Data Driven Modal Decomposition of the Wake behind an NREL-5MW Wind Turbine

The wake produced by a utility-scale wind turbine invested by a laminar, uniform inflow is analyzed by means of two different modal decompositions, the proper orthogonal decomposition (POD) and the dynamic mode decomposition (DMD), in its sparsity-promoting variant. The turbine considered is the NREL-5MW at tip-speed ratio λ=7 and a diameter-based Reynolds number of the order 108. The flow is simulated through large eddy simulation, where the forces exerted by the blades are modeled using the actuator line method, whereas tower and nacelle are modeled employing the immersed boundary method. The main flow structures identified by both modal decompositions are compared and some differences emerge that can be of great importance for the formulation of a reduced-order model. In particular, a high-frequency mode directly related to the tip vortices is found using both methods, but it is ranked differently. The other dominant modes are composed by large-scale low-frequency structures, but with different frequency content and spatial structure. The most energetic 200 POD modes account for ≈20% only of the flow kinetic energy. While using the same number of DMD modes, it is possible to reconstruct the flow field to within 80% accuracy. Despite the similarities between the set of modes, the comparison between these modal-decomposition techniques points out that an energy-based criterion such as that used in the POD may not be suitable for formulating a reduced-order model of wind turbine wakes, while the sparsity-promoting DMD appears able to perform well in reconstructing the flow field with only a few modes.

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A Quasi-Physical Dynamic Reduced Order Model for Thermospheric Mass Density via Hermitian Space-Dynamic Mode Decomposition

Space Weather ◽

10.1029/2018sw001840 ◽

2018 ◽

Vol 16 (5) ◽

pp. 569-588 ◽

Cited By ~ 12

Author(s):

Piyush M. Mehta ◽

Richard Linares ◽

Eric K. Sutton

Keyword(s):

Mass Density ◽

Reduced Order Model ◽

Dynamic Mode Decomposition ◽

Dynamic Mode ◽

Order Model ◽

Reduced Order ◽

Mode Decomposition ◽

Hermitian Space

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Modal Analysis of Wake behind Stationary and Vibrating Cylinders

Journal of Offshore Mechanics and Arctic Engineering ◽

10.1115/1.4049249 ◽

2020 ◽

pp. 1-24

Author(s):

Marek Janocha ◽

Guang Yin ◽

Muk Chen Ong

Keyword(s):

Reynolds Number ◽

Modal Analysis ◽

Reduced Order Model ◽

Dynamic Mode Decomposition ◽

Navier Stokes ◽

Dynamic Mode ◽

Order Model ◽

Reduced Order ◽

Mode Decomposition ◽

Sst Turbulence Model

Abstract The Dynamic Mode Decomposition (DMD) and Proper Orthogonal Decomposition (POD) are used to analyze the coherent structures of turbulent flow around vibrating isolated and piggyback cylinders configurations subjected to a uniform flow at a laminar Reynolds number (Re=200) and a upper transition Reynolds number (Re=3.6×106). Numerical simulations using two-dimensional URANS (Unsteady Reynolds Averaged Navier-Stokes) approach with the k-omega SST turbulence model are used to obtain the flow fields snapshots for the analysis. The wake flows behind the cylinders are decomposed into energy optimal modes (POD modes) and dynamical relevant modes (DMD modes). A reduced-order model for the flow is built based on the modal analysis. A comparison of POD and DMD is performed to characterize their special features. The present study provides new insights into the flow physics of fluid-structure interaction problem of two coupled cylinders. The characteristic vortex shedding frequencies and their harmonics are identified by DMD modes in all the investigated configurations. It is observed that for single cylinder configurations the most energetic and the most dynamically important mode is associated with the fundamental shedding frequency. For the stationary piggyback configuration, the gap flow between the cylinders appears to be a dominant flow feature as evidenced by leading DMD modes. The cylinder vibration increases significantly number of modes necessary to obtain a reduced order model (ROM) at given level of accuracy compared to respective stationary configurations.

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A reduced-order model for compressible flows with buffeting condition using higher order dynamic mode decomposition with a mode selection criterion

Physics of Fluids ◽

10.1063/1.4999699 ◽

2018 ◽

Vol 30 (1) ◽

pp. 016103 ◽

Cited By ~ 22

Author(s):

Jiaqing Kou ◽

Soledad Le Clainche ◽

Weiwei Zhang

Keyword(s):

Compressible Flows ◽

Mode Selection ◽

Selection Criterion ◽

Higher Order ◽

Reduced Order Model ◽

Dynamic Mode Decomposition ◽

Dynamic Mode ◽

Order Model ◽

Reduced Order ◽

Mode Decomposition

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Model Order Reduction of Transmission Line Model

WSEAS TRANSACTIONS ON CIRCUITS AND SYSTEMS ◽

10.37394/23201.2020.19.7 ◽

2020 ◽

Vol 19 ◽

Keyword(s):

Transmission Line ◽

Large Scale ◽

Original System ◽

Reduced Order Model ◽

Benchmark Problems ◽

Transmission Line Model ◽

Order Model ◽

Line Model ◽

Reduced Order ◽

Numerical Effort

Transmission Line model are an important role in the electrical power supply. Modeling of such system remains a challenge for simulations are necessary for designing and controlling modern power systems.In order to analyze the numerical approach for a benchmark collection Comprehensive of some needful real-world examples, which can be utilized to evaluate and compare mathematical approaches for model reduction. The approach is based on retaining the dominant modes of the system and truncation comparatively the less significant once.as the reduced order model has been derived from retaining the dominate modes of the large-scale stable system, the reduction preserves the stability. The strong demerit of the many MOR methods is that, the steady state values of the reduced order model does not match with the higher order systems. This drawback has been try to eliminated through the Different MOR method using sssMOR tools. This makes it possible for a new assessment of the error system Offered that the Observability Gramian of the original system has as soon as been thought about, an H∞ and H2 error bound can be calculated with minimal numerical effort for any minimized model attributable to The reduced order model (ROM) of a large-scale dynamical system is essential to effortlessness the study of the system utilizing approximation Algorithms. The response evaluation is considered in terms of response constraints and graphical assessments. the application of Approximation methods is offered for arising ROM of the large-scale LTI systems which consist of benchmark problems. The time response of approximated system, assessed by the proposed method, is also shown which is excellent matching of the response of original system when compared to the response of other existing approaches .

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Space–time reduced order model for large-scale linear dynamical systems with application to Boltzmann transport problems

Journal of Computational Physics ◽

10.1016/j.jcp.2020.109845 ◽

2021 ◽

Vol 424 ◽

pp. 109845

Author(s):

Youngsoo Choi ◽

Peter Brown ◽

William Arrighi ◽

Robert Anderson ◽

Kevin Huynh

Keyword(s):

Dynamical Systems ◽

Large Scale ◽

Space Time ◽

Reduced Order Model ◽

Boltzmann Transport ◽

Order Model ◽

Linear Dynamical Systems ◽

Reduced Order ◽

Transport Problems

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A high fidelity cost efficient tensorial method based on combined POD-HOSVD reduced order model of flow field

European Journal of Computational Mechanics ◽

10.1080/17797179.2018.1550963 ◽

2018 ◽

Vol 27 (4) ◽

pp. 342-366

Author(s):

Mohammad Kazem Moayyedi ◽

Milad Najaf beygi

Keyword(s):

Flow Field ◽

Reduced Order Model ◽

High Fidelity ◽

Order Model ◽

Reduced Order ◽

Cost Efficient

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Order Reduction based on Coulomb’s and Franklin’s laws Algorithm

10.21203/rs.3.rs-539380/v1 ◽

2021 ◽

Author(s):

Ram Kumar ◽

Afzal Sikander

Keyword(s):

Large Scale ◽

Linear Time ◽

Order Reduction ◽

Absolute Error ◽

Search Space ◽

Engineering Problem ◽

Reduced Order Model ◽

Order Model ◽

Reduced Order ◽

Linear Time Invariant

Abstract The Coulomb and Franklin laws (CFL) algorithm is used to construct a lower order model of higher-order continuous time linear time-invariant (LTI) systems in this study. CFL is quite easy to implement in obtaining reduced order model of large scale system in control engineering problem as it employs the combined effect of Coulomb’s and Franklin’s laws to find the best values in search space. The unknown coefficients are obtained using the CFLA methodology, which minimises the integral square error (ISE) between the original and proposed ROMs. To achieve the reduced order model, five practical systems of different orders are considered. Finally, multiple performance indicators such as the ISE, integral of absolute error (IAE), and integral of time multiplied by absolute error were calculated to determine the efficacy of the proposed methodology. The simulation results were compared to previously published well-known research.

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