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CONTENTS
Volume 9, Number 3, March 2012
 


Abstract
Full-scale shake table seismic experiments and low-amplitude vibration tests on a masonry building are carried out to assess its seismic performance as well as study the effectiveness of a new multifunctional textile material for retrofitting masonry structures against earthquakes. The un-reinforced and the retrofitted with glass fiber reinforced polymer (GFRP) strips masonry building was subjected to a series of earthquake excitations of increasing magnitude in order to progressively induce various small, moderate and severe levels of damage to the masonry walls. The performance of the original and retrofitted building states is evaluated. Changes in the dynamic characteristics (lowest four modal frequencies and damping ratios) of the building are used to assess and quantify the damage states of the masonry walls. For this, the dynamic modal characteristics of the structure states after each earthquake event were estimated by performing low-amplitude impulse hammer and sine-sweep forced vibration tests. Comparisons between the modal results calculated using traditional accelerometers and those using Fiber Bragg Grating (FBG) sensors embedded in the reinforcing textile were carried on to investigate the reliability and accuracy of FBG sensors in tracking the dynamic behaviour of the building. The retrofitting actions restored the stiffness characteristics of the reinforced masonry structure to the levels of the original undamaged un-reinforced structure. The results show that despite a similar dynamic behavior identified, corresponding to reduction of the modal frequencies, the unreinforced masonry building was severely damaged, while the reinforced masonry building was able to withstand, without visual damage, the induced strong seismic excitations. The applied GFRP reinforcement architecture for one storey buildings was experimentally proven reliable for the most severe earthquake accelerations. It was easily placed in a short time and it is a cost effective solution (covering only 20% of the external wall surfaces) when compared to the cost for full wall coverage by GFRPs.

Key Words
masonry structures; glass fiber reinforced polymers; shake table tests; structural identification; health monitoring; damage assessment

Address
Paul Michelis : Institute of Mechanics of Material & Geostructures S.A., 22 Askiton str., Penteli, 152 36, Greece
Costas Papadimitriou, Grigoris K. Karaiskos and Dimitra-Christina Papadioti : University of Thessaly, Department of Mechanical Engineering, Volos 38334, Greece
Clemente Fuggini : D\'Appolonia S.p.A., Industrial Innovation Division, Via Martiri di Cefalonia, 2,
20097 San Donato Milanese (MI), Italy

Abstract
The stochastic optimal control for a piezoelectric spherically symmetric shell subjected to stochastic boundary perturbations is constructed, analyzed and evaluated. The stochastic optimal control problem on the boundary stress output reduction of the piezoelectric shell subjected to stochastic boundary displacement perturbations is presented. The electric potential integral as a function of displacement is obtained to convert the differential equations for the piezoelectric shell with electrical and mechanical coupling into the equation only for displacement. The displacement transformation is constructed to convert the stochastic boundary conditions into homogeneous ones, and the transformed displacement is expanded in space to convert further the partial differential equation for displacement into ordinary differential equations by using the Galerkin method. Then the stochastic optimal control problem of the piezoelectric shell in partial differential equations is transformed into that of the multi-degree-of-freedom system. The optimal control law for electric potential is determined according to the stochastic dynamical programming principle. The frequency-response function matrix, power spectral density matrix and correlation function matrix of the controlled system response are derived based on the theory of random vibration. The expressions of mean-square stress, displacement and electric potential of the controlled piezoelectric shell are finally obtained to evaluate the control effectiveness. Numerical results are given to illustrate the high relative reduction in the root-mean-square boundary stress of the piezoelectric shell subjected to stochastic boundary displacement perturbations by the optimal electric potential control.

Key Words
piezoelectric shell; stochastic vibration; optimal control; boundary perturbation; stochastic response

Address
Z.G. Ying, J. Feng and W.Q. Zhu : Department of Mechanics, School of Aeronautics and Astronautics, Zhejiang University,
Hangzhou 310027, P. R. China
Y.Q. Ni : Department of Civil and Structural Engineering, The Hong Kong Polytechnic University,
Kowloon, Hong Kong

Abstract
Finite element (FE) model updating is a useful tool for global damage detection technique, which identifies the damage of the structure using measured vibration data. This paper presents the application of a finite element model updating method to detect the damage of a small-scale reinforced concrete building structure using measured acceleration data from shaking table tests. An iterative FE model updating strategy using the least-squares solution based on sensitivity of frequency response functions and natural frequencies was provided. In addition, a side constraint to mitigate numerical difficulties associated with ill-conditioning was described. The test structure was subjected to six El Centro 1942 ground motion histories with different Peak Ground Accelerations (PGA) ranging from 0.06 g to 0.5 g, and analytical models corresponding to each stage of the shaking were obtained using the model updating method. Flexural stiffness values of the structural members were chosen as the updating parameters. In model updating at each stage of shaking, the initial values of the parameter were set to those obtained from the previous stage. Severity of damage at each stage of shaking was determined from the change of the updated stiffness values. Results indicated that larger reductions in stiffness values occurred at the slab members than at the wall members, and this was consistent with the observed damage pattern of the test structure.

Key Words
finite element model updating; damage detection; structural health monitoring; vibration; frequency response function; ill-conditioning

Address
Eunjong Yu : Department of Architectural Engineering, Hanyang University, Seoul 133-791, Korea
Lan Chung : Department of Architectural Engineering, Dankook University, Yong-In 448-701, Korea

Abstract
As civil structures are exposed to various external loads, it is essential to assess the structural condition, especially the structural displacement, in every moment. Therefore, a visually servoed paired structured light system was proposed in the previous study. The proposed system is composed of two screens facing with each other, each with a camera, a screen, and one or two lasers controlled by a 2-DOF manipulator. The 6-DOF displacement can be calculated from the positions of three projected laser beams and the rotation angles of the manipulators. In the estimation process, one of well-known iterative methods such as Newton-Raphson or extended Kalman filter (EKF) was used for each measurement. Although the proposed system with the aforementioned algorithms estimates the displacement with high accuracy, it takes relatively long computation time. Therefore, an incremental displacement estimation (IDE) algorithm which updates the previously estimated displacement based on the difference between the previous and the current observed data is newly proposed. To validate the performance of the proposed algorithm, simulations and experiments are performed. The results show that the proposed algorithm significantly reduces the computation time with the same level of accuracy compared to the EKF with multiple iterations.

Key Words
SHM (structural health monitoring); displacement; IDE (incremental displacement estimation); vision; laser

Address
Haemin Jeon : Department of Civil and Environmental Engineering, KAIST, Daejeon 305-701, Korea
Jae-Uk Shin :Robotics Program, KAIST, Daejeon 305-701, Korea
Hyun Myung : Department of Civil and Environmental Engineering, KAIST, Daejeon 305-701, Korea
Robotics Program, KAIST, Daejeon 305-701, Korea

Abstract
It is well known that overloaded vehicles may cause severe damages to bridges, and how to estimate and evaluate the status of the overloaded vehicles passing through bridges become a challenging problem. Therefore, based on the monitored strain data from a structural health monitoring system (SHM) installed on a bridge, a method is recommended to identify and analyze the probability of overloaded vehicles. Overloaded vehicle loads can cause abnormity in the monitored strains, though the abnormal strains may be small in a concrete continuous rigid frame bridge. Firstly, the abnormal strains are identified from the abundant strains in time sequence by taking the advantage of wavelet transform in abnormal signal identification; secondly, the abnormal strains induced by heavy vehicles are picked up by the comparison between the identified abnormal strains and the strain threshold gotten by finite element analysis of the normal heavy vehicle; finally, according to the determined abnormal strains induced by overloaded vehicles, the statistics of the overloaded vehicles passing through the bridge are summarized and the whole probability of the overloaded vehicles is analyzed. The research shows the feasibility of using the monitored strains from a longterm SHM to identify the information of overloaded vehicles passing through a bridge, which can help the traffic department to master the heavy truck information and do the damage analysis of bridges further.

Key Words
bridges; overloaded vehicles; probability analysis; long-term health monitoring; wavelet transform; FEM

Address
Yinghua Li, Liqun Tang, Zejia Liu and Yiping Liu : School of Civil Engineering and Transportation, State Key Laboratory of Subtropical Building Science, South China University of Technology, Guangzhou, China. 510640


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