Conventional-sized specimens have been well and widely applied in research on hydrogen embrittlement. However, when the limited-size core components (nozzles and valves, etc.) of hydrogen energy equipment are evaluated for service damage, traditional testing with conventional-sized samples is no longer applicable and micro-sample testing methods are required. In this paper, recent progress in the characterization of hydrogen embrittlement achieved via a small-sized sample tensile test, small punch test and nanoindentation test is reviewed. The commonly used geometries and dimensions of various small-sized specimens are first described and the in situ hydrogen-containing environment testing cases equipped with small-sized specimens are presented, proving the advantages of direct observations of hydrogen influences on the mechanical property and microstructure evolution. Then, the quantitative analysis of hydrogen embrittlement sensitivity involving a small punch test is discussed, with a focus on the comparisons of the hydrogen embrittlement index calculated using different definition methods. Finally, the nanoindentation test of investigation on the interaction between hydrogen and dislocation in metals and the effect of indentation strain rate are summarized. Furthermore, the specific research directions and applications of micro-size specimens for further investigation on hydrogen embrittlement are identified.

Mechanical behaviors at fatigue crack tips of cracked specimens under negative loading ratios are studied in detail by the finite element method in this paper. Three factors induced by specimen type and loading type on fatigue crack field are discussed, including constraint, compressive loading effect (CL effect) and crack contact closure. For mode I crack under negative loading ratios, the effects of the CL effect and crack contact closure on plastic strain accumulations are dominant, with the constraint effect being minor. The constraint effect has effects on the monotonous plastic zone, while the CL effect and contact closure both have effects on the reversed plastic zone (RPZ) and residual tensile plastic zone (RTPZ). That is, the higher the constraint, the smaller the size of the monotonous plastic zone; the greater the CL effect, or the smaller the contact degree, the larger the size of RPZ and RTPZ. For mode II crack, there is only CL effect on the crack tip field without the effect of constraint and contact closure, so plastic strain accumulation at the mode II crack tip is much greater than that at the mode I crack tip when they are under the same loading level.

The utilization of micro-sample testing has demonstrated its effectiveness in conducting quantitative research on mechanical properties, damage evolutions and fracture features. For in-service equipment, millimicron sampling allows for non-destructive testing and analysis of mechanical performance evolution during operation. This paper presents a comparative study of the miniature uniaxial tensile test (MUTT) and small punch test (SPT) by experimental and finite element methods. As a comparison, the standard conventional-size tensile tests were also carried out. Detailed analyses of the elastoplastic behaviors and damage evolutions of MUTT and SPT were presented, followed by an application case illustrating the characterization of hydrogen embrittlement sensitivity based on MUTT and SPT. An inverse finite element modeling method of load–displacement curve reproduction was used to calibrate the variations of damage parameters of hydrogen-charged MUTT and SPT specimens. Hydrogen embrittlement (HE) indexes were determined by using different calculation methods. The results reveal that the HE sensitivity estimated by MUTT is higher than that measured by SPT, which is related to the different deformation processes and strain rates of the two testing methods.

In the typical vibration signal of a reciprocating air compressor, multi-source nonlinear characteristics are exhibited and are often drowned out in background noise, which leads to a lack of robustness in traditional feature analysis methods and difficulty in effective extraction. To address this issue, an algorithm based on ABC-SGMD is proposed in this paper. The Symplectic Geometry Mode Decomposition (SGMD), which is optimized with the Artificial Bee Colony algorithm (ABC), is utilized to decompose the signal, and a multi-feature fusion model is constructed for fault feature extraction. The extracted features are then input into the Self-Adaptive Evolutionary Extreme Learning Machine (SaDE-ELM), and a fault diagnosis model based on ABC-SGMD and SaDE-ELM is established. Ultimately, the signals of reciprocating air compressors and experimental data are used to demonstrate the applicability of the method. The results manifest that this framework has superiority in handling nonlinear and non-stationary signals.