We conducted high-resolution(HL) reconstruction of turbulence on porous media using machine learning techniques. The previously employed DNS method has been time-consuming and expensive. As a result, research on leveraging maching learning for HL reco...
We conducted high-resolution(HL) reconstruction of turbulence on porous media using machine learning techniques. The previously employed DNS method has been time-consuming and expensive. As a result, research on leveraging maching learning for HL reconstruction has been ongoing. In this study, we aim to investigate the feasibility of restoring the veloctiy field of turbulence in porous meida at a HL through machine learning models.