General repository of the following PhD thesis in Computer Science:
E. Fekhari. (2024). Uncertainty quantification in muti-physics models for wind turbine asset management. PhD thesis, Université Nice Côte d'Azur.
This repository is divided into two folders:
📂 manuscript: containing the LaTex sources of the manuscript.
📂 numerical_experiments: holding the Python/OpenTURNS code generating some figures from the manuscript.
📰 E. Fekhari, B. Iooss, J. Muré, L. Pronzato and M.J. Rendas (2023). "Model predictivity assessment: incremental test-set selection and accuracy evaluation". In: Studies in Theoretical and Applied Statistics, pages 315-347. Springer.
📰 E. Fekhari, V. Chabridon, J. Muré and B. Iooss (2024). "Given-data probabilistic fatigue assessment for offshore wind turbines using Bayesian quadrature". In: Data-Centric Engineering, 5, e5.
📰 E. Vanem, E. Fekhari, N. Dimitrov, M. Kelly, A. Cousin and M. Guiton (2024). "A joint probability distribution for multivariate wind-wave conditions and discussions on uncertainties". In: Journal of Offshore Mechanics and Arctic Engineering; 146(6): 061701.
📰 📣 E. Fekhari, B. Iooss, V. Chabridon and J. Muré (2022). "Efficient techniques for fast uncertainty propagation in an offshore wind turbine multi-physics simulation tool". In: Proceedings of the 5th International Conference on Renewable Energies Offshore (RENEW 2022), Lisbon, Portugal.
📰 📣 E. Fekhari, V. Chabridon, J. Muré and B. Iooss (2023). "Bernstein adaptive nonparametric conditional sampling: a new method for rare event probability estimation". In: Proceedings of the 13th International Conference on Applications of Statistics and Probability in Civil Engineering (ICASP 14), Dublin, Ireland.
📰 A. Lovera, E. Fekhari, B. Jézéquel, M. Dupoiron, M. Guiton and E. Ardillon (2023). "Quantifying and clustering the wake-induced perturbations within a wind farm for load analysis". In: Journal of Physics: Conference Series (WAKE 2023), Visby, Sweden.
📰 E. Vanem, Ø. Lande and E. Fekhari, (2024, to appear). "A simulation study on the usefulness of the Bernstein copula for statistical modeling of metocean variables". In: Proceedings of the ASME 2024 43th International Conference on Ocean, Offshore and Arctic Engineering.
📣 E. Fekhari, B. Iooss, V. Chabridon and J. Muré (2022). "Numerical Studies of Bayesian Quadrature Applied to Offshore Wind Turbine Load Estimation". In: SIAM Conference on Uncertainty Quantification (SIAM UQ22), Atlanta, USA.
📣 E. Fekhari, B. Iooss, V. Chabridon and J. Muré (2022). "Model predictivity assessment: incremental test-set selection and accuracy evaluation". In: 22nd Annual Conference of the European Network for Business and Industrial Statistics (ENBIS 2022), Trondheim, Norway.
📣 E. Fekhari, B. Iooss, V. Chabridon and J. Muré (2022). "Kernel-based quadrature applied to offshore wind turbine damage estimation". In: Proceedings of the Mascot-Num 2022 Annual Conference (MASCOT NUM 2022), Clermont-Ferrand, France.
📣 E. Fekhari, B. Iooss, V. Chabridon and J. Muré (2023). "Rare event estimation using nonparametric Bernstein adaptive sampling". In: Proceedings of the Mascot-Num 2023 Annual Conference (MASCOT-NUM 2023), Le Croisic, France.
📣 E. Fekhari, V. Chabridon, J. Muré and B. Iooss (2024). "Sensitivity-Informed Nonparametric Adaptive Conditional Sampling for Robust Reliability Analysis". In: SIAM Conference on Uncertainty Quantification (SIAM UQ24), Trieste, Italy.
📣 Le Printemps de la Recherche 2022, Nantes, France. "Traitement des incertitudes pour la gestion d’actifs éoliens".
📣 Journées Scientifiques de l’Eolien 2024, Saint-Malo, France. "Evaluation probabiliste de la fiabilité en fatigue des structures éoliennes en mer".
👉 otkerneldesign: Python package generating designs of experiments based on kernel methods such as kernel herding.
👉 bancs: Python package implementing the "Bernstein Adaptive Nonparametric Conditional Sampling" method for rare event estimation.
👉 copulogram: Python package proposing a synthetic visualization tool for multivariate distributions.
👉 ctbenchmark: Python package presenting a standardized process to benchmark different sampling methods for central tendency estimation
This manuscript is based on the CUED PhD thesis template developed by Krishna Kumar.