Method and device for determining failure probability of spigot-and-socket pipe across a strike-slip fault

Abstract

The present invention provides a method and device for determining the failure probability of a spigot-and-socket pipe across a strike-slip fault, wherein the method comprises: obtaining first-class data and second-class data associated with a target area; based on the first-class data and the second-class data, using a preset surface dislocation quantity generation rule, randomly generating a preset number of surface dislocation quantity samples; based on the second-class data, using a preset failure probability calculation rule, determining the failure probability of the interface of the pipeline under each surface dislocation quantity sample corresponding to the situation; based on the failure probability of the interface of the pipeline under each surface dislocation quantity sample corresponding to the situation, determining the annual average failure probability of the spigot-and-socket pipe across a strike-slip fault. Using the method of the present invention, the failure probability of the spigot-and-socket pipe across a strike-slip fault can be determined while considering the uncertainty of the fault surface dislocation.

Description

Technical Field

[0001] The present invention relates to the technical field of engineering pipeline seismic risk assessment, and in particular to a method, device, electronic equipment, non-transient computer-readable storage medium, and computer program product for determining failure probability of a spigot-and-socket pipeline across a strike-slip fault. Background Art

[0002] Buried spigot-and-socket pipelines are an important part of lifeline projects and are often used to transport oil, water, and natural gas, which are necessary to maintain the normal operation of cities. Spigot-and-socket pipelines inevitably have to cross active fault areas. Since the tensile bending stiffness of the spigot-and-socket pipeline interface is much smaller than the stiffness of the pipe section itself, the surface dislocation of the fault caused by an earthquake often leads to leakage at the pipeline interface, thereby endangering the safety of human life and property and affecting the progress of earthquake relief.

[0003] At present, the existing technologies mostly use deterministic methods such as full-scale tests, centrifuge tests, analytical and numerical methods to explore the response of the spigot-and-socket pipe interface under a given fault surface displacement. However, the above existing technical methods ignore the uncertainty of whether the surface ruptures during an earthquake, the location of the surface rupture, the length of the surface rupture zone, the amount of surface displacement, etc.

[0004] Therefore, how to propose a solution that can determine the failure probability of socket-type pipelines across strike-slip faults while taking into account the uncertainty of fault surface dislocation has become an urgent problem to be solved. Summary of the invention

[0005] The present invention provides a method, device, electronic equipment, non-transient computer-readable storage medium, and computer program product for determining failure probability of a spigot-and-socket pipeline across a strike-slip fault, so as to solve the defects in the prior art.

[0006] The present invention provides a method for determining failure probability of a spigot-and-socket pipeline across a strike-slip fault, comprising:

[0007] Acquire first and second types of data associated with a target area; wherein the first type of data is data associated with a strike-slip fault in the target area, and the second type of data is data associated with a pipeline laying condition in the target area, and the pipeline is a spigot-and-socket type pipeline;

[0008] Based on the first type of data and the second type of data, a preset number of surface dislocation samples are randomly generated using a preset surface dislocation generation rule; wherein the surface dislocation samples represent the surface displacement caused by the strike-slip fault at the location where the pipeline passes through the target area;

[0009] Based on the second type of data, using a preset failure probability calculation rule, determining the failure probability of the interface of the pipeline in the case corresponding to each surface dislocation amount sample;

[0010] Based on the failure probability of the interface of the pipeline corresponding to each surface dislocation sample, the annual average failure probability of the socket-and-spigot pipeline across the strike-slip fault is determined.

[0011] The present invention also provides a device for determining the failure probability of a spigot-and-socket pipe across a strike-slip fault, comprising:

[0012] The data acquisition module is configured to: acquire first-type data and second-type data associated with a target area; wherein the first-type data is data associated with a strike-slip fault in the target area, and the second-type data is data associated with a pipeline laying condition in the target area, and the pipeline is a spigot-and-socket type pipeline;

[0013] The surface dislocation amount generating module is configured to: based on the first type of data and the second type of data, use a preset surface dislocation amount generating rule to randomly generate a preset number of surface dislocation amount samples; wherein the surface dislocation amount samples represent the surface displacement amount caused by the strike-slip fault at the position where the pipeline passes through the target area;

[0014] The single sample failure probability calculation module is configured to: determine the failure probability of the interface of the pipeline in the case corresponding to each surface dislocation amount sample based on the second type of data and using a preset failure probability calculation rule;

[0015] The annual average failure probability calculation module is configured to: determine the annual average failure probability of the socket-type pipeline across the strike-slip fault based on the failure probability of the interface of the pipeline corresponding to each surface dislocation sample

[0016] The present invention also provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the method for determining the failure probability of a spigot-and-socket pipeline across a strike-slip fault as described in any one of the above methods is implemented.

[0017] The present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the method for determining the failure probability of a spigot-and-socket pipeline across a strike-slip fault as described in any one of the above methods is implemented.

[0018] The present invention also provides a computer program product, comprising a computer program, which, when executed by a processor, implements any of the above methods for determining the failure probability of a spigot-and-socket pipeline across a strike-slip fault.

[0019] As described above, the method for determining the failure probability of a socket-and-spigot pipe across a strike-slip fault using the present invention can determine the failure probability of a socket-and-spigot pipe across a strike-slip fault while taking into account the uncertainty of the fault surface dislocation. Thus, it has important practical value for the disaster prevention and mitigation design of the socket-and-spigot pipe across a strike-slip fault under different working conditions. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0021] Figure 1 It is one of the flow diagrams of the method for determining the failure probability of a spigot-and-socket pipe across a strike-slip fault provided by an embodiment of the present invention;

[0022] Figure 2 It is a schematic diagram of the relative position relationship between a socket-and-spigot pipe across a strike-slip fault, a surface rupture zone, and a fault trace provided by an embodiment of the present invention;

[0023] Figure 3 This is a second flow chart of a method for determining failure probability of a spigot-and-socket pipeline across a strike-slip fault provided by an embodiment of the present invention;

[0024] Figure 4 is a schematic diagram of the distribution of surface dislocation along the surface rupture zone provided by an embodiment of the present invention;

[0025] Figure 5 This is a third flow chart of a method for determining failure probability of a spigot-and-socket pipeline across a strike-slip fault provided by an embodiment of the present invention;

[0026] Figure 6 is a schematic diagram of the variation law of the average annual failure probability of a cast iron pipeline across a strike-slip fault with the intersection angle ω between the fault and the pipeline provided by an embodiment of the present invention;

[0027] Figure 7 is a schematic diagram of the surface dislocation results at the midpoint of the fault trace under different working conditions provided by an embodiment of the present invention;

[0028] Figure 8 is a schematic structural diagram of a device for determining failure probability of a spigot-and-socket pipe across a strike-slip fault provided by an embodiment of the present invention;

[0029] Fig. 9 It is a structural schematic diagram of the electronic device provided by the present invention. DETAILED DESCRIPTION

[0030] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the drawings of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0031] To solve the above problems of the prior art, the inventors of the present invention have proposed, after research, a solution for determining the failure probability of a spigot-and-socket pipeline across a strike-slip fault as described in the following embodiment.

[0032] Example:

[0033] The implementation details of the scheme for determining the failure probability of a spigot-and-socket pipeline across a strike-slip fault of the present invention are described below in conjunction with the accompanying drawings.

[0034] Figure 1 1 is a flow chart of a method for determining failure probability of a spigot-and-socket pipe across a strike-slip fault provided by an exemplary embodiment of the present invention. This embodiment can be applied to electronic devices (for example, servers or cloud computing platforms), such as Figure 1 As shown, the method for determining the failure probability of a spigot-and-socket pipe across a strike-slip fault includes the following steps:

[0035] S110: Acquire first-category data and second-category data associated with the target area.

[0036] The first type of data is data associated with the strike-slip fault in the target area, the second type of data is data associated with the pipeline laying conditions in the target area, and the pipeline is a socket-and-spigot type pipeline.

[0037] S120. Based on the first type of data and the second type of data, using a preset surface dislocation generation rule, randomly generate a preset number of surface dislocation samples.

[0038] The surface dislocation sample represents the surface displacement caused by the strike-slip fault at the location where the pipeline passes through the target area.

[0039] S130. Based on the second type of data, using a preset failure probability calculation rule, determine the failure probability of the interface of the pipeline in each case corresponding to the surface dislocation sample.

[0040] S140. Determine the average annual failure probability of the spigot-and-socket pipeline across a strike-slip fault based on the failure probability of the interface of the pipeline corresponding to each surface dislocation sample.

[0041] The present invention does not limit the acquisition method. For example, an electronic device (e.g., a server or a cloud computing platform) as an execution subject may communicate with a server storing the "first type of data and the second type of data", or may communicate with a collection device that collects the first type of data and the second type of data to obtain the data.

[0042] Wherein, the target area is a construction area where pipeline laying is required.

[0043] Among them, in step S120, the uncertainty of earthquake events, surface rupture events, surface rupture locations, surface rupture zone lengths, surface dislocations, etc. can be quantitatively characterized during the specific implementation process. In steps S130 and S140, the influence of relevant parameters on the annual average failure probability of the spigot-and-socket pipeline across the strike-slip fault can be analyzed. The specific implementation details of the above steps will be described below and will not be repeated here.

[0044] As described above, the method for determining the failure probability of a socket-and-spigot pipe across a strike-slip fault using the present invention can determine the failure probability of a socket-and-spigot pipe across a strike-slip fault while taking into account the uncertainty of the fault surface dislocation. Thus, it has important practical value for the disaster prevention and mitigation design of the socket-and-spigot pipe across a strike-slip fault under different working conditions.

[0045] exist Figure 1 Based on the embodiment, as an optional implementation method, refer to Figure 2 The first type of data includes the coordinates of the fault trace, parameters characterizing the positioning accuracy and complexity of the fault trace, and seismic activity distribution data. The second type of data includes the coordinates of the pipeline, parameters characterizing the material of the pipeline, the outer diameter of the pipeline, the length of the pipe section, the buried depth of the pipeline, the form of the pipeline interface, the stiffness of the pipeline interface, the strength of the pipeline interface, and the type of backfill material after the pipeline is laid.

[0046] Among them, Figure 2 As shown, the location of the surface rupture zone along the fault trace (i.e. Figure 2 s) in follows a uniform distribution; the offset distance of the surface rupture zone relative to the fault trace follows a normal distribution, with a mean of 0 m, and a standard deviation that is related to the positioning accuracy and complexity of the fault trace given in Table 1. That is, the parameter characterizing the positioning accuracy and complexity of the fault trace can be the standard deviation of the offset distance of the surface rupture zone relative to the fault trace as shown in Table 1.

[0047]

[0048]

[0049] Table 1 Standard deviation of the offset distance of the surface rupture zone relative to the fault trace

[0050] In the above implementation, the fault trace positioning accuracy and complexity can be selected as precise, and the standard deviation is 26.89m.

[0051] exist Figure 1 Based on the embodiment, as an optional implementation method, refer to Figure 3 , step S120 includes:

[0052] S1210. Determine analysis parameters based on the first type of data and the coordinates of the pipeline.

[0053] As an alternative example, refer to Figure 2 , S1210 can be implemented through the following steps:

[0054] First, obtain the surface rupture zone ( Figure 2 The distribution position of the fault trace (red line) along the fault trace is determined, and the offset distance of the surface rupture zone relative to the fault trace is determined according to the parameters characterizing the positioning accuracy and complexity of the fault trace; second, the starting magnitude m is determined according to the seismic activity distribution data. min and maximum magnitude m max , and fitting the regression coefficients a and b of the Gutenberg-Richter relationship; third, according to the coordinates of the fault trace and the coordinates of the pipeline, determine the length of the fault trace L and the intersection angle ω between the fault and the pipeline. Among them, the surface rupture zone ( Figure 2 The distribution positions of the fault traces (red lines) follow a uniform distribution and can be obtained through random simulation or other applicable methods.

[0055] S1220. Based on the analysis parameters, using a first preset rule, determine the location of the surface rupture zone.

[0056] As an alternative example, refer to Figure 2 , S1210 can be implemented through the following steps:

[0057] 1) Based on the starting magnitude, the maximum magnitude and the regression coefficients a and b of the Gutenberg-Richter relationship, the cumulative distribution function of magnitude is determined.

[0058] The Gutenberg-Richter relationship between the number of earthquakes and their magnitude is:

[0059] log 10 λ m = ab·m(3)

[0060] In the formula, λ m represents the average annual occurrence rate of earthquakes above magnitude m; a is a constant related to the total occurrence rate of earthquakes; b is a constant representing the relative proportion of large and small magnitude earthquakes.

[0061] According to the Gutenberg-Richter relationship, the starting magnitude is m. min and maximum magnitude m max , we can obtain the cumulative distribution function of magnitude:

[0062]

[0063] 2) Based on the magnitude cumulative distribution function, determine the number of earthquakes with a target magnitude occurring in the target area within one year.

[0064] When the magnitude interval is taken as 0.1, the annual average occurrence rate of magnitude m earthquakes can be obtained as m for:

[0065] α m =F M (m+0.1)-F M (m) (5)

[0066] 3) Randomly generate earthquake events based on the number of earthquakes of target magnitude in the target area within one year.

[0067] The source locations of a potential earthquake source area are uniformly distributed in space, and the earthquake occurrence time satisfies the Poisson distribution:

[0068]

[0069] Among them, X=0 means that there is no magnitude m earthquake in a year, and X=k means that there are k magnitude m earthquakes in a year.

[0070] Earthquake events are randomly generated based on the above magnitude-frequency relationship.

[0071] 4) In response to the existence of the earthquake event, a surface rupture event is randomly generated based on the target magnitude.

[0072] Optionally, given an earthquake magnitude m, the probability of surface rupture is calculated based on the following formula, and surface rupture events that follow a Bernoulli distribution are randomly generated:

[0073]

[0074] If no earthquake occurs, the surface displacement is 0m.

[0075] 5) In response to the existence of a surface rupture event, the length of the surface rupture zone is randomly generated based on the target magnitude.

[0076] When the ground surface ruptures, the length of the ground rupture zone that follows the log-normal distribution is randomly generated based on the mean and standard deviation of the length of the ground rupture zone in the logarithmic space determined by the following formula:

[0077]

[0078] If there is no surface rupture, the surface dislocation is 0m.

[0079] 6) In response to the existence of a surface rupture event, the position of the surface rupture zone is randomly generated based on the distribution position of the surface rupture zone along the fault trace, the offset distance of the surface rupture zone relative to the fault trace, and the distribution characteristics corresponding to the distribution position and the offset distance.

[0080] Optionally, the position of the surface rupture zone along the fault trace follows a uniform distribution. The offset distance of the surface rupture zone relative to the fault trace follows a normal distribution with a mean of 0 m and a standard deviation of 26.89 m.

[0081] Based on the above two distributions, the position and offset distance of the surface rupture zone along the fault trace are randomly generated to determine the position of the surface rupture zone.

[0082] S1230, in response to determining that the pipeline crosses the surface rupture zone and determining the position where the pipeline crosses the surface rupture zone based on the position of the surface rupture zone and the coordinates of the pipeline, using preset dislocation mean and standard deviation calculation rules, calculate the mean and standard deviation of the surface dislocation amount in logarithmic space.

[0083] As an optional example, the distribution model of surface dislocation along the surface rupture zone includes Figure 4 The double-line model, elliptical model and quadratic model (magnitude 7 in the figure) are shown. The double-line model can be selected in this embodiment. ls is calculated based on the coordinate information of the surface rupture zone and the pipeline. The surface displacement is the distance from the position where the pipeline crosses the surface rupture zone to the nearest end of the surface rupture zone (i.e. Figure 2 ls in , 0≤l s / L r ≤0..5). The surface dislocation obeys the log-normal distribution.

[0084] Based on this, the following calculation formula (1) can be used to calculate the mean and standard deviation of the surface dislocation in logarithmic space;

[0085]

[0086] When l s / L r <(l s / L r )0:00,

[0087] lnδ=1.7969m+8.5206(l s / L r )-10.2855,σ lnδ =1.2906

[0088] When l s / L r ≥(l s / L r )0:00,

[0089] lnδ=1.7658m-7.8962σ lnδ =0.9624 (1)

[0090] Wherein, m represents the target magnitude; l s Indicates the distance from the position where the pipeline crosses the surface rupture zone to the nearest end of the surface rupture zone; L r represents the length of the surface rupture zone; lnδ represents the mean value of the surface dislocation in logarithmic space; σ lnδ Represents the standard deviation of the surface dislocation in logarithmic space.

[0091] Reference Figure 2 , the distance from the position where the pipeline crosses the surface rupture zone to the nearest end of the surface rupture zone is calculated based on the coordinate information of the surface rupture zone and the pipeline. If the pipeline does not cross the surface rupture zone, the surface displacement is 0m.

[0092] S1240. Based on the mean and standard deviation, randomly generate a surface dislocation amount of the pipeline crossing the surface rupture zone.

[0093] As an optional example, based on the mean and standard deviation, a surface dislocation amount is randomly generated using a preset rule for randomly generating surface dislocation amounts.

[0094] Specifically, the following steps may be included: I1. Generate a log-normally distributed random number based on the mean and standard deviation: for example, use the numpy.random.lognormal function in Python's numpy library, which can directly generate a log-normally distributed random number. I2. Convert the generated random number back to the original scale. Since we generate random numbers in logarithmic space, we need to convert the generated random number (logarithmic scale) back to the original surface dislocation scale, which can be achieved by exponentially taking the generated random number. Through the above steps, a surface dislocation can be randomly generated.

[0095] S1250. Repeat the step of determining the position of the surface rupture zone (i.e., S1220) to the step of randomly generating a surface dislocation amount for the pipeline to cross the surface rupture zone (i.e., S1240), until a preset end condition is met, and the preset number of surface dislocation amounts is obtained.

[0096] Based on the above embodiment, as an optional implementation mode, refer to Figure 5 , step S130 may include:

[0097] S1310. Based on the parameters characterizing the material of the pipeline, the form of the pipeline interface, and the type of the backfill material, determine a maximum interface response calculation model and determine necessary data required for calculation in the second type of data.

[0098] S1320, determining the maximum axial displacement λ of the interface based on the maximum interface response calculation model, the necessary data, and each surface dislocation sample max and the maximum relative rotation angle β max (The two make up the maximum response ε of the interface max ).

[0099] S1330. Determine the failure probability of the interface of the pipeline in each corresponding case of the surface dislocation sample based on the maximum axial displacement and the maximum relative rotation angle of the interface.

[0100] It should be noted that construction in different target areas will face different working conditions, and the specific pipe materials, pipe interface forms, and backfill materials involved are also different, which will lead to the selection of the maximum interface response calculation model and the data involved in the calculation in the second type of data will also be adaptively adjusted. Among them, the form of the pipe interface may include but is not limited to blue lead interface, rubber ring interface, asbestos cement interface, etc.

[0101] In steps S1310 to S1330, based on the relevant data of the pipeline laying conditions, taking the pipeline material as cast iron and the backfill material as dense sand as an example, the outer diameter D of the pipeline is determined. os , pipe length L p , pipeline burial depth d, interface stiffness and strength characteristics and other relevant calculation parameters are shown in Table 2.

[0102]

[0103]

[0104] Table 2 Related parameter values ​​for failure probability analysis of cast iron pipelines across strike-slip faults

[0105] Among them, for the blue-lead joint of cast iron pipe, the joint stiffness characteristics and joint bonding strength a C Related, the initial slip of the interface corresponds to the axial force F j The initial slip moment M corresponding to the interface j It can be calculated by the following formula:

[0106] F j =πD os d L a C (9)

[0107]

[0108] Among them, d L is the lead filling depth, which is taken as 0.057m, and the definitions of other parameters are consistent with the previous ones.

[0109] The interface strength characteristics involve the axial displacement λ corresponding to the interface leakage l and the relative rotation angle β l , for D os For 1246mm cast iron pipe blue lead interface, l is 0.45 times the interface depth, β l is 0.5°.

[0110] As an optional example, given the surface dislocation, the fault-pipeline intersection angle ω, and the pipeline outer diameter D os , blue lead interface bonding strength C ,λ max It can be calculated by the following formula

[0111] λ max =f δ,ω ·f F ·f d (11)

[0112]

[0113] f d =0.024d+0.069 (14)

[0114] In the formula, δ, ω, F j The definitions of and d are the same as above, with the units of mm, rad, kN, and m respectively.

[0115] Similarly, β max It can be calculated by the following formula:

[0116]

[0117] g M =0.690-0.920M j (18)

[0118] g d =0.208d+1.455 (19)

[0119] Where M j The unit is kN·mm; other parameter definitions are consistent with the previous text.

[0120] Get the maximum axial displacement λ of the interface max and the maximum relative rotation angle β max , the Bernoulli distribution can be used to determine whether the interface is invalid:

[0121] P[failure|ε max (δ,θ)]=1-I(λ max <λ l )∧I(β max <β l ) (20)

[0122] Among them, θ is the relevant parameter with fixed value, including ω, d, D os , L p ,d L 、a C ; I(λ max <λ l )^I(β max <β l ) is a logical function, only when I(λ max <λ l ) and I(β max <β l ) are equal to 1, and 0 in other cases; I(λ max <λ l ) and I(β max <β l ) is the discriminant function, which takes the value of 1 when the condition is met and takes the value of 0 when the condition is not met. When the probability calculated by formula (20) is 1, it means that the interface fails.

[0123] Based on the above embodiment, as an optional implementation, step S140 may include: using the following calculation formula (2) to calculate and determine the annual average failure probability of the spigot-and-socket pipe across the strike-slip fault;

[0124]

[0125] Wherein, N represents the preset number; P[failure|ε max (δ,θ)] represents the failure probability of the interface of the pipeline in the case corresponding to each surface displacement sample; ε max represents the maximum interface response; δ represents the surface dislocation sample; θ represents the preset value parameter, that is, the related parameter with the same fixed value as mentioned above.

[0126] By adjusting the values ​​of relevant parameters in Table 2, the variation law of the annual average failure probability of cast iron pipelines across strike-slip faults with relevant parameters can be obtained. Taking the intersection angle ω between the fault and the pipeline as an example, by adjusting the values ​​of parameters such as the intersection angle ω between the fault and the pipeline, it can be obtained Figure 6 The figure shows how the average annual failure probability of a cast iron pipeline across a strike-slip fault varies with the angle ω between the fault and the pipeline.

[0127] To verify the accuracy of the above method, the results obtained by the method of the present invention are compared with the results obtained based on the probability method. It should be noted that the verification condition assumes that the length of the fault trace is 100km and a characteristic earthquake with a magnitude of 7 occurs on average every 140 years. Figure 7 The results of the surface dislocation at the midpoint of the fault trace under different working conditions. The magnitude, seismic interval and recurrence period corresponding to each working condition are shown in Table 3.

[0128]

[0129]

[0130] Table 3 Magnitude, earthquake interval and recurrence period corresponding to each working condition

[0131] Referring to Table 3, when the method of the above embodiment of the present invention and the "probability method" as a measurement standard are applied to different working conditions, the following can be obtained: Figure 7 The “diagram of comparison of surface displacement results at the midpoint of the fault trace under different working conditions” is shown in the figure. Figure 7 It can be seen that the results obtained by the method of the present invention are in good agreement with the results obtained based on the probability method, which verifies the accuracy of the method of the present invention.

[0132] In summary, the method for determining the failure probability of a socket-and-spigot pipe across a strike-slip fault using the present invention can determine the failure probability of a socket-and-spigot pipe across a strike-slip fault while taking into account the uncertainty of the fault surface dislocation. Thus, it has important practical value for the disaster prevention and mitigation design of socket-and-spigot pipes across strike-slip faults under different working conditions.

[0133] The following is a description of the device for determining the failure probability of a socket-type pipe across a strike-slip fault provided by the present invention. The device for determining the failure probability of a socket-type pipe across a strike-slip fault described below and the method for determining the failure probability of a socket-type pipe across a strike-slip fault described above can be referenced to each other.

[0134] Figure 8 FIG. 1 is a schematic diagram of a device for determining failure probability of a spigot-and-socket pipe across a strike-slip fault provided by an exemplary embodiment of the present invention. Figure 8As shown, the device for determining the failure probability of a spigot-and-socket pipeline across a strike-slip fault comprises: a data acquisition module 810, configured to: acquire first-type data and second-type data associated with a target area; wherein the first-type data is data associated with the strike-slip fault in the target area, and the second-type data is data associated with the pipeline laying conditions in the target area, and the pipeline is a spigot-and-socket pipeline; a surface dislocation amount generation module 820, configured to: based on the first-type data and the second-type data, use a preset surface dislocation amount generation rule to randomly generate a preset number of surface dislocation amount samples This; wherein the surface dislocation sample represents the surface displacement caused by the strike-slip fault at the position where the pipeline crosses the target area; the single sample failure probability calculation module 830 is configured to: based on the second type of data, use the preset failure probability calculation rule to determine the failure probability of the interface of the pipeline in the case corresponding to each surface dislocation sample; the annual average failure probability calculation module 840 is configured to: based on the failure probability of the interface of the pipeline in the case corresponding to each surface dislocation sample, determine the annual average failure probability of the socket-type pipeline across the strike-slip fault.

[0135] Fig. 9 An example of a physical structure diagram of an electronic device is shown in FIG. Fig. 9 As shown, the electronic device may include: a processor (processor) 910, a communication interface (Communications Interface) 920, a memory (memory) 930 and a communication bus 940, wherein the processor 910, the communication interface 920, and the memory 930 communicate with each other through the communication bus 940. The processor 910 can call the logic instructions in the memory 930 to execute a method for determining the failure probability of a spigot-and-socket pipeline across a strike-slip fault, the method comprising: obtaining a first type of data and a second type of data associated with a target area; wherein the first type of data is data associated with a strike-slip fault in the target area, and the second type of data is data associated with a pipeline laying condition in the target area, and the pipeline is a spigot-and-socket pipeline; based on the first type of data and the second type of data, using a preset surface dislocation amount generation rule, randomly generating a preset number of surface dislocation amount samples; wherein the surface dislocation amount samples characterize the surface displacement amount caused by the strike-slip fault at the position where the pipeline crosses the target area; based on the second type of data, using a preset failure probability calculation rule, determining the failure probability of the interface of the pipeline in the case corresponding to each of the surface dislocation amount samples; based on the failure probability of the interface of the pipeline in the case corresponding to each of the surface dislocation amount samples, determining the average annual failure probability of the spigot-and-socket pipeline across a strike-slip fault.

[0136] In addition, the logic instructions in the above-mentioned memory 930 can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when it is sold or used as an independent product. Based on such an understanding, the technical solution of the present invention can be essentially or partly embodied in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc. Various media that can store program codes.

[0137] On the other hand, the present invention also provides a computer program product, which includes a computer program, which can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the method for determining the failure probability of a spigot-and-socket pipeline across a strike-slip fault provided by the above methods, the method comprising: obtaining a first type of data and a second type of data associated with a target area; wherein the first type of data is data associated with a strike-slip fault in the target area, and the second type of data is data associated with a pipeline laying condition in the target area, and the pipeline is a spigot-and-socket pipeline; based on the first type of data and the second type of data, a preset surface dislocation amount generation rule is used to randomly generate a preset number of surface dislocation amount samples; wherein the surface dislocation amount samples represent the surface displacement amount caused by the strike-slip fault at the position where the pipeline crosses the target area; based on the second type of data, a preset failure probability calculation rule is used to determine the failure probability of the interface of the pipeline in the case corresponding to each of the surface dislocation amount samples; based on the failure probability of the interface of the pipeline in the case corresponding to each of the surface dislocation amount samples, the average annual failure probability of the spigot-and-socket pipeline across a strike-slip fault is determined.

[0138] On the other hand, the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which is implemented when the processor executes the method for determining the failure probability of a spigot-and-socket pipeline across a strike-slip fault provided by the above methods, the method comprising: obtaining a first type of data and a second type of data associated with a target area; wherein the first type of data is data associated with the strike-slip fault in the target area, and the second type of data is data associated with the pipeline laying conditions in the target area, and the pipeline is a spigot-and-socket pipeline; based on the first type of data and the second type of data, a preset surface dislocation amount generation rule is used to randomly generate a preset number of surface dislocation amount samples; wherein the surface dislocation amount samples represent the surface displacement amount caused by the strike-slip fault at the position where the pipeline crosses the target area; based on the second type of data, a preset failure probability calculation rule is used to determine the failure probability of the interface of the pipeline in the case corresponding to each of the surface dislocation amount samples; based on the failure probability of the interface of the pipeline in the case corresponding to each of the surface dislocation amount samples, the average annual failure probability of the spigot-and-socket pipeline across a strike-slip fault is determined.

[0139] The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without paying creative labor.

[0140] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0141] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for determining the failure probability of a spigot-and-socket pipe across a strike-slip fault, characterized in that: include: Acquire first and second types of data associated with a target area; wherein the first type of data is data associated with a strike-slip fault in the target area, and the second type of data is data associated with a pipeline laying condition in the target area, and the pipeline is a spigot-and-socket type pipeline; Based on the first type of data and the second type of data, a preset number of surface dislocation samples are randomly generated using a preset surface dislocation generation rule; wherein the surface dislocation samples represent the surface displacement caused by the strike-slip fault at the location where the pipeline passes through the target area; based on the first type of data and the second type of data, a preset number of surface dislocation samples are randomly generated using a preset surface dislocation generation rule, including: Determine analysis parameters based on the first type of data and the coordinates of the pipeline; determine the position of a surface rupture zone based on the analysis parameters using a first preset rule; in response to determining that the pipeline crosses the surface rupture zone and the position where the pipeline crosses the surface rupture zone based on the position of the surface rupture zone and the coordinates of the pipeline, calculate the mean and standard deviation of the surface dislocation amount in logarithmic space using a preset dislocation mean and standard deviation calculation rule; randomly generate a surface dislocation amount of the pipeline crossing the surface rupture zone based on the mean and standard deviation; repeat the steps of determining the position of the surface rupture zone to randomly generating a surface dislocation amount of the pipeline crossing the surface rupture zone until a preset end condition is met to obtain the preset number of surface dislocation amounts; Based on the second type of data, using a preset failure probability calculation rule, determining the failure probability of the interface of the pipeline in the case corresponding to each surface dislocation amount sample; Based on the failure probability of the interface of the pipeline corresponding to each surface dislocation sample, the annual average failure probability of the socket-and-spigot pipeline across the strike-slip fault is determined.

2. The method according to claim 1, characterized in that The first type of data includes coordinates of fault traces, parameters characterizing the positioning accuracy and complexity of fault traces, and seismic activity distribution data; The second type of data includes the coordinates of the pipeline, parameters characterizing the material of the pipeline, pipeline outer diameter, pipe section length, pipeline burial depth, pipeline interface form, pipeline interface stiffness, pipeline interface strength, and the type of backfill material after pipeline laying.

3. The method according to claim 2, characterized in that The determining of analysis parameters based on the first type of data and the coordinates of the pipeline includes: Obtaining the distribution position of the surface rupture zone along the fault trace, and determining the offset distance of the surface rupture zone relative to the fault trace based on the parameters characterizing the positioning accuracy and complexity of the fault trace; According to the seismic activity distribution data, the starting magnitude and the maximum magnitude are determined, and the regression coefficient of the Gutenberg-Richter relationship is obtained by fitting; The length of the fault and the intersection angle between the fault and the pipeline are determined according to the coordinates of the fault trace and the coordinates of the pipeline.

4. The method according to claim 3, characterized in that The determining the location of the surface rupture zone based on the analysis parameters and using a first preset rule includes: Determine the cumulative distribution function of magnitude based on the starting magnitude, the maximum magnitude and the regression coefficient of the Gutenberg-Richter relationship; Based on the magnitude cumulative distribution function, determining the number of earthquakes with a target magnitude in the target area within one year; Randomly generate earthquake events based on the number of earthquakes with a target magnitude in the target area within one year; In response to the existence of the earthquake event, randomly generating a surface rupture event based on the target magnitude; In response to the existence of a surface rupture event, randomly generating a length of a surface rupture zone based on the target magnitude; In response to the existence of a surface rupture event, the position of the surface rupture zone is randomly generated based on the distribution position of the surface rupture zone along the fault trace, the offset distance of the surface rupture zone relative to the fault trace, and the distribution characteristics corresponding to the distribution position and the offset distance.

5. The method according to claim 1, characterized in that The response is based on the position of the surface rupture zone and the coordinates of the pipeline, determining that the pipeline crosses the surface rupture zone and determining the position where the pipeline crosses the surface rupture zone, and using a preset dislocation mean and standard deviation calculation rule to calculate the mean and standard deviation of the surface dislocation in the logarithmic space, including: The following calculation formula (1) is used to calculate the mean and standard deviation of the surface dislocation in logarithmic space; Where m represents the target magnitude; ls represents the distance from the position where the pipeline crosses the surface rupture zone to the nearest end of the surface rupture zone; Lr represents the length of the surface rupture zone; lnδ represents the mean value of the surface dislocation in logarithmic space; σ lnδ Represents the standard deviation of the surface dislocation in logarithmic space.

6. The method according to claim 1, characterized in that The randomly generating a surface displacement amount of the pipeline crossing the surface rupture zone based on the mean and the standard deviation includes: Based on the mean and the standard deviation, a surface dislocation amount is randomly generated using a preset rule for randomly generating a surface dislocation amount.

7. The method according to claim 2, characterized in that The method of determining the failure probability of the interface of the pipeline in each case corresponding to the surface dislocation sample based on the second type of data and using a preset failure probability calculation rule includes: Based on the parameters characterizing the material of the pipeline, the form of the pipeline interface, and the type of the backfill material, a maximum interface response calculation model is determined, and data required for calculation is determined in the second type of data; Determine the maximum axial displacement and the maximum relative rotation angle of the interface based on the maximum interface response calculation model, the data required for calculation determined in the second type of data, and each of the surface dislocation samples; Based on the maximum axial displacement and the maximum relative rotation angle of the interface, the failure probability of the interface of the pipeline in each corresponding case of the surface misalignment sample is determined.

8. The method according to claim 2, characterized in that: The method of determining the annual average failure probability of the spigot-and-socket pipeline across a strike-slip fault based on the failure probability of the interface of the pipeline corresponding to each surface dislocation sample includes: The following calculation formula (2) is used to calculate and determine the annual average failure probability of the socket-and-spigot pipe across the strike-slip fault; Where N represents the preset number; P[failure|ε max (δ,θ)] represents the failure probability of the pipeline interface in each surface misalignment sample; ε max represents the maximum interface response; δ represents the surface dislocation sample; θ represents the preset value parameter.

9. A device for determining the failure probability of a spigot-and-socket pipe across a strike-slip fault, the device for determining the failure probability of a spigot-and-socket pipe across a strike-slip fault being used to implement the method for determining the failure probability of a spigot-and-socket pipe across a strike-slip fault as claimed in claim 1, characterized in that: include: The data acquisition module is configured to: acquire first-type data and second-type data associated with a target area; wherein the first-type data is data associated with a strike-slip fault in the target area, and the second-type data is data associated with a pipeline laying condition in the target area, and the pipeline is a spigot-and-socket type pipeline; The surface dislocation amount generating module is configured to: based on the first type of data and the second type of data, use a preset surface dislocation amount generating rule to randomly generate a preset number of surface dislocation amount samples; wherein the surface dislocation amount samples represent the surface displacement amount caused by the strike-slip fault at the position where the pipeline passes through the target area; The single sample failure probability calculation module is configured to: determine the failure probability of the interface of the pipeline in the case corresponding to each surface dislocation amount sample based on the second type of data and using a preset failure probability calculation rule; The annual average failure probability calculation module is configured to determine the annual average failure probability of the socket-and-spigot pipeline across the strike-slip fault based on the failure probability of the interface of the pipeline corresponding to each surface dislocation sample.

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