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UID:3017@i2m.univ-amu.fr
DTSTART;TZID=Europe/Paris:20190628T110000
DTEND;TZID=Europe/Paris:20190628T120000
DTSTAMP:20190613T090000Z
URL:https://www.i2m.univ-amu.fr/evenements/direct-numerical-simulation-of-
 pore-scale-turbulence-multiscale-statistics-and-upscaling/
SUMMARY: (...): Direct numerical simulation of pore-scale turbulence: multi
 scale statistics and upscaling
DESCRIPTION:: Turbulent flows in porous media occur in a wide variety of ap
 plications\, from catalysis in packed beds to heat exchange in nuclear rea
 ctor vessels.  In this talk\,  we will review some of the recent developme
 nts in  characterizing  turbulence  in  porous  media  and  using  the  da
 ta  to  develop  volume  averaged\,  upscaled models.   The  porescale  fl
 ow  physics\,  which  are  important  to  properties  such  as  bulk  mixi
 ng  performance and  permeability\,  are  investigated  in  detail  using 
  direct  numerical  simulation  (DNS)  through  a  periodic face  centered
   cubic  (FCC)  unit  cell\,  covering  inertial  through  fully  turbulen
 t  regime.   This  low  porosity arrangement  of  spheres  is  characteriz
 ed  by  rapid  flow  expansions  and  contractions\,  and  results  an  ea
 rly onset to turbulence.  The simulations are performed using a fictitious
  domain approach [Apte et al\, J. Comp.Physics 2009]\, which uses non-body
  conforming Cartesian grids\, with very high resolution. Results are used 
 to  investigate the structure of turbulence in the Eulerian and Lagrangian
  frames\, the distribution and budget of turbulent kinetic energy\, and th
 e characteristics of vorticity and helicity distribution in complex packed
  beds.In addition\, Lagrangian statistics of scale dependent curvature ang
 le are calculated by tracking a large number of fluid particle trajectorie
 s and compared with homogeneous\, isotropic turbulence to understand the e
 ffects of flow confinement on turbulence in porous media.  A Monte-Carlo b
 ased stochastic model to predict the long-time behavior of curvature angle
 s is developed and shown to correctly predict the asymptotic behavioras  o
 btained  from  DNS.  Finally\,  the  porescale  data  is  used  to  close 
  a  spatially-averaged  upscaled  model. A  Darcy-Forchheimer  type  law  
 is  derived\,  and  a  prior  computation  of  the  permeability  and  For
 chheimer coefficient are presented and compared with existing data.http://
 mime.oregonstate.edu/people/apte
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TZID:Europe/Paris
X-LIC-LOCATION:Europe/Paris
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DTSTART:20190331T030000
TZOFFSETFROM:+0100
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