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All issues Volume 120 (2017) MATEC Web Conf., 120 (2017) 07003 References
Open Access
Issue
MATEC Web Conf.
Volume 120, 2017
International Conference on Advances in Sustainable Construction Materials & Civil Engineering Systems (ASCMCES-17)
Article Number 07003
Number of page(s) 11
Section Transportation and Pavement
DOI https://doi.org/10.1051/matecconf/201712007003
Published online 09 August 2017
  1. Kim, Y. R., Editor (2009): “Modeling of Asphalt Concrete”, ASCE Press, McGraw Hill. [Google Scholar]
  2. Witczak, M.W., (2005): “Use of the Dynamic Modulus (E*) Test as a Simple Performance Test for Asphalt Pavement Systems (AC Permanent Deformation Distress)”, Volume I of IV Preliminary Draft Final Report, NCHRP Project 9-19: Superpave Support and Performance Models Management, Arizona State University. [Google Scholar]
  3. Andrei, D., Witczak, M. W., and Mirza, M. W, (1999): “Development of A Revised Predictive Model for the Dynamic (Complex) Modulus of Asphalt Mixtures”, Inter Team Technical Rep. prepared for the NCHRP 1-37A Project, Dept. of Civil Engineering, Univ. of Maryland, College Park, MD. [Google Scholar]
  4. Bari, J., and Witczak, M. W., (2007): “New Predictive Models for the Viscosity and Complex Shear Modulus of Asphalt Binders for Use with the Mechanistic-Empirical Pavement Design Guide”, Transportation Research Record 2001, Transportation Research Board, Washington, D.C., 9–19. [Google Scholar]
  5. Khattab A. M., El-Badawy S. M., Al Hazmi A. A., Elmwafi M., (2014): “Evaluation of Witczak E* Predictive Models for the Implementation of AASHTOWare-Pavement ME Design in the Kingdom of Saudi Arabia”, Construction and Building Materials, V (64): pp. (360–9). [CrossRef] [Google Scholar]
  6. Christensen Jr., D. W., Pellinen, T. K., & Bonaquist, R. F., (2003): “Hirsch Model for Estimating the Modulus of Asphalt Concrete”, Asphalt Paving Technology, Lexington, KY: Journal of the Association of Asphalt Paving Technologists, pp. (97–121). [Google Scholar]
  7. Bari, J., and Witczak, M. W., (2006): “Development of A New Revised Version of the Witczak E* Predictive Models for Hot Mix Asphalt Mixtures”, J. Assoc. Asphalt Paving Technol., Vol. 75, pp. (381–417). [Google Scholar]
  8. Witczak M., El-Basyouny M., El-Badawy S., (2007): “Incorporation of the New (2005) E* Predictive Model in the MEPDG”, NCHRP 1-40D Final Report Addendum, Arizona State University, Tempe, Arizona. [Google Scholar]
  9. El-Badawy, S., Bayomy, F., and Awed, A., (2012): “Performance of MEPDG Dynamic Modulus Predictive Models for Asphalt Concrete Mixtures - Local Calibration for Idaho”, ASCE’s Journal of Materials in Civil Engineering, Volume 24, Issue 11:1412–1421. [CrossRef] [Google Scholar]
  10. Ceylan, H., Schwartz, C. W., Kim, S., and Gopalakrishnan, K.,(2009): “Accuracy of predictive Models for Dynamic Modulus of Hot-Mix Asphalt,” Journal of Materials in Civil Engineering, Vol. 21, No. 6, pp. 286–293. [CrossRef] [Google Scholar]
  11. Martinez, F. O., and Angelone, S. M., (2009) “Evaluation of Different Predictive Dynamic Modulus Models of Asphalt Mixtures Used in Argentina, Bearing Capacity of Roads, Railways, and Airfields”, Tutumluer & Al-Qadi (eds), Taylor & Francis Group, London. [Google Scholar]
  12. Bayomy, F., Abu Abdo, A., Weaver, T., Darveshi, P., Nielsen, R., Jung, S.J., and Baek, S., (2010): “Development and Evaluation of Performance Tests to Enhance Superpave Mix Design and its Implementation in Idaho. Phase A: Evaluation of Mix Resistance to Deformation,” Final Report-Part 1 of ITD project No. RP 181, USDOT Project No. DTOS59-06-G-00029, NIATT Report N09-10A, University of Idaho, pp. 160. [Google Scholar]
  13. El-Badawy, S., Awed, A., and Bayomy, F., (2011): “Evaluation of the MEPDG Dynamic Modulus Prediction Models for Asphalt Concrete Mixtures”, Proc., 1st Integrated Transportation and Development Institute Congress, I. Al-Qadi and S. Murrell, eds., ASCE, Reston, VA, pp. (576–585). [CrossRef] [EDP Sciences] [Google Scholar]
  14. Azari, H., Al-Khateeb, G., Shenoy, A., and Gibson, N. (2007). “Comparison of Simple Performance Test E* of Accelerated Loading Facility Mixtures and Prediction E* Use of NCHRP 1-37A and Witczak’s New Equations.” Transportation Research Record 1998, Transportation Research Board, Washington, D.C., 1–9. [Google Scholar]
  15. Yousefdoost, S., Vuong, B., Rickards, I., Armstrong, P., and Sullivan, B. (2013): “Evaluation of Dynamic Modulus Predictive Models for Typical Australian Asphalt Mixes”, Delivering New Age Solutions: 15th AAPA International Flexible Pavements Conference, 22-25 September, Royal International Conference Centre, Brisbane. [Google Scholar]
  16. Hou, H., Wang, T., Wu, S., Xue, Y., Tan, R., Chen, J., and Zhou, M., (2016): “Investigation on the Pavement Performance of Asphalt Mixture Based on Predicted Dynamic Modulus”, Construction and Building Materials; 106:11–17. [CrossRef] [Google Scholar]
  17. Kim, R., King, M., and Momen, M. (2005). “Typical Dynamic Moduli Values of Hot Mix Asphalt in North Carolina and their Prediction.” Transportation Research Board 84th Annual Meeting Compendium of Papers 05-2568 (CD-ROM), Washington, D.C. [Google Scholar]
  18. Obulareddy, S., (2006): “Fundamental Characterization of Louisiana HMA Mixtures for the 2002 Mechanistic-Empirical Design Guide”, Master Thesis, Louisiana State Univ., Baton Rouge, LA. [Google Scholar]
  19. Awed, A, (2010): “Material Characterization of HMA for MEPDG Implementation in Idaho”, Master’s Thesis, Univ. of Idaho, Moscow, ID. [Google Scholar]
  20. Sakhaeifar, M., Kim, R., and Kabir, P., (2015): “New Predictive Models for the Dynamic Modulus of Hot Mix Asphalt”, Construction and Building Materials; 76:221–231. [CrossRef] [Google Scholar]
  21. Georgouli, K., Loizos, A., and Plati, C. (2016): “Calibration of Dynamic Modulus Predictive Model”, Construction and Building Materials; 102:65–75. [CrossRef] [Google Scholar]
  22. Ministry of Transport (MOT) in the Kingdom of Saudi Arabia. Hot Asphalt Mix Design System Using Superpave System Detailed in Asphalt Institute SP-2 and The AASHTO 2005 Standards. SUPERPAVE Coding System in KSA, Version: 1/2006. [Google Scholar]
  23. AASHTO, (2006): “Standard Method of Test for Viscosity Determination of Asphalt Binder Using Rotational Viscometer”, AASHTO Designation: T48-97, Washington, D.C., USA. [Google Scholar]
  24. AASHTO, (2006): “Standard Method of Test Determining the Rheological Properties of Asphalt Binder Using a Dynamic Shear Rheometer (DSR)”, AASHTO Designation: T315-06, Washington, D.C., USA. [Google Scholar]
  25. AASHTO, (2011). Standard Method of Test for Determining Dynamic Modulus of Hot Mix Asphalt Concrete Mixtures, AASHTO Designation: TP 342-11, American Association of State Highway and Transportation Officials, Washington, D.C., USA. [Google Scholar]
  26. ARA, Inc., ERES Consultants Division (2004). Guide for Mechanistic-Empirical Design of New and Rehabilitated Pavement Structures, NCHRP 1-37A Final Report, Transportation Research Board, National Research Council, Washington, D.C. [Google Scholar]
  27. Garcia G, Thompson M. (2007). HMA Dynamic Modulus Predictive Models –A Review. Research Report FHWA-ICT-07-005, Urbana, IL. [Google Scholar]
  28. ASTM. (2009). “Standard Viscosity-Temperature Chart for Asphalts.” ASTM D2493/D2493M-09, West Conshohocken, PA. [Google Scholar]
  29. Ceylan H., Gopalakrishnan K., Kim S. (2008), Advanced Approaches to Hot-Mix Asphalt Dynamic Modulus Prediction. Canadian Journal of Civil Engineering. 35(7):699–707. [CrossRef] [Google Scholar]
  30. Pellinen TK. (2001), Investigation of the Use of Dynamic Modulus as an Indicator of Hot-Mix Asphalt Performance: PhD Dissertation, Arizona State University, Tempe, Arizona. [Google Scholar]

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