Turbulence pervades our world, from weather patterns to the air entering our lungs. This
book describes methods that reveal its structures and dynamics. Building on the existence of …

We present the first machine-learned multiple-input multiple-output aerodynamic feedback
control under varying operating conditions. Closed-loop control is relevant to many fluid …

In this paper we compare various methods of calibration that can be used in practice to
improve the accuracy of reduced‐order models based on proper orthogonal decomposition …

This paper proposes a large eddy simulation reduced order model (LES-ROM) framework
for the numerical simulation of convection-dominated flows. In this LES-ROM framework, the …

In this paper, we propose a new evolve‐then‐filter reduced order model (EF‐ROM). This is a
regularized ROM (Reg‐ROM), which aims to add numerical stabilization to proper …

In this paper, we propose a novel ROM stabilization strategy for under-resolved convection-
dominated flows, the approximate deconvolution Leray ROM (ADL-ROM). The new ADL …

A domain decomposition method which couples a high and a low-fidelity model is proposed
to reduce the computational cost of a flow simulation. This approach requires to solve the …

We propose the first machine-learned control-oriented flow estimation for multiple-input,
multiple-output plants. The starting point is constant actuation with open-loop actuation …

Partial differential equations (PDEs) are often dependent on input quantities that are
uncertain. To quantify this uncertainty PDEs must be solved over a large ensemble of …

This paper explores some numerical alternatives that can be exploited to derive efficient low‐
order models of the Navier–Stokes equations. It is shown that an optimal solution sampling …