| 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