JP2017083324A - Method for predicting remaining life of metal material - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a method for predicting the remaining life of a metal material, the method enabling the remaining life of the metal material to be appropriately predicted according to the level of deterioration of the metal material.SOLUTION: The remaining life of a metal material (test material) is predicted by the following steps (A)-(C) on the basis of a plurality of kinds of structure parameters showing a state of a micro structure. (A) a metal material corresponding to a metal material used in a high temperature environment is used as a reference material and a relationship between a structure parameter and remaining life information is obtained on the reference material for every kind of the structure parameters; (B) a metal material corresponding to a metal material used in a high temperature environment is used as a test material and one kind of structure parameter selected from the plurality of structure parameters is obtained on the test material; and (C) the remaining life of the test material is predicted using a relationship between: the one kind of structure parameters obtained in the step (B) and structure parameter obtained in the step (A); and the remaining life information.SELECTED DRAWING: None

Description

  The present invention relates to a method for predicting the remaining life or lifetime consumption rate of a metal material.

  Conventionally, a method for predicting the remaining life of a metal material (such as a steel pipe) used in a high-temperature environment in a thermal power plant or the like has been proposed.

  For example, Japanese Unexamined Patent Application Publication No. 2004-3922 (Patent Document 1) discloses a method for predicting the remaining life of a metal material based on a local crystal orientation shift. Specifically, in the method of Patent Document 1, the remaining life of the metal material is estimated by measuring the KAM value of a predetermined region in the crystal grain. The KAM value is a value indicating a minute rotation within the crystal grain, and is a value related to the strain amount within the crystal grain. The KAM value can be measured as follows using, for example, electron beam backscatter diffraction (EBSD). First, an arbitrary analysis section is selected from a plurality of analysis sections (pixels) divided into crystal grains. Then, an average value of crystal orientation differences between the selected analysis section and a plurality of analysis sections around the analysis section is calculated as a KAM value.

  Japanese Patent Laid-Open No. 63-228062 (Patent Document 2) discloses a method for predicting the remaining life of a metal material based on the shape of crystal grains. Specifically, in the method of Patent Document 2, the amount of change in crystal grain shape is measured based on the major axis of the crystal grain, the width of the crystal grain, the circularity of the crystal grain, etc., and the remaining life of the metal material is estimated. doing.

JP 2004-3922 A Japanese Unexamined Patent Publication No. 63-228062

  However, as a result of various studies by the present inventors, it has been found that there are cases where the above-described method cannot appropriately predict the remaining life of the metal material.

  That is, the state of the microstructure of the metal material changes with the deterioration of the metal material, but the amount of change varies depending on the degree of deterioration of the metal material. Specifically, for example, the dislocation density can be cited as an element indicating the state of the microstructure, but the increase amount of the dislocation density is large in a period where the creep deformation amount is small (for example, transition creep region), but creep deformation. It becomes smaller during the period when the amount becomes larger (for example, the acceleration creep region).

  For this reason, in the methods of Patent Documents 1 and 2 for predicting the remaining life based on one piece of information (the amount of strain in crystal grains or the shape of crystal grains) indicating the state of the microstructure, depending on the degree of deterioration of the metal material In some cases, the remaining life cannot be properly predicted.

  The present invention has been made to solve such a problem, and the remaining life of the metal material can be appropriately predicted according to the degree of deterioration of the metal material. An object is to provide a prediction method.

The remaining life prediction method according to an embodiment of the present invention is a remaining life prediction method for predicting the remaining life of a metal material used in a high temperature environment based on a plurality of types of structure parameters related to the microstructure state. The following steps (A) to (C) are provided.
(A) Using a metal material corresponding to a metal material used in the high temperature environment as a reference material, for the reference material, for each type of the structure parameter, the relationship between the structure parameter and the remaining life information regarding the remaining life (B) Obtaining one type of tissue parameter selected from the plurality of types of tissue parameters for the test material using the metal material used in the high temperature environment as a test material (C) A step of predicting the remaining life of the test material from the relationship between the one kind of structure parameter obtained in the step (B) and the structure parameter obtained in the step (A) and the remaining life information.

  The plurality of types of structure parameters may include dislocation density.

  The plurality of types of texture parameters may further include intragranular strain.

  The plurality of types of texture parameters may further include grain boundary strain.

  In the step (B), when the dislocation density of the test material is less than or equal to a predetermined threshold value, the dislocation density is selected as the one type of structural parameter, and the dislocation density of the test material exceeds the predetermined threshold value. In such a case, a texture parameter other than the dislocation density may be selected as the one kind of texture parameter.

The step (A) includes the following steps (a1) and (a2):
The relationship between the structure parameter obtained in the step (A) and the remaining life information is the relationship between the structure parameter obtained in the step (a1) and the creep strain amount, and the step (a2) below. Including the relationship between the amount of creep strain obtained and the remaining life,
The step (C) may include the following steps (c1) and (c2).
(A1) A step of obtaining a relationship between a structure parameter and a creep strain amount for each of the plurality of types of structure parameters for the reference material (a2) A step of obtaining a relationship between a creep strain amount and a remaining life for the reference material ( c1) From the relationship between the one type of structural parameter obtained in the step (B) and the one type of structural parameter obtained in the step (a1) and the amount of creep strain, the amount of creep strain of the test material is determined. Step (c2) Obtaining the remaining life of the test material from the relationship between the creep strain amount obtained in the step (c1) and the creep strain amount obtained in the step (a2) and the remaining life. Step to predict

The plurality of structural parameters include dislocation density,
When the dislocation density is selected as the one type of structure parameter in the step (B), the amount of creep strain obtained in the step (c1) is the same as the structure parameter other than the dislocation density in the step (B). It may be smaller than the amount of creep strain obtained in the step (c1) when selected as the one type of structure parameter.

  In the step (A), a relationship between the tissue parameter and the remaining life may be obtained as a relationship between the tissue parameter and the remaining life information.

  According to the present invention, it is possible to appropriately predict the remaining life of a metal material without being affected by the degree of deterioration of the metal material.

FIG. 1 is a master curve showing the relationship between the dislocation density and the amount of creep strain. FIG. 2 is a master curve showing the relationship between the β-direction intensity deviation and the creep strain amount. FIG. 3 is a master curve showing the relationship between the GROD value and the creep strain amount. FIG. 4 is a master curve showing the relationship between the life consumption rate and the amount of creep strain. FIG. 5 is a master curve showing the relationship between residual stress and creep strain. FIG. 6 is a diagram illustrating an example of the reference Gaussian function and the multiplication Gaussian function.

(Outline of remaining life prediction method)
A remaining life prediction method according to an embodiment of the present invention (hereinafter simply referred to as a prediction method) is suitably used for predicting the remaining life of a material used in a high temperature environment. The remaining life predicted in the present invention includes a life consumption rate (lifetime ratio) described later. In the present embodiment, the high temperature environment means an environment of 500 ° C. or higher, which is a use temperature of a normal thermal power boiler or petroleum refining equipment, for example.

  The prediction method according to the present embodiment can be used, for example, when predicting the remaining life of a metal material used in a power plant or the like under a high temperature and high pressure (for example, 20 MPa or more) environment. Specifically, the prediction method according to the present embodiment can be used, for example, when predicting the remaining life of a steel pipe for boilers that has been extracted from a power plant.

  In the present embodiment, the remaining life of the metal material is predicted based on a plurality of types of parameters (hereinafter referred to as “structural parameters”) relating to the microstructure state to be described later. Hereinafter, a metal material for which the remaining life is predicted is referred to as a test material. In this embodiment, a metal material corresponding to the test material is used as the reference material. The reference material is, for example, a metal material having a microstructure similar to that of the test material. In the following, as an example of the prediction method, a case where a Ni-based alloy is used as both the test material and the reference material will be described.

The prediction method according to the present embodiment includes, for example, the following steps A to C.
Step A: For the reference material, for each type of structure parameter, a relationship between the structure parameter and information on the remaining life (hereinafter referred to as remaining life information) is obtained.
Step B: For a test material, one kind of structure parameter selected from a plurality of kinds of structure parameters is obtained.
Step C: The remaining life of the test material is predicted from the relationship between the one type of structural parameter obtained in Step B and the structural parameter obtained in Step A and the remaining life information.
The steps A to C will be specifically described below.

(Step A: Processing for reference material)
In the present embodiment, step A includes the following steps a1 and a2. The relationship between the structure parameter obtained in step A and the remaining life information includes the relationship between the structure parameter obtained in step a1 below and the creep strain amount, and the creep strain amount and remaining life obtained in step a2 below. The relationship is included.
Step a1: For the reference material, a relationship between the structure parameter and the creep strain amount is obtained for each of a plurality of kinds of structure parameters.
Step a2: For the reference material, a relationship between the amount of creep strain and the remaining life is obtained.

  Each of the above relationships in steps a1 and a2 is experimentally obtained using a plurality of reference materials. The experiment is performed, for example, in an environment simulating an environment where the test material is used.

  In the present embodiment, the plurality of types of structure parameters include dislocation density, intragranular strain, and grain boundary strain. In this embodiment, the intragranular strain means uniform strain and nonuniform strain applied to the entire grain by an external force, and the grain boundary strain is a small crystal orientation generated in the vicinity of the grain boundary by the external force. Means rotation. In the present embodiment, a β-direction intensity deviation described later is measured as a value (measurement parameter) representing intragranular strain, and a GROD (Grain Reference Orientation Deviation) value is measured as a value (measurement parameter) representing grain boundary strain. .

  In the present embodiment, in step a1, the master curve indicating the relationship between the dislocation density and the creep strain amount as the relationship between the structure parameter and the creep strain amount, as shown in FIGS. In this embodiment, a master curve indicating the relationship between the β-direction intensity deviation) and the creep strain amount, and a master curve indicating the relationship between the grain boundary strain (GROD value in the present embodiment) and the creep strain amount are created. . In step a2, the master curve indicating the relationship between the life consumption rate and the creep strain amount is created as shown in FIG. These master curves may be created based on data from past experiments, etc., and when predicting the remaining life of a test material, new experiments are performed and data are collected and created based on that data. Also good. The master curve can be obtained using, for example, the least square method based on experimental data.

In the graphs (master curves) in FIGS. 1 to 4, the horizontal axis indicates the amount of creep strain on a logarithmic scale. In the graph of FIG. 1, the vertical axis indicates the dislocation density (m ⁻² ) on a logarithmic scale. In the graph shown in FIG. 4, the life consumption rate is a ratio of the test elapsed time T to the time Tr until the reference material reaches the creep rupture in the creep test, and is a value obtained by T / Tr.

  Since the dislocation density can be obtained by a known method, a detailed description thereof is omitted. For example, the dislocation density can be calculated by using a half width of a diffraction profile obtained by an X-ray diffraction method. Specifically, the dislocation density can be calculated by, for example, a method using the Williams equation or a method using the Modified Warren-Abelbach equation and the Modified willamson-Hall equation. The dislocation density may be measured, for example, by observation using a transmission electron microscope (TEM), may be calculated using a positron annihilation method (a method for obtaining a dislocation density from a positron annihilation lifetime), and Vickers The hardness (Hv) may be measured and calculated using the Bailey-Hirsch equation based on the measured Hv.

  The β direction intensity deviation can be calculated using a two-dimensional X-ray diffraction pattern. Hereinafter, the β direction intensity deviation will be briefly described. The β direction means the ring direction of the Debye-Scherrer ring, and the β-direction intensity deviation indicates the state of the two-dimensional X-ray diffraction pattern (more specifically, the Debye-Scherrer ring state). In the present embodiment, the standard deviation of the diffraction intensity distribution in the β direction of the two-dimensional X-ray diffraction pattern is obtained as the β direction intensity deviation. When the two-dimensional X-ray diffraction pattern includes a background, the β-direction intensity deviation can be obtained after removing the background from the diffraction pattern. For example, the standard deviation of the residual between the approximate curve of the diffraction intensity distribution in the β direction and the background approximate curve may be obtained as the β direction intensity deviation. The two-dimensional X-ray diffraction pattern changes from a spot-shaped pattern to a ring-shaped pattern as the creep strain increases. That is, Debye-Scherrer ring appears as the creep strain increases. When the two-dimensional X-ray diffraction pattern is a ring-shaped pattern (when the amount of creep strain is large), the intensity distribution in the β direction (ring direction) of the two-dimensional X-ray diffraction pattern is uniform. In this case, the β direction intensity deviation becomes small. On the other hand, when the two-dimensional X-ray diffraction pattern is a spot-like pattern (when the amount of creep strain is small), the intensity distribution in the β direction (ring direction) of the two-dimensional X-ray diffraction pattern becomes non-uniform. In this case, the β direction intensity deviation becomes large.

  Since the GROD value can be obtained by a known method and will not be described in detail, for example, it can be obtained by using electron beam backscatter diffraction (EBSD).

  As shown in FIG. 1, it can be seen that the dislocation density is greatly increased in the initial stage of creep deformation. Further, as shown in FIG. 2, it can be seen that the β-direction intensity deviation is greatly reduced in the middle stage of creep deformation. Further, as shown in FIG. 3, it can be seen that the GROD value is greatly increased in the later stage of creep deformation. That is, the amount of change in dislocation density is large in the early stage of creep deformation, the amount of intragranular strain is large in the middle stage of creep deformation, and the grain boundary is in the later stage of creep deformation. The amount of distortion change is large.

(Step B: Treatment for test material)
In Step B, one kind of structure parameter selected from a plurality of kinds of structure parameters (dislocation density, intragranular strain and intergranular strain) relating to the microstructure state is obtained for the test material. In this embodiment, when intragranular strain is selected as the one type of structural parameter, the β-direction intensity deviation is obtained as a value representing the intragranular strain, and grain boundary strain is selected as the one type of structural parameter. In such a case, a GROD value is obtained as a value representing the grain boundary strain. Hereinafter, an example of a method for selecting tissue parameters in Step B will be described together with a detailed description of Step C.

(Step C: Processing related to prediction of remaining life of test material)
In the present embodiment, step C includes the following steps c1 and c2.
Step c1: The creep strain amount of the test material is obtained from one type of structural parameter obtained in Step B and the relationship between the structural parameter obtained in Step a1 and the creep strain amount.
Step c2: The remaining life of the test material is predicted from the amount of creep strain of the test material obtained in Step c1 and the relationship between the amount of creep strain obtained in Step a2 and the remaining life.

  As described above, in step C, the creep strain amount of the test material is obtained based on the structure parameter selected in step B (step c1), and the remaining life of the test material is predicted based on the obtained creep strain amount (step c1). Step c2). Here, as shown in FIGS. 1 to 3, the amount of change in the microstructure parameters (dislocation density, intragranular strain, intergranular strain) of the microstructure varies depending on the degree of progress of creep deformation.

  Therefore, in the present embodiment, at the initial stage of creep deformation where the amount of change in the dislocation density is large, the dislocation density is obtained as the structure parameter of the test material (step B). Then, the creep strain amount of the test material is obtained based on the dislocation density of the test material obtained in Step B and the master curve shown in FIG. 1 (Step c1). Thereafter, the remaining life of the test material is obtained based on the creep strain amount obtained in step c1 and the master curve shown in FIG. 4 (step c2). In step c2, the life consumption rate obtained from the master curve shown in FIG. 4 may be used as the remaining life of the test material, and a value obtained by subtracting the life consumption rate from 1 may be used as the remaining life of the test material. .

  In Step B, for example, when the dislocation density of the test material is a predetermined threshold value (hereinafter referred to as the first threshold value) or less, the dislocation density is selected as the structure parameter of the test material. The first threshold value for the dislocation density is appropriately set according to the characteristics of the test material. In the present embodiment, the first threshold value is set, for example, to the dislocation density of the reference material when the creep strain amount of the reference material is 0.05. The dislocation density when the creep strain amount of the reference material is 0.05 can be obtained from, for example, the master curve shown in FIG.

  Further, in the middle stage of creep deformation in which the amount of change in intragranular strain becomes large, intragranular strain is obtained as a structural parameter of the test material (step B). In the present embodiment, the β-direction intensity deviation is obtained as a value representing intragranular strain. Then, the amount of creep strain of the test material is obtained based on the intragranular strain (β direction strength deviation) of the test material obtained in step B and the master curve shown in FIG. 2 (step c1). Thereafter, the remaining life of the test material is obtained based on the creep strain amount obtained in step c1 and the master curve shown in FIG. 4 (step c2).

  In Step B, for example, when the dislocation density and intragranular strain of the test material satisfy predetermined conditions, intragranular strain is selected as the structure parameter of the test material. In this embodiment, when the dislocation density of the test material exceeds the first threshold value and the β-direction intensity deviation is equal to or greater than a predetermined threshold value (hereinafter referred to as the second threshold value), intragranular strain is used as the structure parameter of the test material. Select. The second threshold value for the β direction strength deviation is appropriately set according to the characteristics of the test material. In the present embodiment, for example, the second threshold value is set to the β direction strength deviation of the reference material when the creep strain amount is 0.1. The β-direction strength deviation when the creep strain amount of the reference material is 0.1 can be obtained from, for example, the master curve shown in FIG.

  Further, at the later stage of creep deformation in which the amount of change in grain boundary strain becomes large, grain boundary strain is obtained as a structural parameter of the test material (step B). In the present embodiment, a GROD value is obtained as a value representing the grain boundary strain. Then, the amount of creep strain of the test material is obtained based on the grain boundary strain (GROD value) of the test material obtained in step B and the master curve shown in FIG. 3 (step c1). Thereafter, the remaining life of the test material is obtained based on the creep strain amount obtained in step c1 and the master curve shown in FIG. 4 (step c2).

  In Step B, for example, when the intragranular strain of the test material satisfies a predetermined condition, the grain boundary strain is selected as the structure parameter of the test material. In this embodiment, when the β-direction strength deviation of the test material is less than the second threshold value, the grain boundary strain is selected as the structure parameter of the test material.

  When the remaining life of the test material is predicted by the prediction method according to the present embodiment, for example, when the dislocation density of the test material is first measured and the dislocation density is equal to or higher than the first threshold, You may measure a beta direction intensity | strength deviation. Further, for example, first, the β direction strength deviation of the test material is measured, and when the β direction strength deviation is less than the second threshold value, the GROD value of the test material is measured, and the β direction strength deviation is a predetermined threshold value. In the case of (third threshold value) or more, the dislocation density of the test material may be measured. Alternatively, the GROD value of the test material may be measured first, and if the GROD value is less than or equal to a predetermined threshold value (fourth threshold value), the β-direction strength deviation of the test material may be measured. In addition, said 3rd threshold value and said 4th threshold value are suitably set according to the characteristic etc. of a test material. As described above, in the prediction method according to the present embodiment, a plurality of types of structure parameters (dislocation density, intragranular strain (β-direction strength deviation in the present embodiment), and grain boundary strain (GROD value in the present embodiment). ) May be determined first. Then, when the tissue parameter obtained first does not satisfy the predetermined condition, another tissue parameter is obtained, and when the tissue parameter does not satisfy the predetermined condition, further other tissue parameter is obtained, What is necessary is just to obtain the amount of creep strain.

(Operational effect of this embodiment)
As described above, in the prediction method according to the present embodiment, the amount of creep strain is obtained based on the dislocation density in the initial stage of creep deformation where the amount of change in the dislocation density is large. Further, in the middle stage of creep deformation where the amount of change in intragranular strain is large, the amount of creep strain is obtained based on the intragranular strain. Further, in the later stage of creep deformation in which the amount of change in grain boundary strain is large, the amount of creep strain is determined based on the grain boundary strain.

  More specifically, when the dislocation density satisfies a predetermined first condition (in this embodiment, the dislocation density of the test material is not more than the first threshold value), the creep strain amount is obtained based on the dislocation density. Further, when the dislocation density does not satisfy the first condition and the intragranular strain satisfies a predetermined second condition (in this embodiment, the β-direction strength deviation of the test material is equal to or greater than the second threshold). The amount of creep strain is obtained based on the intragranular strain. Further, when the dislocation density and the intragranular strain do not satisfy the first condition and the second condition, the amount of creep strain is obtained based on the grain boundary strain.

  As described above, according to the prediction method according to the present embodiment, the amount of creep strain of the test material is appropriately determined according to the degree of progress of creep deformation of the test material (that is, the degree of deterioration of the test material). Can do. Specifically, the amount of creep strain of the test material can be obtained based on an appropriate structure parameter selected from among a plurality of kinds of structure parameters (dislocation density, intragranular strain, intergranular strain). Thereby, the amount of creep strain of the test material can be predicted with high accuracy. As a result, the remaining life of the test material can be predicted with high accuracy.

(Other embodiments)
In the above-described embodiment, the case where the dislocation density is obtained as the texture parameter has been described, but elastic strain energy or positron annihilation lifetime may be obtained as a value (measurement parameter) representing the dislocation density instead of the dislocation density. Since the elastic strain energy and the positron annihilation lifetime can be obtained by a known measurement method, description of the measurement method is omitted.

In the above-described embodiment, the case where the β-direction intensity deviation is obtained as the value (measurement parameter) representing intragranular strain has been described. However, the residual stress may be obtained as a value representing intragranular strain. The residual stress can be calculated using, for example, a known technique such as the sin ² ψ method or a two-dimensional X-ray diffraction pattern.

  In the above-described embodiment, the case where the GROD value is obtained as a value (measurement parameter) representing the grain boundary strain has been described, but a KAM (Kernel Average Misorientation) value may be obtained. The KAM value can be obtained using, for example, EBSD. Further, a local lattice constant in the vicinity of the grain boundary may be obtained as a value representing the grain boundary distortion. The local lattice constant can be obtained by using, for example, a convergent electron diffraction (CBED) method.

  Further, in the above-described embodiment, the case where the remaining life of the test material is predicted based on the three types of structure parameters has been described, but the remaining life may be predicted based on the two types of structure parameters. The remaining life may be predicted based on the tissue parameters. For example, the remaining life of the test material may be predicted using two types of structure parameters, dislocation density and intragranular strain. Note that when the remaining life of the test material is predicted from two types of structural parameters such as dislocation density and intragranular strain, for example, the residual stress may be measured as a value representing intragranular strain. In this case, in addition to the master curves shown in FIGS. 1 and 4, a master curve showing the relationship between the residual stress and the creep strain amount as shown in FIG. 5 is created. Using this master curve, the amount of creep strain and the life consumption rate (remaining life) can be predicted as in the above-described embodiment. In this case as well, as in the case of using the β-direction intensity deviation and the GROD value, the threshold for the residual stress is appropriately set. Although detailed description is omitted, even when the above-described elastic strain energy, positron annihilation lifetime, KAM value, or the like is used as the tissue parameter, a threshold value for each value is appropriately set.

  In the above-described embodiment, the case where Step A has Steps a1 and a2 and Step C has Steps c1 and c2 has been described. However, the processing in Step A and Step C is not limited to the above example. Specifically, in the above-described embodiment, in step A, the relationship between the texture parameter and the creep strain amount (step a1) and the relationship between the creep strain amount and the remaining life (step a2) are obtained. However, instead of the relationship obtained in steps a1 and a2, the relationship between the tissue parameter and the remaining life may be obtained in step A. In this case, in Step C, the remaining life of the test material can be predicted based on the structure parameter obtained in Step B and the relationship obtained in Step A.

  Specifically, for example, in Step A, for the reference material, a master curve indicating the relationship between the dislocation density and the remaining life, a master curve indicating the relationship between the intragranular strain (for example, β direction strength deviation) and the remaining life, In addition, a master curve indicating the relationship between grain boundary strain (for example, GROD value) and remaining life may be obtained. In Step C, the remaining life of the test material may be predicted based on the dislocation density, intragranular strain or grain boundary strain obtained in Step B, and the master curve obtained in Step A.

  In the above-described embodiment, each structural parameter of the reference material and the test material is obtained by any one method, and the life consumption rate of the test material is predicted based on the obtained structural parameter. However, one type of tissue parameter may be obtained by a plurality of different methods. Specifically, for example, a plurality of methods (such as an X-ray diffraction method and a positron annihilation method) can be considered as a method for obtaining the dislocation density. In the above-described embodiment, the dislocation density is obtained using one method arbitrarily selected from the plurality of methods. However, for example, in the transition creep region, the remaining life of the test material may be predicted using both the dislocation density obtained by the X-ray diffraction method and the dislocation density obtained by the positron annihilation method. Similarly, for example, as a value representing intragranular strain, a plurality of values (β-direction strength deviation, residual stress, etc.) obtained by different methods can be considered. In the above-described embodiment, a value arbitrarily selected from the plurality of values is used as a value representing intragranular strain. However, for example, in the first half of the accelerated creep region, the remaining life of the test material may be predicted using both the β-direction strength deviation and the residual stress as values representing intragranular strain. In these cases, the prediction accuracy of the remaining life of the test material can be improved.

  Hereinafter, a case where one type of tissue parameter is obtained by a plurality of different methods will be described. Below, the case where a dislocation density is calculated | required by two methods, an X-ray diffraction method and a positron annihilation method, is demonstrated. In the first prediction method and the second prediction method described below, the life consumption rate is obtained as the remaining life of the test material. In the prediction method described below, a reference material and a test material defined in the same manner as in the above embodiment can be used.

[First prediction method]
In the prediction method according to the present embodiment, as will be described later, a Gaussian function (hereinafter referred to as a reference Gaussian function) indicating a predicted value of the remaining life of the test material for each measurement method of the structure parameter (dislocation density in the present embodiment). Say). Further, a Gaussian function (hereinafter also referred to as a multiplication Gaussian function) is obtained by multiplying a plurality of reference Gaussian functions obtained for each measurement method of dislocation density by a probability multiplication theorem. Then, the remaining life of the test material is obtained based on the obtained multiplication Gaussian function.

<Derivation of reference Gaussian function>
First, a method for deriving a reference Gaussian function will be described. In the present embodiment, for example, a reference Gaussian function is obtained for each measurement method of dislocation density by executing the following steps Q1 to Q7. Hereinafter, each step will be described.

(Step Q1)
In step Q1, as will be described in detail later, a creep test is performed on a plurality of reference materials. As shown in Table 1 below, the dislocation density, the remaining life, and the creep strain of each of the plurality of reference materials after the creep test are performed. Ask for. The dislocation density is determined by an X-ray diffraction method and a positron annihilation method. In Table 1, the dislocation density and the like are shown using alphabetic characters for the sake of simplicity.

  Referring to Table 1, in step Q1, for example, a plurality of reference materials are subjected to a creep test under arbitrary temperature and stress conditions, and a plurality of creep interrupted materials (hereinafter simply referred to as interrupted materials) and a creep rupture material. (Hereinafter simply referred to as a fractured material). In the example of Table 1, seven interrupted materials and one fractured material are obtained by a creep test. The temperature and stress in the creep test are appropriately set according to, for example, the usage environment of the metal material that predicts the remaining life. The dislocation density of the plurality of interrupted materials and fractured materials obtained by the creep test is determined by an X-ray diffraction method and a positron annihilation method. Further, the remaining life (lifetime consumption rate) and the amount of creep strain are determined for each of the plurality of interrupted materials and fractured materials. In this embodiment, for example, the time required for the fractured material to break in the creep test is Tr, the test interruption time (test elapsed time) of the interruption material is T, and the lifetime consumption rate (= T / Tr). The life consumption rate of the fractured material is 1.0.

(Step Q2)
Step Q2 of the prediction method according to the present embodiment includes the following steps q21 and q22.

(Step q21)
In step q21, based on the creep strain and dislocation density obtained in step Q1, for each dislocation density measurement method, for example, a master curve (hereinafter referred to as a relationship between dislocation density and creep strain) as shown in FIG. , Referred to as a first master curve). In the present embodiment, a first master curve indicating the relationship between the dislocation density and creep strain determined by the X-ray diffraction method, and a first master curve indicating the relationship between the dislocation density and creep strain determined by the positron annihilation method, respectively. Created.

In step q21, one first master curve may be created for one measurement method, or a plurality of first master curves may be created for one measurement method. Specifically, referring to Table 1, for example, when the creep test conditions of the reference materials 1 to 4 and the creep test conditions of the reference materials 5 to 8 are different, a plurality of first measurements are performed for one measurement method. It is conceivable to create one master curve. In such a case, for example, one first master curve is created based on the dislocation densities A _{1 to} A ₄ and the creep strains S _{1 to} S _4, and the dislocation densities A _{5 to} A ₈ and the creep strains S _{5 to} S are generated. ₈ , one first master curve is created, and one first master curve is created based on the dislocation density B _{1 to} B ₄ and the creep strain S _{1 to} S _4, and the dislocation density B _{5 to} B One first master curve may be created based on ₈ and creep strains S _{5 to} S ₈ .

(Step q22)
In step q22, a master curve (hereinafter referred to as a second master curve) showing the relationship between the creep strain and the remaining life as shown in FIG. 4 is obtained based on the creep strain and the remaining life obtained in step Q1. . The second master curve can be created using, for example, the least square method.

In step q22, one second master curve may be created or a plurality of second master curves may be created. Specifically, referring to Table 1, for example, when the creep test conditions of the reference materials 1 to 4 and the creep test conditions of the reference materials 5 to 8 are different, a plurality of second master curves are created. Can be considered. In such a case, for example, one second master curve is created based on the creep strains S _{1 to} S ₄ and the remaining life rt _{1 to} rt _4, and the creep strains S _{5 to} S ₈ and the remaining life rt _{5 to} rt ₈ may create one second master curve.

(Step Q3)
Step Q3 of the prediction method according to the present embodiment includes the following steps q31 and q32.

(Step q31)
In step q31, based on the dislocation density obtained in step Q1 and the first master curve (see FIG. 1) obtained for each measurement method in step q21, for each measurement method, a plurality of reference materials creep strain (hereinafter, (Referred to as first predicted creep strain). Referring to Table 1, in this embodiment, the obtaining a first predicted creep strain AS _n of each reference material based on the dislocation density A _n, first predicted creep strain of each reference material based on the dislocation density B _n Find BS _n .

(Step q32)
In step q32, based on the first predicted creep strain obtained for each measurement method in step q31 and the second master curve (see FIG. 4) obtained in step q22, the remaining life of a plurality of reference materials for each measurement method. (Hereinafter referred to as the first predicted remaining life). Referring to Table 1, in this embodiment, the obtaining a first predicted remaining lifetime At _n based on the first predicted creep strain AS _n, first predicted remaining lifetime Bt _n based on the first predicted creep strain BS _n Ask for.

(Step Q4)
In step Q4, for each measurement method, a standard deviation of the first predicted remaining lives of the plurality of reference materials obtained in step Q3 is obtained with respect to the remaining lives of the plurality of reference materials obtained in step Q1. That is, in step Q4, the degree of variation of the first predicted remaining life determined from the master curve with respect to the actual measured remaining life of the plurality of reference materials is obtained as the standard deviation. Referring to Table 1, for example, when the remaining life rt _n is measured in step Q1 and the first predicted life At _n and Bt _n are obtained in step Q3, in step Q4, the remaining life rt _{n is determined} . Standard deviations AD and BD of the first predicted lifetimes At _n and Bt _n are obtained.

(Step Q5)
In step Q5, the structure parameter (dislocation density in the present embodiment) of the test material is obtained by the same measurement method as in step Q1. In this embodiment, the dislocation density of the test material is obtained by an X-ray diffraction method and a positron annihilation method.

(Step Q6)
Step Q6 of the prediction method according to the present embodiment includes the following steps q61 and q62.

(Step q61)
In step q61, based on the dislocation density of the test material obtained in step Q5 and the first master curve (see FIG. 1) obtained for each measurement method in step q21, the creep strain of the test material is determined for each measurement method. (Hereinafter referred to as second predicted creep strain). In the present embodiment, the creep strain determined from the first master curve is obtained as the second predicted creep strain based on the dislocation density obtained by the X-ray diffraction method. Similarly, based on the dislocation density obtained based on the positron annihilation method, the creep strain determined from the first master curve is obtained as the second predicted creep strain. That is, in step q61, the second predicted creep strain of the test material is obtained for each measurement method.

(Step q62)
In step q62, based on the second predicted creep strain of the test material obtained for each measurement method in step q61 and the second master curve (see FIG. 4) obtained in step q22, the remainder of the test material is determined for each measurement method. A lifetime (hereinafter referred to as a second predicted remaining lifetime) is obtained.

(Step Q7)
In step Q7, the second predicted remaining life obtained for each measurement method in step Q6 is averaged, and the standard deviation (see standard deviations AD and BD in Table 1) obtained for each measurement method in step Q4 is the standard deviation. For each measurement method as a reference Gaussian function. That is, in step Q7, a reference Gaussian function indicating a predicted value of the remaining life of the test material is obtained for each measurement method.

<Prediction of remaining life of test material>
In the present embodiment, the remaining life of the test material (metal material) is predicted by executing the processes of the following steps S1 and S2 using the plurality of reference Gauss functions obtained as described above.

(Step S1)
In Step S1, a Gaussian function (hereinafter referred to as a multiplication Gaussian function) is obtained by multiplying the plurality of reference Gaussian functions obtained in Step Q7 by a probability multiplication theorem. FIG. 6 is a diagram illustrating an example of a normal distribution diagram representing a reference Gaussian function and a multiplication Gaussian function. FIG. 6 shows a reference Gaussian function based on the dislocation density obtained by the X-ray diffraction method, a reference Gaussian function based on the dislocation density obtained by the positron annihilation method, and a multiplication Gauss obtained by multiplying these reference Gaussian functions. Function is shown.

(Step S2)
In step S2, the remaining life of the test material is predicted based on the multiplication Gaussian function obtained in step S1. With reference to FIG. 6, in the present embodiment, for example, a life consumption rate range t _{s to} t _f defined by a half-value width FWHM of a multiplication Gaussian function is predicted as a life consumption rate (remaining life) of a test material. .

<Effect>
As described above, in the present embodiment, first, a plurality of reference Gaussian functions indicating predicted values of the remaining life of the test material are obtained for each measurement method of the tissue parameter. Then, the remaining life of the test material is predicted based on a multiplication Gaussian function obtained by multiplying a plurality of reference Gaussian functions. That is, in the present embodiment, a plurality of different remaining life prediction methods are combined to predict the remaining life of the test material. In this case, even if a large error occurs in the predicted value of the remaining life indicated by any one of the plurality of reference Gaussian functions, the influence of the error can be reduced. Further, as shown in FIG. 6, the standard deviation of the multiplication Gaussian function is smaller than the standard deviation of each reference Gaussian function. Therefore, by predicting the remaining life based on the multiplication Gaussian function, it is possible to reduce the variation in the prediction result. As a result, it is possible to accurately predict the remaining life of the metal material.

[Second prediction method]
In the first prediction method described above, after obtaining the creep strain from the measurement parameter (dislocation density), the remaining life is obtained based on the creep strain. However, the remaining life may be obtained directly from the measurement parameters. Hereinafter, a prediction method for directly obtaining the remaining life from the measurement parameters will be briefly described.

<Derivation of reference Gaussian function>
First, a method for deriving a reference Gaussian function will be described. Note that the processes of steps Q1, Q2, Q3, and Q6 are different between the above-described first prediction method and the prediction method according to the present embodiment. Therefore, in the following, the processes of steps Q1, Q2, Q3 and Q6 will be mainly described.

(Step Q1)
In Step Q1 of the prediction method according to the present embodiment, as shown in Table 2 below, the dislocation density and the remaining life are obtained for each of the plurality of reference materials after the creep test.

(Step Q2)
In Step Q2, a master curve indicating the relationship between the dislocation density and the remaining life is obtained for each measurement method based on the remaining life and the dislocation density obtained in Step Q1.

(Step Q3)
In step Q3, based on the dislocation density obtained in step Q1 and the master curve obtained for each measurement method in step Q2, the remaining life of a plurality of reference materials (hereinafter referred to as first predicted remaining life) for each measurement method. ) Referring to Table 2, in the present embodiment, the obtaining a first predicted remaining lifetime At _n of each reference material based on the dislocation density A _n, first predicted remaining lifetime of each reference material based on the dislocation density B _n Bt _n is obtained.

(Step Q4)
Referring to Table 2, in step Q4, as in the case of the above-described first prediction method, for each measurement method, a plurality of criteria obtained in step Q3 with respect to the remaining lifetimes of the plurality of reference materials obtained in step Q1. A standard deviation of the first predicted remaining life of the material is obtained.

(Step Q5)
In step Q5, the dislocation density of the test material is obtained by the same measurement method as in step Q1, as in the case of the first prediction method described above. In this embodiment, the dislocation density of the test material is obtained by an X-ray diffraction method and a positron annihilation method.

(Step Q6)
In step Q6, based on the dislocation density obtained in step Q5 and the master curve created for each measurement method in step Q2, the remaining life of the test material (hereinafter referred to as second predicted remaining life) for each measurement method. Ask.

(Step Q7)
In step Q7, as in the case of the first prediction method described above, the second predicted remaining life obtained for each measurement method in step Q6 is used as an average value, and the standard deviation obtained for each measurement method in step Q4 (see Table 2). ) As a standard Gaussian function for each measurement method.

<Prediction of remaining life of test material>
Also in the present embodiment, similarly to the case of the first prediction method described above, the test material is executed by executing the processes of steps S1 and S2 using the plurality of reference Gauss functions obtained as described above. Predict the remaining life.

<Effect>
As described above, also in the present embodiment, a plurality of reference Gaussian functions indicating the predicted value of the remaining life of the test material are obtained for each measurement method of the tissue parameter. Then, the remaining life of the test material is predicted based on a multiplication Gaussian function obtained by multiplying a plurality of reference Gaussian functions. That is, also in this embodiment, a plurality of different remaining life prediction methods are combined to predict the remaining life of the test material. In this case, even if a large error occurs in the predicted value of the remaining life indicated by any one of the plurality of reference Gaussian functions, the influence of the error can be reduced. Further, similarly to the case of the first prediction method described above, it is possible to reduce the variation in the prediction results.

[Modification]
In the above-described embodiment, the remaining life of the test material is predicted based on the half-value width of the multiplication Gaussian function, but the remaining life prediction method is not limited to the above example. For example, the remaining life of the test material may be predicted based on the average value of the multiplication Gaussian function, or the remaining life of the test material may be predicted based on the standard deviation of the multiplication Gaussian function.

  In the above-described embodiment, the case where one type of tissue parameter is obtained by two methods has been described. However, one type of tissue parameter may be obtained by three or more measurement methods.

[Example of life prediction]
Hereinafter, an example when the lifetime consumption rate of the test material is actually predicted by the above-described first prediction method will be described together with numerical values. In the following description, the amount of creep strain and the life consumption rate are expressed as percentages. In this prediction example, a Ni-based alloy was used as the reference material and the test material. Further, in this prediction example, the dislocation density was obtained by the X-ray diffraction method and the positron annihilation method.

First, the standard deviation (refer to above-mentioned step Q4) was calculated | required for every measuring method by performing the process of step Q1-step Q4 about a some reference material. As a result, as shown in Table 3 below, the standard deviations were 3.29 × 10 ⁻⁵ and 2.31 × 10 ⁻¹ , respectively.

Next, the dislocation density of the test material was obtained by executing the above-described processing of Step Q5. As a result, as shown in Table 3, the dislocation density determined by the X-ray diffraction method is 6.75 × 10 ¹² (m ⁻² ), and the dislocation density determined by the positron annihilation method is 7.17 × 10. ¹² (m ⁻² ).

Next, the creep strain (second predicted creep strain) of the test material was obtained by executing the process of step q61 described above. As a result, as shown in Table 3, the second predicted creep strain based on the X-ray diffraction method is 1.70 × 10 ⁻² (%), and the second predicted creep strain based on the positron annihilation method is 1.78 × 10 ^-2 (%).

Next, the life consumption rate (second predicted remaining life) of the test material was obtained by executing the process of step q62 described above. As a result, as shown in Table 3, the second predicted remaining lifetime based on the X-ray diffraction method is 2.00 × 10 ⁻¹ (%), and the second predicted remaining lifetime based on the positron annihilation method is 2.12 × 10 ⁻¹ (%).

Then, step Q7 above, by executing the processing in steps S1 and S2, to determine the range t _s ~t _f of lifetime consumption of the test material. As a result, the range of the life consumption rate of the test material was 1.97 × 10 ^{−1 to} 2.05 × 10 ⁻¹ (%). On the other hand, the actual measurement value of the life consumption rate of the test material was 0.2 (%). That is, the actual life consumption rate of the test material was a value within the range of the life consumption rate of the test material predicted by the first prediction method described above. From this, it can be seen that the lifetime consumption rate of the test material can be predicted with high accuracy by the first prediction method.

(Other life prediction examples)
Although detailed description is omitted, even when two values of β-direction strength deviation and residual stress are used as values representing intragranular strain, by performing the same steps as in the above life prediction example, the test material The remaining life can be predicted.

  Hereinafter, an example when the life consumption rate is predicted using the β-direction strength deviation and the residual stress as a value representing the intragranular strain will be described together with numerical values. In the following description, the amount of creep strain and the life consumption rate are expressed as percentages. In this prediction example, a Ni-based alloy was used as the reference material and the test material.

  First, the standard deviation (refer to above-mentioned step Q4) was calculated | required for every measuring method by performing the process of step Q1-step Q4 about a some reference material. As a result, the values shown in Table 4 below were obtained.

  Next, by executing processing similar to the processing in the above-described steps Q5, q61, q62, the β-direction strength deviation, residual stress (MPa), second predicted creep strain, and second predicted remaining life ( Lifetime consumption rate) was determined. As a result, the values shown in Table 4 above were obtained.

Next, by performing the same process as the process of the above-mentioned step Q7, step S1, and step S2, the life consumption rate range t _{s to} t _f of the test material was obtained. As a result, the range of the life consumption rate of the test material was 47.6 to 48.5 (%). On the other hand, the measured value of the life consumption rate of the test material was 48 (%). That is, the actual life consumption rate of the test material was a value within the range of the life consumption rate of the test material predicted in this prediction example. This shows that the life consumption rate of the test material could be predicted with high accuracy.

According to the present invention, the remaining life or life consumption rate of a metal material can be appropriately predicted according to the degree of deterioration of the metal material. The present invention can be suitably used for predicting the remaining lifetime of various metal materials such as stainless steel, Ni-base alloy, Fe-Ni base alloy, and the like.

Claims (8)

A remaining life prediction method for predicting the remaining life of a metal material used in a high temperature environment based on a plurality of kinds of structure parameters relating to the state of a microstructure, comprising the following steps (A) to (C): A method for predicting the remaining life of a metal material.
(A) Using a metal material corresponding to a metal material used in the high temperature environment as a reference material, for the reference material, for each type of the structure parameter, the relationship between the structure parameter and the remaining life information regarding the remaining life (B) Obtaining one type of tissue parameter selected from the plurality of types of tissue parameters for the test material using the metal material used in the high temperature environment as a test material (C) A step of predicting the remaining life of the test material from the relationship between the one kind of structure parameter obtained in the step (B) and the structure parameter obtained in the step (A) and the remaining life information.   The method for predicting the remaining life of a metal material according to claim 1, wherein the plurality of types of structure parameters include dislocation density.   The method for predicting the remaining life of a metal material according to claim 2, wherein the plurality of types of structure parameters further include intragranular strain.   The method for predicting the remaining life of a metal material according to claim 3, wherein the plurality of structure parameters further include grain boundary strain.   In the step (B), when the dislocation density of the test material is less than or equal to a predetermined threshold value, the dislocation density is selected as the one type of structural parameter, and the dislocation density of the test material exceeds the predetermined threshold value. If it is, the structural parameter other than the dislocation density is selected as the one kind of structural parameter, the remaining life prediction method of the metal material according to any one of claims 2 to 4. The step (A) includes the following steps (a1) and (a2):
The relationship between the structure parameter obtained in the step (A) and the remaining life information is the relationship between the structure parameter obtained in the step (a1) and the creep strain amount, and the step (a2) below. Including the relationship between the amount of creep strain obtained and the remaining life,
6. The method for predicting a remaining life of a metal material according to claim 1, wherein the step (C) includes the following steps (c1) and (c2).
(A1) A step of obtaining a relationship between a structure parameter and a creep strain amount for each of the plurality of types of structure parameters for the reference material (a2) A step of obtaining a relationship between a creep strain amount and a remaining life for the reference material ( c1) From the relationship between the one type of structural parameter obtained in the step (B) and the one type of structural parameter obtained in the step (a1) and the amount of creep strain, the amount of creep strain of the test material is determined. Step (c2) Obtaining the remaining life of the test material from the relationship between the creep strain amount obtained in the step (c1) and the creep strain amount obtained in the step (a2) and the remaining life. Step to predict The plurality of structural parameters include dislocation density,
When the dislocation density is selected as the one type of structure parameter in the step (B), the amount of creep strain obtained in the step (c1) is the same as the structure parameter other than the dislocation density in the step (B). The method for predicting a remaining life of a metal material according to claim 6, wherein the remaining lifetime is smaller than an amount of creep strain obtained in the step (c1) when selected as the one type of structural parameter.   6. The method for predicting the remaining life of a metal material according to claim 1, wherein, in the step (A), a relationship between the structure parameter and the remaining life is obtained as a relationship between the structure parameter and the remaining life information. .

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