AI Analysis of the Thermal Effects on Reinforced Concrete Buildings with Floating Columns

Authors

  • Mohamed Laissy Department of Civil Engineering, University of Prince Mugrin, Saudi Arabia
  • Besher Belbol Department of Civil Engineering, University of Prince Mugrin, Saudi Arabia
  • Osama Boshi Department of Civil Engineering, University of Prince Mugrin, Saudi Arabia
  • Abdalla Eldeiasti Department of Civil Engineering, University of Prince Mugrin, Saudi Arabia
Volume: 14 | Issue: 5 | Pages: 16154-16159 | October 2024 | https://doi.org/10.48084/etasr.8160

Abstract

This study investigates the significant structural difficulties caused by the combined influence of floating columns and thermal stresses on Reinforced Concrete (RC) structures in Saudi Arabia. Discontinuities in load flows are created by floating columns, resulting in increased stress concentrations. These stresses are increased by thermal expansion and contraction caused by temperature fluctuations, which can potentially lead to critical structural deformations. This study evaluates structural performance under different temperature conditions using numerical simulations and AI-driven prediction analysis. The findings highlight the importance of incorporating thermal load considerations and accounting for the effects of floating columns in design methods to guarantee the safety, durability, and long-term stability of reinforced concrete buildings in severe climates for long-span structures. This study emphasizes the integration of AI and simulation methods into structural engineering to support building design and performance when subjected to both heat and load impacts.

Keywords:

Thermal loads, Artificial Intelligence, Structural Integrity, Floating Columns, Predictive Analysis

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How to Cite

[1]
Laissy, M., Belbol, B., Boshi, O. and Eldeiasti, A. 2024. AI Analysis of the Thermal Effects on Reinforced Concrete Buildings with Floating Columns. Engineering, Technology & Applied Science Research. 14, 5 (Oct. 2024), 16154–16159. DOI:https://doi.org/10.48084/etasr.8160.

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