In the bustling, sun-drenched city of Algiers, a groundbreaking study is shedding new light on how external wall paintings weather the test of time—and the elements. Aghiles Hammas, a researcher at the National Center for Building Studies and Integrated Research (CNERIB), has turned the city’s facades into a living laboratory, aiming to predict the service life of exterior coatings with unprecedented accuracy.
Hammas and his team inspected 45 buildings, meticulously assessing the degradation of their external wall paintings. “The idea was to understand how different factors like age, proximity to the coast, and facade orientation influence the lifespan of these coatings,” Hammas explains. The results, published in the Journal of Architectural and Engineering Research (Revue de Recherche en Architecture et Génie Civil), could have significant implications for the construction and energy sectors.
The study employed both simple and multiple linear regression analyses to develop a mathematical model that predicts the service life of external wall paintings. The model demonstrated a high correlation between predicted and actual degradation, with a coefficient of determination of 0.95. “This means our model is highly accurate in predicting the service life of these coatings,” Hammas states.
For the construction industry, this research offers a valuable tool for planning and maintenance. By predicting when external wall paintings are likely to degrade, building owners and managers can schedule repairs and replacements more efficiently, reducing costs and improving building aesthetics. Moreover, understanding the factors that accelerate degradation can inform the choice of materials and coatings, enhancing their durability.
The energy sector also stands to benefit. External wall coatings play a crucial role in a building’s thermal performance. Degraded coatings can lead to increased energy consumption for heating and cooling, as they fail to insulate effectively. By extending the service life of these coatings, the research could contribute to more energy-efficient buildings, reducing their carbon footprint.
Hammas’s work also challenges existing models. The study compared its findings with previous research on service life prediction, demonstrating that its model offers good precision despite considering a moderate number of buildings. This suggests that even with limited data, accurate predictions can be made, paving the way for more localized and tailored models.
As cities worldwide grapple with aging infrastructure and the need for sustainable, energy-efficient buildings, Hammas’s research offers a promising path forward. By understanding and predicting the degradation of external wall coatings, we can build smarter, more resilient cities. As Hammas puts it, “This is not just about paint. It’s about creating buildings that last, that perform, and that contribute to a sustainable future.”