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Geomechanics and Engineering Volume 34, Number 3, August10 2023 , pages 285-301 DOI: https://doi.org/10.12989/gae.2023.34.3.285 |
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Probabilistic analysis of anisotropic rock slope with reinforcement measures |
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Zoran Berisavljević, Dušan Berisavljević, Miloš Marjanović and Svetlana Melentijević
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| Abstract | ||
| During the construction of E75 highway through Grdelica gorge in Serbia, a major failure occurred in the zone of reinforced rock slope. Excavation was performed in highly anisotropic Paleozoic schist rock formation. The reinforcement consisted of the two rows of micropile wall with pre-stressed anchors. Forces in anchors were monitored with load cells while benchmarks were installed for superficial displacement measurements. The aim of the study is to investigate possible causes of instability considering different probability distributions of the strength of discontinuities and anchor bond strength by applying different optimization techniques for finding the critical failure surface. Even though the deterministic safety factor value is close to unity, the probability of failure is governed by variability of shear strength of anisotropic planes and optimization method used for locating the critical sliding surface. The Cuckoo search technique produces higher failure probabilities compared to the others. Depending on the assigned statistical distribution of input parameters, various performance functions of the factor of safety are obtained. The probability of failure is insensitive to the variation of bond strength. Different sampling techniques should yield similar results considering that the sufficient number of safety factor evaluations is chosen to achieve converged solution. | ||
| Key Words | ||
| back-analysis; optimization technique; probability of failure; strength anisotropy | ||
| Address | ||
| Zoran Berisavljević, Dušan Berisavljević and Miloš Marjanović: Faculty of Mining and Geology, University of Belgrade, 7 Djusina Street, 11000 Belgrade, Serbia Svetlana Melentijević: Faculty of Geological Science, Universidad Complutense de Madrid, c/ José Antonio Nováis 12, Ciudad Universitaria,28040 Madrid, Spain | ||