English
Related papers

Related papers: Modal decomposition of fluid-structure interaction…

200 papers

The concept of nonlinear modes is useful for the dynamical characterization of nonlinear mechanical systems. While efficient and broadly applicable methods are now available for the computation of nonlinear modes, nonlinear modal testing is…

Systems and Control · Electrical Eng. & Systems 2020-11-18 Maren Scheel , Simon Peter , Remco I. Leine , Malte Krack

In this paper, we generalize the minimum flow decomposition problem (MFD) to incorporate uncertain edge capacities and tackle it from the perspective of robust optimization. In the classical flow decomposition problem, a network flow is…

Optimization and Control · Mathematics 2025-10-17 Moritz Stinzendörfer , Philine Schiewe , Fabricio Oliveira

We present a formalism for dissipation-optimized decomposition of the strain rate tensor (SRT) of turbulent flow data using Proper Orthogonal Decomposition (POD). The formalism includes a novel inverse spectral SRT operator allowing the…

Data-driven dimensionality reduction methods such as proper orthogonal decomposition (POD) and dynamic mode decomposition (DMD) have proven to be useful for exploring complex phenomena within fluid dynamics and beyond. A well-known…

Fluid Dynamics · Physics 2022-12-27 Elena Marensi , Gökhan Yalnız , Björn Hof , Nazmi Burak Budanur

In this work, the application of the multi-dimensional higher order dynamic mode decomposition (HODMD) is proposed for the first time to analyse combustion databases. In particular, HODMD has been adapted and combined with other…

The simulation of atmospheric flows by means of traditional discretization methods remains computationally intensive, hindering the achievement of high forecasting accuracy in short time frames. In this paper, we apply three reduced order…

Fluid Dynamics · Physics 2023-07-19 Arash Hajisharifi , Michele Girfoglio , Annalisa Quaini , Gianluigi Rozza

Elastic topological states have been receiving increased intention in numerous scientific and engineering fields due to their defect-immune nature, resulting in applications of vibration control and information processing. Here, we present…

Applied Physics · Physics 2023-05-31 Shuaifeng Li , Panayotis G. Kevrekidis , Jinkyu Yang

Dynamic mode decomposition (DMD) represents an effective means for capturing the essential features of numerically or experimentally generated flow fields. In order to achieve a desirable tradeoff between the quality of approximation and…

Fluid Dynamics · Physics 2014-12-11 Mihailo R. Jovanović , Peter J. Schmid , Joseph W. Nichols

Phononic materials (PMs) are periodic media that exhibit novel elastodynamic responses. While PMs have made progress in vibration-mitigation applications, recent studies have demonstrated the potential of PMs to passively and adaptively…

Multiscale Proper Orthogonal Decomposition (mPOD) decomposes fluid flows into energy-optimal modes within prescribed frequency bands by combining Proper Orthogonal Decomposition with a multiresolution analysis (MRA). In its classical…

Fluid Dynamics · Physics 2026-04-15 Marek Belda , Lorenzo Schena , Romain Poletti , Martin Isoz , Tomáš Hyhlík , Miguel A. Mendez

Modal analysis of fluid flows is essential to understand flow physics and fluid-solid interaction mechanisms, and to implement flow control. Unlike unstable flow, the intrinsic attenuation of subcritical flow has led to failures to…

Fluid Dynamics · Physics 2022-09-07 Zhen Lyu , Jiaqing Kou , Weiwei Zhang

The performances of a new data processing technique, namely the Empirical Mode Decomposition, are evaluated on a fully developed turbulent velocity signal perturbed by a numerical forcing which mimics a long-period flapping. First, we…

Fluid Dynamics · Physics 2015-05-20 Nicolas Mazellier , Fabrice Foucher

The characterization of intermittent, multiscale and transient dynamics using data-driven analysis remains an open challenge. We demonstrate an application of the Dynamic Mode Decomposition (DMD) with sparse sampling for the diagnostic…

Dynamical Systems · Mathematics 2020-05-18 Krithika Manohar , Eurika Kaiser , Steven L. Brunton , J. Nathan Kutz

Dynamic mode decomposition (DMD) is a recently developed tool for the analysis of the behavior of complex dynamical systems. In this paper, we will propose an extension of DMD that exploits low-rank tensor decompositions of potentially…

Numerical Analysis · Mathematics 2019-08-14 Stefan Klus , Patrick Gelß , Sebastian Peitz , Christof Schütte

We present a new model and a novel loosely coupled partitioned numerical scheme modeling fluid-structure interaction (FSI) in blood flow allowing non-zero longitudinal displacement. Arterial walls are modeled by a {linearly viscoelastic,…

Numerical Analysis · Mathematics 2015-06-05 Martina Bukac , Suncica Canic , Roland Glowinski , Josip Tambaca , Annalisa Quaini

We present parameter-interpolated dynamic mode decomposition (piDMD), a parametric reduced-order modeling framework that embeds known parameter-affine structure directly into the DMD regression step. Unlike existing parametric DMD methods…

Systems and Control · Electrical Eng. & Systems 2026-04-15 Ananda Chakrabarti , Haitham H. Saleh , Indranil Nayak , Balasubramaniam Shanker , Fernando L. Teixeira , Debdipta Goswami

This work investigates the spatio-temporal evolution of coherentstructures in the wake of a high-speed train. SPOD is used to extract energy spectra and empirical modes for both symmetric and antisymmetric components of the fluctuating flow…

For problems involving large deformations of thin structures, simulating fluid-structure interaction (FSI) remains challenging largely due to the need to balance computational feasibility, efficiency, and solution accuracy. Overlapping…

Computational Engineering, Finance, and Science · Computer Science 2020-03-18 Maximilian Balmus , Andre Massing , Johan Hoffman , Reza Razavi , David Nordsletten

A non-intrusive model order reduction (MOR) method that combines features of the dynamic mode decomposition (DMD) and the radial basis function (RBF) network is proposed to predict the dynamics of parametric nonlinear systems. In many…

Fluid-induced slip of fractures is characterized by strong multiphysics couplings. Three physical processes are considered: Flow, rock deformation and fracture deformation. The fractures are represented as lower-dimensional objects embedded…

Geophysics · Physics 2017-12-19 Runar L. Berge , Inga Berre , Eirik Keilegavlen