Abstract
Stability assessment of rock slopes in hydropower engineering regions is an important and complex issue. Rock mass classification systems are a good approach because they can thoroughly consider many factors influencing rock slope stability. The slope stability probability classification (SSPC) system is a novel method. However, it has two limitations when applied to rock slopes: 1) it is only suitable for slopes less than 45 m in height, and 2) there is great subjectivity and randomness in the estimation of intact rock strength. Therefore, this study presents two modifications of the SSPC system by adopting the Hoek-Brown strength criterion and an empirical formula for maximum slope height. Evaluation of results from of 34 typical rock slopes of the major hydropower engineering regions in China indicated that the accuracy rate of the modified SSPC for stability evaluation of these slopes was 61.8%, and the accuracy for stability evaluation of 10 slopes with non-structural control failure was 80%. The stability values of stable and unstable slopes obtained using the modified SSPC were different to those obtained using the Chinese Slope Mass Rating (CSMR) and modified CSMR systems. In addition, the identification accuracy rate of the modified SSPC was significantly higher than that of the CSMR and modified CSMR. Therefore, the modified SSPC can be applied to hydropower engineering regions, providing a new means of rapidly evaluating the slope stability of high rock slopes (slopes > 45 m in height) in these regions.
Highlights
Slope rock mass is a type of very complex material with timespace variability
The main advantages of the method include: (1) it has strong operability, and its evaluation parameters are easy to obtain in the field; (2) the continuous formulae are adopted in the calculation process, which guarantees the non-step property of the graded results; (3) evaluating orientation-independent slope stability is based on the classical slope stability analysis method, evaluating orientation-dependent slope stability embodies the controlling effect of structural surface condition and features values on the slope stability; (4) evaluation result depend on the probability values that the slope may occur in different failure modes, and does depend on a rating weight value such as the Slope Mass Rating (SMR) classification systems
Process and steps The detailed analysis and calculation steps of the modified Slope Stability Probability Classification (SSPC) system are as follows: (1) First, the lithology coefficient mi is determined according to the type of rock slope; the value of geological strength index Geological Strength Index (GSI) is comprehensively determined according to the rock type, weathering degree, rock mass structure and the conditions of discontinuities; the value of D is determined by interpolation in the range of 0 to 1 according to the slope excavation method; and the weight γ of different rocks is determined by referring to the rele vant manual of rock mechanics and the results of laboratory tests in Chen’s database previously mentioned
Summary
Slope rock mass is a type of very complex material with timespace variability. Under the natural state, the rock mass has a long and complicated deformation history, and includes many crisscrossed discontinuous planes such as joints and fractures after experiencing many orogenetic and tectonic movements. The main advantages of the method include: (1) it has strong operability, and its evaluation parameters are easy to obtain in the field; (2) the continuous formulae are adopted in the calculation process, which guarantees the non-step property of the graded results; (3) evaluating orientation-independent slope stability is based on the classical slope stability analysis method, evaluating orientation-dependent slope stability embodies the controlling effect of structural surface condition and features values on the slope stability; (4) evaluation result depend on the probability values that the slope may occur in different failure modes, and does depend on a rating weight value such as the SMR classification systems
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