• Wind and Structures
• /
• 제30권6호
• /
• pp.663-678
• /
• 2020

Robust semi-active vibration control of wind turbines using tuned mass dampers (TMDs) is a promising technique. This study investigates a 1.5 megawatt wind turbine controlled by eight different types of tuned mass damper systems of equal mass: a passive TMD, a semi-active varying-spring TMD, a semi-active varying-damper TMD, a semi-active varying-damper-and-spring TMD, as well as these four damper systems paired with an additional smaller passive TMD near the mid-point of the tower. The mechanism and controllers for each of these TMD systems are explained, such as employing magnetorheological dampers for the varying-damper TMD cases. The turbine is modelled as a lumped-mass 3D finite element model. The uncontrolled and controlled turbines are subjected to loading and operational cases including service wind loads on operational turbines, seismic loading with service wind on operational turbines, and high-intensity storm wind loads on parked turbines. The displacement and acceleration responses of the tower at the first and second mode shape maxima were used as the performance indicators. Ultimately, it was found that while all the semi-active TMD systems outperformed the passive systems, it was the semi-active varying-damper-and-spring system that was found to be the most effective overall - capable of controlling vibrations about as effectively with only half the mass as a passive TMD. It was also shown that by reducing the mass of the TMD and adding a second smaller TMD below, the vibrations near the mid-point could be greatly reduced at the cost of slightly increased vibrations at the tower top.

• 한국항해항만학회지
• /
• 제26권1호
• /
• pp.43-49
• /
• 2002

본 연구에서는 비감쇠 자유진동을 하는 점용접된 사각평판의 고유진동수를 수치해석을 통하여 살펴보고, 실험을 통하여 결과를 검증하였다 설계변수로는 점용접에 미치는 여러 설계변수 중에서 점용접이 차지하는 면적을 사각평판의 면적으로 나눈 면적비와 점용접점 사이의 거리를 평판의 한 변의 길이로 나눈 거리비로 무차원화하여 사용하였으며, 목적함수로는 점용접으로 인한 두께효과를 진동수에 대한 처짐의 비로써 나타낸 등가두께로써 무차원화하여 정의하였다. 수치해석에는 범용유한요소해석 프로그램인 ANSYS 5.6을 사용하였고, 실험에는 B&K Data analyzer를 통하여 주파수분석을 수행하였다. 연구의 결과 다음과 같은 결론을 얻었다. 1. 점용접의 면적비가 단지 4.52%인데 비해 점 용접으로 인한 두께효과는 55%로써 매우 크게 나타났다. 2. 거리비에 따른 두께효과는 거리비가 0.4일 때 가장 크게 나타났다.

• 한국소음진동공학회:학술대회논문집
• /
• 한국소음진동공학회 2011년도 추계학술대회 논문집
• /
• pp.325-330
• /
• 2011

RCP(Reactor coolant pump) must be designed to preserve it's functions on normal or abnormal environments and seismic event same as operating basis earthquake(OBE) and safe shutdown earthquake(SSE). Generally, there are static and dynamic analytical method which can be applied by a floor response spectrum or time history analysis for the seismic qualification. Initially, It was accomplished a detailed structural FE-model for finite element analysis on the bases of 3-dimensional solid model which was made by the RCP drawing. As the result of dynamic characteristic using the detailed FE-model, it's shown about 12Hz natural frequency of 1st bending mode shape and maximum displacement has 11mm with the structural bending by single-point response spectrum(SPRS) method at all elevation. But maximum displacement has 7.6mm by multi-point response spectrum(MPRS) method which was applied to the three floor response spectrum at each elevation. Therefore, On a large heighten structures as RCP, The application by SPRS method causes to be more conservative results. Finally, A simpled equivalent beam model which was developed by use of iteration of detailed FE-model is shown the result more similar with those of natural frequencies and SPRS analysis. And maximum equivalent stress and displacement of the simpled beam has verified with 180MPa and 7.1mm each at 15sec as results by SSE time history method.

• Structural Engineering and Mechanics
• /
• 제77권1호
• /
• pp.47-56
• /
• 2021

This paper deals with damage detection using a Gapped Smoothing Method (GSM) combined with deep learning. Convolutional Neural Network (CNN) is a model of deep learning. CNN has an input layer, an output layer, and a number of hidden layers that consist of convolutional layers. The input layer is a tensor with shape (number of images) × (image width) × (image height) × (image depth). An activation function is applied each time to this tensor passing through a hidden layer and the last layer is the fully connected layer. After the fully connected layer, the output layer, which is the final layer, is predicted by CNN. In this paper, a complete machine learning system is introduced. The training data was taken from a Finite Element (FE) model. The input images are the contour plots of curvature gapped smooth damage index. A free-free beam is used as a case study. In the first step, the FE model of the beam was used to generate data. The collected data were then divided into two parts, i.e. 70% for training and 30% for validation. In the second step, the proposed CNN was trained using training data and then validated using available data. Furthermore, a vibration experiment on steel damaged beam in free-free support condition was carried out in the laboratory to test the method. A total number of 15 accelerometers were set up to measure the mode shapes and calculate the curvature gapped smooth of the damaged beam. Two scenarios were introduced with different severities of the damage. The results showed that the trained CNN was successful in detecting the location as well as the severity of the damage in the experimental damaged beam.

• Wind and Structures
• /
• 제34권2호
• /
• pp.185-197
• /
• 2022

This study aimed to analyze the wind-induced mechanical energy (WME) of a proposed super high-rise and long-span transmission tower-line system (SHLTTS), which, in 2021, is the tallest tower-line system with the longest span. Anew index - the WME, accounting for the wind-induced vibration behavior of the whole system rather than the local part, was first proposed. The occurrence of the maximum WME for a transmission tower, with or without conductors, under synoptic winds, was analyzed, and the corresponding formulae were derived based on stochastic vibration theory. Some calculation data, such as the drag coefficient, dynamic parameters, windshielding areas, mass, calculation point coordinates, mode shape and influence function, derived from wind tunnel testing on reducedscale models and finite element software were used in calculating the maximum WME of the transmission tower under three cases. Then, the influence of conductors, wind speed, gradient wind height and wind yaw angle on WME components and the energy transfer relationship between substructures (transmission tower and conductor) were analyzed. The study showed that the presence of conductors increases the WME of transmission towers and changes the proportion of the mean component (MC), background component (BC) and resonant component (RC) for WME; The RC of WME is more susceptible to the wind speed change. Affected by the gradient wind height, the WME components decrease. With the RC decreasing the fastest and the MC decreasing the slowest; The WME reaches the its maximum value at the wind yaw angle of 30°. Due to the influence of three factors, namely: the long span of the conductors, the gradient wind height and the complex geometrical profile, it is important that the tower-line coupling effect, the potential for fatigue damage and the most unfavorable wind yaw angle should be given particular attention in the wind-resistant design of SHLTTSs

• Smart Structures and Systems
• /
• 제32권5호
• /
• pp.319-338
• /
• 2023

The study presents a new hybrid data-driven method by combining radial basis functions neural networks (RBF-NN) with the Jaya algorithm (JA) to provide effective structural health monitoring of arch dams. The novelty of this approach lies in that only one user-defined parameter is required and thus can increase its effectiveness and efficiency, as compared to other machine learning techniques that often require processing a large amount of training and testing model parameters and hyper-parameters, with high time-consuming. This approach seeks rapid damage detection in arch dams under dynamic conditions, to prevent potential disasters, by utilizing the RBF-NNN to seamlessly integrate the dynamic elastic modulus (DEM) and modal parameters (such as natural frequency and mode shape) as damage indicators. To determine the dynamic characteristics of the arch dam, the JA sequentially optimizes an objective function rooted in vibration-based data sets. Two case studies of hyperbolic concrete arch dams were carefully designed using finite element simulation to demonstrate the effectiveness of the RBF-NN model, in conjunction with the Jaya algorithm. The testing results demonstrated that the proposed methods could exhibit significant computational time-savings, while effectively detecting damage in arch dam structures with complex nonlinearities. Furthermore, despite training data contaminated with a high level of noise, the RBF-NN and JA fusion remained the robustness, with high accuracy.

• Structural Engineering and Mechanics
• /
• 제90권1호
• /
• pp.27-40
• /
• 2024

The prediction of VIV amplitude is essential for the design and fatigue life estimation of steel tubes in tubular transmission towers. Limited to costly and time-consuming traditional experimental and computational fluid dynamics (CFD) methods, a machine learning (ML)-based method is proposed to efficiently predict the VIV amplitude of steel tubes in transmission towers. Firstly, by introducing the first-order mode shape to the two-dimensional CFD method, a simplified response analysis method (SRAM) is presented to calculate the VIV amplitude of steel tubes in transmission towers, which enables to build a dataset for training ML models. Then, by taking mass ratio M^*, damping ratio ξ, and reduced velocity U^* as the input variables, a Kriging-based prediction method (KPM) is further proposed to estimate the VIV amplitude of steel tubes in transmission towers by combining the SRAM with the Kriging-based ML model. Finally, the feasibility and effectiveness of the proposed methods are demonstrated by using three full-scale steel tubes with C-shaped, Cross-shaped, and Flange-plate joints, respectively. The results show that the SRAM can reasonably calculate the VIV amplitude, in which the relative errors of VIV maximum amplitude in three examples are less than 6%. Meanwhile, the KPM can well predict the VIV amplitude of steel tubes in transmission towers within the studied range of M^*, ξ and U^*. Particularly, the KPM presents an excellent capability in estimating the VIV maximum amplitude by using the reduced damping parameter S_G.

• 한국강구조학회 논문집
• /
• 제24권4호
• /
• pp.399-410
• /
• 2012

본 연구에서는 실험적 모드해석 기법을 이용하여 캔틸레버 및 양단고정 직사각형 적층복합판의 동적 테스트가 수행되었다. 균열 성장으로 인한 손상평가를 위하여 적층복합판에 인위적인 단계별 손상(균열)을 가하였으며, 충격해머 모드실험에 의해 얻어진 주파수응답함수(FRF), MAC(Modal Assurance Criterion) 값 및 모드매개변수(진동수, 모드형상, 감쇠비)의 변화를 분석하였다. 각 단계별 손상에 대한 적층복합판의 실험적 모드매개변수를 검증하기 위하여 유한요소해석으로부터 구한 고유진동수와 모드형상을 비교하였다. 손상은 벤치마크로서의 유한요소모델을 보정하는 과정으로부터 얻게 되는 적층복합판의 기하학적 특성 및 구조적 거동의 변화를 통하여 평가될 수 있음을 보여주었다.

• 대한토목학회논문집
• /
• 제11권3호
• /
• pp.37-46
• /
• 1991

이 논문(論文)은 변단면(變斷面) 보의 자유진동(自由振動)을 해석한 연구(硏究)이다. 보의 기하학적(幾何學的) 형상(形狀)은 보의 단면(斷面)이 직선적으로 변하는 변단면(變斷面) 보(tapered beam)를 택하였으며 균일폭 변화높이의 구형단면(矩形斷面), 균일(均一)높이 변화폭(變化幅)의 구형단면(矩形斷面), 정방형단면(正方形斷面) 또는 원형단면(圓形斷面)의 3가지 단면형상(斷面形狀)을 고려하였다. 보의 동적(動的) 평형방정식(平衡方程式)을 이용하여 변단면(變斷面) 보의 자유진동(自由振動)을 지배하는 미분방정식(微分方程式)을 유도하고, 이를 수치해석 기법인 Runge-Kutta method와 행렬(行列)값 탐사법(探査法)을 이용하여 고유진동수(固有振動數)와 진동형(振動形)을 산출할 수 있는 수치해석 기법을 개발하였다. 또한 타(他) 문헌(文獻)의 결과와 본 연구의 결과를 비교하여 본 연구방법의 타당성을 입증하였다. 실제의 수치해석 예는 힌지-힌지, 힌지-고정, 고정-고정, 자유-고정의 4가지 단부조건(端部條件)에 대하여 수치해석하였다. 수치해석의 결과로 $C_i-d_b/d_a$의 관계를 도시(圖示)하였고, 단부조건(端部條件)과 단면형상(斷面形狀)이 무차원 고유진동수에 미치는 영향을 분석하였다.

• 한국강구조학회 논문집
• /
• 제20권6호
• /
• pp.761-771
• /
• 2008

열차운행주파수가 철도교의 고유진동수와 일치하면, 철도교의 공진은 피할 수 없다. 또한, 열차가 교량을 매우 빠르게 통과하면, 계측 가능한 시간응답의 샘플 수는 매우 적다. 본 논문은 그러한 경우에 대하여 철도 교량의 동특성을 매우 효과적으로 추출할 수 있는 TDD기법과 SI기법을 소개한다. 열차통과 직후에 교량의 자유진동 시간응답구간의 상호상관을 이용하여 모드형상은 TDD기법으로 추출하고, 고유진동수 및 감쇠비 등의 시간변수들은 SI기법으로 추출한다. 경부고속철도 시스템에 위치한 2경간 강합성교량의 동특성 추출실험을 통하여 TDD기법과 SI기법의 현장 적용성이 검토되었다. 동특성 추정결과는 기존의 ERADC기법의 결과와 비교 검토되었다. 추정결과는 기존의 방법을 이용하여 획득된 결과와 매우 잘 일치한다.