Purpose This study aims to explore the superiority of the compound dimple (e.g. the rectangular-rectangular dimple) and compare its tribological performance for rough parallel surfaces with those of the traditional one-layer dimple (simple dimple). Design/methodology/approach A mixed-lubrication model for a rough textured surface is established and solved using the finite difference method for film pressure and contact pressure. To accelerate the evaluation of surface deformation, the efficient Continuous convolution fast Fourier transform algorithm is applied. The effects of the compound dimple on the tribological performance for the rough parallel surfaces is numerically investigated. And these effects are compared with those of the simple dimple. Furthermore, a reciprocating friction test is conducted to verify the superiority of the compound dimple. Findings The compound dimple exhibits better tribological performances in comparison with the traditional simple dimple, that is, a larger load-carrying capacity and a smaller friction coefficient. To achieve the best tribological performances for the rough parallel surfaces, the depth ratio of the lower pore to the total pore of the compound dimple and the dimple interval should be reasonably chosen. For the surface with compound dimples, there exists an optimal surface roughness to simultaneously maximize the load-carrying capacity and minimize the friction coefficient. The smaller friction coefficient of the surface with compound dimples is verified by the reciprocating friction test. Originality/value The compound dimple is proposed and the superiority of this novel surface texture is confirmed. This study is expected to provide a new texturing method to improve the tribological performances of the traditional simple dimple.

Traditional finishing technology is difficult to realize the precision machining of complex geometric parts. Abrasive flow machining technology solves this problem well. Taking the spur internal gear as the research object, the wall shear force, static pressure, dynamic pressure and abrasive velocity vector of the internal channel of the straight internal gear under different inlet velocity, abrasive concentration and abrasive particle size are analyzed by using the large eddy simulation method, and the action law of different parameters on the machining of straight internal gear by solid-liquid two-phase abrasive flow is discussed. At the same time, orthogonal test was carried out. The results show that the solid-liquid two-phase abrasive flow machining technology can effectively remove the burrs, pits and bulges on the tooth surface of spur internal gear, reduce the tooth surface roughness and improve the surface quality. The optimal combination of processing parameters and the primary and secondary order of various factors affecting processing are obtained by range analysis and analysis of variance. The regression equation is constructed by regression analysis to verify the effectiveness and accuracy of the model, which provides theoretical support and data reference for actual processing and production.

Traditional finishing technology is difficult to realize the precision machining of complex geometric parts. Abrasive flow machining technology solves this problem well. Taking the spur internal gear as the research object, the wall shear force, static pressure, dynamic pressure and abrasive velocity vector of the internal channel of the straight internal gear under different inlet velocity, abrasive concentration and abrasive particle size are analyzed by using the large eddy simulation method, and the action law of different parameters on the machining of straight internal gear by solid-liquid two-phase abrasive flow is discussed. At the same time, orthogonal test was carried out. The results show that the solid-liquid two-phase abrasive flow machining technology can effectively remove the burrs, pits and bulges on the tooth surface of spur internal gear, reduce the tooth surface roughness and improve the surface quality. The optimal combination of processing parameters and the primary and secondary order of various factors affecting processing are obtained by range analysis and analysis of variance. The regression equation is constructed by regression analysis to verify the effectiveness and accuracy of the model, which provides theoretical support and data reference for actual processing and production.

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