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Long-Term Aging of Asphalt Mixtures for Performance Testing and Prediction: Phase III Results (2021)

Chapter: Chapter 2 - Previous Research Conducted Under the Original NCHRP Project 09-54

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Suggested Citation:"Chapter 2 - Previous Research Conducted Under the Original NCHRP Project 09-54." National Academies of Sciences, Engineering, and Medicine. 2021. Long-Term Aging of Asphalt Mixtures for Performance Testing and Prediction: Phase III Results. Washington, DC: The National Academies Press. doi: 10.17226/26133.
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Suggested Citation:"Chapter 2 - Previous Research Conducted Under the Original NCHRP Project 09-54." National Academies of Sciences, Engineering, and Medicine. 2021. Long-Term Aging of Asphalt Mixtures for Performance Testing and Prediction: Phase III Results. Washington, DC: The National Academies Press. doi: 10.17226/26133.
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Suggested Citation:"Chapter 2 - Previous Research Conducted Under the Original NCHRP Project 09-54." National Academies of Sciences, Engineering, and Medicine. 2021. Long-Term Aging of Asphalt Mixtures for Performance Testing and Prediction: Phase III Results. Washington, DC: The National Academies Press. doi: 10.17226/26133.
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Suggested Citation:"Chapter 2 - Previous Research Conducted Under the Original NCHRP Project 09-54." National Academies of Sciences, Engineering, and Medicine. 2021. Long-Term Aging of Asphalt Mixtures for Performance Testing and Prediction: Phase III Results. Washington, DC: The National Academies Press. doi: 10.17226/26133.
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Suggested Citation:"Chapter 2 - Previous Research Conducted Under the Original NCHRP Project 09-54." National Academies of Sciences, Engineering, and Medicine. 2021. Long-Term Aging of Asphalt Mixtures for Performance Testing and Prediction: Phase III Results. Washington, DC: The National Academies Press. doi: 10.17226/26133.
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Suggested Citation:"Chapter 2 - Previous Research Conducted Under the Original NCHRP Project 09-54." National Academies of Sciences, Engineering, and Medicine. 2021. Long-Term Aging of Asphalt Mixtures for Performance Testing and Prediction: Phase III Results. Washington, DC: The National Academies Press. doi: 10.17226/26133.
×
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Suggested Citation:"Chapter 2 - Previous Research Conducted Under the Original NCHRP Project 09-54." National Academies of Sciences, Engineering, and Medicine. 2021. Long-Term Aging of Asphalt Mixtures for Performance Testing and Prediction: Phase III Results. Washington, DC: The National Academies Press. doi: 10.17226/26133.
×
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Suggested Citation:"Chapter 2 - Previous Research Conducted Under the Original NCHRP Project 09-54." National Academies of Sciences, Engineering, and Medicine. 2021. Long-Term Aging of Asphalt Mixtures for Performance Testing and Prediction: Phase III Results. Washington, DC: The National Academies Press. doi: 10.17226/26133.
×
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Suggested Citation:"Chapter 2 - Previous Research Conducted Under the Original NCHRP Project 09-54." National Academies of Sciences, Engineering, and Medicine. 2021. Long-Term Aging of Asphalt Mixtures for Performance Testing and Prediction: Phase III Results. Washington, DC: The National Academies Press. doi: 10.17226/26133.
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5   Selection of Aging Index Properties The development of the laboratory aging procedure and PAM that was undertaken during the original NCHRP Project 09-54 hinged on the comparison of key aging index properties (AIPs) of laboratory-aged binders and binders extracted and recovered from field cores. There- fore, when developing the long-term aging procedure and associated kinetics model, candidate chemical and rheological AIPs were evaluated in order to select AIPs to track the oxidation levels of a wide range of field- and laboratory-aged materials. The chemical AIPs evaluated included the carbonyl infrared (IR) absorbance area, carbonyl plus sulfoxide (C+S) IR absorbance area, and C+S IR absorbance peaks that were determined using attenuated total reflectance Fourier- transform infrared (ATR-FTIR) spectroscopy. These chemical AIPs were evaluated based on their correlation to the laboratory aging duration. The rheological AIPs evaluated included the dynamic shear modulus, zero shear viscosity, Glover-Rowe parameter, and crossover modulus. These rheological AIPs were evaluated based on the strength of their relationship to the chemical changes that were induced by oxidation. To evaluate the changes in the chemical and rheologi- cal AIPs in terms of oxidation, laboratory loose mixture aging was conducted at multiple tem- peratures ranging from 70°C to 95°C with durations ranging from 8 days to 35 days. Samples were collected at different time intervals for binder extraction and recovery and subsequent AIP testing. The inclusion of sulfoxide in addition to carbonyl was found to affect material rankings and improve the correlation between the chemical AIPs and laboratory aging duration. The relation- ship between the C+S peaks and aging duration demonstrated the overall highest coefficient of determination (R2) values. Furthermore, the C+S peaks could be calculated using the direct outputs of the ATR-FTIR spectrometry data, whereas the calculation of the C+S area required numerical integration under the IR spectrum. Therefore, the C+S peaks AIPs were selected as the most promising chemical AIP. The correlation between the rheological AIPs and the C+S peak for each mixture was used to evaluate the rheological AIPs. Data that corresponded to different aging temperatures ranging from 70°C to 95°C were included in the evaluation. Past studies have demonstrated that the relation- ship between chemistry and rheology is not affected by the aging temperature if the temperature is below 100°C (Petersen 2009; Elwardany et al. 2017; Yousefi Rad et al. 2017). Therefore, the data for multiple aging temperatures were included for each evaluated mixture. The log |G*| at 64°C and 10 radians per second (rad/s) were selected as the rheological AIP to evaluate oxidation levels within the project. Oxidative age hardening was found to affect the dynamic shear modulus (|G*|) most significantly at high temperatures and/or low frequen- cies. Therefore, the AIPs that were evaluated at low, reduced frequencies were found to be the most effective. The log |G*| at 64°C and 10 rad/s constitutes the simplest and most efficient and C H A P T E R 2 Previous Research Conducted Under the Original NCHRP Project 09-54

6 Long-Term Aging of Asphalt Mixtures for Performance Testing and Prediction: Phase III Results effective rheological AIP evaluated, as the other rheological indices required fitting master curve and time-temperature shift (tTS) factor models to the rheological data coupled with subjective interpolation and extrapolation. Selection of the Long-Term Aging Method An experimental program was executed to select the long-term aging method. To select the laboratory aging procedure, the following factors were evaluated: state of the material during aging (compacted specimen versus loose mix), pressure level (oven aging versus pressurized aging), and aging temperature (95°C versus 135°C). The integrity of the specimens following aging, the quantified rate of oxidation of the extracted binder, versatility, ability to mimic field oxidation reactions, and the cost of the various procedures were compared in order to select the most promising aging procedure. The analysis was conducted using HMA mixtures. How- ever, a complementary analysis of the long-term aging of WMA mixtures also was conducted. To assess the aging level that was achieved during the aging trials, comparisons were made among the binders extracted and recovered from long-term laboratory-aged mixtures, binders aged using the standard RTFO and PAV, and binders extracted and recovered from field cores acquired from in-service pavements. Ultimately, loose mixture aging in an oven at 95°C was the recommended laboratory aging procedure for both the HMA and WMA mixtures. Loose mixture aging yielded uniform aging and reduced the aging time significantly compared to compacted specimen aging. In addition, the long-term aged loose mixtures could be compacted with no adjustment to the compac- tion temperature. The aging of large (100-mm-diameter) compacted specimens with wire mesh support in an oven at 85°C led to the development of an aging gradient within the specimens. This lack of uniform properties throughout the compacted specimens was of concern for per- formance testing and was observed directly in uniaxial cyclic fatigue tests to be caused by a high rate of end-failure at the end locations where oxidation was most significant. The application of pressure in compacted specimen aging was found to expedite aging. However, oxidation gradients were observed in the pressure-aged specimens, and the application and/or release of pressure can damage specimens. The application of pressure also was found to expedite the oxidation of the loose mixes. However, a standard binder PAV has inadequate capacity to age the loose mixture quantities that are required for the preparation of performance test specimens. The development of a larger pressurized system for loose mixture aging was deemed impractical. A comparison between binders extracted and recovered from loose mixtures aged at 135°C and 95°C demonstrated that long-term oven aging at 135°C led to changes in the chemistry of the binder that did not occur at temperatures at or below 95°C, and thus, oven aging at 135°C does not adequately reflect field aging. The chemical changes that occur when loose mixtures are aged at 135°C can lead to significantly different cracking performance results compared to the material testing and pavement simulations for aging at 95°C. Climate-Based Determination of Predefined Aging Durations Loose mixture aging at 95°C was performed using component materials for a prolonged duration in an oven. A subset of the mixtures was subjected to loose mixture aging at 70°C and 85°C. Samples were removed periodically from the oven and subjected to extraction and recovery, after which the binder AIPs were measured and used to develop and verify the rigor- ous rheology-based oxidation kinetics model given in Equations (1) through (3). This kinetics model was adapted from the model proposed earlier by Glaser et al. (2013) with log |G*| as the

Previous Research Conducted Under the Original NCHRP Project 09-54 7   AIP rather than C+S absorbance peaks. A rheological AIP was selected for the kinetics model because rheology is related more directly to performance than chemical AIPs. ( )= + −       − +      −G G M k k k tkinetics c f k t c flog * log * 1 1 e (1)0 exp (2)k A E RTf f af= −    exp (3)k A E RTc c ac= −    where |G*|kinetics = long-term aged binder shear modulus at 64°C and 10 rad/s [kilopascal (kPa)], |G*|0 = short-term aged binder shear modulus at 64°C and 10 rad/s (kPa), kf = rate of fast reaction, kc = rate of constant reaction, Af = fast reaction frequency factor, Ac = constant reaction frequency factor, Eaf = fast reaction activation energy, Eac = constant reaction activation energy, R = universal gas constant (or ideal gas constant) [kilojoule per mole kelvin (kJ/mol K)], T = temperature (K), t = reaction time (days), and M = fitting parameter that represents the amount of reactive material involved in the fast reaction. Initially, an experimental study was designed to verify that loose mixture oven aging leads to a kinetics-controlled reaction mechanism, which is a requirement for applying kinetics models without considering diffusion. Then, the relationship between laboratory aging duration and log |G*| at 64°C and 10 rad/s was derived from loose mixture aging conducted at 95°C and was used to determine the parameter M in Equation (1) for all the study mixtures. In addition, the universal values of the reaction parameters included in kf and kc were obtained from the least mean square error optimization of Equation (1) to match the values of log |G*| at 64°C and 10 rad/s obtained from test binders that were extracted and recovered after various durations of laboratory aging at 95°C, 85°C, and 70°C using five calibration mixtures. Table 1 presents the results. Five additional mixtures were used to validate that the kf and kc parameters are mixture-independent. The kinetics model was validated using non-isothermal aging trials of two mixtures. In addi- tion, binders were extracted and recovered at various depths from a select group of field cores obtained from in-service pavements. The AIPs of the field-aged binders were measured and compared to the laboratory-aged oxidation rates to determine the laboratory aging durations that matched the target field AIPs for specific projects. The project-specific aging durations were used to calibrate a climatic aging index (CAI) that can determine the laboratory aging duration that best matches field aging at any location of interest and depth of interest using Enhanced Integrated Climate Model (EICM) hourly pave- ment temperature data determined from NASA’s Modern-Era Retrospective analysis for Research Applicants, Version 2 (MERRA-2) hourly climatic data. The CAI, given in Equation (4), was derived using a simplification of the rigorous oxidation kinetics model. The CAI is based on Parameter Value Af 1.25 x 103 Eaf 95.04 Ac 3.68 x 107 Eac 62.21 Note: Af = fast reaction frequency factor, Ac = constant reaction frequency factor, Eaf = fast reaction activation energy, and Eac = constant reaction activation energy. Table 1. Universal kinetics model parameters.

8 Long-Term Aging of Asphalt Mixtures for Performance Testing and Prediction: Phase III Results the following observations: first, the relationship between log |G*| and aging under isothermal conditions that reflect pavement temperatures is relatively linear; second, the values of kf and kc in Equations (2) and (3) at pavement temperatures make the quantity M k k k tc f f( )( )−      − −1 1 exp small compared to kcMt; and finally, depth-dependent calibration is needed to account for the reduction in the partial pressure of the oxygen that is available to the binder deeper within the pavement due to diffusion. ∑ ( )= = × × − = CAI exp 24 (4) 1 t D A E RToven a i i N where toven = required oven aging duration at 95°C to reflect field aging (days), CAI = climatic aging index, N = total number of hours, A and Ea = fitting parameters (days and kJ/mol, respectively), D = depth correction factor, R = universal gas constant (or ideal gas constant) (kJ/mol K), and Ti = pavement temperature obtained from the EICM at the depth of interest at the hour of interest, i, (K). Note that temperatures below 20°C are excluded from the CAI calculation because prolonged aging at temperatures below 20°C was found not to lead to a significant increase in log |G*| at 64°C and 10 rad/s with aging duration. The A and Ea parameters were first calibrated using the data that correspond to a pavement depth of 6 mm to provide a CAI value equivalent to the laboratory aging duration at 95°C that is required to match the pavement temperature history. Then, the D values were calibrated using data that correspond to depths of 20 mm and deeper. Table 2 presents the resultant coefficient values. Note that the depth correction factor (D) is affected not only by diffusion mechanisms but also by photo-oxidation effects at the pavement surface. Figure 2 demonstrates the relationship between the CAI values and measured laboratory aging durations. Thus, the CAI value was proposed as the laboratory aging duration at 95°C that is required to match a given pavement temperature history and depth. The data presented in Figure 2 that were used to calibrate the CAI parameters correspond to conventional mixtures (i.e., unmodified HMA mixtures without RAP). Thus, the effects of WMA, PMA, and RAP on the relationship between laboratory aging durations and field aging still needed to be investigated given the prevalence of these modern mixtures in current practice. The kinetics model given in Equation (1) could potentially be used as the basis for improving the predictions of changes in asphalt binder properties with oxidative aging within pavement performance prediction frameworks, including Pavement ME Design. To evaluate the ability of the kinetics model to predict the evolution of oxidative aging in pavements, Equation (1) was applied to predict the log |G*| at 64°C and 10 rad/s in the field using hourly pavement temperature Depth D A Ea Surface Layer (6 mm) 1.0000 1.40962 13.3121 20 mm Depth 0.4565 1.40962 13.3121 Deeper Layers (below 20 mm) 0.2967 1.40962 13.3121 Table 2. CAI fitting coefficients.

Previous Research Conducted Under the Original NCHRP Project 09-54 9   history data at different depths obtained from the EICM for eight projects located in various climatic regions within the United States. The log |G*|0 is obtained by short-term aging (STA) the loose mixture for 4 hours at 135°C in the oven, followed by extraction, recovery, and testing the binder. To obtain M, loose mixture STA and long-term aging (LTA) durations at 95°C in the oven are needed, followed by extraction, recovery, and testing the binder. M in Equation (1) is then optimized such that the predicted log |G*| values match the measured values. Any labo- ratory LTA duration can be considered to calibrate M as long as the duration provides log |G*| values that are well dispersed on the oxidation timescale. The aging duration should provide binder log |G*| values that belong to the constant region of the kinetics plot so that the oxidation kinetics obtained are meaningful and reproducible. Note that loose mixture oven aging is kinetics controlled, whereas field aging is affected by both kinetics and diffusion-controlled mechanisms. Thus, to link laboratory aging to field aging in a rigorous manner, the kinetics model would need to be coupled with a diffusion model. However, a suitable diffusion model is not yet available. In addition, ultraviolet (UV) aging is expected to contribute to oxidative aging near the pavement surface, which is not considered within the developed kinetics model that is calibrated using thermal oxidation laboratory aging. Therefore, the kinetics model was first calibrated against field core measurements of log |G*| at a depth of 20 mm, which represents a reasonable depth to evaluate the bulk behavior of surface layers and avoids the effect of UV oxidation at the pavement surface. The calibration was accomplished using Equation (5). The fitting parameters were determined by linear regression for the kinetics model predictions and field core measurements of log |G*| at 20 mm depth. = + ×log * 0.4867 0.615 log * (5)field kineticsG G Figure 3 presents the relationship between the kinetics model predictions of log |G*| at a depth of 20 mm and those measured from field cores. The results demonstrate a strong cor- relation between the measured and predicted values of log |G*| (R2 = 0.75). The kinetics model tends to overpredict field aging, which is expected due to diffusion, that is, the partial pressure of oxygen within the binder at a pavement depth of 20 mm will be less than the oxygen partial pressure at the surface of loose mixture from which the mixture-specific M and |G*|0 values were determined. Note that Equation (5) can be used to obtain accurate predictions of field aging at 20 mm depth. However, this calibrated kinetics model at 20 mm depth was found to underpredict aging near the pavement surface and overpredict aging at depths below 20 mm, which matches intu- ition in the absence of a diffusion model for depths below 20 mm and consideration of UV oxidation for the pavement near-surface. To account for the underprediction at depths near the surface, a depth-dependent calibration was carried out by Elwardany (2017). However, diffusion y = 1x R² = 0.7142 0 5 10 15 20 25 30 35 0 5 10 15 20 25 30 35 M ea su re d D ur at io n at 95 °C (D ay s) Climatic Aging Index, CAI Surface Layer (6 mm) 20 mm depth Deeper Layers (below 20 mm) Figure 2. CAI predictions.

10 Long-Term Aging of Asphalt Mixtures for Performance Testing and Prediction: Phase III Results was still not considered in the sense that the partial pressure of the oxygen that is available to the binder, which is influenced by the mixture’s morphological properties, varies with depth; this is not manifested in the kinetics model. Therefore, additional work was needed to finalize the PAM. This work involved investigating the mixture morphological properties (air void content and binder content) to develop a framework that would incorporate the effect of diffusion. In addition, the calibration and validation of the kinetics model did not account for mixtures other than HMA mixtures. Lastly, the predicted changes in the binder properties with oxidative aging must be related to the changes in the asphalt mixture properties to facilitate the integration of the PAM in pavement performance prediction frameworks. The mixture-specific parameter values used in the kinetics model and expressed in Equa- tion (1) were determined using loose mixture aging. Aging loose mixture in an oven allows the physicochemical effects of the filler on the asphalt binder oxidation rates to be captured, which is important when predicting field aging (Moraes and Bahia 2015; Wu et al. 2014; Petersen 2009; Little, Epps, and Sebaaly 2006; Recasens et  al. 2005; Huang et  al. 2002; Jones 1997; Petersen, Plancher, and Harnsberger 1987). However, determining the kinetics model param- eter values using loose mixture aging is cumbersome. The loose mixture must be prepared and conditioned in an oven at 95°C. The binder must be extracted and recovered at a minimum of three durations of laboratory conditioning. The extracted and recovered binder then must be subjected to dynamic shear rheometer (DSR) testing to determine the dynamic shear modulus (|G*|) value at 64°C and 10 rad/s as a function of laboratory aging time. Therefore, an alterna- tive means to calibrate the kinetics model using binder aging tests rather than mixture aging tests could facilitate the implementation. To this end, an experiment was conducted to relate the binder-derived aging rates to the corresponding loose mixture aging rates. The results of this effort led to two options for calibrating the kinetics model: 1. Loose mixture aging coupled with extraction and recovery (as already described). 2. USAT binder aging coupled with an empirical model to predict loose mixture aging based on filler content and type. The USAT uses thin binder film (0.3 mm thick) to induce a kinetics-controlled reaction (Farrar et al. 2014). Binder samples conditioned for different durations can be tested in a DSR to derive a kinetics model. Therefore, the USAT was selected for binder aging in this study. To best mimic loose mixture aging, USAT short-term aging was conducted in an oven at 135°C for 4 hours y = 0.615x + 0.4867 R² = 0.75 0 0.5 1 1.5 2 2.5 3 3.5 0 0.5 1 1.5 2 2.5 3 3.5 WT-Fine - Opt. %ac, Low %av WT-Fine - Opt. %ac, Medium %av WT-Fine - Opt. %ac, High %av WT-Coarse LTPP-WI LTPP-NM LTPP-SD LTPP-TX ALF-CTRL ALF-SBS lo g G * m ea su re d (k Pa ) log G*kinetics(kPa) Note: WT = WesTrack; LTPP = Long-Term Pavement Performance (WI = Wisconsin, NM = New Mexico, SD = South Dakota, TX = Texas); ALF = Accelerated Loading Facility; CTRL = Control; SBS = Styrene-Butadiene-Styrene; ac = asphalt content; av = air void content Figure 3. Relationship between the kinetics model predictions of log |G*| at a depth of 20 mm and those measured from field cores.

Previous Research Conducted Under the Original NCHRP Project 09-54 11   followed by long-term aging in the same oven at 95°C. The evolution of log |G*| at 64°C for the USAT-aged binder was compared to that of binder extracted and recovered from equivalent loose mixture aging and was used to establish an empirical model to relate USAT binder aging to loose mixture aging. Seven mixtures were used to calibrate the empirical model and three mixtures were used for validation. Equations (6) through (14) comprise the empirical model that was developed to relate the binder and loose mixture aging rates. Separate model parameter values are included for the mix- tures with and without hydrated lime. The model also considers the amount of filler that is present in the mixture using the mass percentage of aggregate that passes the No. 200 sieve, as presented in Equation (7). Figure 4 summarizes the developed empirical model. ( ) ( ) ( ) ( ) ( ) = + + ≤ + + + − + >    log * , 8 8 8 8 , 8 (6) 2 2G a D b D c D a b c d D e D ( ) ( )= − −    3.51 0.32 , hydrated lime 1.61 0.1 , other fillers (7)200 200 S P P {= 0.34, hydrated lime0.5, other fillers (8)I = (9)a al u = − (10)b b Fl u ( ) ( )( ) = + × + × − × +8 8 8 8 (11) 2 F c b a d el u l l l = − (12)c c Il u = (13)d d Sl u = − (14)e e Il u where D = aging duration (days), a, b, c, d, e = dual mechanism mode parameters obtained from either loose mixture or USAT aging, al, bl, cl, dl, el = loose mix dual mechanism model parameters, au, bu, cu, du, eu = USAT dual mechanism model parameters, S = slope correction factor to account for filler effects, I = intercept correction factor to account for filler effects, F = correction factor between fast and slow (constant) rates of reaction mecha- nism, and P200 = percentage passing No. 200 sieve. Figure 5 presents comparisons between the measured and USAT-predicted loose mixture aging rates for the independent validation mixtures. Note that two of the validation mixtures contain hydrated lime (SHRP AAD and AAG), whereas the third mixture does not (NC S9.5B). Generally, the prediction accuracy is good, thereby validating the use of the empirical equation

12 Long-Term Aging of Asphalt Mixtures for Performance Testing and Prediction: Phase III Results Aging Duration (Days) Aging Duration (Days)Aging Duration (Days) lo g |G *| at 6 4° C , 10 ra d/ s (k Pa ) lo g |G *| at 6 4° C , 10 ra d/ s (k Pa ) lo g |G *| at 6 4° C , 10 ra d/ s (k Pa ) Figure 5. Validation of predictive model: (a) SHRP AAD, (b) SHRP AAG, and (c) NC S9.5B mixtures. Fast Rate Slow (constant) Rate = d(D)+e Hydrated Lime? Yes No Figure 4. Summary of developed empirical model to relate binder and loose mix aging rates.

Previous Research Conducted Under the Original NCHRP Project 09-54 13   to obtain the evolution of log |G*| for the loose mix using USAT binder results. These results suggest that the calibrated mixture-specific parameters of the kinetics model can be determined by USAT binder aging, thereby negating the need for loose mixture aging and corresponding extraction and recovery. However, USAT aging is still more cumbersome than the standard RTFO and PAV binder aging and has not been standardized at the time of writing this report. Thus, it would be advantageous if a surrogate means to obtain loose mixture kinetics informa- tion from standard binder aging methods could be established. The previous research conducted under the original NCHRP Project 09-54 represents sig- nificant contributions to the study of asphalt mixture aging. However, several critical short- comings exist that need to be addressed to ensure the accurate and practical characterization and prediction of the long-term aging of asphalt mixtures. First, the consideration of WMA, RAP, and PMA on the relationship between laboratory and field aging requires further inves- tigation. In addition, given that the original project considered only a single field core per project, additional field core replicates can be analyzed to greatly improve the reliability of the developed laboratory aging procedure and PAM. Also, the PAM was established by cali- brating a rheology-based oxidation kinetics model against the field core measurements at a single depth. The calibration process ignored the effects of mixture morphology and diffusion on oxidative aging. Establishing a depth-dependent field calibration of the asphalt kinetics model that considers mixture morphology is required to better account for the effects of dif- fusion. Further, a means to estimate the PAM inputs using standard PG aging methods and data are needed to improve the practicality of implementation. Lastly, the predicted changes in the binder properties with oxidative aging must be related to changes in the asphalt mixture properties to facilitate the integration of the PAM into ME pavement performance prediction frameworks.

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The accurate characterization of the in situ aging of asphalt pavement materials over the service life of the pavement is of utmost importance to the implementation of mechanistic empirical (ME) pavement design and analysis methods.

The TRB National Cooperative Highway Research Program's NCHRP Research Report 973: Long-Term Aging of Asphalt Mixtures for Performance Testing and Prediction: Phase III Results refines the aging procedure developed in the original NCHRP Research Report 871: Long-Term Aging of Asphalt Mixtures for Performance Testing and Prediction. The updates field calibrate the original project aging model (PAM), develop procedures to estimate the PAM inputs, and develop a framework by which the predicted changes in asphalt binder properties that are due to oxidative aging can be related to corresponding changes in asphalt mixture performance.

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