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

Authors :
Al-Hamrani, Abathar
Wakjira, Tadesse G.
Alnahhal, Wael
Ebead, Usama
Source :
Composite Structures. Feb2023, Vol. 305, pN.PAG-N.PAG. 1p.
Publication Year :
2023

Abstract

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 (V pred / V exp ) ratio of 0.97 and a coefficient of variation of 17.91%. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
02638223
Volume :
305
Database :
Academic Search Index
Journal :
Composite Structures
Publication Type :
Academic Journal
Accession number :
161014713
Full Text :
https://doi.org/10.1016/j.compstruct.2022.116473