Simple Predicting Method for Fatigue Crack Growth Rate Based on Tensile Strength of Carbon Steel

Three types of fatigue tests for an annealed carbon steel containing carbon of 0.42%were carried out on smooth specimens and specimens with a small blind hole in order to investigate the fatigue crack growth law.A simple predicting method for crack growth rates has been proposed involving strengthσband the relation between cyclic stress and strain.The validity of proposed method has been confirmed by experiments on several carbon steels with different loadings.

Crack Growth Rate Model Derived from Domain Knowledge-Guided Symbolic Regression

Machine learning(ML)has powerful nonlinear processing and multivariate learning capabilities,so it has been widely utilised in the fatigue field.However,most ML methods are inexplicable black-box models that are difficult to apply in engineering practice.Symbolic regression(SR)is an interpretable machine learning method for determining the optimal fitting equation for datasets.In this study,domain knowledge-guided SR was used to determine a new fatigue crack growth(FCG)rate model.Three terms of the variable subtree ofΔK,R-ratio,andΔK_(th)were obtained by analysing eight traditional semi-empirical FCG rate models.Based on the FCG rate test data from other literature,the SR model was constructed using Al-7055-T7511.It was subsequently extended to other alloys(Ti-10V-2Fe-3Al,Ti-6Al-4V,Cr-Mo-V,LC9cs,Al-6013-T651,and Al-2324-T3)using multiple linear regression.Compared with the three semi-empirical FCG rate models,the SR model yielded higher prediction accuracy.This result demonstrates the potential of domain knowledge-guided SR for building the FCG rate model.

Fatigue Crack Growth Behavior of Different Zones in an Annealed Automatic Gas Tungsten Arc Weld Joint of TA16 and TC4 Titanium Alloys

Based on the investigated microstructure of different zones in the annealed automatic gas tungsten arc weld joint of TA16 and TC4 titanium alloys,the mechanical property of them was assessed under fatigue crack growth rate tests.For evaluation of fatigue crack growth rate,three points bending specimens were used.The correlation between the range of stress intensity factor and crack growth rate was determined in different zones of the annealed weld joint.Fatigue crack growth rates were obviously different in different zones of weld joint of dissimilar titanium alloys,due to their different microstructures.Scanning electron microscope examinations were conducted on the fracture surface in order to determine the relevant fracture mechanisms and crack growth mechanisms with respect to the details of microstructure.

EFFECT OF OVERLOAD ON CRACK GROWTH IN FIBER REINFORCED METAL LAMINATES

This paper is concerned with fatigue behavior of glass fiber reinforced aluminium laminates (GLARE) under overload fatigue loading. The effect of single overload on the crack growth rates in GLARE was investigated, and the mechanism of the retardation of crack growth determined. Crack growth retardation by overload was observed in GLARE, but much smaller than monolithic metals. The retardation of crack growth in GLARE is only controlled by the effective stress intensity factor experienced by the constituent metals at crack tips.

Study on the Overload and Dwell-Fatigue Property of Titanium Alloy in Manned Deep Submersible

With the rapid development of ocean technology, the deep-sea manned submersible is regarded as a high-tech equipment for the exploration and exploitation of ocean resources. The safety of manned cabin has a decisive effect on the whole system. Ti-6 Al-4 V with the superior strength-to-weight ratio and corrosion resistance has been used for the manned cabin. The manned cabin experiences loading spectrum with different maximum stresses and different dwell time during their service life. The load sequence effects on dwell fatigue crack growth behavior of Ti-6 Al-4 V under different dwell time are investigated experimentally in this paper. The experimental results show that the crack tip plastic zone is enlarged by the dwell time and the overload retardation zone increases with dwell time under the same overload rate. A dwell fatigue crack growth model is proposed by modifying the crack tip plastic zone under the loading history with combinations of the single overload and dwell time factors are included in the modified model. Based on the experimental data, the overload retardation zone and the crack growth rates of Ti-6 Al-4 V are predicted by the modified model. A reasonable model for the load sequence effect on the dwell fatigue crack growth rates of Ti-6 Al-4 V is verified.

Effects of Pitting Corrosion on the Fatigue Behavior of Q235 Steel

In order to analyze the distribution and characterizations of corrosion pits on the corroded surface,the steel surface data was measured. Based on the method of the interacting pits,the types of pits corresponding to different exposure time were observed and categorized for completely understanding the effects on the fatigue behavior. The results showed that the conditions for estimating whether the pits interfere with each other should not be ignored; exposure time with 2 years was a critical time. The exposure time and the interacting pits can observably reduce the fatigue life of corroded steel. From these conclusions,the method of fatigue crack growth rate with the multi-pits interaction(FCGR-MPI) was developed and used to predict the fatigue behavior of corroded steel affected with the interacting pits. The predicted lives were also well agreed with the experimental results.

Effect of HIP Treatment on Fatigue Crack Growth Behavior of Ti–6Al–4V Alloy Fabricated by Electron Beam Melting

The effect of hot isostatic pressing treatment on the fatigue crack growth behavior of Ti-6Al-4V alloy fabricated by electron beam melting was investigated. The results indicate that the fatigue crack growth rate of the HIPed samples is higher than that of the as-fabricated one under certain stress intensity factor （AK 〈 18 MPa m^1/2）. With further increase in AK, the fatigue crack growth rates of the studied two samples become similar. The variation of α lamella thickness and the pore defects distribution have an effect on the fatigue crack growth rates in the studied samples, and the latter plays the dominant role.

Effect ofαphase on fatigue crack growth of Ti-6242 alloy

Fatigue crack growth as a function ofαphase volume fraction in Ti-6Al-2Sn-4Zr-2Mo（Ti-6242）alloy was investigated using fatigue testing,optical microscopy,scanning electron microscopy,and transmission electron microscopy.Theα＋βannealing treatments with different solid solution temperatures and cooling rates were conducted in order to tailor microstructure with differentαphase features in the Ti-6242 alloy,and fatigue crack growth mechanism was discussed after detailed microstructure characterization.The results showed that fatigue crack growth rate of Ti-6242 alloy decreased with the decrease in volume fraction of the primaryαphase（αp）.Samples with a large-sizedαgrain microstructure treated at high solid solution temperature and slow cooling rate have lower fatigue crack growth rate.The appearance of secondaryαphase（αs）with the increase of solid solution temperature led to crack deflection.Moreover,a fatigue crack growth transition phenomenon was observed in the Paris regime of Ti-6242 alloy with 29.8% αp（typical bi-modal microstructure）and large-sizedαgrain microstructure,owing to the change of fatigue crack growth mechanism.

Machine learning for predicting fatigue properties of additively manufactured materials

Fatigue properties of materials by Additive Manufacturing(AM) depend on many factors such as AM processing parameter, microstructure, residual stress, surface roughness, porosities, post-treatments, etc. Their evaluation inevitably requires these factors combined as many as possible, thus resulting in low efficiency and high cost. In recent years, their assessment by leveraging the power of Machine Learning(ML) has gained increasing attentions. A comprehensive overview on the state-of-the-art progress of applying ML strategies to predict fatigue properties of AM materials, as well as their dependence on AM processing and post-processing parameters such as laser power, scanning speed, layer height, hatch distance, built direction, post-heat temperature,etc., were presented. A few attempts in employing Feedforward Neural Network(FNN), Convolutional Neural Network(CNN), Adaptive Network-Based Fuzzy Inference System(ANFIS), Support Vector Machine(SVM) and Random Forest(RF) to predict fatigue life and RF to predict fatigue crack growth rate are summarized. The ML models for predicting AM materials' fatigue properties are found intrinsically similar to the commonly used ones, but are modified to involve AM features. Finally, an outlook for challenges(i.e., small dataset, multifarious features,overfitting, low interpretability, and unable extension from AM material data to structure life) and potential solutions for the ML prediction of AM materials' fatigue properties is provided.

Fatigue crack growth behavior of 2624-T39 aluminum alloy with different grain sizes

The microstructure of 2624-T39 aluminum alloy was analyzed by means of metallographic(OM), scanning electron microscope(SEM) and transmission electron microscope(TEM). The effects of different microstructure characteristics on the tensile properties and fatigue crack growth rate of 2624-T39 aluminum alloy were studied.Results showed that the grain size of the alloy was a typical fiber structure along the rolling direction, and the main second phase was the A_(l2)CuMg phase. The grain size of the alloy had an obvious influence on the fatigue crack growth rate, and the alloy showed a lower fatigue crack growth rate due to the larger grain size. The crack initiation zone on the fracture surface of alloys with lower fatigue crack growth rate was relatively rough, the crack propagation zone had obvious fatigue striations, and the transient fracture zone had a large number of smaller dimples.

Mechanical properties and microstructure of an α+β titanium alloy with high strength and fracture toughness

The Ti-Al-Sn-Zr-Cr-Mo-V-Si （Ti-62A） alloy, an alpha-beta alloy with high strength and fracture toughness, is currently used as an advanced structural material in aerospace and non-aerospace applications. Thermo-mechanical processes can be used to optimize the relationship between its strength and fracture toughness. A Ti-62A alloy bar can be machined through a transus β-forged plus α＋β solution treated and aged specimen with a lamellar alpha microstructure. The effects of heat treatment on the mechanical properties were discussed. Heat treatment provided a practical balance of strength, fracture toughness, and fatigue crack growth resistance. A comparison of the Ti-62A alloy with the Ti-62222S alloy under the same thermo-mechanical processing conditions showed that their properties are at the same level.

Effects of trace Zr on the microstructure and properties of 2E12 alloy

Al-4.0Cu-1.4Mg-0.6Mn （2E12） and Al-4.0Cu-1.4Mg-0.6Mn-0.3Zr aluminum billets were manufactured by soft-contact electromagnetic continuous casting （EMC）. Subsequent forging and heat treatment were conducted and the effects of Zr on the microstructure and properties of the Al-4.0Cu-1.4Mg-0.6Mn alloy were studied. The results show that the addition of 0.3% Zr can reduce the dendrite and refine grains. During forging and solution treatment, fine and dispersive Al3Zr particles precipitated from the supersaturated α （Al） solid solution in the heating process of the billet can effectively pin dislocations and subgrain boundaries. Because of the addition of Zr, the mechanical properties are improved with the tensile strength, yield strength, elongation, and contraction of the area increasing by 5.4%, 11.3%, 9.7%, and 12.6%, respectively. Moreover, under the condition of R = 0.1, the fatigue crack growth rate （da/dN） of the Al-4.0Cu-1.4Mg-0.6Mn-0.3Zr alloy is lower than that of the Al-4.0Cu-1.4Mg-0.6Mn alloy.

A fatigue damage-cumulative model in peridynamics

While the present structural integrity evaluation method is based on the philosophy of assumed similitude, Fatigue and Damage Tolerance(F&DT) evaluations for next generation of air-vehicles require high-fidelity physical models within cyberspace. To serve the needs of F&DT evaluation in digital twin paradigm, a fatigue damage-cumulative model within peridynamic framework is proposed in this paper. Based on the concept of fatigue element block and damage accumulation law in form of Coffin-Manson relationship, the proposed model applies to both fatigue crack initiation and fatigue crack growth;fatigue crack growth rates under constant-amplitude and simple variable-amplitude block loading cases can be well predicted for three common structural materials without inputs of Paris law parameters. Additionally, the proposed model can also be easily extended to a probabilistic version;for verification, multiple-site-damage problems are simulated and the statistic nature of fatigue process in experiments can be well captured. In the end, main features of the proposed model are summarized, and distinctions from the other models are discussed. There may be a potential for the peridynamic damage-cumulative model proposed in this work to numerically predict fatigue problems in digital twin paradigm for future generations of aerospace vehicles.

块体择优取向纳米孪晶铜的优异抗疲劳裂纹扩展性能

本文研究了具有不同微观结构(如晶粒尺寸和孪晶厚度)的块体择优取向纳米孪晶Cu(NT-Cu)的疲劳裂纹扩展(FCG)特性,着重讨论了裂纹闭合效应和近门槛值区域的本征FCG阻力.与传统无孪晶的粗晶Cu相比,NT-Cu样品表现出显著提升的疲劳裂纹扩展抗力(有效门槛值应力强度因子范围,△K_(th,eff)).这种增强的裂纹扩展阻力与NT-Cu中特殊的跨孪晶位错滑移模式有关.该位错主导着NT-Cu裂纹尖端的循环变形,有效降低了裂纹尖端循环滑移不可逆水平,从而提高了纳米孪晶材料损伤扩展的本征抗力.