• 한국소음진동공학회논문집
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• 제22권7호
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• pp.619-625
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• 2012

Since the fuel is always exposed to turbulent flow, the grid strap shows flow induced vibration characteristics that impact on the nuclear fuel soundness. The dynamic behavior of grids in nuclear fuels is quite complex, since two pairs of spring and dimple support are contacted with rods by friction in the limited space. This paper focuses on investigation of the grid strap(test fuel strap, TFS) vibration in one cell. TFS consists of a single spring and double dimples. To identify the grid strap vibration, modal analysis of the strap is performed using finite element method(FEM). Modal testing on a $5{\times}5$ grid structure without rods is performed. The modal testing results are compared to analytic results. In addition, random test considering rod effect is performed about a $5{\times}5$ grid with rods under real contact condition in the air. Finally, the strap vibration of a $5{\times}5$ fuel bundle in investigation of flow induced vibration(INFINIT) facility is measured in real fluid velocity condition without heating. It is shown that modal frequencies from the test are almost equal to those peak frequencies in the INFINIT test.

• 대한교통학회지
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• 제28권5호
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• pp.117-129
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• 2010

본 연구는 기존의 단일수단이 아닌 다수단 확률적 사용자 균형상태의 민감도 분석 방법을 설명한다. 다수단 교통망에서의 민감도 분석에 대한 연구의 첫 단계로 우선은 물리적으로 분리되어진 승용차 교통망과 대중교통(버스, 지하철) 교통망으로 구성된 다수단 교통망을 고려하고자 한다. 연구는 우선 승용차와 대중교통 교통망의 임의의 링크 변수에 대한 민감도 분석 방법을 정립하고 실질적인 링크 변수의 적용으로 링크용량과 대중교통 노선빈도에 대한 민감도 분석을 수행해본다. 다음으로 승용차 수단분담율과 대중교통 수단분담율에 대한 민감도 분석 방법을 정립한다. 본 연구의 결과는 경제학의 탄력성과 같이 교통시설의 운영 및 정책변화에 따른 통행자의 행태 변화와 운영 및 정책 효과를 분석해 볼 수 있는 중요한 정보가 될 수 있을 것이다. 또한 협력적 게임의 다수단 교통망 설계 문제를 구성하기 위한 중요한 도구로 활용될 수 있을 것이다.

• 한국전산구조공학회논문집
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• 제34권1호
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• pp.35-42
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• 2021

이 논문에서는 공용중인 구조물의 상시 계측 자료를 사용한 온라인 유한요소 모델 업데이트 방법을 제안한다. 일반적인 최적화 방법에 기반한 기존의 방법은 최적해를 찾기까지 반복적으로 고유치 해석을 수행해야 하므로 상시 업데이트에 사용하기에는 효과적이지 못하다. 제안하는 방법은 별도의 오프라인 작업이나 사용자의 개입이 없이 자동화된 과정으로 계측과 동시에 온라인 유한요소모델 업데이트를 수행할 수 있는 새로운 방법이다. 자동화된 Cov-SSI 알고리즘을 통해 구조물의 진동 계측 신호로부터 고유진동수 및 모드 형상을 식별하고, 이를 다시 역 고유치 신경망에 입력하여 최종적으로 업데이트된 유한요소 모델의 파라미터를 추정한다. 풍하중을 받는 20층 전단 빌딩 구조 모형에 대한 수치예제를 통해 제시한 방법이 자동으로 연속적인 유한요소모델 업데이트를 할 수 있었음을 확인하였다. 또한, 계측 도중 구조물의 특성이 변화하는 시나리오에 대한 예제에서 구조물의 변화가 일어나는 시점과 변화 후 변동된 구조 모델 파라미터 값을 성공적으로 추정할 수 있음을 확인하였다.

• 한국지진공학회논문집
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• 제14권2호
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• pp.67-74
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• 2010

비닐하우스 아치구조에 고정햄머 및 이동가속도계 형식을 취한 충격진동실험을 수행하여 획득한 일련의 진동기록으로 부터 고유진동수, 감쇠율 및 모드형태 등과 같은 모달계수를 추출하기 위하여 최신 고급 주파수영역 시스템판별법인 PolyMAX 및 FDD를 적용하였다. 전자는 입력-출력 데이터 모두를 사용하며, 후자는 출력 데이터 만 을 사용한다. 본 연구의 비닐하우스 강재 파이프 아치와 같이 매우 세장한 구조물에 진동계측 등과 같은 비파괴 실험기법을 적용하여 정적좌굴 하중을 결정할 수 있는 지 여부 및 손상을 감지할 수 있는지 등에 대하여 중점적으로 조사하였다. 대체로 추출한 모달계수는 유한요소해석으로부터 획득한 결과와 좋은 일치를 나타냈으며, 지속적으로 수행 할 후속연구에 가능성을 제시하였다.

• Structural Engineering and Mechanics
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• 제64권5호
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• pp.653-660
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• 2017

The aim of this study is to accurately estimate seismic damage and the collapse mechanism of the historical stone masonry minaret "Hafsa Sultan", which was built in 1522. Surveying measurements and material tests were conducted to obtain a 3D solid model and the mechanical properties of the components of the minaret. The initial Finite Element (FE) model is analyzed and numerical dynamic characteristics of the minaret are obtained. The Operational Modal Analysis (OMA) method is conducted to obtain the experimental dynamic characteristics of the minaret and the initial FE model is calibrated by using the experimental results. Then, linear time history (LTH) and nonlinear time history (NLTH) analyses are carried out on the calibrated FE model by using two different ground motions. Iron clamps which used as connection element between the stones of the minaret considerably increase the tensile strength of the masonry system. The Concrete Damage Plasticity (CDP) model is selected in the nonlinear analyses in ABAQUS. The analyses conducted indicate that the results of the linear analyses are not as realistic as the nonlinear analysis results when compared with existing damage.

• Smart Structures and Systems
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• 제23권5호
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• pp.405-420
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• 2019

In this study, vibration characteristics of offshore wind turbine tower (WTT) with gravity-based foundation (GBF) are identified from dynamic responses under wave-induced excitations. The following approaches are implemented to achieve the objective. Firstly, the operational modal analysis methods such as frequency domain decomposition (FDD) and stochastic subspace identification (SSI) are selected to estimate modal parameters from output-only dynamic responses. Secondly, a GBF WTT model composed of superstructure, substructure and foundation is simulated as a case study by using a structural analysis program, MIDAS FEA. Thirdly, wave pressures acting on the WTT structure are established by nonlinear regular waves which are simulated from a computational fluid software, Flow 3D. Wave-induced acceleration responses of the target structure are analyzed by applying the simulated wave pressures to the GBF WTT model. Finally, modal parameters such as natural frequencies and mode shapes are estimated from the output-only acceleration responses and compared with the results from free vibration analysis. The effect of wave height and period on modal parameter extraction is also investigated for the mode identification of the GBF WTT.

• Smart Structures and Systems
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• 제6권3호
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• pp.183-196
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• 2010

Monitoring and economical design of alternative energy generators such as wind turbines is becoming increasingly critical; however acquisition of the dynamic output data can be a time-consuming and costly process. In recent years, low-cost wireless sensors have emerged as an enabling technology for structural monitoring applications. In this study, wireless sensor networks are installed in three operational turbines in order to demonstrate their efficacy in this unique operational environment. The objectives of the first installation are to verify that vibrational (acceleration) data can be collected and transmitted within a turbine tower and that it is comparable to data collected using a traditional tethered system. In the second instrumentation, the wireless network includes strain gauges at the base of the structure. Also, data is collected regarding the performance of the wireless communication channels within the tower. In both turbines, collected wireless sensor data is used for off-line, output-only modal analysis of the ambiently (wind) excited turbine towers. The final installation is on a turbine with embedded braking capabilities within the nacelle to generate an "impulse-like" load at the top of the tower. This ability to apply such a load improves the modal analysis results obtained in cases where ambient excitation fails to be sufficiently broad-band or white. The improved loading allows for computation of true mode shapes, a necessary precursor to many conditional monitoring techniques.

• Smart Structures and Systems
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• 제26권4호
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• pp.419-433
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• 2020

Investigation of structural integrity has been a critical issue in the field of civil engineering for years. Visual inspection is one of the most available methods to explore deteriorative components in structures. Still, this method is not applicable to invisible damage of structures. Alternatively, system identification methods are capable of tracking modal properties of structures over time. The deviation of these dynamic properties can serve as indicators to access structural integrity. In this study, a modal tracking technique using frequency-domain system identification from seismic responses of structures is proposed. The method first segments the measured signals into overlapped sequential portions and then establishes multiple Hankel matrices. Each Hankel matrix is then converted to the frequency domain, and a temporal-average frequency-domain Hankel matrix can be calculated. This study also proposes the frequency band selection that can divide the frequency-domain Hankel matrix into several portions in accordance with referenced natural frequencies. Once these referenced natural frequencies are unavailable, the first few right singular vectors by the singular value decomposition can offer these references. Finally, the frequency-domain stochastic subspace identification tracks the natural frequencies and mode shapes of structures through quick stabilization diagrams. To evaluate performance of the proposed method, a numerical study is carried out. Moreover, the long-term monitoring strong motion records at a specific site are exploited to assess the tracking performance. As seen in results, the proposed method is capable of tracking modal properties through seismic responses of structures.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2006년도 춘계학술대회논문집
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• pp.232-237
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• 2006

Operation deflection shapes(ODS) is defined as a motion of structure at particular frequency. The ODS is eligible to show any types of structural motions while the modes supply solutions only to linear and stationary motion. The principal vibration source of an auto teller machine(ATM) case was occurred due to resonance which was found by modal analysis. To reduce the vibration of ATM case, the motion of the case was visualized using ODS analysis, which can suggest how to modify the structure. As a result the vibration of the ATM case was greatly reduced with a stiffening bar between the opposite plates.

• Smart Structures and Systems
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• 제17권6호
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• pp.1017-1030
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• 2016

This study focuses on the system identification of reinforced concrete bridges using vector autoregressive model (VAR). First, the time series output response from a bridge establishes the autoregressive (AR) models. AR models are one of the most accurate methods for stationary time series. Burg's algorithm estimates the autoregressive coefficients (ARCs) at p-lag by reducing the sum of the forward and the backward errors. The computed ARCs are assembled in the state system matrix and the eigen-system realization algorithm (ERA) computes: the eigenvector matrix that contains the vectors of the mode shapes, and the eigenvalue matrix that contains the associated natural frequencies. By taking advantage of the characteristic of the AR model with ERA (ARMERA), civil engineering can address problems related to damage detection. Operational modal analysis using ARMERA is applied to three experiments. One experiment is coupled with an artificial neural network algorithm and it can detect damage locations and extension. The neural network uses a specific number of ARCs as input and multiple submatrix scaling factors of the structural stiffness matrix as output to represent the damage.