摘要
制备游艇用玻纤–碳纤混杂增强2597PT不饱和树脂复合材料,应用人工加速老化方法,对其进行盐雾老化实验,研究其在三种盐雾条件下(盐度6%,温度50℃;盐度6%,温度25℃;盐度3%,温度50℃)的性能演变规律,建立其对应的寿命模型并进行寿命预测。研究表明:材料盐雾老化后与老化前相比,特征官能团的吸收峰位置未发生变化;随着老化时间的增加,材料力学性能均呈现下降的趋势,且在盐度6%,温度50℃条件下老化最为严重;在G.M. Gunyaev剩余强度理论基础上,采用origin对其进行非线性拟合,得到老化最严重的盐雾环境(即温度50℃、盐度6%)下材料剩余拉伸强度公式,相关系数R2=0.99,结合CCS《材料与焊接规范》 2018版要求,预测此材料在盐度6%,温度50℃条件下可安全使用约2 000 d。
Carbon-glass hybrid reinforced 2597PT unsaturated resin composites for yachts were prepared.Salt spray aging experiments were carried out by artificial accelerated aging method.The evolution law of the performance under three salt spray conditions(salinity 6%,temperature 50℃;salinity 6%,temperature 25℃;salinity 3%,temperature 50℃)was studied,and the corresponding life model was established and life prediction was carried out.The results show that there is no change in the position of absorption peaks of characteristic functional groups before and after aging in three salt spray environments,and the mechanical properties of materials decrease gradually with the extension of aging time in three salt spray environments,and the most serious aging is at salinity of 6%and temperature of 50℃.On the basis of G.M.Gunyaev’s residual strength theory,the non-linear fitting of origin was used to obtain the formula of residual tensile strength of materials under the most severe aging salt fog environment(temperature 50℃,salinity 6%).The correlation coefficient R2=0.99.Combining with the requirements of the 2018 edition of《The Code for Materials and Welding》of CCS,the above-mentioned material was predicted.It can be used for about 2 000 days.
作者
李萌
Li Meng(Guangdong Zhuhai Supervion Testing Institute of Quality and Metrology,Zhuhai 519000,China;National Quality Supervising Test Center for Materials of Ship and Marine Engineering Equipment,Zhuhai 519000,China)
出处
《工程塑料应用》
CAS
CSCD
北大核心
2019年第3期85-91,共7页
Engineering Plastics Application
基金
广东省质量技术监督局科技计划项目(2017PZ10)
关键词
玻纤–碳纤混杂增强复合材料
盐雾老化
力学性能
寿命预测
carbon-glass fiber reinforced composite reinforced composites
salt fog aging
mechanical performance
life prediction