The Evaluation of applying the ABC optimization algorithm for the optimal design of the shape of double-arched dams (Case study: Morrow Point Dam)

Subject Areas : Article frome a thesis

Seyed Reza Mosavi ¹ , Nader Barahmand ² , Akbar Ghanbari ³ , Arash Totonchi ⁴

1 - Department of Civil Engineering, Larestan Branch, Islamic Azad University, Lar, Iran
2 - Department of Civil Engineering, Larestan Branch, Islamic Azad University, Lar, Iran
3 - Department of Civil Engineering, Larestan Branch, Islamic Azad University, Lar, Iran
4 - Department of Civil Engineering, Marvdasht Branch, Islamic Azad University, Marvdasht, Iran

Received: 2024-04-13 Accepted : 2025-01-19 Published : 2025-06-28

Keywords: Double-arched Dams, Morrow Point Dam, Artificial bee colony algorithm, Optimal dam shape,

Abstract :

Introduction: The determination of the optimal shape of dams plays a critical role due to its significant influence on computational and construction costs as well as the structural safety of the dam. This study aims to evaluate the effectiveness of a metaheuristic optimization algorithm in the optimal design of double-curvature arch dams.

Methods: The Morrow Point Dam was selected as a real-world case study and optimized under various conditions when subjected to the El Centro earthquake. The optimization problem was formulated with the volume of concrete as the objective function, while twenty geometric parameters were defined as design variables. To minimize the concrete volume, a combined framework incorporating the finite element model in Abaqus, an Artificial Neural Network (ANN), and the Artificial Bee Colony (ABC) algorithm was implemented.

Findings: First, an Abaqus model of the dam was constructed. Then, one hundred randomly generated geometries based on the model were produced and used for training the ANN. The dataset was divided into 70% for training, 15% for validation, and 15% for testing. Subsequently, optimization using the ABC algorithm was performed under two scenarios. In the baseline case, the objective function reached 239,229 m³, whereas in the optimized case, the concrete volume was reduced to 238,150 m³. The convergence history revealed that the optimized case demonstrated a continuous reduction in the objective function over time compared to the baseline. Furthermore, the computational time of the ABC algorithm was shorter in the optimized scenario. Overall, the findings confirm that the proposed hybrid framework is an efficient and reliable approach for the optimal design of double-curvature dams and holds potential for application to another structural optimization.

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