• 한국공간구조학회논문집
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• 제7권5호
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• pp.49-56
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• 2007

바닥판 구조물의 진동제어를 위한 제어시스템으로 제어력의 조절에 따라서 수동, 능동, 준능동 제어 시스템이 구분할 수 있다. 본 논문에서는 MR감쇠기와 수동 TMD를 조합한 준능동 TMD(MR-TMD)의 제어기법에 따른 바닥판 구조물의 진동제어성능을 알아보았다 MR-TMD의 감쇠기 모형화 방법에 따라서 Groundhook 모델과 Skyhook 모델이 있으며 주구조물인 바닥판 구조물의 진동제어에 있어서는 Skyhook 모델보다 Groundhook 모델보다 효과적인 것을 볼 수 있다. 그러나 TMD변위가 제한적인 경우에 MR-TMD의 감쇠기를 Skyhook 모델로 모형화하여 진동을 제어할 필요가 있다 그리고 Hybrid 제어기법을 적용할 경우에 바닥판 구조물과 TMD를 동시에 최적으로 제어할 수 있으므로 우수한 제어성능을 보이고 있다.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2007년도 춘계학술대회논문집
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• pp.219-219
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• 2007

• 한국공간구조학회논문집
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• 제20권2호
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• pp.51-58
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• 2020

Recently, deep learning that is the most popular and effective class of machine learning algorithms is widely applied to various industrial areas. A number of research on various topics about structural engineering was performed by using artificial neural networks, such as structural design optimization, vibration control and system identification etc. When nonlinear semi-active structural control devices are applied to building structure, a lot of computational effort is required to predict dynamic structural responses of finite element method (FEM) model for development of control algorithm. To solve this problem, an artificial neural network model was developed in this study. Among various deep learning algorithms, a recurrent neural network (RNN) was used to make the time history response prediction model. An RNN can retain state from one iteration to the next by using its own output as input for the next step. An eleven-story building structure with semi-active tuned mass damper (TMD) was used as an example structure. The semi-active TMD was composed of magnetorheological damper. Five historical earthquakes and five artificial ground motions were used as ground excitations for training of an RNN model. Another artificial ground motion that was not used for training was used for verification of the developed RNN model. Parametric studies on various hyper-parameters including number of hidden layers, sequence length, number of LSTM cells, etc. After appropriate training iteration of the RNN model with proper hyper-parameters, the RNN model for prediction of seismic responses of the building structure with semi-active TMD was developed. The developed RNN model can effectively provide very accurate seismic responses compared to the FEM model.

• Smart Structures and Systems
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• 제12권6호
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• pp.595-617
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• 2013

Semi-active control equipments are used to effectually enhance the seismic behavior of structures. Magneto-rheological (MR) dampers are semi-active devices that can be utilized to control the response of structures during seismic loads and have received voracious attention for response suppression. They supply the adaptability of active devices and stability and reliability of passive devices. This paper presents an optimal fuzzy logic control scheme for vibration mitigation of buildings using magneto-rheological dampers subjected to near-fault ground motions. Near-fault features including a directivity pulse in the fault-normal direction and a fling step in the fault-parallel direction are considered in the requisite ground motion records. The membership functions and fuzzy rules of fuzzy controller were optimized by genetic algorithm (GA). Numerical study is performed to analyze the influences of near-fault ground motions on a building that is equipped with MR dampers. Considering the uncontrolled system response as the base line, the proposed method is scrutinized by analogy with that of a conventional maximum dissipation energy (MED) controller to accentuate the effectiveness of the fuzzy logic algorithm. Results reveal that the fuzzy logic controllers can efficiently improve the structural responses and MR dampers are quite promising for reducing seismic responses during near-fault earthquakes.

• Smart Structures and Systems
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• 제4권6호
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• pp.741-757
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• 2008

The research field of structural control has evolved from the development of passive devices since 1970s, through the intensive investigation on active systems in 1980s, to the recent studies of semi-active control systems in 1990s. Currently semi-active control is considered most promising in civil engineering applications. However, actual implementation of semi-active devices is still limited due mainly to their system maintenance and associated long-term reliability as a result of power requirement. In this paper, the concept of functionally upgraded passive devices is introduced to streamline some of the state-of-the-art researches and guide the development of new passive devices that can mimic the function of their corresponding semi-active control devices for various applications. The general characteristics of this special group of passive devices are discussed and representative examples are summarized. Their superior performances are illustrated with cyclic and shake table tests of two example devices: mass-variable tuned liquid damper and friction-pendulum bearing with a variable sliding surface curvature.

• Smart Structures and Systems
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• 제16권6호
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• pp.1147-1167
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• 2015

Wireless smart sensors, which have become popular for monitoring applications, are an attractive option for implementing structural control systems, due to their onboard sensing, processing, and communication capabilities. However, wireless smart sensors pose inherent challenges for control, including delays from communication, acquisition hardware, and processing time. Previous research in wireless control, which focused on semi-active systems, has found that sampling rate along with time delays can significantly impact control performance. However, because semi-active systems are guaranteed stable, these issues are typically neglected in the control design. This work achieves active control with smart sensors in an experimental setting. Because active systems are not inherently stable, all the elements of the control loop must be addressed, including data acquisition hardware, processing performance, and control design at slow sampling rates. The sensing hardware is shown to have a significant impact on the control design and performance. Ultimately, the smart sensor active control system achieves comparable performance to the traditional tethered system.

• International Journal of Reliability and Applications
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• 제9권2호
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• pp.167-182
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• 2008

The objective of this paper is to discuss the stochastic analysis and the statistical inference of a three-states semi-Markov reliability model. Using the maximum likelihood procedure, the parameters included in this model are estimated. Based on the assumption that the lifetime and repair time of the system are gener-alized Weibull random variables, the reliability function of this system is obtained. Then, the distribution of the first passage time of this system is derived. Many important special cases are discussed. Finally, the obtained results are compared with those available in the literature.

• Smart Structures and Systems
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• 제19권4호
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• pp.351-360
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• 2017

Protection of structures against natural hazards such as earthquakes has always been a major concern. Semi-active control combines the reliability of passive control and versatility and adaptability of active control. So it has recently become a preferred control method. This paper proposes an algorithm based on Uniform Deformation Theory to mitigate vulnerable buildings using magneto-rheological (MR) damper. Due to the successful performance of fuzzy logic in control of systems and its simplicity and intrinsically robustness, it is used here to regulate MR dampers. The particle swarm optimization (PSO) algorithm is also used as an adaptive method to develop a fuzzy control algorithm that is able to create uniform inter-story drifts. Results show that the proposed algorithm exhibited a desirable performance in reducing both linear and nonlinear seismic responses of structures. Performance of the presented method is indicated in compare with passive-on and passive-off control algorithms.

• Structural Engineering and Mechanics
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• 제30권1호
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• pp.1-20
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• 2008

The dynamic characteristics of the passive, semi-active, and active tuned-liquidcolumn dampers (or TLCDs) are studied in this paper. The design of the latter two are based on the first one. A water-head difference (or simply named as water head in this paper) of a passive TLCD is pre-set to form the so-called semi-active one in this paper. The pre-set of water head is released at a proper time instant during an earthquake excitation in order to enhance the vibration reduction of a structure. Two propellers are installed along a shaft inside and at the center of a passive TLCD to form an active one. These two propellers are driven by a servo-motor controlled by a computer to provide the control force. The seismic responses of a five-story shear building with a passive, semiactive, and active TLCDs are computed for demonstration and discussion. The responses of this building with a tuned mass damper (or TMD) are also included for comparison. The small-scale shaking-table experiments of a pendulum-like system with a passive or active TLCD to harmonic and seismic excitations are conducted for verification.

• Smart Structures and Systems
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• 제15권3호
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• pp.807-830
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• 2015

When a building structure requires both health monitoring system and vibration control system, integrating the two systems together will be cost-effective and beneficial for creating a smart building structure with its own sensors (nervous system), processors (brain system), and actuators (muscular system). This paper presents a real-time integrated procedure to demonstrate how health monitoring and vibration control can be integrated in real time to accurately identify time-varying structural parameters and unknown excitations on one hand, and to optimally mitigate excessive vibration of the building structure on the other hand. The basic equations for the identification of time-varying structural parameters and unknown excitations of a semi-active damper-controlled building structure are first presented. The basic equations for semi-active vibration control of the building structure with time-varying structural parameters and unknown excitations are then put forward. The numerical algorithm is finally followed to show how the identification and the control can be performed simultaneously. The results from the numerical investigation of an example building demonstrate that the proposed method is feasible and accurate.