Optimization of Material Consumption in Reinforced Concrete Beams Using Post-Tensioning and Particle Swarm Optimization

J.M. Hernández-Martínez *

Facultad de Ingeniería, Cerro de las Campanas, Universidad Autónoma de Querétaro, Querétaro, 76010, México.

L. F. Perez-Moreno

Facultad de Ingeniería, Cerro de las Campanas, Universidad Autónoma de Querétaro, Querétaro, 76010, México.

M. A. Pérez Lara y. Hernández

Facultad de Ingeniería, Cerro de las Campanas, Universidad Autónoma de Querétaro, Querétaro, 76010, México.

Rico-Garcia E

Facultad de Ingeniería, Cerro de las Campanas, Universidad Autónoma de Querétaro, Querétaro, 76010, México.

*Author to whom correspondence should be addressed.


Abstract

The objective of this work is to evaluate the reduction in concrete and rebar weight in continuous beams of reinforced concrete frame buildings with spans greater than 9 meters, by integrating post-tensioning design with the Particle Swarm Optimization (PSO) algorithm. The study is based on numerical modelling carried out using the SAP2000 API and Python, and was applied to two study cases of a three-story hospital building with four bays in each direction and spans of 9 m and 13 m, respectively.  It was done at the Faculty of Engineering of the Autonomous University of Querétaro, in Querétaro, Mexico, during the period between September 2024 and November 2025. The optimization variables are the width and depth of the beam and the number of post-tensioned strands, while the objective function is defined as a pondered combination of concrete and steel weight, subject to strength and serviceability limit state checks according to applicable design codes. In the case of 9 meters, savings of 46% in concrete and 18% in steel were achieved in comparison to the non-prestressed design. On the other hand, in the case of 13 meters, concrete was reduced by 34% while steel remained the same, concluding that the methodology applied successfully reduces the volume of material used in the continuous beam under study, which can have a significant impact if applied to an entire building, contributing to a sustainable, low-cost design due to lower material consumption and good structural performance.

Keywords: Structural optimization, Particle Swarm Algorithm, Post-tensioned concrete, Material consumption, Python


How to Cite

Hernández-Martínez, J.M., L. F. Perez-Moreno, M. A. Pérez Lara y. Hernández, and Rico-Garcia E. 2026. “Optimization of Material Consumption in Reinforced Concrete Beams Using Post-Tensioning and Particle Swarm Optimization”. Current Journal of Applied Science and Technology 45 (1):12-27. https://doi.org/10.9734/cjast/2026/v45i14649.

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