Fouad Bayomy SJ Jung Richard Nielsen Thomas Weaver

1. Development and Evaluation of Performance Tests to Enhance Superpave Mix Design and its Implementation in Idaho DTOS59-06-G-00029 (NIATT Project No. KLK479) ITD Project No. RP 481 (NIATT Project No. KLK483) Fouad Bayomy SJ Jung Richard Nielsen Thomas Weaver

2. Fouad Bayomy (PI), Dynamic properties, and overall project phases SJ Jung, Fracture and Fatigue studies Richard Nielsen, Reliability Studies Thomas Weaver, Constitutive Modeling Graduate Students Ahmad Abu Abdo Baek, Seung Il ITD Coordinator (s) Mike Santi (Main Contact) Ned Parrish (Research Mgr) Others?? To be identified….. USDOT Ashley Bittner / Ed Weiner, COTR Paul Ziman (FHWA, Boise Office) Others… External Testing / Consulting Idaho Asphalt Supply, Inc. Image analysis (Masad at TTI) X-Ray Tomography (WSU or UT, Austin) NIATT and CE Support Judy LaLonde Don Parks Others Team

3. Why this project? • ITD Moves towards Superpave Mix Design System • Implementation of M-E Design guide at the national level

4. Project Objectives • Evaluate E* for Mixes that are commonly used in Idaho. • Determine E* vs. Temp for various binders used in Idaho, especially for polymer modified asphalts. • Develop constitutive models and develop procedure to estimate E* from given mix design properties. • Study of Gyratory Stability (GS) in relation to E*. • Develop and evaluate mix fracture indicators for ITD mixes. • Incorporate reliability analysis.

5. Funding • US DOT $ 280 k • ITD $ 150 k • UI Match (in kind) $ 154k Total $ 584 k

6. Scope of Work • Phase A (Deformation study) • Phase B (Fatigue and Fracture Study) • Phase C (Implementation and Training) • Phase D (Reporting)

7. Phase A: Mix Resistance to Deformation (E* and GS/CEI) Tasks • Literature Review • Analytical Analysis • Agg and Binders Evaluation • Preparation and Evaluation of HMA Mixtures • Data Analysis • Phase A Reports

8. Phase B: Mix Resistance to Fracture and fatigue Cracking Tasks • Literature Review • Analytical Analysis • Fracture Test Development • Preparation and Evaluation of HMA Mixtures • Data Analysis • Phase B Reports

9. Phases C and D: Implementation, Training & Reports Tasks • Work with ITD to Implement the Products • Develop a training workshop to disseminate the products • Final Report / Peer Review

10. Project Progressas of Dec. 31, 2007

11. Progress

12. Progress

13. Phase A – Deformation Studies

14. Literature Review Phase A – Task 1 A. Abu Abdo

15. Phase A: Task 1 Literature Review

16. Numerical and Analytical Predictive Models Voigt (1889) Reuss (1929) Hirsch (1962) Counto (1964) Hashin (1964)

17. Finite Element Modeling Discrete Element Modeling

18. Empirical Predictive Models • Asphalt Institute Method (Shook and Kallas (1969)) → only for 4 cps. • Refined Witczak Equation (Miller et al. (1983)) → Bigger range of data. • Witczak and Fonesca Model (1996) – MEPDG level 3 → Modified and Aged Binders and wider range of Temp. • Christensen et al. (2003) Model → G*. • Modified Witczak Model (2006) → G* and 𝛿.

19. Factors Affecting the Dynamic Modulus of Asphalt Mixes • Binder • Aggregates • Air voids (Interaction?)

20. Asphalt Binder Properties • Viscoity (RV) • Asphalt Binder Shear Modulus (G*). Measured by the Dynamic Shear Rheometer.

21. Aggregates Properties • Shape Characteristics • Angularity. • Texture. • Form/Sphericity. Measured by AIMS.

22. Aggregates Properties • Orientation (Δ). Measured by: • X-Ray tomography. • Image Analysis. (Isotropy?)

23. Why Aggregate Orientation (Δ)? Anisotropic (After Masad 2002) Isotropic

24. Aggregates Properties • Structure. Measured by the Gyratory Stability (GS). Ndesign Gyratory Stability, GS =  SN.de NG1

25. Model Development Methodology • Quantify the properties of Aggregates using Image Analysis. • Incorporate these properties in a model to predict HMA Dynamic Modulus (E*).

26. Use of E* for Rutting Prediction • Utilize the actual/predicted E* to evaluate permanent deformation in HMA, E* E” =E*.sinΦ Φ E’ =E*.cosΦ

27. Constitutive Models • Use FEA or DEM Simulation to validate our approach with actual test data.

28. Analytical Analysis – Task A2Finite Element Analysis – Task B2 T. Weaver

29. Purpose of Numerical Modeling • Predict E* given aggregate and binder properties • Predict pavement performance and assess influence of multiple variables (loads, environment) on behavior • Comparative assessment of mix designs

30. Numerical Methods • Discrete Element

31. Numerical Methods • Finite Elements

32. Constitutive Models Hooke’s Law

33. Constitutive Models • Viscoelasticity • Viscoplasticity

34. Constitutive Models • Viscoelastoplastic

35. Analyses using Viscoplasticity

36. Analyses with Viscoelastoplastic Model

37. Finite Element Analyses

38. Finite Element Analyses

39. Experimental ProgramPhase A – Tasks 3, 4 and 5 F. Bayomy

40. Mix Matrix • 4 Aggregates Structures (Fine Mix, SP3, SP4 and Coarse Mix). • 8 Binders; PG 70-34, PG 70-28, PG 70-22, PG 64-34, PG 64-28, PG 64-22, PG 58-34 and PG 58-28. • 7 Field Mixes.

42. Aggregate Gradation

43. Test Setups SGC Coring Machine LVDT Fixture SPT

44. Test Setups DSR APA Image Analysis AIMS

45. Tests • Binder G*, and Master Curves - Completed • Gyratory Stability (GS) - Completed • E*, and Flow Number (Fn) (In progress) • APA • Image Analysis

47. Field Mixes In addition to MnROAD Mixes

48. E* Testing is in progress

49. Data Analysis – Task A5

50. Binder Viscosity Results