• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2004.11a
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• pp.365-368
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• 2004

This paper describes a MATLAB based SDM software embodied in a GUI environment (SDMTool), which is a technical high-end tool for structural dynamics modification (SDM) problems. The software is composed of four modules: 1) FE model linker module; 2) FE model updating module; 3) SDM forward problem module; 4) SDM structural optimization module. The software can be useful to engineers performing researches on structural dynamics modification and FE model updating.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.19 no.9
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• pp.884-891
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• 2009

This study investigates some of swarm intelligence algorithms to tackle a traditional damage detection problem having stiffness degradation or damage in mechanical structures. Particle swarm(PSO) and ant colony optimization(ACO) methods have been exploited for localizing and estimating the location and extent damages in a structure. Both PSO and ACO are population-based, stochastic algorithms that have been developed from the underlying concept of swarm intelligence and search heuristic. A finite element (FE) model updating is implemented to minimize the difference in a set of natural frequencies between measured and baseline vibration data. Stiffness loss of certain elements is considered to simulate structural damages in the FE model. It is numerically shown that PSO and ACO algorithms successfully completed the optimization process of model updating in locating unknown damages in a truss structure.

• Smart Structures and Systems
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• v.24 no.6
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• pp.683-692
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• 2019

Traditional damage detection methods for nonlinear structures are often based on simplified models, such as the mass-spring-damper and shear-building models, which are insufficient for predicting the vibration responses of a real structure. Conventional global nonlinear finite element model updating methods are computationally intensive and time consuming. Thus, they cannot be applied to practical structures. A decentralized approach for identifying the nonlinear material parameters is proposed in this study. With this technique, a structure is divided into several small zones on the basis of its structural configuration. The unknown material parameters and measured vibration responses are then divided into several subsets accordingly. The structural parameters of each subset are then updated using the vibration responses of the subset with the Newton-successive-over-relaxation (SOR) method. A reinforced concrete and steel frame structure subjected to earthquake loading is used to verify the effectiveness and accuracy of the proposed method. The parameters in the material constitutive model, such as compressive strength, initial tangent stiffness and yielding stress, are identified accurately and efficiently compared with the global nonlinear model updating approach.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.28 no.4
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• pp.401-408
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• 2015

Conventional model updating methods for the structures have used global structural responses which are modal parameters obtained through vibration measurements. Although models updated by modal parameters estimate global structural responses accurately, they have difficulties to predict local responses for safety assesment of structural members. The safety of structural members in the structures has been evaluated through the stress estimation based on strain measurements. Thus, this study additionally uses measured strain responses of structural members to perform model updating besides modal parameters. In the proposed method, the objective functions are set to the differences of the global and local responses obtained from updated model and measurement and those functions are minimized by NSGA-II, one of the multi-objective optimization techniques. The strain responses predicted from updated model are used for safety assessment of the steel frame structures. The proposed method are verified by numerical and experimental studies through the impact hammer tests for a steel frame specimen.

• Structural Engineering and Mechanics
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• v.87 no.1
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• pp.1-18
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• 2023

The paper presents a Bayesian Finite element (FE) model updating methodology by utilizing modal data. The dynamic condensation technique is adopted in this work to reduce the full system model to a smaller model version such that the degrees of freedom (DOFs) in the reduced model correspond to the observed DOFs, which facilitates the model updating procedure without any mode-matching. The present work considers both the MPV and the covariance matrix of the modal parameters as the modal data. Besides, the modal data identified from multiple setups is considered for the model updating procedure, keeping in view of the realistic scenario of inability of limited number of sensors to measure the response of all the interested DOFs of a large structure. A relationship is established between the modal data and structural parameters based on the eigensystem equation through the introduction of additional uncertain parameters in the form of modal frequencies and partial mode shapes. A novel sampling strategy known as the Metropolis-within-Gibbs (MWG) sampler is proposed to sample from the posterior Probability Density Function (PDF). The effectiveness of the proposed approach is demonstrated by considering both simulated and experimental examples.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2000.04b
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• pp.195-204
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• 2000

The finite element analysis (FEA) is widely used in modern structural dynamics because the performance of structure can be predicted in early stage. However, due to the difficulty in determination of various uncertain parameters, it is not easy to obtain a reliable finite element model. To overcome these difficulties, a updating program of FE model is developed by consisting of pretest, correlation and update. In correlation, it calculates modal assurance criteria, cross orthogonality, mixed orthogonality and coordinate modal assurance criteria. For the model updating, the continuum sensitivity analysis and design optimization tool(DOT) are used. The SENSUP program is developed for model updating giving physical parameter sensitivity. The developed program is applied to practical examples such as the BLDC spindle motor of HDD, and upper housing of induction motor. And the sensor placement for the square plate is compared using several methods.

• Computers and Concrete
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• v.14 no.1
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• pp.73-90
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• 2014

The traditional destructive tests in damage detection require high cost, long consuming time, repairing of damaged members, etc. In addition to these, powerful equipments with advanced technology have motivated development of global vibration based damage detection methods. These methods base on observation of the changes in the structural dynamic properties and updating finite element models. The existence, location, severity and effect on the structural behavior of the damages can be identified by using these methods. The main idea in these methods is to minimize the differences between analytical and experimental natural frequencies. In this study, an application of damage detection using model updating method was presented on a one storey reinforced concrete (RC) building model. The model was designed to be 1/2 scale of a real building. The measurements on the model were performed by using ten uni-axial seismic accelerometers which were placed to the floor level. The presented damage identification procedure mainly consists of five steps: initial finite element modeling, testing of the undamaged model, finite element model calibration, testing of the damaged model, and damage detection with model updating. The elasticity modulus was selected as variable parameter for model calibration, while the inertia moment of section was selected for model updating. The first three modes were taken into consideration. The possible damaged members were estimated by considering the change ratio in the inertia moment. It was concluded that the finite element model calibration was required for structures to later evaluations such as damage, fatigue, etc. The presented model updating based procedure was very effective and useful for RC structures in the damage identification.

• Structural Engineering and Mechanics
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• v.32 no.5
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• pp.667-683
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• 2009

FE model-based dynamic analysis has been widely used to predict the dynamic characteristics of civil structures. In a physical point of view, an FE model is unavoidably different from the actual structure as being formulated based on extremely idealized engineering drawings and design data. The conventional model updating methods such as direct method and sensitivity-based parameter estimation are not flexible for model updating of complex and large structures. Thus, it is needed to develop a model updating method applicable to complex structures without restriction. The main objective of this paper is to present the model updating method based on the hybrid genetic algorithm (HGA) by combining the genetic algorithm as global optimization method and modified Nelder-Mead's Simplex method as local optimization method. This FE model updating method using HGA does not need the derivation of derivative function related to parameters and without application of complicated inverse analysis methods. In order to allow its application on diversified and complex structures, a commercial FEA tool is adopted to exploit previously developed element library and analysis algorithms. Moreover, an output-level objective function making use of measurement and analytical results is also presented to update simultaneously the stiffness and mass of the analysis model. The numerical examples demonstrated that the proposed method based on HGA is effective for the updating of the FE model of bridge structures.

• Structural Engineering and Mechanics
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• v.30 no.4
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• pp.481-500
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• 2008

In this paper, a model updating technique in dynamics is used to identify elastic properties for pultruded GFRP-Glass Fiber Reinforced Plastic framed structural systems used in civil construction. Traditional identification techniques for composite materials may be expensive, while this alternative approach allows to identify several properties simultaneously, with very good precision. Furthermore, the procedure of a non-destructive type has a relatively simple implementation. Properties describing the mechanical behavior for beam and shell finite element modeling are identified. The used formulation is based on the minimization of eigensolution residuals. Important points concerning model updating procedures have been observed, such as the particular vibrational behavior of the test structure, the modeling strategies and the optimal placement of the sensors in the experimental procedure. Results obtained by experimental tests show the efficiency of the proposed procedure.

• Structural Engineering and Mechanics
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• v.53 no.2
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• pp.249-260
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• 2015

Damage detection based on a reference set of measured data usually has the problem of different environmental temperature in the two sets of measurements, and the effect of temperature difference is usually ignored in the subsequent model updating. This paper attempts to identify the structural damage including the temperature difference with artificial measurement noise. Both local damages and the temperature difference are identified in a gradient-based model updating method based on dynamic response sensitivity. The sensitivities of dynamic response with respect to the system parameters and temperature difference are calculated by direct integration method. The measured dynamic responses of the structure from two different states are used directly to identify the structural local damages and the temperature difference. A single degree-of-freedom mass-spring system and a planar truss structure are studied to illustrate the effectiveness of the proposed method.