Regression Modeling for the Formulation Optimization of a Stabilizing Additive for Stone Mastic Asphalt
https://doi.org/10.21122/2227-1031-2025-24-6-479-486
Abstract
This study addresses the urgent issue of improving the durability of Stone Mastic Asphalt pavements, where a key technological challenge is binder drainage at high manufacturing temperatures. Existing solutions based on costly imported stabilizing additives create significant economic barriers to their widespread use. The objective of this research was to develop and scientifically validate an optimal formulation for a cost-effective composite stabilizing additive based on locally available raw materials, including cellulose fiber from waste paper and polymer fiber from industrial waste. To solve this multifactorial optimization problem, the method of multiple regression analysis was employed. The experimental basis for the modeling was derived from laboratory tests on 16 additive formulations with varying component proportions. The independent variables (factors) included the percentages of synthetic fiber, cellulose, and a thermal stabilizer, as well as the final dosage of the additive in the asphalt mix. The dependent variables (responses) were key performance indicators such as binder drainage, tensile strength at 0 °C, and compressive strength at 50 °C. As a result of the study, three linear regression models describing the “composition-property” relationships were developed. The high predictive capability of the models was confirmed by statistical metrics; the coefficient of determination R2 for all equations exceeded 0.90, indicating a high degree of explained variance. Based on these models, an optimization problem with specified criteria and constraints was solved, allowing for the analytical determination of the optimal ranges for component content. Verification of the predictions against strong agreement showed a nearly perfect match between calculated and experimental data. A scientifically validated and patented final additive composition was developed, which ensures compliance with asphalt concrete standards and serves as a competitive alternative to existing analogues.
About the Authors
A. A. AfanasenkaBelarus
Address for correspondence:
Afanasenka Аliаksei А.
Belаrusian National Technical University
65, Nezavisimosty Ave.,
220013, Minsk,
Republic of Belarus
Tel.: +375 29 338-78-40
P. P. Yatsevich
Belarus
Minsk
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Review
For citations:
Afanasenka A.A., Yatsevich P.P. Regression Modeling for the Formulation Optimization of a Stabilizing Additive for Stone Mastic Asphalt. Science & Technique. 2025;24(6):479-486. https://doi.org/10.21122/2227-1031-2025-24-6-479-486
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