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Data Assimilation and Optimization

The development of data assimilation methods and optimization algorithms is of particular interest for applications in the Earth sciences, aerodynamics and space dynamics.


Data assimilation deals with the problem of estimating model parameters or model state variables by combining prior estimates and observations, together with information about their uncertainties, in a statistically optimal manner. CERFACS has well-established data assimilation activities in oceanography, atmospheric chemistry, hydrology/hydraulics and wildfires, which are conducted in close collaboration with CERFACS partners, and leading operational centres and research institutes in forecasting and retrospective analysis.

cmaes_mean_meanOptimization concerns the development of numerical algorithms for solving diverse linear and nonlinear problems. It involves studying the properties of the algorithms, such as convergence and complexity, as well as improving their performance through preconditioning techniques. CERFACS develops derivative-based and derivative-free algorithms for a variety of applications including data assimilation, Earth imaging and aerodynamics design.

Accuracy, efficiency, scalability, robustness and practicability are important considerations when designing methods for data assimilation and optimization. To develop effective methods requires a good understanding of the underlying application and problem characteristics.


Applications in data assimilation :fig_da_website

Hydrology/hydraulics: Water resource management and flood risk monitoring associated with the dynamics of continental waters are of first importance for public safety and financial . Flood and inundation forecasting relies on numerical modeling tools for hydraulics and hydrology combined with a wide range of observations (in situ and spaceborne). CERFACS is developing in collaboration with EDF, CNES, SCHAPI, CNRM, …, variational and ensemble data assimilation methods based on hydrologic/hydraulic solvers (among whom MASCARET and TELEMAC-2D). These implementations are part of active research activities and of their transfer to operational level.

Wildfires: Real-time prediction of wildfire spread and emissions has been identified as a valuable rsearch objective with direct applications in both fire risk management, fire emergency response and fire-induced environmental impact in the context of climate change. The predictive capability for wildfire behavior at regional scales relies on a semi-empirical modeling of a propagating front (i.e. interface between burnt and unburnt areas) at land surface, which involves biomass, topographical and meteorological data that are embedded with uncertainties. CERFACS is currently developing in collaboration with UMD and SPE an ensemble-based data assimilation system named FIREFLY, in order to sequentially estimate input parameters and the simulated fire front position when fire front position observations are available and thereby to improve the forecast performance of fire spread models.


First 360-degrees Large-Eddy Simulation of a full engine

Jérôme DOMBARD |  17 June 2020

Within the PRACE project FULLEST (First fUlL engine computation with Large Eddy SimulaTion), a joint collaboration between CERFACS, SAFRAN and AKIRA technologies, Dr. C. Pérez Arroyo (post doctoral fellow at CERFACS) has carried out under the supervision of Dr. J. Dombard the first high-fidelity simulation of a part of the real engine DGEN380 (for now, from the fan to the combustion chamber). This 360-degrees integrated large-eddy simulation contains around two billion cells on the three instances, carried out with the AVBP code of CERFACS.  The CPU cost is obviously large but still within reach, performing around one turn of fan during 5 days over 14400 skylake cores. Post-treatments are in progress and already show, among other complex phenomena, a strong interaction between the high pressure compressor and the combustion chamber (see forthcoming paper GT2020-16288 C. Pérez Arroyo et al). Below a video showing: in the fan an isosurface at mid-height of the vein colored by the Mach number, in the high pressure compressor a gradient of density, in the bypass of the combustion chamber the static pressure and in the flame tube a temperature field. One of the goals of the project is to create a high-fidelity unsteady database to study interactions between modules and may help other teams to develop new lower order models and/or validate existing ones. Beyond the feasibility and the maturity of the AVBP code, this kind of calculation is an important milestone for the aeronautical industry and would allow to apprehend earlier in the design the effect of integration and installation and thus, to reduce the cycle and therefore the cost of the future aircraft engines. We acknowledge PRACE for awarding us access to Joliot-Curie (Genci) hosted at CEA/TGCC, FRANCE, Safran Tech and DGAC fundings within the project ATOM, along with the invaluable technical support at...Read more

B. Cuenot distinguished as Program Chair of international Symposium on Combustion

superadmin |  29 May 2020

B. Cuenot has been distinguished as Program Chair for the 39th International Symposium on Combustion, to be held in Vancouver (Canada) in 2022. The International Symposium on Combustion is a major event for the combustion community, where the current best research is presented.Read more