Evaluation of Warm Mix Asphalt Produced at Various Temperatures through Dynamic Modulus Testing and Four Point Beam Fatigue Testing

The Virginia Department of Transportation began allowing the use of warm mix asphalt (WMA) in 2008. Although several WMA technologies were investigated prior to implementation, foamed WMA was not. This study evaluated the properties and performance of foamed WMA placed during the initial implementation of the technology to determine whether the technology had performed as expected. Six mixtures produced using plant foaming technologies and placed between 2008 and 2010 were identified and subjected to field coring and laboratory testing. Coring was performed in 2014, resulting in pavement ages from 4 to 6 years. Three comparable hot mix asphalt (HMA) mixtures were cored at 5 years for comparison. Cores were evaluated for air-void contents and permeability and were subjected to dynamic modulus, repeated load permanent deformation, and overlay testing. In addition, binder was extracted and recovered for performance grading. Similar properties were found for the WMA and HMA mixtures. One WMA mixture had high dynamic modulus and binder stiffness, but overlay testing did not indicate any tendency for premature cracking. All binders had aged between two and three performance grades above that specified at construction. WMA binders and one HMA binder aged two grades higher, and the remaining two HMA binders aged three grades higher, indicating a likely influence on aging of the reduced temperatures at which the early foamed mixtures were typically produced. Overall results indicated that foamed WMA and HMA mixtures should be expected to perform similarly.

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Resilient Modulus and Dynamic Modulus of Warm Mix Asphalt

GeoCongress 2008 ◽

10.1061/40971(310)125 ◽

2008 ◽

Cited By ~ 4

Author(s):

Shu Wei Goh ◽

Zhanping You

Keyword(s):

Dynamic Modulus ◽

Resilient Modulus ◽

Warm Mix Asphalt

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Optimization of the Laboratory Fabrication of Small Specimens for Asphalt Mixture Performance Testing

Transportation Research Record Journal of the Transportation Research Board ◽

10.1177/0361198118790845 ◽

2018 ◽

Vol 2672 (28) ◽

pp. 438-450 ◽

Cited By ~ 3

Author(s):

Sonja Pape ◽

Kangjin Lee ◽

Cassie Castorena ◽

Y. Richard Kim

Keyword(s):

Dynamic Modulus ◽

Fatigue Testing ◽

Extraction Procedure ◽

Asphalt Mixture ◽

Performance Testing ◽

Cyclic Fatigue ◽

Fatigue Tests ◽

Void Content ◽

Multiple Test ◽

Air Void

The use of 38-mm-diameter small specimens for uniaxial dynamic modulus and cyclic fatigue asphalt mixture performance testing offers a significant opportunity to improve the efficiency of laboratory-fabricated specimen testing because multiple test specimens can be extracted per Superpave gyratory-compacted (SGC) sample. This study seeks to optimize the procedure used for the extraction of small specimens from SGC samples for dynamic modulus and cyclic fatigue tests. To this end, small cylindrical specimens were cored horizontally and vertically from SGC samples and subjected to performance testing. The dynamic modulus and fatigue test results indicate that the effects of anisotropy are minimal. However, all of the horizontally extracted small specimens exhibited fatigue failure at the specimen ends, outside the range of the gauges; the failure was likely due to the peripheral air void gradients in the SGC samples. Therefore, the authors concluded that small specimens should be vertically cored from SGC samples for the laboratory fabrication of small specimens. Specifically, four small specimens were cored vertically from the inner 100 mm of SGC samples where the air void content is relatively uniform. Four mixtures with different nominal maximum aggregate sizes (NMASs) were used to prepare small specimens using the proposed extraction procedure. These specimens were subjected to dynamic modulus and cyclic fatigue testing. The results demonstrate an increase in specimen-to-specimen variability with an increase in NMAS, which also is expected in large specimen testing.

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Cost-Effective Approaches Based on Machine Learning to Predict Dynamic Modulus of Warm Mix Asphalt with High Reclaimed Asphalt Pavement

Materials ◽

10.3390/ma13153272 ◽

2020 ◽

Vol 13 (15) ◽

pp. 3272 ◽

Cited By ~ 4

Author(s):

Dong Van Dao ◽

Ngoc-Lan Nguyen ◽

Hai-Bang Ly ◽

Binh Thai Pham ◽

Tien-Thinh Le

Keyword(s):

Machine Learning ◽

Elastic Modulus ◽

Asphalt Concrete ◽

Dynamic Modulus ◽

Cost Effective ◽

Warm Mix Asphalt ◽

Dynamic Elastic Modulus ◽

Reclaimed Asphalt Pavement ◽

Reclaimed Asphalt

Warm mix asphalt (WMA) technology, taking advantage of reclaimed asphalt pavements, has gained increasing attention from the scientific community. The determination of technical specifications of such a type of asphalt concrete is crucial for pavement design, in which the asphalt concrete dynamic modulus (E*) of elasticity is amongst the most critical parameters. However, the latter could only be determined by complicated, costly, and time-consuming experiments. This paper presents an alternative cost-effective approach to determine the dynamic elastic modulus (E*) of WMA based on various machine learning-based algorithms, namely the artificial neural network (ANN), support vector machine (SVM), Gaussian process regression (GPR), and ensemble boosted trees (Boosted). For this, a total of 300 samples were fabricated by warm mix asphalt technology. The mixtures were prepared with 0%, 20%, 30%, 40%, and 50% content of reclaimed asphalt pavement (RAP) and modified bitumen binder using Sasobit and Zycotherm additives. The dynamic elastic modulus tests were conducted by varying the temperature from 10 °C to 50 °C at different frequencies from 0.1 Hz to 25 Hz. Various common quantitative indications, such as root mean square error (RMSE), mean absolute error (MAE), and correlation coefficient (R) were used to validate and compare the prediction capability of different models. The results showed that machine learning models could accurately predict the dynamic elastic modulus of WMA using up to 50% RAP and fabricated by warm mix asphalt technology. Out of these models, the Boosted algorithm (R = 0.9956) was found as the best predictor compared with those obtained by ANN-LMN (R = 0.9954), SVM (R = 0.9654), and GPR (R= 0.9865). Thus, it could be concluded that Boosted is a promising cost-effective tool for the prediction of the dynamic elastic modulus (E*) of WMA. This study might help in reducing the cost of laboratory experiments for the determination of the dynamic modulus (E*).

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Ageing evolution of foamed warm mix asphalt combined with reclaimed asphalt pavement

Materiales de Construcción ◽

10.3989/mc.2017.04716 ◽

2017 ◽

Vol 7 (080) ◽

pp. 125 ◽

Cited By ~ 3

Author(s):

M. Perez-Martinez ◽

P. Marsac ◽

T. Gabet ◽

S. Pouget ◽

F. Hammoum

Keyword(s):

Mechanical Performance ◽

Fatigue Testing ◽

Complex Modulus ◽

Asphalt Pavement ◽

Apparent Molecular Weight ◽

Warm Mix Asphalt ◽

Infrared Analysis ◽

Reclaimed Asphalt Pavement ◽

Process Technology ◽

Reclaimed Asphalt

The combination of high rates of reclaimed asphalt pavement (RAP) and warm mix asphalt (WMA) technologies is still ambiguous in terms of durability. With the aim of clarifying this issue, a study comparing a hot mix asphalt with a WMA prepared using the foaming process technology. Both mixes contain 50% of RAP and are submitted to a laboratory ageing procedure. The long term related performance of the mixtures is compared by means of complex modulus and fatigue testing. Penetration and ring and ball tests are undertaken on the recovered bitumens, as well as the ageing evolution, characterised by the Fourier Transform Infrared analysis. Finally, the Apparent Molecular Weight Distribution (AMWD) of the binders is calculated from rheological measurements using the δ-method. Results show a relation between ageing evolution and mechanical performance. After ageing, the overall tendencies are similar for both processes.

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