Cure-induced residual stresses assessment of composite materials based on machining deformation
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摘要: 各向异性的复合材料在固化成型过程中极易产生残余应力,直接影响后续的加工与连接装配。因此,掌握复合材料固化残余应力的分布规律是实现复合材料制件高性能制造的前提和基础。本文在分析传统切割槽法测量应力的基础上,根据变形产生机制将制件在切割槽加工后所产生的变形分为由固化残余应力释放及重力引起的两部分组成。在利用有限元方法给出重力影响制件几何变形规律后,依据弯曲变形理论建立了固化残余应力与试件几何变形之间的映射关系,并据此获得固化残余应力分布状态。与传统切割槽法所得结果对比后表明:本文所提方法能得到与传统切割槽法相一致的应力分布规律;当选择合适的测量点位置后二者对固化残余应力估算的平均误差可控制在14%以内。Abstract: Cure-induced residual stresses are usually unavoidable due to anisotropic properties of composite materials, which have great influence on following machining and assembly process. Therefore, it is necessary to understand the distribution of cure-induced residual stresses in the materials for high performance composite part manufacturing. The traditional slitting method used for residual stresses assessment was analyzed and deformations caused by the slitting process were divided into two groups. One was caused by the release of cure-induced residual stresses and the other was by gravity. After the partial deformation caused by gravity being obtained by using finite element analysis, relationship between the remained deformation and the cure-induced residual stresses was set up by using bending deformation theory, which was used to evaluate the distribution of cure-induced residual stresses. Experimental results show that the proposed method can obtain the same distribution as that of the traditional slitting method and the difference may less than 14% when a proper measurement point is selected.
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Key words:
- composites /
- cure /
- residual stress /
- measurement /
- slitting method
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表 1 试件力学性能
Table 1. Mechanical properties of specimen
Aluminum E=70 GPa G=27 GPa ν=0.33 Composite Ex=Ey=6.5 GPa Gxy=2.5 GPa ν=0.31 表 2 加工参数
Table 2. Machining parameters
Spindle speed/(r·min−1) Feed rate
/(mm·min−1)Cutting depth/mm Cutting times 4000 180 1 29 表 3 铝合金-复合材料层压板应力对比及误差分析
Table 3. Stress comparison and error analysis of aluminum-composite laminate
Depth/mm Slitting method/MPa Semi-analytical method/MPa Error/% 80 100 140 80 100 140 1 0.71 0.49 0.46 0.46 30.8 34.9 35.3 2 −0.19 −0.11 −0.07 −0.05 43.4 60.7 72.0 3 −1.03 −0.67 −0.67 −0.62 35.2 35.0 39.9 4 −1.55 −1.14 −1.16 −1.16 26.2 25.0 24.8 5 −1.85 −1.51 −1.55 −1.59 18.5 16.3 13.9 6 −1.97 −1.80 −1.72 −1.83 8.7 12.6 7.2 7 −1.92 −1.83 −1.92 −1.92 4.9 0.0 0.3 8 −1.74 −1.64 −1.63 −1.77 5.7 6.3 1.9 9 −1.44 −1.42 −1.49 −1.55 0.9 3.5 7.6 10 −1.04 −1.15 −1.11 −1.09 10.7 7.1 4.9 11 −0.57 −0.68 −0.64 −0.55 19.1 12.8 3.3 12 −0.05 −0.12 −0.03 −0.06 124.0 51.1 21.8 13 0.49 0.50 0.55 0.38 2.1 11.4 23.2 14 1.04 1.11 1.20 1.05 6.9 15.7 1.3 15 1.57 1.89 1.84 1.80 20.3 17.7 14.7 16 2.05 2.48 2.36 2.31 20.9 15.0 12.3 17 2.48 2.97 2.94 2.83 19.8 18.8 14.1 18 2.81 3.35 3.34 3.20 19.0 18.6 14.0 19 3.04 3.56 3.49 3.44 17.3 14.7 13.1 20 3.13 3.59 3.49 3.48 14.6 11.5 11.3 21 3.07 3.30 3.28 3.24 7.7 6.9 5.7 22 2.83 2.81 2.79 2.80 0.5 1.2 0.8 23 2.38 2.21 2.22 2.28 7.4 6.7 4.2 24 1.72 1.54 1.63 1.64 10.5 5.2 4.6 25 0.80 0.58 0.69 0.79 28.2 13.7 1.8 26 −0.38 −0.33 −0.30 −0.34 12.3 19.4 9.4 27 −1.85 −1.46 −1.47 −1.57 21.0 20.5 15.2 28 −3.24 −2.50 −2.63 −2.75 22.9 18.7 15.2 29 −4.57 −3.61 −3.73 −3.92 20.9 18.3 14.3 Average error 20.0 17.2 14.1 -
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