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Predicting the strength properties of slurry infiltrated fibrous concrete using artificial neural network
Abstract This paper is aimed at adapting Artificial Neural Networks (ANN) to predict the strength properties of SIFCON containing different minerals admixture. The investigations were done on 84 SIFCON mixes, and specimens were cast and tested after 28 days curing. The obtained experimental data are trained using ANN which consists of 4 input parameters like Percentage of fiber (PF), Aspect Ratio (AR), Type of admixture (TA) and Percentage of admixture (PA). The corresponding output parameters are compressive strength, tensile strength and flexural strength. The predicted values obtained using ANN show a good correlation between the experimental data. The performance of the 4-14-3 architecture was better than other architectures. It is concluded that ANN is a highly powerful tool suitable for assessing the strength characteristics of SIFCON.
Predicting the strength properties of slurry infiltrated fibrous concrete using artificial neural network
Abstract This paper is aimed at adapting Artificial Neural Networks (ANN) to predict the strength properties of SIFCON containing different minerals admixture. The investigations were done on 84 SIFCON mixes, and specimens were cast and tested after 28 days curing. The obtained experimental data are trained using ANN which consists of 4 input parameters like Percentage of fiber (PF), Aspect Ratio (AR), Type of admixture (TA) and Percentage of admixture (PA). The corresponding output parameters are compressive strength, tensile strength and flexural strength. The predicted values obtained using ANN show a good correlation between the experimental data. The performance of the 4-14-3 architecture was better than other architectures. It is concluded that ANN is a highly powerful tool suitable for assessing the strength characteristics of SIFCON.
Predicting the strength properties of slurry infiltrated fibrous concrete using artificial neural network
Reddy, T. Chandra Sekhara (author)
Frontiers of Structural and Civil Engineering ; 12 ; 490-503
2017-12-19
14 pages
Article (Journal)
Electronic Resource
English
Slurry infiltrated fibrous concrete
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Shear strength characteristics of slurry infiltrated fibrous concrete
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Toughness of Slurry Infiltrated Fibrous Concrete (SIFCON)
| British Library Conference Proceedings | 1994
Studies on Slurry-Infiltrated Fibrous Concrete (SIFCON)
| British Library Online Contents | 1993
Properties and Applications of Slurry Infiltrated Fibrous Concrete (Silicon)
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