Bibliography
Major publications by the team in recent years
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1K. Burrage, J. Erhel.
On the performance of various adaptive preconditioned GMRES, in: Numerical Linear Algebra with Applications, 1998, vol. 5, pp. 101-121. -
2J. Carrayrou, J. Hoffmann, P. Knabner, S. Kräutle, C. De Dieuleveult, J. Erhel, J. Van der Lee, V. Lagneau, K. Mayer, K. MacQuarrie.
Comparison of numerical methods for simulating strongly non-linear and heterogeneous reactive transport problems. The MoMaS benchmark case, in: Computational Geosciences, 2010, vol. 14, no 3, pp. 483-502. -
3T. Chacón-Rebollo, R. Lewandowski.
Mathematical and Numerical Foundations of Turbulence Models and Applications, Modeling and Simulation in Science, Engineering and Technology, Birkhäuser Basel, 2014. -
4T. Corpetti, D. Heitz, G. Arroyo, E. Mémin, A. Santa-Cruz.
Fluid experimental flow estimation based on an optical-flow scheme, in: Experiments in fluids, 2006, vol. 40, pp. 80–97. -
5J.-R. De Dreuzy, A. Beaudoin, J. Erhel.
Asymptotic dispersion in 2D heterogeneous porous media determined by parallel numerical simulations, in: Water Resource Research, 2007, vol. 43, no W10439, doi:10.1029/2006WR005394. -
6A. Gronskis, D. Heitz, E. Mémin.
Inflow and initial conditions for direct numerical simulation based on adjoint data assimilation, in: Journal of Computational Physics, 2013, vol. 242, pp. 480-497. [ DOI : 10.1016/j.jcp.2013.01.051 ]
http://www.sciencedirect.com/science/article/pii/S0021999113001290 -
7D. Heitz, E. Mémin, C. Schnoerr.
Variational Fluid Flow Measurements from Image Sequences: Synopsis and Perspectives, in: Experiments in fluids, 2010, vol. 48, no 3, pp. 369–393. -
8H. Hoteit, J. Erhel, R. Mosé, B. Philippe, P. Ackerer.
Numerical Reliability for Mixed Methods Applied to Flow Problems in Porous Media, in: Computational Geosciences, 2002, vol. 6, pp. 161-194. -
9E. Mémin.
Fluid flow dynamics under location uncertainty, in: Geophysical & Astrophysical Fluid Dynamics, 2014, vol. 108, no 2, pp. 119-146.
http://dx.doi.org/10.1080/03091929.2013.836190 -
10N. Nassif, J. Erhel, B. Philippe.
Introduction to computational linear Algebra, CRC Press, 2015. -
11N. Papadakis, E. Mémin.
A variational technique for time consistent tracking of curves and motion, in: Journal of Mathematical Imaging and Vision, 2008, vol. 31, no 1, pp. 81–103.
http://www.irisa.fr/fluminance/publi/papers/Papadakis-Memin-JMIV07.pdf -
12Y. Saad, M. Yeung, J. Erhel, F. Guyomarc'h.
A deflated version of the Conjugate Gradient Algorithm, in: SIAM Journal on Scientific Computing, 2000, vol. 21, no 5, pp. 1909-1926.
Doctoral Dissertations and Habilitation Theses
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13V. Resseguier.
Mixing and fluid dynamics under location uncertainty, Université Rennes 1, January 2017.
https://tel.archives-ouvertes.fr/tel-01507292
Articles in International Peer-Reviewed Journals
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14S. Cai, E. Mémin, P. Dérian, C. Xu.
Motion Estimation under Location Uncertainty for Turbulent Fluid Flow, in: Experiments in Fluids, 2017, pp. 1-17, forthcoming.
https://hal.inria.fr/hal-01589642 -
15B. Chapron, P. Dérian, E. Mémin, V. Resseguier.
Large scale flows under location uncertainty: a consistent stochastic framework, in: Quarterly Journal of the Royal Meteorological Society, 2017, vol. 00, pp. 1 - 15, forthcoming.
https://hal.inria.fr/hal-01629898 -
16P. Dérian, R. Almar.
Wavelet-Based Optical Flow Estimation of Instant Surface Currents From Shore-Based and UAV Videos, in: IEEE Transactions on Geoscience and Remote Sensing, 2017, pp. 1 - 8. [ DOI : 10.1109/TGRS.2017.2714202 ]
https://hal.archives-ouvertes.fr/hal-01573715 -
17J. Erhel, S. Sabit.
Analysis of a global reactive transport model and results for the MoMaS benchmark, in: Mathematics and Computers in Simulation, 2017, vol. 137, pp. 286-298. [ DOI : 10.1016/j.matcom.2016.11.008 ]
https://hal.inria.fr/hal-01405698 -
18P. Héas, C. Herzet.
Reduced Modeling of Unknown Trajectories, in: Archives of Computational Methods in Engineering, January 2018, vol. 25, no 1, pp. 87-101, https://arxiv.org/abs/1702.08846. [ DOI : 10.1007/s11831-017-9229-0 ]
https://hal.archives-ouvertes.fr/hal-01490572 -
19D. Imberti, J. Erhel.
Vary the s in Your s-step GMRES, in: Electronic Transactions on Numerical Analysis (ETNA), 2017, pp. 1-27, forthcoming.
https://hal.inria.fr/hal-01299652 -
20S. Kadri Harouna, E. Mémin.
Stochastic representation of the Reynolds transport theorem: revisiting large-scale modeling, in: Computers and Fluids, August 2017, vol. 156, pp. 456-469. [ DOI : 10.1016/j.compfluid.2017.08.017 ]
https://hal.inria.fr/hal-01394780 -
21J. Marçais, J.-R. De Dreuzy, J. Erhel.
Dynamic coupling of subsurface and seepage flows solved within a regularized partition formulation, in: Advances in Water Resources, 2017, vol. 109, pp. 94-105. [ DOI : 10.1016/j.advwatres.2017.09.008 ]
https://hal-insu.archives-ouvertes.fr/insu-01586870 -
22V. Resseguier, E. Mémin, B. Chapron.
Geophysical flows under location uncertainty, Part I Random transport and general models, in: Geophysical and Astrophysical Fluid Dynamics, April 2017, vol. 111, no 3, pp. 149-176, https://arxiv.org/abs/1611.02572. [ DOI : 10.1080/03091929.2017.1310210 ]
https://hal.inria.fr/hal-01391420 -
23V. Resseguier, E. Mémin, B. Chapron.
Geophysical flows under location uncertainty, Part II Quasi-geostrophy and efficient ensemble spreading, in: Geophysical and Astrophysical Fluid Dynamics, April 2017, vol. 111, no 3, pp. 177-208. [ DOI : 10.1080/03091929.2017.1312101 ]
https://hal.inria.fr/hal-01391476 -
24V. Resseguier, E. Mémin, B. Chapron.
Geophysical flows under location uncertainty, Part III SQG and frontal dynamics under strong turbulence conditions, in: Geophysical and Astrophysical Fluid Dynamics, April 2017, vol. 111, no 3, pp. 209-227. [ DOI : 10.1080/03091929.2017.1312102 ]
https://hal.inria.fr/hal-01391484 -
25V. Resseguier, E. Mémin, D. Heitz, B. Chapron.
Stochastic modelling and diffusion modes for proper orthogonal decomposition models and small-scale flow analysis, in: Journal of Fluid Mechanics, October 2017, vol. 828, 29 p, https://arxiv.org/abs/1611.06832. [ DOI : 10.1017/jfm.2017.467 ]
https://hal.inria.fr/hal-01400119 -
26Y. Yang, E. Mémin.
High-resolution data assimilation through stochastic subgrid tensor and parameter estimation from 4DEnVar, in: Tellus A, April 2017, 19 p.
https://hal.inria.fr/hal-01500140
Invited Conferences
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27Y. Crenner, J. Erhel.
Influence of a fractured medium on pyrite oxidation reaction, in: MAMERN 2017 - International Conference on Approximation Methods and Numerical Modelling in Environment and Natural Resources, Oujda, Morocco, May 2017.
https://hal.inria.fr/hal-01646245 -
28J. Erhel.
Krylov methods applied to reactive transport models, in: SIAM Conference on Mathematical and Computational Issues in the Geosciences, Erlangen, Germany, September 2017.
https://hal.inria.fr/hal-01646268
International Conferences with Proceedings
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29D. Anda-Ondo, J. Carlier, C. Collewet.
Closed-loop control of a spatially developing free shear flow around a steady state, in: 20th World Congress of the International Federation of Automatic Control, Toulouse, France, International Federation of Automatic Control, July 2017.
https://hal.inria.fr/hal-01514361 -
30S. Cai, E. Mémin, P. Dérian, C. Xu.
Location Uncertainty Principle: Toward the Definition of Parameter-free Motion Estimators *, in: EMMCVPR 2017 - 11th International Conference on Energy Minimization Methods in Computer Vision and Pattern Recognition, Venice, Italy, Springer, October 2017, pp. 1-15.
https://hal.inria.fr/hal-01654184 -
31P. Chandramouli, D. Heitz, E. Mémin, S. Laizet.
A Comparative Study of LES Models Under Location Uncertainty, in: Congrès Français de Mécanique, Lille, France, August 2017.
https://hal.inria.fr/hal-01584736 -
32P. Chandramouli, D. Heitz, E. Mémin, S. Laizet.
Analysis of Models Under Location Uncertainty within the Framework of Coarse Large Eddy Simulation (cLES), in: The 16th European Turbulence Conference, Stockholm, Sweden, European Mechanics Society, August 2017.
https://hal.inria.fr/hal-01584735 -
33P. Héas, C. Herzet.
Optimal Low-Rank Dynamic Mode Decomposition, in: Proceedings of the 2017 IEEE International Conference on Acoustics, Speech and Signal Processing, New Orleans 2017, New Orleans, United States, March 2017, https://arxiv.org/abs/1701.01064. [ DOI : 10.1109/ICASSP.2017.7952999 ]
https://hal.archives-ouvertes.fr/hal-01429975
Conferences without Proceedings
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34R. Almar, A. N. Lerma, P. Dérian, B. Castelle, T. Scott.
Transient Surf Zone Circulation Induced by Rhythmic Swash Zone at a Reflective Beach, in: Coastal Dynamics 2017, Helsingør, Denmark, June 2017.
https://hal.archives-ouvertes.fr/hal-01573717 -
35D. Anda-Ondo, J. Carlier, C. Collewet.
Contrôle en boucle fermée d'une couche de mélange spatiale, in: congrès français de mécanique, Lille, France, August 2017.
https://hal.archives-ouvertes.fr/hal-01578477 -
36A. Gronskis, D. Heitz, E. Mémin.
A new hybrid optimization algorithm for variational data assimilation of unsteady wake flows, in: 2nd Workshop on Data Assimilation & CFD Processing for Particle Image and Tracking Velocimetry, Delft, Netherlands, December 2017.
https://hal.archives-ouvertes.fr/hal-01671776 -
37B. Hamlat, J. Erhel, A. Michel, T. Faney.
Modélisation des systèmes cinétiques limités, in: SMAI 2017, La Tremblade, France, June 2017.
https://hal.inria.fr/hal-01646320 -
38D. Imberti, J. Erhel.
Solving large sparse linear systems with a variable s-step GMRES preconditioned by DD, in: DD24 - International Conference on Domain Decomposition Methods, Longyearbyen, Norway, February 2017.
https://hal.inria.fr/hal-01528636 -
39M. Khalid, L. Pénard, E. Mémin.
Application of optical flow for river velocimetry, in: IGARSS 2017 - 37th IEEE Geoscience and Remote Sensing Symposium, Fort Worth, Texas, United States, July 2017, pp. 1-4.
https://hal.archives-ouvertes.fr/hal-01657202 -
40K. Rocha-Brownell, P. Dérian, D. H. Richter, P. P. Sullivan, S. D. Mayor.
Evaluation of a wavelet-based optical flow algorithm through the use of large eddy simulations, in: 28th International Laser Radar Conference, Bucarest, Romania, June 2017.
https://hal.archives-ouvertes.fr/hal-01573724 -
41R. Schuster, D. Heitz, E. Mémin, A. Guibert, P. Loisel.
Stochastic observation model for large scale motion measurement, in: CFM 2017 - 23ème Congrès Français de Mécanique, Lille, France, August 2017, pp. 1-12.
https://hal.archives-ouvertes.fr/hal-01648441 -
42Y. Yang, S. Cai, E. Mémin, D. Heitz.
Ensemble-Variational methods in data assimilation, in: 2nd Workshop on Data Assimilation & CFD Processing for Particle Image and Tracking Velocimetry, Delft, Netherlands, December 2017.
https://hal.archives-ouvertes.fr/hal-01671751
Internal Reports
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43S. Cai, E. Mémin, Y. Yang, C. Xu.
Sea Surface Flow Estimation via Ensemble-based Variational Data Assimilation*, Inria Rennes - Bretagne Atlantique ; IRMAR, University of Rennes 1, September 2017.
https://hal.inria.fr/hal-01589637
Scientific Popularization
Other Publications
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45L. C. Berselli, R. Lewandowski.
On the Bardina's model in the whole space, 2017, working paper or preprint.
https://hal.archives-ouvertes.fr/hal-01590760 -
46J. Erhel, T. Migot.
Characterizations of Solutions in Geochemistry: Existence, Uniqueness and Precipitation Diagram, September 2017, working paper or preprint.
https://hal.inria.fr/hal-01584490 -
47P. Héas, C. Herzet.
Optimal Kernel-Based Dynamic Mode Decomposition, 2017, working paper or preprint. [ DOI : 10.10919 ]
https://hal.archives-ouvertes.fr/hal-01634542 -
48R. Lewandowski.
Navier-Stokes equations in the whole space with an eddy viscosity, May 2017, working paper or preprint.
https://hal.archives-ouvertes.fr/hal-01531260
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49R. Adrian.
Particle imaging techniques for experimental fluid mechanics, in: Annal Rev. Fluid Mech., 1991, vol. 23, pp. 261-304. -
50G. Artana, A. Cammilleri, J. Carlier, E. Mémin.
Strong and weak constraint variational assimilations for reduced order fluid flow modeling, in: J. of Comput. Phys, 2012, vol. 231, no 8, pp. 3264–3288. -
51T. Bewley.
Flow control: new challenges for a new Renaissance, in: Progress in Aerospace Sciences, 2001, vol. 37, pp. 21–58. -
52S. Beyou, A. Cuzol, S. Gorthi, E. Mémin.
Weighted Ensemble Transform Kalman Filter for Image Assimilation, in: TellusA, January 2013, vol. 65, no 18803. -
53S. Cai, E. Mémin, P. Dérian, C. Xu.
Motion Estimation under Location Uncertainty for Turbulent Fluid Flow, in: Exp. in Fluids, 2018, vol. 59, no 8. -
54A. Cammilleri, F. Gueniat, J. Carlier, L. Pastur, E. Mémin, F. Lusseyran, G. Artana.
POD-Spectral Decomposition for Fluid Flow Analysis and Model Reduction, in: Theor. and Comp. Fluid Dyn, 2013, Accepted for publication. -
55H. Choi, P. Moin, J. Kim.
Direct numerical simulation of turbulent flow over riblets, in: Journal of Fluid Mechanics, 1993, vol. 255, pp. 503–539. -
56T. Corpetti, E. Mémin.
Stochastic Uncertainty Models for the Luminance Consistency Assumption, in: IEEE Trans. Image Processing, 2012, vol. 21, no 2, pp. 481–493. -
57G. Evensen.
Sequential data assimilation with a non linear quasi-geostrophic model using Monte Carlo methods to forecast error statistics, in: J. Geophys. Res., 1994, vol. 99 (C5), no 10, pp. 143–162. -
58J. Favier.
Contrôle d'écoulements : approche expérimentale et modélisation de dimension réduite, Institut National Polytechnique de Toulouse, 2007. -
59J. Favier, A. Kourta, G. Leplat.
Control of flow separation on a wing profile using PIV measurements and POD analysis, in: IUTAM Symposium on Flow Control and MEMS, London, UK, September 19-22, 2006. -
60N. Gordon, D. Salmond, A. Smith.
Novel approach to non-linear/non-Gaussian Bayesian state estimation, in: IEEE Processing-F, April 1993, vol. 140, no 2. -
61A. Guégan, P. Schmid, P. Huerre.
Optimal energy growth and optimal control in swept Hiemenz flow, in: J. Fluid Mech., 2006, vol. 566, pp. 11–45. -
62B. Horn, B. Schunck.
Determining Optical Flow, in: Artificial Intelligence, August 1981, vol. 17, no 1-3, pp. 185–203. -
63F.-X. Le Dimet, O. Talagrand.
Variational algorithms for analysis and assimilation of meteorological observations: theoretical aspects, in: Tellus, 1986, no 38A, pp. 97–110. -
64J. Lions.
Optimal Control of Systems Governed by Partial Differential Equations, Springer-Verlag, 1971. -
65L. Mathelin, O. Le Maître.
Robust control of uncertain cylinder wake flows based on robust reduced order models, in: Computer and Fluids, 2009, vol. 38, pp. 1168–1182. -
66B. Protas, J. Wesfreid.
Drag force in the open-loop control of the cylinder wake in the laminar regime, in: Physics of Fluids, February 2002, vol. 14, no 2, pp. 810–826. -
67I. Wygnanski.
Boundary layer flow control by periodic addition of momentum, in: 4th AIAA Shear Flow Control Conference, USA, June 29-July 2, 1997.