Compaction process tracking for asphalt mixture using discrete element method

Qian, Guoping; Hu, Kaikai; Li, Jue; Bai, Xianping; Li, Ningyuan

doi:10.1016/j.conbuildmat.2019.117478

Cited by 77 publications

(34 citation statements)

References 26 publications

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“…From Figure 10 a, it can be seen that, with an increase in compaction times, the spatial acceleration of IA showed an unstable decreasing trend at the initial stage (less than 60 times), a stable decreasing trend at the middle stage (61–112 times), and a stable state at the late stage (113–160 times). This is because the early stage of compaction is the stage of the transition of the AC-25 asphalt mixture from a loose to a dense state, and the motion state of the IA in this stage is random [ 24 ]. However, with the gradual compaction of asphalt mixture, the active range of the IA is gradually reduced, and the spatial acceleration is in an overall downward trend in this stage.…”

Section: Performance Test Results and Discussion Of Iamentioning

confidence: 99%

A New Method for Compaction Quality Evaluation of Asphalt Mixtures with the Intelligent Aggregate (IA)

Zhang

Wang

2021

Materials

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To provide a new method for the evaluation of the compaction quality of asphalt mixture, a real-time data acquisition and processing system (RDAPS) for the motion state of aggregate with a small volume and high precision is developed. The system consists of an intelligent aggregate (IA), analysis software and hardware equipment. The performance of the IA was tested by regarding data sensitivity, high-temperature resistance, and mechanical properties. A new evaluation method was proposed for evaluating the compaction quality of AC-25 and SMA-25 asphalt mixtures based on an IA. The results show that the best transmission baud rate for the IA was 9600 bps, and the corresponding signal transmission distance was 380 m. Only one IA was needed to complete the state data collection for the aggregate within the asphalt mixture in a circular area, with the IA layout point as the center of the circle and a radius of 5 m. The IA conducted reliable data transmission up to 200 °C; however, its compressive strength decreased with increasing temperature until reaching stability. Traditional aggregate could be replaced by an IA to withstand external forces and internal load transfer. Embedding an IA into AC-25 or SMA-25 asphalt mixtures did not have a significant impact on the original mechanical properties of the mixture. The effect of the gradation type of the asphalt mixture on the IA motion state was not significant. When the compaction degree met the specification requirements, the motion data of the IA did not reach a stable state, and the interlocking effect between aggregates in the asphalt mixture could be further optimized. An evaluation method is proposed based on the IA for the compaction quality of AC-25 and SMA-25 asphalt mixtures with the compaction degree as the main index and the spatial attitude angle and spatial acceleration of the IA as the auxiliary indexes.

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Section: Performance Test Results and Discussion Of Iamentioning

confidence: 99%

A New Method for Compaction Quality Evaluation of Asphalt Mixtures with the Intelligent Aggregate (IA)

Zhang

Wang

2021

Materials

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“…Huang used the principal axis orientation and interlayer distance as evaluation indicators obtained by digital image processing (DIP) and Image-Pro Plus (IPP) software to evaluate the migration characteristics of aggregate particles in asphalt mixtures [10]. Qian traced the air void (AV) content and distribution of aggregates and asphalt mortar in the process of asphalt mixture compaction to capture the mesostructural change characteristics of asphalt mixtures during compaction [11]. Cai characterizes the skeleton characteristics of asphalt mixtures under various cycles of compaction repetitions by introducing coarse aggregate contact points, aggregate inclination and some other indexes based on a digital image processing technique [12].…”

Section: Introductionmentioning

confidence: 99%

Study on Migratory Behavior of Aggregate in Asphalt Mixture Based on the Intelligent Acquisition System of Aggregate Attitude Data

Zhang

2021

Sustainability

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In order to provide a new method to study the migration behavior of coarse aggregates in the compaction process of asphalt mixtures, the “Intelligent Aggregate Attitude Acquisition System (IAS)” is developed based on 3D printing technology and wireless intelligent sensing technology, and the “Intelligent Attitude Aggregate (IAA)” is prepared as the acquisition terminal. The Superpave Gyratory Compaction (SGC) test and the Internet of Things (IOT) wireless sensor technology are combined to collect and analyze the attitude data of an SMA-20 asphalt mixture built in IAA at different compaction stages, and the migration behavior of coarse aggregate in the compaction process is quantitatively characterized. The result shows that the IAA is suitable as a “tracking aggregate” to study the aggregate transfer behavior in asphalt mixtures. The IAA in the upper layer tends to move vertically downward, while the particles in the lower layer tend to move horizontally and spatial rotation in the process of rotating compaction. With the increase in asphalt content, the lubrication effect between aggregate particles is obvious, and the friction resistance of aggregate particles decreases when it is embedded downward. Affected by shear force in the process of rotary compaction, the aggregate particles are easier to overcome friction and cause large horizontal migration and spatial rotation. With the increase in compaction temperature, the viscosity of asphalt binder decreases, and the contact friction between aggregate particles decreases. The asphalt content has a significant effect on the displacement in the horizontal plane Dxoy of the aggregate. The asphalt content and compaction temperature have significant effects on the spatial rotation angle Φ of aggregate, but the asphalt content has a greater impact on it.

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“…The recent researches on resilient behavior are always dependent on the approach of phenomenology, which requires a large number of physical model tests and statistical methods to reveal the changes in its mechanical property [19]. In fact, with limited test conditions, the results obtained in the laboratory test may differ greatly from the actual engineering [20]. Additionally, the complexity and randomness in the mesostructure of SRM are difficult to be accurately described by the continuum mechanical model [21].…”

Section: Introductionmentioning

confidence: 99%

Resilient Properties of Soil-Rock Mixture Materials: Preliminary Investigation of the Effect of Composition and Structure

Qian

Yao

et al. 2020

Materials

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The physical composition and stress state of soil-rock mixture (SRM) materials have a crucial influence on their mechanical properties, and play a vital role in improving the performance of subgrade. To reveal the resilient behavior and mesostructure evolution of SRM materials, triaxial tests and discrete element method (DEM) numerical analysis have been carried out. In the triaxial test section, the mechanical response of SRM materials was investigated by preparing samples under different stress states and physical states and conducting triaxial tests on samples. Simultaneously, a new irregular particle modeling method was developed and applied to the discrete element modeling process to analyze the mesostructure evolution of SRM materials under cycling loading. First, a cyclic triaxial test of SRM material is performed on the SRM material, and the effects of bulk stress, octahedral shear stress and rock content on the resilient modulus of the SRM material are analyzed. It is revealed that the resilient modulus increases with increasing bulk stress and rock content, and decreases with increasing octahedral shear stress. Based on a new resilient modulus prediction model, the relationships among the rock content, stress state and resilient modulus are established. Then, based on an improved DEM modeling method, a discrete element model of the SRM is established, and the influence of rock content on coordination number and mesostructure evolution of the SRM is analyzed. The results show that in SRM materials, the increase of crushed rock changes the mesostructure of the SRM material. With the increase of rock content, the internal contact force changes from “between soil and rock” to “between rocks”, and the skeleton formed in the rocks gradually develops overall stiffness. Under the condition of low stress, the anisotropy of the SRM material is mainly caused by the shape and grade distribution of crushed rock. The induced anisotropy caused by the change of stress state has little effect on its mechanical behavior, which may lead to the greater dispersion of multiple SRM test results.

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Compaction process tracking for asphalt mixture using discrete element method

Cited by 77 publications

References 26 publications

A New Method for Compaction Quality Evaluation of Asphalt Mixtures with the Intelligent Aggregate (IA)

A New Method for Compaction Quality Evaluation of Asphalt Mixtures with the Intelligent Aggregate (IA)

Study on Migratory Behavior of Aggregate in Asphalt Mixture Based on the Intelligent Acquisition System of Aggregate Attitude Data

Resilient Properties of Soil-Rock Mixture Materials: Preliminary Investigation of the Effect of Composition and Structure

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