Shape optimal design of materially nonlinear arch dams including dam-water-foundation rock interaction using an improved PSO algorithm

Abstract

An efficient optimization procedure is proposed to find the optimal shape of arch dams including dam-water-foundation rock interaction subject to earthquake. The arch dam is treated as a three-dimensional structure involving the material nonlinearity effects. For this purpose, the nonlinear behavior of the dam concrete is idealized as an elasto-plastic material using the Drucker-Prager model. In order to reduce the computational cost of optimization process, a wavelet back propagation (WBP) neural network is designed to approximate the dam response instead of directly evaluating it by a time-consuming finite element analysis (FEA). An improved particle swarm optimization (IPSO) is also presented. In test example, the computational merits of the proposed methodology for optimizing an existing arch dam are demonstrated.

An adaptive chaos particle swarm optimization for tuning parameters of PID controller

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Hybridizing two-stage meta-heuristic optimization model with weighted least squares support vector machine for optimal shape of double-arch dams

“…In these studies, the effect of arch dam-water-foundation rock interaction was neglected, and the conventional mathematical models were utilized for analysis approximation and optimization task. In recent years, the optimal shape design of arch dams considering dam-waterfoundation rock interaction subjected to earthquake loading has been developed by few researchers [1,[10][11][12][13][14]. * Corresponding author.…”

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“…From the literature, it can be seen that optimization techniques are applicable in many fields. However, among the optimization methods, PSO has become very popular, due to its simplicity and its affinity towards manufacturing and robotics [1][2][3], electrical power systems [4][5][6][7][8], and engineering [9][10][11] and in other areas [12][13][14][15][16][17][18].…”