Corrosion morphology evolution simulation method

Abstract

A corrosion morphology evolution simulation method relates to a metal corrosion surface reconstruction modeling method, and comprises the following steps: S1, extracting corrosion evolution characteristic parameters under different corrosion stages; s2, establishing an initial uniform corrosion model; s3, randomly generating an initial pitting corrosion model based on the initial corrosion pit morphology and the initial mass loss rate; s4, establishing a current uniform corrosion model by a thickness reduction method based on the current uniform corrosion thickness; s5, the position of the corrosion pit in the initial pitting model is not changed, the average increase value of the size of the corrosion pit is determined according to the shape of the current corrosion pit, the random distribution range of the size of the corrosion pit is controlled according to the current pitting mass loss rate, and a current pitting model is generated; s6, deducting the current pitting corrosion model from the current uniform corrosion model to obtain a corrosion morphology evolution model; s7, repeating the steps S4-S6 to establish morphology models at different corrosion stages; and S8, carrying out grid division and numerical calculation. The method can simulate random distribution and in-situ growth characteristics of corrosion 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 have been widely used in the fields of building structures, bridge structures, and offshore wind power due to their light weight and high strength. Steel or steel components will be subject to environmental corrosion during long-term service. On the one hand, corrosion will cause an overall reduction in the thickness of the steel. On the other hand, the difference in the local environment of the corrosion surface will cause the surface to be rough and uneven. Both factors will degrade its mechanical properties, thereby affecting the durability and safety of the structure. The restoration of the true morphology of the metal surface after corrosion in finite element software is the basis for analyzing the mechanical properties of steel structures, and further considering the overall performance of degraded steel structures.

[0003] The current common modeling methods do not match the corrosion parameters of different stages or use regular geometric shapes to simulate the corroded concave and convex surfaces, which are very different from the corrosion test or the actual surface morphology after corrosion, resulting in inaccurate simulation results. Although some three-dimensional topological methods based on reverse modeling can restore part of the real morphology, the topological area and roughness are small, the efficiency is low, and it cannot reflect the impact of comprehensive corrosion on the structural stress distribution. Therefore, in order to finely characterize the impact of the surface morphology after corrosion on the mechanical properties of the structure, it is necessary to reconstruct and model the metal surface after corrosion in three dimensions. Summary of the invention

[0004] The technical problem to be solved by the present invention is to provide a method for simulating the evolution of corrosion morphology, which effectively counts the corrosion parameters using a three-dimensional scanner and a weighing scale, and in the modeling process, considers matching the macroscopic parameters and microscopic morphology that characterize the corrosion, so as to further realize the simulation of corrosion damage and the iteration of corrosion damage; the method can be used for finite element modeling of steel with different corrosion degrees, and for computational analysis of corroded steel structures and evaluation of residual mechanical properties.

[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: S1: Extract the characteristic parameters of corrosion evolution 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 the initial mass loss rate, and deduct 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 using the thickness reduction method to calculate the current pitting mass loss rate; S5: The pit position in the initial pitting model remains unchanged, the mean value of the pit size growth is determined by the current pit morphology, and the random distribution range of the pit size is controlled by the current pitting mass loss rate to generate the current pitting 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.

[0006] 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 pit depth h, diameter-to-depth ratio R, pit fusion degree n, the uniform corrosion thickness is characterized by t, and the mass loss rate is characterized by η.

[0007] Furthermore, in step S1, the corrosion evolution characteristic parameter calculation step is specifically 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 sample corrosion surface, where the xy plane coincides with the zero reference plane, and the coordinates of any scanning point i on the corrosion surface are obtained (x i ,y i ,z i ), the minimum value of the z coordinate 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 pits within the statistical range is calculated. For each pit, the average diameter d and pit depth h of the pit are calculated respectively. The pit depth is the maximum depth of the current pit relative to the uncorroded surface minus the uniform corrosion thickness. It 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 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; 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 .

[0008] Furthermore, in step S2, the specific implementation method is: assuming that the initial uniform corrosion thickness is t1, the sample thickness after deducting 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.

[0009] Further, 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 regulated by the pit fusion degree n; S32: Generate an elliptical pitting sphere with a diameter-to-depth ratio R and a depth that conforms to the normal distribution parameters normal(μ1, σ1) at the center of each pit, 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 volume of all generated pitting spheres and calculate the current pitting volume loss rate , where A is the area of ​​the corrosion surface; S34: Compare the current pitting volume loss rate η dv The actual pitting mass loss rate η at the current stage d :such as η dv <η d , then increase the pitting number Q, repeat S32, S33 until 0.95η d <η dv <1.05η d ; such as η dv >η d , then reduce the number of pitting corrosion Q, repeat S32, S33 until 0.95η d <η dv <1.05η d , generate the initial pitting model.

[0010] Further, 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 subtracting the current uniform corrosion thickness from the initial thickness of the sample D is Dt i The plane size is determined by the corrosion surface range, and the thickness after thickness reduction Dt is determined by i Establish the current uniform corrosion model.

[0011] Furthermore, 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 limits 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 at the current corrosion stage, σ i is the pit depth variance in the current corrosion stage; S53: Calculate the 0.5 volume of all generated pitting spheres and calculate the current pitting volume loss rate , where A is the area of ​​the corrosion surface; S54: Compare the current pitting volume loss rate (η dv ) i The actual pitting mass loss rate (η d ) i :As (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 ; such as (η dv ) i <(η d ) i , then the pit depth h is enlarged iRandom distribution range, repeat S52, S53 until 0.95 (η d ) i <(η dv ) i <1.05(η d ) i .

[0012] Furthermore, in step S6, the specific implementation method is: the current pitting corrosion model generated by cutting the current uniform corrosion model in a solid sectioning manner, and the remaining entity after the sectioning is the corrosion morphology model considering uniform corrosion and pitting corrosion.

[0013] Furthermore, in step S8, the meshing method includes using triangular meshes to perform surface division on the irregular corrosion surface. Based on the divided surface meshes, tetrahedral units are used to perform volume unit division on the corrosion sample.

[0014] Compared with the prior art, 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, so as to achieve 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 in the evolution stage, and the random growth method of the pit depth and size can effectively simulate the initial random corrosion in the actual corrosion process, and the actual evolution process of the pits growing in situ after they appear. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 A flowchart of a corrosion morphology evolution simulation method of the present invention; Figure 2 Schematic diagram of corrosion morphology and 3D scanning point cloud model; Figure 3 Schematic diagram of calculating corrosion evolution characteristic parameters based on the three-dimensional point cloud model of corrosion morphology; Figure 4 This is a schematic diagram of the fitting of the etch pit depth distribution parameters; Figure 5 Create a schematic diagram for the uniform corrosion model; Figure 6 It is a schematic diagram of the corrosion model; Figure 7 Schematic diagram of the pit depth control method when generating a pitting sphere; Figure 8 Generate an overall implementation flow chart for the corrosion morphology model considering uniform corrosion and pitting corrosion; Fig. 9 Generate the effect of corrosion morphology evolution model at different corrosion stages; Fig.10 Schematic diagram of the effect of generating a comprehensive corrosion morphology model. DETAILED DESCRIPTION

[0016] 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 in conjunction with 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.

[0017] Reference Figure 1 This embodiment provides a method for simulating the evolution of corrosion morphology, comprising the following steps: S1: Extract the characteristic parameters of corrosion evolution 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 the initial mass loss rate, and deduct 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 using the thickness reduction method to calculate the current pitting mass loss rate; S5: The pit position in the initial pitting model remains unchanged, the mean value of the pit size growth is determined by the current pit morphology, and the random distribution range of the pit size is controlled by the current pitting mass loss rate to generate the current pitting 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.

[0018] Specifically, step S1, obtain samples of the same specification 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 rust removal and cleaning of the samples at different corrosion stages, such as Figure 2 As shown, the characteristic parameters of corrosion evolution 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.

[0019] In step S1, the corrosion evolution characteristic parameter calculation steps are as follows: 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 sample corrosion surface, where the xy plane coincides with the zero reference plane, and the coordinates of any scanning point i on the corrosion surface are obtained (x i ,yi ,z i ), the minimum value of the z coordinate 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 pits within the statistical range is calculated. For each pit, the average diameter d and pit depth h are calculated respectively. The pit depth is the maximum depth of the current pit relative to the uncorroded surface minus the uniform corrosion thickness, which is obtained by the following calculation method: h=max(z i -t); 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); 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 (take the mean value); 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; 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 .

[0020] Specifically, Figure 5 As shown, in step S2, it is assumed that the initial uniform corrosion thickness is t1, then the sample thickness after deducting 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 the thickness reduction.

[0021] Specifically, 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 regulated by the pit fusion degree n; where the pit fusion degree n is the actual pit fusion degree statistical value; S32: Generate an elliptical pitting sphere with a diameter-to-depth ratio R at the center point of each pit, and a depth that conforms to the normal distribution parameters normal(μ1, σ1), where μ1 is the mean value of the pit depth in the initial corrosion stage, and σ1 is the variance of the pit depth in the initial corrosion stage; the diameter-to-depth ratio R here is the actual diameter-to-depth ratio statistical value; S33: Calculate the 0.5 volume of all generated pitting spheres and calculate the current pitting volume loss rate , where A is the area of ​​the corrosion surface; S34: Compare the current pitting volume loss rate η dv The actual pitting mass loss rate η at the current stage d :such as η dv <η d , then increase the pitting number Q, repeat S32, S33 until 0.95η d <η dv <1.05η d ; such as η dv >η d , then reduce the number of pitting corrosion Q, repeat S32, S33 until 0.95η d <η dv <1.05η d ; Generate an initial pitting model.

[0022] 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.

[0023] Specifically, in step S4, the initial corrosion model is established, and then the 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 subtracting the current uniform corrosion thickness from the initial thickness of the sample D is Dt i The plane size is determined by the corrosion surface range, and the thickness after thickness reduction Dt is determined by i Establish the current uniform corrosion model.

[0024] Specifically, in step S5, the specific method of generating the current pitting model 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 (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 μi -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 at the current corrosion stage, σ i is the pit depth variance in the current corrosion stage; S53: Calculate the 0.5 volume of all generated pitting spheres and calculate the current pitting volume loss rate , where A is the area of ​​the corrosion surface; S54: Compare the current pitting volume loss rate (η dv ) i The actual pitting mass loss rate (η d ) i :As (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 ; such as (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 .

[0025] 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 entity after the sectioning is the corrosion morphology model considering uniform corrosion and pitting corrosion.

[0026] Specifically, step S7, repeat S4-S6 to establish morphology models at different corrosion stages, and 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 follows Fig. 9 shown.

[0027] Specifically, step S8, the irregular corrosion surface is divided by using triangular meshes. Based on the divided surface meshes, the corrosion sample is divided by using tetrahedral units to achieve the following process: Fig.10 shown.

[0028] The present invention characterizes the real corrosion surface based on the specific parameters of pit morphology, uniform corrosion thickness, and mass loss rate, takes into account the random characteristics of pits in terms of depth, size, position, and number, and controls the evolution and generation 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 method of the pit depth and size can effectively simulate the initial random corrosion in the actual corrosion process, and the actual evolution process of the pits growing in situ after they appear.

Claims

1. A method for simulating corrosion morphology evolution, characterized in that: The following steps are involved: S1: Extract the characteristic parameters of corrosion evolution 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 the initial mass loss rate, and deduct 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 using the thickness reduction method to calculate the current pitting mass loss rate; S5: The pit position in the initial pitting model remains unchanged, the mean value of the pit size growth is determined by the current pit morphology, and the random distribution range of the pit size is controlled by the current pitting mass loss rate to generate the current pitting 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.

2. The method for simulating the evolution of corrosion morphology 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; 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.

3. The method for simulating the evolution of corrosion morphology 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 sample corrosion surface, where the xy plane coincides with the zero reference plane, and the coordinates of any scanning point i on the corrosion surface are obtained (x i ,y i ,z i ), the minimum value of the z coordinate 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 pits within the statistical range is calculated. For each pit, the average diameter d and pit depth h are calculated respectively. The pit depth is the maximum depth of the current pit relative to the uncorroded surface minus the uniform corrosion thickness, which 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 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; 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 method for simulating corrosion morphology evolution 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 deducting 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 method for simulating the evolution of corrosion morphology according to claim 4, characterized in that: 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 regulated by the pit fusion degree n; S32: Generate an elliptical pitting sphere with a diameter-to-depth ratio R and a depth that conforms to the normal distribution parameters normal(μ1, σ1) at the center of each pit, 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 volume of all generated pitting spheres and calculate the current pitting volume loss rate , where A is the area of ​​the corrosion surface; S34: Compare the current pitting volume loss rate η dv The actual pitting mass loss rate η at the current stage d :such as η dv <η d , then increase the pitting number Q, repeat S32, S33 until 0.95η d <η dv <1.05η d ; such as η dv >η d , then reduce the number of pitting corrosion Q, repeat S32, S33 until 0.95η d <η dv <1.05η d , generate the initial pitting model.

6. The method for simulating the evolution of corrosion morphology 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 subtracting the current uniform corrosion thickness from the initial thickness of the sample D is Dt i The plane size is determined by the corrosion surface range, and the thickness after thickness reduction Dt is determined by i Establish the current uniform corrosion model.

7. The method for simulating the evolution of corrosion morphology according to claim 6, characterized in that: 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 limits 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 at the current corrosion stage, σ i is the pit depth variance in the current corrosion stage; S53: Calculate the 0.5 volume of all generated pitting spheres and calculate the current pitting volume loss rate , where A is the area of ​​the corrosion surface; S54: Compare the current pitting volume loss rate (η dv ) i The actual pitting mass loss rate (η d ) i :As (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 ; such as (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 .

8. The method for simulating the evolution of corrosion morphology according to claim 1, characterized in that: In step S6, the specific implementation method is: the current pitting corrosion model generated by cutting the current uniform corrosion model in a solid sectioning manner, and the remaining entity after the sectioning is the corrosion morphology model considering uniform corrosion and pitting corrosion.

9. The method for simulating the evolution of corrosion morphology 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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