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 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 × 106. 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.

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Publication Details

Journal
Applied Mechanics
Published
2025-06-16
DOI
https://doi.org/10.3390/applmech6020045
Primary Topic
Asphalt Pavement Performance Evaluation
Type
article
Field-Weighted Citation Impact
0.00

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article

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

Iuri Sidney Bessa, Livia Ingrid Oliveira Costa, Teresa Raquel Lima Farias, Aline Vale et al.
Applied Mechanics
Asphalt Pavement Performance Evaluation
article

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

Iuri Sidney Bessa, Livia Ingrid Oliveira Costa, Teresa Raquel Lima Farias, Aline Vale, Juceline Batista dos Santos Bastos
article en

Abstract

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 × 106. 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.

Applied MechanicsVol. 6(2)
Universidade Federal do Ceará (BR), Instituto Federal de Educação, Ciência e Tecnologia do Ceará (BR)
ArcelorMittal, Conselho Nacional de Desenvolvimento Científico e Tecnológico
Openalex Percentile: Top 86%
Asphalt Pavement Performance Evaluation
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Predictive Performance Evaluation of an Eco-Friendly Pavement Using Baosteel’s Slag Short Flow (BSSF) Steel Slag — Iuri Sidney Bessa, Livia Ingrid Oliveira Costa, et al. · Applied Mechanics (2025) | TGRS Research Map | TGRS