| This study examines the optimization design of geosynthetic reinforced embankment slopes (GRES) considering both economic benefits and technical safety requirements. In engineering design, cost is always a big concern. To minimize the cost, engineers tend to seek an optimal combination of design parameters among the considered alternatives while ensuring the optimal solution is safe. Reliability-based optimization (RBO) is such a technique that provides engineers the optimal design with the minimum cost while all technical design requirements are satisfied. The research goal of this study is to implement a mathematical formulation algorithm of the RBO technique in GRES design. To achieve this goal, slope stability is studied using the limit equilibrium method (LEM). Considering geotechnical uncertainties, the first-order reliability method (FORM) is adopted to perform probabilistic slope stability analysis, address the critical slip surfaces, and assess the reliability of the slope system. The slope stability and reliability are then used as the crucial constraints in the following RBO procedure, wherein the constrained optimization problem will be solved by adopting a genetic algorithm (GA). Sensitivity analysis is carried out on the basis of the probabilistic slope stability analysis to highlight the influence of each involved random variable on the probabilistic performance of the slope system; and thereby, infer the corresponding impact on the optimization design. A framework of how to implement the RBO in GRES design is proposed. An engineering case history is accordingly studied to demonstrate the practical application of the proposed design framework. Compared to the conventional (manual) process, the proposed design framework is more systematic and effective, especially with the large number of design variables involved in geosynthetic reinforced slopes. |
