舰用复合材料S2/430LV热环境下拉伸性能及预报

Tensile properties and prediction of shipborne composites S2/430LV in thermal environment

  • 摘要: 从宏观、微观角度分别对S2/430LV在热-力联合作用下拉伸损伤失效模式和高温热损伤形貌进行研究,并应用DMA和TG等技术手段对材料进行热性能分析,重点揭示了S2/430LV拉伸试样在20~180℃拉伸损伤失效机制及拉伸强度/模量随温度变化规律,并进行预报。研究表明:随着环境温度的增加,430LV树脂软化程度和流动性增加,树脂与纤维丝束粘接能力降低;在热-力联合作用下,拉伸强度和模量随着温度升高而降低,并且均在100℃附近降低最快;试样失效模式随着温度增加也发生变化,在100℃之前,失效模式表现为纤维完全断裂破坏,应力-应变曲线呈显著线弹性特征,但在100℃以后,失效模式变为层间分层失效,失效模式的变化也对材料拉伸承载方式产生一定影响,导致拉伸模量保留率高于强度保留率,应力-应变曲线也出现凹曲线特征;根据Gibson预报模型和Bisby预报模型,利用Origin软件快速、准确获取预报模型未知参数最优值,发现两种模型拟合结果与试验结果高度吻合。

     

    Abstract: The tensile damage failure mode and high-temperature thermal damage morphology of S2/430LV under the combined action of heat and force were studied from macro and micro perspectives, and the thermal properties of the materials were analyzed by DMA and TG. The failure mechanism of S2/430LV tensile specimens at 20-180℃ and the variation rule of tensile strength/modulus with temperature were revealed, and the prediction was made. The results show that with the increase of ambient temperature, the softening degree and fluidity of 430LV resin increase, and the adhesive ability between resin and fiber tow decreases. Under the combined action of heat and force, the tensile strength and modulus decrease with the increase of temperature, and both decrease most rapidly around 100℃. The failure mode of the sample also changes with the increase of temperature. Before 100℃, the failure mode shows complete fracture of the fiber, and the stress-strain curve shows significant linear elastic characteristics. But after 100℃, the failure mode changes to interlaminar delamination failure. The change of the failure mode also has a certain impact on the tensile bearing mode of the material, resulting in the tensile modulus retention rate higher than the strength retention rate, and the stress-strain curve also shows concave curve characteristics. Based on Gibson prediction model and Bisby prediction model, Origin software was used to quickly and accurately obtain the optimal values of unknown parameters of the prediction model. It is found that the fitting results of the two models are highly consistent with the experimental results.

     

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