Fatigue strength reliability analysis method and system of reactor equipment and medium

Abstract

The invention discloses a fatigue strength reliability analysis method and system for reactor equipment and a medium, and relates to the field of reactor structural mechanics. The method is suitable for conventional fatigue analysis calculation of a reactor equipment structure, the randomness of all input parameters is introduced into calculation, uncertainty in the aspects of geometry, materials, loads and the like is involved, a complete fatigue strength reliability analysis process is established, and the reliability of the fatigue strength is improved. Obtaining the failure probability of the fatigue strength and the sensitivity of the fatigue strength to each input parameter; the transition of reactor equipment structure fatigue analysis from a determination theory to a probability theory is realized; in addition, the scheme of the invention can support the subsequent development of structure optimization related to each input parameter, and meet a series of engineering requirements.

Description

Technical Field

[0001] The invention relates to the field of reactor structural mechanics, and in particular to a fatigue strength reliability analysis method, system and medium for reactor equipment. Background Art

[0002] At present, the structures of reactor equipment are basically designed with the finite life design method (safe life design method). When performing fatigue analysis on reactor equipment in engineering, the linear fatigue cumulative damage theory (such as Miner damage law) is usually used. The fatigue damage of the material under each stress is independent, and the total damage can be linearly accumulated to obtain the total fatigue damage.

[0003] According to the requirements of reactor design specifications (such as ASME, RCC-M, etc.) for fatigue performance analysis, the finite element model is first transiently calculated, and the stress history of the position to be evaluated on the structure is extracted through post-processing. For each transient, the peak time point of stress change is selected as the event point in fatigue analysis, and the corresponding stress is used as the input value of event storage stress. The fatigue curve (SN curve) of the material, the number of cycles of each transient and other parameters are defined in the fatigue analysis module of ANSYS, and the fatigue service coefficient of each evaluation position can be directly calculated. However, the above method is essentially a deterministic method, which believes that material properties, structural dimensions and loads are all fixed values, and does not consider the random fluctuations of the input, and does not consider the calculation errors caused by the uncertainty of the design parameters. This method is simple and intuitive, but in most cases it is extremely conservative, which is not conducive to reducing construction costs and improving economy; for structural design optimization, the current method cannot reflect the reliability of the structure and the sensitivity of the structure to the design parameters, and cannot provide more feedback information and guidance for structural design; for in-service equipment, the current technology is difficult to deal with the life extension problem of reactor equipment through monitoring and recording of operating data and then predicting the life.

[0004] For the analysis and calculation of the fatigue strength of reactor equipment structure, the current design of reactor equipment structure adopts the deterministic method. Some design parameters are artificially multiplied by a certain coefficient for conservative treatment during the design process. This method is simple and intuitive, and has high safety. However, this method cannot reflect the reliability of the structure and the sensitivity of the structure to the design parameters, and cannot obtain the true reliability and failure probability. It cannot be used for global optimization of structural geometry, materials, loads, etc. in the structural design stage, and it is also difficult to achieve the life prediction and life extension needs of reactor equipment based on operation monitoring data. Summary of the invention

[0005] The technical problem to be solved by the present invention is that the traditional reactor equipment structure design method, based on the deterministic method, cannot reflect the reliability of the structure and the sensitivity of the structure to the design parameters, and cannot obtain the true reliability and failure probability; the purpose of the present invention is to provide a fatigue strength reliability analysis method, system and medium for reactor equipment, which are suitable for conventional fatigue analysis calculation of reactor equipment structure, introduce the randomness of each input parameter into the calculation, involve the uncertainty in geometry, material and load, establish a complete fatigue strength reliability analysis process, obtain the failure probability of fatigue strength and the sensitivity of fatigue strength to each input parameter; realize the transition of reactor equipment structure fatigue analysis from determinism to probability theory; through the technical characteristics such as fatigue use coefficient and failure probability, sensitivity results of random characteristic parameters, etc., the reliability of fatigue strength of reactor equipment is quantitatively analyzed; in addition, the scheme of the present invention can support the subsequent structural optimization involving each input parameter to meet a series of engineering requirements.

[0006] The present invention is achieved through the following technical solutions:

[0007] This scheme provides a fatigue strength reliability analysis method for reactor equipment, including:

[0008] Step 1: Determine the random characteristic parameters of fatigue strength according to the reactor equipment type, and randomly sample the random characteristic parameters to obtain the input parameters of each sample point;

[0009] Step 2: Parametric modeling of reactor equipment based on random characteristic parameters;

[0010] Step 3: Perform transient calculation based on the input parameters of each sample point to obtain the fatigue service coefficient of each sample point;

[0011] Step 4: Input the fatigue usage coefficient of each sample point into the constructed fatigue strength reliability model to obtain the sensitivity results of failure probability and random characteristic parameters.

[0012] Working principle of this scheme: The traditional reactor equipment structure design method, based on the deterministic method, cannot reflect the reliability of the structure and the sensitivity of the structure to the design parameters, and cannot obtain the true reliability and failure probability; the purpose of the present invention is to provide a fatigue strength reliability analysis method, system and medium for reactor equipment, which is suitable for conventional fatigue analysis calculation of reactor equipment structure, introduces the randomness of each input parameter into the calculation, involves the uncertainty in geometry, material and load, establishes a complete fatigue strength reliability analysis process, obtains the failure probability of fatigue strength and the sensitivity of fatigue strength to each input parameter; realizes the transition of reactor equipment structure fatigue analysis from determinism to probability; through technical features such as fatigue use coefficient and failure probability, sensitivity results of random characteristic parameters, etc., quantitatively analyzes the reliability of fatigue strength of reactor equipment; in addition, the scheme of the present invention can support the subsequent structural optimization involving various input parameters to meet a series of engineering needs.

[0013] A further optimization scheme is to randomly sample random feature parameters based on the Monte Carlo method to obtain the input parameters of each sample point.

[0014] A further optimization scheme is that the random characteristic parameters of fatigue strength are determined according to the reactor equipment type, including the following method:

[0015] The reactor equipment type is obtained, and the influence and uncertainty of the basic features are analyzed according to the reactor equipment type, wherein the basic features include material properties, structural dimensions and load screens; one or more basic features with the greatest influence and uncertainty are selected as random feature parameters. According to the specific reactor equipment type (such as pressure vessel, pressurizer, steam generator, etc.), one or more parameters with greater influence on fatigue strength and greater uncertainty are selected from the material properties (elastic modulus, Poisson's ratio, thermal expansion coefficient, thermal conductivity, specific heat capacity, etc.), structural dimensions, loads, etc., and used as random feature parameters. The specific analysis process can be obtained according to the experimental process.

[0016] A further optimization scheme is that the reactor equipment is parameterized based on random characteristic parameters, including the following method:

[0017] All random characteristic parameters are obtained, each random characteristic parameter is parameterized as an independent variable, a reactor equipment model is constructed, and the reactor equipment model is updated by updating the independent variables.

[0018] A further optimization scheme is that step 4 includes the following sub-steps:

[0019] S41, obtaining the fatigue service coefficient U of the current sample point, if U≤1, it is determined that the structure corresponding to the current sample point has not failed, if U>1, it is determined that the structure corresponding to the current sample point has failed;

[0020] S42, counting the number of sample points of structural failure, and calculating the fatigue strength reliability, and obtaining the failure probability based on the fatigue strength reliability;

[0021] S43, calculating the correlation coefficient parameters between each input parameter and the output parameter based on the input parameter and the fatigue usage coefficient to obtain the sensitivity result of the random characteristic parameter.

[0022] A further optimization scheme is that the method for obtaining the fatigue usage coefficient U includes:

[0023] According to ASME, RCC-M and other specifications, transient calculations are performed on the finite element model of the reactor equipment. The transients are numbered 1, 2, 3, ..., n, and the number of cycles of each transient is recorded as n1, n2, n3, ..., n respectively. n The stress peak, valley value and corresponding time are extracted from each transient stress time history. Based on the maximum principle, the stress peak and valley values ​​under each transient are combined and subtracted to obtain the alternating stress intensity amplitude S. a1 , S a2 , S a3 ,…,S an According to the design fatigue curve, the allowable number of cycles corresponding to each alternating stress intensity amplitude is recorded as N1, N2, N3, ..., N n , then the fatigue service factor U is

[0024]

[0025] Among them, i = 1, 2, 3, ..., n, is the transient number.

[0026] A further optimization scheme is that the fatigue strength reliability is calculated according to the following formula:

[0027]

[0028] Among them, Z represents fatigue strength reliability, N failure Indicates the number of sample points of structural failure, N total Indicates the total number of sample points.

[0029] A further optimization scheme is that the correlation coefficient parameters include Pearson correlation coefficient and Sperman correlation coefficient;

[0030] Pearson correlation coefficient r p Calculated according to the following formula:

[0031] Sperman correlation coefficient r s Calculated according to the following formula:

[0032] Where N is the total number of samples, x i is the i-th input parameter, y i For x i The corresponding output parameters are: For x i The average value of for y i The average value of .

[0033] The present solution also provides a fatigue strength reliability analysis system for reactor equipment, which is used to implement the above-mentioned fatigue strength reliability analysis method for reactor equipment, including:

[0034] A sampling module is used to determine the random characteristic parameters of fatigue strength according to the type of reactor equipment, and to randomly sample the random characteristic parameters to obtain input parameters of each sample point;

[0035] A modeling module, used for parameterizing the reactor equipment based on random characteristic parameters;

[0036] A calculation module, used for performing transient calculation based on input parameters of each sample point to obtain a fatigue use coefficient of each sample point;

[0037] The output module is used to input the fatigue usage coefficient of each sample point into the constructed fatigue strength reliability model to obtain the failure probability and the sensitivity results of the random characteristic parameters.

[0038] The present solution also provides a computer-readable medium having a computer program stored thereon, wherein the computer program is executed by a processor to implement a fatigue strength reliability analysis method for a reactor device as described in the above solution.

[0039] Compared with the prior art, the present invention has the following advantages and beneficial effects:

[0040] The present invention provides a fatigue strength reliability analysis method, system and medium for reactor equipment. The method, system and medium are suitable for conventional fatigue analysis calculations of reactor equipment structures, introduce the randomness of various input parameters into the calculations, involve uncertainties in geometry, material and load, establish a complete fatigue strength reliability analysis process, obtain the failure probability of fatigue strength and the sensitivity of fatigue strength to various input parameters, realize the transition of reactor equipment structure fatigue analysis from determinism to probabilism, quantitatively analyze the reliability of fatigue strength of reactor equipment through technical features such as fatigue use coefficient and failure probability, sensitivity results of random characteristic parameters, etc., and in addition, the scheme of the present invention can support subsequent structural optimization involving various input parameters to meet a series of engineering requirements. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] In order to more clearly illustrate the technical solutions of the exemplary embodiments of the present invention, the drawings required for use in the embodiments will be briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.

[0042] In the attached picture:

[0043] Figure 1 It is a flow chart of fatigue strength reliability analysis method for reactor equipment;

[0044] Figure 2 It is a schematic diagram of the fatigue strength reliability analysis process of the reactor pressure vessel core barrel of Example 4;

[0045] Figure 3 Schematic diagram of the elastic modulus variation range of Example 4;

[0046] Figure 4 This is a schematic diagram of the variation range of the thermal expansion coefficient of Example 4;

[0047] Figure 5 is a schematic diagram of a finite element model of Example 4;

[0048] Figure 6 This is a schematic diagram of the distribution of fatigue usage coefficient results of Example 4. DETAILED DESCRIPTION

[0049] In order to make the objectives, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with embodiments and drawings. The exemplary embodiments of the present invention and their description are only used to explain the present invention and are not intended to limit the present invention.

[0050] The traditional reactor equipment structure design method, based on the deterministic method, cannot reflect the reliability of the structure and the sensitivity of the structure to the design parameters, and cannot obtain the true reliability and failure probability. In view of this, the present invention provides the following embodiments to solve the above technical problems:

[0051] Example 1

[0052] This embodiment provides a fatigue strength reliability analysis method for reactor equipment, such as Figure 1 As shown, including:

[0053] Step 1: Determine the random characteristic parameters of fatigue strength according to the type of reactor equipment, and randomly sample the random characteristic parameters to obtain the input parameters of each sample point; this embodiment randomly samples the random characteristic parameters based on the Monte Carlo method to obtain the input parameters of each sample point.

[0054] The method of determining the random characteristic parameters of fatigue strength according to the reactor equipment type includes:

[0055] The reactor equipment type is obtained, and the influence and uncertainty of the basic features are analyzed according to the reactor equipment type, wherein the basic features include material properties, structural dimensions and load screens; one or more basic features with the greatest influence and uncertainty are selected as random feature parameters. According to the specific reactor equipment type (such as pressure vessel, pressurizer, steam generator, etc.), one or more parameters with greater influence on fatigue strength and greater uncertainty are selected from the material properties (elastic modulus, Poisson's ratio, thermal expansion coefficient, thermal conductivity, specific heat capacity, etc.), structural dimensions, loads, etc., and used as random feature parameters. The specific analysis process can be obtained according to the experimental process.

[0056] Step 2: Parametric modeling of reactor equipment based on random characteristic parameters;

[0057] The method of performing parameterized modeling on the reactor equipment based on random characteristic parameters includes:

[0058] All random characteristic parameters are obtained, each random characteristic parameter is parameterized as an independent variable, a reactor equipment model is constructed, and the reactor equipment model is updated by updating the independent variables.

[0059] Step 3: Perform transient calculation based on the input parameters of each sample point to obtain the fatigue service coefficient of each sample point;

[0060] Step 4: Input the fatigue usage coefficient of each sample point into the constructed fatigue strength reliability model to obtain the sensitivity results of failure probability and random characteristic parameters.

[0061] Step 4 includes the following sub-steps:

[0062] S41, obtaining the fatigue service coefficient U of the current sample point, if U≤1, it is determined that the structure corresponding to the current sample point has not failed, if U>1, it is determined that the structure corresponding to the current sample point has failed;

[0063] The method for obtaining the fatigue usage coefficient U includes:

[0064] According to the ASME and RCC-M specifications, transient calculations are performed on the finite element model of the reactor equipment. The transients are numbered 1, 2, 3, ..., n, and the number of cycles of each transient is recorded as n1, n2, n3, ..., n respectively. n ;

[0065] Extract the stress peak value, valley value and corresponding time under each transient state in the transient calculated stress time history;

[0066] Based on the maximum value principle, the stress peaks and valleys under each transient state are combined and subtracted to obtain the alternating stress intensity amplitude S a1 , S a2 , S a3 ,…,S an ;

[0067] According to the design fatigue curve, the allowable number of cycles corresponding to each alternating stress intensity amplitude is recorded as N1, N2, N3, ..., N n , then the fatigue service factor U is

[0068]

[0069] Among them, i = 1, 2, 3, ..., n, is the transient number.

[0070] S42, counting the number of sample points of structural failure, and calculating the fatigue strength reliability, and obtaining the failure probability based on the fatigue strength reliability;

[0071] S43, calculating the correlation coefficient parameters between each input parameter and the output parameter based on the input parameter and the fatigue usage coefficient to obtain the sensitivity result of the random characteristic parameter.

[0072] Fatigue strength reliability is calculated according to the following formula:

[0073]

[0074] Among them, Z represents fatigue strength reliability, N failure Indicates the number of sample points of structural failure, N total Indicates the total number of sample points.

[0075] The correlation coefficient parameters include Pearson correlation coefficient and Sperman correlation coefficient;

[0076] Pearson correlation coefficient r p Calculated according to the following formula:

[0077] Sperman correlation coefficient r s Calculated according to the following formula:

[0078] Where N is the total number of samples, x i is the i-th input parameter, y i For x i The corresponding output parameters are: For x i The average value of for y i The average value of .

[0079] By analyzing the sensitivity of parameters, the fatigue strength reliability optimization of the structure can be carried out. The input parameters with larger correlation coefficients are optimized, and the result changes are more significant. Finally, other factors such as feasibility and economy can be combined to optimize each parameter. In step 1, the randomness of only one parameter can be considered as needed, which can be used for subsequent optimization research on a certain type of parameter.

[0080] Example 2

[0081] This embodiment provides a fatigue strength reliability analysis system for reactor equipment, which is used to implement a fatigue strength reliability analysis method for reactor equipment described in Embodiment 1, including:

[0082] A sampling module is used to determine the random characteristic parameters of fatigue strength according to the type of reactor equipment, and to randomly sample the random characteristic parameters to obtain input parameters of each sample point;

[0083] A modeling module, used for parameterizing the reactor equipment based on random characteristic parameters;

[0084] A calculation module, used for performing transient calculation based on input parameters of each sample point to obtain a fatigue use coefficient of each sample point;

[0085] The output module is used to input the fatigue usage coefficient of each sample point into the constructed fatigue strength reliability model to obtain the failure probability and the sensitivity results of the random characteristic parameters.

[0086] Example 3

[0087] This embodiment provides a computer-readable medium having a computer program stored thereon. The computer program is executed by a processor to implement a fatigue strength reliability analysis method for a reactor device as described in Embodiment 1.

[0088] Example 4

[0089] In this embodiment, the reactor pressure vessel core cylinder is selected as the research object.

[0090] In order to better understand the above technical solution, the above technical solution will be described in detail below in conjunction with the accompanying drawings and specific implementation methods; Figure 2 As shown:

[0091] S10, determining parameters that need to be considered for random distribution; in this example, the randomness of the elastic modulus and the thermal expansion coefficient is taken into account. Since the values ​​of the two are related to the temperature, the values ​​at representative temperature points are randomly distributed;

[0092] S20, determining the random distribution type and characteristic parameters; in this example, it is assumed that the elastic modulus and thermal expansion coefficient are both normally distributed, and their respective means and standard deviations are determined;

[0093] S30, sampling the input parameters; in this example, the sampling times N = 3000, the Monte Carlo method is used, the Latin square sampling method is selected to avoid duplication of sample points, and 3000 elastic modulus and thermal expansion coefficient combinations with distribution rules are generated to form an input variable data pool. The range of elastic modulus in this example is as follows Figure 3 As shown, the elastic modulus of each sample point at each temperature is between the lower and upper bounds, and the thermal expansion coefficient varies as shown in Figure 4 As shown, the thermal expansion coefficient of each sample point at each temperature is between the lower limit and the upper limit.

[0094] S40, a finite element model of the pressure vessel core barrel structure is established. Since the analysis part is an axisymmetric structure, a two-dimensional axisymmetric model of the structure is established for analysis. The finite element model of this embodiment is as follows: Figure 5 As shown. At the same time, in the model, the input parameters considering random distribution are parameterized;

[0095] S401, finite element calculation is performed on each of the 3000 samples, see S402;

[0096] S402, using the data of the i-th sample point as input for calculation, and calculating the corresponding fatigue service factor according to ASME, RCC-M and other specifications;

[0097] S50, in all the output fatigue service factor results, the number of samples with statistical structure failure is calculated. The results are shown in Figure 6 , where the horizontal axis is the fatigue usage coefficient and the vertical axis is the corresponding sample number. The fatigue strength reliability is calculated according to formula (1);

[0098] S60, based on the input parameters and the corresponding fatigue usage coefficient results, the correlation coefficient between each input parameter and the output parameter is calculated according to formula (2) (3) to obtain the parameter sensitivity.

[0099] Specifically for this embodiment, among the 3000 samples, 201 samples failed due to fatigue, so the reliability can be calculated to be 0.933. Through parameter sensitivity analysis, in terms of elastic modulus, the fatigue result is most sensitive to the third temperature point, with a correlation coefficient of 0.590; in terms of thermal expansion coefficient, the fatigue result is most sensitive to the sixth temperature point, with a correlation coefficient of 0.749.

[0100] The technical method used in this embodiment supports the consideration of uncertainties of multiple types of input parameters at the same time, and can also take into account the randomness of geometric dimensions, pressure and temperature fluctuations, and SN curves. According to the method of this embodiment, the fatigue strength reliability and parameter sensitivity of the structure are analyzed with the same process.

[0101] In this embodiment, the commercial finite element software is ANSYS, and the data sampling and processing software is OPTIMUS.

[0102] Based on the fatigue strength reliability analysis method of the reactor equipment structure provided by the present invention, the randomness of the input parameters can be taken into account during the calculation, and the fatigue strength reliability of the structure can be obtained by calculation, reflecting the failure probability of the structure; based on the correlation coefficient between the fatigue strength reliability and the input parameters, the parameter sensitivity can be obtained, and the structural optimization design that meets the engineering needs can be further carried out; the calculation process established in this scheme is implemented by computer programs, each part of the process is solidified, the calculation results are reliable, and can be used for engineering applications.

[0103] The specific implementation methods described above further illustrate the objectives, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above description is only a specific implementation method of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A fatigue strength reliability analysis method for reactor equipment, characterized in that: include: Step 1: Determine the random characteristic parameters of fatigue strength according to the type of reactor equipment, and randomly sample the random characteristic parameters to obtain the input parameters of each sample point; Step 2: Parametric modeling of reactor equipment based on random characteristic parameters; Step 3: Perform transient calculation based on the input parameters of each sample point to obtain the fatigue service coefficient of each sample point; Step 4: Input the fatigue usage coefficient of each sample point into the constructed fatigue strength reliability model to obtain the sensitivity results of failure probability and random characteristic parameters.

2. A fatigue strength reliability analysis method for reactor equipment according to claim 1, characterized in that: The random feature parameters are randomly sampled based on the Monte Carlo method to obtain the input parameters of each sample point.

3. The fatigue strength reliability analysis method of a reactor device according to claim 1, characterized in that: The method of determining the random characteristic parameters of fatigue strength according to the reactor equipment type includes: The reactor equipment type is obtained, and the influence degree and uncertainty degree of basic characteristics are analyzed according to the reactor equipment type, wherein the basic characteristics include material properties, structural dimensions and load screens; and one or more basic characteristics with the greatest influence degree and uncertainty degree are selected as random characteristic parameters.

4. A fatigue strength reliability analysis method for reactor equipment according to claim 3, characterized in that: The method of performing parameterized modeling on the reactor equipment based on random characteristic parameters includes: All random characteristic parameters are obtained, each random characteristic parameter is parameterized as an independent variable, a reactor equipment model is constructed, and the reactor equipment model is updated by updating the independent variables.

5. The fatigue strength reliability analysis method of a reactor device according to claim 1, characterized in that: Step 4 includes the following sub-steps: S41, obtaining the fatigue service coefficient U of the current sample point, if U≤1, it is determined that the structure corresponding to the current sample point has not failed, if U>1, it is determined that the structure corresponding to the current sample point has failed; S42, counting the number of sample points of structural failure, and calculating the fatigue strength reliability, and obtaining the failure probability based on the fatigue strength reliability; S43, calculating the correlation coefficient parameters between each input parameter and the output parameter based on the input parameter and the fatigue usage coefficient to obtain the sensitivity result of the random characteristic parameter.

6. A fatigue strength reliability analysis method for reactor equipment according to claim 5, characterized in that: The method for obtaining the fatigue usage coefficient U includes: According to the ASME and RCC-M specifications, transient calculations are performed on the reactor equipment finite element model. The transients are numbered 1, 2, 3, ..., n, and the number of cycles of each transient is recorded as n1, n2, n3, ..., n respectively. n ; Extract the peak value, valley value and corresponding time of each transient stress in the transient calculated stress history; Based on the maximum value principle, the stress peaks and valleys under each transient state are combined and subtracted to obtain the alternating stress intensity amplitude S a1 , S a2 , S a3 ,…,S an ; According to the design fatigue curve, the allowable number of cycles corresponding to each alternating stress intensity amplitude is recorded as N1, N2, N3, ..., N n , then the fatigue service factor U is Among them, i = 1, 2, 3, ..., n, is the transient number.

7. A method for analyzing fatigue strength reliability of reactor equipment according to claim 5, characterized in that: Fatigue strength reliability is calculated according to the following formula: Among them, Z represents fatigue strength reliability, N failure Indicates the number of sample points of structural failure, N total Indicates the total number of sample points.

8. The fatigue strength reliability analysis method of a reactor device according to claim 5, characterized in that: The correlation coefficient parameters include Pearson correlation coefficient and Sperman correlation coefficient; Pearson correlation coefficient r p Calculated according to the following formula: Sperman correlation coefficient r s Calculated according to the following formula: Where N is the total number of samples, x i is the i-th input parameter, y i For x i The corresponding output parameters are: For x i The average value of y is i The average value of .

9. A fatigue strength reliability analysis system for reactor equipment, characterized in that: A fatigue strength reliability analysis method for a reactor device according to any one of claims 1 to 8, comprising: A sampling module is used to determine the random characteristic parameters of fatigue strength according to the type of reactor equipment, and to randomly sample the random characteristic parameters to obtain input parameters of each sample point; A modeling module, used for parameterizing the reactor equipment based on random characteristic parameters; A calculation module, used for performing transient calculation based on input parameters of each sample point to obtain a fatigue use coefficient of each sample point; The output module is used to input the fatigue usage coefficient of each sample point into the constructed fatigue strength reliability model to obtain the sensitivity results of the failure probability and random characteristic parameters.

10. A computer readable medium having a computer program stored thereon, characterized in that: The computer program is executed by a processor to implement a fatigue strength reliability analysis method for a reactor device as described in any one of claims 1 to 8.

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