A biphasic approach for the study of lift generation in soft porous media

Qianhong Wu, Sridhar Santhanam, Rungun Nathan, Qiuyun Wang

Research output: Contribution to journalArticlepeer-review

12 Scopus citations

Abstract

Lift generation in highly compressible porous media under rapid compression continues to be an important topic in porous media flow. Although significant progress has been made, how to model different lifting forces during the compression process remains unclear. This is mainly because the input parameters of the existing theoretical studies, including the Darcy permeability of the porous media and the viscous damping coefficient of its solid phase, were manually adjusted so as to match the experimental data. In the current paper, we report a biphasic approach to experimentally and theoretically treat this limitation. Synthetic fibrous porous materials, whose permeability were precisely measured, were subsequently exposed to sudden impacts using a porous-walled cylinder-piston apparatus. The obtained time-dependent compression of the porous media, along with the permeability data, was applied in two different theoretical models to predict the pore pressure generation, a plug flow model and a consolidation model [Q. Wu et al., J. Fluid Mech. 542, 281 (2005a)]. Comparison between the theory and the experiments on the pore pressure distribution proved the validity of the consolidation model. Furthermore, a viscoelastic model, containing a nonlinear spring in conjunction with a linear viscoelastic generalized Maxwell mechanical module, was developed to characterize the solid phase lifting force. The model matched the experimental data very well. The paper presented herein, as one of the series studies on this topic, provides an important biphasic approach to characterize different forces that contribute to the lift generation in a soft porous medium under rapid compression.

Original languageEnglish (US)
Article number043602
JournalPhysics of Fluids
Volume29
Issue number4
DOIs
StatePublished - Apr 1 2017

All Science Journal Classification (ASJC) codes

  • Computational Mechanics
  • Condensed Matter Physics
  • Mechanics of Materials
  • Mechanical Engineering
  • Fluid Flow and Transfer Processes

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