91 citations · 226 across the 11 of their papers we have counts for
11 papers
Orbital cluster-based network modelling
Antonio Colanera, Nan Deng, Matteo Chiatto +2
We propose a novel reduced-order methodology to describe complex multi-frequency fluid dynamics from time-resolved snapshot data. Starting point is the Cluster-based Network Model…
Revisit the intrinsic features of flip-flopping flow behind side-by-side circular cylinders
Wailing Chen, Yuhao Yan, Chunning Ji +4
As one of the most intriguing wake patterns of two side-by-side circular cylinders at an intermediate gap spacing, the flip-flopping (FF) flow has attracted great attention of fund…
Dynamics-augmented cluster-based network model
Chang Hou, Nan Deng, Bernd R. Noack
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 starti…
Trajectory-optimized cluster-based network model for the sphere wake
Chang Hou, Nan Deng, Bernd R. Noack
We propose a novel trajectory-optimized Cluster-based Network Model (tCNM) for nonlinear model order reduction from time-resolved data following Li et al. ["Cluster-based network m…
From snapshots to manifolds - A tale of shear flows
Ehsan Farzamnik, Andrea Ianiro, Stefano Discetti +4
We propose a novel non-linear manifold learning from snapshot data and demonstrate its superiority over Proper Orthogonal Decomposition (POD) for shedding-dominated shear flows. Ke…
Cluster-based hierarchical network model of the fluidic pinball -- Cartographing transient and post-transient, multi-frequency, multi-attractor behaviour
Nan Deng, Bernd R. Noack, Marek Morzyński +1
We propose a self-supervised cluster-based hierarchical reduced-order modelling methodology to model and analyse the complex dynamics arising from a sequence of bifurcations for a…
Route to Chaos in the Fluidic Pinball
Nan Deng, Luc R. Pastur, Marek Morzyński +1
The fluidic pinball has been recently proposed as an attractive and effective flow configuration for exploring machine learning fluid flow control. In this contribution, we focus o…
Low-dimensional Flow Models from high-dimensional Flow data with Machine Learning and First Principles
Nan Deng, Luc R. Pastur, Bernd R. Noack
Reduced-order modelling and system identification can help us figure out the elementary degrees of freedom and the underlying mechanisms from the high-dimensional and nonlinear dyn…
Reduced-order modeling of the fluidic pinball
Luc R. Pastur, Nan Deng, Marek Morzyński +1
The fluidic pinball is a geometrically simple flow configuration with three rotating cylinders on the vertex of an equilateral triangle. Yet, it remains physically rich enough to h…
Galerkin force model for transient and post-transient dynamics of the fluidic pinbal
Nan Deng, Bernd R. Noack, Marek Morzyński +1
We propose an aerodynamic force model associated with a Galerkin model for the unforced fluidic pinball, the two-dimensional flow around three equal cylinders with one radius dista…
Low-order model for successive bifurcations of the fluidic pinball
Nan Deng, Bernd R. Noack, Marek Morzynski +1
We propose the first least-order Galerkin model of an incompressible flow undergoing two successive supercritical bifurcations of Hopf and pitchfork type. A key enabler is a mean-f…