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The activity on uncertainty quantification at CERFACS aims to estimate uncertainties in computational models requiring large computational resources.  We consider applications related to environmental risk, data assimilation and optimization in a high performance computing context.

The principal actions are:

  • Ensemble experimental design for calibration of uncertain model parameters
  • Development cost-effective Surrogate Model methodologies for computationally intensive problems
  • Sensitivity analysis, optimization and data assimilation
  • Development of efficient algorithms for stochastic parameter estimation

These actions are implemented for the following applications:

  • Surrogates for high dimensional problems in hydraulics and aerodynamics.
  • Efficient, scalable and resilient domain decomposition algorithms for exascale computing
  • Surrogate models for large-eddy simulations of pollution dispersion in the atmospheric boundary layer
  • Developing Multifidelity-MLMC algorithms for industrial CFD, multidisciplinary systems and geosciences.
  • Building simple climate models to explore data constraints on climate projections


Models are approximations of systems.  Confidence in model simulations requires an understanding of their uncertainties.

Uncertainties are generally classified according to their nature. There are several sources of error:

  • errors related to simplifications of equations (dimensional reduction, empirical parameterization)
  • errors related to the numerical schemes
  • errors related to spatio-temporal discretization.

Models must be supplemented by data and parameters that describe the system, initial conditions and its boundary conditions. The physical parameters govern the  laws of the system – and sometimes, these data and parameters are only partially and approximately observed and known.

Errors can be further classified into two groups :

  • Epistemic errors linked to a lack of knowledge of system processes
  • Random errors linked to the stochastic nature of the system

Our aim is to understand and quantify the extent to which epistemic and random uncertainties affect the model response.  At CERFACS, we develop a suite of tools to better understand this propagation of uncertainty.

  • Multi-fidelity Monte-Carlo methods to allow the efficient estimation of probabilistic parameter distributions for industrial and geoscience applications
  • Novel surrogate models to allow rapid exploration of parameter response in global climate and CFD problems.
  • Risk assessment tools bridging scales for climate impacts, connecting global uncertainties to local impacts.


At CERFACS, these activity are transversal, with applications ranging from flood forecasting to wildland fire propagation, climate projection uncertainty and combustion chamber ignition models.


  • EDF
  • IRT
  • CMAP
  • Inria


Tribute to Françoise Chatelin

Brigitte Yzel |  23 July 2021

  Tribute to Françoise CHATELIN   Virtual & Face to Face event @ Cerfacs 14 October 2021, CERFACS, Toulouse (France) 2 pm - 6.30 pm   Cerfacs is organizing a half scientific day on Thursday October 14, 2021 in tribute to Françoise Chatelin who left us prematurely on May 14, 2020   After graduating from the Ecole Normale Supérieure in Paris (1960-63), and her PhD in Mathematics at Grenoble University (1971) , Françoise Chatelin led with worldwide recognition her research in many areas, from spectral theory for linear operators in Banach spaces and finite precision to Dickson algebras. Professor Chatelin taught at the Universities Grenoble 2 - Pierre Mendès-France and Paris 9 - Dauphine before moving to Toulouse in 1996. She became Emeritus Professor in 2015. She was a visiting researcher at Berkeley and Stanford Universities, IBM San Jose (Ca) and Yorktown Heights (NY). For almost a decade, she was a scientific manager in Industry (in charge of intensive computing) first at the Centre Scientifique IBM France in Paris (1985 -1992) and then in the Central Research Lab of Thales (known as Thomson-CSF at that time) near Paris (1992-95). Françoise Chatelin was Head of the Qualitative Computing group at the Centre Européen de Recherche et de Formation Avancée en Calcul Scientifique (Cerfacs) in Toulouse, France. Professor Chatelin has authored four books; the first three are now classic references available from SIAM. Her second book Valeurs Propres de Matrices (Masson, Paris, 1988) has received the IBM - France prize for « Best Scientific and technical publication 1988 ». Beyond her scientific contribution, Françoise Chatelin played a structuring role on research at CERFACS through multiple thesis on innovative topics. This event is devoted to the human and scientific tribute of her life. As a faithful image of the active and passionate woman that...Read more

CERFACS is involved in the NextSim project

CERFACS |  19 July 2021

The primary objective is to increase the capabilities of Computational Fluid Dynamics tools on extreme-scale parallel computing platforms for aeronautical design. The Kick-Off Meeting took place on 12 March 2021. This project has received funding from the European High-Performance Computing Joint Undertaking (JU) under grant agreement N° 956104. The JU receives support from the European Union’s Horizon 2020 research and innovation programme and Spain, France, Germany. For more information, please visit  EuroHPC website : Project webpage :Read more