Citation et publications
Cette page regroupe différentes publication. La première est celle permettant de citer la plateforme Uranie si vous l'utiliser dans une de vos analyses. Les autres montrent les champs de recherche et les collaborations qu'ont les membres de l'équide développement de la plateforme Uranie.
J-B. Blanchard, G. Damblin, J-M. Martinez, G. Arnaud, F. Gaudier, The Uranie platform: an open-source software for optimisation, meta-modelling and uncertainty analysis, EPJ Nuclear Sci. Technol. 5 4 (2019)
- Lefebvre L., Segond M., Spaggiari R., Le Gratiet L., Deri E., Iooss B., Damblin G.Improving the Predictivity of a Steam Generator Clogging Numerical Model by Global Sensitivity Analysis and Bayesian Calibration Techniques (2023) Nuclear Science and Engineering, 197 (8), pp. 2136 - 2149
- J-B. Blanchard, Sensitivity analysis with correlated inputs: comparison of indices for the linear case. International Journal for Uncertainty Quantification, 2023, vol. 13, no 6.
- J-B. Blanchard, R. Chocat, G. Damblin, M. Baudin, N. Bousquet, V. Chabridon, B. Iooss, M. Keller, J. Pelamatti, R. Sueur, Fiches pédagogiques sur le traitement des incertitudes dans les codes de calcul. EDF. 2023. ⟨hal-04205632⟩
- G. Damblin, F. Bachoc, S. Gazzo, L. Sargentini et A. Ghione. A generalization of the CIRCE method for quantifying input model uncertainty in presence of several groups of experiments. Nuclear Engineering and Design, 413:112527, 2023
- A. Bouloré, C. Struzik, V. Bouineau, F. Gaudier, G. Damblin, et S. Bernaud. Modelling of UO2 thermal conductivity: Improvement of the irradiation defects contribution and uncertainty quantification. Nuclear Engineering and Design, 407:112304, 2023
- Gauchy C., Stenger J., Sueur R., Iooss B. An Information Geometry Approach to Robustness Analysis for the Uncertainty Quantification of Computer Codes (2022) Technometrics, 64 (1), pp. 80 - 91
- Broto B., Bachoc F., Clouvel L., Martinez J.-M. Block-Diagonal Covariance Estimation and Application to the Shapley Effects in Sensitivity Analysis (2022) SIAM-ASA Journal on Uncertainty Quantification, 10 (1), pp. 379 - 403
- Chaouai Z., Daniel G., Martinez J.-M., Limousin O., Benoit-Lévy A.Application of adversarial learning for identification of radionuclides in gamma-ray spectra Nuclear Instruments and Methods in Physics Research, Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, 1033, art. no. 166670
- R. Cocci, G. Damblin, A. Ghione, L. Sargentini, et D. Lucor. A comprehensive bayesian framework for the development, validation and uncertainty quantification of thermalhydraulicmodels. Annals of Nuclear Energy, 172:109029, 2022
- R. Cocci, G. Damblin, A. Ghione L. Sargentini et D. Lucor. Extension of the CIRCE methodology to improve the inverse uncertainty quantification of several combined thermal-hydraulic models. Nuclear Engineering and Design, 398:111974, 2022
- Sainct R., Feau C., Martinez J.-M., Garnier J. Efficient methodology for seismic fragility curves estimation by active learning on Support Vector Machines (2020) Structural Safety, 86, art. no. 101972
- G. Damblin et A. Ghione. Adaptive use of replicated latin hypercube designs for computing sobol’ sensitivity indices. Reliability Engineering and System Safety, 212:107507, 2021
- G. Damblin et P. Gaillard. Bayesian inference and non-linear extensions of the CIRCE method for quantifying the uncertainty of closure relationships integrated into thermalhydraulic system codes. Nuclear Engineering and Design, 359:110391, 2020
- Kahn, S., Reux, C., Artaud, J. F., Aiello, G., Blanchard, J-B., Bucalossi, J., … & URANIE Team. (2019). Sensitivity analysis of fusion power plant designs using the SYCOMORE system code. Nuclear Fusion, 60(1), 016015