Deep reinforcement learning (DRL) has been applied to a variety of problems during the
past decade and has provided effective control strategies in high-dimensional and non …

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 book is an introduction to machine learning control (MLC), a surprisingly simple model-
free methodology to tame complex nonlinear systems. These systems are assumed to be …

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

Anisotropic particles are common in many industrial and natural turbulent flows. When these
particles are small and neutrally buoyant, they follow Lagrangian trajectories while …

A small amount of polymer additives can cause substantial reduction in the energy
dissipation and friction loss of turbulent flow. The problem of polymer-induced drag …

The ability to actively or passively manipulate a flow field to bring about a desired change is
of immense technological and economical importance. This volume provides a thorough, up …

Manufacturing processes that can create extremely small machines have been developed in
recent years. Microelectromechanical systems (MEMS) refer to devices that have …

This book deals with the simulation of the incompressible Navier-Stokes equations for
laminar and turbulent flows. The book is limited to explaining and employing the finite …

Direct numerical simulations (DNS) and optimal control theory are used in a predictive
control setting to determine controls that effectively reduce the turbulent kinetic energy and …