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Probabilistic Analysis of Reinforced Soil Retaining Structures Using FORM and Surrogate-Based Monte Carlo Simulation
In the present study, reliability analysis of reinforced soil retaining structure (RSRS) under seismic conditions is performed. A reliability-based analysis of RSRS is performed in the present study using the random variable approach. The pseudo-static approach under the framework of the limit equilibrium method of horizontal slices is employed to assess the internal stability of RSRS. The basic approach involves satisfying Coulomb’s failure criterion along the assumed failure surface. The first-order reliability method (FORM) is employed to determine the reliability indices associated with various modes of failure. The system reliability index is also calculated using the same approach, considering the modes of failure to be connected in series. Tension mode is found to be the most critical mode of failure. A unique surrogate-assisted Monte Carlo Simulation (MCS) is carried out to validate the present formulation using the multivariate adaptive regression splines (MARS) method. It is found that the assumption of FORM may lead to the underestimation of the value of the probability of failure of RSRS. Moreover, the surrogate-based MCS outperforms the FORM in terms of computational efficiency and accuracy.
Probabilistic Analysis of Reinforced Soil Retaining Structures Using FORM and Surrogate-Based Monte Carlo Simulation
In the present study, reliability analysis of reinforced soil retaining structure (RSRS) under seismic conditions is performed. A reliability-based analysis of RSRS is performed in the present study using the random variable approach. The pseudo-static approach under the framework of the limit equilibrium method of horizontal slices is employed to assess the internal stability of RSRS. The basic approach involves satisfying Coulomb’s failure criterion along the assumed failure surface. The first-order reliability method (FORM) is employed to determine the reliability indices associated with various modes of failure. The system reliability index is also calculated using the same approach, considering the modes of failure to be connected in series. Tension mode is found to be the most critical mode of failure. A unique surrogate-assisted Monte Carlo Simulation (MCS) is carried out to validate the present formulation using the multivariate adaptive regression splines (MARS) method. It is found that the assumption of FORM may lead to the underestimation of the value of the probability of failure of RSRS. Moreover, the surrogate-based MCS outperforms the FORM in terms of computational efficiency and accuracy.
Probabilistic Analysis of Reinforced Soil Retaining Structures Using FORM and Surrogate-Based Monte Carlo Simulation
Lecture Notes in Civil Engineering
Satyanarayana Reddy, C. N. V. (editor) / Saride, Sireesh (editor) / Krishna, A. Murali (editor) / Agarwal, Ekansh (author) / Pain, Anindya (author) / Sarkar, Shantanu (author)
2021-07-28
10 pages
Article/Chapter (Book)
Electronic Resource
English
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