scholarly journals EFFECT OF SPECIMEN SHAPE ON THE COMPRESSIVE PARAMETERS OF STEEL FIBER REINFORCED CONCRETE AFTER TEMPERATURE EXPOSURE

2018 ◽  
Vol 1 (1) ◽  
pp. 10-20
Author(s):  
Ramoel Serafini ◽  
Felipe Pereira Santos ◽  
Ronney Rodrigues Agra ◽  
Albert De la Fuente ◽  
Antonio Domingues de Figueiredo

This study investigated the effect of specimen shape (cylindrical and cubical) on the compressive strength and elastic modulus of steel fiber reinforced concrete after exposure to the temperatures of 150, 300, 450, and 600 °C. Results show that the compressive strength and elastic modulus of the composite significantly reduce with the increase in temperature, independent of the specimen shape. Additionally, a significant difference in the compressive strength and elastic modulus conversion factors for cube-cylinder was verified with the increase in temperature. This study contributes to the limited amount of studies regarding the effect of elevated temperatures on steel fiber reinforced concretes and shows that the elevated temperatures may have a significant effect in the conversion factors for cube-cylinder.

Author(s):  
Payal Sachdeva ◽  
A.B. Danie Roy ◽  
Naveen Kwatra

Headed bars (HB) with different head shapes (Square, Circular, and Rectangular) and bar diameters (db: 16, 20, and 25 mm) embedded in steel fiber reinforced concrete have been subjected to pull-out test. The influence of head shapes, concrete compressive strength (M20 and M40), db, and steel fibers (0, 0.5, 1, and 1.5%) on the anchorage capacity of HB have been evaluated. Numerical model for improving the anchorage capacity of HB has also been proposed. Results have revealed that the anchorage capacity of HB increases with the increase in concrete compressive strength, db, and steel fibers, which have been validated by non-linear regression analysis using dummy variables. Two failure modes namely, steel and concrete-blowout have been observed and the prevailing mode of failure is steel failure. Based on load-deflection curves and derived descriptive equations, it is observed that the circular HB has displayed the highest peak load.


2020 ◽  
Vol 10 (7) ◽  
pp. 2324 ◽  
Author(s):  
Peng Zhang ◽  
Luoyi Kang ◽  
Juan Wang ◽  
Jinjun Guo ◽  
Shaowei Hu ◽  
...  

Steel-fiber-reinforced concrete (SFRC) is being increasingly applied to various buildings and civil infrastructure as an advanced cementitious composite. In recent years, the requirements for SFRC in the construction industry have increased. Additionally, the fire resistance of SFRC has attracted attention; therefore, numerous investigations regarding the residual properties of SFRC have been conducted. This paper critically reviews the mechanical properties of SFRC subjected to elevated temperatures, including its residual compressive strength, flexural strength, tensile strength, elastic properties, fracture properties, and stress–strain relationships. The residual mechanical performance of SFRC and the action mechanism of steel fibers are reviewed in detail. Moreover, factors affecting the explosive spalling of concrete at high temperatures as well as the effect of steel fibers on the microstructure of heated concrete are discussed. It is demonstrated that, in general, SFRC exhibits better residual mechanical properties when exposed to elevated temperatures than plain concrete and can prevent the risk of explosive spalling more effectively. The purpose of this literature review is to provide an exhaustive insight into the feasibility of SFRC as a refractory building material; additionally, future research needs are identified.


2014 ◽  
Vol 629-630 ◽  
pp. 245-251
Author(s):  
Liang Huo ◽  
Xi Qiang Lin ◽  
Guo You Li ◽  
Tao Zhang

It used conventional techniques and materials prepared high strength fiber reinforced concrete whose strength class is above C100 and it studied the effect of fiber content on the mechanical properties and elastic modulus. It also studied the fire resistance of fiber reinforced concrete. Results suggest that the strength of 28d concrete is above 100MPa and the highest strength is 126.4MPa. Under the same ratio conditions, the greater the volume content of steel fiber concrete flexural strength, the splitting tensile strength is higher. The steel fiber volume only affect elastic modulus of concrete little. When it heats to 300 °C, the no fiber concrete comminuted burst while the fiber concrete does not damaged at elevated temperatures up to 300 °C and continue to heat up, the crushing damage occurs at about 460 °C. Has not been damaged concrete specimens at 300 °C, the quality have emerged about 3% decline, while the compressive strength increased by 35%-52%, the highest strength reached 180.3MPa.


2021 ◽  
Vol 5 (7 (113)) ◽  
pp. 59-65
Author(s):  
Nadia Moneem Al-Abdaly ◽  
Salwa R. Al-Taai ◽  
Hamza Imran ◽  
Majed Ibrahim

Because of the incorporation of discontinuous fibers, steel fiber-reinforced concrete (SFRC) outperforms regular concrete. However, due to its complexity and limited available data, the development of SFRC strength prediction techniques is still in its infancy when compared to that of standard concrete. In this paper, the compressive strength of steel fiber-reinforced concrete was predicted from different variables using the Random forest model. Case studies of 133 samples were used for this aim. To design and validate the models, we generated training and testing datasets. The proposed models were developed using ten important material parameters for steel fiber-reinforced concrete characterization. To minimize training and testing split bias, the approach used in this study was validated using the 10-fold Cross-Validation procedure. To determine the optimal hyperparameters for the Random Forest algorithm, the Grid Search Cross-Validation approach was utilized. The root mean square error (RMSE), coefficient of determination (R2), and mean absolute error (MAE) between measured and estimated values were used to validate and compare the models. The prediction performance with RMSE=5.66, R2=0.88 and MAE=3.80 for the Random forest model. Compared with the traditional linear regression model, the outcomes showed that the Random forest model is able to produce enhanced predictive results of the compressive strength of steel fiber-reinforced concrete. The findings show that hyperparameter tuning with grid search and cross-validation is an efficient way to find the optimal parameters for the RF method. Also, RF produces good results and gives an alternate way for anticipating the compressive strength of SFRC


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