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Inertial particles advected by a background flow can show complex structures. We consider inertial particles in a 2D Taylor-Green (TG) flow and characterize particle dynamics as a function of the particle's Stokes number using dynamic mode…

Fluid Dynamics · Physics 2021-02-11 Omstavan Samant , Jaya Kumar Alageshan , Sarveshwar Sharma , Animesh Kuley

The present focus of heart flow studies is largely based on flow within the left ventricle and how this flow changes when subject to disease. However, despite recent advancements, a simple tractable model of even healthy left ventricular…

Fluid Dynamics · Physics 2019-03-18 Giuseppe Di Labbio , Lyes Kadem

This thesis examines the empirical mode decomposition (EMD), a method for decomposing multicomponent signals, from a modern, both theoretical and practical, perspective. The motivation is to further formalize the concept and develop new…

Numerical Analysis · Mathematics 2023-02-08 Laslo Hunhold

In order to shed light on the Vertical-Axis Wind Turbines (VAWT) wake characteristics, in this paper we present high-fidelity CFD simulations of the flow around an exemplary H-shaped VAWT turbine, and we propose to apply Proper Orthogonal…

Numerical Analysis · Mathematics 2024-02-19 Armin Sheidani , Sajad Salavatidezfouli , Giovanni Stabile , Gianluigi Rozza

We present a novel reduced-order fluid simulation technique leveraging Dynamic Mode Decomposition (DMD) to achieve fast, memory-efficient, and user-controllable subspace simulation. We demonstrate that our approach combines the strengths of…

This paper presents the modal truncation and singular value decomposition (SVD) technique as two main algorithms for dynamic model reduction of the power system. The significance and accuracy of the proposed methods are investigated with…

Systems and Control · Electrical Eng. & Systems 2020-04-17 Mohammad Khatibi , Fatemeh Rahmani , Tanushree Agarwal

This paper discusses the application of Dynamic Mode Decomposition (DMD) to the extraction of modal properties of linear mechanical systems, i.e., experimental modal analysis (EMA). First, theoretical background of the DMD is briefly…

Dynamical Systems · Mathematics 2026-03-17 Akira Saito , Tomohiro Kuno

A phase proper orthogonal decomposition (Phase POD) method is demonstrated, utilizing phase averaging for the decomposition of spatio-temporal behaviour of statistically non-stationary turbulent flows in an optimized manner. The proposed…

Fluid Dynamics · Physics 2024-03-01 Yisheng Zhang , Azur Hodzic , Fabien Evrard , Berend Van Wachem , Clara M. Velte

The simulation of stochastic wind loads is necessary for many applications in wind engineering. The proper orthogonal decomposition (POD)-based spectral representation method is a popular approach used for this purpose due to its…

Computational Engineering, Finance, and Science · Computer Science 2023-05-11 Thays Guerra Araujo Duarte , Srinivasan Arunachalam , Arthriya Subgranon , Seymour M J Spence

Accurate and rapid prediction of flow-fields is crucial for aerodynamic design. This work proposes a discontinuous Galerkin method (DGM) whose performance enhances with increasing data, for rapid simulation of transonic flow around airfoils…

Fluid Dynamics · Physics 2024-11-15 Yiwei Feng , Lili Lv , Weixiong Yuan , Liang Xu , Tiegang Liu

This paper presents a computationally efficient, linearised numerical method for modelling aerodynamic interactions between wind farms. The linearised two-dimensional incompressible equations are solved using Fourier transforms in the…

Fluid Dynamics · Physics 2026-05-07 Alexia Everley , Hossein A. Kafiabad , Majid Bastankhah

Currently, it is challenging to investigate aneurismal hemodynamics based on current in-vivo data such as Magnetic Resonance Imaging or Computed Tomography due to the limitations in both spatial and temporal resolutions. In this work, we…

Fluid Dynamics · Physics 2024-10-17 Thien-Tam Nguyen , Davina Kasperski , Phat Kim Huynh , Trung Quoc Le , Trung Bao Le

Natural ventilation can play an important role towards preventing the spread of airborne diseases in indoor environments. However, quantifying natural ventilation flow rates is a challenging task due to significant variability in the…

Fluid Dynamics · Physics 2023-04-04 Yunjae Hwang , Catherine Gorlé

Dynamic Mode Decomposition (DMD) has received increasing research attention due to its capability to analyze and model complex dynamical systems. However, it faces challenges in computational efficiency, noise sensitivity, and difficulty…

Machine Learning · Computer Science 2025-02-20 Biqi Chen , Ying Wang

We present a new stochastic approach to describe and remodel the conversion process of a wind farm at a sampling frequency of 1Hz. When conditioning on various wind direction sectors, the dynamics of the conversion process appear as a…

Data Analysis, Statistics and Probability · Physics 2015-09-11 Patrick Milan , Matthias Wächter , Joachim Peinke

Dynamic Mode Decomposition (DMD) and its extensions (EDMD) have been at the forefront of data-based approaches to Koopman operators. Most (E)DMD algorithms assume that the entire state is sampled at a uniform sampling rate. In this paper,…

Systems and Control · Electrical Eng. & Systems 2024-04-11 Ramachandran Anantharaman , Alexandre Mauroy

Within wind farms, wake effects between turbines can significantly reduce overall energy production. Wind farm flow control encompasses methods designed to mitigate these effects through coordinated turbine control. Wake steering, for…

Machine Learning · Computer Science 2025-08-26 Elie Kadoche , Pascal Bianchi , Florence Carton , Philippe Ciblat , Damien Ernst

To provide automatic generation control (AGC) service, wind farms (WFs) are required to control their operation dynamically to track the time-varying power reference. Wake effects impose significant aerodynamic interactions among turbines,…

Optimization and Control · Mathematics 2021-08-25 Kaixuan Chen , Jin Lin , Yiwei Qiu , Feng Liu , Yonghua Song

This work aims to improve fuel chamber injectors' performance in turbofan engines, thus implying improved performance and reduction of pollutants. This requires the development of models that allow real-time prediction and improvement of…

Machine Learning · Computer Science 2023-06-21 León Mata , Rodrigo Abadía-Heredia , Manuel Lopez-Martin , José M. Pérez , Soledad Le Clainche

To enhance the accuracy of power load forecasting in wind farms, this study introduces an advanced combined forecasting method that integrates Variational Mode Decomposition (VMD) with an Improved Particle Swarm Optimization (IPSO)…

Machine Learning · Computer Science 2024-12-17 Qiang Xie
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