• Structural Engineering and Mechanics
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• v.63 no.2
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• pp.251-257
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• 2017

A local damage identification method using measured structural static displacement is proposed in this study. Based on the residual force vector deduced from the static equilibrium equation, residual strain energy (RSE) is introduced, which can localize the damage in the element level. In the case of all the nodal displacements are used, the RSE can localize the true location of damage, while incomplete displacement measurements are used, some suspicious damaged elements can be found. A model updating method based on static displacement response sensitivity analysis is further utilized for accurate identification of damage location and extent. The proposed method is verified by two numerical examples. The results indicate that the proposed method is efficient for damage identification. The advantage of the proposed method is that only limited static displacement measurements are needed in the identification, thus it is easy for engineering application.

• Proceedings of the KSR Conference
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• 2002.10b
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• pp.1065-1073
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• 2002

A new damage identification technique using static displacement data is developed to assess the structural integrity of bridge structures. In the conventional damage assessment techniques using dynamic response, it is usually difficult to obtain a significant natural frequencies variation from the measured data because the natural frequencies variation is intrinsically not sensitive to the damage of a bridge. In this proposed identification method, the stiffness reduction of the bridges can be estimated using the static displacement data measured periodically and a specific loading test is not required. The static displacement data due to the dead load of the bridge structure can be measured by devices such as a laser displacement sensor. In this study, structural damage is represented by the reduction in the elastic modulus of the element. The damage factor of the element is introduced to estimate the stiffness reduction of the bridge under consideration. Finally, the proposed algorithm is verified using various numerical simulation and compared with other damage identification method. Also, the effect of noise and number of damaged elements on the identification are investigated. The results show that the proposed algorithm is efficient for damage identification of the bridges.

• Smart Structures and Systems
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• v.15 no.1
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• pp.81-97
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• 2015

Recently, a new output-only modal identification method based on time-frequency independent component analysis (ICA) has been developed by the authors and shown to be useful for even highly-damped structures. In many cases, it is of interest to identify the complex modes of structures with non-proportional damping. This study extends the time-frequency ICA based method to a complex ICA formulation for output-only modal identification of non-proportionally-damped structures. The connection is established between complex ICA model and the complex-valued modal expansion with sparse time-frequency representation, thereby blindly separating the measured structural responses into the complex mode matrix and complex-valued modal responses. Numerical simulation on a non-proportionally-damped system, laboratory experiment on a highly-damped three-story frame, and a real-world highly-damped base-isolated structure identification example demonstrate the capability of the time-frequency complex ICA method for identification of structures with complex modes in a straightforward and efficient manner.

• Structural Engineering and Mechanics
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• v.54 no.2
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• pp.291-304
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• 2015

Compared with the identification of linear structures, it is more challenging to conduct identification of nonlinear structure systems, especially when the locations of structural nonlinearities are not clear in structural systems. Moreover, it is highly desirable to develop methods of parametric identification using partial measurements of structural responses for practical application. To cope with these issues, an identification method is proposed in this paper for the detection and parametric identification of structural nonlinear restoring forces using only partial measurements of structural responses. First, an equivalent linear structural system is proposed for a nonlinear structure and the locations of structural nonlinearities are detected. Then, the parameters of structural nonlinear restoring forces at the locations of identified structural nonlinearities together with the linear part structural parameters are identified by the extended Kalman filter. The proposed method simplifies the identification of nonlinear structures. Numerical examples of the identification of two nonlinear multi-story shear frames and a planar nonlinear truss with different nonlinear models and locations are used to validate the proposed method.

• Smart Structures and Systems
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• v.26 no.1
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• pp.63-75
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• 2020

Substructure pseudo-dynamic hybrid simulation (SPDHS) combining the advantages of physical experiments and numerical simulation has become an important testing method for evaluating the dynamic responses of structures. Various parameter identification methods have been proposed for online model updating. However, if there is large model gap between the assumed numerical models and the real models, the parameter identification methods will cause large prediction errors. This study presents an ANN (artificial neural network) method based on forgetting factor. During the SPDHS of model updating, a dynamic sample window is formed in each loading step with forgetting factor to keep balance between the new samples and historical ones. The effectiveness and anti-noise ability of this method are evaluated by numerical analysis of a six-story frame structure with BRBs (Buckling Restrained Brace). One BRB is simulated in OpenFresco as the experimental substructure, while the rest is modeled in MATLAB. The results show that ANN is able to present more hysteresis behaviors that do not exist in the initial assumed numerical models. It is demonstrated that the proposed method has good adaptability and prediction accuracy of restoring force even under different loading histories.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.20 no.3
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• pp.269-278
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• 2022

The buffer is a critical barrier component in an engineered barrier system, and its purpose is to prevent potential radionuclides from leaking out from a damaged canister by filling the void in the repository. No experimental parameters exist that can describe the buffer expansion phenomenon when Kyeongju bentonite, which is a buffer candidate material available in Korea, is exposed to groundwater. As conventional experiments to determine these parameters are time consuming and complicated, simple swelling pressure tests, numerical modeling, and machine learning are used in this study to obtain the parameters required to establish a numerical model that can simulate swelling. Swelling tests conducted using Kyeongju bentonite are emulated using the COMSOL Multiphysics numerical analysis tool. Relationships between the swelling phenomenon and mechanical parameters are determined via an artificial neural network. Subsequently, by inputting the swelling tests results into the network, the values for the mechanical parameters of Kyeongju bentonite are obtained. Sensitivity analysis is performed to identify the influential parameters. Results of the numerical analysis based on the identified mechanical parameters are consistent with the experimental values.

• Structural Engineering and Mechanics
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• v.39 no.6
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• pp.751-765
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• 2011

The present paper deals with the identification of a concentrated damage in an elastic parabolic arch through the minimization of an objective function which measures the differences between numerical and experimental values of static displacements. The damage consists in a notch that reduces the height of the cross section at a given abscissa and therefore causes a variation in the flexural stiffness of the structure. The analytical values of static displacements due to applied loads are calculated by means of the principle of virtual work for both the undamaged and damaged arch. First, pseudo-experimental data are used to study the inverse problem and investigate whether a unique solution can occur or not. Various damage intensities are considered to assess the reliability of the identification procedure. Then, the identification procedure is applied to an experimental case, where displacements are measured on a prototype arch. The identified values of damage parameters, i.e., location and intensity, are compared to those obtained by means of a dynamic identification technique performed on the same structure.

• Journal of the Korean Society for Precision Engineering
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• v.12 no.9
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• pp.22-29
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• 1995

An experimental method to identify the rigid properties (mass, moment of inertia, center of mass) of mounted structures is presented. A direct system identification method is developed and applied to identify the mass, damping and stiffness martix directly from the translational response of vibration testing. Conventional method is sensitive to noise since it needs artificial rotational response of temporary center of mass which is made by the linear transformation of translational response. A presented method needs only the translational response, and it is robuster to noise than conventional method. Several experimental and numerical implementations show the presented method is effective.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.17 no.4 s.121
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• pp.324-332
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• 2007

Sensor placement method for damage identification has been developed for model updating using Taguchi method. In order to select the optimal sensor location, the analysis of variance of objective function using orthogonal array was carried out. Then, modal data at the selected locations were used for damage identification using model updating. The numerical model of a cantilever beam was used in order to compare the damage identification results with conventional sensor location method.

• Journal of Multimedia Information System
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• v.4 no.4
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• pp.263-270
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• 2017

Various security threats exist in the smart grid environment due to the fact that information and communication technology are grafted onto an existing power grid. In particular, smart metering data exposes a variety of information such as users' life patterns and devices in use, and thereby serious infringement on personal information may occur. Therefore, we are in a situation where a de-identification algorithm suitable for metering data is required. Hence, this paper proposes a new de-identification method for metering data. The proposed method processes time information and numerical information as de-identification data, respectively, so that pattern information cannot be analyzed by the data. In addition, such a method has an advantage that a query such as a direct range search and aggregation processing in a database can be performed even in a de-identified state for statistical processing and availability.