Sub-particle-scale investigation of seepage in sands
| Autor: | Simon J. Carr, Catherine O'Sullivan, Way Way Sim, H. F. Taylor |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2017 |
| Předmět: |
Technology
CONSTRICTION SIZE Water flow POROUS-MEDIA FLOW IMAGES 0211 other engineering and technologies 02 engineering and technology Computational fluid dynamics Sands 010502 geochemistry & geophysics PORE Geological & Geomatics Engineering 01 natural sciences Seepage Permeability 0905 Civil Engineering Physics::Geophysics Hydraulic head TORTUOSITY 0999 Other Engineering Engineering Hydraulic conductivity Geotechnical engineering Engineering Geological 0503 Soil Sciences Geosciences Multidisciplinary Z661 021101 geological & geomatics engineering 0105 earth and related environmental sciences Civil and Structural Engineering Permeameter Science & Technology SIZE DISTRIBUTIONS business.industry Geology Geotechnical Engineering and Engineering Geology Laboratory tests (IGC: D04/E13) Volumetric flow rate MODEL Permeability (earth sciences) Flow velocity Numerical modelling Physical Sciences SIMULATION business |
| ISSN: | 0038-0806 |
| Popis: | While seepage poses significant challenges to many geotechnical projects and hydraulic conductivity is a key soil property, the fundamental pore-scale understanding of the water flow in soil is poor. The seepage velocities considered in geotechnical engineering are area-averaged flow rates and their relation to the actual fluid velocity is unclear. Some of the predictive formulae for sand currently used in engineering practice were developed using simplified particle-scale analytical models whose validity is not well-established. Recent advances in modelling and imaging enable these uncertainties associated with seepage to be addressed and this paper proposes a first principles simulation approach in which the flow in the void space is modelled by applying Computational Fluid Dynamics (CFD) to void geometries obtained using X-ray micro-Computed Tomography (microCT). The model was verified by comparing it to hydraulic conductivity data from laboratory permeameter tests on the same materials. The generated data provide significant sub-particle-scale insight into fluid velocities and head loss. The results are used to show that the existing models for predicting hydraulic conductivity struggle to account for the full range of particle variables and fail to explain the true governing variables, which relate to the micro-scale properties of the void space. |
| Databáze: | OpenAIRE |
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