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Degradation Models and Maintenance Strategies for Reinforced Concrete Structures in Coastal Environments under Climate Change: A Review

Author(s): ORCID

ORCID
ORCID
ORCID
Medium: journal article
Language(s): English
Published in: Buildings, , n. 3, v. 14
Page(s): 562
DOI: 10.3390/buildings14030562
Abstract:

Modern engineering faces challenges in ensuring technical standards for service, durability, and sustainability. Political, administrative, and budgetary factors, coupled with climate change, pose tasks to structural integrity, affecting industries and economies. Marine infrastructures represent a strategic asset of a country as they handle a large part of the economic exchanges. This article analyzes five essential factors that play a fundamental role in the performance analysis of coastal structures: chloride-induced corrosion, degradation models, maintenance strategies, monitoring, and climate change. We start with reinforcement corrosion, which is considered as the main cause of distress, particularly in coastal zones, for the long-term behavior of structures. Additional pressure from the influences of climate change is becoming evident and extreme, leading to a reduction in capacity. To guarantee the lifespan of infrastructures, degradation models contribute by estimating the long-term performance of the asset as a strategic piece to the development of effective maintenance solutions. Artificial Neural Networks (ANNs) have gained recent prominence in this field due to their ability to learn intricate patterns from historical data, making them valuable instruments for predicting structural deterioration. Additionally, quantifying the condition of the structure from monitoring data plays a crucial part in providing information on the current situation of the structure. Finally, this review summarizes the challenges associated with the maintenance of aging marine structures considering aspects such as corrosion, monitoring, and the future challenges this area will face due to climate change.

Copyright: © 2024 by the authors; licensee MDPI, Basel, Switzerland.
License:

This creative work has been published under the Creative Commons Attribution 4.0 International (CC-BY 4.0) license which allows copying, and redistribution as well as adaptation of the original work provided appropriate credit is given to the original author and the conditions of the license are met.

  • About this
    data sheet
  • Reference-ID
    10773833
  • Published on:
    29/04/2024
  • Last updated on:
    29/04/2024
 
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