CN113848116A - Workpiece service life prediction method based on machined surface layer fatigue model - Google Patents

Workpiece service life prediction method based on machined surface layer fatigue model Download PDF

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CN113848116A
CN113848116A CN202111081596.9A CN202111081596A CN113848116A CN 113848116 A CN113848116 A CN 113848116A CN 202111081596 A CN202111081596 A CN 202111081596A CN 113848116 A CN113848116 A CN 113848116A
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surface layer
microcrack
crack
fatigue life
tip
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陈明
俞威威
安庆龙
明伟伟
刘公雨
马海善
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Jiangsu Haibo Tool Industry Research Institute Co ltd
Shanghai Jiaotong University
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Jiangsu Haibo Tool Industry Research Institute Co ltd
Shanghai Jiaotong University
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N3/00—Investigating strength properties of solid materials by application of mechanical stress
    • G01N3/08—Investigating strength properties of solid materials by application of mechanical stress by applying steady tensile or compressive forces
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N3/00—Investigating strength properties of solid materials by application of mechanical stress
    • G01N3/40—Investigating hardness or rebound hardness
    • G01N3/42—Investigating hardness or rebound hardness by performing impressions under a steady load by indentors, e.g. sphere, pyramid
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2203/00—Investigating strength properties of solid materials by application of mechanical stress
    • G01N2203/0001—Type of application of the stress
    • G01N2203/0003—Steady
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2203/00—Investigating strength properties of solid materials by application of mechanical stress
    • G01N2203/0014—Type of force applied
    • G01N2203/0016—Tensile or compressive
    • G01N2203/0017—Tensile
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2203/00—Investigating strength properties of solid materials by application of mechanical stress
    • G01N2203/0014—Type of force applied
    • G01N2203/0016—Tensile or compressive
    • G01N2203/0019—Compressive
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2203/00—Investigating strength properties of solid materials by application of mechanical stress
    • G01N2203/0058—Kind of property studied
    • G01N2203/006—Crack, flaws, fracture or rupture
    • G01N2203/0062—Crack or flaws
    • G01N2203/0066—Propagation of crack
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2203/00—Investigating strength properties of solid materials by application of mechanical stress
    • G01N2203/0058—Kind of property studied
    • G01N2203/0069—Fatigue, creep, strain-stress relations or elastic constants
    • G01N2203/0073—Fatigue
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2203/00—Investigating strength properties of solid materials by application of mechanical stress
    • G01N2203/0058—Kind of property studied
    • G01N2203/0076—Hardness, compressibility or resistance to crushing
    • G01N2203/0078—Hardness, compressibility or resistance to crushing using indentation
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2203/00—Investigating strength properties of solid materials by application of mechanical stress
    • G01N2203/02—Details not specific for a particular testing method
    • G01N2203/06—Indicating or recording means; Sensing means
    • G01N2203/067—Parameter measured for estimating the property
    • G01N2203/0676—Force, weight, load, energy, speed or acceleration
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2203/00—Investigating strength properties of solid materials by application of mechanical stress
    • G01N2203/02—Details not specific for a particular testing method
    • G01N2203/06—Indicating or recording means; Sensing means
    • G01N2203/067—Parameter measured for estimating the property
    • G01N2203/0682—Spatial dimension, e.g. length, area, angle

Abstract

A coupling multi-integrity index-based method for predicting fatigue life of a processed surface layer is characterized in that the effective load of a component is modeled through a maximum depth reference for measuring the life of the surface layer; and establishing an effective crack length model according to the size of the tip plastic region, establishing the correlation between the surface layer microstructure and the fatigue life of the surface layer microstructure, and obtaining a microcrack propagation threshold value and a processed surface layer fatigue life prediction model according to the crack tip plastic induced closure effect. The method can quantitatively predict the influence degree of integrity indexes of different processing surfaces on the fatigue life of the surface layer. The model is expected to greatly reduce the workload of fatigue tests, has stronger pertinence to the fatigue performance evaluation of the surface layer, and ensures that the evaluation processing technology has more direct effect on the fatigue performance.

Description

Workpiece service life prediction method based on machined surface layer fatigue model
Technical Field
The invention relates to the technology in the field of machining, in particular to a workpiece service life prediction method based on a machined surface layer fatigue model.
Background
The fatigue failure of the component directly threatens the service safety, reliability and economy of mechanical equipment and engineering components, and is a long-standing problem in the field of domestic and foreign mechanical engineering. The fatigue damage of key components can easily cause catastrophic accidents, and cause serious personal casualties and property loss. In the fatigue life composition of components in the field of mechanical engineering, the crack initiation life is usually far longer than the propagation life, and the percentage of the total life can reach 70-80%. Therefore, if the surface/subsurface state of the component can be actively regulated and controlled, the fatigue crack initiation is inhibited, and the method has great significance for enhancing the fatigue performance of the component and prolonging the service life of the component.
The existing method for evaluating the fatigue performance of a component containing different processed surface layers generally adopts a fatigue life evaluation strategy which takes macroscopic fracture failure as a life measurement cut-off criterion. However, this method is not suitable for evaluating the fatigue properties of the machined surface layer. For the evaluation of the fatigue performance of the machined surface layer, related research is not yet developed, and an applicable fatigue life prediction model of the machined surface layer is to be established.
Disclosure of Invention
Aiming at the defects in the prior art, the invention provides a processing surface layer fatigue life prediction method based on coupling multiple integrity indexes, which can quantitatively predict the influence degree of different processing surface integrity indexes on the surface layer fatigue life. The model is expected to greatly reduce the workload of fatigue tests, has stronger pertinence to the fatigue performance evaluation of the surface layer, and ensures that the evaluation processing technology has more direct effect on the fatigue performance.
The invention is realized by the following technical scheme:
the invention relates to a workpiece service life prediction method based on a fatigue model of a processed surface layer, which models the effective load of a component through a maximum depth reference for measuring the service life of the surface layer; and establishing an effective crack length model according to the size of the tip plastic region, establishing the correlation between the surface layer microstructure and the fatigue life of the surface layer microstructure, and obtaining a microcrack propagation threshold value and a processed surface layer fatigue life prediction model according to the crack tip plastic induced closure effect.
The maximum depth is 1000 μm and is recorded as lthAnd the influence of different milling processes on the fatigue life of the surface layer is compared.
The modeling of the payload of the component means: stress is applied to the tip of a microcrack with a length l and the effective stress sigma after residual stress action is containedeff(l)＝σreal+σres(l) Wherein: sigmareal+σres(l)＜σs，σrealFor the actual applied stress, σres(l) Is the residual stress, σ, in the surface layer at a distance l from the surfacesIs the yield strength of the material.
The effective crack length model is established by the following steps:
Figure BDA0003264178170000021
wherein: l is the microcrack length, leffEffective length of microcracks, KsStress intensity factor, σ, of microcrack tipsEquivalent initial microcrack length l as machined surface for yield strength limit of material0Less than lthThe cracks will grow according to the propagation law of microcracks. Since the size of the microcracks is very small, the plastic zone extent of the microcrack tips caused by stress concentration reaches the same order of magnitude as their own size and is therefore not negligible.
According to the study by Dugdale et al in the paper (dying of steel sheets contacting sheets), the effective length of the microcracks is transformed into:
Figure BDA0003264178170000022
wherein: l is the microcrack length, leffEffective length of microcracks, σsThe yield strength of the local area at the tip of the crack.
The correlation between the surface layer microstructure and the fatigue life thereof is as follows: introducing the mechanical performance index for the microstructure of the surface layer to be processed, namely the microhardness H (l) into a fatigue life model:
Figure BDA0003264178170000023
wherein: the stress intensity factor range of the microcrack tip under the action of cyclic load is
Figure BDA0003264178170000024
The microhardness H and the yield strength sigmasSatisfy H ═ C σsWherein: the parameter C corresponds to 4.22 of the Ti6Al4V titanium alloy base material.
And the parameter C is obtained by calculating the value C when the microhardness of the matrix material is about 3.8GPa (130-degree diagonal diamond rectangular pyramid pressure head, the load is 10mN, the load retention time is 2s) and the yield strength is about 900MPa through a nano indentation test and a static tensile test.
The fatigue life prediction model of the processed surface layer
Figure BDA0003264178170000025
Wherein:
Figure BDA0003264178170000026
Figure BDA0003264178170000027
ΔKthSClothe micro-crack propagation threshold value of the crack tip plasticity induction closing effect is considered;
Figure BDA0003264178170000028
σFLimis the fatigue strength limit of the material, Δ KthLIs the macrocrack expansion threshold value and the maximum stress intensity factor of the materialSeed of Japanese apricot
Figure BDA0003264178170000029
Figure BDA00032641781700000210
CSIs the material constant, mSIs the slope of the crack propagation rate curve, nSIs the coefficient of influence, k, of the stress intensity factorSIs a parameter whose degree of crack closure varies with crack propagation, KICIs the fracture toughness of the material, the range of the stress intensity factor Delta KSIs the driving factor for promoting the micro-crack to spread, and the retardation factor for inhibiting the micro-crack to spread is the crack spreading threshold value delta KthSThe size of which is related to the length of the microcracks and the metallurgical structure of the material.
Technical effects
The invention integrally solves the technical problem that the fatigue life of the processed surface layer cannot be predicted in the prior art. Compared with the prior art, the fatigue life of the machined surface layer of the component is stripped from the traditional overall fatigue life evaluation method through the fatigue life prediction model of the machined surface layer, and the influence degree of integrity indexes of different machined surfaces on the fatigue life of the surface layer can be predicted quantitatively through the model. Compared with the traditional method of analyzing the influence of different processing technologies (actually different processing surface integrity configurations) on the fatigue life by developing a conventional fatigue test and testing the overall fatigue life of a sample piece or a structural member, the method provided by the invention greatly reduces the cost of manpower and material resources and improves the efficiency.
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FIG. 1 is a flow chart of the present invention.
Detailed Description
As shown in fig. 1, the present embodiment relates to a workpiece life prediction method based on a fatigue model of a machined surface layer, modeling a payload of a component by a maximum depth reference for measuring a life of the surface layer; establishing an effective crack length model according to the size of a tip plastic region, establishing a correlation between a surface layer microstructure and the fatigue life of the surface layer microstructure, obtaining a microcrack propagation threshold value according to a crack tip plastic induced closure effect, and obtaining a processed surface layer fatigue life prediction model, wherein the method specifically comprises the following steps:
step 1-1: the principle for setting the maximum depth reference of the surface layer is that the surface layer can cover the real modified zone depth of all the surface layers to be researched and processed, and the depth is small as much as possible. In the embodiment, the depth of the surface layer is set to be 1000 μm in a unified manner and recorded as lth, so as to compare the influence of different milling processes on the fatigue life of the surface layer. It is worth to be noted that the national standard 'test method for the small fatigue crack growth rate of metal material' also indicates that the component subsurface layer belongs to a crack growth zone within the range of 1000 μm, so that the theory of crack growth is applied; and when the crack length is more than 1000 mu m, entering a macrocrack expansion stage, wherein the expansion rate conforms to the conventional macrocrack growth rule.
Step 2-1: the payload is mainly related to the magnitude of the actual external load and the residual stress of the surface layer. The retarding effect of residual stress on fatigue crack propagation varies with the magnitude of the peak stress of the external load. Under a small external load stress, namely a high cycle fatigue mode, the component only generates elastic deformation macroscopically, and the residual stress forms a superposition effect on the external load to jointly influence the expansion of the crack tip. According to the above analysis, the stress is applied externally at the tip of a microcrack of length l and contains the effective stress sigma after the action of residual stresseff(l)＝σreal+σres(l),ifσreal+σres(l)＜σsWherein: sigmarealIs the actual external load stress, σres(l) Is the residual stress, σ, in the surface layer at a distance l from the surfacesIs the yield strength of the material.
Step 3-1: equivalent initial microcrack length l as machined surface0Less than lthAt this time, the cracks will grow according to the propagation law of microcracks. Since the size of the microcracks is very small, the plastic zone extent of the microcrack tips caused by stress concentration reaches the same order of magnitude as their own size and is therefore not negligible. This example is based on the effective crack length considering the tip plasticity zone size proposed by Irwin in the article (Closure to "cleavage of 'Fracture Mode Transition for a CrackTracering a Plate'")Model (model)
Figure BDA0003264178170000031
Wherein: l is the microcrack length, leffIs the effective length of the microcracks, KsIs the stress intensity factor, σ, of the microcrack tipsIs the yield strength limit of the material. According to the study of Dugdale et al in the thesis (dying of steel sheets relating sheets), the above formula can be transformed into:
Figure BDA0003264178170000041
the right side of the above equation contains the yield strength term σsIt refers to the yield strength of the local area of the crack tip.
Step 4-1: in order to establish the correlation between the surface layer microstructure and its fatigue life, the micro-hardness h (l), which is an index for characterizing the mechanical properties of the surface layer microstructure, may be introduced into the fatigue life model. The microstructure state of the material determines the magnitude of its microhardness. In general, the microhardness H of a material is related to its yield strength σsClosely related, the relationship between the two can be approximately expressed by: h ═ C σs
Step 4-2: to determine the magnitude of C, this example obtained a microhardness of about 3.8GPa (130 ° diagonal diamond pyramid indenter, load 10mN, dwell time 2s) and a yield strength of about 900MPa by performing a nanoindentation test and a static tensile test on a Ti6Al4V titanium alloy base material, from which a C value of 4.22 was given. For σ in the above formulasAfter substitution, the following results:
Figure BDA0003264178170000042
the stress intensity factor range of the microcrack tip under cyclic loading is:
Figure BDA0003264178170000043
step 5-1: stress intensity factor range Δ KSIs a driving factor for promoting the micro-crack propagation, and a retardation factor for inhibiting the micro-crack propagation is a crack propagation threshold value delta KthSThe size of which is related to the length of the microcracks and the metallurgical structure of the material. It should be noted that, for a macrocrack, the stress field at the tip of the crack can better follow the linear elastic mechanics law, and therefore the expansion threshold value is generally a constant; for microcracks, the crack propagation threshold is a variable related to the crack length and is closely related to the fatigue strength limit of the material. A number of experiments were carried out earlier in Haddad et al in the paper (Prediction of non-propagating cracks) to give a threshold value for microcrack propagation Δ KthSThe semi-empirical equation of (c):
Figure BDA0003264178170000044
wherein: sigmaFLimIs the fatigue strength limit of the material, Δ KthLIs the macrocracks propagation threshold of the material.
Step 5-2: aiming at the expansion rate of the microcrack, by comprehensively considering the characteristics that the size of a plastic region at the tip of the fatigue microcrack is close to the length scale of the microcrack, the closure level of the microcrack changes along with the expansion of the microcrack, the expansion of the microcrack is strongly controlled by the fatigue strength limit and the like, which are obviously different from the expansion of the macrocrack, on the basis of a classical Chapetti model, a correction model with wider applicability can be obtained:
Figure BDA0003264178170000045
Figure BDA0003264178170000046
wherein: Δ KthSCloThe micro-crack propagation threshold value of the crack tip plasticity induction closing effect is considered; maximum stress intensity factor
Figure BDA0003264178170000051
CSIs the material constant, mSIs the slope of the crack propagation rate curve, nSIs the coefficient of influence, k, of the stress intensity factorSIs a parameter whose degree of crack closure varies with crack propagation, KICIs the fracture toughness of the material.
Step 6-1: on the basis of the model, the fatigue life prediction model of the machined surface layer is as follows:
Figure BDA0003264178170000052
the foregoing embodiments may be modified in many different ways by those skilled in the art without departing from the spirit and scope of the invention, which is defined by the appended claims and all changes that come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein.

Claims (8)

1. A coupling multi-integrity index-based method for predicting the fatigue life of a processed surface layer is characterized in that the effective load of a component is modeled through a maximum depth reference for measuring the life of the surface layer; establishing an effective crack length model according to the size of a tip plastic region, establishing a correlation between a surface layer microstructure and the fatigue life of the surface layer microstructure, obtaining a microcrack propagation threshold value according to a crack tip plastic induced closure effect, and obtaining a processed surface layer fatigue life prediction model;
the fatigue life prediction model of the processed surface layer
Figure FDA0003264178160000011
Wherein: l0＜lth，
Figure FDA0003264178160000012
Figure FDA0003264178160000013
ΔKthSCloA microcrack propagation threshold value for considering a crack tip plasticity induced closure effect;
Figure FDA0003264178160000014
σFLimΔ K, the fatigue strength limit of a materialthLIs the macrocrack propagation threshold value and the maximum stress intensity factor of the material
Figure FDA0003264178160000015
Figure FDA0003264178160000016
CSIs the material constant, mSFor the slope of the crack propagation rate curve, nSIs the influence coefficient of the stress intensity factor, kSA parameter for which the degree of crack closure varies with crack propagation, KICThe range of the stress intensity factor Delta K is the fracture toughness of the materialSThe driving factor for promoting the micro-crack propagation and the retarding factor for inhibiting the micro-crack propagation are the crack propagation threshold value delta KthS。
2. The coupled multiple integrity indicator based machined surface layer fatigue life prediction method of claim 1, wherein said modeling a payload of a component is: stress is applied to the tip of a microcrack with a length l and the effective stress sigma after residual stress action is containedeff(l)＝σreal+σres(l) Wherein: sigmareal+σres(l)＜σs，σrealFor the actual applied stress, σres(l) Is the residual stress, σ, in the surface layer at a distance l from the surfacesIs the yield strength of the material.
3. The coupled multiple integrity indicator-based method for predicting fatigue life of a machined surface layer as claimed in claim 1, wherein said establishing an effective crack length model comprises:
Figure FDA0003264178160000017
wherein: l is the microcrack length, leffEffective length of microcracks, KsStress intensity factor, σ, of microcrack tipsEquivalent initial microcrack length l as machined surface for yield strength limit of material0Less than lthThe cracks will grow according to the propagation law of microcracks.
4. The coupled multiple integrity indicator based method of predicting fatigue life of a machined surface layer as claimed in claim 1, wherein said effective length of said microcracks is transformed to:
Figure FDA0003264178160000018
wherein: l is the microcrack length, leffEffective length of microcracks, σsThe yield strength of the local area at the tip of the crack.
5. The method for predicting fatigue life of processed surface layer based on coupled multiple integrity indicators as claimed in claim 1, wherein the correlation between the microstructure of the surface layer and the fatigue life thereof is: introducing the mechanical performance index for the microstructure of the surface layer to be processed, namely the microhardness H (l) into a fatigue life model:
Figure FDA0003264178160000021
wherein: the stress intensity factor range of the microcrack tip under the action of cyclic load is
Figure FDA0003264178160000022
6. The method as claimed in claim 1, wherein the microhardness H and yield strength σ are measured by a computersSatisfy H ═ C σsWherein: the parameter C corresponds to 4.22 of the Ti6Al4V titanium alloy base material.
7. The method for predicting the fatigue life of a processed surface layer based on the coupled multiple integrity indexes as claimed in claim 1, wherein the parameter C is calculated to obtain a value C when the microhardness of the base material is about 3.8GPa (130-degree diagonal diamond rectangular pyramid pressure head with a load of 10mN and a load-holding time of 2s) and the yield strength is about 900MPa through a nano indentation test and a static tensile test.
8. The method for predicting the fatigue life of the processed surface layer based on the coupled multiple integrity indexes as claimed in any one of claims 1 to 7, which is characterized by comprising the following steps:
step 1-1: the given principle of the maximum depth reference of the surface layer is that the surface layer can cover the real modified zone depth of all the surface layers to be researched and processed, and a small value is measured as much as possible; in the embodiment, the depth of the surface layer is temporarily set to be 1000 μm in a unified reference and recorded as lth, so as to compare the influence of different milling processes on the fatigue life of the surface layer;
step 2-1: stress is externally loaded at the tip of a microcrack with the length l and the effective stress sigma after the action of residual stress is containedeff(l)＝σreal+σres(l),ifσreal+σres(l)＜σsWherein: sigmarealIs the actual external load stress, σres(l) Is the residual stress, σ, in the surface layer at a distance l from the surfacesIs the yield strength of the material;
step 3-1: equivalent initial microcrack length l as machined surface0Less than lthThen, the crack will grow according to the expansion rule of the microcrack; the size of the microcrack is very small, and the plastic area range of the microcrack tip caused by stress concentration reaches the same order of magnitude as the size of the microcrack tip, so that the size of the plastic area range cannot be ignored; effective crack length model based on consideration of tip plastic zone size
Figure FDA0003264178160000023
Wherein: l is the microcrack length, leffIs the effective length of the microcracks, KsIs the stress intensity factor, σ, of the microcrack tipsIs the yield strength limit of the material, the formula further transforms to:
Figure FDA0003264178160000024
the right side of the above equation contains the yield strength term σsIt refers to the yield strength of the local area at the tip of the crack;
step 4-1: to build up a surface layerThe correlation between the microstructure and the fatigue life thereof can introduce the mechanical performance index, namely microhardness H (l), of the microstructure of the surface layer of the definite machining into a fatigue life model; the microstructure state of the material determines the microhardness of the material, namely H ═ C sigma is satisfiedsWherein: the microhardness of the material is H, and the yield strength is sigmas；
Step 4-2: carrying out a nano indentation test and a static tensile test on a Ti6Al4V titanium alloy base material to obtain the microhardness of the base material, wherein the yield strength is about 900MPa, and the C value is set to be 4.22; for σ in the above formulasAfter substitution, the following results:
Figure FDA0003264178160000031
the stress intensity factor range of the microcrack tip under cyclic loading is:
Figure FDA0003264178160000032
step 5-1: stress intensity factor range Δ KSIs a driving factor for promoting the micro-crack propagation, and a retardation factor for inhibiting the micro-crack propagation is a crack propagation threshold value delta KthSAccording to the threshold value of microcrack propagation Δ KthSThe semi-empirical equation of (c):
Figure FDA0003264178160000033
wherein: sigmaFLimIs the fatigue strength limit of the material, Δ KthLIs the macrocracks propagation threshold of the material;
step 5-2: for the propagation rate of the microcracks, a more broadly applicable correction model is obtained:
Figure FDA0003264178160000034
wherein: Δ KthSCloThe micro-crack propagation threshold value of the crack tip plasticity induction closing effect is considered; maximum stress intensity factor
Figure FDA0003264178160000035
CSIs the material constant, mSIs the slope of the crack propagation rate curve, nSIs the coefficient of influence, k, of the stress intensity factorSIs a parameter whose degree of crack closure varies with crack propagation, KICIs the fracture toughness of the material;
step 6-1: on the basis of the model, the fatigue life prediction model of the machined surface layer is as follows:
Figure FDA0003264178160000036
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Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103526140A (en) * 2013-10-12 2014-01-22 中南大学 Heat treatment method for improving fatigue resistance of Al-Cu-Mg alloy
CN109142049A (en) * 2018-07-24 2019-01-04 北京工业大学 A kind of Prediction method for fatigue life based on crackle spreading rate model
CN110705131A (en) * 2019-10-31 2020-01-17 上海交通大学 Mechanical component service life prediction method based on high cycle fatigue of machined surface layer
US20200394347A1 (en) * 2019-06-12 2020-12-17 Sichuan University Method for assessing fatigue damage and fatigue life based on abaqus
CN112257221A (en) * 2020-08-31 2021-01-22 南京航空航天大学 Method for calculating matrix crack propagation rate of metal matrix composite under spectral loading

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103526140A (en) * 2013-10-12 2014-01-22 中南大学 Heat treatment method for improving fatigue resistance of Al-Cu-Mg alloy
CN109142049A (en) * 2018-07-24 2019-01-04 北京工业大学 A kind of Prediction method for fatigue life based on crackle spreading rate model
US20200394347A1 (en) * 2019-06-12 2020-12-17 Sichuan University Method for assessing fatigue damage and fatigue life based on abaqus
CN110705131A (en) * 2019-10-31 2020-01-17 上海交通大学 Mechanical component service life prediction method based on high cycle fatigue of machined surface layer
CN112257221A (en) * 2020-08-31 2021-01-22 南京航空航天大学 Method for calculating matrix crack propagation rate of metal matrix composite under spectral loading

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