The study, published in the journal Scientific Reports, describes factors that influence degradation, such as age, thickness, temperature and traffic levels. Based on data analysis, key parameters affecting the durability of structures, such as annual temperature, precipitation and humidity, were determined.
Professor Ghazi Al-Khatib, lead author of the study, said the findings could help engineers proactively detect potential problems and develop prevention strategies. Machine learning models based on regression analysis have shown high accuracy in predicting failure.
Professor Al-Khatib emphasized the importance of considering critical factors when planning the maintenance of reinforced concrete structures, which can significantly increase their durability and safety.
Source: Ferra
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