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A three‐parameter Weibull small sample aggregation method is proposed to address the problem of small sample fatigue data in practical engineering. First, based on the empirical assumption that the shape parameter is a constant and data equivalent conversion and aggregation, the small sample fatigue life data are converted into "equivalent large samples." Second, through the linear relationship between logarithmic scale parameter and stress, an iterative procedure is established to estimate the scale parameters of small sample data. At the same time, the moment and rank estimation methods are used to solve the location parameters quickly. Finally, P–S–N curves with different survival rates are given, and a 7‐series aluminum alloy is selected to verify the correctness and reliability of the method proposed in this study. The results show that the predicted life obtained by the method still has high accuracy under a high survival rate, which can provide a theoretical basis for solving practical engineering problems. Highlights: A three‐parameter Weibull small sample aggregation method is proposed.The WSSA program is used to estimate the P–S–N curve of small sample data.The fatigue data of aluminum alloys verify the effectiveness of this method. [ABSTRACT FROM AUTHOR]

Fatigue is a phenomenon of high uncertainty,especially for components with multiple damage sites.The fatigue life（ either mean value or probability distribution of the random variable） of a complex component with multiple damage sites is not equal to that of a simple component with only one damage site.A multi-site damage component is a series system with many weak links（ damage sites） in probability sense.A probabilistic fatigue life prediction model for multi-site damage component is presented based on a systematic thought,as well as the order statistics and extreme statistics concept.Such developed model can naturally reflect the effect of the dependence among different damage sites.Experimental result and the example on multi-site damage component fatigue life prediction shows that the fatigue life of a multi-site damage component is much lower than that of a single site damage component.

The most applied principles for parameter estimation are maximum likelihood and least square error. This paper presents a new principle with regard to the parameter estimation of the three-parameter Weibull distribution. By transforming the cumulative distribution function, constructed is a mapping from the value of the random variable and its corresponding cumulative distribution probability to the scale parameter. The scale parameter estimated by such a mapping is the random variable value and the corresponding cumulative distribution probability dependent when the shape parameter and/ or location parameter applied in the mapping is subject to error. Given a set of random variable values or a set of sample values, a larger error in the shape/location parameter brings about larger differences between the scale parameter values obtained with the individual random variable values or sample values, respectively. Based on such a causal relationship between the discrepancy and the shape/ location parameter value applied in the mapping relation, a new parameter estimation method is proposed. For the Weibull distribution parameter estimation according to a set of sample values, the right shape parameter and location parameter are those minimizing the discrepancy between the scale parameter values obtained with the individual sample values, respectively. Case studies demonstrate that the proposed method outperforms the maximum likelihood method and the Weibull plot-based least squares method. [ABSTRACT FROM AUTHOR]

High-speed trains have a large amount of ancillary equipment, which is suspended from the underside of the train by means of a suspension structure. Due to the large mass of the ancillary equipment, the suspension structure is subjected to various loads during train operation and there is a risk of fatigue failure. In this paper, the stress distribution at the suspension point and the lo-cation of the maximum stress point under load are investigated in detail based on actual test loads at the suspension point and finite element simulation analysis. In order to further investigate the fracture failure of the suspension points, experimental studies were carried out. Firstly, static strength tests were carried out to obtain the load–displacement curves of the structural members and to determine the fracture strength of the structure based on the displacement sensors, and secondly, fatigue tests at different stress levels were carried out to obtain the load–life curves of the structural members and to investigate the probabilistic load–life curves at different reliability levels. The test results show that the structural component has a high fracture strength of 65kN, while the conditional fatigue strength is relatively low, corresponding to a load level of 12.5kN at a median life of 106 cycles. The above research work provides the necessary basis for the design, optimization and reliability assessment of the suspension structures of high-speed trains. [ABSTRACT FROM AUTHOR]

With the development of flexible devices, the demand for wearable power sources has increased and gradually become imperative. Zinc–air batteries (ZABs) have attracted lots of research interest due to their high theoretical energy density and excellent safety properties, which can meet the wearable energy supply requirements. Here, the flexibility of energy storage devices is discussed first, followed by the chemistries and development of flexible ZABs. The design of flexible electrodes, the properties of solid‐state electrolytes (SSEs), and the construction of deformable structures are discussed in depth. The researchers working on flexible energy storage devices will benefit from the work. [ABSTRACT FROM AUTHOR]

This paper focuses on the reliability estimation of Weibull distributions with zero-failure data. Since no product failure occurred in the tests, the conventional maximum likelihood method was not applicable. Recent methods ignore the estimation of location parameter and tend to be conservative. This study developed a new estimation technique to address these problems. A prior model between the life dispersion boundary and shape parameter is constructed by considering the historical failure data of similar high-reliability products. The failure probabilities for all samples were inferred using the E-Bayesian method, after which the reliability was estimated. Afterward, a confidence interval for reliability was obtained based on the bootstrap confidence interval and modified maximum likelihood method. A Monte Carlo simulation study demonstrated that the proposed method is satisfactory in terms of point estimates, confidence intervals, coverage probabilities, and computational efficiency. Finally, a real engineering example is introduced to illustrate the application of this method. [ABSTRACT FROM AUTHOR]

Lithium–sulfur (Li–S) batteries suffer from poor‐cycle stability and low Coulombic efficiency, which are mainly caused by the intrinsic polysulfides shuttle, resulting from not only concentration gradient diffusion but also slow conversion kinetics of polysulfides. Herein, nitrogen‐doped carbon‐coated cobalt nickel selenide (Co‐NiSe2@NC) with hollow structures is presented which can simultaneously accommodate the volume expansion of sulfur to maintain the integrity of the electrode, trap the polysulfides, and catalyze the conversion between lithium sulfide and lithium polysulfides to inhibit the polysulfides shuttle. When used to host 70 wt% sulfur, the resulted Co‐NiSe2@NC‐S composites electrode delivers a high initial discharge capacity of 930.4 mAh g−1 at 0.5 C, and after 200 cycles, a reversible discharge capacity of 544.6 mAh g−1 can still be maintained. [ABSTRACT FROM AUTHOR]