Journal of Jilin University(Engineering and Technology Edition) ›› 2022, Vol. 52 ›› Issue (6): 1375-1385.doi: 10.13229/j.cnki.jdxbgxb20210062

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Dynamic modulus of porous asphalt concrete and its prediction model

Zhao-yi HE1(),Jin-feng LI1,Wen ZHOU2,Zhi-tao GUAN1   

  1. 1.School of Civil Engineering，Chongqing Jiaotong University，Chongqing 400074，China
    2.Guangxi Communications Investment Group Corporation Ltd. ，Nanning 530022，China
  • Received:2021-01-22 Online:2022-06-01 Published:2022-06-02

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Abstract:

The dynamic modulus of dense gradation asphalt mixture AC-13， stone mastic asphalt SMA-13 and six kinds of porous asphalt concrete （PAC-16， PAC-13a， PAC-13b， PAC-13c， PAC-10 and PAC-5） were tested at different temperatures and different loading frequencies. The dynamic modulus of asphalt mixture are respectively increased with the loading frequency increasing and decreased with temperature increasing， and the changing amplitudes are both gradually reduced. Compared with PAC-13b with 20.3% void content， the average values of 196.8% and 125.1% increase in dynamic modulus for SBS asphalt AC-13 and SMA-13，respectively. For the porous asphalt mixtures with closely void content， a slightly reduction of dynamic modulus is observed for porous asphalt mixture with the increase of nominal maximum particle size. When the mixtures have same the nominal maximum particle size， the dynamic modulus of porous asphalt mixture is increased about 15.8% with the reduction of void content 1%. According to the time-temperature superposition principle， the expression of the shift factor is established to describe the effect of temperature， and the master curves of different asphalt mixtures are modeled， calculated and plotted by Sigmoidal function. Various factors， such as loading frequency， testing temperature， asphalt binder viscosity， volumetric properties of asphalt mixture and aggregate gradation， are considered to develop the predictive dynamic modulus equation for different asphalt mixture. The results show that the predicted values are in good agreement with the measured results， indicating that the predicted dynamic modulus model can be applied in structure design and analysis of asphalt pavement.

Key words: civil engineering, porous asphalt concrete, dynamic modulus, temperature-time dependent, master curve, prediction model

CLC Number: 

  • U414

Fig.1

Aggregate gradation composition of asphalt mixtures"

Fig.2

Prepared specimens"

Fig.3

Dynamic modulus measuring instrument"

Fig.4

Phase lag between sinusoidal stressand recoverable strain"

Fig.5

Relationship between dynamic modulus and loading frequency under different temperatures"

Fig.6

Relationship between dynamic modulus and temperature under different loading frequencies"

Fig.7

Compared with PAC-13， the increase rate of dynamic modulus of AC-13 and SMA-13 mixtures"

Fig.8

Compared with PAC-5， the increase rate of dynamic modulus of PAC-10， PAC-13b and PAC-16 mixtures"

Fig.9

Compared with PAC-13c， the increase rateof dynamic modulus of PAC-13a andPAC-13b mixtures"

Fig.10

Dynamic modulus of 70# and SBS modifiedasphalt AC-13 mixtures under loadingfrequencies of 10 Hz"

Fig.11

Compared with 70# asphalt， the increaserate of dynamic modulus of SBS modifiedasphalt AC-13 mixtures"

Table 1

Constant coefficient of dynamic master curves"

级配类型δαβγbR2
70#沥青AC-131.8042.853-0.3547-0.53210.31280.9980
SBS沥青AC-132.1082.519-0.2656-0.52030.30340.9993
SMA-132.0762.487-0.1469-0.51280.29360.9993
PAC-161.2303.142-0.3875-0.47240.32600.9995
PAC-13a1.2993.197-0.4899-0.40930.32230.9994
PAC-13b1.1653.161-0.4101-0.48600.29160.9996
PAC-13c1.0753.083-0.4273-0.50560.28970.9998
PAC-101.1573.019-0.4005-0.47050.31410.9992
PAC-51.1563.085-0.4384-0.44530.30710.9994

Fig.12

Dynamic modulus master curves of differentasphalt mixture"

Fig.13

Comparison between the measured andpredicted dynamic modulus fordifferent asphalt mixture"

Fig.14

Comparison between the measured and thepredicted dynamic modulus for reported in other literatures"

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