With an increasing number of offshore operations taking place at sea, the occurrence of
dropped objects has become more widespread and frequent. These incidents can result in a …

Computational Fluid Dynamics (CFD) generates high-dimensional spatiotemporal data. The
data-driven method approach to extracting physical information from CFD has attracted …

The chaotic state of microfluidic devices such as electroosmotic micromixers has received
extensive attention. Its unsteady flow and multi-physics mask low-dimensional structure and …

We propose a Cluster-Based Control (CBC) strategy for model-free feedback drag reduction
with multiple actuators and full-state feedback. CBC consists of three steps. First, the input of …

In this study we propose a novel data-driven reduced-order model for complex dynamics,
including nonlinear, multi-attractor, multi-frequency and multiscale behaviours. The starting …

A data-driven approach to estimate the global spectrum of gravitational planar liquid jets
(sheet or curtain flows) is presented in this work. The investigation is carried out by means of …

A large eddy simulation (LES) of a squirrel cage fan (SCF) provides a precise representation
of turbulent flows with different degrees of complexity. This study comprehensively analyzes …

Uniform flow past side-by-side circular cylinders is a classical fluid dynamic model that
triggers rich phenomena, from which asymmetric wakes usually emerge. Such asymmetry …

Flow past one or multiple bluff bodies is almost ubiquitous in nature and industrial
applications, and its rich underlying physics has made it one of the most typical problems in …

This study introduces the Extended Cluster-based Network Modeling (eCNM), a
methodology to analyze complex fluid flows. The eCNM focuses on characterizing dynamics …