Dataset of optimal reinforced concrete structural elements: Beam and column sections

Published: 30 October 2023| Version 1 | DOI: 10.17632/tdszj84x29.1


This repository houses a meticulously curated dataset of optimal reinforced concrete structural elements, specifically focusing on beam and column sections. The data is generated leveraging the Section-Based DataBase Schema (SBDBS) framework, a robust mechanism hosted on the Mendeley Data repository, dedicated to the creation of optimal reinforced concrete sections. The dataset extends a profound insight into the design parameters and load capacities of the optimal beam and column sections, encapsulating essential metrics like dimensions, number of rebars, moment capacities, and cost per meter. The tabulated design parameters and load capacities of optimal beam sections, showcasing a comprehensive blend of data ranging from dimensions (B, H) to load capacities (Mn+, Mu+, Mn-, Mu-) and cost. In a similar vein, the design parameters and load capacities of optimal column sections, provided a deep dive into the critical attributes of columns, hence offering a rich resource for both academic and practical endeavors in the realm of structural engineering. Moreover, this dataset serves as an indispensable asset for researchers, engineers, and decision-makers aiming to delve into cost-effective, robust, and optimized design of reinforced concrete structures. By offering a tangible glimpse into the optimal configurations, this dataset significantly contributes to advancing the narrative of structural optimization, fostering informed decision-making, and propelling forward the frontiers of structural design optimization.


Steps to reproduce

To reproduce or regenerate the dataset provided in this repository, users are guided to the "Section-Based DataBase Schema (SBDBS)" framework outlined by Tanhadoust (2023) in the Mendeley Data repository. By utilizing the provided code (doi: 10.17632/8hns8wpx7c.1), users can modify the design variables, boundaries of size, and other features to suit their specific needs. Following the multi-objective brute force search method as demonstrated in the SBDBS, users will be able to create their own dataset of optimized reinforced concrete structural elements. This approach ensures a structured and replicable method for deriving optimal designs in reinforced concrete elements based on the provided variables and parameters.


Isfahan University of Technology


Civil Engineering, Structural Engineering, Genetic Algorithm, Multi-Objective Optimization, Optimization in Structural Design, Structural Element, Concrete Structure, Reinforced Concrete Structure, Structural Optimization