JP6264311B2 - Method for predicting corrosion products - Google Patents

Description

  The present invention relates to a corrosion product prediction method for predicting the type and amount of a corrosion product in a metal material.

  Conventionally, galvanized steel sheets have been used to suppress corrosion of steel materials. For example, Non-Patent Document 1 introduces a corrosion mechanism of a galvanized steel sheet, and describes that a corrosion product generated by the corrosion of zinc suppresses corrosion of a base steel sheet. Non-Patent Document 2 states that there are various types of corrosion products, and the corrosion inhibition effects of the respective corrosion products are different.

Here, the type of the corrosion product varies depending on the corrosive environment, and the corrosion in the atmospheric environment may vary depending on the type of salt adhering to the zinc and the amount of components in the atmosphere such as CO ₂ and SO _2. Are known. If the corrosion inhibition effect by such a corrosion product can be clarified, it can be applied to the development of a material having excellent corrosion resistance. However, since corrosion in an atmospheric environment proceeds under a thin water film, it is difficult to elucidate the experimental corrosion mechanism, and there are many unclear points about the corrosion inhibition effect of corrosion products.

  In recent years, with the development of computer technology, it is expected that the corrosion phenomenon will be reproduced by computer simulation and applied to the elucidation of the corrosion mechanism. For example, in Non-Patent Document 3, in the dissimilar metal contact corrosion between the galvanizing and the base steel sheet, the mass transfer and chemical reaction in the water film in which corrosion occurs are numerically simulated, and the generation position and generation of the corrosion product Techniques for numerical analysis of quantities have been reported. In this method, the elution amount of zinc ions represented by the following formula (1), the production amount of hydroxide ions represented by the following formula (2), and the production reaction of corrosion products by these ions are minutely determined. The calculation is performed every hour, and by repeating this calculation, the generation behavior of the corrosion product in a predetermined corrosion time is to be simulated.

Zn → Zn ²⁺ + 2e ⁻ (1)
O ₂ + 2H ₂ O + 4e ⁻ → 4OH ⁻ Formula (2)

Sakae Fujita, Hiroshi Kashiyama, “Perforated Corrosion and Anticorrosion Mechanism of Rusted Steel Sheets in Automobiles”, Materials and Environment, Japan Corrosion and Corrosion Protection Association, 2001, Vol.50, No.3, p115-123 Xiaoge Gregory Zhang, "Corrosion and Electrochemistry of Zinc", Plenum Press, 1996, p157-158 Nobuhiro Okada, Masamitsu Matsumoto, Katsuhiro Nishihara, Masaya Kimoto, Ikuo Kudo, Shinji Fujimoto, “Numerical Analysis Model of Galvanic Corrosion Considering Ion Migration and Reaction”, Iron and Steel, Japan Iron and Steel Institute, 2009, Vol .95, No.2, p144-153

  However, in the corrosion product prediction method using computer simulation proposed in Non-Patent Document 3, both the calculation of the electrochemical reaction of corrosion and the calculation of the chemical reaction related to the formation of the corrosion product (chemical equilibrium calculation) are performed. Since the calculation is performed sequentially until the target time, the calculation load is very large, and there is a problem that it takes enormous calculation time to simulate the corrosion form after a long time has passed. That is, the prediction method proposed in Non-Patent Document 3 is not a practical means for predicting the corrosion form after a long time has elapsed.

  This invention is made | formed in view of the above, Comprising: It aims at providing the prediction method of the corrosion product which can estimate the kind and production amount of a corrosion product rapidly.

  In order to solve the above-described problems and achieve the object, the corrosion product prediction method according to the present invention predicts the type and amount of the corrosion product after a predetermined time by numerical calculation. In the method, a polarization curve measuring step for measuring a polarization curve indicating a relationship between a potential of a metal material in an aqueous solution and a current density, and a material balance and an electrical medium of each ion in the aqueous solution with the polarization curve as a boundary condition. A concentration distribution calculating step for calculating a concentration distribution of each ion in the aqueous solution at the predetermined time based on a sex condition, and a chemical equilibrium calculation for the formation reaction of the corrosion product based on the obtained concentration of each ion And a chemical equilibrium calculation step.

  Further, the corrosion product prediction method according to the present invention is such that the form of corrosion of the metal material is different metal contact corrosion, and the polarization curve measurement step includes a polarization curve of an anode which is a corroding metal, and corrosion prevention. And measuring a polarization curve of a cathode which is a metal on the side to be measured.

  The corrosion product prediction method according to the present invention is characterized in that the anode is zinc or zinc plating, and the cathode is iron or a steel material.

  The corrosion product prediction method according to the present invention is characterized in that the solute of the aqueous solution is NaCl.

  The corrosion product prediction method according to the present invention is characterized in that the NaCl concentration is 100 ppm to 5000 ppm.

  According to the method for predicting a corrosion product according to the present invention, the concentration distribution of each ion generated by an electrochemical reaction is calculated at a predetermined time, and the chemical equilibrium calculation relating to the formation reaction of the corrosion product is performed based on the concentration distribution. Thus, it is possible to easily predict the type and generation amount of the corrosion product generated at the predetermined time. In addition, the corrosion product prediction method according to the present invention may be performed only once instead of sequentially performing chemical equilibrium calculation as in the prior art, so that the corrosion form can be predicted quickly regardless of the elapsed time of corrosion. .

FIG. 1 is a flowchart showing an example of a corrosion product prediction method according to an embodiment of the present invention. FIG. 2 is a diagram showing an example of the polarization curves of zinc and iron in an aqueous solution used in the polarization curve measurement step according to the embodiment of the present invention. FIG. 3 is a flowchart showing a method for predicting corrosion products according to a conventional method. FIG. 4 is a diagram schematically showing an analysis model of dissimilar metal contact corrosion used in the example of the present invention. FIG. 5 is a graph showing the result of numerical calculation of the concentration distribution of each ion in the aqueous solution after the sample was immersed in a 100 ppm NaCl aqueous solution for one day in the example of the present invention. FIG. 6 is a graph showing the result of numerical calculation of the concentration distribution of each ion in the aqueous solution after the sample was immersed in a 5000 ppm NaCl aqueous solution for one day in the example of the present invention. FIG. 7 is a table showing the initial concentration of each ion used in the chemical equilibrium calculation in the example of the present invention. FIG. 8 is a table showing reaction equations, equilibrium constants, and solubility products for the formation of each corrosion product used in the chemical equilibrium calculation in the examples of the present invention. FIG. 9 is a table showing the amount of each corrosion product determined by chemical equilibrium calculation in an example of the present invention. FIG. 10 is a table showing the corrosion products identified by X-ray diffraction after the corrosion test. FIG. 11 is a graph showing changes in X-ray diffraction intensity of each corrosion product after the corrosion test with respect to NaCl concentration. FIG. 12 is a graph showing a change in the concentration of each corrosion product shown in FIG. 9 with respect to the NaCl concentration. FIG. 13 is a table showing the concentrations of corrosion products determined by the prediction method of the present invention and Non-Patent Document 3.

  Hereinafter, a method for predicting a corrosion product according to an embodiment of the present invention will be described with reference to the drawings. In addition, this invention is not limited to the following embodiment. In addition, constituent elements in the following embodiments include those that can be easily replaced by those skilled in the art or those that are substantially the same.

  In the corrosion product prediction method according to the present embodiment, the concentration of ions in the aqueous solution generated by the corrosion of the metal material is numerically calculated mainly in the field where the corrosion of the metal material is a problem, particularly in the field of automobiles, building materials, and the like. By calculating the chemical equilibrium based on the composition obtained by calculation, the type and amount of the corrosion product generated in the aqueous solution after a predetermined time has elapsed are predicted.

  Here, in this embodiment, the distinction between the corrosive side and the anticorrosive side is clear, and because it is suitable for numerical analysis, different metal contact corrosion is assumed as the corrosion mode. In this embodiment, zinc (Zn) or galvanization is used as the metal (anode) on the corrosive side (side eluted in the aqueous solution), and iron (Fe) or steel as the metal (cathode) on the anticorrosion side The use of materials is assumed. And the aqueous solution in this embodiment assumes the electrolyte solution which contains NaCl as a solute, for example from 100 ppm to 5000 ppm.

  Specifically, the method for predicting corrosion products according to the present embodiment performs three steps of a polarization curve measurement step, a concentration distribution calculation step, and a chemical equilibrium calculation step, as shown in FIG.

  In the polarization curve measurement step, the polarization curve of the metal material in the aqueous solution (hereinafter referred to as the electrolyte solution) is measured (step S1 in FIG. 1). Here, the polarization curve indicates the relationship between the electric potential in the electrolyte solution of the metal material and the current density. When the zinc is used as the corroding metal (anode) and iron is used as the anticorrosive metal (cathode), the polarization curve is, for example, a curve as shown in FIG.

  In the polarization curve measurement step, as shown in FIG. 2, the anode (zinc) side polarization curve (anode polarization curve) and the cathode (iron) side polarization curve (cathode polarization curve) in the electrolyte solution are respectively measured. In FIG. 2, for each of zinc and iron, polarization curves when the NaCl concentration of the electrolyte solution is 100 ppm (0.01 mass%) and 5000 ppm (0.5 mass%) are shown as an example.

  In the concentration distribution calculating step, the polarization curve measured in the polarization curve measuring step is used as a boundary condition, and based on the mass balance of each ion in the electrolyte solution and the electrical neutral condition, each ion in the electrolyte solution at a predetermined time t A density distribution is calculated (step S2 in FIG. 1). In the concentration distribution calculation step, it is assumed that the surface of the metal material (here, zinc and iron) is covered with a thin electrolyte solution. Then, the electrolyte solution is divided into minute grid-like regions (cells), and the ion concentration change is calculated for each cell. Hereinafter, mathematical formulas used in the concentration distribution calculating step will be described first.

  The material balance equation for each ion species i is expressed by the following equation (3).

Here, in the above formula (3), C _i is the concentration of ionic species i, t is time, N _i is the flux of ionic species i, r _i is shown the production or consumption rate of the ionic species i by a chemical reaction Yes. Since the present invention is characterized in that the formation reaction of corrosion products is not taken into account when obtaining the concentration distribution of each ion, the value of r _i in the above equation (3) is set to zero.

Moreover, since there is no occurrence and disappearance of the material in the electrolyte, the flux N _i in the formula (3), when there is no flow of electrolyte is represented by the Nernst-Planck equation represented by the following formula (4).

Here, in the above formula (4), D _i is the diffusion coefficient of ion species i, C _i is the concentration of ion species i, z _i is the valence of ion species i, u _i is the mobility of ion species i, F represents a Faraday constant, and φ represents a potential.

In addition, “D _i ∇C _i ” in the first term on the right side in the above formula (4) is the amount of ion species i moving by diffusion, and “z _i u _i FC _i ∇φ” in the second term on the right side is The amount of ionic species i moving by electrophoresis is shown. Therefore, the expression obtained by substituting the above expression (4) into the above expression (3) is, in other words, “an ion species i in which a change in the concentration C _i of the ion species i per unit time in a certain cell moves due to diffusion”. , The amount of ion species i that migrates by electrophoresis, and the amount of ionic species i produced or consumed by chemical reaction.

Since the Nernst-Einstein relationship shown in the following equation (5) is established between the diffusion coefficient D _i and the mobility u _i in the above equation (4), the following equation (5) is expressed by the above equation (5). Substitute in 4). In the following formula (5), R is a gas constant, and T is an absolute temperature.

  Further, the ions in each cell must be electrically neutral. Therefore, the above formula (5) needs to satisfy the electrical neutral requirement shown in the following formula (6). In the following formula (6), N is the total number of ion species i.

  The current density I in the solution is expressed by the following formula (7).

  The above equations (3), (6), and (7) are solved simultaneously by, for example, the finite element method using the polarization curve measured in the polarization curve measurement step as a boundary condition, thereby obtaining a predetermined time t. The concentration, potential and current density of ions in each cell can be determined. “Solving the polarization curve as a boundary condition” means that, for example, the electrolyte solution is surrounded by a predetermined boundary, and the above equations (3), (6), and (7) It means solving based on boundary conditions as shown in the following equations (8) to (10) indicating the boundary.

Here, in the above formulas (8) to (10), Γ _a is the surface of the anode, Γ _c is the surface of the cathode, Γ _b is the boundary other than the anode and the cathode, and f _a (i) is the potential in the polarization curve of the anode. And a function representing the relationship between the current density and f _c (i) is a function representing the relationship between the potential and the current density in the polarization curve of the cathode.

  The elution reaction of a certain metal M at the anode is represented by the following formula (11). In the following formula (11), n is the number of metal valence electrons.

M → M ^{n +} + ne ⁻ Expression (11)

  On the other hand, the reduction reaction of dissolved oxygen in the aqueous solution at the cathode is represented by the following formula (12).

O ₂ + 2H ₂ O + 4e ⁻ → 4OH ⁻ Formula (12)

Since the number of electrons that flowed per unit time / unit area can be determined from the current density I obtained by simultaneously solving the above formula (3), the above formula (6), and the above formula (7), the above formula ( 11) or the above formula (12), the amount of ions M _i generated per unit time and unit area on the anode surface or cathode surface can be determined. Here, the flux N _i of a substance in the electrolyte portion in contact with the electrodes is represented by the following formula (13). In the following formula (13), l is a normal vector on the electrode surface.

  In the concentration distribution calculating step, it is necessary to divide the electrolyte solution to be calculated into fine calculation elements (cells, meshes) as described above, but the size and shape of the cells are not particularly limited.

  Hereinafter, a specific calculation method of the ion concentration distribution using each of the above equations will be described. Here, in the following description, a case will be described in which the concentration distribution of each ion in the electrolyte solution is calculated when the time t = 3 seconds and the metal material is immersed in the electrolyte solution for 3 seconds.

(Calculation of concentration distribution of each ion at t = 1)
First, the above equations (3), (6), and (7) are simultaneously solved using the polarization curve measured in the polarization curve measurement step as a boundary condition, and the ions in each cell at the time of t = 1 are solved. Concentration, potential and current density are calculated. The initial concentration of the solution is used as the concentration value in this calculation. Further, the amount of ions generated in each cell at the time point t = 1 is calculated by the above formula (11) or the above formula (12).

(Calculation of concentration distribution of each ion at t = 2)
Next, the equation (3), the equation (6), and the equation (7) are solved simultaneously using the polarization curve as a boundary condition, and the concentration, potential, and current density of ions in each cell at the time of t = 2. Is calculated. At this time, in the cell in contact with the electrode, the ion generation amount calculated in the previous process (t = 1) is taken into consideration by reflecting it in the equation (3) as the flux obtained by the equation (13). Further, the amount of ions generated in each cell at the time point t = 2 is calculated by the above formula (11) or the above formula (12).

(Calculation of concentration distribution of each ion at t = 3)
Next, the equation (3), the equation (6), and the equation (7) are solved simultaneously using the polarization curve as a boundary condition, and the concentration, potential, and current density of ions in each cell at the time of t = 3. Is calculated. At this time, in the cell in contact with the electrode, the ion generation amount calculated in the previous process (t = 2) is taken into consideration by reflecting the amount of the ion obtained in Equation (13) in Equation (3).

  As described above, in the concentration distribution calculation step, the simultaneous calculation of the above formula (3), the above formula (6), and the above formula (7) is repeatedly performed for each cell until the target time t. The concentration distribution of each ion is calculated.

  In the chemical equilibrium calculation step, a chemical equilibrium calculation relating to the formation reaction of the corrosion product is performed based on the obtained concentration of each ion (step S3 in FIG. 1). In the chemical equilibrium calculation step, the concentration of each ion obtained in the concentration distribution calculation step is input as the initial value of the reactant, and chemical equilibrium calculation is performed. In addition, what is necessary is just to input the substance which may be produced | generated from the density | concentration of each ion obtained at the density | concentration distribution calculation step as a corrosion product calculated | required by chemical equilibrium calculation. The chemical equilibrium calculation will be described in detail in the examples described later.

  Here, the corrosion product prediction method in the prior art (Non-Patent Document 3) is the same as the present invention in the polarization curve measurement step (step S101) as shown in FIG. However, in Non-Patent Document 3, for each of the concentration distribution calculation step (step S102) and the chemical equilibrium calculation step (step S103), as shown in step S104 and step S105, the calculation is repeatedly repeated until the target time t. Do. Thus, in Non-Patent Document 3, although the numerical accuracy is calculated sequentially, the prediction accuracy is good, but the calculation takes a long time, and it is practically impossible to simulate the corrosion form after a long time has passed. .

  On the other hand, according to the method for predicting a corrosion product according to the present invention described above, the concentration distribution of each ion generated by an electrochemical reaction is calculated at a predetermined time, and the chemistry relating to the formation reaction of the corrosion product is based on this. By performing the equilibrium calculation, it is possible to easily predict the type and amount of corrosion products generated at the predetermined time. In addition, the corrosion product prediction method according to the present invention may be performed only once instead of sequentially performing chemical equilibrium calculation as in the prior art, so that the corrosion form can be predicted quickly regardless of the elapsed time of corrosion. .

  Hereinafter, the present invention will be described more specifically with reference to examples. Note that this embodiment does not limit the corrosion phenomenon, conditions, calculation method, and the like targeted by the present invention, and can be implemented with appropriate modifications within a range that can meet the spirit of the present invention. These are all included in the technical scope of the present invention.

[Experimental Example 1]
Here, the result of the corrosion product prediction method according to the present invention is compared with the result of an actual corrosion product generation experiment, and whether or not the type and amount of the corrosion product can be appropriately predicted by the present invention. I confirmed.

<Prediction experiment of corrosion products>
First, the type and amount of corrosion products were predicted by the prediction method according to the present invention. Here, as shown in FIG. 4, an analysis model was used that assumed a case where different metal contact corrosion of zinc (anode 1) and iron (cathode 2) occurred via a NaCl aqueous solution (electrolyte solution 3). . In this analytical model, as shown in the figure, the anode 1 and the cathode 2 are arranged adjacent to each other so that the electrolyte solution 3 is formed on the anode 1 and the cathode 2, and the electrolyte solution A gas phase 4 is formed on 3. Moreover, the width of the anode 1 and the cathode 2 in the analysis model is 65 mm, respectively, and the liquid film thickness of the electrolyte solution 3 is 3 mm.

(Polarization curve measurement step)
Here, zinc is eluted as zinc ions (Zn ²⁺ ) in the NaCl aqueous solution by the anodic reaction shown in the above formula (1). On the other hand, on the surface of iron, hydroxide ions (OH ⁻ ) are generated by the cathode reaction shown in the above formula (2). Based on these, the polarization curve (see FIG. 2), which is the relationship between potential and current density in each equation, was measured.

(Concentration distribution calculation step)
Using the polarization curve as a boundary condition, the above equations (3), (6), and (7) were solved by the finite element method, and the concentration distribution of each ion after one day (86400 seconds) was calculated. . In addition, the size of the cell (mesh) at the time of analysis by the finite element method was 3 mm in length × 5.8 mm in width. Moreover, the NaCl concentration of NaCl aqueous solution was made into 100 ppm (0.01 mass%) and 5000 ppm (0.5 mass%).

FIGS. 5 and 6 show zinc ions (Zn ²⁺ ), hydroxide ions (OH ⁻ ), sodium ions (Na ⁺ ) after one day (immersion) at the interface between zinc and iron and an aqueous NaCl solution. ) And chloride ion (Cl ⁻ ) concentration distribution. 5 shows the concentration distribution when the NaCl concentration is 100 ppm, and FIG. 5 shows the concentration distribution when the NaCl concentration is 5000 ppm. Thus, in the concentration distribution calculation step, the concentration of each ion at each position in the NaCl aqueous solution is obtained.

(Chemical equilibrium calculation step)
Next, chemical equilibrium calculation was performed based on the concentration of each ion shown in FIGS. Here, as shown in the figure, the zinc ion concentration is highest at a position of 5 mm on the zinc side from the interface between zinc and iron. Therefore, here, the chemical equilibrium calculation was performed using the concentration of each ion at a position of 5 mm on the zinc side from the interface between zinc and iron.

FIG. 7 shows the initial concentration of each ion used in the chemical equilibrium calculation. Here, the gas phase was in a state in which atmospheric CO ₂ was saturated, and the amount of H ₂ O was 55.51 Mol corresponding to a 1 L aqueous solution. For Zn, OH ⁻ , Na ⁺ , and Cl ⁻ , the values of the calculation results of the concentration distribution described above were used. As the corrosion products, is a zinc-based corrosion products has been confirmed in environments where chlorides are _{present, ZnO, Zn (OH) 2} , Zn 5 (OH) 6 (CO 3) 2, ZnCl 2 · Four types of 4Zn (OH) ₂ were considered.

  FIG. 8 shows the reaction formula, equilibrium constant, and solubility product of each corrosion product. In FIG. 1-No. 3 shows the dissociation reaction of water and carbonic acid. 4-No. The reaction formula 7 shows the formation reaction of the corrosion product. Based on these conditions, chemical equilibrium calculation was performed, and the calculation results shown in FIG. 9 were obtained.

As shown in FIG. 9, in the 100 ppm NaCl aqueous solution, Zn ₅ (OH) ₆ (CO ₃ ) ₂ was the main corrosion product, and Zn (OH) ₂ was the next most corrosion product. Further, in the 100 ppm NaCl aqueous solution, ZnCl ₂ .4Zn (OH) ₂ was hardly generated. On the other hand, in the 5000 ppm NaCl aqueous solution, ZnCl ₂ · 4Zn (OH) ₂ became the main corrosion product, and the production amount decreased in the order of Zn ₅ (OH) ₆ (CO ₃ ) ₂ and Zn (OH) ₂ . In any NaCl concentration, ZnO was hardly generated.

<Corrosion product generation experiment>
Next, in order to compare with the prediction result of the corrosion product according to the present invention, an actual corrosion product generation experiment was performed. In this experiment, first, plating of a half surface of a galvanized steel sheet (width 150 mm × length 70 mm × thickness 0.8 mm) was removed with hydrochloric acid to obtain a zinc-iron pair sample. Next, an enclosure having a width of 130 mm was provided on the sample, and a NaCl aqueous solution having a concentration of 100 ppm and 5000 ppm was put therein so as to have a height of 3 mm, and the sample was corroded for one day. And the phase of the corrosion product formed on the sample was identified by X-ray diffraction.

In FIG. 10, the identification result of the corrosion product by X-ray diffraction is shown. As shown in the drawing, in the 100 ppm NaCl aqueous solution, ZnO, Zn ₅ (OH) ₆ (CO ₃ ) ₂ and ZnCl ₂ .4Zn (OH) ₂ were recognized as corrosion products. Further, in the 5000 ppm NaCl aqueous solution, ZnO, Zn (OH) ₂ , Zn ₅ (OH) ₆ (CO ₃ ) ₂ and ZnCl ₂ .4Zn (OH) ₂ were recognized as corrosion products.

Next, in order to know the change in the amount of each corrosion product produced, the diffraction intensity in X-ray diffraction was examined. In the measurement using Cu-Kα rays, ZnO is 34.4 °, Zn (OH) ₂ is 20 °, Zn ₅ (OH) ₆ (CO ₃ ) ₂ is 33.3 °, and ZnCl ₂ · 4Zn (OH). ₂ used the diffraction intensity at 11.3 °.

FIG. 11 shows the relationship between the X-ray diffraction intensity of each corrosion product and the NaCl concentration (change in the X-ray diffraction intensity of each corrosion product with respect to the NaCl concentration). In addition, since it is known that Zn (OH) ₂ becomes ZnO by a dehydration reaction, it is shown as the sum of ZnO and Zn (OH) ₂ (ZnO + Zn (OH) ₂ ) in FIG. As shown in the figure, the X-ray diffraction intensities of ZnO + Zn (OH) ₂ and Zn ₅ (OH) ₆ (CO ₃ ) ₂ decreased with increasing NaCl concentration. On the other hand, the X-ray diffraction intensity of ZnCl ₂ .4Zn (OH) ₂ increased as the NaCl concentration increased.

Here, in order to compare the prediction result of the corrosion product according to the present invention with the result in the actual corrosion product generation experiment, the concentration and NaCl concentration obtained from the production amount of each corrosion product shown in FIG. (Change in the concentration of each corrosion product with respect to NaCl concentration) is shown in FIG. In this figure, ZnO and Zn (OH) ₂ are shown as their sum (ZnO + Zn (OH) ₂ ). As shown in the figure, the concentrations of ZnO + Zn (OH) ₂ and Zn ₅ (OH) ₆ (CO ₃ ) ₂ decreased with increasing NaCl concentration. On the other hand, the concentration of ZnCl ₂ · 4Zn (OH) ₂ increased with increasing NaCl concentration.

  Thus, according to FIG. 11 and FIG. 12, the prediction result of the corrosion product according to the present invention can reproduce the tendency of the result in the actual corrosion product generation experiment, and the type and amount of the corrosion product. Is considered to have been properly predicted.

[Experiment 2]
Here, the calculation time required for the corrosion product prediction method according to the present invention and the calculation time required for the corrosion product prediction method described in Non-Patent Document 3 were compared.

In the prediction method according to the present invention, when four types of corrosion products (ZnO, ZnZnO, Zn (OH) ₂ , Zn ₅ (OH) ₆ (CO ₃ ) ₂ , ZnCl ₂ .4Zn (OH) ₂ ) are taken into consideration The numerical calculation (concentration distribution calculation step) for obtaining the concentration distribution of each ion after 50 seconds (immersion) required 9 seconds for a 100 ppm NaCl aqueous solution and 86 seconds for a 5000 ppm NaCl aqueous solution. . Similarly, it took 93 seconds for the 100 ppm NaCl aqueous solution and 2 seconds for the 5000 ppm NaCl aqueous solution to calculate the concentration distribution of each ion after the passage of one day (immersion). The chemical equilibrium calculation step was completed within 1 second.

On the other hand, in the prediction method described in Non-Patent Document 3, when only one type of corrosion product (Zn (OH) ₂ ) is considered, the corrosion product after 50 seconds (immersion) is predicted. The numerical calculation took 103020 seconds for a 100 ppm NaCl aqueous solution and 289740 seconds for a 5000 ppm NaCl aqueous solution. And the prediction of the corrosion product after the passage of one day (dipping) could not be performed because it took a huge amount of time.

  Thus, according to the corrosion product prediction method of the present invention, it is possible to quickly predict the corrosion form regardless of the elapsed time of corrosion.

[Experiment 3]
Here, the prediction result of the corrosion product according to the present invention was compared with the prediction result of the corrosion product described in Non-Patent Document 3, and the calculation accuracy of the present invention was confirmed. Here, for each of the prediction methods of the present invention and Non-Patent Document 3, numerical calculation results after 50 seconds (immersion) when only Zn (OH) ₂ was considered as a corrosion product were compared.

FIG. 13 shows the Zn (OH) ₂ concentration after 50 seconds at a position of 5 mm from the zinc-iron interface to the zinc side, as determined by the prediction method of the present invention and Non-Patent Document 3. As shown in the figure, the order of the Zn (OH) ₂ concentration of the present invention and that of Non-Patent Document 3 are the same in the case of a 100 ppm NaCl aqueous solution and the case of a 5000 ppm NaCl aqueous solution. Therefore, it can be seen that the prediction method according to the present invention has the same accuracy as that of Non-Patent Document 3.

  The method for predicting a corrosion product according to the present invention has been specifically described above with reference to modes and examples for carrying out the invention. However, the gist of the present invention is not limited to these descriptions, and claims are made. Should be interpreted broadly based on the description of the scope. Needless to say, various changes and modifications based on these descriptions are also included in the spirit of the present invention.

1 Anode 2 Cathode 3 Electrolyte Solution 4 Gas Phase

Claims (5)

In the corrosion product prediction method for predicting the type and amount of corrosion products after a predetermined time by numerical calculation,
A polarization curve measuring step for measuring a polarization curve indicating a relationship between a potential and a current density in an aqueous solution of a metal material;
A concentration distribution calculating step for calculating a concentration distribution of each ion in the aqueous solution at the predetermined time based on a mass balance of each ion in the aqueous solution and an electrical neutral condition using the polarization curve as a boundary condition;
Based on the concentration of each ion obtained at the predetermined time, the chemical equilibrium calculation related to the formation reaction of the corrosion product is performed only once, so that the type and amount of the corrosion product generated at the predetermined time are determined. A predicted chemical equilibrium calculation step;
A method for predicting corrosion products, comprising: The form of corrosion of the metal material is dissimilar metal contact corrosion,
2. The corrosion generation according to claim 1, wherein the polarization curve measuring step measures a polarization curve of an anode which is a metal to be corroded and a polarization curve of a cathode which is a metal to be protected. How to predict things.   The said anode is zinc or galvanization, and the said cathode is iron or a steel material, The prediction method of the corrosion product of Claim 1 or Claim 2 characterized by the above-mentioned.   The method for predicting a corrosion product according to any one of claims 1 to 3, wherein the solute of the aqueous solution is NaCl.   The method for predicting a corrosion product according to claim 4, wherein the NaCl concentration is 100 ppm to 5000 ppm.

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