Section-Based DataBase Schema: optimal design of reinforced concrete elements based on multi-objective brute force search (Code)

Published: 31 October 2023| Version 2 | DOI: 10.17632/8hns8wpx7c.2
Amin Tanhadoust


This repository contains Python codes implementing the Section Beam Database Search (SBDBS) method for optimizing Reinforced Concrete (RC) beam design. Utilizing a multi-objective optimization approach, the codes facilitate the generation of optimal beam sections considering various design variables, adhering to ACI code constraints. By employing non-dominated sorting improved brute force search method, the SBDBS significantly reduces computational cost, ensuring optimal solutions for cost, moment resistance, and energy dissipation. Intended for researchers, engineers, and decision-makers, this tool aids in achieving cost-effective, robust RC design.


Steps to reproduce

# Steps to Reproduce 1. Clone the repository to your local machine. 2. Ensure you have the necessary dependencies installed. 3. Navigate to the directory containing the `` and `` files. 4. Open `` in a text editor or IDE. - Adjust the parameters: `Fc`, `Fy`, `beta1`, `B_range`, `d_range`, `SN_range`, `Cn`, and `Cover`. 5. Run `` to generate the `pareto` output for columns. 6. Similarly, open `` in a text editor or IDE. - Adjust the parameters: `Fc`, `Fy`, `beta1`, `B_range`, `H_range`, `Td_range`, `TN1_range`, `Cd_range`, `CN_range`, `Cn`, and `Cover`. 7. Run `` to generate the `pareto` output for beams.


Isfahan University of Technology


Combinatorial Optimization, Multi-Objective Optimization, Reinforced Concrete, Structural Database, Optimization in Structural Design, Reinforced Concrete Structure, Structural Optimization, Beam-Column