This overview presents examples of applications of high frame rate imaging diagnostics in
fundamental and applied combustion research. Progress in the performance of high frame …

In recent years the fluid mechanics community has been intensely focused on pursuing
solutions to its long-standing open problems by exploiting the new machine learning (ML) …

Data-driven decompositions are becoming essential tools in fluid dynamics, allowing for
tracking the evolution of coherent patterns in large datasets, and for constructing low-order …

A tool to analyse correlated events in turbulent flows based on an extended proper
orthogonal decomposition (POD) is proposed in this paper. A general definition of extended …

We present a new model reduction approach to fluid simulation, enabling large, real-time,
detailed flows with continuous user interaction. Our reduced model can also handle moving …

Based on time-resolved PIV (TRPIV) data, a new proper orthogonal decomposition (POD)
application is developed to recover the time information between two consecutive PIV time …

Data reconstruction of rotating turbulent snapshots is investigated utilizing data-driven tools.
This problem is crucial for numerous geophysical applications and fundamental aspects …

Internal hydrodynamics and its coupling with structural dynamics are non-negligible
processes in the design phase of aerospace systems. An improved understanding of the …

Data-driven decompositions of particle image velocimetry (PIV) measurements are widely
used for a variety of purposes, including the detection of coherent features (eg vortical …

The aim of this paper is to make use of PIV and high-speed PIV in a research engine of
moderate tumbling ratio in order to analyze both the spatial structure of the flow and its …