DESIGN AND MODELING

Mathematical model of the process of compaction of asphalt concrete mixtures by rollers with metal rollers

Authors

  • Timur R. Mulekaev Specialist expert, Moscow, Russia

How to cite

GOST Mulekaev T. R. Mathematical model of the process of compaction of asphalt concrete mixtures by rollers with metal rollers // STROITEL'NYE I DOROZHNYE MASHINY. 2024. Vol. 68. No. 11-12. P. 45-57.
APA Mulekaev, T. R. (2024). Mathematical model of the process of compaction of asphalt concrete mixtures by rollers with metal rollers. STROITEL'NYE I DOROZHNYE MASHINY, 68(11-12), 45-57.

Abstract

The process of compaction of asphalt concrete mixtures is a complex multifactorial interaction between the working bodies of the rollers and the coating material, which determines the qualitative characteristics of the roadway and its operational properties. Modern approaches to modeling this process are characterized by insufficient integration of energy principles with the mechanics of interaction of metal rollers and asphalt concrete mixture, which determines the urgency of developing a comprehensive mathematical model. As part of the research, a nonlinear dynamic model of the compaction process was developed, taking into account the viscoelastic properties of the asphalt concrete mixture, vibration compaction parameters and the energy characteristics of the roller-material interaction. The model is based on the principles of continuum mechanics and oscillation theory using harmonic balance methods for a multistep system. Experimental verification of the model was carried out on the basis of field density measurements and laboratory tests of asphalt concrete samples using a gyratory compactor. The results showed that the proposed model provides a prediction of the degree of compaction with a coefficient of determination $R2=0.92-0.96$ for various modes of operation of the rollers. It was found that the optimal vibration frequency exceeds the natural frequency of the system by 15- 22%, and the energy absorption efficiency reaches a maximum with an oscillation amplitude of 0,6-0,8 mm for type II mixtures. The practical significance of the model lies in the possibility of optimizing the sealing parameters at the design stage of the technological process, which makes it possible to improve the quality of the road surface and reduce energy consumption by 12-18%. The developed mathematical apparatus can be integrated into intelligent compaction systems to ensure automatic control of the asphalt concrete pavement construction process.

Keywords

mathematical modeling asphalt concrete coating vibration sealing metal rollers energy approach dynamic system

Funding

The authors did not declare any external funding for this research.

References

Ahmad K.N., Chen X., Khan A. Optimizing asphalt compaction: Vibratory roller amplitude and predictive modeling // Construction and building materials. 2025. Vol. 463. Art. 132878.

Ahmed M.U., Tarefder R.A. Asphalt pavement density measurement using non-destructive testing methods: current practices, challenges, and future vision // Construction and building materials. 2022. Vol. 344. Art. 128141.

Azari H., Liu H., Shams S. Innovative density profiling of asphalt pavement // Public Roads. 2024. Vol. 87. № 5. pp. 12-18.

Commuri S., Zaman M., Barman M. Quality control of subgrade soil using intelligent compaction // Innovative infrastructure solutions. 2016. Vol. 1. Art. 20.

Imran S.A. Modeling and analysis of the interaction between roller drum and pavement material during compaction: dis.... PhD. Norman: University of Oklahoma, 2018. 185 р.

Kassem E., Scullion A., Lytton R. Development of compaction monitoring system for asphalt pavements // Construction and building materials. 2015. Vol. 96. pp. 334-345.

Liu D., Wang X., Chen F. Modeling of asphalt mixture-screed interaction: a nonlinear dynamic vibration model for improving paving density // Construction and building materials. 2022. Vol. 311. Art. 125003.

Liu Y., Chen X., Wang Z. Vibratory compaction response based on the contact model of roller- subgrade system // Construction and building materials. 2022. Vol. 365. Art. 130021.

Man T. Mathematical modeling of pavement gyratory compaction: a perspective on granular- fluid assemblies // Mathematics. 2023. Vol. 11. № 9. Art. 2096.

Praticò F.G., Perri G. The prediction of the compaction curves and energy of bituminous mixtures // Infrastructures. 2024. Vol. 10. № 6. Art. 132.

Validating a density-profiling system for asphalt compaction assessment: interim report. Washington: FHWA, 2024. 156 p.

Yu S., Shen S., Lu M. Data sensing and compaction condition modeling for asphalt pavements // Automation in construction. 2023. Vol. 154. Art. 105021.

Yu S., Wang J., Zhang L. Recent development in intelligent compaction for asphalt pavement construction: leveraging smart sensors and machine learning // Sensors. 2024. Vol. 24. № 9. Art. 2777.

Zhan Y., Zhang Y., Nie Z. Intelligent paving and compaction technologies for asphalt pavement // Automation in construction. 2023. Vol. 156. Art. 105081.

Zhao Y., Xie S., Gao Y., Zhang Y., Zhang K. Prediction of the number of roller passes and degree of compaction of asphalt layer based on compaction energy // Construction and building materials. 2021. Vol. 277. Art. 122274.

Published

2025-10-22

Issue

Section

DESIGN AND MODELING

Metrics

427 views
0 downloads
Want to publish with us?
Submit an article

Similar Articles

1 2 3 4 5 6 > >> 

You may also start an advanced similarity search for this article.