Development of a prior model to predict the cracking performance of asphalt mixture in general for asphalt material selection and mix design

References

• Abdo, A. M. A., et al., 2014. Semi-circular notched beam testing procedure for hot mixture asphalt. Proceedings of the Institution of Civil Engineers - Transport, 167 (1), 48–58.
   Web of Science ®Google Scholar
• Al-Qadi, I. L., et al., 2017. Impact of high recycled mixed on HMA overlay crack development rate. Road Materials and Pavement Design, 18, 311–327.
   Web of Science ®Google Scholar
• Anderson, R. M., et al., 2011. Evaluation of the relationship between asphalt binder properties and non-load related cracking. Journal of the Association of Asphalt Paving Technologists, 80, 649–662.
   Google Scholar
• Armaghani, D. J., et al., 2020. Hybrid ANN-based techniques in predicting cohesion of sandy-soil combined with fiber. The Geomechanics and Engineering, 20 (3), 191–205.
   Web of Science ®Google Scholar
• Bodin, D., et al., 2004. Continuum damage approach to asphalt concrete fatigue modeling. Journal of Engineering Mechanics, 130, 700–708.
   Web of Science ®Google Scholar
• Braham, A. F., Buttlar, W. G., and Marasteanu, M. O, 2007. Effect of binder type, aggregate, and mixture composition on fracture energy of hot-mix asphalt in cold climates. Transportation Research Record, 2001, 102–109.
   Google Scholar
• Christensen, D. W., and Bonaquist, R. F, 2005. Practical application of continuum damage theory to fatigue phenomena in asphalt concrete mixtures. Journal of Association of Asphalt Paving Technologist (AAPT), 74, 963–995.
   Google Scholar
• David, H. A., and Gunnink, J. L, 1997. The paired t test under artificial pairing. The American Statistician, 51, 9–12.
   Web of Science ®Google Scholar
• Ghanizadeh, A. R., et al., 2022. Developing predictive models of collapse settlement and coefficient of stress release of sandy-gravel soil via evolutionary polynomial regression. Applied Sciences, 12 (19), 9986.
   Google Scholar
• Huang, J., et al., 2022a. Investigating the effects of ensemble and weight optimization approaches on neural networks’ performance to estimate the dynamic modulus of asphalt concrete. Road Materials and Pavement Design, 24 (8), 1939–1959.
   Web of Science ®Google Scholar
• Huang, J., et al., 2022b. Development of a new stacking model to evaluate the strength parameters of concrete samples in laboratory. Iranian Journal of Science and Technology, Transactions of Civil Engineering, 46, 4355–4370.
   Web of Science ®Google Scholar
• Huang, J., et al., 2022c. The use of GA and PSO in evaluating the shear strength of steel fiber reinforced concrete beams. KSCE Journal of Civil Engineering, 26, 3918–3931.
   Web of Science ®Google Scholar
• Huang, J., and Xue, J, 2022. Optimization of SVR functions for flyrock evaluation in mine blasting operations. Environmental Earth Sciences, 81.
   Web of Science ®Google Scholar
• Kim, J., Roque, R., and Byron, T, 2009. Viscoelastic analysis of flexible pavements and its effects on top-down cracking. Journal of Materials in Civil Engineering, 21, 324–332.
   Web of Science ®Google Scholar
• Lane, D. M, 2003. Online statistics education: a multimedia course of study.
   Google Scholar
• Lee, H., et al., 2018. Development of quality standards for inclusion of high recycled asphalt pavement content in asphalt mixtures – phase II. Ames: Iowa Department of Transportation.
   Google Scholar
• Li, X.-j., et al., 2008. Effect of factors affecting fracture energy of asphalt concrete at low temperature. Road Materials and Pavement Design, 9, 397–416.
   Web of Science ®Google Scholar
• Martin, A. E., et al., 2019. Evaluating the effects of recycling agents on asphalt mixtures with high RAS and RAP binder ratios.
   Google Scholar
• Mensching, D. J., Rowe, G. M., and Sias Daniel, J, 2017. A mixture-based black space parameter for low-temperature performance of hot mix asphalt. Road Materials and Pavement Design, 18, 404–425.
   Web of Science ®Google Scholar
• Mirzaiyanrajeh, D., et al., 2022. Performance evaluation of pelletized solid polymer modified asphalt mixtures. Transportation Research Record, 2676, 67–81.
   Web of Science ®Google Scholar
• Momeni, E., et al., 2015. Prediction of uniaxial compressive strength of rock samples using hybrid particle swarm optimization-based artificial neural networks. Measurement, 60, 50–63.
   Web of Science ®Google Scholar
• Newcomb, D. E., et al., 2021. Test methods to quantify cracking resistance of asphalt binders and mixtures. Minnesota. Department of Transportation.
   Google Scholar
• Ozer, H. O., et al., 2016. Development of the fracture-based flexibility index for asphalt concrete cracking potential using modified semi-circle bending test parameters. Construction and Building Materials, 115, 390–401.
   Web of Science ®Google Scholar
• Parsajoo, M., et al., 2021. Tensile strength prediction of rock material using non-destructive tests: A comparative intelligent study. Transportation Geotechnics, 31, 100652.
   Web of Science ®Google Scholar
• Rahbar-Rastegar, R., Sias Daniel, J., and Reinke, G, 2017. Comparison of asphalt binder and mixture cracking parameters. Road Materials and Pavement Design, 18, 211–233.
   Web of Science ®Google Scholar
• Roque, R, et al., 2010. Top-down cracking of hot-mix asphalt layers: models for initiation and propagation. NCHRP 1-42A Report 162, Transportation Research Board, National Research Council, Washington, D.C.
   Google Scholar
• Sawilowsky, S. S, 2002. Fermat, Schubert, Einstein, and Behrens-Fisher: the probable difference between two means when σ_1^2≠σ_2^2. Journal of Modern Applied Statistical Methods, 1, 461–472.
   Google Scholar
• Shen, J., Huang, B., and Hachiya, Y, 2004. Validation of performance-based method for determining rejuvenator content in HMA. International Journal of Pavement Engineering, 5, 103–109.
   Google Scholar
• Tran, N. H., Taylor, A. J., and Willis, R., 2012. Effect of rejuvenator on performance properties of HMA mixtures with high RAP and RAS contents. NCAT Report No. 12-05, National Center for Asphalt Technology, Auburn, AL, 70 pp.
   Google Scholar
• Underwood, B. S., et al., 2006. Characterization and performance prediction of ALF mixtures using a viscoelastoplastic continuum damage model. Proceedings of the Technical Session of the Association-of-Asphalt-Paving-Technologists, Savannah, GA, F, 27-9.
   Google Scholar
• Yu, X., et al., 2022. Refined decomposition: a new separation method for RAP materials and its effect on aggregate properties. Construction and Building Materials.
   Google Scholar
• Zaumanis, M., and Valters, A, 2018. Comparison of two low-temperature cracking tests for use in performance-based asphalt mixture design. International Journal of Pavement Engineering, 21, 1461–1469.
   Web of Science ®Google Scholar
• Zhang, R., et al., 2019a. Impact of aging on the viscoelastic properties and cracking behavior of asphalt mixtures. Transportation Research Record, 2673, 406–415.
   Web of Science ®Google Scholar
• Zhang, R., et al., 2021b. Evaluation of the correlations between laboratory measured material properties with field cracking performance for asphalt pavement. Construction and Building Materials, 301, 124126.
   Web of Science ®Google Scholar
• Zhang, R., et al., 2023. Evaluation of the state of practice asphalt binder and mixture tests for assessing the compatibility of complex asphalt materials. Road Materials and Pavement Design.
   Web of Science ®Google Scholar
• Zhang, W., et al., 2019b. Effects of in-place volumetric properties on field rutting and cracking performance of asphalt pavement. Journal of Materials in Civil Engineering, 31 (8).
   Web of Science ®Google Scholar
• Zhang, R., Huang, J., and Zheng, W, 2022a. Evaluation of the significance of different mix design variables on asphalt mixtures’ cracking performance measured by laboratory performance tests. Construction and Building Materials, 350.
   Web of Science ®Google Scholar
• Zhang, R., Sias, J. E., and Dave, E. V, 2020. Development of new performance indices to evaluate the fatigue properties of asphalt binders with ageing. Road Materials and Pavement Design, 23, 377–396.
   Web of Science ®Google Scholar
• Zhang, R., Sias, J. E., and Dave, E. V, 2021a. Comparison and correlation of asphalt binder and mixture cracking parameters incorporating the aging effect. Construction and Building Materials, 301, 124075.
   Web of Science ®Google Scholar
• Zhang, R., Sias, J. E., and Dave, E. V, 2022b. Using mix design information for modelling of fundamental viscoelasticity of asphalt mixtures. Construction and Building Materials, 329.
   Web of Science ®Google Scholar
• Zhu, Y., et al., 2017. Comprehensive evaluation of low-temperature fracture indices for asphalt mixtures. Road Materials and Pavement Design, 18, 467–490.
   Web of Science ®Google Scholar