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6/6/22 11:00 - 13:00 Machine Learning and Data-Driven Approaches for Aerodynamic Analysis and Uncertainty Quantification Minisymposium organized by Esther Andrés |
Room: Spitsbergen MS86A Chair: Esther Andrés |
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Data-Driven Reduced Order Modeling for Aerodynamic Flow Predictions
Derrick A. Hines Chaves and Philipp Bekemeyer Comparison of uncertainty quantification methods for mathematical and mechanical problems in intermediate dimensions Jacques Peter and Quentin Bennehard A comparison of machine learning methods for pressure coefficient prediction of an aeronautical configuration Alejandro Gorgues, Rodrigo Castellanos, Jaime Bowen and Esther Andrés Reynolds stress correction by machine learning methods with physical constraints Thomas Philibert, Andrea Ferrero, Angelo Iollo and Francesco Larocca MPI-Parallel Machine Learning Algorithms for the Analysis of High-Speed Video Data Alexander Ruettgers and Anna Petrarolo Neural network prediction of the flow field in a periodic domain with hyper-neural network parametrization Ondřej Bublík, Václav Heidler, Aleš Pecka and Jan Vimmr |
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