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热-氧-辐照复合环境下硅泡沫加速老化研究进展 被引量:1

Research progress on accelerated aging of silicon rubber foam under thermo-oxygen-irradiation complexconditions
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摘要 硅泡沫是特殊工程装置中的关键结构材料,其在服役过程中不仅承受机械载荷,还将长期承受气氛-温度-辐照等复杂环境载荷。研究发现,硅泡沫在热-氧-辐照-机械等多种应力作用下发生老化,从而导致材料性能下降,且硅泡沫内部具有多级复杂微结构,与传统的硅橡胶热降解相比,在热-氧-辐照组合条件下的硅泡沫老化本质上更复杂,准确预测硅泡沫寿命一直面临巨大挑战。开发新的实验技术、发展更强的数值建模能力、建立硅泡沫多应力因子老化的理论模型等,对于预测硅泡沫使用寿命和指导性能评估具有重要意义。本文从单因子热氧老化、辐射老化机理以及多因子加速老化三个方面对近年来硅泡沫加速老化研究成果进行了梳理,对当前的研究进展进行了综述。 Silicone rubber foam is a significant structural material in specific systems.It works effectively under mechanical and complex environmental loads such as thermal,oxygen,irradiation,and so on.Previous studies have showed that the silicone rubber foam ages under complex conditions such as heat,oxygen,irradiation,and mechanical,which leads to the deterioration of its material properties.The aging mechanism of porous silicon rubber foam under the combination of thermal oxygen and irradiation is more complicated in contrast to the ordinary thermal degradation of rubber.It has always been challenging to predict the service life of silicon rubber foam accurately.The development of new experimental techniques for enhancing numerical modeling ability and establishing a theoretical multi-field aging model has been a key concern.Further,it is essential for predicting the life of silicon rubber foam and guiding performance evaluation.In this study,the research results of accelerated the aging of silicon rubber foam have been presented,primarily in three aspects including thermo-oxygen aging,radiation aging,and multi-field speed-up aging.Furthermore,the current research progress and latest developments in this field of study have been summarized.
作者 岳动华 靳凡 韦利明 王罗斌 YUE Donghua;JIN Fan;WEI Liming;WANG Luobin(China Academy of Engineering Physics,Institute of Systems Engineering,Mianyang 621999,China)
出处 《辐射研究与辐射工艺学报》 CAS CSCD 2022年第3期1-14,共14页 Journal of Radiation Research and Radiation Processing
关键词 硅泡沫 多因子加速老化 阿伦尼乌斯老化模型 寿命预测 Silicon rubber foam Multi-factor accelerated aging Arrheniusaging model Life prediction
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