Modification of Dynamic Modulus Predictive Models for Asphalt ...

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Figure 14: Measured Values vs. Predicted Values of Dynamic Modulus on log-log Scale (Mix/Laydown condition) [31] The results indicate the Witczak model well simulates the trend of dynamic modulus values. The best fitting lines parallelly deviate from the lines of equality. By applying a multiplier or shift factor for each method, the Witczak model showed high accuracy on predicting dynamic modulus values for Florida mixtures. It should be noticed that using DSR test results to estimate a binder’s viscosity results in lower predicted dynamic modulus values. Argentina Study [32] Materials studied in this research contain both lab produced mixtures and field cores. Field cores were taken from 17 sections around Rosario in the Littoral region of Argentina containing 42 types of mixtures. Eight laboratory mixtures were designed and compacted to sample cylinders using Marshall Procedures. Lab data were used to evaluate the 2000 Witczak model, the Hirsch clarify model, and the Heukelomp and Klomp equation developed in 1964. Figure 15 through Figure 18 show the dynamic modulus values predicted by the Witczak and Hirsch models versus laboratory results on log-log scale for lab produced mixtures and field mixes, respectively. 37
Figure 15: Comparison of Values Using the Witczak Predictive Equation [32] Figure 16: Comparison of Values Using the Hirsch Model [32] 38
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 and 8: Figure 38: G* Master Curve for Asph
Page 9 and 10: ACKNOLEDGEMENTS I would like to exp
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: Figure 12: Measured Values vs. Pred
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
Page 63 and 64: Hirsch Model Predicted Dynamic Modu
Page 65 and 66: Table 13: ANOVA Table for Hirsch Mo
Page 67 and 68: 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), |
Page 73 and 74: G*, Pa G*, Pa temperatures. As show
Page 75 and 76: Phase Angle 75 65 55 45 35 25 15 37
Page 77 and 78: (| | ) ( ( )) where | | = dynamic s
Page 79 and 80: calibration variable D IN, D IA , D
Page 81 and 82: Table 21: Regression Results of 0%-
Page 83 and 84: Modified Witczak Model Predicted Dy
Page 85 and 86: Modified Witczak Model Predicted Dy
Page 87 and 88: Table 22: Regression Results of RAS
Page 89 and 90:
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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Model Predicted E*, psi Model Predi
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Page 105 and 106:
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are larger than the variability of
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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
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Table 32: Project Effect Calibratio
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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 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
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Mix Temp. Freq. BC-21 BC-23 BC-24 B
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Mix Temp. Freq. BC-27 BC-28 BC-29 B
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29 1.585 2773000 52.32 4360000 47.8
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