Softness abrasive flow processing method can effectively resolve the processing problem of workpiece with large plane or irregular geometric surface. Based on this advantage, to overcome the processing problem of hard brittle materials of existing methods, a surface-constrained softness abrasive flow processing method is proposed. Through setting the narrow constrained flow passage on the surface of workpiece, and adopting the multi-directional injection method, the high speed vortex abrasive flow can create and polish the workpiece. Traditional modelling method of abrasive flow is hard to reflect the particle-wall contact effect which is with important significant in fluid-based processing field. To address this problem, a computational fluid dynamics coupled with discrete element method (CFD-DEM) modelling approach oriented to abrasive flow is proposed, and the particle-wall collision distributions and the material removal distributions can be obtained. On this basis, the processing uniformity of the proposed processing method is studied. The results show that the inlet-diameter greatly affected the uniformity of particle-wall collision distribution, and the collision distribution can obtain an optimal value with the increase of inlet-diameter; with the change of particles flow pattern, the mechanism of fluid viscosity on the material removal will be different, and the uniformity of material removal can increase by the processing of low viscosity abrasive flow. Finally, a processing apparatus is developed, and the comparative experiments have validated the effectiveness of the proposed processing method and modelling method, and the experimental results show that the roughness of silicon wafer can decrease from 506.71 nm to 10.17 nm by means of the proposed processing method.
JI Shiming
,
GE Jiangqin
,
GAO Tao
,
TAN Dapeng
,
CHEN Guoda
,
LI Chen
. Study on Machinability of Surface-constrained Softness Abrasive Flow Based on CFD-DEM Coupled Method[J]. Journal of Mechanical Engineering, 2018
, 54(5)
: 129
-141
.
DOI: 10.3901/JME.2018.05.129
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