scholarly journals Finite Element Model Update via Bayesian Estimation and Minimization of Dynamic Residuals

AIAA Journal ◽  
1997 ◽  
Vol 35 (5) ◽  
pp. 879-886 ◽  
Author(s):  
Kenneth F. Alvin
Keyword(s):  
Finite Element ◽  
Finite Element Model ◽  
Bayesian Estimation ◽  
Element Model ◽  
Model Update ◽  
Dynamic Residuals

scholarly journals Finite element model update via Bayesian estimation and minimization of dynamic residuals

AIAA Journal ◽  
1997 ◽  
Vol 35 ◽  
pp. 879-886 ◽  
Author(s):  
Kenneth F. Alvin
Keyword(s):  
Finite Element ◽  
Finite Element Model ◽  
Bayesian Estimation ◽  
Element Model ◽  
Model Update ◽  
Dynamic Residuals

scholarly journals Bayesian Inference of Vocal Fold Material Properties from Glottal Area Waveforms Using a 2D Finite Element Model

2019 ◽  
Vol 9 (13) ◽  
pp. 2735 ◽  
Author(s):  
Paul J. Hadwin ◽  
Mohsen Motie-Shirazi ◽  
Byron D. Erath ◽  
Sean D. Peterson
Keyword(s):  
Finite Element ◽  
Finite Element Model ◽  
Bayesian Estimation ◽  
Material Properties ◽  
Vocal Fold ◽  
Vocal Folds ◽  
Element Model ◽  
Lumped Element ◽  
Subglottal Pressure ◽  
Contact Pressures

Bayesian estimation has been previously demonstrated as a viable method for developing subject-specific vocal fold models from observations of the glottal area waveform. These prior efforts, however, have been restricted to lumped-element fitting models and synthetic observation data. The indirect relationship between the lumped-element parameters and physical tissue properties renders extracting the latter from the former difficult. Herein we propose a finite element fitting model, which treats the vocal folds as a viscoelastic deformable body comprised of three layers. Using the glottal area waveforms generated by self-oscillating silicone vocal folds we directly estimate the elastic moduli, density, and other material properties of the silicone folds using a Bayesian importance sampling approach. Estimated material properties agree with the “ground truth” experimental values to within 3 % for most parameters. By considering cases with varying subglottal pressure and medial compression we demonstrate that the finite element model coupled with Bayesian estimation is sufficiently sensitive to distinguish between experimental configurations. Additional information not available experimentally, namely, contact pressures, are extracted from the developed finite element models. The contact pressures are found to increase with medial compression and subglottal pressure, in agreement with expectation.

Geometric Model Update of Blisks and its Experimental Validation for a Wide Frequency Range

2017 ◽  
Author(s):  
Thomas Maywald ◽  
Thomas Backhaus ◽  
Sven Schrape ◽  
Arnold Kühhorn
Keyword(s):  
Finite Element ◽  
Finite Element Model ◽  
Blue Light ◽  
Experimental Validation ◽  
Industrial Robot ◽  
Simulation Models ◽  
Element Model ◽  
Measurement Results ◽  
Model Update ◽  
Geometric Deviations

The contribution discusses a model update procedure and its experimental validation in the context of blisk mistuning. Object of investigation is an industrial test blisk of an axial compressor which is milled from solid using a state of the art 5-axis milling machine. First, the blisk geometry is digitized by a blue light fringe projector. Digitization is largely automated using an industrial robot cell in order to guarantee high repeatability of the measurement results. Additionally, frequency mistuning patterns are identified based on vibration measurements. Here, the system excitation is realized by a modal impact hammer. The blade response is detected using a laser scanning vibrometer. Furthermore, all blades except the currently excited one are detuned with additional masses. Applying these masses allows to identify a blade dominated natural frequency for each blade and every mode of interest. Finally, these blade dominated frequencies are summarized to mode specific mistuning patterns. The key part of the contribution presents a model update approach which is focused on small geometric deviations between real engine parts and idealized simulation models. Within this update procedure the nodal coordinates of an initially tuned finite element blisk model were modified in order to match the geometry of the real part measured by blue light fringe projection. All essential pre- and post-processing steps of the mesh morphing procedure are described and illustrated. It could be proven that locally remaining geometric deviations between updated finite element model and the optical measurement results are below 5 μm. For the purpose of validation blade dominated natural frequencies of the updated finite element blisk model are calculated for each sector up to a frequency of 17 kHz. Finally, the numerically predicted mistuning patterns are compared against the experimentally identified counterparts. At this point a very good agreement between experimentally identified and numerically predicted mistuning patterns can be proven across several mode families. Even mistuning patterns of higher modes at about 17 kHz are well predicted by the geometrically mistuned finite element model. Within the last section of the paper, possible uncertainties of the presented model update procedure are analyzed. As a part of the study the digitization of the investigated blisk has been repeated for ten times. These measurement results serve as input for the model update procedure described before. In the context of this investigation ten independent geometrical mistuned simulation models are created and the corresponding mistuning patterns are calculated.

Finite Element Model Updating for a Suspension Bridge Using Deep Neural Networks

2019 ◽  
Author(s):  
Wonsuk Park
Keyword(s):  
Finite Element ◽  
Eigenvalue Problem ◽  
Finite Element Model ◽  
Suspension Bridge ◽  
Element Model ◽  
Inverse Eigenvalue Problem ◽  
Dynamic Finite Element ◽  
Model Update ◽  
Inverse Eigenvalue ◽  
The Finite Element Model

<p>The finite element model for the performance evaluation of an existing structure should be able to accurately reflect the current state of the structure. As one of popular methods, the dynamic finite element model update finds the optimal parameters for the finite element model closest to the measured modal frequencies and shapes by using error minimization procedures. In this study, we propose a new method to construct an inverse eigenvalue problem that can directly obtain the parameters of the finite element model from the measurement modal information by developing a deep neural network to solve the inverse eigenvalue problem quickly and accurately. The solution of the inverse eigenvalue problem is obtained by using the mode frequencies and shapes measured as the input of the network and using the corresponding model parameter as the output. As an application example of the developed method, the dynamic finite element model update of a suspension bridge for given response data is presented. Unlike the existing update method based on the optimization procedure, this method can be updated in real time, and various update solutions considering the measurement error can be easily obtained.</p>

An Improved Method of Bridge Finite Element Model Update by Stepwise Regression

2014 ◽  
Vol 578-579 ◽  
pp. 940-945
Author(s):  
Yong Peng Luo ◽  
Fang Lin Huang ◽  
Zhong Ping Tang ◽  
Jun Li Xie
Keyword(s):  
Finite Element ◽  
Finite Element Model ◽  
Response Surface ◽  
Stepwise Regression ◽  
Dynamic Test ◽  
Element Model ◽  
Response Surface Model ◽  
Surface Model ◽  
Rigid Frame ◽  
Model Update

With the increasing of variables and orders of polynomial expansion, the undetermined coefficients of the response surface model have increased dramatically. The insignificant expansion terms should be eliminated because not all of the expansion terms have significant effect on the response. The improved and practical updating method based on response surface model by stepwise regression, which can effectively reduce the undetermined coefficients on the premise of guaranteeing the correcting accuracy, is proposed in this paper. The method is also applied to update the finite element model of a bridge with prestressed reinforced concrete rigid frame-continuous girders based on the in-situ dynamic test results. The results show that the updated finite element model can match the mechanical properties of the bridge well.

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