A method for simulating corrosion morphology evolution

Abstract

A corrosion morphology evolution simulation method, involving a metal corrosion surface reconstruction modeling method, includes the following steps: S1: extracting characteristic parameters of corrosion evolution at different corrosion stages; S2: establishing an initial uniform corrosion model; S3: randomly generating an initial pitting corrosion model based on the initial pit morphology and initial mass loss rate; S4: establishing the current uniform corrosion model using a thickness reduction method based on the current uniform corrosion thickness; S5: generating the current pitting corrosion model by keeping the pit positions in the initial pitting corrosion model unchanged, determining the mean pit size growth value based on the current pit morphology, and controlling the random distribution range of the pit size based on the current pitting mass loss rate; S6: subtracting the current pitting corrosion model from the current uniform corrosion model to obtain a corrosion morphology evolution model; S7: repeating S4-S6 to establish morphology models at different corrosion stages; and S8: meshing and numerical calculation. This method can simulate the random distribution and in-situ growth characteristics of pits in real corrosion evolution.

Description

Technical Field

[0001] The invention relates to a metal corrosion surface reconstruction modeling method, and in particular to a corrosion morphology evolution simulation method. Background Art

[0002] Steel structures, due to their lightweight and high-strength properties, are widely used in architectural structures, bridge structures, and offshore wind power. However, steel or steel components are subject to environmental corrosion during long-term service. Corrosion reduces the overall thickness of the steel and creates surface roughness due to differences in the local environment surrounding the corroded surface. Both factors degrade its mechanical properties, thereby affecting the durability and safety of the structure. Restoring the true morphology of metal surfaces after corrosion in finite element software is fundamental to analyzing the mechanical properties of steel structures, further allowing for consideration of the overall performance of degraded steel structures.

[0003] Currently, common modeling methods do not match corrosion parameters at different stages or use regular geometric shapes to simulate corroded concave and convex surfaces. This can lead to inaccurate simulation results that differ significantly from corrosion tests or actual post-corrosion surface morphologies. Some 3D topology methods based on inverse modeling can partially restore the actual morphology, but the topology area and roughness are small, resulting in low efficiency and an inability to reflect the impact of comprehensive corrosion on structural stress distribution. Therefore, in order to accurately characterize the impact of post-corrosion surface morphology on structural mechanical properties, 3D reconstruction modeling of the corroded metal surface is required. Summary of the Invention

[0004] The technical problem to be solved by the present invention is to provide a corrosion morphology evolution simulation method, which uses a three-dimensional scanner and a weighing scale to effectively count the corrosion parameters. During the modeling process, the macro parameters and micro morphology describing the corrosion are considered to be consistent, further realizing the simulation and iteration of corrosion damage. The method can be used for finite element modeling of steel with different corrosion degrees, computational analysis of corroded steel structures, and residual mechanical property evaluation.

[0005] The technical solution adopted by the present invention to solve the technical problem is: a corrosion morphology evolution simulation method, comprising the following steps:

[0006] S1: Extract corrosion evolution characteristic parameters at different corrosion stages, including pit morphology, uniform corrosion thickness, and mass loss rate;

[0007] S2: Based on the initial uniform corrosion thickness, the initial uniform corrosion model is established by the thickness reduction method;

[0008] S3: Randomly generate an initial pitting corrosion model based on the initial pit morphology and initial mass loss rate, and subtract the initial pitting corrosion model from the initial uniform corrosion model to obtain the initial corrosion model;

[0009] S4: Based on the current uniform corrosion thickness, the current uniform corrosion model is established by the thickness reduction method to calculate the current pitting corrosion mass loss rate;

[0010] S5: The pit positions in the initial pitting corrosion model remain unchanged, the mean pit size growth value is determined based on the current pit morphology, and the random distribution range of the pit size is controlled based on the current pitting corrosion mass loss rate to generate the current pitting corrosion model;

[0011] S6: The current uniform corrosion model is subtracted from the current pitting corrosion model to obtain the corrosion morphology evolution model;

[0012] S7: Repeat S4-S6 to establish morphology models at different corrosion stages;

[0013] S8: Meshing, numerical calculation.

[0014] Furthermore, in step S1, the corrosion evolution characteristics at different corrosion stages are samples of the same specifications at different corrosion time stages under the same corrosion environment; after rust removal and cleaning of the samples at different corrosion stages, a three-dimensional scanner is used to obtain a three-dimensional point cloud model of the corrosion surface morphology, and the three-dimensional point cloud model of the surface morphology is further processed to obtain the corrosion evolution characteristic parameters at different corrosion stages; wherein, the pit morphology includes the pit depth h, the diameter-to-depth ratio R, the pit fusion degree n, the uniform corrosion thickness is characterized by t, and the mass loss rate is characterized by η.

[0015] Furthermore, in step S1, the corrosion evolution characteristic parameter calculation step is specifically as follows:

[0016] Taking the uncorroded surface of the sample as the zero reference plane, an xyz rectangular coordinate system is established in the three-dimensional point cloud model of the corroded surface of the sample, where the xy plane coincides with the zero reference plane, and the coordinates of any scanning point i on the corroded surface are obtained (x i ,y i ,z i ), the minimum z coordinate value of all scanning points in the corrosion area is the uniform corrosion thickness t;

[0017] The number of pits within the range of the three-dimensional point cloud model of the corrosion surface is counted. For each pit, the average pit diameter d and pit depth h are calculated. The pit depth is the maximum depth of the current pit relative to the uncorroded surface minus the uniform corrosion thickness. The following calculation method is used to obtain it: h = max(z i )-t;

[0018] The diameter-to-depth ratio R is the ratio of the average diameter d of the etch pit to the depth h of the etch pit. The diameter-to-depth ratio R of each etch pit is calculated and the statistical value of the diameter-to-depth ratio is calculated;

[0019] The pit fusion degree n is the ratio of the distance between the center points of adjacent pits to the sum of the average radius of the pits. The specific calculation formula is: , calculate the pit fusion degree n of any adjacent pits and calculate the pit fusion degree statistics;

[0020] The distribution law of the surface pit depth h during the corrosion stage was fitted with the normal distribution to obtain the normal distribution parameters normal (μ, σ), where μ is the mean pit depth and σ is the variance of the pit depth.

[0021] The mass loss rate η is the ratio of the difference between the initial mass m0 of the sample and the residual mass m of the corrosion sample divided by the initial mass m0. The specific calculation formula is: η=(m0-m) / m0; the mass loss rate η includes the uniform corrosion mass loss rate η j and pitting mass loss rate η d ; Uniform corrosion mass loss rate η j The volume loss rate can be calculated based on the uniform corrosion thickness t and the initial thickness D of the sample. The specific calculation formula is: η j =t / D; the calculation method of pitting mass loss rate is η d =η-η j .

[0022] Furthermore, in step S2, the specific implementation method is as follows: assuming that the initial uniform corrosion thickness is t1, the sample thickness after subtracting the initial uniform corrosion thickness from the initial thickness D of the sample is D-t1, the plane size is determined by the corrosion surface range, and the initial uniform corrosion model is established with the thickness after thickness reduction D-t1.

[0023] Furthermore, in step S3, the initial pitting corrosion model is a randomly distributed pit ellipsoid, and the specific generation method includes:

[0024] S31: Based on the initial uniform corrosion surface, a uniform random distribution function is used to generate Q number of pit center points within the corrosion surface range, and the distance between two adjacent center points is controlled by the pit fusion degree n;

[0025] S32: Generate an elliptical pitting sphere at the center of each pit with a diameter-to-depth ratio R and a depth that conforms to the normal distribution parameters normal(μ1,σ1), where μ1 is the mean pit depth in the initial corrosion stage and σ1 is the variance of the pit depth in the initial corrosion stage;

[0026] S33: Calculate the 0.5 times volume of all generated pitting spheres and calculate the current pitting volume loss rate , where A is the area of ​​the corroded surface;

[0027] S34: Compare the current pitting volume loss rate η dv The actual pitting mass loss rate η at the current stage d : If η dv <η d, then increase the number of pitting Q, repeat S32, S33 until 0.95η d <η dv <1.05η d If η dv >η d , then reduce the number of pitting Q, repeat S32, S33 until 0.95η d <η dv <1.05η d , generate the initial pitting corrosion model.

[0028] Furthermore, in step S4, the specific implementation method is: assuming that the uniform corrosion thickness in the current corrosion stage is t i , then the thickness of the sample after deducting the current uniform corrosion thickness from the initial thickness D of the sample is Dt i The plane size is determined by the corrosion surface range and the thickness Dt after thickness reduction is determined by the corrosion surface range and the plane size ... i Establish the current uniform corrosion model.

[0029] Furthermore, in step S5, the specific generation method includes:

[0030] S51: Based on the current uniformly corroded surface, determine the location of the pitting center point in the initial pitting model;

[0031] S52: Based on the pit depth h of the current corrosion stage i The normal distribution parameter normal(μ i , σ i ) and the diameter-to-depth ratio R, and limit the pit depth h i The upper limit is close to μ i +2σ i , the lower limit is close to μ i -2σ i , satisfying the pit depth h i The confidence interval is above 95%, and an elliptical pitting sphere is generated at the center of each pit; i is the mean pit depth in the current corrosion stage, σ i is the variance of the pit depth in the current corrosion stage;

[0032] S53: Calculate the 0.5 times volume of all generated pitting spheres and calculate the current pitting volume loss rate , where A is the area of ​​the corroded surface;

[0033] S54: Compare the current pitting volume loss rate (η dv ) i Compared with the actual pitting mass loss rate (η d ) i :If (η dv ) i>(η d ) i , then reduce the pit depth h i Random distribution range, repeat S52, S53 until 0.95 (η d ) i <(η dv ) i <1.05(η d ) i ; If (η dv ) i <(η d ) i , then the pit depth h is enlarged i Random distribution range, repeat S52, S53 until 0.95 (η d ) i <(η dv ) i <1.05(η d ) i .

[0034] Furthermore, in step S6, the specific implementation method is: the current pitting corrosion model generated by solid sectioning is removed from the current uniform corrosion model, and the remaining entity after sectioning is the corrosion morphology model considering uniform corrosion and pitting corrosion.

[0035] Furthermore, in step S8, the meshing method includes using triangular meshes to perform surface meshing on the irregular corrosion surface, and using tetrahedral elements to perform volume element meshing on the corrosion sample based on the meshed surface.

[0036] Compared with the existing technology, the present invention has the following beneficial effects: by characterizing the real corrosion surface based on the specific parameters of pit morphology, uniform corrosion thickness, and mass loss rate, the random characteristics of pits in terms of depth, size, position and number are taken into account, and the mass loss rate and pitting parameter characteristics at different corrosion stages are used to control the evolution and generation of the apparent morphological characteristics at different corrosion stages, thereby realizing the scientific expression and fitting reconstruction of the corrosion morphology; the initial pit positions used in the pit generation and reconstruction are randomly generated, the pit positions are fixed during the evolution stage, and the random growth method of the pit depth and size can effectively simulate the actual evolution process of the initial random corrosion in the actual corrosion process and the in-situ growth of the pits after they appear. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 This is a flow chart of a corrosion morphology evolution simulation method of the present invention;

[0038] Figure 2 Schematic diagram of corrosion morphology and 3D scanning point cloud model;

[0039] Figure 3Schematic diagram of calculating corrosion evolution characteristic parameters based on the three-dimensional point cloud model of corrosion morphology;

[0040] Figure 4 This is a schematic diagram of the fitting of the etch pit depth distribution parameters;

[0041] Figure 5 Create a schematic diagram for the uniform corrosion model;

[0042] Figure 6 Schematic diagram of the corrosion model;

[0043] Figure 7 Schematic diagram of the pit depth control method when generating a pitted sphere;

[0044] Figure 8 Generate an overall implementation flow chart for the corrosion morphology model considering uniform corrosion and pitting corrosion;

[0045] Figure 9 Generate the effect of corrosion morphology evolution model at different corrosion stages;

[0046] Figure 10 Schematic diagram of the effect of generating a comprehensive corrosion morphology model. DETAILED DESCRIPTION

[0047] In order to make the technical problems, technical solutions and beneficial effects solved by the present invention more clearly understood, the present invention is further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0048] Reference Figure 1 This embodiment provides a corrosion morphology evolution simulation method, comprising the following steps:

[0049] S1: Extract corrosion evolution characteristic parameters at different corrosion stages, including pit morphology, uniform corrosion thickness, and mass loss rate;

[0050] S2: Based on the initial uniform corrosion thickness, the initial uniform corrosion model is established by the thickness reduction method;

[0051] S3: Randomly generate an initial pitting corrosion model based on the initial pit morphology and initial mass loss rate, and subtract the initial pitting corrosion model from the initial uniform corrosion model to obtain the initial corrosion model;

[0052] S4: Based on the current uniform corrosion thickness, the current uniform corrosion model is established by the thickness reduction method to calculate the current pitting corrosion mass loss rate;

[0053] S5: The pit positions in the initial pitting corrosion model remain unchanged, the mean pit size growth value is determined based on the current pit morphology, and the random distribution range of the pit size is controlled based on the current pitting corrosion mass loss rate to generate the current pitting corrosion model;

[0054] S6: The current uniform corrosion model is subtracted from the current pitting corrosion model to obtain the corrosion morphology evolution model;

[0055] S7: Repeat S4-S6 to establish morphology models at different corrosion stages;

[0056] S8: Meshing, numerical calculation.

[0057] Specifically, step S1 is to obtain samples of the same specifications under the same corrosion environment at different corrosion time stages, and use a three-dimensional scanner to obtain a three-dimensional point cloud model of the corrosion surface morphology after cleaning the samples at different corrosion stages, such as Figure 2 As shown in the figure, the corrosion evolution characteristic parameters at different corrosion stages are obtained, where the pit morphology includes the pit depth h, the diameter-to-depth ratio R, the pit fusion degree n, the uniform corrosion thickness is characterized by t, and the mass loss rate is characterized by η.

[0058] In step S1, the corrosion evolution characteristic parameter calculation steps are as follows:

[0059] like Figure 3 As shown in the figure, the uncorroded surface of the sample is taken as the zero reference plane, and an xyz rectangular coordinate system is established in the three-dimensional point cloud model of the corroded surface of the sample, where the xy plane coincides with the zero reference plane, and the coordinates of any scanning point i on the corroded surface are obtained (x i ,y i ,z i ), the minimum z coordinate value of all scanning points in the corrosion area is the uniform corrosion thickness t;

[0060] Based on the three-dimensional point cloud model of the corrosion surface, the number of corrosion pits within the range is counted. For each corrosion pit, the average diameter d and the depth h of the corrosion pit are calculated respectively. The corrosion pit depth is the maximum depth of the current corrosion pit relative to the uncorroded surface minus the uniform corrosion thickness, and is obtained by the following calculation method: h = max(z i )-t;

[0061] The diameter-to-depth ratio R is the ratio of the average pit diameter d to the pit depth h, such as Figure 3 As shown, the diameter-to-depth ratio R of each etch pit is calculated and the statistical value of the diameter-to-depth ratio is calculated (the average value is taken);

[0062] The pit fusion degree n is the ratio of the distance between the center points of adjacent pits to the sum of the average radius of the pits. The specific calculation formula is: , calculate the pit fusion degree n of any adjacent pits and calculate the statistical value of the pit fusion degree (take the mean);

[0063] The distribution law of the surface pit depth h in the corrosion stage is fitted with the normal distribution to obtain the normal distribution parameters normal (μ, σ), where μ is the mean of the pit depth and σ is the variance of the pit depth, as shown in Figure 4 As shown;

[0064] The mass loss rate η is the ratio of the difference between the initial mass m0 of the sample and the residual mass m of the corrosion sample divided by the initial mass m0. The specific calculation formula is: η=(m0-m) / m0; the mass loss rate η includes the uniform corrosion mass loss rate η j and pitting mass loss rate η d ; Uniform corrosion mass loss rate η j The volume loss rate can be calculated based on the uniform corrosion thickness t and the initial thickness D of the sample. The specific calculation formula is: η j =t / D; the calculation method of pitting mass loss rate is η d =η-η j .

[0065] Specifically, if Figure 5 As shown, in step S2, it is assumed that the initial uniform corrosion thickness is t1, then the sample thickness after subtracting the initial uniform corrosion thickness from the initial thickness D of the sample is D-t1, the plane size is determined by the corrosion surface range, and the initial uniform corrosion model is established with the thickness D-t1 after thickness reduction.

[0066] Specifically, in step S3, the initial pitting model is a randomly distributed pit ellipsoid, and the specific generation method includes:

[0067] S31: Based on the initial uniform corrosion surface, a uniform random distribution function is used to generate Q number of pit center points within the corrosion surface range, and the distance between two adjacent center points is controlled by the pit fusion degree n. Here, the pit fusion degree n is the actual pit fusion degree statistical value.

[0068] S32: Generate an elliptical pitting sphere at the center of each pit with a diameter-to-depth ratio R and a depth that conforms to the normal distribution parameters normal(μ1,σ1), where μ1 is the mean depth of the pit in the initial corrosion stage and σ1 is the variance of the depth of the pit in the initial corrosion stage; the diameter-to-depth ratio R here is the actual statistical value of the diameter-to-depth ratio;

[0069] S33: Calculate the 0.5 times volume of all generated pitting spheres and calculate the current pitting volume loss rate , where A is the area of ​​the corroded surface;

[0070] S34: Compare the current pitting volume loss rate η dv The actual pitting mass loss rate η at the current stage d : If η dv <η d , then increase the number of pitting Q, repeat S32, S33 until 0.95η d <η dv <1.05η d If ηdv >η d , then reduce the number of pitting Q, repeat S32, S33 until 0.95η d <η dv <1.05η d ; Generate an initial pitting corrosion model.

[0071] Specifically, in step S3, the initial uniform corrosion model is subtracted from the initial pitting corrosion model to obtain the initial corrosion model, such as Figure 6 shown.

[0072] Specifically, in step S4, the initial corrosion model is established, and the subsequent corrosion model iteration is established. According to the uniform corrosion thickness of the current corrosion stage, t i , then the thickness of the sample after deducting the current uniform corrosion thickness from the initial thickness D of the sample is Dt i The plane size is determined by the corrosion surface range and the thickness Dt after thickness reduction is determined by the corrosion surface range and the plane size ... i Establish the current uniform corrosion model.

[0073] Specifically, in step S5, the current pitting corrosion model is generated in the following manner:

[0074] S51: Based on the current uniformly corroded surface, determine the location of the pitting center point in the initial pitting model;

[0075] S52: Based on the pit depth h of the current corrosion stage i The normal distribution parameter normal(μ i , σ i ) and the diameter-to-depth ratio R (the actual diameter-to-depth ratio is taken as the statistical value), and the pit depth h is limited i The upper limit is close to μ i +2σ i , the lower limit is close to μ i -2σ i (like Figure 7 As shown), satisfying the mean pit depth μ i The confidence interval is above 95%, and an elliptical pitting sphere is generated at the center of each pit; i is the mean pit depth in the current corrosion stage, σ i is the variance of the pit depth in the current corrosion stage;

[0076] S53: Calculate the 0.5 times volume of all generated pitting spheres and calculate the current pitting volume loss rate , where A is the area of ​​the corroded surface;

[0077] S54: Compare the current pitting volume loss rate (η dv ) i Compared with the actual pitting mass loss rate (η d) i :If (η dv ) i >(η d ) i , then reduce the pit depth h i Random distribution range, repeat S52, S53 until 0.95 (η d ) i <(η dv ) i <1.05(η d ) i ; If (η dv ) i <(η d ) i , then the pit depth h is enlarged i Random distribution range, repeat S52, S53 until 0.95 (η d ) i <(η dv ) i <1.05(η d ) i .

[0078] Specifically, in step S6, the current pitting corrosion model is generated by cutting the current uniform corrosion model in a solid sectioning manner, and the remaining solid after the sectioning is the corrosion morphology model considering uniform corrosion and pitting corrosion.

[0079] Specifically, step S7, repeat S4-S6 to establish morphology models at different corrosion stages. The overall implementation flow chart is as follows: Figure 8 As shown in the figure, the morphology simulation effects of different corrosion stages are achieved as shown in the figure. Figure 9 shown.

[0080] Specifically, step S8 is to use triangular mesh to divide the irregular corrosion surface. Based on the divided surface mesh, the corrosion sample is divided into volume units using tetrahedron units. The process is as follows: Figure 10 shown.

[0081] The present invention characterizes the real corroded surface based on the specific parameters of pit morphology, uniform corrosion thickness, and mass loss rate, taking into account the random characteristics of pits in terms of depth, size, position and number, and controls the evolution of surface morphology characteristics at different corrosion stages with the mass loss rate and pitting parameter characteristics at different corrosion stages, thereby achieving scientific expression and fitting reconstruction of the corrosion morphology; the initial pit positions used in the pit generation and reconstruction are randomly generated, the pit positions are fixed during the evolution stage, and the random growth mode of the pit depth and size can effectively simulate the actual evolution process of the initial random corrosion in the actual corrosion process and the in-situ growth of the pits after they appear.

Claims

1. A corrosion morphology evolution simulation method, characterized in that: The following steps are involved: S1: Extract corrosion evolution characteristic parameters at different corrosion stages, including pit morphology, uniform corrosion thickness, and mass loss rate; S2: Based on the initial uniform corrosion thickness, the initial uniform corrosion model is established by the thickness reduction method; S3: Randomly generate an initial pitting corrosion model based on the initial pit morphology and initial mass loss rate, and subtract the initial pitting corrosion model from the initial uniform corrosion model to obtain the initial corrosion model; S4: Based on the current uniform corrosion thickness, the current uniform corrosion model is established by the thickness reduction method to calculate the current pitting corrosion mass loss rate; S5: The pit positions in the initial pitting corrosion model remain unchanged, the mean pit size growth value is determined based on the current pit morphology, and the random distribution range of the pit size is controlled based on the current pitting corrosion mass loss rate to generate the current pitting corrosion model; S6: The current uniform corrosion model is subtracted from the current pitting corrosion model to obtain the corrosion morphology evolution model; S7: Repeat S4-S6 to establish morphology models at different corrosion stages; S8: Meshing, numerical calculation; In step S3, the initial pitting model is a randomly distributed pit ellipsoid, and the specific generation method includes: S31: Based on the initial uniform corrosion surface, a uniform random distribution function is used to generate Q number of pit center points within the corrosion surface range, and the distance between two adjacent center points is controlled by the pit fusion degree n; S32: Generate an elliptical pitting sphere at the center of each pit with a diameter-to-depth ratio R and a depth that conforms to the normal distribution parameters normal(μ1,σ1), where μ1 is the mean pit depth in the initial corrosion stage and σ1 is the variance of the pit depth in the initial corrosion stage; S33: Calculate the 0.5 times volume of all generated pitting spheres and calculate the current pitting volume loss rate , where A is the area of ​​the corroded surface, d is the average diameter of the corrosion pit, h is the depth of the corrosion pit, D is the initial thickness of the specimen, and t1 is the initial uniform corrosion thickness; S34: Compare the current pitting volume loss rate η dv The actual pitting mass loss rate η at the current stage d : If η dv <η d , then increase the number of pitting Q, repeat S32, S33 until 0.95η d <η dv <1.05η d If η dv >η d , then reduce the number of pitting Q, repeat S32, S33 until 0.95η d <η dv <1.05η d , generate the initial pitting corrosion model; In step S5, the specific generation method includes: S51: Based on the current uniformly corroded surface, determine the location of the pitting center point in the initial pitting model; S52: Based on the pit depth h of the current corrosion stage i The normal distribution parameter normal(μ i , σ i ) and the diameter-to-depth ratio R, and limit the pit depth h i The upper limit is close to μ i +2σ i , the lower limit is close to μ i -2σ i , the confidence interval of the pit depth hi is above 95%, and an elliptical pitting sphere is generated at the center of each pit; where μ i is the mean pit depth in the current corrosion stage, σ i is the variance of the pit depth in the current corrosion stage; S53: Calculate the 0.5 times volume of all generated pitting spheres and calculate the current pitting volume loss rate , where A is the area of ​​the corroded surface, d is the average diameter of the pit, h is the depth of the pit, D is the initial thickness of the sample, and t i is the uniform corrosion thickness at the current corrosion stage; S54: Compare the current pitting volume loss rate (η dv ) i Compared with the actual pitting mass loss rate (η d ) i :If (η dv ) i >(η d ) i , then reduce the pit depth h i Random distribution range, repeat S52, S53 until 0.95 (η d ) i <(η dv ) i <1.05(η d ) i ; If (η dv ) i <(η d ) i , then the pit depth h is enlarged i Random distribution range, repeat S52, S53 until 0.95 (η d ) i <(η dv ) i <1.05(η d ) i .

2. The corrosion morphology evolution simulation method according to claim 1, characterized in that: In step S1, the corrosion evolution characteristics at different corrosion stages are samples of the same specifications at different corrosion time stages under the same corrosion environment; after rust removal and cleaning of the samples at different corrosion stages, a three-dimensional scanner is used to obtain a three-dimensional point cloud model of the corrosion surface morphology, and the three-dimensional point cloud model of the surface morphology is further processed to obtain the corrosion evolution characteristic parameters at different corrosion stages; among them, the pit morphology includes the pit depth h, the diameter-to-depth ratio R, the pit fusion degree n, the uniform corrosion thickness is characterized by t, and the mass loss rate is characterized by η.

3. The corrosion morphology evolution simulation method according to claim 2, characterized in that: In step S1, the corrosion evolution characteristic parameter calculation steps are as follows: Taking the uncorroded surface of the sample as the zero reference plane, an xyz rectangular coordinate system is established in the three-dimensional point cloud model of the corroded surface of the sample, where the xy plane coincides with the zero reference plane, and the coordinates of any scanning point i on the corroded surface are obtained (x i ,y i ,z i ), the minimum z coordinate value of all scanning points in the corrosion area is the uniform corrosion thickness t; Based on the three-dimensional point cloud model of the corrosion surface, the number of corrosion pits within the range is counted. For each corrosion pit, the average diameter d and the depth h of the corrosion pit are calculated respectively. The corrosion pit depth is the maximum depth of the current corrosion pit relative to the uncorroded surface minus the uniform corrosion thickness, and is obtained by the following calculation method: h = max(z i )-t; The diameter-to-depth ratio R is the ratio of the average diameter d of the etch pit to the depth h of the etch pit. The diameter-to-depth ratio R of each etch pit is calculated and the statistical value of the diameter-to-depth ratio is calculated; The pit fusion degree n is the ratio of the distance between the center points of adjacent pits to the sum of the average radius of the pits. The specific calculation formula is: , calculate the pit fusion degree n of any adjacent pits and calculate the pit fusion degree statistics; The distribution law of the surface pit depth h during the corrosion stage was fitted with the normal distribution to obtain the normal distribution parameters normal (μ, σ), where μ is the mean pit depth and σ is the variance of the pit depth. The mass loss rate η is the ratio of the difference between the initial mass m0 of the sample and the residual mass m of the corrosion sample divided by the initial mass m0. The specific calculation formula is: η = (m0-m) / m0; the mass loss rate η includes the uniform corrosion mass loss rate η j and pitting mass loss rate η d ; Uniform corrosion mass loss rate η j The volume loss rate can be calculated based on the uniform corrosion thickness t and the initial thickness D of the sample. The specific calculation formula is: η j =t / D; the calculation method of pitting mass loss rate is η d =η-η j .

4. The corrosion morphology evolution simulation method according to claim 1, characterized in that: In step S2, the specific implementation method is: assuming that the initial uniform corrosion thickness is t1, the sample thickness after subtracting the initial uniform corrosion thickness from the initial thickness D of the sample is D-t1, the plane size is determined by the corrosion surface range, and the initial uniform corrosion model is established with the thickness D-t1 after thickness reduction.

5. The corrosion morphology evolution simulation method according to claim 1, characterized in that: In step S4, the specific implementation method is: assuming that the uniform corrosion thickness in the current corrosion stage is t i , then the thickness of the sample after deducting the current uniform corrosion thickness from the initial thickness D of the sample is Dt i The plane size is determined by the corrosion surface range and the thickness Dt after thickness reduction is determined by the corrosion surface range and the plane size ... i Establish the current uniform corrosion model.

6. The corrosion morphology evolution simulation method according to claim 1, characterized in that: In step S6, the specific implementation method is: the current pitting corrosion model generated by solid sectioning is cut off from the current uniform corrosion model, and the remaining entity after sectioning is the corrosion morphology model considering uniform corrosion and pitting corrosion.

7. The corrosion morphology evolution simulation method according to claim 1, characterized in that: In step S8, the meshing method includes using triangular meshes to perform surface division on the irregular corrosion surface; and using tetrahedral units to perform volume unit division on the corrosion sample based on the divided surface meshes.

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