Modification of Dynamic Modulus Predictive Models for Asphalt ...

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Figure 72: b Calibration Coefficient for the 1999 Witczak Model ....................................... 115 Figure 73: g 1 Calibration Coefficient for the 1999 Witczak Model ..................................... 116 Figure 74: g 2 Calibration Coefficient for the 1999 Witczak Model ..................................... 116 Figure 75: δ Calibration Coefficient for the 2006 Witczak Model ....................................... 119 Figure 76: α Calibration Coefficient for the 2006 Witczak Model ....................................... 120 Figure 77: b Calibration Coefficient for the 2006 Witczak Model ....................................... 120 Figure 78: g 1 Calibration Coefficient for the 2006 Witczak Model ..................................... 121 Figure 79: g 2 Calibration Coefficient for the 2006 Witczak Model ..................................... 121 Figure 80: p 0 Calibration Coefficient for the Hirsch Model ................................................. 123 Figure 81: p 1 Calibration Coefficient for the Hirsch Model ................................................. 123 Figure 82: p 2 Calibration Coefficient for the Hirsch Model ................................................. 124 vii
ACKNOLEDGEMENTS I would like to express my gratitude to all those who helped me during the writing of this thesis. My deepest gratitude goes first and foremost to my advisor Dr. Chris Williams for his support, guidance, and leadership throughout the course of my graduate studies and this research. I gratefully acknowledge the help of Dr. Stephenson, who has offered me valuable suggestions in statistical analysis. I would also like to thank Dr. Schaefer for his assistance in my academic studies and being part of my advisory committee. I would additionally like to thank Debra Haugen and Andrew Cascione who provided valuable information to help me complete this research. Last but not least, I would like to thank my family for their continuous support and encouragement. I own much to my parents who provided great support and understanding even though they were in a difficult time. This thesis would not have been possible without their helps. viii
Page 1 and 2: Modification of Dynamic Modulus Pre
Page 3 and 4: CHAPTER 5: CONCLUSIONS AND RECOMMEN
Page 5 and 6: Table 36: Project Effect Calibratio
Page 7: Figure 38: G* Master Curve for Asph
Page 11 and 12: CHAPTER 1: INTRODUCTION BACKGROUND
Page 13 and 14: well-known procedures among them. T
Page 15 and 16: and Hirsch Models (Chapter 4), and
Page 17 and 18: Table 1. The percentages in Table 1
Page 19 and 20: The binder grading results showed b
Page 21 and 22: maximum stress, and maximum strain
Page 23 and 24: Gyratory Compactor (SGC) is used to
Page 25 and 26: Figure 3: Master Curve Construction
Page 27 and 28: The penetration viscosities were us
Page 29 and 30: V 1S V 2S Va ’ Vc Vv V m V 1P V 2
Page 31 and 32: Previous Evaluation of the Witczak
Page 33 and 34: Figure 6: Master Curve Comparison f
Page 35 and 36: Figure 9: Summary of Percent Error
Page 37 and 38: Figure 12: Measured Values vs. Pred
Page 39 and 40: Figure 15: Comparison of Values Usi
Page 41 and 42: Effects of Fibers on Asphalt Concre
Page 43 and 44: Project Mix Number Table 5: Experim
Page 45 and 46: 500' 500' 500' 500' 500' 500' 500'
Page 47 and 48: Iowa DOT Demonstration Project The
Page 49 and 50: Percent Passing, % Table 7: Iowa De
Page 51 and 52: Percent Passing, % 100.0 90.0 80.0
Page 53 and 54: Percent Passing, % Table 9: Indiana
Page 55 and 56: Figure 28: Universal Testing Machin
Page 57 and 58: shear stress to achieve a preset st
Page 59 and 60:
ORIGINAL MODEL EVALUATION A total n
Page 61 and 62:
Witczak 2006 Model Predicted Dynami
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Hirsch Model Predicted Dynamic Modu
Page 65 and 66:
Table 13: ANOVA Table for Hirsch Mo
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MN vs. MO Yes 0% vs. 4% Yes MN vs.
Page 69 and 70:
Table 16: Volumetric Properties of
Page 71 and 72:
| | where η = viscosity (Poise), |
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G*, Pa G*, Pa temperatures. As show
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Phase Angle 75 65 55 45 35 25 15 37
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(| | ) ( ( )) where | | = dynamic s
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calibration variable D IN, D IA , D
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Table 21: Regression Results of 0%-
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Modified Witczak Model Predicted Dy
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Modified Witczak Model Predicted Dy
Page 87 and 88:
Table 22: Regression Results of RAS
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decreasing with increasing RAS cont
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CP1 IN , CP1 IA , CP1 MN , CP1 MO =
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Equation 34. where P 1 c = modified
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MODIFIED MODEL EVALUATION The afore
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Dynamic modulus E*, psi Dynamic mod
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Page 101 and 102:
Model Predicted E*, psi Model Predi
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Page 105 and 106:
Page 107 and 108:
are larger than the variability of
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Page 111 and 112:
Dynamic modulus E*, psi 10000000 10
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5%, and 6% RAS contents. The δ cal
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0.1 0.05 3% RAS 5% RAS 6% RAS 0 -0.
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Table 29: Coefficient Correlation C
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1.5 1 0.5 0 -0.5 -1 -1.5 6% RAS -2
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Table 31: 2006 Witczak Modification
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10000 8000 6000 4000 3% RAS 4% RAS
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dummy variables. A statistical anal
Page 129 and 130:
Table 32: Project Effect Calibratio
Page 131 and 132:
Table 36: Project Effect Calibratio
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REFERENCES [1] New Hampshire Depart
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[26] D. W. Christen and D. A. Ander
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Table 39: Dynamic Modulus Test Resu
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Page 141 and 142:
Page 143 and 144:
Page 145 and 146:
Page 147 and 148:
Page 149 and 150:
APPENDIX B: DSR TEST RESULTS Table
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APPENDIX C: DSR FREQUENCY SWEEP TES
Page 153 and 154:
Mix Temp. Freq. BC-21 BC-23 BC-24 B
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Mix Temp. Freq. BC-27 BC-28 BC-29 B
Page 157:
29 1.585 2773000 52.32 4360000 47.8
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