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Dimethicone-assisted laser cutting of CFRP hole

Chen Xinghua, Li Wenyuan, Rong Youmin, Zhang Guojun, Chen Long, Huang Yu

Archives of Civil and Mechanical Engineering

2022

Vol. 22, no. 4

art. no. e182, 2022

When cutting carbon fiber reinforced polymer (CFRP) plate with UV nanosecond laser, the surface heat-affected zone (HAZ) such as fiber exposure and carbonization will occur, which affects the surface morphology and properties of CFRP. In this paper, dimethicone-assisted laser cutting technology is proposed. Compared with laser direct cutting, we found that dimethicone-assisted cutting has obvious advantages in cutting CFRP. Due to the heat transfer inhibition of dimethicone, there is almost no burning phenomenon of matrix materials. The orthogonal test method was used to study the three key process parameters (laser scanning speed, repetition frequency and concentric circle spacing) of dimethicone-assisted laser cutting CFRP. It is concluded that the HAZ width can be controlled at 38.70–54.77 μm with dimethicone, compared with the traditional direct machining (HAZ width: 109.64–439.13 μm). Under the optimal cutting parameters of laser scanning speed of 500 mm/s, repetition rate of 50 kHz and concentric circle spacing of 0.04 mm, the minimum HAZ is 38.70 μm, which is reduced by 85.89% (the HAZ width of laser direct machining is 274.37 μm).

Modeling of a Bingham model of a magnetorheological damper considering stochastic uncertainties in their geometric variables

Chen Ke, Yu Xiaopeng, Wang Haishuo, Zheng Hongmei, Zhang Guojun, Wu Rui

Journal of Theoretical and Applied Mechanics

2021

Vol. 59 nr 1

53--65

Stochastic uncertainty theory is used to develop a new Bingham model of magnetorheological dampers superior to the existing model. Some input variables are defined as stochastic variables by the stochastic factor method, and the stochastic Bingham model is developed by the algebraic synthesis method. Curves of the damping force obtained by the stochastic Bingham model and the Bingham model in the literature are compared with experimental results, revealing that the curves obtained by the stochastic Bingham model are much closer to the experimental curves. Therefore, we confirm that the stochastic Bingham model is superior to the model from the literature.