Abstract
Purpose Computing seepage discharge in earth dams involves inherent complexities and challenges that require the use of probabilistic algorithms to accurately capture their uncertain characteristics and identify optimal solutions. This study aims to investigate the impact of uncertainty in seepage flow estimation using a novel hybrid approach, combining the analysis of Laplacian equations with the probabilistic finite element method (PFEM) and a metaheuristic algorithm. Design/methodology/approach To achieve this purpose, a finite element-based FORTRAN program was developed to model the problem using the Galerkin finite element method, which was validated using laboratory findings. Subsequently, Monte Carlo loops were incorporated into each model, consisting of 2000 iterations and the probability distribution function and cumulative distribution function were computed for each sub-model. A total of 138 earth dams were analysed to investigate the influence of different characteristics on seepage, including variations in dam geometry, soil permeability and water levels (both downstream and upstream). Effective seepage flow (ESF), was introduced in both deterministic and probabilistic models. Findings The findings indicated that the downstream slope has a more significant impact on ESF than the upstream slope, with a difference of 1.29%. Additionally, the ratio of dam height to bottom width (H/B) directly affects the ESF, resulting in a 20% increase in ESF for every 16% increase in H/B. Originality/value This study introduces a novel hybrid approach for estimating seepage flow in earth dams by integrating the Unlike traditional deterministic models, which often overlook the inherent .PFEM with a metaheuristic algorithman advanced uncertainties in seepage characteristics, this research effectively captures these uncertainties throughprobabilistic framework.
Published Version
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