Prediction of the Behaviours by the Prismatic Beams with Polypropylene Fibers under High Temperature Effects through Artificial Neural Networks

Fatih Altun, Tamer Dirikgil

Abstract

In order to improve the mechanical qualities of a concrete, various kinds of fibers are added to the concrete. In the studies, polypropylene (PP) fibers are employed as a fiber type. It has a significant place in the researches that PP fibers not only improve the mechanical qualities of the concrete under normal temperatures, but also prevents the bursting of the concrete with the internal vapour compression under high temperatures. The distributions and locations of the fibers in the concrete and the variables employed for experimental proceedings affect the mechanical results. This makes it difficult to link the obtained results to each other. In order to establish a complicated link, it is inevitable to create a learning mechanism. In this study, multilayered perceptrons (MLP) and radial basis function artificial neural network (RBFNN) models were used and their flexure strengths were sought to be predicted. Both of the neural network models put in a successful performance and enabled the prediction of the experimental results with a satisfying approximation.

References

  1. Alexandridis, A., Triantis, D., Stavrakas, I., Stergiopoulos, C., 2012. A neural network approach for compressive strength prediction in cement-based materials through the study of pressure-stimulated electrical signals. Construction and Building Materials, vol. 30, pp. 294-300.
  2. Astrom, K. J., Eykhoff, P., 1971. Automatica 7, pp. 123- 162.
  3. Matlab R2009b, 2009. The Mathwork Inc. Company, Massachusetts, U.S.A
  4. TSI. TS EN 206/1, 2002. Concrete. Turkish Standards Ankara. In Turkish.
Download


Paper Citation


in Harvard Style

Altun F. and Dirikgil T. (2012). Prediction of the Behaviours by the Prismatic Beams with Polypropylene Fibers under High Temperature Effects through Artificial Neural Networks . In Proceedings of the 4th International Joint Conference on Computational Intelligence - Volume 1: NCTA, (IJCCI 2012) ISBN 978-989-8565-33-4, pages 611-615. DOI: 10.5220/0004114006110615


in Bibtex Style

@conference{ncta12,
author={Fatih Altun and Tamer Dirikgil},
title={Prediction of the Behaviours by the Prismatic Beams with Polypropylene Fibers under High Temperature Effects through Artificial Neural Networks},
booktitle={Proceedings of the 4th International Joint Conference on Computational Intelligence - Volume 1: NCTA, (IJCCI 2012)},
year={2012},
pages={611-615},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004114006110615},
isbn={978-989-8565-33-4},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 4th International Joint Conference on Computational Intelligence - Volume 1: NCTA, (IJCCI 2012)
TI - Prediction of the Behaviours by the Prismatic Beams with Polypropylene Fibers under High Temperature Effects through Artificial Neural Networks
SN - 978-989-8565-33-4
AU - Altun F.
AU - Dirikgil T.
PY - 2012
SP - 611
EP - 615
DO - 10.5220/0004114006110615