A method for evaluating reliability of a passive system of a nuclear power plant

Abstract

The embodiment of the application discloses a kind of nuclear power plant passive system reliability evaluation methods, belong to system reliability evaluation technical field, solve the problem that existing system reliability evaluation method cannot truly reflect the failure probability and main contribution factor of passive system.The nuclear power plant passive system reliability evaluation method includes the following steps: whether the passive system can be analyzed to carry out the explicit function division of hardware configuration scheme, if yes, the passive system is functionally divided, and all hardware configuration schemes obtained;And each hardware configuration scheme and its corresponding physical process failure probability are logically combined to obtain the system failure probability of the passive system system;If not, the system failure probability of the passive system is obtained based on sampling mode.The system failure probability of passive system obtained by the method in the application is closer to the real situation of passive system.

Description

Technical Field

[0001] This invention relates to the field of system reliability assessment technology, and in particular to a method for assessing the reliability of passive systems in nuclear power plants. Background Technology

[0002] System reliability assessment is a crucial component of probabilistic safety assessment for nuclear power plants. Currently, system reliability assessment primarily focuses on evaluating system hardware, establishing fault tree models based on success criteria (i.e., the minimum hardware configuration required to perform system functions) to analyze system failures caused by equipment malfunctions. However, passive systems rely on natural circulation, and factors such as cold sources, heat sources, and the system's operating environment have significant uncertainties. These uncertainties may lead to the system failing to perform its functions (i.e., physical process failure) even when hardware failure is not or only partially occurs.

[0003] Hardware failure and physical process failure are mutually conditional; that is, the probability of physical process failure varies under different hardware configurations. This logical relationship should be considered in the system reliability evaluation model. Current methods fail to reflect this mutually conditional relationship between physical process failure and hardware failure.

[0004] Meanwhile, since the hardware success criteria are usually calculated based on design conditions (which are conservative in most cases), while the failure probability of the physical process is calculated based on the actual operating environment of the system, the two are not simply logically related by "OR". In the fault tree, they are simply expressed as logically "OR", which cannot truly reflect the failure probability and main contributing factors of the passive system. Summary of the Invention

[0005] Based on the above analysis, the embodiments of the present invention aim to provide a logical combination method for reliability assessment of passive systems in nuclear power plants, in order to solve the problem that existing system reliability assessment methods cannot truly reflect the failure probability and main contributing factors of passive systems.

[0006] This invention discloses a method for reliability assessment of passive systems in nuclear power plants, comprising:

[0007] Analyze whether the passive system can be clearly functionally divided according to the hardware configuration scheme.

[0008] If possible, the passive system is functionally divided to obtain all hardware configuration schemes; and each hardware configuration scheme and its corresponding physical process failure probability are logically combined to obtain the system failure probability of the passive system.

[0009] If not, the system failure probability of the passive system is obtained based on a sampling method.

[0010] Based on the above solution, the present invention also makes the following improvements:

[0011] Furthermore, the system failure probability P of the passive system obtained through the aforementioned logical combination method sys Represented as:

[0012] P sys =P C1 ×P C1_POF +...+P Ci ×P Ci_POF +...+P CN ×P CN_POF (1)

[0013] Among them, P Ci Let P represent the probability of the i-th hardware configuration scheme occurring. Ci_POF Let N represent the probability of physical process failure under the i-th hardware configuration scheme, and let N represent the total number of the hardware configuration schemes.

[0014] Furthermore, the probability of occurrence of each hardware configuration scheme is obtained by constructing a fault tree.

[0015] Furthermore, the method of obtaining the system failure probability of the passive system based on sampling includes:

[0016] Set the number of simulated samplings;

[0017] During each simulation sampling, the device status of each device in the passive system and the parameter value of each system status parameter are randomly selected, and the system status of the passive system under this simulation sampling is obtained based on the random sampling results; the device status and system status are both success or failure.

[0018] The system failure probability of the passive system is obtained based on the number of times the system state is in failure and the set number of simulation samplings.

[0019] Furthermore, the device status of each device in the passive system is randomly selected, including:

[0020] Based on the probability density distribution function of the equipment failure data, randomly select the equipment failure probability value q from it;

[0021] A random number ζ is drawn from the interval (0,1). If ζ < q, the device status is invalid; otherwise, the device status is successful.

[0022] Furthermore, the system state parameters are physical parameters that describe the operating conditions of the passive system.

[0023] Furthermore, the system state of the passive system under this simulation sampling is obtained based on the random sampling results, including:

[0024] Obtain a physical model to describe the thermal behavior of the system;

[0025] The parameter values ​​of the device status and system status parameters are used as input conditions for the physical model;

[0026] Run the physical model to obtain the model output values;

[0027] The model output value is compared with the set safety threshold to determine the system state under this simulation sampling.

[0028] Furthermore, the system failure probability P of the passive system obtained through sampling is... sys Represented as:

[0029] P sys =S / N s (2)

[0030] Where, N s This indicates the set number of simulation samplings, and S represents the number of times the system state is in failure.

[0031] Furthermore, by analyzing the flowchart of the passive system, it can be determined whether the passive system can be clearly functionally divided.

[0032] Furthermore, the aforementioned explicit functional division refers to the ability to exhaustively list all possible hardware configuration schemes for the passive system;

[0033] The aforementioned hardware configuration scheme refers to a possible hardware state of a passive system resulting from the success / failure state of each device in the passive system.

[0034] Compared with the prior art, the present invention can achieve at least one of the following beneficial effects:

[0035] The reliability assessment method for passive systems of nuclear power plants disclosed in this invention has the following advantages:

[0036] (1) By analyzing whether the passive system can be clearly divided into hardware configuration schemes, the methods for obtaining the system failure probability under the conditions of clearly divided and undivided functions are given respectively. That is, by analyzing the failure mechanism of the passive system under different functional division methods, the obtained system failure probability is closer to the real situation of the passive system. At the same time, the main contributing factors to the system failure are closer to the real situation, which is conducive to design improvement.

[0037] (2) When the system design can clearly define n hardware configuration schemes and their physical process failure probabilities:

[0038] Determine possible hardware configuration schemes: The probability of occurrence of a hardware configuration scheme can be calculated using the fault tree method. The fault tree method is a mature logical method with commercial software available, which facilitates logical combination with physical process failures (functional failures).

[0039] Physical process failure probability: The system state needs to be calculated using thermal software. The hardware configuration scheme (equipment success / failure status) is the input condition for the calculation. Under a certain system hardware configuration, the failure probability of the system physical process can be calculated, which can simplify the analysis process and improve the calculation efficiency.

[0040] Logical combination of system hardware and physical process failure: In this case, there is a one-to-one correspondence between the hardware configuration scheme and the corresponding physical process failure probability. This embodiment provides a method for describing this logical combination using a fault tree. This method is simple to learn and easy to implement in engineering.

[0041] (3) When the system design makes it difficult to clearly define the functional division into n hardware configuration schemes:

[0042] In this situation, the system hardware configuration status and physical process failure (functional failure) cannot be analyzed separately. This invention provides a method to combine them through sampling to reflect the logical relationship between the two.

[0043] In this invention, the above-described technical solutions can be combined with each other to achieve more preferred combinations. Other features and advantages of this invention will be set forth in the following description, and some advantages may become apparent from the description or be learned by practicing the invention. The objects and other advantages of this invention can be realized and obtained from what is particularly pointed out in the description and drawings. Attached Figure Description

[0044] The accompanying drawings are for illustrative purposes only and are not intended to limit the invention. Throughout the drawings, the same reference numerals denote the same parts.

[0045] Figure 1 This is a flowchart of the reliability assessment method for passive systems of nuclear power plants provided in Embodiment 1 of the present invention;

[0046] Figure 2 This is a schematic diagram of a passive system consisting of three rows of water supply pipelines.

[0047] Figure 3 This is a structural diagram of a passive safety system including a containment sump filter and an IRWST filter; wherein,

[0048] Figure 3 (a) indicates the AP1000's emergency core cooling system;

[0049] Figure 3 (b) shows a schematic diagram of the modular design structure of the P1000 filter screen;

[0050] Figure 4 This is a flowchart for obtaining the system failure probability of the passive system based on a sampling method;

[0051] Figure 5 A fault tree diagram that combines the logical combination of hardware configuration schemes and physical process failures (probabilities) described by fault tree;

[0052] Figure 6 A fault tree model is constructed based on a passive system diagram formed by three rows of water supply pipelines; among which,

[0053] Figure 6 (a) represents a fault tree model of a water pipeline in operation;

[0054] Figure 6 (b) represents the fault tree model of the two water pipelines during operation;

[0055] Figure 6 (c) represents the fault tree model when all three water pipelines are not in operation;

[0056] Figure 7 A system logic combination fault tree diagram is constructed based on a passive system diagram formed by three rows of water supply pipelines. Detailed Implementation

[0057] Preferred embodiments of the present invention will now be described in detail with reference to the accompanying drawings, which form part of this application and are used together with the embodiments of the present invention to illustrate the principles of the present invention, but are not intended to limit the scope of the present invention.

[0058] Example 1

[0059] A specific embodiment of the present invention discloses a method for reliability assessment of passive systems in nuclear power plants, the flowchart of which is shown below. Figure 1 As shown. The method includes:

[0060] Step S1: Analyze whether the passive system can be clearly functionally divided according to the hardware configuration scheme.

[0061] If possible, proceed to step S2;

[0062] If not, proceed to step S3;

[0063] Step S2: Perform functional division on the passive system to obtain all hardware configuration schemes; and logically combine each hardware configuration scheme with its corresponding physical process failure probability to obtain the system failure probability of the passive system.

[0064] Step S3: Obtain the system failure probability of the passive system based on the sampling method.

[0065] Compared with the prior art, this embodiment analyzes whether the passive system can be clearly functionally divided by hardware configuration scheme, and provides methods for obtaining the system failure probability under different functional division methods. That is, by analyzing the failure mechanism of the passive system under different functional division methods, the obtained system failure probability is closer to the real situation of the passive system.

[0066] In step S1, the ability to clearly define the functions of the passive system is determined by analyzing its flowchart. In practice, technicians can determine the system's operational flow by analyzing the flowchart, and thus determine whether the passive system can be clearly defined in terms of hardware configuration schemes. Clearly defined functions here mean being able to exhaustively list all possible hardware configuration schemes for the passive system. A hardware configuration scheme refers to a possible hardware state of the passive system resulting from each device exhibiting a successful / failed state; for example, if only one water supply line is available in the passive system, this is considered a "hardware configuration scheme."

[0067] For example, Figure 2 This is a schematic diagram of a passive system structure consisting of three rows of water supply pipelines (valve galleries: PCS valve gallery). Analysis of the flowchart of this passive system reveals that it allows for a clear functional division of hardware configuration schemes. In this system, each row of water pipelines can be considered a separate "column," and each column can operate independently (i.e., supply water independently), with all columns operating in parallel. By combining the operational status of each row of water pipelines, various hardware configuration schemes can be formed. Specifically,

[0068] 1) Analyze the contribution of each parallel "column" to the system's functionality;

[0069] Example: Figure 2 The three water supply lines (valve gallery: PCS valve gallery) in the containment, the water supply of lines 1, 2 and 3 in operation; is there any possibility of success when there is no cooling water on the outer wall of the containment (i.e. all three water supply lines fail).

[0070] 2) Based on the above analysis results, run different numbers of parallel "columns" to obtain all hardware configuration schemes, for example: Figure 2 The three columns of water supply pipelines (valve assembly: PCS valve gallery) can form four hardware configuration schemes:

[0071] a) One water pipeline is in operation;

[0072] b) Two water pipelines are in operation;

[0073] c) All three water lines are not operational; that is, all water lines fail; at this time, there is no cooling water (Note: The function of this system is to transfer heat from inside the containment to the atmosphere. The role of the cooling water on the outer wall is to enhance heat exchange. Even without the cooling water on the outer wall, there is still a possibility of success).

[0074] d) Three water pipelines are in operation;

[0075] For example, Figure 3 This is a passive system that includes a containment sump filter and an IRWST filter. Figure 3 (a) describes the AP1000's emergency core cooling system. In the event of a coolant loop rupture, after the safety injection tank and core makeup water tank have completed injection, water is passively injected into the coolant loop through the Internal Refueling Water Tank (IRWST). Filters within the IRWST intercept debris to ensure core cooling. When the IRWST level reaches low-low, a significant amount of water has accumulated in the bottom area of ​​the containment, triggering passive recirculation of the core from the containment. During the recirculation phase in the containment sump, the sump filters effectively ensure long-term core cooling. The AP1000 filters employ a modular design, consisting of many small filter units, with a structure as follows: Figure 3 As shown in (b), the filter unit is designed as a pocket-like structure with one end open and the remaining sides closed by perforated metal sheets. Each IRWST filter consists of approximately 600 filter units, and the inlet of each filter unit is designed with a certain taper. When many filter units are combined together, a channel is formed between adjacent filter units to store the fluid passing through the perforated plate. The opening of the filter unit faces the direction of fluid inflow, which can prevent larger debris from entering the containment. The fluid collects at the bottom of the filter unit and flows into the passive core cooling system. Each containment recirculation filter consists of 2550 filter units. The filter design takes into account the impact of debris from the containment on the filter structure. The fluid inflow direction of the containment recirculation filter is the side of the filter unit. By analyzing the flowchart of this passive system, it can be seen that the passive system cannot be clearly functionally divided into hardware configuration schemes. The reason is: each IRWST filter consists of approximately 600 filter units, and each containment recirculation filter consists of 2550 filter units, as shown in (b). Figure 3 (b) The probability of blockage occurring can be described by the probability density curve of the blockage area, which cannot be exhaustively listed.

[0076] The above analysis shows that technicians can determine the system's operation process and whether the system can be clearly divided into functions by analyzing the flowchart of the passive system.

[0077] Typically, hardware configuration significantly impacts system thermal behavior. For different hardware configurations, the probability of physical process failure needs to be calculated separately. Physical process failure refers to system failure caused by deviations in system operating parameters from design values, leading to a discrepancy between actual system operation and design conditions. Preferably, during step S2, a passive system reliability model is established using a fault tree approach, and the probability of occurrence for each hardware configuration is calculated using the fault tree. Simultaneously, physical process failure under that hardware configuration is treated as a basic event and combined with the hardware configuration using an "AND" logic, while different hardware configurations are combined using an "OR" logic. The system failure probability P of the passive system is obtained through this logical combination. sys Represented as:

[0078] P sys =P C1 ×P C1_POF +...+P Ci ×P Ci_POF +...+P CN ×P CN_POF (1)

[0079] Among them, P Ci Let P represent the probability of the i-th hardware configuration scheme occurring. Ci_POF Let N represent the probability of physical process failure under the i-th hardware configuration scheme, and let N represent the total number of the hardware configuration schemes.

[0080] A fault tree diagram is used to describe the logical combination of hardware configuration schemes and physical process failures (probabilities). Here, "△" represents a transition gate, indicating that the input is a fault tree that calculates the probability of the current hardware configuration scheme occurring; "○" represents a basic event, indicating that the input is the probability of physical process failure under the current hardware configuration scheme.

[0081] It should be noted that since the operating conditions of devices under different hardware configurations are not the same, the calculation methods for the probability of physical process failure may differ. This embodiment does not limit the calculation method for the probability of physical process failure under each hardware configuration, as long as the probability of physical process failure under each hardware configuration can be obtained. Various calculation methods for the probability of physical process failure have been studied. Here, only one common calculation process for the probability of physical process failure is provided for reference:

[0082] Step 1: Based on the model describing the system behavior (e.g., a thermal model, usually provided by the design team), determine the probability density distribution of the input parameters. Methods include:

[0083] ① Fitting a probability distribution based on historical data;

[0084] Example: Atmospheric temperature, normal distribution (provided by meteorological departments and other professional departments)

[0085] ② Determine its distribution range based on the design tolerance (the probability distribution of such parameters can usually be taken as a uniform distribution);

[0086] Example: Figure 1 For the medium system, the containment diameter is assumed to be uniformly distributed: [Design value - Permissible deviation, Design value + Permissible deviation]

[0087] ③ The probability density distribution of the input parameters is determined by experts, including designers and operators.

[0088] Step 2: Randomly select multiple sets of input parameter samples based on the probability density distribution of the input parameters; this can be achieved using sampling functions from commercial application platforms. Example: Using MATLAB as an example, a uniform distribution sampling function is used.

[0089] X = rand[lower limit, upper limit]

[0090] Step 3: For each set of input parameter samples, based on the model describing the system behavior under the current hardware configuration, calculate the model output value. Determine whether the system has failed based on the output value: a system failure occurs if the output value exceeds the safety threshold given in the system design. Example: Figure 2 In the example system, a system failure occurs when the pressure inside the containment exceeds the design pressure limit.

[0091] Step 4: Calculate the probability of physical process failure of the system under the current hardware configuration.

[0092] Physical process failure probability = Number of system failures / Number of samples

[0093] Step S3: Obtain the system failure probability of the passive system based on sampling. The flowchart is as follows: Figure 4 shown, specifically,

[0094] Step S31: Set the number of simulated samplings; here, the number of simulated samplings is the sample size. Typically, this sample size should be sufficient to generate several system failures (system failures here include physical process failures and hardware failures) to meet the requirements for calculating the probability of system failure.

[0095] Step S32: During each simulation sampling, randomly select the device status of each device in the passive system and the parameter value of each system status parameter, and obtain the system status of the passive system under this simulation sampling based on the random sampling result; the device status and system status are both success or failure.

[0096] Specifically, in this step, the following is performed:

[0097] Step S321: Randomly select the device status of each device in the passive system in the following manner:

[0098] For each device in the system, failure data (usually failure probability and failure rate) and its probability distribution (e.g., log-normal distribution, uniform distribution) are obtained from the device failure database. A random sampling method is used to obtain the device status (success / failure) in each round of simulation based on the above data. Here, failure probability (q) refers to the probability of a component failing while performing its functional requirements, that is, the probability that the component has failed before or at the time of the requirement. Failure rate (λ) refers to the probability that a component that has not failed at time t will fail within a unit of time at time t. In this case, q = 1 - e^(-λ / t). -λt .

[0099] The process of obtaining equipment status through random sampling is briefly described below:

[0100] 1. Based on the probability density distribution function of the equipment failure data, randomly select the equipment failure probability value q from it;

[0101] 2. Draw a random number ζ in the interval (0,1). If ζ < q, the device status is invalid; otherwise, the device status is successful.

[0102] Step S322: Randomly select the parameter values ​​of each system state parameter in the passive system using the following method:

[0103] System state parameters, which are physical parameters describing the system's operating conditions, such as power, ambient temperature, and pressure, are input parameters of the physical model describing the system's thermal behavior. These parameters are subject to uncertainty in actual operation, and this uncertainty is described using probability distributions (such as normal distribution, uniform distribution, bimodal normal distribution, etc.). They are usually obtained through historical data statistics, design documents, expert judgment, and other methods. Based on the probability distribution of the above parameters, random sampling methods (such as Monte Carlo simulation, MATLAB and other program platforms with different sampling functions) are used to obtain the parameter values ​​used in each round of simulation.

[0104] Step S323: Obtain the system state of the passive system under this simulation sampling based on the random sampling results, including:

[0105] Step S3231: Obtain a physical model to describe the thermal behavior of the system; here, a physical model describing the thermal behavior of the system is used (usually the model used in system design and safety evaluation, both of which must be completed in nuclear power plant design).

[0106] Step S3232: Use the parameter values ​​of the device status and system status parameters as input conditions for the physical model;

[0107] Step S3233: Run the physical model and obtain the model output values; (e.g., the pressure inside the containment vessel in the example)

[0108] Step S324: Compare the model output value with the set safety threshold to determine the system state under this simulation sampling.

[0109] Example: For Figure 2 In the example of a passive system, the model calculates the pressure inside the containment chamber. The design limit for containment pressure is 0.5 MPa. If the model calculates a value greater than this, the system is considered to have failed.

[0110] Step S33: Based on the number of times the system state is in failure and the set number of simulation samplings, obtain the system failure probability of the passive system. Specifically, the system failure probability P of the passive system obtained through sampling is... sys Represented as:

[0111] P sys =S / N s (2)

[0112] Where, N s This indicates the set number of simulation samplings, and S represents the number of times the system state is in failure.

[0113] In summary, probabilistic safety assessment is one of the important methods for nuclear power plant safety analysis, complementing and reinforcing deterministic safety assessment. A probabilistic safety analysis report must be submitted in nuclear power plant safety assessment work. Passive safety systems are widely used in advanced reactor design. Given their operational characteristics, physical process failures must be considered in system reliability assessments, as clearly stipulated in the Nuclear Safety Guidelines "Level 1 Probabilistic Safety Analysis of Nuclear Power Plants" (HAD102 / 19). Compared with existing methods that simply logically superimpose system hardware failures and physical process failures, the method provided in this embodiment better reflects the actual operating conditions of the power plant, reveals its true risk level, and helps identify weaknesses in system design and operation management. The specific advantages of this embodiment are as follows:

[0114] 1) The system design can clearly define n hardware configuration schemes and their physical process failure probabilities:

[0115] Determine possible hardware configuration schemes: The probability of occurrence of a hardware configuration scheme can be calculated using the fault tree method. The fault tree method is a mature logical method with commercial software available, which facilitates logical combination with physical process failures (functional failures).

[0116] Physical process failure probability: The system state needs to be calculated using thermal software. The hardware configuration scheme (equipment success / failure status) is the input condition for the calculation. Under a certain system hardware configuration condition, the physical process failure probability of the system can be calculated, which can simplify the analysis process and improve the calculation efficiency.

[0117] Logical combination of system hardware and physical process failures: In this case, there is a one-to-one correspondence between the hardware configuration scheme and the corresponding physical process failure probability. This embodiment presents a method for describing this logical combination using a fault tree. This method is simple to learn and easy to implement in engineering.

[0118] 2) The system design makes it difficult to clearly define the functional division into n hardware configuration schemes.

[0119] In this situation, the system hardware configuration status and physical process failure (functional failure) cannot be analyzed separately. This invention provides a method to combine them through sampling to reflect the logical relationship between the two.

[0120] Example 2

[0121] Embodiment 2 of this invention uses a passive system formed by three rows of feedwater pipelines as an example to illustrate the execution process of the logical combination method for reliability assessment of a nuclear power plant passive system. A schematic diagram of the passive system composed of three rows of feedwater pipelines is shown below. Figure 5 As shown.

[0122] As described in Example 1, the passive system formed by three rows of water supply pipelines can be clearly functionally divided. Example 1 also provides four hardware configuration schemes for this system, namely:

[0123] a) One water pipeline is in operation;

[0124] b) Two water pipelines are in operation;

[0125] c) None of the three water pipelines are operational;

[0126] d) Three water pipelines are in operation;

[0127] The different emergency configurations described above may result in varying water spray volumes, affecting thermal behavior. Using existing methods, the probability of physical process failure for each hardware configuration can be obtained; this process will not be elaborated upon here.

[0128] For each possible system configuration, a fault tree model is established, and its probability of occurrence is calculated. Specifically, Figure 6 A fault tree model is constructed based on a passive system diagram formed by three rows of water supply pipelines; among which, Figure 6 (a) represents a fault tree model of a water pipeline in operation; Figure 6 (b) represents the fault tree model of the two water pipelines during operation; Figure 6 (c) represents the fault tree model when all three water pipelines are not in operation. Furthermore, fault tree calculation is not required when all three water pipelines are in operation. Figure 6 In the figure, PCCS-1, PCCS-2, and PCCS-3 are fault tree models for calculating faults in the first, second, and third columns of water pipelines (valves), respectively. In the figure, "△" is the transfer gate symbol in the fault tree (similar to a subroutine interface).

[0129] After determining the probability of occurrence of each hardware configuration scheme and the corresponding probability of physical process failure, the logical combination process can be executed. The probability of physical process failure under each hardware configuration scheme is treated as a basic event and connected to the desired hardware configuration scheme using an AND gate. Different hardware configuration schemes have different probabilities of physical process failure; logically, this is expressed as: for each hardware configuration scheme, the physical process fails under that hardware configuration condition. Example: For... Figure 2 For passive systems, establish a fault tree model as follows: Figure 7 As shown, where:

[0130] --Only one valve is available, and in this case, the physical process fails. Figure 7 The logic gate "@PCCS-2" is in the middle.

[0131] --Two valves are available, and the physical process fails in this case. Figure 7 Middle logic gate "@PCCS-3"

[0132] --All three valves are unusable (without cooling water), and the physical process fails under these conditions. Figure 7 Basic events in PCCS-4

[0133] --All three types of valves are usable (no fault tree calculation required to determine their probability of occurrence), and in this case, the physical process fails. Figure 7 The basic event "PROCESS3"

[0134] The above situations are logically combined using a fault tree. Each situation is a possible path of system failure. The logical expression is: system failure under configuration 1 "or"... "or" system failure under configuration i "or"... "or" system failure under configuration N;

[0135] System failure probability P sys The expression is:

[0136] P sys =P f1 +...+P fi +...+P fN

[0137] =P C1 ×PC1_POF +...+P Ci ×P Ci_POF +...+P CN ×P CN_POF

[0138] Among them, P fi This represents the probability of system failure under the i-th hardware configuration scheme.

[0139] like Figure 7 As shown, each of the above cases ( Figure 7 The logic gates "@PCCS-2", "@PCCS-3", "@PCCS-4" and the basic event "PROCESS3" are possible pathways to system failure. These various cases are connected using an "OR" gate. Figure 7 The logic gate "@PCCS".

[0140] Those skilled in the art will understand that all or part of the processes of the methods described in the above embodiments can be implemented by a computer program instructing related hardware, and the program can be stored in a computer-readable storage medium. The computer-readable storage medium may be a disk, optical disk, read-only memory, or random access memory, etc.

[0141] The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for reliability assessment of passive systems in nuclear power plants, characterized in that, include: Analyze whether the passive system can be clearly functionally divided according to the hardware configuration scheme. If possible, the passive system is functionally divided to obtain all hardware configuration schemes; and each hardware configuration scheme and its corresponding physical process failure probability are logically combined to obtain the system failure probability of the passive system. If not, obtain the system failure probability of the passive system based on a sampling method; The system failure probability of the passive system obtained through the aforementioned logical combination method Represented as: (1) in, Indicates the first The probability of occurrence of a certain hardware configuration scheme. Indicates the first The probability of physical process failure under various hardware configuration schemes This represents the total number of the aforementioned hardware configuration schemes; The method of obtaining the system failure probability of the passive system based on sampling includes: Set the number of simulated samplings; During each simulation sampling, the device status of each device in the passive system and the parameter value of each system status parameter are randomly selected, and the system status of the passive system under this simulation sampling is obtained based on the random sampling results; the device status and system status are both success or failure. The system failure probability of the passive system is obtained based on the number of times the system state is in failure and the set number of simulation samplings.

2. The reliability assessment method for passive systems of nuclear power plants according to claim 1, characterized in that, The probability of occurrence for each hardware configuration scheme is obtained by constructing a fault tree.

3. The reliability assessment method for passive systems of nuclear power plants according to claim 1, characterized in that, Randomly select the device status of each device in the passive system, including: Based on the probability density distribution function of the equipment failure data, randomly select equipment failure probability values. ; Draw a random number in the interval (0,1). ,if If the device status fails, the device status is invalid; otherwise, the device status is successful.

4. The reliability assessment method for passive systems of nuclear power plants according to claim 1, characterized in that, The system state parameters are physical parameters that describe the operating conditions of the passive system.

5. The reliability assessment method for passive systems of nuclear power plants according to claim 1, characterized in that, The system state of the passive system under this simulation sampling is obtained based on the random sampling results, including: Obtain a physical model to describe the thermal behavior of the system; The parameter values ​​of the device status and system status parameters are used as input conditions for the physical model; Run the physical model to obtain the model output values; The model output value is compared with the set safety threshold to determine the system state under this simulation sampling.

6. The reliability assessment method for passive systems of a nuclear power plant according to any one of claims 1-5, characterized in that, The system failure probability of the passive system obtained through sampling. Represented as: (2) in, This indicates the set number of simulated samplings. This indicates the number of times the system has been in a state of failure.

7. The reliability assessment method for passive systems of nuclear power plants according to claim 1, characterized in that, By analyzing the flowchart of the passive system, it can be determined whether the passive system can be clearly functionally divided.

8. The reliability assessment method for passive systems of nuclear power plants according to claim 7, characterized in that, The aforementioned clear functional division refers to the ability to exhaustively list all possible hardware configuration schemes for a passive system; The aforementioned hardware configuration scheme refers to a possible hardware state of a passive system resulting from the success / failure state of each device in the passive system.

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