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With the popularity of high-rise buildings, wall inspection and cleaning are becoming more difficult and associated with danger. The best solution is to replace manual work with wall-climbing robots. Therefore, this paper proposes a design method for a rolling-adsorption wall-climbing robot (RWCR) based on vacuum negative pressure adsorption of the crawler. It can improve the operation efficiency while solving the safety problems.

The pulleys and tracks are used to form a dynamic sealing chamber to improve the dynamic adsorption effect and motion flexibility of the RWCR. The mapping relationship between the critical minimum adsorption force required for RWCR downward slip, longitudinal tipping and lateral overturning conditions for tipping and the wall inclination angle is calculated using the ultimate force method. The pressure and gas flow rate distribution of the negative pressure chamber under different slit heights of the negative pressure mechanism is analysed by the fluid dynamics software to derive the minimum negative pressure value that the fan needs to provide.

Simulation and test results show that the load capacity of the RWCR can reach up to 6.2 kg on the smooth glass wall, and the maximum load in the case of lateral movement is 4.2 kg, which verifies the rationality and effectiveness of the design.

This paper presents a new design method of a RWCR for different rough wall surfaces and analyses the ultimate force state and hydrodynamic characteristics.

The purpose of this study is to solve the issues of time-consuming and complicated computation of traditional measures, as well as the underutilization of two-dimensional (2D) phase-trajectory projection matrix, so a new set of features were proposed based on the projection of attractors trajectory to characterize the friction-induced attractors and to reveal the tribological behavior during the running-in process.

The frictional running-in experiments were conducted by sliding a ball against a static disk, and the friction coefficient was collected to reconstruct the friction-induced attractors. The projection of the attractors in 2D subspace was then mapped and the distribution of phase points was adapted to conduct the feature extraction.

The evolution of the proposed moment measures could be described as “initial rapid decrease/increase- midterm gradual decrease/increase- finally stable,” which could effectively reveal the convergence degree of the friction-induced attractors. Moreover, the measures could also describe the relative position of the attractors in phase–space domain, which reveal the amplitude evolution of signals to some extent.

The proposed measures could reveal the evolution of tribological behaviors during the running-in process and meet the more precise real-time running-in status identification.

With the rapid advancement in the automotive industry, the friction coefficient (FC), wear rate (WR) and weight loss (WL) have emerged as crucial parameters to measure the performance of automotive braking systems, so the FC, WR and WL of friction material are predicted and analyzed in this work, with an aim of achieving accurate prediction of friction material properties.

Genetic algorithm support vector machine (GA-SVM) model is obtained by applying GA to optimize the SVM in this work, thus establishing a prediction model for friction material properties and achieving the predictive and comparative analysis of friction material properties. The process parameters are analyzed by using response surface methodology (RSM) and GA-RSM to determine them for optimal friction performance.

The results indicate that the GA-SVM prediction model has the smallest error for FC, WR and WL, showing that it owns excellent prediction accuracy. The predicted values obtained by response surface analysis are closed to those of GA-SVM model, providing further evidence of the validity and the rationality of the established prediction model.

The relevant results can serve as a valuable theoretical foundation for the preparation of friction material in engineering practice.

The purpose of this paper is to explore the correction mechanism of resilient safety culture on new generation of construction workers (NGCWs)' unsafe behavior and test the multiple mediation effects of job crafting and perceived work meaningfulness based on the context of Chinese construction industry in order to find a new way to effectively correct the NGCWs' unsafe behavior.

A theoretical model of correction mechanism was established based on literature research and theoretical deduction. An empirical study was employed based on confirmatory factor analysis and regression analysis with a sample of 404 NGCWs in China.

The results indicated that resilient safety culture can effectively correct NGCWs' unsafe behavior through job crafting and perceived work meaningfulness. Job crafting and perceived work meaningfulness can play independent and serial mediating roles between resilient safety culture and unsafe behavior.

Research results only represent a short-term law about the correction mechanism of NGCWs' unsafe behavior based on a questionnaire study from China's construction industry. It is necessary to continue to implement a longitudinal study to test it in a relatively long period in future research. The findings also need to be verified based on the young construction workers in other countries.

This study provides a theoretical basis and feasible management reference for construction enterprises in China to correct NGCWs' unsafe behavior from the perspective of resilient safety culture. Furthermore, the construction of resilient safety culture in construction enterprises can help NGCWs better carry out job crafting and perceive the meaning of work.

This paper clarifies the correction mechanism of resilient safety culture on unsafe behavior of NGCWs, and further tests the independent mediating roles and a serial mediating role of job crafting and perceived work meaningfulness between resilient safety culture and unsafe behavior, which fills the research gap about the influence mechanism of resilient safety culture on young construction workers' unsafe behavior and enriches the theoretical system of unsafe behavior correction of construction workers.

The assembly simulation in tolerance analysis is one of the most important steps for the tolerance design of mechanical products. However, most assembly simulation methods are based on the rigid body assumption, and those assembly simulation methods considering deformation have a poor efficiency. This paper aims to propose a novel efficient and precise tolerance analysis method based on stable contact to improve the efficiency and reliability of assembly deformation simulation.

The proposed method comprehensively considers the initial rigid assembly state, the assembly deformation and the stability examination of assembly simulation to improve the reliability of tolerance analysis results. The assembly deformation of mating surfaces was first calculated based on the boundary element method with optimal initial assembly state, then the stability of assembly simulation results was assessed by the density-based spatial clustering of applications with noise algorithm to improve the reliability of tolerance analysis. Finally, combining the small displacement torsor theory, the tolerance scheme was statistically analyzed based on sufficient samples.

A case study of a guide rail model demonstrated the efficiency and effectiveness of the proposed method.

The present study only considered the form error when generating the skin model shape, and the waviness and the roughness of the matching surface were not considered.

To the best of the authors’ knowledge, the proposed method is original in the assembly simulation considering stable contact, which can effectively ensure the reliability of the assembly simulation while taking into account the computational efficiency.