JP6544402B2 - Method of predicting corrosion of metals by numerical analysis - Google Patents

Description

  The present invention relates to a method of predicting corrosion of metallic materials widely used in the industrial field by numerical analysis. In the present invention, specifically, in order to predict the quality and performance life of a structure, numerical distribution (numerical simulation) is used to calculate potential distribution and current density distribution in an electrolyte solution which is a corrosive medium, It is a technology related to corrosion evaluation that predicts the corrosion resistance of metals.

  Conventionally, the corrosion resistance of a metal material is evaluated by a corrosion promotion test, an air exposure test, or an electrochemical measurement. For example, in the case of evaluating the corrosion resistance of steel materials, test pieces and actual parts are obtained by a salt spray test (SST) or a combined cycle test (CCT: combined cyclic corrosion test) combining the wet and dry atmospheric conditions with this. It is carried out to promote the corrosion of the steel and to judge the superiority or inferiority of the corrosion resistance in a short time. On the other hand, because such a corrosion promotion test is a severe corrosive environment compared to the environment in which steel materials are actually used, it is not possible to reproduce the corrosion resistance hierarchy of steel materials of different corrosion types and types in actual use environments. There is. Therefore, air exposure tests for evaluating corrosion resistance are widely performed by installing test pieces outdoors or indoors and corroding them in an environment close to actual use. However, since the exposure test has a long time to determine the superiority or inferiority of the corrosion resistance, it is not suitable for the development of a corrosion resistant material for which an early judgment of the corrosion resistance is required.

  On the other hand, with recent development of computer technology and speeding up of calculation, attempts to predict corrosion phenomena by computer simulation are actively performed. If corrosion of metals can be predicted by numerical analysis, analysis of the causes of corrosion and corrosion mechanisms that are difficult to analyze in experiments may be possible, and the corrosion resistance of metals can be evaluated in a short time.

  Patent document 1 and patent document 2 consider the metal in a corrosion medium as a continuum which consists of a plurality of analysis segments electrically connected, and determine the polarization characteristic of the metal concerned numerically. Disclose. This method considers the corrosion medium in the model as a Laplace field according to the Laplace equation, performs numerical analysis, and calculates the potential distribution of the metal that is the target structure and the inflow and outflow of current to obtain the driving force for corrosion and the corrosion rate. Is a method of estimating

  In addition, Non-Patent Document 1 reports a technology for analyzing the corrosion of a seawater pump by the boundary element method. Here, the potential distribution and current distribution in the corrosive medium seawater are determined by solving the Laplace equation with the polarization curve of cast iron (FC200) as the pump material as the boundary condition, and the potential at the interface between cast iron and seawater and We propose a model to predict the corrosion of cast iron from the current density. Here, the electrical conductivity in the aqueous solution uses the value obtained from the experiment.

  Non-Patent Document 2 simulates the corrosion of reinforcing bars in concrete. The mass transfer of corrosion factors such as chloride and oxygen in concrete is predicted, and furthermore, the corrosion current density is obtained by the Tafel equation to predict the corrosion of reinforcing bars. In this model, mass transfer is calculated using the diffusion equation by treating concrete as pores and treating it as a uniform medium like a solution.

  Non-Patent Document 3 predicts corrosion of zinc and steel by performing numerical calculation in consideration of mass transfer and chemical reaction in galvanizing and dissimilar metal contact corrosion under a thin water film of a base steel sheet. In this model, the formation and distribution of corrosion products of zinc and steel are calculated every minute time, and the eluted metal ions calculated from the anode reaction given as the boundary conditions are the chemical species by mass transfer calculation and The precipitation reactions that react and form metal oxides and hydroxides are predicted by equilibrium calculations using equilibrium constants, which predict the distribution and amount of various corrosion products.

JP, 2008-249562, A Japanese Patent Application Publication No. 2008-32421

Everla Times No. 223 (2009-3) 37-45 Concrete Engineering Annual Proceedings, Vol. 24, No. 1, (2002) 831-836 Materials and Environment, Vol. 61, (2012), 376-383.

  Various methods can be considered for modeling corrosion analysis and numerical analysis methods. Among these, the current density corresponding to the corrosion rate and the distribution of the potential serving as the driving force of the corrosion reaction in the region assuming the electrolyte solution which is a corrosive medium are widely practiced. It is a method to obtain by solving The corrosion of metal is evaluated by the inflow and outflow of the current at the interface between the electrolyte solution and the metal and the potential difference. As a solution method of such an equation, a difference method, a finite element method, or the like is used as a continuum model in which the electrolyte solution region is elementized. The polarization characteristics of the metal, which is the relationship between the electric potential of the metal surface in the electrolyte solution and the current density, are given as boundary conditions, and the distribution of the electric potential and current in each element, and the material balance in the element and at the boundary are calculated.

  In making such calculations, the conductivity in the electrolyte solution is often calculated as constant. Alternatively, the conductivity may be calculated from the concentration of chemical species dissolved in the entire electrolyte solution and in each element.

  In the actual corrosion phenomenon, the corrosion not only proceeds as dissolution (ionization) of the metal, but also involves the formation of so-called "rust" or "corrosion products", which form oxides and hydroxides of the metal. Hereinafter, precipitates of dissolved metal (oxides, hydroxides, etc.) are referred to as corrosion products. Corrosion products have a significant effect on the corrosion rate of metals. For example, zinc active in an electrolyte solution exerts excellent corrosion resistance in an atmospheric environment because the corrosion products of zinc cover the surface to reduce the corrosion rate of metallic zinc.

  In Patent Document 1 and Patent Document 2, the corrosive medium in the model is analyzed as Laplace field according to the Laplace equation, and soil is taken as an example of the medium, and the electrical physical property value is given as a specific resistance of 5000 Ω · cm. In the present invention, when the medium is an aqueous solution, the corrosion polarization characteristics in the aqueous solution can be evaluated if the electric conductivity of the aqueous solution is given. However, the electrical property values given here are conditions given only from the corrosive environment, and the effects of the formation of corrosion products accompanying corrosion are not taken into consideration.

  Also in Non-Patent Document 1 and Non-Patent Document 2, the electric conductivity is given to the corrosion medium as seawater and concrete, and the Laplace equation and the equation of mass transport are solved. However, the prediction of the formation of corrosion products and the consequent effects on corrosion media and corrosion are not taken into account in the calculations.

  Non-Patent Document 3 calculates potential distribution and current density distribution in consideration of mass transport in dissimilar metal catalytic corrosion of zinc and steel in an aqueous solution. In this document, the amount of oxides and hydroxides produced is calculated using the concentrations of various types of chemical species in the aqueous solution which is the corrosive medium and the equilibrium constants of the precipitation reactions of oxides and hydroxides. And predict the distribution. However, changes in the electrochemical properties at the interface of the metal with the aqueous solution due to the formation of corrosion products were not considered, and it was not possible to accurately estimate the corrosion rate of the metal in the presence of the corrosion products.

  As described above, in the prior art, the influence on the corrosion rate due to the deposition of the metal corrosion products on the metal surface is not considered in the numerical calculation, and the metal corrosion can be predicted with high accuracy by the numerical analysis. It was not.

  Then, an object of the present invention is to provide a corrosion prediction method of metal by numerical analysis which can predict corrosion of metal in contact with an electrolyte solution with high accuracy by numerical analysis in view of the above-mentioned subject.

  In order to solve the above problems, the present inventors focused attention on the consideration of the influence on the corrosion rate due to the deposition of metal corrosion products on the metal surface in numerical calculation. Since the corrosion product is insulating, the formation of the corrosion product has focused on the fact that the overvoltage necessary for the dissolution of the metal surface is increased. As a result, in consideration of the corrosion products formed on the metal surface, the current density flowing in and out of the interface between the metal and the electrolyte solution is corrected and used as a boundary condition, which actually involves the formation of corrosion products. In light of the fact that the potential distribution and the current density distribution of the case can be properly predicted, the present invention has been completed.

The essential features of the present invention completed based on the above findings are as follows.
(1) A method of predicting corrosion of a metal in contact with an electrolyte solution by numerical analysis,
Measuring a polarization curve which is the relationship between the potential E of the metal surface in the electrolyte solution and the current density i;
Obtaining a corrected polarization curve in which the value of the current density in the polarization curve is reduced;
Obtaining the potential distribution in the electrolyte solution at a predetermined time in a system in which the metal and the electrolyte solution are in contact, by using the corrected polarization curve as a boundary condition by numerical calculation;
The metal corrosion prediction method by numerical analysis characterized by having.

  (2) Assuming that the polarization curve is i = f (E) where the current density i is expressed as a function of the potential E, the corrected polarization curve is i = α × f (E), 0.0010 ≦ α < The corrosion prediction method of metal by numerical analysis as described in the above (1), which is 1.000.

(3) The method further includes the step of determining the generation amount p of the corrosion product generated per unit area on the surface of the metal by numerical calculation,
Assuming that the polarization curve is i = f (E) where the current density i is expressed as a function of the potential E, the corrected polarization curve is i = β × f (E), β = g (p) and The corrosion prediction method of metal by numerical analysis as described in the above (1), wherein 0.0010 ≦ β <1.000.

  (4) Any one of the above (1) to (3), further including the step of obtaining the current density distribution in the electrolyte solution at the predetermined time by numerical calculation from the potential distribution in the electrolyte solution at the predetermined time Method of predicting corrosion of metal by numerical analysis as described in paragraph (1).

  (5) Of the current density distribution in the electrolyte solution, using the current density in the vicinity of the interface with the metal in the electrolyte solution, the amount of corrosion of the metal at the predetermined time is calculated according to Faraday's law. The metal corrosion prediction method by numerical analysis as described in said (4) which further has a process.

  (6) Any one of the above (1) to (5), wherein the metal is one or more metals selected from zinc, iron, aluminum, copper and nickel, or an alloy containing the metal as a main component Method of predicting corrosion of metal by numerical analysis described in paragraph.

  (7) Any one of the above-mentioned (1) to (6), wherein the form of the corrosion is contact corrosion of dissimilar metals in which two metals are in contact and the corrosion of one metal is accelerated by the potential difference between the metals. Method of predicting corrosion of metal by numerical analysis described in paragraph.

  (8) The method of predicting metal corrosion by numerical analysis according to (7), wherein the two metals are a combination of zinc or zinc plating and iron or steel.

  (9) A method for designing a steel structure, characterized in that corrosion resistance is predicted by the method of predicting corrosion of a metal according to any one of the above (1) to (8), and the material is selected.

  (10) A method of designing a steel material, wherein corrosion resistance is predicted by the method of predicting corrosion of a metal according to any one of the above-mentioned numerical analysis (1) to (8) to design anticorrosion performance.

  (11) A corrosion prediction program that causes a computer to execute a method for predicting metal corrosion by numerical analysis according to any one of (1) to (8) above.

  According to the method of predicting corrosion of metal by numerical analysis of the present invention, since the numerical calculation taking into consideration the influence on the corrosion rate due to the deposition of the corrosion product of the metal on the metal surface is performed, the corrosion of the metal in contact with the electrolyte solution It is possible to predict with higher accuracy by numerical analysis.

3 is a flowchart of a method of predicting corrosion of a metal by numerical analysis according to an embodiment of the present invention. It is a figure which shows an example of the continuum model of the dissimilar metal contact corrosion of two metals. It is a figure explaining formation of a metal corrosion product. It is a figure which shows the model shape of the dissimilar metal contact corrosion of zinc and iron which were used in Example 1. FIG. (A) is a model top view of the experiment of the dissimilar metal contact corrosion of zinc and iron performed in Example 1, (b) is an A-A 'sectional view of (a). It is a figure which shows the model shape of the dissimilar metal contact corrosion of zinc and iron which were performed in Example 2. FIG.

  The present invention is a method of predicting corrosion of a metal in contact with an electrolyte solution by numerical analysis. One embodiment is described with reference to FIGS.

  FIG. 1 is a flowchart of a method of predicting corrosion of metal by numerical analysis according to an embodiment of the present invention. FIG. 2 is a model diagram of a system in which a metal and an electrolyte solution are in contact for applying such numerical analysis, and the electrolyte solution is in a state in which two metals A and B are in contact and electrically shorted. Shows an example of a model of heterogeneous metal contact corrosion in which

  In the model shown in FIG. 2, a thin film of a metal and an electrolyte solution in contact with the metal is divided into two-dimensional lattice-like regions (hereinafter referred to as "cells") in these cross sections, and the boundary element method or The potential, current density, concentration of chemical species, etc. in each cell are calculated using the finite element method etc. to predict the amount of corrosion and the precipitation reaction of the compound. Alternatively, thin films of metal and electrolyte solution may be partitioned into three-dimensional microcube regions, which may be used as cells. Note that since metal corrosion can be predicted by determining the potential distribution in the electrolyte solution, the metal may not be divided into cells, and only the electrolyte solution may be divided into cells. Hereinafter, a typical example of the calculation procedure will be described.

  First, in step S1, the shapes of the metal and the electrolyte solution to be a corrosive medium are set, and the initial concentrations and physical property values of chemical species in the electrolyte solution are set. Physical property values include the diffusion coefficient used to calculate the transport of chemical species and the charge of ions.

  Next, in step S2, boundary conditions used for numerical analysis are set. Here, as boundary conditions at the interface between the metal and the electrolyte solution, conventionally, a polarization curve represented by a function i = f (E) of the current density i of the metal surface in the electrolyte solution and the potential E was set. . On the other hand, in the present embodiment, a corrected polarization curve in which the value of the current density in the polarization curve is reduced is obtained and used as a boundary condition. Details will be described later.

ここで、Фは電位、C_x, D_x, z_x, u_x, R_x はそれぞれ化学種xの濃度、拡散係数、価数、移動度および反応量を表し、Fはファラデー定数を表す。 Next, in step S3, the potential distribution in the electrolyte solution at a certain time t is determined by numerical calculation. For numerical calculation, the Laplace equation shown in equation (1) or the Nernst-Plank equation shown in equation (2) is solved.

Here, Ф represents the potential, C _x , D _x , z _x , u _x , and R _x each represent the concentration of the chemical species x, diffusion coefficient, valence, mobility and reaction amount, and F represents the Faraday constant.

  At this time, at the interface between the metal and the electrolyte solution, the above-mentioned corrected polarization curve is taken as the boundary condition, and at the interface between the electrolyte solution and the gas phase, and at the end of the electrolyte solution, no current flows in and out. Perform numerical calculation as.

  By discretizing equation (1) and solving, the potential in each cell at a certain time t can be calculated, that is, the potential distribution in the electrolyte solution at a certain time t can be obtained. In the case where the metal is divided into cells, the potential of each cell in the metal, that is, the potential distribution in the metal can also be obtained by the calculation.

  In addition, in order to solve the Nernst-Plank equation for mass transport shown in equation (2), it is necessary to satisfy equation (1) for each ion and molecule in each cell in the electrolyte solution, as well as electrically neutral conditions. It becomes a simultaneous equation by adding the equation of. By solving the simultaneous equations, in addition to the potentials of the cells at a certain time t, the concentrations of ions and molecules of the cells are also derived as calculation results. As a result, in addition to the potential distribution in the electrolyte solution at a certain time t, the concentration distribution of chemical species can be obtained.

Next, in step S4, from the potential distribution in the electrolyte solution at a certain time t, the current density distribution in the electrolyte solution at that time t is determined by numerical calculation. Specifically, the current density in each cell is calculated according to Ohm's law of equation (3), that is, the current density distribution in the electrolyte solution at a certain time t can be obtained. Here, σ represents the electrical conductivity of the electrolyte solution. The electrical conductivity σ is a function of the concentration of chemical species. When the potential distribution is determined by equation (2), the concentration distribution of chemical species is also obtained. Therefore, the electric conductivity for each cell obtained from the concentration of chemical species for each cell is applied to equation (3). When the potential distribution is determined by equation (1), the movement of chemical species in the solution is not taken into consideration, and the uniform electrical conductivity determined from the concentration of the solution is defined as the electrical conductivity of each cell. Apply In the case where the potential distribution in the metal is obtained, the current density distribution in the metal can also be determined by the equation (3).

  Although a typical calculation method of potential and current density is shown here, in the present invention, the method of determining the potential and current density by calculating the electrolyte solution as a potential field is not limited thereto. .

In step S5, it is determined whether the time t at which the numerical calculation has been performed exceeds the preset time t _set . If it does not exceed the set time t _set , Δt is added and the process returns to step S3 to calculate the potential distribution and current density distribution in the electrolyte solution at a new time t. If it exceeds the set time t _set , the process proceeds to step S6.

In step S6, of the current density distribution in the electrolyte solution, the current density in the vicinity of the interface with the metal in the electrolyte solution is used to corrode the metal at the set time t _set according to Faraday's law shown in equation (4). Calculate the quantity. Here, n and z are the amount and the valence of the metal (chemical species) dissolved by corrosion, and t is time. When the current density distribution in the metal is obtained, the current density near the interface with the electrolyte solution in the metal may be used. That is, the current density of the metal or electrolyte solution near the metal / electrolyte solution boundary may be used. Here, “in the vicinity of the interface” means a range in which a current density that can be considered equivalent to the current density flowing in and out of the interface between the electrolyte solution and the metal can be obtained, specifically, within 10 mm from the interface More preferably, it is an area of the electrolyte solution or metal within 1 mm.

  In the actual calculation, by repeating steps S3 and S4, the current density in the vicinity of the interface with the metal in the electrolyte solution is obtained at various times, so that the minute time is calculated using equation (4). The amount of corrosion is determined for each time, and this amount is integrated to obtain the amount of corrosion after a predetermined time has elapsed and the distribution of the amount of corrosion within the metal surface.

  Finally, in step S7, various calculation results are output, and the method ends.

  Here, the potential distribution, the current density distribution, and the amount of corrosion obtained by the numerical calculation above are strongly influenced by the corrosion products formed up to that time. Many corrosion products have electrical properties of insulators and semiconductors such as oxides and hydroxides, and they have extremely low electrical conductivity compared to metals and electrolyte solutions. Formation and deposition of such a substance in the electrolyte solution changes the potential distribution and current density distribution in the electrolyte solution and the metal. As a result, the corrosion reaction and formation of corrosion products after that time also change.

  Therefore, the present invention provides a method of predicting metal corrosion by numerical analysis that reproduces the influence of the generated corrosion products on such a corrosion phenomenon.

FIG. 3 shows a diagram illustrating the formation of metal corrosion products. Here, when metal A generates metal ion A ⁺ in the solution by corrosion, the concentration of A ⁺ increases with time, and from the relationship with the solubility product of oxide or hydroxide, oxide AO or Suppose that hydroxide A (OH) is formed. As mentioned earlier, many of the corrosion products are insulators or semiconductors, which are electrochemically reactive as compared to the metal before corrosion. Therefore, the corrosion reactivity differs between the interface between the metal surface on which the corrosion product is not deposited and the electrolyte solution and the interface between the metal surface on which the corrosion product is deposited and the electrolyte solution.

  Therefore, when calculating the distribution of the potential Φ and the distribution of the current density i in the electrolyte solution by numerical calculation, the polarization curve used as the boundary condition is corrected in consideration of the formation of a corrosion product. This makes it possible to obtain a potential distribution or current density distribution close to the corrosion phenomenon actually observed.

  That is, in step S2, first, a polarization curve [i = f (E)] which is a relationship between the current density i of the metal surface in the electrolyte solution and the potential E is measured. Then, a corrected polarization curve is created in which the value of the current density in the polarization curve is reduced. Specifically, the corrected polarization curve is set to i = α × f (E), 0.0010 ≦ α <1.000. Then, instead of the polarization curve, this corrected polarization curve is used as a boundary condition at the interface between the metal and the electrolyte solution.

  Here, α is a factor depending on the form and electrical properties of the corrosion product. When α is less than 0.0010, the current density of the corrosion reaction becomes small, and it is assumed that the corrosion inhibition effect of the base metal by the corrosion product is large. In fact, since the corrosion products are physically broken or damaged, the corrosion rate is not suppressed to such a small level, and the difference between the actual corrosion phenomenon and the numerical calculation becomes large. When α is 1.000, it corresponds to the polarization curve measured in the solution, and when α is more than 1.000, it means that the formation of corrosion product promotes the corrosion of metal, but in any case corrosion Corrosion effects due to product deposition are not reproduced. The more preferable range of α from this viewpoint is 0.0010 or more and 0.800 or less, and the more preferable range is 0.0100 or more and 0.500 or less.

  It is necessary to measure the polarization curve using the same metal as the target metal of numerical analysis, and further measure the electrolyte concentration of the electrolyte solution to be target of numerical analysis in the electrolyte solution of the same electrolyte concentration. Is preferred.

  The polarization characteristic used as the boundary condition may be either an internal polarization curve or an external polarization curve. Although the internal polarization curve can not be obtained by experiment, it can be determined by extrapolating from the external polarization curve, and is more preferable because more detailed electrode reactions can be given as boundary conditions.

  Since the coverage and density of the corrosion products on the metal surface vary depending on the amount of corrosion products formed, it is preferable to optimize the correction polarization characteristics used as boundary conditions depending on the location of the metal surface. That is, it is preferable to set the correction polarization curve to be the boundary condition in consideration of the generation amount of the corrosive substance in the cell, which is the boundary. Therefore, as another correction method of the polarization curve, the generation amount p of the corrosion product generated per unit area on the surface of the metal is determined by numerical calculation, and the correction polarization curve is i = β × f (E), β = There is a method of setting g (p) and 0.0010 ≦ β <1.000.

  Here, as the generation amount p, it is possible to use the volume, weight, amount of substance of the corrosion product, and the area ratio when the thickness is constant. When a plurality of types of corrosion products are simultaneously generated, the total amount of only specific corrosion products may be used, or may be calculated as the total amount of all corrosion products. However, the range of β is 0.0010 ≦ β <1.000 for the same reason as α.

For example, β = 1−V _c / V ₀ can be set. That is, as the cell in which a large amount of corrosion product is generated, β becomes smaller, and the value of the current density in the polarization curve is made smaller.
V ₀ : The area or volume (unit area or unit volume) of any cell located at the interface with the metal in the electrolyte solution
V _c : Area or volume occupied by corrosion products in the cell

The calculation method of V _c / V ₀ will be described below. First, the volume V _c is calculated from the relationship between the calculated total amount (g or mol) of corrosion products in the cell j and the density of these corrosion products. That is, for example, in the case of calculation from mass, it is calculated by V _c = m / d. Here, V _c represents the volume (cm ³ ) of the corrosion product occupying the cell j, m represents the mass of the corrosion product (g), and d represents the density of the corrosion product (g / cm ³ ). When a corrosion product consists of many components, although it may calculate about all the components, it may calculate about only the oxide and hydroxide which are main components of a corrosion product. By dividing this value by the volume V ₀ of the initial cell j originally occupied only by the aqueous solution, V _c / V ₀ is calculated.

  The boundary condition may be a constant condition regardless of the time interval of sequential calculation. In this case, β determined at a specific time is used. However, since the influence of the formed corrosion product changes constantly, it is desirable to set a new condition for each time interval of sequential calculation. That is, β can be calculated for each time step in sequential calculation. Therefore, the calculation at each time step is to obtain a corrected polarization curve using β obtained in the previous step.

  The metal to which the method for predicting corrosion of a metal according to the numerical analysis of the present invention is applied is not particularly limited, but one or more metals selected from zinc, iron, aluminum, copper and nickel, or an alloy containing the metal as a main component Can be suitably applied. Further, it is particularly effective to apply the method of predicting corrosion of metal by numerical analysis of the present invention to contact corrosion by dissimilar metals as shown in FIG. In this case, the corrected polarization curve of metal A is taken as the boundary condition at the interface between metal A and the electrolyte solution, and the corrected polarization curve of metal B is taken as the boundary condition at the interface between metal B and the electrolyte solution. Examples of dissimilar metal contact corrosion include combinations of zinc or zinc plating with iron or steel.

  The deposition of corrosion products on metal surfaces is clearer in the atmospheric environment than in the electrolyte solution and the effect is also greater. Therefore, in order to predict atmospheric corrosion of metal, it is suitable for numerical calculation in which the thickness of the electrolyte solution on the metal surface is less than 10 mm.

  In the design of a steel structure, it is preferable to select a material by predicting the corrosion resistance by the method of predicting corrosion of a metal by the above-described numerical analysis. That is, when the amount of corrosion predicted by the numerical calculation according to the present invention can be considered to be sufficiently smaller than the required life of the steel structure with respect to the metal material, using the metal material as the material of the steel structure it can.

  Further, in the method of designing a steel material, it is preferable to design the anticorrosion performance by predicting the corrosion resistance by the method of predicting corrosion of a metal by the above-described numerical analysis. By changing the composition and structure of the steel material, the polarization curve and the component eluted in the electrolyte also change, so the amount of corrosion of the metal predicted by calculation also differs. That is, the composition and structure of the steel material can be designed such that the corrosion amount of the metal predicted by the numerical calculation according to the present invention becomes sufficiently smaller than the required life of the steel material.

(program)
An object of the present invention is to provide a system or apparatus with a storage medium storing a program code of software for realizing each process of the above-described embodiment, and a computer (or CPU or MPU) of the system or apparatus uses the storage medium. It is also achieved by reading and executing the stored program code. In this case, the program code itself read out from the storage medium implements the functions of the above-described embodiments, and the storage medium storing the program and the program code constitutes the present invention.

  Here, as a storage medium for storing the program code, for example, a flexible disk, hard disk, ROM, RAM, magnetic tape, non-volatile memory card, CD-ROM, CD-R, DVD, optical disk, magneto-optical disk, MO, etc. Is considered. Also, a computer network such as a LAN (local area network) or a WAN (wide area network) can be used to supply the program code.

Example 1
Numerical values of dissimilar metal contact corrosion of zinc and iron in contact with each other covered with 0.6, 1.2 or 2.0 mol / L NaCl aqueous solution with a thickness of 0.01, 0.05 or 0.1 mm It predicted by calculation. FIG. 4 shows a model of the shape used in the present embodiment. The region Ω is the region of the aqueous NaCl solution, and the concentration of Na ⁺ and Cl ⁻ is set to 0.6, 1.2, 2.0 mol / L as the initial concentration of the species, and the initial concentration of the species to be considered in this solution Concentrations and diffusion coefficients were set as shown in Table 1. In the region Ω, it was assumed that the mass transport equation of equation (2) holds, and for each chemical species, diffusion due to concentration gradient in aqueous solution and migration due to charge were considered. The influence of convection is not considered here.

As the boundary conditions for solving equation (2), the anodic polarization curve of zinc measured in the same concentration aqueous NaCl solution as i _a _ _{z n} = f (E _a _ _{z n} ) and the cathodic polarization curve of iron i _c When _ _Fe = f (E _c _ _Fe ), the boundary condition of boundary 1 is i _a _ _zn = α _a × f (E _a _ _{z n} ), and the boundary condition of boundary 2 is i _a _ _Fe = α _c × It was f (E _a _ _Fe ). In the other boundaries, no current flow (∂Ф / ∂Ф n = 0: where n represents a unit vector) was used as the boundary condition.

  Under this condition, the calculation was sequentially performed from time 0 to time 60 min, and the potential distribution and current density distribution were calculated, and the concentration of chemical species and the concentration distribution of reaction products at that time were calculated.

In this calculation of heterogeneous metal catalytic corrosion, it was assumed that zinc was corroded by an anodic reaction, and iron was a reduction reaction of oxygen at its surface as a cathodic reaction. The anodic reaction of zinc and the reduction reaction of oxygen on iron are represented by formulas (5) and (6) respectively.
^{Zn → Zn 2+ + 2e - ····} (5)
2H ₂ O + O ₂ + 4 e ⁻ → 4 OH ⁻ ··· (6)

  Based on this reaction equation, the amount of dissolution of Zn is calculated using Faraday's law from the current density at the interface between zinc and aqueous solution, and this is integrated with respect to the calculation time to calculate the amount of corrosion of zinc after 60 minutes. I asked.

  In order to evaluate the validity of these numerical calculation results, corrosion experiments were conducted under the same conditions as the numerical calculation. FIG. 5 shows a schematic view of a test piece in which 10 mm × 10 mm × 5 mmt of zinc and iron (both having a purity of 99.999%) used in the corrosion test are brought into contact with each other and fixed. An aqueous solution of NaCl having the same concentration and the same thickness as the conditions calculated numerically was formed on the surface of the test piece. In order to keep the thin salt water film once formed on the metal surface in a fixed state, the test piece is promptly room temperature, relative humidity is RH 98% (equivalent to 0.6 M), RH 93% (equivalent to 1.2 M), RH 85 The test piece was corroded by placing it in a constant temperature and humidity chamber set to% (equivalent to 2.0 M).

  After corroding the test piece in a constant temperature and humidity chamber for 60 minutes, the potential distribution on the surface was measured using a scanning Kelvin probe. The same temperature and relative humidity as in the constant temperature and humidity chamber were maintained during measurement with the Kelvin probe so as not to change the corrosion state. After the measurement is completed, the test piece is promptly washed with distilled water and dried, and then the central portion of the test piece shown in the cross-sectional view taken along line AA 'of FIG. From the above, the amount of corrosion of zinc was determined from the thickness by observing with a scanning electron microscope (SEM).

Table 2 shows the conditions of the NaCl aqueous solution used in calculation and experiment, α _a on the Zn (anode) side and α _c on the iron (cathode) side as parameters for considering the influence of corrosion products used in the calculation, these We show the comparison of the result of calculation with the boundary condition as the boundary condition and the measurement result of potential and corrosion amount by experiment. Regarding potentials, the surface of zinc to iron was measured every 1 mm in the longitudinal direction of the test piece at all 20 points, and the calculated potential at all 20 points was within the range of ± 50 mV with respect to the experimental results ○, not so The case was marked x. The corrosion amount distribution was evaluated as ○ when the calculated corrosion amount / (experimental corrosion amount) = 0.5 to 1.5 at all 20 measurement points, and x when out of this range. With respect to No. 1 to No. 7 which is the scope of the present invention, the distribution of potential and corrosion amount could be predicted with high accuracy for different solution concentrations and solution thicknesses. However, as shown in the comparative example, in the case where either α _a or α _c is less than 0.0010 or greater than 1.000, neither the potential nor the corrosion amount can reproduce the experiment. In addition, the difference between the calculation result and the experimental result is large even when either α _a or α _c is 1.00, which does not take into account the change in polarization characteristics due to the formation of corrosion products, and the experimental result is reproduced I can not do it.

(Example 2)
The heterogeneous metal catalytic corrosion of zinc and iron in contact with each other covered with a 1.0 or 2.0 mol / L NaCl aqueous solution with a thickness of 0.01 or 0.1 mm was predicted by numerical calculation. FIG. 6 shows a model of the shape used in this example. The region Ω is the region of the aqueous NaCl solution, and the concentration of Na ⁺ and Cl ⁻ is 1.0 or 2.0 mol / L as the initial concentration of the species, and the initial concentration and diffusion coefficient of the species to be considered in this solution Were set as shown in Table 3. In this example, the interface between zinc and iron and the solution was divided into 10 boundaries in total, and the boundaries 1 to 10 were made. The short boundary at the interface between zinc and iron is because the corrosion reaction is the largest in this region and the change in potential and current density is large. In the region Ω, it was assumed that the mass transport equation of equation (2) holds, and for each chemical species, diffusion due to concentration gradient in aqueous solution and migration due to charge were considered. The influence of convection is not considered here.

As the boundary conditions for solving equation (2), the anodic polarization curve of zinc measured in the same concentration aqueous NaCl solution as i _a _ _{z n} = f (E _a _ _{z n} ) and the cathodic polarization curve of iron i _c Assuming that _ _Fe = f (E _c _ _Fe ), the boundary conditions of boundaries 1 to 5 are i _a _ _zn = β × f (E _a _ _{z n} ), and the boundary condition is β = 1 − V _c / V ₀ It was determined. Here, V _c represents the volume of a corrosion product of Zn, and V ₀ represents a unit volume. On the other hand, in the present embodiment, the formation of iron-based corrosion products is not taken into consideration, and the boundary conditions of the boundaries 6 to 10 are set to i _{c — Fe} = f (E _{c — Fe} ). Strictly speaking, although Zn corrosion products are also formed on iron due to the diffusion and migration of substances, the calculation was carried out on the assumption that the effects were ignored. Here, 0.00110 ≦ β <1.000, and when the calculated value of β is less than 0.0010, β is set to 0.0010. At the boundaries other than the metal / solution interface, no current flow (∂Ф / の n = 0: where n represents a unit vector) was used as the boundary condition.

V _c can be calculated from the respective density values, since the amounts of Zn (OH) ₂ and ZnCO ₃ considered as corrosion products of zinc can be determined by calculation, and these two corrosion products can be obtained. the sum of components was V _c. Since V _c can be determined at each time step in sequential calculation, β is determined using this V _c . Calculations were sequentially performed by carrying out the calculation at the next time step with the corrected polarization curve obtained in this way as a boundary condition.

Under these conditions, the calculation was sequentially performed from time 0 to time 1440 min, and the potential distribution and current density distribution were calculated, and the concentration of chemical species and the concentration distribution of reaction products at that time were calculated. The chemical reactions in the aqueous solution considered the reactions shown in Table 4 on the zinc surface, and the reactions shown in Table 5 on the iron surface. Among them, Zn (CO ₃ ) and Zn (OH) ₂ were considered as corrosion products, and it was calculated on the assumption that the excess concentration in the solution would be rapidly precipitated when the equilibrium concentration was reached.

  In the same manner as in Example 1, the amount of corrosion of zinc after 10, 60, and 1440 min was determined.

  In order to evaluate the validity of these numerical calculation results, corrosion experiments were conducted under the same conditions as the numerical calculation. FIG. 5 shows a schematic view of a test piece in which 10 mm × 10 mm × 5 mmt of zinc and iron (both having a purity of 99.999%) used in the corrosion test are brought into contact with each other and fixed. An aqueous solution of NaCl having the same concentration and the same thickness as the conditions calculated numerically was formed on the surface of the test piece. In order to keep the thin salt water film once formed on the metal surface in a fixed state, the test piece is promptly set to room temperature and relative humidity to RH 95% (equivalent to 1.0 M) and RH 85% (equivalent to 2.0 M) The test piece was corroded by placing it in the constant temperature and humidity chamber.

  The test piece was corroded in a constant temperature and humidity chamber for 10, 60 and 1440 minutes, and then the potential distribution on the surface was measured using a scanning Kelvin probe. The same temperature and relative humidity as in the constant temperature and humidity chamber were maintained during measurement with the Kelvin probe so as not to change the corrosion state. After the measurement is completed, the test piece is promptly washed with distilled water and dried, and then the central portion of the test piece shown in the cross-sectional view taken along line AA 'of FIG. From the above, the amount of corrosion of zinc was determined from the thickness by observing with a scanning electron microscope (SEM).

Table 6 shows the conditions and corrosion time of the NaCl aqueous solution used for calculation and experiment, and the value of β used for correction of the polarization curve used as the boundary condition. The correction method is as follows: when the polarization curve of zinc in each solution is i _a _ _{z n} = f (E _a _ _{z n} ), β = 1− with respect to the volume amount Vc of corrosion product determined from equilibrium calculation. A polarization curve corrected with β at the boundary 1 to 5 of the electrolyte solution and the metal was applied by using V _c / V ₀ and correcting it as i _{a — zn} = β × f (E _{a — zn} ). Note that since the value of β is updated for each time step calculation for each of the boundaries 1 to 5, Table 6 describes the average β value of all the time step calculations for the boundary 3. Further, β = 1.000 means that the polarization curve of the metal was used as the boundary condition as it is without correcting the polarization curve.

  The comparison between the results calculated under these conditions and the measurement results of potential and corrosion amount by experiments is shown. Regarding potentials, the surface of zinc to iron was measured every 1 mm in the longitudinal direction of the test piece at all 20 points, and the calculated potential at all 20 points was within the range of ± 50 mV with respect to the experimental results ○, not so The case was marked x. The corrosion amount distribution of this example measures all ten points at intervals of 1 mm in the longitudinal direction of the test piece in the same manner as the electric potential only for the area of Zn, and the corrosion amount at all ten measurement points The case where the corrosion amount in the experiment) = 0.5 to 1.5 was evaluated as ○, and the case outside this range was evaluated as x. With respect to No. 1 to No. 9 within the scope of the present invention, the distribution of potential and corrosion amount could be predicted with high accuracy with respect to different solution concentrations, solution thicknesses and corrosion times. However, as shown in the comparative example, in the case where the polarization curve is not changed according to the generation amount of the corrosion product, that is, when β is 1.000, both the potential and the amount of corrosion can not be reproduced. In addition, even when the amount of corrosion product increases, that is, when β is less than 0.0010, the difference between the calculation result and the experimental result is large, and the experimental result can not be reproduced.

(Example 3)
Similar to Examples 1 and 2, the dissimilar metal catalytic corrosion of zinc and iron in an atmospheric corrosive environment was predicted by numerical calculation. The shape shown in FIG. 6 is used as a calculation model of this example. The region Ω simulates sea salt adhering in an actual atmospheric environment, is a region of a solution having a composition simulating seawater, and the initial concentration of chemical species is set as shown in Table 7. The diffusion coefficients to be considered for the chemical species included in the composition of this solution were set as shown in Table 8. In the region Ω, it was assumed that the mass transport equation of equation (2) holds, and for each chemical species, diffusion due to concentration gradient in aqueous solution and migration due to charge were considered. The influence of convection is not considered here.

As a boundary condition for solving the equation (2), the anodic polarization curve of zinc measured in artificial seawater (a solution for metal corrosion test, made by Yahata Pharmaceutical Co., Ltd.) is calculated in the same manner as the calculation i _a _ _{z n} = f (E _a _ _zn), when the cathodic polarization curves of iron and _{i c _ Fe = f (E} c _ Fe), from the boundary 1 of 5 boundary conditions _{i a _ zn = β × f} (E a _ zn) The boundary condition is determined as β = 1−V _c / V ₀ . Here, V _c represents the volume of a corrosion product of Zn, and V ₀ represents a unit volume. On the other hand, the formation of iron-based corrosion products is not taken into consideration, and the boundary conditions of the boundaries 6 to 10 are set as i _{c — Fe} = f (E _{c — Fe} ). Strictly speaking, although Zn corrosion products are also formed on iron due to the diffusion and migration of substances, the calculation was carried out on the assumption that the effects were ignored. Here, 0.00110 ≦ β <1.000, and when the calculated value of β is less than 0.0010, β is set to 0.0010. At the boundaries other than the metal / solution interface, no current flow (∂Ф / の n = 0: where n represents a unit vector) was used as the boundary condition.

  In an actual atmospheric corrosion environment, the temperature and humidity change continuously, and the concentration and average thickness of the aqueous solution film formed on the metal surface change accordingly. For this reason, also in numerical calculation, it is desirable to set the concentration and thickness of the aqueous solution accompanying changes in temperature and relative humidity for each unit time of calculation, and integrate the calculation results. However, in the present embodiment, in order to reduce the calculation load, the calculation was performed with the aqueous solution concentration kept constant at approximately the same concentration as the artificial seawater.

As in Example 2, V _c can be calculated from the values of the respective densities, since the amounts of Zn (OH) ₂ and ZnCO ₃ considered as corrosion products of zinc can be determined by calculation. The sum of the two corrosion product components is designated V _c . Since V _c can be determined at each time step in sequential calculation, β is determined using this V _c . Calculations were sequentially performed by carrying out the calculation at the next time step with the corrected polarization curve obtained in this way as a boundary condition.

Under this condition, the potential distribution and current density distribution are calculated by sequentially calculating up to the corrosion period shown in Table 9 (up to 4 weeks), and the concentration of chemical species and the concentration distribution of reaction products at that time Was calculated. The chemical reactions in the aqueous solution considered the reactions shown in Table 4 on the zinc surface and the reactions shown in Table 5 on the iron surface, as in Example 2. Among them, Zn (CO ₃ ) and Zn (OH) ₂ were considered as corrosion products, and it was calculated on the assumption that the excess concentration in the solution would be rapidly precipitated when the equilibrium concentration was reached.

  The amount of corrosion of zinc after each corrosion period was determined in the same manner as in Examples 1 and 2.

  In order to evaluate the validity of the calculation, an exposure test was conducted using a test piece having the shape shown in FIG. 5 as in Example 2. The exposure test was conducted in Minami-Toda-cho, Kawasaki-ku, Kawasaki-shi, Kanagawa Prefecture, and a test piece was placed under the eaves to prevent direct rain. A four week test was conducted, recording temperature and relative humidity every minute. Similar to Example 2, the validity of the numerical calculation results is the distribution of potential by Kelvin probe and the distribution of thickness of zinc determined by observing a test piece cut in the longitudinal direction with a scanning electron microscope (SEM) investigated.

Table 9 shows the corrosion period at each level and the value of β used to correct the polarization curve used as the boundary condition. The correction method is β = for the volume amount Vc of the corrosion product determined from the equilibrium calculation, _assuming that the polarization curve of zinc in each level of artificial seawater is i _a _ _{z n} = f (E _a _ _{z n} ). A polarization curve corrected with β at a boundary 1 to 5 of electrolyte solution and metal was applied by correcting 1 a − V _c / V ₀ with I _{a — z n} = β × f (E _{a — z n} ). Since the value of β is updated for each time step calculation every boundaries 1 to 5, Table 9 describes the average β value of all time step calculations for each boundary 1 to 5. Further, β = 1.000 means that the polarization curve of the metal was used as the boundary condition as it is without correcting the polarization curve. The polarization curves of No. 1 to No. 4, which are inventive examples, were corrected using the value (0.0010 to 1.000) of β according to the formation amount of the corrosion product. On the other hand, although β has different values for boundaries 1 to 5, in the comparative example, the value of any of β among boundaries 1 to 5 is out of the range of 0.0010 to 1.000.

  Table 9 shows a comparison of the calculated and exposed test results. As for the potential, the surface of zinc to iron was measured at 1 mm intervals in all 20 points in the longitudinal direction of the test piece, and the calculated potential of all 20 points was within the range of ± 100 mV with respect to the experimental result ○, not so The case was marked x. The corrosion amount distribution measures all 10 points at 1 mm intervals in the longitudinal direction of the test piece in the same way as the electric potential only for the area of Zn, and at all 10 measurement points (calculation amount of corrosion) / (experimental corrosion amount O) when it was 0.25-2.0, and the case out of this range was evaluated as x.

  As a result of comparing the distribution of corrosion and potential in the exposure test with the calculation of 7, 14, 21 and 28 days (4 weeks), the present invention accurately predicts both the potential distribution and the distribution of corrosion in any corrosion period. It was possible. On the other hand, as shown in the comparative example, when the polarization curve is not changed according to the generation amount of the corrosion product, or when the correction is out of the range in the present invention, the potential and the corrosion amount both largely deviate from the experimental results. It turned out that it became. Actual corrosion phenomena can be predicted with high accuracy by applying the present invention using the corrected polarization curve as a boundary condition in consideration of formation of corrosion products.

  According to the method of predicting corrosion of metal by numerical analysis of the present invention, it is possible to predict corrosion of metal in contact with an electrolyte solution more accurately by numerical analysis. Therefore, the design of metal structures and products, the evaluation of quality deterioration due to the corrosion of materials and structures, and the development of corrosion resistant materials can be carried out optimally and with high precision, which is an industrially extremely useful technology.

Claims (11)

A method of predicting corrosion of metal in contact with an electrolyte solution by numerical analysis,
Measuring a polarization curve which is the relationship between the potential E of the metal surface in the electrolyte solution and the current density i;
Obtaining a corrected polarization curve in which the value of the current density in the polarization curve is reduced;
Obtaining the potential distribution in the electrolyte solution at a predetermined time in a system in which the metal and the electrolyte solution are in contact, by using the corrected polarization curve as a boundary condition by numerical calculation;
I have a,
The method further includes the step of determining the generation amount p of the corrosion product generated per unit area on the surface of the metal by numerical calculation,
Assuming that the polarization curve is i = f (E) where the current density i is expressed as a function of the potential E, the corrected polarization curve is i = β × f (E), β = g (p) and A method of predicting corrosion of metal by numerical analysis characterized by satisfying 0.0010 ≦ β <1.000 . From the potential distribution of the electrolyte solution at a predetermined time, further comprising corrosion prediction of metal by numerical analysis according to claim 1 the step of obtaining numerically the current density distribution of the electrolyte solution at a predetermined time Method. In the step of calculating the amount of corrosion of the metal at the predetermined time according to Faraday's law using the current density in the vicinity of the interface with the metal in the electrolyte solution among the current density distribution in the electrolyte solution The corrosion prediction method of metal by numerical analysis according to claim 2 . A method of predicting corrosion of metal in contact with an electrolyte solution by numerical analysis,
  Measuring a polarization curve which is the relationship between the potential E of the metal surface in the electrolyte solution and the current density i;
  Obtaining a corrected polarization curve in which the value of the current density in the polarization curve is reduced;
  Obtaining the potential distribution in the electrolyte solution at a predetermined time in a system in which the metal and the electrolyte solution are in contact, by using the corrected polarization curve as a boundary condition by numerical calculation;
Have
  The method further includes the step of obtaining the current density distribution in the electrolyte solution at the predetermined time by numerical calculation from the potential distribution in the electrolyte solution at the predetermined time.
  In the step of calculating the amount of corrosion of the metal at the predetermined time according to Faraday's law using the current density in the vicinity of the interface with the metal in the electrolyte solution among the current density distribution in the electrolyte solution The metal corrosion prediction method by numerical analysis characterized by having. Assuming that the polarization curve is i = f (E) where the current density i is expressed as a function of the potential E, the corrected polarization curve is i = α × f (E), 0.0010 ≦ α <1.000.
The corrosion prediction method of metal by numerical analysis according to claim 4 .   The numerical analysis according to any one of claims 1 to 5, wherein the metal is one or more metals selected from zinc, iron, aluminum, copper, and nickel, or an alloy containing the metal as a main component. How to predict metal corrosion by   The numerical analysis according to any one of claims 1 to 6, wherein the form of the corrosion is heterogeneous metal catalytic corrosion in which two metals are in contact and the corrosion of one metal is accelerated by the potential difference between the metals. How to predict metal corrosion by   The method of predicting corrosion of metal by numerical analysis according to claim 7, wherein the two metals are a combination of zinc or zinc plating and iron or steel.   A method of designing a steel structure, comprising selecting a material by predicting corrosion resistance by the method of predicting corrosion of metal by numerical analysis according to any one of claims 1 to 8.   A method of designing a steel material, comprising: predicting corrosion resistance by the method of predicting corrosion of metal by numerical analysis according to any one of claims 1 to 8; and designing anticorrosion performance.   The corrosion prediction program which makes a computer perform the corrosion prediction method of metal by numerical analysis of any one of Claims 1-8.

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