Method for constructing relationship between non-soluble deposit density and corrosion rate on basis of finite element simulation

Abstract

The present invention belongs to the field of material performance simulation. Specifically disclosed is a method for constructing a relationship between the non-soluble deposit density and the corrosion rate on the basis of finite element simulation. In the method of the present invention, by means of establishing a finite element model, constructing a relationship between the non-soluble deposit density and the porosity and performing simulation analysis on corrosion behaviors under different non-soluble deposit density conditions, a relationship between the non-soluble deposit density and the corrosion rate is constructed. The method of the present invention can effectively predict corrosion behaviors of a material under different non-soluble deposit density conditions, can provide a scientific basis for material protection design, and has wide application prospects.

Description

A method for simulating the relationship between ash density and corrosion rate based on finite elements TECHNICAL FIELD

[0001] The present application belongs to the field of material performance simulation, and particularly relates to a method for simulating the relationship between ash density and corrosion rate based on finite elements. BACKGROUND

[0002] In power transmission systems, especially in the long-term service of power station equipment, corrosion problems can cause serious damage to the equipment and affect the service. During the service of these equipment, a large amount of pollutants will be deposited on the surface, which will significantly affect the corrosion behavior. Therefore, it is of practical significance to study the influence of pollutants on the corrosion performance of equipment, improve the prediction accuracy of corrosion behavior, and provide new technical solutions for material corrosion prevention.

[0003] At present, the research on the influence of soluble salt pollutants on corrosion performance is relatively mature, and the corrosion behavior in the solution can be analyzed by analogy, and a large number of previous research documents can be referred to. The presence of insoluble pollutants such as dust changes the environment on the surface of the equipment and affects the progress of the corrosion reaction, but the research in this regard is often lacking in systematicness and depth, and most of the research is to statistically analyze the corrosion rate under mixed pollutants by phenomenological theory. It is still difficult to reduce and separate the influence of ash density and salt density from the experimental means, and the research on the influence of insoluble pollutants on corrosion performance is still relatively insufficient. SUMMARY

[0004] In view of the above-mentioned deficiencies of the prior art in the research on the influence of insoluble pollutants on corrosion performance, the present application provides a method for simulating the relationship between ash density and corrosion rate based on finite elements.

[0005] To achieve the above-mentioned purpose, the specific technical solutions include the following:

[0006] A method for simulating the relationship between ash density and corrosion rate based on finite elements, comprising the following steps:

[0007] (1) Constructing the relationship between ash density and porosity: collecting the dust-related information of the material surface in the field environment, determining the data set of ash density used in the simulation; and regarding the dust as an insoluble component in the solution, regarding the structure of the dust and the solution as a porous structure, and constructing the relationship between the ash density and the porosity;

[0008] (2) constructing a finite element simulation model: a computer software is used to construct a finite element simulation model, the finite element simulation model comprises a droplet region and a dust region, the shape of the droplet region is similar or identical to the shape of a droplet on a metal substrate surface, the droplet region and the dust region have an intersection part, the intersection part is taken as an actual research object, and the intersection part is set as a pore layer region having pores;

[0009] (3) simulation of metal corrosion under different porosities: based on the finite element simulation model constructed above, simulation of metal corrosion under different porosities is performed to obtain the relationship between porosity and corrosion current density;

[0010] (4) obtaining the relationship between ash density and corrosion rate: the relationship between porosity and corrosion rate is constructed through the relationship among corrosion current density, corrosion depth and corrosion rate, and finally the relationship between ash density and corrosion rate is obtained through the relationship between ash density and porosity.

[0011] In the method of the present application, the relationship between ash density and corrosion rate can be obtained by sequentially constructing the relationship between ash density and porosity, constructing a finite element simulation model, and simulating metal corrosion under different porosities. The method of the present application is based on finite element model simulation, systematically analyzes the influence of insoluble pollutants on the corrosion performance of power transmission equipment, improves the prediction accuracy of corrosion behavior, provides a scientific basis for equipment maintenance and protection strategies, and thus improves the operation reliability and safety of the power transmission system.

[0012] Preferably, in step (1), the relationship between ash density and porosity is:

[0013] wherein ε is the porosity, NSDD is the ash density, and S is the surface area of a carrier on which the dust is located.

[0014] Preferably, in step (2), the shape of the droplet region is elliptical, the shape of the dust region is rectangular, and the finite element simulation model adopts a mesh division manner.

[0015] Preferably, in step (2), the computer software is COMSOL simulation software.

[0016] Preferably, in step (2), the effective diffusion coefficients of various substances in the pore layer region are determined according to the Bruggeman equation, and the Bruggeman equation is:

[0017] D i,eff = D i *ε 1.5 (Formula 8), wherein D i represents the effective diffusion coefficient of species i in the current solution environment, and ε is the porosity.

[0018] Preferably, in step (3), the simulation uses a third-order current distribution as a physical field interface.

[0019] Further preferably, in the third-order current distribution, the Butler-Volmer formula is used to describe the electrode reaction kinetics, and the effective diffusion coefficients of various substances in the pore layer region are considered.

[0020] In step (4), the relationship formula of the corrosion current density, the corrosion depth, and the corrosion rate includes the following formula:

[0021] The relationship between the corrosion depth and the current density at time t is:

[0022] The expression of the maximum corrosion depth at time t is: max (t)=max(d(x,t))(Formula 11),

[0023] The calculation formula of the average corrosion depth is:

[0024] The calculation formula of the average corrosion rate is:

[0025] In the above formula, i(x,τ) represents the corrosion current density, d(x,t) represents the corrosion depth, d max (t) represents the maximum corrosion depth, represents the average corrosion depth, z is the charge quantity, F is the Faraday constant, a represents the droplet width, and R represents the average corrosion rate.

[0026] Compared with the prior art, the method of the present application has the following beneficial effects: by establishing a finite element model, constructing the relationship between the ash density and the porosity, and simulating and analyzing the corrosion behavior under different ash density conditions, the present application further constructs the relationship between the ash density and the corrosion rate. The method of the present application can effectively predict the corrosion behavior of materials under different ash density conditions, provides a scientific basis for material protection design, and has a wide application prospect. BRIEF DESCRIPTION OF DRAWINGS

[0027] FIG. 1 is a finite element simulation model constructed by COMSOL simulation software in Example 1.

[0028] FIG. 2 is a line graph of the relationship between the total thickness change of the electrode and time obtained by simulation calculation in Example 1.

[0029] FIG. 3 is a graph of the relationship between the electrode thickness change and the arc length obtained by simulation calculation in Example 1. DETAILED DESCRIPTION

[0030] In order to better illustrate the purpose, technical scheme and advantages of the present application, the present application will be further described below through specific examples. The test methods used in the examples and / or comparative examples are all conventional methods unless otherwise specified; the materials, reagents and the like used are all commercially available unless otherwise specified.

[0031] Example 1

[0032] (1) Collecting the dust-related information on the insulator in the field environment: in the field environment, the thickness of the contaminant on the insulator is regarded as the thickness of the dust, and the part of the contaminant is dissolved in water. The water can dissolve the soluble substances such as salt in the part of the contaminant, and after drying, the remaining insoluble dust is used to simulate the state of the corrosion of the substrate surface covered with droplets or water film, and the structure of the corrosion of the substrate surface covered with droplets or water film and dust is regarded as a porous structure. The dust density is related to the porosity of the porous structure, and the specific operation is as follows:

[0033] First, the part of the contaminant on the surface of the insulator is removed, and the thickness of the gap of the contaminant on the surface of the insulator is measured by using a light microscope, and the average value is obtained by repeating multiple times. Since the remaining components in the contaminant are very small, the average height of the contaminant covering the surface of the substrate can be regarded as the average height of the dust layer, i.e. the covering height of the dust particles on the surface of the substrate (in this embodiment, the insulator), which is represented by h 灰 .

[0034] Then, the part of the contaminant on the surface of the insulator is dissolved in distilled water, and the soluble salt in the contaminant is dissolved in water, and the insoluble dust is filtered and dried to obtain the mass of the dust layer, and the average value is obtained by repeating multiple times, i.e. the mass of the dust layer, which is represented by m 灰 .

[0035] Among them, the product of the covering height h 灰 of the dust particles on the surface of the substrate (insulator) and the surface area S of the insulator is regarded as the apparent volume V0 of the dust; the volume of the dust after the contaminant is dissolved in distilled water and dried is regarded as the actual volume V 灰 , and the relationship between the dust density and the porosity ε is obtained according to the dust density and the porosity formula:

[0036] Dust density formula

[0037] Among them, m 灰 represents the mass of the dust layer, S is the surface area of the insulator, ρ0 is the apparent average density of the dust layer, and ρ 灰 is the actual average density of the dust layer, h灰 is the average height of the dust layer on the surface of the substrate.

[0038] According to the above formula 1-3, by actually measuring the apparent volume V0, ρ 灰 and the actual volume V 灰 of a plurality of groups of dust, the dust density NSDD and porosity ε data of the plurality of groups of dust can be obtained, and the upper and lower limits of the dust density NSDD used in the simulation simulation are determined.

[0039] (2) Using COMSOL simulation software, a finite element simulation model is constructed by referring to the shape of the metal surface and the liquid droplet:

[0040] Fe is selected as the metal substrate, and the modeling shape is determined by the shape of the liquid droplet on the surface of the metal substrate. The liquid droplet in this embodiment is a water droplet, and the modeling shape is an elliptical shape. The major axis of the ellipse is determined according to half of the maximum diameter of the water droplet in the actual experiment, and the minor axis is determined according to the height of the water droplet. The contact angle of the water droplet with the metal surface is determined by experiment. The liquid droplet is regarded as an axisymmetric shape, and a two-dimensional axisymmetric model is used to simplify the calculation when the geometric model is constructed;

[0041] (3) The ellipse graph representing the liquid droplet and the rectangular graph representing the dust are constructed by using the geometric toolbar in the COMSOL simulation software, and the intersection of the two is taken as the actual research object. In the constructed geometric model, the part of the liquid droplet away from the surface h 灰 is set as a porous pore layer region, and the porosity thereof is ε. A part of the model is shown in FIG. 1, in which the lower part of the ellipse is the metal substrate, and the blue part represents the pore layer with insoluble dust. The upper part represents the part of the liquid droplet that is above the pore layer;

[0042] In this embodiment, the geometric parameters of the model are shown in Table 1:

[0043] Table 1

[0044] (4) According to the principle of corrosion electrochemistry, COMSOL simulation software is used to simulate the metal corrosion under different porosities:

[0045] Since the three-dimensional model has rotational symmetry, the model is cut and processed, and a more detailed grid division is used on the surface of the metal substrate. The results are shown in FIG. 1.

[0046] A cubic current distribution is used as a physical field interface, and the electrode reaction on the surface is described by the Butler-Volmer formula related to the H + concentration, which describes the electrode reaction kinetics, and specifically includes the following formulas:

[0047] n = ac + a a (Form 6),

[0048] η = E - E eq,ref (T) (Formula 7);

[0049] where i loc,expr is the local current density expression, i0is the exchange current density, a a and a C are the polarization rates of the cathode and anode, their sum is n, η is the overpotential, is the magnitude of the current electrode potential E away from the reference equilibrium electrode potential E eq,ref , i0ref(T) is the reference exchange current density at standard temperature, which is related to the concentration c i and the reaction coefficient v of the substance i , T is the thermodynamic temperature, F is the Faraday constant, and R is the gas constant.

[0050] and uses water-based electrical neutrality as a charge conservation model, sets various physical parameters, including the diffusion coefficient of the initial concentration of ions; when using the Butler-Volmer equation to describe the electrode reaction kinetics, input the exchange current density, symmetry factor and reference potential of the oxygen reduction and iron dissolution reaction and other parameters. The parameters applied for specific cases need to be fitted by actual electrochemical tests.

[0051] where, for the electrode reaction, it is set to occur in the solution on the metal surface, the cathode reaction considers the effect of oxygen concentration on the reaction rate, and the cathode reaction part uses the oxygen reduction reaction to describe, and the solution part occurs hydrolysis reaction of metal ions; The boundary condition concentration is added in turn and calculated; for the anode iron dissolution reaction, the generation and diffusion of iron ions and the effect of pH on the reaction rate are considered. For non-faraday reactions, set it to occur in the solution domain, consider the hydrolysis reaction of iron ions and the self-dissociation reaction of water; for the setting of the pore layer, the effective diffusion coefficient of each substance is determined according to the Bruggeman equation:

[0052] D i,eff = D i * ε 1.5 (Formula 8),

[0053] where D i represents the effective diffusion coefficient of species i in the current solution environment.

[0054] During the calculation process, a plurality of data are substituted into the above formulas (4-8) for simulation calculation, and each set of data includes O2, H + , OH -The concentration of Na, Cl, Fe, reaction rate, equilibrium constant, rate constant, and other parameters can be determined according to different conditions to obtain multiple sets of data. One set of data used in the present embodiment is shown in Table 2. Based on the above corrosion electrochemical principles and calculations, the corrosion current density of the iron-based metal material at time t can be obtained.

[0055] (5) Determine the relationship between the gray density and the corrosion rate change:

[0056] In step (4), the relationship between porosity and current density is constructed by continuously changing the porosity data settings in the model, and multiple sets of porosity and current density data are obtained. Then, through the relationship between current density, corrosion depth, and corrosion rate (equations 9-13 below), the relationship between porosity and corrosion rate is further constructed. The specific formulas involved are as follows:

[0057] According to Faraday's law, the amount of substance that reacts at time t and the current can be written as follows:

[0058] where n is the amount of substance of the corrosion reactant, z is the charge amount, F is the Faraday constant, and I(τ) represents the current.

[0059] The relationship between the change in corrosion depth and the current density is:

[0060] The expression for the maximum corrosion depth at time t is: max (t) = max(d(x, t)) (equation 11),

[0061] The calculation formula for the average corrosion depth is:

[0062] The average corrosion rate calculation formula R is:

[0063] In the above equations, i(x, τ) represents the current density, d(x, t) represents the corrosion depth, d max (t) represents the maximum corrosion depth, represents the average corrosion depth, z is the charge amount, F is the Faraday constant, a represents the droplet width, and R represents the average corrosion rate.

[0064] Table 2

[0065] In this example, the single set of parameters in Table 2 is applied as a specific example to illustrate the principles and methods of the present application. The results are shown in Figure 2. In the presence of dust as insoluble, the electrode corrosion depth increases with time, and due to the effect of diffusion, the corrosion changes with distance as shown in Figure 3, where the arc length represents the length from a point on the metal substrate to the center of the ellipse, and the x-axis represents the electrode corrosion. It can be found that in the presence of dust, the corrosion near the metal interior is slower, and the outside oxygen concentration is higher, mainly for the cathodic reaction, and the corrosion near the inside part reaches the maximum.

[0066] The present application models the insoluble dust and liquid droplets as a porous structure, and through the dust density, porosity, and three current distribution corrosion model, establishes the relationship between the dust density and the metal corrosion rate in the presence of insoluble, and provides a new theoretical model and numerical calculation method for constructing the prediction corrosion rate model.

[0067] Finally, it should be noted that the above examples are only used to illustrate the technical solutions of the present application, but not to limit the protection scope of the present application. Although the present application has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present application can be modified or replaced by equivalents without departing from the essence and scope of the technical solutions of the present application.

Claims

1. A method for simulating the relationship between gray density and corrosion rate based on finite elements, characterized in that, The method comprises the following steps: (1) constructing the relationship between the grey density and the porosity: collecting the information about the dust on the surface of the material in the field environment, determining the data set of the grey density used in the simulation, and regarding the dust as the insoluble component in the solution, regarding the structure of the mixture of the dust and the solution as the porous structure, and constructing the relationship between the grey density and the porosity; (2) constructing the finite element simulation model: constructing the finite element simulation model by using the computer software, wherein the finite element simulation model comprises a droplet region and a dust region, the shape of the droplet region is similar or identical to the shape of the droplet on the surface of the metal matrix, the droplet region and the dust region have an intersection part, the intersection part is taken as the actual research object, and the intersection part is set as the pore layer region with pores; (3) simulating the metal corrosion under different porosities: based on the finite element simulation model constructed above, the metal corrosion under different porosities is simulated to obtain the relationship between the porosity and the corrosion current; (4) obtaining the relationship between the grey density and the corrosion rate: constructing the relationship between the porosity and the corrosion rate by using the relationship between the corrosion current density, the corrosion depth and the corrosion rate, and finally obtaining the relationship between the grey density and the corrosion rate by using the relationship between the grey density and the porosity.

2. The method of correlating simulated gray density with corrosion rate based on finite elements as claimed in claim 1, wherein, In step (1), the relationship between the grey density and the porosity is as follows: wherein ε is the porosity, NSDD is the grey density, and S is the surface area of the carrier on which the dust is located.

3. The method of correlating simulated gray density with corrosion rate based on finite elements as recited in claim 1, wherein, In step (2), the shape of the droplet region is an ellipse, the shape of the dust region is a rectangle, and the finite element simulation model adopts the mesh division manner.

4. The method of correlating gray density to corrosion rate based on finite element modeling of claim 1, wherein, In step (2), the effective diffusion coefficients of each species within the pore layer region are determined according to the Bruggeman equation: D i,eff = D i * ε 1.5 , where D i represents the effective diffusion coefficient of species i in the current solution environment, and ε is the porosity.

5. The method of correlating gray density to corrosion rate based on finite element modeling of claim 1, wherein, In step (3), the simulation adopts the third-order current distribution as the physical field interface.

6. The method of correlating gray density to corrosion rate based on finite element modeling of claim 5, wherein, In the third-order current distribution, the Butler-Volmer formula is used to describe the electrode reaction kinetics, and the corrosion current density is calculated by considering the effective diffusion coefficient of each substance in the pore layer region.

7. The method of correlating gray density to corrosion rate based on finite element modeling of claim 1, wherein, In step (4), the relationship between the corrosion current density, the corrosion depth and the corrosion rate comprises the following formula: Corrosion depth at time t versus current density: The expression for the maximum corrosion depth at time t is: d max (t) = max(d(x, t)), The formula for calculating the average corrosion depth is: Average corrosion rate calculation formula: In the above formula, i(x, t) represents the corrosion current density, d(x, t) represents the corrosion depth, d max (t) represents the maximum corrosion depth, wherein z represents the average corrosion depth, z is the charge quantity, F is the Faraday constant, a represents the droplet width, and R represents the average corrosion rate.

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