Abstract Space–time scale-resolved diagnostic and computational campaigns routinely
produce high-fidelity multi-disciplinary truth-model quality datasets for complex …

A comprehensive review of modelling techniques for the flow-induced vibration (FIV) of bluff
bodies is presented. This phenomenology involves bidirectional fluid–structure interaction …

Variational autoencoders (VAEs) have shown promising potential as artificial neural
networks (NN) for developing reduced-order models (ROMs) in the context of turbulent …

A data-driven reduced-order model (ROM) based on long short-term memory neural network
(LSTM-NN) for the prediction of the flow past a circular cylinder undergoing two-degree-of …

The coherent structures and wake dynamics of a two-degree-of-freedom vibrating cylinder
with a low mass ratio at R e= 5300 are investigated by means of proper orthogonal …

Projection-based reduced-order models (ROMs) play a crucial role in simplifying the
complex dynamics of fluid systems. Such models are achieved by projecting the Navier …

Predicting the subcritical transition in fluid dynamic systems remains a challenging task, but
recent advancements utilizing edge tracking methods, polynomial Lyapunov functions, and …

The extraction of the most dynamically important coherent flow structures using reduced
order models (ROM) is a challenging task in various fluid dynamics applications. In …

Bluff bodies have extensive implementation in engineering. For instance, marine risers,
jumpers, umbilicals, and bundle flowlines are the examples of the circular bluff bodies which …

A comprehensive review of modelling techniques for the flow-induced vibration (FIV) of bluff
bodies is presented. This phenomenology involves bidirectional fluid–structure interaction …