Abstract

The drying-wetting cycles caused by operation of the Three Gorges Reservoir have considerable effect on the deterioration of reservoir bank rock mass, and the degradation of reservoir rock mass by the drying-wetting cycle is becoming obvious and serious along with the periodic operation. At present, the strength of the rock prediction research mainly focuses on the uniaxial strength, and few studies consider the drying-wetting effect and confining pressure. Therefore, in this paper, typical sandstone from a reservoir bank in the Three Gorges Reservoir area is taken as the research object, while the drying-wetting cycle test, wave velocity test and strength test are carried out for the research on the strength prediction of sandstone under the action of the drying-wetting cycle. The results show that the ultrasonic wave velocity Vp of the sandstone has an exponential function relation with the drying-wetting cycle number n, and the initial stage of drying-wetting cycles has the most significant influence on the wave velocity. Under different confining pressures, the compressive strength of sandstone decreases linearly with the increase of the drying-wetting cycle numbers, and the plastic deformation increases gradually. The damage variable of the sandstone has a power function relation with the increase of drying-wetting cycle numbers. A traditional strength prediction model based on P-wave velocity was established combined with the damage theory and Lemaitre strain equivalence hypothesis; in view of the defects of the traditional strength prediction model, a modified model considering both the drying-wetting cycle number and confining pressures was proposed, where the calculated results of the modified model are closer to the test strength value, and the prediction error is obviously decreased. This indicated that the modified model considering the drying-wetting cycle number and confining pressure is reasonable and feasible.

Highlights

  • Periodic operation of the Three Gorges Reservoir has changed the geological environment, which can lead to geological disasters, such as landslides, causing huge economic losses and social impacts

  • By taking sandstone as a research object, a series of tests under drying–wetting cycles with acid solution with pH of 7, 5 and 3 were conducted [8], and the results demonstrated that deviatoric stress is positively correlated with uniaxial compressive strength and cohesion, and showed a negative correlation with constant materials and angles of internal friction

  • The strength characteristics of argillaceous sandstone under drying–wetting cycles in an acid environment and simulated properties, such as particle contact and crack distribution of the specimens at peak strength during a triaxial compression test were researched by utilizing a particle flow code in 2 dimensions (PFC2D) program [9]

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Summary

Introduction

Periodic operation of the Three Gorges Reservoir has changed the geological environment, which can lead to geological disasters, such as landslides, causing huge economic losses and social impacts. The physical and mechanical properties of ignimbrites in Central Anatolia under 50 drying-wetting cycles were studied, and researchers found that the weight, porosity, water, P-wave velocity and uniaxial compressive strength had varying degrees of change [5]. By taking sandstone as a research object, a series of tests under drying–wetting cycles with acid solution with pH of 7, 5 and 3 were conducted [8], and the results demonstrated that deviatoric stress is positively correlated with uniaxial compressive strength and cohesion, and showed a negative correlation with constant materials and angles of internal friction. Based on porosity, density, longitudinal wave velocity, Poisson’s ratio and point load index, the uniaxial strength of carbonate rock was predicted separately through multivariate linear regression analysis and an artificial neural network [17].

Test Scheme
Ultrasonic Characteristics
Traditional Model for Predicting Strength Based on Wave Velocity
Error Analysis of Traditional Prediction Model
Proposed
Conclusions

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