Method for rapidly optimizing fatigue strength of metal material under different stress ratios

Abstract

The invention relates to the technical field of material science and engineering application, in particular to a method for rapidly optimizing fatigue strength of a metal material under different stress ratios. According to the method, the relation among the tensile strength, the stress ratio and the fatigue strength of the metal material is discussed, and the rapid fatigue strength optimization method of the metal material under different stress ratios is established by utilizing a parabolic equation of a P-C model. The method not only considers the nonlinear relationship between the fatigue strength and the tensile strength, but also considers the fatigue sensitivity of different metal materials under various stress ratios, and has scientific significance and engineering value. Besides, the tensile strength critical optimization value sigma bc and the fatigue strength theoretical optimization value # imgabs0 # (namely, the maximum fatigue strength value # imgabs1 # exists when the tensile strength is sigma bc) of the metal material at a certain stress ratio can be obtained through calculation, the optimization direction can be provided for anti-fatigue design, and the optimization efficiency is greatly improved.

Description

Technical Field

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

[0002] Fatigue fracture is the most common failure form of components. In the current situation where there is a constant demand for component service conditions and environments in the engineering field, the optimization of component fatigue performance has received increasing attention. In order to avoid failure accidents caused by low component fatigue performance, the research on the optimization of fatigue strength of metal materials will be a long-term topic.

[0003] The optimization of fatigue performance of materials under different stress ratios is an important issue closely related to the safety of component service. Some scholars have designed a variety of processes and conducted fatigue tests at different stress ratios and found that the process material with the best performance in the axisymmetric load fatigue test is not the highest in the high stress ratio fatigue test. Therefore, it is of great significance to explore the best process for fatigue performance at a specific stress ratio, or to select the process with the best overall performance.

[0004] In the 1850s, some scientists pointed out that fatigue strength and tensile strength have an approximately linear relationship, which had a profound impact on the fatigue field at that time. People can achieve the purpose of improving fatigue strength by improving the tensile strength of materials. However, with the progress of materials science and processing technology in recent years, there has been a new understanding of fatigue strength research, that is, the fatigue strength of materials does not increase with the increase of tensile strength, but tends to decrease. Recently, Pang et al. proposed a general relationship between tensile strength and fatigue strength, that is, a parabolic relationship, and predicted that the highest fatigue strength of the material under a certain tensile strength will greatly improve efficiency.

[0005] In summary, facing the complex relationship between tensile strength, fatigue strength and stress ratio, conducting a large number of experiments to explore the optimization method of fatigue strength is undoubtedly very time-consuming and labor-intensive. Therefore, it is an urgent problem to explore the relationship between the three through a small number of experiments and establish a rapid optimization method for fatigue strength of materials under different stress ratios. Summary of the invention

[0006] In order to optimize the fatigue strength of materials under specific stress ratios, the purpose of the present invention is to provide a method for quickly optimizing the fatigue strength of metal materials under different stress ratios. This method not only considers the nonlinear relationship between tensile strength and fatigue strength, but also considers the changes in fatigue strength of different materials under various stress ratios by establishing the relationship between tensile strength, fatigue strength and stress ratio. Only a small amount of data is needed to obtain the optimization target, providing guidance for designing a fast optimization method.

[0007] In order to achieve the above object, the technical solution adopted by the present invention is:

[0008] A method for quickly optimizing fatigue strength of metal materials under different stress ratios, the method specifically comprising the following steps:

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

[0010] (2) Perform a tensile test on each group of samples in step (1), mainly to obtain the tensile strength σ b ;

[0011] (3) Each group of samples in step (1) is subjected to fatigue strength tests under symmetrical axial load and asymmetrical axial load, and the fatigue strength σ under stress ratio R=-1 and R≠-1 is obtained respectively. -1 and σ w ;

[0012] (4) Using the data from steps (2) and (3), we can calculate the σ of each group of samples. -1 With σ b The values ​​are fitted by formula (1) to obtain the fitting parameters C and P;

[0013]

[0014] (5) The average stress σ of fatigue strength under the condition of R≠-1 is calculated by formula (2): m , each group of data is divided into m / σ b and σ w / σ -1 Draw rectangular coordinates for the horizontal and vertical coordinates respectively, fit the data points through the (0,1) coordinate using formula (3) to obtain the parameter G;

[0015]

[0016] (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 formula (4);

[0017]

[0018] (7) Substitute the above obtained fitting parameters C, P and b into formula (5),

[0019]

[0020] Among them, σ bc is the critical optimization value of the tensile strength of the material under a certain R condition, that is, this method determines that the same series of materials under a certain R condition have a tensile strength of 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] Then the theoretically optimal fatigue strength value of the same series of materials under this R can be obtained by this method.

[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 fatigue strength value of the material under the R condition and the corresponding optimization method.

[0025] In the above step (1), at least two different heat treatment processes are selected for the same series of metal materials for experiments; each process of the same series of materials is a sample prepared by different processing, with different tissue characteristics or different strength levels, and the strength difference is ensured to be large.

[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 b value is taken as the average.

[0027] In the above step (3), the fatigue experiment needs to ensure the same temperature and atmosphere environmental conditions as the tensile experiment; select 1-2 non-symmetric axial loads for fatigue strength testing to ensure higher prediction accuracy; at least 3 pairs of up-and-down methods are required for each group of fatigue strength, and the fatigue strength is represented by the maximum stress value.

[0028] In the above step (7), formula (5) is used to calculate the critical optimization value of the tensile strength under the condition of -1 < R < 1.

[0029] In the above step (9), if the fatigue strength value obtained by the designed plan exceeds the acceptable error range, use this data to repeat steps (4)-(8) for recalculation to obtain the iterated σ bc and value; and design a heat treatment plan again until the obtained fatigue strength is within the acceptable error range.

[0030] The design idea of the present invention revolves around the basic principle of fatigue damage, considering the multiple effects of tensile properties and stress ratio on fatigue strength and quantitatively integrating them through formulas, specifically in the following aspects:

[0031] (1) Tensile strength reflects the comprehensive ability of a material to resist fracture, while fatigue damage is localized and is often related to inclusions, localized inhomogeneous structures, defect holes, etc. Due to the difference in the damage mechanisms of the two, they are not linearly correlated as in the traditional concept. Formula (1) well describes the relationship between the tensile strength and fatigue strength of a material, and can obtain the optimal value of fatigue strength under the same stress ratio.

[0032] (2) Fatigue damage is affected by stress ratio, and the different plastic deformation capabilities of materials will lead to different damage degrees. Therefore, a new parameter, fatigue sensitivity coefficient, is established to represent the damage degree of the material due to stress ratio. It is also found that it is related to the ratio of average stress to tensile strength, so the stress ratio damage gradient G (Formula (3)) is introduced to represent this relationship.

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

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

[0035] 1. The present invention has scientific significance and practical value. The present invention not only takes into account the parabolic relationship between fatigue strength and tensile strength of general materials, but also focuses on the influence of various stress ratios on fatigue strength of different materials, and realizes rapid optimization of fatigue strength by calculating the theoretical optimal value of tensile strength.

[0036] 2. The present invention has good universality. The prediction formula has multiple meaningful parameters C, P and b to be applicable to materials with different organizational characteristics and strength levels, and establishes the relationship between 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 invention is purposeful in optimizing the fatigue strength of 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 target and provide guidance for fatigue strength evaluation. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 Flowchart of the rapid optimization method for fatigue strength of metal materials under different stress ratios.

[0039] Figure 2 is the σ of the two groups of processes for 18Ni maraging steel -1 / σ b -σ b Relationship diagram.

[0040] Figure 3 is the σ of the two groups of processes for 18Ni maraging steel m / σ b -σ w / σ -1 Relationship diagram.

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

[0042] Figure 5 This is the optimal result of fatigue strength of 18Ni martensite. DETAILED DESCRIPTION

[0043] The present invention is further described below in conjunction with embodiments and drawings.

[0044] Example:

[0045] like Figure 1 As shown in the figure, the operation flow of the method for rapid optimization of fatigue strength of metal materials at different stress ratios. This embodiment optimizes the fatigue strength of 18Ni maraging steel at various stress ratios. The tensile strength and fatigue strength of 18Ni maraging steel at stress ratios R=-1 and 0.1 after two different heat treatment processes are measured as experimental data, and 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: Heat treatment of 18Ni maraging steel at 500°C / 5h and 630°C / 3h is performed as two groups of preparatory materials for establishing the fatigue strength optimization method.

[0047] Step 2: Design tensile specimens for the above two groups of materials and conduct tensile tests. The tensile strength σ b They are 1939MPa and 1358MPa respectively.

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

[0049] Step 4: The σ of the above two groups of materials -1With σ b The value is obtained by the formula Fitting (such as Figure 2 As shown), C and P were obtained to be 0.728 and 2.171×10 -4 (See Table 1).

[0050] Step 5: Use the formula Calculate the average stress σ of fatigue strength of two groups of materials under the condition of R = 0.1 m Value, the two sets of data are divided into m / σ b and σ w / σ -1 Draw a rectangular coordinate system for the horizontal and vertical coordinates respectively, and pass the (0,1) coordinate through the formula Perform a linear fit (such as Figure 3 As shown in Table 1, the parameter G values ​​are 2.585 and 1.321 respectively.

[0051] Step 6: Compare the G value obtained in step 5 with σ -1 and σ b By formula Fitting (such as Figure 4 As shown), b is obtained as 0.831.

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

[0053] Step 8: Get the parameter values ​​C, P and b, and and Substitute into the formula The optimal fatigue strength value of the material at R = 0.1 and 0.5 is obtained by this method. 1008MPa and 1361MPa respectively (such as Figure 5 shown).

[0054] Step 9. In order to evaluate the accuracy of the prediction results, three heat treatment processes were designed: 550℃ / 5h, 600℃ / 3h and 575℃ / 1h, and the fatigue strength was measured as shown in Table 1. Among them, the optimal fatigue strength value of 600℃ / 3h under R=0.1 is 1076MPa; the optimal fatigue strength value of 500℃ / 5h under R=0.5 is 1496MPa, and the deviations from the theoretical optimal value of step 8 are -6.32% and -9.02%, respectively, which are within the acceptable error range. Therefore, 600℃ / 3h can be used as the fatigue strength optimization method of 18Ni maraging steel under R=0.1, and 500℃ / 5h can be used as the optimization method of this material under R=0.5.

[0055] Table 118 Summary of fatigue strength optimization related data of Ni maraging steel

[0056]

[0057] The implementation results show that the method of the present invention explores the relationship between the tensile strength, stress ratio and fatigue strength of metal materials, and uses the parabolic equation of the PC model to establish a rapid optimization method for the fatigue strength of metal materials at different stress ratios. The present invention not only considers the nonlinear relationship between fatigue strength and tensile strength, but also considers the fatigue sensitivity of different metal materials at various stress ratios, which has scientific significance and engineering value. In addition, the present invention can calculate the critical optimization value σ of the tensile strength of metal materials at a certain stress ratio bc and fatigue strength theoretical optimization value (That is, when the tensile strength is σ bc The fatigue strength reaches its maximum value when ), can provide optimization direction for anti-fatigue design and greatly improve optimization efficiency. Since the present invention can obtain corresponding parameters C, P and b through prediction formula for different metal materials, the method of the present invention is generally applicable to metal materials with different organizational characteristics and strength levels, especially low carbon steel and alloy steel, and more materials will be further optimized in the future.

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

Claims

1. A method for rapidly optimizing fatigue strength of metal materials under different stress ratios, characterized in that: The method specifically includes the following steps: (1) Perform two or more preparation or optimization processes on the metal material to be optimized to obtain metal materials with different tensile strengths; (2) Perform a tensile test on each group of samples in step (1), mainly to obtain the tensile strength σ b ; (3) Each group of samples in step (1) is subjected to fatigue strength tests under symmetrical axial load and asymmetrical axial load, and the fatigue strength σ under stress ratio R=-1 and R≠-1 is obtained respectively. -1 and σ w ; (4) Using the data from steps (2) and (3), we can calculate the σ of each group of samples. -1 With σ b The values ​​are fitted by formula (1) to obtain the fitting parameters C and P; (5) The average stress σ of fatigue strength under the condition of R≠-1 is calculated by formula (2): m , each group of data is divided into m / σ b and σ w / σ -1 Draw rectangular coordinates for the horizontal and vertical coordinates respectively, fit the data points through the (0,1) coordinate using formula (3) 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 formula (4); (7) Substitute the obtained fitting parameters C, P, and b into formula (5); Among them, σ bc is the critical optimization value of the tensile strength of the material under a certain R condition, that is, this method determines that the same series of materials under a certain R condition have a tensile strength of σ bc The fatigue strength of the sample was the highest; (8) Set σ under a certain R condition bc Substituting into formula (6), The optimal value of fatigue strength of the same series of materials under this R can be obtained by this method. (9) Design a heat treatment scheme for the metal to be optimized so that its fatigue strength under a certain target R condition is within Within the acceptable error range, the optimal value of the fatigue strength of the material under R conditions and the corresponding optimization method are obtained.

2. The method for rapidly optimizing fatigue strength of metal materials under different stress ratios according to claim 1, characterized in that: In step (1), at least two different heat treatment processes are selected for experiments on the same series of metal materials; each process of the same series of materials is a sample prepared by different processing methods, with different tissue characteristics or different strength levels, and a large strength difference is ensured.

3. The method for rapidly optimizing fatigue strength of metal materials under different stress ratios according to claim 1, characterized in that: In step (2), in order to ensure data repeatability, at least three samples are required for each group to undergo tensile testing. b The values ​​are averaged.

4. The method for rapidly optimizing fatigue strength of metal materials under different stress ratios according to claim 1, characterized in that: In step (3), the fatigue experiment needs to ensure the same temperature and atmosphere environmental conditions as the tensile experiment; select 1-2 asymmetric axial loads for fatigue strength testing to ensure high prediction accuracy; at least 3 pairs of up-and-down methods are required for each group of fatigue strength, and the fatigue strength is represented by the maximum stress value.

5. The method for rapid optimization of fatigue strength of metal materials under 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 rapidly optimizing fatigue strength of metal materials under different stress ratios according to claim 1, characterized in that: In step (9), if the fatigue strength value obtained by the designed solution exceeds Acceptable error range, using this data to repeat steps (4)-(8) to recalculate and obtain the iterative σ bc and value; The heat treatment scheme is designed again until the fatigue strength is within Within the acceptable error range.

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