Detention rockfill dams are generally known as economic and efficient structural methods for flood mitigation and watershed management. Despite the existing studies in the context of rockfill dam design, designers still rely on time-consuming and costly experimental tests which can only lead into practical guidelines. Moreover, investigation of various rockfill dam design alternatives in terms of hydraulic performance needs an exhaustive framework to obtain the optimal design values. With respect to these, this research study aims to investigate the optimal dam thickness and mean diameter of coarse aggregates in detention rockfill dams in order to improve the hydraulic characteristics, e.g., reduction in flood peak discharge and increase in flood duration while the construction cost is minimized. Here, a methodology based on data-driven simulation model, multi-objective optimization model, multi-criterion decision making model, and social choice method is suggested to find the optimal design parameters of detention rockfill dam. This methodology adapts data to model and model to optimum design variables. Experimental results are converted to data-driven simulation model based on multilayer perceptron neural network, which can model the relationship between design variables of detention rockfill dam and parameters of flood hydrograph. The simulation model is used in a robust multi-objective optimization algorithm, non-dominated sorting genetic algorithm-ΙΙ (NSGA-ΙΙ), to establish a trade-off between the conflicting objectives. Eventually, PROMETHEE decision making model and Borda count social choice method are used to find the best agreed-upon design optimal point on the trade-off curve. Results indicate that the best non-dominated solution can be considered as 10.01 and 5 cm for the optimum thickness of detention rockfill dam and optimum mean diameter of coarse aggregates in the porous media, respectively. The similar optimum characteristics of detention rockfill dam using PROMETHEE and Borda count social choice method depict the stable performance of the proposed methodology.
- Borda count social choice method
- Detention rockfill dam
- Multilayer perceptron (MLP) neural network
ASJC Scopus subject areas
- Civil and Structural Engineering
- Water Science and Technology