scholarly journals Versatile reduced-order model of leading-edge vortices on rotary wings

2018 ◽  
Vol 3 (11) ◽  
Author(s):  
D. Chen ◽  
D. Kolomenskiy ◽  
R. Onishi ◽  
H. Liu
Keyword(s):  
Leading Edge ◽  
Reduced Order Model ◽  
Order Model ◽  
Reduced Order ◽  
Rotary Wings ◽  
Leading Edge Vortices

scholarly journals Nonlinear reduced order model of high aspect ratio rectangular wing plate

2018 ◽  
Vol 7 (4.13) ◽  
pp. 195-201
Author(s):  
Thinesh C ◽  
M Y Harmin
Keyword(s):  
Leading Edge ◽  
Reduced Order Model ◽  
Computational Time ◽  
Plate Model ◽  
Order Model ◽  
Reduced Order ◽  
Nonlinear Properties ◽  
First Case ◽  
Trailing Edges ◽  
Nonlinear Deformations

This paper presents a Combined Modal Finite Element (CMFE) approach to develop a Nonlinear Reduced Order Model (NROM) in order to characterize the nonlinear properties of the wing plate model. The wing plate model is subjected to three types of loading cases. The first case considers a uniformly distributed loading on the whole wing plate model for describing the bending deflection; the second case considers a uniformly distributed loading on both leading and trailing edges with one of them of an opposite direction for describing the twisting deflection; the third case considers the loading on the leading edge for describing a combination of bending-twisting deflection. The accuracy of the results is represented in the form of mean error, the standard deviation of the error and the percentage of error. From the findings, the NROMs are able to predict the nonlinear deformations of the wing plate with a minimal computational time and reasonably good accuracy. The results also indicate the importance of the selection modes when conducting the analysis.  

Probabilistic Analysis of Geometric Uncertainty Effects on Blade-Alone Forced Response

2004 ◽  
Author(s):  
Jeffrey M. Brown ◽  
Ramana V. Grandhi
Keyword(s):  
Stress Measurement ◽  
Approximation Error ◽  
Leading Edge ◽  
Monte Carlo Sampling ◽  
Forced Response ◽  
Small Sample ◽  
Reduced Order Model ◽  
Order Model ◽  
Element Analysis ◽  
Reduced Order

This paper investigates the effect of manufacturing variations on the blade-alone forced response of a transonic low aspect ratio fan. A simulated set of coordinate measurement machine measurements from a single rotor, representative of actual manufacturing variations, are used to investigate geometric effects. A reduced order model is developed to rapidly solve for the forced response and is based on eigensensitivity analysis and dynamic response mode superposition. An approximation error analysis is conducted to quantify accuracy of the new tool and errors between approximate and full finite element analysis solutions are shown to be small for low order modes with some high order modes having moderate error. A study of the simulated measured blade results show a significant amount of forced response variation along the leading edge of the airfoil. Statistics from this simulated measured rotor are used with Monte Carlo sampling to generate random blades realizations that are solved with the reduced order model. This procedure allows the prediction of the variation across an entire fleet of blades from a small sample of blades. The large variations predicted, up to 40%, could have a significant impact of the blade design process including the procedures to account for foreign object damage damage tolerance, how non-intrusive stress measurement systems are used, and how mistuning prediction algorithms are validated.

Model Order Reduction of Transmission Line Model

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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