Artificial neural networks and guided gene expression programming to predict wall pressure spectra beneath turbulent boundary layers
Nachiketa Narayan Kurhade,
Nagabhushana Rao Vadlamani,
Akash Haridas
Abstract:This study evaluates the efficacy of two machine learning (ML) techniques, namely, artificial neural networks (ANNs) and gene expression programing (GEP), that use data-driven modeling to predict wall pressure spectra (WPS) underneath turbulent boundary layers. Different datasets of WPS from experiments and high-fidelity numerical simulations covering a wide range of pressure gradients and Reynolds numbers are considered. For both ML methods, an optimal hyperparameter environment is identified that yields accu… Show more
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