The recent development of machine learning (ML) and Deep Learning (DL) increases the
opportunities in all the sectors. ML is a significant tool that can be applied across many …

SIMPLE aerodynamic configurations under even modest conditions can exhibit complex
flows with a wide range of temporal and spatial features. It has become common practice in …

Digital twin can be defined as a virtual representation of a physical asset enabled through
data and simulators for real-time prediction, optimization, monitoring, controlling, and …

THE field of fluid mechanics involves a range of rich and vibrant problems with complex
dynamics stemming from instabilities, nonlinearities, and turbulence. The analysis of these …

We consider the frequency domain form of proper orthogonal decomposition (POD), called
spectral proper orthogonal decomposition (SPOD). Spectral POD is derived from a space …

Aerodynamic modeling plays an important role in multiphysics and design problems, in
addition to experiment and numerical simulation, due to its low-dimensional representation …

Turbulent flows are characterized by the non-linear cascades of energy and other inviscid
invariants across a huge range of scales, from where they are injected to where they are …

Used to analyze the time-evolution of fluid flows, dynamic mode decomposition (DMD) has
quickly gained traction in the fluids community. However, the existing DMD literature focuses …

Closed-loop turbulence control is a critical enabler of aerodynamic drag reduction, lift
increase, mixing enhancement, and noise reduction. Current and future applications have …

This article discusses the description of wall-bounded turbulence as a deterministic high-
dimensional dynamical system of interacting coherent structures, defined as eddies with …