Use of fine aggregate matrix for computational modeling of low temperature fracture of asphalt concrete

2018 ◽  
Vol 51 (6) ◽  
Author(s):  
Jia-Liang Le ◽  
Rebecca Hendrickson ◽  
Mihai O. Marasteanu ◽  
Mugurel Turos
Keyword(s):  
Low Temperature ◽  
Computational Modeling ◽  
Asphalt Concrete ◽  
Fine Aggregate ◽  
Temperature Fracture ◽  
Fine Aggregate Matrix

Factors Study in Low-Temperature Fracture Resistance of Asphalt Concrete

2010 ◽  
Vol 22 (2) ◽  
pp. 145-152 ◽  
Author(s):  
Xinjun Li ◽  
Mihai O. Marasteanu ◽  
Andrea Kvasnak ◽  
Jason Bausano ◽  
R. Christopher Williams ◽  
...  
Keyword(s):  
Low Temperature ◽  
Asphalt Concrete ◽  
Fracture Resistance ◽  
Temperature Fracture

Experimental Testing and Analysis Procedure to Determine the Apparent Film Thickness of Asphalt Binder in Fine Aggregate Matrix Mixtures

2021 ◽  
Vol 2675 (7) ◽  
pp. 166-179
Author(s):  
Lucas Henrique Vieira ◽  
Thiago Delgado de Souza ◽  
Alexis Jair Enríquez-León ◽  
Francisco Thiago Sacramento Aragão ◽  
Otávio da Fonseca Martins Gomes ◽  
...  
Keyword(s):  
Film Thickness ◽  
Asphalt Concrete ◽  
Experimental Testing ◽  
Asphalt Binder ◽  
Analysis Procedure ◽  
Fine Aggregate ◽  
Concrete Mixtures ◽  
Proper Design ◽  
Fine Aggregate Matrix ◽  
Imagej Software

The fine aggregate matrix (FAM) is an important constituent of an asphalt concrete mixture; the FAM is where some key damage phenomena such as cracking start and propagate. The proper design and fabrication of isolated FAM testing samples that are representative of the material existing within asphalt concrete mixtures requires the objective determination of key characteristics such as the apparent film thickness (FT) of the asphalt binder and the specific surface area of the aggregates. These relevant parameters facilitate the estimation of the binder content. This study presents an experimental testing and analysis protocol to determine the apparent FT that covers particles of fine aggregate in FAM mixtures. The method is based on tests using a scanning electron microscope and a digital image analysis procedure using the open-source Fiji/ImageJ software. The results indicated that apparent FT ranged between 0.5 µm and 30 µm. An additional validation effort was pursued and demonstrated the applicability of the proposed methodology, which can provide meaningful information to improve volumetric-based FAM mix design methods and generate materials that are more representative of those existing in the asphalt concrete mixtures.

Testing and Modeling of Fine Aggregate Matrix and Its Relationship to Asphalt Concrete Mix

2015 ◽  
Vol 2507 (1) ◽  
pp. 120-127 ◽  
Author(s):  
Padmini Gudipudi ◽  
B. Shane Underwood
Keyword(s):  
Asphalt Concrete ◽  
Mechanical Response ◽  
Strong Relationship ◽  
Axial Direction ◽  
Unique Element ◽  
Fine Aggregate ◽  
Length Scales ◽  
Multiple Length Scales ◽  
Fine Aggregate Matrix ◽  
Term Performance

The study of the fundamental properties of asphalt concrete (AC) can be used to improve and maximize the performance potential of these materials. In this paper, the fundamental approach is examined by coupling its essential hypothesis to an investigation of AC across multiple length scales. Asphalt and aggregate materials from the state of Arizona were used to prepare fine aggregate matrix (FAM) and AC samples. Laboratory tests on these materials were conducted to investigate the modulus and damage characteristics for two binder types. A comparison of mechanical response across length scales is not new, and the unique element of this study is testing both materials in the axial direction (tension–compression) for both modulus and fatigue. A strong relationship between these two materials was observed; this relationship suggests that tests on FAM samples can provide much needed insight in understanding the behavior of AC for various conditions. The study also investigated upscaling of the FAM properties to those of the AC mixture through a homogenized continua approach. Multiple upscale models were evaluated in this upscaling process, but the chosen method produced the best overall match to experimental data. The findings from this modeling effort were also used to upscale the behaviors of FAM to identify the fatigue characteristics of AC mixtures and evaluate the long-term performance of the material.

Use of Fine Aggregate Matrix Experimental Data in Improving Reliability of Fatigue Life Prediction of Asphalt Concrete: Sensitivity of This Approach to Variation in Input Parameters

2017 ◽  
Vol 2631 (1) ◽  
pp. 65-73 ◽  
Author(s):  
Padmini P. Gudipudi ◽  
B. Shane Underwood
Keyword(s):  
Experimental Data ◽  
Fatigue Life ◽  
Asphalt Concrete ◽  
Failure Criteria ◽  
Fine Aggregate ◽  
Performance Predictions ◽  
Input Parameters ◽  
Fine Aggregate Matrix ◽  
Input Variables ◽  
Life Predictions

Asphalt concrete (AC) material performance has been assessed by numerous mechanistic models over the years. Often these models are purported to enable more accurate prediction of the pavement service life than existing empirical models. Most of these models use fundamental material properties, which are obtained by performing experiments on the materials, as input variables. However, by introducing more variables, these models create the potential for greater uncertainty because the variables have inherent variability. Variations observed in these input parameters affect the reliability of any resulting performance predictions. In an effort to improve the reliability of fatigue life predictions, experimental data from the fine aggregate matrix (FAM) phase was used in this study for predicting fatigue life. From the comparative assessment, it was observed that the reliability of fatigue life predictions was improved by more than 50% when data from the FAM phase rather than AC data were used. An upscaling procedure was used in predicting the AC material fundamental properties and then in performing a reliability analysis with the predicted data. More reliable fatigue prediction results were also observed when the AC predicted data were used; however, this improvement was not as good as that in the FAM phase. A parametric sensitivity analysis was performed to determine whether variation in any one parameter resulted in a greater impact on the resultant reliability than did variation of other parameters. From the analysis, it was observed that the variation of the modulus parameter affected the reliability predictions more than did the variation of the other input parameters considered in this study, regardless of the model failure criteria used.

Using Predictive Models to Estimate the Properties of Binders in Reclaimed Asphalt Pavement Mixes using Fine Aggregate Matrix Mix Testing

2019 ◽  
Vol 2673 (6) ◽  
pp. 501-511 ◽  
Author(s):  
Mohamed Elkashef ◽  
Shawn S. Hung ◽  
David Jones ◽  
John Harvey
Keyword(s):  
Predictive Models ◽  
Asphalt Concrete ◽  
Asphalt Pavement ◽  
Reliable Estimate ◽  
Reclaimed Asphalt Pavement ◽  
Fine Aggregate ◽  
Current Form ◽  
Reclaimed Asphalt ◽  
Shear Moduli ◽  
Fine Aggregate Matrix

A number of predictive models, such as the Hirsch and Al-Khateeb models, have been proposed to determine the properties of asphalt binders from asphalt concrete mix testing results. Fine aggregate matrix (FAM) mix testing can also provide useful insights into the likely performance of asphalt concrete mixes. Consequently, FAM mix testing can be an appropriate means of assessing the predictive power of these models. In this study, FAM mixes prepared with two virgin binders, PG58-28 and PG64-16, and then with different percentages of reclaimed asphalt pavement (RAP) were tested to determine their stiffness and phase angle using temperature-frequency sweeps in a dynamic shear rheometer. The data from the control mixes with no RAP were used along with the rheological properties of the virgin binders to fit the Hirsch and Al-Khateeb models. The fitted models were then used to estimate the properties of the binders in the 15% and 25% RAP FAM mixes. A comparison of the estimated binder properties with the measured binder properties clearly indicated that the fitting parameters are binder dependent. Moreover, the estimated binder moduli deviate from the measured moduli, particularly at high temperatures. The estimated complex shear moduli from the model were found to be consistently higher than the measured shear moduli values of the chemically extracted binders. It was thus concluded that the predictive models studied, in their current form, fail to provide a reliable estimate of the binder properties in mixes containing RAP.

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