The Poly-SAFE method: A semi-analytical representation of finite element models via nested polynomial reduction of modal data

2014 ◽  
Vol 111 ◽  
pp. 301-316 ◽  
Author(s):  
Diego Cárdenas ◽  
Hugo Elizalde ◽  
Pier Marzocca ◽  
Oliver Probst ◽  
Ricardo Ramirez ◽  
...  
Keyword(s):  
Finite Element ◽  
Analytical Representation ◽  
Finite Element Models ◽  
Safe Method ◽  
Modal Data ◽  
Polynomial Reduction

scholarly journals Correction of Finite Element Models Using Experimental Modal Data.

1991 ◽  
Vol 57 (537) ◽  
pp. 1591-1595 ◽  
Author(s):  
Kukil SOHN ◽  
Masaaki OKUMA ◽  
Akio NAGAMATSU
Keyword(s):  
Finite Element ◽  
Finite Element Models ◽  
Modal Data

Validating and Updating Finite Element Models Using Experimental Measurements of Dynamics

1990 ◽  
Vol 204 (1) ◽  
pp. 45-50
Author(s):  
C F McCulloch ◽  
P Vanhonacker ◽  
E Dascotte
Keyword(s):  
Finite Element ◽  
Structural Dynamics ◽  
Model Updating ◽  
Measured Data ◽  
Physical Parameters ◽  
Experimental Measurements ◽  
Finite Element Models ◽  
Data Sets ◽  
Modal Data ◽  
Modelling Assumptions

A method is proposed for updating finite element models of structural dynamics using the results of experimental modal analysis, based on the sensitivities to changes in physical parameters. The method avoids many of the problems of incompatibility and inconsistency between the experimental and analytical modal data sets and enables the user to express confidence in measured data and modelling assumptions, allowing flexible but automated model updating.

scholarly journals Computationally efficient reduction of modal data from finite element models by nested sets of B-splines

2015 ◽  
Vol 134 ◽  
pp. 549-564
Author(s):  
Diego Cárdenas ◽  
Hugo Elizalde ◽  
Oliver Probst ◽  
Walter Lacarbonara ◽  
Pier Marzocca ◽  
...  
Keyword(s):  
Finite Element ◽  
Finite Element Models ◽  
Computationally Efficient ◽  
B Splines ◽  
Modal Data ◽  
Efficient Reduction ◽  
Nested Sets

The Influence of Experimental Errors on the Correction Parameters of Finite Element Models

1997 ◽  
Author(s):  
Stefan Keye
Keyword(s):  
Finite Element ◽  
Natural Frequencies ◽  
Numerical Models ◽  
Element Model ◽  
Finite Element Models ◽  
Correction Factors ◽  
Modal Data ◽  
Experimental Errors ◽  
Measurement Uncertainties ◽  
The Impact

Abstract A simulation study has been performed on the influence of experimental errors on the accuracy of finite element model corrections. The impact of measurement uncertainties on the sub-structure correction factors, natural frequencies, and mode shape correlation is investigated using simulated modal data. Different numerical models are used to assess the effects of modelization error magnitudes and locations.

Correlating and Updating Finite Element Models of Different Fidelity Using an Energy-Based Approach

2020 ◽  
Author(s):  
Alexander Hardenberg ◽  
Arnold Kühhorn ◽  
Maren Fanter
Keyword(s):  
Finite Element ◽  
Kinetic Energy ◽  
Finite Element Model ◽  
Model Updating ◽  
Three Dimensional ◽  
Element Model ◽  
Finite Element Models ◽  
Modal Data ◽  
Aero Engine ◽  
Turbine Casing

Abstract Building finite element models of complex structures requires the engineer to make various simplifying assumptions. While there exists no unique way of modeling, the resulting model depends to a level on experience and engineering judgment. The inherent model uncertainties can be subdivided into three categories: idealization errors, discretization errors and parameter errors. Understanding the effect of different modeling assumptions and minimizing these uncertainties is key for creating efficient and physical meaningful finite element models. In this paper the effects of different modeling assumptions are analyzed by comparing finite element models of an aero engine turbine casing. Various models of different fidelity are created reaching from simple shell element representations neglecting geometric features like bosses, fixings and holes, to higher fidelity mixed dimensional models using coupled shell and three-dimensional elements. To quantify their impact on the stiffness and mass properties, the different models are correlated with a high-fidelity three-dimensional finite element model using numerical modal data. A novel method is proposed based on the strain and kinetic energy distribution to assess the effect of different modeling assumptions on the model structure. This is done by splitting the discretized model into multiple sections of interest and calculating the deviation of energies within the related splits. The derived strain and kinetic energy deviations are then used in addition to other correlation criteria like the modal assurance criteria or the relative difference in eigenfrequencies to analyze the impact of the different modeling assumptions. Having quantified the differences, the difficulties of error localization using modal data are discussed in the context of the correlation results. Finally, the effectiveness of the derived deviation values are demonstrated by updating a finite element model of an aero engine turbine casing in the presence of structural simplifications using an evolutionary optimization algorithm and comparing the model updating strategy to the standard sensitivity-based updating approach. If the resulting updated model is used to predict structural modifications or untested loading conditions, the updated parameters might lose their physical meaning when altering regions of the model not in error. Therefore, it is important to examine the physical significance of the updated parameters. It is shown, how the energy-based model updating can help to address this problem. All in all, the proposed energy-based approach can be used to compare various modeling strategies in order to build efficient finite element models as well as assist in the choice of parameters for subsequent model updating to validate the numerical model against test data.

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