Parameter Identification of Complex Structures Using Finite Element Model Updating Techniques

2015 ◽  
Author(s):  
Dimitrios Giagopoulos ◽  
Alexandros Arailopoulos
Keyword(s):  
Finite Element ◽  
Finite Element Model ◽  
Model Updating ◽  
Complex Geometry ◽  
Element Model ◽  
Mode Shapes ◽  
Cad Model ◽  
Modal Characteristics ◽  
Acceleration Time Histories ◽  
The Finite Element Model

In this work, an integrated reverse engineering strategy is presented that takes into account the complete process, from the developing of CAD model and the experimental modal analysis procedures to computational effective model updating techniques. Modal identification and structural model updating methods are applied, leading to develop high fidelity finite element model of geometrically complex and lightweight bicycle frame, using acceleration measurements. First, exploiting a 3D Laser Scanner, the digital shape of the real bike frame was developed and the final parametric CAD model was created. Next the finite element model of the frame was created by using quadrilateral shell and hexahedral solid elements. Due to complex geometry of the structure, the developed model consists of about one million degrees of freedom. The identification of modal characteristics of the frame is based on acceleration time histories, which are obtained through an experimental investigation of its dynamic response in a support-free state by imposing impulsive loading. A high modal density modal model is obtained. The modal characteristics are then used to update the finite element model. Single and multiobjective structural identification methods with appropriate substructuring methods, are used for estimating the parameters (material properties and shell thickness properties) of the finite element model, based on minimizing the deviations between the experimental and analytical modal characteristics (modal frequencies and mode shapes). Direct comparison of the numerical and experimental data verified the reliability and accuracy of the methodology applied.

scholarly journals Bayesian Model-Updating Using Features of Modal Data: Application to the Metsovo Bridge

2020 ◽  
Vol 9 (2) ◽  
pp. 27 ◽  
Author(s):  
Costas Argyris ◽  
Costas Papadimitriou ◽  
Panagiotis Panetsos ◽  
Panos Tsopelas
Keyword(s):  
Finite Element ◽  
Finite Element Model ◽  
Model Updating ◽  
Element Model ◽  
Modal Identification ◽  
Monte Carlo Algorithm ◽  
Mode Shapes ◽  
Model Parameters ◽  
Modal Data ◽  
Acceleration Time Histories

A Bayesian framework is presented for finite element model-updating using experimental modal data. A novel likelihood formulation is proposed regarding the inclusion of the mode shapes, based on a probabilistic treatment of the MAC value between the model predicted and experimental mode shapes. The framework is demonstrated by performing model-updating for the Metsovo bridge using a reduced high-fidelity finite element model. Experimental modal identification methods are used in order to extract the modal characteristics of the bridge from ambient acceleration time histories obtained from field measurements exploiting a network of reference and roving sensors. The Transitional Markov Chain Monte Carlo algorithm is used to perform the model updating by drawing samples from the posterior distribution of the model parameters. The proposed framework yields reasonable uncertainty bounds for the model parameters, insensitive to the redundant information contained in the measured data due to closely spaced sensors. In contrast, conventional Bayesian formulations which use probabilistic models to characterize the components of the discrepancy vector between the measured and model-predicted mode shapes result in unrealistically thin uncertainty bounds for the model parameters for a large number of sensors.

Model structure correction and updating of aeroengine casings using fictitious mass modifications

2005 ◽  
Vol 219 (1) ◽  
pp. 19-30 ◽  
Author(s):  
H Shahverdi ◽  
C Mares ◽  
J E Mottershead
Keyword(s):  
Finite Element ◽  
Finite Element Model ◽  
Model Updating ◽  
Element Model ◽  
Mode Shapes ◽  
Combined Model ◽  
Shell Elements ◽  
Turbine Casing ◽  
The Finite Element Model

In this paper the results of a finite element model updating exercise, carried out on closely axisymmetric aeroengine casings, are presented. The correction of the combustion chamber outer casing (CCOC) model is considered and, after assembly with the turbine casing (TC), the quality of the resulting combined model is investigated. The dynamics of both casings is characterized by pairs of close modes, which may be separated by fictitious point mass modifications. The natural frequencies and mode shapes of the fictitiously modified CCOC are determined from receptances obtained from the CCOC in its original (unmodified) configuration. The modifications are shown to improve the understanding of both the CCOC and the system formed by connecting the CCOC to the TC. A particular problem is revealed when model updating is applied to the CCOC. An analysis of the mode shapes locates a modelling error on an inner shell of the structure but it is found that the finite element model is unable to be parameterized for the correction of two pairs of wrongly ordered predicted modes. This can only be achieved by firstly correcting the ‘structure’ of the model itself. The main error is found to be a geometrical inaccuracy, and, when this is put right, the sequence of the modes is corrected. Model updating is then applied to the thickness of certain shell elements and the CCOC is found to be in excellent agreement with measured data, as is the complete model formed from the two models of the CCOC and the TC together.

scholarly journals Sensitivity Analysis of the Influence of Structural Parameters on Dynamic Behaviour of Highly Redundant Cable-Stayed Bridges

2013 ◽  
Vol 2013 ◽  
pp. 1-11 ◽  
Author(s):  
B. Asgari ◽  
S. A. Osman ◽  
A. Adnan
Keyword(s):  
Sensitivity Analysis ◽  
Finite Element ◽  
Finite Element Model ◽  
Model Updating ◽  
Structural Parameters ◽  
Element Model ◽  
Structural Behavior ◽  
Model Tuning ◽  
The Finite Element Model ◽  
Cable Stayed Bridges

The model tuning through sensitivity analysis is a prominent procedure to assess the structural behavior and dynamic characteristics of cable-stayed bridges. Most of the previous sensitivity-based model tuning methods are automatic iterative processes; however, the results of recent studies show that the most reasonable results are achievable by applying the manual methods to update the analytical model of cable-stayed bridges. This paper presents a model updating algorithm for highly redundant cable-stayed bridges that can be used as an iterative manual procedure. The updating parameters are selected through the sensitivity analysis which helps to better understand the structural behavior of the bridge. The finite element model of Tatara Bridge is considered for the numerical studies. The results of the simulations indicate the efficiency and applicability of the presented manual tuning method for updating the finite element model of cable-stayed bridges. The new aspects regarding effective material and structural parameters and model tuning procedure presented in this paper will be useful for analyzing and model updating of cable-stayed bridges.

Dynamic Characteristics and Finite Element Model Updating of Micromachined Torsion Structures

2013 ◽  
Vol 284-287 ◽  
pp. 1831-1835
Author(s):  
Wei Hsin Gau ◽  
Kun Nan Chen ◽  
Yunn Lin Hwang
Keyword(s):  
Finite Element Analysis ◽  
Finite Element ◽  
Finite Element Model ◽  
Model Updating ◽  
Speckle Pattern ◽  
Element Model ◽  
Mode Shapes ◽  
Electronic Speckle Pattern Interferometry ◽  
Finite Element Model Updating ◽  
Element Analysis

In this paper, two experimental techniques, Electronic Speckle Pattern Interferometry and Stroboscopic Interferometry, and two different finite element analysis packages are used to measure or to analyze the frequencies and mode shapes of a micromachined, cross-shaped torsion structure. Four sets of modal data are compared and shown having a significant discrepancy in their frequency values, although their mode shapes are quite consistent. Inconsistency in the frequency results due to erroneous inputs of geometrical and material parameters to the finite element analysis can be salvaged by applying the finite element model updating procedure. Two updating cases show that the optimization sequences converge quickly and significant improvements in frequency prediction are achieved. With the inclusion of the thickness parameter, the second case yields a maximum of under 0.4% in frequency difference, and all parameters attain more reliable updated values.

Hydroelastic Modal Analysis of the Perforated Cylindrical Shell in SMART

2011 ◽  
Author(s):  
Youngin Choi ◽  
Seungho Lim ◽  
Kyoung-Su Park ◽  
No-Cheol Park ◽  
Young-Pil Park ◽  
...  
Keyword(s):  
Finite Element ◽  
Finite Element Model ◽  
Dynamic Characteristics ◽  
Natural Frequencies ◽  
Element Model ◽  
Mode Shapes ◽  
Steam Generators ◽  
Structure Interaction ◽  
The Finite Element Model ◽  
Reactor Internals

The System-integrated Modular Advanced ReacTor (SMART) developed by KAERI includes components like a core, steam generators, coolant pumps, and a pressurizer inside the reactor vessel. Though the integrated structure improves the safety of the reactor, it can be excited by an earthquake and pump pulsations. It is important to identify dynamic characteristics of the reactor internals considering fluid-structure interaction caused by inner coolant for preventing damage from the excitations. Thus, the finite element model is constructed to identify dynamic characteristics and natural frequencies and mode shapes are extracted from this finite element model.

scholarly journals Vibration-based Bayesian model updating of civil engineering structures applying Gaussian process metamodel

2019 ◽  
Vol 22 (16) ◽  
pp. 3487-3502
Author(s):  
Hossein Moravej ◽  
Tommy HT Chan ◽  
Khac-Duy Nguyen ◽  
Andre Jesus
Keyword(s):  
Finite Element ◽  
Finite Element Model ◽  
Bayesian Approach ◽  
Model Updating ◽  
Numerical Models ◽  
Element Model ◽  
The Body ◽  
Structural Safety ◽  
Discrepancy Function ◽  
The Finite Element Model

Structural health monitoring plays a significant role in providing information regarding the performance of structures throughout their life spans. However, information that is directly extracted from monitored data is usually susceptible to uncertainties and not reliable enough to be used for structural investigations. Finite element model updating is an accredited framework that reliably identifies structural behavior. Recently, the modular Bayesian approach has emerged as a probabilistic technique in calibrating the finite element model of structures and comprehensively addressing uncertainties. However, few studies have investigated its performance on real structures. In this article, modular Bayesian approach is applied to calibrate the finite element model of a lab-scaled concrete box girder bridge. This study is the first to use the modular Bayesian approach to update the initial finite element model of a real structure for two states—undamaged and damaged conditions—in which the damaged state represents changes in structural parameters as a result of aging or overloading. The application of the modular Bayesian approach in the two states provides an opportunity to examine the performance of the approach with observed evidence. A discrepancy function is used to identify the deviation between the outputs of the experimental and numerical models. To alleviate computational burden, the numerical model and the model discrepancy function are replaced by Gaussian processes. Results indicate a significant reduction in the stiffness of concrete in the damaged state, which is identical to cracks observed on the body of the structure. The discrepancy function reaches satisfying ranges in both states, which implies that the properties of the structure are predicted accurately. Consequently, the proposed methodology contributes to a more reliable judgment about structural safety.

Impact of Accelerometer Placement on Modal Extraction of Offshore Wind Structures

2020 ◽  
Author(s):  
M. Richmond ◽  
S. Siedler ◽  
M. Häckell ◽  
U. Smolka ◽  
A. Kolios
Keyword(s):  
Finite Element ◽  
Finite Element Model ◽  
Model Updating ◽  
Sensor Placement ◽  
Element Model ◽  
Offshore Wind ◽  
Mode Shapes ◽  
Modal Parameters ◽  
Optimal Sensor Placement ◽  
Permanent Campaign

Abstract The modal parameters extracted from a structure by accelerometers can be used for damage assessment as well as model updating. To extract modal parameters from a structure, it is important to place accelerometers at locations with high modal displacements. Sensor placement can be restricted by practical considerations, and installation might be conducted more based on engineering judgement rather than analysis. This leads to the question of how important the optimal sensor placement is, and if fewer sensors suffice to extract the modal parameters. In this work, an offshore wind substation (OSS) from the Wikinger offshore wind farm (owned by Iberdrola) is instrumented with 12, 3-axis accelerometers. This sensor setup consists of 6 sensors in a permanent campaign where sensors were placed based purely on engineering judgement, as well as 6 sensors in a temporary campaign, placed based on a placement analysis. An optimal sensor placement study was conducted using a finite element model of the structure in the software package FEMtools, resulting in optimal layouts. The temporary campaign sensors were placed such that they, in combination with the permanent campaign, can be used to complete the proposed layouts. Samples for each setup are processed using the software ARTeMIS modal to extract the mode shapes and natural frequencies through the Stochastic Subspace Identification (SSI) technique. The frequencies found by this approach are then clustered together using a k-means algorithm for a comparison within clusters. The modal assurance criterion (MAC) values are calculated for each result and compared to the finite element model from which the optimal sensor placement study was conducted. This is to match mode shapes between the two and thus determine the importance of off diagonal MAC elements in the sensor optimization process. MAC values are also calculated relative to a cluster-averaged set of eigenvectors to determine how they vary over the 1.5 months. The results show that for all sensor layouts, the three lower frequency modes are consistently identified. The most optimized sensor layout, consisting of only 3 sensors, was able to distinguish an additional, higher frequency mode which was never identified in the 6-sensor permanent layout. However, the reduced sensor layout shows slightly more scatter in the results than the 6-sensor layout. There is a higher signal to noise ratio in the temporary campaign which results in scatter. We conclude that with an optimized placement of accelerometers, more modes can be identified and distinguished. However, off diagonal elements in the original MAC matrix, as well as loss of sensor degrees of freedom, can result in additional scatter in the measurements. Some of these findings can be extended to other offshore jacket structures, such as those of wind turbines, in that it gives a better understanding of the consequence of an optimal sensor placement study.

Sign in / Sign up

Export Citation Format

Share Document