Dynamic Condensation and Synthesis of Unsymmetric Structural Systems

2002 ◽  
Vol 69 (5) ◽  
pp. 610-616 ◽  
Author(s):  
G. Visweswara Rao
Keyword(s):  
Model Reduction ◽  
Degrees Of Freedom ◽  
Structural Systems ◽  
Structural System ◽  
Lanczos Algorithm ◽  
Order Model ◽  
Reduction Procedure ◽  
Reduced Order ◽  
Large Size ◽  
Dynamic Condensation

In this paper model reduction of an unsymmetric and damped structural system is presented using a two-sided dynamic condensation technique. The method is an iterative one and essentially utilizes orthonormalized complex eigenvectors of the unsymmetric system. The eigensolution of the reduced order model with specified master degrees-of-freedom is obtained by Lanczos algorithm. The model reduction procedure is further utilized in substructure synthesis and eigenvalue analysis of large size unsymmetric systems. Application of the condensation technique is illustrated via two example problems of rotor bearing systems.

scholarly journals Implementing model reduction to the JuliaFEM platform

2018 ◽  
Vol 51 (1) ◽  
pp. 36-54 ◽  
Author(s):  
Marja Liisa Rapo ◽  
Jukka Aho ◽  
Hannu Koivurova ◽  
Tero Frondelius
Keyword(s):  
Finite Element Method ◽  
Finite Element ◽  
Model Reduction ◽  
Open Source ◽  
Degrees Of Freedom ◽  
Mass Matrices ◽  
Dynamic Condensation ◽  
Dynamic Analyses ◽  
Reduction Methods ◽  
Large Model

JuliaFEM is an open source finite element method solver written in the Julia language. This paper presents an implementation of two common model reduction methods: the Guyan reduction and the Craig-Bampton method. The goal was to implement these algorithms to the JuliaFEM platform and demonstrate that the code works correctly. This paper first describes the JuliaFEM concept briefly after which it presents the theory of model reduction, and finally, it demonstrates the implemented functions in an example model. This paper includes instructions for using the implemented algorithms, and reference the code itself in GitHub. The reduced stiness and mass matrices give the same results in both static and dynamic analyses as the original matrices, which proves that the code works correctly. The code runs smoothly on relatively large model of 12.6 million degrees of freedom. In future, damping could be included in the dynamic condensation now that it has been shown to work.

A Reduced Order Model of Unsteady Flows in Turbomachinery

1994 ◽  
Author(s):  
Kenneth C. Hall ◽  
Răzvan Florea ◽  
Paul J. Lanzkron
Keyword(s):  
Fluid Motion ◽  
Unsteady Flows ◽  
Reduced Order Model ◽  
Lanczos Algorithm ◽  
Order Model ◽  
Reduced Order ◽  
Unsteady Aerodynamic ◽  
Natural Modes ◽  
Wide Range ◽  
Modes Of Vibration

A novel technique for computing unsteady flows about turbomachinery cascades is presented. Starting with a frequency domain CFD description of unsteady aerodynamic flows, we form a large, sparse, generalized, non-Hermitian eigenvalue problem which describes the natural modes and frequencies of fluid motion about the cascade. We compute the dominant left and right eigenmodes and corresponding eigenfrequencies using a Lanczos algorithm. Then, using just a few of the resulting eigenmodes, we construct a reduced order model of the unsteady flow field. With this model, one can rapidly and accurately predict the unsteady aerodynamic loads acting on the cascade over a wide range of reduced frequencies and arbitrary modes of vibration. Moreover, the eigenmode information provides insights into the physics of unsteady flows. Finally we note that the form of the reduced order model is well suited for use in active control of aeroelastic and aeroacoustic phenomena.

scholarly journals A Reduced Order Model of Mistuning Using a Subset of Nominal System Modes

1999 ◽  
Author(s):  
M.-T. Yang ◽  
J. H. Griffin
Keyword(s):  
Degrees Of Freedom ◽  
Reduced Order Model ◽  
Reduced Order Models ◽  
Order Model ◽  
Disk System ◽  
Element Analysis ◽  
Reduced Order ◽  
Nominal System ◽  
Harmonic Response ◽  
Bladed Disk

Reduced order models have been reported in the literature that can be used to predict the harmonic response of mistuned bladed disks. It has been shown that in many cases they exhibit structural fidelity comparable to a finite element analysis of the full bladed disk system while offering a significant improvement in computational efficiency. In these models the blades and disk are treated as distinct substructures. This paper presents a new, simpler approach for developing reduced order models in which the modes of the mistuned system are represented in terms of a sub-set of nominal system modes. It has the following attributes: the input requirements are relatively easy to generate; it accurately predicts mistuning effects in regions where frequency veering occurs; as the number of degrees of freedom increases it converges to the exact solution; it accurately predicts stresses as well as displacements; and it accurately models the deformation and stresses at the blades’ bases.

Identification of Structural Systems With Limited Number of Sensors and Actuators

2004 ◽  
Author(s):  
Jun Yu ◽  
Maura Imbimbo ◽  
Raimondo Betti
Keyword(s):  
Degrees Of Freedom ◽  
Dynamic Models ◽  
Solution Space ◽  
Order Model ◽  
Sensors And Actuators ◽  
Common Assumption ◽  
Reduced Order ◽  
Different Types ◽  
The Common ◽  
Inverse Vibration

The common assumption in the so-called linear inverse vibration problem, which provides the mass/stiffness/damping matrices of second order dynamic models, is the availability of a full set of sensors and actuators. In “reduced-order” problems (with limited number of instrumentation), only the components of the eigenvector matrix regarding the measured degrees of freedom can be successfully identified while nothing can be said about the components connected to the unmeasured degrees of freedom. This paper presents a recently developed “reduced-order” model and expands such a model to a “full-order” one that is quite useful in damage detection. The five representative categories of “reduced-order” problems, defined by considering different types of geometrical conditions, are analyzed and a discussion on their solution space has been performed. The effectiveness and robustness of this approach is shown by means of a numerical example.

scholarly journals H∞ Model Reduction of 2D Markovian Jump System with Roesser Model

2012 ◽  
Vol 6-7 ◽  
pp. 135-142
Author(s):  
Xue Song Han ◽  
Yu Bo Duan
Keyword(s):  
Model Reduction ◽  
Reduced Order Model ◽  
Markovian Jump Systems ◽  
Linear Matrix ◽  
Roesser Model ◽  
Markovian Jump ◽  
Order Model ◽  
Existence Of A Solution ◽  
Reduced Order ◽  
Jump Systems

This paper extends the results obtained for one-dimensional Markovian jump systems to investigate the problem of H∞model reduction for a class of linear discrete time 2D Markovian jump systems with state delays in Roesser model which is time-varying and mode-independent. The reduced-order model with the same randomly jumping parameters is proposed which can make the error systems stochastically stable with a prescribed H∞ performance. A sufficient condition in terms of linear matrix inequalitiesSubscript text(LMIs) plus matrix inverse constraints are derived for the existence of a solution to the reduced-order model problems. The cone complimentarity linearization (CCL) method is exploited to cast them into nonlinear minimization problems subject to LMI constraints. A numerical example is given to illustrate the design procedures.

scholarly journals Empirical Reduced-Order Modeling for Boundary Feedback Flow Control

2008 ◽  
Vol 2008 ◽  
pp. 1-11 ◽  
Author(s):  
Seddik M. Djouadi ◽  
R. Chris Camphouse ◽  
James H. Myatt
Keyword(s):  
Model Reduction ◽  
Reduction Method ◽  
Linear Subspace ◽  
Balanced Truncation ◽  
Order Model ◽  
Reduced Order ◽  
Domain Identification ◽  
Controllability And Observability ◽  
Obstacle Geometry ◽  
Proper Orthogonal

This paper deals with the practical and theoretical implications of model reduction for aerodynamic flow-based control problems. Various aspects of model reduction are discussed that apply to partial differential equation- (PDE-) based models in general. Specifically, the proper orthogonal decomposition (POD) of a high dimension system as well as frequency domain identification methods are discussed for initial model construction. Projections on the POD basis give a nonlinear Galerkin model. Then, a model reduction method based on empirical balanced truncation is developed and applied to the Galerkin model. The rationale for doing so is that linear subspace approximations to exact submanifolds associated with nonlinear controllability and observability require only standard matrix manipulations utilizing simulation/experimental data. The proposed method uses a chirp signal as input to produce the output in the eigensystem realization algorithm (ERA). This method estimates the system's Markov parameters that accurately reproduce the output. Balanced truncation is used to show that model reduction is still effective on ERA produced approximated systems. The method is applied to a prototype convective flow on obstacle geometry. AnH∞feedback flow controller is designed based on the reduced model to achieve tracking and then applied to the full-order model with excellent performance.

On the Uniqueness of Solutions for the Identification of Linear Structural Systems

2005 ◽  
Vol 73 (1) ◽  
pp. 153-162 ◽  
Author(s):  
Guillermo Franco ◽  
Raimondo Betti ◽  
Richard W. Longman
Keyword(s):  
Prior Knowledge ◽  
Degrees Of Freedom ◽  
Identification Problem ◽  
Minimum Amount ◽  
Structural Systems ◽  
Structural System ◽  
Uniqueness Of Solutions ◽  
Stiffness Identification ◽  
Shear Type ◽  
Forced Excitation

This work tackles the problem of global identifiability of an undamped, shear-type, N degrees of freedom linear structural system under forced excitation without any prior knowledge of its mass or stiffness distributions. Three actuator/sensor schemes are presented, which guarantee the existence of only one solution for the mass and stiffness identification problem while requiring a minimum amount of instrumentation (only 1 actuator and 1 or 2 sensors). Through a counterexample for a 3DOF system it is also shown that fewer measurements than those suggested result invariably in non-unique solutions.

Model Reduction for the Electrostatically Actuated Silicon Diaphragm Based on Modal-Type Dynamic Condensation

2014 ◽  
Author(s):  
X. Z. Lin ◽  
Z. M. Hu ◽  
J. M. Huang
Keyword(s):  
Dynamic Models ◽  
Reduced Order Model ◽  
Order Model ◽  
Reduced Order ◽  
Electrostatically Actuated ◽  
Stiffness Matrices ◽  
Electric Driving ◽  
Dynamic Condensation ◽  
Simulation Results ◽  
Modal Type

A method for constructing reduced-order models (ROM) of an electrostatically actuated clamped silicon diaphragm is presented. This reduced-order model is constructed by using basis the spatially dependent eigen-functions. A commercial finite element package is firstly used to form the system mass and stiffness matrices representing the model. These matrices are then manipulated in MATLAB™ and reduced using modal type dynamic condensation. The eigen-value problem is then solved for the reduced mass and stiffness matrices and subset of the modes are used to producing low-order but highly accurate models of electrostatically actuated diaphragm. The reduced-order model can accounts for general residual stress and strain hardening and allows for any other electric driving signal simulations. Once the ROM has been generated, it can be reused to simulate the quasi-state and dynamics behaviors of the device over a range of different electric driving waveforms. The calculated results show that the resulting ROM can capture the static/dynamic behaviors of the device very well. The simulation results also show good agreement with the fully meshed dynamic models simulation results, thus the efficiency and accuracy of the modeling technology are valid.

Interface Reduction in Craig–Bampton Component Mode Synthesis by Orthogonal Polynomial Series

2017 ◽  
Vol 140 (5) ◽  
Author(s):  
Luigi Carassale ◽  
Mirko Maurici
Keyword(s):  
Degrees Of Freedom ◽  
Axial Compressor ◽  
Component Mode Synthesis ◽  
Order Model ◽  
Reduced Order ◽  
Interface Reduction ◽  
Interface Displacement ◽  
Polynomial Series ◽  
Efficient Representation

The component mode synthesis (CMS) based on the Craig–Bampton (CB) method has two strong limitations that appear when the number of the interface degrees-of-freedom (DOFs) is large. First, the reduced-order model (ROM) obtained is overweighed by many unnecessary DOF. Second, the reduction step may become extremely time consuming. Several interface reduction (IR) techniques addressed successfully the former problem, while the latter remains open. In this paper, we tackle this latter problem through a simple IR technique based on an a-priory choice of the interface modes. An efficient representation of the interface displacement field is achieved adopting a set of orthogonal basis functions determined by the interface geometry. The proposed method is compared with other existing IR methods on a case study regarding a rotor blade of an axial compressor.

Nonlinear Dynamic Analysis of Cantilever Beam Using POD Based Reduced Order Model

2015 ◽  
Vol 786 ◽  
pp. 398-403 ◽  
Author(s):  
Kulkarni Atul Shankar ◽  
Manoj Pandey
Keyword(s):  
Dynamic Analysis ◽  
Large Deformation ◽  
Cantilever Beam ◽  
Nonlinear Dynamic ◽  
Degrees Of Freedom ◽  
Numerical Technique ◽  
Nonlinear Dynamic Analysis ◽  
Reduced Order Model ◽  
Order Model ◽  
Reduced Order

In this paper, a reduced order model is obtained for nonlinear dynamic analysis of a cantilever beam. Nonlinearity in the system is basically due to large deformation. A reduced order model is an efficient method to formulate low order dynamical model which can be obtained from data obtained from numerical technique such as finite element method (FEM). Nonlinear dynamical models are complex with large number of degrees of freedom and hence, are computationally intensive. With formulation of reduced order models (i.e. Macromodels) number of degrees of freedom are reduced to fewer degrees of freedom by using projection based method like Galerkin’s projection, so as to make system computationally faster and cost effective. These macromodels are obtained by extracting global basis functions from fully meshed model runs. Macromodels are generated using technique called proper orthogonal decomposition (POD) which gives good linear fit for the nonlinear systems. Using POD based macromodel, response of system can be computed using fewer modes instead of considering all modes of system. Macromodel is generated to obtain the response of cantilever beam with large deformation and hence, simulation time is reduced by factor of 90 approximately with error of order of 10-4. Further, method of POD based reduced order model is aplied to beam with different loading conditions to check the robustness of the macromodel. POD based macromodel response gives good agreement with FEA model response for a cantilever beam.

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