| Ensemble of surrogates combining Kriging and Artificial Neural Networks for reliability analysis with local goodness measurement C Ren, Y Aoues, D Lemosse, ES De Cursi Structural Safety 96, 102186, 2022 | 45 | 2022 |
| Reliability assessment of an offshore wind turbine jacket under one ultimate limit state considering stress concentration with active learning approaches C Ren, Y Aoues, D Lemosse, ES De Cursi Ocean Engineering 281, 114657, 2023 | 8 | 2023 |
| Comparative study of load simulation approaches used for the dynamic analysis on an offshore wind turbine jacket with different modeling techniques C Ren, Y Aoues, D Lemosse, ES De Cursi Engineering Structures 249, 113308, 2021 | 8 | 2021 |
| AK-MDAmax: Maximum fatigue damage assessment of wind turbine towers considering multi-location with an active learning approach C Ren, Y Xing Renewable Energy 215, 118977, 2023 | 6 | 2023 |
| Reliability assessment of an offshore wind turbine jacket with active learning approaches C Ren Normandie Université, 2022 | 6 | 2022 |
| ALK-PE: An efficient active learning Kriging approach for wave energy converter power matrix estimation C Ren, J Tan, Y Xing Ocean Engineering 286, 115566, 2023 | 4 | 2023 |
| Global sensitivity analysis of offshore wind turbine jacket C Ren, Y Aoues, D Lemosse, ES De Cursi Proceedings of the 5th International Symposium on Uncertainty Quantification …, 2021 | 4 | 2021 |
| Structural reliability assessment of offshore wind turbine jacket considering corrosion degradation C Ren, Y Aoues, D Lemosse, ES De Cursi 14th WCCM-ECCOMAS Congress, 2020 | 3 | 2020 |
| Applying a machine learning method for cumulative fatigue damage estimation of the IEA 15MW wind turbine with monopile support structures C Ren, Y Xing IOP Conference Series: Materials Science and Engineering 1294 (1), 012014, 2023 | 2 | 2023 |
| Application of an active learning method for cumulative fatigue damage assessment of floating wind turbine mooring lines C Ren, Y Xing, KS Patel Results in Engineering, 102122, 2024 | 1 | 2024 |
| Application of a data-driven approach for maximum fatigue damage prediction of an unbonded flexible riser T Dai, J Zhang, C Ren, Y Xing, S Sævik, N Ye, X Jin, J Wu Ocean Engineering 306, 118053, 2024 | | 2024 |
| An efficient active learning Kriging approach for expected fatigue damage assessment applied to wind turbine structures C Ren, Y Xing Ocean Engineering 305, 118034, 2024 | | 2024 |
| PRACTICAL EXAMPLES OF IMPLEMENTING CHALLENGE-BASED LEARNING IN ENGINEERING EDUCATION FOR STUDENTS, LIFE-LONG LEARNERS AND EDUCATORS–EXPERIENCE AT THE UNIVERSITY OF STAVANGER … M Shahverdi, Y Xing, C Ren INTED2024 Proceedings, 2239-2246, 2024 | | 2024 |
| Assessment of a novel PTO system for swell energy convertors using digital twin modelling C Ren, Y Xing, L Moen IOP Conference Series: Materials Science and Engineering 1294 (1), 012009, 2023 | | 2023 |
| Structural Reliability Assessment of Offshore Wind Turbine Supports by Combining Adaptive Kriging and Artificial Neural Network Chao Ren, Younes Aoues, Didier Lemosse, and Eduardo Souza de Cursi The 32nd European Safety and Reliability Conference, 2022 | | 2022 |
| Numerical analysis of the impact of flanges, cutout and stiffener on wind turbine tower behaviour C REN, Y AOUES, D LEMOSSE, ES DE CURSI | | |
| Reliability assessment of an offshore wind turbine jacket considering stress concentration with active learning approaches C REN, Y AOUES, D LEMOSSE, E SOUZA DE CURSI Available at SSRN 4290322, 0 | | |
Younes AouesMCF INSA de ROUENVerified email at insa-rouen.fr
