Probabilistic approach to characterise laboratory rutting behaviour of asphalt concrete mixtures

Singh, Priyansh; Swamy, Aravind Krishna

doi:10.1080/10298436.2018.1480780

Cited by 16 publications

(5 citation statements)

References 20 publications

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“…In this study, a total of 33 asphalt mixes of varying binder grades, aggregate gradation, and RAP content were collected from different parts of New Mexico according to AASHTO T 168 ( 32 ) standard specification. Table 1 summarizes the properties of the collected mixes.…”

Section: Methodsmentioning

confidence: 99%

New Model for Predicting Rutting Performance of Superpave Asphalt Mixes

Hasan

Tarefder

2022

Transportation Research Record: Journal of the Transportation R

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This study presents a new model for predicting rutting performance and stripping characteristics of Superpave asphalt concrete (AC) mixes from laboratory Hamburg Wheel Tracking Device (HWTD) test data. A total of 33 AC mixes were used and tested for HWTD to determine the rutting and stripping susceptibility of the mixes. The combined Franken–power approach was used to fit the rut data. The pertinent regression coefficients were then correlated to the mix’s physical and volumetric properties, that is, binder grade, reclaimed asphalt pavement content, effective asphalt content, voids in mineral aggregate, and aggregate gradation. A logistic regression analysis was employed in the model to capture the stripping characteristic of the mixes. The developed model was validated with a new set of HWTD test data. The model was observed to be capable of predicting the rutting and stripping characteristics of the AC mixes, which agreed reasonably well with laboratory test results. Therefore, the proposed model could be used for mix screening purposes at the mix design stage to avoid the significant consequences of failure in the field, and as a tool to determine rutting performance when laboratory testing is not feasible.

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Section: Methodsmentioning

confidence: 99%

New Model for Predicting Rutting Performance of Superpave Asphalt Mixes

Hasan

Tarefder

2022

Transportation Research Record: Journal of the Transportation R

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“…Modeling history-dependent nature is still an issue with these models. There are other empirical models, such as the Zhou and Scullion three-stage model, Francken model, and cubic equation model (3)(4)(5). These models depict the relation between strain and number of cycles, and they do not consider the effect of other independent variables affecting the strain.…”

Section: Literature Reviewmentioning

confidence: 99%

System Identification Framework for Modeling of Static Creep and Dynamic Creep Behavior of Dense-Graded Asphalt Mixtures

2023

Transportation Research Record: Journal of the Transportation R

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The response of two dense-graded asphalt concrete (AC) mixtures under static and dynamic creep tests conducted in compression is modeled using the principles of the system identification framework in this study. The AC materials under static and dynamic creep loading conditions exhibit complex behavior patterns such as history dependency, plasticity, and temperature dependency. It is desired to formulate a constitutive model describing these complex phenomena. The empirical approach is outside the scope of this study. A viscoelastic continuum damage model requires individual experimentation to characterize linear and damage behavior. A viscoplastic model requires incremental deviator stress for plastic deformation. Both static and dynamic creep tests do not satisfy this condition. Therefore, the “system identification” approach is used in this study. Two methods of system identification approach—that is, black box and grey box modeling—are adopted to characterize static and dynamic creep behavior of AC. Of these two models under consideration, the black box models were versatile in modeling complex loading situations with a high degree of accuracy but lacked physical interpretation. While the grey box models have a physical interpretation, they are not as versatile as black box models.

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“…Prior research used the Hamburg wheel tracking test and dynamic stability test to examine rutting features of flexible pavement [35]- [39]. However, because the asphalt concrete (AC) mixtures were placed in a rigid steel or hard plastic mold, the middle layer, bottom layer, and base course had no bearing on the rutting performance, which reduced it to a characteristic of the asphalt concrete material rather than the pavement structure.…”

Section: Fig 2 -Cross-section Of Rutting or Permanent Deformation [13]mentioning

confidence: 99%

Permanent Deformation Characteristics of Flexible Pavement Under Palm Oil Freight Truck Loading

Setiawan¹

2023

IJIE

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Most of previous studies employed dynamic stability test and Hamburg wheel tracking test to investigate permanent deformation characteristics of asphalt concrete (AC) layer. However, the permanent deformation performance only focuses on the surface course and neglected the influence of middle layer and base course. The present study investigates the permanent deformation characteristics of four (4) different configurations of flexible pavement and analyzes the contribution of AC surface and AC base course to the total permanent deformation of AC layer as the response to various truck’s speed, hauling loads, and loading cycles. Finite element modeling was performed to evaluate critical locations below the tire tread of single unit two-axles truck with the greatest magnitude of permanent deformation and to determine the optimum configuration of flexible pavement by considering the linear viscoelastic behavior of two types of AC mixtures. It can be concluded that the largest permanent deformation is measured below the right edge of the outer tire. The contribution of AC surface course on the total permanent deformation due to the increase in truck’s speed is only about 14.81% to 16.39%, while the contribution of AC surface course on the total permanent deformation due to the increase in truck’s hauling loads as well as the increase in the number of passing trucks is only around 14.76% to 16.44%. On the other hand, the contribution of AC base course on the total permanent deformation due to the increase in truck’s speed from is reaching 83.61% to 85.19%, while the contribution of AC base course on the total permanent deformation due to the increase in truck’s hauling loads as well as the increase in the number of passing trucks is achieving 83.56% to 85.24%.

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Probabilistic approach to characterise laboratory rutting behaviour of asphalt concrete mixtures

Cited by 16 publications

References 20 publications

New Model for Predicting Rutting Performance of Superpave Asphalt Mixes

New Model for Predicting Rutting Performance of Superpave Asphalt Mixes

System Identification Framework for Modeling of Static Creep and Dynamic Creep Behavior of Dense-Graded Asphalt Mixtures

Permanent Deformation Characteristics of Flexible Pavement Under Palm Oil Freight Truck Loading

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