Predictive Performance Evaluation of an Eco-Friendly Pavement Using Baosteel’s Slag Short Flow (BSSF) Steel Slag

Predicting pavement performance is essential for highway planning and construction, considering traffic, climate, material quality, and maintenance. This study’s main objective is to evaluate Baosteel’s Slag Short Flow (BSSF) steel slag as a sustainable aggregate in pavement engineering by means of...

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Bibliographic Details
Main Authors: Livia Costa, Iuri Bessa, Juceline Bastos, Aline Vale, Teresa Farias
Format: Article
Language:English
Published: MDPI AG 2025-06-01
Series:Applied Mechanics
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Online Access:https://www.mdpi.com/2673-3161/6/2/45
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Summary:Predicting pavement performance is essential for highway planning and construction, considering traffic, climate, material quality, and maintenance. This study’s main objective is to evaluate Baosteel’s Slag Short Flow (BSSF) steel slag as a sustainable aggregate in pavement engineering by means of durability. The research integrates pavement performance prediction using BSSF and assesses its impact on fatigue resistance and percentage of cracked area (%CA). Using the Brazilian mechanistic-empirical design method (MeDiNa), eight scenarios were analyzed with soil–slag mixtures (0%, 25%, 50%, and 75% slag) in base and subbase layers under two traffic levels over 10 years. An asphalt mixture with 15% steel slag aggregate (SSA) was used in the surface layer and compared to a reference mixture. Higher SSA percentages were applied to the base layer, while lower percentages were used in subbase layers, facilitating field implementation. The resilient modulus (MR) and permanent deformation (PD) were design inputs. The results show that 15% SSA does not affect rutting damage, with %CA values below Brazilian limits for traffic of 1 × 10<sup>6</sup>. The simulations confirm BSSF as an effective and sustainable alternative for highway pavement construction, demonstrating its potential to improve durability and environmental impact while maintaining performance standards.
ISSN:2673-3161