Publications

Articles

[1]S. Girard, P. Armand, C. Duchenne, and T. Yalamas, “Stochastic perturbations and dimension reduction for modelling uncertainty of atmospheric dispersion simulations,” Atmospheric Environment, p. 117313, 2020, doi:10.1016/j.atmosenv.2020.117313. [🗎 get pdf].

[2]C.-E. Gerrer and S. Girard, “Overcoming the obstacle of time-dependent model output for statistical analysis by nonlinear method,” HighTech and Innovation Journal, 2020.https://hightechjournal.org/index.php/HIJ/article/view/79/pdf.

[3]V. Mallet, A. Tilloy, D. Poulet, S. Girard, and F. Brocheton, “Meta-modeling of ADMS-urban by dimension reduction and emulation,” Atmospheric Environment, vol. 184, pp. 37–46, 2018, doi:https://doi.org/10.1016/j.atmosenv.2018.04.009.

[4]M. Kajino et al., “Lessons learned from atmospheric modeling studies after the fukushima nuclear accident: Ensemble simulations, data assimilation, elemental process modeling, and inverse modeling,” Geochemical Journal, vol. 52, no. 2, pp. 85–101, 2018, doi:https://doi.org/10.2343/geochemj.2.0503.

[5]S. Girard, V. Mallet, I. Korsakissok, and A. Mathieu, “Emulation and sobol’ sensitivity analysis of an atmospheric dispersion model applied to the fukushima nuclear accident,” Journal of Geophysical Research: Atmospheres, 2016, doi:10.1002/2015JD023993. [🗎 get pdf].

[6]S. Girard, I. Korsakissok, and V. Mallet, “Screening sensitivity analysis of a radionuclides atmospheric dispersion model applied to the Fukushima disaster,” Atmospheric Environment, vol. 95, no. 0, pp. 490–500, 2014, doi:10.1016/j.atmosenv.2014.07.010. [🗎 get pdf].

[7]S. Girard, T. Romary, P. Stabat, J.-M. Favennec, and H. Wackernagel, “Sensitivity analysis and dimension reduction of a steam generator model for clogging diagnosis,” Reliability Engineering and System Safety, 2013. [🗎 get pdf].

Longer texts

[1]S. Girard, Physical and statistical models for steam generator clogging diagnosis. Springer International Publishing, 2014. [🗎 get pdf].

[2]S. Girard, “Diagnostic du colmatage des générateurs de vapeur à l’aide de modèles physiques et statistiques,” PhD thesis, École des Mines ParisTech, 2012.https://pastel.archives-ouvertes.fr/pastel-00798355.

Talks & proceedings

[1]C.-E. Gerrer and S. Girard, “Health monitoring using statistical learning and digital twins,” in NAFEMS20, 2020. [🗎 get pdf].

[2]R. Périllat, S. Girard, and I. Korsakissok, “Solutions rapides pour la prévision des risques de pollution atmosphérique,” in Lambda mu 22, 2020. [🗎 get pdf].

[3]S. Girard, P. Armand, C. Duchenne, and T. Yalamas, “Generalized perturbation scheme for uncertainty propagation in atmospheric dispersion simulations,” in 19th international conference on harmonisation within atmospheric dispersion modelling for regulatory purposes, HARMO19, 2019. [🗎 get pdf].

[4]C.-E. Gerrer and S. Girard, “Non linear dimension reduction of dynamic model output,” in Proceedings of the 13th international modelica conference, regensburg, germany, march 4–6, 2019, 2019, doi:10.3384/ecp19157189. [🗎 get pdf].

[5]C.-E. Gerrer and S. Girard, “Health monitoring by physical modeling and statistical learning,” in 4th international conference on system reliability and safety, 2019.

[6]S. Girard and T. Yalamas, “Health monitoring by statistical learning and physical modelling,” in Computational science engineering, data science & artificial intelligence (MATHIAS 2019), 2019.

[7]S. Girard, “Expériences numériques avec des modèles spatio-temporels,” in Rencontre chercheurs–ingénieurs « appréhender la grande dimension », 2019.

[8]S. Girard, T. Yalamas, and M. Baudin, “Statistical learning and 0D/1D modelling: Application to battery ageing,” in Lambda mu 21 proceedings, 2018. [🗎 get pdf].

[9]S. Girard, “Pronostic de durée de vie en fatigue par apprentissage statistique et modélisation physique,” in Journées de la conception robuste et fiable, 2017.https://tinyurl.com/pronostic-fatigue-mer.

[10]C. Duchenne, P. Armand, M. Marcilhac, S. Girard, and T. Yalamas, “A new method for assessing the uncertainty associated with 3D dispersion simulations in any variable meteorological conditions,” in 18th international conference on harmonisation within atmospheric dispersion modelling for regulatory purposes, HARMO18, 2017.

[11]S. Girard, I. Korsakissok, and V. Mallet, “Sensitivity analysis of radionuclides atmospheric dispersion following the Fukushima accident,” in European geosciences union (EGU) general assembly, 2014.

[12]S. Girard, T. Romary, P. Stabat, J.-M. Favennec, and H. Wackernagel, “Towards a better understanding of clogged steam generators: A sensitivity analysis of dynamic thermohydraulic model output,” in 19th international conference on nuclear engineering (ICONE19), 2011. [🗎 get pdf].

[13]S. Girard, T. Romary, and H. Wackernagel, “Réduction de dimension d’un modèle thermohydraulique,” in Xèmes journées de géostatistique, 2011.