Comparison of dynamic elastisty modulus with different prediction approaches for Karaman – Konya highway pavement

Year 2021, , 2102 - , 15.07.2021

Kemal Armağan , Mehmet Saltan , Serdal Terzi , Nevzat Kıraç

https://doi.org/10.53635/jit.849544

Abstract

In pavement design and analysis processes among mechanistic-empirical pavement design method, defining the Dynamic Elasticity Modulus(E*) of asphalt layers are very important. In analysis processes, predicting the deteriorations and E* requires some special devices and a lot of time. To simplify this process different prediction models and different approaches have been developed to predict E*. These prediction approaches prepared with huge amount of input data gathered both from construction site and laboratory tests to predict the binder and the volumetric properties of the HMA. In this paper four prediction equations have been applied to predict E* and compared the results with each other. The infrastructure model has chosen as an existing highway section with known HMA material properties. The analyses have done for five different temperatures (10⁰F, 40⁰F, 70⁰F, 100⁰F and 130⁰F) by using two different frequency values (4Hz and 10 Hz). The aim of this research study is doing a comparative assessment of four widely used E* prediction models. Results have shown a large bias between compared E*prediction results due to temperature, frequency, and material properties. Higher Frequency and newest models have shown higher E* values.

Keywords

Pavement, dynamic elasticity modulus, mechanistic empirical design

References

• Audu, H. A. P., Oghorodje, E. E., & Oviri, D. E. (2016). Sensitivity Analysis On Flexible Road Pavement Life Cycle Cost Model. Nigerian Journal of Technology, 35(2), 278-289. https://doi.org/10.4314/njt.v35i2.7
• Scheving, A. G. (2011), Life Cycle Cost Analysis of Asphalt and Concrete Pavements, Master of Science, School of Science and Engineering, Reykjavík University, Iceland.
• AASHTO. 1972. Interim Guide for the Design of Pavement Structures. American Association of State Highway and Transportation Officials.
• AASHTO. 1986. Guide for the Design of Pavement Structures. American Association of State Highway and Transportation Officials.
• AASHTO. 1993. Guide for the Design of Pavement Structures. American Association of State Highway and Transportation Officials.
• Guclu, A., Ceylan, H., Gopalakrishnan, K., & Kim, S. (2009). Sensitivity analysis of rigid pavement systems using the mechanistic-empirical design guide software. Journal of Transportation Engineering, 135(8), 555-562. https://doi.org/10.1061/(ASCE)TE.1943-5436.0000036
• Shahji, S. (2006). Sensitivity Analysis of AASHTO's 2002 Flexible and rigid pavement design methods.
• Liu, P., Wang, D., & Oeser, M. (2015). Application of semi-analytical finite element method coupled with infinite element for analysis of asphalt pavement structural response. Journal of Traffic and Transportation Engineering (English Edition), 2(1), 48-58. https://doi.org/10.1016/j.jtte.2015.01.005
• Liu, P., Wang, D., & Oeser, M. (2017). Application of semi-analytical finite element method to analyze asphalt pavement response under heavy traffic loads. Journal of traffic and transportation engineering (English edition), 4(2), 206-214. https://doi.org/10.1016/j.jtte.2017.03.003
• Guide for Mechanistic-Empirical Design of New and Rehabilitated Pavement Structures (NCHRP 1-37A), 2004. Li, X. Y., Zhang, R., Zhao, X., & Wang, H. N. (2014). Sensitivity analysis of flexible pavement parameters by mechanistic-empirical design guide. In Applied Mechanics and Materials, 590, 539-545. https://doi.org/10.4028/www.scientific.net/AMM.590.539
• 2002 Mechanistic-Empirical Pavement Design Guide (MEPDG), Federal Highway Administration, USA.
• Kannekanti, V., & Harvey, J. (2006). Sensitivity analysis of 2002 design guide rigid pavement distress prediction models.
• Nam Tran, P. E., Robbins, M. M., & Rodezno, C. (2017). Pavement ME Design–Impact of Local Calibration, Foundation Support, and Design and Reliability Thresholds.
• Zhang, C., Wang, H., You, Z., & Ma, B. (2015). Sensitivity analysis of longitudinal cracking on asphalt pavement using MEPDG in permafrost region. Journal of Traffic and Transportation Engineering (English Edition), 2(1), 40-47. https://doi.org/10.1016/j.jtte.2015.01.004
• Wu, Z., Yang, X., & Sun, X. (2017). Application of Monte Carlo filtering method in regional sensitivity analysis of AASHTOWare Pavement ME design. Journal of traffic and transportation engineering (English edition), 4(2), 185-197. https://doi.org/10.1016/j.jtte.2017.03.006
• Ali, Y., Irfan, M., Ahmed, S., Khanzada, S., & Mahmood, T. (2015). Sensitivity analysis of dynamic response and fatigue behaviour of various asphalt concrete mixtures. Fatigue & Fracture of Engineering Materials & Structures, 38(10), 1181-1193. https://doi.org/10.1111/ffe.12297
• Shu, X., & Huang, B. (2009). Predicting dynamic modulus of asphalt mixtures with differential method. Road materials and pavement design, 10(2), 337-359. https://doi.org/10.1080/14680629.2009.9690198
• Shu, X., & Huang, B. (2008). Dynamic modulus prediction of HMA mixtures based on the viscoelastic micromechanical model. Journal of Materials in Civil Engineering, 20(8), 530-538. https://doi.org/10.1061/(ASCE)0899-1561(2008)20:8(530)
• Final Document Appendix CC-1, (2001), Correlation of CBR Values with Soil Index Properties, Guide for Mechanistic Empirical Design of New and Rehabilitated Pavement Structures, NCHRP 1-37A.
• Marasteanu, M. O., Clyne, T. R., Li, X., & Skok, E. L. (2003). Dynamic and Resilient Modulus of Mn/DOT Asphalt Mixtures.
• Hou, H., Wang, T., Wu, S., Xue, Y., Tan, R., Chen, J., & Zhou, M. (2016). Investigation on the pavement performance of asphalt mixture based on predicted dynamic modulus. Construction and Building Materials, 106, 11-17. https://doi.org/10.1016/j.conbuildmat.2015.10.178
• Plati, C., Georgouli, K., & Loizos, A. (2013). Asphalt concrete stiffness modulus estimation utilizing an algorithm approach. In Airfield and Highway Pavement 2013: Sustainable and Efficient Pavements 1219-1228.
• M-E Pavement Design Manual, (2015), Colorado Department of Transportation.
• Georgouli, K., Plati, C., & Loizos, A. (2016). Assessment of dynamic modulus prediction models in fatigue cracking estimation. Materials and Structures, 49(12), 5007-5019. https://doi.org/10.1617/s11527-016-0840-6