Issue |
E3S Web Conf.
Volume 586, 2024
2024 The International Conference on Structural and Civil Engineering (ICSCE 2024)
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|
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Article Number | 02003 | |
Number of page(s) | 7 | |
Section | Structural Health Monitoring and Structural Mechanics | |
DOI | https://doi.org/10.1051/e3sconf/202458602003 | |
Published online | 06 November 2024 |
Application of AI for modelling and structural analysis of a parametric 2D frame with voice assistant
Civil Engineering, Faculty of engineering, Universidad San Ignacio de Loyola (USIL). Av. La Fontana 550, La Molina, Lima, Perú
* Corresponding author: rick.delgadillo@usil.pe
Structural calculations are essential for civil engineering, but specialized software for their analysis is limited. The lack of availability of efficient tools has generated the need to explore new ways to optimize these calculations. This work addresses the aforementioned problem, proposing the use of Python and automation technologies to offer an innovative and accessible solution to improve efficiency in the field of structural analysis of 2D frames. This proposal seeks to reduce work times by relying on AI, as well as to promote accessibility in this field. To achieve this purpose, the Python library AnaStruct, specifically designed for structural analysis using matrix methods, is used. This tool enables the detailed definition of structural elements, constraints and loads, as well as the visualization of the analysis results. In addition, the Speech Recognition library is implemented for interaction through voice reception, which speeds up the data entry process and structural analysis commands. Through surveys conducted, it is observed that the program achieved an average reduction of the analysis time between 73.33% and 94.29%, compared to traditional methods. Where 100% of the respondents unanimously confirmed that it improves efficiency, and 78.6% expressed their willingness to recommend it for future projects.
© The Authors, published by EDP Sciences, 2024
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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