Prediction device, prediction method, and prediction program

Abstract

A prediction device according to the present invention comprises a prediction unit that calculates a first fraction for a first period and a second fraction for a second period for each phase of a plating layer on the basis of how much of each of a plurality of components is included in the plating layer, calculates the period length of the first period, which is until a portion of the corrosion of the plating layer reaches a base steel, on the basis of a corrosion rank for each phase, the first fraction for each phase, and a first corrosion speed for each phase, calculates the period length of the second period, which follows the first period, on the basis of the corrosion rank for each phase, the second fraction for each phase, and a second corrosion speed for each phase, and calculates the total of the period length of the first period and the period length of the second period as prediction results for the corrosion resistance of the plating layer.

Description

Prediction device, prediction method, and prediction program

[0001] This application claims priority to Japanese Patent Application No. 2023-186777, filed on October 31, 2023, the contents of which are incorporated herein by reference.

[0002] Since steel corrodes when exposed to the atmosphere, it is necessary to subject the steel to anti-corrosion treatment such as plating in order to use the steel for a long period of time. Plated steel is cheaper than stainless steel. In recent years, from the viewpoint of carbon neutrality, importance has been placed on life cycle costs, and highly corrosion-resistant plated steel sheets that can protect steel from corrosion for a long period of time have been attracting attention. An example of highly corrosion-resistant plated steel sheets is zinc-aluminum-magnesium (Zn-Al-Mg) alloy plated steel sheet (see Patent Documents 1 and 2).

[0003] Patent No. 7136351 Patent No. 7040695

[0004] Various properties are required of plated steel sheets, such as corrosion resistance, sacrificial corrosion protection, workability, abrasion resistance, and color tone. However, the properties of plated steel sheets are evaluated independently by each steel company, and are not uniformly evaluated by all steel companies. For this reason, end users may have difficulty selecting the optimal plated steel sheet based on the properties.

[0005] Furthermore, these properties are highly dependent on the alloy composition of the plating layer. In other words, the properties of the plating layer depend on the substances (phases) formed by the bonding of the elements of each metal component and the content of these substances. For example, a Zn-Al plating layer contains Zn and Al phases. Here, as the content of Al increases, the Al phase in the plating layer increases. As a result, the properties of the plating layer approach those of Al, and the corrosion resistance of the plating layer improves. On the other hand, the sacrificial corrosion protection that is excellent in the Zn phase decreases in a plating layer with a small amount of Zn phase.

[0006] Furthermore, if the corrosion resistance of galvanized steel sheets can be known, end users can choose the most suitable galvanized steel sheets that prioritize life cycle costs. Also, knowing the corrosion resistance of galvanized steel sheets will reduce confusion regarding the maintenance and replacement frequency of galvanized steel sheets. For this reason, many users are interested in the corrosion resistance (service life, lifespan) of galvanized steel sheets.

[0007] In order to improve the accuracy of predicting the corrosion resistance of a coating layer, it is desirable to calculate the corrosion rate based on the results of exposure tests and accelerated corrosion tests previously obtained for various types of coated steel sheets. However, in recent years, coating layers have come to contain not only Al and Zn but also Mg, and since the corrosion resistance of Al, Zn, and Mg differs, predicting the corrosion resistance of a coating layer has become even more difficult. Thus, there is a problem in that it is not possible to improve the accuracy of predicting the corrosion resistance of a coating layer.

[0008] In view of the above circumstances, an object of the present invention is to provide a prediction device, a prediction method, and a prediction program that can improve the accuracy of predicting the corrosion resistance of a plating layer.

[0009] One aspect of the present invention is a prediction device including a prediction unit that calculates a first proportion in a first period and a second proportion in a second period of each phase constituting the plating layer based on the respective contents of a plurality of components contained in the plating layer; calculates a length of the first period until part of the corrosion of the plating layer reaches the base steel based on the corrosion ranking of each phase, the first proportion of each phase, and a first corrosion rate of each phase; calculates a length of the second period following the first period based on the corrosion ranking of each phase, the second proportion of each phase, and a second corrosion rate of each phase; and calculates the sum of the length of the first period and the length of the second period as a predicted result of the corrosion resistance of the plating layer.

[0010] One aspect of the present invention is a prediction method executed by the above-mentioned prediction device, the prediction method including the steps of: calculating a first proportion in a first period and a second proportion in a second period of each phase constituting the plating layer based on the respective contents of a plurality of components contained in the plating layer; calculating a length of the first period until part of the corrosion of the plating layer reaches the base steel based on the corrosion ranking of each phase, the first proportion of each phase, and a first corrosion rate of each phase; calculating a length of the second period following the first period based on the corrosion ranking of each phase, the second proportion of each phase, and the second corrosion rate of each phase; and calculating the sum of the length of the first period and the length of the second period as a prediction result of the corrosion resistance of the plating layer.

[0011] One aspect of the present invention is a prediction program for causing a computer to execute the steps of: calculating a first proportion in a first period and a second proportion in a second period of each phase constituting the plating layer based on the content of each of a plurality of components contained in the plating layer; calculating the length of the first period until part of the corrosion of the plating layer reaches the base steel based on the corrosion ranking of each phase, the first proportion of each phase, and a first corrosion rate of each phase; calculating the length of the second period following the first period based on the corrosion ranking of each phase, the second proportion of each phase, and a second corrosion rate of each phase; and calculating the sum of the length of the first period and the length of the second period as a predicted result of the corrosion resistance of the plating layer.

[0012] According to the present invention, it is possible to improve the accuracy of predicting the corrosion resistance of a plating layer.

[0013] FIG. 1 is a diagram showing an example of the configuration of a prediction device in an embodiment. FIG. 2 is a diagram showing an example of a model of the corrosion morphology of a Zn-Al-Mg coating layer in an embodiment. FIG. 3 is a diagram showing an example of the liquidus temperature of Zn-Al-Mg in an embodiment. FIG. 4 is a diagram showing an example of the 1 molar molecular weight and density of each phase in an embodiment. FIG. 5 is a diagram showing an example of a database of the area fraction of each phase in an embodiment. FIG. 6 is a flowchart showing an example of a process for calculating the adhesion weight of each phase in an embodiment. FIG. 7 is a diagram showing an example of the corrosion rate of each phase in a first period in an embodiment. FIG. 8 is a flowchart showing an example of a process for calculating the length of a period (first period) during which partial corrosion can be confirmed on the surface of the coating layer and the length of a period (second period) after partial corrosion has reached the interface between the coating layer and the steel sheet in an embodiment.

[0014] An embodiment of the present invention will be described in detail with reference to the drawings. In the following, a prediction device, a prediction method, and a prediction program will be described using a zinc (Zn)-aluminum (Al)-magnesium (Mg) plating layer as an example of a plating layer, but the plating layer in the embodiment is not limited to a Zn-Al-Mg plating layer.

[0015] 1 is a diagram showing an example of the configuration of a prediction device 1 according to an embodiment. The prediction device 1 is an information processing device that predicts the corrosion resistance of a plating layer, and is, for example, a personal computer or a smartphone terminal. The prediction device 1 includes a storage device 11, a storage unit 12, a prediction unit 13, a display unit 14, and a communication unit 15.

[0016] The storage device 11 is a non-volatile recording medium (non-transitory recording medium). The prediction program is loaded from the storage device 11 into the storage unit 12.

[0017] The prediction unit 13 is, for example, a processor such as a CPU (Central Processing Unit). The prediction unit 13 is realized as software by executing a prediction program loaded from the storage device 11 onto the storage unit 12. The prediction program may be recorded on a computer-readable recording medium. Examples of computer-readable recording media include portable media such as flexible disks, magneto-optical disks, ROMs (Read Only Memory), and CD-ROMs (Compact Disc Read Only Memory), and non-transitory recording media such as storage devices built into computer systems, including hard disks and solid state drives (SSDs).

[0018] The prediction unit 13 may be realized using hardware including an electronic circuit (electronic circuit or circuitry) using, for example, an LSI (Large Scale Integration circuit), an ASIC (Application Specific Integrated Circuit), a PLD (Programmable Logic Device), or an FPGA (Field Programmable Gate Array).

[0019] The prediction unit 13 predicts the corrosion resistance of the plating layer based on the contents (input values) of Zn, Al, and Mg. For example, the prediction unit 13 calculates the proportion of each phase constituting the plating layer, and predicts the service life (service years) of the plating layer based on the calculated proportions.

[0020] The display unit 14 includes a display device such as a liquid crystal display, etc. The display unit 14 displays, for example, the prediction result.

[0021] The communication unit 15 communicates with an external communication device (not shown) via a communication line such as the Internet, a local area network (LAN), a wide area network (WAN), etc. The communication unit 15 may transmit, for example, a prediction result to the communication device (not shown).

[0022] Next, details of the prediction device, prediction method, and prediction program will be described. Ideally, it would be desirable to predict the service life of a plated steel sheet based on a database of exposure test results for the plated steel sheet. However, plated steel sheets used in the field of building materials are required to have a service life (corrosion resistance) of 30 to 50 years or more. For this reason, it is practically difficult to create a database of recently developed plated steel sheets. However, it is possible to predict the corrosion resistance of a plated steel sheet in an exposure test by accurately predicting the corrosion resistance of the coating layer based on the results (knowledge) of an accelerated corrosion test (e.g., a cyclic corrosion test) that has some correlation with the exposure test.

[0023] Therefore, the prediction device 1 predicts the corrosion resistance of a plating layer based on accumulated knowledge about accelerated corrosion, which has a certain degree of correlation with exposure tests. The degree of acceleration (corrosion rate) of the accelerated corrosion test can be changed by changing the saltwater concentration and the cycle interval. Furthermore, if the corrosion rate of each substance (each phase) that makes up the plating layer can be obtained, it is possible to predict the corrosion resistance of the plated steel sheet.

[0024] Furthermore, the prediction device 1 predicts the corrosion resistance of a plating layer using a corrosion model based on knowledge gained from numerous accelerated corrosion tests. In order to calculate the corrosion resistance (service life) of a plating layer, the corrosion mode of the plating layer must be fully theoretically elucidated, and knowledge of the corrosion mode must be reflected in the corrosion model. In this regard, the relationship between the corrosion model and accelerated corrosion tests and the relationship between the corrosion model and exposure tests have been fully confirmed.

[0025] 2 is a diagram (cross-sectional view) showing an example of a corrosion model (corrosion model) of a Zn-Al-Mg plating layer in an embodiment. The plating layer 101 is a Zn-Al-Mg plating layer. The plating layer 101 is present on the surface of a steel material 102, and thus has sacrificial corrosion protection properties for the steel material 102. For example, the plating layer 103-1 shows the range of a ternary eutectic structure.

[0026] During the corrosion period, which includes period I (first period) and period II (second period) exemplified below, the plating layer 101 (Zn-Al-Mg plating layer) corrodes depending on the usage environment.

[0027] Stage I: This is the period when the coating layer corrodes partially from the surface. Stage II: This is the period when some of the corrosion of the coating layer reaches the interface between the coating layer and the steel material, and the coating layer corrodes while providing sacrificial protection to the base steel material (base steel). The steel sheet remains protected from corrosion until the coating layer, which provides sacrificial protection to the base steel sheet, disappears.

[0028] The end of Period II marks the end of the service life of the coating layer. When Period II ends, red rust spots formed on the steel material due to corrosion can be seen from the surface of the coating layer. That is, the prediction device 1 calculates the number of cycles at which the weight of the coating layer remaining on the surface of the steel sheet decreases in the accelerated corrosion test and the weight or thickness of the coating layer given as the input value (initial value) finally becomes zero as the service life (corrosion resistance) of the coating layer.

[0029] The reason for distinguishing the corrosion period (service life) into these two periods is that in Period I, the corrosion rate is specific to the phases that make up the coating layer. In contrast, in Period II, corrosion of the coating layer is accelerated by corrosion protection of the steel sheet (base steel). Therefore, in Period II, the corrosion rate in Period I (first corrosion rate) must be multiplied by the acceleration factor to obtain a corrosion rate corrected for each phase (second corrosion rate).

[0030] The prediction device 1 calculates the corrosion rate of each phase constituting the plating layer for each of Periods I and II based on the composition of the plating layer (input value). The prediction device 1 calculates the overall corrosion resistance (service life) of the plating layer by summing the service life corresponding to the corrosion rate of each phase.

[0031] FIG. 3 is a diagram (liquidus diagram) showing an example of the liquidus temperature of Zn-Al-Mg (Reference 1: P. Liang, T. Tarfa, J.A. Robinson, et al., "Experimental investigation and thermodynamic calculation of the Al±Mg±Zn system," Thermochimica Acta 314 (1998) 87-110) in an embodiment.

[0032] The liquidus lines in the liquidus diagram shown in Figure 3 correspond to contour lines on a map. For example, the thick liquidus lines in the liquidus diagram shown in Figure 3 correspond to valleys on a map. The thick liquidus lines represent the solidification process of the Zn-Al-Mg alloy. That is, when a predetermined position is input to the prediction device 1 as an input value (initial value) of each Zn-Al-Mg content in the liquidus diagram shown in Figure 3, the solidification of the Zn-Al-Mg alloy progresses so that the temperature decreases along the thick liquidus lines at positions close to that position.

[0033] <Input> Information on the plating layer for which corrosion resistance (service life) is to be calculated is provided to the prediction unit 13. Specifically, to confirm the change in corrosion resistance due to differences in the components of the Zn-Al-Mg-based plating layer, the Al and Mg components are provided to the prediction unit 13 in "at%" or "mass%." The total percentage of the Zn, Al, and Mg components is 100%. Therefore, this can be expressed as "(Zn at% , Al at% , Mg at%) = (100 - x - y, x, y)." The atomic weights of Zn, Al, and Mg are Zn = 65.38, Al = 26.98, and Mg = 24.305. Using these, the "mass%" equivalent to "at%" is calculated.

[0034] The density of each of the components Zn, Al, and Mg is also provided to the prediction unit 13. The prediction unit 13 calculates the theoretical density "ρ" based on the density of each of the components Zn, Al, and Mg. Here, the density of Zn is "ρZn = 7.14 g / cm 3 " and the density of Al is "ρAl = 2.7 g / cm 3 " and the density of Mg is "ρMg=1.738g / cm 3 The prediction unit 13 calculates the theoretical density "ρ" based on the density and "mass%" of each component.

[0035] In addition to the components of the plating layer to be predicted, the thickness of the plating layer "L μm" and the deposition weight of the plating layer must be provided to the prediction unit 13. The deposition weight of the plating layer is, for example, 5 to 100 μm and 20 to 630 g / m ２When converting between plating thickness and coating weight, the coating weight is obtained by multiplying the plating thickness by the theoretical density "ρ". Also, the plating thickness [μm] is obtained by dividing the plating coating weight by the specific gravity.

[0036] In the embodiment, a numerical value related to the coating weight is used in the prediction calculation. Here, "coating weight = ρL g / m 2 " is given to the prediction unit 13. For example, in the case of 100% Zn plating, 100 g / m ２ The equivalent plating thickness is 100 ÷ 7.12 ≒ 14 μm.

[0037] The thinner the plating layer, the shorter its service life. If the plating layer is thick, even if a large amount of the plating layer corrodes, the thickness is sufficient to resist that corrosion, so the first period "τ1" is longer and the timing of the start of the second period "τ2" is delayed. In contrast, if the plating layer is thin, the first period "τ1" is shorter and the timing of the start of the second period "τ2" is earlier.

[0038] In addition, for a Zn-Al-Mg-based plating layer with a plating thickness of 20 μm, the second period "τ2" tends to begin when 30% of the entire plating layer has corroded. For a Zn-Al-Mg-based plating layer with a plating thickness of 30 μm, the second period "τ2" tends to begin when 50% of the entire plating layer has corroded. Therefore, the proportion of the plating layer corroded in the first period "τ1" (G = 0.0 to 1.0) must be input into the prediction unit 13 as the proportion of the plating layer (= 1 - G) at the time when the second period "τ2" begins. Assuming that the structure of the plating layer is homogeneous, Equations (1) and (2) hold true based on the proportion "G" and the plating adhesion weight "ρL."

[0039] TM1=ρL G…(1) TM2=ρL (1-G)…(2)

[0040] Here, "TM1" represents the adhesion weight (corrosion weight loss) of the plating layer corroded in the first period "τ1", and "TM2" represents the adhesion weight (corrosion weight loss) of the plating layer corroded in the second period "τ2".

[0041] The corrosion resistance of a plating layer varies depending on the proportion of each phase (each constituent phase) that makes up the plating layer. As the proportion of highly corrosion-resistant phases (phases that corrode slowly) increases, the service life of the plating layer becomes longer. Note that corrosion resistance here refers to the corrosion weight loss (amount of wear) of the plating layer alone, excluding the steel material. It is distinguished from corrosion resistance, which is the effect of the plating layer corroding in place of the steel material to protect it from corrosion (sacrificial corrosion protection).

[0042] When a coating layer contains Zn, Al, and Mg, the phases that make up the coating layer can be classified into six types. These six types (phases 1 through 6) are classified according to the solidification process of Zn, Al, and Mg alloys. Therefore, the ranges (input ranges) of the Zn, Al, and Mg content are limited. For example, the input range for Zn is 25-85 at%; the input range for Al is 10-73 at%; and the input range for Mg is 2-18%.

[0043] The definitions of each phase are shown below. The first phase, "Pure_Al phase," contains trace amounts of Zn (up to 16.5 at%) and Al. The second phase, "Al-Zn(α) phase," is a mixed phase of Al and Zn (Zn content: 16.5 at%). The third phase, "Zn-Al(β) phase," is a mixed phase of Zn and Al (Zn content: 59 at%). The fourth phase, "Pure_Zn(η) phase," is a mixed phase of Zn and Al (Zn content: 98.4-100 at%). The fifth phase, "MgZn2 phase," is a single phase (crystal grains) that forms from the liquid phase simultaneously with or first after the formation of the Pure_Al phase. The size of the "MgZn2 phase" is typically 1 μm or larger. The sixth phase, "ternary eutectic structure," is a phase composed of fine Pure_Al, fine Pure_Zn, and fine MgZn2, and is a mixed structure formed by a ternary eutectic reaction. The overall composition is "Zn-9at%Al-5at%Mg."

[0044] These definitions clarify the atomic structure of each phase, making it possible to theoretically calculate the molecular weight and density of each phase.

[0045] 4 is a diagram showing an example of the 1-molar molecular weight and density of each phase in an embodiment. When the component composition of the plating layer and the molecular weight of each constituent phase are given, it is possible to calculate the weight and number of moles of each phase constituting the plating layer if the volume fraction of each phase is known.

[0046] FIG. 5 is a diagram showing an example of a database of the area fraction of each phase in an embodiment. FIG. 5 shows a portion of the database in table form. The database includes actual measurement results of the correspondence between each Al-Zn-Mg component and the area fraction SP (≒ volume fraction VP) of each phase. Using the database, the component composition of the plating layer, and the molecular weight of each phase, the prediction unit 13 calculates the weight and number of moles of each phase constituting the plating layer.

[0047] To create the database shown in Figure 5, a plating layer similar to the Zn-Al-Mg plating layer shown in Figure 2 was fabricated. The cross-section of this plating layer was observed using an EPMA (Electron Probe Micro Analyzer). The proportion of each phase was calculated so that it was classified into values ​​close to the component values ​​of each phase. Based on the calculated proportion of each phase, the area fraction SP (≒volume fraction VP) of each phase was calculated.

[0048] A hot-dip galvanizing simulator developed in-house was used to prepare the plated steel sheets used in creating the database. This hot-dip galvanizing simulator allows for complete nitrogen substitution throughout the test. This simulator allows a series of plating operations to be carried out in an oxygen-free state (less than 5 ppm), and the temperature during the process can also be monitored.

[0049] The plating bath was made using metals with a purity of 99% or more, and a Zn-Al-Mg alloy was produced by vacuum melting. A 1.2 mm cold-rolled steel sheet (JIS G 3141) for general structural use was used as the base sheet for the plating. To suppress the reactivity of iron (Fe) with the plating layer, a coating of Cr: 0.1 g / m was applied to the plating surface, which had been thoroughly degreased, washed, and pickled. 2 " and "Ni: 0.1 g / m 2 " were deposited in sequence.

[0050] This was used as a plating base sheet. The temperature was raised to 800°C at a rate of 10°C / s, and then 20% H2-N2 gas was sprayed onto the plating base sheet and held for 60 seconds, resulting in surface reduction of the plating base sheet. After cooling the plating base sheet to the plating bath temperature, the plating base sheet was immersed in the plating bath for 1 second. After the plated steel sheet was removed from the plating bath, it was wiped with N2 gas, and the thickness of the plating layer was controlled to be 25 μm in each case. The flow rate of the sprayed N2 gas was controlled so that the time from the melting point to 380°C (the solidification completion temperature) was 20 seconds. The plating bath temperature was set to the melting point (= the liquidus temperature described in Reference 1 above) + 20°C.

[0051] The vapor deposition process suppressed the formation of an intermetallic compound layer containing Fe and Al between the plating bath and the plated steel sheet. This ensured that the plating layer's composition was nearly identical to that of the plating bath, eliminating the influence of Fe. However, because the plating layer was extremely thin, the diffusion of Fe into the plating layer was inhibited when the plated steel sheet was immersed in the plating bath. However, Fe immediately diffused into the plating bath after the plating process. As a result, traces of these (Ni layer, Cr layer) hardly remained in the plating layer, and the interfacial alloy layer was almost nonexistent in the plating layer. This minimized the influence of the base steel on the plating alloy layer.

[0052] The cooling rate of 20 seconds refers to the normal time (20 seconds) from immersion in the plating bath to reaching the top roll. To prevent the plating bath from wrapping around the top roll, the temperature of the plated steel sheet is controlled by gas spraying during the plating solidification process so that the plated steel sheet passes through after it has completely solidified. In addition, 20mm square plated steel sheets are cut from the center of the plated steel sheet. Vertical resin embedding is applied to the plated steel sheet, and the plated steel sheet is then polished.

[0053] EPMA observation was performed on the cross section of the coating layer of the polished coated steel sheet. It was confirmed that the Al-Fe alloy layer and other components remained near the interface, and that the coating layer consisted of coating bath make-up components, as well as the thickness of the coating layer. Scanning electron microscope (SEM) images were obtained within the field of view where the coating layer thickness was confirmed, and EPMA was used to obtain Zn, Al, and Mg composition map images (EPMA map images) at the locations where the SEM images were obtained. From these, the area ratios of each phase were determined in a database.

[0054] Typically, a coating layer solidifies from the surface, and the final solidification portion of the coating process is located near the interface between the base steel and the coating layer. As a result, a structure with a bias in composition is formed in the horizontal cross section of the coating layer. For this reason, the area ratio of each phase is measured from the cross section of the coating layer.

[0055] To confirm the area ratio of each phase, the plating layer was observed under a scanning electron microscope at a magnification of 500, and the measurement of the area ratio of each phase was repeated until the total field of view of the plating layer reached 100,000 μm. A partial image of the plating layer was cut out from the EPMA image, and the cut-out partial image was divided into a 5 μm × 5 μm mesh.

[0056] A phase in which Al and Zn are detected, the Zn content is 16.5 at% or less, and the contents of other elements are 5 at% or less is classified as Phase 1, "Pure_Al phase." A phase in which Al and Zn are detected, and the Zn content is 16.5 to 37.75 at% is classified as Phase 2, "Al-Zn(α) phase." A phase in which Zn and Al are detected, and the Zn content is 37.75 to 59 at% is classified as Phase 3, "Zn-Al(β) phase." A phase in which Zn and Al are detected, and the Zn content is 59 to 98.4 at% is classified as Phase 3, "Zn-Al(β) phase," and Phase 4, "Pure_Zn(η) phase." A phase in which the Mg content is 33.3 at% (±3 at%) and the Zn content is 66.6 at% (±3 at%) is classified as Phase 5, "MgZn2 phase" (single phase). A phase in which Zn, Al, and Mg are detected, and the Zn content is 80 at% or more, the Mg content is 1 to 10 at%, and the Al content is less than 5 to 15 at%, is classified as Phase 6, a "ternary eutectic structure."

[0057] As shown above, in many cases, phases can be classified based on the Zn content. Exceptionally, the interface between the coating layer and the steel material and the resin interface are sometimes classified as "other." Therefore, the area ratio of each phase is confirmed in the ranges other than those classified as "other."

[0058] In the following, the subscripts of letters represent the phase number (nth phase). For example, the area fraction "SP1" represents the area fraction of the first phase. For example, the volume fraction "VP2" represents the volume fraction of the second phase.

[0059] The area ratios of SP1 to SP6 (≒volume ratios VP1 to VP6) can be confirmed in the database. Therefore, the total volume of each phase that makes up the plating layer, "V = V1 + V2 + V3 + V4 + V5 + V6", and the density of the nth phase, "ρ n "The volume ratio "VP n ", the prediction unit 13 calculates the volume "V n " is calculated as in equation (3).

[0060] V n =VP n ÷100÷V … (3)

[0061] Density of nth phase "ρ n " and the volume of the nth phase "V n ", the prediction unit 13 calculates the content (weight) of each phase in the plating layer "m n " is calculated as in equation (4).

[0062] m n =V n ×ρ n …(4)

[0063] The total content (weight) "M" of each phase in the plating layer is expressed by the formula (5).

[0064] M=m1+m2+m3+m4+m5+m6...(5)

[0065] When displaying in "Mass %", the prediction unit 13 calculates the content (weight) of each phase "m n " and the content (weight) of each phase "MS n (expressed as Mass%) as shown in equation (6).

[0066] MS n = m n / M×100 … (6)

[0067] The prediction unit 13 calculates the content (weight) of each phase "MS n " by the total coating weight of the plating layer "ρL" to obtain the weight of the nth phase contained in the plating layer "RM n " is calculated as in equation (7).

[0068] RM n = ρL × MS n …(7)

[0069] The prediction unit 13 calculates the weight of the nth phase "RM n " and molecular weight "N n " and the number of moles of n phase "mol n " may be calculated as in equation (8).

[0070] mol n =RM n / N n …(8)

[0071] The total number of moles "MOL" is expressed as in formula (9).

[0072] MOL=mol1+mol2+mol3+mol4+mol5+mol6...(9)

[0073] The prediction unit 13 calculates the mole percentage of the nth phase, "mol% n " may be calculated as in equation (10).

[0074] mol% n = mol n / MOL...(10)

[0075] In this way, the prediction unit 13 calculates the proportion of each phase in the plating layer. Based on the proportion of each phase, the prediction unit 13 uniformly distributes each phase in a model of the corrosion morphology of the plating layer. The prediction unit 13 calculates the corrosion weight loss in each of the first period "τ1" and the second period "τ2". This makes it possible to determine the corrosion resistance (service life) of the plating layer. It should be noted here that there is an order in which each phase corrodes.

[0076] In exposure tests and accelerated corrosion tests (combined cyclic corrosion tests), each phase corroded in order of decreasing corrosion potential. Specifically, cross-sectional observations of the plating layer in numerous corrosion tests conducted by our company confirmed that the phases corroded in the following order (corrosion order): Phase 3 "Zn-Al (β) phase," Phase 6 "ternary eutectic structure," Phase 5 "MgZn2 phase," Phase 4 "Pure_Zn (η) phase," Phase 2 "Al-Zn (α) phase," and Phase 1 "Pure_Al phase."

[0077] Next, an example of the operation of the prediction device 1 will be described. FIG. 6 is a flowchart showing an example of a process for calculating the adhesion weight of each phase in an embodiment. Since each phase corrodes in the order described above, the proportion of phases with low corrosion potential increases in the first period "τ1". The proportion of phases with high corrosion potential increases in the second period "τ2". The prediction unit 13 calculates the proportion of each phase of the adhesion weight "TM1" of the plating layer corroding in the first period "τ1" and the proportion of each phase of the adhesion weight "TM2" of the plating layer corroding in the second period "τ2" as follows:

[0078] In the example below, "SUM" is a variable that represents the total weight. The total weight "SUM" is assigned a total weight depending on the processing content of each step. The total weight "SUM" is used to determine whether the timing for the end of the first period "τ1" has arrived. In other words, the total weight "SUM" is used to determine whether corrosion has reached the boundary between the plating layer corroded in the first period "τ1" and the plating layer corroded in the second period "τ2". Here, the timing for the end of the first period "τ1" is determined based on the proportion "G" of the plating layer corroded in the first period "τ1".

[0079] The prediction unit 13 initializes the total weight "SUM" (variable) with the adhesion weight of the third phase (step S101). The prediction unit 13 determines whether the adhesion weight "TM1" of the plating layer corroding in the first period - the total weight "SUM" is equal to or less than 0 (step S102).

[0080] If the adhesion weight "TM1" of the plating layer corroding in the first period - the total weight "SUM" is equal to or less than 0 (step S102: YES), the prediction unit 13 calculates the adhesion weight "TM2" of the plating layer corroding in the second period. Here, the adhesion weight "TM2" is calculated as "TM2 = SUM - TM1 + RM6 + RM5 + RM4 + RM2 + RM1" (step S103-1).

[0081] If the adhesion weight "TM1" of the plating layer corroding in the first period - the total weight "SUM" exceeds 0 (step S102: NO), the prediction unit 13 selects one phase for each iteration from step S106 in the order of the fifth phase → the fourth phase → the second phase → the first phase. The prediction unit 13 calculates the adhesion weight "RM n " to the total weight "SUM" (step S104). The prediction unit 13 determines whether the adhesion weight of the first phase "RM1" has been added to the total weight "SUM" (step S105).

[0082] If it is determined that the adhesion weight of the phases other than the first phase has been added to the total weight "SUM" (step S105: YES), the prediction unit 13 determines whether the total weight "SUM" minus the adhesion weight "TM1" of the plating layer corroding in the first period is equal to or less than 0 (step S106). If it is determined that the total weight "SUM" minus the adhesion weight "TM1" of the plating layer corroding in the first period exceeds 0 (step S106: NO), the prediction unit 13 returns the process to step S104.

[0083] If it is determined that the total weight "SUM" minus the adhesion weight "TM1" of the plating layer corroding in the first period is equal to or less than 0 (step S106: YES), the prediction unit 13 returns the process to step S103. Here, if the adhesion weight "RM6" of the sixth phase was added to the total weight "SUM" in step S104, the adhesion weight "TM2" is "TM2 = SUM - TM1 + RM5 + RM4 + RM2 + RM1" (step S103-2). If the adhesion weight "RM5" of the fifth phase was added to the total weight "SUM" in step S104, the adhesion weight "TM2" is "TM2 = SUM - TM1 + RM4 + RM2 + RM1" (step S103-3). If the fourth phase adhesion weight "RM4" is added to the total weight "SUM" in step S104, the adhesion weight "TM2" is calculated as "TM2 = SUM - TM1 + RM2 + RM1" (step S103-4). If the second phase adhesion weight "RM2" is added to the total weight "SUM" in step S104, the adhesion weight "TM2" is calculated as "TM2 = SUM - TM1 + RM1" (step S103-5).

[0084] If it is determined that the first phase adhesion weight "RM1" has been added to the total weight "SUM" (step S105: YES), the prediction unit 13 returns the process to step S103. Here, the adhesion weight "TM2" is "TM2 = SUM - TM1" (step S103-6).

[0085] <Corrosion Rate> The prediction unit 13 calculates the service life of the plating layer based on the adhesion weight "TM1" and corrosion rate "r1" in the first period "τ1" and the adhesion weight "TM2" and corrosion rate "r2" in the second period "τ2". Hereinafter, the corrosion rate of the n-phase in the first period "τ1" will be referred to as "r1 ｎ The corrosion rate of the n-phase in the second period "τ2" is expressed as "r2 ｎ " is written as ".

[0086] In accelerated corrosion tests (combined cyclic corrosion tests), the corrosion rate is the corrosion weight loss per specified cycle. Therefore, the units of the corrosion rates "r1" and "r2" of the plating layer are "g / m 2 In exposure tests, the units of the corrosion rates "r1" and "r2" of the plating layer are "g / m ２ / year (day, month)" etc. The corrosion rates "r1" and "r2" of the plating layer change depending on the corrosive environment of the accelerated corrosion test or exposure test.

[0087] Single-phase metal specimens were prepared to prevent the alloy components of each phase from being rapidly cooled, resulting in uneven composition. These specimens were then subjected to various corrosion tests to determine the corrosion rate of each phase.

[0088] FIG. 7 is a diagram showing an example of the corrosion rate of each phase in the first period in an embodiment. In a cyclic corrosion test (JIS H 8502 JASO M609-91), the corrosion rate is as shown in FIG. 7. In the corrosion rate "r2," the acceleration of corrosion depends on the composition of the steel plate. When ordinary mild steel is used in the test, in the cyclic corrosion test (JIS H 8502 JASO M609-91), the corrosion rate "r2" is often 30 to 50 times the corrosion rate "r1."

[0089] 8 is a flowchart showing an example of a process for calculating "TIME1," the length of a period (first period) during which partial corrosion can be observed on the surface of the coating layer, and "TIME2," the length of a period (second period) after partial corrosion has reached the interface between the coating layer and the steel sheet, in an embodiment. Steps S201 to S206 shown in FIG. 8 are similar to steps S101 to S106 shown in FIG. 6.

[0090] If the adhesion weight "TM1" of the plating layer corroding in the first time period - the total weight "SUM" is equal to or less than 0 (step S202: YES), the prediction unit 13 calculates the adhesion weight "TM2" of the plating layer corroding in the second time period (step S203-1). The prediction unit 13 also calculates the period length "TIME1" of the first time period and the period length "TIME2" of the second time period, where "TIME1 = SUM / r13" and "TIME2 = (SUM - TM1) / r23 + RM6 / r26 + RM5 / r25 + RM4 / r24 + RM2 / r22 + RM1 / r21" (step S207-1).

[0091] If it is determined that the total weight "SUM" minus the deposition weight of the plating layer corroding in the first period "TM1" is equal to or less than 0 (step S206: YES), the prediction unit 13 returns the process to step S203. The prediction unit 13 also calculates the period length "TIME1" of the first period and the period length "TIME2" of the second period. Here, if the deposition weight of the sixth phase "RM6" was added to the total weight "SUM" in step S204, then "TIME1 = RM3 / r13 + (SUM - RM3) / r16" holds. Furthermore, "TIME2 = (SUM - TM1) / r26 + RM5 / r25 + RM4 / r24 + RM2 / r22 + RM1 / r21" holds (step S207-2). In step S204, if the fifth phase adhesion weight "RM5" is added to the total weight "SUM", then "TIME1 = RM3 / r13 + RM6 / r16 + (SUM - RM3 - RM6) / r15". Also, "TIME2 = (SUM - TM1) / r25 + RM4 / r24 + RM2 / r22 + RM1 / r21" (step S207-3). In step S204, if the fourth phase adhesion weight "RM4" is added to the total weight "SUM", then "TIME1 = RM3 / r13 + RM6 / r16 + RM5 / r15 + (SUM - RM3 - RM6 - RM5) / r14". Also, "TIME2 = (SUM - TM1) / r24 + RM2 / r22 + RM1 / r21" (step S207-4). If the second phase adhesion weight "RM2" is added to the total weight "SUM" in step S204, then "TIME1 = RM3 / r13 + RM6 / r16 + RM5 / r15 + RM4 / r14 + (SUM - RM3 - RM6 - RM5 - RM4) / r12" and "TIME2 = (SUM - TM1) / r22 + RM1 / r21" (step S207-5).

[0092] If it is determined that the first phase adhesion weight "RM1" has been added to the total weight "SUM" (step S205: YES), the prediction unit 13 returns the process to step S203. The prediction unit 13 also calculates the period length "TIME1" of the first period and the period length "TIME2" of the second period, where "TIME1 = RM3 / r13 + RM6 / r16 + RM5 / r15 + RM4 / r14 + RM2 / r12 + (SUM - RM3 - RM6 - RM5 - RM4 - RM2) / r11". Furthermore, "TIME2 = (SUM - TM1) / r21" (step S207-6).

[0093] In this way, the prediction unit 13 calculates the period "TIME1" of the first period "τ1" and "TIME2" of the second period "τ2". The prediction unit 13 calculates the corrosion resistance (service life) of the plating layer as "TIME = TIME1 + TIME2".

[0094] As described above, the prediction unit 13 (proportion calculation unit) calculates the proportion of each phase constituting the coating layer in a first period (first proportion) and the proportion of each phase constituting the coating layer in a second period (second proportion) based on the respective contents of multiple components contained in the coating layer. The prediction unit 13 (first period calculation unit) calculates the length of the first period until part of the corrosion of the coating layer reaches the base steel based on the corrosion ranking of each phase, the first proportion of each phase, and the first corrosion rate of each phase. The prediction unit 13 (second period calculation unit) calculates the length of the second period following the first period based on the corrosion ranking of each phase, the second proportion of each phase, and the second corrosion rate of each phase. The second corrosion rate is a rate obtained by correcting the first corrosion rate in accordance with the acceleration of corrosion of the coating layer due to corrosion protection of the base steel. The prediction unit 13 (prediction result calculation unit) calculates the sum of the length of the first period and the length of the second period as a prediction result of the corrosion resistance of the coating layer.

[0095] In this way, the prediction unit 13 calculates the length of the corrosion period (service life) based on the corrosion ranking of each phase, the proportion of each phase, and the corrosion rate of each phase. This makes it possible to improve the accuracy of predicting the corrosion resistance of the plating layer. End users of plated steel sheets can efficiently select materials based on the prediction results. In addition, the time until the adoption of plated steel sheets is approved can be shortened, which can reduce labor costs.

[0096] In this way, the prediction unit 13 may distinguish the corrosion period (service life) into Stage I and Stage II. That is, the prediction unit 13 may calculate the corrosion period in Stage I separately from the corrosion period in Stage II. This makes it possible to further improve the accuracy of predicting the corrosion resistance of the plating layer.

[0097] (Modification) To improve the accuracy of predicting the corrosion resistance (service life) of a coating layer, actual data from a corrosion test may be reflected in the corrosion resistance prediction results. High prediction accuracy can be achieved by adjusting the predicted service life "TIME" to the service life "TIME'" (actual data) obtained from the corrosion test using a correction function "f" (TIME' = f(TIME)).

[0098] Examples of each data point obtained in the corrosion test are shown below.・(Zn, Al, Mg) = (80, 13, 7) at%, plating thickness 20 μm, red rust generation cycles = 210 ・(Zn, Al, Mg) = (80, 17, 8) at%, plating thickness 20 μm, red rust generation cycles = 240 ・(Zn, Al, Mg) = (70, 22, 8) at%, plating thickness 20 μm, red rust generation cycles = 300 ・(Zn, Al, Mg) = (70, 24, 10) at%, plating thickness 20 μm, red rust generation cycles = 300 ・(Zn, Al, Mg) = (52, 34, 13) at%, plating thickness 20 μm, red rust generation cycles = 840 ・(Zn, Al, Mg) = (25, 73, 2) at%, plating thickness 20 μm, red rust generation cycles = 840

[0099] The corrosion test may further increase the number of data points, and the prediction unit 13 may correct the predicted results of the useful life using a technique such as machine learning (e.g., supervised learning) based on many data points.

[0100] Although an embodiment of the present invention has been described above in detail with reference to the drawings, the specific configuration is not limited to this embodiment, and includes designs within the scope of the gist of the present invention.

[0101] 1... Prediction device, 11... Storage device, 12... Storage unit, 13... Prediction unit, 14... Display unit, 101... Plating layer, 102... Steel material, 103... Plating layer

Claims

1. A prediction device comprising a prediction unit that calculates a first ratio in a first period and a second ratio in a second period of each phase constituting the plating layer based on the respective contents of a plurality of components contained in the plating layer, calculates a length of the first period until part of the corrosion of the plating layer reaches the base steel based on the corrosion ranking of each phase, the first ratio of each phase, and a first corrosion rate of each phase, calculates a length of the second period following the first period based on the corrosion ranking of each phase, the second ratio of each phase, and a second corrosion rate of each phase, and calculates a sum of the length of the first period and the length of the second period as a predicted result of the corrosion resistance of the plating layer.

2. A prediction device as described in claim 1, wherein the second corrosion rate is a rate obtained by correcting the first corrosion rate in accordance with the accelerated corrosion of the plating layer due to corrosion protection of the base steel.

3. A prediction method executed by a prediction device, comprising the steps of: calculating a first ratio in a first period and a second ratio in a second period of each phase constituting the plating layer based on the respective contents of a plurality of components contained in the plating layer; calculating a length of the first period until part of the corrosion of the plating layer reaches the base steel based on the corrosion ranking of each phase, the first ratio of each phase and a first corrosion rate of each phase; calculating a length of the second period following the first period based on the corrosion ranking of each phase, the second ratio of each phase and a second corrosion rate of each phase; and calculating a sum of the length of the first period and the length of the second period as a predicted result of the corrosion resistance of the plating layer.

4. A prediction program for causing a computer to execute the steps of: calculating a first ratio in a first period and a second ratio in a second period of each phase constituting the plating layer based on the respective contents of multiple components contained in the plating layer; calculating a length of the first period until part of the corrosion of the plating layer reaches the base steel based on the corrosion ranking of each phase, the first ratio of each phase and a first corrosion rate of each phase; calculating a length of the second period following the first period based on the corrosion ranking of each phase, the second ratio of each phase and a second corrosion rate of each phase; and calculating the sum of the length of the first period and the length of the second period as a predicted result of the corrosion resistance of the plating layer.

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