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Co-auteurs

Nombre de documents

36

Didier LUCOR


Article dans une revue24 documents

  • A Gineau, E. Longatte, D. Lucor, P. Sagaut. Macroscopic model of fluid structure interaction in cylinder arrangement using theory of mixture. Computers and Fluids, Elsevier, 2020, 202, pp.104499. ⟨10.1016/j.compfluid.2020.104499⟩. ⟨hal-02860336⟩
  • Rodrigo Méndez Rojano, Simon Mendez, Didier Lucor, Alexandre Ranc, Muriel Giansily-Blaizot, et al.. Kinetics of the coagulation cascade including the contact activation system: sensitivity analysis and model reduction. Biomechanics and Modeling in Mechanobiology, Springer Verlag, 2019, 18 (4), pp.1139-1153. ⟨10.1007/s10237-019-01134-4⟩. ⟨hal-02873826⟩
  • Rodrigo Méndez Rojano, Simon Mendez, Didier Lucor, Alexandre Ranc, Muriel Giansily-Blaizot, et al.. Kinetics of the coagulation cascade including the contact activation system: Sensitivity analysis and model reduction. Biomechanics and Modeling in Mechanobiology, Springer Verlag, 2019, 18, pp.1139-1153. ⟨hal-02385373⟩
  • Kevin Bouaou, Ioannis Bargiotas, Thomas Dietenbeck, Emilie Bollache, Gilles Soulat, et al.. Analysis of aortic pressure fields from 4D flow MRI in healthy volunteers: Associations with age and left ventricular remodeling. Journal of Magnetic Resonance Imaging, Wiley-Blackwell, 2019, 50, pp.982–993. ⟨10.1002/jmri.26673⟩. ⟨hal-02384661⟩
  • Olivier Adjoua, Stéphanie Pitre-Champagnat, Didier Lucor. Reduced-order modeling of hemodynamics across macroscopic through mesoscopic circulation scales. International Journal for Numerical Methods in Biomedical Engineering, John Wiley and Sons, In press. ⟨hal-02193737⟩
  • Jan Van Langenhove, Didier Lucor, Frédéric Alauzet, Anca Belme. Goal-oriented error control of stochastic system approximations using metric-based anisotropic adaptations. Journal of Computational Physics, Elsevier, 2018, 374, pp.384-412. ⟨hal-01703054⟩
  • Didier Lucor, Olivier Le Maitre. Cardiovascular Modeling With Adapted Parametric Inference. ESAIM: Proceedings and Surveys, EDP Sciences, 2018, 62, pp.91-107. ⟨10.1051/proc/201862091⟩. ⟨hal-02340331⟩
  • J.C. Chassaing, C.T. Nitschke, A. Vincenti, P. Cinnella, D. Lucor. Advances in Parametric and Model-Form Uncertainty Quantification in Canonical Aeroelastic Systems. Aerospace Lab, Alain Appriou, 2018, pp.1-19. ⟨10.12762/2018.AL14-07⟩. ⟨hal-01935239⟩
  • Antoine Brault, L Dumas, D Lucor. Uncertainty quantification of inflow boundary condition and proximal arterial stiffness coupled effect on pulse wave propagation in a vascular network. International Journal for Numerical Methods in Biomedical Engineering, John Wiley and Sons, 2017, 33 (10), ⟨10.1002/cnm.2859⟩. ⟨hal-01326126v2⟩
  • Christian T. Nitschke, Paola Cinnella, Didier Lucor, Jean-Camille Chassaing. Model-form and predictive uncertainty quantification in linear aeroelasticity. Journal of Fluids and Structures, Elsevier, 2017, 73, pp.137-161. ⟨10.1016/j.jfluidstructs.2017.05.007⟩. ⟨hal-02171192⟩
  • Mélanie Rochoux, Annabelle Collin, Cong Zhang, Arnaud Trouvé, Didier Lucor, et al.. Front shape similarity measure for shape-oriented sensitivity analysis and data assimilation for Eikonal equation. ESAIM: Proceedings and Surveys, EDP Sciences, In press, pp.1-22. ⟨hal-01625575⟩
  • Nabil El Moçayd, Sophie Ricci, Nicole Goutal, Mélanie C. Rochoux, Sébastien Boyaval, et al.. Polynomial Surrogates for Open-Channel Flows in Random Steady State. Environmental Modeling & Assessment, Springer, 2017, ⟨10.1007/s10666-017-9582-2⟩. ⟨hal-01763259⟩
  • Laurent Dumas, Tamara El Bouti, Didier Lucor. A Robust and Subject-Specific Hemodynamic Model of the Lower Limb Based on Noninvasive Arterial Measurements. Journal of Biomechanical Engineering, American Society of Mechanical Engineers, 2017, 139 (1), ⟨10.1115/1.4034833⟩. ⟨hal-02166372⟩
  • A. Resmini, J. Peter, Didier Lucor. Mono-block and non-matching multi-block structured mesh adaptation based on aerodynamic functional total derivatives for RANS flow. International Journal for Numerical Methods in Fluids, Wiley, 2016, ⟨10.1002/fld.4296⟩. ⟨hal-01426042⟩
  • J van Langenhove, Didier Lucor, A Belme. ROBUST UNCERTAINTY QUANTIFICATION USING PRECONDITIONED LEAST-SQUARES POLYNOMIAL APPROXIMATIONS WITH l1-REGULARIZATION. International Journal for Uncertainty Quantification, Begell House Publishers, 2016, 6, pp.57 - 77. ⟨10.1615/Int.J.UncertaintyQuantification.2016015915⟩. ⟨hal-01446842⟩
  • E. Bollache, N. Kachenoura, I. Bargiotas, A. Giron, A. de Cesare, et al.. How to estimate aortic characteristic impedance from magnetic resonance and applanation tonometry data?. Journal of Hypertension, Lippincott, Williams & Wilkins, 2015, pp.9. ⟨10.1097/HJH.0000000000000448⟩. ⟨hal-01150778⟩
  • E. Bollache, N. Kachenoura, A. Redheuil, F. Frouin, E. Mousseaux, et al.. Descending aorta subject-specific one-dimensional model validated against in vivo data. Journal of Biomechanics, Elsevier, 2014, 47 (2), pp.424-431. ⟨10.1016/j.jbiomech.2013.11.009⟩. ⟨hal-02635214⟩
  • M.C. Rochoux, S Ricci, D Lucor, B Cuenot, A Trouvé. Towards predictive data-driven simulations of wildfire spread – Part I: Reduced-cost Ensemble Kalman Filter based on a Polynomial Chaos surrogate model for parameter estimation. Natural Hazards and Earth System Sciences, European Geosciences Union, 2014, 14 (11), pp.2951-2973. ⟨10.5194/nhess-14-2951-2014⟩. ⟨hal-01332351⟩
  • Xingsi Han, Pierre Sagaut, Didier Lucor. On sensitivity of RANS simulations to uncertain turbulent inflow conditions. Computers and Fluids, Elsevier, 2012, 61, ⟨10.1016/j.compfluid.2011.04.009⟩. ⟨hal-01298917⟩
  • Xingsi Han, Pierre Sagaut, Didier Lucor, Imran Afgan. Stochastic response of the laminar flow past a flat plate under uncertain inflow conditions. International Journal of Computational Fluid Dynamics, Taylor & Francis, 2012, 26 (2), pp.101-117. ⟨10.1080/10618562.2012.655687⟩. ⟨hal-01298915⟩
  • J. -C. Chassaing, Didier Lucor, J. Tregon. Stochastic nonlinear aeroelastic analysis of a supersonic lifting surface using an adaptive spectral method. Journal of Sound and Vibration, Elsevier, 2012, 331 (2), pp.394-411. ⟨10.1016/j.jsv.2011.08.027⟩. ⟨hal-01459745⟩
  • M. Meldi, Didier Lucor, P. Sagaut. Is the Smagorinsky coefficient sensitive to uncertainty in the form of the energy spectrum?. Physics of Fluids, American Institute of Physics, 2011, 23 (12), pp.125109. ⟨10.1063/1.3663305⟩. ⟨hal-01298914⟩
  • Jordan Ko, Didier Lucor, Pierre Sagaut. Effects of base flow uncertainty on Couette flow stability. Computers and Fluids, Elsevier, 2011, 43 (1), pp.82-89. ⟨10.1016/j.compfluid.2010.09.029⟩. ⟨hal-01298902⟩
  • Marcello Meldi, Pierre Sagaut, Didier Lucor. A stochastic view of isotropic turbulence decay. Journal of Fluid Mechanics, Cambridge University Press (CUP), 2011, 668, pp.351-362. ⟨10.1017/S0022112010005793⟩. ⟨hal-01298899⟩

Communication dans un congrès8 documents

  • Franck Nicoud, Rodrigo Mendez, Alexandre Ranc, Muriel Giansily, Didier Lucor, et al.. Numerical assessment of device-related thrombus formation triggered by the contact system. International Conference on Computational & Mathematical Biomedical Engineering, P. Nithiarasu, M. Ohta, M. Oshima, Jun 2019, Sendai, Japan. ⟨hal-02397305⟩
  • Olivier Adjoua, Didier Lucor. Blood flow reduced-order modeling across macroscopic through mesoscopic scales. International Conference on Computational & Mathematical Biomedical Engineering, P. Nithiarasu, M. Ohta, and M. Oshima, Jun 2019, Sendai, Japan. ⟨hal-02397286⟩
  • Frida Svelander, David Larsson, Didier Lucor, Reidar Winter, Matilda Larsson, et al.. Patient-specific finite element simulation of left ventricle hemodynamics and mitral valve disease based on echocardiography. World Congress of Biomechanics, Jul 2019, Dublin, Ireland. ⟨hal-02397313⟩
  • Mélanie Rochoux, Cong Zhang, Nicolas Frebourg, Annabelle Collin, Philippe Moireau, et al.. Front Data Assimilation and Sensitivity Analysis for Data-Driven Wildland Fire Spread Simulations. International Fire Behavior and Fuels Conference, Apr 2019, Marseille, France. ⟨hal-02397312⟩
  • Siham El Garroussi, Matthias de Lozzo, Sophie Ricci, Didier Lucor, Nicole Goutal, et al.. Uncertainty quantification in a two-dimensional river hydraulic model. International Conference on Uncertainty Quantification in Computational Sciences and Engineering, M. Papadrakakis, V. Papadopoulos, G. Stefanou, Jun 2019, Crete, Greece. ⟨hal-02397318⟩
  • Jean-Philippe Argaud, Sibo Cheng, Bertrand Iooss, Didier Lucor, Angélique Poncot. Iterative methods for improving error covariance modeling in variational assimilation. International Conference on Uncertainty Quantification in Computational Sciences and Engineering, M. Papadrakakis, V. Papadopoulos, G. Stefanou, Jun 2019, Crete, Greece. ⟨hal-02397315⟩
  • Antoine Brault, Laurent Dumas, Didier Lucor. Uncertainty quantification of inflow boundary condition effect on pulse wave propagation in human arterial network. CMBE15. 4th International Conference on Computational & Mathematical Biomedical Engineering, 2015, Cachan, France. pp.754-757. ⟨hal-02171831⟩
  • A Resmini, J Peter, D Lucor. High Dimensional stochastic investigation of 2D RANS flow about an helicopter airfoil. International Workshop on Numerical Prediction of Detached Flows, Oct 2014, MADRID, Spain. ⟨hal-01077350⟩

Chapitre d'ouvrage2 documents

  • Bruno Després, Didier Lucor, Gaël Poëtte. Robust uncertainty propagation in systems of conservation laws with the entropy closure method. Uncertainty quantification in computational fluid dynamics, Springer, Heidelberg, 2013. ⟨hal-01437645⟩
  • Meldi M., Didier Lucor, Sagaut P.. Quantification of the effects of uncertainties in turbulent flows through generalized polynomial chaos. 13th European Turbulence Conference (ETC 13), 2011. ⟨hal-01307214⟩

Pré-publication, Document de travail2 documents

  • Sibo Cheng, Jean-Philippe Argaud, Bertrand Iooss, Angélique Ponçot, Didier Lucor. A graph clustering approach to localization for adaptive covariance tuning in data assimilation based on state-observation mapping. 2020. ⟨meteo-02460851v2⟩
  • Sibo Cheng, Jean-Philippe Argaud, Bertrand Iooss, Didier Lucor, Angélique Ponçot. Background Error Covariance Iterative Updating with Invariant Observation Measures for Data Assimilation. 2019. ⟨hal-02307657⟩