The field of fluid mechanics is rapidly advancing, driven by unprecedented volumes of data
from experiments, field measurements, and large-scale simulations at multiple …

Supersonic jets, particularly shock-containing jets, often exhibit high-intensity, discrete-
frequency acoustic tones. These tones are the signature of an aeroacoustic resonance loop …

Data-driven discovery is revolutionizing how we model, predict, and control complex
systems. Now with Python and MATLAB®, this textbook trains mathematical scientists 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 …

The sparse identification of nonlinear dynamics (SINDy) is a recently proposed data-driven
modelling framework that uses sparse regression techniques to identify nonlinear low-order …

We propose a general dynamic reduced-order modelling framework for typical experimental
data: time-resolved sensor data and optional non-time-resolved particle image velocimetry …

Organized structures in turbulent jets can be modeled as wavepackets. These are
characterized by spatial amplification and decay, both of which are related to stability …

Data-driven methods have become an essential part of the methodological portfolio of fluid
dynamicists, motivating students and practitioners to gather practical knowledge from a …

In fluid dynamics, predicting and characterizing bifurcations, from the onset of unsteadiness
to the transition to turbulence, is of critical importance for both academic and industrial …

This work proposes a feedback-loop strategy to suppress intrinsic oscillations of resonating
flows in the fully nonlinear regime. The frequency response of the flow is obtained from the …