Prediction Model on Permeability Coefficient of Porous Asphalt Concrete under Repeated Clogging Based on Void Characteristic Parameters
Publication: Journal of Materials in Civil Engineering
Volume 35, Issue 5
Abstract
Porous asphalt concrete (PAC) is commonly applied in locations with heavy rainfall. However, because of the mix’s characteristics and service environment, it is impossible to ensure the duration of its permeability performance. This paper explores the aspects that influence PAC’s permeability performance. A comprehensive clogging model is also developed, which includes PAC mix parameters. First, three clogging materials were produced. Second, the effect of nominal maximum aggregate size, porosity, and clogging material on PAC’s permeability is discussed. Finally, models are proposed to predict PAC’s clogging factor and clogging times . The results revealed that the remaining PAC mix parameters, except for the nominal maximum aggregate size, were associated strongly with the and . The prediction models established for and in PAC mixes were highly reliable, with correlation values over 0.90 in all cases. In addition, the mixture parameters that had the greatest influence on the clogging factor and clogging times are differed. The uniformity and curvature coefficients influenced the clogging factor the most, while the initial permeability coefficient affected the clogging times the most.
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Data Availability Statement
All data, models, and code generated or used during the study appear in the published article.
Acknowledgments
The authors gratefully acknowledge the financial support by the National Natural Science Foundation of China (51408287, 51668038, and 51868042), the Distinguished Young Scholars Fund of Gansu Province (1606RJDA318), the Natural Science Foundation of Gansu Province (1606RJDA318), Industry Support and Guidance Project by University and College in Gansu Province (2020C-13), Foundation of A Hundred Youth Talents Training Program of Lanzhou Jiaotong University, and Special Funds for Guiding Local Scientific and Technological Development by the Central Government (22ZY1QA005).
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Received: May 24, 2022
Accepted: Aug 31, 2022
Published online: Feb 27, 2023
Published in print: May 1, 2023
Discussion open until: Jul 27, 2023
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