Artificial Neural Network Model for FRP Shear Contribution of RC Beams Strengthened with Externally Bonded FRP Composites

DOI

10.2991/icmea-17.2018.38How to use a DOI?

Keywords

artificial neural network; fiber reinforced polymer (FRP); reinforced concrete (RC) beam; shear-strengthening

Abstract

Fiber reinforced polymers (FRP) have been widely used in retrofitting or strengthening concrete structures in recent years. This is due to the various advantages of FRP composites, including high strength-weight ratio, high tensile modulus, superior corrosion resistance and ease of applying in strengthening applications. One of the most important applications of FRP is shear strengthening for reinforced concrete (RC) beams. In this paper, two different artificial neural network (ANN) models are proposed for predicting the FRP shear contribution of RC beams strengthened in shear with U-wrapping FRP sheets with/without additional anchorage system, respectively. To verify the accuracy of the ANN models, the predictions from five existing design guidelines are applied to comparison. It is found that the proposed ANN models can improve the accuracy of predicting the shear contribution for U-wrapping FRP configuration whether with anchorage or without one.

Copyright

© 2018, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Weiwen Li
AU  - Xiaoli Ren
AU  - Chengyue Hu
PY  - 2018/02
DA  - 2018/02
TI  - Artificial Neural Network Model for FRP Shear Contribution of RC Beams Strengthened with Externally Bonded FRP Composites
BT  - Proceedings of the 4th Annual International Conference on Material Engineering and Application (ICMEA 2017)
PB  - Atlantis Press
SP  - 166
EP  - 169
SN  - 2352-5401
UR  - https://doi.org/10.2991/icmea-17.2018.38
DO  - 10.2991/icmea-17.2018.38
ID  - Li2018/02
ER  -