Ultimate Limit State Reliability-Based Optimization of MSE Wall Considering External Stability

Zafar Mahmood, Mohsin Usman Qureshi, Zubair Ahmed Memon and Qadir Bux alias Imran Latif
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Zafar Mahmood: Department of Civil and Architectural Engineering, College of Engineering, University of Buraimi, P.O. Box 890, Al Buraimi 512, Oman
Mohsin Usman Qureshi: Faculty of Engineering, Sohar University, P.O. Box 44, Sohar 311, Oman
Zubair Ahmed Memon: Department of Engineering Management, Prince Sultan University, Riyadh 11586, Saudi Arabia
Qadir Bux alias Imran Latif: Department of Civil and Environmental Engineering, College of Engineering, University of Nizwa, P.O. Box 33, Nizwa 616, Ad-Dakhliyah, Oman

Sustainability, 2022, vol. 14, issue 9, 1-16

Abstract: We present reliability-based optimization (RBO) of the Mechanically Stability Earth (MSE) walls, using constrained optimization, considering the external stability, under ultimate limit state conditions of sliding, eccentricity, and bearing capacity. The design is optimized for a target reliability index of 3 that corresponds to an approximate failure probability of 1 in 1000. Reliability index is calculated by the first-order reliability method (FORM). The MSE wall, founded on cohesionless soil, with horizontal backfill and uniform live traffic surcharge, is studied. The RBO results are reported for the height of MSE wall ranging from 1.5 m to 20 m. For target reliability index of 3, the optimized length to height ratio, L o p t / H , of the MSE wall is greater than 0.7 (the minimum length to height ratio requirement of AASHTO) for H ≤ 4.5 m, and then it decreases below the minimum required value of 0.7 for H > 4.5 m. The RBO approach presented in this study will help practitioners to achieve cost-effectiveness in design.

Keywords: MSE wall; external stability; constrained optimization; reliability-based optimization; first-order reliability method (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
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