A method and device for generating a dynamic submarine cable insulation layer bending stress distribution cloud diagram, an electronic device and a storage medium

Abstract

This invention discloses a method, apparatus, electronic device, and storage medium for generating a dynamic bending stress distribution cloud map of submarine cable insulation, belonging to the field of finite element simulation analysis. The method includes: acquiring the geometric dimensions, target bending radius, and fixture span parameters of the insulation layer of the dynamic submarine cable under test; establishing a finite element simulation model based on the parameters, and setting the contact relationship between the insulation layer and the pressure block and fixture, as well as a virtual spring base with variable stiffness; calculating the vertical downward displacement of the pressure block according to the target bending radius, and performing iterative solutions during the process of loading the pressure block displacement from zero to the displacement amount while the stiffness of the virtual spring base synchronously decays to zero to obtain stress data; extracting the stress data when the stiffness decays to zero, and generating a stress distribution cloud map of the insulation layer under the target bending radius. By implementing this invention, the problem of difficulty in simultaneously ensuring computational convergence stability in the numerical simulation of bending conditions of submarine cable insulation in existing technologies can be solved.

Description

Technical Field

[0001] This invention relates to the field of finite element simulation analysis technology, specifically to a method, apparatus, electronic device, and storage medium for generating dynamic bending stress distribution cloud maps of submarine cable insulation layers. Background Technology

[0002] As the "main artery" for energy transmission in deep-sea areas, dynamic submarine cables endure repeated mechanical bending loads over long periods in complex marine dynamic environments. The stress distribution of their insulation layer directly determines the cable's electrical performance and service life. Currently, generating bending stress distribution cloud maps of the insulation layer using finite element simulation technology is a key method for assessing the structural safety of submarine cables and optimizing insulation design.

[0003] However, in nonlinear finite element simulation modeling of insulation layers under bending conditions, there exists an irreconcilable contradiction between convergence and accuracy. In the initial loading stage, the insulation layer model and the external fixture have not yet established a stable contact relationship, essentially existing in an under-constrained "floating" state. This makes it highly susceptible to rigid body displacement, leading to singularities in the system stiffness matrix and causing the simulation calculation to be interrupted due to non-convergence. Furthermore, to force convergence, existing techniques typically apply additional artificial constraints, but these constraints persist in the actual stress stage after the contact relationship is established. This results in the inclusion of unreal constraint reactions in the final stress contour plot, causing severe distortion in the simulation results and failing to accurately reflect the true physical response of the insulation layer under free bending conditions. Summary of the Invention

[0004] This invention provides a method, apparatus, electronic device, and storage medium for generating dynamic bending stress distribution cloud maps of submarine cable insulation layers. This solves the problem in the prior art that numerical simulations of bending conditions of submarine cable insulation layers are difficult to balance computational convergence stability and stress result accuracy.

[0005] An embodiment of the present invention provides a method for generating a dynamic bending stress distribution cloud map of submarine cable insulation, comprising: Obtain the geometric dimensions, target bending radius, and preset fixture span parameters of the insulation layer of the dynamic submarine cable under test; Based on the geometric dimensions and the span parameters of the fixtures, a finite element simulation model was established, which includes an insulation layer model, two fixture models, and a pressure block model. The insulation layer model is horizontally mounted above the two fixture models, and the pressure block model is located at the mid-span position above the insulation layer model. In the finite element simulation model, the contact connection relationship between the insulation layer model, the pressure block model, and the two fixture models is established, and a virtual spring base with a variable stiffness coefficient is applied to the insulation layer model to generate the model to be solved. Calculate the required vertical downward displacement of the pressure block model based on the target bending radius and the span parameters of the fixer; Based on the vertical downward displacement, with the goal of achieving a force equilibrium state in each iteration, iterative calculations are performed on the model to be solved to generate simulation results containing stress data. During the iterative calculations on the model to be solved, the displacement loading value of the pressure block model in the model to be solved is increased from zero to the vertical downward displacement, and the stiffness coefficient value of the virtual spring base is simultaneously reduced from a preset initial high stiffness value to zero. The stress data corresponding to the attenuation of the stiffness coefficient of the virtual spring base to zero is extracted from the simulation calculation results, and a stress distribution cloud map of the insulation layer under the target bending radius is generated based on the extracted stress data.

[0006] Furthermore, the geometric parameters include the outer diameter of the insulation layer, the thickness of the insulation layer, and the axial length of the insulation layer; The finite element simulation model, based on geometric dimensions and clamp span parameters, includes an insulation layer model, two clamp models, and a pressure block model. Based on the outer diameter, thickness, and axial length of the insulation layer in the geometric parameters, a circular tubular geometry is constructed as the insulation layer model. Based on the preset fixture geometry parameters, two rigid bodies with the same structure are constructed as two fixture models, and the two fixture models are arranged at intervals in the horizontal direction. The horizontal distance between the central axes of the two fixture models is set to be equal to the fixture span parameter. Based on the preset geometric parameters of the pressure block, a rigid body is constructed as the pressure block model, and the loading center axis of the pressure block model is set on the perpendicular bisector of the line connecting the two fixer models.

[0007] Furthermore, calculating the required vertical downward displacement of the pressure block model based on the target bending radius and the fixer span parameter includes: The span parameter of the fixer is defined as the chord length of the virtual circle, and the target bending radius is defined as the radius of the virtual circle; Based on the Pythagorean theorem, calculate the perpendicular distance from the center of the virtual circle to the chord length of the virtual circle; Calculate the difference between the radius of the virtual circle and the vertical distance, and determine the difference as the vertical downward displacement.

[0008] Furthermore, the required vertical downward displacement of the compaction block model is calculated using the following formula: In the formula, This indicates the vertical downward displacement. Indicates the target bending radius. This indicates the span parameter of the fastener.

[0009] Furthermore, based on the vertical downward displacement, and with the goal that the result of each iteration of the solution is a state of force equilibrium, iterative solution calculations are performed on the model to be solved to generate simulation calculation results containing stress data, including: Establish a displacement loading mapping relationship that monotonically increases from zero to the vertical downward displacement over time; Establish a stiffness decay mapping relationship that monotonically decays to zero over time from the initial high stiffness value; Repeat the model solving operation until the current cumulative time variable equals the preset total simulation time, and generate the simulation calculation results; The model solving operation includes: The displacement loading value corresponding to the current cumulative time variable is matched from the displacement loading mapping relationship, and the loading boundary of the block model is updated to the displacement loading value; wherein, the initial cumulative time variable is a preset time step; Match the stiffness coefficient value corresponding to the current cumulative time variable from the stiffness attenuation mapping relationship, and update the stiffness attribute of the virtual spring base to the stiffness coefficient value; Based on the loading boundary and the stiffness property, force balance calculation is performed on the model to be solved to generate the insulation layer stress data corresponding to the current cumulative time variable; If the current cumulative time variable is equal to the preset total simulation duration, the insulation layer stress data corresponding to the current cumulative time variable will be used as the simulation calculation result. If the current cumulative time variable is not equal to the preset total simulation duration, calculate the sum of the current cumulative time variable and the time step, and update the current cumulative time variable with the calculation result.

[0010] Furthermore, the step of extracting the stress data corresponding to the attenuation of the stiffness coefficient value of the virtual spring base to zero from the simulation calculation results, and generating a stress distribution cloud map of the insulation layer under the target bending radius based on the extracted stress data, includes: Analyze the simulation results and extract the nodal stress values ​​of each finite element mesh node in the insulation layer model; Establish a visual mapping rule between stress values ​​and display colors; wherein, the visual mapping rule defines the correspondence between different stress value ranges and different color levels; Based on the node stress values ​​and the visual mapping rules, the rendering color of each finite element mesh node is determined. The geometric surface of the insulation layer model is interpolated and rendered using the rendering color to generate a visualized insulation layer stress distribution cloud map.

[0011] Based on the above method embodiments, the present invention provides corresponding apparatus embodiments.

[0012] An embodiment of the present invention provides a device for generating a dynamic bending stress distribution cloud map of submarine cable insulation, comprising: a parameter acquisition module, a model construction module, a displacement calculation module, a simulation control module, and a cloud map generation module; The parameter acquisition module is used to acquire the geometric dimension parameters, target bending radius, and preset fixture span parameters of the insulation layer of the dynamic submarine cable under test. The model building module is used to establish a finite element simulation model based on geometric dimension parameters and fixture span parameters, including an insulation layer model, two fixture models, and a pressure block model. The insulation layer model is horizontally mounted above the two fixture models, and the pressure block model is located at the mid-span position above the insulation layer model. The module establishes the contact connection relationships between the insulation layer model and the pressure block model and the two fixture models in the finite element simulation model, and applies a virtual spring base with a variable stiffness coefficient to the insulation layer model to generate the model to be solved. The displacement calculation module is used to calculate the required vertical downward displacement of the pressure block model based on the target bending radius and the span parameter of the fastener. The simulation control module is used to perform iterative calculations on the model to be solved based on the vertical downward displacement, with the goal that the result of each iteration of the calculation is a state of force equilibrium, and generate simulation calculation results containing stress data; wherein, during the process of performing iterative calculations on the model to be solved, the displacement loading value of the pressure block model in the model to be solved is driven to increase from zero to the vertical downward displacement, and the stiffness coefficient value of the virtual spring base is simultaneously reduced from the preset initial high stiffness value to zero; The cloud map generation module is used to extract the stress data corresponding to the attenuation of the stiffness coefficient value of the virtual spring base to zero from the simulation calculation results, and generate a cloud map of the insulation layer stress distribution under the target bending radius based on the extracted stress data.

[0013] Furthermore, the model building module includes: an insulation layer model building unit, a fastener model building unit, and a pressure block model building unit; The insulation layer model construction unit is used to construct a cylindrical geometric body as an insulation layer model based on the insulation layer outer diameter, insulation layer thickness and insulation layer axial length in the geometric dimension parameters. The fixture model construction unit is used to construct two rigid bodies with the same structure as two fixture models according to the preset fixture geometric parameters, and to arrange the two fixture models at intervals in the horizontal direction, and to set the horizontal distance between the central axes of the two fixture models to be equal to the fixture span parameter. The block model construction unit is used to construct a rigid body as a block model according to the preset block geometry parameters, and to set the loading center axis of the block model on the perpendicular bisector of the line connecting the two fixer models.

[0014] Based on the above method embodiments, the present invention provides corresponding electronic device embodiments.

[0015] An embodiment of the present invention provides an electronic device, including a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor. When the processor executes the computer program, it implements the method for generating a dynamic submarine cable insulation layer bending stress distribution cloud map as described in any of the above-described method embodiments.

[0016] Based on the above method embodiments, the present invention provides corresponding storage medium embodiments.

[0017] An embodiment of the present invention provides a storage medium storing a computer program thereon, wherein, when the computer program is running, it controls the device where the storage medium is located to execute the method for generating a dynamic submarine cable insulation layer bending stress distribution cloud map as described in any of the above-described method embodiments.

[0018] Compared with the prior art, the present invention has the following beneficial effects: This invention provides a method, apparatus, electronic device, and storage medium for generating dynamic bending stress distribution cloud maps of submarine cable insulation layers. The method obtains the geometric dimensions, target bending radius, and preset fixture span parameters of the insulation layer of the dynamic submarine cable under test. Based on the geometric dimensions and fixture span parameters, a finite element simulation model is constructed, including an insulation layer model, two fixture models, and a pressure block model located at the mid-span. The contact connection between the insulation layer model, the pressure block model, and the fixture models is established in the simulation model. Simultaneously, a virtual spring base with a variable stiffness coefficient is applied to the insulation layer model. The vertical downward displacement of the pressure block model is calculated based on the target bending radius and fixture span parameters. As the displacement loading value of the pressure block model gradually increases from zero to the vertical downward displacement, and the stiffness coefficient of the virtual spring base synchronously decreases from a preset initial high stiffness value to zero, iterative solution calculations are performed on the model to be solved with force balance as the objective, generating simulation calculation results containing stress data. The stress data corresponding to the decrease in the stiffness coefficient of the virtual spring base to zero is extracted from the simulation calculation results, and a stress distribution cloud map of the insulation layer under the target bending radius is generated accordingly.

[0019] This invention establishes a synchronous evolution mechanism between displacement loading and virtual spring stiffness decay during the iterative solution process. In the initial loading stage, the undecayed initial high stiffness value fills the contact gap, thus constructing temporary elastic boundary conditions for the under-constrained model. This effectively suppresses rigid body displacement and stiffness matrix singularities caused by under-constraint, ensuring computational convergence. Simultaneously, as the contact relationship is gradually established, the invention drives the stiffness coefficient value to decay synchronously to zero. This allows the auxiliary constraint force provided by the virtual base to be gradually replaced by the real contact reaction force as the stiffness decreases, achieving a smooth transition from "virtual constraint" to "real contact." This ensures that artificially introduced constraint forces are completely eliminated during final data extraction, resulting in a pure, interference-free, and realistic insulation layer stress distribution cloud map. Attached Figure Description

[0020] Figure 1 This is a flowchart illustrating a method for generating a dynamic bending stress distribution cloud map of a submarine cable insulation layer according to an embodiment of the present invention.

[0021] Figure 2 This is a schematic diagram of a device for generating a dynamic bending stress distribution cloud map of a submarine cable insulation layer, according to an embodiment of the present invention. Detailed Implementation

[0022] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0023] like Figure 1 As shown, to address the problem in existing technologies where numerical simulations of submarine cable insulation bending conditions struggle to balance computational convergence stability and stress result accuracy, an embodiment of the present invention provides a method for generating dynamic bending stress distribution cloud maps of submarine cable insulation, comprising at least the following steps: Step S1: Obtain the geometric dimensions, target bending radius, and preset fixture span parameters of the insulation layer of the dynamic submarine cable under test; Specifically, in the method for generating the bending stress distribution cloud map of the dynamic submarine cable insulation layer, the first step is to determine the basic input data for simulation analysis, i.e., to perform parameter acquisition. The geometrical parameters of the insulation layer of the dynamic submarine cable under test include the outer diameter, thickness, and axial length of the insulation layer. The outer diameter refers to the outer contour diameter of the cross-section of the cable insulation layer, the thickness refers to the radial thickness of the insulation layer wall, and the axial length determines the longitudinal span of the constructed finite element model. These geometrical parameters are typically derived from the design drawings of the submarine cable product or obtained through physical measurements of actual submarine cable samples to ensure that the subsequently established finite element model can accurately reproduce the geometric characteristics of the real submarine cable insulation layer.

[0024] Simultaneously, to simulate specific bending conditions, a target bending radius needs to be obtained. The target bending radius represents the desired final bending degree of the submarine cable insulation layer in the simulation experiment; this value is typically set based on submarine cable testing standards or the minimum bending radius requirements in actual engineering. Furthermore, the preset fixture span parameter corresponds to the horizontal distance between the two bottom support structures in a physical bending test. The fixture span parameter and the target bending radius together determine the depth to which the pressure block model needs to be pressed down during loading, and are key variables in defining the simulation boundary conditions.

[0025] By accurately obtaining the aforementioned geometric dimensions, target bending radius, and fixture span parameters, necessary data support can be provided for the subsequent construction of a high-fidelity finite element simulation model and the calculation of accurate loading displacement, thereby ensuring the consistency between the simulation environment and the actual physical conditions and laying the foundation for solving the convergence problem in numerical simulation.

[0026] Step S2: Based on the geometric dimensions and the span parameters of the fixtures, establish a finite element simulation model that includes an insulation layer model, two fixture models, and a pressure block model. The insulation layer model is horizontally mounted above the two fixture models, and the pressure block model is located at the mid-span position above the insulation layer model. Establish the contact connection relationship between the insulation layer model and the pressure block model and the two fixture models in the finite element simulation model, and apply a virtual spring base with a variable stiffness coefficient to the insulation layer model to generate the model to be solved. In a preferred embodiment, the geometric parameters include the outer diameter of the insulating layer, the thickness of the insulating layer, and the axial length of the insulating layer; The finite element simulation model, based on geometric dimensions and clamp span parameters, includes an insulation layer model, two clamp models, and a pressure block model. Based on the outer diameter, thickness, and axial length of the insulation layer in the geometric parameters, a circular tubular geometry is constructed as the insulation layer model. Based on the preset fixture geometry parameters, two rigid bodies with the same structure are constructed as two fixture models, and the two fixture models are arranged at intervals in the horizontal direction. The horizontal distance between the central axes of the two fixture models is set to be equal to the fixture span parameter. Based on the preset geometric parameters of the pressure block, a rigid body is constructed as the pressure block model, and the loading center axis of the pressure block model is set on the perpendicular bisector of the line connecting the two fixer models.

[0027] Specifically, based on the acquired geometric parameters and the preset fixture span parameters, a finite element simulation model is constructed. The geometric parameters include the outer diameter, thickness, and axial length of the insulation layer. The outer diameter defines the external contour dimensions of the model's cross-section, the thickness defines the solid region of the tube wall, and the axial length determines the longitudinal range of the simulation computation domain. During the modeling process, based on the outer diameter, thickness, and axial length data of the insulation layer, a cylindrical geometry is constructed using finite element preprocessing functions. This cylindrical geometry is defined as the insulation layer model to digitally reconstruct the physical morphology of the submarine cable insulation layer under test. Since the insulation layer is typically made of cross-linked polyethylene or other polymer materials, the insulation layer model is usually set as a deformable body to facilitate subsequent calculations of its stress-strain response.

[0028] Specifically, when establishing the insulation layer model, a linear elastic constitutive model or a hyperelastic constitutive model (such as the Mooney-Rivlin model) is adopted based on the mechanical properties of the actual submarine cable insulation material (e.g., cross-linked polyethylene XLPE). In this embodiment, the elastic modulus of the insulation layer is set to 800 MPa to 1200 MPa (e.g., 1000 MPa), and the Poisson's ratio is set to 0.3 to 0.45 (e.g., 0.4). In addition, to ensure the calculation accuracy under large bending deformation conditions and to avoid shear self-locking, a three-dimensional linear reduced integral hexahedral element (e.g., C3D8R element) is used to discretize the insulation layer model, and at least three mesh layers are divided in the thickness direction to ensure that the stress gradient changes during the bending process can be accurately captured. Furthermore, since significant stress concentration zones will appear on the compression and tension sides of the submarine cable insulation layer under bending conditions, the insulation layer model is not only divided into layers in the thickness direction, but also uniformly discretized in the circumferential direction, for example, into 36 to 72 elements. In the mid-span region of the axial direction, i.e., the area of ​​most intense pressure and contact, the mesh is locally refined. By controlling the aspect ratio of the mesh to be close to 1:1:1, the accuracy of calculating local contact stress and penetration is further improved.

[0029] Meanwhile, to simulate the constraint and loading effect of the experimental fixture on the insulation layer, a corresponding fixture model needs to be constructed. Based on the preset fixture geometry parameters, two identical rigid bodies are constructed and defined as two fixture models. Considering that the elastic modulus of the fixture material (such as steel) is much greater than that of the insulation layer material, the fixture models are set as discrete or analytical rigid bodies, thus ignoring the deformation of the fixture models themselves and improving computational efficiency. The two fixture models are arranged horizontally at intervals, and their spatial coordinates are adjusted so that the horizontal distance between the central axes of the two fixture models is strictly equal to the fixture span parameter, thereby replicating the support span of the real test bench. Furthermore, based on the preset pressure block geometry parameters, a rigid body is constructed as the pressure block model, and the loading center axis of the pressure block model is precisely set on the perpendicular bisector of the line connecting the two fixture models, ensuring that the subsequent loading process meets the geometric symmetry requirement of three-point bending.

[0030] After completing the geometric assembly of all components, the insulation layer model is horizontally mounted above the two fixture models, with the pressure block model positioned at the mid-span above the insulation layer model. At this point, the physical interactions between the components are further defined in the finite element simulation model. Specifically, contact connections are established between the insulation layer model and the pressure block model, and between the insulation layer model and the two fixture models. In the contact property settings, the outer surface of the insulation layer model (with lower hardness) is selected as the slave surface, and the outer surfaces of the pressure block model and the fixture models (with higher hardness) are selected as the master surfaces. Contact pairs are then constructed based on the master and slave surfaces. This contact connection allows the transmission of normal pressure and tangential friction between the contact surfaces, while preventing slave surface nodes from penetrating the master surface mesh.

[0031] When defining the contact connection, the relative sliding behavior between the insulating layer surface and the metal tooling surface is taken into account, and the penalty method or kinematic contact algorithm is used to handle the tangential contact behavior. The tangential friction coefficient is set to 0.1 to 0.3 (e.g., 0.2) to simulate the real surface friction effect; at the same time, a "hard contact" setting is adopted for the normal behavior, allowing the contact surface to transmit pressure under compression and zero pressure when separated under tension.

[0032] To address the computational divergence problem that may arise from the insulation layer model being underconstrained during the initial loading phase, a virtual spring base with a variable stiffness coefficient is applied to the insulation layer model before generating the solution model. The virtual spring base is not a real physical component, but rather a boundary condition constraint attached to specific nodes or surfaces of the insulation layer model. The virtual spring base is configured to have stiffness properties that change with the analysis step time or incremental step. During the model construction phase, the evolution rule of this stiffness coefficient is predefined, enabling it to provide high stiffness support initially and gradually decrease as the loading process progresses.

[0033] In practice, the virtual spring base can be implemented by creating grounding spring elements (Spring1 or Ground Spring) connecting the nodes of the insulation layer model to the ground in finite element software, or by applying an elastic foundation property to the outer surface of the insulation layer model. The initial high stiffness value is set according to the principle of being sufficient to limit the rigid body displacement of the insulation layer model, but much smaller than the structural stiffness of the insulation material itself, to avoid causing excessive numerical singularities. For example, the initial high stiffness value can be set from 1 N / mm to 100 N / mm.

[0034] The model to be solved constructed through the above steps not only restores the geometric and contact nonlinear characteristics of the submarine cable insulation bending test, but also effectively suppresses the rigid body displacement of the model before the contact relationship is established and stabilized by introducing a virtual spring base, thus eliminating the singularity of the stiffness matrix and ensuring the convergence and stability of the subsequent nonlinear iterative solution process.

[0035] Step S3: Calculate the required vertical downward displacement of the pressure block model based on the target bending radius and the span parameter of the fixer; In a preferred embodiment, calculating the required vertical downward displacement of the pressure block model based on the target bending radius and the fixer span parameter includes: The span parameter of the fixer is defined as the chord length of the virtual circle, and the target bending radius is defined as the radius of the virtual circle; Based on the Pythagorean theorem, calculate the perpendicular distance from the center of the virtual circle to the chord length of the virtual circle; Calculate the difference between the radius of the virtual circle and the vertical distance, and determine the difference as the vertical downward displacement.

[0036] In a preferred embodiment, the required vertical downward displacement of the compaction block model is calculated using the following formula: In the formula, This indicates the vertical downward displacement. Indicates the target bending radius. This represents the span parameter of the fixation device. The vertical downward displacement calculated using the above formula can be used as a clear displacement boundary condition input into the subsequent iterative solution process, thereby ensuring that the finite element simulation model can accurately achieve the expected bending shape at the end of loading, and avoiding simulation results that do not meet the target curvature requirements due to deviations in loading displacement estimation.

[0037] Specifically, after constructing the model to be solved, the calculation stage for the loading boundary conditions begins. Specifically, based on the target bending radius and the span parameters of the fixer, the required vertical downward displacement of the pressure block model is calculated. The core of this step is to establish the geometric correspondence between the actual bending condition and the displacement loading of the finite element model, ensuring that the simulation loading process can accurately simulate the preset degree of bending.

[0038] In a preferred embodiment, a virtual geometry construction method is used to determine the vertical downward displacement. The fixer span parameter is defined as the chord length of a virtual circle, which corresponds to the horizontal distance between the support points of the two fixer models; simultaneously, the target bending radius is defined as the radius of the virtual circle, which represents the radius of curvature of the submarine cable insulation layer under ideal bending conditions. A right-angled triangle geometry is constructed based on the Pythagorean theorem, where the radius of the virtual circle forms the hypotenuse of the right-angled triangle, and half the chord length of the virtual circle forms the right-angled base. The vertical distance from the center of the virtual circle to the chord length of the virtual circle is calculated using the Pythagorean theorem. Subsequently, the difference between the radius of the virtual circle and the vertical distance is calculated, and this difference is determined as the required vertical downward displacement of the pressure block model. This calculation logic, based on the geometric symmetry of three-point bending, can accurately derive the travel required for the pressure block model to reach the target bending state from the initial contact position.

[0039] Step S4: Based on the vertical downward displacement, with the goal that the result of each iteration of the calculation is a state of force equilibrium, perform iterative calculation on the model to be solved to generate simulation calculation results containing stress data; wherein, during the iterative calculation of the model to be solved, the displacement loading value of the pressure block model in the model to be solved is increased from zero to the vertical downward displacement, and the stiffness coefficient value of the virtual spring base is simultaneously reduced from the preset initial high stiffness value to zero; In a preferred embodiment, the step of performing iterative solution calculations on the model to be solved based on the vertical downward displacement, with the goal of ensuring that the result of each iteration of the solution calculation is a state of force equilibrium, and generating simulation calculation results containing stress data, includes: Establish a displacement loading mapping relationship that monotonically increases from zero to the vertical downward displacement over time; Establish a stiffness decay mapping relationship that monotonically decays to zero over time from the initial high stiffness value; Repeat the model solving operation until the current cumulative time variable equals the preset total simulation time, and generate the simulation calculation results; The model solving operation includes: The displacement loading value corresponding to the current cumulative time variable is matched from the displacement loading mapping relationship, and the loading boundary of the block model is updated to the displacement loading value; wherein, the initial cumulative time variable is a preset time step; Match the stiffness coefficient value corresponding to the current cumulative time variable from the stiffness attenuation mapping relationship, and update the stiffness attribute of the virtual spring base to the stiffness coefficient value; Based on the loading boundary and the stiffness property, force balance calculation is performed on the model to be solved to generate the insulation layer stress data corresponding to the current cumulative time variable; If the current cumulative time variable is equal to the preset total simulation duration, the insulation layer stress data corresponding to the current cumulative time variable will be used as the simulation calculation result. If the current cumulative time variable is not equal to the preset total simulation duration, calculate the sum of the current cumulative time variable and the time step, and update the current cumulative time variable with the calculation result.

[0040] Specifically, based on the calculated vertical downward displacement, the process enters the iterative solution stage of the finite element solver. In this stage, with the goal of achieving a force equilibrium state in each iteration, nonlinear iterative calculations are performed on the model to be solved, generating simulation results containing stress data. To address the rigid body displacement divergence problem caused by under-constraint in the initial loading stage of the insulation layer model, and to ensure that the final results are not affected by artificial constraints, a synchronous evolution strategy is adopted during the iterative solution calculation of the model to be solved: on the one hand, the displacement loading value of the pressure block model in the model to be solved is driven to gradually increase from zero to the vertical downward displacement; on the other hand, the stiffness coefficient value of the virtual spring base is synchronously controlled to gradually decrease from a preset initial high stiffness value to zero.

[0041] In a preferred embodiment, the above iterative solution process is implemented by establishing a clear time mapping relationship. First, a displacement loading mapping relationship is established, which monotonically increases from zero to the vertical downward displacement over time; this displacement loading mapping relationship defines the evolution path of the compression depth of the block model as the simulation progresses, ensuring a smooth loading process. Simultaneously, a stiffness decay mapping relationship is established, which monotonically decays from the initial high stiffness value to zero over time; this stiffness decay mapping relationship defines the degradation path of the virtual spring base's support capacity as the simulation progresses. The initial high stiffness value is set to provide sufficient spurious constraints to the insulation layer model to resist rigid body displacement in the early stages of the simulation, while setting the final value to zero aims to completely eliminate this spurious constraint at the end of the simulation.

[0042] In a finite element method (FEM) solver, the displacement loading mapping and stiffness decay mapping are typically implemented by defining time-amplitude curves. Specifically, a first amplitude curve (Amp_Displacement) is established, whose ordinate value increases linearly from 0 to 1 with each time step, and is associated with the displacement boundary conditions of the compaction block model; a second amplitude curve (Amp_Stiffness) is established, whose ordinate value decreases linearly from 1 to 0 with each time step, and is associated with the stiffness properties of the virtual spring base. During the solution process, the solver automatically queries the amplitude coefficient corresponding to the current time at each increment step and multiplies it by a preset baseline value, thereby achieving synchronous control of loading and decay.

[0043] Subsequently, the model solving operation is repeated until the current cumulative time variable equals the preset total simulation duration. This model solving operation discretizes the continuous physical process into a series of time steps. The specific execution logic is as follows: First, the current cumulative time variable is determined. Upon entering the loop for the first time, the initial cumulative time variable is set to the preset time step. Next, based on the current cumulative time variable, the corresponding displacement loading value is matched from the displacement loading mapping relationship, and the loading boundary conditions of the block model are updated to this displacement loading value, thereby driving the block model to move downwards. Simultaneously, based on the current cumulative time variable, the corresponding stiffness coefficient value is matched from the stiffness decay mapping relationship, and the stiffness attribute parameters of the virtual spring base are updated to this stiffness coefficient value, thereby dynamically adjusting the strength of the auxiliary support.

[0044] After updating the boundary conditions and material properties, the Newton-Raphson algorithm of the finite element solver is used to perform force equilibrium calculations on the model to be solved based on the updated loading boundary and stiffness properties. The solver continuously corrects the nodal displacements until the internal and external forces are in equilibrium, thereby generating the insulation layer stress data corresponding to the current cumulative time variable. Specifically, the determination of the force equilibrium state depends on a preset quantization convergence criterion. In each nonlinear iteration step, the solver calculates the unbalanced force vector between the external nodal force vector caused by the external load and the internal nodal force vector generated by the internal stress. The system determines that the current iteration step has strictly reached the force equilibrium state only when the norm of the unbalanced force vector is less than the specific tolerance of the average force generated by the stiffness update in the previous increment step, and / or the correction amount of the nodal displacement is less than the specific tolerance of the total displacement increment, thus ensuring the accuracy of the numerical solution. After each balancing calculation, the current cumulative time variable is evaluated: if the current cumulative time variable equals the preset total simulation time, it indicates that the loading process is complete and the virtual spring stiffness has completely decayed to zero. In this case, the insulation layer stress data corresponding to the current cumulative time variable is output as the final simulation result. If the current cumulative time variable does not equal the preset total simulation time, a time stepping operation is performed, calculating the sum of the current cumulative time variable and the preset time step, and updating the current cumulative time variable with the calculated sum. Then, the next round of model solving is initiated. In practical applications, considering the strong nonlinearity that may be caused by large deformations and drastic changes in contact state, the preset time step preferably adopts an adaptive step size control strategy. That is, when the Newton-Raphson iteration fails to meet the convergence criterion within the preset maximum number of iterations, the solver will automatically reduce the current time step, for example, to 25% or 50% of the current step, and re-execute the balancing calculation. Conversely, if multiple consecutive incremental steps converge quickly, the time step is appropriately increased to maximize the solution efficiency while ensuring the stability of computational convergence.

[0045] Through the above-mentioned iterative solution process of synchronous evolution, this application can ensure the convergence of calculation by using a high-stiffness virtual spring in the early stage when the insulation layer model has not yet established a stable contact, and gradually eliminate the influence of the virtual spring in the later stage of loading after the contact is established. Thus, while ensuring the stability of the simulation process, it ensures that the stress data obtained in the end is pure and truly reflects the stress state of the insulation layer.

[0046] Step S5: Extract the stress data corresponding to the attenuation of the stiffness coefficient value of the virtual spring base to zero from the simulation calculation results, and generate a stress distribution cloud map of the insulation layer under the target bending radius based on the extracted stress data.

[0047] In a preferred embodiment, the step of extracting the stress data corresponding to the attenuation of the stiffness coefficient value of the virtual spring base to zero from the simulation calculation results, and generating a stress distribution cloud map of the insulation layer under the target bending radius based on the extracted stress data, includes: Analyze the simulation results and extract the nodal stress values ​​of each finite element mesh node in the insulation layer model; Establish a visual mapping rule between stress values ​​and display colors; wherein, the visual mapping rule defines the correspondence between different stress value ranges and different color levels; Based on the node stress values ​​and the visual mapping rules, the rendering color of each finite element mesh node is determined. The geometric surface of the insulation layer model is interpolated and rendered using the rendering color to generate a visualized insulation layer stress distribution cloud map.

[0048] Specifically, after the iterative solution process is complete, the finite element simulation software outputs a simulation result file containing the entire loading history. To obtain a realistic mechanical response free from artificial constraints, post-processing is required. This involves extracting the stress data corresponding to the point where the stiffness coefficient of the virtual spring base decays to zero from the simulation results. Since the stiffness coefficient of the virtual spring base decays synchronously with time during the simulation, the moment when the stiffness coefficient decays to zero signifies that the auxiliary virtual constraints have been completely removed, and the insulation layer model remains in equilibrium only under real contact constraints. The extracted stress data at this point accurately reflects the true stress state of the insulation layer at the target bending radius, eliminating the influence of the spurious support reaction force introduced by the virtual spring on the accuracy of the results. Subsequently, a stress distribution cloud map of the insulation layer at the target bending radius is generated based on the extracted stress data, allowing technicians to visually assess the stress concentration areas and peak values ​​of the insulation layer.

[0049] In a preferred embodiment, the above-described contour map generation process involves a complete technical path from underlying numerical analysis to graphical rendering. First, a post-processing program analyzes the simulation results, reads a database file containing the model's physical field information, and extracts the nodal stress values ​​of each finite element mesh node in the insulation layer model. These nodal stress values ​​typically refer to the nodal von Mises stress or principal stress values ​​after extrapolation and averaging through element integration points, forming the basic data source for contour map rendering.

[0050] Subsequently, to transform abstract numerical values ​​into visualized images, a visual mapping rule was established between stress values ​​and display colors. This visual mapping rule is essentially a color lookup table, defining the correspondence between different stress value ranges and different color gradations. For example, high stress value ranges are mapped to warm colors (such as red), low stress value ranges are mapped to cool colors (such as blue), and intermediate transitional color gradations are set, thus establishing an intuitive index logic of "value-color".

[0051] When establishing the visual mapping rule, the system first traverses the extracted set of node stress values, searches for and determines the maximum and minimum stress values, and uses these as the dynamic upper and lower limits of the color lookup table. Then, the numerical range between the maximum and minimum stress values ​​is divided into several sub-ranges (e.g., 10 or 12 sub-ranges), and each sub-range is assigned a corresponding discrete color level or continuous gradient color to ensure that the stress cloud map under different size parameters or bending conditions has the best visual contrast and recognizability that is automatically adapted.

[0052] Next, based on the extracted nodal stress values ​​and the preset visual mapping rules, the rendering color of each finite element mesh node on the insulation layer model is determined one by one. The system will traverse each mesh node, query which value range of the visual mapping rules the stress value of the node falls into, and assign the corresponding RGB color value to the node accordingly.

[0053] Finally, the geometric surface of the insulation layer model is interpolated and rendered using the determined rendering colors. Since the finite element mesh is discrete, a graphics interpolation algorithm (such as the Glaude shading method) is used to calculate the pixel colors within the mesh cells to achieve a smooth transition of color between mesh nodes, thereby generating a visualized insulation layer stress distribution cloud map. Through these post-processing techniques, complex tensor calculation results can be transformed into easily understandable color cloud maps, effectively assisting engineers in quickly identifying potential failure risk points of the submarine cable insulation layer under dynamic bending conditions.

[0054] Based on the above method embodiments, the present invention provides corresponding apparatus embodiments.

[0055] like Figure 2 As shown, an embodiment of the present invention provides a device for generating a dynamic bending stress distribution cloud map of submarine cable insulation, including: a parameter acquisition module, a model construction module, a displacement calculation module, a simulation control module, and a cloud map generation module; The parameter acquisition module is used to acquire the geometric dimension parameters, target bending radius, and preset fixture span parameters of the insulation layer of the dynamic submarine cable under test. The model building module is used to establish a finite element simulation model based on geometric dimension parameters and fixture span parameters, including an insulation layer model, two fixture models, and a pressure block model. The insulation layer model is horizontally mounted above the two fixture models, and the pressure block model is located at the mid-span position above the insulation layer model. The module establishes the contact connection relationships between the insulation layer model and the pressure block model and the two fixture models in the finite element simulation model, and applies a virtual spring base with a variable stiffness coefficient to the insulation layer model to generate the model to be solved. The displacement calculation module is used to calculate the required vertical downward displacement of the pressure block model based on the target bending radius and the span parameter of the fastener. The simulation control module is used to perform iterative calculations on the model to be solved based on the vertical downward displacement, with the goal that the result of each iteration of the calculation is a state of force equilibrium, and generate simulation calculation results containing stress data; wherein, during the process of performing iterative calculations on the model to be solved, the displacement loading value of the pressure block model in the model to be solved is driven to increase from zero to the vertical downward displacement, and the stiffness coefficient value of the virtual spring base is simultaneously reduced from the preset initial high stiffness value to zero; The cloud map generation module is used to extract the stress data corresponding to the attenuation of the stiffness coefficient value of the virtual spring base to zero from the simulation calculation results, and generate a cloud map of the insulation layer stress distribution under the target bending radius based on the extracted stress data.

[0056] In a preferred embodiment, the geometric parameters of the model building module include the outer diameter of the insulating layer, the thickness of the insulating layer, and the axial length of the insulating layer. Based on geometric dimensions and clamp span parameters, a finite element simulation model was established, including an insulation layer model, two clamp models, and a pressure block model, comprising: Based on the outer diameter, thickness, and axial length of the insulation layer in the geometric parameters, a circular tubular geometry is constructed as the insulation layer model. Based on the preset fixture geometry parameters, two rigid bodies with the same structure are constructed as two fixture models, and the two fixture models are arranged at intervals in the horizontal direction. The horizontal distance between the central axes of the two fixture models is set to be equal to the fixture span parameter. Based on the preset geometric parameters of the pressure block, a rigid body is constructed as the pressure block model, and the loading center axis of the pressure block model is set on the perpendicular bisector of the line connecting the two fixer models.

[0057] In a preferred embodiment, the displacement calculation module calculates the required vertical downward displacement of the pressure block model based on the target bending radius and the fixer span parameter, including: The span parameter of the fixer is defined as the chord length of the virtual circle, and the target bending radius is defined as the radius of the virtual circle; Based on the Pythagorean theorem, calculate the perpendicular distance from the center of the virtual circle to the chord length of the virtual circle; Calculate the difference between the radius of the virtual circle and the vertical distance, and determine the difference as the vertical downward displacement.

[0058] In a preferred embodiment, the displacement calculation module calculates the required vertical downward displacement of the block model using the following formula: In the formula, This indicates the vertical downward displacement. Indicates the target bending radius. This indicates the span parameter of the fastener.

[0059] In a preferred embodiment, the simulation control module, based on the vertical downward displacement, and aiming that the result of each iteration of the calculation is a state of force equilibrium, performs iterative calculations on the model to be solved, generating simulation calculation results containing stress data, including: Establish a displacement loading mapping relationship that monotonically increases from zero to the vertical downward displacement over time; Establish a stiffness decay mapping relationship that monotonically decays to zero over time from the initial high stiffness value; Repeat the model solving operation until the current cumulative time variable equals the preset total simulation time, and generate the simulation calculation results; The model solving operation includes: The displacement loading value corresponding to the current cumulative time variable is matched from the displacement loading mapping relationship, and the loading boundary of the block model is updated to the displacement loading value; wherein, the initial cumulative time variable is a preset time step; Match the stiffness coefficient value corresponding to the current cumulative time variable from the stiffness attenuation mapping relationship, and update the stiffness attribute of the virtual spring base to the stiffness coefficient value; Based on the loading boundary and the stiffness property, force balance calculation is performed on the model to be solved to generate the insulation layer stress data corresponding to the current cumulative time variable; If the current cumulative time variable is equal to the preset total simulation duration, the insulation layer stress data corresponding to the current cumulative time variable will be used as the simulation calculation result. If the current cumulative time variable is not equal to the preset total simulation duration, calculate the sum of the current cumulative time variable and the time step, and update the current cumulative time variable with the calculation result.

[0060] In a preferred embodiment, the cloud map generation module extracts the stress data corresponding to the attenuation of the stiffness coefficient value of the virtual spring base to zero from the simulation calculation results, and generates a cloud map of the insulation layer stress distribution under the target bending radius based on the extracted stress data, including: Analyze the simulation results and extract the nodal stress values ​​of each finite element mesh node in the insulation layer model; Establish a visual mapping rule between stress values ​​and display colors; wherein, the visual mapping rule defines the correspondence between different stress value ranges and different color levels; Based on the node stress values ​​and the visual mapping rules, the rendering color of each finite element mesh node is determined. The geometric surface of the insulation layer model is interpolated and rendered using the rendering color to generate a visualized insulation layer stress distribution cloud map.

[0061] Specifically, this invention provides a device for generating a dynamic bending stress distribution cloud map of submarine cable insulation. The device includes a parameter acquisition module, a model construction module, a displacement calculation module, a simulation control module, and a cloud map generation module. The parameter acquisition module is configured to perform basic data receiving operations, specifically responsible for reading the geometric dimensions of the insulation layer of the dynamic submarine cable under test, the preset target bending radius, and the pre-set fixture span parameters. By reading the input information through the parameter acquisition module, an accurate numerical basis can be provided for subsequently establishing the geometric boundary conditions and physical constraints for finite element simulation analysis.

[0062] The model building module is responsible for assembling a finite element simulation model, including an insulation layer model, two fixture models, and a pressure block model, within a computer virtual workspace based on the received geometric dimension parameters and fixture span parameters. In a specific implementation scenario, the geometric dimension parameters encompass the outer diameter, thickness, and axial length of the insulation layer. The model building module generates a cylindrical three-dimensional solid geometry based on the actual physical values ​​of the insulation layer's outer diameter, thickness, and axial length, defining this cylindrical three-dimensional solid geometry as the insulation layer model. Simultaneously, combining the preset fixture geometric parameters, it generates two rigid body components with identical shapes as two fixture models. These two fixture models are placed spaced apart along a horizontal baseline, ensuring that the horizontal distance between the central axes of the two fixture models equals the input value of the fixture span parameter. Further combining the preset pressure block geometric parameters, it generates a rigid body component as the pressure block model, precisely setting the loading center axis of the pressure block model so that it coincides with the perpendicular bisector of the line connecting the two fixture models. In terms of spatial assembly, the model building module horizontally places the insulation layer model above the two fixture models, allowing the pressure block model to hover at the mid-span position directly above the insulation layer model. After completing the alignment, the model building module establishes contact connections between the outer surface of the insulation layer model and the outer surfaces of the pressure block model and the two fixture models, respectively, and adds a virtual spring base with a variable stiffness coefficient to the insulation layer model, thereby outputting a complete model to be solved.

[0063] The displacement calculation module is used to transform physical bending parameters into spatial motion boundary conditions required by the simulation software. Specifically, the displacement calculation module calculates the vertical downward displacement required to drive the pressure block model based on the target bending radius and the fixer span parameter. During the geometric calculation operation, the displacement calculation module maps the fixer span parameter to the length of a chord of a virtual circle, and simultaneously maps the target bending radius to the radius of the virtual circle. Using the geometric logic of the Pythagorean theorem, the displacement calculation module uses the radius of the virtual circle and half the length of its chord as the hypotenuse and base of a right triangle, respectively, to calculate the vertical distance from the center of the virtual circle to its chord. Finally, the displacement calculation module calculates the numerical difference between the radius of the virtual circle and the vertical distance, and directly establishes this difference as the required vertical downward displacement of the pressure block model. This purely geometric transformation method avoids complex nonlinear estimations, ensuring that the loading stroke of the pressure block model strictly corresponds to the desired bending shape.

[0064] The simulation control module, as the core of the nonlinear analysis, initiates iterative calculations to solve the model based on the vertical downward displacement. The core purpose of the simulation control module is to ensure that the output of each iteration is in a state of strict force equilibrium. Throughout the nonlinear solution process, the simulation control module controls the displacement loading value of the pressure block model to gradually increase from zero to the vertical downward displacement as the simulation time step progresses, while strictly and synchronously controlling the stiffness coefficient value of the virtual spring base to gradually decrease from a preset initial high stiffness value to zero. Specifically, the simulation control module constructs a displacement loading mapping relationship that monotonically increases from zero to the vertical downward displacement as the simulation time progresses, and simultaneously constructs a stiffness decay mapping relationship that monotonically decreases from the initial high stiffness value to zero as the simulation time progresses. Subsequently, the model solution operation is repeatedly executed until the current cumulative time variable accumulates to equal the preset total simulation time. In a single model solving operation, the simulation control module uses the current cumulative time variable to consult the displacement loading mapping relationship to obtain the corresponding displacement loading value, updates the loading boundary of the pressure block model with the queried displacement loading value, and sets the initial cumulative time variable to a preset time step. Simultaneously, the simulation control module uses the current cumulative time variable to consult the stiffness attenuation mapping relationship to obtain the corresponding stiffness coefficient value, and updates the physical stiffness property of the virtual spring base with the queried stiffness coefficient value. Based on the updated loading boundary and stiffness properties, the simulation control module initiates the finite element low-level solver to perform force equilibrium calculations and outputs the insulation layer stress data corresponding to the current cumulative time variable. Under the condition that the current cumulative time variable is exactly equal to the preset total simulation duration, the simulation control module will extract the insulation layer stress data corresponding to the current cumulative time variable and use the extracted insulation layer stress data as the final simulation calculation result; if it is found in the numerical comparison that the current cumulative time variable is not equal to the preset total simulation duration, the simulation control module will perform a summation operation on the current cumulative time variable and the time step, and use the result of the summation operation to overwrite and update the current cumulative time variable, and enter the next solution round.

[0065] The cloud map generation module handles data post-processing and visualization. It accurately extracts the pure stress data corresponding to the decrease in stiffness coefficient of the virtual spring base to zero from the simulation results, and renders a cloud map of the insulation layer stress distribution under the target bending radius based on the extracted pure stress data. The specific operation process is as follows: The cloud map generation module reads and parses the simulation result file, extracting the nodal stress values ​​of each finite element mesh node in the mesh structure of the insulation layer model. Next, it establishes a visual mapping rule between the stress value and the display color, using this rule to define the binding correspondence between different stress value ranges and different display color levels. Based on the extracted nodal stress values ​​and the established visual mapping rule, the cloud map generation module determines and assigns values ​​to the rendering colors that each finite element mesh node should present. Finally, using the determined rendering colors, a graphic interpolation rendering algorithm is applied to draw color transitions on the geometrically continuous surface of the insulation layer model, outputting a visually visible insulation layer stress distribution cloud map. By running the provided generation device, numerical singularities generated in the initial loading stage without stable constraints can be completely eliminated. At the same time, it ensures that the stress response data exported at the analysis termination stage does not contain any interference reaction forces caused by false supports, thus achieving the technical effect of balancing computational convergence stability and absolute accuracy of simulation results.

[0066] It should be noted that the embodiments of the device described above correspond to the embodiments of the present invention described above, and can realize the method for generating the dynamic submarine cable insulation layer bending stress distribution cloud map as described in any one of the above embodiments of the present invention. Furthermore, the embodiments of the device described above are merely illustrative. The modules described as separate components may or may not be physically separate, and the components shown as modules may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. In addition, in the accompanying drawings of the device embodiments provided by the present invention, the connection relationship between modules indicates that they have a communication connection, which can be specifically implemented as one or more communication buses or signal lines. Those skilled in the art can understand and implement this without creative effort.

[0067] Based on the above-described method embodiments of the present invention, a corresponding embodiment of an electronic device is provided.

[0068] An embodiment of the present invention provides an electronic device, including a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor. When the processor executes the computer program, it implements the method for generating a dynamic submarine cable insulation layer bending stress distribution cloud map according to any one of the present invention, or, when the processor executes the computer program, it implements the functions of each module in the above-described device embodiments.

[0069] For example, the computer program may be divided into one or more modules, which are stored in the memory and executed by the processor to complete the present invention. The one or more modules may be a series of computer program instruction segments capable of performing specific functions, which describe the execution process of the computer program in the terminal device.

[0070] The terminal device may be a desktop computer, laptop, handheld computer, or cloud server, etc. The terminal device may include, but is not limited to, a processor and a memory.

[0071] The processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor can be a microprocessor or any conventional processor. The processor is the control center of the terminal device, connecting all parts of the terminal device via various interfaces and lines.

[0072] The memory can be used to store the computer programs and / or modules. The processor implements various functions of the terminal device by running or executing the computer programs and / or modules stored in the memory and by calling data stored in the memory. The memory may mainly include a program storage area and a data storage area. The program storage area may store the operating system, applications required for at least one function, etc.; the data storage area may store data created based on the use of the mobile phone, etc. In addition, the memory may include high-speed random access memory, and may also include non-volatile memory, such as hard disk, memory, plug-in hard disk, smart media card (SMC), secure digital card (SD card), flash card, at least one disk storage device, flash memory device, or other volatile solid-state storage device.

[0073] Based on the above method embodiments, the present invention provides corresponding storage medium embodiments; Another embodiment of the present invention provides a storage medium comprising a stored computer program, wherein, when the computer program is executed, the device containing the storage medium is controlled to execute any of the above-described methods for generating a dynamic submarine cable insulation layer bending stress distribution cloud map.

[0074] The aforementioned storage medium is a computer-readable storage medium, and the computer program includes computer program code, which may be in the form of source code, object code, executable file, or certain intermediate forms. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording media, USB flash drive, portable hard drive, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc.

[0075] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of this application. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of those different embodiments or examples.

[0076] The above description represents the preferred embodiments of the present invention. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principles of the present invention, and these improvements and modifications are also considered to be within the scope of protection of the present invention.

Claims

1. A method for generating a dynamic bending stress distribution cloud map of submarine cable insulation, characterized in that, include: Obtain the geometric dimensions, target bending radius, and preset fixture span parameters of the insulation layer of the dynamic submarine cable under test; Based on the geometric dimensions and the span parameters of the fixtures, a finite element simulation model was established, which includes an insulation layer model, two fixture models, and a pressure block model. The insulation layer model is horizontally mounted above the two fixture models, and the pressure block model is located at the mid-span position above the insulation layer model. In the finite element simulation model, the contact connection relationship between the insulation layer model, the pressure block model, and the two fixture models is established, and a virtual spring base with a variable stiffness coefficient is applied to the insulation layer model to generate the model to be solved. Calculate the required vertical downward displacement of the pressure block model based on the target bending radius and the span parameters of the fixer; Based on the vertical downward displacement, with the goal of achieving a force equilibrium state in each iteration, iterative calculations are performed on the model to be solved to generate simulation results containing stress data. During the iterative calculations on the model to be solved, the displacement loading value of the pressure block model in the model to be solved is increased from zero to the vertical downward displacement, and the stiffness coefficient value of the virtual spring base is simultaneously reduced from a preset initial high stiffness value to zero. The stress data corresponding to the attenuation of the stiffness coefficient of the virtual spring base to zero is extracted from the simulation calculation results, and a stress distribution cloud map of the insulation layer under the target bending radius is generated based on the extracted stress data.

2. The method for generating a dynamic bending stress distribution cloud map of submarine cable insulation as described in claim 1, characterized in that, The geometric parameters include the outer diameter of the insulation layer, the thickness of the insulation layer, and the axial length of the insulation layer. The finite element simulation model, based on geometric dimensions and clamp span parameters, includes an insulation layer model, two clamp models, and a pressure block model. Based on the outer diameter, thickness, and axial length of the insulation layer in the geometric parameters, a circular tubular geometry is constructed as the insulation layer model. Based on the preset fixture geometry parameters, two rigid bodies with the same structure are constructed as two fixture models, and the two fixture models are arranged at intervals in the horizontal direction. The horizontal distance between the central axes of the two fixture models is set to be equal to the fixture span parameter. Based on the preset geometric parameters of the pressure block, a rigid body is constructed as the pressure block model, and the loading center axis of the pressure block model is set on the perpendicular bisector of the line connecting the two fixer models.

3. The method for generating a dynamic bending stress distribution cloud map of submarine cable insulation as described in claim 2, characterized in that, The step of calculating the required vertical downward displacement of the pressure block model based on the target bending radius and the span parameter of the fastener includes: The span parameter of the fixer is defined as the chord length of the virtual circle, and the target bending radius is defined as the radius of the virtual circle; Based on the Pythagorean theorem, calculate the perpendicular distance from the center of the virtual circle to the chord length of the virtual circle; Calculate the difference between the radius of the virtual circle and the vertical distance, and determine the difference as the vertical downward displacement.

4. The method for generating a dynamic submarine cable insulation layer bending stress distribution cloud map as described in claim 3, characterized in that, The required vertical downward displacement of the compaction model is calculated using the following formula: In the formula, This indicates the vertical downward displacement. Indicates the target bending radius. This indicates the span parameter of the fastener.

5. The method for generating a dynamic submarine cable insulation layer bending stress distribution cloud map as described in claim 4, characterized in that, The step involves performing iterative calculations on the model to be solved based on the vertical downward displacement, with the goal of achieving a state of force equilibrium in each iteration. This generates simulation results containing stress data, including: Establish a displacement loading mapping relationship that monotonically increases from zero to the vertical downward displacement over time; Establish a stiffness decay mapping relationship that monotonically decays to zero over time from the initial high stiffness value; Repeat the model solving operation until the current cumulative time variable equals the preset total simulation time, and generate the simulation calculation results; The model solving operation includes: The displacement loading value corresponding to the current cumulative time variable is matched from the displacement loading mapping relationship, and the loading boundary of the block model is updated to the displacement loading value; wherein, the initial cumulative time variable is a preset time step; Match the stiffness coefficient value corresponding to the current cumulative time variable from the stiffness attenuation mapping relationship, and update the stiffness attribute of the virtual spring base to the stiffness coefficient value; Based on the loading boundary and the stiffness property, force balance calculation is performed on the model to be solved to generate the insulation layer stress data corresponding to the current cumulative time variable; If the current cumulative time variable is equal to the preset total simulation duration, the insulation layer stress data corresponding to the current cumulative time variable will be used as the simulation calculation result. If the current cumulative time variable is not equal to the preset total simulation duration, calculate the sum of the current cumulative time variable and the time step, and update the current cumulative time variable with the calculation result.

6. The method for generating a dynamic bending stress distribution cloud map of submarine cable insulation as described in claim 5, characterized in that, The step of extracting the stress data corresponding to the attenuation of the stiffness coefficient value of the virtual spring base to zero from the simulation calculation results, and generating a stress distribution cloud map of the insulation layer under the target bending radius based on the extracted stress data, includes: Analyze the simulation results and extract the nodal stress values ​​of each finite element mesh node in the insulation layer model; Establish a visual mapping rule between stress values ​​and display colors; wherein, the visual mapping rule defines the correspondence between different stress value ranges and different color levels; Based on the node stress values ​​and the visual mapping rules, the rendering color of each finite element mesh node is determined. The geometric surface of the insulation layer model is interpolated and rendered using the rendering color to generate a visualized insulation layer stress distribution cloud map.

7. A device for generating a dynamic bending stress distribution cloud map of submarine cable insulation, characterized in that, include: The module includes a parameter acquisition module, a model building module, a displacement calculation module, a simulation control module, and a contour map generation module. The parameter acquisition module is used to acquire the geometric dimension parameters, target bending radius, and preset fixture span parameters of the insulation layer of the dynamic submarine cable under test. The model building module is used to establish a finite element simulation model based on geometric dimension parameters and fixture span parameters, including an insulation layer model, two fixture models, and a pressure block model. The insulation layer model is horizontally mounted above the two fixture models, and the pressure block model is located at the mid-span position above the insulation layer model. The module establishes the contact connection relationships between the insulation layer model and the pressure block model and the two fixture models in the finite element simulation model, and applies a virtual spring base with a variable stiffness coefficient to the insulation layer model to generate the model to be solved. The displacement calculation module is used to calculate the required vertical downward displacement of the pressure block model based on the target bending radius and the span parameter of the fastener. The simulation control module is used to perform iterative calculations on the model to be solved based on the vertical downward displacement, with the goal that the result of each iteration of the calculation is a state of force equilibrium, and generate simulation calculation results containing stress data; wherein, during the process of performing iterative calculations on the model to be solved, the displacement loading value of the pressure block model in the model to be solved is driven to increase from zero to the vertical downward displacement, and the stiffness coefficient value of the virtual spring base is simultaneously reduced from the preset initial high stiffness value to zero; The cloud map generation module is used to extract the stress data corresponding to the attenuation of the stiffness coefficient value of the virtual spring base to zero from the simulation calculation results, and generate a cloud map of the insulation layer stress distribution under the target bending radius based on the extracted stress data.

8. The apparatus for generating a dynamic submarine cable insulation layer bending stress distribution cloud map as described in claim 7, characterized in that, The model building module includes: an insulation layer model building unit, a fastener model building unit, and a pressure block model building unit; The insulation layer model construction unit is used to construct a cylindrical geometric body as an insulation layer model based on the insulation layer outer diameter, insulation layer thickness and insulation layer axial length in the geometric dimension parameters. The fixture model construction unit is used to construct two rigid bodies with the same structure as two fixture models according to the preset fixture geometric parameters, and to arrange the two fixture models at intervals in the horizontal direction, and to set the horizontal distance between the central axes of the two fixture models to be equal to the fixture span parameter. The block model construction unit is used to construct a rigid body as a block model according to the preset block geometry parameters, and to set the loading center axis of the block model on the perpendicular bisector of the line connecting the two fixer models.

9. An electronic device, characterized in that, The device includes a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein the processor executes the computer program to implement the method for generating a dynamic bending stress distribution cloud map of a submarine cable insulation layer as described in any one of claims 1 to 6.

10. A storage medium, characterized in that, The storage medium includes a stored computer program, wherein, when the computer program is executed, it controls the device containing the storage medium to perform the method for generating a dynamic submarine cable insulation layer bending stress distribution cloud map as described in any one of claims 1 to 6.

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