| Artificial neural networks modeling of wall pressure spectra beneath turbulent boundary layers J Dominique, J Van den Berghe, C Schram, MA Mendez Physics of Fluids 34 (3), 2022 | 24 | 2022 |
| Challenges and opportunities for machine learning in fluid mechanics MA Mendez, J Dominique, M Fiore, F Pino, P Sperotto, J Berghe arXiv preprint arXiv:2202.12577, 2022 | 10 | 2022 |
| A 1D model for the unsteady gas dynamics of ejectors J Van den Berghe, BRB Dias, Y Bartosiewicz, MA Mendez Energy 267, 126551, 2023 | 8 | 2023 |
| An extension of the compound flow theory with shear and friction JV Berghe, MA Mendez, Y Bartosiewicz arXiv preprint arXiv:2401.07236, 2024 | | 2024 |
| An extension of the compound flow theory with shear and friction J Van den Berghe, MA Mendez, Y Bartosiewicz arXiv e-prints, arXiv: 2401.07236, 2024 | | 2024 |
| Reinforcement Twinning: from digital twins to model-based reinforcement learning L Schena, P Marques, R Poletti, S Ahizi, JV Berghe, MA Mendez arXiv preprint arXiv:2311.03628, 2023 | | 2023 |
| A Machine Learning-based Calibration of a 1D ejector model from CFD J Van den Berghe, JB Vemula, Y Bartosiewicz, MA Mendez 36th International Conference on Efficiency, Cost, Optimization, Simulation …, 2023 | | 2023 |
| Calibration of a 1D ejector model from full-scale experiments J Van den Berghe, M Delsipee, P Planquart, Y Bartosiewicz, MA Mendez ASTFE Digital Library 8, 1151, 2023 | | 2023 |
| Unsteady 1D gas dynamics in ejectors: a pipeline analogy J Van den Berghe, BRB Dias, Y Bartosiewicz, MA Mendez 22nd Computational Fluids Conference, 2023 | | 2023 |
| An overview on the development and calibration of a 1D ejector model J Van den Berghe, Y Bartosiewicz, MA Mendez 14th Symposium of VKI PhD Research 2023, 2023 | | 2023 |
| An extension of the compound flow theory with J Van den Berghe, MA Mendez, Y Bartosiewicz | | |
