Graphene is an ideal material in the reinforcement of metal-matrix composites owing to its outstanding mechanical and physical properties. Herein, we have investigated the surface enhancement of iron via a computational nanoindentation process using molecular dynamics simulations. The findings of our study show that graphene can enhance the critical yield strength, hardness and elastic modulus of the composite to different degrees with the change of the number of graphene layers. In the six tested models, the composite with trilayer graphene on the surface produces the strongest reinforcement, with an increased magnitude of 432.1% and 169.5% in the hardness and elastic modulus, respectively, compared with pure iron. Furthermore, it is revealed that high temperature could weaken the elastic bearing capacity of the graphene, resulting in a decrease on the elastic mechanical properties of the graphene/Fe composite.

We have investigated the nano-indentation responses of graphene/aluminum systems via computational nano-indentation processes by using molecular dynamics simulations. The effects of system temperature, grain-orientation and bilayer graphene are also investigated. We demonstrate that, the graphene coating enlarges the load-carrying area by about 5.36 times and changes the deformation behaviors of aluminum substrate during nano-indentation processes. The load bearing capacity of graphene/Al system is significantly improved by about 4.7 times compared with that of bare Al system. It is revealed that higher system temperature weakens the ultimate indentation depth and corresponding load. The grain orientation of aluminum substrate hardly affect the indentation mechanical properties of graphene/Al system. The strengthening effect of bilayer graphene is about 1.5 times that of monolayer graphene.

Load spectrum is the basis of wear analysis and life prediction in journal bearing. This paper proposed a method to generate the wear load spectrum from the measured loads that avoiding the errors introduced by the assumptions of traditional constant load. An axle pin load sensor that can recognize the load value and its orientation is developed to test the original wear loads of journal bearing in a concrete pump under working conditions. The interactive influence of perpendicular components in the measured loads is involved by introducing two effect coefficients. Subsequently, the amplitude distribution of the wear load and its lasting time are extracted from the measured complex load-time history using the rain-flow counting method and Weibull distribution. The wear load spectrum is generated by dividing the continuous load into eight load steps. The validity of the approach is supported by finite element analysis on the wear simulation of journal bearing using the generated load spectrum and the measured load. In addition, the effects of load types and load sequence on the wear are discussed based on the proposed method and the FE model. This study provides guidelines to efficiently generate the wear load spectrum for journal bearing, and enhances its reliability of wear prediction in the experimental tests and theoretical analysis.

Molecular dynamics (MD) simulations were carried out to study the mechanical properties of co-continuous Al/SiC nanocomposites under tensile loading. Three cases of different models were implemented to investigate the influence of volume fraction (Vf) of SiC, thickness of SiC skeletons and shape of Al nanowire on the mechanical properties of the nanocomposites. It is found that the ultimate strength and Young's modulus of nanocomposites increase nonlinearly with the Vf of SiC, whereas the limit strains decrease with the increasing Vf of SiC. The Young's modulus obtained by MD simulations are in good agreement with the prediction by micromechanics methods and experimental results. In addition, the thickness of SiC skeletons and the shape of Al nanowire have a significant impact on the mechanical behaviors of co-continuous Al-SiC nanocomposites. This study on the mechanical properties of co-continuous Al-SiC nanocomposites will be helpful to further understanding the mechanical behaviors of the metal/ceramics co-continuous composites.

The detection equipment for measuring the burnup depth in spent fuel rods is a vital component of the spent fuel management system. which can determine the burnup depth of spent fuel board and plays a crucial role in safeguarding the safety, economic efficiency, and structural integrity of the fuel assembly. This study introduces an innovative technical approach for assessing the burnup depth of spent fuel veneers, utilizing transmitted thermal neutron imaging technology. We have significantly enhanced the design of a thermal neutron moderator collimator, leading to remarkable improvements in the quality of the thermal neutron beam. Following moderation by the collimator, the ultimate thermal neutron injection rate at the designated sample location exceeds 10³ n/cm², with thermal neutrons comprising over 74% of the collimated neutron beam. This advanced measurement system enables us to obtain a detailed two-dimensional distribution map of thermal neutrons transmitted through spent fuel boards with varying burnup depths. By analyzing the grayscale intensity patterns in these maps, we can accurately evaluate the burnup degree within the simulated spent fuel plate. Furthermore, we establish a correlation between the transmitted thermal neutron count in the imaging field and the burnup depth of the spent fuel veneer. This allows for precise determination of burnup depth through the analysis of the two-dimensional distribution of transmission thermal neutron intensity. Our findings demonstrate the feasibility of a scheme for detecting the burnup depth in spent fuel boards based on transmission thermal neutron imaging technology, and obtained a linear relationship between the neutron transmission count and the burnup depth of the spent fuel plate, laying a solid theoretical foundation for future research and development of testing equipment to assess burnup in spent fuel veneers.