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• W2018555332 endingPage "176" @default.
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• W2018555332 abstract "Permeable pavements provide a frictional surface for vehicles during rainfall runoff and function as a porous infrastructure interface, allowing the infiltration and evaporation of rainfall runoff, as well as treatment of pollutants when designed for solute and particulate separation. The hydraulic conductivity (k sat ) of permeable pavement is an important hydraulic property. A series of empirical and pore structure models using constant head and pore-based measurements, including total porosity (φ t ), effective porosity (φ e ), and pore size distribution indices generated through X-ray tomography (XRT) were used to study permeable pavement. XRT results indicate that the pore matrix is heterodisperse, with φ t ≠ φ e . Results indicate that the traditional models based on a simple pore structure do not reproduce measured k sat values. More complex pore structure models, even with modification from the original form, gave better results. A modified Kozeny-Kovàcs model was used to reproduce the measured k sat values. The modified model introduces φ e and the characteristic pore diameter (D e ) instead of φ t and specific surface area, respectively. Such permeable pavement pore structure parameters with the modified Kozeny-Kovàcs model can be predicted. These results can be useful in the design stage of permeable pavement when a target value of k sat is desired to obtain both friction benefits to improve vehicle safety in wet conditions and to control the infiltration-evaporation of rainfall. The k sat results are combined with continuous simulation modeling using historical rainfall for a Cincinnati, Ohio, highway site on I-75 to provide results illustrating permeable pavement as a low impact development infrastructure component in the highway environment." @default.
• W2018555332 created "2016-06-24" @default.
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• W2018555332 date "2010-01-01" @default.
• W2018555332 modified "2023-09-24" @default.
• W2018555332 title "Application of Kozeny–Kovàcs Model to Predict the Hydraulic Conductivity of Permeable Pavements" @default.
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• W2018555332 doi "https://doi.org/10.3141/2195-17" @default.
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