Modelling of expansion ratio and half-life of foamed bitumen using gene expression programming

References

• Ali, A.W., et al., 2012. Laboratory evaluation of foamed warm mix asphalt. International Journal of Pavement Research and Technology, 5 (2), 93–101.
   Google Scholar
• Ali, A., et al., 2013. Workability evaluation of foamed warm-mix asphalt. Journal of Materials in Civil Engineering, 26 (6), 04014011. doi: 10.1061/(ASCE)MT.1943-5533.0000904
   Web of Science ®Google Scholar
• Alkroosh, I. and Nikraz, H, 2011. Correlation of pile axial capacity and CPT data using gene expression programming. Geotechnical and Geological Engineering, 29 (5), 725–748. doi: 10.1007/s10706-011-9413-1
   Google Scholar
• Barinov, E.N, 1990. Formation and properties of bituminous foams. Chemistry and Technology of Fuels and Oils, 26 (10), 544–548. doi: 10.1007/BF01129435
   Web of Science ®Google Scholar
• Bieder, A., et al., 2012. Foaming of bitumen – a key process for different low temperature asphalts. In: Eurasphalt & eurobitume congress Istanbul, P5EE-500.
   Google Scholar
• Bowering, R.H., 1970. Properties and behaviour of foamed bitumen mixtures for road building. In: Proceedings of the 5th Australian road research board conference, Canberra, Australia. ARRB, 38–57.
   Google Scholar
• Bowering, R.H. and Martin, C.L, 1976. Foamed bitumen production and application of mixtures evaluation and performance of pavements. Journal of Association of Asphalt Paving Technologists, 45, 453–477.
   Google Scholar
• Chomicz-Kowalska, A., 2015. Statistical methods for evaluating associations between selected foamed bitumen parameters. In: Proceedings of the 6th international conference on bituminous mixtures and pavements–ICONFBMP, 10–12 June 2015, Thessaloniki, Greece, 3–12.
   Google Scholar
• Fang, X., Garcia-Hernandez, A., and Lura, P, 2016. Overview on cold cement bitumen emulsion asphalt. RILEM Technical Letters, 1, 116–121. doi: 10.21809/rilemtechlett.2016.23
   Google Scholar
• Ferreira, C, 2001. Gene expression programming: a new adaptive algorithm for solving problems. Complex Systems, 13 (2), 87–129.
   Google Scholar
• Gandomi, A. H., et al., 2011. Nonlinear genetic-based models for prediction of flow number of asphalt mixtures. Journal of Materials in Civil Engineering, 23 (3), 248–263. doi: 10.1061/(ASCE)MT.1943-5533.0000154
   Web of Science ®Google Scholar
• Güllü, H, 2017. A novel approach to prediction of rheological characteristics of jet grout cement mixtures via genetic expression programming. Neural Computing and Applications, 28 (1), 407–420. doi: 10.1007/s00521-016-2360-2
   Google Scholar
• Hailesilassie, B. W., et al., 2017. A closer scientific look at foam bitumen. Road Materials and Pavement Design, 18 (2), 362–375. doi: 10.1080/14680629.2016.1213513
   Web of Science ®Google Scholar
• Hailesilassie, B.W., Hugener, M., and Partl, M.N, 2015. Influence of foaming water content on foam asphalt mixtures. Construction and Building Materials, 85, 65–77. doi: 10.1016/j.conbuildmat.2015.03.071
   Web of Science ®Google Scholar
• Haiying, C., Zhiyong, H., and Lei, J, 2015. Response surface methodology of foamed bitumen expansion ratio. International Journal of Heat and Technology, 33 (3), 35–42. doi: 10.18280/ijht.330305
   Web of Science ®Google Scholar
• Hassan, M, 2010. Evaluation of the environmental and economic impacts of warm-mix asphalt using life-cycle assessment. International Journal of Construction Education and Research, 6 (3), 238–250. doi: 10.1080/15578771.2010.507619
   Google Scholar
• He, G.P. and Wong, W.G, 2006. Decay properties of the foamed bitumen. Construction and Building Materials, 20 (10), 866–877. doi: 10.1016/j.conbuildmat.2005.06.027
   Web of Science ®Google Scholar
• Iwański, M. and Chomicz-Kowalska, A, 2013. Laboratory study on mechanical parameters of foamed bitumen mixtures in the cold recycling technology. Procedia Engineering, 57, 433–442. doi: 10.1016/j.proeng.2013.04.056
   Google Scholar
• Iwański, M., Chomicz-Kowalska, A., and Maciejewski, K, 2015. Application of synthetic wax for improvement of foamed bitumen parameters. Construction and Building Materials, 83, 62–69. doi: 10.1016/j.conbuildmat.2015.02.060
   Web of Science ®Google Scholar
• Jenkins, K.J., et al., 2000. Developments in the uses of foamed bitumen in road pavements. HERON, 45 (3), 167–176.
   Google Scholar
• Jenkins, K.J, 2002. Mix design considerations for cold and half-warm bituminous mixes with emphasis on foamed bitumen. PhD Thesis. University of Stellenbosch, South Africa.
   Google Scholar
• Jenkins, K.J., Van de Ven, M.F.C., and De Groot, J.L.A., 1999. Characterization of foamed bitumen. In: 7th conference on asphalt pavements for Southern Africa, Victoria Falls, Zimbabwe, 1–18.
   Google Scholar
• Lesueur, D., et al., 2004. Foamability and foam stability. Road Materials and Pavement Design, 5 (3), 277–302. doi: 10.1080/14680629.2004.9689973
   Google Scholar
• Liu, J., et al., 2017. Prediction models of mixtures’ dynamic modulus using gene expression programming. International Journal of Pavement Engineering, 18 (11), 971–980. doi: 10.1080/10298436.2016.1138113
   Web of Science ®Google Scholar
• Liu, J., Yan, K., and Liu, J, 2018. Rheological properties of warm mix asphalt binders and warm mix asphalt binders containing polyphosphoric acid. International Journal of Pavement Research and Technology, 11 (5), 481–487. doi: 10.1016/j.ijprt.2018.03.005
   Google Scholar
• Lundberg, R., et al., 2016. Production and durability of cold Mix asphalt. In: 6th Eurasphalt & Eurobitume congress Prague. doi:10.14311/EE.2016.074.
   Google Scholar
• Mollahasani, A., Alavi, A.H., and Gandomi, A.H, 2011. Empirical modeling of plate load test moduli of soil via gene expression programming. Computers and Geotechnics, 38 (2), 281–286. doi: 10.1016/j.compgeo.2010.11.008
   Web of Science ®Google Scholar
• Mousavi, S.M., et al., 2012. A new predictive model for compressive strength of HPC using gene expression programming. Advances in Engineering Software, 45 (1), 105–114. doi: 10.1016/j.advengsoft.2011.09.014
   Web of Science ®Google Scholar
• Namutebi, M., Birgisson, B., and Bagampadde, U, 2011. Foaming effects on binder chemistry and aggregate coatability using foamed bitumen. Road Materials and Pavement Design, 12 (4), 821–847. doi: 10.1080/14680629.2011.9713896
   Web of Science ®Google Scholar
• Newcomb, D.E., et al., 2015. Properties of foamed asphalt for warm mix asphalt applications. NCHRP Report-807, Project 09-53.
   Google Scholar
• Nivedya, M.K., et al., 2013. Rheological investigations on foamed bitumen. In: Airfield and highway pavement: sustainable and efficient pavements, 9–12 June 2013, Los Angeles, California, United States, 967–976.
   Google Scholar
• Ozcan, F., 2012. Gene expression programming based formulations for splitting tensile strength of concrete. Construction and Building Materials, 26 (1), 404–410. doi: 10.1016/j.conbuildmat.2011.06.039
   Web of Science ®Google Scholar
• Ozturk, H.I. and Kutay, M.E, 2013. Novel testing procedure for assessment of quality of foamed warm mix asphalt binders. Journal of Materials in Civil Engineering, 26 (8), 04014042. doi: 10.1061/(ASCE)MT.1943-5533.0000924
   Web of Science ®Google Scholar
• Ramanujam, J.M. and Jones, J.D, 2007. Characterization of foamed-bitumen stabilisation. International Journal of Pavement Engineering, 8 (2), 111–122. doi: 10.1080/10298430601149676
   Google Scholar
• Redelius, P., Östlund, J.A., and Soenen, H, 2016. Field experience of cold mix asphalt during 15 years. Road Materials and Pavement Design, 17 (1), 223–242. doi: 10.1080/14680629.2015.1068702
   Web of Science ®Google Scholar
• Ruckel, P.J., Acott, S.M., and Bowering, R.H, 1983. Foamed-asphalt paving mixtures: preparation of design mixes and treatment of test specimens. Transportation Research Record, 911, 88–95.
   Google Scholar
• Saleh, M, 2006. Effect of aggregate gradation, mineral fillers, bitumen grade, and source on mechanical properties of foamed bitumen-stabilized mixes. Transportation Research Record: Journal of the Transportation Research Board, 1952, 90–100. doi: 10.1177/0361198106195200110
   Web of Science ®Google Scholar
• Saltan, M. and Terzi, S, 2005. Comparative analysis of using artificial neural networks (ANN) and gene expression programming (GEP) in backcalculation of pavement layer thickness. Indian Journal of Engineering and Materials Sciences, 12, 42–50.
   Web of Science ®Google Scholar
• Sunarjono, S, 2008. The influence of foamed bitumen characteristics on cold-mix asphalt properties. PhD Thesis. University of Nottingham.
   Google Scholar
• Taskiran, T, 2010. Prediction of California bearing ratio (CBR) of fine grained soils by AI methods. Advances in Engineering Software, 41 (6), 886–892. doi: 10.1016/j.advengsoft.2010.01.003
   Web of Science ®Google Scholar
• Terzi, S, 2005. Modeling the deflection basin of flexible highway pavements by gene expression programming. Journal of Applied Sciences, 5 (2), 309–314. doi: 10.3923/jas.2005.309.314
   Google Scholar
• Terzi, S., et al., 2013. Modeling Marshall stability of steel fiber reinforced asphalt concrete by genetic expression programming. In: 2nd international Balkans conference on challenges of civil engineering. Tirana: Epoka University, 1030–1039.
   Google Scholar
• Thom, N, 2014. Principles of pavement engineering (2nd ed.). London: Thomas Telford.
   Google Scholar
• Tutu, K.A. and Tuffour, Y.A, 2016. Warm-mix asphalt and pavement sustainability: a review. Open Journal of Civil Engineering, 6 (2), 84. doi: 10.4236/ojce.2016.62008
   Google Scholar
• Vaitkus, A., Vorobjovas, V., and Ziliut, L, 2009. The research on the use of warm mix asphalt for asphalt pavement structures. In: XXVII international Baltic road conference, Riga, Latvia, 24–26.
   Google Scholar
• Wang, A., Cheng, H., and Wang, J, 2009. Research on foamed asphalt technology and equipment. In: Energy and environment technology, 2009. ICEET'09, 1, Guilin, China, 287–291.
   Google Scholar
• White, G., 2014. Foamed bitumen stabilisation for Australian airports. In: Airfield Engineering and Maintenance Summit, Singapore, 25–28.
   Google Scholar
• Wirtgen, 2012. Wirtgen cold recycling technology (1st ed). Windhagen: Wirtgen GmbH.
   Google Scholar
• Yan, K.Z., Xu, H.B., and Shen, G.H, 2014. Novel approach to resilient modulus using routine subgrade soil properties. International Journal of Geomechanics, 14 (6), 04014025. doi: 10.1061/(ASCE)GM.1943-5622.0000369
   Web of Science ®Google Scholar
• Yan, K. and You, L., 2014. Investigation of complex modulus of asphalt mastic by artificial neural networks. International Journal of Engineering & Materials Sciences, 21 (4), 445–450.
   Google Scholar
• You, L., et al., 2018a. Laboratory testing of rheological behavior of water-foamed bitumen. Journal of Materials in Civil Engineering, 30 (8), 04018153. doi: 10.1061/(ASCE)MT.1943-5533.0002362
   Web of Science ®Google Scholar
• You, L., et al., 2018b. Characteristics of water-foamed asphalt mixture under multiple freeze-thaw cycles: laboratory evaluation. Journal of Materials in Civil Engineering, 30 (11), 04018270. doi: 10.1061/(ASCE)MT.1943-5533.0002474
   Web of Science ®Google Scholar
• Yuo, Z., Goh, S.W., and Dai, Q., 2011. Laboratory evaluation of warm mix asphalt. Michigan Technological University , No. RC-1556.
   Google Scholar