Discharge Capacity and Clogging Effects in Pervious Concrete: a Finite Volume Modeling Approach
Abstract
Pervious concrete, characterized by its composition of coarse aggregate embedded in cement paste without fine aggregates, creates a network of interconnected pores that enable water flow within the material’s internal structure. This paper presents an analysis of the unsaturated flow behavior within pervious concrete elements specifically designed as entrance filters in sewage systems for pedestrian and light traffic areas. The study employs finite volume modeling techniques, incorporating experimental data obtained from physical tests, to simulate these pervious concrete elements and evaluate their discharge capacity relative to the flow generated by a design storm event. By accurately representing the flow dynamics, valuable insights into the performance and functionality of pervious concrete as an innovative solution for sustainable urban drainage systems are provided. The behavior of water within the porous structure is analyzed through the solution of Richard’s equation, which governs the multiphase flow in porous media. The pervious concrete is considered as an unsaturated homogeneous medium, the water is treated as an incompressible fluid and a capillarity model utilizing the Van Genuchten parameters is incorporated to capture the capillary phenomena occurring within the porous network. The detrimental effects of clogging on the permeability are investigated by simulating pore clogging through the variation of permeability in specific regions, enabling the assessment of its influence on the discharge capacity. The enhanced understanding of the hydraulic performance, unsaturated flow and clogging mechanisms of pervious concrete elements provide critical insights for optimizing their design and implementation in urban drainage systems, contributing to the development of improved stormwater management strategies that promote sustainable and resilient urban environments.
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PDFAsociación Argentina de Mecánica Computacional
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ISSN 2591-3522