Di Qi, Purdue University, Statistical reduced-order models and machine learning-based closure strategies for turbulent dynamical systems
ZoomThe capability of using imperfect statistical reduced-order models to capture crucial statistics in complex turbulent systems is investigated. Much simpler and more tractable block-diagonal models are proposed to approximate the complex and high-dimensional turbulent dynamical equations using both parameterization and machine learning strategies. A systematic framework of correcting model errors with empirical information theory is…