Simulation Method for Coating Performance Based on High and Low Temperature Cycling and Pre-stress Loading

Abstract

This invention relates to the field of materials testing technology and discloses a simulation method for coating performance based on high and low temperature cycling and prestress loading. By acquiring measured operating data of pipes or components, a composite geometric model of the coating substrate containing microporous structures is constructed. Surface roughness and interface curvature characteristics are quantified using reverse engineering. A dynamic temperature-pressure coupling equation is generated based on the thermal expansion effect of high-pressure media. The microporous optical load is converted into an equivalent heat flux density using a ray tracing algorithm. The transient boundary conditions of the temperature and stress fields are correlated. The crack initiation path is simulated using the extended finite element method. The lifetime decay curve is predicted using the Paris formula. Material parameters are dynamically corrected based on experimental data to generate a multi-parameter collaborative optimization model. This invention solves the problems of distorted interface stress assessment and lifetime prediction bias under composite loading, providing multi-physics collaborative simulation support for optimizing the compressive strength performance of coatings.

Description

Technical Field

[0001] This invention relates to the field of material testing technology involving repeated or combined forces, and particularly to a method for simulating coating performance based on high and low temperature cycling and prestress loading. Background Technology

[0002] This research on coating performance under high and low temperature cycling and prestressing focuses on simulating the service environment of coatings in pipelines, aerospace, and other fields under alternating high-pressure media and extreme temperatures. By establishing a multiphysics coupling model of the coating-substrate system, and combining the effects of thermal expansion, interfacial stress distribution, and microporous structure, prestressing and alternating temperature loads are applied simultaneously to reveal the crack initiation, propagation mechanism, and fatigue failure law of the coating under thermo-mechanical synergy. This provides theoretical support and optimization path for improving the compressive strength and thermal cycling life of coatings under complex working conditions.

[0003] Existing coating performance testing methods mostly employ single environmental load simulations, which cannot effectively reproduce the combined working conditions of coatings subjected to alternating medium pressure and temperature in high-pressure pipeline applications, leading to distorted mechanical response assessments. Existing test equipment and simulation models do not fully couple the synergistic effects of prestressing loading and wide-temperature-range cycling, especially in stress concentration areas caused by the coating's microporous structure, making it difficult to quantify the risk of interfacial delamination due to differences in thermal expansion coefficients. Furthermore, the lack of multiphysics-coupled failure analysis models results in significant deviations in the fatigue damage mechanism and life prediction of coatings under high-pressure-temperature cyclic combined loading, hindering the optimization of coating material reliability settings under harsh conditions. Summary of the Invention

[0004] To address the shortcomings of existing technologies, this invention provides a simulation method for coating performance based on high and low temperature cycling and prestress loading. This invention solves the problem that existing testing methods cannot accurately evaluate the mechanical properties and failure behavior of coatings under combined conditions of high pressure medium pressure and high and low temperature cycling.

[0005] To solve the above-mentioned technical problems, the specific technical solution of the present invention is as follows:

[0006] The coating performance simulation method based on high and low temperature cycling and prestress loading provided by this invention includes:

[0007] Step 1: Obtain measured operating condition data of the pipeline or component. The measured operating condition data includes internal pressure distribution, temperature gradient, high pressure medium material parameters and surface morphology scanning data. Construct a composite geometric model of the coating substrate based on the measured operating condition data.

[0008] Step 2: Convert the microporous structure in the surface morphology scanning data of the measured working condition data into a digital model, calculate the optical load distribution based on the geometric features of the microporous structure, and import the digital model and optical load distribution into the composite geometric model of the coating and substrate to obtain the mechanical and thermal property parameters of the coating and substrate materials.

[0009] Step 3: Import the mechanical and thermal properties of the coating and substrate materials into the preset finite element simulation platform, and generate a dynamic temperature-pressure coupling equation based on the thermal expansion characteristics of the high-pressure medium.

[0010] Step 4: Perform thermo-mechanical coupling analysis in the finite element simulation platform, set the prestress and temperature cycle range, associate the temperature field and stress field based on the dynamic temperature-pressure coupling equation, and convert the optical load distribution into an equivalent heat flux density superimposed on the thermal boundary conditions of the coating surface through the ray tracing algorithm.

[0011] Step 5: Perform non-uniform meshing on the coating-substrate composite interface region and micropore region of the coating-substrate composite geometric model. The coating-substrate composite interface region adopts a hexahedral-dominated fine mesh, and the micropore edges adopt a tetrahedral transition mesh.

[0012] Step 6: Apply temperature cycling and prestress step by step in the finite element simulation platform, calculate the superposition value of thermal stress and mechanical stress at each time step through the transient solver, and extract the stress peak value and distribution data of the composite interface region of the coating substrate.

[0013] Step 7: Input the stress peak value and distribution data into the fracture mechanics analysis module, determine the crack propagation direction based on the stress intensity factor, and calculate the damage index and remaining life under cyclic loading by combining the fatigue cumulative damage model.

[0014] Furthermore, in the coating performance simulation method based on high and low temperature cycling and prestress loading described in this invention, the step of constructing the composite geometric model of the coating substrate includes:

[0015] A parametric model matching the pipes or components in the measured working condition data is generated through a preset 3D modeling platform. The coating thickness and substrate size of the parametric model are consistent with the measured data.

[0016] The micropore size and distribution density in the surface morphology scanning data are converted into the topology of the coating substrate composite geometric model using reverse engineering methods;

[0017] Based on the curvature characteristics of the surface topography scanning data, the curvature characteristics of the coating-substrate composite interface region are marked in the coating-substrate composite geometric model, and surface roughness parameters are generated.

[0018] The high-stress gradient region in the composite geometric model of the coating substrate is automatically refined using an adaptive mesh generation tool. The mesh convergence is verified based on the surface roughness parameter to control the iteration residual threshold.

[0019] Furthermore, in the coating performance simulation method based on high and low temperature cycling and prestress loading described in this invention, the step of generating the dynamic temperature-pressure coupling equation includes:

[0020] The high-pressure medium material parameters in the measured working condition data are called up. The high-pressure medium material parameters include the coefficient of thermal expansion and the pressure-temperature correlation characteristics.

[0021] The pressure fluctuation curve caused by the thermal expansion of the high-pressure medium under the temperature cycling conditions was calculated using fluid dynamics simulation.

[0022] By correlating the pressure fluctuation curve with the thermophysical parameters of the coating and the substrate, a dynamic coupling equation between the temperature field and the stress field is established.

[0023] The dynamic coupling equation is input into the thermo-mechanical coupling analysis of the finite element simulation platform as the boundary condition for transient loading.

[0024] Furthermore, the coating performance simulation method based on high and low temperature cycling and prestress loading described in this invention is characterized in that the step of setting the prestress and temperature cycling range includes:

[0025] In the thermo-mechanical coupling analysis of the finite element simulation platform, the medium pressure is defined as the initial prestress loading value, and the medium pressure is matched with the characteristics of the high-pressure medium;

[0026] The influence of the microporous structure of the composite geometric model of the coating substrate on the local heat distribution is quantified by the ray tracing algorithm described above, and a non-uniform heat flux load distribution map is generated.

[0027] The heat flux load distribution map is input into the optical heat transfer interface of the finite element simulation platform, and the temperature gradient change on the coating surface is calculated based on the dynamic temperature-pressure coupling equation.

[0028] The temperature gradient change is transiently coupled with the mechanical stress field in the thermo-mechanical coupling analysis to output the stress superposition result in the time domain.

[0029] Furthermore, the coating performance simulation method based on high and low temperature cycling and prestress loading described in this invention is characterized in that the non-uniform mesh generation step includes:

[0030] Based on the stress gradient distribution of the coating-substrate composite interface region in the coating-substrate composite geometric model, a hexahedral-dominated fine mesh is divided, and tetrahedral transition units are set at the micropore edges based on the generated surface roughness parameters.

[0031] An implicit time integration algorithm is used to solve the established dynamic temperature-pressure coupling equation, and an adaptive time step is set to balance the calculation accuracy and efficiency.

[0032] The stress-strain curves during the heating and cooling stages in the finite element simulation platform are automatically extracted using scripts to identify the critical inflection point of peel stress in the composite interface region of the coating and substrate.

[0033] By comparing the critical inflection point with the mesh convergence analysis results, the mesh density of the coating-matrix composite geometric model is dynamically adjusted to optimize computational stability.

[0034] Furthermore, the coating performance simulation method based on high and low temperature cycling and prestress loading described in this invention includes the following steps for calculating the damage index and remaining life under cyclic loading using a fatigue cumulative damage model: simulating the interface delamination crack initiation path of the coating-substrate composite geometric model using the extended finite element method; obtaining the correlation data between crack propagation rate and stress distribution based on the extracted stress peak and distribution data; and establishing a fatigue crack propagation model based on the Paris formula to predict the life decay curve under different temperature cycles.

[0035] The stress cloud map and interface peeling stress distribution map in the finite element simulation platform are generated by the preset post-processing platform, and the optimized high stress concentration area is located according to the stress cloud map.

[0036] Based on the distribution data of the high stress concentration area, the component ratio of the coating material is adjusted in reverse to generate a multi-parameter collaborative optimization model corresponding to the lifetime decay curve.

[0037] Furthermore, the coating performance simulation method based on high and low temperature cycling and prestress loading described in this invention also includes:

[0038] The interfacial peel strength output by the fracture mechanics analysis module is compared with the residual data from the actual high and low temperature-pressure combined test.

[0039] The thermal expansion coefficient of the coating material and the interface strength parameters generated therein are dynamically updated by fitting the deviation between the simulation and experimental results using the least squares method.

[0040] Accelerated life tests were set up to collect failure mode data under combined loads, and the fracture toughness parameters of the material constitutive model in the dynamic thermo-pressure coupling equation were corrected.

[0041] The remaining lifetime is recalculated based on the corrected model parameters, and the calibrated coating compressive strength optimization path corresponding to the multi-parameter collaborative optimization model is output.

[0042] Beneficial effects of this invention;

[0043] This invention constructs a composite geometric model of a coating substrate containing microporous structures using measured operating data. By combining reverse engineering to quantify interface curvature characteristics and surface roughness parameters, it solves the stress assessment deviation problem caused by geometric distortion in existing modeling. Based on the thermal expansion effect of high-pressure media, a dynamic temperature-pressure coupling equation is generated. A ray tracing algorithm converts the microporous optical load into an equivalent heat flux density, correlating the transient boundary conditions of the temperature and stress fields to accurately characterize the synergistic mechanism of temperature cycling and pressure fluctuations. A non-uniform meshing strategy using hexahedral fine meshes and tetrahedral transition elements, combined with an implicit time integration algorithm, is employed to solve the thermo-mechanical coupling equation, improving the calculation accuracy of the interface stress peak. By simulating crack propagation paths and lifetime decay trends using the extended finite element method and the Paris formula, and combining experimental data for closed-loop verification and dynamic correction of material parameters, a multi-parameter collaborative optimization model is generated. This provides high-precision multiphysics simulation support for optimizing the compressive strength and predicting the lifetime of coatings under high-pressure and high-low temperature alternating conditions, significantly improving the systematic nature of coating reliability design in complex environments. Attached Figure Description

[0044] To more clearly illustrate the technical solution of the present invention, the drawings used in the embodiments will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on the drawings without creative effort.

[0045] Figure 1 A flowchart of a coating performance simulation method based on high and low temperature cycling and prestress loading provided for embodiments of the present invention. Detailed Implementation

[0046] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below in conjunction with specific embodiments and corresponding drawings. Obviously, the described embodiments are only a part of the embodiments of this invention, and not all of them. Based on the embodiments of this invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this invention. The technical solutions provided by various embodiments of this invention will be described in detail below with reference to the accompanying drawings. To better understand the objectives of this invention, it will be described in further detail below.

[0047] Please see Figure 1 The present invention provides a method for simulating coating performance based on high and low temperature cycling and prestress loading, comprising:

[0048] Step 1: Obtain measured operating condition data of the pipeline or component. The measured operating condition data includes internal pressure distribution, temperature gradient, high pressure medium material parameters and surface morphology scanning data. Construct a composite geometric model of the coating substrate based on the measured operating condition data.

[0049] The specific implementation process of Step 1 is as follows: Surface morphology scanning data of the pipe or component is acquired using a 3D laser scanner. Internal pressure distribution and temperature gradient parameters are obtained using pressure sensors and thermocouples. Simultaneously, the coefficient of thermal expansion and pressure-temperature correlation curves are extracted from the material property database of the high-pressure medium. Actual operating condition data is imported into 3D modeling software via a data interface module. Noise reduction processing is performed on the point cloud of the surface morphology scanning data based on reverse engineering algorithms. The geometric contours of the coating and substrate are reconstructed, generating a parametric model with coating thickness and substrate dimensions consistent with the actual component. For microporous structures, topological mapping technology is used to convert the pore size and distribution density in the scanning data into pore features of the geometric model, forming a composite structure that includes surface roughness parameters.

[0050] During model construction, curvature analysis tools were used to quantify the geometric undulations of the coating-substrate composite interface region, marking curvature extrema and generating surface roughness parameters. These parameters serve as input conditions for mesh generation, guiding subsequent adaptive meshing tools in local refinement strategies for high-stress gradient regions. A dynamic calibration module using measured data and model parameters was employed to adjust the dimensional deviations of the geometric model, ensuring the model matches the physical structure of the actual working conditions and providing a high-fidelity geometric basis for thermo-mechanical coupling simulation.

[0051] The above steps, through measured data acquisition, reverse engineering reconstruction, and parametric modeling, achieved high-precision construction of the composite geometric model of the coating substrate, laying the data and model foundation for the simulation analysis of interface stress distribution under composite loads, and solving the stress assessment deviation problem caused by geometric feature distortion in existing methods.

[0052] Step 2: Convert the microporous structure in the surface morphology scanning data of the measured working condition data into a digital model, calculate the optical load distribution based on the geometric features of the microporous structure, and import the digital model and optical load distribution into the composite geometric model of the coating and substrate to obtain the mechanical and thermal property parameters of the coating and substrate materials.

[0053] The specific implementation process of step 2 is as follows: The micropore structure in the surface morphology scanning data is processed into a 3D point cloud using reverse engineering software. A noise reduction algorithm is used to remove scanning noise while preserving the geometric features of the pores, generating a digital model containing the micropore diameter, depth, and distribution density. Based on the geometric features of the micropore structure, the optical load calculation module is invoked, and a ray tracing algorithm is used to simulate the scattering, reflection, and absorption effects of incident light by the micropores, quantifying the differences in local light intensity distribution and generating a non-uniform optical load distribution map. This distribution map is imported into the composite geometric model of the coating substrate through the data interface module and correlated with the boundary conditions of the coating surface to characterize the differences in heat flux density caused by the micropores.

[0054] After superimposing the digital model with the optical load distribution, the elastic modulus, Poisson's ratio, and thermal conductivity parameters of the coating and substrate materials are retrieved from the material property database. Combined with the pressure-temperature correlation curve of the high-pressure medium, a set of mechanical and thermophysical property parameters required for thermo-mechanical coupling analysis is generated. This parameter set is mapped to the corresponding region of the geometric model through the material assignment module of the finite element simulation platform, forming multiphysics simulation input conditions that match the actual measured conditions. These steps, through digital reconstruction of the microporous structure and quantification of the optical load, achieve accurate modeling of the non-uniform thermal load on the coating surface, providing key input parameters for establishing the dynamic temperature-pressure coupling equation.

[0055] Through the above process, the micropore geometric features and optical load distribution in the measured data are systematically integrated into the coating-substrate composite model, which solves the problem of temperature field evaluation distortion caused by ignoring micropore thermal flow disturbance in existing methods, and provides a high-fidelity material parameter basis for interface stress analysis under composite load.

[0056] Step 3: Import the mechanical and thermal properties of the coating and substrate materials into the preset finite element simulation platform, and generate a dynamic temperature-pressure coupling equation based on the thermal expansion characteristics of the high-pressure medium.

[0057] The specific implementation process of step 3 is as follows: Using the data import module of the finite element simulation platform, the elastic modulus, Poisson's ratio, and thermal conductivity parameters of the coating and substrate materials, as well as the thermal expansion coefficient and pressure-temperature correlation curve of the high-pressure medium, are input into the material property library. Based on the dynamic thermal expansion characteristics of the high-pressure medium, the fluid dynamics simulation module is called to calculate the thermal expansion volume change of the medium under temperature cycling conditions, generating a pressure fluctuation curve that varies with time. This curve is correlated with the thermophysical parameters of the coating and substrate through a multiphysics coupling interface, establishing a mathematical relationship between the temperature field gradient and the dynamic response of the stress field, forming a dynamic temperature-pressure coupling equation.

[0058] During equation generation, the thermal flux density distribution on the coating surface and the medium pressure fluctuation data are superimposed using a thermo-mechanical coupling analysis module to define transient boundary conditions for temperature cycling and prestressing loading. Utilizing the heat conduction equation and elasticity equation in the finite element solver, the thermal strain and mechanical stress fields caused by temperature field changes are superimposed to construct a temperature-stress biaxial coupled iterative calculation model. The interaction between the temperature and stress fields is solved synchronously using an implicit algorithm, achieving transient thermo-mechanical coupling simulation of the coating interface region.

[0059] The above steps accurately quantify the temperature-stress synergistic mechanism of the coating interface under composite load by dynamically correlating the thermal expansion effect of the high-pressure medium with material parameters. This solves the problem of stress assessment deviation caused by neglecting thermo-pressure coupling in existing single-physics simulations, and provides a high-precision multiphysics analysis basis for subsequent crack propagation simulation and life prediction.

[0060] Step 4: Perform thermo-mechanical coupling analysis in the finite element simulation platform, set the prestress and temperature cycle range, associate the temperature field and stress field based on the dynamic temperature-pressure coupling equation, and convert the optical load distribution into an equivalent heat flux density superimposed on the thermal boundary conditions of the coating surface through the ray tracing algorithm.

[0061] The specific implementation process of step 4 is as follows: Using the thermo-mechanical coupling analysis module of the finite element simulation platform, the pressure-temperature correlation curve of the high-pressure medium is invoked. The medium pressure is defined as the initial prestress loading value, and its value matches the characteristic parameters of the high-pressure medium in actual working conditions. The temperature cycling range is set based on the temperature gradient in the measured data. The heating / cooling rate and the number of cycles are input through the transient boundary condition loading interface to form a temperature alternating load spectrum consistent with the service environment. Based on the dynamic temperature-pressure coupling equation, the temperature field gradient change is correlated with the elastic response of the stress field. The heat conduction equation and the elasticity equation are solved simultaneously through a matrix iterative algorithm to establish a transient calculation model with temperature-stress biaxial coupling.

[0062] The optical load distribution of the microporous structure is quantized a second time using a ray tracing algorithm to simulate the scattering path and energy absorption characteristics of light within the micropores, generating an equivalent heat flux density distribution map. This distribution map is superimposed onto the coating surface through a thermal boundary condition mapping module and fused with the temperature field data output from the dynamic thermo-pressure coupling equation to form a composite boundary condition with non-uniform heat flux-pressure interaction. During the solution process, an implicit time integration algorithm is used to perform step-by-step iterative calculations of the thermo-mechanical coupling equation, updating the stress distribution state after the superposition of temperature gradient and prestress in real time, and outputting transient stress field data for each time step.

[0063] The above steps, through the initial loading of prestress, the transient definition of temperature cycling, and the boundary superposition of heat flux density, realize the dynamic correlation analysis of temperature field and stress field under composite load, solve the problem of interface stress evaluation distortion caused by simplified heat flux distribution or load separation in existing methods, and provide multi-physics field collaborative boundary condition support for accurate simulation of coating interface peeling behavior.

[0064] Step 5: Perform non-uniform meshing on the coating-substrate composite interface region and micropore region of the coating-substrate composite geometric model. The coating-substrate composite interface region adopts a hexahedral-dominated fine mesh, and the micropore edges adopt a tetrahedral transition mesh.

[0065] The specific implementation process of step 5 is as follows: Stress gradient analysis is performed on the composite geometric model of the coating-substrate system using an adaptive meshing tool to identify high stress concentration areas at the interface. Based on the geometric feature data generated from surface roughness parameters, a hexahedral-dominated meshing strategy is adopted in the composite interface region of the coating-substrate system. Regularly arranged mesh elements improve the accuracy of stress distribution calculation, while mesh size gradient control reduces computational resource consumption. For the micropore edge region, due to its complex geometric curvature and high surface roughness, tetrahedral transition elements are used to connect the refined mesh region with the regular mesh region to adapt to the geometric morphology of the pore edge and maintain mesh continuity.

[0066] After mesh generation, residual analysis is performed on the mesh density of the interface region and micropore edges using a mesh convergence verification module. Based on a preset iterative residual threshold, stress calculation results under different mesh densities are compared, and the local mesh refinement level is dynamically adjusted. Stress-strain curves during the heating and cooling stages are automatically extracted using scripts to identify critical inflection points in interface peeling stress. The mesh distribution is then optimized based on the convergence analysis results to ensure the calculation results meet stability requirements.

[0067] The above steps, through stress gradient-driven non-uniform mesh generation, geometric adaptation of tetrahedral transition elements, and dynamic mesh optimization, solve the computational stability problem under complex geometry and transient loads, providing a reliable numerical analysis basis for high-precision extraction of coating interface stress peaks and crack propagation simulation, and supporting the accurate construction of subsequent fatigue damage models.

[0068] Step 6: Apply temperature cycling and prestress step by step in the finite element simulation platform, calculate the superposition value of thermal stress and mechanical stress at each time step through the transient solver, and extract the stress peak value and distribution data of the composite interface region of the coating substrate.

[0069] The specific implementation process of step 6 is as follows: Using the load loading module of the finite element simulation platform, cyclic temperature loads and prestress are applied step-by-step. The temperature change rate and number of cycles during the heating and cooling stages are defined to form an alternating temperature spectrum consistent with the actual measured conditions. The initial prestress is set according to the pressure characteristics of the high-pressure medium and mapped to the boundary surface of the coating-substrate composite model through the pressure loading interface. The transient solver calls the implicit time integration algorithm, dynamically adjusting the calculation step size based on adaptive time step control. The step size is shortened during periods of rapid temperature change to improve calculation accuracy, and extended during periods of stable temperature to improve efficiency, simultaneously solving the heat conduction equation and the elasticity equation.

[0070] After each time step calculation, the thermal stress caused by thermal expansion and the mechanical prestress are vector-superimposed using the stress superposition module to generate transient stress field distribution data under combined load. Post-processing tools are used to extract the stress peak value and its spatial coordinates at the coating-substrate composite interface region, and the high stress concentration locations with high risk of interface delamination are analyzed in conjunction with the distribution cloud map. Scripts are used to automatically filter stress extrema at key time points, generating stress-time variation curves and peak value statistics tables to provide input parameters for crack propagation simulation.

[0071] The above steps, through step-by-step loading, transient solution and stress superposition calculation, accurately quantify the dynamic response of interface stress under the combined effect of temperature cycling and prestressing, and solve the problem of stress assessment distortion caused by load separation or static assumptions in existing methods, providing a high-precision stress data foundation for subsequent fatigue damage models and life prediction.

[0072] Step 7: Input the stress peak value and distribution data into the fracture mechanics analysis module, determine the crack propagation direction based on the stress intensity factor, and calculate the damage index and remaining life under cyclic loading by combining the fatigue cumulative damage model.

[0073] The specific implementation process of step 7 is as follows: The stress peak value and distribution data of the coating-substrate composite interface region are input into the fracture mechanics analysis module through the data interface module. The extended finite element method (XFEM) is then used to simulate the initiation path of interface delamination cracks. Based on the calculated stress intensity factor at the crack tip, the tendency of the crack to propagate along the interface or the matrix is ​​identified through a direction determination algorithm, generating a crack propagation direction map. Combining the stress distribution data and the crack propagation path, the correlation between the crack propagation rate and the local stress peak value is established, providing input parameters for the fatigue cumulative damage model.

[0074] In the fatigue cumulative damage model, the relationship between crack length and the number of temperature cycles is constructed based on the Paris formula. The influence of the thermal expansion difference between the coating and the substrate on crack propagation is introduced through a temperature-stress biaxial correction module, predicting the life decay curves under different temperature cycling conditions. The damage index is calculated using a cumulative damage integral algorithm, comparing the stress amplitude of each cycle with the material's fatigue limit to generate a curve showing the change in the damage index with the number of cycles. Combined with the remaining life prediction module, the service life assessment results of the coating are output.

[0075] A 3D visualization map, superimposed with the crack propagation path and the interface peeling stress distribution map, is generated using a post-processing platform to locate high-damage-risk areas. Based on damage index and remaining life data, the component ratio and interface structure parameters of the coating material are inversely optimized to generate a multi-parameter synergistic optimization scheme. These steps, through closed-loop iteration of crack propagation simulation, damage accumulation quantification, and life prediction models, solve the life assessment bias problem caused by neglecting the synergistic effect of composite loads in existing methods, providing high-precision simulation support for optimizing the compressive strength of coatings.

[0076] The coating performance simulation method based on high and low temperature cycling and prestress loading provided by this invention has the following specific implementation process:

[0077] First, measured operating condition data of the pipeline or component are acquired using a 3D laser scanner and pressure sensors, including internal pressure distribution, temperature gradient, high-pressure medium material parameters, and surface morphology scanning data. Based on the measured data, the composite geometric model of the coating substrate is reconstructed in 3D modeling software, ensuring that the coating thickness and substrate dimensions in the model are consistent with the actual component. Reverse engineering algorithms are used to process the microporous structure in the surface morphology scanning data into point clouds, mapping its topology to the geometric model, and curvature analysis tools are used to quantify the roughness characteristics of the interface region.

[0078] Secondly, the digital model of the microporous structure is imported into the finite element simulation platform, and combined with the optical load calculation module, a local optical load distribution is generated based on the geometric characteristics of the micropores. The scattering and absorption effects of light by the micropores are simulated using a ray tracing algorithm, converting the optical load into an equivalent heat flux density distribution. This heat flux density distribution serves as the thermal boundary condition of the coating surface, and together with the thermal expansion characteristics of the high-pressure medium, it contributes to the establishment of the dynamic temperature-pressure coupling equation.

[0079] Subsequently, the material parameters of the high-pressure medium, including the coefficient of thermal expansion and the pressure-temperature correlation curve, were used to calculate the dynamic pressure fluctuations caused by the thermal expansion of the medium under temperature cycling through fluid dynamics simulation. The pressure fluctuations were correlated with the thermophysical parameters of the coating and substrate to derive the dynamic coupling equations between the temperature field and the stress field. In the finite element simulation platform, the initial prestress value was set to the medium pressure, and transient boundary conditions were used to couple the temperature gradient change with the mechanical stress field.

[0080] To address the high stress gradient characteristics at the coating-substrate composite interface, hexahedral meshing is employed to improve the accuracy of stress distribution calculation. Due to the high geometric complexity at the micropore edges, tetrahedral transition elements are used to balance mesh quality and computational efficiency. The mesh density is iteratively adjusted based on surface roughness parameters using the convergence verification module of an adaptive meshing tool until the residual threshold meets preset conditions.

[0081] During the loading phase, cyclic temperature loads and prestresses are applied stepwise, and the transient thermo-mechanical coupling equations are solved using an implicit time integration algorithm. The superposition of thermal and mechanical stresses at each time step is calculated using a transient solver, and the stress peak values ​​and spatial distribution data of the interface region are extracted. Based on the stress distribution data, the extended finite element method is used to simulate the initiation path of interface delamination cracks, and the crack propagation rate and life decay trend are predicted by combining the stress intensity factor and the Paris formula.

[0082] Furthermore, the residuals of the simulated interfacial peel strength output were compared with those of the high-low temperature-pressure combined test data. The deviation was fitted using the least squares method, and the thermal expansion coefficient and interfacial strength parameters of the coating material were dynamically corrected. Based on the corrected parameters, the remaining lifetime was recalculated iteratively, and high stress concentration areas were located using the stress cloud map generated by the post-processing platform. The component ratio of the coating material was then optimized in reverse, forming a multi-parameter synergistic optimization path to improve compressive strength.

[0083] The above steps, through measured data-driven model construction, multi-physics coupling analysis, and dynamic parameter correction, achieve high-precision simulation and lifetime prediction of coating interface stress distribution under composite loads, providing systematic multi-scale simulation support for optimizing coating compressive performance.

[0084] Specifically, the coating performance simulation method based on high and low temperature cycling and prestress loading described in this invention includes the following steps in constructing a composite geometric model of the coating substrate:

[0085] A parametric model matching the pipes or components in the measured working condition data is generated through a preset 3D modeling platform. The coating thickness and substrate size of the parametric model are consistent with the measured data.

[0086] The micropore size and distribution density in the surface morphology scanning data are converted into the topology of the coating substrate composite geometric model using reverse engineering methods;

[0087] Based on the curvature characteristics of the surface topography scanning data, the curvature characteristics of the coating-substrate composite interface region are marked in the coating-substrate composite geometric model, and surface roughness parameters are generated.

[0088] The high-stress gradient region in the composite geometric model of the coating substrate is automatically refined using an adaptive mesh generation tool. The mesh convergence is verified based on the surface roughness parameter to control the iteration residual threshold.

[0089] The specific steps for constructing the composite geometric model of the coating substrate include the following:

[0090] Using a pre-defined 3D modeling platform, measured operating data of pipes or components, including internal pressure distribution, temperature gradient, and surface morphology scanning data, are retrieved to generate a parametric model. The coating thickness and substrate dimensions of the parametric model are defined based on the measured data, and the model's geometric features maintain a strict correspondence with the actual component. During the modeling process, a calibration module based on measured data is used to dynamically adjust the model dimensions to match the physical structure under actual operating conditions.

[0091] Based on surface topography scanning data, micropore size and distribution density information are extracted using reverse engineering methods. Three-dimensional point cloud processing technology is employed to denoise and reconstruct the scanning data, transforming discrete micropore geometric features into a continuous topological structure. A parametric mapping algorithm is then used to correlate the micropore distribution density with local regions in the geometric model, forming a composite geometric model incorporating the micropore structure.

[0092] In the geometric model, based on the curvature characteristics of the surface topography scanning data, a curvature analysis tool is used to annotate the features of the coating-substrate composite interface region. Local curvature extrema in the interface region are identified through curvature gradient calculation and correlated with surface roughness parameters. Surface roughness parameters are generated by quantifying the geometric undulations of the interface region, providing geometric feature inputs for subsequent mesh generation and stress analysis.

[0093] For regions with high stress gradients, an adaptive meshing tool is used to locally refine the geometric model. In the coating-substrate composite interface region, hexahedral meshes are preferentially used to improve the accuracy of stress distribution calculation. Due to the high geometric complexity at the micropore edges, tetrahedral transition elements are used to connect the refined mesh region with the regular mesh region. A mesh convergence verification module controls the iteration process based on surface roughness parameters and residual thresholds until the meshing results meet the preset convergence conditions.

[0094] The above steps, through measured data-driven parametric modeling, reverse engineering feature reconstruction, and adaptive mesh generation, established a composite geometric model of the coating substrate that matches the actual working conditions, providing a high-precision geometric foundation for subsequent multiphysics coupling analysis.

[0095] Specifically, the coating performance simulation method based on high and low temperature cycling and prestress loading described in this invention includes the following step in generating the dynamic temperature-pressure coupling equation:

[0096] The high-pressure medium material parameters in the measured working condition data are called up. The high-pressure medium material parameters include the coefficient of thermal expansion and the pressure-temperature correlation characteristics.

[0097] The pressure fluctuation curve caused by the thermal expansion of the high-pressure medium under the temperature cycling conditions was calculated using fluid dynamics simulation.

[0098] By correlating the pressure fluctuation curve with the thermophysical parameters of the coating and the substrate, a dynamic coupling equation between the temperature field and the stress field is established.

[0099] The dynamic coupling equation is input into the thermo-mechanical coupling analysis of the finite element simulation platform as the boundary condition for transient loading.

[0100] The specific steps for generating dynamic temperature-pressure coupling equations include the following:

[0101] When calling high-pressure medium material parameters from measured operating data, the thermal expansion coefficient and pressure-temperature correlation characteristics are extracted through a pre-defined material database interface. These material parameters are loaded into the fluid dynamics simulation platform via a parameterized input module, forming a set of medium thermodynamic properties. Based on the physical properties of the high-pressure medium, a correlation model between its thermal expansion effect and temperature change is established, providing input conditions for subsequent pressure fluctuation calculations.

[0102] Using a fluid dynamics simulation platform, temperature cycling boundary conditions were set to simulate the dynamic thermal expansion behavior of a high-pressure medium during heating and cooling processes. The finite volume method was employed to perform transient solutions for the flow and heat transfer processes of the medium, outputting the pressure fluctuation curve of the medium over time under temperature cycling. This curve characterizes the dynamic pressure response properties caused by thermal expansion, providing input loads for thermo-mechanical coupling analysis.

[0103] When correlating pressure fluctuation curves with the thermophysical parameters of the coating and substrate, a coupling relationship between the temperature and stress fields is constructed based on the heat conduction equation and the elasticity equation. The pressure fluctuation data of the medium is mapped to the surface nodes of the coating-substrate composite model through a multiphysics interface. Combining the thermal conductivity of the coating material and the elastic modulus of the substrate, a dynamic transfer equation for temperature gradient and thermal stress is established. This equation describes the transient influence mechanism of temperature field changes on local stress in matrix form.

[0104] After inputting the dynamic coupling equations into the thermo-mechanical coupling analysis module of the finite element simulation platform, the time-varying laws of temperature and pressure are defined through the transient boundary condition loading interface. In the thermo-mechanical coupling solver, the pressure fluctuation curve is applied as a time-varying load to the coating surface, while the temperature cycle range is associated with the material's thermal expansion constitutive model. The interaction between the temperature field and the stress field is solved simultaneously through an implicit iterative algorithm, achieving multi-field co-simulation under dynamic temperature-pressure coupling conditions.

[0105] The above steps, through fluid dynamics simulation and multiphysics coupling modeling, accurately quantify the dynamic influence of high-pressure medium thermal expansion on coating interface stress, providing physically driven boundary condition inputs for stress distribution analysis under composite loads.

[0106] Specifically, the coating performance simulation method based on high and low temperature cycling and prestress loading described in this invention is characterized in that the step of setting the prestress and temperature cycling range includes:

[0107] In the thermo-mechanical coupling analysis of the finite element simulation platform, the medium pressure is defined as the initial prestress loading value, and the medium pressure is matched with the characteristics of the high-pressure medium;

[0108] The influence of the microporous structure of the composite geometric model of the coating substrate on the local heat distribution is quantified by the ray tracing algorithm described above, and a non-uniform heat flux load distribution map is generated.

[0109] The heat flux load distribution map is input into the optical heat transfer interface of the finite element simulation platform, and the temperature gradient change on the coating surface is calculated based on the dynamic temperature-pressure coupling equation.

[0110] The temperature gradient change is transiently coupled with the mechanical stress field in the thermo-mechanical coupling analysis to output the stress superposition result in the time domain.

[0111] The specific steps for setting the prestressing and temperature cycling range include the following:

[0112] In the thermo-mechanical coupling analysis module of the finite element simulation platform, the characteristic parameters of the high-pressure medium are called through the preset material property library, and the medium pressure is defined as the initial prestress loading value. The initial prestress is applied to the boundary surface of the coating substrate composite model through the pressure loading interface. Its value is matched with the thermal expansion coefficient and operating pressure of the high-pressure medium, forming an initial stress state consistent with the actual service environment.

[0113] Based on the micropore structure data of the composite geometric model of the coating substrate, a ray tracing algorithm is used to simulate the scattering, reflection, and absorption behavior of incident light by the micropores. The influence of micropore size and distribution density on the local heat transfer path is quantified using a geometric optics model, generating a non-uniform heat flux load distribution map. This distribution map is correlated to the coating surface through a heat flux density mapping module, characterizing the differences in heat distribution caused by the micropore geometry.

[0114] The non-uniform heat flux load distribution map is input into the optical heat transfer interface of the finite element simulation platform. Combined with the temperature field boundary conditions in the dynamic thermo-pressure coupling equation, the transient temperature gradient change on the coating surface is calculated. The temperature gradient is correlated with the thermal conductivity parameter of the coating material through the heat conduction equation to generate time-varying temperature field distribution data, which serves as the input load for the thermo-mechanical coupling analysis.

[0115] In the transient coupling solution process, the thermal strain caused by the temperature gradient change is superimposed with the elastic strain of the mechanical stress field. A dynamic relationship between the temperature field and the stress field is established through a multi-field coupling matrix, and an implicit time integration algorithm is used to simultaneously solve for the superimposed value of thermal stress and prestress at each time step. Finally, the stress distribution cloud map in the time domain and the stress-time curves of key nodes are output, reflecting the transient response characteristics of interface stress under combined loads.

[0116] The above steps, through initial prestress definition, micropore heat flow distribution modeling, and multi-field transient coupling analysis, realize the simulation of stress dynamic response under the combined action of temperature cycling and mechanical load, providing a high-precision multi-physics simulation basis for the quantitative evaluation of coating interface peeling behavior.

[0117] Specifically, the coating performance simulation method based on high and low temperature cycling and prestress loading described in this invention is characterized in that the non-uniform mesh generation step includes:

[0118] Based on the stress gradient distribution of the coating-substrate composite interface region in the coating-substrate composite geometric model, a hexahedral-dominated fine mesh is divided, and tetrahedral transition units are set at the micropore edges based on the generated surface roughness parameters.

[0119] An implicit time integration algorithm is used to solve the established dynamic temperature-pressure coupling equation, and an adaptive time step is set to balance the calculation accuracy and efficiency.

[0120] The stress-strain curves during the heating and cooling stages in the finite element simulation platform are automatically extracted using scripts to identify the critical inflection point of peel stress in the composite interface region of the coating and substrate.

[0121] By comparing the critical inflection point with the mesh convergence analysis results, the mesh density of the coating-matrix composite geometric model is dynamically adjusted to optimize computational stability.

[0122] The specific steps for non-uniform mesh generation include the following:

[0123] Based on the stress gradient distribution data of the coating-substrate composite interface region, high stress concentration areas were identified using stress analysis tools, and a hexahedral-dominated mesh refinement strategy was preferentially adopted. The regular arrangement of hexahedral meshes in the interface region improved the calculation accuracy of stress distribution, while reducing computational resource consumption through mesh size gradient control. Due to the complex geometry and high surface roughness parameters of the micropore edge region, tetrahedral transition elements were used to connect the refined region and the regular mesh region to adapt to the curvature changes of the micropores and maintain mesh continuity.

[0124] In solving the dynamic temperature-pressure coupling equations, an implicit time integration algorithm is employed to handle the nonlinear thermo-mechanical coupling problem. An adaptive time step control module dynamically adjusts the time step based on the transient change rates of the temperature and stress fields. When the temperature or stress gradient changes drastically, the time step is automatically shortened to improve computational accuracy; during periods of gradual change, the time step is extended to enhance solution efficiency, achieving a balanced optimization between accuracy and efficiency.

[0125] By automatically calling the post-processing data interface of the finite element simulation platform via scripts, stress-strain curves of the coating-substrate composite interface region during the heating and cooling stages are extracted. Peak detection algorithms are used to identify stress abrupt change points in the curves, and curvature change analysis is combined to locate the critical inflection point of delamination stress. This inflection point characterizes the starting location of interface delamination risk, providing key input parameters for subsequent lifetime analysis.

[0126] The stress values ​​corresponding to the critical inflection points are compared with the mesh convergence analysis results to evaluate the computational stability under the current mesh density. If the stress deviation at the critical inflection point exceeds a preset threshold, the interface region is locally refined or sparsed using the mesh re-meshing module. The adjusted mesh density is then re-verified based on surface roughness parameters and residual convergence criteria until the computational results meet the stability requirements.

[0127] The above steps effectively solve the computational stability problem under complex geometry and transient loads by using a stress gradient-driven mesh generation strategy, adaptive time step control, and dynamic mesh optimization, providing a reliable numerical analysis basis for the accurate simulation of coating interface peeling behavior.

[0128] Specifically, the coating performance simulation method based on high and low temperature cycling and prestress loading described in this invention includes the following steps for calculating the damage index and remaining life under cyclic loading using a fatigue cumulative damage model: simulating the interface delamination crack initiation path of the coating-substrate composite geometric model using the extended finite element method; obtaining the correlation data between crack propagation rate and stress distribution based on the extracted stress peak and distribution data; and establishing a fatigue crack propagation model based on the Paris formula to predict the life decay curve under different temperature cycles.

[0129] The stress cloud map and interface peeling stress distribution map in the finite element simulation platform are generated by the preset post-processing platform, and the optimized high stress concentration area is located according to the stress cloud map.

[0130] Based on the distribution data of the high stress concentration area, the component ratio of the coating material is adjusted in reverse to generate a multi-parameter collaborative optimization model corresponding to the lifetime decay curve.

[0131] The specific steps for calculating the damage index and remaining life under cyclic loading using a fatigue cumulative damage model include the following:

[0132] Within the framework of the extended finite element method, the initiation path of interfacial delamination cracks is simulated based on the interfacial stress distribution data of the composite geometric model of the coating substrate. A crack tip stress intensity factor extraction module is used to obtain crack propagation rate data at different temperature cycling stages, and the correlation between these rates and local stress peaks is established. The simulation results of the crack propagation path are mapped to the geometric model using a path tracing algorithm, forming a dynamic evolution map of interfacial delamination risk.

[0133] A fatigue crack propagation model based on the Paris formula correlates the crack propagation rate with the stress intensity factor amplitude, establishing a quantitative relationship between the number of temperature cycles and crack length growth. Through a biaxial temperature and stress correction module, the influence of the thermal expansion difference of the coating material on crack propagation is introduced, generating lifetime decay curves under different temperature cycling conditions. This curve characterizes the remaining lifetime trend of the coating under combined loading, providing input parameters for damage index calculation.

[0134] The system uses a pre-defined post-processing platform to call upon the output data of the finite element simulation platform to generate an interface delamination stress distribution map and a 3D stress cloud map. Using a stress peak clustering algorithm, the spatial coordinates and amplitude characteristics of high-stress concentration areas are located in the cloud map. A thermo-coupling analysis module overlays the distribution data of the high-stress areas with the crack propagation map to identify key locations of interface delamination risk.

[0135] Based on the distribution characteristics of high stress concentration areas, the component ratio parameters of the coating material are adjusted in reverse. A response surface model of the coating component ratio and interfacial stress amplitude is established through a material parameter optimization interface, and a multi-parameter collaborative optimization scheme is generated by combining the lifetime decay curve. This scheme verifies the effect of component adjustment on suppressing interfacial peeling stress through iterative calculations, and finally outputs an optimized coating material configuration path that matches the target lifetime.

[0136] The above steps, through crack propagation simulation, lifetime decay modeling, and material inverse optimization, realize the quantitative assessment of damage and the improvement of anti-peeling performance of coatings under composite loads, and provide a closed-loop simulation verification system for multi-physics collaborative design of coating materials.

[0137] Specifically, the coating performance simulation method based on high and low temperature cycling and prestress loading described in this invention further includes:

[0138] The interfacial peel strength output by the fracture mechanics analysis module is compared with the residual data from the actual high and low temperature-pressure combined test.

[0139] The thermal expansion coefficient of the coating material and the interface strength parameters generated therein are dynamically updated by fitting the deviation between the simulation and experimental results using the least squares method.

[0140] Accelerated life tests were set up to collect failure mode data under combined loads, and the fracture toughness parameters of the material constitutive model in the dynamic thermo-pressure coupling equation were corrected.

[0141] The remaining lifetime is recalculated based on the corrected model parameters, and the calibrated coating compressive strength optimization path corresponding to the multi-parameter collaborative optimization model is output.

[0142] The coating performance simulation method based on high and low temperature cycling and prestress loading described in this invention further includes the following specific steps:

[0143] The interface peel strength data output from the fracture mechanics analysis module is synchronously accessed with actual high / low temperature-pressure combined test data via a data interface module. The residual calculation module is then used to compare and analyze the simulation and experimental results. By defining a residual threshold range, regions with significant deviations in interface peel strength are identified, generating a residual distribution map. This map is used to locate sensitive areas of parameter mismatch in the simulation model, providing data input for parameter calibration.

[0144] Based on the deviation data from the residual distribution map, a linear correlation model between simulation and experimental results is established using a least squares fitting algorithm. A parameter optimization engine is used to dynamically adjust the thermal expansion coefficient and interface strength parameters of the coating material, gradually converging the simulation results to the experimental data. The parameter update process is achieved through iterative calculations, with the residual threshold re-verified after each iteration until the deviation value meets the preset convergence criterion.

[0145] An accelerated life testing platform was set up to simulate coating failure modes under combined loading conditions. A multi-axis loading device was used to apply the combined effects of high- and low-temperature cycling and mechanical prestress. Strain sensors and infrared thermal imagers were used to collect data on interface delamination, crack propagation, and heat distribution. The failure mode data was input into the material constitutive model correction module. Based on sensitivity analysis of fracture toughness parameters, the fracture toughness parameters in the dynamic thermo-baric coupling equation were adjusted to match the experimentally observed failure evolution.

[0146] Based on the corrected coefficient of thermal expansion, interfacial strength parameters, and fracture toughness parameters, the thermo-mechanical coupling simulation process was re-executed to calculate the remaining lifetime of the coating under combined loads. The lifetime prediction results were cross-validated with experimental lifetime data using a multi-parameter collaborative optimization model to generate a calibrated optimization path for compressive strength. This path, through combined optimization of material composition, interfacial structure, and process parameters, outputs a coating performance improvement scheme that matches the target service conditions.

[0147] The above steps, through closed-loop verification of experimental-simulation data, dynamic parameter updates, and failure mode-driven model correction, construct a high-precision coating performance prediction and optimization system, providing an iteratively verifiable solution for the reliable design of coating compressive strength under complex working conditions.

[0148] The following is an explanation of the technical feature terms in the technical solution of this invention:

[0149] Coating-substrate composite geometric model: refers to a digital model constructed using 3D modeling tools, which includes the geometric structure and dimensional parameters of the coating and the substrate. Its coating thickness and substrate shape are consistent with the actual part, and it integrates the topological features of the microporous structure (such as pore size and distribution density). The surface morphology scanning data is converted into a simulateable geometric entity through reverse engineering.

[0150] Dynamic temperature-pressure coupling equation: A mathematical model describing the synergistic effect of thermal expansion and temperature cycling of high-pressure media. It calculates the fluctuation curve of medium pressure with temperature through fluid dynamics simulation, and establishes the transient correlation between temperature field and stress field by combining the thermal conductivity and elastic modulus parameters of coating and substrate, which is used to simulate the interactive effect of thermo-mechanical load.

[0151] Ray tracing algorithm: A computational method based on the principles of geometric optics, used to quantify the scattering, reflection and absorption effects of light on microporous structures, generate a non-uniform heat flux density distribution map, and characterize the local heat distribution differences caused by micropores by mapping the heat flux density to the boundary conditions of the coating surface.

[0152] Hexahedral mesh and tetrahedral transition elements: To address the high stress gradient characteristics of the coating-substrate composite interface region, a regularly arranged hexahedral mesh is used to improve computational accuracy; due to the high geometric complexity of the micropore edges, a tetrahedral mesh is used to adapt to the curvature changes, and adaptive meshing is used to balance computational efficiency and convergence.

[0153] Implicit time integration algorithm: A numerical method for solving nonlinear thermo-mechanical coupling equations. It dynamically adjusts the calculation step size through adaptive time step control. When the temperature or stress changes drastically, the step size is shortened to improve accuracy, and the step size is extended during the calm phase to improve solution efficiency.

[0154] Extended Finite Element Method (XFEM): A numerical method for simulating crack propagation. Based on interface stress distribution data, it tracks the crack initiation path without re-meshing, calculates the crack propagation rate through stress intensity factor, and predicts the life decay trend by combining a fatigue cumulative damage model.

[0155] The Paris formula is a mathematical model that characterizes the law of fatigue crack propagation. It correlates the crack propagation rate with the magnitude of the stress intensity factor and introduces the influence of thermal expansion differences through a biaxial correction module of temperature and stress to generate life prediction curves under different temperature cycles.

[0156] Residual comparison and dynamic parameter update: The interface peel strength output by simulation is compared with the experimental data. The deviation is fitted by least squares method, and the thermal expansion coefficient and interface strength parameters of the coating material are iteratively corrected so that the simulation results converge to the experimental values ​​and the model prediction accuracy is improved.

[0157] Accelerated life testing: By applying a combined load of high and low temperature cycles and mechanical prestress through a multi-axis loading device, data on interface delamination, crack propagation, and thermal distribution are collected to correct the fracture toughness parameters of the material constitutive model and optimize the adaptability of the dynamic temperature-pressure coupling equation to actual working conditions.

[0158] Multi-parameter collaborative optimization model: Based on the distribution data of high stress concentration areas and the life decay curve, the coating component ratio and interface structure parameters are adjusted in reverse. The optimization scheme is verified by the response surface model, and the compressive performance improvement path that matches the target service conditions is output.

[0159] This invention addresses the problem in existing technologies where single-load simulations cannot reproduce complex working conditions by constructing a composite geometric model of a coating substrate containing microporous structures. Based on measured working condition data, reverse engineering methods are used to quantify the micropore diameter, distribution density, and interface curvature characteristics in the surface morphology scanning data, generating a parametric model consistent with the real component. A ray tracing algorithm is used to convert the micropore optical load into an equivalent heat flux density, and a dynamic temperature-pressure coupling equation is established by combining the thermal expansion effect of high-pressure media. This accurately characterizes the synergistic effect of temperature cycling and pressure fluctuations on the coating surface, providing multiphysics boundary condition inputs for transient analysis of interfacial stress distribution.

[0160] This invention overcomes the distortion in the assessment of prestress and temperature alternation coupling effects by using non-uniform mesh generation and multi-field co-simulation. A hexahedral mesh is used to refine the mesh in the coating-substrate composite interface region, and tetrahedral transition elements are used to divide the micropore edges based on surface roughness parameters, improving the accuracy of stress gradient calculation. An implicit time integration algorithm is used to simultaneously solve the thermo-mechanical coupling equations. A transient solver extracts the peak and distribution data of interface stress, and the extended finite element method and Paris formula are correlated to simulate crack propagation paths and lifetime decay trends, achieving dynamic assessment of the damage index under composite loading.

[0161] This invention optimizes the coating performance prediction model through closed-loop verification using experimental and simulation data. The interfacial peel strength output from fracture mechanics analysis is compared with the residuals from high / low temperature and pressure combined test data. The material's thermal expansion coefficient and interfacial strength parameters are dynamically corrected using the least squares method. Based on failure mode data from accelerated life testing, the fracture toughness parameters of the material constitutive model are corrected, generating a calibrated multi-parameter collaborative optimization path. This results in a coating compressive strength enhancement scheme that matches the target service conditions, overcoming the limitations of existing models in predicting life under complex operating conditions.

[0162] The specific implementation of this invention is as follows: Based on a coating performance simulation method using high and low temperature cycling and prestress loading, the surface morphology scanning data of the pipe or component is first acquired using a 3D laser scanner. Internal pressure distribution, temperature gradient, and high-pressure medium material parameters are then obtained using pressure sensors and thermocouples. Based on the measured data, the composite geometric model of the coating substrate is reconstructed in 3D modeling software. A reverse engineering algorithm is used to denoise and reconstruct the topology of the point cloud data of the microporous structure, generating a parametric model containing pore size, distribution density, and interface curvature features. Surface roughness parameters of the interface region are extracted using a curvature analysis tool, providing geometric feature input for subsequent mesh generation.

[0163] In the finite element simulation platform, the thermal expansion coefficient and pressure-temperature correlation characteristics of the high-pressure medium are used to calculate the pressure fluctuation curve caused by the thermal expansion of the medium under temperature cycling through fluid dynamics simulation. Based on the heat conduction equation and the elasticity equation, the pressure fluctuation is correlated with the thermal conductivity and elastic modulus parameters of the coating and the substrate to establish a dynamic temperature-pressure coupling equation. The scattering effect of the microporous structure on the local heat flow distribution is quantified by the ray tracing algorithm to generate a non-uniform heat flow load distribution map, which is then input into the simulation platform as a transient thermal boundary condition. A hexahedral mesh is used to refine the mesh in the coating-substrate composite interface region, and tetrahedral transition elements are used to divide the micropore edges in combination with surface roughness parameters. An adaptive time step control module is used to balance computational efficiency and accuracy.

[0164] The thermo-mechanical coupling equations are solved using an implicit time integration algorithm, and temperature cycling and prestressing are applied stepwise to extract peak and distribution data of interfacial stress. Crack initiation paths are simulated using the extended finite element method, and lifetime decay curves under different temperature cycles are predicted using the Paris formula. The interfacial peel strength output from the simulation is compared with the residuals from high-low temperature-pressure joint test data, and the thermal expansion coefficient and interfacial strength parameters of the coating material are dynamically corrected using the least squares method. Failure mode data are collected through accelerated life testing, and the fracture toughness parameters of the material constitutive model are optimized. A calibrated multi-parameter collaborative optimization path is generated, outputting a coating pressure resistance improvement scheme matched to the service conditions of high-pressure pipelines, achieving high-precision simulation of interfacial stress distribution and lifetime prediction under complex working conditions.

Claims

1. A simulation method for coating performance based on high and low temperature cycling and prestress loading, characterized in that, include: Acquire measured operating condition data of pipelines or components, including internal pressure distribution, temperature gradient, high-pressure medium material parameters and surface morphology scanning data, and construct a composite geometric model of coating substrate based on the measured operating condition data; The microporous structure in the surface morphology scanning data of the measured working condition data is converted into a digital model. The optical load distribution is calculated based on the geometric features of the microporous structure. The digital model and the optical load distribution are imported into the composite geometric model of the coating and substrate to obtain the mechanical and thermal property parameters of the coating and substrate materials. The mechanical and thermal properties of the coating and substrate materials are imported into a pre-set finite element simulation platform, and a dynamic temperature-pressure coupling equation is generated based on the thermal expansion characteristics of the high-pressure medium. In the finite element simulation platform, a thermo-mechanical coupling analysis is performed, the prestress and temperature cycle range are set, the temperature field and stress field are associated based on the dynamic thermo-pressure coupling equation, and the optical load distribution is converted into an equivalent heat flux density and superimposed on the thermal boundary condition of the coating surface through a ray tracing algorithm. The coating-substrate composite interface region and micropore region of the coating-substrate composite geometric model are divided into non-uniform meshes. The coating-substrate composite interface region adopts a hexahedral-dominated fine mesh, and the micropore edges adopt a tetrahedral transition mesh. In the finite element simulation platform, temperature cycling and prestress are applied step by step. The superposition value of thermal stress and mechanical stress at each time step is calculated by the transient solver, and the stress peak value and distribution data of the composite interface region of the coating substrate are extracted. The stress peak value and distribution data are input into the fracture mechanics analysis module. The crack propagation direction is determined based on the stress intensity factor. The damage index and remaining life under cyclic loading are calculated by combining the fatigue cumulative damage model.

2. The coating performance simulation method based on high and low temperature cycling and prestress loading according to claim 1, characterized in that, The steps for constructing the composite geometric model of the coating substrate include: A parametric model matching the pipes or components in the measured working condition data is generated through a preset 3D modeling platform. The coating thickness and substrate size of the parametric model are consistent with the measured data. The micropore size and distribution density in the surface morphology scanning data are converted into the topology of the coating substrate composite geometric model using reverse engineering methods; Based on the curvature characteristics of the surface topography scanning data, the curvature characteristics of the coating-substrate composite interface region are marked in the coating-substrate composite geometric model, and surface roughness parameters are generated. The high-stress gradient region in the composite geometric model of the coating substrate is automatically refined using an adaptive mesh generation tool. The mesh convergence is verified based on the surface roughness parameter to control the iteration residual threshold.

3. The coating performance simulation method based on high and low temperature cycling and prestress loading according to claim 2, characterized in that, The steps for generating the dynamic temperature-pressure coupling equation include: The high-pressure medium material parameters in the measured working condition data are called up. The high-pressure medium material parameters include the coefficient of thermal expansion and the pressure-temperature correlation characteristics. The pressure fluctuation curve caused by the thermal expansion of the high-pressure medium under the temperature cycling conditions was calculated using fluid dynamics simulation. By correlating the pressure fluctuation curve with the thermophysical parameters of the coating and the substrate, a dynamic coupling equation between the temperature field and the stress field is established. The dynamic coupling equation is input into the thermo-mechanical coupling analysis of the finite element simulation platform as the boundary condition for transient loading.

4. The coating performance simulation method based on high and low temperature cycling and prestress loading according to claim 3, characterized in that, The steps for setting the prestress and temperature cycling range include: In the thermo-mechanical coupling analysis of the finite element simulation platform, the medium pressure is defined as the initial prestress loading value, and the medium pressure is matched with the characteristics of the high-pressure medium; The influence of the microporous structure of the coating substrate composite geometry model on the local heat distribution is quantified by the ray tracing algorithm described above, and a non-uniform heat flux load distribution map is generated. The heat flux load distribution map is input into the optical heat transfer interface of the finite element simulation platform, and the temperature gradient change on the coating surface is calculated based on the dynamic temperature-pressure coupling equation. The temperature gradient change is transiently coupled with the mechanical stress field in the thermo-mechanical coupling analysis to output the stress superposition result in the time domain.

5. The coating performance simulation method based on high and low temperature cycling and prestress loading according to claim 4, characterized in that, The steps of non-uniform mesh generation include: Based on the stress gradient distribution of the coating-substrate composite interface region in the coating-substrate composite geometric model, a hexahedral-dominated fine mesh is divided, and tetrahedral transition units are set at the micropore edges based on the generated surface roughness parameters. An implicit time integration algorithm is used to solve the established dynamic temperature-pressure coupling equation, and an adaptive time step is set to balance the calculation accuracy and efficiency. The stress-strain curves during the heating and cooling stages in the finite element simulation platform are automatically extracted using scripts to identify the critical inflection point of peel stress in the composite interface region of the coating substrate. By comparing the critical inflection point with the mesh convergence analysis results, the mesh density of the coating-matrix composite geometric model is dynamically adjusted to optimize computational stability.

6. The coating performance simulation method based on high and low temperature cycling and prestress loading according to claim 5, characterized in that, The steps for calculating the damage index and remaining life under cyclic loading using the fatigue cumulative damage model include: simulating the interface delamination crack initiation path of the coating substrate composite geometric model using the extended finite element method; obtaining the correlation data between crack propagation rate and stress distribution based on the extracted stress peak and distribution data; and establishing a fatigue crack propagation model based on the Paris formula to predict the life decay curve under different temperature cycles. The stress cloud map and interface peeling stress distribution map in the finite element simulation platform are generated by the preset post-processing platform, and the optimized high stress concentration area is located according to the stress cloud map. Based on the distribution data of the high stress concentration area, the component ratio of the coating material is adjusted in reverse to generate a multi-parameter collaborative optimization model corresponding to the lifetime decay curve.

7. The coating performance simulation method based on high and low temperature cycling and prestress loading according to claim 6, characterized in that, Also includes: The interfacial peel strength output by the fracture mechanics analysis module is compared with the residual data from the actual high and low temperature-pressure combined test. The thermal expansion coefficient of the coating material and the interface strength parameters generated therein are dynamically updated by fitting the deviation between the simulation and experimental results using the least squares method. Accelerated life tests were set up to collect failure mode data under combined loads, and the fracture toughness parameters of the material constitutive model in the dynamic thermo-pressure coupling equation were corrected. The remaining lifetime is recalculated based on the corrected model parameters, and the calibrated coating compressive strength optimization path corresponding to the multi-parameter collaborative optimization model is output.

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