OPTIMIZATION OF A SELF-SUPPORTED TOWER MODEL USING PARTICLE SWARM OPTIMIZATION HEURISTIC TECHNIQUE

Abstract

Due to the telecommunications boom in Cuba, the demand for towers has been on the rise. The conception of the design of these structures is governed by codes and standards, where part of its elements are not used to the limit of their capacity. Structural optimization has become a global trend in order to take full advantage of the strength of the structural elements of lattice towers. In recent decades, a considerable number of heuristic optimization techniques have been developed, with Particle Swarm (PSO) being one of the most used in tower design optimization. In this framework, the present research is developed, which aims to optimize a self-supported tower model by distributing the cross sections of its elements, applying the PSO heuristic technique, under extreme wind conditions in Cuba. The optimization is carried out on a theoretical model of a 36 m high self-supporting tower with a triangular section. The objective function to optimize is the weight of the tower, which was parameterized in the MATLAB software using the Finite Element Method (FEM). As a result of the optimization process, a theoretical model of a self-supporting tower with a weight of 34.28 kN was obtained, which resists the state of wind load under Cuban conditions.