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| Nonlinear creep intrinsic modeling of hard rock considering aging damage |
| SONG Zhanping1，2，3，WANG Bowen1，2，FAN Shengyuan1，2，ZHANG Yutao1，2，WANG Junbao1，2，3 |
(1. School of Civil Engineering，Xi'an University of Architecture and Technology，Xi'an，Shaanxi 710055，China；
2. Shaanxi Key Laboratory of Geotechnical and Underground Space Engineering，Xi'an University of Architecture and Technology，Xi'an，Shaanxi 710055，China；3. Institute of Intelligent Infrastructure Construction，Xi'an University of Architecture and Technology，Xi'an，Shaanxi 710055，China)
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Abstract In order to investigate the deformation characteristics of hard rock during the whole creep process，this study carried out indoor creep tests on hard tuff with constant peripheral pressure and graded ascending axial pressure. Through the characterization of hard rock creep under different stress paths，combined with scanning electron microscope(SEM) tests，the relationship between the fine-scale damage evolution mechanism and macroscopic damage characteristics was explored. Based on the introduction of damage variables into the deterioration effect of rock mechanical properties over time during the creep process，an intrinsic model of damage creep was constructed that can describe the whole process of hard rock creep. At the same time，by optimising the BP neural network model，the identification and prediction of the model parameters were improved. The results show that，with increasing the bias stress level，the hard tuff shows more obvious brittle-ductile deformation transformation characteristics，and the rock creep phenomenon is more obvious. Under the continuous action of a higher bias stress，the accumulation of rock damage and the deterioration of mechanical properties are more adequate，which leads to the accelerated creep characteristics of the hard tuff during the damage stage with increasing the peripheral pressure，and the damage of the hard rock becomes more intense. Compared with Burgers，the improved damage constitutive model can better describe the whole process of hard rock creep，which verifies the reasonableness of the model. Based on the optimised BP neural network model，the accelerated creep curve of hard rock under high stress level can be accurately predicted，which improves the applicability of the model. The results of this study not only enrich the theoretical study of hard rock creep constitutive model，but also provide theoretical guidance for the design of long-term stability of engineering rock bodies in hard rock formations.
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2024, Vol. 43 
