CN115952614A - Bolt head lower fillet rolling process optimization method - Google Patents

Abstract

The invention discloses a bolt head lower fillet rolling process optimization method, which comprises the following steps: obtaining a true stress-strain curve and mechanical property parameters of the bolt material through a tensile test; testing the roughness and fatigue life of the bolts corresponding to the non-rolling process and the different rolling processes; determining a proper grid size and fatigue algorithm by combining ABAQUS and FE-safe simulation, and calculating to obtain the fatigue life of the non-rolled bolt; on the basis, obtaining a residual stress distribution result and a fatigue life of the rolled bolt by ABAQUS and FE-safe simulation calculation, and optimizing and verifying a fatigue life prediction model according to a fatigue life experiment result; analyzing the relation between the fillet rolling process and the fatigue life by using the optimized fatigue life prediction model; and aiming at the bolt structure, selecting a fillet rolling process parameter range, calculating the fatigue life of the bolt after fillet rolling by using a fatigue life prediction model, and selecting a reasonable process parameter range according to the fatigue life.

Description

A method for optimization of bolt head fillet rolling process

technical field

The invention belongs to the technical field of fasteners. The invention considers the effects of fillet rolling on the surface morphology, work hardening and residual stress of bolts, and establishes a method for effectively predicting the fatigue life of bolts after fillet rolling. The control range of the parameters of the bolt fillet rolling process is obtained.

Background technique

Fasteners are widely used, and they have the functions of connection, adjustment and even transmission in mechanical equipment. They are the core basic parts that affect the assembly quality and service life of equipment, and are known as "industrial rice". Bolts are the most widely used fasteners, and fatigue damage is the main cause of their failure. During the service process, the fillet under the head is one of the main stress concentration parts of the bolt, and it is also a high incidence of fatigue fracture. Fillet rolling is the key process of bolt manufacturing, which can significantly improve the fatigue strength of the bolt head shank. The rounded corner rolling under the head can reduce the roughness of the rounded corners, reduce surface defects, cause work hardening of the surface layer and form residual compressive stress, and inhibit the formation and expansion of cracks, thereby greatly improving the fatigue life of the bolt.

The parameters of the fillet rolling process of bolts are complex for the strengthening of bolts. At present, there are few studies on this aspect and they are concentrated on the experimental part, and the numerical simulation analysis is even rarer. In the actual production process, rolling parameters are often determined according to on-site production experience, but the process parameters adopted for workpieces of different specifications and materials have not formed a systematic and standard specification, and many products often choose the same process parameters. Organically linking process-residual stress-fatigue performance has guiding significance for process parameter optimization, product performance improvement and new product process design.

Contents of the invention

At present, the research on the fillet rolling process under the head of bolts is less and mainly based on experiments, and the common fatigue finite element analysis of bolts does not consider the role of initial processing. The invention combines ABAQUS and FE-safe to establish a finite element model of bolt fillet rolling and fatigue, and compares and verifies it with test results, and calculates the fatigue life of bolts under different rolling processes based on the model. In addition to considering the effect of residual stress, the model also introduces factors such as work hardening and surface roughness into the model. At the same time, the mesh size and fatigue algorithm are optimized. Design and optimization provide guidance.

The invention provides a bolt fillet rolling and fatigue finite element model based on ABAQUS and FE-safe to predict the fatigue life before and after bolt rolling, and optimize the bolt fillet rolling process based on this. Its operation is as follows:

The present invention relates to a method for optimizing the rounded corner rolling process under the bolt head, comprising the following steps:

Step 1, take the metal material of the same material and treatment state as the bolt to prepare a standard tensile sample for tensile test, obtain the true stress-strain curve and tensile strength of the corresponding material; use different rolling processes to roll the bolt, and test The roughness of the fillet under the bolt head before and after rolling; the fatigue test is carried out on the bolts without rolling and under different rolling processes, and the fatigue life results of the unrolled bolts and the bolts with different rolling processes are obtained;

Step 2: Establish a geometric model in ABAQUS according to the geometric dimensions of the bolts, define material parameters and mesh division, apply constraints and fatigue loads to the bolts, and use different mesh sizes to solve the stress distribution of unrolled bolts under a cyclic load The finite element result file; the material parameters include elastic modulus, normal temperature tensile stress-strain data, Poisson's ratio, density of the material;

Import the finite element result file obtained by ABAQUS into FE-safe, input the material parameters and add the load spectrum, select Morrow’s modified maximum principal strain algorithm to generate the fatigue life calculation file, and obtain the first simulation result of the fatigue life; In the simulation results, the grid size corresponding to the fatigue life value of the measured fatigue life error value ≤ 10% in step 1 is selected as the grid size of the bolt fillet position, and the establishment of the finite element model for the fatigue analysis of the unrolled bolt is completed; The material parameters input in FE-safe include material type, elastic modulus of material, tensile strength of material, Poisson’s ratio of material, roughness of unrolled bolt;

Step 3: On the bolt grid model obtained in step 2, according to the actual rolling depth, rolling angle and roller fillet radius, a fillet rolling model is established in ABAQUS, and then constraints and fatigue loads are applied to the bolts. The finite element result file of the stress distribution of the rolled bolt under a cyclic load is obtained by solving in ABAQUS;

Import the finite element result file obtained by ABAQUS into FE-safe, consider the work hardening and roughness of the fillet surface, select different fatigue life algorithms to generate the fatigue life calculation file, and solve the fatigue considering the work hardening and roughness of the fillet surface The second simulation result of life; in the second simulation result, the error value of the measured fatigue life of the bolt breaking at the fillet in step 1 is ≤10%, or in the second simulation result, it is selected to be greater than or equal to the bolt at the thread in step 1 The fatigue life algorithm corresponding to the measured fatigue life of the fracture is determined as the fatigue life algorithm of the bolt, and the establishment of the bolt fillet rolling-fatigue analysis finite element model is completed;

Step 4, according to the bolt rolling-fatigue analysis finite element model obtained in step 3, input different rolling process conditions, solve the fatigue life of the bolts under different rolling conditions, select the process conditions, and pass the bolt fillet rolling process Test, test the fatigue life corresponding to different processes, and compare with the calculated value, the error between simulation and test is within 10%, so as to verify and optimize the model;

Step 5, according to the actual bolt specification, through the bolt fillet rolling-fatigue analysis finite element model, determine the optimal fillet rolling process of the bolt.

As a preference, the present invention provides a method for optimizing the fillet rolling process under the bolt head. The tensile test in step 1 is based on the GBT_228.1-2010 standard, the fatigue test is carried out according to the NASM1312-11 standard, and the roughness test method is the sample block comparison method. , the measurement standard is GB/T1031-1995.

The invention discloses a method for optimizing the rolling process of the fillet under the bolt head. The parameters of the rolling process of the bolt are as follows: a rolling force of 800N, a rolling speed of 500rad/s, a rolling time of 2s, and a roller fillet radius of 0.45mm.

As a preference, a method for optimizing the fillet rolling process under the bolt head of the present invention is to establish a geometric model in ABAQUS according to the geometric dimensions of the bolt, define material parameters and mesh division; the material parameters include: modulus of elasticity, tensile strength at room temperature Tensile stress-strain data, Poisson's ratio, density;

Import the finite element result file obtained by ABAQUS into FE-safe, input material parameters and add load spectrum; the material parameters input into FE-safe include material type, elastic modulus, tensile strength, Poisson's ratio, and roughness.

As a preference, in the present invention, a method for optimizing the rounded corner rolling process under the bolt head, the model in steps 2 and 3 is consistent with the size of the sample, and the sample is an M6 type flat head and countersunk head TC4 titanium alloy high-lock bolt, and the mesh at the rounded corner When dividing the grid, the thickness of the grid should not exceed 0.01mm.

In industrial application, in step 2, when the rest of the bolt area is meshed, it is divided based on the global sprinkle point.

As a preference, in the present invention, a method for optimizing the fillet rolling process under the bolt head, in step 2,

The fatigue model expression modified by Morrow is:

In the formula, Δε _t - total strain range; N _f - fatigue life; σ′ _f - fatigue strength coefficient; ε′ _f - fatigue ductility coefficient; b- fatigue strength index; c- fatigue ductility index; E- elastic modulus of material ; σ _m is the mean stress. In the above formula, the tensile strength, Poisson's ratio, and roughness determine the values of σ′ _f , ε′ _f , b, and c.

As a preference, in the present invention, a method for optimizing the rounded corner rolling process under the bolt head, the fatigue criterion selected for the bolt after rolling at the rounded corner in step 3 is the Brown-Miller model, and the fatigue life model expression after Morrow's correction is: :

where Δγ and Δε are the shear strain and normal strain on the critical surface, respectively. In the revised model, the tensile strength, Poisson's ratio, and roughness determine the values of Δγ, Δε, b, and c.

A method for optimizing the rounded corner rolling process under the bolt head according to the present invention, in step 3

Rolling process parameters affect the residual stress at the fillet, work hardening and the size change of the fillet to indirectly affect the fatigue life, such as forging simulation, to study the influence of deformation temperature, deformation speed, mold fatigue size and deformation on forming , there is no direct model expression, and finally the simulation results can only be fitted with an equation to reflect the law.

The invention discloses a method for optimizing the rounded corner rolling process under the bolt head. After optimization, the optimum rolling process for TC4 titanium alloy M6 bolts is as follows: the rolling depth of flat head bolts is 0.02 mm, the rolling angle is 45°, and the rolling angle of countersunk head bolts is 0.02 mm. The pressing depth is 0.45mm, and the rolling angle is 25°. The best rolling radius of the two is 90%-95% of the bolt fillet size.

The invention discloses a method for optimizing the rounded corner rolling process under the bolt head. After optimization, the optimized rolling process for 100° countersunk head bolts of TC4 titanium alloy M6 specifications is as follows: the radius of the rounded corner of the roller is 0.45mm, the rolling angle is 25°, and the rolling angle is 25°. The pressing depth is 0.045mm.

The present invention utilizes ABAQUS and FE-safe to establish bolt fillet rolling and fatigue finite element models and conducts test verification to obtain the relationship between bolt fatigue life and fillet rolling process. By accurately predicting fatigue life, the bolt head lower circle The design and optimization of corner rolling process provides a feasible method, which reduces the lengthy and tedious process test process.

Description of drawings

In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings that need to be used in the description of the embodiments will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present invention. For those skilled in the art, other drawings can also be obtained based on these drawings without creative effort.

Figure 1 is the fatigue calculation flow chart of ABAQUS combined with FE-safe;

Figure 2 shows the effect of the mesh size at the fillet on the fatigue life calculation results when the initial stress of the bolt is zero.

Fig. 3 is the prediction cloud chart of the fatigue life of the bolt in embodiment 1.

Fig. 4 is the fatigue life of flat head bolts under different rolling depths in embodiment 1;

Fig. 5 is the fatigue life of the countersunk bolts at the non-rolling angle in Example 2.

Fig. 6 is the prediction diagram of the fatigue life of the bolt after different rolling angles rolling by the rollers in Example 1;

Fig. 7 is the prediction result diagram of fatigue life of bolts with different rolling depths in embodiment 2;

Fig. 8 is a diagram showing the fatigue life prediction results of bolts after being rolled by rollers at different rolling angles in Example 2;

FIG. 9 is a graph showing the results of fatigue life prediction of bolts after rolling by rollers with different fillet sizes in Example 2. FIG.

Detailed ways

The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without creative efforts fall within the protection scope of the present invention.

Example 1

A process optimization method based on the fatigue life of the bolt after fillet rolling, comprising the following steps:

Step 1: Prepare a standard tensile sample of the same state material as the bolt for tensile test, obtain the corresponding true stress-strain curve and mechanical performance parameters, carry out the bolt fatigue test under non-rolling and different rolling processes, test the rolling roughness before and after pressing, and get the corresponding fatigue life results;

This example takes the TC4 flat-head high-lock bolts of M6 specification as the research object. According to the GBT_228.1-2010 standard, the standard tensile specimen of the annealed Ti-6Al-4V is subjected to solution aging treatment on a computer-controlled electronic universal testing machine. WDW-300 conducts a tensile test (temperature 24°C, relative humidity 50%, deformation speed 2mm/min), and uses the high-precision extensometer (extensometer measuring distance 25mm) that comes with the equipment to record the stress-strain during the stretching process data.

The rolling process parameters of the bolts are rolling force 800N, rolling speed 500rad/s, and rolling time 2s. Use the sample comparison method to estimate the roughness of the fillet surface, and the measurement standard is GB/T1031-1995. The bolt fatigue test is carried out on a fatigue testing machine after assembly according to the NASM1312-11 standard. The maximum fatigue load is about 8676N, the minimum load is 10% of the maximum load, and the loading frequency is 140HZ.

The fatigue test results are shown in Table 1. The fatigue fracture position of the unrolled bolts is all at the lower fillet of the bolt head, and the fracture position of the rolled bolts is all at the thread.

Table 1 Bolt specimen fatigue test results (unit/thousand times)

Step 2: Combining ABAQUS and FE-safe simulation to determine the appropriate mesh size and fatigue algorithm to obtain the fatigue life of unrolled bolts. As shown in Figure 1, according to the geometric shape of the bolt and the fatigue test standard, the geometric model of the bolt is established in ABAQUS and the static analysis of the bolt under fatigue load is completed, and the stress result is imported into FE-safe to calculate the fatigue life, combined with The test results determine the appropriate mesh size at the fillet (where the mesh thickness is not more than 0.01mm) and the fatigue algorithm.

Specifically, the material model parameters involved in ABAQUS include: elastic modulus, normal temperature tensile stress-strain data, Poisson’s ratio, density, and the material model parameters involved in FE-safe include: material type, elastic modulus, tensile strength, Poisson's ratio, roughness. Based on the test results in step 1 and related literature, the stress-strain data of TC4 after solution aging are shown in Table 2, and other parameter settings of the material model are shown in Table 3.

Table 2 True stress-strain data of TC4 quasi-static tensile plastic stage

Table 3 Material model parameters

其中x为圆角处的网格尺寸；Mesh quality is one of the core factors affecting the accuracy of finite element. In order to determine a reasonable mesh size, the influence of mesh size on finite element results is analyzed. When the initial stress of the bolt is zero, a certain load is applied. The influence of the grid size at the fillet on the fatigue calculation (the fatigue life is the minimum value of the predicted fatigue life of the bolt) is shown in Figure 2. The fitting curve equation is:

where x is the grid size at the fillet;

In order to achieve a balance between calculation accuracy and efficiency, and to facilitate subsequent data processing, the size of the mesh at the fillet along the depth direction is selected to be 0.01 mm, and the simulation results have better convergence at this time.

The fatigue criterion selected in step 2 is the maximum principal strain criterion, and the Morrow average stress correction is performed.

The fatigue model expression modified by Morrow is:

In the formula, Δε _t - total strain range; N _f - fatigue life; σ′ _f - fatigue strength coefficient; ε′ _f - fatigue ductility coefficient; b- fatigue strength index; c- fatigue ductility index; E- elastic modulus of material amount; σ _m is the mean stress. In the above formula, the tensile strength, Poisson's ratio, and roughness determine the values of σ′ _f , ε′ _f , b, and c.

The fatigue model is the above formula, which is the criterion for calculating the fatigue life.

The fatigue finite element simulation results of unrolled bolts are shown in Figure 3a. The fatigue fracture position is also at the fillet position, and the minimum fatigue life is 30,000 times. The simulation calculation results are close to the test values, and the reliability of the fatigue simulation model is good.

Step 3: Based on the model in step 2, the complex rolling process is simplified into a two-dimensional rolling model, and the residual stress distribution after rolling and the stress spectrum under fatigue load are obtained in ABAQUS. Combined with ABAQUS and FE-safe simulation to calculate the residual stress and fatigue life of the bolt after rolling, combined with the test results to select the appropriate fatigue algorithm and optimize the model.

On the basis of the model in step 2, the influence of rolling on the shape of the bolt fillet and work hardening is considered. Based on the experimental results of step 1, the roughness of the bolt after rolling is 0.8 μm. According to the work hardening rate of general cold working of titanium alloy, the grid strength of the surface layer of the bolt after rolling is set to 1300 MPa, and the rest of the material parameters are consistent with step 2. The rolling process parameters are rolling depth of 0.02mm, roller fillet radius of 0.45mm, and rolling angle of 45°.

The fatigue fatigue criterion selected for the bolts after fillet rolling in step 3 is the Brown-Miller model, and the Morrow average stress correction is performed.

The fatigue criterion selected for the rolled bolts at the fillet in step 3 is the Brown-Miller model, and the fatigue life model expression after Morrow correction is:

where Δγ and Δε are the shear strain and normal strain on the critical surface, respectively. In the revised model, the tensile strength, Poisson's ratio, and roughness determine the values of Δγ, Δε, b, and c. The fatigue model is the above formula, which is the criterion for calculating the fatigue life. The simulated fatigue life after bolt rolling is 494,000 times (as shown in Figure 3b). Since the influence of threads is not considered in the model, the simulated calculated value is the fatigue life at the fillet. The simulated value of the bolt fillet is greater than the test value, and the actual life of the bolt fillet is also greater than the test value. Therefore, the analysis of the relationship between the fillet rolling process and the fatigue life using this model is reliable.

Step 4: According to the optimized model, the residual stress and fatigue life results of the bolts under different rolling conditions are obtained, and the optimized process parameters are obtained based on the calculation results.

Figure 4 shows the fatigue life prediction of bolts at different rolling depths. As the rolling depth increases, the fatigue life of the bolt increases rapidly, reaching a maximum value of about 494,000 times when the rolling depth is about 0.02mm, and the fatigue life of the bolt is nearly 17 times higher than that before rolling. For the fillet of the bolt. But with the further increase of rolling amount, the fatigue life of bolts decreased rapidly.

Figure 5 shows the prediction results of fatigue life of bolts after roller rolling with different fillet sizes. The fillet radius of the roller is less than 0.4mm, and the fatigue life of the bolt after rolling is less than 100,000 times; when the fillet radius is 0.47mm, the fatigue life reaches the maximum value of about 759,000 times, and the fatigue life of the bolt is nearly 25 times higher than that before rolling ; But the radius of the fillet of the roller increases further, and the fatigue life of the bolt decreases rapidly.

Figure 6 shows the fatigue life prediction of bolts after rolling with different rolling angles. The rolling angle has relatively little effect on the fatigue life of flat-head bolts, and because of the relationship between the rounded corners of the flat-head bolts and the rolling fixture, the rolling angle can only change within a very small range (10°). Therefore, 45° can be the best rolling angle.

According to the above calculation results, the rolling optimization process of TC4 titanium alloy M6 flat-head high-lock bolts is as follows: the radius of the roller fillet is 0.47mm, the rolling angle is 45°, and the rolling depth is 0.02mm. The measured bolt fatigue life is more than 200,000 times.

Example 2

Consistent with the steps in Example 1, a finite element model of M6 size 100° countersunk head TC4 titanium alloy bolt fillet rolling and fatigue was established in combination with ABAQUS, and the optimized range of process parameters was obtained by analyzing the relationship between process parameters and fatigue life through calculation.

Figure 7 shows the prediction results of bolt fatigue life at different rolling depths. As the rolling depth increases, the fatigue life of the bolt increases rapidly and reaches the maximum value when the rolling depth is about 0.045mm; with the further increase of the rolling amount, the fatigue life of the bolt slightly There is a decline. According to processing requirements, the maximum rolling depth at the bolt fillet cannot exceed 0.05mm.

Figure 8 shows the prediction results of fatigue life of bolts after different rolling angles of rollers. As the rolling angle increases, the fatigue life of the bolt first increases and then decreases and reaches the maximum when the rolling angle is 25°.

Figure 9 shows the prediction results of fatigue life of bolts after roller rolling with different fillet sizes. In the range of 0.2mm-0.45mm, the fatigue life of the bolt increases exponentially with the increase of the fillet radius of the roller.

According to the above calculation results, the rolling optimization process of TC4 titanium alloy M6 specification 100° countersunk head bolts is as follows: the radius of the roller fillet is 0.45mm, the rolling angle is 25°, and the rolling depth is 0.045mm. The measured bolt fatigue life is more than 200,000 times.

The above-mentioned embodiments are only examples for clearly illustrating the present invention, rather than limiting the implementation. For those of ordinary skill in the art, other changes or changes in different forms can be made on the basis of the above description. It is not necessary and impossible to exhaustively list all the embodiments here. However, the obvious changes or variations derived therefrom are still within the protection scope of the present invention.

Claims (8)

1. A method for optimizing the fillet rolling process under the bolt head, is characterized in that, comprises the steps: Step 1, take the metal material of the same material and treatment state as the bolt to prepare a standard tensile sample for tensile test, obtain the true stress-strain curve and tensile strength of the corresponding material; use different rolling processes to roll the bolt, and test The roughness of the fillet under the bolt head before and after rolling; the fatigue test is carried out on the bolts without rolling and under different rolling processes, and the fatigue life results of the unrolled bolts and the bolts with different rolling processes are obtained; Step 2: Establish a geometric model in ABAQUS according to the geometric dimensions of the bolts, define material parameters and mesh division, apply constraints and fatigue loads to the bolts, and use different mesh sizes to solve the stress distribution of unrolled bolts under a cyclic load The finite element result file; the material parameters include elastic modulus, normal temperature tensile stress-strain data, Poisson's ratio, density of the material; Import the finite element result file obtained by ABAQUS into FE-safe, input the material parameters and add the load spectrum, select Morrow’s modified maximum principal strain algorithm to generate the fatigue life calculation file, and obtain the first simulation result of the fatigue life; In the simulation results, select the grid size corresponding to the fatigue life value of the measured fatigue life error value ≤ 10% in step 1 as the grid size of the bolt fillet position, and complete the establishment of the finite element grid model for fatigue analysis of unrolled bolts ;The material parameters input in FE-safe include material type, elastic modulus of material, tensile strength of material, Poisson's ratio of material, roughness of unrolled bolt; Step 3: On the bolt grid model obtained in step 2, according to the actual rolling depth, rolling angle and roller fillet radius, a fillet rolling model is established in ABAQUS, and then constraints and fatigue loads are applied to the bolts. The finite element result file of the stress distribution of the rolled bolt under a cyclic load is obtained by solving in ABAQUS; Import the finite element result file obtained by ABAQUS into FE-safe, consider the work hardening and roughness of the fillet surface, select different fatigue life algorithms to generate the fatigue life calculation file, and solve the fatigue considering the work hardening and roughness of the fillet surface The second simulation result of life; in the second simulation result, the error value of the measured fatigue life of the bolt breaking at the fillet in step 1 is ≤10%, or in the second simulation result, it is selected to be greater than or equal to the bolt at the thread in step 1 The fatigue life algorithm corresponding to the measured fatigue life of the fracture is determined as the fatigue life algorithm of the bolt, and the establishment of the bolt fillet rolling-fatigue analysis finite element model is completed; Step 4, according to the bolt fillet rolling-fatigue analysis finite element model obtained in step 3, input different rolling process conditions, solve the fatigue life of the bolts under different rolling conditions, select the process conditions, and roll through the bolt fillet Compression process test, test the fatigue life corresponding to different processes, and compare with the calculated value, the error between simulation and test is within 10%, so as to verify and optimize the model; Step 5, according to the actual bolt specifications, through the bolt fillet rolling-fatigue analysis finite element model obtained in step 4, determine the optimal bolt fillet rolling process. 2. A method for optimizing the fillet rolling process under the bolt head according to claim 1, characterized in that: the tensile test in step 1 is based on the GBT_228.1-2010 standard, the fatigue test is carried out according to the NASM1312-11 standard, and the rough The testing method of the test is the block comparison method, and the measurement standard is GB/T1031-1995. 3. A method for optimizing the rounded corner rolling process under the bolt head according to claim 1, characterized in that: the rolling process parameters of the bolt are rolling force 800N, rolling speed 500rad/s, rolling time 2s, rolling time The fillet radius is 0.45mm. 4. A method for optimizing the fillet rolling process under the bolt head according to claim 1, characterized in that: The size of the model in steps 2 and 3 is the same as that of the sample. The sample is an M6-type flat head and countersunk head TC4 titanium alloy high-lock bolt. When the fillet is meshed, the mesh thickness should not exceed 0.01mm. 5. A method for optimizing the fillet rolling process under the bolt head according to claim 1, characterized in that: in step 2, The fatigue model expression modified by Morrow is:

where Δε _t is the total strain range; N _f is the fatigue life; σ′ _f is the fatigue strength coefficient; ε′ _f is the fatigue ductility coefficient; b is the fatigue strength index; c is the fatigue ductility index; E is the elastic modulus of the material ; σ _m is the average stress, where σ′ _f , ε′ _f , b, c are parameters automatically calculated and determined by FE-safe according to the material model parameters; the material model parameters include the tensile strength of the material, Poisson’s ratio, roughness Spend. 6. A method for optimizing the fillet rolling process under the bolt head according to claim 1, characterized in that: The fatigue criterion selected for the rolled bolts at the fillet in step 3 is the Brown-Miller model, and the fatigue life model expression after Morrow correction is:

where Δγ and Δε _n are the shear strain and normal strain on the critical surface, respectively. 7. A method for optimizing the rolling process of rounded corners under the bolt head according to claim 1, characterized in that: the optimal rolling process for TC4 titanium alloy M6 bolts is: the rolling depth of flat-head bolts is 0.02mm, and the rolling angle 45°, the rolling depth of countersunk head bolts is 0.45mm, and the rolling angle is 25°. The best rolling radius of the two is 90%-95% of the bolt fillet size. 8. A method for optimizing the rolling process of the fillet under the bolt head according to claim 1, characterized in that: the rolling optimization process of the TC4 titanium alloy M6 specification 100° countersunk head bolt is: the radius of the fillet of the roller is 0.45mm , Rolling angle 25°, rolling depth 0.045mm.

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