Probabilistic stability analysis of reinforced soil retaining structures under static and seismic conditions
Creators: name: Agarwal, Ekansh
Publisher: name: RMIT University
Year: 2024
Subjects: classificationCode: 400502
subject: Civil geotechnical engineering

description: Reinforced soil retaining structures (RSRS) are becoming popular nowadays as they are very easy to construct and economical as compared to their conventional counterparts. RSRS are generally designed using the limit equilibrium methods because they manifest a reasonable agreement with the laboratory experiments. The stability of these structures depends upon various failure modes which satisfy both the internal and the external factors of safety. For the overall stability of the RSRS, all the associated failure modes must be satisfied in static as well as earthquake loading. In the present study, an efficient and accurate reliability-based design of the RSRS including reinforced walls and slopes, is conducted using the pseudo-static (PS) and modified pseudo-dynamic frameworks (MPD). The internal stability of RSRS is evaluated using a rigorous (5N-1) formulation of Horizontal Slice Method (HSM) in dry and partially saturated backfill conditions. The formulation satisfies the horizontal, vertical, and moment equilibrium equations for each slice in the slope wedge and considers least assumptions. The external stability analysis is performed using the two-part wedge mechanism. The reliability index of the system is computed by considering the modes of failure to be connected in series. In addition, the present study identifies that the wall height (H), shear wave velocity of the soil (Vs), and predominant frequency of the input motion (ω) govern the response of RSRS. Reliability index depends on a parameter termed as the normalized frequency (ωH/Vs) and its value decreases with an increase in the value of ωH/Vs. The study infers that the FORM suffers from few critical shortcomings such as linear assumption of limit state surface at the most probable point of failure and its ability to consider only the statistical uncertainties excluding the effect of epistemic uncertainties. Thus, a computationally efficient surrogate assisted MCS (Multivariate Adaptive Regression Splines) is carried out to validate the present formulation and provide numerical insights by capturing the system dynamics over the entire design domain. Adoption of the efficient surrogate assisted approach allowed the quantification of epistemic uncertainty associated with the system using Gaussian White Noise (GWN). Subsequently, its effects on the system reliability index and probabilistic behavior of the critical parameters are presented. In addition, the collocation based stochastic response surface method (SRSM) is used to probabilistically analyze the geosynthetic reinforced slopes (GRS). The horizontal seismic acceleration coefficient (kh), internal friction angle of soil (ϕ), soil unit weight (γ), shear wave velocity (Vs), and friction angle at the interface between soil and reinforcement (ϕb) are chosen as the random variables, owing to their high influence on the stability of the GRS. The influence of correlation on the stability of the GRS is also illustrated. Moreover, the system reliability analysis considering the internal and external modes of failure is performed. The results confirm the necessity of performing the system reliability analysis to estimate an accurate value of probability of failure (Pf) of GRS. The effect of foundation soil type along with the exciting frequency of soil on the stability of GRS is also examined in detail. The results demonstrate that a 3rd order PCE based stochastic response surface method is an accurate yet efficient method for the reliability-based analysis of the GRS in PS and MPD cases. When compared to the conventional MCS, it reduces the computation time from 865.733 minutes to 1.661 minutes in case of internal stability analysis and 0.16 minutes to 0.13 minutes for external stability analysis for a particular set of input parameters. This is a major finding of this study. In the SRSM, the performance function is evaluated 125 (internal stability) and 625 (external stability) times whereas in direct MCS, it is evaluated at least 95000 times to attain a similar level of accuracy. Apart from SRSM, for further validation, the probabilistic analysis is performed in both analytical and numerical domains using the Fourth Moment Normal Transformation (FMNT). FMNT can estimate the probability of failure of a GRS with unknown marginal distribution of input random variables. The use of FMNT with commercially available numerical software packages is precisely explained. The accuracy of the proposed technique, when used with different distributions of random variables, is also illustrated. The results show considerable efficiency of FMNT in estimating the probability of failure when used in analytical domain as well as with numerical software. In the end, the use of SRSM for the probabilistic stability analysis of RSRS with partially saturated backfills is demonstrated. The present study demonstrates that it is imperative to consider the probabilistic deviations of the critical performance parameters for RSRS to ensure adequate safety and serviceability under operational condition while quantifying the reliability of such systems. The current research will provide practicing engineers with reliable and comprehensive probabilistic methods to assess the stability of RSRS in real-world applications.