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3D reconstruction of moisture damage resulted volumetric changes in porous asphalt mixture
Highlights MIST was used to simulate actual field moisture damage. Distinctly volumetric changes were detected by CT and 3D reconstruction. Expansion of interconnected pores was observed after moisture damage. Moisture failure clearly identified by threshold segmentation. High-viscosity asphalt can effectively improve moisture resistance.
Abstract Porous asphalt pavements are widely used to make moisture penetrate pavement surface faster than dense-graded mixtures, thus improving driving safety. Long-term interaction with moisture makes its moisture susceptibility deserve intensive attention. Methods currently used to detect moisture susceptibility do not factually simulate the mechanism of moisture damage in pumping action. Meanwhile, there is less concern about the variation in volumetric properties, such as air void content, distribution, interconnectivity of pores and asphalt volume after moisture damage. This study simulated field moisture damage with different hydrodynamic pressures by MIST (Moisture Induced Sensitivity Tester) to detected evolution of volumetric properties of porous asphalt mixture. X-ray Computed Tomography and Mimics software were used for acquiring internal structure, processing 3D reconstruction and analysis of asphalt mixture. Resilient modulus test was conducted to evaluate moisture damage degree and moisture resistance of SBS and HVA (high viscosity modified asphalt) mixtures were compared. The results show that distinctly growths of air voids and moisture damage degree were found when MIST-conditioning pressure increased from 276 kPa to 414 kPa for SBS mixtures. Extension of pores for SBS-414 kPa is most obvious and high-viscosity asphalt can effectively improve moisture resistance. Hydraulic pressure can significantly influence the moisture damage degree, so it should be selected according to the actual traffic conditions instead of constant default.
3D reconstruction of moisture damage resulted volumetric changes in porous asphalt mixture
Highlights MIST was used to simulate actual field moisture damage. Distinctly volumetric changes were detected by CT and 3D reconstruction. Expansion of interconnected pores was observed after moisture damage. Moisture failure clearly identified by threshold segmentation. High-viscosity asphalt can effectively improve moisture resistance.
Abstract Porous asphalt pavements are widely used to make moisture penetrate pavement surface faster than dense-graded mixtures, thus improving driving safety. Long-term interaction with moisture makes its moisture susceptibility deserve intensive attention. Methods currently used to detect moisture susceptibility do not factually simulate the mechanism of moisture damage in pumping action. Meanwhile, there is less concern about the variation in volumetric properties, such as air void content, distribution, interconnectivity of pores and asphalt volume after moisture damage. This study simulated field moisture damage with different hydrodynamic pressures by MIST (Moisture Induced Sensitivity Tester) to detected evolution of volumetric properties of porous asphalt mixture. X-ray Computed Tomography and Mimics software were used for acquiring internal structure, processing 3D reconstruction and analysis of asphalt mixture. Resilient modulus test was conducted to evaluate moisture damage degree and moisture resistance of SBS and HVA (high viscosity modified asphalt) mixtures were compared. The results show that distinctly growths of air voids and moisture damage degree were found when MIST-conditioning pressure increased from 276 kPa to 414 kPa for SBS mixtures. Extension of pores for SBS-414 kPa is most obvious and high-viscosity asphalt can effectively improve moisture resistance. Hydraulic pressure can significantly influence the moisture damage degree, so it should be selected according to the actual traffic conditions instead of constant default.
3D reconstruction of moisture damage resulted volumetric changes in porous asphalt mixture
Cui, Peide (author) / Wu, Shaopeng (author) / Xiao, Yue (author) / Niu, Yunya (author) / Yuan, Gaoming (author) / Lin, Juntao (author)
2019-08-05
Article (Journal)
Electronic Resource
English
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