A method for predicting low-cycle fatigue life of metastable austenitic dual-phase steel

Abstract

The present invention relates to a method for predicting the low cycle fatigue life of metastable austenitic dual-phase steel, comprising: S1, calculating the elastic strain energy density ΔW through low cycle fatigue test data; e , plastic strain energy density ΔW' p , and calculate the total strain energy density ΔW' t and strain energy density ratio Q; S2, construct a low-cycle fatigue life prediction model for metastable austenitic dual-phase steel; S3, calculate the parameters of the low-cycle fatigue life prediction model for metastable austenitic dual-phase steel; S4, use the low-cycle fatigue life prediction model to predict fatigue life. The present invention takes into account the influence of martensite generated during cyclic loading of metastable austenitic dual-phase steel on fatigue crack propagation. From an energy perspective, the martensite generated during cyclic loading will affect both elastic strain energy and plastic strain energy. The present invention takes into account the strain ratio R and equivalent stress σ eq The impact on fatigue life, fatigue life prediction model prediction is more accurate.

Description

Technical Field

[0001] The present invention relates to the technical field of fatigue life prediction of metal materials, and in particular to a method for predicting the low-cycle fatigue life of metastable austenitic dual-phase steel. Background Art

[0002] Metals hold a crucial position among engineering materials due to their excellent combination of strength and toughness. Fatigue failure is a major failure mode faced by these materials. Therefore, the evaluation, prediction, and optimization of metal fatigue performance have become critical disciplines for ensuring the long-term service safety of engineering components under cyclic loading. As machinery evolves toward higher temperatures, higher speeds, and larger sizes, mechanical stresses are increasing, operating conditions are becoming increasingly harsh, and fatigue failures are becoming increasingly common. For example, fatigue failure accounts for 50% to 90% of the failures of many mechanical components and structures, such as shafts, crankshafts, connecting rods, gears, springs, bolts, pressure vessels, offshore platforms, turbine blades, and welded structures. Therefore, structural components and systems subjected to cyclic loading require the highest possible reliability in fatigue life assessment. Fatigue strength is crucial not only in cutting-edge industries such as aerospace, aviation, shipbuilding, and nuclear power, but is also a key factor influencing the reliability and service life of general mechanical products. Therefore, research on fatigue strength is imperative for my country's machinery industry.

[0003] Considering the huge application prospects of metastable austenitic dual-phase steel and the ability of its structural parts to bear repeated loads during service, its low-cycle fatigue behavior is worthy of attention. The relevant research on the fatigue properties of metal materials has a long history. Among them, the measurement, evaluation and prediction of fatigue damage resistance are important branches that are directly related to the fatigue resistance design and application of materials. Based on the cycle life, the most widely used classical theories for measuring fatigue damage include the stress-life method represented by the Basquin formula and the strain-life method represented by the Coffin-Manson formula: the former measures fatigue damage by the size of the cyclic stress amplitude, and is usually used for cycles greater than 10. 4 High cycle fatigue (HCF) of cyc; the latter measures fatigue damage by cyclic plastic strain amplitude and is mostly used for cycles less than 10 4 cyc low-cycle fatigue (LCF). These methods are all based on actual engineering data, with simple formulas, easy operation, and a good application background. However, the mismatch between the stress amplitude and strain amplitude measurement results of material fatigue performance evaluation reveals an inconsistency between the two. In this case, the material fatigue optimization direction obtained by selecting different measurement standards often contradicts each other. Therefore, how to achieve an objective and unified evaluation of the fatigue performance of metal materials, and further realize prediction and optimization, will become a key technical issue that needs to be addressed in material fatigue research.

[0004] For metastable austenitic dual-phase steels, deformation-induced martensite influences crack initiation and propagation during cyclic loading to fatigue at a given strain amplitude. Numerous studies have demonstrated that martensite formation during cyclic loading strongly influences the fatigue mechanical behavior of various steel types. First, at high strain amplitudes (>0.9%), the number of nucleation sites for martensite increases, and the increased martensite formation also leads to more crack initiation sites in fatigue specimens. Furthermore, deformation-induced martensite acts as an elastic reinforcing phase (i.e., a composite material) in metastable austenitic dual-phase steels. As loading continues, the martensite transformation affects the strain increment, resulting in a composite microstructure that alters crack paths and local mechanical properties, thereby affecting low-cycle fatigue life. Furthermore, deformation-induced martensite formation is accompanied by volume expansion. During the austenite-to-martensite transformation, the compressive stress generated by this volume expansion and energy absorption delays crack initiation and propagation by gradually strengthening and toughening the material. Finally, the induced α′-martensite causes a compressive residual stress field and extensive crack closure, which also leads to a decrease in the fatigue crack growth rate (FCGR), which also affects the low-cycle fatigue life. Summary of the Invention

[0005] The purpose of the present invention is to provide a method for predicting the low cycle fatigue life of metastable austenitic dual-phase steel, which can effectively solve the problems of complicated prediction process, long time consumption and high cost in the previous low cycle fatigue life prediction.

[0006] The technical solution adopted in the present invention is as follows:

[0007] The present invention proposes a method for predicting the low-cycle fatigue life of metastable austenitic dual-phase steel, comprising the following steps:

[0008] S1. First, the metastable austenitic dual-phase steel is cyclically loaded to low-cycle fatigue under a certain loading mode to obtain cyclic loading fatigue test data; the elastic strain energy density is calculated based on the fatigue test data. , plastic strain energy density , and calculate the total strain energy density and strain energy density ratio ;in

[0009] ;

[0010] ;

[0011] ;

[0012] ;

[0013] Where, elastic strain energy density , unit MJ / m3, is twice the stress amplitude, is the equivalent stress, unit MPa, is twice the plastic strain amplitude;

[0014] in , R is the stress ratio;

[0015] S2. Construct a low-cycle fatigue life prediction model. The low-cycle fatigue life prediction model is as follows:

[0016]

[0017] Where, is fatigue life; plastic strain energy density , unit MJ / m3; The maximum martensite content when cyclically loaded to low cycle fatigue under a certain loading mode at a set strain amplitude; is the cyclic hardening index;

[0018] S3. Calculate the low cycle fatigue life prediction model parameters;

[0019] The parameters are calculated by fitting the following formula 、 :

[0020]

[0021] Where, is the cyclic strength coefficient, unit: MPa; is the plastic strain amplitude, unit is dimensionless; is the stress amplitude, in MPa, obtained from fatigue test data;

[0022] Parameter calculation using the martensitic transformation kinetics model 、 :

[0023] =

[0024] in, is the maximum martensite content of the cyclically loaded specimen during fatigue, is the total strain amplitude, obtained from fatigue test data;

[0025] Calculation parameters The value of c: the value calculated in step S3 、 , and the one obtained in step S4 、 Substituting this into the low-cycle fatigue life prediction model, a low-cycle fatigue life prediction model for metastable austenitic dual-phase steel is obtained as shown below:

[0026]

[0027] Right now:

[0028] Will As a whole, nonlinear curve fitting is performed to calculate the parameters 、 The value of

[0029] S4. Using the low cycle fatigue life prediction model obtained in step S3, predict the low cycle fatigue life under any strain amplitude.

[0030] Compared with the prior art, the present invention has the following beneficial effects:

[0031] 1. Total strain energy density Considering the mean stress The influence of symmetrical cyclic loading and asymmetrical cyclic loading is considered, that is, for symmetrical cyclic loading: , ; For asymmetric cyclic loading: The mean stress is an influencing factor of strain-life. Consider the mean stress This makes up for the fact that the material's effect on the average stress was not considered in the previous low-cycle fatigue life prediction model. Sensitivity of the effect and neglect of mean stress Influence on plastic deformation of materials;

[0032] 2. The plastic strain energy density takes into account the influence of stress ratio R. This low-cycle fatigue life prediction model can adapt to cyclic loading under different stress ratios. The main limitation of previous low-cycle fatigue life prediction models is that they do not consider the mean stress effect. Research has confirmed that the stress ratio R of many materials will change the fatigue crack growth (FCG) behavior.

[0033] 3. The low-cycle fatigue life prediction model proposed in this invention combines the classic Manson-Coffin formula and strain range division method, etc., and is based on the energy SWT model and plastic strain energy life model, which makes up for the shortcomings of previous model predictions;

[0034] 4. The low cycle fatigue life prediction model in this invention proposes the strain energy density ratio The concept of , while fully considering the influence of elastic strain energy density on fatigue life, calculates the weight value of the influence of elastic strain energy density on the fatigue life of metastable austenitic dual-phase steel. This method is insensitive to the discrete values ​​of the data and can more accurately predict the low-cycle fatigue life;

[0035] 5. The low-cycle fatigue life prediction model proposed in the present invention takes into account the effect of martensite generated during cyclic loading on fatigue crack propagation in metastable austenitic dual-phase steel. From an energy perspective, the martensite generated during cyclic loading affects both the elastic strain energy and the plastic strain energy of the metastable austenitic dual-phase steel. Both of these factors are taken into account in the fatigue life prediction model of the present invention, making the results of the fatigue life prediction model more accurate.

[0036] 6. The low-cycle fatigue life prediction model proposed in the present invention only requires a set strain amplitude for the test steel. Based on the strain amplitude, the stress amplitude corresponding to the metastable austenitic dual-phase steel at that strain amplitude can be predicted. Furthermore, the martensite content generated when cyclically loaded to fatigue at that strain amplitude can be predicted, and the low-cycle fatigue life of the metastable austenitic dual-phase steel can be accurately predicted. This significantly simplifies cumbersome testing methods, saves testing costs and time, and has broad prospects for industrial application.

[0037] 7. The low-cycle fatigue life prediction model proposed in this invention overcomes the limitation of traditional models that can only use a single variable as the research object, and provides a new fatigue analysis auxiliary means for the fields of materials science and engineering. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 Schematic diagram of the process of the present invention;

[0039] Figure 2 Schematic diagram of stress amplitude-plastic strain amplitude fitting of the present invention;

[0040] Figure 3 The martensite content of the present invention is With the total strain amplitude Fitting schematic diagram;

[0041] Figure 4 This is a schematic diagram of the fitting curve of the fatigue life prediction model of the present invention;

[0042] Figure 5 This is a comparison chart of the low-cycle fatigue life prediction model proposed in this invention and the test results. DETAILED DESCRIPTION

[0043] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0044] The present invention proposes a method for predicting the low cycle fatigue life of metastable austenitic dual-phase steel, such as Figure 1 The specific implementation process is as follows:

[0045] S1. First, the metastable austenitic dual-phase steel is cyclically loaded to low-cycle fatigue under a certain loading mode to obtain cyclic loading fatigue test data; the elastic strain energy density is calculated based on the fatigue test data. , plastic strain energy density , and calculate the total strain energy density and strain energy density ratio ;in

[0046] ;

[0047] ;

[0048] ;

[0049] ;

[0050] Where, elastic strain energy density , unit MJ / m3, is twice the stress amplitude, is the equivalent stress, unit MPa, is twice the plastic strain amplitude;

[0051] in , R is the stress ratio;

[0052] S2. Construct a low-cycle fatigue life prediction model. The low-cycle fatigue life prediction model is as follows:

[0053]

[0054] Where, is the fatigue life; plastic strain energy density , unit MJ / m3; The maximum martensite content when cyclically loaded to low cycle fatigue under a certain loading mode at a set strain amplitude; is the cyclic hardening index;

[0055] S3. Calculate the low cycle fatigue life prediction model parameters;

[0056] The parameters are calculated by fitting the following formula 、 :

[0057]

[0058] Where, is the cyclic strength coefficient, unit: MPa; is the plastic strain amplitude, unit is dimensionless; is the stress amplitude, in MPa, obtained from fatigue test data;

[0059] The parameters are calculated by the following formula 、 :

[0060] =

[0061] in, is the maximum martensite content of the cyclically loaded specimen during fatigue, is the total strain amplitude, obtained from fatigue test data;

[0062] Calculation parameters The value of c: the value calculated in step S3 、 , and the one obtained in step S4 、 Substituting this into the low-cycle fatigue life prediction model, a low-cycle fatigue life prediction model for metastable austenitic dual-phase steel is obtained as shown below:

[0063]

[0064] Right now:

[0065] Will As a whole, nonlinear curve fitting is performed to calculate the parameters 、 The value of

[0066] S4. Using the low cycle fatigue life prediction model obtained in step S3, accurately predict the low cycle fatigue life under any strain amplitude.

[0067] Among them, the strain amplitudes mentioned are all in percentage. That is, when substituting into the model, there is no need to substitute the percentage sign, and the corresponding value before the percentage sign can be directly substituted.

[0068] To verify the low-cycle fatigue life prediction method for metastable austenitic duplex steel proposed in this invention, the fatigue life prediction of experimental metastable austenitic economized TRIP duplex stainless steel (hereinafter referred to as economized TRIP duplex steel), which has great application prospects, is further elaborated on as an example.

[0069] Symmetrical cyclic loading is performed on the economical TRIP dual-phase steel. At this time, the stress ratio R=-1 and the strain amplitude is selected. Cyclic loading was carried out under conditions of 0.5%, 0.7%, 0.9%, 1.1% and 1.3% until fatigue failure.

[0070] Record the strain amplitude, fatigue life (i.e., number of cycles to fatigue failure), and stress amplitude of the low-cycle fatigue test, and calculate and summarize the relevant test data required for the low-cycle fatigue life prediction model; the data are as follows:

[0071]

[0072] By stress amplitude and plastic strain amplitude The cyclic hardening index can be calculated by 、 .

[0073] (1)

[0074] in The calculation process is as follows: fit the experimental data through Origin software, first input the experimental data into Origin, and the horizontal axis data is the plastic strain amplitude , the vertical axis is the stress amplitude Then select nonlinear curve fitting and enter the above formula. The fitting result is as follows Figure 2 As shown, we can get 0.27, ;

[0075] Then put Substitute the value of into the following formula

[0076] (2)

[0077] in , where R is the stress ratio; this embodiment uses symmetrical cyclic loading, R=-1. It can be obtained:

[0078] (3)

[0079] in is the plastic strain energy density considering the strain ratio R, in MJ / m3; It is twice the nominal stress amplitude (engineering stress amplitude), the unit is MPa; is the fatigue life, i.e. the number of cycles to fatigue failure, in cycles; is the cyclic hardening index, dimensionless, It is twice the plastic strain amplitude.

[0080] Then calculate the elastic strain energy density , the unit is MJ / m3

[0081] (4)

[0082] in is twice the nominal stress amplitude (engineering stress amplitude), is twice the elastic strain amplitude.

[0083] = (5)

[0084] Where: is the maximum martensite content when the specimen is cyclically loaded to fatigue, is the total strain amplitude, obtained from fatigue test data; the maximum content of martensite in the duplex steel and strain amplitude The relationship between the parameters can be obtained 、 .

[0085] in 、 The calculation process is as follows: fit the experimental data through Origin software, first input the experimental data into the Origin software 、 , then select nonlinear curve fitting, input the above formula (5), the fitting result is as follows Figure 3 As shown, we can get =4.5, =1.25.

[0086] Substituting into formula (5) we can write: =

[0087] For formula (6),

[0088] (6)

[0089] Replace with X , replace with Y , then formula (6) can be transformed into:

[0090] (7)

[0091] Then, Origin software was used to perform nonlinear fitting on the experimental data. The fitting results are shown in the figure. Figure 4 As shown, we can get: The expression is as follows:

[0092] (8)

[0093] Therefore, according to the equality of the corresponding coefficients of formula (7) and formula (8), we can find and the value of c, where =0.95819, c=1.3562*10^7.

[0094] Then 、 、 、 、 Substitute the values ​​of , c into formula (9),

[0095] (9)

[0096] The energy life prediction model can be expressed as:

[0097] (10)

[0098] The specific strain amplitude is given below to verify the fatigue life prediction accuracy, as follows:

[0099] Example 1:

[0100] 1. Choose low strain amplitude The total strain amplitude is calculated using the above formula (1) The corresponding stress value , where the plastic strain amplitude is =0.4976516% The details are as follows:

[0101] =615.27*0.4976516^0.27=509.60725

[0102] 2. Calculate elastic strain energy density , plastic strain energy density , total strain energy density and strain energy density ratio ; The details are as follows:

[0103] =509.60725*2*0.00234837*2=4.7869855;

[0104] = *509.60725*2*0.4976516*2=583.096095;

[0105] =583.096095+4.7869855=587.883081;

[0106] = ;

[0107] 3. Calculate strain amplitude =0.5%, symmetrical cyclic loading to fatigue, the maximum martensite content is calculated using the martensite phase transformation kinetics model, as follows:

[0108] = =1.89202

[0109] 4. The low-cycle fatigue life prediction model of the present invention is used to calculate the low-cycle fatigue life under the condition of 0.5% strain amplitude, as follows:

[0110]

[0111] Simplified and sorted: 3141

[0112] The fatigue life at a strain amplitude of 0.5% is calculated using the low-cycle fatigue life prediction model and the actual fatigue life obtained from the test Compared with the above, the calculated deviation is within 10%. The calculation process is as follows:

[0113]

[0114] Example 2:

[0115] 1. Calculate the higher strain amplitude using the above formula (1) The corresponding stress amplitude , where the plastic strain amplitude is =0.8974542% The details are as follows:

[0116] =615.27*0.8974542^0.27=597.55662

[0117] 1. Calculate elastic strain energy density , plastic strain energy density , total strain energy density and strain energy density ratio ; The details are as follows:

[0118] =597.55662*2*0.00254582*2=6.0508638;

[0119] = *597.55662*2*0.8974542*2=1233.021039;

[0120] =1233.021039+6.0508638=1239.071903;

[0121] = ;

[0122] 3. Calculate strain amplitude = 0.9%, and symmetrical cyclic loading to fatigue, the maximum martensite content is calculated using the martensite phase transformation kinetics model, as follows:

[0123] = =3.94472

[0124] 4. The low-cycle fatigue life prediction model of the present invention is used to calculate the low-cycle fatigue life under the condition of 0.9% strain amplitude, as follows:

[0125]

[0126] Simplified and sorted: 499

[0127] The fatigue life when the total strain amplitude is 0.9% is calculated by the low-cycle fatigue life prediction model. and the actual fatigue life obtained from the test Compared with the above, the calculated deviation is within 10%. The calculation process is as follows:

[0128]

[0129] Example 3:

[0130] 1. Calculate the high strain amplitude using the above formula (1) The corresponding stress amplitude , where the plastic strain amplitude is =1.2969946% The details are as follows:

[0131] =615.27*1.2969946^0.27=660.02296

[0132] 1. Calculate elastic strain energy density , plastic strain energy density , total strain energy density and strain energy density ratio ; The details are as follows:

[0133] =660.02296*2*0.00300539*2=7.9345056;

[0134] = *660.02296*2*1.2969946*2=1968.232242;

[0135] =7.9345056+1968.232242=1976.1667476;

[0136] = ;

[0137] 3. Calculate strain amplitude =1.3%, and symmetrical cyclic loading to fatigue, the maximum martensite content is calculated using the martensite phase transformation kinetics model, as follows:

[0138] = =6.24657

[0139] 4. The low-cycle fatigue life prediction model of the present invention is used to calculate the low-cycle fatigue life under the condition of 1.3% strain amplitude, as follows:

[0140]

[0141] Simplified and sorted: 140

[0142] The fatigue life when the total strain amplitude is 1.3% is calculated by the low-cycle fatigue life prediction model. and the actual fatigue life obtained from the experiment Compared with the above, the calculated deviation is within 10%. The calculation process is as follows:

[0143]

[0144] The examples of the present invention are specifically verified using a low strain amplitude of 0.5%, a medium-high strain amplitude of 0.9%, and a high strain amplitude of 1.3%. Figure 5 A comparison chart of the low-cycle fatigue life prediction model proposed in the present invention and the test results;

[0145] The results show that the low-cycle fatigue life prediction model predicts the low-cycle fatigue life of duplex stainless steel with an error of less than 10%, and the prediction accuracy meets engineering requirements. Therefore, the proposed method can effectively predict the low-cycle fatigue life of metastable austenitic duplex steel.

[0146] The low-cycle fatigue life prediction model for metastable austenitic dual-phase steel proposed in the present invention only requires a given strain amplitude during cyclic loading of the test steel under a certain loading mode, and can predict the stress amplitude to which the test steel is subjected at this strain amplitude, and further can predict the maximum martensite content produced when cyclically loaded to fatigue at this strain amplitude, and further can accurately predict the low-cycle fatigue life of the test steel at this strain amplitude.

[0147] Matters not described in detail in this invention are all known technologies.

[0148] The specific embodiments described above are merely descriptions of preferred embodiments of the present invention and do not limit the scope of the present invention. Without departing from the design spirit of the present invention, various modifications and improvements made to the technical solutions of the present invention by ordinary technicians in this field should fall within the scope of protection determined by the claims of the present invention.

Claims

1. A method for predicting low-cycle fatigue life of metastable austenitic dual-phase steel, characterized by: It includes the following steps: S1. First, the metastable austenitic dual-phase steel is cyclically loaded to low-cycle fatigue under a certain loading mode, thereby obtaining cyclic loading fatigue test data; Calculation of elastic strain energy density ΔW from fatigue test data e , plastic strain energy density ΔW p ', and calculate the total strain energy density ΔW' t and strain energy density ratio Q; in ΔW e =DsDe e ; ΔW' t =ΔW e +ΔW p '; Where, elastic strain energy density ΔW e , unit MJ / m 3 ,Δσ is twice the stress amplitude,σ eq is the equivalent stress, unit MPa; Δε p is twice the plastic strain amplitude; in R is the stress ratio; S2. Construct a low-cycle fatigue life prediction model. The low-cycle fatigue life prediction model is as follows: Where N f is the fatigue life, that is, the number of cycles to fatigue failure; plastic strain energy density ΔW p ', unit MJ / m 3 ; f max is the maximum martensite content when cyclically loaded to low cycle fatigue under a certain loading mode at a set strain amplitude; n' is the cyclic hardening index; S3. Calculate the low cycle fatigue life prediction model parameters; The parameters K' and n' are calculated by fitting the following formula: Where, K' is the cyclic strength coefficient, unit MPa; is the plastic strain amplitude, unit is dimensionless; is the stress amplitude, in MPa, obtained from fatigue test data; Parameters β and γ are calculated using the martensitic transformation kinetics model: Among them, f max is the maximum martensite content of the cyclically loaded specimen during fatigue, is the total strain amplitude, obtained from fatigue test data; Calculate the values ​​of parameters α and c: Substitute K' and n' calculated in step S3, and β and γ obtained in step S4 into the low-cycle fatigue life prediction model to obtain a low-cycle fatigue life prediction model for metastable austenitic dual-phase steel, as shown below: Right now: Will Treat it as a whole and perform nonlinear curve fitting to calculate the values ​​of parameters α and c; S4. Using the low cycle fatigue life prediction model obtained in step S3, the low cycle fatigue life of the metastable austenitic dual-phase steel under any strain amplitude can be predicted.

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