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Machine learning ensemble models coupled with FEM to simulate reinforced concrete structures under carbonation-induced corrosion

Grant number: 23/04364-9
Support Opportunities:Regular Research Grants
Duration: September 01, 2023 - August 31, 2025
Field of knowledge:Engineering - Civil Engineering - Structural Engineering
Principal Investigator:Emerson Felipe Félix
Grantee:Emerson Felipe Félix
Host Institution: Faculdade de Engenharia (FEG). Universidade Estadual Paulista (UNESP). Campus de Guaratinguetá. Guaratinguetá , SP, Brazil
Associated researchers: Edna Possan ; Lisiane Pereira Prado ; Rogério Carrazedo


With the purpose to model the corrosion phenomenon and its effects on the mechanical behavior of reinforced concrete structures, a numerical approach will be proposed and implemented for physical nonlinear analysis based on the mechanics of continuous damage coupled to formulations that map the CO2 diffusion and the corrosion potential. As an original contribution, models of concrete carbonation and corrosion potential will be created by Machine Learning Ensemble techniques, considering Regression Trees and Artificial Neural Networks. The numerical simulations will be performed at a mesoscopic level using the positional finite element method, allowing the triphasic representation of reinforced concrete (mortar, coarse aggregates, and reinforcements). This approach, as well as the use of Machine Learning algorithms, has been applied by the research coordinator in the development of models and degradation studies in the last ten years, indicating its potential for mapping the behavior of concrete structures subjected to chemical and mechanical loads. The purpose of this project is to evaluate the potential of the combined use of Machine Learning Ensemble techniques with the finite element method, as well as to use these techniques to significantly improve the accuracy and robustness of concrete carbonation and potential corrosion models, providing more reliable tools to design and manage reinforced concrete structures. (AU)

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