scholarly journals Failure Analysis of Steel Fiber-Reinforced Concrete T-Beams without Shear Stirrups

2022 ◽  
Vol 12 (1) ◽  
pp. 411
Author(s):  
Inkyu Rhee

The shear failure of a reinforced concrete member is a sudden diagonal tension failure; flexible failure is gradual, associated with significant cracks, and leads to extensive sagging. Therefore, reinforced shear rebars are commonly used to ensure that flexible failure occurs before shear failure under extreme conditions. Extensive efforts are underway to replace conventional shear reinforcements with steel fibers. Here, a nonlinear analysis of a steel fiber-reinforced concrete T-beam was performed in order to estimate the maximum shear capacity with the aid of experimental test data. A continuum-damaged plasticity model and modified compression field theory were used for nonlinear analysis. Three 360 × 360-mm web elements were selected between the shear span; changes in the principal axis caused by crack development and propagation were traced. Changes in the crack angle according to the average strain of the bottom longitudinal reinforcement and the vertical strain of the web element were also determined. For verification, a strut-tie model was used to predict shear capacity. The experimental results and the finite element analyses were in good agreement.

Materials ◽  
2020 ◽  
Vol 13 (17) ◽  
pp. 3902 ◽  
Author(s):  
Shasha Lu ◽  
Mohammadreza Koopialipoor ◽  
Panagiotis G. Asteris ◽  
Maziyar Bahri ◽  
Danial Jahed Armaghani

When designing flat slabs made of steel fiber-reinforced concrete (SFRC), it is very important to predict their punching shear capacity accurately. The use of machine learning seems to be a great way to improve the accuracy of empirical equations currently used in this field. Accordingly, this study utilized tree predictive models (i.e., random forest (RF), random tree (RT), and classification and regression trees (CART)) as well as a novel feature selection (FS) technique to introduce a new model capable of estimating the punching shear capacity of the SFRC flat slabs. Furthermore, to automatically create the structure of the predictive models, the current study employed a sequential algorithm of the FS model. In order to perform the training stage for the proposed models, a dataset consisting of 140 samples with six influential components (i.e., the depth of the slab, the effective depth of the slab, the length of the column, the compressive strength of the concrete, the reinforcement ratio, and the fiber volume) were collected from the relevant literature. Afterward, the sequential FS models were trained and verified using the above-mentioned database. To evaluate the accuracy of the proposed models for both testing and training datasets, various statistical indices, including the coefficient of determination (R2) and root mean square error (RMSE), were utilized. The results obtained from the experiments indicated that the FS-RT model outperformed FS-RF and FS-CART models in terms of prediction accuracy. The range of R2 and RMSE values were obtained as 0.9476–0.9831 and 14.4965–24.9310, respectively; in this regard, the FS-RT hybrid technique demonstrated the best performance. It was concluded that the three hybrid techniques proposed in this paper, i.e., FS-RT, FS-RF, and FS-CART, could be applied to predicting SFRC flat slabs.


2018 ◽  
Vol 171 ◽  
pp. 421-432 ◽  
Author(s):  
Jong-Han Lee ◽  
Baiksoon Cho ◽  
Jae-Bong Kim ◽  
Kun-Joon Lee ◽  
Chi-Young Jung

2012 ◽  
Vol 256-259 ◽  
pp. 926-929
Author(s):  
Li Bing Jin ◽  
De Cai Chen ◽  
Ji Peng Qi

In order to study the shear capacity enhancement effect of prestressed technology to steel fiber reinforced concrete, the practical formulas were proposed for evaluating the shear-strength of unbonded prestressed steel-fiber reinforced concrete beams (UPSFRCB) through the test and study of shear capacity of UPSFRCB with simply supported ends. Various factors affecting the shear strength of UPSFRCB, such as steel fiber, prestress and shear-span to depth ratio were analyzed. The result is of importance to the popularization and application of prestressed steel-fiber reinforced concrete.


2019 ◽  
Author(s):  
Miguel Abambres ◽  
Eva Olivia Leontien Lantsoght

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. In this paper we propose the use of artificial intelligence 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-based formula that predicts the shear capacity of SFRC beams without shear reinforcement. The proposed model yields maximum and mean relative errors of 0.0% for the 430 data points, which represents a better prediction (mean Vtest / VANN = 1.00 with a coefficient of variation of 1E-15) than the existing expressions, where the best model yields a mean value of Vtest / Vpred = 1.01 and a coefficient of variation of 27%.


2021 ◽  
Author(s):  
Miguel Abambres ◽  
Lantsoght E

<p>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. In this paper we propose the use of artificial intelligence 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-based formula that predicts the shear capacity of SFRC beams without shear reinforcement. The proposed model yields maximum and mean relative errors of 0.0% for the 430 data points, which represents a better prediction (mean <i>V<sub>test</sub> / V<sub>ANN</sub></i> = 1.00 with a coefficient of variation of 1× 10<sup>-15</sup>) than the existing expressions, where the best model yields a mean value of <i>V<sub>test </sub>/ V<sub>pred</sub></i> = 1.01 and a coefficient of variation of 27%.</p>


Fibers ◽  
2019 ◽  
Vol 7 (12) ◽  
pp. 102 ◽  
Author(s):  
Juan Andres Torres ◽  
Eva O.L. Lantsoght

For shear-critical structural elements where the use of stirrups is not desirable, such as slabs or beams with reinforcement congestion, steel fibers can be used as shear reinforcement. The contribution of the steel fibers to the shear capacity lies in the action of the steel fibers bridging the shear crack, which increases the shear capacity and prevents a brittle failure mode. This study evaluates the effect of the amount of fibers in a concrete mix on the shear capacity of steel fiber-reinforced concrete beams with mild steel tension reinforcement and without stirrups. For this purpose, 10 beams were tested. Five different fiber volume fractions were studied: 0.0%, 0.3%, 0.6%, 0.9%, and 1.2%. For each different steel fiber concrete mix, the concrete compressive strength was determined on cylinders and the tensile strength was determined in a flexural test on beam specimens. Additionally, the influence of fibers on the shear capacity was analyzed based on results reported in the literature, as well as based on the expressions derived for estimating the shear capacity of steel fiber-reinforced concrete beams. The outcome of these experiments is that a fiber percentage of 1.2% or fiber factor of 0.96 can be used to replace minimum stirrups according to ACI 318-14 and a 0.6% fiber volume fraction or fiber factor of 0.48 to replace minimum stirrups according to Eurocode 2. A fiber percentage of 1.2% or fiber factor of 0.96 was observed to change the failure mode from shear failure to flexural failure. The results of this study support the inclusion of provisions for steel fiber-reinforced concrete in building codes and provides recommendations for inclusion in ACI 318-14 and Eurocode 2, so that a wider adoption of steel fiber reinforced concrete can be achieved in the construction industry.


2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Faten Y. Taqi ◽  
Mohammed A. Mashrei ◽  
Hayder M. Oleiwi

Abstract This paper offers a finite element method (FEM) to simulate the behavior of steel fiber reinforced concrete (SFRC) beams with corrosion of the longitudinal reinforcement using the ABAQUS package. This work was undertaken with the concrete damaged plasticity model (CDP). The expansion of corrosion product was utilized to represent the steel-concrete boundary to study the behavior of SFRC beams. Three beams with three volume fractions of steel fiber (0.8 %, 1.2 %, and 1.8 %) and three reinforced concrete (RC) beams with and without stirrups were created and tested under four-point loading to assess the shear capacity of beams. Corrosion of rebars at one of the RC beams that does not contain shear reinforcements will be studied. The crack patterns and load deflections of these beams were compared with experimental results found by the authors. The conclusions of this analysis will be valuable in considering the structural behavior of SFRC structures with uniform steel bar corrosion using FEM. Analytical results showed that the suggested model is qualified in better simulation and in accuracy of numerical and experimental results. The differences between analytical and experimental results were less than 8 % for load carrying capacity and 14 % for deflection; these differences are also satisfactory within the limits of the engineering conclusion.


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