Optimization of concrete durability using artificial intelligence: Modeling and prediction of eco-concrete performance with fly ash
Kaoutar BAZZAR, Salma CHRIT, Adil HAFIDI ALAOUI
Abstract. Dealing with the waste and by-products of industry is a major environmental and economic issue. The effort of optimization of materials, especially concrete, is of great importance in construction. Cement production contributes a large share of global CO₂ emissions. Using fly ash to partially replace cement can create eco-friendly concrete which is one of the potential sustainable strategies. This valorization tactic results in lower quantities of fly ash disposed of in dump. In addition, it also reduces the amount of cement consumed, that too without altering the mechanical performance (which is satisfactory). In recent years, artificial intelligence (AI) has proved to be a strong ally helping improve and predict the performance of eco-concrete. One may estimate early-age compressive strength through machine learning algorithms using different parameters like fly ash content or particle size distribution. Instead, deep learning techniques can be used to forecast long-term durability with large experimental and in-situ datasets for characteristics such as ettringite formation and porosity. The approach proposes to study the influence of fineness of fly ash, optimize the key factors affecting the mechanical behavior, and investigate the reasons behind expansion and cracking. All in all, these methods help in making the construction industry sustainable.
Keywords
Sustainable Concrete, Fly Ash, Mechanical Strength, Artificial Intelligence, Machine Learning
Published online 1/10/2026, 8 pages
Copyright © 2026 by the author(s)
Published under license by Materials Research Forum LLC., Millersville PA, USA
Citation: Kaoutar BAZZAR, Salma CHRIT, Adil HAFIDI ALAOUI, Optimization of concrete durability using artificial intelligence: Modeling and prediction of eco-concrete performance with fly ash, Materials Research Proceedings, Vol. 58, pp 24-31, 2026
DOI: https://doi.org/10.21741/9781644903933-4
The article was published as article 4 of the book Emerging Research in Materials for Environment, and Civil Infrastructure
Content from this work may be used under the terms of the Creative Commons Attribution 3.0 license. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI.
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