Optimization of Clay Core in Embankment Dams Using New Combined Model RM&GA, A Case Study

ABSTRACT: Optimizing all components of a zoned embankment simultaneously poses significant challenges. Hence, a more practical approach is to optimize each component individually while considering their inherent interactions. This paper focuses on determining the optimal dimensions of the central clay core in embankment dams, prioritizing stability considerations. To achieve this objective, a novel approach is presented, utilizing a combined model that integrates regression models (RMs) and genetic algorithms (GAs) for optimization. Within this framework, the genetic algorithm explores optimal configurations while incorporating constraints such as seepage rate, hydraulic gradient, and stability safety factors. These constrains are formulated by SPSS based on the calculated parameters of about 200 dam sections with different geometrics and hypothetical materials, as well as statistical analysis on 454 generated data. The outcomes of the applied proposed model on a case study demonstrate its efficacy in accurately estimating seepage rates, hydraulic gradients, and safety factors using analytical models. Moreover, the combined model offers valuable insights into determining optimal clay core dimensions and appropriate slope parameters for zoned earth dams, thereby enhancing overall cost-effective dam design and stability.