Data-driven model reduction constructs reduced-order models of large-scale systems by
learning the system response characteristics from data. Existing methods build the reduced …

All rights are solely and exclusively licensed by the Publisher, whether the whole or part of
the material is concerned, specifically the rights of translation, reprinting, reuse of …

This article reviews state-of-the-art numerical techniques for fluid–structure interaction (FSI)
of full-scale wind-turbine systems. Simulation of floating wind turbines subjected to …

This work presents a collection of advanced computational methods, and their coupling, that
enable prediction of fatigue-damage evolution in full-scale composite blades of wind …

This paper envisions the possibility of a Conscious Aircraft: an aircraft of the future with
features of consciousness. To serve this purpose, three main fields are examined …

Loss of thrust (LOT) emergencies create the need for quickly providing pilots with valid
trajectories for safely landing the aircraft. It is easy to pre-compute total lost of thrust …

Dynamic Data Driven Applications Systems (DDDAS) is a systems design framework that
focuses on integrating high-dimensional physical model simulations, run-time …

Sensors are crucial to modern mechanical systems. The location of these sensors can often
make them vulnerable to outside interferences and failures, and the use of sensors over a …

This work presents a data-driven online adaptive model reduction approach for systems that
undergo dynamic changes. Classical model reduction constructs a reduced model of a large …

Abstract Dynamic Data Driven Applications Systems (DDDAS) is a paradigm for systems
analysis and design, and a framework that dynamically couples high-dimensional physical …