Experimental assessment and modeling of static creep behavior of modified asphalt mixture with crumb rubber using gyratory compactor and Marshall method

Lyacia Sadoudi; Mohammed Amin Benbouras; Ratiba  Mitiche-Kettab

doi:10.7764/RDLC.25.1.5

Authors

Lyacia Sadoudi Departement of Civil Engineering, University of Sciences and Techology Houari Boumediene, Algiers (Algeria)
Mohammed Amin Benbouras Departement of Civil Engineering, University of Sciences and Techology Houari Boumediene, Algiers (Algeria)
Ratiba Mitiche-Kettab Department of Civil Engineering, National Polytechnic School, Algiers (Algeria)

DOI:

https://doi.org/10.7764/RDLC.25.1.5

Abstract

Pavement surface deformations are related to design deficits, or problems of stability of the materials pavement. To have a sustainable material that ensures a long enough life for the pavement, several research have been developed. This work focuses on the effect of crumb rubber on the static creep behavior of asphalt mixtures, aiming to improve their mechanical performances and rutting resistance on the one hand, and to contribute to environmental sustainability on the other. Crumb rubber was incorporated into asphalt mixtures at varying percentages (0.25%, 0.5%, and 0.75%) using a dry process. Samples of asphalt mixture compacted with gyratory compactor and Marshall Method were tested at two temperature levels, (20°C and 60°). The modification of asphalt, temperature and mode of compaction are parameters that influence creep properties and rutting resistance. During the static creep test, total deformation (ε_Tot), initial deformation (ε_In), permanent deformation (ε_Per), creep stiffness and Creep compliance were recorded. Results showed that the presence of crumb rubber at low content in asphalt mixture improve their performances, while at high content of crumb rubber, a decrease in the performance of the asphalt mixtures was observed. Also, the properties of static creep recorded during the creep test are better for the specimens compacted with Gyratory compactor comparing with those compacted with Marshall Method. Aiming to predict creep stiffness and creep compliance as a function of crumb rubber content and Axial micro deformation, a model was developed using adaptive neuro-fuzzy inference system (ANFIS) approach. The results demonstrate that the developed ANFIS models provide accurate predictions with strong agreement with experimental results.

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References

Akpolat, M. (2022). Investigation of rutting, fatigue and cracking resistance parameters of CR modified warm asphalt binders compare with SBS modified binders. Revista de la Construcción, 21(2), 309–328. https://doi.org/10.7764/RDLC.21.2.309

Alioua, S., Arab, A., Benbouras, M. A., & Leghouchi, A. (2024). Modeling static liquefaction susceptibility of saturated clayey sand using advanced ma-chine-learning techniques. Transportation Infrastructure Geotechnology, 11(5), 2903-2931. https://doi.org/10.1007/s40515-024-00396-5

Al-Mistarehi, B. W., Obaidat, Y. T., Khedaywi, T. S., & Al-Smadi, A. T. (2022). Behavior of modified asphalt using polystyrene concrete in static creep: Experimental and numerical study. Iranian Journal of Science and Technology, Transactions of Civil Engineering, 46(3), 2359-2367. https://doi.org/10.1007/s40996-022-00866-1

Al-Omari, A. A., Khasawneh, M. A., Al-Rousan, T. M., & Al-Theeb, S. F. (2021). Static creep of modified superpave asphalt concrete mixtures using crumb tire rubber, microcrystalline synthetic wax, and nano-silica. International Journal of Pavement Engineering, 22(6), 794-805. https://doi.org/10.1080/10298436.2019.1646913

Amin, B. (2021). Predicting shear stress parameters in consolidated drained conditions using artificial intelligence methods. Basic and Applied Sciences - Scientific Journal of King Faisal University, 22(1), 1-7. https://doi.org/10.37575/b/sci/0069

Arabani, M., Tahami, S. A., & Hamedi, G. H. (2018). Performance evaluation of dry process crumb rubber-modified asphalt mixtures with nanomaterial. Road Materials and Pavement Design, 19(5), 1241-1258. https://doi.org/10.1080/14680629.2017.1302356

Bansal, S., Kumar Misra, A., & Bajpai, P. (2017). Evaluation of modified bituminous concrete mix developed using rubber and plastic waste materials. International Journal of Sustainable Built Environment, 6(2), 442-448. https://doi.org/10.1016/j.ijsbe.2017.07.009

Behroozikhah, A., Morafa, S. H., & Aflaki, S. (2017). Investigation of fatigue cracks on RAP mixtures containing Sasobit and crumb rubber based on fracture energy. Construction and Building Materials, 141, 526-532. https://doi.org/10.1016/j.conbuildmat.2017.03.011

Benbouras, M. A., & Lefilef, L. (2023). Progressive machine learning approaches for predicting the soil compaction parameters. Transportation Infrastruc-ture Geotechnology, 10(2), 211-238. https://doi.org/10.1007/s40515-021-00212-4

Benbouras, M. A., Sadoudi, L., & Leghouchi, A. (2025). Prediction of the resilient modulus of subgrade soil using machine-learning techniques. Transpor-tation Infrastructure Geotechnology, 16(1), 87-104.

Bioud, N. E.-I., Laid, I. O., & Benbouras, M. A. (2023). Estimating the fundamental period of infilled RC frame structures via deep learning. Asian Journal of Civil Engineering, 14(1), 59-73.

Brahma, A., Beneldjouzi, M., Hadid, M., & Benbouras, M. A. (2025). Prediction of inelastic displacement ratios in soil-structure interaction on very soft soils using neural architecture search-based ML hybrid technique. Asian Journal of Civil Engineering, 26(8), 3257-3278. https://doi.org/10.1007/s42107-025-01371-2

Chandra, S., & Choudhary, R. (2013). Performance characteristics of bituminous concrete with industrial wastes as filler. Journal of Materials in Civil Engineering, 25(11), 1666-1673. https://doi.org/10.1061/(ASCE)MT.1943-5533.0000730

Cheriet, F., Soudani, K., & Haddadi, S. (2015). Influence of natural rubber on creep behavior of bituminous concrete. Procedia - Social and Behavioral Sciences, 195, 2769-2776. https://doi.org/10.1016/j.sbspro.2015.06.391

Da Silva, L., Benta, A., & Picado-Santos, L. (2018). Asphalt rubber concrete fabricated by the dry process: Laboratory assessment of resistance against reflection cracking. Construction and Building Materials, 160, 539-550. https://doi.org/10.1016/j.conbuildmat.2017.11.081

Debiche, F., Benbouras, M. A., Petrisor, A.-I., Baba Ali, L. M., & Leghouchi, A. (2024). Advancing landslide susceptibility mapping in the Medea region using a hybrid metaheuristic ANFIS approach. Land, 13(6), 889. https://doi.org/10.3390/land13060889

Debiche, F., Mitiche-Kettab, R., Benbouras, M. A., Benbellil, B., Djerbal, L., & Petrisor, A. I. (2018). Use of GIS systems to analyze soil compressibility, swelling and bearing capacity under superficial foundations in Algiers region, Algeria. Urbanism. Arhitectura. Constructii, 9(4), 357-370.

Duarte, G. M., & Faxina, A. L. (2021). Asphalt concrete mixtures modified with polymeric waste by the wet and dry processes: A literature review. Con-struction and Building Materials, 312, 125408. https://doi.org/10.1016/j.conbuildmat.2021.125408

Faramarzi, M., Arabani, M., Haghi, A. K., & Mottaghitalab, V. (2015). Carbon nanotubes-modified asphalt binder: Preparation and characterization. International Journal of Pavement Research and Technology, 8(1), 29-36.

Fouchal, A., Tikhamarine, Y., Benbouras, M. A., Souag-Gamane, D., & Heddam, S. (2025). Biological oxygen demand prediction using artificial neural network and random forest models enhanced by the neural architecture search algorithm. Modeling Earth Systems and Environment, 11(1), 9. https://doi.org/10.1007/s40808-024-02178-x

Habal, A. H. Y., & Benbouras, M. A. (2025). California bearing ratio and compaction parameters prediction using advanced hybrid machine learning methods. Asian Journal of Civil Engineering, 26(1), 121-146. https://doi.org/10.1007/s42107-024-01179-6

Han, L., Zheng, M., Li, J., Li, Y., Zhu, Y., & Ma, Q. (2017). Effect of nano silica and pretreated rubber on the properties of terminal blend crumb rubber modified asphalt. Construction and Building Materials, 157, 277-291. https://doi.org/10.1016/j.conbuildmat.2017.08.187

Lakshman Singh, K., & Panda, D. (2019). Study on strength characteristics improvement of polyethylene modified bituminous concrete mixes. Key Engineering Materials, 803, 216-221. https://doi.org/10.4028/www.scientific.net/KEM.803.216

Modarres, A., & Hamedi, H. (2014). Effect of waste plastic bottles on the stiffness and fatigue properties of modified asphalt mixes. Materials & Design, 61, 8-15. https://doi.org/10.1016/j.matdes.2014.04.046

Oldham, D. J., Fini, E. H., & Chailleux, E. (2015). Application of a bio-binder as a rejuvenator for wet-processed asphalt shingles in pavement construc-tion. Construction and Building Materials, 86, 75-84. https://doi.org/10.1016/j.conbuildmat.2015.03.085

Poovaneshvaran, S., Zheng, L. W., Hasan, M. R. M., Yang, X., & Diab, A. (2021). Workability, compactibility, and engineering properties of rubber-modified asphalt mixtures prepared via wet process. International Journal of Pavement Research and Technology, 14(5), 560-569. https://doi.org/10.1007/s42947-020-1006-z

Rath, P., Majidifard, H., Jahangiri, B., Chen, S., & Buttlar, W. G. (2021). Laboratory and field evaluation of pre-treated dry-process rubber-modified asphalt binders and dense-graded mixtures. Transportation Research Record, 2675(10), 381-394.

Rodríguez-Fernández, I., Tarpoudi Baheri, F., Cavalli, M. C., Poulikakos, L. D., & Bueno, M. (2020). Microstructure analysis and mechanical performance of crumb rubber modified asphalt concrete using the dry process. Construction and Building Materials, 259, 119662. https://doi.org/10.1016/j.conbuildmat.2020.119662

Semahi, S., Benbouras, M. A., Zemmouri, N., & Attia, S. (2025). Adaptive Neuro-Fuzzy Inference System-based Prediction of Heating and Cooling Loads in Residential Buildings. Urbanism. Arhitectură. Construcţii, 16(2), 225-252.

Sadoudi, L., Mitiche-Kettab, R., & Bachir, D. S. (2019). Evaluation of the workability, Marshall parameters, and stiffness modulus of rubber modified bituminous concrete. International Journal of Sustainable Building Technology and Urban Development, 10(2), 43-55.

Sadoudi, L., Benbouras, M. A., Habal, A. H. Y., & Ouldkhaoua, Y. (2025a). Advanced hybrid AI models for predicting softening point and penetration of modified bitumen. Periodica Polytechnica Civil Engineering, 69(4), 1409-1426. https://doi.org/10.3311/PPci.24861

Sadoudi, L., Benbouras, M. A., & Mitiche-Kettab, R. (2025b). Modeling of creep compliance and creep modulus behavior in modified asphalt mixes using Artificial Neural Networks (ANN) and Adaptive Neuro-Fuzzy Inference Systems (ANFIS). Engineering Review, 45(3), 1-20. https://doi.org/10.30765/er.2480

Singh, H., Chopra, T., Jain, S., Kaur, A., & Kamotra, S. (2019). Effect of aggregate type and polymer modification on the performance of bituminous concrete mixes. International Journal of Applied Science and Engineering, 16(1), 1-13.

Subhy, A., Airey, G. D., & Presti, D. L. (2017). An investigation of the mechanical properties of rubber modified asphalt mixtures using a modified dry process. In Bearing Capacity of Roads, Railways and Airfields (pp. 343-348). CRC Press.

Taherkhani, H., & Afroozi, S. (2018). Investigating the creep properties of asphaltic concrete containing nano-silica. Sādhanā, 43(2), 24. https://doi.org/10.1007/s12046-018-0792-3

Tai Nguyen, H. T., & Nhan Tran, T. (2018). Effects of crumb rubber content and curing time on the properties of asphalt concrete and stone mastic as-phalt using dry process. International Journal of Pavement Research and Technology, 11(3), 236-244. https://doi.org/10.1016/j.ijprt.2017.09.014

Wahhab, H. I. A. A., Rafiq, W., & Khaliludin, M. (2024). Modeling and design optimization of dense graded modified crumb rubber asphalt mixtures using response surface methodology. Construction and Building Materials, 435, 136895. https://doi.org/10.1016/j.conbuildmat.2024.136895

Wulandari, P. S., & Tjandra, D. (2017). Use of crumb rubber as an additive in asphalt concrete mixture. Procedia Engineering, 171, 1384-1389. https://doi.org/10.1016/j.proeng.2017.01.451

Zachariah, J. P., Sarkar, P. P., & Pal, M. (2021). A study on the moisture damage and rutting resistance of polypropylene modified bituminous mixes with crushed brick aggregate wastes. Construction and Building Materials, 269, 121357. https://doi.org/10.1016/j.conbuildmat.2020.121357