Abstract To study the progressive evolution law and effective control measures of the traction sliding failure of the rock slope with bedding planes parallel to the slope (bedding rock slope), taking a highway bedding slope in China as an example, through finite element numerical calculation, the elastic-plastic damage constitutive model of the slip plane was assigned. The evolution law of slip plane damage over time and the method for determining the initial crack length were analysed from the dual perspectives of shear stress and slope displacement. The optimal anchoring angle for slope anchoring engineering was determined through mathematical analysis, and the treatment effect of the pile-anchor combined structure on reinforcing bedding rock slope traction-type slip failure was further explored. The results show that during the progressive failure process, the shear stress distribution on the slip surface is camel-hump shaped, with peak points appearing on the slip plane and continuously advancing towards the rear edge of the slope body along the slip plane until reaching the traction-type failure boundary; the toe of the slope is the first to experience slope displacement and remains the maximum throughout the process, with the rear edge of the traction slip plane deforming throughout the entire process. An exponential fitting relationship is established for the distribution of slip plane displacement, with a fitting goodness of 0.996; the stress camel-hump point on the slip plane can define the damaged section of the slip plane, that is, the initial crack length value of the bedding rock slope, the progressive line intersection point defined by the start and end points of slip plane displacement coincides with the stress camel-hump point, with only a 1.8% error between the two; the slope anchoring angle has a monotonic distribution characteristic, establishing a quantitative relationship between the optimal anchoring angle and the dip angle and internal friction angle of the slip plane; after reinforcement with the pileanchor combined structure, the slope displacement of the bedding rock slope slip plane is reduced by 93.33%, indicating a good treatment effect.

A series of annealing treatments were designed to investigate the microstructure structure and surface morphology of hydrogenated diamond-like carbon coating with gradient Cr and Si (DCrSi) in different environments (argon & isostatic pressure) at different temperatures (400°C, 500°C, and 600°C). The pressure effect on the stability of DCrSi coatings was deduced from the analysis of the microstructure structure and surface morphology by using scanning electron microscopy (SEM), surface roughness test, and Raman spectroscopy. The experiment results show that no apparent change to the layer structure can be found in the argon annealed and HIPped coatings. Similar to argon annealed coatings, with increasing HIPping temperature, the surface roughness of coatings increases, and the sp3 content of the coatings reduces. The relatively low roughness of the HIPped surfaces compared with the argon annealed ones could be attributed to the delayed transformation from sp3 carbon bonding to sp2 carbon bonding (i.e., graphitization) by high pressure. Compared with Si-free DCr coating, for Si-containing DCrSi coatings, Si bonded with C from broken C-H bonding and C-C bonding to form SiC quasi compound. Adding silicon into DLC can increase the density of the coatings.

In this paper, the deformation-induced martensitic transformation behavior of 304 and 316 stainless steels is studied. The results show that martensitic transformation occurs in both 304 stainless steel and 316 stainless steel. With the increase of the strain, the martensitic transformation of the stainless steel samples increases, but the 304 stainless steel increases more significantly. The external shape of stainless steel has a certain influence on martensitic transformation behavior, and the martensite content of bar-shaped stainless steel is lower than that of plate-shaped samples under the same strain. The study results can provide technical guidance for the selection of stainless steel materials in the power grid.

In current assembly process of the aircraft complex structural parts, there are problems such as nonlinear, multilevel strong coupling and large uncertainty transfer relationship between assembly quality and its deviation sources. In this paper, an assembly deviation transfer method based on transfer entropy network graph is proposed to address the challenges. Firstly, the source of assembly deviation is analysed by constructing a multi-level assembly coordination network with assembly deviation detection data. Secondly, an assembly deviation propagation model is established by combining transfer entropy and complex network graph theory. This model provides insights into the topological relationship of assembly deviations and introduces causal metrics for evaluation. The effectiveness of method is demonstrated through its application in the assembly of an aircraft nose, thereby verifying its practicality and utility.

Currently, there is not enough research on the mechanism that causes the vibration of landing gear walk when an aircraft anti-skid brake is activated. This paper aims to provide a comprehensive analysis of the characteristics of the landing gear walk and the associated research. It shows that the walk vibration is caused by a cantilever beam’s tip mass and that the study should focus on the landing gear walk’s characteristics. Firstly, according to the transverse vibration theory of cantilever beams, the transcendental equation for calculating the natural frequency of the landing gear can be obtained. After that, the influence of the structural parameters of the landing gear on each order of the natural frequency is analyzed. To ensure that the conclusions derived are applicable to all landing gear structures, the structural parameters are selected to cover both small unmanned aerial vehicles and large civil aircraft. Finally, the influence of the axial pressure of the landing gear on its inherent frequency is analyzed.

In response to the issue of coordinated guidance for vehicle groups, a neural network-based time-to-go prediction method has been designed. The influence of the motion state of both the vehicle and the target on the prediction results has been considered in this method. Compared with the classical method, the prediction error of the moving target is obviously reduced. A guidance law with a time synergy coefficient is proposed. This method adjusts the flight trajectory of the vehicles by the time-to-go error, ensuring that the cluster of vehicle arrive at the target simultaneously. According to the simulation results, the prediction error of the neural network is less than 0.4 s, and the maximum coordination error is 0.2 s, which achieves the effect of cooperative interception.

China is developing rapidly in renewable energy development, electricity market reform, and carbon market construction, using market mechanisms for efficient planning and investment. The electricity and carbon markets are interrelated for market entities. This context has led to a dual-level optimization model for renewable energy investment planning, considering cost recovery and new power system goals. The model includes deriving electricity carbon coupling quotations for conventional units based on dynamic carbon emission characteristics and proposing an electricity spot market mechanism influenced by carbon quota trading. The model’s upper level maximizes renewable energy investment capacity, determining its size and location, while the lower level simulates electricity spot and voluntary emission reduction market trading to guide investment decisions. The model transformed into a mixed integer linear programming problem for optimal solutions was validated numerically, examining various factors affecting optimal renewable energy investment capacity.

Turbulent Rayleigh-Bénard convection holds significant scientific and engineering implications, with one of the most debated topics in convection research being the ultimate scaling of the Nusselt number at extremely high Rayleigh numbers. A widely adopted method for investigating this issue is direct numerical simulation (DNS); however, achieving the ultimate Rayleigh number with DNS can be prohibitively expensive. To overcome this limitation, one approach is to employ a small simulation domain size for high Rayleigh number cases. This study explores the impact of simulation domain size by conducting DNS with a large geometrical aspect ratio. Specifically, we perform spectral analysis on the covariance of wall-normal velocity and temperature, along with its transport equations. The results reveal that the characteristic length scale in the intermediate length-scale region linearly increases with wall-normal distance. Moreover, the spectral analysis indicates that large-scale structures play a crucial role in the dynamics of the covariance of wall-normal velocity and temperature. However, the study suggests that these large-scale structures have a minimal impact on the scaling of the Nusselt number. This is attributed to the fact that large-scale structures remain in regions away from the wall, and no processes transfer them from large to small-scale structures. As a consequence, the dynamics of the covariance of wall-normal velocity and temperature in the close vicinity of the wall experience little influence from large-scale dynamics.

A modelling framework based on the resolvent analysis and machine learning is proposed to predict the turbulent energy in incompressible channel flows. In the framework, the optimal resolvent response modes are selected as the basis functions modelling the low-rank behaviour of high-dimensional nonlinear turbulent flow-fields, and the corresponding weight functions are determined by data-driven neural networks. Turbulent-energy distribution in space and scales, at the friction Reynolds number 1000, is predicted and compared to the data of direct numerical simulation. Close agreement is observed, suggesting the feasibility and reliability of the proposed framework for turbulence prediction.

Aiming at the docking requirements of small satellites in orbit service, an axial, radial double-locking satellite docking mechanism was designed to realize the docking and separation of small satellites. Capture docking using the butt bar and the groove. The mechanism possesses multiple advantages, such as simple structure and fast response. A dynamic model considering contact, collision, buffering, and friction was established, and ADAMS software simulated the docking process. Apart from that, the dynamics and motion data of the mechanism were obtained. As revealed by the results, under the initial conditions of the general light and small docking mechanism, the mechanism can achieve the set task and complete the docking with a small collision force. What’s more, the buffer device can absorb 85.5% of the energy of the satellite, and the mechanism has a certain attitude correction ability. Altogether, this exploration can provide a reference for designing satellite docking mechanisms and formulating a docking strategy in the future.