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Artificial Intelligence Applied in the Concrete Durability Study

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Hygrothermal Behaviour and Building Pathologies

Part of the book series: Building Pathology and Rehabilitation ((BUILDING,volume 14))

Abstract

Interest in artificial intelligence (AI) in engineering research and practice has increased in recent years, especially the use of artificial neural network (ANN). The ANN has similar characteristics to biological neural networks, efficiently recognizing patterns and behaviors, suited to provide an accurate tool to map and understand the concrete degradation. This chapter presents the positive aspects of artificial neural network to model different concrete degradation mechanisms and provides a detailed procedure for ANN design. As example, the concrete carbonation depth is modeled by an ANN and the results show the its ability to map the carbonation phenomenon.

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Acknowledgments

The financial support by the Coordination for the Improvement of Higher Education Personnel (CAPES) and the Brazilian National Council for Scientific and Technological Development (CNPq) is gratefully acknowledged.

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Authors and Affiliations

  1. University of São Paulo, São Paulo, Brazil

    E. F. Felix & R. Carrazedo

  2. University of Latin American Integration, Foz Do Iguaçu, Brazil

    E. Possan

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  1. E. F. Felix
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  2. E. Possan
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  3. R. Carrazedo
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Correspondence to E. F. Felix .

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Editors and Affiliations

  1. CONSTRUCT-LFC, Department of Civil Engineering, University of Porto, Porto, Portugal

    J.M.P.Q. Delgado

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Felix, E.F., Possan, E., Carrazedo, R. (2021). Artificial Intelligence Applied in the Concrete Durability Study. In: Delgado, J. (eds) Hygrothermal Behaviour and Building Pathologies. Building Pathology and Rehabilitation, vol 14. Springer, Cham. https://doi.org/10.1007/978-3-030-50998-9_5

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