Method for analyzing reliability of impact bearing capacity of submarine pipeline under multi-source random inducement coupling

Abstract

The invention discloses a submarine pipeline impact bearing capacity reliability analysis method under multi-source random inducement coupling, and relates to the technical field of submarine pipeline systems. The method for analyzing the reliability of the impact bearing capacity of the submarine pipeline under multi-source random inducement coupling mainly comprises the following steps: constructing a non-stationary random field-large deformation finite element analysis coupling numerical model according to a seabed soil body geometric model, a falling object geometric model and a pipeline geometric model, and solving the non-stationary random field-large deformation finite element analysis coupling numerical model to obtain an impact process; utilizing a Monte Carlo simulation method and a rigid-plastic shell-beam collaborative theory model to obtain probability statistical characteristics of energy absorbed by the soil body; and obtaining the failure probability of the corrected structure by using a rigid-plastic shell-beam collaborative theory model and a Monte Carlo simulation method. By implementing the reliability analysis method for the impact bearing capacity of the submarine pipeline under multi-source random inducement coupling, provided by the invention, the impact bearing capacity of the submarine pipeline can be efficiently and reliably evaluated.

Description

Technical Field

[0001] The present invention relates to the technical field of submarine pipeline systems, and more particularly to a reliability analysis method for impact bearing capacity of submarine pipelines under multi-source random inducement coupling. Background Art

[0002] Submarine pipelines are crucial for connecting submarine facilities with onshore terminals and transporting oil and gas resources. They offer numerous advantages, including efficiency, economy, and cleanliness, and are therefore widely used in the offshore oil and gas development industry, often considered its "lifeline." Pipeline safety in service is crucial. Statistics indicate that impact loads caused by third-party activities are the primary cause of pipeline failure. Pipeline protection requires trenching and burial depth, with pipeline burial depth being a key factor influencing the effectiveness of this protection. However, due to the complex interplay of geological evolution, the marine environment, and physical and chemical factors, marine soil strength exhibits significant spatial variability. Under these conditions, the response characteristics of soil, pipelines, and pipe-soil interactions under transient impact loads differ significantly from those under ideal homogeneous soil conditions. The failure mechanism of pipeline structures is complex, and their failure behavior exhibits strong nonlinearity and high uncertainty. Furthermore, actual engineering projects are subject to numerous inherent uncertainties. For example, the energy of impact loads can vary depending on the type and mass of objects dropped during platform hoisting operations. The dimensions and mechanical properties of pipeline materials can fluctuate due to errors in processing, manufacturing, and construction. These uncertainties further exacerbate the randomness of the mechanical system of the object-soil-pipeline interaction, making it more difficult to estimate the extent of pipeline impact damage. Currently, there are no effective methods for estimating pipeline damage. The quantitative relationship between pipeline burial depth and structural damage is unknown, and burial depth is primarily determined based on engineering experience, lacking a theoretical basis. This presents a significant risk to pipeline service.

[0003] The spatial variability of soil strength significantly affects the behavioral characteristics of soil, structure, and their interactions under impact loads, resulting in obvious nonlinear and uncertain structural responses. The failure mechanism is complex, and the pipeline damage is more severe than that under homogeneous soil conditions. At the same time, the inherent random factors of the project will further increase the risk of structural failure. Accurately assessing the bearing capacity of the structure under impact loads requires full consideration of the influence of the above two factors. To meet the above requirements, it is necessary to rely on the construction of a complex random process-mechanical analysis coupling system and a large number of sampling calculations, which places extremely high demands on model construction theory and methods and computing resources. At present, there is no effective impact bearing capacity assessment method.

[0004] The above content is only used to assist in understanding the technical solution of the present invention and does not constitute an admission that the above content is prior art. Summary of the Invention

[0005] The purpose of the present invention is to provide a reliability analysis method for the impact bearing capacity of submarine pipelines under multi-source random inducement coupling, which can realize efficient and reliable evaluation of the impact bearing capacity of submarine pipelines.

[0006] The present invention provides a reliability analysis method for the impact bearing capacity of a submarine pipeline under multi-source random inducement coupling, comprising the following steps: S1: constructing a non-stationary random field-large deformation finite element analysis coupling numerical model based on a seabed soil geometric model, a falling object geometric model, and a pipeline geometric model, and solving the coupled numerical model to obtain an impact process; S2: obtaining a probability statistical characteristic of soil energy absorption using a Monte Carlo simulation method and a rigid-plastic shell-beam collaborative theoretical model based on the non-stationary random field-large deformation finite element analysis coupling numerical model; S3: obtaining a corrected structural failure probability based on the probability statistical characteristic of soil energy absorption using a rigid-plastic shell-beam collaborative theoretical model and a Monte Carlo simulation method.

[0007] The present invention also provides a computer program product, comprising a computer program, which, when executed by a processor, implements the steps of the above-mentioned method for analyzing the impact bearing capacity reliability of submarine pipelines under multi-source random inducement coupling.

[0008] The implementation of the reliability analysis method for submarine pipeline impact bearing capacity under multi-source random inducement coupling provided by the present invention has the following beneficial effects: This paper develops a non-stationary random field-large deformation finite element analysis (NSRF-LDFEA) coupled numerical model: Based on the subroutine-field variable collaborative mapping algorithm, a read-update-store information transfer mechanism is used to transfer the non-stationary lognormal random field describing the spatial variability of soil strength to the soil unit integration points in the finite element analysis model. The model captures the evolution of soil strength during the flow of soil materials in real time, realizes the dynamic correlation between the two, and completes the coupling, numerical discretization, and solution of the control equations of the random process system and the mechanical analysis system. This model can reasonably describe the behavioral characteristics of soil, pipelines, and their interactions under the conditions of spatial variability of soil strength, and effectively estimate the degree of damage to pipelines under impact loads. This paper establishes an equivalent energy principle: using a rigid-plastic shell-beam synergistic theoretical model to estimate the impact energy required for pipeline damage, and then derive the impact energy absorbed by the soil layer surrounding the pipeline. The statistical characteristics of structural damage under the condition of spatial variability of soil strength are equivalently converted into the statistical characteristics of energy absorbed by the soil around the pipeline. This effectively characterizes the effect of spatial variability of soil strength on structural response and decouples it from the mechanical analysis system. This lays the foundation for constructing a reliability analysis model that comprehensively considers spatial variability of soil strength and inherent engineering uncertainties. The present invention constructs a reliability analysis model for the impact bearing capacity of pipelines under the coupling of multi-source random inducements: combining the rigid-plastic shell-beam synergistic theoretical model and the probabilistic statistical characteristics of soil energy absorption with inherent engineering uncertainty factors, a pipeline impact bearing capacity assessment model based on reliability theory is constructed, which realizes the coupling of the spatial variability of soil strength and the effects of inherent engineering uncertainty factors on structural response in the probability space, effectively captures the evolution law of structural failure risk under highly nonlinear and strong random conditions, and ensures a reliable assessment of structural bearing capacity.

[0009] The present invention derives the equivalent energy principle based on the random finite element analysis theory to describe the structural failure behavior and the probabilistic characteristics of the soil energy absorption effect under the condition of spatial variability of soil strength; based on the structural reliability theory and the rigid-plastic shell-beam synergistic theoretical model, the spatial variability of soil strength and the influence of inherent uncertainties in engineering on the structural response characteristics are superimposed in the probabilistic characteristic space, thereby achieving an efficient and reasonable description of the failure characteristics and damage degree of the pipeline structure under the coupling of multi-source random inducements, and clarifying the quantitative relationship between soil strength-soil burial depth-pipeline failure probability.

[0010] This paper combines the theories and methods of probability analysis and numerical analysis to construct a method for assessing the bearing capacity of structures under impact loads. By constructing an NSRF-LDFEA coupled numerical model and the principle of equivalent energy, it accurately describes the structural response under conditions of spatial variability in soil strength and decouples it from the mechanical analysis system. Furthermore, by combining reliability theory with the rigid-plastic shell-beam synergistic theoretical model, the effects of spatial variability in soil strength and inherent engineering uncertainty on the structure are coupled in probability space, thereby rationally describing the evolution of structural failure risk under the combined effects of the two and achieving an efficient and reliable assessment of its bearing capacity. Compared with traditional methods, this method has significant advantages in considering the dimensionality of random factors and the efficiency of computational analysis. It provides theoretical guidance and technical reserves for determining pipeline burial depth in engineering safety design, ensuring the service safety of major infrastructure and the stable development of offshore oil and gas resources. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] The present invention will be further described below with reference to the accompanying drawings and embodiments, in which: Figure 1 This is a flow chart of the reliability analysis method for the impact bearing capacity of submarine pipelines under multi-source random inducement coupling provided by the present invention; Figure 2 Schematic diagram of the comparison between the NSRF-LDFEA coupled numerical model provided by the present invention and the normalized load-displacement curve obtained by experimental analysis; Figure 3 Schematic diagram of the comparison between the NSRF-LDFEA coupled numerical model provided by the present invention and the normalized load-displacement curve obtained by experimental analysis; Figure 4Schematic diagram of the analysis results of the impact resistance bearing capacity of the target pipeline provided by the present invention; Figure 5 It is a schematic diagram of a flow chart for implementing the reliability analysis method for the impact bearing capacity of submarine pipelines under multi-source random inducement coupling provided by the present invention. DETAILED DESCRIPTION

[0012] In order to have a clearer understanding of the technical features, purposes and effects of the present invention, specific embodiments of the present invention are now described in detail with reference to the accompanying drawings.

[0013] Figure 1 A schematic diagram of a method for analyzing the impact bearing capacity reliability of a submarine pipeline under multi-source random inducement coupling in this embodiment is shown. In this embodiment, the method for analyzing the impact bearing capacity reliability of a submarine pipeline under multi-source random inducement coupling includes the following steps: S1: Based on the geometric models of seabed soil, falling object, and pipeline, a non-stationary random field-large deformation finite element analysis coupled numerical model is constructed and solved to obtain the impact process; In an exemplary embodiment, step S1 includes: S11: Construct a non-stationary lognormal random field numerical discrete model based on the seabed soil geometry model; In an exemplary embodiment, step S11 includes: S111: Construct a seabed soil geometric model and, based on the seabed soil geometric model, construct a stationary random field theoretical model; In an exemplary embodiment, step S111 specifically includes: S1111: Based on the three-dimensional geometric dimensions of the seabed soil, a seabed soil geometric model is established, and based on the area enclosed by the outer surface of the seabed soil geometric model, the topological space of the stationary random field theory model is determined; In an exemplary embodiment, the three-dimensional geometric dimensions of the seabed soil body include length, height and width; S1112: Construct a stationary random field theory model based on the topological space of the stationary random field theory model; In an exemplary embodiment, step S1112 includes: constructing a stationary random field theory model according to the topological space of the stationary random field theory model, such as formula: , , , in, is the mean function of the stationary random field theory model, Represents the mean operation; It is a stationary random field theory model; is a topological space median coordinates; represents the sampling space, The sampling space The sample values ​​in ; To characterize the probability distribution of stationary random field theory models; is the autocovariance function, is the covariance function; is the standard deviation function of the stationary random field theory model; is the autocorrelation function, is the autocorrelation distance; S112: Based on the stationary random field theoretical model and the seabed soil geometric model, a stationary random field numerical discrete model is obtained; In an exemplary embodiment, step S112 specifically includes: S1121: Use the super Latin square sampling method to extract a series of coordinate nodes in the topological space, and use their corresponding node values ​​in the stationary random field theoretical model to form a characteristic node value set that characterizes the characteristics of the stationary random field; S1122: Approximate and estimate the stationary random field theoretical model according to the characteristic node value set to obtain an approximate stationary random field theoretical model; In an exemplary embodiment, step S1122 specifically includes: S1122: approximating and estimating the stationary random field theoretical model according to the characteristic node value set to obtain an approximate stationary random field theoretical model, such as formula: , , in, is an approximate theoretical model of a stationary random field. and is an unknown linear function, express The transpose of is the number of feature nodes in the feature node value set, is the first Node values, is the set of node values ​​corresponding to the characteristic node set in the stationary random field, Node value set The number of terms in the spectral decomposition of the autocovariance matrix, are independent standard normal random variables, and Node value sets The eigenvalues ​​and eigenvectors of the autocovariance matrix, for The transpose of is a stationary random field theoretical model and characteristic node set The covariance matrix of S1123: Meshing the seabed soil geometric model to obtain a seabed soil mesh model and a coordinate set corresponding to its mesh nodes; using the unit nodes of the seabed soil mesh model as nodes for numerical discretization of a stationary random field approximate theoretical model to obtain a stationary random field numerical discretization model; S113: Convert the stationary random field numerical discrete model into a non-stationary lognormal random field numerical discrete model; In an exemplary embodiment, step S113 specifically includes: S1131: According to the Nataf principle, the numerical discrete model of the stationary random field is converted into the numerical discrete model of the stationary lognormal random field; In an exemplary embodiment, step S1131 specifically includes: according to the Nataf principle, converting the stationary random field numerical discrete model into a stationary lognormal random field numerical discrete model, such as formula: , , in, A stationary lognormal random field discrete numerical model is used to characterize the spatial variability of soil strength. is the inverse function of the lognormal cumulative probability function; is the standard normal cumulative probability function; A stationary standard normal random field discrete numerical model is used to characterize the spatial variability of soil strength. and are the mean and standard deviation of the lognormal distribution, and are the mean and standard deviation of the undrained shear strength of the seabed surface; S1132: Using the scaling multiplier method, the stationary lognormal random field numerical discrete model is converted into a non-stationary lognormal random field numerical discrete model; In an exemplary embodiment, step S1132 specifically includes: using a scaling multiplier method to convert the stationary lognormal random field numerical discrete model into a non-stationary lognormal random field numerical discrete model, such as formula: , in, A non-stationary lognormal random field discrete numerical model is used to characterize the spatial variability of soil strength; is the scaling factor, is the first discrete model of the stationary lognormal random field. The depth value of each unit node, Undrained shear strength with depth increasing gradient; S12: Construct a large deformation finite element analysis mesh model based on the seabed soil geometry model, the falling object geometry model, and the pipeline geometry model; S13: Based on the non-stationary lognormal random field numerical discretization model and the large deformation finite element analysis grid model, a non-stationary random field-large deformation finite element analysis coupled numerical model is constructed and solved to obtain the impact process; In an exemplary embodiment, step S13 specifically includes: constructing a non-stationary random field-large deformation finite element analysis coupled numerical model based on the non-stationary lognormal random field numerical discrete model and the large deformation finite element analysis grid model and solving it to obtain the impact process, such as the formula: , , , , , , , , , in, 、 、 、 、 、 are the node displacement, velocity, acceleration, mass, stiffness and external load matrix in the large deformation finite element analysis mesh model, Indicates the current time step The undrained shear strength value at each soil unit integration point is: represents the function that characterizes the undrained shear strength with the field variable value as the independent variable, and The starting and ending times of the current time step are The value of the field variable at each soil unit integration point; 、 and They are the initial moment, the starting moment of the current time step and the ending moment. Temperature field value at each soil unit integration point; and The current time step and the previous time step are The value of the solution-correlated variable at each soil unit integration point; 、 、 They represent the node stiffness, geometric relationship and physical relationship matrices in the non-stationary random field-large deformation finite element analysis coupled numerical model respectively; Represents the node velocity matrix in the large deformation finite element analysis mesh model at the midpoint of the current time step, represents the node velocity matrix in the large deformation finite element analysis mesh model at the midpoint of the previous time step, and denote the time increments of the previous time step and the current time step, respectively. Represents the node acceleration matrix in the large deformation finite element analysis mesh model at the start of the current time step, Represents the node displacement matrix in the large deformation finite element analysis mesh model at the end of the current time step, Represents the node displacement matrix in the large deformation finite element analysis mesh model at the start of the current time step, Represents the node acceleration matrix in the large deformation finite element analysis mesh model at the end of the current time step, Represents the node external load matrix in the large deformation finite element analysis mesh model at the end of the current time step, Represents the node strain matrix in the large deformation finite element analysis mesh model at the end of the current time step, Represents the node stress matrix in the large deformation finite element analysis mesh model at the end of the current time step; S2: Based on the non-stationary random field-large deformation finite element analysis coupled numerical model, the Monte Carlo simulation method and the rigid-plastic shell-beam synergy theory model are used to obtain the probabilistic statistical characteristics of soil energy absorption; In an exemplary embodiment, step S2 specifically includes: S21: Based on the non-stationary random field-large deformation finite element analysis coupled numerical model, the Monte Carlo simulation method is used to obtain the cumulative probability curve of the pipeline dent depth; In an exemplary embodiment, step S21 specifically includes: S211: Monte Carlo simulation method is used to drive the non-stationary random field-large deformation finite element analysis coupled numerical model to perform sampling simulation on the pipeline structure response and obtain the pipeline structure response data statistical series; S212: According to the pipeline structure response data statistical sequence, according to the depression depth δ Rearrange the sequence in ascending order, determine the dent depth interval, and count the frequency and cumulative frequency falling into each dent depth interval to obtain the cumulative probability curve of the pipeline dent depth: In an exemplary embodiment, step S212 specifically includes: according to the pipeline structure response data statistical sequence, according to the depression depth δ Rearrange the sequence in ascending order, determine the dent depth interval, and count the frequency and cumulative frequency falling into each dent depth interval to obtain the cumulative probability curve of the pipeline dent depth, as shown in the formula: , , in, For the The depth range of the depression, For the The lower boundary value of the depression depth interval, 、 are the minimum and maximum pipeline depression depths in the pipeline structure response statistical series respectively; The number of interval divisions for the pipeline structure response statistical series; S22: Based on the cumulative probability curve of the pipeline dent depth, the probability statistical characteristics of soil energy absorption are obtained using the rigid-plastic shell-beam synergy theory model; In an exemplary embodiment, step S22 specifically includes: S221: For each sample value of the indentation depth in the pipeline structure response data statistical series, the rigid-plastic shell-beam synergistic theory model is used to estimate the impact energy required to cause the pipeline to produce the damage of that degree; In an exemplary embodiment, step S221 specifically includes: for each indentation depth sample value in the pipeline structure response data statistical sequence, using the rigid-plastic shell-beam synergistic theoretical model to estimate the impact energy required to cause the pipeline to produce a certain degree of damage, such as the formula: , in, The depth of the depression that causes pipeline damage The impact energy required; Represents the inverse function of the rigid-plastic theory model, which is used to solve the impact energy required to cause a specified degree of damage to the pipeline; is a vector representing the pipe size and material parameters; 、 、 are the outer diameter and wall thickness of the pipe and the yield strength of the steel material; S222: Based on the total impact energy of the falling object and the impact energy required to cause the pipeline to have a certain degree of damage, the energy absorption value of the soil around the pipeline under the corresponding non-stationary random field conditions is obtained; In an exemplary embodiment, step S222 specifically includes: obtaining the energy absorption value of the soil around the pipeline under the corresponding non-stationary random field conditions based on the total impact energy of the falling object impact input and the impact energy required to cause the pipeline to produce a certain degree of damage, such as the formula: , in, is the energy absorption value of the soil around the pipeline under the corresponding non-stationary random field conditions, The total impact energy input for the falling object impact; S223: According to the energy absorption value of the soil around the pipeline under the corresponding non-stationary random field conditions, the cumulative probability curve of the pipeline dent depth is converted into the probability statistical characteristics of the soil energy absorption; In an exemplary embodiment, step S223 specifically includes: according to the energy absorption value of the soil around the pipeline under the corresponding non-stationary random field conditions, converting the cumulative probability curve of the pipeline dent depth into a probability statistical characteristic of soil energy absorption, such as the formula: , in, Impact energy absorbed by the soil around the pipeline Less than the characteristic value of absorbed energy The probability of failure; Pipeline depression depth Not less than the characteristic value of the depression depth The probability of failure when and Pipeline depression depth Less than the characteristic value of the depression depth The cumulative probability of S3: Based on the statistical characteristics of soil energy absorption probability, the rigid-plastic shell-beam synergy theory model and the Monte Carlo simulation method are used to obtain the modified structural failure probability; In an exemplary embodiment, step S3 specifically includes: S31: Based on the probabilistic statistical characteristics of soil energy absorption, the structural limit state equation is constructed using the rigid-plastic shell-beam synergy theory model and reliability theory; In an exemplary embodiment, the structural limit state equation is as follows: , in, Represents structure-function function; It is a rigid-plastic theory model; is a vector representing the inherent uncertainty factors of the project; Indicates the characteristic value of the soil around the pipeline absorbing the impact energy; Characterize critical failure criteria of structures; Indicates the depth of the pipe depression Less than the characteristic value of the depression depth The cumulative probability of Indicates the impact energy absorbed by the soil around the pipeline Less than the characteristic value of absorbed energy The inverse function of the failure probability; S32: Based on the structural limit state equation, the Monte Carlo simulation method is used to obtain the structural failure probability; In an exemplary embodiment, step S32 specifically includes: according to the structural limit state equation, using the Monte Carlo simulation method, obtaining the structural failure probability, such as the formula: , in, is the probability of structural failure; is the failure domain, is the joint probability density distribution of random variables under the coupling of soil strength spatial variability and engineering inherent random factors, The number of sampling simulations performed to solve the failure probability using the Monte Carlo simulation method; is the indicator function; S33: Correcting the structural failure probability to obtain a corrected structural failure probability; In an exemplary embodiment, step S33 specifically includes: correcting the structural failure probability to obtain a corrected structural failure probability, such as the formula: , in, To correct the probability of structural failure; is the failure probability when the impact energy absorbed by the soil around the pipeline is less than the characteristic energy under the condition of spatial variability of soil strength; In an exemplary embodiment, the above-mentioned method for analyzing the impact bearing capacity reliability of submarine pipelines under multi-source random inducement coupling further includes: evaluating the impact bearing capacity of the structure using a modified structural failure probability to obtain an evaluation result; In an exemplary embodiment, the above-mentioned evaluation of the structural impact bearing capacity using the modified structural failure probability to obtain an evaluation result is specifically: the structural impact bearing capacity is evaluated using the modified structural failure probability to obtain an evaluation result, such as the formula: , in, is the indicator function; is the critical structural failure probability.

[0014] In some embodiments, the above-mentioned method for reliability analysis of submarine pipeline impact bearing capacity under multi-source random inducement coupling can also be implemented in the following manner. The method for reliability analysis of submarine pipeline impact bearing capacity under multi-source random inducement coupling of this embodiment includes the following contents: (1) First, a non-stationary random field (NSRF) is constructed based on the expansion optimal linear estimation (EOLE) algorithm to achieve the theoretical expression and numerical discretization of the spatial variability characteristics of soil strength. Then, through the subroutine mapping technology, the non-stationary random field is coupled with the Gaussian points of the soil unit in the large deformation finite element analysis (LDFEA) model that describes the mechanical failure characteristics of soil and pipelines. The numerical coupling and solution domain discretization of the control equations of the above-mentioned random process system and the mechanical analysis system are realized, and the dynamic explicit central difference algorithm is used to solve the equation. The NSRF-LDFEA coupled numerical model is constructed to describe the structural response characteristics under the condition of spatial variability of soil strength. (2) Based on the Monte-Carlo simulation (MCS) method, the NSRF-LDFEA coupled numerical model is used to perform sampling simulation of pipeline damage and obtain a sample sequence of pipeline damage degree. , and then estimate its statistical characteristics, namely the cumulative probability curve of pipeline dent depth ; (3) Derivation of equivalent energy criterion: Estimate the energy required for pipeline damage using the rigid-plastic shell-beam synergy theory model , and through the total energy of the impact load Perform subtraction to obtain the energy absorbed by the soil , thus converting the statistical characteristics of pipeline damage degree into statistical characteristics of soil energy absorption degree, that is, the failure probability curve of soil energy absorption degree ; (4) Combining the soil energy absorption accumulation curve, the rigid-plastic shell-beam synergistic theoretical model and reliability theory, the structural limit state equation is constructed to estimate the structural damage degree and safety state under the coupling of soil strength spatial variability and engineering inherent uncertainties, and to divide the failure domain in the multidimensional probability characteristic space. On this basis, the joint probability density function of the above random factors is combined with the MCS method In the failure domain The integral of the estimated structure failure probability is obtained , to evaluate the pipeline's impact bearing capacity performance.

[0015] In some embodiments, the above-mentioned method for reliability analysis of submarine pipeline impact bearing capacity under multi-source random inducement coupling can also be implemented in the following manner. The method for reliability analysis of submarine pipeline impact bearing capacity under multi-source random inducement coupling in this embodiment includes: 1. Construction of a non-stationary random field-large deformation finite element analysis coupling numerical model; 2. Establishment of the equivalent energy principle; 3. Construction of a reliability analysis model under multi-source random inducement coupling, specifically as follows: 1. Construction of non-stationary random field-large deformation finite element analysis coupling model: 1.1 Construction of non-stationary random field model: 1.1.1 Construction of stationary random field theoretical model: (1) According to the three-dimensional geometric dimensions of the seabed soil, i.e. length ,high ,width , establish the seabed soil geometry model , and the area enclosed by its outer surface determines the topological space of the stationary random field (SRF) theoretical model the boundaries; (2) Furthermore, based on the conditions of stationarity, ergodicity and Gaussianity, the probability characteristics of soil strength parameters, i.e., the mean value of the undrained shear strength at the surface of the seabed soil, can be used to calculate the , standard deviation , soil strength horizontal and vertical related distances , , according to formulas (1) – (3), a stationary random field theoretical model describing the spatial variability of soil strength is established; (1) (2) (3) Where: is the mean function of the stationary random field theory model, Represents the mean operation; It is a stationary random field theory model; is a topological space median coordinates; represents the sampling space, for The sample values ​​in ; is the autocovariance function, is the covariance function; is the standard deviation function of the stationary random field theory model; is the autocorrelation function. In the present invention, the Gaussian autocorrelation function can be separated, and its one-dimensional expression is shown in formula (3). is the autocorrelation distance.

[0016] 1.1.2 Numerical discretization of stationary random fields: (1) Use Latin hypercube sampling (LHS) to extract a series of coordinate nodes in the topological space , with its corresponding node values ​​in the stationary random field theoretical model constituting the characteristic node value set that characterizes the stationary random field characteristics ; (2) According to the principle of extended optimal linear estimation: the stationary random field theoretical model is based on the characteristic node value set The form of the linear function is approximated according to formula (4), and the unknown linear function is approximated according to the minimum variance principle by combining the spectral decomposition method of the characteristic node value set. , Estimation is performed to obtain the approximate theoretical model of the stationary random field The expression of is shown in formula (5); (3) The seabed soil geometric model established in step 1.1.1 Perform grid division to obtain the corresponding grid model and its corresponding coordinate set of grid nodes ; Take the unit nodes of the soil mesh model as the nodes of the numerical discretization of the stationary random field approximate theoretical model, and let , and further the numerical discrete node coordinate set Substituting into formula (5), we get the numerical discrete model of stationary random field .

[0017] (4) (5) Where: Represents an approximate theoretical model of a stationary random field; and is the linear function to be solved; is the characteristic node set in the stationary random field The set of corresponding node values; 、 Node value set Autocovariance matrix The eigenvalues ​​and eigenvectors of are independent standard normal random variables, for the number of terms in the spectral decomposition; Stationary random field theory model With feature node set The covariance matrix of .

[0018] 1.1.3 Non-stationary transition of stationary random field model: (1) Considering the non-negative characteristics of soil strength, the lognormal distribution is generally used to describe its probability characteristics. Therefore, the stationary normal random field established in step 1.1.2 needs to be converted into the corresponding lognormal random field. According to the Nataf principle, the numerical discrete model of the stationary normal random field representing the spatial variability of soil strength is converted into the numerical discrete model of the stationary lognormal random field according to equations (6)-(7). (2) Due to the consolidation process of soil under overburden pressure, the statistical characteristics of soil strength parameters are related to the spatial coordinate position, which is generally manifested as the mean and coefficient of variation increase with the depth coordinate. In order to accurately describe this feature, it is necessary to further convert the stationary lognormal random field into a non-stationary lognormal random field. The present invention uses the scaling multiplier method to achieve the above conversion, as shown in formula (8), introducing the vertical coordinate z is the scaling factor of the independent variable And multiply it with the numerical discrete model of the log-normal stationary random field to obtain the corresponding numerical discrete model of the non-stationary log-normal random field.

[0019] (6) (7) (8) Where: A stationary standard normal random field discrete numerical model is used to characterize the spatial variability of soil strength. A stationary lognormal random field discrete numerical model is used to characterize the spatial variability of soil strength. A non-stationary lognormal random field discrete numerical model is used to characterize the spatial variability of soil strength; and are the mean and standard deviation of the lognormal distribution, and is the mean and standard deviation of the undrained shear strength of the seabed surface; is the standard normal cumulative probability function; is the inverse function of the lognormal cumulative probability function; is the scaling factor, Undrained shear strength with depth Increasing gradient.

[0020] 1.2 Construction of mesh model for large deformation finite element analysis: 1.2.1 Mesh model construction and assembly: (1) Establish the corresponding geometric model according to the geometric dimensions of the falling object and the pipe , ; Since the stiffness of the two is large and the deformation is small during the analysis process, the Lagrangian algorithm is used to discretize the two grids to obtain their corresponding grid models , ; (2) The seabed soil has a low stiffness and is prone to large deformation during impact loading, causing mesh distortion. Therefore, the soil mesh model in step 1.1.2 The Euler algorithm is used to describe it to solve the above-mentioned large deformation problem of soil. At the same time, the penalty function algorithm is used to describe the contact between soil, falling objects and pipeline mesh models to achieve information transfer between Euler mesh and Lagrangian mesh. (3) The falling object mesh model , pipeline grid model and soil mesh model Assemble within the same Cartesian coordinate system and adjust their relative positions to ensure that the pipeline is located at the specified burial depth and the impact load is applied to the mid-span of the pipeline, thereby determining the solution domain of the falling object-pipeline-soil mechanics analysis system; 1.2.2 Definition of material properties and conditions: (1) The mass and constitutive relationship of each grid model are defined according to the material properties of the falling object, pipeline, and soil, and the mass matrix and stiffness matrix corresponding to each model are determined: the rate-dependent kinematic hardening constitutive model Cowper-Symonds model is used to describe the stress-strain relationship of the pipeline steel material, accurately capturing the hardening effect of the material strain rate on the material strength during high-speed impact; the Mohr-Coulomb model is used to describe the elastic-plastic behavior of the soil material, in which the soil strength is mainly expressed in terms of undrained shear strength. Characterization, elastic modulus is , which is an approximate undrained condition, and the Poisson's ratio is For falling objects, the structural deformation during the impact process is ignored, and they are simplified into rigid bodies through rigid body constraints, and the ideal linear elastic model is used as their constitutive model. (2) Define the initial conditions, boundary conditions and contact relationships of the mechanical analysis system jointly constructed by each grid model, and complete the numerical discretization of the control equation of the mechanical system described by the LDFEA model as shown in formula (9): apply the initial ground stress field to the soil grid model and balance it with gravity, so that the stress of each soil unit at the initial moment of calculation remains within its own yield surface, in a convergence state with initial stress but no initial strain, so as to accurately simulate the initial state of the soil that has undergone a long geological evolution process under real conditions; apply fixed constraints to the bottom of the soil grid model and lateral displacement constraints to the side boundaries; apply fixed end constraints to both ends of the pipeline; apply the impact velocity to the falling object grid model as its initial condition, and combine its mass to obtain the initial impact energy input to the mechanical system. ; A general contact algorithm is used to describe the contact relationship between soil, falling objects and pipelines.

[0021] 1.3 Construction and solution of non-stationary random field-nonlinear large deformation finite element analysis coupling model: By developing a subroutine mapping algorithm, the construction and solution of the coupling between the non-stationary lognormal random field numerical discrete model and the nonlinear large deformation finite element analysis model are realized. The specific algorithm is as follows: (1) The non-stationary lognormal random field numerical discrete model constructed in step 1 is introduced into the LDFEA model in the form of temperature field as the initial condition. ,in is the node coordinate of the soil unit; at the same time, the constitutive model of the soil material is modified, and the undrained shear strength is calculated according to formula (10) Su Set as a function of the field variable (FV) to associate the random field with the soil material strength and bind it to the integration points of the soil element to capture the evolution of the soil material strength during the calculation process; (2) During the calculation process, the temperature field value at the unit integration point at the start of the current time step is read through the subroutine and assigned to the field variable, as shown in formula (11); (3) Based on the field variable values, the undrained shear strength of the soil material at the unit integration point is updated according to the relationship in formula (10), realizing the association between the soil material strength and the non-stationary lognormal random field, and completing the coupling and numerical discretization of the control equations of the non-stationary random field-large deformation finite element analysis model, as shown in formula (12); (4) Solve the displacement values ​​according to Equations (13)–(16) using the explicit central difference algorithm, and substitute them into the geometric equations and physical equations to obtain the structural stress and strain fields and describe the structural response characteristics; (5) The end time of the current time step t j +Δ t j The temperature field value of is stored in the solution dependent variable (SDV) according to formula (17) for reading in the next time step; (6) Order Repeat steps (2) – (5) to calculate the next time step until , and complete the solution of the entire impact process.

[0022] (9) (10) (11) (12) (13) (14) (15) (16) (17) Where: 、 、 、 、 、 are the node displacement, velocity, acceleration, mass, stiffness and external load matrices in the LDFEA model, respectively. Their subscripts represent the specific moment positions of the current time step. 、 Respectively represent the start and end time of the current time step, 、 Represent the midpoint of the previous time step and the current time step respectively, represents the time increment of the current time step; 、 、 They represent the node stiffness, geometric relationship and physical relationship matrices in the NSRF-LDFEA coupling model respectively; The current time step Undrained shear strength value at each soil unit integration point; and The starting and ending times of the current time step are The value of the field variable at each soil unit integration point; 、 and They are the initial moment, the starting moment of the current time step and the ending moment. Temperature field value at each soil unit integration point; 、 The current time step and the previous time step are The value of the solution-correlated variable at each soil unit integration point; 2 Construction of equivalent energy principle: 2.1 Estimation of statistical characteristics of pipeline structure response: (1) The MCS method is used to drive the NSRF-LDFEA coupled numerical model constructed in step 1 to perform sampling simulation on the pipeline structure response and obtain the pipeline structure response data statistical series. , where the number of sampling simulations is = 400, For the The parameters characterizing the statistical characteristics of the non-stationary random field are obtained by sampling. For the The dent depth of the cross section at the center of the impact load of the pipeline under the non-stationary random field condition obtained by sampling is used to characterize the structural response; (2) According to the statistical sequence of structural response , according to the depth of the depression Rearrange the sequence in ascending order of values; to convert the structure response statistics sequence The equal division principle determines the depression depth interval according to formula (18) , and count the frequency and cumulative frequency of each depression depth interval to determine the relationship between cumulative frequency and depression depth

[0023] (18) Where: 、 are the minimum and maximum pipeline depression depths in the pipeline structure response statistical series respectively; The number of interval divisions for the pipeline structure response statistical series; For the Depth interval of depression The lower boundary value of .

[0024] 2.2 Estimation of statistical characteristics of soil energy absorption: (1) For each sample value of the concave depth in the structural response statistical sequence in step 2.1 ,According to the rigid-plastic shell-beam synergistic theory model, the impact energy required to cause the pipeline to produce this degree of damage is estimated according to formula (19); (2) Furthermore, as shown in Equation (20), the energy absorption value of the soil around the pipeline under the corresponding non-stationary random field conditions can be obtained by subtracting the energy that causes pipeline damage from the total impact energy input to the system; (3) According to the probability relationship shown in formula (21), the cumulative frequency-dent depth relationship can be expressed as Equivalent conversion to failure probability-soil energy absorption relationship , to quantify the effect of spatial variability of soil strength on structural response; (19) (20) (twenty one) Where: The depth of the depression that causes pipeline damage The impact energy required; The impact energy absorbed by the soil around the pipeline; is the total impact energy input by the falling object; is a vector representing the pipe size and material parameters; 、 、 are the outer diameter and wall thickness of the pipe and the yield strength of the steel material; Pipeline depression depth Less than the characteristic value of the depression depth The cumulative probability of Impact energy absorbed by the soil around the pipeline Less than the characteristic value of absorbed energy The probability of failure; Pipeline depression depth The probability of failure when Represents the inverse function of the rigid-plastic theory model and is used to solve the impact energy required to cause a specified degree of damage to the pipeline.

[0025] 3 Construction of reliability analysis model under the coupling of multi-source random inducements: 3.1 Construction of structural limit state equations: According to the reliability theory, the structural limit state equation is constructed according to formula (22) to determine the failure domain Ω of the structure in the probability characteristic space under the influence of variability factors. f The structural response is estimated based on the rigid-plastic shell-beam synergistic theory model, where the input energy is the total energy of the system minus the characteristic energy absorption value of the soil. .

[0026] (twenty two) Where: Represents structure-function function; is a vector representing the inherent uncertainty factors of the project; is the vector representing the spatial variability factor of soil strength; Indicates the characteristic value of the soil around the pipeline absorbing the impact energy; Characterizes the critical failure criterion of the structure, which is the ratio of the maximum acceptable pipe dent deformation depth to the pipe diameter; It is a rigid-plastic theory model used to estimate the indentation depth caused by pipeline damage under a specified impact load.

[0027] 3.2 Solution of structural failure probability: According to the MCS method, the joint probability density distribution is solved according to formula (23): In the failure domain The integral value of the structural failure probability is obtained

[0028] (twenty three) Where: is the probability of structural failure; is the indicator function, ; The number of sampling simulations performed for the MCS method to solve the failure probability; It is the joint probability density distribution of random variables under the coupling of spatial variability of soil strength and inherent random factors of engineering.

[0029] 3.3 Correction of structural failure probability: The structural failure probability is corrected according to formula (24) to quantify the failure probability when the impact energy absorbed by the soil around the pipeline is less than the characteristic energy under the condition of spatial variability of soil strength. The contribution to the probability of structural failure is achieved by coordinating steps 3.1-3.2 to realize the coupling of the effects of soil strength spatial variability and engineering inherent variability factors on structural response in the probability characteristic space. As shown in formula (25), according to the modified structural failure probability The impact resistance of the structure can be evaluated. If it is less than the critical structural failure probability , then its carrying capacity meets the requirements; otherwise, if it is greater than or equal to the critical failure probability, then its carrying capacity does not meet the requirements.

[0030] (twenty four) (25) Where: is the modified structural failure probability; is the critical structure failure probability; is the indicator function.

[0031] In some embodiments, the above-mentioned method for reliability analysis of submarine pipeline impact bearing capacity under multi-source random inducement coupling can also be implemented in the following manner. The method for reliability analysis of submarine pipeline impact bearing capacity under multi-source random inducement coupling of this embodiment includes the following contents: 1. Verification of NSRF-LDFEA coupled numerical model: The description of the structural response in the method proposed in this example is based on the NSRF-LDFEA coupled numerical model, so the accuracy of this numerical model must be verified first. Using the pipeline impact test and pipeline in-situ stability test with detailed experimental process records in the published literature as the target, the NSRF-LDFEA coupled numerical model constructed in this example was used to numerically reconstruct them and verify: (1) the model's ability to describe the stress-strain behavior of the structure under impact loads; and (2) the model's ability to describe soil failure behavior and pipe-soil interaction.

[0032] (1) Pipeline impact test verification: The arrangement of pipeline impact test is as follows Figure 2 As shown in the figure, the pipe specimen is suspended in the axial direction without support and has fixed constraints at both ends. The impact load is applied to the mid-span of the pipe by a rigid knife-shaped indenter through a loading device, and the load-displacement curve during the loading process is recorded by a sensor. The outer diameter of the pipe specimen is , wall thickness is The yield strength, elastic modulus and Poisson's ratio of steel materials are According to the above experimental arrangement and parameters, the experiment was numerically reproduced based on the coupled numerical model constructed in the present invention. Figure 2 A comparison of the load-displacement curves obtained from experiments and numerical simulations is presented in Figure 2. It can be seen that throughout the entire impact load loading and unloading process, the curves obtained from numerical simulations agree well with the experimental results in terms of both trend and magnitude. This demonstrates that the coupled numerical model constructed in this paper can accurately capture the effects of loading rate and loading history on the material stress-strain relationship and reasonably describe the structural response characteristics under impact loading.

[0033] (2) Experimental verification of pipeline in-situ stability: The in-situ stability of the pipeline is mainly determined by the ultimate bearing capacity of the soil under the conditions of pipe-soil interaction. In order to accurately approximate the soil properties under actual working conditions, the in-situ stability test of the pipeline is carried out in a centrifuge with a centrifugal acceleration of 40 times the acceleration of gravity. The outer diameter of the corresponding prototype pipe of the pipeline sample is , a vertical quasi-static displacement load is applied to the pipe sample so that it moves at a speed of Penetrate into the soil to the designed depth The load-displacement curve during the loading process was recorded by sensors. The soil material in the experiment was clay, and its undrained shear strength increased linearly with the increase of vertical depth, which is According to the above experimental arrangement and parameters, the experiment was numerically reproduced based on the coupled numerical model constructed in this embodiment. Figure 3 The results of the comparison of the load-displacement curves obtained by the coupled numerical model and experiments are given in the figure. Overall, the two are in good agreement. The minor deviation is mainly caused by the uncalibrated roughness coefficient of the pipe-soil interface. This parameter is difficult to measure, and its value is generally determined based on literature research and engineering experience, which introduces a certain error into the numerical model. The above analysis and verification prove that the coupled numerical model can reasonably describe the failure behavior of soil and pipe-soil interaction, effectively capture the influence of soil strain softening and strain rate effect on soil strength, and accurately estimate the ultimate bearing capacity of soil.

[0034] Below, we conduct an example analysis of the reliability of the pipeline structure's impact bearing capacity: Taking the structural impact resistance reliability analysis of an actual submarine pipeline project as an example, the method proposed in this embodiment is applied to illustrate its effectiveness and feasibility. The geometric dimensions and material parameters of the target submarine pipeline are listed in Table 1. The designed buried depth of the pipeline is The soil in the sea area where the pipeline is located is clay, and its strength parameter probability statistical characteristics are listed in Table 2. The design impact load is determined by the mass of , the initial velocity is The sphere is applied.

[0035] Table 1 Target pipeline geometric dimensions and material strength parameters

[0036] Table 2 Probabilistic statistical characteristics of soil strength parameters

[0037] Based on the above information, the method proposed in this embodiment is used to analyze the impact bearing capacity of the target pipeline. The results and corresponding analysis are as follows.

[0038] Figure 4 (a) shows the probability density distribution and cumulative probability distribution of the structural response statistical series obtained by sampling calculation using the MCS method combined with the coupled numerical model. It can be seen that under the condition of spatial variability in soil strength, the soil strength distribution pattern around the pipeline is variable, which triggers a variety of soil shear failure, pipe-soil interaction, and structural failure behaviors under the action of impact loads, as well as competition and transformation between different behaviors, resulting in significant variability in the degree of damage to the pipeline under the same working conditions. Overall, the average value of the indentation depth, which represents the degree of impact damage to the pipeline, is higher than the indentation depth under the mean soil condition, indicating that the pipeline is more susceptible to failure under conditions of spatial variability in soil strength. Therefore, this factor must be taken into account. Otherwise, the bearing capacity of the structure will be overestimated, and overly radical protective measures will be adopted, introducing potential risks to the engineering design.

[0039] Figure 4 (b) shows the statistical characteristics of pipeline structure damage probability with the sampling number N sv MCS The change relationship of N sv MCS ≥ 300, as N sv MCS The increase in the average depth of the depression, which represents the degree of structural damage μ δ and standard deviation σ δ Basically remain stable and tend to converge. Sampling times Nsv MCS = 400, μ δ and σ δ and sampling times N sv MCS =500, the relative errors of the corresponding results are Δ μ δ,r = 0.02% and Δ σ δ,r = 1.97%. It can be seen that the number of samples in this interval N sv MCS There is no significant effect on the fluctuation of the statistical characteristics of the pipeline structure response, so the sampling times used in the present invention are N sv MCS = 400 is reasonable. According to the structural response statistics series {( x sv,i , δ i ( x sv,i )); i = 1, 2, 3,…, N sv MCS}The probabilistic characteristics of structural response characteristics can be accurately estimated.

[0040] Figure 4 Panel (c) compares the pipeline indentation depths estimated by the NSRF-LDFEA coupled numerical model and the rigid-plastic shell-beam synergistic theoretical model under different impact energy conditions, demonstrating good agreement between the two. The rigid-plastic shell-beam synergistic theoretical model can reasonably describe the nonlinear factors in structural failure behavior under impact loading and accurately estimate the damage extent. Therefore, it is feasible to use this model to estimate the impact energy required to cause a specified degree of pipeline damage, laying the foundation for the construction of equivalent energy criteria and reliability analysis models.

[0041] Figure 4 (d) shows the cumulative probability-pipeline depression depth curve that characterizes the statistical characteristics of the structural response under the equivalent energy criterion and the failure probability-energy absorption energy curve that characterizes the statistical characteristics of the energy absorption effect of the soil around the pipeline. It can be seen that there is a one-to-one correspondence between the two. For example, when the depression depth characteristic value is δ c = 0.06 D p When , the cumulative probability is P c,sv= 0.057. According to the equivalent energy criterion, the effective probability of soil energy absorption failure is P f,sv = 1 – P c,sv = 0.927, and the corresponding energy absorption characteristic value is P -1 f,sv (1 – P c,sv ) = δ -1 RPSB ( δ c , x p ) = 72 kJ. This principle can be used to effectively quantify the effect of spatial variability in soil strength on structural response.

[0042] Table 3 Pipeline structure failure probability

[0043] Table 3 gives the failure criteria when η δ,c = 10%, the probability of structural failure under different variability factors is considered, including: A-considering both the spatial variability of soil strength and the inherent variability of engineering (the method of the present invention); B-considering only the spatial variability of soil strength; C-considering only the inherent variability of engineering. The structural failure probabilities under the three conditions are P ud,A f,s = 0.759, P ud,B f,s = 0.507 and P ud,C f,s = 0.223. From the perspective of relative difference, the probability of structural failure under condition A is higher than that under conditions B and C. r B p = 33.2% and r C p = 70.6%. It can be seen that the spatial variability of soil strength, the inherent variability of the project, and the coupling effect of the two have a significant impact on the probability of structural failure, greatly increasing the failure risk. These factors need to be considered in safety design, confirming the necessity of the analysis method proposed in this paper.

[0044] Figure 5 It is a schematic diagram of a flowchart for implementing the reliability analysis method for the impact bearing capacity of submarine pipelines under multi-source random inducement coupling of this embodiment.

[0045] This embodiment provides a computer program product, including a computer program. When the computer program is executed by a processor, the steps of the above-mentioned method for analyzing the impact bearing capacity reliability of a submarine pipeline under multi-source random inducement coupling are implemented.

[0046] The embodiments of the present invention are described above in conjunction with the accompanying drawings, but the present invention is not limited to the above-mentioned specific implementation methods. The above-mentioned specific implementation methods are merely illustrative and not restrictive. Under the guidance of the present invention, ordinary technicians in this field can also make many forms without departing from the scope of protection of the present invention and the claims, all of which are protected by the present invention.

Claims

1. A reliability analysis method for submarine pipeline impact bearing capacity under multi-source random inducement coupling, characterized by: The following steps are involved: S1: Based on the geometric models of seabed soil, falling object, and pipeline, a non-stationary random field-large deformation finite element analysis coupled numerical model is constructed and solved to obtain the impact process; S2: Based on the non-stationary random field-large deformation finite element analysis coupled numerical model, the Monte Carlo simulation method and the rigid-plastic shell-beam synergistic theoretical model are used to obtain the probabilistic statistical characteristics of soil energy absorption; S3: According to the statistical characteristics of the soil energy absorption probability, the rigid-plastic shell-beam synergistic theoretical model and the Monte Carlo simulation method are used to obtain the modified structural failure probability.

2. The reliability analysis method for submarine pipeline impact bearing capacity under multi-source random induction coupling according to claim 1 is characterized in that: Step S1 includes: S11: Construct a non-stationary lognormal random field numerical discrete model based on the seabed soil geometry model; S12: Construct a large deformation finite element analysis mesh model based on the seabed soil geometry model, the falling object geometry model, and the pipeline geometry model; S13: Based on the non-stationary lognormal random field numerical discrete model and the large deformation finite element analysis grid model, a non-stationary random field-large deformation finite element analysis coupled numerical model is constructed and solved to obtain the impact process.

3. The reliability analysis method for submarine pipeline impact bearing capacity under multi-source random induction coupling according to claim 2 is characterized in that: Step S11 includes: S111: constructing a seabed soil geometric model, and constructing a stationary random field theoretical model based on the seabed soil geometric model; S112: Obtaining a stationary random field numerical discrete model based on the stationary random field theoretical model and the seabed soil geometric model; S113: Converting the stationary random field numerical discrete model into a non-stationary lognormal random field numerical discrete model.

4. The reliability analysis method for submarine pipeline impact bearing capacity under multi-source random induction coupling according to claim 2 is characterized in that: Step S13 specifically includes: constructing a non-stationary random field-large deformation finite element analysis coupled numerical model based on the non-stationary lognormal random field numerical discrete model and the large deformation finite element analysis grid model and solving it to obtain the impact process, such as the formula: ， ， ， ， ， ， ， ， ， in, 、 、 、 、 、 are the node displacement, velocity, acceleration, mass, stiffness and external load matrix in the large deformation finite element analysis mesh model, Indicates the current time step The undrained shear strength value at each soil unit integration point is: represents the function that characterizes the undrained shear strength with the field variable value as the independent variable, and The starting and ending times of the current time step are The value of the field variable at each soil unit integration point; 、 and They are the initial moment, the starting moment of the current time step and the ending moment. Temperature field value at each soil unit integration point; and The current time step and the previous time step are The value of the solution-correlated variable at each soil unit integration point; 、 、 They represent the node stiffness, geometric relationship and physical relationship matrices in the non-stationary random field-large deformation finite element analysis coupled numerical model respectively; Represents the node velocity matrix in the large deformation finite element analysis mesh model at the midpoint of the current time step, represents the node velocity matrix in the large deformation finite element analysis mesh model at the midpoint of the previous time step, and denote the time increments of the previous time step and the current time step, respectively. Represents the node acceleration matrix in the large deformation finite element analysis mesh model at the start of the current time step, Represents the node displacement matrix in the large deformation finite element analysis mesh model at the end of the current time step, Represents the node displacement matrix in the large deformation finite element analysis mesh model at the start of the current time step, Represents the node acceleration matrix in the large deformation finite element analysis mesh model at the end of the current time step, Represents the node external load matrix in the large deformation finite element analysis mesh model at the end of the current time step, Represents the node strain matrix in the large deformation finite element analysis mesh model at the end of the current time step, Represents the nodal stress matrix in the large deformation finite element analysis model at the end of the current time step.

5. The reliability analysis method for submarine pipeline impact bearing capacity under multi-source random induction coupling according to claim 1 is characterized in that: Step S2 specifically includes: S21: according to the non-stationary random field-large deformation finite element analysis coupled numerical model, using a Monte Carlo simulation method, obtaining a cumulative probability curve of the pipeline dent depth; S22: According to the cumulative probability curve of the pipeline dent depth, using the rigid-plastic shell-beam synergistic theoretical model, the probability statistical characteristics of soil energy absorption are obtained.

6. The reliability analysis method for submarine pipeline impact bearing capacity under multi-source random induction coupling according to claim 1 is characterized in that: Step S3 specifically includes: S31: Based on the probabilistic statistical characteristics of soil energy absorption, the structural limit state equation is constructed using the rigid-plastic shell-beam synergistic theoretical model and reliability theory; S32: Obtaining a structural failure probability using a Monte Carlo simulation method according to the structural limit state equation; S33: Correcting the structural failure probability to obtain a corrected structural failure probability.

7. The reliability analysis method for submarine pipeline impact bearing capacity under multi-source random induction coupling according to claim 6 is characterized in that: Step S32 specifically includes: according to the structural limit state equation, using the Monte Carlo simulation method, obtaining the structural failure probability, such as the formula: ， in, is the probability of structural failure; is the failure domain, is the joint probability density distribution of random variables under the coupling of soil strength spatial variability and engineering inherent random factors, The number of sampling simulations performed to solve the failure probability using the Monte Carlo simulation method; is the indicator function, Represents structure-functionality function.

8. The reliability analysis method for submarine pipeline impact bearing capacity under multi-source random induction coupling according to claim 6 is characterized in that: Step S33 specifically includes: correcting the structural failure probability to obtain a corrected structural failure probability, such as the formula: ， in, To correct the probability of structural failure; It is the failure probability when the impact energy absorbed by the soil around the pipeline is less than the characteristic energy under the condition of spatial variability of soil strength.

9. The reliability analysis method for submarine pipeline impact bearing capacity under multi-source random induction coupling according to claim 1 is characterized in that: Also includes: The impact bearing capacity of the structure is evaluated using the modified structural failure probability to obtain the evaluation results.

10. A computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method for reliability analysis of the impact bearing capacity of a submarine pipeline under multi-source random inducement coupling according to any one of claims 1 to 9 are implemented.

Images