For system identification of large structures, it is not practical to identify the entire structure due to the prohibitive computational time and difficulty in numerical convergence. This paper explores the possibility of performing system identification at substructure level, taking advantage of reduction in both the number of unknowns and the number of degrees of freedom involved. Another advantage is that different portions (substructures) of a structural system can be identified independently and even concurrently with parallel computing. Two substructural identification methods are formulated on the basis whether substructural approach is used to obtain first-order or second-order model. For substructural first-order model, identification at the substructure level will be performed by means of the Observer/Kalman filter Identification (OKID) and the Eigensystem Realization Algorithm (ERA) whereas identification at the global level will be performed to obtain second-order model in order to evaluate the system's stiffness and mass parameters. In the case of substructural second-order model, identification will be performed at the substructure level throughout the identification process. The efficiency of the proposed technique is shown by numerical examples for multi-storey shear buildings subjected to random forces, taking into consideration the effects of noisy measurement data. The results indicate that both the proposed methods are effective and efficient for damage identification of large structures.

This paper aims at investigating the damage process of steel members leading to the failure under strong repeated loading, proposing the damage index using various factors related to the damage, and developing the analysis method for evaluating the damage state. Cantilever-type steel members were analyzed under uniaxial load and combined with a constant axial load, considering a horizontal displacement history. In analyzing the models, loading patterns and steel types (SS400, SM570, Posten80) were considered as main parameters. From the analysis results, the effects of parameter on the failures mode, the deformation capacity, the damage process are also discussed. Each failure process was compared as steel types. Consequently, the failure of steel members under strong repeated loading was determined by loading. Especially it was seen that the state of the failure is closely related to the local strain.

In the present study, finite element linear buckling analysis is performed for grid-stiffened composite plates. A hybrid element with drilling degrees of freedom is employed to reduce the effect of the sensitivity of mesh distortion and to match the degrees of freedom between skins and stiffeners. The preliminary static stress distribution is analyzed for the determination of accurate load distribution. Parametric study of grid structures is performed and three types of buckling modes are observed. The maximum limit of buckling load was found at the local skin-buckling mode. In order to maximize buckling loads, stiffened panels need to be designed to be buckled in skin-buckling mode.

A typical marine platform in the Bay of Campeche is studied from the standpoint of structural reliability, and several characteristics of its deck such as slenderness and diameter/thickness ratios of the legs and actual degree of correlation between some variables are taken into account. The global and local buckling capacities of the deck legs are compared and the correlation coefficient between the critical axial load and the critical moment is assessed in order to validate its influence on the structural reliability. In addition, the influence of the vertical load, and its uncertainty, on the variance of the decks capacity, and latter on, on the platform's failure probability is assessed. The results presented may be used in future studies to further extend and upgrade the first version of the Reference Norm (PEMEX, 2000) and, in the longer term, to improve the current practice in the Design and Requalification of Offshore Marine Platforms in the Bay of Campeche.

Generalized CMAC (GCMAC) is a type of neural network known to be fast in learning. The network may be useful in structural engineering applications such as the identification and the control of structures. The derivatives of a trained GCMAC is relatively poor in accuracy. Therefore to improve the accuracy, a new algorithm is proposed. If GCMAC is directly differentiated, the accuracy of the derivative is not satisfactory. This is due to the quantization of input space and the shape of basis function used. Using the periodicity of the predicted output by GCMAC, the derivative can be improved to the extent of having almost no error. Numerical examples are considered to show the accuracy of the proposed algorithm.

This paper discusses the enhancement of the buckling capacity of column strips by use of piezoelectric layer. The analytical model for obtaining the buckling capacity of the piezoelectric coupled column with general boundary conditions modelled with different types of springs applied at the ends of the column is derived the first time. Based on this proposed model, the buckling capacity of the column strips can be accurately predicted by solving an eigenvalue problem. The computational results show the great potential of the piezoelectric materials in enhancing the buckling capacity of the column strips. The optimal locations of the piezoelectric layer for higher buckling capacity are also obtained for the columns with. standard pinned-pinned, fixed-free, and fixed-pinned structures. In addition, the buckling capacity and the increase of buckling capacity are discussed for those columns with the general boundaries as well. This research may provide a benchmark for the buckling analysis of the piezoelectric coupled strips.

A recently developed semi-active control system employing magneto-rheological (MR) fluid dampers is applied to vibration control of a wind excited tall building. The semi-active control system with MR fluid dampers appears to have the reliability of passive control devices and the adaptability of fully active control systems. The system requires only small power source, which is critical during severe events, when the main power source may fail. Numerical simulation studies are performed to demonstrate the efficiency of the MR dampers on the third ASCE benchmark problem. Multiple MR dampers are assumed to be installed in the 76-story building. Genetic algorithm is applied to determine the optimal locations and capacities of the MR dampers. Clipped optimal controller is designed to control the MR dampers based on the acceleration feedback. To verify the robustness with respect to the variation of the external wind force, several cases with different wind forces are considered in the numerical simulation. Simulation results show that the semi-actively controlled MR dampers can effectively reduce both the peak and RMS responses the tall building under various wind force conditions. The control performance of the MR dampers for wind is found to be fairly similar to the performance of an active tuned mass damper.