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Title: Novel trends on the assessment and management of maritime infrastructures: outcomes from GIIP project
Authors: Rincon, L.
Matos, J.
Pereira, E. V.
Marcelino, J.
Oliveira Santos, L.
Moscoso, Y.
Bastidas-Arteaga, E.
Keywords: Maintenance actions;Neuronal networks;Markov chains;Monitoring practice;Corrosion;Maritime infrastructures
Issue Date: Jun-2022
Publisher: WCSCM
Abstract: Climatic conditions, load, fatigue, aging and other factors causes a de-terioration in civil infrastructures. As a consequence, repair and maintenance work actions are needed, being the former considered as more expensive than the latter ones. Indeed, an accurate method for measuring corrosion is a fundamental prerequisite for the detection of damaged areas and for planning an effective re-pairing of concrete maritime structures. In this article a comparation between two surrogate models, Markov Chains and Neuronal Networks, is presented and ap-plied to predict the results of corrosion sensors of an infrastructure data set. The proposed methodology benefits from current monitoring practice and have the objective to develop a modular decision support system for the integrated asset management, taking into account operational, economic and environmental cri-teria. The results could contribute to the possibility of adapting these degradation models to aggressive environments and repaired structures, thus generating ac-curate maintenance strategies, and reducing costs. This methodology is part of the ongoing study “GIIP- Intelligent Port Infrastructure Management”.
Appears in Collections:DE/NOE - Comunicações a congressos e artigos de revista

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