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The activity on uncertainty quantification at CERFACS aims to estimate uncertainties for numerical models requiring large computational resources. We develop environmental risk assessments, data assimilation approaches, probabilistic optimization and coupling improvements for High Performance Computing applications.

At CERFACS, the activity on uncertainty quantification relates to the transversal axis “Data-Driven Modeling” and is at the crossroads of the Environment, Climate, Aerodynamics and Combustion thematic axes. Applications at CERFACS concern flood forecasting, prediction of atmospheric dispersion of pollutants, wildfire propagation, representation of climatic variability and combustion chamber ignition calculations.

The main actions are :

  • Ensemble-based simulations with scalar and functional variables, including dimension reduction strategy
  • Development and evaluation of reduced models for large scale problems
  • Use of reduced models for sensitivity analysis, optimization and data assimilation
  • Development of efficient algorithms for stochastic estimation with solvers of increasing complexity (multi-fidelity, multi-level Monte Carlo/MLMC)

These actions are deployed on the following applications:

  • Development of uncertainty quantification algorithms for real scale computation with efficient, scalable and robust domain decomposition algorithms
  • Development of reduced models for sensitivity analysis and ensemble data assimilation, application in hydraulics and aerodynamics for large uncertain variables
  • Application of reduced models for atmospheric boundary layer simulations in the context of uncertainty quantification, application to micro-scale meteorology and in particular to pollutant dispersion
  • Application of multi-fidelity and MLMC algorithms for industrial computational fluid mechanics, multidisciplinary systems and geosciences.
  • Parametric sensitivity tests of global climate model projections to assess uncertainties in regional and global climate risks
  • Simple climate models to assess data constraints on global climate projection uncertainty




Sparse Days in Saint-Girons IV

Brigitte Yzel |  29 March 2022

Sparse Days Meeting 2022 🗓️  20-22 June 2022  @ Saint-Girons, France   🌐   Sparse Days 2022 will be held in Saint-Girons, Ariège, from 20-22 June. This enhanced version of Sparse Days is being co-organized by Cerfacs and ENSEEIHT/IRIT. It will be the fourth meeting in Saint- Girons following the tradition of the previous meetings held in 1994, 2003, and 2015. The tradition involves coupling our highly successful annual technical meeting with the ambience and hospitality of this wonderful Pyrenean town which encourages fruitful informal exchanges between participants.    Read more

Press releases on the NextSim EuroHPC project

CERFACS |  9 February 2022

Press talks about the NextSim EuroHPC project. CERFACS is involved in two major points. The first topic is to extend the numerical capabilities of the code to perform scale-resolving simulations of jet noise configurations on exascale supercomputers. The second focus is to exploit data from these simulations by extracting or visualising relevant physical information during the computation. CERFACS is involved in the NextSim project (). The primary objective is to increase the capabilities of Computational Fluid Dynamics tools on extreme-scale parallel computing platforms for aeronautical design. 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. This project has received funding from the Agence Nationale de la Recherche (ANR) under grant agreement N° ANR-20-EHPC-0002-02. For more information, please visit Read more