Bibliography

Major publications by the team in recent years

• 1E. Abbate, A. Iollo, G. Puppo.
  An all-speed relaxation scheme for gases and compressible materials, in: Journal of Computational Physics, 2017, vol. 351, pp. 1-24. [ DOI : 10.1016/j.jcp.2017.08.052 ]
  https://hal.inria.fr/hal-01586863
• 2M. Bergmann, C.-H. Bruneau, A. Iollo.
  Enablers for robust POD models, in: Journal of Computational Physics, 2009, vol. 228, n^o 2, pp. 516–538.
• 3M. Bergmann, J. Hovnanian, A. Iollo.
  An accurate cartesian method for incompressible flows with moving boundaries, in: Communications in Computational Physics, 2014, vol. 15, n^o 5, pp. 1266–1290.
• 4M. Bergmann, A. Iollo.
  Modeling and simulation of fish-like swimming, in: Journal of Computational Physics, 2011, vol. 230, n^o 2, pp. 329 - 348.
• 5M. Bergmann, A. Iollo.
  Bioinspired swimming simulations, in: Journal of Computational Physics, 2016, vol. 323, pp. 310 - 321.
• 6F. Bernard, A. Iollo, G. Puppo.
  Accurate Asymptotic Preserving Boundary Conditions for Kinetic Equations on Cartesian Grids, in: Journal of Scientific Computing, 2015, 34 p.
• 7A. Bouharguane, A. Iollo, L. Weynans.
  Numerical solution of the Monge–Kantorovich problem by density lift-up continuation, in: ESAIM: Mathematical Modelling and Numerical Analysis, November 2015, vol. 49, n^o 6, 1577.
• 8A. De Brauer, A. Iollo, T. Milcent.
  A Cartesian Scheme for Compressible Multimaterial Models in 3D, in: Journal of Computational Physics, 2016, vol. 313, pp. 121-143.
• 9F. Luddens, M. Bergmann, L. Weynans.
  Enablers for high-order level set methods in fluid mechanics, in: International Journal for Numerical Methods in Fluids, December 2015, vol. 79, pp. 654-675.
• 10T. Meuel, Y. L. Xiong, P. Fischer, C.-H. Bruneau, M. Bessafi, H. Kellay.
  Intensity of vortices: from soap bubbles to hurricanes, in: Scientific Reports, December 2013, vol. 3, pp. 3455 (1-7).
• 11Y. L. Xiong, C.-H. Bruneau, H. Kellay.
  A numerical study of two dimensional flows past a bluff body for dilute polymer solutions, in: Journal of Non-Newtonian Fluid Mechanics, 2013, vol. 196, pp. 8-26.

Publications of the year

Doctoral Dissertations and Habilitation Theses

• 12M. Braun.
  Reduced Order Modelling and Uncertainty Propagation Applied to Water Distribution Networks, Université de Bordeaux, April 2019.
  https://tel.archives-ouvertes.fr/tel-02278297

Articles in International Peer-Reviewed Journals

• 13E. Abbate, A. Iollo, G. Puppo.
  An asymptotic-preserving all-speed scheme for fluid dynamics and nonlinear elasticity, in: SIAM Journal on Scientific Computing, September 2019.
  https://hal.archives-ouvertes.fr/hal-02373325
• 14E. Abbate, A. Iollo, G. Puppo.
  An implicit scheme for moving walls and multi-material interfaces in weakly compressible materials, in: Communications in Computational Physics, January 2020.
  https://hal.archives-ouvertes.fr/hal-02373329
• 15S. Avgerinos, F. Bernard, A. Iollo, G. Russo.
  Linearly implicit all Mach number shock capturing schemes for the Euler equations, in: Journal of Computational Physics, 2019. [ DOI : 10.1016/j.jcp.2019.04.020 ]
  https://hal.inria.fr/hal-02419411
• 16F. Bernard, A. Iollo, G. Puppo.
  BGK Polyatomic Model for Rarefied Flows, in: Journal of Scientific Computing, March 2019, vol. 78, n^o 3, pp. 1893-1916. [ DOI : 10.1007/s10915-018-0864-x ]
  https://hal.inria.fr/hal-02419447
• 17M. G. Carlino, P. Ricka, M. S. Phan, S. Bertoluzza, M. Pennacchio, G. Patanè, M. Spagnuolo.
  Geometry description and mesh construction from medical imaging, in: ESAIM: Proceedings and Surveys, 2019, vol. 2019, pp. 1 - 10, forthcoming.
  https://hal.inria.fr/hal-02072342
• 18A. Ferrero, A. Iollo, F. Larocca.
  Reduced order modelling for turbomachinery shape design, in: International Journal of Computational Fluid Dynamics, November 2019, pp. 1-12. [ DOI : 10.1080/10618562.2019.1691722 ]
  https://hal.inria.fr/hal-02403455
• 19M. Jedouaa, C.-H. Bruneau, E. Maitre.
  An efficient interface capturing method for a large collection of interacting bodies immersed in a fluid, in: Journal of Computational Physics, February 2019, vol. 378, pp. 143-177. [ DOI : 10.1016/j.jcp.2018.11.006 ]
  https://hal.archives-ouvertes.fr/hal-01236468
• 20T. Taddei.
  An offline/online procedure for dual norm calculations of parameterized functionals: empirical quadrature and empirical test spaces, in: Advances in Computational Mathematics, September 2019. [ DOI : 10.1007/s10444-019-09721-w ]
  https://hal.archives-ouvertes.fr/hal-02369312

Invited Conferences

• 21M. Bergmann, A. Iollo.
  Sampling and clustering on the POD-Grassmann manifold, in: CSE19 - SIAM Conference on Computational Science and Engineering, Spokane, United States, February 2019.
  https://hal.inria.fr/hal-02424383
• 22M. Bergmann, A. Iollo, S. Riffaud, A. Ferrero, A. Scardigli, E. Lombardi, H. Telib.
  Reduced-Order Models: Convergence Between Data and Simulation, in: CSE19 - SIAM Conference on Computational Science and Engineering, Spokane, United States, February 2019.
  https://hal.inria.fr/hal-02424387

International Conferences with Proceedings

• 23A. Ferrero, A. Iollo, F. Larocca.
  RANS closure approximation by artificialneural networks, in: ETC 2019 - 13th European Turbomachinery Conference on Turbomachinery Fluid Dynamics and Thermodynamics, Lausanne, Switzerland, April 2019.
  https://hal.inria.fr/hal-02403432

Conferences without Proceedings

• 24M. Bergmann, A. Fondanèche, A. Iollo.
  AMR enabled quadtree discretization of incompressible Navier-Stokes equations with moving boundaries, in: International Congress on Industrial and Applied Mathematics (ICIAM) 2019, Valencia, Spain, July 2019.
  https://hal.inria.fr/hal-02421748

Other Publications

• 25A. Barone, M. G. Carlino, A. Gizzi, S. Perotto, A. Veneziani.
  Efficient Estimation of Cardiac Conductivities: a Proper Generalized Decomposition Approach, December 2019, working paper or preprint.
  https://hal.inria.fr/hal-02417508
• 26T. Taddei.
  A registration method for model order reduction: data compression and geometry reduction, January 2020, https://arxiv.org/abs/1906.11008 - working paper or preprint.
  https://hal.archives-ouvertes.fr/hal-02430234

References in notes

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• 28S. Bagheri.
  Koopman-mode decomposition of the cylinder wake, in: Journal of Fluid Mechanics, 2013.
• 29P. Barton, D. Drikakis, E. Romenski, V. Titarev.
  Exact and approximate solutions of Riemann problems in non-linear elasticity, in: Journal of Computational Physics, 2009, vol. 228, n^o 18, pp. 7046-7068.
• 30M. Bergmann, C.-H. Bruneau, A. Iollo.
  Enablers for robust POD models, in: Journal of Computational Physics, 2009, vol. 228, n^o 2, pp. 516–538.
• 31M. Bergmann, A. Ferrero, A. Iollo, E. Lombardi, A. Scardigli, H. Telib.
  A zonal Galerkin-free POD model for incompressible flows, in: Journal of Computational Physics, 2018, vol. 352, pp. 301–325.
• 32A. Bouharguane, A. Iollo, L. Weynans.
  Numerical solution of the Monge-Kantorovich problem by density lift-up continuation, in: ESAIM: M2AN, 2015, vol. 49, n^o 6, pp. 1577-1592.
• 33A. D. Brauer, A. Iollo, T. Milcent.
  A Cartesian scheme for compressible multimaterial models in 3D, in: Journal of Computational Physics, 2016, vol. 313, pp. 121-143. [ DOI : 10.1016/j.jcp.2016.02.032 ]
  http://www.sciencedirect.com/science/article/pii/S0021999116000966
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  An experimental study of entrainment and transport in the turbulent near wake of a circular cylinder, in: Journal of fluid mechanics, 1983, vol. 136, pp. 321–374.
• 35L. Cordier, M. Bergmann.
  Two typical applications of POD: coherent structures eduction and reduced order modelling, in: Lecture series 2002-04 on post-processing of experimental and numerical data, Von Kármán Institute for Fluid Dynamics, 2002.
• 36S. Gavrilyuk, N. Favrie, R. Saurel.
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• 38X. Jin.
  Construction d'une chaîne d'outils numériques pour la conception aérodynamique de pales d'éoliennes, Université de Bordeaux, 2014.
• 39B. Lambert, L. Weynans, M. Bergmann.
  Local lubrication model for spherical particles within incompressible Navier-Stokes flows, in: Phys. Rev. E, Mar 2018, vol. 97, 033313 p.
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• 40F. Luddens, M. Bergmann, L. Weynans.
  Enablers for high-order level set methods in fluid mechanics, in: International Journal for Numerical Methods in Fluids, December 2015, vol. 79, pp. 654-675. [ DOI : 10.1002/fld.4070 ]
• 41J. Lumley, A. Yaglom, V. Tatarski.
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• 44R. Mittal, G. Iaccarino.
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• 45P. J. Schmid.
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