PSI - Issue 22

Mahdi Shadab Fara et al. / Procedia Structural Integrity 22 (2019) 345–352 Shadab Far and Huang / Structural Integrity Procedia 00 (2018) 000–000

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slip surface. Afterward, by defining the geotechnical parameters as random variables, the problem was established as a reliability model, and the probability of slope failure was calculated using the Monte Carlo sampling method. Next, an algorithm was proposed for uncertainty modeling of groundwater level and applied to the case study. The results were then presented as failure probability diagram versus groundwater level. The main contributions of this study are as follows: • Applying the simulated annealing method instead of the conventional circular approach to find the critical slip surface, the resulting safety factor decreased from 1.138 to 1.074. • Considering the uncertainty in groundwater level as a normal random variable, the probability of failure in creased from 21.360% to 26.06%. • The failure probability curve obtained from this paper further demonstrated that a more critical situation is detected after considering the uncertainty of groundwater level and, consequently, a greater failure probability is calculated by the Monte Carlo analysis. • The results of the parametric study showed that the insu ffi cient understanding of the groundwater distribution function and modeling a uniformly distributed groundwater level leads to a high failure probability. However, a relatively lower failure probability is obtained if a clear understanding of the groundwater distribution function is available. Providing the relationship between the safety factor and groundwater level in this paper and accessing the corre sponding failure probability, the influence of groundwater level on slope failure was simply determined because of its practical significance in engineering projects.

Acknowledgements

The materials presented in this research work are supported by China State Construction Engineering Corporation Ltd. (Grant No. CSCEC-2017-Z-29). Additionally, the authors would like to appreciate the facilities and support provided by Tongji University to conduct this research.

References

Pandit, K., Sarkar, K., Sharma, M., 2018. Optimization techniques in slope stability analysis methods. Landslides: Theory, Practice and Modelling, Advances in Natural and Technological Hazards Research 50, 227–264. Zolfaghari, A.R., Heath, A.C., McCombie, P.F., 2005. Simple genetic algorithm search for critical non-circular failure surface in slope stability analysis. Computers and Geotechnics 32(3), 139–152. Cheng, Y.M., Li, L., Chi, S.C., Wei, W.B., 2007. Particle swarm optimization algorithm for the location of the critical non-circular failure surface in two-dimensional slope stability analysis. Computers and Geotechnics 34(2), 92–103. Sanaeirad, A., Kashani, A., 2016. Slope stability optimization with non-circular slip surface and using firefly algorithm, simulate annealing and imperialistic competitive algorithm. Amirkabir Jounrnal of Science and Research Civil and Enviromental Engineering (ASJR-CEE) 48(2), 81–85. Cheng, Y.M., Li, L., Chi, S.C., 2007. Performance studies on six heuristic global optimization methods in the location of critical slip surface. Computers and Geotechnics 34(6), 462–484. Su, X., 2009. Global optimization of general failure surfaces in slope analysis by hybrid Simulated Annealin. Rocscience, Inc. Toronto, Ontario. El-Ramly, H., Morgenstern, N.R., Cruden, D.M., 2002. Probabilistic slope stability analysis for practice. Canadian Geotechnical Journal 39(3), 665–683. Hamedifar, H., Bea, R.G., Pestana-Nascimento, J.M., Roe, E.M., 2014. Role of probabilistic methods in sustainable geotechnical slope stability analysis. Procedia Earth and Planetary Science 9, 132–142. El-Ramly, H., Morgenstern, N. R., Cruden, D. M., 2006. Lodalen slide: a probabilistic assessment. Canadian Geotechnical Journal 43(9), 956–968. Hassan, A.M., Wol ff , T.F., 1999. Search algorithm for minimum reliability index of earth slopes. Journal of Geotechnical and Geoenvironmental Engineering 125(4), 301–308.

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