Full-scale field testing on a highway composite pavement dynamic responses

Chen, Xiaobin; Zhang, Jiasheng; Wang, Xuan

doi:10.1016/j.trgeo.2015.05.002

Cited by 20 publications

(9 citation statements)

References 21 publications

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“…From the table, it is observed that the peak values of longitudinal strain in the asphalt pavement structure decrease with increasing truck speed under reinforced and unreinforced conditions. Based on the analysis of previous studies (25)(26)(27), the reason for the decreasing regularity of the peak values is probably the low natural frequency of the asphalt pavement. When the truck is running at low speed, the dominant frequency of vehicle loading is close to the natural frequency of asphalt pavement, so the vibration of the pavement is amplified.…”

Section: Discussion On Dynamic and Static Test Resultsmentioning

confidence: 98%

“…As the asphalt mixture is a viscoelastic material, the higher the vehicle speed, the smaller the effect on the asphalt layer. In other words, the increase in speed is equivalent to the reduction of the load ( 25 ). The vehicle speed, therefore, increases and the reinforcement effect decreases.…”

Section: Discussion On Dynamic and Static Test Resultsmentioning

confidence: 99%

“…Before installation, the KM-HAS strain gages were placed centrally over the prepared fine asphalt mixture bed at predetermined locations, as shown in Figure 4 a . Willis et al ( 22 ) and Chen X et al ( 25 ) highlighted that the longitudinal strain has more sensibility than the transverse strain at the same location of asphalt pavement, so the KM-HAS strain gages were only used to monitor the longitudinal strain to reduce the workload and cost.…”

Section: Field Trial Programmentioning

confidence: 99%

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Full-Scale Field Investigation of Asphalt Pavements Reinforced with Geocells

Wang

Zhang

Zhu

et al. 2020

Transportation Research Record: Journal of the Transportation R

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Based on full-scale field trials, this study investigated the mechanical properties of geocell-reinforced asphalt pavements. The field site is a four-lane highway in Hubei province in China. The dynamic load tests were performed for the geocell-reinforced and unreinforced pavement under three different conditions of axle loads and running speeds. The static load tests were carried out under three different axle loads which were the same as the dynamic load tests. The dynamic and static responses were studied in relation to the peak of the longitudinal strain, creep strain, and the improvement factors. Field trial results revealed that the longitudinal strain peak value of the pavement structure reinforced by Polypropylene geocell was significantly reduced in comparison with the pavement response without geocell. In addition, the reinforcement system had a certain inhibiting effect on the creep strain and the improvement factor increased with increasing axle load and decreased with increasing speed. Under 100 kN axle load, the improvement factors were 0.78, 0.68, 0.54, and 0.39 at speeds of 0, 20, 40, and 60 km/h. Under 150 kN axle load, the improvement factors were 0.96, 0.89, 0.75, and 0.61 at speeds of 0, 20, 40, and 60 km/h. Under 200 kN axle load, the improvement factors are 1.21, 1.1, 0.97, and 0.79 at speeds of 0, 20, 40, and 60 km/h. This research helps to provide a new and effective method of asphalt pavement reinforcement.

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Section: Discussion On Dynamic and Static Test Resultsmentioning

confidence: 98%

Section: Discussion On Dynamic and Static Test Resultsmentioning

confidence: 99%

Section: Field Trial Programmentioning

confidence: 99%

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Full-Scale Field Investigation of Asphalt Pavements Reinforced with Geocells

Wang

Zhang

Zhu

et al. 2020

Transportation Research Record: Journal of the Transportation R

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“…Many researchers have investigated pavements' mechanical responses with several methods, such as field tests [7][8][9][10][11][12][13][14], theoretical analysis [15][16][17], and finite-element method simulations [4,9,[14][15][16][17][18][19][20][21][22][23][24][25][26]. Firstly, some research has studied the pavement responses through field testing.…”

Section: Introductionmentioning

confidence: 99%

A Study on the Design Depth of Permeable Road Pavement through Dynamic Load Experiment

2022

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This study investigated vertical strain and stress through a dynamic load experiment at the testing area of Ke-Da Road, Pingtung, Taiwan. A thirty-five-ton truck was moved at constant speeds of 40, 60, and 80 km/h to simulate heavy load conditions to study the mechanical variations. From the results, it was found that the strain and stress curves of the permeable road pavement showed asymmetry due to the viscoelastic property of the open-grade friction course. The results showed that vertical strains and vertical stresses of permeable road pavement were greatly affected by the axle configuration and the change in traffic speed. Furthermore, to propose the design thickness of a permeable road pavement, the pavement strain and stress were modelled with respect to depth using regression based on these collected data. According to the stress regression models and considering the construction uncertainty, the recommend design depth of a permeable pavement is 30 cm. The findings of this study would be helpful in determining the permeable road pavement depth when subjected to heavy traffic load, and the material combination of open-graded friction concrete, porous asphalt concrete, and permeable cement concrete was proposed in this study during the design period.

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“…Flexible pavement responses to traffic loadings are mainly affected by the properties of the materials [20]. A variety of three-dimensional (3-D), finite element simulations have been developed to analyse the responses of flexible pavements [21][22][23][24][25][26].…”

Section: Introductionmentioning

confidence: 99%

A viscoplastic model for permanent deformation prediction of reinforced cold mix asphalt

Shanbara

Ruddock

Atherton

2018

Construction and Building Materials

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A reliable viscoplastic model of natural and synthetic fibres reinforced cold bitumen emulsion mixture is developed and applied to characterize the rutting behaviour of asphalt pavement by using finite element analysis. It is indicated that the traffic load parameters such as temperature, static loading condition and vehicular speed not only affects the rutting depth, it accelerates the rutting rate, causing the pavement earlier enter into rutting failure with shortened service life. Several finite element models (FEM) have been developed to simulate the behaviour of hot mix asphalts (HMAs), but none exists for cold mix asphalt (CMA) reinforced by natural and synthetic fibres. This research presents the first three dimension (3-D), finite element model (FEM) to assess the viscoplastic behaviour of reinforced CMA mixtures. The model is also able to predict rutting (permanent deformation) of asphalt mixtures under different traffic and environmental loadings, traditional HMA used as a comparison. The enhancement of the performance of CMA mixtures against permanent deformation using finite element software (ABAQUS) was validated by comparing the models' predictions with measurements from wheel-tracking tests at different temperatures (45°C and 60°C). A very good level of agreement 2 was found between the rutting predicted by the model and the experimental test. The results show that the finite element model can successfully predict rutting of flexible pavements under different temperatures and wheel loading conditions. Finally, the natural and synthetic fibres reinforced CMA mixtures are much more effective at resisting permanent deformation damage than conventional cold and hot asphalt mixtures.

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Full-scale field testing on a highway composite pavement dynamic responses

Cited by 20 publications

References 21 publications

Full-Scale Field Investigation of Asphalt Pavements Reinforced with Geocells

Full-Scale Field Investigation of Asphalt Pavements Reinforced with Geocells

A Study on the Design Depth of Permeable Road Pavement through Dynamic Load Experiment

A viscoplastic model for permanent deformation prediction of reinforced cold mix asphalt

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