Fatigue life prediction of magnetorheological elastomers subjected to dynamic equi-biaxial cyclic loading

Prediction of fatigue life is of great significance in ensuring that dynamically loaded rubber components exhibit safety and reliability in service. In this text, the dynamic equi-biaxial fatigue behaviour of magnetorheological elastomer (MREs) using a bubble inflation method is described. Wöhler (S–N) curves for both isotropic and anisotropic MREs were produced by subjecting the compounds to cycling over a range of stress amplitudes (σ_a) between 0.75 MPa and 1.4 MPa. Changes in physical properties, including variation in stress–strain relations and complex modulus (E*) during the fatigue process were analysed. It was found that the complex modulus of MRE samples decreased throughout the entire fatigue test and failure took place at a limiting value of approximately 1.228MPa ± 4.38% for isotropic MREs and 1.295 ± 10.33% for anisotropic MREs. It was also determined that a dynamic stored energy criterion can be used as a plausible predictor in determining the fatigue life of MREs.     

Fatigue lifetime of AZ91 magnesium alloy subjected to cyclic thermal and mechanical loadings

In the present paper, thermo-mechanical fatigue (TMF) and low cycle fatigue (LCF) or isothermal fatigue (IF) lifetimes of a cast magnesium alloy (the AZ91 alloy) were studied. In addition to a heat treatment process (T6), several rare elements were added to the alloy to improve the material strength in the first step. Then, the cyclic behavior of the AZ91 was investigated. For this objective, strain-controlled tension–compression fatigue tests were carried out. The temperature varied between 50 and 200 °C in the out-of-phase (OP) TMF tests. The constraint factor which was defined as the ratio of the mechanical strain to the thermal strain, was set to 75%, 100% and 125%. For LCF tests, mechanical strain amplitudes of 0.20%, 0.25% and 0.30% were considered at constant temperatures of 25 and 200 °C. Experimental fatigue results showed that the cyclic hardening behavior occurred at the room temperature in the AZ91 alloy. At higher temperatures, this alloy had a brittle fracture. But also, it was not significantly clear that the cyclic hardening or the cyclic softening behavior would be occurred in the material. Then, the high temperature LCF lifetime was more than that at the room temperature. The OP-TMF lifetime was the least value in comparison to that of LCF tests. At the end of this article, two energy-based models were applied to predict the fatigue lifetime of this magnesium alloy.     

Cyclic strain hardening of polygonal and acicular ferrite/bainite microstructures in microalloyed steels in the temperature range − 150°C to 27°C

Cyclic strain hardening has been observed to be markedly sensitive to microstructural changes in microalloyed steels. Two significantly different microstructures - polygonal ferrite grains of average grain size 10–120 μm and acicular ferrite/upper bainite colonies of dimensions 200–625 μm - were examined in order to determine the influence of each on cyclic strain hardening and related properties. Tests were conducted at temperatures between ?150 and 27°C. The cyclic strain hardening exponent, β_c, was significantly more sensitive to changes in the size of the polygonal ferrite grains than to changes in the acicular ferrite/upper bainite colony size.     

Constitutive modeling of the thermo-mechanical fatigue and lifetime behavior of the cast steel 1.4849

A life prediction model for the austenitic steel 1.4849 is developed that can be integrated efficiently in the industrial product development process. The material is characterized by isothermal low-cycle-fatigue (LCF) and thermo-mechanical-fatigue (TMF) tests over a wide temperature range. A simple rheological constitutive model is adjusted to the experimental results, whereby special value is set on a physically reasonable and efficient reduction of the parameter set. The Manson–Coffin damage law is enhanced by a temperature dependent parameter in order to reproduce adequately the failure characteristics of the material. Application of the derived model in a thermo-mechanical simulation of a turbine housing illustrates its good quality: the predicted critical positions correlate well with the experimental results.     

氮等离子体浸没离子注入技术改善轴承钢滚动接触疲劳寿命和机械性能的研究

研究了氮等离子体浸没离子注入(N-PIII)技术处理后GCr15轴承钢表面的滚动接触疲劳特征和机械性能。测试了改性前后试样的滚动接触疲劳寿命和磨痕光学形貌、摩擦磨损行为及纳米压痕硬度。结果表明,处理后试样的最大显微硬度较基体增大近一倍,摩擦系数从0.95下降到0.15。在赫兹接触应力为5.1 GPa,90%置信区间下的L10和L50寿命分别增加了99.6%和236.3%。分析不同处理参数下的Weibull分布曲线和光学显微形貌可知,脉冲偏压、材料内部缺陷、基体表面粗糙度、注入时间和N离子注入剂量对疲劳寿命均有很大影响。疲劳寿命和相关机械性能的改善主要源于N-PIII处理所导致的氮化物强化相和残余压应力的共同作用。     

A neural-network approach to describe the scatter of cyclic stress–strain curves

In order to predict a product’s durability in the early phases of development it is necessary to know the stress–strain behaviour of the material, its resistance to fatigue and the loading states in the material. These parameters, however, tend to exhibit a considerable degree of uncertainty. Due to a lack of knowledge of the actual circumstances in which the product is used, during the early development phase, simulations based on statistical methods are used. The results of the experiments show that the cyclic stress–strain curves demonstrate not only a large amount of scatter, but also a dependence on the temperature, the size of the cross-section, the content of alloying elements, the loading rate, etc.This article presents a method for modelling cyclic stress–strain curve scatter using a hybrid neural network for an arbitrary selection of the influencing factors. In an example of the measured data for a high pressure die-cast aluminium alloy it is clear that the suggested method is suitable for describing cyclic stress–strain curves. The main advantage of a hybrid neural network in comparison with a conventional method is the neural network’s ability to precisely describe the influence of various factors, and their combinations, based on the form and scatter of the cyclic stress–strain curve families. Defining the model parameters, i.e., training the neural network, is a procedure that does not require any additional user interventions; however, it enables us to gather knowledge that would otherwise require a lot of research. Thus, the trained neural network is a robust tool that can be used to predict cyclic stress–strain curves for random values of influencing factors. The capabilities of the presented method are only limited by the quantity of the measured data used for the neural-network training.     

The influence of the temperature on the stress‐strain curves of a bearing steel and a case hardening steel

In the present paper the influence of the temperature and strain rate on the stress strain behaviour of two different steels were investigated. Two microstructures were considered: pearlitic and austenitic. Tensile tests with the bearing steel 100Cr6 and the case hardening steel 20MnCr5 were accomplished at various temperatures. For this purpose the Ludwik equation was used to describe the stress‐strain curve. The parameter of the constitutive equation was determined for each steel and microstructure. Especially for the austenitic state the parameters of the used material law were described as a function of the temperature.     

Calculating the fatigue life of smooth specimens of two-phase titanium alloys subject to symmetric uniaxial cyclic load of constant amplitude

A system of microstructure-dependent fatigue failure models that allows calculating the number of stress cycles to failure of smooth specimens in the absence of data on the fatigue resistance of the material is proposed. Fatigue life is represented as the sum of the number of stress cycles to the initiation of a microstructurally short crack with a depth equal to one grain size and the number of stress cycles to the instant the growing physically small and long crack reaches the depth taken as a fatigue failure criterion. To fill the models, it is necessary to test standard specimens under monotonic short-term tension to determine the elastic modulus, Poisson’s ratio, and the proportional limit and to analyze the microstructure and texture of the material to determine the Taylor factor, the magnitude of the Burgers vector, and the distance between neighboring parallel slip planes in the lattice, depending on which slip system is activated relative to the tension direction. The models are applicable to metals and alloys in which a fatigue crack is initiated along a persistent slip band in a surface grain under high-cycle loading. The models are validated against fatigue test data for flat specimens of different two-phase titanium alloys (VT3-1, IMI 834, Ti–6Al–4V, VT6, VT16, VT22, VT23, LCB) with different types of microstructure (bimodal, globular, fine-grained β-transformed) subject to symmetric in-plane bending. The plotted S–N curves are in a satisfactory agreement with experimental data.     

Dynamic mechanical response of polyetheretherketone (PEEK) exposed to cyclic loads in the high stress tensile regime

Tensile fatigue tests of PEEK at high load levels were carried out and analyzed regarding the dynamic mechanic behavior of the material during the tests. The experiments were conducted in the high stress tensile regime of PEEK. After a short period of unsteady temperature increase distinct material changes were observed during the tests at medium and high load levels. The storage modulus increased continuously while the loss modulus, loss factor (tan δ) and the dissipation energy rate decreased continuously. It was concluded that the accumulation of residual stresses because of partially irreversible deformation causes this effect.