Method for rapid optimization of fatigue strength of a metallic material at different stress ratios

Abstract

The present application relates to the field of material science and engineering application technology, in particular to a kind of metal material fatigue strength under different stress ratio fast optimization method.The method discusses the relationship among tensile strength of metal material, stress ratio and fatigue strength, and the parabolic equation of P-C model is used to establish the fatigue strength fast optimization method of metal material under different stress ratio.The present application not only considers the nonlinear relationship between fatigue strength and tensile strength, but also considers the fatigue sensitivity of different metal materials under each stress ratio, which has scientific significance and engineering value.In addition, the present application can calculate the critical optimization value σ bc of tensile strength of metal material under a certain stress ratio and the theoretical optimization value of fatigue strength (i.e., the maximum fatigue strength when the tensile strength is σ bc ), which can provide an optimization direction for fatigue-resistant design and greatly improve the optimization efficiency.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of material science and engineering application, in particular to a method for quickly optimizing fatigue strength of metal materials under different stress ratios. BACKGROUND

[0002] Fatigue fracture is the most common failure mode of components, and in the engineering field, there is a constant demand for component service conditions and environment, and the optimization of component fatigue performance is getting more and more attention. And in order to avoid failure accidents caused by low fatigue performance of components, the research on the optimization of fatigue strength of metal materials will be a long-term task.

[0003] The optimization of fatigue performance of materials under different stress ratios is an important problem closely related to the safety of components in service. Some scholars have found that the material with the best performance in the axial symmetric load fatigue experiment is not the strongest in the high stress ratio fatigue experiment by designing various processes and conducting fatigue tests under different stress ratios. Therefore, it is of great significance to explore the process with the best fatigue performance under a certain stress ratio or to select the process with the best overall performance.

[0004] In the 1950s, some scientists pointed out that the fatigue strength and the tensile strength were approximately linearly related, which had a deep impact on the field of fatigue at that time. People can improve the fatigue strength by improving the tensile strength of the material. However, in recent years, with the progress of material science and processing technology, there has been a new understanding of fatigue strength research, that is, the fatigue strength of the material does not increase with the increase of the tensile strength, but shows a downward trend. Recently, Pang et al. proposed a general relationship between tensile strength and fatigue strength, that is, a parabolic relationship, which can predict and evaluate the highest fatigue strength of the material under a certain tensile strength, which will greatly improve the efficiency.

[0005] In summary, in the face of the complex relationship between tensile strength, fatigue strength and stress ratio, it is undoubtedly very time-consuming and laborious to conduct a large number of experiments to explore the optimization method of fatigue strength. Therefore, it is necessary to establish a method for quickly optimizing the fatigue strength of materials under different stress ratios by exploring the relationship between the three through a small number of experiments. SUMMARY

[0006] In order to realize the optimization of fatigue strength of materials under a certain stress ratio, the purpose of the present application is to provide a method for quickly optimizing fatigue strength of metal materials under different stress ratios. This method establishes the relationship between tensile strength, fatigue strength and stress ratio, not only considers the nonlinear relationship between tensile strength and fatigue strength, but also considers the change of fatigue strength of different materials under different stress ratios. Only a small amount of data is needed to obtain the optimization target, which provides guidance for the design of quick optimization method.

[0007] In order to achieve the above purpose, the technical scheme adopted by the present application is:

[0008] A method for rapid optimization of fatigue strength of metal materials under different stress ratios, which specifically comprises the following steps:

[0009] (1) Two or more preparation or optimization processes are performed on the metal materials to be optimized to obtain metal materials with different tensile strengths;

[0010] (2) The samples in step (1) are subjected to tensile tests to obtain the tensile strength σ b ;

[0011] (3) The samples in step (1) are subjected to fatigue strength tests under symmetric axial load and asymmetric axial load to obtain the fatigue strengths σ -1 and σ w under the conditions of stress ratio R = -1 and R ≠ -1, respectively;

[0012] (4) The σ -1 and σ b values of each group of samples are fitted by formula (1) using the data in steps (2) and (3) to obtain fitting parameters C and P;

[0013]

[0014] (5) The average stress σ m of the fatigue strength under the condition of R ≠ -1 is calculated by formula (2), and the data of each group is plotted in a rectangular coordinate system with σ m / σ b and σ w / σ -1 as the horizontal and vertical coordinates, respectively, and the data points are fitted by formula (3) through the (0, 1) coordinate to obtain parameter G;

[0015]

[0016] (6) The parameters G of each group of samples and the corresponding σ -1 and σ b are fitted by formula (4) to obtain fitting parameter b;

[0017]

[0018] (7) The fitting parameters C, P and b obtained above are substituted into formula (5),

[0019]

[0020] where σ bc is the critical optimized value of the tensile strength of the material under a certain R condition, i.e., the method determines that the tensile strength of the same series of materials under a certain R condition is σ bcThe fatigue strength of the sample is the highest;

[0021] (8) Substitute σ under a certain R condition bc into formula (6),

[0022]

[0023] to obtain the theoretically optimal value of the fatigue strength of the same series of materials identified by this method under this R.

[0024] (9) Design a heat treatment plan for the metal to be optimized so that its fatigue strength under a certain target R condition is within the acceptable error range, so as to obtain the optimal value of the fatigue strength of the material under the R condition and the corresponding optimization method.

[0025] In the above step (1), at least two groups of different heat treatment processes are selected for experiments on the same series of metal materials; the processes of each group of the same series of materials are samples prepared by different processing methods, with different tissue characteristics or different strength levels, and ensure a large strength difference.

[0026] In the above step (2), in order to ensure data repeatability, at least three samples are required for each group to conduct tensile experiments, and the σ [[ID=​​​​​​​​​​​​​​​​​​​​​​​(1)Tensile strength reflects the comprehensive ability of the material to resist fracture, while fatigue damage is localized, often related to inclusions, local non-uniform structure, defect holes, etc. Due to the difference in damage mechanism, it is not linearly related to the traditional concept. Formula (1) well describes the relationship between the tensile strength and the fatigue strength of the material, and the optimal value of the fatigue strength under the same stress ratio can be obtained.

[0032] (2) Fatigue damage is affected by stress ratio, and the difference in plastic deformation capacity of the material will cause the difference in damage degree, so a new parameter-fatigue sensitivity coefficient is established to represent the damage degree of the material under stress ratio. It is found that it is related to the ratio of average stress and tensile strength, so stress ratio damage gradient G (formula (3)) is introduced to represent this relationship.

[0033] (3) A large amount of data has been verified that stress ratio damage gradient G is related to fatigue ratio (the ratio of fatigue strength and tensile strength), and the two are negatively correlated. This phenomenon is represented by formula (4), and formula (1) and (3) can be combined to describe the relationship among tensile strength, stress ratio and fatigue strength.

[0034] The advantages and beneficial effects of the present application are as follows:

[0035] 1. The present application has scientific significance and practical value. The present application not only considers that the fatigue strength of general materials is approximately parabolic with the tensile strength, but also focuses on the influence of different stress ratios on the fatigue strength of different materials, and realizes the rapid optimization of fatigue strength by calculating the theoretical optimal value of tensile strength.

[0036] 2. The present application has good universality. The prediction formula has multiple meaningful parameters C, P and b to adapt to materials with different organizational characteristics and strength levels, and establishes the relationship among the tensile strength, fatigue strength and stress ratio of the same series of metal materials, providing a reference for fatigue strength optimization.

[0037] 3. The present application has the purpose of fatigue strength optimization for the same series of materials. The prediction formula of the method can calculate the theoretical optimal value of the fatigue strength of the material under a certain stress ratio, which can be used as the anti-fatigue optimization goal, and provide guidance for fatigue strength evaluation. BRIEF DESCRIPTION OF DRAWINGS

[0038] Figure 1 It is a flow chart of the rapid fatigue strength optimization method of metal materials under different stress ratios.

[0039] Figure 2 It is a σ -1 / σ b -σ b relationship diagram of 18Ni maraging steel of two groups of processes.

[0040] Figure 3 σ for two processes of 18Ni martensitic aging steel m / σ b -σ w / σ -1 Relationship diagram.

[0041] Figure 4 G-σ for two processes of 18Ni martensitic aging steel -1 / σ b Relationship diagram.

[0042] Figure 5 The result is the optimal fatigue strength value for 18Ni martensite. Detailed Implementation

[0043] The present invention will now be further described in conjunction with embodiments and accompanying drawings.

[0044] Example:

[0045] like Figure 1 The diagram illustrates the operational flow of a rapid optimization method for the fatigue strength of metallic materials under different stress ratios. This embodiment focuses on optimizing the fatigue strength of 18Ni martensitic aging steel at various stress ratios. Experimental data were obtained by measuring the tensile strength of 18Ni martensitic aging steel after two different heat treatment processes and at stress ratios R = -1 and 0.1. This data was then used to optimize the fatigue strength of the material at R = 0.1 and 0.5. The specific steps are as follows:

[0046] Step 1: 18Ni martensitic aging steel was subjected to heat treatment at 500℃ for 5 hours and 630℃ for 3 hours as two sets of preliminary materials for establishing a fatigue strength optimization method.

[0047] Step two: Design tensile specimens for the two sets of materials mentioned above and conduct tensile tests to determine the tensile strength σ. b The values ​​are 1939 MPa and 1358 MPa, respectively.

[0048] Step 3: Fatigue strength tests were conducted on two groups of 18Ni martensitic aging steel materials at 500℃ / 5h under conditions of R = -1 and 0.1. -1 and σ w σ -1 =595MPa and σ w =1056MPa; fatigue strength σ at 630℃ / 3h under conditions of R=-1 and 0.1 -1 and σ w σ -1 =588MPa and σ w =858MPa, as shown in Table 1.

[0049] Step four, σ of the above two groups of materials -1With σ b Values ​​are obtained through formulas Perform fitting (e.g.) Figure 2 As shown in the figure, C and P were obtained as 0.728 and 2.171 × 10⁻⁶, respectively. -4 (See Table 1).

[0050] Step 5, using the formula Calculate the average stress σ of the fatigue strength of the two groups of materials under the condition R = 0.1. m The value is σ, which represents the two sets of data. m / σ b and σ w / σ -1 Draw a rectangular coordinate system with x and y coordinates respectively, and pass through the (0,1) coordinate using the formula. Perform linear fitting (e.g.) Figure 3 As shown in Table 1, the parameter G values ​​were 2.585 and 1.321 respectively.

[0051] Step six, compare the G value obtained in step five with σ -1 and σ b Through formula Perform fitting (e.g.) Figure 4 As shown in the figure, b is 0.831.

[0052] Step 7: Substitute the obtained parameter values ​​C, P, and b into the formula. In the calculation, we obtain: under the condition R = 0.1, σ bc =1906.8MPa; under the condition of R=0.5, σ bc =2100.5MPa.

[0053] Step eight will yield the parameter values ​​C, P, and b, and and Substitute into the formula respectively In this study, the theoretical optimal fatigue strength values ​​for the material at R = 0.1 and 0.5 were obtained, as determined by this method. 1008MPa and 1361MPa respectively (e.g. Figure 5 (As shown).

[0054] Step nine: To evaluate the accuracy of the prediction results, three heat treatment processes were designed: 550℃ / 5h, 600℃ / 3h, and 575℃ / 1h. The fatigue strength was measured as shown in Table 1. Among these, the optimal fatigue strength at 600℃ / 3h was 1076 MPa under R=0.1; and the optimal fatigue strength at 500℃ / 5h was 1496 MPa under R=0.5. The deviations from the theoretical optimal values ​​in Step eight were -6.32% and -9.02%, respectively, both within acceptable error ranges. Therefore, 600℃ / 3h can be used as the optimization method for the fatigue strength of 18Ni martensitic aging steel under R=0.1, and 500℃ / 5h can be used as the optimization method for this material under R=0.5.

[0055] Table 1. Summary of Fatigue Strength Optimization Data for 118Ni Martensitic Aging Steel

[0056]

[0057] The results show that the method of this invention explores the relationship between tensile strength, stress ratio, and fatigue strength of metallic materials, and establishes a rapid optimization method for fatigue strength of metallic materials under different stress ratios using the parabolic equation of the PC model. This invention not only considers the nonlinear relationship between fatigue strength and tensile strength, but also the fatigue sensitivity of different metallic materials under various stress ratios, possessing scientific significance and engineering value. Furthermore, this invention can calculate the critical optimization value σ of tensile strength of metallic materials at a certain stress ratio. bc and the theoretical optimized value of fatigue strength (i.e., when the tensile strength is σ) bc There is a maximum fatigue strength. This invention provides optimization directions for fatigue-resistant design, greatly improving optimization efficiency. Since the corresponding parameters C, P, and b can be obtained through prediction formulas for different metallic materials, the method is generally applicable to various metallic materials with different microstructures and strength levels, especially low-carbon steel and alloy steel. Further optimization for more materials is expected in the future.

[0058] The above embodiments are merely illustrative of the principles and performance of the present invention and are not exhaustive. People can obtain other embodiments based on these embodiments without creative effort, and these embodiments all fall within the protection scope of the present invention.

Claims

1. A method for rapid optimization of fatigue strength of a metallic material at different stress ratios, characterized in that, The method specifically comprises the following steps: (1) preparing or optimizing the metal material to be optimized by two or more processes to obtain metal materials with different tensile strengths; (2) Each group of samples in step (1) is subjected to a tensile test to obtain the tensile strength σ b ; (3) Each group of samples in step (1) is subjected to fatigue strength tests of symmetric axial load and asymmetric axial load, respectively obtaining fatigue strengths σ -1 and σ w under the conditions of stress ratio R = -1 and R≠ -1 (4) Using the data from steps (2) and (3), the σ -1 values for each group of samples are fitted by equation (1) to obtain the fitting parameters C and P. b values for each group of samples are fitted by equation (1) to obtain the fitting parameters C and P. (5) Calculate the average stress σ of fatigue strength under the condition of R≠-1 by formula (2) m The data of each group is plotted as a rectangular coordinate system with σ m / σ b and σ w / σ -1 respectively as the horizontal and vertical coordinates. The data points are fitted by formula (3) through the (0, 1) coordinate to obtain the parameter G. (6) The parameter G of each group of samples is compared with the corresponding σ -1 and σ b The fitting parameter b is obtained by fitting with formula (4); (7) substituting the obtained fitting parameters C, P and b into formula (5), wherein σ bc is the critical optimized value of the tensile strength of the material under certain R conditions, i.e. the method determines that under certain R conditions the same series of materials has the highest fatigue strength at a tensile strength of σ bc of the sample; (8) σ in a certain R condition bc Substitute into equation (6), The theoretical optimal value of fatigue strength of the same series of materials under the R identified by the method can be obtained (9) Designing heat treatment scheme for the metal to be optimized, so that its fatigue strength under a certain target R condition is within the acceptable error range, thereby obtaining the optimal value of the fatigue strength of the material under the R condition and the corresponding optimization method. can be accepted.

2. The method for rapid optimization of fatigue strength of metallic materials at different stress ratios according to claim 1, characterized in that, In step (1), at least two groups of different heat treatment processes are selected for the same series of metal materials; each group of processes of the same series of materials is a sample prepared by different processes, and has different organizational characteristics or different strength levels.

3. The method for rapid optimization of fatigue strength of metallic materials at different stress ratios according to claim 1, characterized in that, In step (2), to ensure data repeatability, at least three samples per group are needed to perform the stretching experiment, and the value of σ b is averaged.

4. The method for rapid optimization of fatigue strength of metallic materials at different stress ratios according to claim 1, characterized in that, In step (3), the fatigue experiment and the tensile experiment have the same temperature and atmosphere environment conditions; 1-2 non-symmetrical axial loads are selected for fatigue strength testing; at least 3 pairs of ascending and descending methods are required for each group of fatigue strengths, and the fatigue strength is represented by the maximum stress value.

5. The method for rapid optimization of fatigue strength of metallic materials at different stress ratios according to claim 1, characterized in that, In step (7), formula (5) is used to calculate the critical optimization value of the tensile strength under the condition of-1<R<1.

6. The method for rapid optimization of fatigue strength of metallic materials at different stress ratios according to claim 1, characterized in that, In step (9), if the designed scheme obtains a fatigue strength value exceeding the acceptable error range, the data is repeated to recalculate using steps (4) - (8) to obtain the σ bc and value after iteration; and the heat treatment regime is again designed until the resulting fatigue strength is within the acceptable error range. the acceptable error range.

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