• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2005년도 추계학술대회논문집
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• pp.79-83
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• 2005

SEA is a useful tool to predict noise and vibration response in high frequency region but has a weak point not to be able to express modal behavior in low frequency region. For a structure with middle subsystem having relatively higher modal density than excited subsystem and receiving subsystem, we studied the possibility that the modal behavior of receiving subsystem can express by considering finite mobility of excited subsystem. For a simply three-coupled beams which is chosen for feasibility study, the response of receiving beam was investigated with varying the length & area moment of inertia of middle beam. In case that the middle beam has relatively higher modal density than exciting beam, the application to finite mobility of excited beam led to express modal behavior of receiving beam relatively well.

• 대한기계학회논문집A
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• 제40권12호
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• pp.1061-1066
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• 2016

주름 강판의 주름은 강판의 중량당 굽힘 강성을 획기적으로 증가시킨다. 그러나 주름 강판은 같은 중량을 갖는 평판보다 낮은 차음 성능을 보인다. 특히, 특정한 주파수대역에서는 투과손실이 크게 감소한다. 이 문제의 주 요인은 주름단위에서의 국부적 공진으로 알려져 있다. 특정 주파수대역에서 다수의 국부적 공진모드가 발생하고 모드밀도가 급속히 증가한다. 본 연구에서는 음 투과손실과 모드 밀도 사이의 관계를 검토한다. 최종적으로, 중량의 증가 없이 주름 강판의 차음 성능을 향상시키기 위한 모드 밀도의 측면에서의 설계전략을 제시한다.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2002년도 춘계학술대회논문집
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• pp.359-364
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• 2002

Statistical energy method is widely used for the prediction of vibrational and acoustical behavior of complex structures, such as ship building and automobile in mid-, high frequency ranges. However. in order to convince this SEA result, it is important to verify estimated SEA parameters, e. g. modal density, energy in each subsystem, damping loss factor, coupling loss factor. with possible other method. For modal density parameter, the experimental estimations via Experimental Modal Analysis are checked with those from finite element method for both beam- plate and plate-plate cans. Loss factors are calculated by Lyon's simple method for the two subsystem. finally. modal experiments are carried out by varying the mass added on the junction of two subsystem for the purpose of investigating the influence on the coupling loss factor's behavior.

• Smart Structures and Systems
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• 제19권5호
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• pp.499-512
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• 2017

Traditional structural dynamic analysis and Structural Health Monitoring (SHM) of large scale concrete civil structures rely on manufactured embedding transducers to obtain structural dynamic properties. However, the embedding of manufactured transducers is very expensive and low efficiency for signal acquisition. In dynamic structural analysis and SHM areas, piezoelectric transducers are more and more popular due to the advantages like quick response, low cost and adaptability to different sizes. In this paper, the applicable feasibility assessment of the designed "artificial" piezoelectric transducers called Concrete Piezoelectric Smart Module (CPSM) in dynamic structural analysis is performed via three major experiments. Experimental Modal Analysis (EMA) based on Ibrahim Time Domain (ITD) Method is applied to experimentally extract modal parameters. Numerical modal analysis by finite element method (FEM) modeling is also performed for comparison. First ten order modal parameters are identified by EMA using CPSMs, PCBs and FEM modeling. Comparisons are made between CPSMs and PCBs, between FEM and CPSMs extracted modal parameters. Results show that Power Spectral Density by CPSMs and PCBs are similar, CPSMs acquired signal amplitudes can be used to predict concrete compressive strength. Modal parameter (natural frequencies) identified from CPSMs acquired signal and PCBs acquired signal are different in a very small range (~3%), and extracted natural frequencies from CPSMs acquired signal and FEM results are in an allowable small range (~5%) as well. Therefore, CPSMs are applicable for signal acquisition of dynamic responses and can be used in dynamic modal analysis, structural health monitoring and related areas.

• Nuclear Engineering and Technology
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• 제41권6호
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• pp.821-830
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• 2009

In this paper, modal testing and finite element modeling results to identify the modal parameters of a nuclear fuel rod as well as its cladding tube are discussed. A vertically standing full-size cladding tube and a fuel rod with lead pellets were used in the modal testing. As excessive flow-induced vibration causes a failure in fuel rods, such as fretting wear, the vibration level of fuel rods should be low enough to prevent failure of these components. Because vibration amplitude can be estimated based on the modal parameters, the dynamic characteristics must be determined during the design process. Therefore, finite element models are developed based on the test results. The effect of a lumped mass attached to a cladding tube model was identified during the finite element model optimization process. Unlike a cladding tube model, the density of a fuel rod with pellets cannot be determined in a straightforward manner because pellets do not move in the same phase with the cladding tube motion. The density of a fuel rod with lead pellets was determined by comparing natural frequency ratio between the cladding tube and the rod. Thus, an improved fuel rod finite element model was developed based on the updated cladding tube model and an estimated fuel rod density considering the lead pellets. It is shown that the entire pellet mass does not contribute to the fuel rod dynamics; rather, they are only partially responsible for the fuel rod dynamic behavior.

• Smart Structures and Systems
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• 제17권3호
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• pp.445-470
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• 2016

In this study, the Bayesian probabilistic framework is investigated for modal identification and modal identifiability based on the field measurements provided in the structural health monitoring benchmark problem of an instrumented cable-stayed bridge named Ting Kau Bridge (TKB). The comprehensive structural health monitoring system on the cable-stayed TKB has been operated for more than ten years and it is recognized as one of the best test-beds with readily available field measurements. The benchmark problem of the cable-stayed bridge is established to stimulate investigations on modal identifiability and the present paper addresses this benchmark problem from the Bayesian prospective. In contrast to deterministic approaches, an appealing feature of the Bayesian approach is that not only the optimal values of the modal parameters can be obtained but also the associated estimation uncertainty can be quantified in the form of probability distribution. The uncertainty quantification provides necessary information to evaluate the reliability of parametric identification results as well as modal identifiability. Herein, the Bayesian spectral density approach is conducted for output-only modal identification and the Bayesian model class selection approach is used to evaluate the significance of different modes in modal identification. Detailed analysis on the modal identification and modal identifiability based on the measurements of the bridge will be presented. Moreover, the advantages and potentials of Bayesian probabilistic framework on structural health monitoring will be discussed.

• 대한조선학회논문집
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• 제53권6호
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• pp.514-520
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• 2016

Oil and gas production riser systems need to be designed considering a wide band quarter-modal analysis which contains low-, wave-, VIV(Vortex induced vibration) frequencies. The VIV can be separated into cross-flow(CF) and in-line(IL) components. In this study, the various idealized tri- and quarter-modal spectra are suggested to analyze fatigue damage on the production riser system. In order to evaluate the fatigue damage increment caused by the IL's motion, tri- and quarter-modal spectral fatigue damages are calculated in time domain. And the fatigue damage calculated from two different modal spectra are compared quantitatively. Then the suitability of existent wide band fatigue damage models for quarter modal spectrum was evaluated by comparison of frequency domain calculation and time domain calculation. The result show that although spectral density of IL motion is not remarkable in quantity, the effect on the fatigue damage is significant and existent fatigue damage models are not adequately estimating damage by quarter-modal spectra.

• Earthquakes and Structures
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• 제15권3호
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• pp.263-273
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• 2018

Operational modal analysis is being widely used in aerospace, mechanical and civil engineering. Common research fields include optimal design and rehabilitation under dynamic loads, structural health monitoring, modification and control of dynamic response and analytical model updating. In many practical cases, influence of noise contamination in the recorded data makes it difficult to identify the modal parameters accurately. In this paper, an improved frequency domain method called Enhanced Least Square Complex Frequency (eLSCF) is developed to extract modal parameters from noisy recorded data. The proposed method makes the use of pre-defined approximate mode shape vectors to refine the cross-power spectral density matrix and extract fundamental frequency for the mode of interest. The efficiency of the proposed method is illustrated using an example five story shear frame loaded by random excitation and different noise signals.

• Smart Structures and Systems
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• 제10권4_5호
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• pp.375-391
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• 2012

This paper reports the structural health monitoring benchmark study results for the Canton Tower using Bayesian methods. In this study, output-only modal identification and finite element model updating are considered using a given set of structural acceleration measurements and the corresponding ambient conditions of 24 hours. In the first stage, the Bayesian spectral density approach is used for output-only modal identification with the acceleration time histories as the excitation to the tower is unknown. The modal parameters and the associated uncertainty can be estimated through Bayesian inference. Uncertainty quantification is important for determination of statistically significant change of the modal parameters and for weighting assignment in the subsequent stage of model updating. In the second stage, a Bayesian model updating approach is utilized to update the finite element model of the tower. The uncertain stiffness parameters can be obtained by minimizing an objective function that is a weighted sum of the square of the differences (residuals) between the identified modal parameters and the corresponding values of the model. The weightings distinguish the contribution of different residuals with different uncertain levels. They are obtained using the Bayesian spectral density approach in the first stage. Again, uncertainty of the stiffness parameters can be quantified with Bayesian inference. Finally, this Bayesian framework is applied to the 24-hour field measurements to investigate the variation of the modal and stiffness parameters under changing ambient conditions. Results show that the Bayesian framework successfully achieves the goal of the first task of this benchmark study.

• Smart Structures and Systems
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• 제17권2호
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• pp.209-230
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• 2016

The Canton Tower is a high-rise slender structure with a height of 610 m. A structural health monitoring system has been instrumented on the structure, by which data is continuously monitored. This paper presents an investigation on the identified modal properties of the Canton Tower using ambient vibration data collected during a whole day (24 hours). A recently developed Fast Bayesian FFT method is utilized for operational modal analysis on the basis of the measured acceleration data. The approach views modal identification as an inference problem where probability is used as a measure for the relative plausibility of outcomes given a model of the structure and measured data. Focusing on the first several modes, the modal properties of this supertall slender structure are identified on non-overlapping time windows during the whole day under normal wind speed. With the identified modal parameters and the associated posterior uncertainty, the distribution of the modal parameters in the future is predicted and assessed. By defining the modal root-mean-square value in terms of the power spectral density of modal force identified, the identified natural frequencies and damping ratios versus the vibration amplitude are investigated with the associated posterior uncertainty considered. Meanwhile, the correlations between modal parameters and temperature, modal parameters and wind speed are studied. For comparison purpose, the frequency domain decomposition (FDD) method is also utilized to identify the modal parameters. The identified results obtained by the Bayesian method, the FDD method and a finite element model are compared and discussed.