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Suggested Citation:"Chapter 1 - Background." National Academies of Sciences, Engineering, and Medicine. 2017. Long-Term Aging of Asphalt Mixtures for Performance Testing and Prediction. Washington, DC: The National Academies Press. doi: 10.17226/24959.
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Suggested Citation:"Chapter 1 - Background." National Academies of Sciences, Engineering, and Medicine. 2017. Long-Term Aging of Asphalt Mixtures for Performance Testing and Prediction. Washington, DC: The National Academies Press. doi: 10.17226/24959.
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Suggested Citation:"Chapter 1 - Background." National Academies of Sciences, Engineering, and Medicine. 2017. Long-Term Aging of Asphalt Mixtures for Performance Testing and Prediction. Washington, DC: The National Academies Press. doi: 10.17226/24959.
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Suggested Citation:"Chapter 1 - Background." National Academies of Sciences, Engineering, and Medicine. 2017. Long-Term Aging of Asphalt Mixtures for Performance Testing and Prediction. Washington, DC: The National Academies Press. doi: 10.17226/24959.
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Suggested Citation:"Chapter 1 - Background." National Academies of Sciences, Engineering, and Medicine. 2017. Long-Term Aging of Asphalt Mixtures for Performance Testing and Prediction. Washington, DC: The National Academies Press. doi: 10.17226/24959.
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Suggested Citation:"Chapter 1 - Background." National Academies of Sciences, Engineering, and Medicine. 2017. Long-Term Aging of Asphalt Mixtures for Performance Testing and Prediction. Washington, DC: The National Academies Press. doi: 10.17226/24959.
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Suggested Citation:"Chapter 1 - Background." National Academies of Sciences, Engineering, and Medicine. 2017. Long-Term Aging of Asphalt Mixtures for Performance Testing and Prediction. Washington, DC: The National Academies Press. doi: 10.17226/24959.
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Suggested Citation:"Chapter 1 - Background." National Academies of Sciences, Engineering, and Medicine. 2017. Long-Term Aging of Asphalt Mixtures for Performance Testing and Prediction. Washington, DC: The National Academies Press. doi: 10.17226/24959.
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Suggested Citation:"Chapter 1 - Background." National Academies of Sciences, Engineering, and Medicine. 2017. Long-Term Aging of Asphalt Mixtures for Performance Testing and Prediction. Washington, DC: The National Academies Press. doi: 10.17226/24959.
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3 Aging has long been recognized as a major driver of distress for asphalt concrete and, by extension, asphalt pavements. Aging causes the material to stiffen and embrittle, which leads to a high potential for cracking. The term aging with regard to asphalt concrete can have multiple interpretations. The term has been applied to mean the overall deterioration of an asphalt pave- ment from exposure to both climatological and load factors. In other cases, aging refers only to the effects of environment, which include oxidative aging, ultraviolet radiation, thermal effect, steric hardening, and moisture-related damage (Wright 1965). However, the most common usage of the term aging, and the one used in this report, is to describe the process of asphalt binder oxidation. The issue of oxidative aging of asphalt binder has been recognized and studied for over a cen- tury. Hubbard and Reeve (1913) published the results of a study that examined the effects of a year of outdoor weathering on the physical (weight, hardness, etc.) and chemical (solubility) properties of paving-grade asphalt cements. Subsequent studies have confirmed the basic findings that oxidation, and not volatilization alone, is responsible for the changes in asphalt properties that occur due to exposure (Thurston and Knowles 1936, Van Oort 1956, Corbett and Merz 1975), although volatilization may play a greater role in some of the binders produced today. Sig- nificant research also has been conducted to investigate the chemical aspects of the aging process, and excellent reviews of these studies can be found in the literature (Wright 1965, Lee and Huang 1973, Jemisson et al. 1992, Petersen 2009). In some of the cited studies, researchers have used sophisticated experimental studies to propose conceptual, empirical, and/or analytical models for the aging of asphalt binder (Lunsford 1994, Liu et al. 1996, Petersen and Harnsberger 1998, Glover et al. 2008). A review of the pertinent literature showed that although significant research has been devoted to understanding and modeling the aging of asphalt binder, relatively little has been devoted to the aging of asphalt mixtures (Bell 1989, Brown 2000, Airey 2003, Houston et al. 2005). The lack of significant research in this area, particularly in the years since the conclusion of the Strategic Highway Research Program (SHRP), reflects the complexities involved in studying mixture aging. For example, when physicochemical interactions between asphalt binder and aggregate occur, and when the material becomes structured and contains air voids, the aging process becomes more complex than for binder alone. To date, no comprehensive study has been undertaken that links the known behavior of an asphalt binder to that of an asphalt mixture, which is affected by these and other interacting factors. Without such a study, and given the current state of under- standing of the relationship between the properties of an asphalt binder and an asphalt mixture that contains that asphalt binder, it is argued that the only way to determine the impact of aging on mixture properties is direct experimentation of the mixtures (Bell and Sosnovske 1994, Bell et al. 1994, Anderson et al. 1994). C H A P T E R 1 Background

4 Long-Term Aging of Asphalt Mixtures for Performance Testing and Prediction The accurate characterization of asphalt mixture properties in terms of the service life of a pavement is becoming more important as more powerful pavement design and performance prediction methods are implemented. One example of such characterization is shown in Fig- ure 1. The results shown in this figure were obtained from the viscoelastic continuum damage finite element program, FlexPAVE™, a software program that was developed under the FHWA- sponsored Asphalt Mixture Performance-Related Specifications project (Kim et al. 2018). The figure presents the damage contours within a 10-cm thick asphalt layer in a pavement under California climatic conditions. This analysis employed the material properties obtained from aging a mixture composed of SHRP AAD-1 asphalt binder and Federal Highway Adminis- tration Accelerated Loading Facility – (FHWA ALF–) graded aggregate in a forced-draft oven at 95°C for about 9 days. More details of the material properties can be found elsewhere (Qi et al. 2004). The effects of aging on the propensity of the pavement to exhibit top-down cracking can be seen clearly by comparing Figure 1 (a) and (b); i.e., the damage intensity at the top of the asphalt layer becomes much greater when the aged material properties are used in the analysis. The accuracy of the aging model to represent the long-term aging of asphalt mixtures at different depths of in-service pavements is critical to a mechanistic pavement analysis model’s ability to predict top-down cracking. Project Objectives and Scope The objective of this project was to develop a calibrated and validated procedure to simulate the long-term aging of asphalt mixtures for performance testing and prediction. The key prod- ucts are a laboratory aging procedure and associated procedures that prescribe a set of laboratory aging conditions to represent the long-term-aged state of asphalt mixtures in a pavement as a function of climate and depth. The results of this project provide a basis for the future develop- ment of a methodology that integrates the effects of long-term aging in Pavement ME Design. Short- Term Aged Loose Mix, 95°C, 8.9 Days 0 1 2 3 4 5 6 7 8 9 10 1 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 1 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 Z (cm ) 0 1 2 3 4 5 6 7 8 9 10 Z (cm ) X (m) -1.5 -1 -0.5 0 0.5 1 1.5 X (m) -1.5 -1 -0.5 0 0.5 1 1.5 (a) (b) Figure 1. Damage contours from 10-cm thick asphalt pavements in California after 20 years of service: (a) short-term aging only and (b) long-term aging.

Background 5 In addition, this procedure would allow long-term aging to be considered in terms of full-scale and accelerated pavement test results. Future research is suggested to establish a diffusion model framework that accounts for differ- ences in asphalt mixture morphology (e.g., air voids, film thickness) within the aging modeling framework and that can be incorporated into mechanistic design and analysis methods. In addi- tion, future work is suggested to calibrate the aging procedure for warm-mix asphalt (WMA) and mixtures containing reclaimed asphalt pavement (RAP). Previous Research into Long-Term Aging of Asphalt Mixtures Several asphalt mixture laboratory aging procedures have been tried. These procedures can be broadly classified based on the (a) state of the material during aging (compacted specimen versus loose mix), (b) pressure level (oven aging versus pressurized aging), and (c) aging tem- perature. Thus, the discussion of the laboratory aging of asphalt mixtures in this section focuses on these factors. In addition, a review of relevant aging models is presented. Key elements required for developing an aging model include binder aging index properties (AIPs), oxida- tion kinetics modeling, and diffusion modeling. Compacted Specimen Aging Versus Loose Mixture Aging The standard method used to assess the long-term aging of asphalt mixtures in the United States is American Association of State Highway and Transportation Officials (AASHTO) R 30 (2002), which is meant to represent 5 to 10 years of aging in the field. However, two speci- men integrity problems have been found using compacted specimen aging as recommended in AASHTO R 30: 1. Distortion: Changes in air void content and geometry due to specimen softening and slump- ing have been reported when using AASHTO R 30 (Reed 2010). To overcome this problem, the NCHRP Project 9-23 protocol proposes wrapping specimens in metal wire mesh secured with three clamps to prevent the samples from undergoing geometric distortion (Houston et al. 2005). However, this approach has been reported only to reduce, but not eliminate, specimen distortion during aging (Reed 2010). 2. Oxidation gradient: The NCHRP 9-23 project (Houston et al. 2005) demonstrated that the long-term oven aging of compacted specimens leads to both radial and vertical oxidation gradients in mixture specimens, which is a concern for the use of long-term oven aging of compacted specimens in performance testing because properties differ throughout a speci- men (Houston et al. 2005). It is important to note that the objective of this study was to develop a long-term aging pro- cedure that could be used in the fabrication of performance test specimens. A performance test specimen should satisfy representative volume element requirements; i.e., it should have uniform material properties throughout the specimen so that the performance measured from the specimen can be related to a specific state of the material. An aging gradient would lead to multiple dynamic modulus (|E*|) values within the specimen as well as to variable fatigue per- formance throughout the specimen. In addition, the aging gradient in a laboratory-aged specimen does not replicate field aging gradients. In the field, aging is greatest at the surface and reduces with depth. However, in laboratory-aged specimens, aging is greatest at the periphery and reduces towards the center of the specimen. Hence, the direction of aging gradients differs between field cores and compacted specimens prepared in the laboratory (Houston et al. 2005).

6 Long-Term Aging of Asphalt Mixtures for Performance Testing and Prediction Although the laboratory aging of loose (uncompacted) asphalt mixtures has received less attention than compacted specimens, several studies recommend aging loose mixtures in the laboratory to simulate the aging of asphalt pavements instead of aging compacted specimens (Mollenhauer and Mouillet 2011, Van den Bergh 2011). However, most of these studies were intended to prepare RAP materials rather than to investigate compaction and subsequent per- formance testing (Partl et al. 2013, Mollenhauer and Mouillet 2011, Van den Bergh 2011). Geometry distortion is not a concern with loose mix aging because the specimens are compacted following aging. In addition, the aging gradient is not a problem, because the loose mix is aged as a single layer of coated aggregate particles and, thus, oxygen and heat can circulate easily and evenly throughout the mix. Also, the increased surface area of the binder film that is exposed to oxygen is believed to accelerate aging in loose mixtures more so than in compacted specimens. However, the compaction of aged loose mix for performance testing can lead to a potential spec- imen integrity concern because aged binder is stiffer than unaged binder and thus is expected to be less compactable than unaged material. Table 1 provides a summary of the advantages and disadvantages of using loose and compacted asphalt mixture aging. Oven Aging Versus Pressure Aging Long-term oven aging is the most common method used to simulate the oxidative aging of asphalt mixtures in the laboratory. As discussed, the current standard procedure, AASHTO R 30, consists of conditioning compacted asphalt concrete specimens in an oven at 85°C for 5 days. However, other oven aging procedures have been tried and are cited in the literature. Although these procedures are somewhat similar in terms of methodology, they differ in terms of temperature and duration (e.g., Bell et al. 1994, Houston et al. 2005, Reed 2010). The summaries of compacted and loose mixture aging trials (refer to Appendix A) dem- onstrate that long-term oven aging requires considerable time to produce oxidation levels that correspond to field conditions near the end of a pavement’s service life. Hence, researchers have attempted to conduct long-term aging trials using both loose mix and compacted speci- mens under air pressure to expedite oxidative aging (e.g., Kumar and Goetz 1977, Von Quintus et al. 1992, Bell et al. 1994). Different pressure and temperature combinations were tried in these studies. Generally, these earlier studies suggest that air/oxygen pressure expedites oxidative aging. However, in the case of aging compacted specimens, the loss of integrity during aging is a concern unless low temperatures are used, which will adversely affect the aging rate. The standardized pressure aging equipment that is widely used in the asphalt industry is the PAV. The PAV has been used to age both loose mix and compacted specimens. One of the Loose Mix Pros Homogenous aging in the mixture Higher oxidation rate than compacted mix Maintaining specimen integrity a non-issue Cons Difficulties associated with compaction of aged loose mix, which limits its use for producing specimens for performance testing Limited amount of materials can be aged in a standard pressure aging vessel (PAV) chamber Compacted Specimen Pros Can produce aged sample for performance tests if slumping is minimized through use of wire mesh Cons Slower oxidation rate than loose mix Integrity of the specimens is compromised at high temperatures and pressures due to slump, cracking upon pressure release, and differences in the coefficient of thermal expansion between binder and aggregate Oxidation gradients exist radially and throughout height of the specimen Table 1. Comparison between loose mix and compacted specimens in the aging procedure.

Background 7 main shortcomings of PAV aging compared to oven aging is the amount of material that can be aged. Based on previous studies of loose mixture aging, in order to obtain uniform aging, a uniform thin layer of loose mix should be placed in the PAV, which reduces the capacity of the equipment to a very low level (around 1 kg) (Partl et al. 2013). Despite this capacity prob- lem, however, it is believed that the air/oxygen pressure in the PAV can expedite aging and reduce the time required to achieve any desired level of aging in an asphalt mixture specimen. Furthermore, if a smaller geometry for asphalt mixture cores is used, more specimens can be aged together. However, concern remains with respect to maintaining compacted specimen integrity during pressure aging and upon pressure release, which needs to be considered care- fully when assessing PAV aging of compacted mix specimens (Bell et al. 1994). Table 2 presents a brief summary of the pros and cons of conducting oven versus pressurized aging. Laboratory Aging Temperature The oxidation of asphalt binder involves several independent and concurrent reactions. Tem- perature can affect the rate of oxidation, the binder species that are oxidized, and the nature of the oxidized species that are formed. Thus, temperature is a critical factor in laboratory simula- tions of long-term aging. Increasing the aging temperature increases the rate of oxidation, which is a desirable attribute. However, it can also disrupt polar molecular associations, which leads to the oxidation of molecules that are inaccessible at lower temperatures. In addition, at ambient temperatures, the oxidation of sulfides in asphalt binders leads to the formation of sulfoxides. Elevated temperatures can deplete these sulfoxides through secondary oxidation reactions that convert sulfoxides to sulfones. Thus, accelerated aging of asphalt binder at significantly high temperatures may lead to a fundamentally different aged asphalt binder than asphalt aged in the field (at a lower temperature) (Branthaver et al. 1993). The literature indicates that the disrup- tion of polar molecular associations and sulfoxide decomposition become critical at tempera- tures that exceed 100°C (Petersen 2009). Furthermore, aging at temperatures above 100°C can lead to asphalt mastic drain-down from the loose mix because the low viscosity of the asphalt binder at elevated temperatures. Aging Index Properties (AIPs) Properly quantifying the extent of aging for both laboratory- and field-aged binders is essen- tial to this study. Asphalt binder is the asphalt mixture constituent that undergoes oxidative aging. Hence, the oxidation of a pavement is best tracked using binder properties, because the mixture is subjected to other factors, including mechanical degradation that is caused by traffic loading, thermal-induced stress, and moisture, all of which could confound test results. Herein, the binder properties that are used to measure the extent of oxidation are referred to as AIPs. Oven Aging Pros Available and easy to perform and controlLarge amount of material can be aged Cons High variability among ovens, especially in terms of air drafting More time needed to age materials in the oven than in the PAV Maintaining compacted specimen integrity is required, especially at high temperatures Pressure Aging Pros Pressure can expedite the aging process More reliable than oven aging due to less equipment variability between laboratories Cons Due to limited capacity of the vessel, less material can be aged in each aging cycle unless new device is developed Integrity of compacted samples during and after testing is a major concern Table 2. Comparison between oven and PAV aging methods.

8 Long-Term Aging of Asphalt Mixtures for Performance Testing and Prediction AIPs can be divided into two main categories: chemical functional groups and rheological parameters. Chemical AIPs provide the most direct indicators of oxygen uptake and can be mea- sured using Fourier transform infrared (FTIR) spectroscopy techniques. Also, different rheo- logical properties have been introduced as aging indices (e.g., the crossover modulus, low shear viscosity, etc.) (Petersen 2009, Underwood et al. 2010, Farrar et al. 2013). Rheological AIPs are advantageous over chemical AIPs because they can be related directly to the mechanical proper- ties of an asphalt mixture and are readily relatable to pavement distresses (Glaser et al. 2013a). However, a comprehensive study to elucidate the rheological properties that most directly relate to the chemical changes that result from oxidation is lacking in the literature. Carbonyl and sulfoxide are the two major chemical functional groups that are produced upon oxidation of an asphalt binder. The carbonyl chemical functional group has long been used to indicate the level of oxidation within asphalt binder and is directly related to changes in asphalt binder viscosity (Petersen 2009). The ketone functional group is the major compo- nent of the carbonyl infrared absorption region. Ketone formation changes the polarity of the associated aromatic ring components within an asphalt binder, which leads to an increase in the asphaltene content, thereby increasing viscosity (Petersen 2009, Petersen and Glaser 2011). The change in the sulfoxide fraction during aging has received less consideration in the past. Petersen and Glaser (2011) conducted a thorough study to understand the role of sulfoxide formation on physical properties during oxidative age hardening in asphalt binders. By evaluat- ing the relationship between the sum of the absorbances of the ketones and sulfoxides and the logarithm of viscosity, Peterson and Glaser (2011) showed that the alcohols that are produced during oxidative aging have a significant impact on viscosity, especially for asphalt with a high sulfur content. FTIR-based AIPs have been represented by both absorbance peaks (e.g., Petersen 2009, Petersen and Glaser 2011) and areas (e.g., Han, 2011, Jin et al. 2011, Lamontage et al. 2001, Zhang et al. 2011). Peaks are determined directly by evaluating absorbance at specific wave numbers. In this study, changes in the carbonyl and sulfoxide peaks were tracked at wave num- bers 1702 cm–1 and 1032 cm–1, respectively. Areas are calculated by determining the area under the FTIR spectrum that lies between specific wave numbers. In this study, the carbonyl area, carbonyl + sulfoxide (C + S) area, and C + S peaks are used in comparisons. Although numerous AIPs have been proposed in the literature, a comprehensive study to elucidate the chemical and rheological AIPs that are the best for tracking oxidation is not available. Modeling of Oxidative Aging To prepare an aged compacted specimen in the lab that represents specific time in service, climate, depth within the pavement, and level of air voids, a solid understanding of binder oxidation kinetics and diffusion is required. The Global Aging System (GAS) model (Mirza and Witczak 1995) is an empirical model that allows for the prediction of the change in binder viscosity as a function of age, given the mean annual air temperature (MAAT); the model also considers the gradient of aging with pavement depth. The GAS model assumes a hyperbolic aging function that predicts a decreasing rate of change of viscosity with an increase in age, under the assumption that most age hardening occurs within the first 10 years of a pavement’s service life. The simplicity of the GAS model makes it an attractive option. However, the GAS model has been criticized because it does not account for aging deeper than 1.5 in. below the pavement surface (Mirza and Witczak 1995, Prapaitrakul 2009). In addition, the model does not directly account for differences in asphalt binder kinetics among binder types. Also, the method used to account for air void content is based on a relatively small set of conditions, which is the reason this adjustment factor is considered optional (Mirza and Witczak 1995).

Background 9 A preliminary fundamentals-based, one-dimensional combined asphalt oxidation kinetics and diffusion model was developed at Texas A&M University. This model is referred to as the transport model (Lunsford 1994, Prapaitrakul 2009, Han 2011). The transport model includes several sub-models to predict pavement aging, including 1) oxygen diffusion/flow from the atmo- sphere into the interconnected air voids in a pavement, 2) oxygen diffusion through the asphalt- aggregate matrix, 3) heat transfer, and 4) oxidation kinetics. Implementation of the transport model currently requires detailed information about air void content and distribution as well as the temperature gradient throughout the pavement depth at a higher level of accuracy than can be provided by available databases, including the Enhanced Integrated Climatic Model (EICM). Although the oxygen percolation and diffusion components of the transport model are still under development, oxidation kinetics modeling has received significant attention in the past. All asphalt materials exhibit relatively similar kinetics, which can be described as trends in AIPs that are indicated by an initial fast reaction period, also known as the spurt, followed by a slower reaction period that has an approximately constant rate (Petersen et al. 1996, Petersen 1998, Petersen et al. 2011, Prapaitrakul 2009, Han 2011). Asphalt binder oxidation kinetics has been modeled successfully using the Arrhenius expression of temperature and pressure dependency (Petersen 2009, Prapaitrakul 2009, Glaser et al. 2013b). The Arrhenius equation, presented as Equation 1 in this report, describes the temperature dependency of the oxidation rate. Herrington et al. (1994) proposed Equation 2 through Equa- tion 4 for modeling the oxidation kinetics of asphalt binder using viscosity as an AIP. Herrington et al.’s (1994) kinetics model considers both the initial fast reaction period (i.e., the spurt) and the constant rate period. Researchers at Texas A&M University also conducted a series of proj- ects that led to a kinetics model, as expressed in Equation 3 through Equation 8, using similar principles and the same Arrhenius equation as Herrington et al. (1994) (Lau et al. 1992, Davison et al. 1994, Liu et al. 1996, Domke et al. 2000, Glover et al. 2014). In the Texas A&M University kinetics model, the carbonyl area is used as the AIP. In addition, Glover et al. (2014) presented an interrelationship among kinetics parameters to describe the fast and constant rate reactions. Glover et al. (2005) developed interrelationships between Arrhenius parameters of fast and con- stant rates, as shown in Equation 6 through Equation 8. This simplification reduced the number of unknowns to only two parameters in addition to the short-term-aged binder, CA. In addition, Glaser et al. (2013b) used stoichiometry to derive the kinetics model given in Equation 9 using C + S absorbance peaks as an AIP. Their kinetics model has only one adjust- able parameter besides short-term-aged binder aging level, which implies that the kinetics model can be calibrated using isothermal aging. They validated their model using 12 asphalt binders from a wide variety of sources. Equation 3 and Equation 4 are applied along with Glaser et al.’s (2013b) model to describe the temperature dependency of the oxidation reaction. Glaser et al. (2013b) proposed that the kinetics of asphalt binder can be modeled using a single material- dependent parameter that corresponds to the quantity of reactive material within an asphalt, M, and proposed that the Arrhenius parameters, kf and kc, are the same for all binders. Equation 10 shows the form of Glaser et al.’s (2013b) model, which incorporates the pressure dependency of the reaction rate. If the Arrhenius parameters can be applied universally, as Glaser et al.’s results suggest, the measurement of the AIPs that correspond to various durations of aging at a single temperature is all that is needed to characterize the kinetics model for a given binder (Glaser et al. 2013b, 2015). exp (1)k AP E RT a = −   α log log 1 exp (2)M k t k to f c( )( )η = η + − − +

10 Long-Term Aging of Asphalt Mixtures for Performance Testing and Prediction exp (3)k A E RT f f af = −    exp (4)k A E RT c c ac = −    1 exp (5)CA CA M k t k to f c( )( )= + − − + 0.85 10.4 (6)E Eaf ac= − 0.52exp 0.3328 (7)A Ef af( )= 0.0266exp 0.3347 (8)A Ec ac( )= 1 1 exp (9)C S C S M k k k t k Mto c f f c( )( )( ) ( )+ = + + −   − − + 1 . . 1 exp (10)C S C S M k P k P k P t k MP to c n f m f m c n( )( )( ) ( )+ = + + −   − − + where k = rate of reaction, kf = rate of fast reaction, kc = rate of constant reaction, A = frequency (pre-exponential) factor, Af = fast reaction frequency factor (s–1), Ac = constant reaction frequency factor (s–1), Eaf = fast reaction activation energy (kJ/mol), Ea = activation energy, Eac = constant reaction activation energy (kJ/mol), P = absolute oxygen pressure, α = reaction order with respect to oxygen pressure, m = reaction order of fast reaction, n = reaction order of constant reaction, R = universal gas constant, or ideal gas constant (kJ/mol•K), t = reaction time (s), T = reaction temperature (Kelvin), M = fitting parameter related to fast reaction reactive material, h = long-term aged binder viscosity, ho = short-term aged viscosity, CA = long-term aged binder carbonyl area, CAo = short-term aged binder carbonyl area, (C + S) = long-term aged binder C+S absorbance peaks, and (C + S)o = short-term aged binder C+S absorbance peaks. Although significant research efforts have been dedicated to modeling the kinetics of asphalt binder aging, relatively little attention has been devoted to modeling the kinetics of asphalt binders within asphalt mixtures. The lack of major studies in this area reflects the complexities involved in studying mixture aging. Oxidation reaction rates and mechanisms are affected by

Background 11 the complex physicochemical interactions between the asphalt binder and the aggregate (Moraes and Bahia 2015, Wu et al. 2014, Petersen 2009, Little et al. 2006, Recasens et al. 2005, Huang et al. 2002, Jones 1997, Petersen et al. 1987). The kinetics modeling used in this study applied Glaser et al.’s (2013b) work using a rheology- based AIP of loose mix aging data to account for the effect of mineral filler on aging rates. The kinetics model outputs can be calibrated based on concepts related to diffusion from the trans- port model in an effort to incorporate more fundamental behaviors than the GAS model and still be less cumbersome than the transport model.

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TRB's National Cooperative Highway Research Program (NCHRP) Research Report 871: Long-Term Aging of Asphalt Mixtures for Performance Testing and Prediction presents a proposed standard method for long-term laboratory aging of asphalt mixtures for performance testing. The method is intended for consideration as a replacement for the method in AASHTO R 30, “Mixture Conditioning of Hot Mix Asphalt (HMA),” which was the most commonly used method for aging asphalt materials for performance testing for input to prediction models for the past 25 years. The method improves on R 30 in that the laboratory aging time is specifically determined by the climate at the project location.

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