Resistance factors for reliability based-design of fiber reinforced concrete suspended slabs in flexure

Leblouba, Moussa; Barakat, Samer; Altoubat, Salah; Maalej, Mohamed; Awad, Raghad

doi:10.1016/j.jobe.2022.104911

Cited by 2 publications

(3 citation statements)

References 19 publications

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“…The obtained ϕ of 0.6 is comparable with previous reduction factors suggested by Leblouba et al 21 for suspended FRC slabs ( ϕ = 0.78) and Awad et al 19 for FRC slabs on ground ( ϕ = 0.8). These differences may be attributed to the adopted model and failure mode.…”

Section: Resultssupporting

confidence: 90%

“…These differences may be attributed to the adopted model and failure mode. Leblouba et al 21 and Awad et al 19 suggested their reduction factors for slabs with the flexural failure mode, while this study focuses on punching shear failures. Moreover, Leblouba et al 21 and Awad et al 19 calibrated conventional formulas in ACI 360R 20 and ACI 544 22 design guides, respectively; on the other hand, this study calibrates a data‐driven model.…”

Section: Resultsmentioning

confidence: 99%

“…Most recently, Leblouba et al 21 developed a reliability‐based design procedure to calibrate flexural design resistance factor for suspended SFRC slabs using conventional ACI 544 22 formulas. The authors have recommended an aggregated factor of 0.78 to account for FRC suspended slab to achieve β of 2.5.…”

Section: Introductionmentioning

confidence: 99%

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Data‐driven reliability and cost‐based design optimization of steel fiber reinforced concrete suspended slabs

Alotaibi

Nassif

Barakat

2023

Structural Concrete

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The governing failure mode for flat slabs is punching shear, which occurs when the punching forces exceed the slab resistances in the critical area around the column surface. Recently, considerable knowledge has been obtained on understanding steel fiber reinforced concrete (SFRC) suspended slabs as a sustainable and reliable technique to enhance post-cracking behavior and resist loading effects, including punching shear. The properties of the materials, loading, and dimension vary inevitably and may be represented in the form of statistical distributions. In this study, all parameters affecting the punching shear of the SFRC suspended slabs were treated as random variables.Monte Carlo simulations (MCS) and punching shear model developed previously using Artificial Neural Network (ANN) were combined (ANN-MCS) to conduct a reliability analysis, cost optimization, and model calibration. Reliability results have shown that the inclusion of fibers increased the safety level (20% in terms of the reliability index β) of the slabs against punching shear. Furthermore, a reliability-based cost optimization was performed on the ANN-MCS model. The optimization outcomes demonstrated steel ratio has a significant impact on SFRC slab cost, and thus it should be minimized/reduced when the steel fibers are included in the mix. Moreover, the ANN model was calibrated following a code calibration procedure to account for the model, material, and fabrication uncertainties. The calibration results have shown that a reduction factor of 0.6 should be applied to the ANN-based model to achieve the target reliability level, β ≥ 2.5.

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Section: Resultssupporting

confidence: 90%