Publications published or recently submitted

  1. P. Chandramouli, A. Gronskis, D. Heitz, S. Laizet and E. Mémin, Coarse-grid large eddy simulations in a wake flow with new stochastic small scale models, Computer and Fluid, 168, 2018.
  2. A. Gronskis, C. Robinson, D. Heitz, E. Mémin, A 4DVar PIV-data assimilation for flow spatio-temporaL reconstruction, submitted
  3. P. Chandramouli, E. Mémin , B. Chapron, D. Heitz, and S. Laizet, A stochastic fluid model bridging turbulence inhomogeneity, streaks and wave-current interaction, to be submitted.
  4. P. Chandramouli, E. Mémin , D. Heitz, A very fast 3D Flow reconstruction method from long-sequence 2D cross-plane observations, submitted Experiment in Fluids.
  5. B. Pinier, E. Mémin, S. Laizet, and R. Lewandowski, A model under location uncertainty for the mean velocity in wall bounded flows, submitted, 2018.
  6. A. Cammilleri, G. Artana, E. Mémin, and L. Pastur, Data assimilation of Ginzburg-Landau Equation, in preparation
  7. B. Chapron, P. Dérian, E. Mémin and V. resseguier, Large scale flows under location uncertainty: a consistent stochastic framework, Quart. J. of the Roy. Meteo. Soc., 144 (710), 2018.
  8. V. Resseguier, E. Mémin, B. Chapron, Geophysical flows under location uncertainty, Part I: Random transport and general models, Geophysical & Astrophysical Fluid Dynamics, 2017, 111(3): 149-176, PDF
  9. V. Resseguier, E. Mémin, B. Chapron, Geophysical flows under location uncertainty, Part II: Quasigeostrophic models and efficient ensemble spreading, Geophysical & Astrophysical Fluid Dynamics, 2017, 111(3): 177-208, PDF
  10. V. Resseguier, E. Mémin, B. Chapron, Geophysical flows under location uncertainty, Part III: SQG and frontal dynamics under strong turbulence, Geophysical & Astrophysical Fluid Dynamics, 2017, 111(3): 209-227, PDF
  11. V. Resseguier, E. Mémin, D. Heitz and B. Chapron, Stochastic modeling and diffusion modes for POD models and small-scale flow analysis, J. of Fluid Mech., 828: 888-917, 2017, PDF
  12. S. Kadri-Harouna and E. Mémin, Stochastic representation of the Reynolds transport theorem: revisiting large-scale modeling, Comp. and Fluids, 156, pp.456-469, 2017
  13. Y. Yang and E. Mémin, High-resolution data assimilation through stochastic subgrid tensor and parameter estimation from 4DEnVar, 2017, Tellus A, 69 (1), 2017 PDF

Conferences

  1. A. Gronskis, D. Heitz and E. Mémin, Control of unsteady wake flows using local oscillations of body surface: a data assimilation study, CAN, Rennes, 2018.
  2. A. Gronskis, D. Heitz and E. Mémin, Estimation des efforts sur un cylindre par assimilation de mesures PIV dans son sillage, CFTL, Dourdan 2018.
  3. P. Chandramouli, D. Heitz, S. Laizet and E. Mémin, Variational data assimilation and turbulence modeling, CNA, Rennes, 2018.
  4. A. Gronskis, D. Heitz and E. Mémin, A new hybrid algorithm for variational data assimilation of unsteady wake flow. 2nd Workshop on Data Assimilation & CFD Processing for Particle Image and Tracking Velocimetry, December 13 to 14, 217, Delft, The Netherlands
  5. P. Chandramouli, D. Heitz, E. Mémin, S. Laizet (2017) "A Comparative Study of LES Models Under Location Uncertainty", Congrès Français de Mécanique. Lille, FR.
  6. Pranav Chandramouli, Dominique Heitz, Etienne Mémin, Sylvain Laizet (2017) "Analysis of Models Under Location Uncertainty within the Framework of Coarse Large Eddy Simulation (cLES)", The 16th European Turbulence Conference. Stockholm, SE.

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    Last update Thu Mar 6 11:54:10 2014