Zobrazeno 1 - 10
of 40
pro vyhledávání: '"Morzyñski, Marek"'
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 two-dimensional incompressible flow of the unforced fluidic pinball. T
Externí odkaz:
http://arxiv.org/abs/2111.13028
Publikováno v:
Proceedings of the ASME 2018 5th Joint US-European Fluids Engineering Summer
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 on the route to chaos in this system without actuation, as the Reynolds
Externí odkaz:
http://arxiv.org/abs/2104.05709
Autor:
Deng, Nan, Pastur, Luc R., R., Bernd R. Noack Bernd, Cornejo-Maceda, Guy, Lusseyran, François, Jean-Christophe, Jean-Christophe Loiseau, Morzyński, Marek
Publikováno v:
22e Rencontre du Non-Lineaire, Mar 2019, Paris, France
In this work, we are interested in the transient dynamics of a fluid configuration consisting of three fixed cylinders whose axes distribute over an equilateral triangle in transverse flow << fluidic pinball >>. As the Reynolds number is increased on
Externí odkaz:
http://arxiv.org/abs/2104.05105
Publikováno v:
11th Chaotic Modeling and Simulation International Conference. CHAOS 2018. Springer Proceedings in Complexity. Springer, Cham
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 host a range of interacting frequencies and to allow testing of control
Externí odkaz:
http://arxiv.org/abs/2104.05104
We stabilize the flow past a cluster of three rotating cylinders, the fluidic pinball, with automated gradient-enriched machine learning algorithms. The control laws command the rotation speed of each cylinder in an open- and closed-loop manner. Thes
Externí odkaz:
http://arxiv.org/abs/2011.06661
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 distance to each other. The starting point is a Galerkin model of a bluff-b
Externí odkaz:
http://arxiv.org/abs/2011.06254
We propose an automated analysis of the flow control behaviour from an ensemble of control laws and associated time-resolved flow snapshots. The input may be the rich data base of machine learning control (MLC) optimizing a feedback law for a cost fu
Externí odkaz:
http://arxiv.org/abs/2008.12924
We propose an automatable data-driven methodology for robust nonlinear reduced-order modelling from time-resolved snapshot data. In the kinematical coarse-graining, the snapshots are clustered into few centroids representable for the whole ensemble.
Externí odkaz:
http://arxiv.org/abs/2001.02911
Reduced-order representations of an ensemble of cylinder wake transients are investigated. Locally linear embedding identifies a two-dimensional manifold with a maximum error of 1% from new snapshot data. This representation outperforms a 50-dimensio
Externí odkaz:
http://arxiv.org/abs/1906.07822
Autor:
Li, Yiqing, Cui, Wenshi, Jia, Qing, Li, Qiliang, Yang, Zhigang, Morzyński, Marek, Noack, Bernd R.
We address a challenge of active flow control: the optimization of many actuation parameters guaranteeing fast convergence and avoiding suboptimal local minima. This challenge is addressed by a new optimizer, called explorative gradient method (EGM).
Externí odkaz:
http://arxiv.org/abs/1905.12036