• 한국유체기계학회 논문집
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• 제3권3호
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• pp.19-24
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• 2000

It is well known that the finite element analysis often has an inaccuracy when it is in conflict with test results. Model updating is concerned with the correction of analytical model by processing records of response from test results. The famous one of the model updating methods is FRF sensitivity method. However, it has demerit that the solution is not unique. So, the neural network is recommended when an unique and exact solution is desired. The generalization ability of radial basis function neural network is used in model updating. As an application model, a cantilever and a rotor system are used. Specially the machined clearance($C_p$) of a journal bearing is updated.

• 소음진동
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• 제9권1호
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• pp.163-173
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• 1999

Precise and reasonable modelling is necessary and indispensable to the analysis of dynamic characteristics of mechanical structures. Also. the effective prediction of the change of modal properties due to the variation of design parameters is required especially for the application of finite element method to the structural dynamics problems. To meet those necessity and requirement, three model updating algorithms are proposed for finite element methods. Those algorithms are based on sensitivity analysis of the modal data obtained from experimental modal analysis(EMA) and analytical modal analysis(AMA). The adapted sensitivity analysis methods of the algorithms are 1)eigensensitivity(EGNS) method. 2)frequency response function sensitivity(FRFS) method. 3)sensitivity based element-by-element method (SBEEM), Singular value decomposition(SVD) is used for performing eigenanalysis and parameter estimation in the updating process. Those algorithms are applied to finite element of a plate and the updating capability of each algorithm is compared in terms of accuracy. reliability and stability of the updating process. It is shown that the model updating method using frequency response function is superior to the other methods in view of various updating capabilities.

• Earthquakes and Structures
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• 제5권1호
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• pp.111-127
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• 2013

This paper describes effects of infill walls on behavior of RC frame with low strength, including numerical modeling, modal testing and finite-element model updating. For this purpose full scaled, one bay and one story RC frame is produced and tested for plane and brick in-filled conditions. Ambient-vibration testis applied to identify dynamic characteristics under natural excitations. Enhanced Frequency Domain Decomposition and Stochastic Subspace Identification methods are used to obtain experimental dynamic characteristics. A numerical modal analysis is performed on the developed two-dimensional finite element model of the frames using SAP2000 software to provide numerical frequencies and mode shapes. Dynamic characteristics obtained by numerical and experimental are compared with each other and finite element model of the frames are updated by changing some uncertain modeling parameters such as material properties and boundary conditions to reduce the differences between the results. At the end of the study, maximum differences in the natural frequencies are reduced on average from 34% to 9% and a good agreement is found between numerical and experimental dynamic characteristics after finite-element model updating. In addition, it is seen material properties are more effective parameters in the finite element model updating of plane frame. However, for brick in-filled frame changes in boundary conditions determine the model updating process.

• Computers and Concrete
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• 제14권1호
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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.

• Smart Structures and Systems
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• 제10권4_5호
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• pp.459-470
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• 2012

This paper summarizes a study for the modal analysis and model updating conducted using the monitoring data obtained from the Canton Tower of 610 m tall, which was established as an international benchmark problem by the Hong Kong Polytechnic University. Modal properties of the tower were successfully identified using frequency domain decomposition and stochastic subspace identification methods. Finite element model updating using the measurement data was further performed to reduce the modal property differences between the measurements and those of the finite element model. Over-fitting during the model updating was avoided by using an optimization scheme with a regularization term.

• Structural Engineering and Mechanics
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• 제62권3호
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• pp.303-310
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• 2017

The model updating problems, which are to find the optimal approximation to the discrete quadratic model obtained by the finite element method, are critically important to the vibration analysis. In this paper, the structured model updating problem is considered, where the coefficient matrices are required to be symmetric and positive semidefinite, represent the interconnectivity of elements in the physical configuration and minimize the dynamics equations, and furthermore, due to the physical feasibility, the physical parameters should be positive. To the best of our knowledge, the model updating problem involving all these constraints has not been proposed in the existed literature. In this paper, based on the semidefinite programming technique, we design a general-purpose numerical algorithm for solving the structured model updating problems with incomplete measured data and present some numerical results to demonstrate the effectiveness of our method.

• Structural Engineering and Mechanics
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• 제68권1호
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• pp.39-51
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• 2018

In this study, a frequency domain model updating method is presented using power spectral density (PSD) data. It uses the sensitivity of PSD function with respect to the unknown structural parameters through a decomposed form of transfer function. The stiffness parameters are captured with high accuracy through solving the sensitivity equations utilizing the least square approach. Using numerically noise polluted data, the model updating results of a truss model prove robustness of the method against measurement and mass modelling errors. Results prove the capabilities of the method for parameter estimation using highly noise polluted data of low ranges of excitation frequency.

• Smart Structures and Systems
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• 제10권4_5호
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• pp.427-442
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• 2012

An effective approach for updating finite element model is presented which can provide reliable estimates for structural updating parameters from identified operational modal data. On the basis of the dynamic perturbation method, an exact relationship between the perturbation of structural parameters such as stiffness change and the modal properties of the tested structure is developed. An iterative solution procedure is then provided to solve for the structural updating parameters that characterise the modifications of structural parameters at element level, giving optimised solutions in the least squares sense without requiring an optimisation method. A regularization algorithm based on the Tikhonov solution incorporating the generalised cross-validation method is employed to reduce the influence of measurement errors in vibration modal data and then to produce stable and reasonable solutions for the structural updating parameters. The Canton Tower benchmark problem established by the Hong Kong Polytechnic University is employed to demonstrate the effectiveness and applicability of the proposed model updating technique. The results from the benchmark problem studies show that the proposed technique can successfully adjust the reduced finite element model of the structure using only limited number of frequencies identified from the recorded ambient vibration measurements.

• Computers and Concrete
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• 제14권6호
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• pp.745-765
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• 2014

In this paper, it is aimed to determine the finite element model updating effects on the structural behavior of long span concrete highway bridges. Birecik Highway Bridge located on the 81stkm of Sanliurfa-Gaziantep state highway over Firat River in Turkey is selected as a case study. The bridge consist of fourteen spans, each of span has a nearly 26m. The total bridge length is 380m and width of bridge is 10m. Firstly, the analytical dynamic characteristics such as natural frequencies and mode shapes are attained from finite element analyses using SAP2000 program. After, experimental dynamic characteristics are specified from field investigations using Operational Modal Analysis method. Enhanced Frequency Domain Decomposition method in the frequency domain is used to extract the dynamic characteristics such as natural frequencies, mode shapes and damping ratios. Analytically and experimentally identified dynamic characteristics are compared with each other and finite element model of the bridge is updated to reduce the differences by changing of some uncertain parameters such as section properties, damages, boundary conditions and material properties. At the end of the study, structural performance of the highway bridge is determined under dead load, live load, and dynamic loads before and after model updating to specify the updating effect. Displacements, internal forces and stresses are used as comparison parameters. From the study, it is seen that the ambient vibration measurements are enough to identify the most significant modes of long span highway bridges. Maximum differences between the natural frequencies are reduced averagely from %46.7 to %2.39 by model updating. A good harmony is found between mode shapes after finite element model updating. It is demonstrated that finite element model updating has an important effect on the structural performance of the arch type long span highway bridge. Maximum displacements, shear forces, bending moments and compressive stresses are reduced %28.6, %21.0, %19.22, and %33.3-20.0, respectively.

• Structural Engineering and Mechanics
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• 제65권2호
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• pp.173-181
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• 2018

In this paper, finite element (FE) model updating based on multi-objective optimization with the surrogate model for a steel plate girder bridge is investigated. Conventionally, FE model updating for bridge structures uses single-objective optimization with finite element analysis (FEA). In the case of the conventional method, computational burden occurs considerably because a lot of iteration are performed during the updating process. This issue can be addressed by replacing FEA with the surrogate model. The other problem is that the updating result from single-objective optimization depends on the condition of the weighting factors. Previous studies have used the trial-and-error strategy, genetic algorithm, or user's preference to obtain the most preferred model; but it needs considerable computation cost. In this study, the FE model updating method consisting of the surrogate model and multi-objective optimization, which can construct the Pareto-optimal front through a single run without considering the weighting factors, is proposed to overcome the limitations of the single-objective optimization. To verify the proposed method, the results of the proposed method are compared with those of the single-objective optimization. The comparison shows that the updated model from the multi-objective optimization is superior to the result of single-objective optimization in calculation time as well as the relative errors between the updated model and measurement.