03.1 - Aerodynamics – CFD Methods and Validation
MACHINE LEARNING INTEGRATION IN COMPUTATIONAL FLUID DYNAMICS FOR RAPID FLOW FIELD PREDICTION
M. Nemati¹, A. Jahangirian¹; ¹amirkabir university of technology, Iran
This study introduces a deep learning approach integrated with Computational Fluid Dynamics (CFD) for efficient prediction of aerodynamic turbulent flow fields, particularly for wing section geometries. Utilizing minimal datasets, the research leverages the PARSEC method for precise airfoil geometry extraction, significantly enhancing prediction speed and accuracy. This method demonstrates versatility and robustness in predicting complex flow patterns, showcasing potential for diverse aerodynamic applications.