Fatigue Life Prediction of Rolling Bearings Based on Modified SWT Mean Stress Correction

The existing engineering empirical life analysis models are not capable of considering the constitutive behavior of materials under contact loads;as a consequence,these methods may not be accurate to predict fatigue lives of roll-ing bearings.In addition,the contact stress of bearing in operation is cyclically pulsating,it also means that the bear-ing undergo non-symmetrical fatigue loadings.Since the mean stress has great effects on fatigue life,in this work,a novel fatigue life prediction model based on the modified SWT mean stress correction is proposed as a basis of which to estimate the fatigue life of rolling bearings,in which,takes sensitivity of materials and mean stress into account.A compensation factor is introduced to overcome the inaccurate predictions resulted from the Smith,Watson,and Topper(SWT)model that considers the mean stress effect and sensitivity while assuming the sensitivity coefficient of all materials to be 0.5.Moreover,the validation of the model is finalized by several practical experimental data and the comparison to the conventional SWT model.The results show the better performance of the proposed model,especially in the accuracy than the existing SWT model.This research will shed light on a new direction for predicting the fatigue life of rolling bearings.

Energetical Theories on Fatigue Life Prediction

Current developments on fatigue life prediction methods have been systematically reviewed.In con- sideration of the irreversibility of energy dissipation during fatigue damage process,the main contents for fatigue damage estimation and localized equivalence as well as simulation models have been established.A frame of energy-based fatigue life prediction method has been proposed,meanwhile, the procedure in application to a practical structure component has been described.

Fatigue Life Prediction of Horizontal Press Frame Based on Statistical Probability and Its Redesign

Horizontal press as an important part of hydro-forming machine is used to output the horizontal force to keep the high internal pressure during tube hydro-forming. However,the horizontal press frame is usually mounted on the press bed and not pre-stressed. Meanwhile it will be subjected to the reaction force caused by liquid pressure. Stresses are concentrated severely on the assemble region due to deformation,and total fatigue life will decrease. In order to predict the total fatigue life of the frame,the simulations are used firstly to determine to stress concentration region,and then strain gauge measurements are carried out under different loads. Next,the methods of statistical probability are conducted to calculate the fatigue life based on long-term load history. Finally a structure with the considerable longer fatigue life is redesigned.

Bi-variable damage model for fatigue life prediction of metal components

Based on the theory of continuum damage mechanics,a bi-variable damage mechanics model is developed,which,according to thermodynamics,is accessible to derivation of damage driving force,damage evolution equation and damage evolution criteria. Furthermore,damage evolution equations of time rate are established by the generalized Drucker＇s postulate. The damage evolution equation of cycle rate is obtained by integrating the time damage evolution equations,and the fatigue life prediction method for smooth specimens under repeated loading with constant strain amplitude is constructed. Likewise,for notched specimens under the repeated loading with constant strain amplitude,the fatigue life prediction method is obtained on the ground of the theory of conservative integral in damage mechanics. Thus,the material parameters in the damage evolution equation can be obtained by reference to the fatigue test results of standard specimens with stress concentration factor equal to 1,2 and 3.

Fatigue life prediction model of 2.5D woven composites at various temperatures

As one of the new structural layout in the family of woven composites, 2.5D Woven Composites（2.5D-WC） have recently attracted an increasing interest owing to its excellent properties, i.e. high specific strength and fatigue resistance, in the aerospace and automobile industry. Indepth understanding of the fatigue behavior of this material at un-ambient temperatures is critical for the engineering applications, especially in aero-engine field. Here, fatigue behavior of 2.5D-WC at different temperatures was numerically investigated based on the unit cell approach. Firstly, the unit cell model of 2.5D-WC was established using ANSYS software. Subsequently, the temperature-dependent fatigue life prediction model was built up. Finally, the fatigue lives alongside the damage evolution processes of 2.5D-WC at ambient temperature（20 ℃） and unambient temperature（180 ℃） were analyzed. The results show that numerical results are in good agreement with the relevant experimental results at 20 and 180 ℃. Fatigue behavior of 2.5D-WC is also sensitive to temperature, which is partially attributed to the mechanical properties of resin and the change of inclination angle of warp yarns. We hope that the proposed fatigue life prediction model and the findings could further promote the engineering application of 2.5D-WC, especially in aero-engine field.

A DAMAGE MECHANICS MODEL FOR FATIGUE LIFE PREDICTION OF FIBER REINFORCED POLYMER COMPOSITE LAMINA

A damage mechanics fatigue life prediction model for the fiber reinforced polymer lamina is established. The stiffness matrix of the lamina is derived by elastic constants of fiber and matrix. Two independent damage degrees of fiber and matrix are introduced to establish constitutive relations with damage. The damage driving forces and damage evolution equations for fiber and matrix are derived respectively. Fatigue tests on 0° and 90° unidirectional laminates are conducted respectively to identify parameters in damage evolution equations of fiber and matrix. The failure criterion of the lamina is presented. Finally, the life prediction model for lamina is proposed.

Fatigue Life Prediction for NiTi Shape Memory Alloy Micro-tubes Under Uniaxial Stress-Controlled One-Way Shape Memory Cyclic Loading

By choosing the dissipation energy as the damage variable,corresponding damage evolution equations are established,respectively,for the mechanical cyclic loading part and the thermal one during the thermo-mechanical cyclic loading of NiTi shape memory alloys(SMAs)involving one-way shape memory effect(simply denoted as the OWSME cycling).And then,the evolution law of total damage is obtained by a superposition of such two damage parts.Finally,the uniaxial OWSME fatigue lives of NiTi SMA micro-tubes are predicted by combining the proposed damage model with an adopted failure criterion.The results show that all the predicted fatigue lives are located within the twice scatter band with regard to the experimental ones,and most of them are located within a scatter band of 1.5 times.It is indicated that the predicted OWSME fatigue lives are in good agreement with the experimental ones.

APPLYING REGRESSION AND STOCHASTIC TIME SERIES ANALYSIS TO THE PREDICTION OF PITTING FATIGUE LIFE FOR GEARS

Based upon the methods for the calculation of load capacity of involute cylindrical gears(ISO / DIS6336), the new method system that can be adaptcd for applying condition is found byapplying regresson analysis and stochastic time series analysis to the prediction of pitting life for thegeart, the function is established between pitting area and revolving period of gear, the theoreticalmodel is advanced for tredicting the pitting fatigue life of gear, the problem it solved for obtainingthe applying model by establishing the residue model, the method it put forward the model aboutpredicting pitting fatigue life of gear with damaged condition under middle / low speed and heavyduty.

Multiaxial fatigue life prediction of composite materials

In order to analyze the stress and strain fields in the fibers and the matrix in composite materials,a fiber-scale unit cell model is established and the corresponding periodical boundary conditions are introduced.Assuming matrix cracking as the failure mode of composite materials,an energy-based fatigue damage parameter and a multiaxial fatigue life prediction method are established.This method only needs the material properties of the fibers and the matrix to be known.After the relationship between the fatigue damage parameter and the fatigue life under any arbitrary test condition is established,the multiaxial fatigue life under any other load condition can be predicted.The proposed method has been verified using two different kinds of load forms.One is unidirectional laminates subjected to cyclic off-axis loading,and the other is filament wound composites subjected to cyclic tension-torsion loading.The fatigue lives predicted using the proposed model are in good agreements with the experimental results for both kinds of load forms.

Microstructural characteristics and low-cycle fatigue properties of AZ91 and AZ91-Ca-Y alloys extruded at different temperatures

The commercial AZ91 alloy and nonflammable SEN9(AZ91-0.3Ca-0.2Y,wt%)alloy are extruded at 300°C and 400°C.Their microstructure,tensile and compressive properties,and low-cycle fatigue(LCF)properties are investigated,with particular focus on the influence of the extrusion temperature.In the AZ91 and SEN9 materials extruded at 300°C(300-materials),numerous fine Mg_(17)Al_(12)particles are inhomogeneously distributed owing to localized dynamic precipitation during extrusion,unlike those extruded at 400°C(400-materials).These fine particles suppress the coarsening of recrystallized grains,decreasing the average grain size of 300-materials.Although the four extruded materials have considerably different microstructures,the difference in their tensile yield strengths is insignificant because strong grain-boundary hardening and precipitation hardening effects in 300-materials are offset almost completely by a strong texture hardening effect in 400-materials.However,owing to their finer grains and weaker texture,300-materials have higher compressive yield strengths than400-materials.During the LCF tests,{10-12}twinning is activated at lower stresses in 400-materials than in 300-materials.Because the fatigue damage accumulated per cycle is smaller in 400-materials,they have longer fatigue lives than those of 300-materials.A fatigue life prediction model for the investigated materials is established on the basis of the relationship between the total strain energy density(ΔW_(t))and the number of cycles to fatigue failure(N_(f)),and it is expressed through a simple equation(ΔW_(t)=10·N_(f)-0.59).This model enables fatigue life prediction of both the investigated alloys regardless of the extrusion temperature and strain amplitude.

Numerical Simulation of Low Cycle Fatigue Behavior of Ti_(2)AlNb Alloy Subcomponents

Many titanium alloy subcomponents are subjected to fatigue loading in aerospace engineering,resulting in fatigue failure.The fatigue behavior of Ti_(2)AlNb alloy subcomponents was investigated based on the Seeger fatigue life theory and the improved Lemaitre damage evolution theory.Firstly,the finite element models of the standard openhole specimen and Y-section subcomponents have been established by ABAQUS.The damage model parameters were determined by fatigue tests,and the reliability of fatigue life simulation results of the Ti_(2)AlNb alloy standard open-hole specimen was verified.Meanwhile,the fatigue life of Ti_(2)AlNb alloy Y-section subcomponents was predicted.Under the same initial conditions,the average error of fatigue life predicted by two different models was 20.6%.Finally,the effects of loading amplitude,temperature,and Y-interface angle on fatigue properties of Ti_(2)AlNb Y-section subcomponents were investigated.These results provide a new idea for evaluating the fatigue life of various Ti_(2)AlNb alloy subcomponents.

A data-driven approach for predicting the fatigue life and failure mode of self-piercing rivet joints

In lightweight automotive vehicles,the application of self-piercing rivet(SPR)joints is becoming increasingly widespread.Considering the importance of automotive service performance,the fatigue performance of SPR joints has received considerable attention.Therefore,this study proposes a data-driven approach to predict the fatigue life and failure modes of SPR joints.The dataset comprises three specimen types:cross-tensile,cross-peel,and tensile-shear.To ensure data consistency,a finite element analysis was employed to convert the external loads of the different specimens.Feature selection was implemented using various machine-learning algorithms to determine the model input.The Gaussian process regression algorithm was used to predict fatigue life,and its performance was compared with different kernel functions commonly used in the field.The results revealed that the Matern kernel exhibited an exceptional predictive capability for fatigue life.Among the data points,95.9%fell within the 3-fold error band,and the remaining 4.1%exceeded the 3-fold error band owing to inherent dispersion in the fatigue data.To predict the failure location,various tree and artificial neural network(ANN)models were compared.The findings indicated that the ANN models slightly outperformed the tree models.The ANN model accurately predicts the failure of joints with varying dimensions and materials.However,minor deviations were observed for the joints with the same sheet.Overall,this data-driven approach provided a reliable predictive model for estimating the fatigue life and failure location of SPR joints.

Fatigue characteristics of sand-cast AZ91D magnesium alloy

The fatigue characteristics of the AZ91D-T6 alloy samples taken from engine blocks have been investigated at 20℃ and elevated temperature(150℃).The fatigue strength and cyclic stress amplitude of the alloy significantly decrease with the increase of the test temperature,although cyclic hardening occurs continuously until failure for both temperatures.With the increase of the temperature,the decreased fatigue life of the alloy tested at the same stress amplitude is mainly attributed to the decreased matrix strength and the increased hysteresis energies.Fatigue failure of the engine blocks made of AZ91D-T6 alloy is mainly controlled by casting defects.For the defect-free specimens,the crack initiation behavior is determined by the single-slip(20℃)and by environment-assisted cyclic slip(150℃)during fatigue,respectively.The low-cycle fatigue lives of the alloy can be predicted using the Coffin-Manson relation and Basquin laws,the three-parameter equation and the energy-based concepts,while the high-cycle fatigue lives of the alloy fitted well with the developed long crack life model and MSF life models.

Investigating fatigue behavior of gear components with the acoustic emission technique

A novel method is presented to evaluate the complicated fatigue behavior of gears made of20Cr2Ni4 A.Fatigue tests are conducted in a high-frequency push-pull fatigue tester,and acoustic emission（AE）technique is used to acquire metal fatigue signals.After analyzing large number of AE frequency spectrum,we find that：the crack extension can be expressed as the energy of specific frequency band,which is abbreviated as F-energy.To further validate the fatigue behavior,some correlation analysis is applied between F-energy and some AE parameters.Experimental results show that there is significant correlation among the Fenergy,root mean square（RMS）,relative energy,and hits.The findings can be used to validate the effectiveness of the F-energy in predicting fatigue crack propagation and remaining life for parts in-service.F-energy,as a new AE parameter,is first put forward in the area of fatigue crack growth.

Machine learning-based predictions of fatigue life and fatigue limit for steels

To predict the fatigue life for oblique hyperbola-and bilinear-mode S-N curves of metallic materials with various strengths,a machine-learning approach for direct analysis was employed.Additionally,to determine the fatigue limit of the utilized materials(AISI 316,AISI 4140 and CA6 NM series)with different S-N curve modes using finite-fatigue life data,a Bayesian optimization-based inverse analysis was performed.The results indicated that predictions of the fatigue life for the utilized datasets via the random forest(RF)algo rithm for AISI 4140 and CA6 NM,and artificial neural network(ANN)for AISI 316,distribute within 2 factor error lines for most data.In the Bayesian optimization-based inverse analysis,the specific explanatory variables corresponding to the optimized maximum fatigue life were treated as the fatigue limits.The predicted fatigue limits either approximated to or slightly underestimated the experimental results,except for several cases with large errors.Using the inverse analysis to predict the fatigue limit for both S-N curve modes is applicable for current employed data-set.However,the explored maximum fatigue lives via BO corresponding to the predicted fatigue limit were underestimated for AISI 4140 and CA6 NM,and was overestimated for AISI 316 because of effect of shape of S-N curves.By combining the ANN or RF direct and BO inverse algorithms,whole S-N curves(including the fatigue limit)were evaluated for the S-N curve shapes of the oblique hyperbola and bilinear modes.

Short-range ordering plays a determining role in the low-cycle fatigue life improvement of fcc metals: A conclusive study on low solid-solution hardening Ni-Cr alloys

The effect of short-range ordering (SRO) on the low-cycle fatigue (LCF) behavior of low solid-solution hardening Ni-Cr alloys with high stacking fault energies (SFEs) was systematically studied under cycling at constant total strain amplitude (Δε t /2) in the range of 0.1%–0.7%. The results show that an inducement of SRO structures can notably improve the fatigue life of the alloy regardless of Δε t /2, and several unique fatigue characteristics have been detected, including the transition of fatigue cracking mode from intergranular cracking to slip band cracking, the non-negligible evolution from non-Masing behavior in pure Ni to Masing behavior in the Ni-40Cr alloy, and the secondary cyclic hardening behavior in the Ni-10Cr and Ni-20Cr alloys. All these experimental phenomena are tightly associated with the transformation in cyclic deformation mechanisms that is induced by SRO based on the “glide plane softening” effect. Furthermore, a comprehensive fatigue life prediction model based on total hysteresis energy has been reasonably proposed, focusing on the analyses of the macroscopic model parameters (namely the fatigue cracking resistance exponent β and the crack propagation resistance parameter W 0 ) and microscopic damage mechanisms. In brief, on the premise that the effects of SFE and friction stress can be nearly ignored, as in the case of the present low solid-solution hardening Ni-Cr alloys with high SFEs, an enhancement of SRO in face-centered cubic metals has been convincingly confirmed to be an effective strategy to improve their LCF performance.

Modified Coffin-Manson equation to predict the fatigue life of structural materials subjected to mechanical-thermal coupling non-coaxial loading

With regard to the structures subjected to severe mechanical-thermal coupling fatigue conditions,the consistency between service conditions and loading conditions was the prerequisite for the fatigue prop-erties test and fatigue life prediction.A miniature piezoelectric-driven instrument integrating with a tripodal piezoelectric actuator and envelope-type heating function was developed to investigate the mechanical-thermal coupling fatigue properties and obtain the fatigue life of materials under approximate service conditions.A physical model was described to quantitatively calculate the alternating deformation under the mechanical-thermal coupling tensile-bending combined condition.Accordingly,a fatigue life prediction method based on the Coffin-Manson equation under tensile-bending combined loading was proposed to estimate the mechanical-thermal coupling fatigue life in terms of the total coupling defor-mation and plastic strain amplitude.The feasibility of the proposed instrument was verified through the analysis of displacement responses of high entropy alloy specimens under the thermal-mechanical cou-pling tensile-bending combined condition at temperatures ranging from RT to 600°C.The comparison between fatigue lives directly measured through thermal-mechanical coupling experiments and theoreti-cally predicted fatigue lives indicated the availability of the modified Coffin-Manson equation.

A discussion of fatigue properties of notched specimens subjected to prestressing treatment machined from FGH4097

Experimental and numerical investigations were performed to reveal the effect of prestress on the fatigue properties of FGH4097 so as to quantitatively evaluate the overspeed benefit of the disc of aeroengine. A corresponding experiment was performed to examine the effect of prestress on the fatigue life of FGH97. A complete model describing the fatigue properties of the prestressed notch specimen was proposed. After the modification of mean stress, stress gradient and prestressing treatment, the model is finally verified by fatigue test of presstressed notch specimens machined from FGH4097 with satisfactory accuracy and good engineering applicability. The new model highlights that for the variable fatigue loads, the introduction of appropriate prestress is expected to benefit to the notch specimens and certainly to the disc of aeroengine regards of their fatigue properties. Both the calculation method of fatigue life parameters and the prestress correction model are proved to have good prediction accuracy.

Research on Nonlinear Dynamic Simulation and Fatigue Reliability Life Prediction for Synthesis Transmission System of Self-Propelled Gun

Aiming to the puzzle that the inner load of nonlinear synthesis transmission system is difficult to obtain,a new kind of virtual prototype establishment and simulation method is put forward. The influence on nonlinear vibration with flexible rotor, bearing backlash is analyzed based on a virtual prototype. To validate the virtual prototype of nonlinear gear transmission system, the corresponding test platform is established. The consistency between simulation results and test results proves that the simulation results of the virtual prototype can be used to calculate the fatigue reliability life of key components. A new kind of fatigue reliability life prediction method of gear system considering multi-random parameter distribution is put forward based on the fatiguestatistic theory. Considering the periodicity of gear meshing, linear interpolation method is adopted to obtain the stress-time course of random load spectrum based on the gear's complicated torque provided by virtual prototype.The gear's P-Sa-Sm-N curved cluster can be simulated based on material's P-S-N curve. The simulation process considers the parameter distributions of stress concentration coefficients, dimension coefficients and surface quality treatment coefficients, and settles the puzzle that traditional test methods cannot acquire the gear's fatigue life of all reliability levels. This method can provide the distribution function and the interval of fatigue reliability life of gear's danger region, and has a guide meaning for the gear maintenance periods determination and reliability evaluation.

A Methodology to Predict Fatigue Life of Cast Iron:Uniform Material Law for Cast Iron

Mechanical, physical and manufacturing properties of east iron make it attractive for many fields of application, such as cranks and cylinder holds. As in design of all metals, fatigue life prediction is an intrinsic part of the design process of structural sections that are made of cast iron. A methodology to predict high-cycle fatigue life of cast iron is proposed. Stress amplitude-strain amplitude, strain amplitude-number of loading cycles relationships of cast iron are investigated. Also, fatigue life prediction in terms of Smith, Watson and Topper parameter is carried out using the proposed method. Results indicate that the analytical outcomes of the proposed methodology are in good accordance with the experimental data for the two studied types of cast iron： EN-GJS-400 and EN-GJS-600.