Evaluation method of RPV surface crack initiation probability under transient condition

Abstract

The invention relates to a method for evaluating the crack initiation probability of an RPV surface crack under a transient working condition, and belongs to the field of safety analysis of nuclear pressure-bearing equipment. The method comprises the following steps: sampling a random variable and determining a sampled multivariate sample; calculating a stress intensity factor of the crack evaluation point caused by multiple loads under the transient condition; calculating a stress intensity factor of the crack evaluation point after the influence of the crack tip plastic zone is brought into the transient condition; calculating the reference temperature of the crack evaluation point after neutron irradiation embrittlement is considered under the transient condition; constructing a fracture toughness probability distribution model of the crack evaluation points under the transient condition; calculating the crack initiation probability of the crack at the current moment under the transient condition; judging whether the current moment is the last moment of the transient working condition, if so, ending the calculation process of the crack initiation probability under the transient working condition, and otherwise, updating the transient moment; and evaluating the crack initiation probability of the RPV surface cracks under all samples. According to the method, the crack initiation probability of the RPV surface crack under the transient working condition can be efficiently and accurately evaluated.

Description

Technical Field

[0001] The present invention belongs to the field of safety analysis of nuclear pressure-bearing equipment, and particularly relates to a method for evaluating the initiation probability of RPV surface cracks under transient conditions. Background Art

[0002] The nuclear reactor pressure vessel (RPV) is the mechanical equipment with the highest safety level in a nuclear power plant and needs to serve as a barrier to prevent the leakage of radioactive substances from the reactor core. During long-term service, the RPV will show a trend of material aging and decreased fracture resistance under the action of neutron irradiation. At the same time, the superposition of mechanical, thermal, residual stress and other loads during service may also promote the initiation of crack defects inside the structure, posing a challenge to the structural integrity of the RPV. In order to ensure the safe and stable operation of the nuclear power plant, it is necessary to regularly conduct a scientific and reasonable structural integrity assessment of the in-service nuclear reactor pressure vessel.

[0003] The existing RPV structural integrity assessment mainly uses the deterministic fracture mechanics method. Based on conservative assumptions, this method determines the safety of the vessel by comparing the lower envelope curve of the material fracture toughness and the stress intensity factor at the crack tip of the nuclear reactor pressure vessel with a surface crack under transient conditions. This method is simple and practical, but it cannot reasonably quantify the uncertainties of influencing factors such as loads and materials, and thus it is difficult to reasonably evaluate the structural integrity of the in-service RPV. Summary of the Invention

[0004] The purpose of the present invention is to overcome the limitations of the existing assessment methods and provide a method for evaluating the initiation probability of RPV surface cracks under transient conditions, so as to reasonably evaluate the structural integrity of the in-service RPV.

[0005] To achieve the above purpose, the technical solution of the present invention is: a method for evaluating the initiation probability of RPV surface cracks under transient conditions, which couples the fracture mechanics theory and the probability assessment technology, and uses the Latin hypercube sampling method on the basis of introducing the RPV steel irradiation embrittlement model to efficiently and accurately evaluate the initiation probability of RPV surface cracks under transient conditions; the method includes the following steps:

[0006] Step 1: Input the initial conditions, including the geometric dimensions, material properties, operation data and transient conditions of the RPV, as well as the crack characteristic data;

[0007] Step 2: Sample the random variables and determine the multivariate samples after sampling;

[0008] Step 3: Calculate the stress intensity factor at the crack evaluation point caused by multiple loads under transient conditions;

[0009] Step 4: Calculate the stress intensity factor at the crack evaluation point considering the influence of the crack tip plastic zone under transient conditions;

[0010] Step 5: Calculate the reference temperature of the crack evaluation point considering neutron irradiation embrittlement under transient conditions;

[0011] Step 6: Construct a fracture toughness probability distribution model for the crack evaluation point under transient conditions;

[0012] Step 7: Calculate the crack initiation probability at the current moment under transient conditions;

[0013] Step 8: Determine whether the current moment is the last moment of the transient condition. If so, end the calculation process of the crack initiation probability under this transient condition. Otherwise, update the transient moment and then repeat Steps 3 to 8;

[0014] Step 9: Evaluate the crack initiation probability of the RPV surface crack under the current sample;

[0015] Step 10: Determine whether the current sample is the last sample. If so, end the calculation. Otherwise, start from the next sample and repeat Steps 3 to 10.

[0016] In an embodiment of the present invention, in Step 1, the geometric dimensions, material properties, operating data, and transient conditions of the RPV, as well as the crack characteristic data, specifically include:

[0017] 1) The RPV radius R i , the surfacing thickness t c and the base material thickness t b ;

[0018] 2) The Young's modulus of the base material and the weld and their yield stresses at different temperatures;

[0019] 3) The average values and standard deviations of the chemical composition contents of Cu, Ni, P, Si, and Mn;

[0020] 4) The average value and standard deviation of the initial reference temperature RT (ini.) ;

[0021] 5) The standard deviation of the temperature offset ΔRT caused by irradiation embrittlement;

[0022] 6) The average value and standard deviation of the neutron fluence F 0 on the inner surface of the RPV, and the attenuation coefficient μ of the neutron fluence along the container wall thickness direction;

[0023] 7) The effective full power years EFPY of the nuclear reactor, the operating temperature T op ;

[0024] 8) The internal pressure and the temperature distribution in the container wall thickness direction at each moment under transient conditions;

[0025] 9) The thermal stress distribution in the container wall thickness direction at each moment under transient conditions;

[0026] 10) Residual stress distribution in the wall thickness direction of the container caused by welding;

[0027] 11) Position, direction, and size of surface cracks;

[0028] 12) Sample size N.

[0029] In an embodiment of the present invention, in step 2, according to the sample size N set in step 1, the Latin hypercube sampling method is used to sample the random variables to determine the multivariate sample after sampling, which specifically includes the following steps:

[0030] The first step: Generate a set of pseudo-random numbers, and the number of pseudo-random numbers is the same as the set sample size N;

[0031] The second step: Based on the sample size N and the pseudo-random numbers, obtain the sampling values of the cumulative probability φ of the reference temperature correction value ΔRT that follows the standard uniform distribution; (mod.) of;

[0032] The third step: Based on the standard deviation of the temperature offset ΔRT input in step 1, the average values and standard deviations of the chemical composition contents of Cu, Ni, P, Si, and Mn, the average value and standard deviation of the neutron fluence F on the inner surface of the RPV 0 and the average value and standard deviation of the initial reference temperature RT (ini.) and the average value and standard deviation of, according to the sample size N and the pseudo-random numbers, use the Latin hypercube sampling method for the standard deviation of the temperature offset ΔRT, the chemical composition contents of Cu, Ni, P, Si, and Mn, the neutron fluence F on the inner surface of the RPV 0 and the initial reference temperature RT (ini.) for sampling to obtain the standard deviation of the temperature offset ΔRT that follows the normal distribution, the chemical composition contents of Cu, Ni, P, Si, and Mn, the neutron fluence F on the inner surface of the RPV 0 and the initial reference temperature RT (ini.) of the sampling values;

[0033] The fourth step: Determine the multivariate sample after sampling, and this sample is a combination of the cumulative probability φ, the standard deviation of the temperature offset ΔRT, the chemical composition contents of Cu, Ni, P, Si, and Mn, the neutron fluence F on the inner surface of the RPV 0 and the initial reference temperature RT (ini.) of the sampling values.

[0034] In an embodiment of the present invention, in step 3, calculate the stress intensity factor K' of the crack evaluation point caused by multiple loads under transient conditions, which specifically includes the following steps:

[0035] The first step: According to the surface crack size and the surfacing thickness t c, based on the shape factors of the surface crack stress intensity factors under different stress conditions, the shape factor of the base metal part and the shape factor of the surfacing part are calculated by the linear interpolation method;

[0036] Step 2: Calculate the stress intensity factor K' at the crack evaluation point under the internal pressure condition pressure ;

[0037] Step 3: Calculate the stress intensity factor K' at the crack evaluation point under the thermal stress condition th ;

[0038] Step 4: Calculate the stress intensity factor K' at the crack evaluation point considering the residual stress WRS ;

[0039] Step 5: Calculate the sum K' of the stress intensity factors at the crack evaluation point considering the load condition.

[0040] In an embodiment of the present invention, in step 4, based on the sum K' of the stress intensity factors obtained in step 3, the stress intensity factor K at the crack evaluation point considering the influence of the crack tip plastic zone is calculated, which specifically includes the following steps:

[0041] Step 1: Based on the temperature distribution in the wall thickness direction of the container at each moment under the transient working condition input in step 1, through the relative position between the crack evaluation point and the wall thickness of the container, the temperature T of the crack evaluation point is calculated by the linear interpolation method cracktip ;

[0042] Step 2: Based on the yield stress of the base metal at different temperatures input in step 1, according to the temperature T of the crack evaluation point cracktip The yield stress σ of the base metal is calculated by the linear interpolation method ys ;

[0043] Step 3: Calculate the stress intensity factor K at the crack evaluation point considering the influence of the crack tip plastic zone according to the estimation formula of the crack tip plastic zone size under the plane strain condition.

[0044] In an embodiment of the present invention, in step 5, calculate the reference temperature RT at the crack evaluation point considering neutron irradiation embrittlement (irr.) , which specifically includes the following steps:

[0045] Step 1: Based on the attenuation coefficient μ of the neutron fluence along the wall thickness direction of the container input in step 1 and the sampling value of the neutron fluence F on the inner surface of the RPV under the current sample obtained in step 2 0 Calculate the neutron fluence F at the crack evaluation point;

[0046] Step 2: Based on the neutron fluence F at the crack assessment point obtained in Step 1 and the sampling values of the chemical composition contents of Cu, Ni, P, Si, and Mn under the current sample obtained in Step 2, calculate the average value of the temperature offset ΔRT at the crack assessment point according to the RPV steel irradiation embrittlement model.

[0047] Step 3: Based on the average value of the temperature offset ΔRT at the crack assessment point obtained in Step 2 and the sampling value of the standard deviation of the temperature offset ΔRT under the current sample obtained in Step 2, calculate the temperature offset ΔRT caused by irradiation embrittlement at the crack assessment point;

[0048] Step 4: Calculate the reference temperature correction value ΔRT based on the sampling value of the cumulative probability φ under the current sample obtained in Step 2 (mod.) ;

[0049] Step 5: Based on the temperature offset ΔRT caused by irradiation embrittlement at the crack assessment point obtained in Step 3, the reference temperature correction value ΔRT obtained in Step 4 (mod.) and the sampling value of the initial reference temperature RT under the current sample obtained in Step 2 (ini.) calculate the reference temperature RT at the crack assessment point considering neutron irradiation embrittlement (irr.) .

[0050] In an embodiment of the present invention, in Step 6, based on the temperature T at the crack assessment point obtained in Step 4 cracktip and the reference temperature RT at the crack assessment point considering neutron irradiation embrittlement obtained in Step 5 (irr.) , construct the fracture toughness K c probability distribution model at the crack assessment point, which specifically includes the following steps:

[0051] Step 1: Drawing on the statistical weakest link theory, set the location parameter, scale parameter, and shape parameter of the Weibull probability distribution model according to the law of the change of fracture toughness with temperature;

[0052] Step 2: Based on the location parameter, scale parameter, and shape parameter set in the previous step, construct the fracture toughness K c probability distribution model at the crack assessment point.

[0053] In an embodiment of the present invention, in Step 7, based on the stress intensity factor K at the crack assessment point considering the influence of the crack tip plastic zone obtained in Step 4, and the fracture toughness K c probability distribution model at the crack assessment point constructed in Step 6, calculate the crack initiation probability pci at the current moment τ under transient conditions τ ;

[0054] In an embodiment of the present invention, in step 9, based on the calculation results at all times under transient conditions in step 7, the probability of crack initiation PCI on the RPV surface for the current sample is evaluated; PCI is defined as the maximum value of pci among all times under transient conditions. τ of the maximum value.

[0055] Compared with the prior art, the present invention has the following beneficial effects:

[0056] 1. The present invention couples fracture mechanics theory with probability assessment technology. By quantifying the uncertainties of various influencing factors related to the safety of the RPV, it can eliminate the excessive conservatism in the existing deterministic fracture mechanics assessment method and achieve a reasonable assessment of the probability of crack initiation on the RPV surface.

[0057] 2. By considering the combined effects of multiple loads such as internal pressure, thermal stress, and residual stress, it can systematically evaluate the probability of crack initiation on the RPV surface at any time under transient conditions, providing a direct basis for analyzing the service reliability of in-service RPVs.

[0058] 3. The Latin hypercube sampling method is adopted to effectively improve the efficiency of multivariate random sampling and achieve a high-precision assessment of the probability of crack initiation of cracked equipment with a small sample size. Description of the Drawings

[0059] Figure 1 is a schematic diagram of the crack evaluation point on the RPV surface.

[0060] Figure 2 is a flowchart of a method for evaluating the probability of crack initiation on the RPV surface under a transient condition.

[0061] Figure 3 is a schematic diagram of the input data of a method for evaluating the probability of crack initiation on the RPV surface under a transient condition.

[0062] Figure 4 is a sampling flowchart of a method for evaluating the probability of crack initiation on the RPV surface under a transient condition.

[0063] Figure 5 is a flowchart for calculating the stress intensity factor of the crack evaluation point under thermal stress conditions of a method for evaluating the probability of crack initiation on the RPV surface under a transient condition.

[0064] Figure 6 is a flowchart for calculating the stress intensity factor of the crack evaluation point considering residual stress of a method for evaluating the probability of crack initiation on the RPV surface under a transient condition.

[0065] Figure 7 (a) is the internal pressure change curve under transient conditions in the embodiment of the present invention.

[0066] Figure 7 (b) Temperature distribution in the wall thickness direction of the container under transient conditions in the embodiment of the present invention.

[0067] Figure 7 (c) Thermal stress distribution in the wall thickness direction of the container at each moment under transient conditions in the embodiment of the present invention.

[0068] Figure 7 (d) Residual stress distribution in the wall thickness direction of the container caused by welding under transient conditions in the embodiment of the present invention.

[0069] Figure 8 It is the crack initiation probability results at all moments under transient conditions obtained according to the embodiment of the present invention. Detailed implementation manners

[0070] The technical solution of the present invention will be specifically described below in conjunction with the accompanying drawings.

[0071] It should be noted that the following detailed descriptions are all exemplary and are intended to provide further descriptions of the present invention. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by those of ordinary skill in the technical field to which the present invention belongs.

[0072] It should be noted that the terms used herein are only for describing specific implementation manners and are not intended to limit the exemplary implementation manners according to the present invention.

[0073] Without conflict, the embodiments in the present invention and the features in the embodiments can be combined with each other.

[0074] The present invention provides a method for evaluating the crack initiation probability of the RPV surface under transient conditions. By coupling the fracture mechanics theory and the probability assessment technology, and based on the introduction of the RPV steel irradiation embrittlement model, the Latin hypercube sampling method is used to efficiently and accurately evaluate the crack initiation probability of the RPV surface under transient conditions; the method includes the following steps:

[0075] Step 1: Input initial conditions, including the geometric dimensions, material properties, operating data and transient conditions of the RPV, as well as crack characteristic data;

[0076] Step 2: Sample the random variables and determine the multivariate samples after sampling;

[0077] Step 3: Calculate the stress intensity factor of the crack evaluation point caused by multiple loads under transient conditions;

[0078] Step 4: Calculate the stress intensity factor of the crack evaluation point considering the influence of the crack tip plastic zone under transient conditions;

[0079] Step 5: Calculate the reference temperature of the crack evaluation point considering neutron irradiation embrittlement under transient conditions;

[0080] Step 6: Construct a fracture toughness probability distribution model for crack assessment points under transient conditions;

[0081] Step 7: Calculate the crack initiation probability at the current moment under transient conditions;

[0082] Step 8: Determine whether the current moment is the last moment of the transient condition. If so, end the calculation process of the crack initiation probability under this transient condition. Otherwise, update the transient moment and then repeat Steps 3 to 8;

[0083] Step 9: Evaluate the crack initiation probability of the RPV surface crack under the current sample;

[0084] Step 10: Determine whether the current sample is the last sample. If so, end the calculation. Otherwise, start from the next sample and repeat Steps 3 to 10.

[0085] The following is the specific implementation process of the present invention.

[0086] Figure 1 It is a schematic diagram of the crack assessment point on the RPV surface. As Figure 1 shown, the total wall thickness of the RPV is t, where the surfacing thickness is t c and the base metal thickness is t b ; According to the direction of the surface crack, it can be divided into circumferential cracks and axial cracks. The distance from the deepest point of the crack to the inner surface of the container is the crack depth (denoted by a), and half of the crack length is the crack semi-length (denoted by c). Take the deepest point of the surface crack as the crack assessment point.

[0087] As Figure 2 shown, a method for evaluating the crack initiation probability of the RPV surface crack under transient conditions of the present invention includes the following steps:

[0088] Step 1: Input the geometric dimensions, material properties, operating data, and transient conditions of the RPV, as well as crack characteristic data. As Figure 3 shown, the input data specifically includes the following content:

[0089] 1) The RPV radius R i , the surfacing thickness t c and the base metal thickness t b ;

[0090] 2) The Young's modulus of the base metal and the weld and their yield stresses at different temperatures;

[0091] 3) The average values and standard deviations of the chemical composition contents of Cu, Ni, P, Si, and Mn;

[0092] 4) The average value and standard deviation of the initial reference temperature RT (ini.) ;

[0093] 5) Standard deviation of the temperature offset ΔRT caused by irradiation embrittlement;

[0094] 6) Average value and standard deviation of the neutron fluence F on the inner surface of the RPV, and attenuation coefficient μ of the neutron fluence along the container wall thickness direction; 0

[0095] 7) Effective full power years EFPY of the nuclear reactor, operating temperature T op ;

[0096] 8) Temperature distribution in the inner pressure and container wall thickness direction at each moment under transient conditions;

[0097] 9) Thermal stress distribution in the container wall thickness direction at each moment under transient conditions;

[0098] 10) Residual stress distribution in the container wall thickness direction caused by welding;

[0099] 11) Position, direction and size of surface cracks;

[0100] 12) Sample size N;

[0101] Step 2: According to the sample size set in Step 1, use the Latin hypercube sampling method to sample the random variables to determine the multivariate sample after sampling, as Figure 4 shown, specifically including the following:

[0102] The first step: Generate a set of pseudo-random numbers, and the number of pseudo-random numbers is the same as the set sample size N;

[0103] The second step: Based on the sample size N and the pseudo-random numbers, obtain the sampling value of the cumulative probability φ of the reference temperature correction value ΔRT that follows the standard uniform distribution (mod.) ;

[0104] The third step: Based on the standard deviation of the temperature offset ΔRT input in Step 1, the average values and standard deviations of the chemical composition contents of Cu, Ni, P, Si, Mn, the average value and standard deviation of the neutron fluence F on the inner surface of the RPV 0 and the average value and standard deviation of the initial reference temperature RT (ini.) , according to the sample size N and the pseudo-random numbers, use the Latin hypercube sampling method to sample the standard deviation of the temperature offset ΔRT, the chemical composition contents of Cu, Ni, P, Si, Mn, the neutron fluence F on the inner surface of the RPV 0 and the initial reference temperature RT (ini.) to obtain the standard deviation of the temperature offset ΔRT, the chemical composition contents of Cu, Ni, P, Si, Mn, the neutron fluence F on the inner surface of the RPV 0 and the initial reference temperature RT that follow the normal distribution(ini.) Sampling value;

[0105] Step 4: Determine the nth multi - variable sample after sampling, where n is the current sampling sequence number, and the nth sample is the combination of the cumulative probability φ, the standard deviation of the temperature offset ΔRT, the chemical component contents of Cu, Ni, P, Si, Mn, the neutron fluence F on the inner surface of the RPV 0 and the initial reference temperature RT (ini.) of the nth sampling value;

[0106] Step 3: Calculate the stress intensity factor K' at the crack assessment point caused by multiple loads under transient conditions, which specifically includes the following:

[0107] Step 1: According to the surface crack size and the surfacing thickness t c , based on the shape factors of the surface crack stress intensity factor under different stress conditions given in the "Rules for In - Service Inspection of Nuclear Island Mechanical Equipment in Pressurized Water Reactor Nuclear Power Plants (RSE - M 2010)" of France, use the linear interpolation method to calculate the shape factors i 0 , i 1 , i 2 , i 3 of the base metal part and the shape factors i r0 , i r1 ; Some shape factors are shown in Table 1;

[0108] Table 1 Some shape factors given in RSE - M 2010 (when the Young's modulus ratio of surfacing to base metal is 1)

[0109]

[0110] Step 2: Calculate the stress intensity factor K' at the crack assessment point under internal pressure conditions pressure , including the following two steps a) and b):

[0111] a) Based on the internal pressure at each moment under the transient conditions input in Step 1, calculate the internal pressure P using the linear interpolation method according to the current transient moment i ;

[0112] b) Calculate the stress intensity factor K' at the crack assessment point under internal pressure conditions pressure ;

[0113]

[0114] In the formula, a is the crack depth;

[0115] Step 3: Calculate the stress intensity factor K' at the crack assessment point under thermal stress conditions th , as Figure 5 shown, including the following two steps a) and b):

[0116] a) Calculate the additional stress coefficient σ of the surfacing part under thermal stress conditions 0r_th and σ 1r_th ;

[0117] σ 0r_th = σ r0_th - σ 0_th

[0118]

[0119] where Δσ th is the thermal stress difference at the interface between the surfacing and the base metal, t c is the surfacing thickness, t is the total wall thickness of the nuclear reactor pressure vessel including the base metal and the surfacing, σ j_th is the j-th order stress fitting coefficient of the thermal stress in the base metal, σ jr_th is the j-th order stress fitting coefficient of the additional thermal stress of the surfacing, σ rj_th is the j-th order stress fitting coefficient of the thermal stress in the surfacing;

[0120] b) Calculate the stress intensity factor K' at the crack evaluation point under thermal stress conditions th ;

[0121]

[0122] Fourth step: Calculate the stress intensity factor K' at the crack evaluation point considering the residual stress WRS , as shown in Figure 6 and includes the following two steps a) and b):

[0123] a) Calculate the additional stress coefficient σ of the surfacing part considering the residual stress 0r_WRS and σ 1r_WRS ;

[0124] σ 0r_WRS = σ r0_WRS - σ 0_WRS

[0125]

[0126] where Δσ WRS is the residual stress difference at the interface between the surfacing and the base metal, σ j_WRS is the j-th order stress fitting coefficient of the residual stress in the base metal, σ jr_WRS is the j-th order stress fitting coefficient of the additional residual stress of the surfacing, σ rj_WRS is the j-th order stress fitting coefficient of the residual stress in the surfacing;

[0127] b) Calculate the stress intensity factor K' at the crack evaluation point considering the residual stress WRS ;

[0128]

[0129] Step 5: Calculate the sum K' of the stress intensity factors at the crack assessment point considering the above loads;

[0130] K′ = K′ pressure + K′ th + K′ WRS

[0131] Step 4: Based on the sum K' of the stress intensity factors obtained in Step 3, calculate the stress intensity factor K at the crack assessment point considering the influence of the crack tip plastic zone, which specifically includes the following:

[0132] First step: Based on the temperature distribution in the wall thickness direction of the container at each moment under the transient working conditions input in Step 1, calculate the temperature T at the crack assessment point by using the linear interpolation method through the relative position between the crack assessment point and the wall thickness of the container cracktip ;

[0133] Second step: Based on the yield stress of the base metal at different temperatures input in Step 1, calculate the yield stress σ of the base metal by using the linear interpolation method according to the temperature T cracktip at the crack assessment point ys ;

[0134] Third step: Calculate the stress intensity factor K at the crack assessment point considering the influence of the crack tip plastic zone according to the estimation formula for the size of the crack tip plastic zone under plane strain conditions;

[0135]

[0136] Step 5: Calculate the reference temperature RT at the crack assessment point considering neutron irradiation embrittlement (irr.) , which specifically includes the following:

[0137] First step: Based on the attenuation coefficient μ of the neutron fluence along the wall thickness direction of the container input in Step 1 and the sampled value of the neutron fluence F on the inner surface of the RPV obtained in Step 2 0 , calculate the neutron fluence F at the crack assessment point;

[0138] F = F 0 e -μx

[0139] where x is the distance from the crack assessment point to the inner surface of the container;

[0140] Second step: Based on the neutron fluence F at the crack assessment point obtained in the first step and the sampled values of the chemical composition contents of Cu, Ni, P, Si, and Mn in the current sample obtained in Step 2, calculate the average value of the temperature offset ΔRT at the crack assessment point according to the irradiation embrittlement model of domestic RPV steel

[0141]

[0142] A = 0.5 + 0.5tanh{[lg 10 (F) + 1.1390w Cu - 0.4483w Ni - 19.12025] / 0.6287}

[0143] where w p is the chemical composition content of P, w Mn is the chemical composition content of Mn, w Ni is the chemical composition content of Ni, w Si is the chemical composition content of Si, w Cu is the chemical composition content of Cu;

[0144] Step 3: Based on the average value of the crack evaluation point temperature offset ΔRT obtained in the second step and the sampled value of the standard deviation of the temperature offset ΔRT under the current sample obtained in step 2, calculate the temperature offset ΔRT caused by irradiation embrittlement at the crack evaluation point;

[0145]

[0146] where σ ΔRT is the sampled value of the standard deviation of the temperature offset ΔRT under the current sample;

[0147] Step 4: Calculate the reference temperature correction value ΔRT based on the sampled value of the cumulative probability φ under the current sample obtained in step 2 (mod.) ;

[0148] ΔRT (mod.) = -15.602 + 67.559[ln(1 - φ)] 1 / 4.306

[0149] Step 5: Calculate the reference temperature RT at the crack evaluation point considering neutron irradiation embrittlement (irr.) ;

[0150] RT (irr.) = RT( ini.) + ΔRT - ΔRT (mod.)

[0151] Step 6: Based on the temperature T cracktip at the crack evaluation point obtained in step 4 (irr.) and the reference temperature RT at the crack evaluation point considering neutron irradiation embrittlement obtained in step 5 c , construct the fracture toughness K

[0152] Step 1: Draw on the weakest link theory of statistics and set the location parameter α, scale parameter β, and shape parameter χ of the Weibull probability distribution model according to the law of the change of fracture toughness with temperature;

[0153] α = 13.1788 + 6.7096exp[0.03366(T cracktip -RT (irr.) )]

[0154] β = 15.8797 + 42.213exp[0.01208(T cracktip -RT (irr.) )]

[0155] χ = 4

[0156] Step 2: Based on the location parameter α, scale parameter β, and shape parameter χ set in the previous step, construct the fracture toughness K c probability distribution model of the crack evaluation point;

[0157]

[0158] In the formula, P f is the cumulative failure probability;

[0159] Step 7: Based on the stress intensity factor K of the crack evaluation point considering the influence of the crack tip plastic zone obtained in Step 4, and the fracture toughness K c probability distribution model of the crack evaluation point constructed in Step 6, calculate the crack initiation probability pci τ at the current moment τ under transient conditions, and the calculation formula is:

[0160]

[0161] In the formula, is the fracture toughness of the crack evaluation point when the cumulative failure probability P f is 0;

[0162] Step 8: Determine whether the current moment is the last moment of the transient condition. If so, end the calculation process of the crack initiation probability under the transient condition. Otherwise, update the transient moment, and then repeat Steps 3 to 8;

[0163] Step 9: Based on the calculation results at all moments under the transient condition in Step 7, evaluate the crack initiation probability PCI of the RPV surface crack under the nth sample;

[0164] The crack initiation probability PCI of the RPV surface crack under the nth sample is:

[0165] PCI = Max(pci τ )

[0166] Step 10. Determine whether the current sample is the last sample. If so, end the calculation; otherwise, repeat Steps 3 to 10 starting from the next sample.

[0167] The following uses an embodiment of an actual application to specifically illustrate the technical solution of the present invention:

[0168] Assume that there is a surface crack in a nuclear reactor pressure vessel, and it is necessary to evaluate the crack initiation probability caused by this crack under the transient of a large-break loss-of-coolant accident. The nuclear reactor pressure vessel includes the total wall thickness t = 0.2 m of the base material and the surfacing, where the surfacing thickness t c = 0.0075 m, the radius R i = 1.994 m, the equivalent full power years EFPY = 48 years, the operating temperature T op = 288 °C, and the attenuation coefficient μ of the neutron fluence along the wall thickness direction of the container is 9.449 m -1 . The partial operating parameters, material parameters, and mechanical properties of the equipment are shown in Tables 2 and 3.

[0169] Table 2 Partial operating parameters and material parameters of a nuclear reactor

[0170]

[0171] * The average value of ΔRT will be calculated in Step 5

[0172] Table 3 Material mechanical properties of nuclear reactor pressure vessels at different temperatures

[0173]

[0174] Now, use the method of the present invention to evaluate the crack initiation probability of this nuclear reactor pressure vessel, and the process is as follows:

[0175] Step 1. Obtain the geometric dimensions, material properties, operating data, transient conditions, and crack characteristic data of the RPV. Assume that the crack is an axial surface crack located in the base material, the crack depth a = 0.01 m, and the crack semi-length c = 0.03 m. Obtain the internal pressure and temperature distribution in the wall thickness direction of the container at each moment under the transient conditions through transient thermal-hydraulic analysis, as shown in Figure 7 (a) and (b) respectively. Perform transient stress analysis based on the time-varying internal pressure and temperature to obtain the thermal stress distribution in the wall thickness direction of the container at each moment under the transient conditions, as shown in Figure 7 (c). To consider the influence of residual stress, it is also necessary to obtain the residual stress distribution in the wall thickness direction of the container caused by welding, as shown in Figure 7 (d). Set the sample size to 100,000;

[0176] Step 2: According to the sample size set in Step 1, use the Latin hypercube sampling method to sample the random variables to determine the multivariate sample after sampling, which specifically includes the following contents:

[0177] The first step: Generate a set of pseudo-random numbers, and the number of pseudo-random numbers is the same as the set sample size N;

[0178] The second step: Based on the sample size N and the pseudo-random numbers, obtain the sampling value of the cumulative probability φ of the reference temperature correction value ΔRT that follows the standard uniform distribution (mod.) ;

[0179] The third step: Based on the standard deviation of the temperature offset ΔRT input in Step 1, the average values and standard deviations of the chemical component contents of Cu, Ni, P, Si, Mn, the average value and standard deviation of the neutron fluence F on the inner surface of the RPV 0 and the average value and standard deviation of the initial reference temperature RT (ini.) , according to the sample size N and the pseudo-random numbers, use the Latin hypercube sampling method to sample the standard deviation of the temperature offset ΔRT, the chemical component contents of Cu, Ni, P, Si, Mn, the neutron fluence F on the inner surface of the RPV 0 and the initial reference temperature RT (ini.) , and obtain the sampling values of the standard deviation of the temperature offset ΔRT, the chemical component contents of Cu, Ni, P, Si, Mn, the neutron fluence F on the inner surface of the RPV 0 and the initial reference temperature RT (ini.) that follow the normal distribution;

[0180] The fourth step: Determine the multivariate sample after sampling, and this sample is the combination of the sampling values of the cumulative probability φ, the standard deviation of the temperature offset ΔRT, the chemical component contents of Cu, Ni, P, Si, Mn, the neutron fluence F on the inner surface of the RPV 0 and the initial reference temperature RT (ini.) ;

[0181] The following takes the first transient moment under a certain multivariate sample after sampling (see Table 4) as an example for calculation and explanation.

[0182] Table 4 Example of a certain multivariate sample after sampling

[0183]

[0184] Step 3: Calculate the stress intensity factor K' at the crack evaluation point caused by multiple loads under transient conditions, which specifically includes the following contents:

[0185] The first step: According to the surface crack size and the surfacing thickness t c, based on the shape factor of the surface crack stress intensity factor under different stress conditions given in the "In-Service Inspection Rules for Nuclear Island Mechanical Equipment of Pressurized Water Reactor Nuclear Power Plants (RSE-M 2010)" in France, the shape factor i of the base metal part is calculated by the linear interpolation method 0 、i 1 、i 2 、i 3 and the shape factor i of the surfacing part r0 、i r1 ; it can be obtained that i 0 = 0.99895, i 1 = 0.62946, i 2 = 0.49215, i 3 = 0.41683, i r0 = 0.55321, i r1 = 0.22265;

[0186] Step 2: Calculate the stress intensity factor K' of the crack evaluation point under the internal pressure condition pressure , including the following two steps a) and b):

[0187] a) Based on the internal pressure at each moment in the transient working condition input in Step 1, the internal pressure P is calculated by the linear interpolation method according to the current transient moment i , and the internal pressure P i = 15.71 MPa can be determined;

[0188] b) Calculate the stress intensity factor K' of the crack evaluation point under the internal pressure condition pressure ;

[0189]

[0190] In the formula, a is the crack depth, which is 0.01 m here;

[0191] The stress intensity factor K' of the crack evaluation point under the internal pressure condition can be determined pressure = 2.781 MPa·m 1 / 2 ;

[0192] Step 3: Calculate the stress intensity factor K' of the crack evaluation point under the thermal stress condition th , including the following two steps a) and b):

[0193] a) Calculate the additional stress coefficient σ 0r_th 、σ 1r_th of the surfacing part under the thermal stress condition;

[0194] σ 0r_th = σ r0_th - σ 0_th

[0195]

[0196] In the formula, Δσ th is the thermal stress difference at the interface between the surfacing and the base metal, t c is the surfacing thickness, t is the total wall thickness of the nuclear reactor pressure vessel including the base metal and the surfacing, σ j_th is the j-th order stress fitting coefficient of the thermal stress in the base metal, σ jr_th is the j-th order stress fitting coefficient of the additional thermal stress of the surfacing, σ rj_th is the j-th order stress fitting coefficient of the thermal stress in the surfacing;

[0197] σ can be determined 0r_th = -101.08 MPa·m 1 / 2 , σ 1r_th = 9.56 MPa·m 1 / 2 ;

[0198] b) Calculate the stress intensity factor K' at the crack evaluation point under thermal stress conditions th ;

[0199]

[0200] The stress intensity factor K' at the crack evaluation point under thermal stress conditions can be determined th = 19.91 MPa·m 1 / 2 ;

[0201] Step 4: Calculate the stress intensity factor K' at the crack evaluation point considering the residual stress WRS , including the following two steps a) and b):

[0202] a) Calculate the additional stress coefficients σ 0r_WRS , σ 1r_WRS ;

[0203] σ 0r_WRS = σ r0_WRS - σ 0_WRS

[0204]

[0205] In the formula, Δσ WRS is the residual stress difference at the interface between the surfacing and the base metal, σ j_WRS is the j-th order stress fitting coefficient of the residual stress in the base metal, σ jr_WRS is the j-th order stress fitting coefficient of the additional residual stress of the surfacing, σ rj_WRS is the j-th order stress fitting coefficient of the residual stress in the surfacing;

[0206] σ can be determined 0r_WRS = 22.91 MPa·m 1 / 2 , σ1r_WRS = -724.99 MPa·m 1 / 2 ;

[0207] b) Calculate the stress intensity factor K' at the crack evaluation point considering the residual stress WRS ;

[0208]

[0209] The stress intensity factor K' at the crack evaluation point considering the residual stress can be determined WRS = 16.06 MPa·m 1 / 2 ;

[0210] Step 5: Calculate the sum K' of the stress intensity factors at the crack evaluation point considering the above loads

[0211] K′ = K′ pressure + K′ th + K′ WRS

[0212] The sum K' of the stress intensity factors at the crack evaluation point considering the above loads can be determined as K' = 38.74 MPa·m 1 / 2 ;

[0213] Step 4: Based on the sum K' of the stress intensity factors obtained in Step 3, calculate the stress intensity factor K at the crack evaluation point considering the influence of the crack tip plastic zone, which specifically includes the following contents

[0214] First step: Based on the temperature distribution in the wall thickness direction of the container at each moment under the transient working conditions input in Step 1, calculate the temperature T at the crack evaluation point by using the linear interpolation method through the relative position between the crack evaluation point and the wall thickness of the container cracktip . The temperature T at the crack evaluation point at the first transient moment can be determined cracktip = 287.9 °C;

[0215] Second step: Based on the yield stress of the base material at different temperatures input in Step 1, calculate the yield stress σ of the base material by using the linear interpolation method according to the temperature T at the crack evaluation point cracktip The yield stress σ of the base material can be determined ys . The yield stress σ of the base material at the first transient moment can be determined ys = 441.58 MPa;

[0216] Third step: Calculate the stress intensity factor K at the crack evaluation point considering the influence of the crack tip plastic zone according to the estimation formula for the size of the crack tip plastic zone under plane strain conditions

[0217]

[0218] The stress intensity factor K at the crack evaluation point considering the influence of the plastic zone at the crack tip can be determined as K = 39.53 MPa·m 1 / 2 ;

[0219] Step 5: Calculate the reference temperature RT at the crack evaluation point considering neutron irradiation embrittlement (irr.) , which specifically includes the following content:

[0220] First step: Based on the attenuation coefficient μ of the neutron fluence along the vessel wall thickness direction input in Step 1 and the sampled value of the neutron fluence F on the inner surface of the RPV obtained in Step 2 0 , calculate the neutron fluence F at the crack evaluation point;

[0221] F = F 0 e -μx

[0222] where x is the distance from the crack evaluation point to the inner surface of the vessel, which is 0.01 m here;

[0223] The neutron fluence F at the crack evaluation point can be determined as F = 6.86×10 19 n / cm 2 ;

[0224] Second step: Based on the neutron fluence F at the crack evaluation point obtained in the first step and the sampled values of the chemical composition contents of Cu, Ni, P, Si, and Mn in the current sample obtained in Step 2, calculate the average value of the temperature offset ΔRT at the crack evaluation point according to the irradiation embrittlement model of domestic RPV steel

[0225]

[0226] A = 0.5 + 0.5tanh{[lg 10 (F) + 1.1390w Cu - 0.4483w Ni - 19.12025] / 0.6287}

[0227] where w p is the chemical composition content of P, which is 0.00323 wt%, w Mn is the chemical composition content of Mn, which is 1.375 wt%, w Ni is the chemical composition content of Ni, which is 0.572 wt%, w Si is the chemical composition content of Si, which is 0.185 wt%, w Cu is the chemical composition content of Cu, which is 0.131 wt%;

[0228] The average value of the temperature offset ΔRT at the crack evaluation point can be determined is 46.604 °C;

[0229] Step 3: Based on the average value of the temperature offset ΔRT of the crack evaluation point obtained in the second step and the sampled value of the standard deviation of the temperature offset ΔRT under the current sample obtained in Step 2, calculate the temperature offset ΔRT caused by irradiation embrittlement at the crack evaluation point;

[0230]

[0231] In the formula, σ ΔRT is the sampled value of the standard deviation of the temperature offset ΔRT under the current sample, which is 2.97 °C here;

[0232] It can be determined that the temperature offset ΔRT caused by irradiation embrittlement at the crack evaluation point is 49.58 °C;

[0233] Step 4: Calculate the reference temperature correction value ΔRT based on the sampled value of the cumulative probability φ under the current sample obtained in Step 2 (mod.) ;

[0234] ΔRT (mod.) = -15.602 + 67.559[ln(1 - φ)] 1 / 4.306

[0235] It can be determined that the reference temperature correction value ΔRT (mod.) is 14.72 °C;

[0236] Step 5: Calculate the reference temperature RT of the crack evaluation point considering neutron irradiation embrittlement (irr.) ;

[0237] RT (irr.) = RT (ini.) + ΔRT - ΔRT (mod.)

[0238] It can be determined that the reference temperature RT of the crack evaluation point considering neutron irradiation embrittlement (irr.) is 20.36 °C;

[0239] Step 6: Based on the temperature T of the crack evaluation point obtained in Step 4 cracktip and the reference temperature RT of the crack evaluation point considering neutron irradiation embrittlement obtained in Step 5 (irr.) , construct the fracture toughness K c probability distribution model of the crack evaluation point, which specifically includes the following content:

[0240] First step: Drawing on the statistical weakest link theory, set the location parameter α, scale parameter β, and shape parameter χ of the Weibull probability distribution model according to the law of the change of fracture toughness with temperature;

[0241] α = 13.1788 + 6.7096exp[0.03366(T cracktip - RT (irr.) )]

[0242] β = 15.8797 + 42.213exp[(0.01208(T cracktip - RT (irr.) )]

[0243] χ = 4

[0244] The fracture toughness K of the crack evaluation point can be determined c The location parameter α of the probability distribution model is 54679.66, the scale parameter β is 1085.04, and the shape parameter χ is 4;

[0245] Step 2: Based on the location parameter α, scale parameter β, and shape parameter χ set in the previous step, construct the fracture toughness K c probability distribution model of the crack evaluation point;

[0246]

[0247] where P f is the cumulative failure probability;

[0248] Step 7: Based on the stress intensity factor K of the crack evaluation point considering the influence of the crack tip plastic zone obtained in Step 4, and the fracture toughness K c probability distribution model of the crack evaluation point constructed in Step 6, calculate the crack initiation probability pci at the current moment τ under transient conditions τ , and the calculation formula is:

[0249]

[0250] where is the fracture toughness of the crack evaluation point when the cumulative failure probability P f is 0, and here

[0251] It can be determined that the crack initiation probability of the crack at the first transient moment under the current sample is 0;

[0252] Step 8: Determine whether the current moment is the last moment of the transient condition. If so, end the calculation process of the crack initiation probability under the transient condition. Otherwise, update the transient moment, and then repeat Steps 3 to 8;

[0253] Step 9: Based on the calculation results at all moments under the transient condition in Step 7, evaluate the crack initiation probability PCI of the RPV surface crack under the nth sample;

[0254] The crack initiation probability PCI of the RPV surface under the current sample is as follows:

[0255] PCI = Max(pci τ )

[0256] After calculating all moments under the transient condition, it can be determined that the crack initiation probability of the RPV surface under the current sample is 5.64×10 -7 , and the calculation results are as Figure 8 shown;

[0257] Step 10: Determine whether the current sample is the last sample. If so, end the calculation; otherwise, repeat Steps 3 to 10 starting from the next sample.

[0258] The above are only the preferred embodiments of the present invention and are not intended to limit the scope of the present invention. Various changes can be made to the above embodiments of the present invention. All simple, equivalent changes and modifications made according to the claims and the content of the specification of the present invention application fall within the scope of the claims of the present invention patent. The content not described in detail in the present invention is all conventional technical content.

Claims

1. A method for evaluating the probability of crack initiation on the surface of an RPV under transient conditions, characterized in that: By coupling fracture mechanics theory with probability assessment technology, the Latin hypercube sampling method is used on the basis of introducing the radiation embrittlement model of RPV steel to efficiently and accurately evaluate the initiation probability of RPV surface cracks under transient conditions.

2. The method for evaluating the probability of crack initiation on the surface of an RPV under transient conditions according to claim 1, characterized in that: The method comprises the following steps: Step 1: Input initial conditions, including RPV geometry, material properties, operating data and transient conditions, and crack characteristics data; Step 2, sampling the random variables and determining the multivariate sample after sampling; Step 3, calculating the stress intensity factor of the crack assessment point caused by multiple loads under transient conditions; Step 4, calculating the stress intensity factor of the crack assessment point after incorporating the influence of the crack tip plastic zone under transient conditions; Step 5, calculating the reference temperature of the crack assessment point after considering neutron irradiation embrittlement under transient conditions; Step 6: construct a fracture toughness probability distribution model of the crack assessment point under transient conditions; Step 7, calculating the probability of crack initiation at the current moment under transient conditions; Step 8, determine whether the current moment is the last moment of the transient condition, if so, end the calculation process of the crack initiation probability under the transient condition, otherwise update the transient moment, and then repeat steps 3 to 8; Step 9, evaluating the probability of crack initiation on the RPV surface under the current sample; Step 10: Determine whether the current sample is the last sample. If so, end the calculation. Otherwise, repeat steps 3 to 10 starting from the next sample.

3. The method for evaluating the probability of crack initiation on the surface of an RPV under transient conditions according to claim 2, characterized in that: In step 1, the RPV geometry, material properties, operating data and transient conditions, as well as crack characteristics data, include: 1) RPV radius R i , cladding thickness t c and base material thickness t b ; 2) Young's modulus of the base metal and weld and its yield stress at different temperatures; 3) The average and standard deviation of the chemical composition contents of Cu, Ni, P, Si and Mn; 4) Initial reference temperature RT (ini.) The mean and standard deviation of 5) Standard deviation of the temperature offset ΔRT caused by radiation embrittlement; 6) The average value and standard deviation of the neutron flux F0 on the inner surface of the RPV, and the attenuation coefficient μ of the neutron flux along the thickness direction of the container wall; 7) Effective full power annual EFPY and operating temperature T of nuclear reactor op ; 8) Internal pressure and temperature distribution in the direction of vessel wall thickness at each moment under transient conditions; 9) Thermal stress distribution in the wall thickness direction of the container at each moment under transient conditions; 10) Residual stress distribution in the container wall thickness direction caused by welding; 11) Location, direction and size of surface cracks; 12) Sample size N.

4. The method for evaluating the probability of crack initiation on the surface of an RPV under transient conditions according to claim 3, characterized in that: In step 2, according to the sample size N set in step 1, the Latin hypercube sampling method is used to sample the random variable to determine the multivariate sample after sampling, which specifically includes the following steps: Step 1: Generate a set of pseudo-random numbers, the number of which is the same as the set sample size N; Step 2: Based on the sample size N and pseudo-random numbers, obtain the reference temperature correction value ΔRT that obeys the standard uniform distribution (mod.) The sampling value of the cumulative probability φ; Step 3: Based on the standard deviation of the temperature offset ΔRT input in step 1, the average and standard deviation of the chemical composition content of Cu, Ni, P, Si, and Mn, the average and standard deviation of the neutron injection F0 on the inner surface of the RPV, and the initial reference temperature RT (ini.) The mean and standard deviation of the temperature offset ΔRT, the chemical composition content of Cu, Ni, P, Si, Mn, the neutron injection F0 on the inner surface of the RPV and the initial reference temperature RT are calculated using the Latin hypercube sampling method according to the sample size N and the pseudo-random number. (ini.) Sampling was performed to obtain the standard deviation of the temperature offset ΔRT that obeyed the normal distribution, the chemical composition content of Cu, Ni, P, Si, and Mn, the neutron injection F0 on the inner surface of the RPV, and the initial reference temperature RT (ini.) The sampling value of Step 4: Determine the multivariate sample after sampling, which is the cumulative probability φ, the standard deviation of the temperature offset ΔRT, the chemical composition content of Cu, Ni, P, Si, and Mn, the neutron injection F0 on the inner surface of the RPV, and the initial reference temperature RT (ini.) A combination of sampled values.

5. The method for evaluating the probability of crack initiation on the surface of an RPV under transient conditions according to claim 4, characterized in that: In step 3, the stress intensity factor K' of the crack assessment point caused by multiple loads under transient conditions is calculated, which specifically includes the following steps: Step 1: According to the surface crack size and surfacing thickness t c , based on the shape coefficient of the surface crack stress intensity factor under different stress conditions, the shape coefficient of the parent material part and the shape coefficient of the cladding part are calculated by linear interpolation method; Step 2: Calculate the stress intensity factor K' at the crack assessment point under internal pressure conditions pressure ; Step 3: Calculate the stress intensity factor K' at the crack assessment point under thermal stress conditions th ; Step 4: Calculate the stress intensity factor K' at the crack assessment point after considering the residual stress WRS ; Step 5: Calculate the sum of stress intensity factors K' at the crack assessment points under the considered load conditions.

6. The method for evaluating the probability of crack initiation on the surface of an RPV under transient conditions according to claim 5, characterized in that: In step 4, based on the sum of stress intensity factors K' obtained in step 3, the stress intensity factor K of the crack assessment point after incorporating the influence of the crack tip plastic zone is calculated, which specifically includes the following steps: Step 1: Based on the temperature distribution in the direction of the container wall thickness at each moment under the transient working condition input in step 1, the temperature T of the crack assessment point is calculated by the relative position of the crack assessment point and the container wall thickness using the linear interpolation method. cracktip ; Step 2: Based on the yield stress of the base material at different temperatures input in step 1, according to the temperature T of the crack evaluation point cracktip The yield stress σ of the parent material is calculated by linear interpolation method. ys ; Step 3: Calculate the stress intensity factor K of the crack assessment point after incorporating the influence of the crack tip plastic zone based on the estimation formula for the size of the crack tip plastic zone under plane strain conditions.

7. The method for evaluating the probability of crack initiation on the surface of an RPV under transient conditions according to claim 6, characterized in that: In step 5, the reference temperature RT of the crack assessment point after considering neutron irradiation embrittlement is calculated. (irr.) , specifically including the following steps: Step 1: Calculate the neutron fluence F at the crack assessment point based on the attenuation coefficient μ of the neutron fluence along the container wall thickness direction input in step 1 and the sampling value of the neutron fluence F0 on the inner surface of the RPV under the current sample obtained in step 2; Step 2: Based on the neutron injection F of the crack assessment point obtained in the first step and the sampling values ​​of the chemical composition content of Cu, Ni, P, Si, and Mn in the current sample obtained in step 2, according to the RPV steel irradiation embrittlement model, calculate the average value of the temperature offset ΔRT of the crack assessment point Step 3: Calculate the average value of the temperature offset ΔRT of the crack assessment point obtained in step 2 and the sampling value of the standard deviation of the temperature offset ΔRT under the current sample obtained in step 2, calculate the temperature offset ΔRT caused by radiation embrittlement at the crack assessment point; Step 4: Calculate the reference temperature correction value ΔRT based on the sampling value of the cumulative probability φ under the current sample obtained in step 2 (mod.) ; Step 5: Based on the temperature offset ΔRT caused by irradiation embrittlement of the crack assessment point obtained in step 3 and the reference temperature correction value ΔRT obtained in step 4 (mod.) And the initial reference temperature RT of the current sample obtained in step 2 (ini.) The sampling value of the crack evaluation point after neutron irradiation embrittlement is calculated by (irr.) .

8. The method for evaluating the probability of crack initiation on the surface of an RPV under transient conditions according to claim 7, characterized in that: In step 6, based on the temperature T of the crack evaluation point obtained in step 4 cracktip and the reference temperature RT of the crack assessment point after neutron irradiation embrittlement obtained in step 5 (irr.) , construct the fracture toughness K of the crack evaluation point c The probability distribution model specifically includes the following steps: Step 1: Based on the statistical weakest link theory, the location parameter, scale parameter and shape parameter of the Weibull probability distribution model are set according to the law of fracture toughness changing with temperature. Step 2: Based on the position parameters, scale parameters and shape parameters set in the previous step, construct the fracture toughness K of the crack evaluation point c Probability distribution model.

9. The method for evaluating the probability of crack initiation on the surface of an RPV under transient conditions according to claim 8, characterized in that: In step 7, the stress intensity factor K of the crack evaluation point after incorporating the influence of the crack tip plastic zone obtained in step 4 and the fracture toughness K of the crack evaluation point constructed in step 6 are used. c Probability distribution model, calculate the crack initiation probability pci at the current time τ under transient conditions τ。 10. The method for evaluating the probability of crack initiation on the surface of an RPV under transient conditions according to claim 9, characterized in that: In step 9, based on the calculation results at all times under transient conditions in step 7, the probability of crack initiation PCI of the RPV surface under the current sample is evaluated; PCI is defined as the pci at all times under transient conditions. τ The maximum value of .

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