Grain size based low cycle fatigue life prediction model for nickel-based superalloy

Nickel-based superalloys are easy to produce low cycle fatigue(LCF)damage when they are subjected to high temperature and mechanical stresses.Fatigue life prediction of nickel-based superalloys is of great importance for their reliable practical application.To investigate the effects of total strain and grain size on LCF behavior,the high temperature LCF tests were carried out for a nickel-based superalloy.The results show that the fatigue lives decreased with the increase of strain amplitude and grain size.A new LCF life prediction model was established considering the effect of grain size on fatigue life.Error analyses indicate that the prediction accuracy of the new LCF life model is higher than those of Manson-Coffin relationship and Ostergren energy method.

Life Prediction Model of Machine Tool based on Deep Learning

In view of the shortage of traditional life prediction methods for machine tools,such as low accuracy of life prediction and few samples basis attributes,a life prediction model of machine tools combined with machine tool attributes is proposed.The life prediction model of machine tool adopts KL dispersion distribution theory,uses modal superposition method to carry out machine tool life analysis,calculates the theoretical life of machine tool,and then carries on the simulation,obtains the machine tool life prediction value.Compared with the traditional method of machine tool life prediction,the model is based on the application life fatigue damage model,which superimposes the service times and maintenance cycle of the machine tool,derives the influence factor of machine tool life,and obtains the linear relationship between the influence factor of machine tool life and the life of machine tool.The influence factor of machine tool life is introduced as the life prediction parameter of machine tool.The data transformation relationship of HT300 parts is constructed.The original part data is enhanced.The effective training set is obtained.The life prediction model of machine tool based on deep learning is completed.The quantitative analysis of machine tool life is carried out.The experiment of machine tool life prediction using training data set proves the validity of the model.Regression test was carried out on the training data set to reflect the robustness of the model.The prediction accuracy of the model is further verified by Weibull test.

Life Prediction Model for a Nickel-base Single Crystal Superalloy DD3

The possibility of a life prediction model for nickel base single crystal blades has been studied. The fatigue creep (FC) and thermal fatigue creep(TMFC) as well as creep experiments have been carried out with different hold time of DD3. The hold time and the frequency as well as the temperature range are the main factors influencing the life. An emphasis has been put on the micro mechanism of the rupture of creep, FC and TMFC. Two main factors are the voiding and degeneration of the material for the cre...

Review on fatigue life prediction models of welded joint

Fatigue assessment of welded joint is still far from being completely solved now,since many influencing factors coexist and some important ones should be considered in the developed life prediction models reasonably.Thus,such influencing factors of welded joint fatigue are firstly summarized in this work;and then,the existing life prediction models are reviewed from two aspects,i.e.,uniaxial and multiaxial ones;finally,significant conclusions of existing experimental and theoretical researches and some suggestions on improving the fatigue assessment of welded joints,especially for the low-cycle fatigue with the occurrence of ratchetting,are provided.

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.

Cycle life prediction and match detection in retired electric vehicle batteries

The lifespan models of commercial 18650-type lithium ion batteries （nominal capacity of 1150 mA-h） were presented. The lifespan was extrapolated based on this model. The results indicate that the relationship of capacity retention and cycle number can be expressed by Gaussian function. The selecting function and optimal precision were verified through actual match detection and a range of alternating current impedance testing. The cycle life model with high precision （〉99%） is beneficial to shortening the orediction time and cutting the prediction cost.

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.

Casing life prediction using Borda and support vector machine methods

Eight casing failure modes and 32 risk factors in oil and gas wells are given in this paper. According to the quantitative analysis of the influence degree and occurrence probability of risk factors, the Borda counts for failure modes are obtained with the Borda method. The risk indexes of failure modes are derived from the Borda matrix. Based on the support vector machine （SVM）, a casing life prediction model is established. In the prediction model, eight risk indexes are defined as input vectors and casing life is defined as the output vector. The ideal model parameters are determined with the training set from 19 wells with casing failure. The casing life prediction software is developed with the SVM model as a predictor. The residual life of 60 wells with casing failure is predicted with the software, and then compared with the actual casing life. The comparison results show that the casing life prediction software with the SVM model has high accuracy.

QUICK ASSESSMENT METHODOLOGY FOR RELIABILITY OF SOLDER JOINTS IN BALL GRID ARRAY (BGA) ASSEMBLY——PART Ⅰ: CREEP CONSTITUTIVE RELATION AND FATIGUE MODEL

In this study, a new unified creep constitutive relation and a mod- ified energy-based fatigue model have been established respectively to describe the creep flow and predict the fatigue life of Sn-Pb solders. It is found that the relation successfully elucidates the creep mechanism related to current constitutive relations. The model can be used to describe the temperature and frequency dependent low cycle fatigue behavior of the solder. The relation and the model are further employed in part Ⅱ to develop the numerical simulation approach for the long-term reliability assessment of the plastic ball grid array (BGA) assembly.

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.

Predicting the shelf life of Trachinotus ovatus during frozen storage using a back propagation(BP)neural network model

The research aimed to create a shelf life prediction model for Trachinotus ovatus in different freezing temperatures by using back propagation(BP)neural network model.The pH,total volatile basic nitrogen(TVB-N),thiobarbituric acid(TBA),water retention(water holding capacity[WHC];cooking loss),and sensory evaluation were measured under 266 K,255 K,243 K,233 K,and 218 K temperatures.The results of TVB-N and water retention during 266 K,255 K,233 K,and 218 K conditions were selected to build a BP neural network model and verify the model at 243 K.Results indicated that low temperatures retarded the rise of pH,TVB-N,and TBA values,improving water retention capacity of Trachinotus ovatus.The BP neural network model had high regression coefficients(r2:0.8642-0.9904),low mean square error(MES:0.1658-1.7882),and relative error within 10%and could accurately predict the quality change of Trachinotus ovatus under the freezing temperatures of 266 K-218 K.Therefore,(BP)neural network model has great potential in predicting the shelf life of Trachinotus ovatus in frozen storage.

Low cycle fatigue behavior of zirconium−titanium−steel composite plate

The low cycle fatigue behavior of zirconium−titanium−steel composite plate under symmetrical and asymmetric stress control was studied.The effects of mean stress and stress amplitude on cyclic deformation,ratcheting effect and damage mechanism were discussed in detail.The results show that under symmetric stress control,the forward ratcheting deformation is observed.Under asymmetric stress control,the ratcheting strain increases rapidly with mean stress and stress amplitude increasing.Under high stress amplitude,the influence of mean stress is more significant.In addition,by studying the variation of strain energy density,it is found that the stress amplitude mainly promotes the fatigue damage,while the mean stress leads to the ratcheting damage.In addition,fractographic observation shows that the crack initiates in the brittle metal compound at the interface,and the steel has higher resistance to crack propagation.Finally,the accuracy of life prediction model considering ratcheting effect is discussed in detail,and a high-precision life prediction model directly based on mean stress and stress amplitude is proposed.

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.

Methodology for predicting the life of plasma-sprayed thermal barrier coating system considering oxidation-induced damage

The lifespan of plasma-sprayed thermal barrier coating(TBC)systems is difficult to predict owing to the variety of microstructures and deterioration histories.In this study,we developed a novel TBC damage model to reflect deterioration histories;thus,it can be applied to various TBCs.Damage to TBCs is classifed into oxidation and mechanical damage;therefore,a detailed deterioration history can be reflected.In addition,by introducing a virtual S–N diagram,a life prediction model that can be applied to TBCs with various microstructures was established.We used the proposed damage and life prediction models in isothermal aging and thermal cycle tests with different aging cycles.The predicted lifespan of TBCs by using the proposed models was within 95%of the results obtained by performing actual tests in the temperature range of 1150–1350℃.