Evaluation of the Deterioration of Ceramic Claddings by Application of Artificial Neural Networks
Publication: Journal of Performance of Constructed Facilities
Volume 34, Issue 5
Abstract
The definition of models to evaluate the durability of buildings can be a challenging task due to the large set of variables, and their complexity, which affect the performance and durability of buildings. Recently, several methodologies have been developed to predict the service life of buildings and their components. The knowledge acquired through these models allowed for the adopting of more rational and sustainable solutions. This study proposes the application of artificial neural networks (ANNs) to estimate the service life of ceramic claddings of buildings in Brasília, Brazil. The variables that impact the service life of these claddings are identified through a stepwise regression analysis. Based on these variables, an ANN model was created to evaluate the degradation of ceramic claddings. The validity of the models proposed, a multiple linear regression (MLR) model and an ANN model, is discussed as well as the physical sense of the results obtained. According to similar studies and the empirical knowledge linked to the degradation of ceramic tile claddings, the models proposed lead to coherent results.
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Data Availability Statement
All data used during the study were provided by a third party (Materials Laboratory of the University of Brasília). Direct requests for these materials may be made to the provider as indicated in the Acknowledgments. All models and code generated or used during the study appear in the published article.
Acknowledgments
The authors are grateful for the support of Instituto Superior Técnico (IST) of University of Lisbon and of the Foundation for Science and Technology (FCT), the data supplied by Materials Laboratory of the University of Brasília (LEM-UnB), and the financial support provided by the National Council for Scientific and Technological Development (CNPq) and the Erasmus Mundus Program.
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Published In
Journal of Performance of Constructed Facilities
Volume 34 • Issue 5 • October 2020
Copyright
©2020 American Society of Civil Engineers.
History
Received: Apr 9, 2019
Accepted: Feb 12, 2020
Published online: Jun 19, 2020
Published in print: Oct 1, 2020
Discussion open until: Nov 19, 2020
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