干湿循环和动载耦合作用会导致煤矿岩石物理力学性质的劣化,引起地下岩体工程结构的破坏,诱发煤矿地下工程地质灾害和工程事故。基于纵波波速变化和Weibull分布统计损伤理论,推导了干湿循环与动载耦合作用下煤矿砂岩的损伤演化方程,探讨了动弹性模量取值方法对损伤演化的影响,发现以动态应力-应变曲线30%与70%峰值应力连线的斜率作为动弹性模量更能反映出本次试验砂岩的损伤演化规律。在此基础上,分析了干湿循环次数对总损伤变量和总损伤率演化的影响,得出干湿循环与动载耦合作用后砂岩的总损伤变量随着干湿循环次数的增加而增大,总损伤率随应变增长先增加后减小;建立了干湿循环和动载耦合作用下砂岩的动态本构模型并对其进行了验证,以期为深部地下岩体工程稳定性分析提供依据。
Abstract
Coupling wetting-drying cycles and dynamic loading deteriorates the physical and mechanical properties of coalmine rock, damages underground structure and even induces geological hazards and accidents in coalmine underground engineering. In the light of longitudinal wave velocity variation and Weibull distribution statistical damage theory, we deduced the damage evolution equation of coalmine sandstone under coupling wetting-drying cycles and dynamic loading, and investigated the damage evolution with the dynamic elastic modulus determined by different methods. We found that the method of determining dynamic elastic modulus as the average slope between 30% and 70% peak stress on dynamic stress-strain curve is more suitable for the damage evolution rule of tested coalmine sandstone. Moreover, we further examined the influence of wetting-drying cycle on total damage variable and total damage ratio, and unveiled that under coupling wetting-drying cycles and dynamic loading, damage variable enlarged with the proceeding of cyclic wetting and drying, while damage ratio increased first and then reduced with the growth of dynamic strain. Finally, we built and validated a dynamic constitutive model for coalmine sandstone under coupling wetting-drying cycles and dynamic loading. The test results are expected to offer basis for the stability analysis in deep underground rock engineering.
关键词
煤矿砂岩 /
干湿循环 /
动载作用 /
动弹性模量 /
损伤演化 /
本构模型
Key words
coalmine sandstone /
wetting-drying cycles /
dynamic loading /
dynamic elastic modulus /
damage evolution /
constitutive model
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基金
中国博士后科学基金项目(2018M642504);
安徽省自然科学基金项目(1808085QE148);
安徽省教育厅科学研究项目资助(KJ2017A097);
安徽省住房城乡建设科学技术计划项目(2017YF-08);
安徽理工大学青年教师科学研究资助项目(QN201607);
安徽理工大学博士基金项目(11674);
国家级大学生创新训练项目(201810361029)
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