MS004B Data-Driven innovations and machine learning In aerodynamic analysis, optimization and uncertainty quantification II
Main Organizer:
Dr.
Esther Andrés Pérez
(
INTA
, Spain
)
Chaired by:
Dr. Esther Andrés Pérez (INTA , Spain) , Dr. Domenico Quagliarella (CIRA , Italy)
Dr. Esther Andrés Pérez (INTA , Spain) , Dr. Domenico Quagliarella (CIRA , Italy)
Scheduled presentations:
-
Sparse Adaptive Multi-Fidelity Design of Experiments for data fusion in aerodynamics
-
Geometric Parameter Based Machine Learning for Pressure Distribution Prediction on Aerodynamic Surfaces
-
Towards a Digital Twin of Incompressible Fluid Flows Based on Physics-Informed Gaussian Processes
-
An Autoencoder Framework for Multi-Fidelity Aerodynamic Data
-
A Generative Approach To Transonic Wing Pressure Prediction
-
Multi-fidelity neural network surrogates for efficient multi-objective optimization of composite shell dynamics
