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>

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.

A Method for FE Model Updating of Coupled Vibro-Acoustic Systems Using Constrained Optimization

2013 ◽  
Author(s):  
D. V. Nehete ◽  
S. V. Modak ◽  
K. Gupta
Keyword(s):  
Finite Element ◽  
Constrained Optimization ◽  
Model Updating ◽  
Numerical Study ◽  
Element Model ◽  
Rectangular Cavity ◽  
Mode Shapes ◽  
Fe Model ◽  
Structural Dynamic ◽  
Fe Model Updating

Finite element (FE) model updating is now recognized as an effective approach to reduce modeling inaccuracies present in an FE model. FE model updating has been researched and studied well for updating FE models of purely structural dynamic systems. However there exists another class of systems known as vibro-acoustics in which acoustic response is generated in a medium due to the vibration of enclosing structure. Such systems are commonly found in aerospace, automotive and other transportation applications. Vibro-acoustic FE modeling is essential for sound acoustic design of these systems. Vibro-acoustic system, in contrast to purely structural system, has not received sufficient attention from FE model updating perspective and hence forms the topic of present paper. In the present paper, a method for finite element model updating of coupled structural acoustic model, constituted as a problem of constrained optimization, is proposed. An objective function quantifying error in the coupled natural frequencies and mode shapes is minimized to estimate the chosen uncertain parameters of the system. The effectiveness of the proposed method is validated through a numerical study on a 3D rectangular cavity attached to a flexible panel. The material property and the stiffness of joints between the panel and rectangular cavity are used as updating parameters. Robustness of the proposed method under presence of noise is investigated. It is seen that the method is not only able to obtain a close match between FE model and corresponding ‘measured’ vibro-acoustic characteristics but is also able to estimate the correction factors to the updating parameters with reasonable accuracy.

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.

scholarly journals Finite Element Modelling and Updating of Welded Thin-Walled Beam

2018 ◽  
Vol 15 (4) ◽  
pp. 5874-5889 ◽  
Author(s):  
M. S. M. Fouzi ◽  
K. M. Jelani ◽  
N. A. Nazri ◽  
Mohd Shahrir Mohd Sani
Keyword(s):  
Finite Element ◽  
Model Updating ◽  
Normal Mode Analysis ◽  
Mode Analysis ◽  
Modal Parameters ◽  
Fe Model ◽  
Fe Modelling ◽  
Welded Structure ◽  
Thin Walled ◽  
Fe Model Updating

This article concentrates on the finite element (FE) modelling approach to model welded thin-walled beam and the adoption of model updating technique to enhance the dynamic characteristic of the FE model. Four different types of element connectors which are RBE2, CBAR, CBEAM and CELAS format are used to construct the FE model of welded structure. Normal mode analysis is performed using finite element analysis (FEA) software, MSC Patran/Nastran to extract the modal parameters (natural frequency and mode shape) of the FE model. The precision of predicted modal parameters obtained from the four models of welded structure are compared with the measured counterparts. The dynamic characteristics of a measured counterpart is obtained through experimental modal analysis (EMA) using impact hammer method with roving accelerometer under free-free boundary conditions. In correlation process, the CBAR model has been selected for updating purposes due to its accuracy in prediction with measured counterparts and contains updating parameters compared to the others. Ahead of the updating process, sensitivity analysis is made to select the most sensitive parameter for updating purpose. Optimization algorithm in MSC Nastran is used in FE model updating process. As a result, the discrepancy between EMA and FEA is managed to be reduced. It shows the percentage of error for updated CBAR model shrinks from 7.85 % to 2.07 % when compared with measured counterpart. Hence, it is found that using FE model updating process provides an efficient and systemic way to perform a feasible FE model in replicating the real structure.

Sensitivity-Based Finite Element Model Updating Using Dynamic Condensation Approach

2018 ◽  
Vol 18 (08) ◽  
pp. 1840004 ◽  
Author(s):  
Tianyi Zhu ◽  
Wei Tian ◽  
Shun Weng ◽  
Hanbin Ge ◽  
Yong Xia ◽  
...  
Keyword(s):  
Finite Element ◽  
Optimization Design ◽  
Large Scale ◽  
Model Updating ◽  
Element Model ◽  
Fe Model ◽  
Large Scale Structures ◽  
Dynamic Condensation ◽  
Scale Structures ◽  
Fe Model Updating

An accurate finite element (FE) model is frequently used in damage detection, optimization design, reliability analysis, nonlinear analysis, and so forth. The FE model updating of large-scale structures is usually time-consuming or even impossible. This paper proposes a dynamic condensation approach for model updating of large-scale structures. The eigensolutions are calculated from a condensed eigenequation and the eigensensitivities are calculated without selection of additional master DOFs, which is helpful to improve the efficiency of FE model updating. The proposed model updating method is applied to an eight-storey frame and the Jun Shan Yangtze Bridge. By employing the dynamic condensation approach, the number of iterations for the eigensensitivities is gradually increased according to the model updating process, which contributes to accelerate the convergence of model updating.

Investigation of a Software for Finite Element Model Updating of Bridges Based on Interface Technology between VC++ and MATLAB

2013 ◽  
Vol 540 ◽  
pp. 1-10
Author(s):  
Yang Liu ◽  
Zhan Lv ◽  
Hong Zhang
Keyword(s):  
Finite Element ◽  
Finite Element Model ◽  
Model Updating ◽  
Element Model ◽  
Steel Tube ◽  
Finite Element Model Updating ◽  
Fe Model ◽  
Arch Bridge ◽  
Fe Model Updating

To develop an effective software for finite element (FE) model updating of bridges, the interface technology between VC++ and MATLAB was investigated firstly, and then a software for updating FE model of bridges, named Doctor for Bridges (version 1.0) was developed. Finally, a model ofconcrete-filled steel tube arch bridge was applied to verify the performance and effectiveness of the proposed software.

scholarly journals Condition Assessment of Joints in Steel Truss Bridges Using a Probabilistic Neural Network and Finite Element Model Updating

2021 ◽  
Vol 13 (3) ◽  
pp. 1474
Author(s):  
Jiawang Zhan ◽  
Chuang Wang ◽  
Zhiheng Fang
Keyword(s):  
Neural Network ◽  
Finite Element ◽  
Model Updating ◽  
Probabilistic Neural Network ◽  
Fe Model ◽  
Damage Localization ◽  
Truss Bridges ◽  
Steel Truss ◽  
Fe Model Updating ◽  
Steel Truss Bridges

The condition of joints in steel truss bridges is critical to railway operational safety. The available methods for the quantitative assessment of different types of joint damage are, however, very limited. This paper numerically investigates the feasibility of using a probabilistic neural network (PNN) and a finite element (FE) model updating technique to assess the condition of joints in steel truss bridges. A two-step identification procedure is developed to achieve damage localization and severity assessment. A series of FE models with single or multiple damages are simulated to generate the training and testing data samples and validate the effectiveness of the proposed approach. The influence of noise on the identification accuracy is also evaluated. The results show that the change rate of modal curvature (CRMC) can be used as a damage-sensitive input of the PNN and the accuracy of preliminary damage localization can exceed 90% when suitable training patterns are utilized. Damaged members can be localized in the correct substructure even with noise contamination. The FE model updating method used can effectively quantify the joint deterioration severity and is robust to noise.

Sign in / Sign up

Export Citation Format

Share Document