The aging of asphalt pavements leads to less flexible asphalt mixtures that are prone to cracking and spalling. In this study, the relationship between lab and field aging was evaluated based on both theoretical asphalt aging models and practical asphalt and asphalt mixture performance tests. The results show that the corresponding field aging duration calculated using the mixture testing, especially the cracking test, is more conservative than the traditional aging models or binder rheological measurements. 5 and 12 days appear to simulate 16 and 38 years of field aging (in New Hampshire) for the top 12.5 mm pavement, respectively, based on the asphalt binder test results. In contrast, the theoretical aging model considers climatic conditions and suggests that 5 and 12 days simulate in-field aging of 6.2 and 15.0 years, respectively. The asphalt mixture test results indicate that the laboratory aging conditions simulate minimal field aging durations. This is because the damage to the asphalt pavement structure caused by climatic conditions and traffic loads is fully considered. This could be very useful for designing a more reliable and durable pavement incorporating intricate field conditions.

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This research aimed to investigate the attenuation mode of the layer modulus of asphalt pavement in accelerated pavement testing (APT). A full-scale experimental section was constructed and tested using the APT facility. Two non-destructive testing (NDT) methods, named falling weight deflectometer (FWD) technique and portable seismic property analyzer (PSPA) test, were used to obtain the layer moduli of asphalt pavement during the APT test. The variation patterns of layer moduli obtained by FWD and PSPA tests were calculated and compared after the temperature was corrected to 20 ℃. It was found that the variation pattern of surface layer modulus based on field FWD measurements was consistent with the one measured from PSPA tests. That is the modulus of the surface layer increases with the APT load repetitions firstly and then decreases with the rise of the repetitions. The modulus values of the surface layer measured from PSPA tests are obviously larger than those backcalculated based on deflection basins. The ratio of the measured surface layer modulus based on the PSPA test to the backcalculated one based on the FWD test ranges between 2.06 and 2.71. The backcalculated base layer modulus always declines with the increasing loading repetitions. The attenuation patterns of the surface layer modulus and the base layer modulus in the damage stage are described as E_a=421100*N^-0.6119 and E_b=128000*N^-0.1096, respectively.

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In a mechanistic-empirical (ME) pavement design method, the modulus of asphalt concrete (AC) is essential. The in-situ AC modulus can be obtained by the surface wave method (SWM). However, the measured modulus needs to be adjusted to the design frequency values. This study aimed to propose a frequency adjustment method for the in-situ AC seismic modulus. For this purpose, coring and dynamic modulus tests, FWD (Falling Weight Deflectometer) tests, and PSPA (Portable Seismic Pavement Analyzer) tests were carried out in the accelerated pavement test (APT). The master curves generated by the dynamic modulus results correlated well with the moduli determined from the other tests. Based on this relationship, a frequency adjustment factor was developed for the seismic modulus of the undamaged AC layer. For the damaged AC layer, the proposed factor was modified by incorporating the effect of the damage. Finally, to validate the frequency adjustment factor, the measured maximum tensile strains in the APT were compared with the values determined from the adjusted seismic moduli. The results prove that the frequency adjustment factor is appropriate to obtain the design modulus from the surface wave test. The PSPA test is also recommended to obtain the in-situ AC seismic modulus.

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The modulus back-calculation of asphalt pavement layers using falling weight deflectometer (FWD) data has become one of the most important methods of evaluating pavement bearing capacity. Several back-calculation methods have been proposed to estimate material properties. A new modulus back-calculation method called the deflection basin regulation algorithm (DBRA) has emerged recently. This algorithm requires an inertial point and two characteristic points in a deflection basin for back-calculating the moduli of three-layer pavement. However, the existing characteristic point positions are determined based on the theoretically calculated deflections and have not been verified by measured deflections. In this research, the field-measured deflection basins of different pavement structures are used to determine the optimal characteristic point positions to improve the new back-calculation method. First, the optimal point positions are determined based on the effects of the positions on the back-calculation variability. Then the back-calculated results based on the optimal characteristic points are compared to the results obtained using the MODULUS program. Finally, the improved modulus back-calculation method is also verified by the deflections from two pavement structures at different temperatures and loading levels. It was found that the optimal characteristic point positions were located at distances of 0 and 60 cm from the load center. Both comparative analysis and independent verification prove that the determined optimal characteristic point positions work well for back-calculating the layer moduli of other pavement structures. The findings of this research may facilitate the application of the DBRA for modulus back-calculation.

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This paper focuses on empirically investigating the inertia effects of past behavior in commuting modal shift behavior and contributes to the current state of the art by three aspects. Firstly, this study introduces and tests the potential influences of the inertia effects of past behavior on the traveler’s preferences regarding level-of-service (LOS) variables, besides the impacts of inertia effects on the preference for the frequently used transport mode in the past. Secondly, the mode-specific inertia effects are investigated to distinguish the differences in the inertia effects for different transport modes based on posterior individual-specific parameter estimations. Thirdly, the factors contributing to the heterogeneity of inertia effects including demographics and travel contexts, are quantitatively examined. A joint random parameter logit model using a revealed and stated preference survey regarding commuting behavior is employed to unravel the three aspects. The results reveal significant interactions of inertia terms with LOS variables indicating the influences of past behavior on travelers’ evaluations on attributes of their previous choices. The mean values and variances of inertia effects for different transport modes are significantly and substantially distinct. For instance, the inertia effects of frequently using car are substantially positive representing strong stickiness to the car, while the inertia effects of frequently using the metro have large variances among travelers and mostly appear as dispositions to change. Besides, the effects of personal characteristics and travel contexts on the magnitude of the inertia effects of different transport modes are identified as well. A demand estimation analysis is utilized to investigate the influences of three aspects on predicting travel demands in various contexts. Incorporating the interactions and mode-specific inertia effects can remarkably improve the model performance. The demand estimation will be biased if they are neglected.

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The temperature field of asphalt pavement with thick asphalt layer (>30 cm) was analyzed. Based on the cumulative effect of air temperature and solar radiation on pavement temperature, a regression analysis was conducted on the measured pavement temperature from four selected test sites and the obtained meteorological data. The prediction models for different sites were determined as a function of depth, average air temperature and total solar radiation. Then, the cause for the difference between the models at each site was analyzed, and the historical mean monthly air temperatures were incorporated into the model. The model can be applied to the pavement temperature prediction in different areas. The results show that the model has high applicability and high accuracy.

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Asphalt concrete (AC) modulus reduction caused by repeated axle loading significantly affects pavement long-term performance; including when built on a semi-rigid layer. However, quantifying this effect is challenging. The primary objective of this paper was to monitor and evaluate modulus reduction and fatigue damage accumulation at various AC depths utilizing data obtained from two semi-rigid pavement sections. During loading, a non-destructive method, portable seismic pavement analyzer (PSPA), was used to predict the modulus ratio. PSPA test results show that the damage is nonlinear with respect to the loading passes. Also, depth and AC thickness can influence the development of damage. A developed model showed that it could predict the aforementioned nonlinear relationship. The model parameters can be used to identify the damage level at various AC depths. Unexpected compared with previous understanding, the damage in AC layers was found to increased first, then decreased, and finally increased with the depth. Since PSPA is cheap, portable, and easy to apply, this method to identify the damage level in AC layers is proven to be applicable and practical.

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Asphalt pavement is a multi-layer continuous structure with an interlayer bonding condition that can greatly influence its bearing capacity and must be monitored over the whole service length. Hence, proper maintenance and rehabilitation measures are taken and better feedback can be made for the design. Nevertheless, asphalt pavement interlayer bonding condition plays a hidden role and is difficult to quantify unless applying damage discovery techniques like drilling core process. The original structure is destroyed by the damage detection approaches, the results also suffer from low coverage rate and high dispersion, therefore, actual engineering demands are not satisfied. Here, some recent methods are briefly presented based on asphalt pavement interlayer bonding condition non-destructive diagnosis and their restrictions are discussed. Moreover, a new technique is provided with the merits of utilizing only mechanical simulation and overall superficial distresses condition evaluation index with high accuracy. This simulation procedure adopts bridging principles to build a connection between asphalt pavement superficial distresses and asphalt pavement micro mechanic parameters. It uses a structure behavior equation capable of identifying four typical deterioration modes and has specific physical meaning parameters to predict asphalt pavement overall superficial distresses. The established model allows the asphalt pavement interlayer bonding acting as a hypothetical input variable. The known input variables include easily obtainable design parameters of the asphalt pavement structure, historical superficial distresses, surface deflection, traffic load, and environmental factors, however, the output is the predicted asphalt pavement overall superficial distresses condition. The asphalt pavement interlayer bonding condition is defined by contrasting the theoretical asphalt pavement overall superficial distresses conditions between its complete bonding condition and discontinuous bonding condition to a certain degree. Examples in parts of the Jingha highway show that great discrepancies exist between theoretical asphalt pavement overall superficial distress in the condition of complete interlayer bonding and actual asphalt pavement overall superficial distress. The actual asphalt pavement sections in overall superficial conditions are deteriorated much faster than normal ones. By setting the asphalt pavement interlayer bonding continuations as 75% and 90% for K315-K316 section and K316-K317 section, respectively, the revised and predicted overall superficial distresses of the theoretical asphalt pavement are consistent with the real ones. The hypothetical values are then chosen as the diagnosed quantitative asphalt pavement interlayer bonding continuations and are proven to be correct through drilling core sample results. The analyses in other sections show that middle traffic volume asphalt pavement structure is quite weak when its interlayer bonding continuation is 70%, and under this value, its bearing capacity is almost equivalent to the situation when its interlayer bonding continuation is 0%; when its interlayer bonding continuation is 85% or more, its bearing capacity is almost equivalent to the situation where its interlayer bonding continuation is 100%. This proposed non-destructive diagnosis method for asphalt pavement interlayer bonding condition is effective and shows good application prospects in road engineering.

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The asphalt-based pavement performance evaluation includes the derivation of the dynamic moduli and loading frequencies of pavement layers under various traffic- and climatic-induced loading conditions. The traffic-induced strain pulses and loading frequencies of commonly used (semi-rigid, flexible, and steel deck) asphalt pavements were experimentally determined by vehicular loading field tests with embedded strain gauges for different axle loads, motion speeds, and temperatures. It was found that the axle load values had no noticeable effect on the pavement loading frequency, which was mainly controlled by the vehicular motion speed. The transverse frequencies were found to be higher than longitudinal ones, while the distributions of loading frequencies by pavement depth differed for three pavements under study. The frequency values at temperatures over 35 °C exceeded those at lower temperatures, while in the temperature range from 4 to 31 °C, the motion speed vs. loading frequency relations for three pavements were nearly identical. The loading frequency f increased approximately linearly with the motion speed V, according to the unified fitting equation for three types of pavements under study, namely f = 0.127 × V. This unified equation was further proved valid to predict the dynamic modulus properties of field asphalt pavement layers. Moreover, several previous prediction models for loading frequency, including the Brown model, Ullidtz model, MEPDG procedure and Ulloa model, were compared to the results in this study. These previous models were found to overestimate the loading frequencies within the asphalt layer. The prediction errors of the Brown model and the Ullidtz model were pronounced. The loading frequencies calculated by the MEPDG procedure and the Ulloa model need to be modified by dividing 2.8 and 1.7, respectively.

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The modulus of asphalt mixture is traditionally measured from the laboratory dynamic modulus test. However, different laboratory test methods often lead to obviously different test results. To evaluate the moduli of asphalt mixtures as constructed in field pavements, this study back-calculated the moduli of the pavement layers, based on measured strain data in Accelerated Pavement Testing (APT). Field tests were conducted to measure strains at different locations of the built pavement section at different temperatures and wheel motion speed. The loading frequencies of the asphalt layer subject to different motion speeds were calculated based on the duration of measured strain pulses. Subsequently, the relationship between the motion speed and the loading frequency was established. An finite element (FE) model of the pavement section was created, which was used to back-calculate the moduli of asphalt pavement layers using the measured strain data. Based on the back-calculation results at different loading conditions, the master curve of the field asphalt layer was determined. This master curve was further used to compare with that obtained from laboratory uniaxial compressive test. The relationship between the field and laboratory moduli was determined to be E_Laboratory= 1.298E_Field.

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The modulus of an asphalt layer subjected to repeated loadings was measured to reasonably analyze the damage development therein. The ratio of the reduction in the modulus to the modulus of the undamaged asphalt layer is used to reflect the damage of the asphalt layer; the evolution of the damage with the number of the loadings was analyzed. Full-scale accelerated pavement testing was conducted to simulate the repeated vehicle loadings on the asphalt layer. Falling-weight deflectometer, pavement seismic property analyzer (PSPA), and uniaxial compression dynamic modulus tests were conducted to obtain the modulus of the undamaged asphalt layer in the unloaded area. PSPA was used to obtain the moduli of the damaged asphalt layers in the loading area; the ratios of the reduction in these moduli to the modulus of the undamaged asphalt layer were calculated. The damage development in the asphalt layer was analyzed, and a nonlinear damage-evolution model was established, which assisted in obtaining the speed of the damage development in the asphalt layers at different depths. It is found that the S-type master curve can be used to unify the undamaged moduli derived from the three tests. The results of the field-detection method are in accordance with the predictions obtained from the laboratory master curves. In addition, the regression parameter in the damage-evolution model assists in judging the speed of the damage development in the asphalt layer. The normalization result shows that the lateral asphalt layer at the outer edge of the wheel paths and that at the center of the wheel gap experience slower damage as the depth increases. The mid-depth asphalt layers at the other positions and directions experience faster damage. In conclusion, the nonlinear damage-evolution model can provide the basis for damage development judgment and lay foundation for optimizing the maintenance timing and strategy.

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Temperature is one of the most important factors affecting functional as well as structural performance of asphalt pavements with thick asphalt layer (>30 cm). For a successful pavement design, it is vital to accurately predict the pavement temperatures at various depths. However, most previous researches focused on the temperature predictions for conventional asphalt pavements, of which the asphalt thickness is less than 30 cm. This suggests their proposed models are applicable in top layers, but may not be so effective for temperature predictions at deeper depths. As a result, the primary objective of this research was to develop a statistical model to predict temperatures at deep depths. Three test sites were selected, and they were instrumented with a number of sensors and a data logger to record the pavement temperature hourly. Also, all test sections can provide meteorological monitoring to collect hourly air temperatures and hourly total solar radiation. The recorded meteorological conditions were found to have cumulative effect on the measured pavement temperatures at various depths. On basis of their relationship, a statistical regression was performed, and the temperature prediction model was determined as a function of depth, average air temperature and total solar radiation calculated in the cumulative time. For an improvement in applicability, historical mean monthly air temperatures were also incorporated into the mode. The accuracy and applicability of the improved model were validated by applying it to additional sites for which the measured pavement temperatures and meteorological data were available. Also, by comparing with existing models, the developed model was testified to be more effective for asphalt pavements with thick asphalt layer, promising the model's potential use.

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Buton rock asphalt (BRA) is a natural asphalt modifier that can improve different properties of mixture. The traditional mixing process for BAR mixture is to mix aggregates with BRA firstly, and then mix them with heated base asphalt and mineral powder in that order. However, it results in an unevenness of asphalt film thickness, which can influence the performance of mixtures. Therefore, the primary objective of this research is to develop an advanced mixing process for BRA mixture. Six mixing processes were attempted. Air void, dynamic stability (DS), indirect tensile strength, and tensile strength ratio (TSR) were selected as the evaluation parameters. By comparison, the optimum mixing process is changed by adding the BRA and base asphalt in different orders. Lastly, contact angle measurements and inverse gas chromatography (IGC) were conducted to analyze the adhesion work in different mixing processes, which can explain the improvements of the advanced mixing process.@en

The determination of a single temperature to stimulate permanent deformation is quite significant in pavement design and maintenance. The practical use of this single temperature to replace the seasonal temperature fluctuation throughout the whole year can apparently simplify the prediction of permanent deformation of an asphalt pavement. This single temperature is termed effective temperature (T_eff) and is defined as a simulated temperature to achieve a permanent deformation, which is accumulated due to the traffic loading and pavement temperature within an entire year. However, most previous studies on effective temperature focus on investigating the performance temperature for permanent deformation instead of simplifying the prediction of this distress. For this reason, the primary goal of this study was to develop a T_eff model and simplify the prediction of permanent deformation of asphalt pavement. The predicted distress and the T_eff results used to build the models and find the optimized coefficients were obtained by the rut depth prediction model, which was based on shear stress and widely applied in China. The proposed T_eff models incorporated degree-days and the earth temperature, which was represented by mean annual air temperature (MAAT). By incorporating those parameters, these temperature models predominantly considered the effect of high temperature on the permanent deformation and can be utilized to improve their prediction in various regions. In addition, the asphalt mixture properties and vehicle speeds were also incorporated in the models. By comparing with different models in previous studies, the proposed models were testified to be reasonable.

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