Background
Optimal design of marine renewable energy structures requires modeling several coupled phenomena. As a consequence, numerical simulations become expensive and complexe especially in the stochastic framework with uncertainties modeled as random variables. Moreover, compared to other industries, such as aeronautic or shipbuilding, engineers have only few feedbacks. Therefore, mastering all the conception steps and benefiting from the sensor measurements on the structure is of prime concern.
Scientific advances and innovation
- To take into account the different sources of error (modeling error, discretization error) in the computation of probability of failure.
- To develop methods that enable spatial or temporal zooms on critical details for the reliability analysis.
- To update models from sensor measurements to improve its quality.
Expected technical and economic impact
The expected impact of the MUSCAS project is to develop numerical tools in order to consider coupled phenomena in a stochastic framework on complex structures, such as jacket foundations of wind turbine. To use these tools for reliability analysis and for goal-oriented sensor positioning.
Key project milestones
- February 2018 - The project begins
Results
Parametric studies on 2-dimensional mechanical problems with random elasticity parameters have shown the influence of the mesh size on the estimation of the probability of failure. The discretization error may not be negligible.
A numerical strategy was developed to adapt the finite element discretization during the estimation of the probability of failure using multi-level kriging. By exploiting a posteriori error estimators, it is possible to optimize the construction of the meta model : computations close to the limit state are done on a fine mesh to guarantee precision whereas computations far for the limit state can be done on a coarse mesh which is sufficient to get a trend and cheap. A second approach, based on a priori error estimators, enables the construction of a multi-level kriging meta model who enables to compute the probability of failure without discretization error. Those two methods have been used on two-dimensionnal mechanical problems with 2 random variables.
In the context of fatigue of offshore structures, the local stress (that can be computed or measured) is polluted bu the measurement error or the discretization error. Considering the local stress is bounded by two values at each time step, a method to build a stress history maximizing the damage and a stress history minimizing the dommage has been developed. From those two histories, two extreme damages (minimum and maximum) are computed using Rainflow counting and S-N curves.
From synthetic data, a stochastic model of the damage evolution based on a cumulative Gamma process has been developed. It enables the computation of probability of failure, conditional probabilities and generation of possible trajectories of damage.
Publications and papers published
Oral communications ans posters
- A Monitoring Methodology of Bio-Colonisation on Mooring Lines of Floating Wind Turbines – Benjamin DECUREY, Ludovic MELL, Franck SCHOEFS – poster at FAID march 2019.
- Prise en compte de l’erreur de discrétisation pour l’estimation de probabilité de défaillance par surface de réponse– Ludovic Mell, Valentine Rey, Franck Schoefs. Communication at the Congrès français de mécanique (CFM) in Brest in August, 2019
- Computation of discretization errors bounds on the fatigue damage of shear plates, Ludovic Mell, Valentine Rey, Franck Schoefs – Presentation at 4th International Conference of Renewable Energy Offshore, 14th October 2020
- Auto-adaptive Multi-Fidelity Kriging approach to estimate structural reliability, Ludovic Mell, Valentine Rey, Franck Schoefs. ASCE Engineering Mechanics Institute International Conference 2021, Session MS-32 Uncertainty Quantification in Engineering Mechanics: Theory, Methods, and Practice, March 24th 2021
- A multifidelity approach using discretization error bounds to estimate the probability of failure of structures, World Congress Computational Mechanics (digital), Ludovic Mell, Valentine Rey, Franck Schoefs, 2021
- Finite element-fidelity parametrization of kriging metamodels for structural reliability assessement, 31st European Safety and Reliability Conference – ESREL – 19-23 Septembre 2021 , Ludovic Mell, Valentine Rey, Franck Schoefs, 2021.
- Stratégie multi-fidélité pour le calcul de probabilité de défaillance des structures – Ludovic Mell, Valentine Rey, Franck Schoefs – Presentation at 11 èmes Journées Fiabilité des Matériaux et des Structures, March 2020 reported in 2022
Publications
- Multifidelity adaptive kriging metamodel based on discretization error bounds, Ludovic Mell, Valentine Rey, Franck Schoefs , International Journal of Numerical methods and Engineering, June 2020
For a non-specialist audience:
- Workshop on material failure led by Valentine Rey, at the “Village des Sciences” at Centrale Nantes, as part of the Science Fair, Nantes, 03/04 October 2019
- “Les énergies marines en France : pourquoi, comment ?”, Pint Of Science, with Ludovic Mell, 20 may 2019
