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The purpose of this study is to investigate the effect of iron content on the friction and wear performances of Cu–Fe-based friction materials under dry sliding friction and wear test condition.

Cu–Fe-based friction materials with different iron content were prepared by powder metallurgy route. The tribological properties of Cu–Fe-based friction materials against GCr15 steel balls were studied at different applied loads and sliding speeds. Meanwhile, microstructure and phases of Cu–Fe-based friction materials were investigated.

Cu–Fe-based friction materials with different iron content are suitable for specific applied load and sliding speed, respectively. Low iron content Cu–Fe-based friction material is suitable for a high load 60 N and low sliding speed 70 mm/min and high iron content Cu–Fe-based friction material will be more suitable for a high load 60 N and high sliding speed 150 mm/min. The abrasive wear is the main wear mechanism for two kinds of Cu–Fe-based friction materials.

The friction and wear properties of Cu–Fe-based friction materials with different iron content were determined at different applied loads and sliding speeds, providing a direction and theoretical basis for the future development of Cu–Fe-based friction materials.

The purpose of this paper is to propose a seamless active interaction control method integrating electromyography (EMG)-triggered assistance and the adaptive impedance control scheme for parallel robot-assisted lower limb rehabilitation and training.

An active interaction control strategy based on EMG motion recognition and adaptive impedance model is implemented on a six-degrees of freedom parallel robot for lower limb rehabilitation. The autoregressive coefficients of EMG signals integrating with a support vector machine classifier are utilized to predict the movement intention and trigger the robot assistance. An adaptive impedance controller is adopted to influence the robot velocity during the exercise, and in the meantime, the user’s muscle activity level is evaluated online and the robot impedance is adapted in accordance with the recovery conditions.

Experiments on healthy subjects demonstrated that the proposed method was able to drive the robot according to the user’s intention, and the robot impedance can be updated with the muscle conditions. Within the movement sessions, there was a distinct increase in the muscle activity levels for all subjects with the active mode in comparison to the EMG-triggered mode.

Both users’ movement intention and voluntary participation are considered, not only triggering the robot when people attempt to move but also changing the robot movement in accordance with user’s efforts. The impedance model here responds directly to velocity changes, and thus allows the exercise along a physiological trajectory. Moreover, the muscle activity level depends on both the normalized EMG signals and the weight coefficients of involved muscles.

Well-constructed transportation infrastructure may effectively decrease barriers to the flow of innovative human resources and inventive elements, accelerating enterprise innovation activities. This study will explore how HSR helps enterprises achieve ambidextrous innovation, including the mediating mechanism of absorbed slack resources, innovative talents, and the heterogeneous effects of management shareholding ratio and financing constraints.

Based on resource dependence theory and social network theory, this study employs a quasi-natural experiment of China’s high-speed railway and builds a multi-time point DID model to investigate its influence on enterprise ambidextrous innovation.

Results suggest that the HSR positively influences both exploitative and exploratory innovation, and the influence is more substantial on exploitative innovation. Further analysis finds two influencing channels through which HSR influences enterprise ambidextrous innovation: providing redundant resources and attracting innovative talents. Heterogeneity analysis indicates that HSR has a more significant positive effect on exploratory innovation for enterprises with high management shareholding. In the low financing constraint group, the HSR opening has a more significant impact on ambidextrous innovation.

In ambidextrous innovation, enterprises should rationalize the allocation of resources, attach importance to the innovative talent introduction, and choose differentiated paths based on intrinsic characteristics. Meanwhile, the government should actively improve the HSR routes and continuously improve the innovative environment.

This study enriches the theoretical research framework of HSR and ambidextrous innovation by identifying the channel mechanisms and boundary conditions through which HSR affects ambidextrous innovation and expands the consequences of HSR and the antecedents of ambidextrous.

This paper aims to establish the microstructures and the process-structure relationships in duplex stainless steel powders consolidated by selective laser melting (SLM).

A priori data on energy density levels most appropriate to consolidation of duplex stainless steel powders through SLM served as the basis to converge on the laser settings. Experimental designs with varying laser power and scan speeds and test pieces generated allowed metallographic evaluations based on optical and scanning electron microscopy and electro backscatter diffraction analyses.

Duplex stainless steel powders are established for processing by SLM. However, the dynamic point heat source and associated transient thermal fields affect the microstructures to be predominantly ferritic, with grains elongated in the build direction. Austenite precipitated either at the grain boundaries or as Widmanstätten laths, whereas the crystallographic orientations and the grain growth are affected around the cavities. Considerable CrN precipitation is also evidenced.

Duplex stainless steels are relatively new candidates to be brought into the additive manufacturing realm. Considering the poor machinability and other difficulties, the overarching result indicating suitability of duplex powders by SLM is of considerable value to the industry. More significantly, the metallographic evaluation and results of the current research allowed further understanding of the material consolidation aspects and pave ways for fine tuning and establishment of the process-structure-property relationships for this important process-material combination.

To prepare a new type of composite for selective laser sintering 3D printing, the surface of Al₂O₃ nanoparticles was modified by the coupling agent (3-methacryloxypropyl)-trimethoxy silane (KH570) before coated with thermoplastic epoxy resin (TER).

Laser diffraction confirmed that the size distribution of prepared powder materials in this study ranged between 20 to 80 µm. Thermogravimetric analysis (TGA) showed that the loading of organic matter was below 5 per cent. Fourier transform infrared spectroscopy indicated that the silane coupling agent molecule bound strongly with the alumina. X-ray diffraction confirmed the prepared powder materials to be α-alumina. Through the angle of repose (AOR) test, the AOR = 18.435º was obtained, suggesting the high flowability of prepared powder materials. Scanning electron microscopy (SEM) observation demonstrated that the shape of the prepared powder materials was sphere-like grains.

Molding properties of prepared powder materials were studied on the basis of particle size distribution, particle size, sphericity, crystal structure and the reaction mode of the TER. This prepared powder materials can be well applied to the production of epoxy resin-coated Al₂O₃ composite parts with high precision and good mechanical performance.

This composite can be well applied to the production of epoxy resin-coated Al₂O₃ composite parts with high precision and good mechanical performance.

The purpose of this paper is to extract electrochemical reaction kinetics parameters, such as Tafel slope, exchange current density and equilibrium potential, which cannot be directly measured, this study aims to propose an improved particle swarm optimization (PSO) algorithm.

In traditional PSO algorithms, each particle’s historical optimal solution is compared with the global optimal solution in each iteration step, and the optimal solution is replaced with a certain probability to achieve the goal of jumping out of the local optimum. However, this will to some extent undermine the (true) optimal solution. In view of this, this study has improved the traditional algorithm: at each iteration of each particle, the historical optimal solution is not compared with the global optimal solution. Instead, after all particles have iterated, the optimal solution is selected and compared with the global optimal solution and then the optimal solution is replaced with a certain probability. This to some extent protects the global optimal solution.

The polarization curve plotted by this equation is in good agreement with the experimental values, which demonstrates the reliability of this algorithm and provides a new method for measuring electrochemical parameters.

This study has improved the traditional method, which has high accuracy and can provide great support for corrosion research.

This purpose of this paper is to design a peg-in-hole controller for a cable-driven serial robot with compliant wrist (CDSR-CW) using cable tensions and joint positions. The peg is connected to the robot link through a CW. It is required that the controller does not rely on any external sensors such as 6-axis wrist force/torque (F/T) sensor, and only the compliance matrix’s estimated value of the CW is known.

First, the peg-in-hole assembly system based on a CDSR-CW is analyzed. Second, a characterization algorithm using micro cable tensions and joint positions to express the elastic F/T at the CW is established. Next, under the premise of only knowing the compliance matrix’s estimate, a peg-in-hole controller based on force/position hybrid control is proposed.

The experiment results show that the plug contact F/T can be tracked well. This verifies the validity and correctness of the characterization algorithm and peg-in-hole controller for CDSR-CWs in this paper.

First, to the authors’ knowledge, there is no relevant work about the peg-in-hole assembly task using a CDSR-CW. Besides, the proposed characterization algorithm for the elastic F/T makes the peg-in-hole controller get rid of the dependence on the F/T sensor, which expands the application scenarios of the peg-in-hole controller. Finally, the controller does not require an accurate compliance matrix, which also increases its applicability.

This paper aims to verify whether selective laser melting (SLM) could be used for manufacturing mold with conformal cooling channels and determine whether the mechanical properties development of SLM manufacturing maraging steel mold would be beneficial to improve the quality of mold.

A series of block specimens and cylindrical tensile specimens are manufactured by SLM, and then are heat treated by solution treatment (ST) and solution treatment + aging treatment (ST + AT), respectively. The development of microstructure, microhardness and tensile strength of specimens is investigated. Then, a mold with conformal cooling channels is designed and manufactured by SLM and machined after ST with microhardness decreasing.

The morphology of microstructure varies widely under different heat treatment. The microhardness and tensile strength decrease after ST with cellular structure broken, which is conducive to mechanical finishing for mold to improve surface accuracy. After that, the hardness and strength of the mold increase significantly by AT with the precipitation of Ni3Mo, Fe2Mo and Ni3Ti particles. The maraging steel mold with conformal cooling channels can be manufactured by SLM successfully. And the surface accuracy of mold could be improved easily by machining.

Compared with the traditional mold with simple cooling channels, the mold with conformal cooling channels can be manufactured by SLM directly. The hardness of maraging steel mold manufactured by SLM can be reduced through ST, which is conducive to mechanical finishing for overcoming the defect of low precision of SLM directly manufacturing mold. This provides a new way for manufacturing mold of high quality.

The pulsed-laser powder bed fusion (PBF) process is an additive manufacturing technology that uses a laser with pulsed beam to melt metal powder. In this case, stainless steel SS316L alloy is used to produce complex components. To produce components with acceptable mechanical performance requires a comprehensive understanding of process parameters and their interactions. This study aims to understand the influence of process parameters on reducing porosity and increasing part density.

The response surface method (RSM) is used to investigate the impact of changing critical parameters on the density of parts manufactured. Parameters considered include: point distance, exposure time, hatching distance and layer thickness. Part density was used to identify the most statistically significant parameters, before each parameter was analysed individually.

A clear correlation between the number and shape of pores and the process parameters was identified. Point distance, exposure time and layer thickness were found to significantly affect part density. The interaction between these parameters also critically affected the development of porosity. Finally, a regression model was developed and verified experimentally and used to accurately predict part density.

The study considered a range of selected parameters relevant to the SS316L alloy. These parameters need to be modified for other alloys according to their physical properties.

This study is believed to be the first systematic attempt to use RSM for the design of experiments (DOE) to investigate the effect of process parameters of the pulsed-laser PBF process on the density of the SS316L alloy components.

The purpose of this study is to establish a finite element (FE) model with the random distribution of the Nylon12/hydroxyapatite (PA12/HA) composite material in selective laser sintering (SLS) process for considering the material anisotropy, which aims to obtain the law of temperature and stress changes in PA12/HA sintering.

By using python script in Abaqus, the FE model is established in which the two materials are randomly distributed and are assigned to their intrinsic temperature-dependent physical parameters. Molten pool sizes at various process parameters were evaluated in terms of numerical simulation and scanning electron microscope analysis, identifying a good agreement between them. Evaluation of temperature and stress distribution under the condition of different HA contents was also conducted.

It shows that the uneven distribution and quantity of HA powder play a vital role in stress concentration and temperature increase. Additionally, the influence of HA addition on the mechanical performance of SLS-fabricated parts shows that it is conducive to improve compressive strength when the HA ratio is less than 5% because an excess of HA powder tends to bring about a certain amount of microspores resulting in a decrease in part density.

The FE model of the PA12/HA composite material with parameterized random distribution in SLS can be applied in other similar additive manufacturing technologies. It provides a feasible guideline for the numerical analysis of properties of composite materials.