Calculation of Load-Carrying Capacity of Square Concrete Filled Tube Columns Based on Neural Network

Article Preview

Abstract:

Concrete filled steel tubes of square columns under axial load are in complicated stress, the influence of every factor on mechanics performance is difficult to ascertain accurately. Neural network performs well obtaining the relationship between input and output variables by self-studying, self-organizing, self-adapting and nonlinear mapping. In this paper a three-layer back-propagation model of network is successfully trained and set up according to experimental data of square CFT columns under load. Ten groups of experimental data were verified by the model, the results show the predicted values are in accord with test values, precision in calculation is good enough for structure design. So the neural network model can be used as an auxiliary method to calculate the capacity of square concrete filled tube columns in the project. With the increase of experimental data, the neural network precision of prediction will be improved in the future.

You might also be interested in these eBooks

Info:

Periodical:

Pages:

847-850

Citation:

Online since:

July 2011

Authors:

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2011 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

[1] Han L.H. Tao Z. Civil Engineering Journal. Vol. 2(2001), pp.17-25, in Chinese.

Google Scholar

[2] Han L H. Theory and Practice of Concrete Filled Steel Tube Structure( Science Press, Beijing 2004), in Chinese.

Google Scholar

[3] Wang H. J., Hasegawa A. and Shoe Y. Civil Engineering Symposium. Vol. 6(1999). pp.84-85.

Google Scholar

[4] Fan H. Journal of Zhuzhou Institute of Technology. Vol. 4(2002), pp.32-34, in Chinese.

Google Scholar

[5] Zhang X.W. Zhong P . Sichuan Building Science Research. Vol. 4(1994). pp.16-20, in Chinese.

Google Scholar

[6] Tao Z. ,Wei Z.B. and Han L.H. Vol. 10 (1998), pp.10-14, in Chinese.

Google Scholar

[7] Li S.P., Huo D, et al. Journal of Building Structures. Vol. 1 (1998), pp.41-51, in Chinese.

Google Scholar

[8] Fujimoto T, A. Mukai, I. Nishiyama, K. Sakino. Journal of Structural Engineering. Vol. 2(2004), pp.123-129.

Google Scholar

[9] Brain U. Journal of Structural Engineering. Vol. 3. (2000), pp.84-91.

Google Scholar

[10] Min X.L. and Liu G.H. Computer Applications. Vol. 8. (2001), pp.164-165. in Chinese.

Google Scholar

[11] Wei, H., Iwasaki, S., Hasegawa, A., Shioi, Y. & Miyamoto, Y. Journal of Constructional Steel Vol. 10(2002), pp.519-526.

Google Scholar

[12] Luo H.C. Computer Simulation. Vol. 5(2004), pp.109-111, in Chinese.

Google Scholar

[13] Zuo M S, Li S P, Wang Q. Journal of Building Structure, Vol. 3(1992), pp.31-36, in Chinese.

Google Scholar

[14] Zhang Z G. Journal of Building Structures, Vol. 6 (1989), pp.31-36, in Chinese.

Google Scholar