The IUP Journal of Structural Engineering
ANN-Based Shear Capacity of Steel Fiber-Reinforced Concrete Beams Without Stirrups

Article Details
Pub. Date : Apr, 2020
Product Name : The IUP Journal of Structural Engineering
Product Type : Article
Product Code : IJSE30420
Author Name : M Abambres, E Lantsoght*
Availability : YES
Subject/Domain : Science and Technology
Download Format : PDF Format
No. of Pages : 22



Comparing experimental results on the shear capacity of Steel Fiber-Reinforced Concrete (SFRC) beams without mild steel stirrups to the ones predicted by current design equations and other available formulations still shows significant differences. The paper proposes the use of Artificial Intelligence (AI) to estimate the shear capacity of these members. A database of 430 test results reported in the literature is used to develop an Artificial Neural Network (ANN)-based formula that predicts the shear capacity of SFRC beams without shear reinforcement.


Since concrete is strong in compression but weak in tension, adding steel fibers to the material can be a solution to the limited strength in tension-they keep crack widths small (Amin et al., 2016). In structural applications, Steel Fiber-Reinforced Concrete (SFRC) is combined with regular steel reinforcement.


Experimental data, Artificial Neural Networks (ANN), Design formula, Concrete beams, Steel Fiber-Reinforced Concrete (SFRC), Shear capacity

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