation methods:

[0062] 1) Use the phenomenon identification classification model to modify the input parameters related to the identified phenomenon in the integrated reactor system analysis program, extract the results related to the object of concern and its criteria calculated by the integrated reactor system analysis program through the phenomenon identification classification model, and output them, and determine the degree of influence of the identified phenomenon on the object of concern and its criteria based on the output results.

[0063] 2) The integrated reactor system analysis program is used to simulate different parameter combinations related to the identified phenomena, objects of concern and their criteria, and the parameter combinations are used to train the neural network model to obtain a trained phenomenon identification and grading model, and the trained phenomenon identification and grading model is used to perform parameter sensitivity analysis, and the degree of influence of the identified phenomena on the objects of concern and their criteria is determined based on the results of the sensitivity analysis.

[0064] This embodiment uses artificial intelligence to perform phenomenon classification, which can automatically complete a large number of sensitivity calculations, save manpower, and improve the accuracy of phenomenon classification.

[0065] There are many types of equipment that affect the integrated reactor for each type of accident focus and its criteria, including the core, primary and secondary circuit heat exchangers, pressurizer, upper chamber, downcomer and other equipment in the integrated reactor. The phenomena produced by each component in each device are identified.

[0066] In order to better understand the present application, the breach area and the core active area in a loss of coolant accident are taken as examples to further illustrate phenomenon identification and phenomenon classification.

[0067] According to the design characteristics of the integrated reactor and the accident process, the LOCA is divided into the breach blowdown stage, the pressure relief valve blowdown stage, and the injection stage. The threat to thermal safety caused by the LOCA is that the system coolant water load is lost, resulting in the inability to remove the core heat, and ultimately causing the cladding temperature to be too high and the fuel elements to be damaged. Therefore, in the LOCA, the focus is on the fuel cladding temperature, and the criterion is that the fuel elements are intact.

[0068] For example, breach-related phenomena include:

[0069] (1) Breaking pipeline resistance

[0070] The resistance of the breach pipeline will affect the speed of coolant loss at the breach in the subcritical flow stage, affect the water loading of the system, and further affect the heat extraction of the fuel elements.

[0071] (2) Critical flow

[0072] The critical flow at the breach controls the mass and energy loss of the system, as well as the system's pressure relief rate, affecting the system's water loading and, in turn, the heat extraction of the fuel elements.

[0073] (3) Subcritical flow

[0074] In the later stages of the accident, the flow at the rupture is mainly subcritical flow, which also affects the water loading of the system and thus affects the heat extraction of the fuel elements.

[0075] Phenomena related to the core active area include:

[0076] (1) Water level swelling

[0077] This phenomenon characterizes the two-phase mixed water level in the core. When the mixed water level is higher than the top of the core, the fuel elements will not heat up. It determines the mass distribution of the two-phase mixture in the pressure vessel and the exposure degree of the core, affecting the heat extraction of the fuel elements.

[0078] (2) Decay heat

[0079] The core decay heat heats the fuel elements and may cause the temperature of the fuel cladding to rise. It is the main heat source after a loss of coolant accident and can cause the coolant to boil and produce steam, resulting in water loss.

[0080] (3) Energy storage release

[0081] There is stored energy in the pressure vessel and the reactor internals. The release of stored energy is also a heat source after the accident, which may reduce the coolant load and increase the temperature of the fuel cladding.

[0082] (4) Flash evaporation

[0083] This thermal hydraulic phenomenon is a phase change process from liquid to vapor when the pressure in the system changes rapidly. This phenomenon reduces the system's depressurization rate, delays the time for the system to balance the pressure with the containment, and affects the water loading in the core and the peak temperature of the fuel cladding.

[0084] (5) Flow resistance

[0085] The core active area resistance may affect the coolant loss flow during the pressure relief valve spraying stage, and have some impact on the system coolant loading and residual heat extraction.

[0086] For the above example phenomena, identify the key parameters of the phenomena, such as pipeline resistance related to the breached pipeline resistance and subcritical flow, CD coefficient related to critical flow, initial core cavitation fraction related to water level swelling, decay heat power related to decay heat, non-heating thermal component energy storage related to energy storage release, and core active zone resistance related to flow resistance. After identifying the key parameters of the phenomenon, select a system analysis program for the integrated reactor, such as RELAP5, and use artificial intelligence for the key parameters, such as the phenomenon identification hierarchical model combined with RELAP5 to perform sensitivity analysis on each key parameter. The sensitivity analysis includes but is not limited to the following two implementation methods:

[0087] 1) Use the phenomenon identification and grading model to batch modify the input cards of RELAP5 and then run them in batches. For example, the CD coefficient related to the critical flow at the breach can be fixed in the position in the RELAP5 input card. The position can be batch modified using the phenomenon identification and grading model. The parameter change can be changed from 0.1 to 2.0 and then batch calculated. After the calculation, the same cladding peak temperature is extracted through the phenomenon identification and grading model and the result is output. Different CD coefficient inputs correspond to different cladding peak temperature output results, which can clearly understand the influence of the critical flow phenomenon on the cladding peak temperature.

[0088] 2) Prepare the input data and output result data of the neural network model (such as multilayer perceptron (MLP), convolutional neural network (CNN), etc.) by simulating different parameter combinations through RELAP5; select the key parameters that need to be subjected to sensitivity analysis; preprocess the collected data, including data cleaning, normalization and other steps to ensure that the data is suitable for training the neural network model; use the preprocessed data to train the neural network model to obtain a trained phenomenon recognition and grading model; use the trained phenomenon recognition and grading model to perform parameter sensitivity analysis, such as changing the value of the input parameter and observing the change in the output to evaluate the sensitivity of each parameter; based on the results of the sensitivity analysis, determine the degree of influence of the parameter on the peak temperature of the cladding.

[0089] After completing the sensitivity analysis in the above manner, the phenomena can be graded according to the results of the sensitivity analysis. Very important phenomena are classified as "H", medium-important phenomena are classified as "M", low-important phenomena are classified as "L", and non-existent phenomena are classified as "-".

[0090] For example, the results of the phenomenon classification are shown in Table 2.

[0091] Table 2

[0092]

[0093]

[0094] Step 140 , determine whether the phenomenon list is complete, if not, repeat the above phenomenon identification and phenomenon classification, that is, step 130 , until the phenomenon list is complete. If yes, execute step 150 .

[0095] In some embodiments, an expert database may be constructed first, and consulting experts for integrated reactor phenomenon identification and classification analysis may be selected from the expert database, and whether the phenomenon list is complete may be determined based on the opinions of the consulting experts. Examples are as follows:

[0096] (1) Collect expert information related to the field of integrated reactors based on scientific research paper databases, reports and speeches at professional conferences and seminars, news reports and interviews within the industry, and membership directories of professional associations and academic institutions.

[0097] (2) Clean and preprocess the collected expert information, including removing duplicate data and standardizing data formats.

[0098] (3) Extract relevant information of experts from the text data after data cleaning and preprocessing, such as research fields, published papers, participated projects, published patents, etc.

[0099] (4) Use knowledge graph technology to associate various types of expert information to form a structured knowledge network.

[0100] After the expert database is constructed, consulting experts can be selected from the expert database. For example, an expert recommendation system can be constructed using a machine learning algorithm (such as collaborative filtering, content recommendation, etc.), and the expert recommendation system is used to select appropriate consulting experts from the established expert database. These consulting experts judge and confirm the phenomenon list obtained in step 130, and then judge whether the phenomenon list is complete based on the opinions of these consulting experts.

[0101] This embodiment constructs an expert database and selects consulting experts through artificial intelligence, and can select experts who are more familiar with the relevant reactor type field to judge and confirm the phenomenon list, thereby improving the accuracy of the phenomenon list.

[0102] Step 150: Output a phenomenon identification and classification report.

[0103] Figure 2 Schematic diagram of a computing device provided in an embodiment of the present application. Figure 2 As shown, computing device 200 includes one or more processors 210 , one or more memories 220 coupled to processor 210 , and one or more communication modules 240 coupled to processor 210 .

[0104] The communication module 240 is used for two-way communication. The communication module 240 has at least one antenna to facilitate communication. The communication interface may represent any interface necessary for communicating with other network elements.

[0105] Processor 210 may be of any type suitable for the local technology network, and may include, as non-limiting examples, one or more of: a general purpose computer, a special purpose computer, a microprocessor, a digital signal processor (DSP), and a processor based on a multi-core processor architecture. Computing device 200 may have multiple processors, such as application specific integrated circuit chips, which are driven in time to a clock that synchronizes a master processor.

[0106] The memory 220 may include one or more non-volatile memories and one or more volatile memories. Examples of non-volatile memories include, but are not limited to, read-only memory (ROM) 224, electrically programmable read-only memory (EPROM), flash memory, hard disk, compact disk (CD), digital video disk (DVD), and other magnetic and / or optical memories. Examples of volatile memories include, but are not limited to, random access memory (RAM) 222 and other volatile memories that do not persist during the duration of a power outage.

[0107] The computer program 230 includes computer executable instructions that are executed by the associated processor 210. The program 230 may be stored in the ROM 224. The processor 210 may perform any suitable actions and processes by loading the program 230 into the RAM 222.

[0108] The embodiment of the present application can be implemented by the program 230, so that the computing device 200 can execute the reference Figure 1 Any process disclosed in the discussion. The embodiments of the present application may also be implemented by hardware or by a combination of software and hardware.

[0109] In some embodiments, the program 230 may be tangibly contained in a computer-readable medium, which may be contained in the computing device 200 (e.g., memory 220) or other storage device accessible to the computing device 200. The computing device 200 may load the program 230 from the computer-readable medium to the RAM 222 for execution. The computer-readable medium may include any type of tangible non-volatile memory, such as ROM, EPROM, flash memory, hard disk, CD, DVD, etc. The computer-readable medium has the program 230 stored thereon.

[0110] Generally, various embodiments of the present application may be implemented in hardware or dedicated circuits, software, logic, or any combination thereof. Certain aspects may be implemented in hardware, while other aspects may be implemented in firmware or software, which may be performed by a controller, microprocessor, or other computing device. Although various aspects of the embodiments of the present application are shown and described as block diagrams, flow charts, or using some other graphical representations, it should be understood that, as non-limiting examples, the blocks, devices, systems, techniques, or methods described herein may be implemented in hardware, software, firmware, dedicated circuits or logic, general hardware or controllers or other computing devices, or some combination thereof.

[0111] The present application also provides at least one computer program product tangibly stored on a non-transitory computer readable storage medium. The computer program product includes computer executable instructions, such as instructions included in program modules, which are executed in a device on a target real or virtual processor to perform the above-mentioned reference Figure 1 The method described. Typically, program modules include routines, programs, libraries, objects, classes, components, data structures, etc. that perform specific tasks or implement specific abstract data types. In various embodiments, the functions of program modules can be combined or separated between program modules as needed. Machine executable instructions for program modules can be executed in local or distributed devices. In distributed devices, program modules can be located in local and remote storage media.

[0112] The program code for executing the method of the present application can be written in any combination of one or more programming languages. These program codes can be provided to a processor or controller of a general-purpose computer, a special-purpose computer or other programmable data processing equipment so that when the program code is executed by the processor or controller, the function / operation specified in the flow chart and / or the block diagram is realized. The program code can be executed completely on the machine as an independent software package, partially on the machine, partially on the machine, partially on a remote machine, partially on a remote machine, or all on a remote machine or server.

[0113] In the context of this application, computer program codes or related data may be carried by any appropriate carrier to enable a device, apparatus or processor to perform various processes and operations as described above. Examples of carriers include signals, computer readable media, etc.

[0114] The computer readable medium may be a computer readable signal medium or a computer readable storage medium. The computer readable medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared or semiconductor systems, devices or apparatuses, or any suitable combination of the foregoing. More specific examples of computer readable storage media include an electrical connection with one or more wires, a portable computer floppy disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0115] In addition, although the operations are described in a specific order, this should not be construed as requiring to perform these operations in the specific order or sequence shown, or to perform all the operations shown, to obtain the desired result. In some cases, multitasking and parallel processing may be advantageous. Similarly, although several specific implementation details are included in the above discussion, these details should not be interpreted as limiting the scope of the application, but can be interpreted as a description of the specific features of a particular embodiment. Some of the features described in the context of a separate embodiment may also be implemented in combination in a single embodiment. On the contrary, the various features described in the context of a single embodiment may also be implemented in multiple embodiments individually or in any suitable sub-combination.

[0116] Although the present application has been described in language specific to structural features and / or methodological acts, it should be understood that the present application defined in the appended claims is not necessarily limited to the specific features or acts described above. Instead, the specific features and acts described above are disclosed as example forms of implementing the claims.

Claims

1. An integrated reactor phenomenon identification and classification analysis method, characterized in that: include: Determine an accident list for the integrated reactor, the accident list including the following five types of accidents: increase in heat output of the primary system, decrease in heat removal capacity of the secondary system, abnormal reactivity and probability distribution, increase in reactor coolant charge, and decrease in reactor coolant charge; Determine the objects of concern and their criteria related to the safety of the integrated reactor, including the fuel cladding temperature, system pressure and system water loading, and the criteria include the integrity of the fuel elements, the system pressure not exceeding the design pressure and the pressurizer not overflowing; Identify phenomena related to the safety of the integrated reactor under each accident in the accident list, and classify the identified phenomena to form a list of phenomena of the integrated reactor, wherein the phenomena are phenomena that affect the object of concern and its criteria; Determine whether the phenomenon list is complete. If not, repeat the above phenomenon identification and phenomenon classification until the phenomenon list is complete, and output a phenomenon identification and classification report.

2. The method according to claim 1, characterized in that The grading of the identified phenomena includes: The phenomenon recognition and grading model is used to analyze the impact of the identified phenomenon on the object of interest and its criteria, and the phenomenon is graded according to the impact.

3. The method according to claim 2, characterized in that The degree of influence of the phenomenon identified by using the phenomenon identification classification model analysis on the object of interest and its criteria includes: modifying input parameters in an integrated reactor system analysis program associated with the identified phenomenon using a phenomenon identification hierarchical model; Extracting and outputting the results related to the object of interest and its criteria calculated by the integrated reactor system analysis program through the phenomenon identification classification model; The degree of influence of the identified phenomenon on the object of interest and its criteria is determined according to the output result.

4. The method according to claim 2, characterized in that The degree of influence of the phenomenon identified by using the phenomenon identification classification model analysis on the object of interest and its criteria includes: simulating, by an integrated reactor system analysis program, different parameter combinations associated with the identified phenomena and the objects of interest and their criteria; Using the parameter combination to train a neural network model to obtain a trained phenomenon recognition and classification model; The trained phenomenon recognition and grading model is used to perform parameter sensitivity analysis, and the degree of influence of the identified phenomenon on the object of interest and its criteria is determined based on the result of the sensitivity analysis.

5. The method according to claim 1, characterized in that The determination of whether the phenomenon list is complete includes: Build an expert database; Selecting consulting experts for the integrated reactor phenomenon identification and classification analysis from the expert database; Determine whether the list of phenomena is complete based on the opinions of the consulting experts.

6. The method according to claim 5, characterized in that The construction of the expert database includes: Gathering expert information related to the field of integrated reactors; Carry out data cleaning and preprocessing on the collected expert information; Extract relevant information of experts from the text data after data cleaning and preprocessing, and associate various types of information of experts to form a structured knowledge network.

7. The method according to claim 6, characterized in that The collection of expert information related to the integrated reactor field includes: Expert information related to the field of integrated reactors is collected based on scientific research paper databases, reports and speeches at professional conferences and seminars, news reports and interviews within the industry, and membership directories of professional associations and academic institutions.

8. The method according to claim 5, characterized in that The consulting experts selected from the expert database for the integrated reactor phenomenon identification and classification analysis include: Build an expert recommendation system; The expert recommendation system is used to select consulting experts from the expert database for the integrated reactor phenomenon identification and classification analysis.

9. A computing device, characterized in that include: at least one processor; as well as At least one memory having instructions stored thereon, which, when executed individually or collectively by the at least one processor, cause the computing device to perform the method according to any one of claims 1 to 8.

10. A computer storage medium, characterized in that: The computer storage medium stores instructions, which, when executed individually or collectively by at least one processor of a computing device, cause the computing device to perform the method according to any one of claims 1 to 8.

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