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

Recurrent neural network (RNN) and Long Short-term Memory (LSTM) networks are the
common go-to architecture for exploiting sequential information where the output is …

Deep neural networks are being widely used for feature representation learning in diverse
problem areas ranging from object recognition and speech recognition to robotic perception …

Open-and closed-loop control of a turbulent mixing layer is experimentally performed in a
dedicated large scale, low speed wind-tunnel facility. The flow is manipulated by an array of …

Open-and closed-loop control of a turbulent mixing layer is experimentally performed in a
dedicated large scale, low speed wind-tunnel facility. The flow is manipulated by an array of …

The optimization and control of fluid systems, such as a wing in a high-speed flow, is a
central challenge in modern engineering. Turbulent fluids are characterized by high …

A novel framework for closed-loop control of turbulent flows is tested in an experimental
mixing layer flow. This framework, called Machine Learning Control (MLC), provides a …

Deep learning became the method of choice in recent year for solving a wide variety of
predictive analytics tasks. For sequence prediction, recurrent neural networks (RNN) are …

Deep learning consists of various machine learning algorithms that aim to learn multiple
levels of abstraction from data in a hierarchical manner. It is a tool to construct models using …