Method for predicting stress corrosion crack, and computer

Abstract

To efficiently acquire data used for generation of a prediction model.SOLUTION: A method for predicting stress corrosion crack includes: conducting a stress corrosion crack test on a test piece formed of a metal material (S110); acquiring, for the test piece, the correspondence between hardness at each of a plurality of portions different from each other and the test result of the stress corrosion crack test (S120); generating, by using the correspondence, a prediction model for predicting the result related to the occurrence of stress corrosion crack in the metal material on the basis of the composition and hardness of the metal material (S130); and predicting the result related to the occurrence of stress corrosion crack in the metal material by using the prediction model (S140).SELECTED DRAWING: Figure 1

Description

Technical Field

[0001] The present disclosure relates to a method for predicting stress corrosion cracking and a computer.

Background Art

[0002] Tanks for storing fuels and the like are formed of metal materials such as steel materials, aluminum materials, and nickel materials. Such metal materials may develop stress corrosion cracking due to aging deterioration. When stress corrosion cracking occurs in an existing tank, fuels and the like leak from the tank. For this reason, there is a desire to predict the occurrence of stress corrosion cracking in advance.

[0003] As a technique for predicting the deterioration mechanism of metal materials in advance, a prediction model is proposed to be created by machine learning with the composition of metal materials such as carbon steel and stainless steel and the environment to which the metal materials are exposed as input items (explanatory variables) and damage mechanisms such as stress corrosion cracking as teacher materials (objective variables) (for example, Non-Patent Document 1).

[0004] Also, as a stress corrosion cracking test, a technique has been proposed in which a test piece is made of a metal material having the same composition as the plate material constituting the tank, and a stress corrosion cracking test is performed on the test piece under conditions similar to those of the tank (for example, Patent Document 1).

Prior Art Documents

Patent Documents

[0005]

Patent Document 1

Non-Patent Documents

[0006]

Non-Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0007] When creating a prediction model such as that in Non-Patent Document 1, the higher the number of data obtained for creating the prediction model, the higher the prediction accuracy.

[0008] However, a stress corrosion cracking test requires at least about two weeks until test results for one test piece in one environment are obtained. For this reason, there has been a problem that an enormous amount of time is required to create a highly accurate prediction model.

[0009] Therefore, there is a demand for the development of a technology capable of efficiently acquiring data used for creating a prediction model.

[0010] In view of such problems, an object of the present disclosure is to provide a method for predicting stress corrosion cracking and a computer capable of efficiently acquiring data used for creating a prediction model.

Means for Solving the Problems

[0011] In order to solve the above problems, a method for predicting stress corrosion cracking according to one aspect of the present disclosure includes performing a stress corrosion cracking test on a test piece formed of a metal material, obtaining a correspondence relationship between the hardness at each of a plurality of different locations on the test piece and the test results of the stress corrosion cracking test, generating a prediction model for predicting a result regarding the occurrence of stress corrosion cracking of the metal material based on the composition and hardness of the metal material using the correspondence relationship, and predicting a result regarding the occurrence of stress corrosion cracking of the metal material using the prediction model.

[0012] Also, the result regarding the occurrence of stress corrosion cracking may be the presence or absence of the occurrence of stress corrosion cracking.

[0013] Also, the result regarding the occurrence of stress corrosion cracking may be the probability of the occurrence of stress corrosion cracking.

[0014] Further, based on the results regarding the occurrence of stress corrosion cracking of the predicted metal material, it may further include performing stress corrosion cracking countermeasures on the member formed of the metal material.

[0015] Further, the metal material may be a steel material.

[0016] Further, the stress corrosion cracking test may be performed by exposing the test piece to ammonia.

[0017] In order to solve the above problems, a computer according to an aspect of the present disclosure includes a prediction model that predicts results regarding the occurrence of stress corrosion cracking of a metal material, generated using the correspondence between the hardness at each of a plurality of different locations of a test piece formed of the metal material and the test results of a stress corrosion cracking test, based on the composition and hardness of the metal material.

Advantages of the Invention

[0018] According to the present disclosure, it becomes possible to efficiently acquire the data used for creating the prediction model.

Brief Description of the Drawings

[0019]

Figure 1

Figure 2

Figure 3

Figure 4

Figure 5

Figure 6

Figure 7

Figure 8

Figure 9

Figure 10

[0020] Hereinafter, embodiments of the present disclosure will be described in detail with reference to the accompanying drawings. The dimensions, materials, and other specific numerical values shown in the embodiments are merely examples for facilitating understanding, and do not limit the present disclosure unless otherwise specified. In the present specification and drawings, elements having substantially the same functions and configurations are denoted by the same reference numerals, and redundant descriptions are omitted. Further, elements not directly related to the present disclosure are not shown.

[0021] [First Embodiment: Stress Corrosion Cracking Prediction Method] FIG. 1 is a flowchart showing the processing flow of a stress corrosion cracking prediction method according to the first embodiment. As shown in FIG. 1, the stress corrosion cracking prediction method according to the first embodiment includes, for example, a test step S110, an acquisition step S120, a generation step S130, a prediction step S140, and a countermeasure step S150. In the stress corrosion cracking prediction method according to the first embodiment, for example, the result regarding the occurrence of stress corrosion cracking when liquid ammonia is stored in an existing tank such as an LPG tank is predicted. Hereinafter, each step will be described.

[0022] [Test Step S110] In test step S110, a stress corrosion cracking test is performed on the test piece. The stress corrosion cracking (SCC) test is carried out by attaching a jig to the test piece and immersing the test piece and the jig in a liquid while stress is applied (loaded) to the test piece by the jig. The test piece is formed of a metal material. In this embodiment, the metal material is the material used for the existing tank. The metal material is, for example, a steel material (steel product). The steel material is, for example, carbon steel, stainless steel, or nickel steel. The carbon steel is, for example, SLA325A. The Ni steel is, for example, 9% Ni steel.

[0023] In this embodiment, a test piece and a jig are used such that a hardness distribution can be obtained in the test piece. FIG. 2 is a diagram for explaining an example of the test body 100 according to this embodiment. As shown in FIG. 2, the test body 100 according to this embodiment includes a test piece 110 and a jig 120.

[0024] The test piece 110 is, for example, a plate member 112 having a notch 114. The plate member 112 is, for example, rectangular in shape. The plate member 112 has a substantially uniform plate thickness. The plate member 112 is, for example, 30 mm × 20 mm × thickness 2 mm. The notch 114 is, for example, a substantially triangular shape that extends from the center of the plate member 112 toward one end 112a.

[0025] The jig 120 includes a pressing portion 122, a support portion 124, and screws 126a and 126b.

[0026] The pressing portion 122 has a main body 122a and a protrusion 122b. A hole through which the screws 126a and 126b described later can pass is formed in the main body 122a. The main body 122a is brought into contact with the end 112a of the test piece 110.

[0027] The protrusion 122b protrudes from the main body 122a. The protrusion 122b is brought into contact with the notch 114 of the test piece 110. The protrusion 122b is, for example, semi-circular in shape.

[0028] The support portion 124 is formed with screw grooves into which the screws 126a and 126b can be screwed. The support portion 124 is abutted against the end portion 112b of the test piece 110 opposite to the end portion 112a.

[0029] The screws 126a and 126b are inserted into the holes formed in the main body of the pressing portion 122 in a state where the test piece 110 is sandwiched between the pressing portion 122 and the support portion 124, and are screwed into the screw grooves of the support portion 124. When the screws 126a and 126b are screwed into the screw grooves of the support portion 124, the pressing portion 122 and the support portion 124 move in a direction approaching each other, and the notch 114 of the test piece 110 is expanded by the protrusion 122b of the pressing portion 122.

[0030] Thereby, portions where the stress application conditions are different from each other, that is, portions where the strains are different from each other, are formed in the test piece 110. The hardness of the portions where the strains are different is different from each other. Therefore, in a state where stress is applied to the test piece 110 by the jig 120, a plurality of portions having different hardnesses from each other are formed in the test piece 110.

[0031] In the present embodiment, two test bodies 100 are created, which are formed of substantially the same metal material and have substantially the same shape, and to which substantially the same stress is applied to the test piece 110 by the jig 120. Then, one of the first test bodies 100 is immersed in, for example, liquid ammonia, and a stress corrosion cracking test is performed. The other second test body 100 is used in the acquisition step S120. In the stress corrosion cracking test, an oxidizing agent or a reducing agent that is an acceleration factor for stress corrosion cracking may be added to the liquid ammonia. Also, in the stress corrosion cracking test, the environment in which stress corrosion cracking is accelerated may be adjusted by controlling the electrochemical potential.

[0032] [Acquisition Step S120] In the acquisition step S120, the correspondence between the hardness at each of a plurality of different locations on the test piece 110 and the test results of the stress corrosion cracking test is acquired. That is, in the acquisition step S120, the correspondence between the hardness at substantially the same location on the test piece 110 and the test results of the stress corrosion cracking test is acquired at each of a plurality of different locations on the test piece 110.

[0033] In the acquisition step S120, first, the hardness of the surface of the test piece 110 of the second test body 100 is measured. In the present embodiment, the hardness is measured at a predetermined interval (for example, an interval of 0.5 mm) across the entire region 130 on the surface of the test piece 110 of the second test body 100. The region 130 has a size of, for example, 4 mm × 5 mm. In the acquisition step S120, for example, the Vickers hardness is measured using a Vickers hardness tester. For example, when the test piece 110 (initial test piece 110) in a state where no stress is applied is a steel material with HV175 and a maximum strain of 5% is applied by the jig 120, the maximum value of the hardness in the region 130 is, for example, HV235, and the minimum value is, for example, HV175.

[0034] Also, in the acquisition step S120, the results of the stress corrosion cracking test performed on the test piece 110 of the first test body 100 in the test step S110 are acquired. In the present embodiment, the locations where stress corrosion cracking has occurred are acquired in the region 130 on the surface of the test piece 110 of the first test body 100. Note that the region 130 in which the presence or absence of stress corrosion cracking is acquired on the test piece 110 of the first test body 100 and the region 130 in which the hardness is measured on the test piece 110 of the second test body 100 are the same region. In the acquisition step S120, for example, a scanning electron microscope (SEM) is used to acquire the locations where stress corrosion cracking has occurred.

[0035] Then, an XY coordinate system is set in the region 130, and at each coordinate position in the XY coordinate system, the measured hardness is associated with the presence or absence of stress corrosion cracking, and a correspondence relationship between the hardness and the presence or absence of stress corrosion cracking is obtained. In this way, by performing the above test step S110 and acquisition step S120 using one set of test specimens 100, in a metal material of one composition, a plurality (the number of different hardnesses) of correspondence relationships between the hardness and the presence or absence of stress corrosion cracking can be obtained.

[0036] Therefore, for example, by performing the above test step S110 and acquisition step S120 using a plurality of test pieces 110 having different compositions from each other, in each of a plurality of compositions of the metal material, a plurality of correspondence relationships between the hardness and the presence or absence of stress corrosion cracking can be obtained.

[0037] FIG. 3 is a diagram for explaining an example of the correspondence relationship according to the first embodiment. As shown in FIG. 3, in the acquisition step S120, for example, a correspondence relationship in which the composition of the metal material constituting the test piece 110, the hardness at each coordinate position, and the presence or absence of stress corrosion cracking at each coordinate position are associated with each other is obtained. In the example shown in FIG. 3, among the compositions of the metal material, only the chemical components defined by the steel material standard are shown, and the content ratio of iron (Fe) is omitted. The chemical components defined by the steel material standard are, for example, carbon (C), silicon (Si), manganese (Mn), phosphorus (P), sulfur (S), nickel (Ni), and vanadium (V).

[0038] [Generation step S130] In the generation step S130, using the correspondence relationship obtained in the above acquisition step S120, a prediction model for predicting the result regarding the occurrence of stress corrosion cracking of the metal material is generated based on the composition and hardness of the metal material.

[0039] In the generation step S130, for example, using the correspondence relationship obtained in the above acquisition step S120, with the composition and hardness of the metal material as explanatory variables and the presence or absence of stress corrosion cracking as the target variable, machine learning is performed to create a prediction model. As the machine learning algorithm, various known algorithms can be used. The machine learning algorithm is, for example, a support vector machine.

[0040] [Prediction step S140] In the prediction step S140, the prediction model created in the above generation step S130 is used to predict the results regarding the occurrence of stress corrosion cracking in the metal material. In the prediction step S140, for example, the composition and tensile strength of the metal material are obtained from the mill sheet of the steel material constituting the tank. Then, the tensile strength is converted into hardness. Subsequently, the composition of the metal material obtained from the mill sheet and the converted hardness are input into the prediction model to output a prediction of the presence or absence of stress corrosion cracking. In addition, when the hardness is described on the mill sheet, the composition and hardness of the metal material obtained from the mill sheet are input into the prediction model to output a prediction of the presence or absence of stress corrosion cracking.

[0041] Also, when the tank is formed of multiple types of steel plates, the composition and hardness of the metal material are obtained from the corresponding mill sheets for each type of steel plate, and these are input into the prediction model. Then, a prediction of the presence or absence of stress corrosion cracking is output for each type of steel plate.

[0042] [Countermeasure step S150] In the countermeasure step S150, based on the predicted results regarding the occurrence of stress corrosion cracking in the metal material, countermeasures against stress corrosion cracking are taken for the members formed of the metal material. In the countermeasure step S150, for example, for the steel plate predicted to have stress corrosion cracking, countermeasures against stress corrosion cracking are taken. The countermeasures against stress corrosion cracking are, for example, sacrificial corrosion protection with zinc, imparting compressive residual stress by peening, coating by welding with a material having high stress corrosion cracking resistance (overlay), and changing to a material having high stress corrosion cracking resistance.

[0043] Also provided is a computer comprising a prediction model that performs the above test step S110 and acquisition step S120, and predicts a result regarding the occurrence of stress corrosion cracking of a metallic material, generated using the correspondence relationship acquired in the acquisition step S120, based on the composition and hardness of the metallic material. In the acquisition step S120, for example, the computer may acquire the correspondence relationship between the hardness at each of a plurality of different locations of the test piece 110 and the test result of the stress corrosion cracking test in response to an operation input by the user.

[0044] As described above, the stress corrosion cracking prediction method according to the first embodiment includes performing a stress corrosion cracking test on the test piece 110 and acquiring the correspondence relationship between the hardness at each of a plurality of different locations of the test piece 110 and the presence or absence of stress corrosion cracking. That is, the stress corrosion cracking prediction method according to the first embodiment performs a stress corrosion cracking test on the test piece 110 formed of a metallic material of one composition, with a plurality of locations having different hardnesses formed thereon. When performing the stress corrosion cracking test once using a test piece 110 with uniform hardness, only one correspondence relationship between the hardness and the presence or absence of stress corrosion cracking can be obtained. However, in the test step S110 and the acquisition step S120 according to the first embodiment, by performing the stress corrosion cracking test only once, it is possible to acquire the presence or absence of stress corrosion cracking for each of a plurality of different hardnesses in a metallic material of one composition. Therefore, by performing the stress corrosion cracking test only once, a plurality (for example, 70) of correspondence relationships between the hardness and the presence or absence of stress corrosion cracking can be obtained.

[0045] Thereby, the stress corrosion cracking prediction method according to the first embodiment can efficiently acquire the data used for creating the prediction model. Therefore, the stress corrosion cracking prediction method according to the first embodiment can improve the prediction accuracy of the prediction model in a short time.

[0046] Also, in the stress corrosion cracking prediction method according to the first embodiment, a countermeasure step S150 is performed. Thereby, based on the presence or absence of stress corrosion cracking predicted using a high-precision prediction model, it is possible to perform stress corrosion cracking countermeasures on a member formed of a metallic material. Therefore, the stress corrosion cracking prediction method according to the first embodiment can surely perform stress corrosion cracking countermeasures and can also avoid a situation where stress corrosion cracking countermeasures are performed unnecessarily.

[0047] Also, as described above, the stress corrosion cracking prediction method according to the first embodiment uses a test piece 110 formed of a steel material. Thereby, it is possible to accurately predict the results regarding the occurrence of stress corrosion cracking in a steel material in which stress corrosion cracking is likely to occur.

[0048] Also, as described above, in the first embodiment, the test piece 110 is immersed in liquid ammonia to perform a stress corrosion cracking test. Thereby, it is possible to accurately predict the results regarding the occurrence of stress corrosion cracking in a metallic material used for a tank storing liquid ammonia and equipment for transporting liquid ammonia. For example, it becomes possible to accurately predict the results regarding the occurrence of stress corrosion cracking when storing liquid ammonia in an existing tank such as an LPG tank.

[0049] [Second Embodiment: Stress Corrosion Cracking Prediction Method] FIG. 4 is a flowchart showing the processing flow of the stress corrosion cracking prediction method according to the second embodiment. As shown in FIG. 4, the stress corrosion cracking prediction method according to the second embodiment includes, for example, a test step S110, an acquisition step S220, a generation step S230, a prediction step S140, and a countermeasure step S250. Note that since the test step S110 and the prediction step S140 in the first embodiment described above have substantially the same processing, the same reference numerals are given and the description thereof is omitted. In the second embodiment, the acquisition step S220, the generation step S230, and the countermeasure step S250 with different processing will be described.

[0050] [Acquisition Step S220] In the acquisition step S220 according to the second embodiment, the correspondence relationship between the hardness at each of a plurality of different locations on the test piece 110 and the probability of stress corrosion cracking is acquired. In the acquisition step S220 according to the second embodiment, for example, the correspondence relationship between each of a plurality of areas on the test piece 110 having different hardness ranges and the probability of stress corrosion cracking is acquired. That is, in the acquisition step S220, the correspondence relationship between the area of one hardness range and the probability of stress corrosion cracking is acquired for each of a plurality of areas on the test piece 110 having different hardness ranges.

[0051] FIG. 5 is a first process diagram of the acquisition step S220 according to the second embodiment. FIG. 6 is a second process diagram of the acquisition step S220 according to the second embodiment.

[0052] In the acquisition step S220, first, the hardness is measured, for example, at intervals of 0.5 mm over the entire area 130 of the surface of the test piece 110 of the second test body 100. Then, a hardness contour map is created, and the area 130 of the surface of the test piece 110 is divided into a plurality of areas having different hardness ranges.

[0053] When the maximum value of the hardness in the area 130 is HV235 and the minimum value is HV175, for example, the hardness range is varied by HV5 and divided into 12 areas. For example, as shown in FIG. 5, it is divided into area A1, area A2, area A3,..., area 12. Note that the hardness range decreases in the order of area A1, area A2, area A3,..., area 12. Area A1 is an area in the range of HV230 or more and less than HV235. Area A2 is an area in the range of HV225 or more and less than HV230. Area A3 is an area in the range of HV220 or more and less than HV225. Area A12 is an area in the range of HV175 or more and less than HV180. Also, based on the measurement result of the hardness, the area of each area (for example, [mm 2 ) is calculated.

[0054] Then, the results of the stress corrosion cracking test on the test piece 110 of the first test body 100 performed in the above test step S110 are obtained. In the present embodiment, the occurrence point of stress corrosion cracking is specified from the stress corrosion cracking (crack) generated in the surface region 130 of the test piece 110 of the first test body 100. For example, assuming that stress corrosion cracking progresses with the point having the highest hardness among the locations where stress corrosion cracking has occurred as the occurrence point (starting point), the occurrence point and the hardness of the occurrence point are specified for each generated stress corrosion cracking.

[0055] In the example shown in the upper figure of FIG. 6, as a result of the stress corrosion cracking test, stress corrosion cracking occurred from HV230 to HV200, and thus the hardness of the occurrence point P of the stress corrosion cracking is HV230. Further, in the example shown in the lower figure of FIG. 6, as a result of the stress corrosion cracking test, stress corrosion cracking occurred from HV210 to HV190, and thus the hardness of the occurrence point P of the stress corrosion cracking is HV210.

[0056] Then, for each area corresponding to the hardness of the occurrence point P, the number of specified occurrence points P is tabulated. Subsequently, in each area, the number of occurrence points is divided by the area of the area to calculate the occurrence probability of stress corrosion cracking for each area, and the correspondence between each of the plurality of areas divided by a predetermined hardness range and the occurrence probability of stress corrosion cracking is obtained.

[0057] FIG. 7 is a diagram for explaining an example of the correspondence according to the second embodiment. As shown in FIG. 7, in the acquisition step S220, for example, a correspondence in which the composition of the metal material constituting the test piece 110, the hardness range for each area, and the occurrence probability of stress corrosion cracking in the hardness range are associated with each other is obtained.

[0058] [Generation step S230] In the generation step S230 according to the present embodiment, for example, using the correspondence obtained in the above acquisition step S220, machine learning is performed with the composition and hardness range of the metal material as explanatory variables and the occurrence probability of stress corrosion cracking as an objective variable to create a prediction model.

[0059] [Countermeasure step S250] In the countermeasure step S250 according to this embodiment, based on the predicted probability of stress corrosion cracking of the metal material, countermeasures against stress corrosion cracking are taken for the member formed of the metal material. In the countermeasure step S250, for example, countermeasures against stress corrosion cracking are taken for a steel plate predicted to have a probability of stress corrosion cracking occurrence equal to or higher than a predetermined value. The predetermined value is, for example, 50%.

[0060] Also, a computer is provided that includes the above test step S110 and acquisition step S220, and has a prediction model for predicting the result regarding the occurrence of stress corrosion cracking of the metal material generated using the correspondence relationship acquired in the acquisition step S220 based on the composition and hardness of the metal material. In the acquisition step S220, similar to the above acquisition step S120, for example, in response to an operation input by the user, the computer may acquire the correspondence relationship between the hardness at each of a plurality of different locations of the test piece 110 and the test result of the stress corrosion cracking test.

[0061] As described above, the method for predicting stress corrosion cracking according to the second embodiment includes performing a stress corrosion cracking test on the test piece 110 and acquiring the correspondence relationship between the hardness at each of a plurality of different locations of the test piece 110 and the occurrence probability of stress corrosion cracking. That is, similar to the first embodiment, the method for predicting stress corrosion cracking according to the second embodiment performs a stress corrosion cracking test in a state where a plurality of locations having different hardnesses are formed in the test piece 110 formed of a metal material of one composition. When performing a stress corrosion cracking test using a test piece 110 with uniform hardness, in order to obtain the correspondence relationship between the hardness range and the occurrence probability of stress corrosion cracking, it is necessary to perform a plurality of stress corrosion cracking tests using a plurality of test pieces 110 with different hardnesses included in the hardness range. However, in the test step S110 and the acquisition step S220 according to the second embodiment, by performing the stress corrosion cracking test only once, it is possible to obtain the occurrence probability of stress corrosion cracking for each of a plurality of different hardness ranges in a metal material of one composition. Therefore, by performing only one stress corrosion cracking test, a plurality (for example, 12) of correspondence relationships between the hardness range and the occurrence probability of stress corrosion cracking can be obtained.

[0062] As a result, the stress corrosion cracking prediction method according to the second embodiment can efficiently acquire the data used for creating the prediction model. Therefore, the stress corrosion cracking prediction method according to the second embodiment can improve the prediction accuracy of the prediction model in a short time.

[0063] In addition, the stress corrosion cracking prediction method according to the second embodiment performs the countermeasure step S250. Thereby, based on the occurrence probability of stress corrosion cracking predicted using a high-precision prediction model, it is possible to perform stress corrosion cracking countermeasures on a member formed of a metal material. Therefore, the stress corrosion cracking prediction method according to the second embodiment can surely perform stress corrosion cracking countermeasures and can also avoid a situation where stress corrosion cracking countermeasures are performed unnecessarily.

[0064] [Deformation Example of Specimen] FIG. 8 is a diagram for explaining a specimen 200 according to the first modification. As shown in FIG. 8, the specimen 200 according to the first modification includes a test piece 210 and a jig 220. As shown in FIG. 8, the test piece 210 according to the first modification is a plate member made of a metal material whose plate thickness gradually decreases from one end 210a toward the other end 210b. Then, by a pressing mechanism (not shown), the surface 214 of the test piece 210 is pressed against the curved surface 222 of the jig 220 to form a plurality of locations on the surface 212 of the test piece 210 where the stress application conditions are different from each other. The surface 212 is the surface for obtaining the test result of the stress corrosion cracking test, that is, the surface for measuring the hardness. The surface 214 of the test piece 210 is the surface on the side opposite to the direction in which the test piece 210 of the surface 212 is pressed against the jig 220.

[0065] FIG. 9 is a diagram for explaining a test piece 300 according to a second modification. In FIG. 9, the upper diagram shows a side view of a test piece 310 and a jig 320. In FIG. 9, the lower diagram shows a plan view of the test piece 310 and the jig 320. As shown in FIG. 9, the test piece 300 according to the second modification is formed by constraint welding a test piece 310 and a jig 320. As shown in FIG. 9, before being constraint welded, the test piece 310 according to the second modification is a plate member of a metal material having a rectangular shape and a substantially uniform plate thickness. Further, the jig 320 is a member of a metal material having an inclined surface 322. Then, by constraint welding one end surface 312 of the test piece 310 and the inclined surface 322 of the jig 320, the test piece 300 according to the second modification is formed. Thereby, a plurality of locations where the stress application conditions are different from each other are formed in the test piece 310 of the test piece 300.

[0066] FIG. 10 is a diagram for explaining a test piece 400 according to a third modification. The upper left diagram in FIG. 10 shows a plan view of a test piece 410. The upper right diagram in FIG. 10 shows a side view of the test piece 410 as viewed from the end portion 410d side. The lower diagram in FIG. 10 shows a side view of the test piece 410 as viewed from the end portion 410a side. As shown in FIG. 10, the test piece 400 according to the third modification includes a test piece 410 and a jig (not shown). As shown in FIG. 10, the test piece 410 according to the third modification has a rectangular shape. The test piece 410 is a plate member of a metal material whose plate thickness gradually decreases from one end portion 410a toward the other end portion 410b. Further, the end portion 410c of the test piece 410 has an inclined surface. Then, by a jig (not shown), the end portion 410c of the test piece 410 and the end portion 410d on the opposite side of the end portion 410c are pulled in a direction away from each other, so that a plurality of locations where the stress application conditions are different from each other are formed in the test piece 410 of the test piece 400.

[0067] The embodiments have been described above with reference to the accompanying drawings. Needless to say, the present disclosure is not limited to the above embodiments. It is obvious that those skilled in the art can conceive of various modifications or variations within the scope described in the claims, and it is naturally understood that those also belong to the technical scope of the present disclosure.

[0068] For example, in the above first and second embodiments, a case was cited in which a set of test specimens 100 was used, a stress corrosion cracking test was performed on the first test specimen 100, and hardness measurement was performed on the second test specimen 100. However, a stress corrosion cracking test and hardness measurement may be performed on a single test specimen 100. In this case, first, the hardness of the test specimen 100 may be measured, and after measuring the hardness, a stress corrosion cracking test may be performed.

[0069] Also, in the above first and second embodiments, cases where the countermeasure steps S150 and S250 are performed were cited. However, the countermeasure steps S150 and S250 are not essential steps.

[0070] Also, in the above first and second embodiments, a steel material was cited as an example of the metal material. However, there is no limitation on the type of main metal constituting the metal material. For example, the metal material may be an aluminum material such as an aluminum alloy, a nickel material such as a nickel alloy, or the like.

[0071] Also, in the test step S110 of the above first embodiment, a case was cited in which the test piece 110 was immersed in liquid ammonia and a stress corrosion cracking test was performed. However, in the test step S110, it is sufficient that the test piece 110 is exposed to the environment in which the member to be predicted is exposed and a stress corrosion cracking test is performed. For example, the test piece 110 may be exposed to a gaseous ammonia environment, a neutral chloride aqueous solution (e.g., seawater), high-temperature high-purity water (high-pressure water at about 300°C), or humid air, and a stress corrosion cracking test may be performed.

[0072] The present disclosure can contribute, for example, to Goal 12 of the Sustainable Development Goals (SDGs), "Ensure sustainable consumption and production patterns."

Explanation of symbols

[0073] S110 Test process S120 Acquisition process S130 Generation process S140 Prediction process S150 Countermeasure process S220 Acquisition process S250 Countermeasure process 110 Test piece 210 Test piece 310 Test piece 410 Test piece

Claims

1. Performing a stress corrosion cracking test on a test piece formed of a metallic material, Obtaining the correspondence between the hardness at each of a plurality of different locations on the test piece and the test results of the stress corrosion cracking test, Generating a prediction model for predicting the results related to the occurrence of stress corrosion cracking of the metallic material based on the composition and hardness of the metallic material, using the correspondence, Predicting the results related to the occurrence of stress corrosion cracking of the metallic material using the prediction model, A method for predicting stress corrosion cracking, comprising the above steps.

2. The method for predicting stress corrosion cracking according to claim 1, wherein the results related to the occurrence of stress corrosion cracking are the presence or absence of stress corrosion cracking.

3. The method for predicting stress corrosion cracking according to claim 1, wherein the results related to the occurrence of stress corrosion cracking are the probability of stress corrosion cracking.

4. The method for predicting stress corrosion cracking according to claim 1, further comprising taking measures against stress corrosion cracking for a member formed of the metallic material based on the predicted results related to the occurrence of stress corrosion cracking of the metallic material.

5. The method for predicting stress corrosion cracking according to claim 1, wherein the metallic material is a steel material.

6. The method for predicting stress corrosion cracking according to claim 1, wherein the stress corrosion cracking test is performed by exposing the test piece to ammonia.

7. A computer comprising a prediction model for predicting the results related to the occurrence of stress corrosion cracking of a metallic material, generated using the correspondence between the hardness at each of a plurality of different locations on a test piece formed of the metallic material and the test results of a stress corrosion cracking test, based on the composition and hardness of the metallic material.

Images