Estimating Fracture Eenergy of Concrete Using Artificial Neural Networks

Authors

1 Faculty of Civil Engineering, Sahand University of Technology

2 Faculty of Mechanical Engineering, Sahand University of Technology

3 Mining Engineering, Sahand University of Technology

Keywords

References

[1]        Kaplan, M., "Crack Ppropagation and the Ffracture of Concrete", American Concrete Institute ACI. J., 1961, 58 (5),591-610.
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[4]        Ince, R., "Prediction of Fracture Parameters of Concrete by Artificial Neural Networks", Engineering Fracture Mechanics, 2004, 71 (15), 2143-2159.
[5]        Roesler, J., Paulino, G. H., Park, K., Gaedicke, C., "Concrete Fracture Prediction Using Bilinear Softening", Cement and Concrete Composites, 2007, 29 (4), 300-312.
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[8]        Zhao, Z., Kwon, S. H., Sandra, S. P., "Effect of Specimen Size on Fracture Energy and Softening Curve of Concrete: Part I. Experiments and Fracture Energy", Cement and Concrete Research, 2008, 38 (8-9), 1049-1060.
[9]        Hu, X., Duan, K., "Influence of Fracture Process Zone Height on Fracture Energy of Concrete", Cement and Concrete Research, 2004, 34 (8), 1321-1330.
[10]     Topcu, I. B., Karakurt, C., Sarıdemir, M., "Predicting the Strength Development of Cements Produced with Different Pozzolans by Neural Network and Fuzzy Logic", Materials & Design, 2008, 29 (10), 1986-1991.
]11[    منهاج، م.، "هوش محاسباتی (جلد اول): مبانی شبکه‏های عصبی"، مرکز نشر دانشگاه صنعتی امیر‏کبیر، چاپ ششم، تهران، 1388.
[12]     INCE, R., "Artificial Neural Network Based Analysis of Effective Crack Model in Concrete Fracture", Fatigue & Fracture of Engineering Materials & Structures, 2010, 33 (9), 595-606.
 
Journal of Civil and Environmental Engineering
Volume 42.1, Issue 66 - Serial Number 66
Spring 2012
June 2012
Pages 1-8

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