Tuned liquid column damper (TLCD) is used to reduce wind induced building acceleration by tuning its natural
frequency to that of a building. After building construction, its natural frequency may differ from the original one. Thus,
TLCD installed at a building should have the shifted natural frequency without its serious structural modification.
Conventional TLCD changes its natural frequency by only regulating liquid height, which destroys U shape of TLCD.
This study proposes new concept of TLCD which yields wide range of natural frequency with very simple modification
maintaining original shape. Vertical columns of TLCD are divided into several individual cell type small columns. The
liquid in individual cell type columns cannot move by air pressure if their tops are sealed. By taking appropriate number
of cell type columns in sealed condition, sectional area ratio of vertical and horizontal columns is changed, which can
provide new natural frequency same to shifted natural frequency of a building. TLCD's with multi cells are analytically
evaluated and experimentally verified using shaking table test according to the number of sealed cell type small columns.
Proc. SPIE. 5391, Smart Structures and Materials 2004: Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems
KEYWORDS: Detection and tracking algorithms, Matrices, Interference (communication), Control systems, Earthquakes, Finite element methods, System identification, Algorithm development, Control systems design, Systems modeling
In the previous study, authors developed a probabilistic algorithm for active control of structures. In the probabilistic control algorithm, the control force is determined by the probability that the structural energy exceeds a specified target critical energy, and the direction of a control force is determined by Lyapunov controller design method. In this paper, an experimental verification of the proposed probabilistic control algorithm is presented. A three-story test structure equipped with an active mass driver (AMD) was used. The effectiveness of the control algorithm was examined exciting the test structure using a sinusoidal signal, a scaled E-Centro earthquake and a broadband Gaussian white noise. Specially, experiments on control had been performed under a different condition to that of system identification in order to prove the stability and robustness of the proposed control algorithm. Experimental results indicate that the probabilistic control algorithm can achieve a significant response reduction under various types of ground excitations even when the modeling error exists.
The committee technique for neural networks has been widely used for pattern recognitions in speech and vision studies. In this study, the committee technique is applied to damage estimation of structures for the purpose of structural health monitoring. The input to the neural networks consists of the modal parameters, and the output is composed of the element-level damage indices. Multiple neural networks are constructed and each individual neural networks is trained independently with different initial synaptic weights. Then, the estimated damage indices from different neural networks are averaged. Several committee methods were investigated and used to estimate the element-level damage locations and severities. The validity of the committee technique for damage estimation was examined on a frame structure through numerical simulation. Then experiments were carried out on a bridge model with a composite cross section subjected to vehicle loadings. It has been found that the estimated damage indices improve significantly by employing the committee technique.