A device aging modeling analysis method and device, storage medium and electronic device

Abstract

The application discloses a kind of device aging modeling analysis method, device, storage medium and electronic equipment, including obtaining PSA model, judging integrity verification to the PSA model;According to the PSA model that passes through the integrity verification, the equipment of nuclear power plant is classified and constructed first classification set according to modeling state, the first classification set includes explicit modeling device, implicit modeling device and unmodeled device;The first classification set is continued to be divided based on the PSA model and forms second classification set;Risk contribution index corresponding to the device in the second classification set is calculated based on the PSA model, and the risk contribution index includes conditional core damage probability, conditional early large radioactive release probability and risk increase equivalent;According to the consequence severity of the risk contribution index judgment corresponding device.

Description

Technical Field

[0001] This invention relates to the field of equipment aging analysis technology, and specifically to an equipment aging modeling and analysis method, apparatus, storage medium, and electronic device. Background Technology

[0002] As the operating time of nuclear power plants worldwide gradually approaches their design life, equipment aging has become a significant factor affecting the safe operation of nuclear power plants. In recent years, with the development of Probabilistic Safety Analysis (PSA) and risk-guided application technologies, analytical methods for optimizing Aging Management Programs (AMPs) based on risk insights have gradually emerged. This method typically includes: analyzing the probability of equipment aging failure, analyzing the severity of the consequences of equipment aging failure, and combining the analysis results to form a risk matrix for AMP optimization.

[0003] In existing technologies, risk indicators such as Conditional Core Damage Probability (CCDP), Conditional Large Early Release Probability (CLERP), and Risk Achievement Worth (RAW) are typically used based on the PSA model to analyze the consequences of equipment aging failure. However, the modeling methods for different equipment in the PSA model vary. Some equipment participates directly in the PSA calculation as basic events, while others are only indirectly reflected in the PSA model through parameters or equivalent logic. There are even equipment that are not included in the PSA model. Existing technologies lack a unified risk analysis method for equipment in different modeling states, resulting in poor consistency in the analysis results of equipment aging consequences. Furthermore, the risks of unmodeled equipment are difficult to incorporate into a unified risk propagation chain for quantitative analysis, easily leading to incomplete risk analysis results.

[0004] Patent document CN116681277A discloses a PSA data analysis method considering aging effects, including: acquiring engineering objects of nuclear power plants, identifying and screening engineering objects to obtain aging-sensitive objects to be analyzed; modeling the aging failure rate of the objects to be analyzed to obtain a model of the objects to be analyzed; optimizing the standard PSA fault tree model based on the model of the objects to be analyzed to obtain an optimized PSA fault tree model; and conducting risk assessment based on the optimized PSA fault tree model. However, it does not address the problem that existing methods lack a unified risk analysis method for explicitly modeled equipment, implicitly modeled equipment, and unmodeled equipment, resulting in poor consistency and completeness of equipment aging consequence analysis results.

[0005] Patent document CN109358583A discloses a method for preventing the failure of critical sensitive equipment in nuclear power units. The method includes the following steps: First, identifying SPV (Special Purpose Vehicle) equipment. Based on relevant equipment classification guidelines, identify equipment whose failure, even a single component, could lead to reactor shutdown, power reduction, or significant power fluctuations. Second, identifying sensitive components. Collect data, conduct vulnerability analysis on the SPV equipment, and use fault tree analysis for identification. Third, analyzing mitigation strategies in four areas: operation, isolation, maintenance, and technology. Fourth, developing corrective actions. Fifth, daily SPV management. However, this method does not address the lack of a unified risk analysis method for explicitly modeled, implicitly modeled, and unmodeled equipment, resulting in poor consistency and completeness in the analysis of equipment aging consequences.

[0006] In summary, neither of the two existing patents mentioned above addresses the lack of a unified risk analysis method for explicitly modeled devices, implicitly modeled devices, and unmodeled devices, resulting in poor consistency and completeness of the analysis results for the consequences of device aging. Summary of the Invention

[0007] Based on the above-mentioned technical problems, this invention proposes a method, apparatus, storage medium, and electronic device for equipment aging modeling and analysis, which solves the problem that existing methods lack a unified risk analysis method for explicitly modeled equipment, implicitly modeled equipment, and unmodeled equipment, resulting in poor consistency and completeness of equipment aging consequence analysis results.

[0008] To achieve the above objectives, this invention proposes a method for equipment aging modeling and analysis.

[0009] A method for modeling and analyzing equipment aging includes: Obtain the PSA model and perform integrity verification on the PSA model; Based on the PSA model that has passed the integrity verification, the equipment of the nuclear power plant is classified according to its modeling status to construct a first classification set, which includes explicitly modeled equipment, implicitly modeled equipment, and unmodeled equipment; the first classification set is further divided based on the PSA model to form a second classification set; Based on the PSA model, the risk contribution index corresponding to the equipment in the second classification set is calculated. The risk contribution index includes the probability of conditional core damage, the probability of a large amount of radioactive release in the early stage of condition, and the risk increase equivalent. The severity of the consequences for the corresponding equipment is determined based on the aforementioned risk contribution indicators.

[0010] Furthermore, the integrity of the PSA model is verified, including: verifying whether the PSA model includes a primary PSA model and a secondary PSA model; verifying whether the PSA model includes a power operation model, a low-power operation model, and a shutdown operation model; verifying whether the PSA model includes an internal event model; verifying whether devices in the PSA model whose aging failure affects the frequency of initiation events are linked to the event tree in the PSA model; and verifying whether the modeled devices in the PSA model have passive failure modes.

[0011] Furthermore, the integrity verification of the PSA model also includes supplementing the PSA model that fails the integrity verification with one or more of the following: the primary PSA model or the secondary PSA model; the low-power operating condition model or the shutdown operating condition model; the internal event model; the fault tree coupling logic between the equipment affected by aging failure and the frequency of the initiation event, and establishing the link relationship corresponding to the event tree; the passive failure mode of the modeled equipment.

[0012] Furthermore, the modeling state includes: explicit modeling, implicit modeling, and no modeling.

[0013] Further, based on the PSA model that has passed the integrity verification, the equipment of the nuclear power plant is classified according to the modeling status to construct a first classification set, including: marking the equipment of the nuclear power plant according to the explicit modeling, implicit modeling and unmodeling methods respectively, and constructing the first classification set.

[0014] Furthermore, based on the PSA model, the first classification set is further divided into a second classification set, including: dividing the devices marked as explicit modeling and implicit modeling according to the consequences of aging failure to form the second classification set.

[0015] Furthermore, the second category set includes: explicit devices of initiating events, explicit devices of system failures, implicit devices of initiating events, implicit devices of system failures, and unmodeled devices.

[0016] Further, based on the PSA model, the risk contribution index corresponding to the equipment in the second classification set is calculated, including: calculating the conditional core damage probability and conditional early mass radioactive release probability corresponding to the explicit equipment of the initiating event and the implicit equipment of the initiating event, respectively; and calculating the risk increase equivalent of the explicit equipment of system failure and the implicit equipment of system failure.

[0017] Furthermore, the conditional core damage probability is expressed as follows: ,in The condition is the core damage probability. Let Fi be the probability of core damage, and Fi be the frequency of occurrence of the i-th type of initiating event; the expression for the probability of a large amount of radioactive release in the early stage under the condition is as follows: ,in The probability of a large-scale radioactive release in the early stages under the aforementioned conditions. High release frequency in the early stages. Let i be the frequency of occurrence of the i-th type of initiating event.

[0018] Furthermore, the risk increase equivalent is expressed as follows: ,in Increase the equivalent of the risk corresponding to the i-th basic event. The probability of the top event is given when the basic event is under normal failure probability conditions. The top event includes core damage events or early large-scale radioactive release events.

[0019] Furthermore, it also includes: constructing equivalent basic events based on the unmodeled device, mapping the equivalent basic events to the initiating event path or mitigation system path in the PSA model respectively, correcting the initiating event occurrence frequency parameter and mitigation system failure probability parameter in the PSA model, and recalculating the risk contribution index based on the corrected PSA model.

[0020] Further, judging the severity of consequences for the corresponding equipment based on the risk contribution index includes: comparing the risk contribution index with data from a preset risk set to determine the severity of consequences, wherein the preset risk set includes multiple risk limits corresponding to equipment in different second category sets.

[0021] To achieve the above objectives, the present invention also proposes an equipment aging modeling and analysis device.

[0022] An equipment aging modeling and analysis device, comprising: The verification module is used to acquire the PSA model and perform integrity verification on the PSA model. The construction module is used to classify the equipment of the nuclear power plant according to the modeling status based on the PSA model that has passed the integrity verification, and to construct a first classification set, the first classification set including explicitly modeled equipment, implicitly modeled equipment and unmodeled equipment; and to further divide the first classification set based on the PSA model to form a second classification set. The calculation module is used to calculate the risk contribution index corresponding to the equipment in the second classification set based on the PSA model. The risk contribution index includes the probability of conditional core damage, the probability of a large amount of radioactive release in the early stage of condition, and the risk increase equivalent. The judgment module is used to determine the severity of the consequences for the corresponding equipment based on the risk contribution index.

[0023] Based on the above technical solution, the present invention has at least the following beneficial effects: 1. This invention proposes a method, apparatus, storage medium, and electronic device for equipment aging modeling and analysis. By verifying the integrity of the PSA model, it ensures that the PSA model used in subsequent risk analysis has a complete accident sequence and risk propagation logic. The device is classified according to its modeling state in the PSA model, and further subdivided into a second category set based on basic events, which can distinguish the role paths of different types of equipment in the accident risk propagation process. Furthermore, based on the PSA model, risk contribution indicators such as the probability of conditional core damage, the probability of early-stage large-scale radioactive release, and the risk increase equivalent are calculated for the corresponding equipment. This allows for quantitative analysis of the consequences of equipment aging failure from multiple dimensions, including core damage risk, radioactive release risk, and risk sensitivity. This improves the consistency and completeness of the aging risk analysis results for equipment in different modeling states, as well as the accuracy of judging the severity of equipment consequences, greatly reducing the probability of major accidents caused by aging identification errors.

[0024] 2. This invention proposes a method, apparatus, storage medium, and electronic device for equipment aging modeling and analysis. By verifying the completeness of the primary PSA model, secondary PSA model, different operating condition models, and internal event models in the PSA model, and supplementing the missing accident models, operating condition models, and equipment failure logic, the accident propagation path after equipment aging failure can form a complete association between the event tree and the fault tree. This avoids the risk calculation results being too low due to missing accident sequences, missing operating conditions, or missing equipment failure logic, thereby improving the accuracy and reliability of equipment aging risk analysis results.

[0025] 3. This invention proposes a method, apparatus, storage medium, and electronic device for equipment aging modeling and analysis. By classifying equipment into explicit modeling, implicit modeling, and no modeling, and further dividing it into a second category based on whether equipment aging failure affects the occurrence of an initiating event or the function of a mitigation system, different types of equipment are subjected to risk propagation analysis corresponding to either the frequency change path of the initiating event or the failure path of the mitigation system. Specifically, for initiating event equipment, the probability of conditional core damage and the probability of a large amount of early-stage radioactive release reflect the risk of consequences after an accident. For system failure equipment, the risk increase equivalent reflects the amplification of the overall risk level by the equipment failure. This avoids the distortion of analysis results caused by using the same risk index for equipment with different action paths, and improves the consistency of aging consequence analysis results for different types of equipment.

[0026] 4. This invention proposes a method, apparatus, storage medium, and electronic device for equipment aging modeling and analysis. It constructs equivalent basic events for unmodeled equipment and maps them to the initiating event path or mitigation system path in the PSA model. It corrects the occurrence frequency parameters of the initiating event and the failure probability parameters of the mitigation system, enabling unmodeled equipment to participate in the accident propagation calculation of the event tree and fault tree. This avoids unmodeled equipment being ignored by default because it has not entered the PSA risk propagation chain, thereby reducing the omission of equipment aging risks and improving the completeness of the judgment results on the severity of equipment consequences. Attached Figure Description

[0027] The accompanying drawings, which form part of this specification, are used to provide a further understanding of the invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an undue limitation of the invention. In the drawings: Figure 1 A flowchart of a device aging modeling and analysis method according to one embodiment is shown; Figure 2 A schematic diagram of a simplified PSA model of the device's passive failure modes is shown in one embodiment; Figure 3 A schematic diagram of a PSA model following a passive failure mode of a supplementary device is shown in one embodiment. Figure 4 A schematic diagram illustrating an embodiment where aging failure affects the frequency of initiation events is not linked to a PSA model; Figure 5 A schematic diagram illustrating a device linked to a PSA model in one embodiment where supplemental aging failure affects the frequency of initiation events is shown. Figure 6 A schematic diagram of the structure of a device aging modeling and analysis apparatus according to one embodiment is shown; Figure 7 A schematic diagram of the structure of a device aging modeling and analysis product according to one embodiment is shown; Figure 8 A schematic diagram of the structure of an electronic device according to an embodiment is shown. Detailed Implementation

[0028] It should be noted that, unless otherwise specified, the embodiments and features described in the present invention can be combined with each other. The present invention will now be described in detail with reference to the accompanying drawings and embodiments.

[0029] The present invention will be further described in detail below with reference to specific embodiments, which should not be construed as limiting the scope of protection claimed by the present invention.

[0030] Example

[0031] To address the problem that existing methods lack a unified risk analysis approach for explicitly modeled devices, implicitly modeled devices, and unmodeled devices, resulting in poor consistency and completeness of equipment aging consequence analysis results, this invention proposes an equipment aging modeling analysis method, apparatus, storage medium, and electronic device.

[0032] The embodiments of this application will be described in detail below with reference to the accompanying drawings and examples.

[0033] It should be noted that the terms "first," "second," etc., in the specification, claims, and drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence.

[0034] To achieve the above objectives, the present invention also proposes a method for equipment aging modeling and analysis.

[0035] like Figure 1 The figure illustrates a device aging modeling and analysis method according to an embodiment of the present invention. The process mainly includes the following steps: S101: Obtain the PSA model and perform integrity verification on the PSA model.

[0036] Furthermore, the integrity verification steps include: verifying whether the PSA model contains a primary PSA model and a secondary PSA model; verifying whether the PSA model includes a power operation model, a low-power operation model, and a shutdown operation model; verifying whether the PSA model includes an internal event model; verifying whether devices in the PSA model whose aging failure affects the frequency of initiation events are linked to the event tree in the PSA model; and verifying whether the modeled devices in the PSA model have passive failure modes. The integrity verification can be performed on the PSA model in any order.

[0037] Furthermore, the Level 1 PSA model is used to analyze and calculate the Core Damage Frequency (CDF); the Level 2 PSA model is used to calculate the Early Large Release of Radioactive Materials (LERF); internal events refer to the most basic analysis objects of the Level 1 PSA model, events caused by equipment or systems within the plant, including loss of water accidents, total power outages, main steam pipe ruptures, steam generator heat transfer tube ruptures, and main feedwater loss.

[0038] Specifically, acquiring the nuclear power plant's already constructed features, such as... Figure 2 and Figure 4 The PSA model shown was subjected to integrity verification, and it was found that... Figure 2 The passive failures of pump 001GP and electric valve 001QM were simplified, and their initiation event frequency analysis only used database data, failing to model the nuclear power plant-specific equipment that affects the initiation event frequency. Therefore, corresponding modifications are required. Figure 3 An example of fault tree modeling for a PSA mitigation system following the passive failure of supplementary pump 001GP and electric valve 001QM is given. Figure 5 A fault tree modeling example for calculating the PSA initiation event frequency is given after supplementing the electric valve 001QM and manual valve 002QM that affect the initiation event frequency, and a PSA model that satisfies integrity verification is constructed.

[0039] Furthermore, for PSA models that have not passed complete verification, one or more of the following can be added based on the corresponding failed items: the first-level PSA model or the second-level PSA model; the low-power operating condition model or the shutdown operating condition model; the internal event model; the fault tree coupling logic between the equipment affected by aging failure and the frequency of the initiation event, and establish the link relationship corresponding to the event tree; the passive failure mode of the modeled equipment.

[0040] Furthermore, the supplemented PSA model is re-inputted and integrity verification continues until the integrity verification is satisfied, at which point the current PSA model is saved.

[0041] S102: Based on the PSA model that has passed the integrity verification, the equipment of the nuclear power plant is classified according to the modeling status to construct a first classification set, which includes explicitly modeled equipment, implicitly modeled equipment, and unmodeled equipment; the first classification set is further divided based on the PSA model to form a second classification set.

[0042] Furthermore, in this invention, explicit modeling refers to modeling an object or influencing factor directly as a node, event, logic gate, state, or parameter in the PSA model. Implicit modeling refers to not directly establishing an independent model in the PSA model, but indirectly reflecting its influence through assumptions, boundary conditions, conservative treatments, parameter reduction, rule constraints, etc. Unmodeled refers to physical equipment identified in the nuclear power plant that is not explicitly or implicitly modeled in the current PSA model.

[0043] Specifically, Table 1 below is a list of equipment in the first category set obtained after the nuclear power plant equipment is divided according to the PSA model. The first column is the equipment code, the second column is the equipment description, the third column is the modeling status of the equipment in the PSA model, i.e., explicit modeling, implicit modeling or no modeling, the fourth column is the master equipment code, only implicitly modeled equipment has a corresponding master equipment, and the fifth column is whether the equipment has an induced gas initiation event after aging failure.

[0044] Table 1. List of Equipment in Category 1

[0045] Furthermore, the devices in the first classification set are divided into a second classification set according to the failure consequences after aging. The second classification set includes devices with explicit initiation events, devices with explicit system failures, devices with implicit initiation events, devices with implicit system failures, and unmodeled devices.

[0046] Furthermore, based on the event tree in PSA, the devices in the first classification set are labeled and divided. Explicitly modeled devices that cause an initiating event after aging failure but do not cause a mitigation of system failure are labeled as initiating event explicit devices. Explicitly modeled devices that cause a mitigation of system failure after aging failure are labeled as system failure explicit devices. Implicitly modeled devices that cause an initiating event after primary device aging failure but do not cause a mitigation of system failure are labeled as initiating event implicit devices. Implicitly modeled devices that cause a mitigation of system failure after primary device aging failure are labeled as system failure implicit devices.

[0047] Furthermore, the first category set obtained above is divided and labeled, and the results are shown in Table 2 below, which is the equipment details table of the second category set. Among them, 001RF is the heat exchanger, which is labeled as an explicit system failure device; 002DI is the return water flow restrictor plate with equipment code 002BA, which is labeled as an implicit system failure device; 001PO is the system main pump, which is labeled as an explicit initiating event device; and 011RF is the oil cooler with equipment number RCS001MO, which is labeled as an implicit initiating event device.

[0048] Table 2. List of Equipment in Category 2

[0049] S103: Calculate the risk contribution index corresponding to the equipment in the second classification set based on the PSA model. The risk contribution index includes the probability of conditional core damage, the probability of a large amount of radioactive release in the early stage of condition, and the risk increase equivalent.

[0050] Furthermore, since equipment that causes mitigation system failure due to aging does not directly trigger an accident, its PSA propagation chain is: accident has occurred - mitigation system failure - risk amplification. This aligns with the risk increase equivalent expression, which states that when the equipment inevitably fails, the overall risk is amplified by a certain amount. Therefore, the risk increase equivalent is calculated for this type of equipment. On the other hand, for other equipment that will cause an initiating event after aging, the PSA propagation chain is: equipment aging - initiating event - accident sequence unfolding - whether the core is damaged. This is related to the degree of danger after the accident occurs. Therefore, the probability of conditional core damage and the probability of conditional early large-scale radioactive release are calculated for this type of equipment.

[0051] Further, the probability of conditional core damage and the probability of conditional early mass radioactive release corresponding to the explicit device and the implicit device of the initiating event are calculated, respectively, wherein the probability of conditional core damage is expressed as follows: , in The condition is the core damage probability. Let Fi be the probability of core damage, and Fi be the frequency of occurrence of the i-th type of initiating event; the expression for the probability of a large amount of radioactive release in the early stage under the condition is as follows: , in The probability of a large-scale radioactive release in the early stages under the aforementioned conditions. High release frequency in the early stages. Let i be the frequency of occurrence of the i-th type of initiating event.

[0052] Furthermore, the core damage probability and occurrence frequency of the explicit initiation event device are calculated based on the PSA model; the core damage probability and occurrence frequency of the implicit initiation event device are the core damage probability and occurrence frequency of the corresponding main device.

[0053] Furthermore, the risk increase equivalent of the explicit and implicit devices of the system failure is calculated, and its expression is as follows: , in Increase the equivalent of the risk corresponding to the i-th basic event. The probability of the top event is given when the basic event is under normal failure probability conditions. The top event includes core damage events or early large-scale radioactive release events.

[0054] Furthermore, as shown in Tables 3 and 4 below, risk contribution indicators were calculated for different equipment. In Table 3, the risk increase equivalent under different consequences was calculated for equipment with equipment codes 001RF and 002DI. In Table 4, the probability of conditional core damage and the probability of conditional early mass radioactive release were calculated for equipment with equipment codes 001PO and 011RF under different operating conditions. POSA represents the full-power operating condition, and POSB represents the hot shutdown operating condition.

[0055] Table 3. List of Equipment in Category II

[0056] Table 4. List of Equipment in Category 2

[0057] Preferably, equivalent basic events are constructed based on the unmodeled devices, and the equivalent basic events are mapped to the initiating event path or mitigation system path in the PSA model, respectively. The occurrence frequency parameter of the initiating event and the failure probability parameter of the mitigation system in the PSA model are corrected, and the risk contribution index is recalculated based on the corrected PSA model.

[0058] Furthermore, acquire equipment functional information, system attribution information, and aging failure mode information for unmodeled equipment. Aging failure modes include one or more of the following: structural fracture, leakage, jamming, failure to operate, performance degradation, and loss of function; determine the corresponding risk propagation path based on the functional attributes of the unmodeled equipment. When unmodeled equipment fails due to aging and may directly cause coolant loss, feedwater loss, power loss, or other initiating events, it is classified as an initiating event-type equipment. When unmodeled equipment fails due to aging and does not directly cause initiating events, but instead leads to a decline in the functionality of safety systems, mitigation systems, or support systems, it is classified as a mitigation system-type equipment. For mitigation system-type equipment, corresponding equivalent basic events are established based on the equipment failure mode, and these equivalent basic events are linked to the fault tree logic of the corresponding mitigation system. For initiating event-type equipment, corresponding equivalent basic events are established based on the equipment failure mode, and these equivalent basic events are linked to the fault tree logic of the corresponding initiating event. If a mitigation system-type equipment may affect the frequency of a certain initiating event and belongs to the special design of a nuclear power plant, then corresponding equivalent basic events need to be established based on the equipment failure mode, and these equivalent basic events need to be linked to the fault tree logic for calculating the frequency of the corresponding initiating event.

[0059] Specifically, in this embodiment, the unmodeled device is a secondary passive cooling pipe, which may rupture due to aging and corrosion. Since it is a special design feature of nuclear power plants and not included in the general database, it is constructed as an equivalent basic event of secondary passive cooling pipe rupture and added to the fault tree corresponding to the main steam pipe rupture initiation event. Subsequently, the occurrence frequency of the initiation event is requantized, and the accident sequence frequency, core damage frequency, and early large-scale radioactive release frequency associated with this initiation event are updated. In other embodiments, the unmodeled device can be a cooling water distribution valve, which may experience a decrease in the cooling capacity of the safety injection system due to aging and jamming. Therefore, it is constructed as an equivalent basic event of cooling water distribution valve failure and added to the safety injection system fault tree. Subsequently, the corresponding system failure probability is requantized, and the associated minimum cut set, top event probability, and accident sequence probability are updated.

[0060] Furthermore, after completing the above mapping, a modified PSA model is formed; the risk contribution index is recalculated based on the modified PSA model; for initiating event-type equipment, the probability of conditional core damage and the probability of conditional early mass radioactive release are recalculated; for mitigation system-type equipment, the risk increase equivalent corresponding to the consequences of core damage and the consequences of early mass radioactive release is recalculated; finally, the recalculated risk contribution index is compared with the risk contribution index of other equipment in the second classification set to determine the severity of aging consequences and aging status of the unmodeled equipment.

[0061] S104: Determine the severity of the consequences for the corresponding equipment based on the risk contribution index.

[0062] Furthermore, a preset risk set is set, which includes risk limits corresponding to different types of equipment in the second category set.

[0063] Specifically, as shown in Table 5 below, which is the explicit equipment risk limit table for the initiating event, calculate the CCDP and CLERP values ​​under their respective operating conditions, and use the following screening criteria to determine the severity of the consequences.

[0064] Table 5. Risk Limits for Explicit Devices Initiating Events

[0065] The table below shows the risk limits for explicit equipment in system failure. The maximum RAW value of the basic events related to aging failure should be calculated separately under the consequences of core damage (CD) and early large radioactive release (LER), and the severity of the consequences should be determined according to the following screening criteria.

[0066] Table 6. Risk Limits for Explicit Devices in System Failures

[0067] Table 7 below shows the implicit equipment risk limit table for the initiating event. Calculate the CCDP and CLERP values ​​of the main equipment under their respective operating conditions, and use the following screening criteria to determine the severity of the consequences.

[0068] Table 7 Risk Limits for Initiating Events of Implicit Devices

[0069] Table 8 below shows the risk limits for implicit equipment in system failure. The maximum RAW value of the corresponding failure mode of the main equipment is calculated under the consequences of core damage (CD) and early large radioactive release (LER), and the severity of the consequences is determined according to the following screening criteria.

[0070] Table 8. Risk Limits for Implicit Devices in System Failures

[0071] Specifically, in this embodiment, the risk contribution indicators calculated by different devices in step S103 are compared according to the above preset risk set to determine the severity of the corresponding consequences as shown in Table 9 below.

[0072] Table 9: Correspondence between the severity of consequences

[0073] Furthermore, based on the results of the above analysis, the aging management outline is updated and resource allocation is optimized to better suit the actual risk levels of nuclear power plant equipment. Specifically, in this embodiment, the aging failure consequences of equipment 001RF are minor, and its original aging failure detection frequency of once every 5 years is changed to once every 10 years; the original aging failure detection frequency of equipment 001PO was once every 6 years, and it is changed to once every 12 years; the original aging failure detection method of equipment 011RF was disassembly inspection, and it is changed to visual inspection; the aging failure consequences of 002DI are moderate, and the current aging management outline configuration is considered reasonable, so no modifications are made.

[0074] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, as some steps may be performed in other orders or simultaneously according to this application. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are preferred embodiments, and the actions and modules involved are not necessarily essential to this application.

[0075] Based on another aspect of the embodiments of this application, the present invention also provides a device for equipment aging modeling and analysis. For example... Figure 6 As shown, the device includes: Verification module 601 is used to acquire the PSA model and perform integrity verification on the PSA model; The construction module 602 is used to classify the equipment of the nuclear power plant according to the modeling status based on the PSA model that has passed the integrity verification, and to construct a first classification set, the first classification set including explicitly modeled equipment, implicitly modeled equipment and unmodeled equipment; and to further divide the first classification set based on the PSA model to form a second classification set. Calculation module 603 is used to calculate the risk contribution index corresponding to the equipment in the second classification set based on the PSA model. The risk contribution index includes the probability of conditional core damage, the probability of a large amount of radioactive release in the early stage of condition, and the risk increase equivalent. The judgment module 604 is used to judge the severity of the consequences of the corresponding equipment based on the risk contribution index.

[0076] As an optional solution, the above-mentioned device is also used to: perform integrity verification on the PSA model, including: verifying whether the PSA model includes a primary PSA model and a secondary PSA model; verifying whether the PSA model includes a power operation model, a low-power operation model, and a shutdown operation model; verifying whether the PSA model includes an internal event model; verifying whether devices in the PSA model whose aging failure affects the frequency of initiation events are linked to the event tree in the PSA model; and verifying whether the modeled devices in the PSA model have passive failure modes.

[0077] As an optional solution, the above-mentioned device is also used to: perform integrity verification on the PSA model, and further includes: supplementing the PSA model that fails the integrity verification with one or more of the following: the primary PSA model or the secondary PSA model; the low-power operating condition model or the shutdown operating condition model; the internal event model; the fault tree coupling logic between the equipment affected by aging failure and the frequency of the initiation event, and establishing the link relationship corresponding to the event tree; the passive failure mode of the modeled equipment.

[0078] As an optional solution, the above-mentioned device is also used for: the modeling state, including: explicit modeling, implicit modeling and no modeling.

[0079] As an optional solution, the above-mentioned apparatus is further used to: classify the equipment of the nuclear power plant according to the modeling status based on the PSA model that has passed the integrity verification, and construct a first classification set, including: marking the equipment of the nuclear power plant according to the explicit modeling, the implicit modeling and the unmodeling methods respectively, and constructing the first classification set.

[0080] As an optional solution, the above-mentioned device is also used to: further divide the first classification set into a second classification set based on the PSA model, including: dividing the devices marked as explicit modeling and implicit modeling according to the consequences of aging failure to form the second classification set.

[0081] As an alternative, the above-mentioned apparatus is also used for: the second classification set, including: explicit devices for initiating events, explicit devices for system failures, implicit devices for initiating events, implicit devices for system failures, and unmodeled devices.

[0082] As an optional solution, the above-mentioned device is also used to: calculate the risk contribution index corresponding to the equipment in the second classification set based on the PSA model, including: calculating the conditional core damage probability and conditional early mass radioactive release probability corresponding to the explicit device of the initiating event and the implicit device of the initiating event, respectively; and calculating the risk increase equivalent of the explicit device of system failure and the implicit device of system failure.

[0083] As an optional solution, the above-mentioned device is also used for: the conditional core damage probability, the expression of which is as follows: ,in The condition is the core damage probability. Let Fi be the probability of core damage, and Fi be the frequency of occurrence of the i-th type of initiating event; the expression for the probability of a large amount of radioactive release in the early stage under the condition is as follows: ,in The probability of a large-scale radioactive release in the early stages under the aforementioned conditions. High release frequency in the early stages. Let i be the frequency of occurrence of the i-th type of initiating event.

[0084] As an optional solution, the above-mentioned device is also used for: the risk increase equivalent, the expression of which is as follows: ,in Increase the equivalent of the risk corresponding to the i-th basic event. The probability of the top event is given when the basic event is under normal failure probability conditions. The top event includes core damage events or early large-scale radioactive release events.

[0085] As an optional solution, the above-mentioned apparatus is further used to: construct equivalent basic events based on the unmodeled device, map the equivalent basic events to the initiating event path or mitigation system path in the PSA model respectively, correct the initiating event occurrence frequency parameter and mitigation system failure probability parameter in the PSA model, and recalculate the risk contribution index based on the corrected PSA model.

[0086] As an optional solution, the above-mentioned device is also used to: determine the severity of the consequences of the corresponding equipment based on the risk contribution index, including: comparing the risk contribution index with data in a preset risk set to determine the severity of the consequences, wherein the preset risk set includes multiple risk limits corresponding to equipment in different second classification sets.

[0087] In this application embodiment, the terms "module" or "unit" refer to a computer program or part of a computer program that has a predetermined function and works with other related parts to achieve a predetermined goal, and can be implemented wholly or partially using software, hardware (such as processing circuitry or memory), or a combination thereof. Similarly, a processor (or multiple processors or memory) can be used to implement one or more modules or units. Furthermore, each module or unit can be part of an overall module or unit that includes the functionality of that module or unit.

[0088] Regarding the apparatus in the above embodiments, the specific manner in which each module performs its operation has been described in detail in the embodiments related to the method, and will not be elaborated upon here.

[0089] According to one aspect of this application, a computer program product is provided, the computer program product comprising a computer program.

[0090] The sequence numbers of the embodiments in this application are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0091] Figure 7 A schematic block diagram of a computer system architecture for implementing an electronic device according to embodiments of the present application is shown.

[0092] It should be noted that, Figure 7 The computer system 700 of the electronic device shown is merely an example and should not impose any limitation on the functionality and scope of use of the embodiments of this application.

[0093] like Figure 7 As shown, the computer system 700 includes a central processing unit (CPU) 701, which is coupled to a read-only memory (ROM) 702. The CPU 701 can perform various appropriate actions and processes based on programs stored in the ROM or loaded from storage section 708 into random access memory (RAM). The RAM 703 also stores various programs and data required for system operation. The CPU 701, ROM 702, and RAM 703 are interconnected via a bus 704. An input / output interface 705 (I / O interface) is also connected to the bus 704.

[0094] The following components are connected to the input / output interface 705: Input section 706, including but not limited to one or more of the following: keyboard, mouse, touch screen, touchpad, buttons, microphone, camera, biometric device, and various sensors; Output section 707, including but not limited to one or more of the following: display (e.g., liquid crystal display (LCD), organic light-emitting diode display (OLED), mini-LED display, micro-LED display, e-ink screen, head-up display (HUD), etc.), speaker, buzzer, indicator light, vibration device, etc.; Storage section 708, including but not limited to hard disk, solid-state drive, flash memory, etc. (the specific types can be found in the relevant description of memory in this application); and Communication section 709, including one or more of the following: wired communication modules (e.g., local area network (LAN) card, modem, Ethernet interface, CAN bus interface, USB interface, serial interface, etc.) and / or wireless communication modules (e.g., Wi-Fi module, Bluetooth module, Zigbee module, LoRa module, 4G / 5G communication module, NB-IoT module, etc.). The communication unit 709 performs communication processing via networks such as the Internet, local area network, wide area network, and vehicle networks (such as CAN bus, vehicle Ethernet). The driver 710 can also be connected to the input / output interface 705 as needed. Removable media 711, such as disks, optical disks, magneto-optical disks, semiconductor memory, USB flash drives, memory cards (such as SD cards, TF cards), etc., can be installed on the driver 710 as needed so that computer programs read from them can be installed into the storage unit 708 as required.

[0095] Specifically, according to embodiments of this application, the processes described in the various method flowcharts can be implemented as computer software programs. For example, embodiments of this application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via communication section 709, and / or installed from removable medium 711. When the computer program is executed by central processing unit 701, it performs various functions defined in the system of this application.

[0096] According to another aspect of the embodiments of this application, an electronic device for a device aging modeling and analysis method is also provided. This embodiment uses this electronic device as an example of a terminal device. Figure 8As shown, the electronic device includes a memory 802 and a processor 804. The memory 802 stores a computer program, and the processor 804 is configured to execute the steps in any of the above method embodiments via the computer program.

[0097] Optionally, in this embodiment, the aforementioned electronic device may be located in at least one of a plurality of network devices in a computer network.

[0098] Optionally, in this embodiment, the processor may be configured to execute the methods in the embodiments of this application via a computer program.

[0099] Alternatively, as those skilled in the art will understand, Figure 8 The structure shown is for illustrative purposes only. Figure 8 This does not limit the structure of the aforementioned electronic devices. For example, the electronic device may also include components that are more... Figure 8 The more or fewer components shown (such as network interfaces, etc.), or having the same Figure 8 The different configurations shown.

[0100] The memory 802 can be used to store software programs and modules, such as the program instructions / modules corresponding to the device aging modeling and analysis method and apparatus in this embodiment. The processor 804 is coupled to the memory 802. By running the software programs and modules stored in the memory 802, various functional applications and data processing are executed, thereby realizing the aforementioned device aging modeling and analysis method. In some instances, the memory 802 may further include a memory remotely located relative to the processor 804. These remote memories can be connected to the terminal via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof. Specifically, the memory 802 can be used, but is not limited to, to store collected operational data or device data. As an example, such as... Figure 8 As shown, the memory 802 may include, but is not limited to, the verification module 601, construction module 602, calculation module 603, and judgment module 604 in the aforementioned device aging modeling and analysis device. Furthermore, it may include, but is not limited to, other module units in the aforementioned device, which will not be elaborated upon in this example.

[0101] Optionally, the transmission device 806 described above is used to receive or send data via a network. Specific examples of the network described above may include wired networks and wireless networks. In one example, the transmission device 806 includes a Network Interface Controller (NIC), which can be connected to other network devices and routers via a network cable to communicate with the Internet or a local area network. In another example, the transmission device 806 is a Radio Frequency (RF) module, which is used to communicate with the Internet wirelessly.

[0102] In addition, the above-mentioned electronic device also includes: a display 808 for displaying the above-mentioned operating data or device data; and a connection bus 810 for connecting the various module components in the above-mentioned electronic device.

[0103] In the embodiments of this application, the processor can be any hardware unit with data processing and instruction execution capabilities, including but not limited to a central processing unit (CPU), microprocessor, microcontroller unit (MCU), digital signal processor (DSP), graphics processing unit (GPU), neural processing unit (NPU), tensor processing unit (TPU), application-specific integrated circuit (ASIC), field-programmable gate array (FPGA), complex programmable logic device (CPLD), system-on-chip (SoC), microcontroller, or any combination of the above devices. The processor can be a single-core processor or a multi-core processor; it can be integrated into a single chip or distributed across multiple chips or multiple physical devices.

[0104] In embodiments of this application, the memory may include random access memory (RAM), such as static random access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDR SDRAM), etc. The memory may also include non-volatile memory, such as read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), flash memory (including but not limited to NAND Flash, NOR Flash), solid-state drive (SSD), embedded multimedia card (eMMC), universal flash storage (UFS), magnetic storage devices (such as hard disks), ferroelectric memory (FRAM), magnetoresistive memory (MRAM), phase-change memory (PCM), resistive random access memory (ReRAM), or one or more other non-volatile solid-state storage media.

[0105] In this application, "memory," "computer-readable storage medium," and "computer-readable medium" refer to the same or related concepts and can be used interchangeably. Specifically, when the aforementioned types of memory are used to store computer program instructions and / or data, they constitute the computer-readable storage medium as referred to in this application; conversely, the physical implementation of the computer-readable storage medium as referred to in this application can be any one or more of the aforementioned types of memory. Those skilled in the art should understand that the computer-readable storage medium can be a single medium or a distributed medium (e.g., a combination of storage media distributed across multiple physical devices or multiple chips).

[0106] In this application, the computer-readable storage medium is a non-transitory computer-readable storage medium, which refers to a physical storage device capable of storing information in a non-transitory manner. This includes, but is not limited to, various types of random access memory, read-only memory, flash memory, solid-state drives, magnetic storage devices, and other storage media with physical form, but excludes transiently propagating signals themselves (such as electromagnetic carrier waves, modulation signals, etc.). Those skilled in the art should understand that "non-transitory" here means that the storage medium has a persistent physical form relative to transiently propagating signals, and does not limit the storage medium to be non-volatile memory; although the aforementioned types of random access memory are volatile memories, they still fall under the category of non-transitory computer-readable storage media as defined in this application.

[0107] According to one aspect of this application, a computer-readable storage medium is provided, from which a processor of an electronic device reads computer instructions, and the processor executes the computer instructions, causing the electronic device to perform a device aging modeling and analysis method provided in one of the various alternative implementations of the above-described device aging modeling and analysis.

[0108] Optionally, in this embodiment, the computer-readable storage medium described above may be configured to store methods for performing the embodiments of this application.

[0109] Optionally, in this embodiment, those skilled in the art will understand that all or part of the steps in the various methods of the above embodiments can be implemented by a program instructing the hardware related to the terminal device, and the program can be stored in a computer-readable storage medium.

[0110] The sequence numbers of the embodiments in this application are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0111] If the integrated units in the above embodiments are implemented as software functional units and sold or used as independent products, they can be stored in the aforementioned computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause one or more electronic devices to execute all or part of the steps of the methods described in the various embodiments of this application.

[0112] In the above embodiments of this application, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0113] In the several embodiments provided in this application, it should be understood that the disclosed application can be implemented in other ways. The device embodiments described above are merely illustrative; for example, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the displayed or discussed mutual couplings, direct couplings, or communication connections may be through some interfaces; indirect couplings or communication connections between units or modules may be electrical or other forms.

[0114] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0115] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0116] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

[0117] In summary, as can be seen from the above description, the embodiments of the present invention achieve the following technical effects: 1. This invention proposes a method, apparatus, storage medium, and electronic device for equipment aging modeling and analysis. By verifying the integrity of the PSA model, it ensures that the PSA model used in subsequent risk analysis has a complete accident sequence and risk propagation logic. The device is classified according to its modeling state in the PSA model, and further subdivided into a second category set based on basic events, which can distinguish the role paths of different types of equipment in the accident risk propagation process. Furthermore, based on the PSA model, risk contribution indicators such as the probability of conditional core damage, the probability of early-stage large-scale radioactive release, and the risk increase equivalent are calculated for the corresponding equipment. This allows for quantitative analysis of the consequences of equipment aging failure from multiple dimensions, including core damage risk, radioactive release risk, and risk sensitivity. This improves the consistency and completeness of the aging risk analysis results for equipment in different modeling states, as well as the accuracy of judging the severity of equipment consequences, greatly reducing the probability of major accidents caused by aging identification errors.

[0118] 2. This invention proposes a method, apparatus, storage medium, and electronic device for equipment aging modeling and analysis. By verifying the completeness of the primary PSA model, secondary PSA model, different operating condition models, and internal event models in the PSA model, and supplementing the missing accident models, operating condition models, and equipment failure logic, the accident propagation path after equipment aging failure can form a complete association between the event tree and the fault tree. This avoids the risk calculation results being too low due to missing accident sequences, missing operating conditions, or missing equipment failure logic, thereby improving the accuracy and reliability of equipment aging risk analysis results.

[0119] 3. This invention proposes a method, apparatus, storage medium, and electronic device for equipment aging modeling and analysis. By classifying equipment into explicit modeling, implicit modeling, and no modeling, and further dividing it into a second category based on whether equipment aging failure affects the occurrence of an initiating event or the function of a mitigation system, different types of equipment are subjected to risk propagation analysis corresponding to either the frequency change path of the initiating event or the failure path of the mitigation system. Specifically, for initiating event equipment, the probability of conditional core damage and the probability of a large amount of early-stage radioactive release reflect the risk of consequences after an accident. For system failure equipment, the risk increase equivalent reflects the amplification of the overall risk level by the equipment failure. This avoids the distortion of analysis results caused by using the same risk index for equipment with different action paths, and improves the consistency of aging consequence analysis results for different types of equipment.

[0120] 4. This invention proposes a method, apparatus, storage medium, and electronic device for equipment aging modeling and analysis. It constructs equivalent basic events for unmodeled equipment and maps them to the initiating event path or mitigation system path in the PSA model. It corrects the occurrence frequency parameters of the initiating event and the failure probability parameters of the mitigation system, enabling unmodeled equipment to participate in the accident propagation calculation of the event tree and fault tree. This avoids unmodeled equipment being ignored by default because it has not entered the PSA risk propagation chain, thereby reducing the omission of equipment aging risks and improving the completeness of the judgment results on the severity of equipment consequences.

[0121] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

[0122] It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes the element.

[0123] It should be noted that, in the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the present invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

Claims

1. A method for modeling and analyzing equipment aging, characterized in that, include: Obtain the PSA model and perform integrity verification on the PSA model; Based on the PSA model that has passed the integrity verification, the equipment of the nuclear power plant is classified according to the modeling status to construct a first classification set, which includes explicitly modeled equipment, implicitly modeled equipment, and unmodeled equipment. Based on the PSA model, the first classification set is further divided to form a second classification set; Based on the PSA model, the risk contribution index corresponding to the equipment in the second classification set is calculated. The risk contribution index includes the probability of conditional core damage, the probability of a large amount of radioactive release in the early stage of condition, and the risk increase equivalent. The severity of the consequences for the corresponding equipment is determined based on the aforementioned risk contribution indicators.

2. The method according to claim 1, characterized in that, The integrity verification of the PSA model includes: Verify whether the PSA model contains a first-level PSA model and a second-level PSA model; Verify whether the PSA model includes a power operation model, a low power condition model, and a shutdown condition model; Verify whether the PSA model includes an internal event model; Verify whether devices whose aging failure affects the frequency of initiating events in the PSA model are linked to the event tree in the PSA model; Verify whether the device modeled in the PSA model has a passive failure mode.

3. The method according to claim 2, characterized in that, The integrity verification of the PSA model also includes: For PSA models that fail the integrity verification, supplement with one or more of the following: The primary PSA model or the secondary PSA model; The low-power operating condition model or the reactor shutdown operating condition model; The internal event model; The fault tree coupling logic between the equipment affected by aging failure and the frequency of the initiating event is established, and a link relationship corresponding to the event tree is established. The passive failure mode of the modularized device.

4. The method according to claim 1, characterized in that, The modeling state includes: Explicit modeling, implicit modeling, and no modeling.

5. The method according to claim 4, characterized in that, Based on the PSA model that has passed the integrity verification, the equipment of the nuclear power plant is classified according to its modeling status to construct a first classification set, including: The equipment in the nuclear power plant is labeled according to the explicit modeling, implicit modeling, and unmodeling methods respectively, and the first classification set is constructed.

6. The method according to claim 4, characterized in that, Based on the PSA model, the first classification set is further divided to form a second classification set, including: The devices labeled as explicitly modeled and implicitly modeled are divided into the second category set according to the consequences of aging failure.

7. The method according to claim 1, characterized in that, The second category set includes: Explicit device of initiating event, explicit device of system failure, implicit device of initiating event, implicit device of system failure, and unmodeled device.

8. The method according to claim 7, characterized in that, Based on the PSA model, the risk contribution index corresponding to the equipment in the second classification set is calculated, including: Calculate the conditional core damage probability and the conditional early mass radioactive release probability corresponding to the explicit device of the initiation event and the implicit device of the initiation event, respectively; Calculate the risk increase equivalent of the explicit and implicit devices that fail in the system.

9. The method according to claim 7, characterized in that, The conditional core damage probability is expressed as follows: ， in The condition is the core damage probability. Let Fi be the probability of core damage, and Fi be the frequency of occurrence of the i-th type of initiating event; the expression for the probability of a large amount of radioactive release in the early stage under the condition is as follows: ， in The probability of a large-scale radioactive release in the early stages under the aforementioned conditions. High release frequency in the early stages. Let i be the frequency of occurrence of the i-th type of initiating event.

10. The method according to claim 1, characterized in that, The risk increase equivalent is expressed as follows: ， in Increase the equivalent of the risk corresponding to the i-th basic event. The probability of the top event is given when the basic event is under normal failure probability conditions. The top event includes core damage events or early large-scale radioactive release events.

11. The method according to claim 1, characterized in that, Also includes: Based on the unmodeled equipment, equivalent basic events are constructed, and the equivalent basic events are mapped to the initiating event path or mitigation system path in the PSA model. The initiating event occurrence frequency parameter and mitigation system failure probability parameter in the PSA model are corrected, and the risk contribution index is recalculated based on the corrected PSA model.

12. The method according to claim 1, characterized in that, The severity of the consequences for the corresponding equipment is determined based on the aforementioned risk contribution indicators, including: The risk contribution index is compared with the data in a preset risk set to determine the severity of the consequences. The preset risk set includes multiple risk limits corresponding to devices in different second category sets.

13. A device for modeling and analyzing equipment aging, characterized in that, include: The verification module is used to acquire the PSA model and perform integrity verification on the PSA model. A construction module is used to classify the equipment of the nuclear power plant according to the modeling status based on the PSA model that has passed the integrity verification, and to construct a first classification set, the first classification set including explicitly modeled equipment, implicitly modeled equipment and unmodeled equipment; Based on the PSA model, the first classification set is further divided to form a second classification set; The calculation module is used to calculate the risk contribution index corresponding to the equipment in the second classification set based on the PSA model. The risk contribution index includes the probability of conditional core damage, the probability of a large amount of radioactive release in the early stage of condition, and the risk increase equivalent. The judgment module is used to determine the severity of the consequences for the corresponding equipment based on the risk contribution index.

14. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes a stored computer program, wherein the computer program, when executed by an electronic device, performs the method according to any one of claims 1 to 12.

15. A computer program product, comprising a computer program, characterized in that, When executed by a processor, the computer program implements the steps of the method according to any one of claims 1 to 12.

16. An electronic device comprising a memory and a processor, characterized in that, The memory stores a computer program, and the processor is configured to execute the method according to any one of claims 1 to 12 through the computer program.

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