A method for predicting notch fatigue strength of metal materials

Abstract

The present invention discloses a method for predicting the notch fatigue strength of metal materials, which belongs to the technical field of material and component fatigue performance testing. The method explores the damage increase between the fatigue performance of notched components and smooth components, and explores the quantitative relationship. By establishing the fatigue damage increase and stress concentration coefficient K of different stress concentration effects, the fatigue damage increase and stress concentration coefficient K of different notched components are analyzed. t The material constant C can be obtained by the relationship between them, which can effectively predict the material's t This method rationally considers the influence of stress concentration on fatigue damage and can predict the notch fatigue strength of the same series of metal materials with only a small number of fatigue tests. It is expected to replace the traditional empirical model and achieve efficient and accurate prediction.

Description

Technical Field

[0001] The present invention relates to the field of material science and engineering application technology, and in particular to a method for predicting notch fatigue strength of metal materials. Background Art

[0002] In recent years, with economic development and the demand for high production efficiency, major equipment across various industries has become increasingly large-scale, systematized, and complex. Consequently, some notched components have been designed to achieve high mobility, ease of assembly, and multifunctionality to meet diverse requirements. However, the presence of notches often leads to stress concentrations in critical structures during service, severely impacting the mechanical properties, particularly fatigue resistance, of these components. Given the unpredictability of fatigue failure, research on notch fatigue, particularly the prediction of notch fatigue strength, has garnered significant attention.

[0003] Regarding the exploration of notch fatigue strength prediction methods, scholars such as Neuber, Peterson, and Yu have successively proposed empirical formulas based on the notch arc radius and basic properties. However, these formulas have limited applicability and are not accurate for the fatigue strength prediction of components with many notch types, such as grooves, cuts, chamfers, and holes. Therefore, establishing a quantitative relationship between the fatigue damage increase between notched and smooth components and achieving accurate prediction of notch fatigue strength has become an urgent problem to be solved. Summary of the Invention

[0004] The present invention aims to provide a method for predicting the notch fatigue strength of metallic materials. This method, based on the relationship between notch fatigue damage amplification and stress concentration factors, establishes a relationship between fatigue strength under different stress concentration effects. This method, with its unique parameters and simple and rapid application, effectively reduces the number of tests required to explore the fatigue performance of notched components, improving the efficiency of obtaining notch fatigue strength. It is expected to replace traditional correlation models and achieve efficient prediction of notch fatigue strength.

[0005] In order to achieve the above object, the technical solution adopted by the present invention is:

[0006] A method for predicting notch fatigue strength of metal materials, the method specifically comprising the following steps:

[0007] (1) Prepare smooth specimens of target metal material and at least one set of notched specimens; the theoretical stress concentration factor K of the smooth specimen is t =1, stress concentration factor K of notched specimen t >1;

[0008] (2) Fatigue strength test is performed on smooth specimens and notched specimens of target metal materials to obtain the fatigue strength σ of the smooth specimens w and fatigue strength of notched specimen σ wn ;

[0009] (3) Substitute the fatigue strength obtained in step (2) into formula (1) to obtain K in step (1) t Parameter M under value K , and M K Value and corresponding K t The value is fitted using formula (2) to obtain the parameter C;

[0010]

[0011]

[0012] (4) The obtained parameter C is compared with the fatigue strength σ of the smooth specimen w Substituting into formula (3), we can calculate the K t Notch fatigue strength σ wn Predicted value;

[0013]

[0014] In the above step (2), fatigue strength tests of smooth and notched specimens need to be carried out under the same loading conditions; to ensure the accuracy of the prediction results, no less than two groups of notched fatigue strength data can be selected.

[0015] In the above step (3), the parameter value M of the smooth sample is K is 0, and is the same as the notch fatigue M K The values ​​are fitted together by formula (2).

[0016] In the above step (3), the fatigue notch coefficient With K t By formula K f =K t C The parameter value C is obtained by fitting, replacing the above step (3).

[0017] The advantages and beneficial effects of the present invention are as follows:

[0018] 1. This paper combines an in-depth understanding of the nature of fatigue damage, explores the quantitative relationship between fatigue damage of notched components and smooth components, analyzes the influence of stress concentration effect on material fatigue damage, and proposes a new theoretical model of notch fatigue strength.

[0019] 2. The prediction method of the present invention has a single parameter, simple calculation, and high accuracy. It can effectively predict the notch fatigue strength of metal materials under different stress concentration effects with only a small number of fatigue tests, offering advantages such as low cost and high efficiency.

[0020] 3. This invention solves the problem of different Kt The parameters of the present invention can be regarded as material constants, and the same series of metals can be directly obtained at any K t The notch fatigue strength is reduced, which greatly saves costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 For metal materials with different K t Flowchart of the notch fatigue strength prediction method under different conditions.

[0022] Figure 2 The 30CrMnSiA steel in Example 1 has different K t Notch fatigue strength prediction under the following conditions: (a) experimental data K t With M K (b) The relationship between the predicted value and the experimental value.

[0023] Figure 3 The 40CrNi2Si2MoVA steel in Example 2 has different K t Notch fatigue strength prediction under the following conditions: (a) experimental data K t With M K (b) The relationship between the predicted value and the experimental value. DETAILED DESCRIPTION

[0024] The present invention is described in detail below with reference to the accompanying drawings and embodiments.

[0025] Figure 1 The metal material of the present invention has different K t The operation process of the method for predicting fatigue strength under certain conditions is simple and effective, and is described below in conjunction with an embodiment.

[0026] Example 1:

[0027] This embodiment is a t The notch fatigue strength of 30CrMnSiA steel was predicted, and the smooth (K t =1), K t = 3 samples were subjected to high cycle fatigue tests to determine the fatigue strength (experimental data) and used to predict the remaining untested K t =2 and K t = Notch fatigue strength of 4 specimens (verification data).

[0028] Step 1: Through fatigue strength test, the fatigue strength σ of the smooth specimen of 30CrMnSiA steel w is 637.5MPa, K t =3 notch fatigue strength σ wnIt is 241.3MPa, as shown in Table 1.

[0029] Step 2, by formula Calculate K t =1, K t =3M K The values ​​are 0 and 0.621, respectively, corresponding to K t By formula Fitting (such as Figure 2 (a) shows), the parameter C value is obtained to be 0.884.

[0030] Step 3, the obtained parameter C value 0.884 and the fatigue strength σ of the smooth specimen w =637.5MPa substituted into the formula In the above equation, the material can be obtained at different K t Lower fatigue strength σ wn Predicted values ​​(as shown in Table 1).

[0031] Step 4: To verify the accuracy of the predicted data, calculate the predicted K t =2 and K t =4 Deviation of notch fatigue strength of specimen, the deviation value is shown in Table 1, the prediction accuracy is as follows Figure 2 As shown in (b), the prediction deviation is within ±10% (this step is for verification of the method and can be omitted in actual operation).

[0032] Table 1 30CrMnSiA steel at different K t Summary table of forecast-related data for conditions

[0033]

[0034] Example 2:

[0035] This embodiment is a t The notch fatigue strength of 40CrNi2Si2MoVA steel was predicted, and the smooth (K t =1), K t = 3 samples were subjected to high cycle fatigue tests to determine the fatigue strength (experimental data) and used to predict the remaining untested K t =2 and K t =5 notch fatigue strength (verification data).

[0036] Step 1: Through fatigue strength test, the fatigue strength σ of the smooth specimen of 40CrNi2Si2MoVA steel w is 1600MPa, K t =3 fatigue strength σ wn It is 710 MPa, as shown in Table 2.

[0037] Step 2, by formula Calculate K t =1, K t =3M K The values ​​are 0 and 0.556, respectively, corresponding to K t By formula Fitting (such as Figure 3 (a) shows), the parameter C value is obtained to be 0.740.

[0038] Step 3, the obtained parameter C value 0.740 and the fatigue strength σ of the smooth specimen w =1600MPaSubstitute into the formula In the above equation, the material can be obtained at different K t Lower fatigue strength σ wn Predicted values ​​(as shown in Table 2).

[0039] Step 4: To verify the accuracy of the predicted data, calculate the predicted K t =2 and K t =5 Deviation of notch fatigue strength of the specimen, the deviation value is shown in Table 2, the prediction accuracy is as follows Figure 3 As shown in (b), the prediction deviation is within ±5% (this step is for verification of the method and can be omitted in actual operation).

[0040] Table 2 40CrNi2Si2MoVA steel at K t Summary table of forecast-related data for conditions

[0041]

[0042] The above embodiments are merely illustrative of the principles and performance of the present invention and are not exhaustive. People can also obtain other embodiments based on this embodiment without creative work, and these embodiments all fall within the scope of protection of the present invention.

Claims

1. A method for predicting notch fatigue strength of metal materials, characterized by: The method specifically comprises the following steps: (1) Prepare smooth specimens of target metal material and at least one set of notched specimens; the theoretical stress concentration factor K of the smooth specimen is t =1, stress concentration factor K of notched specimen t >1; (2) Fatigue strength test is performed on smooth specimens and notched specimens of target metal materials to obtain the fatigue strength σ of the smooth specimens w and fatigue strength of notched specimen σ wn ; (3) Substitute the fatigue strength obtained in step (2) into formula (1) to obtain K in step (1) t Parameter M when the value K , and M K Value and corresponding K t The value is fitted using formula (2) to obtain the parameter C; (4) The obtained parameter C is compared with the fatigue strength σ of the smooth specimen w Substituting into formula (3), we can calculate the material's K t >1Notch fatigue strength of the specimen σ wn Predicted value; 2. The method for predicting notch fatigue strength of metal materials according to claim 1, characterized in that: In step (2), fatigue strength tests of smooth specimens and notched specimens need to be performed under the same loading conditions; to ensure the accuracy of the prediction results, no less than two groups of notched fatigue strength data can be selected.

3. The method for predicting notch fatigue strength of metal materials according to claim 1, characterized in that: In step (3), the parameter value M of the smooth sample K is 0, and is the same as the notch fatigue M K The values ​​are fitted together by formula (2).

Images