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Using Numerical Modelling and Artificial Intelligence for Predicting the Degradation of the Resistance to Vertical Shear in Steel – Concrete Composite Beams Under Fire

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Applied Computer Sciences in Engineering (WEA 2020)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1274))

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Abstract

In this paper the combination of numerical modelling and artificial intelligence for predicting the degradation of the resistance to vertical shear in composite beams under fire is exposed. This work presents a technique that integrates the backpropagation learning method with a method to calculate the initial weights in order to train the Multilayer Perceptron Model (MLP). The method used to calculate the initial weights of the MLP is based on the quality of similarity measure proposed on the framework of the extended Rough Set Theory (RST). The artificial neural network models were trained and tested using numerical results from the thermal-structural analysis carried out by the two-dimensional fire-dedicated FE software Super Tempcalc and the computational tool SCBEAM which was developed by the authors for the resistances determinations. The results revealed that the proposed approach accurately permits the prediction of the degradation of the resistance to vertical shear in steel – concrete composite beams under fire.

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Acknowledgements

The authors gratefully acknowledge the support provided by CAPES (Coordination for the Improvement of Higher Level Personnel, Brazil) and FAPESP (São Paulo Research Foundation, Brazil). The authors would also like to thank Eng. Natoya Corneilla Thomas for her appreciated assistance.

Author information

Authors and Affiliations

  1. Department of Civil Engineering, University of Camaguey, Carretera Circunvalación Norte km 5 1/2., 74650, Camaguey, Cuba

    Rafael Larrua Quevedo & Yisel Larrua Pardo

  2. Department of Structural and Geotechnical Engineering, Polytechnic School of the University of Sao Paulo (EPUSP), Av. Prof. Almeida Prado TRAV. 2, 83, 05508-900, São Paulo, SP, Brazil

    Valdir Pignatta Silva

  3. Research and Development Department, AMV Soluciones, Avenida de Madrid 40, Oficina 14, 36204, Vigo, Spain

    Yaima Filiberto Cabrera

  4. Department of Computer Sciences, University of Camaguey, Camaguey, Cuba. Carretera Circunvalación Norte km 5 1/2., 74650, Camaguey, Cuba

    Yaile Caballero Mota

Authors
  1. Rafael Larrua Quevedo
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  2. Yisel Larrua Pardo
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  3. Valdir Pignatta Silva
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  4. Yaima Filiberto Cabrera
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  5. Yaile Caballero Mota
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Corresponding author

Correspondence to Yaima Filiberto Cabrera .

Editor information

Editors and Affiliations

  1. Universidad Distrital Francisco José de Caldas, Bogotá, Colombia

    Juan Carlos Figueroa-García

  2. Infantry School of the National Colombian Army, Bogotá, Colombia

    Fabián Steven Garay-Rairán

  3. National University of Colombia, Bogotá, Colombia

    Germán Jairo Hernández-Pérez

  4. Corporación Unificada Nacional CUN, Bogotá, Colombia

    Yesid Díaz-Gutierrez

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Larrua Quevedo, R., Larrua Pardo, Y., Pignatta Silva, V., Filiberto Cabrera, Y., Caballero Mota, Y. (2020). Using Numerical Modelling and Artificial Intelligence for Predicting the Degradation of the Resistance to Vertical Shear in Steel – Concrete Composite Beams Under Fire. In: Figueroa-García, J.C., Garay-Rairán, F.S., Hernández-Pérez, G.J., Díaz-Gutierrez, Y. (eds) Applied Computer Sciences in Engineering. WEA 2020. Communications in Computer and Information Science, vol 1274. Springer, Cham. https://doi.org/10.1007/978-3-030-61834-6_4

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  • DOI: https://doi.org/10.1007/978-3-030-61834-6_4

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-61833-9

  • Online ISBN: 978-3-030-61834-6

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