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This paper presents a hybrid approach for assessing the durability of self-compacting concrete (SCC) in Algeria using Fuzzy-logic and Bayesian network (BN) methods. The methodology comprises three principal steps: Constructing a database based on expert opinions, learning the Bayesian Network (BN) structure, and using the BN for durability assessment. Focusing on the influence of uncertainties for eighty-six (86) basic events, probabilistic inference techniques combined with fuzzy set theories are used to predict SCC durability. The study classifies and evaluates the impact of critical events on SCC durability, conducting a comparative analysis between coastal and desert regions. Results indicate a significant SCC durability rate of 84.73%, highlighting influences from material defects, bad design, corrosion, poor construction sites, external forces, and cracks. These insights aid decision-makers in improving SCC structures.

Item Type	Journal
Divisions	» Laboratory of Research on Electromechanical and Dependability
ePrint ID	5179
Date Deposited	2024-10-05
Further Information	Google Scholar
URI	https://univ-soukahras.dz/en/publication/article/5179

@article{uniusa5179,
    title={Self-Compacting Concrete Durability Assessment via Fuzzy-Logic and Bayesian Networks},
    author={Khalil Abdi, Yacine Sahraoui, Nabil Kebaili and Mourad Nahal},
    journal={Iranian Journal of Science and Technology, Transactions of Civil Engineering}
    year={2024},
    volume={},
    number={},
    pages={1-21},
    publisher={Springer International Publishing}
}