The National Academies Press

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From page 77... ... 77 Research Approach Overview To facilitate the integration of the PAM results into pavement performance prediction frameworks, the predicted changes in the binder AIPs (log \|G* \| at 64°C, 10 rad/s in this case) Read the entire page →
From page 78... ... 78 Long-Term Aging of Asphalt Mixtures for Performance Testing and Prediction: Phase III Results Binder Testing (Extraction & Recovery, DSR Testing) Material-Specific Kinetics Parameters Prediction of Age- and Depth-Dependent Cracking Properties Loose Mix Oven Aging at 95°C Mixture Performance Testing Dynamic Modulus Test (AASHTO TP 132) Read the entire page →
From page 79... ... Development of a Framework to Predict Changes in Asphalt Mixture Performance Due to Oxidative Aging 79 chemistry. This ARC mix was included in the experimental study to ensure that AMAC could be applied to binders with high-aging susceptibility. Read the entire page →
From page 80... ... 80 Long-Term Aging of Asphalt Mixtures for Performance Testing and Prediction: Phase III Results mixtures were used to estimate the mass required for the compaction mold. Compaction trials were carried out, and the small specimens were extracted to measure their air void contents. Read the entire page →
From page 81... ... Development of a Framework to Predict Changes in Asphalt Mixture Performance Due to Oxidative Aging 81 Asphalt Mixture Testing Dynamic Modulus Testing. Frequency sweep tests were conducted using an AMPT and small specimen geometry in accordance with AASHTO PP 99. Read the entire page →
From page 82... ... 82 Long-Term Aging of Asphalt Mixtures for Performance Testing and Prediction: Phase III Results The Hirsch model, as detailed in AASHTO TP 133-19, was used to find the maximum storage modulus value used in Equation (35) Read the entire page →
From page 83... ... Development of a Framework to Predict Changes in Asphalt Mixture Performance Due to Oxidative Aging 83 The cyclic fatigue test data were analyzed using simplified viscoelastic continuum damage (S-VECD) theory, as outlined in AASHTO TP 133-19. Read the entire page →
From page 84... ... 84 Long-Term Aging of Asphalt Mixtures for Performance Testing and Prediction: Phase III Results where α = damage evolution parameter, t = time, m = maximum value of the tangential slope of the relaxation modulus versus time plot, E∞ = long-time equilibrium modulus (kPa) , Eg = modulus of Prony term number g (kPa) Read the entire page →
From page 85... ... Development of a Framework to Predict Changes in Asphalt Mixture Performance Due to Oxidative Aging 85 C11, C12 = fitting parameters, and Nf = number of cycles to failure. In addition to the two engineering properties (C and S) Read the entire page →
From page 86... ... 86 Long-Term Aging of Asphalt Mixtures for Performance Testing and Prediction: Phase III Results for each discrete unit using the climatic conditions of Raleigh, North Carolina, as an example. Linear interpolation of the measured mixture properties was conducted to populate the information needed for the 17 calculated laboratory aging durations. Read the entire page →
From page 87... ... Development of a Framework to Predict Changes in Asphalt Mixture Performance Due to Oxidative Aging 87 FlexPAVE 1.1 uses two overlapping triangles to form a reference area within which the damage evolution can be considered. The top of the inverted triangle has a 170-cm-wide base that is located at the top of the surface layer and a vertex that is located at the bottom of the bottom asphalt layer. Read the entire page →
From page 88... ... 88 Long-Term Aging of Asphalt Mixtures for Performance Testing and Prediction: Phase III Results is shown in blue. The transition in color from blue to red shows the areas where damage is accumulated. Read the entire page →
From page 91... ... 0 5 10 15 20 25 30 35 40 45 50 1.0E-9 1.0E-6 1.0E-3 1.0E+0 1.0E+3 1.0E+6 Ph as e An gl e (° ) Reduced Frequency (Hz) Read the entire page →
From page 92... ... -4 -2 0 2 4 6 8 -20 0 20 40 60 Lo g( a T ) Temperature (°C) Read the entire page →
From page 93... ... Development of a Framework to Predict Changes in Asphalt Mixture Performance Due to Oxidative Aging 93 0.0E+00 5.0E+06 1.0E+07 1.5E+07 2.0E+07 2.5E+07 1.0E-10 1.0E-06 1.0E-02 1.0E+02 1.0E+06 E' (k Pa ) Reduced Frequency (Hz) Read the entire page →
From page 94... ... 94 Long-Term Aging of Asphalt Mixtures for Performance Testing and Prediction: Phase III Results Figure 61 shows an upward shift of the damage characteristic curves as the aging level increases for all mixtures. Generally, the damage characteristic curves of the stiff mixtures tend to be higher than those of the other mixtures; however, this outcome does not imply better or worse performance. Read the entire page →
From page 95... ... Development of a Framework to Predict Changes in Asphalt Mixture Performance Due to Oxidative Aging 95 0.0 0.2 0.4 0.6 0.8 1.0 0.0E+00 1.0E+05 2.0E+05 3.0E+05 C S STA 2D 4D 7D 17D RS9.5B 30% (b) Read the entire page →
From page 96... ... y = 0.5656x y = 0.5117x y = 0.5209x y = 0.3573x 0E+0 1E+4 2E+4 3E+4 0.0E+0 1.0E+4 2.0E+4 3.0E+4 4.0E+4 Cu m ul at iv e (1 -C ) Nf (Cycle) Read the entire page →
From page 97... ... Development of a Framework to Predict Changes in Asphalt Mixture Performance Due to Oxidative Aging 97 is presented herein that can be used to predict the mixture long-term aging properties, assuming that the mixture short-term aging properties are known, whether measured or assumed. For this work, the mixture short-term aging properties were measured. Read the entire page →
From page 98... ... 98 Long-Term Aging of Asphalt Mixtures for Performance Testing and Prediction: Phase III Results A common form of the tTS factor function is shown in Equation (44) Read the entire page →
From page 99... ... Development of a Framework to Predict Changes in Asphalt Mixture Performance Due to Oxidative Aging 99 that separate functional forms must be used to characterize the tTS and tAS factors. The functional forms for both shift factors and a method to calibrate both shift factors are presented. Read the entire page →
From page 100... ... 100 Long-Term Aging of Asphalt Mixtures for Performance Testing and Prediction: Phase III Results viscosity yields Equation (47) Read the entire page →
From page 101... ... Development of a Framework to Predict Changes in Asphalt Mixture Performance Due to Oxidative Aging 101 Equations (47) Read the entire page →
From page 102... ... 102 Long-Term Aging of Asphalt Mixtures for Performance Testing and Prediction: Phase III Results Equation (47) can be modified to include only the tTS factor, as shown in Equation (50) Read the entire page →
From page 103... ... Development of a Framework to Predict Changes in Asphalt Mixture Performance Due to Oxidative Aging 103 where aA = tAS factor, c = fitting parameter, \|G* \|LTA, Tref, 10rad/s = dynamic shear modulus at a certain long-term aging condition and at the reference temperature and 10 rad/s, and \|G* Read the entire page →
From page 104... ... 104 Long-Term Aging of Asphalt Mixtures for Performance Testing and Prediction: Phase III Results at each long-term aging condition and were used to construct individual master curves for each aging level. An algorithm was then developed to determine the optimized tAS factors by systematically shiing the long-term aging storage modulus (E′) Read the entire page →
From page 105... ... Development of a Framework to Predict Changes in Asphalt Mixture Performance Due to Oxidative Aging 105 (optimized shift factors obtained using the algorithm) and the fitted line on the smooth master curve shift was studied. Read the entire page →
From page 106... ... 106 Long-Term Aging of Asphalt Mixtures for Performance Testing and Prediction: Phase III Results both tAS and tTS are included because, as the previous analysis shows, slight deviations can translate into large discrepancies in the continuity of the individual isotherms. Nevertheless, this correlation may be accurate enough to calculate the c variable for the tAS factor and thus eliminate the need for dynamic modulus testing of long-term aged mixtures. Read the entire page →
From page 107... ... Development of a Framework to Predict Changes in Asphalt Mixture Performance Due to Oxidative Aging 107 aging data to calculate the tTS factors, provide good storage modulus predictions with aging. Another functional form for fitting short-term aging storage modulus data can be considered in future work to mitigate the issue observed in the storage modulus extrapolation at high, reduced frequencies. Read the entire page →
From page 108... ... 108 Long-Term Aging of Asphalt Mixtures for Performance Testing and Prediction: Phase III Results data shown in Figure 69 (e) and Figure 69 (f ) Read the entire page →
From page 109... ... Development of a Framework to Predict Changes in Asphalt Mixture Performance Due to Oxidative Aging 109 align at C values between 0.4 and 0.6. The obtained optimized shift factors along with the difference in log \|G* Read the entire page →
From page 110... ... 110 Long-Term Aging of Asphalt Mixtures for Performance Testing and Prediction: Phase III Results Obtaining n directly for a given mixture requires cyclic fatigue testing at multiple age levels, which is not practical. Thus, several attempts were made to estimate the parameter n for the shift factor equation. Read the entire page →
From page 111... ... Development of a Framework to Predict Changes in Asphalt Mixture Performance Due to Oxidative Aging 111 The change in the failure criterion DR can also be predicted as a function of aging level, which in this analysis is based on changes in log \|G* \| due to aging. Read the entire page →
From page 113... ... Development of a Framework to Predict Changes in Asphalt Mixture Performance Due to Oxidative Aging 113 obtained from this optimization is considered universal and can be applied to all the other mixtures (i.e., excluding ACTRL and LTX) Read the entire page →
From page 114... ... 114 Long-Term Aging of Asphalt Mixtures for Performance Testing and Prediction: Phase III Results 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 D R log \|G* Read the entire page →
From page 115... ... Figure 75. Damage evolution with time: (a) Read the entire page →
From page 116... ... 116 Long-Term Aging of Asphalt Mixtures for Performance Testing and Prediction: Phase III Results "Total damage" refers to the damage calculated using the entire reference cross-sectional area of the pavement; "top damage" refers to the damage calculated using the top part of the total reference area; and "bottom damage" refers to the damage calculated using the bottom part of the total reference area, as defined by Kim et al. Read the entire page →
From page 117... ... Development of a Framework to Predict Changes in Asphalt Mixture Performance Due to Oxidative Aging 117 stiffness. Aging increases the stiffness (i.e., increases the induced stress) Read the entire page →
From page 118... ... 118 Long-Term Aging of Asphalt Mixtures for Performance Testing and Prediction: Phase III Results high RAP-containing mixtures, polymer-modified mixtures, and mixtures with low PG binder. Level 1 provides greater accuracy of the \|E* Read the entire page →
From page 119... ... Development of a Framework to Predict Changes in Asphalt Mixture Performance Due to Oxidative Aging 119 Figure 76. Flow chart summarizing inputs required for PAM and AMAC. Read the entire page →

From page 77...

... 77 Research Approach Overview To facilitate the integration of the PAM results into pavement performance prediction frameworks, the predicted changes in the binder AIPs (log |G* | at 64°C, 10 rad/s in this case)