Methods, apparatus, equipment and readable storage media for assessing the residual strength of pipelines

Abstract

This invention provides a method, apparatus, device, and readable storage medium for assessing the remaining strength of pipelines. The method includes: constructing a geometric model of the pipeline containing pitting clusters based on pipeline dimensions and pitting cluster information; constructing a finite element model of the pipeline's remaining strength; solving the finite element model of the pipeline's remaining strength using the arc-length method to obtain the pipeline's remaining strength; constructing a new geometric model of the pipeline containing pitting clusters; forming a discrete sequence of pipeline remaining strengths using N pipeline remaining strengths; and calculating the mean, coefficient of variation, and pipeline remaining strength at preset quantiles of the discrete sequence of pipeline remaining strengths for assessing the pipeline's remaining strength. This invention provides a better quantitative assessment of the random characteristics of pitting cluster defects, resulting in a more accurate assessment of the remaining strength of pipelines containing pitting cluster defects, thus providing a reliable theoretical basis for the formulation of safety design and operation and maintenance strategies for subsea pipelines.

Description

Technical Field

[0001] This invention relates to the field of pipeline engineering technology, and in particular to a method, apparatus, equipment, and readable storage medium for assessing the residual strength of pipelines. Background Technology

[0002] Submarine pipelines, serving as the medium connecting subsea facilities and onshore terminals, play a crucial role in transporting oil and gas resources. They possess advantages such as high efficiency and economy, and are considered the "lifeline" of the offshore oil and gas development industry. The safety of submarine pipelines during their service life is a necessary condition for the stable and efficient development of oil and gas resources. my country's existing submarine pipelines are widely distributed, operating across five marine corrosion zones, resulting in severe corrosion problems. Relevant statistics indicate that corrosion is the leading cause of submarine pipeline failures. As pipelines age, corrosion defects continuously develop and mature, reducing pipe wall thickness and load-bearing capacity. Under working internal pressure loads, these defects cause stress concentration in the structure, leading to pipeline burst failure, ultimately resulting in oil spills or even explosions, causing severe economic losses and environmental pollution. Therefore, accurately assessing the remaining strength of pipelines with corrosion defects under working internal pressure loads is of great significance for ensuring their structural safety.

[0003] Due to the complex marine environment and microbial corrosion, the outer surface of pipelines often develops complex pitting corrosion clusters with interwoven internal pores and highly random geometric features. Related research indicates that the local geometric characteristics of pitting corrosion clusters affect the stress-strain distribution and failure path development of pipelines under internal pressure loads, thus impacting their residual strength. Furthermore, pitting corrosion clusters often exist in clusters, with interactions between adjacent clusters further reducing the pipeline's structural load-bearing capacity. However, current assessments of the residual strength of pipelines containing pitting corrosion clusters simplify these defects to ideally shaped rectangular or elliptical defects and assign a single, definitive value to the pipeline's residual strength. This does not align with the actual randomness of the geometric characteristics of pitting corrosion clusters, leading to significant discrepancies between the assessed residual strength and the actual situation. This hinders the development of safe design and operation and maintenance strategies for subsea pipelines. Summary of the Invention

[0004] The main objective of this invention is to provide a method, apparatus, device, and readable storage medium for assessing the residual strength of pipelines. This aims to address the current technical problem where the assessment of the residual strength of pipelines with pitting defects simplifies these defects to ideal rectangular or elliptical shapes and assigns a single, definitive value, which does not align with the randomness of the geometric characteristics of pitting defects. This results in a significant deviation between the assessed residual strength of pipelines with pitting defects and the actual situation.

[0005] In a first aspect, the present invention provides a method for assessing the remaining strength of a pipeline, the method comprising:

[0006] Based on the pipe dimensions and pitting cluster information, a pipe geometric model containing pitting clusters is constructed.

[0007] By performing finite element analysis on the geometric model of the pipeline containing pitting corrosion clusters, and setting the material properties and external loads of the pipeline, a finite element model of the pipeline's remaining strength is constructed.

[0008] The finite element model of the pipeline's remaining strength was solved using the arc length method to obtain the pipeline's remaining strength.

[0009] A new geometric model of the pipeline containing pitting corrosion clusters is constructed. The new geometric model of the pipeline containing pitting corrosion clusters is used as the geometric model of the pipeline containing pitting corrosion clusters. The steps described above are returned: by performing finite element meshing on the geometric model of the pipeline containing pitting corrosion clusters, and setting the material properties and external loads of the pipeline, a finite element model of the pipeline's remaining strength is constructed.

[0010] When N pipe remaining strengths are obtained, the N pipe remaining strengths are used to form a discrete sequence of pipe remaining strengths, where N is a positive integer greater than or equal to 100;

[0011] The mean, coefficient of variation, and residual strength of the pipeline at preset quantiles are calculated to evaluate the residual strength of the pipeline.

[0012] Optionally, the pipe dimensions include the pipe outer diameter, pipe wall thickness, and pipe length; the pitting cluster information includes the pitting cluster size, pitting cluster type, and pitting cluster spacing; and the step of constructing a pipe geometric model containing pitting clusters based on the pipe dimensions and pitting cluster information includes:

[0013] An initial pipe geometric model is constructed based on the pipe's outer diameter, wall thickness, and length.

[0014] Based on the size, type, and spacing of the pitting clusters, establish the axial, circumferential, and radial boundary ranges of the pitting clusters.

[0015] Within the axial, circumferential, and radial boundaries of the established pitting cluster, multiple spherical geometric models with uniformly distributed radii and spatial positions are generated.

[0016] The generated spherical geometric models with uniformly distributed radii and spatial positions are assembled with the initial pipe geometric model into the same geometric space, and Boolean operations are performed to construct a pipe geometric model containing pitting clusters.

[0017] Optionally, the pitting cluster size includes the pitting cluster length, pitting cluster depth, and pitting cluster width; the pitting cluster type includes single pitting clusters, circumferentially distributed pitting clusters, and axially distributed pitting clusters; and establishing the axial, circumferential, and radial boundary ranges of the pitting clusters based on the pitting cluster size, pitting cluster type, and pitting cluster spacing includes:

[0018] Construct a cylindrical coordinate system (θ, r, z) with the center of the initial pipe geometry model as the origin;

[0019] Based on the pitting cluster length, pitting cluster depth, pitting cluster width, single pitting cluster, circumferentially distributed pitting cluster, axially distributed pitting cluster, and pitting cluster spacing, the axial boundary range of the pitting cluster is established as follows:

[0020] l c,1 ≤z≤l c,2 ,

[0021]

[0022] The circumferential boundary range of the pitting cluster is defined as follows:

[0023] dis c,j ≤r, (j=1,2),

[0024]

[0025] k c,j =tan(θ) c,j ),

[0026]

[0027] The radial boundary range of the pitting cluster is defined as follows:

[0028] (r p -d d )+r≤r≤r p +r,

[0029] Among them, l c,1 and l c,2 The upper and lower boundaries formed by the lengths of the pitting clusters, l d d is the length of the pitting cluster. d w represents the pitting cluster depth. d s is the width of the pitting cluster.c s represents the spacing between pitting clusters in a circumferentially distributed pitting pattern. l dis represents the pitting cluster spacing of axially distributed pitting clusters. c,1 and dis c,2 For the sphere model sp i The distance from the center of the circle to the upper and lower boundaries formed by the width of the pitting cluster, where i is the distance of the sphere model sp. i The subscript θ represents the i-th sphere model. c,1 and θ c,2 r is the central angle corresponding to the upper and lower boundaries formed by the width of the pitting cluster. p Let r be the radius of the complete pipe, and sp be the radius of the sphere model. i The radius.

[0030] Optionally, the construction of the new pipeline geometry model containing pitting clusters includes:

[0031] Within the axial, circumferential, and radial boundaries of the established pitting cluster, multiple new spherical geometric models with uniformly distributed radii and spatial positions are generated.

[0032] The newly generated sphere geometric model with multiple radii and spatial positions uniformly distributed is assembled with the initial pipeline geometric model into the same geometric space, and Boolean operations are performed to construct a new pipeline geometric model containing pitting clusters.

[0033] Optionally, the step of constructing a finite element model of the pipe's residual strength by performing finite element analysis on the geometric model of the pipe containing pitting corrosion clusters and setting the pipe's material properties and external loads includes:

[0034] Based on the pipe dimensions, the degrees of freedom in six directions at both ends of the geometric model of the pipe containing pitting clusters are constrained;

[0035] For the geometric model of the pipeline containing pitting corrosion clusters, the pitting corrosion cluster region is divided into free meshes, and the non-pitting corrosion cluster region is divided into structured meshes, resulting in multiple model elements;

[0036] Based on the material properties of the pipeline and the external load, the stress-strain relationship function of each model element is constructed using the Lamberg-Osgood relation model;

[0037] A finite element model of the pipeline's remaining strength is constructed based on the stress-strain relationship function of each model element.

[0038] Optionally, the solution of the finite element model of the pipe's remaining strength using the arc-length method includes:

[0039] The arc-length method is used to solve for the residual strength of the pipe in each load step using Formula 1:

[0040] Ki μ i =F i ,

[0041] Among them, K i Let μ be the initial tangent stiffness matrix for the i-th load step. i Let F be the initial displacement matrix for the i-th load step. i Let i be the load of the i-th load step. This represents the displacement increment in the j-th iteration within the i-th load step. This represents the increment of the proportional load factor in the j-th iteration within the i-th load step. The residual of the j-th iteration step in the i-th load step. For the node internal load in the j-th iteration step of the i-th load step, Let be the external load of the node in the j-th iteration step of the i-th load step.

[0042] Optionally, the calculation of the mean, coefficient of variation, and residual pipeline strength at preset quantiles of the discrete sequence of residual pipeline strength includes:

[0043] Calculate the mean and coefficient of variation of the discrete sequence of the remaining strength of the pipeline;

[0044] The kernel density estimation method is used to fit the probability distribution of the discrete sequence of pipeline residual strength. The pipeline residual strength at the preset quantile is calculated using Formula 2, which is:

[0045]

[0046] Where f(x) is the probability density function obtained by fitting the probability distribution of the discrete sequence of the pipeline's remaining strength using the kernel density estimation method, x i Let x be the value of the i-th experimental point of random variable x, N be the total number of experimental points in the random variable sequence, h be the smoothing parameter, K(u) be the kernel function, and u be the independent variable of the kernel function.

[0047] Secondly, the present invention also provides a pipeline residual strength assessment device, the pipeline residual strength assessment device comprising:

[0048] The first construction module is used to construct a pipeline geometric model containing pitting clusters based on the pipeline size and pitting cluster information;

[0049] The second construction module is used to construct a finite element model of the pipe's remaining strength by performing finite element meshing on the geometric model of the pipe containing pitting clusters and setting the pipe's material properties and external loads.

[0050] The solver module is used to solve the finite element model of the pipe's remaining strength using the arc length method, and obtain the pipe's remaining strength.

[0051] The third construction module is used to construct a new pipeline geometric model containing pitting corrosion clusters, use the new pipeline geometric model containing pitting corrosion clusters as the geometric model of the pipeline containing pitting corrosion clusters, and return the step of constructing a finite element model of the pipeline's remaining strength by performing finite element meshing on the geometric model of the pipeline containing pitting corrosion clusters and setting the material properties and external loads of the pipeline.

[0052] The component module is used to form a discrete sequence of pipe remaining strengths when N pipe remaining strengths are obtained, where N is a positive integer greater than or equal to 100;

[0053] The calculation module is used to calculate the mean, coefficient of variation, and residual strength of the pipeline at preset quantiles of the discrete sequence of residual strength, so as to evaluate the residual strength of the pipeline.

[0054] Thirdly, the present invention also provides a pipeline residual strength assessment device, the pipeline residual strength assessment device including a processor, a memory, and a pipeline residual strength assessment program stored in the memory and executable by the processor, wherein when the pipeline residual strength assessment program is executed by the processor, the steps of the pipeline residual strength assessment method as described above are implemented.

[0055] Fourthly, the present invention also provides a readable storage medium storing a pipeline remaining strength assessment program, wherein when the pipeline remaining strength assessment program is executed by a processor, it implements the steps of the pipeline remaining strength assessment method as described above.

[0056] In this invention, a pipeline geometric model containing pitting clusters is constructed based on pipeline dimensions and pitting cluster information. A finite element model of the pipeline's remaining strength is constructed by performing finite element analysis on the geometric model and setting the pipeline's material properties and external loads. The remaining strength of the pipeline is obtained by solving the finite element model using the arc-length method. A new pipeline geometric model containing pitting clusters is constructed and used as the geometric model of the pipeline containing pitting clusters. The process then returns to the previous step of performing finite element analysis on the geometric model of the pipeline containing pitting clusters and setting the pipeline's material properties and external loads to construct the finite element model of the pipeline's remaining strength. When N pipeline remaining strengths are obtained, a discrete sequence of pipeline remaining strengths is formed from these N remaining strengths, where N is a positive integer greater than or equal to 100. The mean, coefficient of variation, and pipeline remaining strength at preset quantiles of the discrete sequence of pipeline remaining strengths are calculated for evaluation of the pipeline's remaining strength. This invention, by repeatedly constructing N random geometric models of pipelines containing pitting clusters based on pipeline dimensions and pitting cluster information, and by constructing a finite element model of the pipeline's remaining strength, and solving the finite element model of the pipeline's remaining strength, yields a discrete sequence of pipeline remaining strengths consisting of N pipeline remaining strengths. Then, statistical indices are calculated on this discrete sequence of pipeline remaining strengths, thus providing a better quantitative assessment of the random characteristics of pitting cluster defects. This results in a more accurate assessment of the remaining strength of pipelines containing pitting cluster defects, providing a reliable theoretical basis for the formulation of safety design and operation and maintenance strategies for subsea pipelines. Attached Figure Description

[0057] Figure 1 This is a schematic flowchart of an embodiment of the pipeline residual strength assessment method of the present invention;

[0058] Figure 2 for Figure 1 A detailed flowchart of step S10;

[0059] Figure 3 This is a schematic diagram of the boundary of a sphere geometric model according to an embodiment of the pipeline residual strength assessment method of the present invention;

[0060] Figure 4 This is a schematic diagram of pitting cluster types in an embodiment of the pipeline residual strength assessment method of the present invention;

[0061] Figure 5 for Figure 1 A detailed flowchart of step S20;

[0062] Figure 6 This is a schematic diagram showing the probability density and cumulative density distribution of the discrete sequence of the residual strength of the pipeline under different working conditions.

[0063] Figure 7This is a schematic diagram of a typical example of pipeline failure containing a single point corrosion cluster defect;

[0064] Figure 8 This is a functional module diagram of an embodiment of the pipeline residual strength assessment device of the present invention;

[0065] Figure 9 This is a schematic diagram of the hardware structure of an embodiment of the pipeline residual strength assessment device of the present invention.

[0066] The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0067] It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0068] In a first aspect, embodiments of the present invention provide a method for evaluating the remaining strength of a pipeline.

[0069] To more clearly demonstrate the pipeline residual strength assessment method provided in the embodiments of this application, we will first introduce the application scenarios of the pipeline residual strength assessment method provided in the embodiments of this application.

[0070] The pipeline residual strength assessment method provided in this application is applied to assess the residual strength of subsea pipelines with corrosion defects under working internal pressure loads. This is of great significance for ensuring the structural safety of subsea pipelines. However, due to the complex marine environment and microbial corrosion, the outer surface of the pipeline often forms pitting corrosion cluster defects with complex shapes. The internal pores are interwoven and the geometric features are highly random. Therefore, it is necessary to accurately assess the residual strength of pipelines containing pitting corrosion cluster defects based on their characteristics.

[0071] In one embodiment, reference is made to Figure 1 , Figure 1 This is a schematic flowchart of an embodiment of the pipeline residual strength assessment method of the present invention, as shown below. Figure 1 As shown, the method for assessing the remaining strength of the pipeline includes:

[0072] Step S10: Based on the pipe dimensions and pitting cluster information, construct a pipe geometric model containing pitting clusters.

[0073] In this embodiment, the pipe dimensions include, but are not limited to, the pipe outer diameter, pipe wall thickness, and pipe length. The pitting cluster information includes, but is not limited to, the pitting cluster size, pitting cluster type, and pitting cluster spacing. Based on the pipe dimensions and pitting cluster information, a pipe geometric model containing pitting clusters is constructed in the same geometric space.

[0074] Step S20: By performing finite element analysis on the geometric model of the pipeline containing pitting clusters and setting the material properties and external loads of the pipeline, a finite element model of the pipeline's remaining strength is constructed.

[0075] In this embodiment, finite element analysis is performed based on the geometric model of the pipeline containing pitting corrosion clusters. The material properties of the pipeline are set, including elastic modulus E, Poisson's ratio v, and yield strength σ. y Ultimate tensile strength σ uts Setting external loads on the pipeline involves applying loads to the pipeline's geometric model to construct a finite element model that yields the pipeline's remaining strength.

[0076] Step S30: Solve the finite element model of the pipeline's remaining strength using the arc length method to obtain the pipeline's remaining strength.

[0077] In this embodiment, based on the material properties and external loads of the pipeline, the stress-strain relationship of the pipeline geometry model is described using the Lamberg-Osgood relation model. According to the stress failure criterion, when the van mitris stress of the element in the corrosion region reaches the ultimate tensile strength σ of the material, the stress-strain relationship is determined. uts At this time, the corresponding internal pressure load is the remaining strength of the pipeline structure. The arc length method is used to solve the finite element model of the pipeline's remaining strength. In this invention, the construction of the finite element model and the solution of the finite element model can be achieved by establishing corresponding scripts using the Python programming language, and executing the corresponding script commands through the large-scale general-purpose finite element engineering simulation software Abaqus.

[0078] Step S40: Construct a new geometric model of the pipeline containing pitting corrosion clusters. Use the new geometric model of the pipeline containing pitting corrosion clusters as the geometric model of the pipeline containing pitting corrosion clusters. Then return to the step of constructing a finite element model of the pipeline's remaining strength by performing finite element subdivision on the geometric model of the pipeline containing pitting corrosion clusters and setting the material properties and external loads of the pipeline.

[0079] In this embodiment, considering the highly random geometric characteristics of pitting cluster defects, a new pipeline geometric model containing pitting clusters is reconstructed based on the pipeline size and pitting cluster information. A finite element model of the pipeline's remaining strength is also reconstructed, and the finite element model of the reconstructed pipeline's remaining strength is solved to obtain a new pipeline remaining strength. Then, the steps S20-S30 are repeated.

[0080] Step S50: When N pipe remaining strengths are obtained, a discrete sequence of pipe remaining strengths is formed from the N pipe remaining strengths, where N is a positive integer greater than or equal to 100.

[0081] In this embodiment, by repeatedly executing steps S20-S30, a new pipeline geometric model containing pitting clusters is constructed based on the pipeline size and pitting cluster information. This new pipeline geometric model containing pitting clusters is used as the geometric model of the pipeline containing pitting clusters. N pipeline residual strength values ​​that we need for statistical analysis and evaluation are obtained. These N pipeline residual strength values ​​are then combined into a discrete sequence of pipeline residual strength.

[0082] Step S60: Calculate the mean, coefficient of variation, and residual strength of the pipeline at preset quantiles for the discrete sequence of residual strength of the pipeline, so as to evaluate the residual strength of the pipeline.

[0083] In this embodiment, the mean, coefficient of variation, and residual strength of the pipeline at preset quantiles are calculated based on the discrete sequence of residual strength of the pipeline. From a statistical perspective, the residual strength of the pipeline containing pitting defects is quantitatively evaluated. The mean reflects the average level of the discrete sequence of residual strength of the pipeline, and the coefficient of variation, i.e., the coefficient of variation, is used to reflect the degree of dispersion of the discrete sequence of residual strength of the pipeline. The preset quantiles can be, for example, 5% and 95% quantiles. This effectively quantifies the impact of the randomness of pitting defects on the residual strength of the pipeline structure, realizes a comprehensive evaluation of the pipeline's load-bearing capacity level, and avoids the conservatism of the evaluation results caused by traditional methods.

[0084] In this embodiment, based on the pipeline size and pitting cluster information, a finite element model of the pipeline's remaining strength can be constructed and solved using the Python programming language and the finite element engineering simulation software Abaqus. This yields a discrete sequence of the pipeline's remaining strength, which further quantifies the stochastic characteristics of pitting cluster defects from a statistical perspective. This enables a comprehensive assessment of the pipeline's load-bearing capacity level and provides a more accurate assessment of the remaining strength of pipelines containing pitting cluster defects. Consequently, it provides a reliable theoretical basis for the formulation of safety design and operation and maintenance strategies for subsea pipelines.

[0085] Further, in one embodiment, the pipe dimensions include the pipe outer diameter, pipe wall thickness, and pipe length; the pitting cluster information includes the pitting cluster size, pitting cluster type, and pitting cluster spacing, as referred to... Figure 2 , Figure 2 for Figure 1 A detailed flowchart of step S10 is shown below. Figure 2 As shown, step S10 includes:

[0086] Step S101: Based on the pipe outer diameter, pipe wall thickness and pipe length, an initial pipe geometric model is constructed;

[0087] Step S102: Based on the size, type, and spacing of the pitting clusters, establish the axial, circumferential, and radial boundary ranges of the pitting clusters.

[0088] Step S103: Within the axial, circumferential and radial boundary ranges of the established pitting cluster, generate multiple spherical geometric models with uniformly distributed radii and spatial positions.

[0089] Step S104: Assemble the generated multiple sphere geometric models with uniformly distributed radii and spatial positions and the initial pipeline geometric model into the same geometric space, and perform Boolean operations to construct a pipeline geometric model containing pitting clusters.

[0090] In this embodiment, generating multiple spherical geometric models with uniformly distributed radii and spatial positions is used to better address the problem of the strong randomness in the geometric characteristics of pitting corrosion cluster defects. (Refer to...) Figure 3 , Figure 3 This is a schematic diagram of the boundary of a spherical geometric model of an embodiment of the pipeline residual strength assessment method of the present invention, as shown below. Figure 3 As shown, the axial, circumferential, and radial boundaries of the pitting clusters are established, forming a closed space that defines the derivation and development of pores within the pitting clusters. Further, based on this closed space, the radius and spatial location of the sphere model are determined. Within the established axial, circumferential, and radial boundaries of the pitting clusters, multiple sphere geometric models with uniformly distributed radii and spatial locations are generated. If the pipeline geometric model containing the pitting clusters cannot be generated normally, steps S102-S104 are repeated until the pipeline geometric model containing the pitting clusters is generated.

[0091] Further, in one embodiment, the pitting cluster size includes the pitting cluster length, pitting cluster depth, and pitting cluster width; the pitting cluster type includes single pitting clusters, circumferentially distributed pitting clusters, and axially distributed pitting clusters; step S102 includes:

[0092] Construct a cylindrical coordinate system (θ, r, z) with the center of the initial pipe geometry model as the origin;

[0093] Based on the pitting cluster length, pitting cluster depth, pitting cluster width, single pitting cluster, circumferentially distributed pitting cluster, axially distributed pitting cluster, and pitting cluster spacing, the axial boundary range of the pitting cluster is established as follows:

[0094] l c,1 ≤z≤l c,2 ,

[0095]

[0096] The circumferential boundary range of the pitting cluster is defined as follows:

[0097] dis c,j ≤r, (j=1,2),

[0098]

[0099] k c,j=tan(θ) c,j ),

[0100]

[0101] The radial boundary range of the pitting cluster is defined as follows:

[0102] (r p -d d )+r≤r≤r p +r,

[0103] Among them, l c,1 and l c,2 The upper and lower boundaries formed by the lengths of the pitting clusters, l d d is the length of the pitting cluster. d w represents the pitting cluster depth. d s is the width of the pitting cluster. c s represents the spacing between pitting clusters in a circumferentially distributed pitting pattern. l dis represents the pitting cluster spacing of axially distributed pitting clusters. c,1 and dis c,2 For the sphere model sp i The distance from the center of the circle to the upper and lower boundaries formed by the width of the pitting cluster, where i is the distance of the sphere model sp. i The subscript θ represents the i-th sphere model. c,1 and θ c,2 r is the central angle corresponding to the upper and lower boundaries formed by the width of the pitting cluster. p Let r be the radius of the complete pipe, and sp be the radius of the sphere model. i The radius.

[0104] In this embodiment, refer to Figure 4 , Figure 4 This is a schematic diagram of pitting cluster types in an embodiment of the pipeline residual strength assessment method of the present invention, as shown below. Figure 4 As shown, the types of pitting clusters mainly include single pitting clusters (a), circumferentially distributed pitting clusters (b), and axially distributed pitting clusters (c). Among them, the pitting cluster defects in the circumferentially distributed pitting clusters (b) and the axially distributed pitting clusters (c) are composed of two single pitting cluster defects. There is an interaction between the pitting cluster defects. By considering the circumferentially distributed pitting clusters (b) and the axially distributed pitting clusters (c), the problem of interaction between multiple pitting cluster defects is solved.

[0105] Furthermore, in one embodiment, the construction of the new pipeline geometry model containing pitting clusters includes:

[0106] Within the axial, circumferential, and radial boundaries of the established pitting cluster, multiple new spherical geometric models with uniformly distributed radii and spatial positions are generated.

[0107] The newly generated sphere geometric model with multiple radii and spatial positions uniformly distributed is assembled with the initial pipeline geometric model into the same geometric space, and Boolean operations are performed to construct a new pipeline geometric model containing pitting clusters.

[0108] In this embodiment, based on the size, type, and spacing of the pitting clusters, multiple new spherical geometric models with uniformly distributed radii and spatial positions are regenerated within the axial, circumferential, and radial boundaries of the established pitting clusters. This is to better address the problem of the strong randomness of the geometric characteristics of pitting cluster defects.

[0109] Furthermore, in one embodiment, reference is made to Figure 5 , Figure 5 for Figure 1 A detailed flowchart of step S20 is shown below. Figure 5 As shown, step S20 includes:

[0110] Step S201: Based on the pipe dimensions, constrain the degrees of freedom in six directions at both ends of the geometric model of the pipe containing pitting clusters.

[0111] Step S202: The pitting cluster region of the geometric model of the pipeline containing pitting clusters is divided into free meshes, and the non-pitting cluster region is divided into structured meshes to obtain multiple model elements.

[0112] Step S203: Based on the material properties of the pipeline and the external load, construct the stress-strain relationship function for each model element using the Lamberg-Osgood relation model;

[0113] Step S204: Based on the stress-strain relationship function of each model element, construct a finite element model of the remaining strength of the pipeline.

[0114] In this embodiment, the basic idea of ​​finite element modeling is to discretize the continuous geometric structure into a finite number of elements, and set a finite number of nodes in each element, thus treating the continuum as a collection of elements connected only at the nodes. Simultaneously, the nodal values ​​of the field function are selected as basic unknowns, and an approximate interpolation function is assumed in each element to represent the distribution law of the field function within the element. Then, a set of finite element equations is established to solve for the nodal unknowns, thereby transforming an infinite-degree-of-freedom problem in a continuous domain into a finite-degree-of-freedom problem in a discrete domain. After modeling steps such as constraining the degrees of freedom, meshing, and setting the material properties and external loads of the pipeline, a finite element model of the pipeline's residual strength is constructed. Fixed constraints are set, constraining all six degrees of freedom in the model's spatial directions, including translational and rotational degrees of freedom in the X, Y, and Z directions. The stress-strain relationship of the pipeline's geometric model is described based on the Lamberg-Osgood relation model. According to the stress failure criterion, when the van der Mises stress of the element within the corrosion region reaches the material's ultimate tensile strength σ...uts When the internal pressure load is at this point, it is the remaining strength of the pipe structure.

[0115] Furthermore, in one embodiment, solving the finite element model of the pipe's remaining strength using the arc-length method includes:

[0116] The arc-length method is used to solve for the residual strength of the pipe in each load step using Formula 1:

[0117] K i μ i =F i ,

[0118] Among them, K i Let μ be the initial tangent stiffness matrix for the i-th load step. i Let F be the initial displacement matrix for the i-th load step. i Let i be the load of the i-th load step. This represents the displacement increment in the j-th iteration within the i-th load step. This represents the increment of the proportional load factor in the j-th iteration within the i-th load step. The residual of the j-th iteration step in the i-th load step. For the node internal load in the j-th iteration step of the i-th load step, Let be the external load of the node in the j-th iteration step of the i-th load step.

[0119] In this embodiment, the arc length method is an iterative control method for nonlinear solutions. It has a high reputation because it can generate changing incremental values ​​when the load and displacement increments are uncertain and can track the structural loading path well. It is one of the most stable, efficient and reliable iterative control methods in structural nonlinear analysis. The finite element engineering simulation software Abaqus also incorporates the arc length method into its calculation module. Therefore, the finite element model of the remaining strength of the pipeline can be solved conveniently by using the arc length method in the finite element engineering simulation software Abaqus.

[0120] Further, in one embodiment, the calculation of the mean, coefficient of variation, and residual pipeline strength at preset quantiles of the discrete sequence of residual pipeline strength includes:

[0121] Calculate the mean and coefficient of variation of the discrete sequence of the remaining strength of the pipeline;

[0122] The kernel density estimation method is used to fit the probability distribution of the discrete sequence of pipeline residual strength. The pipeline residual strength at the preset quantile is calculated using Formula 2, which is:

[0123]

[0124] Where f(x) is the probability density function obtained by fitting the probability distribution of the discrete sequence of the pipeline's remaining strength using the kernel density estimation method, x i Let x be the value of the i-th experimental point of random variable x, N be the total number of experimental points in the random variable sequence, h be the smoothing parameter, K(u) be the kernel function, and u be the independent variable of the kernel function.

[0125] In this embodiment, typical working conditions (such as the working conditions corresponding to the maximum and minimum values) in the discrete sequence of the pipeline's remaining strength can be selected to draw their geometric characteristics and stress distribution cloud maps, explore the connection mechanism between the geometric characteristics of pitting clusters and the development law of failure paths, and reveal the failure behavior of pipelines with pitting cluster defects.

[0126] Furthermore, since the pipeline residual strength assessment method proposed in this invention is based on nonlinear finite element analysis, this invention further validates it.

[0127] (I) Verification of Nonlinear Finite Element Analysis Script

[0128] Foreign scholars have conducted numerical analysis on the residual strength of pipes containing pitting defects of different sizes, with an outer diameter of D. p =762mm, pipe wall thickness is t p =17.5mm, the pipe steel material is API5LX65, and its elastic modulus is E s =210GPa, Poisson's ratio is ν s =0.3, the external dimension of the pitting cluster defect is length l d =100-300mm, width w d =50-200mm, depth d d=4.4-13.1mm. Based on the nonlinear finite element analysis script constructed in this invention, the above numerical analysis was reproduced. The comparison results of the residual strength of the two are shown in Table 1. Table 1 is a comparison table of the residual strength analysis values ​​of foreign scholars and the evaluation values ​​of this invention for pipelines with pitting cluster defects of different sizes. According to Table 1, it can be seen that the analysis results of the two are in good agreement, with the maximum, minimum and average absolute relative errors being 4.33%, 1.07% and 2.32%, respectively, which meet the accuracy requirements in engineering design. In addition, since the geometric characteristics of pitting cluster defects are obviously random, the geometric characteristics of pitting cluster defects in this invention are all randomly generated. Therefore, under the same working condition, there will inevitably be differences between the geometric characteristics of pitting cluster defects in the script and those in the literature, which will affect the structural failure behavior and residual strength, and ultimately lead to a certain degree of deviation in the analysis results of the two. This phenomenon is consistent with the actual situation. The above comparative analysis shows that the nonlinear finite element analysis script constructed in this invention can describe the failure behavior of pipelines with pitting cluster defects of different corrosion degrees well and reasonably estimate their residual strength.

[0129] Table 1.

[0130]

[0131] Where, p b,ref p represents the residual intensity obtained from the analysis in the literature. b,scr The residual strength obtained from the nonlinear finite element analysis script constructed in this invention is ARE, where ARE is the absolute relative error, and ARE = ​​|(p b,scr -p b,ref ) / p b,ref |

[0132] (II) Verification of the computational analysis

[0133] Taking a pipeline in a certain project as the research object, its residual strength was evaluated to verify the applicability of the method proposed in this invention. The pipeline was made of API 5L X80 steel, and its mechanical properties and geometric dimensions are shown in Table 2. Table 2 is a table of geometric dimensions and material mechanical properties of the pipeline in a certain project. Three sets of working conditions were set in the analysis to explore the failure characteristics of the structure under different pitting cluster types. The specific types, external dimensions and spacing are shown in Table 3. Table 3 is a table of pitting cluster types and sizes corresponding to the three working conditions.

[0134] Table 2.

[0135] D(mm) t(mm) <![CDATA[E s (GPa)]]> <![CDATA[ν s ]]> <![CDATA[σ y (MPa)]]> <![CDATA[σ ts (MPa)]]> 458.1 8.1 210 0.3 534.1 718.2

[0136] Table 3.

[0137] Operating conditions Defect types <![CDATA[l d (mm)]]> <![CDATA[w d (mm)]]> <![CDATA[d d (mm)]]> <![CDATA[s c (mm)]]> <![CDATA[s l (mm)]]> 1 Single-point erosion cluster 40.5 50 6.48 / / 2 Circumferentially distributed pitting clusters 40.5 50 6.48 7.2 / 3 Axial distribution pitting clusters 40.5 50 6.48 / 12.18

[0138] Based on the method proposed in this invention, the above-mentioned operating conditions of the target pipeline are analyzed. Simultaneously, as a comparative analysis, a traditional method is also used to analyze the above-mentioned operating conditions, which simplifies pitting cluster defects into rectangular defects to estimate the remaining strength of the pipeline structure. The results are expressed as p. b,rec Indicates, refer to Figure 6 , Figure 6 This is a schematic diagram showing the probability density and cumulative density distribution of the discrete sequence of the residual strength of the pipeline under different working conditions. Figure 6 In (a), a single-point etch cluster defect is shown. Figure 6 (b) shows a circumferentially distributed pitting cluster defect. Figure 6 (c) represents axially distributed pitting defects, such as... Figure 6 As shown:

[0139] (1) Every value in the discrete sequence of residual intensity is greater than the analysis result p in the traditional method. b,rec The mean μ of the residual intensity discrete sequence p This can characterize the load-bearing capacity level of the pipeline structure. Due to the influence of the interaction between defects, the average residual strength of the pipeline in working conditions 1-3 decreases sequentially. Among them, for pipelines containing axially distributed pitting defects, the average value decreases by approximately Δμ compared to the average value of pipelines containing single pitting defects. p =2.3MPa, this is because the interaction between axially distributed defects is more significant, a point cited in many related studies. Under the three defect types described in working conditions 1-3, the differences between the mean residual strength of the corresponding pipeline and the traditional method are Δp, respectively. b,μ =0.9MPa, 1.8MPa, 3.4MPa. The above analysis shows that the traditional method does not consider the contribution of the material within the pitting cluster defects to the bearing capacity, and the evaluation results are conservative. Moreover, this conservatism will gradually increase with the introduction of interaction factors between defects, causing unnecessary safety and operation and maintenance investment in the project.

[0140] (2) Due to the randomness of the geometric characteristics of pitting cluster defects, their residual strength exhibits considerable variability. Under the condition of a single pitting cluster defect, the range of its residual strength is within p b = Between 20 and 21.5 MPa, the corresponding coefficient of variation is cov p =0.0076, for interacting pitting clusters, the variability of the pipe's residual strength is further enhanced. Under the condition of axially distributed pitting clusters, its residual strength ranges from p b = Between 17.5 and 19.5 MPa, the corresponding coefficient of variation is cov p =0.018. To explore the intrinsic relationship between the geometric characteristics of pitting clusters and their failure behavior, a single pitting cluster defect is used as an example, referring to... Figure 7 , Figure 7This is a schematic diagram of a typical example of pipeline failure containing a single point corrosion cluster defect, such as... Figure 7 As shown, Figure 7 (a) shows the van der Mises stress contour plot, representing an example of minimum residual strength. Figure 7 (b) is the vertical coordinate contour map, showing the instance with the minimum residual intensity. Figure 7 (c) shows the van der Mises stress contour plot, representing the instance with the maximum residual strength. Figure 7 (d) is the vertical coordinate contour map, showing the instance with the maximum residual intensity. Figure 7 The local geometric features and failure paths of pitting clusters for the two instances with the minimum and maximum residual strength are given. Figure 7 (a)-(b) are examples with the minimum residual strength. It can be seen that the corrosion degree of the material in the pitting cluster defect is relatively uniform, and the area with the weakest residual wall thickness is located on the same axial straight line. Therefore, the material burst failure path tends to develop along this straight line. This failure path is more consistent with the failure path of rectangular defects. Therefore, the residual strength of this example is pb = 20.1 MPa, which is very close to the result in the traditional evaluation method. Figure 7 Examples (c)-(d) represent the cases with the highest residual strength. Within the pitting cluster defects, the residual wall thickness distribution is uneven. The region with the smallest residual wall thickness is located at the edge of the YOZ plane. Simultaneously, there is a significant amount of material between these regions, requiring a larger internal pressure load to trigger burst failure. This geometric feature causes the failure path to deviate from this region to avoid the obstruction of the thicker material. Therefore, the failure path initially develops along the weakest region from A to B, then deflects, developing along the region with the second smallest residual wall thickness to C. This path deflection increases the total length of the failure path, and the average residual wall thickness along this path is larger, allowing more material to participate in resisting the circumferential tensile force induced by the internal pressure load. Therefore, the pipe in this example has a relatively high residual strength, p. b =21.5MPa. The above analysis shows that the burst failure of the structure tends to develop along the weakest area of ​​the material, and the failure path depends on the geometric characteristics of the pitting clusters. However, the traditional method does not consider the influence of the randomness of the geometric characteristics of the pitting cluster defects on the residual strength, and the obtained residual strength is a single definite value, which is difficult to comprehensively describe the load-bearing capacity level of the structure.

[0141] (3) Kernel density estimation can better describe the cumulative distribution characteristics of the discrete sequence of residual strength of the pipeline. Based on kernel density estimation, the residual strength value p corresponding to its quantile can be obtained. b,5％ and p b,95％ The results are shown in Table 4, which lists the statistical values ​​of the remaining strength of the pipeline under different working conditions. The quantile values ​​mentioned above have clear statistical significance and can constitute a 90% confidence interval for the remaining strength [p]. b,5％ p b,95％ ], combined with the mean μ characterizing the bearing capacity levelp This can provide a comprehensive description of the residual strength of structures with discrete characteristics. Based on the above statistical values, further research on pipeline failure probability risk assessment can be carried out to obtain the failure probability confidence interval and quantify the impact range of pitting cluster randomness on structural residual strength and failure risk.

[0142] Table 4.

[0143] Operating conditions Defect types <![CDATA[p b,5％ (MPa)]]> <![CDATA[μ p (MPa)]]> <![CDATA[p b,95％ (MPa)]]> 1 Single-point erosion cluster 20.63 20.87 21.07 2 Circumferentially distributed pitting clusters 19.94 20.38 20.81 3 Axial distribution pitting clusters 17.81 18.49 19

[0144] Secondly, embodiments of the present invention also provide a device for assessing the remaining strength of a pipeline.

[0145] Reference Figure 8 , Figure 8 This is a schematic diagram of the functional modules of an embodiment of the pipeline residual strength assessment device of the present invention.

[0146] In this embodiment, the pipeline residual strength assessment device includes:

[0147] The first construction module 10 is used to construct a pipeline geometric model containing pitting clusters based on the pipeline size and pitting cluster information;

[0148] The second construction module 20 is used to construct a finite element model of the remaining strength of the pipeline by performing finite element meshing on the geometric model of the pipeline containing pitting clusters and setting the material properties and external loads of the pipeline.

[0149] The solver module 30 is used to solve the finite element model of the pipe's remaining strength using the arc length method to obtain the pipe's remaining strength.

[0150] The third construction module 40 is used to construct a new pipeline geometric model containing pitting corrosion clusters, use the new pipeline geometric model containing pitting corrosion clusters as the geometric model of the pipeline containing pitting corrosion clusters, and return to the step of constructing a finite element model of the pipeline's remaining strength by performing finite element subdivision on the geometric model of the pipeline containing pitting corrosion clusters and setting the material properties and external loads of the pipeline.

[0151] The component module 50 is used to form a discrete sequence of pipe remaining strengths when N pipe remaining strengths are obtained, where N is a positive integer greater than or equal to 100;

[0152] The calculation module 60 is used to calculate the mean, coefficient of variation, and residual strength of the pipeline at preset quantiles of the discrete sequence of residual strength of the pipeline, so as to evaluate the residual strength of the pipeline.

[0153] Further, in one embodiment, the pipe dimensions include the pipe outer diameter, pipe wall thickness, and pipe length; the pitting cluster information includes the pitting cluster size, pitting cluster type, and pitting cluster spacing; the first construction module 10 includes:

[0154] The first building unit is used to construct the initial pipe geometry model based on the pipe's outer diameter, pipe wall thickness, and pipe length.

[0155] Establishment unit, used to establish the axial, circumferential and radial boundary range of pitting clusters based on the size, type and spacing of the pitting clusters;

[0156] The generation unit is used to generate multiple spherical geometric models with uniformly distributed radii and spatial positions within the axial, circumferential, and radial boundary ranges of the established pitting cluster.

[0157] The second building unit is used to assemble multiple sphere geometric models with uniformly distributed radii and spatial positions, along with the initial pipeline geometric model, into the same geometric space, and perform Boolean operations to construct a pipeline geometric model containing pitting clusters.

[0158] Further, in one embodiment, the pitting cluster size includes the pitting cluster length, pitting cluster depth, and pitting cluster width; the pitting cluster type includes single pitting clusters, circumferentially distributed pitting clusters, and axially distributed pitting clusters; and the establishment unit is used for:

[0159] Construct a cylindrical coordinate system (θ, r, z) with the center of the initial pipe geometry model as the origin;

[0160] Based on the pitting cluster length, pitting cluster depth, pitting cluster width, single pitting cluster, circumferentially distributed pitting cluster, axially distributed pitting cluster, and pitting cluster spacing, the axial boundary range of the pitting cluster is established as follows:

[0161] l c,1 ≤z≤l c,2 ,

[0162]

[0163] The circumferential boundary range of the pitting cluster is defined as follows:

[0164] dis c,j ≤r, (j=1,2),

[0165]

[0166] k c,j =tan(θ) c,j ),

[0167]

[0168] The radial boundary range of the pitting cluster is defined as follows:

[0169] (r p -d d )+r≤r≤r p +r,

[0170] Among them, l c,1 and l c,2 The upper and lower boundaries formed by the lengths of the pitting clusters, l d d is the length of the pitting cluster. d w represents the pitting cluster depth. d s is the width of the pitting cluster. c s represents the spacing between pitting clusters in a circumferentially distributed pitting pattern. l dis represents the pitting cluster spacing of axially distributed pitting clusters. c,1 and dis c,2 For the sphere model sp i The distance from the center of the circle to the upper and lower boundaries formed by the width of the pitting cluster, where i is the distance of the sphere model sp. i The subscript θ represents the i-th sphere model. c,1 and θ c,2 r is the central angle corresponding to the upper and lower boundaries formed by the width of the pitting cluster. p Let r be the radius of the complete pipe, and sp be the radius of the sphere model. i The radius.

[0171] Furthermore, in one embodiment, the third building module 40 is used for:

[0172] Within the axial, circumferential, and radial boundaries of the established pitting cluster, multiple new spherical geometric models with uniformly distributed radii and spatial positions are generated.

[0173] The newly generated sphere geometric model with multiple radii and spatial positions uniformly distributed is assembled with the initial pipeline geometric model into the same geometric space, and Boolean operations are performed to construct a new pipeline geometric model containing pitting clusters.

[0174] Furthermore, in one embodiment, the second building module 20 is used for:

[0175] Based on the pipe dimensions, the degrees of freedom in six directions at both ends of the geometric model of the pipe containing pitting clusters are constrained;

[0176] For the geometric model of the pipeline containing pitting corrosion clusters, the pitting corrosion cluster region is divided into free meshes, and the non-pitting corrosion cluster region is divided into structured meshes, resulting in multiple model elements;

[0177] Based on the material properties of the pipeline and the external load, the stress-strain relationship function of each model element is constructed using the Lamberg-Osgood relation model;

[0178] A finite element model of the pipeline's remaining strength is constructed based on the stress-strain relationship function of each model element.

[0179] Furthermore, in one embodiment, the solving module 30 is used for:

[0180] The arc-length method is used to solve for the residual strength of the pipe in each load step using Formula 1:

[0181] K i μ i =F i ,

[0182] Among them, K i Let μ be the initial tangent stiffness matrix for the i-th load step. i Let F be the initial displacement matrix for the i-th load step. i Let i be the load of the i-th load step. This represents the displacement increment in the j-th iteration within the i-th load step. This represents the increment of the proportional load factor in the j-th iteration within the i-th load step. The residual of the j-th iteration step in the i-th load step. For the node internal load in the j-th iteration step of the i-th load step, Let be the external load of the node in the j-th iteration step of the i-th load step.

[0183] Furthermore, in one embodiment, the calculation module 60 is used for:

[0184] Calculate the mean and coefficient of variation of the discrete sequence of the remaining strength of the pipeline;

[0185] The kernel density estimation method is used to fit the probability distribution of the discrete sequence of pipeline residual strength. The pipeline residual strength at the preset quantile is calculated using Formula 2, which is:

[0186]

[0187] Where f(x) is the probability density function obtained by fitting the probability distribution of the discrete sequence of the pipeline's remaining strength using the kernel density estimation method, x i Let x be the value of the i-th experimental point of random variable x, N be the total number of experimental points in the random variable sequence, h be the smoothing parameter, K(u) be the kernel function, and u be the independent variable of the kernel function.

[0188] The functions of each module in the above-mentioned pipeline residual strength assessment device correspond to the steps in the above-mentioned pipeline residual strength assessment method embodiment, and their functions and implementation processes will not be described in detail here.

[0189] Thirdly, embodiments of the present invention provide a pipeline residual strength assessment device, which may be a personal computer (PC), laptop computer, server or other device with data processing capabilities.

[0190] Reference Figure 9 , Figure 9 This is a schematic diagram of the hardware structure of an embodiment of the pipeline residual strength assessment device of the present invention. In this embodiment, the pipeline residual strength assessment device may include a processor 1001 (e.g., a Central Processing Unit, CPU), a communication bus 1002, a user interface 1003, a network interface 1004, and a memory 1005. The communication bus 1002 is used to realize communication between these components; the user interface 1003 may include a display screen or an input unit such as a keyboard; the network interface 1004 may optionally include a standard wired interface or a wireless interface (e.g., Wireless Fidelity, Wi-Fi interface); the memory 1005 may be high-speed random access memory (RAM) or stable memory (non-volatile memory), such as a disk storage device; the memory 1005 may also optionally be a storage device independent of the aforementioned processor 1001. Those skilled in the art will understand that… Figure 9 The hardware structure shown does not constitute a limitation of the invention and may include more or fewer components than shown, or combine certain components, or have different component arrangements.

[0191] Continue to refer to Figure 9 , Figure 9 The memory 1005, which serves as a computer storage medium, may include an operating system, a network communication module, a user interface module, and a pipeline remaining strength assessment program. The processor 1001 can call the pipeline remaining strength assessment program stored in the memory 1005 and execute the pipeline remaining strength assessment method provided in this embodiment of the invention.

[0192] Fourthly, embodiments of the present invention also provide a readable storage medium.

[0193] The present invention stores a pipeline remaining strength assessment program on a readable storage medium, wherein when the pipeline remaining strength assessment program is executed by a processor, the steps of the pipeline remaining strength assessment method as described above are implemented.

[0194] The method implemented when the pipeline residual strength assessment procedure is executed can be referred to in various embodiments of the pipeline residual strength assessment method of the present invention, and will not be repeated here.

[0195] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or system. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or system that includes that element.

[0196] The sequence numbers of the above embodiments of the present invention are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0197] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) as described above, and includes several instructions to cause a terminal device to execute the methods described in the various embodiments of the present invention.

[0198] The above are merely preferred embodiments of the present invention and do not limit the scope of the patent. Any equivalent structural or procedural transformations made based on the description and drawings of the present invention, or direct or indirect applications in other related technical fields, are similarly included within the scope of patent protection of the present invention.

Claims

1. A method for assessing the residual strength of a pipeline, characterized in that, The method for assessing the remaining strength of the pipeline includes: Based on the pipe dimensions and pitting cluster information, a pipe geometric model containing pitting clusters is constructed. By performing finite element analysis on the geometric model of the pipeline containing pitting corrosion clusters, and setting the material properties and external loads of the pipeline, a finite element model of the pipeline's remaining strength is constructed. The finite element model of the pipeline's remaining strength was solved using the arc length method to obtain the pipeline's remaining strength. A new geometric model of the pipeline containing pitting corrosion clusters is constructed. The new geometric model of the pipeline containing pitting corrosion clusters is used as the geometric model of the pipeline containing pitting corrosion clusters. The steps described above are returned: by performing finite element meshing on the geometric model of the pipeline containing pitting corrosion clusters, and setting the material properties and external loads of the pipeline, a finite element model of the pipeline's remaining strength is constructed. When N pipe remaining strengths are obtained, the N pipe remaining strengths are used to form a discrete sequence of pipe remaining strengths, where N is a positive integer greater than or equal to 100; Calculate the mean, coefficient of variation, and residual strength of the pipeline at preset quantiles for the discrete sequence of residual strength of the pipeline, so as to evaluate the residual strength of the pipeline. The pipe dimensions include the pipe outer diameter, pipe wall thickness, and pipe length. The pitting cluster information includes the pitting cluster size, pitting cluster type, and pitting cluster spacing. The process of constructing a pipe geometric model containing pitting clusters based on the pipe dimensions and pitting cluster information includes: An initial pipe geometric model is constructed based on the pipe's outer diameter, wall thickness, and length. Based on the size, type, and spacing of the pitting clusters, establish the axial, circumferential, and radial boundary ranges of the pitting clusters. Within the axial, circumferential, and radial boundaries of the established pitting cluster, multiple spherical geometric models with uniformly distributed radii and spatial positions are generated. The generated spherical geometric models with uniformly distributed radii and spatial positions are assembled with the initial pipe geometric model into the same geometric space, and Boolean operations are performed to construct a pipe geometric model containing pitting clusters.

2. The pipeline residual strength assessment method as described in claim 1, characterized in that, The dimensions of the pitting cluster include the pitting cluster length, pitting cluster depth, and pitting cluster width. The types of pitting clusters include single pitting clusters, circumferentially distributed pitting clusters, and axially distributed pitting clusters. Establishing the axial, circumferential, and radial boundary ranges of the pitting clusters based on the pitting cluster dimensions, pitting cluster types, and pitting cluster spacing includes: Construct a cylindrical coordinate system (θ, r, z) with the center of the initial pipe geometry model as the origin; Based on the pitting cluster length, pitting cluster depth, pitting cluster width, single pitting cluster, circumferentially distributed pitting cluster, axially distributed pitting cluster, and pitting cluster spacing, the axial boundary range of the pitting cluster is established as follows: ， ， The circumferential boundary range of the pitting cluster is defined as follows: ， ， ， ， The radial boundary range of the pitting cluster is defined as follows: ， Among them, l c,1 and l c,2 The upper and lower boundaries formed by the lengths of the pitting clusters, l d d is the length of the pitting cluster. d w represents the pitting cluster depth. d s is the width of the pitting cluster. c s represents the spacing between pitting clusters in a circumferentially distributed pitting pattern. l dis represents the pitting cluster spacing of axially distributed pitting clusters. c,1 and dis c,2 For the sphere model sp i The distance from the center of the circle to the upper and lower boundaries formed by the width of the pitting cluster, where i is the distance of the sphere model sp. i The subscript θ represents the i-th sphere model. c,1 and θ c,2 r is the central angle corresponding to the upper and lower boundaries formed by the width of the pitting cluster. p Let r be the radius of the complete pipe, and sp be the radius of the sphere model. i The radius.

3. The pipeline residual strength assessment method as described in claim 1, characterized in that, The construction of the new pipeline geometry model containing pitting clusters includes: Within the axial, circumferential, and radial boundaries of the established pitting cluster, multiple new spherical geometric models with uniformly distributed radii and spatial positions are generated. The newly generated sphere geometric model with multiple radii and spatial positions uniformly distributed is assembled with the initial pipeline geometric model into the same geometric space, and Boolean operations are performed to construct a new pipeline geometric model containing pitting clusters.

4. The pipeline residual strength assessment method as described in claim 1, characterized in that, The process of constructing a finite element model of the pipeline with pitting corrosion clusters by performing finite element analysis on the geometric model and setting the material properties and external loads of the pipeline includes: Based on the pipe dimensions, the degrees of freedom in six directions at both ends of the geometric model of the pipe containing pitting clusters are constrained; For the geometric model of the pipeline containing pitting corrosion clusters, the pitting corrosion cluster region is divided into free meshes, and the non-pitting corrosion cluster region is divided into structured meshes, resulting in multiple model elements; Based on the material properties of the pipeline and the external load, the stress-strain relationship function of each model element is constructed using the Lamberg-Osgood relation model; A finite element model of the pipeline's remaining strength is constructed based on the stress-strain relationship function of each model element.

5. The pipeline residual strength assessment method as described in claim 1, characterized in that, The method of solving the finite element model of the pipeline's remaining strength using the arc length method includes: The arc-length method is used to solve for the residual strength of the pipe in each load step using Formula 1: ， ， ， Among them, K i Let μ be the initial tangent stiffness matrix for the i-th load step. i Let F be the initial displacement matrix for the i-th load step. i Let i be the load of the i-th load step. This represents the displacement increment in the j-th iteration within the i-th load step. This represents the increment of the proportional load factor in the j-th iteration within the i-th load step. The residual of the j-th iteration step in the i-th load step. For the node internal load in the j-th iteration step of the i-th load step, Let be the external load of the node in the j-th iteration step of the i-th load step.

6. The pipeline residual strength assessment method as described in claim 1, characterized in that, The calculation of the pipeline residual strength discrete sequence, including the mean, coefficient of variation, and pipeline residual strength at preset quantiles, includes: Calculate the mean and coefficient of variation of the discrete sequence of the remaining strength of the pipeline; The kernel density estimation method is used to fit the probability distribution of the discrete sequence of pipeline residual strength to obtain a probability density function. Based on the probability density function, the pipeline residual strength at preset quantiles is further calculated. The probability density function is as follows: ， ， Where f(x) is the probability density function obtained by fitting the probability distribution of the discrete sequence of the pipeline's remaining strength using the kernel density estimation method, x i Let x be the value of the i-th experimental point of random variable x, N be the total number of experimental points in the random variable sequence, h be the smoothing parameter, K(u) be the kernel function, and u be the independent variable of the kernel function.

7. A device for assessing the residual strength of a pipeline, characterized in that, The pipeline residual strength assessment device includes: The first construction module is used to construct a pipeline geometric model containing pitting clusters based on the pipeline size and pitting cluster information; The second construction module is used to construct a finite element model of the pipe's remaining strength by performing finite element meshing on the geometric model of the pipe containing pitting clusters and setting the pipe's material properties and external loads. The solver module is used to solve the finite element model of the pipe's remaining strength using the arc length method, and obtain the pipe's remaining strength. The third construction module is used to construct a new pipeline geometric model containing pitting corrosion clusters, use the new pipeline geometric model containing pitting corrosion clusters as the geometric model of the pipeline containing pitting corrosion clusters, and return the step of constructing a finite element model of the pipeline's remaining strength by performing finite element meshing on the geometric model of the pipeline containing pitting corrosion clusters and setting the material properties and external loads of the pipeline. The component module is used to form a discrete sequence of pipe remaining strengths when N pipe remaining strengths are obtained, where N is a positive integer greater than or equal to 100; The calculation module is used to calculate the mean, coefficient of variation, and residual strength of the pipeline at preset quantiles of the discrete sequence of residual strength, so as to evaluate the residual strength of the pipeline. The pipe dimensions include the pipe outer diameter, pipe wall thickness, and pipe length; the pitting cluster information includes the pitting cluster size, pitting cluster type, and pitting cluster spacing; the first construction module includes: The first building unit is used to construct the initial pipe geometry model based on the pipe's outer diameter, pipe wall thickness, and pipe length. Establishment unit, used to establish the axial, circumferential and radial boundary range of pitting clusters based on the size, type and spacing of the pitting clusters; The generation unit is used to generate multiple spherical geometric models with uniformly distributed radii and spatial positions within the axial, circumferential, and radial boundary ranges of the established pitting cluster. The second building unit is used to assemble multiple sphere geometric models with uniformly distributed radii and spatial positions, along with the initial pipeline geometric model, into the same geometric space, and perform Boolean operations to construct a pipeline geometric model containing pitting clusters.

8. A device for assessing the residual strength of a pipeline, characterized in that, The pipeline remaining strength assessment device includes a processor, a memory, and a pipeline remaining strength assessment program stored in the memory and executable by the processor, wherein when the pipeline remaining strength assessment program is executed by the processor, it implements the steps of the pipeline remaining strength assessment method as described in any one of claims 1 to 6.

9. A readable storage medium, characterized in that, The readable storage medium stores a pipeline remaining strength assessment program, wherein when the pipeline remaining strength assessment program is executed by a processor, it implements the steps of the pipeline remaining strength assessment method as described in any one of claims 1 to 6.

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