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Sensitivity analysis and genetic algorithm-based shear capacity model for basalt FRC one-way slabs reinforced with BFRP bars

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submitted on 2023-11-06, 10:15 and posted on 2023-11-06, 11:11 authored by Abathar Al-Hamrani, Tadesse G. Wakjira, Wael Alnahhal, Usama Ebead

Fiber-reinforced polymer (FRP) composites are increasingly used in concrete structures owing to their superior corrosion resistance. However, FRP-reinforced concrete (RC) structures exhibit less ductile response compared to steel RC structures. Recently, the use of basalt fiber reinforced concrete (BFRC) reinforced with BFRP bars was investigated to achieve a reasonable level of ductility in BFRC-BFRP one-way slabs. The shear behavior of such a slab depends on different design parameters. This paper aims to identify the impact of each design parameter on the shear behavior of BFRC-BFRP one-way slabs using a fractional factorial design of experiment (DOE). A 3D finite element model was first developed and validated against available experimental results. The developed model is then used to conduct a sensitivity analysis considering five factors that influence the shear behavior of BFRC-BFRP one-way slabs. These factors are the longitudinal reinforcement ratio, shear span-to-depth ratio, effective depth, concrete compressive strength, and volume fraction of basalt macro fibers (BMF). Finally, a design equation that can predict the shear capacity of one-way BFRC-BFRP slabs was proposed based on genetic algorithm. The proposed model showed the best prediction accuracy compared to the available design codes and guidelines with a mean of predicted to experimental shear capacities (Vpred/Vexp) ratio of 0.97 and a coefficient of variation of 17.91%.

Other Information

Published in: Composite Structures
License: http://creativecommons.org/licenses/by/4.0/
See article on publisher's website: https://dx.doi.org/10.1016/j.compstruct.2022.116473

Funding

Open Access funding provided by the Qatar National Library

History

Language

  • English

Publisher

Elsevier

Publication Year

  • 2023

License statement

This Item is licensed under the Creative Commons Attribution 4.0 International License

Institution affiliated with

  • Qatar University
  • College of Engineering - QU

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