Nonlinear Aeroelastic Panel Flutter Based on Proper Orthogonal Decomposition

It is commonly accepted that 36 in vacuo natural modes (NMS) are needed for converged, limit-cycle oscillations (LCOs) of isotropic or laminated anisotropic rectangular panels in supersonic air flow. It’s computationally costly for nonlinear aeroelastic panel response using such a large number of modes, and it also causes complexity and difficultly in designing controllers for panel flutter suppression. Based on Hamilton principle, the aeroelastic finite element motion equations of the 3-D panel are established by using the von Karman large deflection theory, first-order piston theory aerodynamics, the proper orthogonal decomposition (POD) method are adopted to construct a reduced order model of the panel, then the reduced panel flutter equations are solved in time domain using a numerical integration method. Comparing with the LCOs calculated by using 36NMS, the results obtained by using the reduced order model based on POD method (POD/ROM) show a good agreement.

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Reduced-Order Model of a Bladed Rotor With Geometric Mistuning

Volume 5: Turbo Expo 2007 ◽

10.1115/gt2007-27276 ◽

2007 ◽

Cited By ~ 2

Author(s):

Alok Sinha

Keyword(s):

Proper Orthogonal Decomposition ◽

Orthogonal Decomposition ◽

Reduced Order Model ◽

Order Model ◽

Reduced Order ◽

Coordinate Measurement ◽

Coordinate Measurement Machine ◽

Bladed Disk ◽

Bladed Rotor ◽

Proper Orthogonal

This paper deals with the development of an accurate reduced-order model of a bladed disk with geometric mistuning. The method is based on vibratory modes of various tuned systems and proper orthogonal decomposition of coordinate measurement machine (CMM) data on blade geometries. Results for an academic rotor are presented to establish the validity of the technique.

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Thermal-electrochemical simulation of lead-acid battery using reduced-order model based on proper orthogonal decomposition for real-time monitoring purposes

Journal of Energy Storage ◽

10.1016/j.est.2021.103491 ◽

2021 ◽

Vol 44 ◽

pp. 103491

Author(s):

Amir Babak Ansari ◽

Vahid Esfahanian ◽

Farschad Torabi

Keyword(s):

Proper Orthogonal Decomposition ◽

Real Time ◽

Orthogonal Decomposition ◽

Reduced Order Model ◽

Lead Acid Battery ◽

Real Time Monitoring ◽

Order Model ◽

Reduced Order ◽

Electrochemical Simulation ◽

Proper Orthogonal

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Reduced-Order Model of Unsteady Flows in a Turbomachinery Fan Modeled Using a Novel Proper Orthogonal Decomposition

Volume 2C: Turbomachinery ◽

10.1115/gt2019-90323 ◽

2019 ◽

Author(s):

Elizabeth H. Krath ◽

Forrest L. Carpenter ◽

Paul G. A. Cizmas ◽

David A. Johnston

Keyword(s):

Proper Orthogonal Decomposition ◽

Reference Conditions ◽

Stable Solution ◽

Orthogonal Decomposition ◽

Reduced Order Model ◽

Computational Time ◽

Order Model ◽

Reduced Order ◽

Proper Orthogonal ◽

Model Rotor

Abstract This paper presents a novel, more efficient reduced-order model based on the proper orthogonal decomposition (POD) for the prediction of flows in turbomachinery. To further reduce the computational time, the governing equations were written as a function of specific volume instead of density. This allowed for the pre-computation of the coefficients of the system of ordinary differential equations that describe the reduced-order model. A penalty method was developed to implement time-dependent boundary conditions and achieve a stable solution for the reduced-order model. Rotor 67 was used as a validation case for the reduced-order model, which was tested for both on- and off-reference conditions. This reduced-order model was shown to be more than 10,000 times faster than the full-order model.

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