Comparing of Direct and Sensitivity-Base Model Updating Methods in Structural Dynamics and Its Application for Updating of Cantilever Model

2008 ◽  
Author(s):  
K. Abasi ◽  
M. Asayesh ◽  
M. Nikravesh
Keyword(s):  
Structural Dynamics ◽  
Model Updating ◽  
A Priori ◽  
Physical Parameters ◽  
Fe Model ◽  
Structural Components ◽  
Modal Data ◽  
Fe Model Updating ◽  
Fixed Boundary Condition ◽  
Small Rotation

Reliable finite element (FE) modeling in structural dynamics is very important for studies related to the safety of structural components used in industry. FE model updating is a tool to produce these reliable models. The method uses an initial FE model and experimental modal data of the structural components to modify physical parameters of the initial FE model, and a number of approaches have been developed to perform this task. This paper presents an overview of model updating and particularly its application for updating of cantilever model. An example of the need for model updating is a cantilever beam, where often the beam is assumed to be rigidly fixed at the clamped end. However, during tests it is often found that the beam has either a small rotation or deflection at the clamped end. If one has to construct the FE model without the knowledge of the experimental modal data, the natural assumption would be to include an ideal, fixed boundary condition, which may not be true. Even with such a simple structure the FE model is not reliable a priori, and based on intuition or engineering judgments it is difficult to estimate the values of the boundary stiffnesses. However, after creating an initial FE model, the model should be updated based on the experimental modal data obtained from modal tests so that the FE model may be used with confidence for further analysis.

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 A Copula-Based and Monte Carlo Sampling Approach for Structural Dynamics Model Updating with Interval Uncertainty

2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Xueqian Chen ◽  
Zhanpeng Shen ◽  
Xin’en Liu
Keyword(s):  
Monte Carlo ◽  
Structural Dynamics ◽  
Model Updating ◽  
Monte Carlo Sampling ◽  
Interval Uncertainty ◽  
Fe Model ◽  
Copula Model ◽  
Copula Approach ◽  
Spring System ◽  
Fe Model Updating

As the uncertainty is widely existent in the engineering structure, it is necessary to study the finite element (FE) modeling and updating in consideration of the uncertainty. A FE model updating approach in structural dynamics with interval uncertain parameters is proposed in this work. Firstly, the mathematical relationship between the updating parameters and the output interesting qualities is created based on the copula approach and the vast samples of inputs and outputs are obtained by the Monte Carlo (MC) sampling technology according to the copula model. Secondly, the samples of updating parameters are rechosen by combining the copula model and the experiment intervals of the interesting qualities. Next, 95% confidence intervals of updating parameters are calculated by the nonparameter kernel density estimation (KDE) approach, which is regarded as the intervals of updating parameters. Lastly, the proposed approach is validated in a two degree-of-freedom mass-spring system, simple plates, and the transport mirror system. The updating results evidently demonstrate the feasibility and reliability of this approach.

The Application of Bees Algorithm in Finite Element Model Updating

2010 ◽  
Author(s):  
Laleh Fatahi ◽  
Shapour Moradi ◽  
Pejman Razi
Keyword(s):  
Finite Element ◽  
Objective Function ◽  
Model Updating ◽  
Research Work ◽  
Modal Testing ◽  
Bees Algorithm ◽  
Physical Parameters ◽  
Piping System ◽  
Fe Model ◽  
Fe Model Updating

This research work is aimed to investigate the application of bees algorithm (BA) to the finite element (FE) model updating. BA is an evolutionary optimization algorithm that imitates the natural foraging behavior of the honeybees to find the global optimum of an objective function. Here, the weighted squared sum of the error between the measured modal parameters and the FE model predictions is considered as the objective function. To demonstrate the effectiveness of the proposed method, BA is applied on a piping system to update several physical parameters of its FE model. The results obtained from the numerical model are compared with the experimental ones obtained through the modal testing. The results show that BA successfully updates the FE model. Moreover, the performance of this approach is compared with two popular optimization methods; the genetic algorithm (GA) and the particle swarm optimization (PSO). The comparison shows the advantage of BA over GA and its similarity to PSO in terms of accuracy in the presented case study. However, BA reaches to the optimum solution faster than PSO and GA. Therefore, it can be concluded that BA is a robust and accurate optimization method that could be a good candidate for the FE model updating.

FE Model Updating for Damage Detection – Application to a Welded Structure

2009 ◽  
Vol 413-414 ◽  
pp. 393-400 ◽  
Author(s):  
Nurulakmar Abu Husain ◽  
Andy Snaylam ◽  
Hamed Haddad Khodaparast ◽  
S. James ◽  
Geoff Dearden ◽  
...  
Keyword(s):  
Structural Damage ◽  
Model Updating ◽  
Physical Parameters ◽  
Model Parameters ◽  
Fe Model ◽  
Automotive Body ◽  
Modal Properties ◽  
Numerical Predictions ◽  
Welded Structure ◽  
Fe Model Updating

Finite Element (FE) model updating is initially developed to update numerical models of structures to match their experimentally measured modal properties (i.e., natural frequencies and modes). In FE model updating, uncertain physical parameters of a structure are modified so that the discrepancies between the numerically estimated and experimentally measured modal properties are minimized. The process of updating is employed not only in parameter identification; it can also be developed for structural damage identification. In this work, a welded structure that is intended to represent a common configuration used in automotive body construction is investigated. It is known that presence of any damage in the welds of such a structure could affect its dynamic behavior. So, in theory modal test data can allow damage to be assessed accurately. As a typical automotive body contains thousands of welds, the effects of damage in the welds could be influential. The FE model updating process using experimental data is presented. It is carried out using NASTRAN optimization code. The procedure aims to adjust the uncertain properties of the FE model (from the weld joints) by minimizing the differences between the measured modal properties and the corresponding numerical predictions. The initial parameter values used in the numerical model are the nominal values. The procedure brings the numerical results of the structure as close as possible to the experimental ones, according to an objective function, therefore altering some of the FE model parameters of the structure. It may be concluded that when the identified values of certain parameters deviates from the nominal values to certain extent, there is a fault or damage at that particular joint.

Probabilistic Finite Element Model Updating of Civil Engineering Structures: A Comparative Study

2019 ◽  
Author(s):  
Javier F. Jiménez Alonso ◽  
Emma J. Hudson ◽  
Aleksandar Pavic ◽  
Andrés Sáez
Keyword(s):  
Finite Element ◽  
Civil Engineering ◽  
Model Updating ◽  
Likelihood Method ◽  
Physical Parameters ◽  
Fe Model ◽  
Engineering Structures ◽  
Slice Sampling ◽  
Civil Engineering Structures ◽  
Fe Model Updating

<p>Finite element (FE) model updating of civil engineering structures is usually performed under the modal domain. According to this approach, the value of the main physical parameters of the structure is modified in order to reduce the relative differences between the experimental and numerical modal parameters of the structure. To date, two methods are widely used to perform the FE model updating: (i) the maximum likelihood method and (ii) the Bayesian method. The second method is usually implemented via sampling methods. Thus, the FE model updating consists in determining an efficient sampling of each considered physical parameter of the model. Herein, two sampling techniques, the Metropolis-Hastings (M-H) algorithm and the Slice Sampling (SS) algorithm, are compared when they are implemented for the FE model updating of a laboratory steel footbridge.</p>

scholarly journals Vision-Based Structural FE Model Updating Using Genetic Algorithm

2021 ◽  
Vol 11 (4) ◽  
pp. 1622
Author(s):  
Gun Park ◽  
Ki-Nam Hong ◽  
Hyungchul Yoon
Keyword(s):  
Genetic Algorithm ◽  
Model Updating ◽  
Structural Parameters ◽  
Fe Model ◽  
Structural Members ◽  
Stiffness Reduction ◽  
Before And After ◽  
Scale Test ◽  
Fe Model Updating ◽  
Story Building

Structural members can be damaged from earthquakes or deterioration. The finite element (FE) model of a structure should be updated to reflect the damage conditions. If the stiffness reduction is ignored, the analysis results will be unreliable. Conventional FE model updating techniques measure the structure response with accelerometers to update the FE model. However, accelerometers can measure the response only where the sensor is installed. This paper introduces a new computer-vision based method for structural FE model updating using genetic algorithm. The system measures the displacement of the structure using seven different object tracking algorithms, and optimizes the structural parameters using genetic algorithm. To validate the performance, a lab-scale test with a three-story building was conducted. The displacement of each story of the building was measured before and after reducing the stiffness of one column. Genetic algorithm automatically optimized the non-damaged state of the FE model to the damaged state. The proposed method successfully updated the FE model to the damaged state. The proposed method is expected to reduce the time and cost of FE model updating.

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