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Centre of basic and applied research specialized in modelling and numerical simulation, Cerfacs, through its facilities and expertise in high-performance computing, deals with major scientific and technical research problems of public and industrial interest.

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Cerfacs funded for the EoCoE-II European center of excellence

superadmin |  11 October 2018

The European center of excellence EoCoE-II brings together 20 partners from 7 European countries around exascale computing for energy-oriented numerical models. As a follow-up to the proof-of-principle phase of EoCoE (energy-oriented center of excellence), EoCoE-II will build on its unique,...Read more


Cerfacs funded by the EU for more than 1 MEuros thanks to the IS-ENES3 and ESiWACE2 projects

superadmin |  4 October 2018

IS-ENES3 is the third phase of the distributed e-infrastructure of ENES (European Network for Earth System modelling), enabling the European climate modelling community to address the challenges of international intercomparison project CMIP6. IS-ENES3 will develop, document and deploy new and...Read more

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CALENDAR

RESEARCH PUBLICATIONS

Douasbin, Q., Scalo, C., Selle, L. and Poinsot, T. (2018) Delayed-time domain impedance boundary conditions (D-TDIBC), Journal of Computational Physics, 371 (October), pp. 50-66, doi:10.1016/j.jcp.2018.05.003

[url] [doi]

@ARTICLE{AR-CFD-18-127, author = {Douasbin, Q. and Scalo, C. and Selle, L. and Poinsot, T. }, title = {Delayed-time domain impedance boundary conditions (D-TDIBC)}, year = {2018}, number = {October}, volume = {371}, pages = {50-66}, doi = {10.1016/j.jcp.2018.05.003}, journal = {Journal of Computational Physics}, abstract = {Defining acoustically well-posed boundary conditions is one of the major numerical and theoretical challenges in compressible Navier–Stokes simulations. We present the novel Delayed-Time Domain Impedance Boundary Condition (D-TDIBC) technique developed to impose a time delay to acoustic wave reflection. Unlike previous similar TDIBC derivations (Fung and Ju, 2001–2004 [1], [2], Scalo et al., 2015 [3] and Lin et al., 2016 [4]), D-TDIBC relies on the modeling of the reflection coefficient. An iterative fit is used to determine the model constants along with a low-pass filtering strategy to limit the model to the frequency range of interest. D-TDIBC can be used to truncate portions of the domain by introducing a time delay in the acoustic response of the boundary accounting for the travel time of inviscid planar acoustic waves in the truncated sections: it gives the opportunity to save computational resources and to study several geometries without the need to regenerate computational grids. The D-TDIBC method is applied here to time-delayed fully reflective conditions. D-TDIBC simulations of inviscid planar acoustic-wave propagating in truncated ducts demonstrate that the time delay is correctly reproduced, preserving wave amplitude and phase. A 2D thermoacoustically unstable combustion setup is used as a final test case: Direct Numerical Simulation (DNS) of an unstable laminar flame is performed using a reduced domain along with D-TDIBC to model the truncated portion. Results are in excellent agreement with the same calculation performed over the full domain. The unstable modes frequencies, amplitudes and shapes are accurately predicted. The results demonstrate that D-TDIBC offers a flexible and cost-effective approach for numerical investigations of problems in aeroacoustics and thermoacoustics.}, keywords = {COMB, Impedance boundary condition, Time delay, Characteristic boundary conditions ,NSCBC, Computational aeroacoustics, Thermoacoustics}, url = {https://www.sciencedirect.com/science/article/pii/S002199911830295X}}

Lac, C., Chaboureau, J. P., Masson, V., Pinty, J. -P., Tulet, P., Escobar, J., Leriche, M., Barthe, C., Aouizerats, B., Augros, C., Aumond, P., Auguste, F., Bechtold, P., Berthet, S., Bielli, S., Bosseur, F., Caumont, O., Cohard, J. -M., Colin, J., Couvreux, F., Cuxart, J., Delautier, G., Dauhut, T., Ducrocq, V., Filippi, J. -B., Gazen, D., Geoffroy, O., Gheusi, F., Honnert, R., Lafore, J. P., Lebeaupin Brossier, C., Libois, Q., Lunet, T., Mari, C., Maric, T., Mascart, P., Mogé, M., Molinié, G., Nuissier, O., Pantillon, F., Peyrillé, P., Pergaud, J., Perraud, E., Pianezze, J., Redelsperger, J. -L., Ricard, D., Richard, E., Riette, S., Rodier, Q., Schoetter, R., Seyfried, L., Stein, J., Suhre, K., Taufour, M., Thouron, O., Turner, S., Verrelle, A., Vié, B., Visentin, F., Vionnet, V. and Wautelet, P. (2018) Overview of the Meso-NH model version 5.4 and its applications, Geoscientific Model Development, 11, pp. 1929-1969, doi:10.5194/gmd-11-1929-2018

[pdf] [doi]

@ARTICLE{AR-CMGC-18-132, author = {Lac, C. and Chaboureau, J.P. and Masson, V. and Pinty, J.-P. and Tulet, P. and Escobar, J. and Leriche, M. and Barthe, C. and Aouizerats, B. and Augros, C. and Aumond, P. and Auguste, F. and Bechtold, P. and Berthet, S. and Bielli, S. and Bosseur, F. and Caumont, O. and Cohard, J.-M. and Colin, J. and Couvreux, F. and Cuxart, J. and Delautier, G. and Dauhut, T. and Ducrocq, V. and Filippi, J.-B. and Gazen, D. and Geoffroy, O. and Gheusi, F. and Honnert, R. and Lafore, J.P. and Lebeaupin Brossier, C. and Libois, Q. and Lunet, T. and Mari, C. and Maric, T. and Mascart, P. and Mogé, M. and Molinié, G. and Nuissier, O. and Pantillon, F. and Peyrillé, P. and Pergaud, J. and Perraud, E. and Pianezze, J. and Redelsperger, J.-L. and Ricard, D. and Richard, E. and Riette, S. and Rodier, Q. and Schoetter, R. and Seyfried, L. and Stein, J. and Suhre, K. and Taufour, M. and Thouron, O. and Turner, S. and Verrelle, A. and Vié, B. and Visentin, F. and Vionnet, V. and Wautelet, P. }, title = {Overview of the Meso-NH model version 5.4 and its applications}, year = {2018}, volume = {11}, pages = {1929-1969}, doi = {10.5194/gmd-11-1929-2018}, journal = {Geoscientific Model Development}, pdf = {https://cerfacs.fr/wp-content/uploads/2018/09/Globc-Article-emili-gmd-11-1929-2018.pdf}}

Serazin, G., Penduff, T., Barnier, B., Molines, J. M., Arbic, B. K., Muller, M. and Terray, L. (2018) Inverse Cascades of Kinetic Energy as a Source of Intrinsic Variability : A Global OGCM Study, Journal of Physical Oceanography, 48, pp. 1385-1408, doi:10.1175/JPO-D-17-0136.1

[pdf] [Supplementary Material] [doi]

@ARTICLE{AR-CMGC-18-106, author = {Serazin, G. and Penduff, T. and Barnier, B. and Molines, J.M. and Arbic, B.K. and Muller, M. and Terray, L. }, title = {Inverse Cascades of Kinetic Energy as a Source of Intrinsic Variability : A Global OGCM Study}, year = {2018}, volume = {48}, pages = {1385-1408}, doi = {10.1175/JPO-D-17-0136.1}, journal = {Journal of Physical Oceanography}, pdf = {https://cerfacs.fr/wp-content/uploads/2018/09/Article-GlobC_Serazin_terray-et_al_JPO_2018.pdf}, supplementaryMaterial = {https://doi.org/10.1175/JPO-D-17- 0136.s1}}

Dupuis, R., Jouhaud, J. -C. and Sagaut, P. (2018) Surrogate Modeling of Aerodynamic Simulations for Multiple Operating Conditions Using Machine Learning, AIAA Journal, 56 (9), pp. 3622-3635, doi:10.2514/1.J056405

[url] [doi]

@ARTICLE{AR-CFD-18-110, author = {Dupuis, R. and Jouhaud, J.-C. and Sagaut, P. }, title = {Surrogate Modeling of Aerodynamic Simulations for Multiple Operating Conditions Using Machine Learning}, year = {2018}, number = {9}, volume = {56}, pages = {3622-3635}, doi = {10.2514/1.J056405}, journal = {AIAA Journal}, abstract = {This paper describes a methodology, called local decomposition method, which aims at building a surrogate model based on steady turbulent aerodynamic fields at multiple operating conditions. The various shapes taken by the aerodynamic fields due to the multiple operation conditions pose real challenges as well as the computational cost of the high-fidelity simulations. The developed strategy mitigates these issues by combining traditional surrogate models and machine learning. The central idea is to separate the solutions with a subsonic behavior from the transonic and high-gradient solutions. First, a shock sensor extracts a feature corresponding to the presence of discontinuities, easing the clustering of the simulations by an unsupervised learning algorithm. Second, a supervised learning algorithm divides the parameter space into subdomains, associated to different flow regimes. Local reduced-order models are built on each subdomain using proper orthogonal decomposition coupled with a multivariate interpolation tool. Finally, an improved resampling technique taking advantage of the subdomain decomposition minimizes the redundancy of sampling. The methodology is assessed on the turbulent two-dimensional flow around the RAE2822 transonic airfoil. It exhibits a significant improvement in terms of prediction accuracy for the developed strategy compared with the classical method of surrogate modeling.}, keywords = {surrogate models, POD, aerodynamics, machine learning}, url = {https://arc.aiaa.org/doi/10.2514/1.J056405}}

Menegoz, M., Cassou, C., Swingedouw, D., Bretonnière, P. A. and Doblas-Reyes, F. (2018) Role of the Atlantic Multidecadal Variability in modulating the climate response to a Pinatubo-like volcanic eruption, Climate Dynamics, 51 (5-6), pp. 1863-1883, doi:10.1007/s00382-017-3986-1

[pdf] [doi]

@ARTICLE{AR-CMGC-18-6, author = {Menegoz, M. and Cassou, C. and Swingedouw, D. and Bretonnière, P.A. and Doblas-Reyes, F. }, title = {Role of the Atlantic Multidecadal Variability in modulating the climate response to a Pinatubo-like volcanic eruption}, year = {2018}, number = {5-6}, volume = {51}, pages = {1863-1883}, doi = {10.1007/s00382-017-3986-1}, journal = {Climate Dynamics}, pdf = {https://cerfacs.fr/wp-content/uploads/2018/09/GLOBC_Article_Cassou_et_al_Climdyn_Roleoftheatlanticvariability_092018.pdf}}

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Plume simulation and deep learning to support wildfire understanding and prediction

 

Objectives of the internship Predicting wildland fire remains a challenge since spread rate and direction highly depend on the multi-scale...Read more


In situ data analysis and visualization for large-scale CFD simulations

 

Contexte The European Centre for Advanced Research and Training in Scientific Computing (CERFACS) works to solve, through modelling and numerical...Read more

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