Tensile properties of ZT7H/5429 composite laminates under hygrothermal environment
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摘要:
为湿热环境条件下ZT7H/5429复合材料层合板的拉伸破坏应变基准值提供了一种精细化确定方法。通过在不同湿热环境下对含孔复合材料层合板进行拉伸试验，定量分析了温度和湿度对于层合板拉伸破坏应变的影响，并采用小子样整体推断技术建立了拉伸破坏应变预测模型。结果表明：拉伸破坏应变随温度升高而下降，并且下降幅度趋于平缓，而湿度所产生的影响并不显著。在拉伸破坏应变预测曲面的基础上，通过引入单侧容限系数进一步确定了拉伸破坏应变B基准值。相比传统单点法仅分析单一状态试验数据来获得B基准值，该方法充分考虑了不同状态下试验数据之间的关系模型，得到的B基准值具有2%～25%的提升，为复合材料结构的精细化设计提供了理论依据。
Abstract:A refined method for determining the basis values of tensile failure strain for ZT7H/5429 composite laminates in hygrothermal environment was proposed. Through the tension tests of the composite laminates with open hole under different environmental conditions, the influence of temperature and humidity on the tensile failure strain was quantitatively analyzed, and a tensile failure strain prediction model was established based on small sample holistic inference technology. The results showed that the tensile failure strain decreased with the increase of temperature, and the decline became flat gradually, while the influence of humidity was not so significant. Based on the tensile failure strain prediction surface, the B-basis value of tensile failure strain was further determined by introducing one-sided tolerance-limit factor. Compared with the traditional single-point method of only analyzing the test results in the single state, the proposed method fully took into account the connection between the experimental data in different states and the B-basis values increased by 2% to 25% in most cases, providing a theoretical basis for the refined design of composite structures.
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Key words:
- composite laminates /
- hygrothermal environment /
- tensile property /
- B-basis value /
- small sample
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表 1 ZT7H/5429复合材料层合板试验矩阵
Table 1. ZT7H/5429 composite laminates test matrix
参数 数值及说明 材料 ZT7H/5429 铺层顺序 [−45/0/45/90/0/0/−45/90/45/0]s 开孔直径/mm 6.35 试件尺寸/mm3 250 × 36 × 2.5 温度/℃ 25 60 100 130 试件
数量相对
湿度/%20 8 8 8 8 50 8 8 8 7 80 8 8 8 8 
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表 2 线性回归分析结果
Table 2. Results of linear regression analysis
相对湿度/% $\hat C$ $\hat m$ 20 10099 −0.093 50 7518 −0.015 80 8243 −0.043
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表 3 线性异方差回归分析结果
Table 3. Results of linear variance regression analysis
参数 $\hat C$ $\hat m$ $\hat \lambda $ ${\hat \eta _0}$ ${\hat \eta _1}$ 估计结果 8552 −0.052 −0.014 0.012 −0.008
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表 4 传统单点法与本文方法比较
Table 4. Comparison of the traditional single-point method with the proposed method
温度/℃ 相对湿度/% 拉伸许用值/10−6 提升率/% 单点法 本文方法 25 20 7150 6965 −2.59 25 50 6819 6948 1.90 25 80 6069 6931 14.21 60 20 6122 6549 6.98 60 50 6853 6533 −4.67 60 80 6084 6517 7.12 100 20 5149 6318 22.70 100 50 6807 6303 −7.41 100 180 5225 6287 20.34 130 20 5771 6203 7.48 130 50 6092 6188 1.57 130 80 5994 6172 2.98
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