The objective of model updating is to improve the accuracy of a dynamic model based on the correlation between the measured data and the analytical (finite element) model. In this paper, we intend to update the mass and stiffness matrices of an analytical model when only modal frequencies or spatially incomplete modal data are available. While the proposed method is systematic in nature, it also preserves the initial configuration of the analytical model, and physical equality and/or inequality constraints can be easily incorporated into the solution procedure. Numerical examples associated with a simple 5-DoF (degree of freedom) mass-spring system are chosen to illustrate the detailed procedure and the effectiveness of the proposed method. Numerical scenarios ranging from the updating for stiffness terms only to that for all mass and stiffness terms based on various kinds of incomplete modal data are studied. The obtained model updating results are excellent when the measured modal data are noise-free. Uncertainty studies are also conducted based on simulations of corrupted modal data, but a thorough theoretical analysis of the noise effect on the proposed method is still needed.
Modal identification involves estimating the modal parameters, such as modal frequencies, damping ratios, and mode shapes, of a structural system from measured data. Under the condition that noisy impulse response signals associated with multiple input and output locations have been measured, the primary objective of this study is to apply the local or global noise removal technique for improving the modal identification based on the polyreference time domain (PTD) method. While the traditional PTD method improves modal parameter estimation by over-specifying the computational model order to absorb noise, this paper proposes an approach using the actual system order as the computational model order and rejecting much noise prior to performing modal parameter estimation algorithms. Two noise removal approaches are investigated: a "local" approach which removes noise from one signal at a time, and a "global" approach which removes the noise of multiple measured signals simultaneously. The numerical investigation in this article is based on experimental measurements from two test setups: a cantilever beam with 3 inputs and 10 outputs, and a hanged plate with 4 inputs and 32 outputs. This paper demonstrates that the proposed noise-rejection method outperforms the traditional noise-absorption PTD method in several crucial aspects.
The present paper develops a new method for damage localization and severity estimation based on the employment of modal strain energy. This method is able to determine the damage locations and estimate their severities, requiring only the information about the changes of a few lower natural frequencies. First, a damage quantification method is formulated and iterative approach is adopted for determining the damage extent. Then a damage localization algorithm is proposed, in which a damage indicator is formulated where unity value corresponds to the true damage scenario. Finally, numerical studies and model tests are conducted to demonstrate the effectiveness of the developed algorithm.
Hurricanes Katrina and Rita resulted in the largest number of platforms destroyed and damaged in the history of Gulf of Mexico operations. With the trend of global warming, sea level rising and the frequency and intensity of typhoon increase. How to determine a reasonable deck elevation against the largest hurricane waves has become a key issue in offshore platforms design and construction for the unification of economy and safety. In this paper, the multivariate compound extreme value distribution （MCEVD） model is used to predict the deck elevation with different combination of tide, surge height, and crest height. Compared with practice recommended by American Petroleum Institute （API）, the prediction by MCEVD has probabilistic meaning and universality.
Modal strain energy based methods for damage detection have received much attention. However, most of published articles use numerical methods and some studies conduct modal tests with simple 1D or 2D structures to verify the damage detection algorithms. Only a few studies utilize modal testing data from 3D frame structures. Few studies conduct performance comparisons between two different modal strain energy based methods. The objective of this paper is to investigate and compare the effectiveness of a traditional modal strain energy method(Stubbs index) and a recently developed modal strain energy decomposition(MSED) method for damage localization, for such a purpose both simulated and measured data from an offshore platform model being used. Particularly, the mode shapes used in the damage localization are identified and synthesized from only two measurements of one damage scenario because of the limited number of sensors. The two methods were first briefly reviewed. Next, using a 3D offshore platform model, the damage detection algorithms were implemented with different levels of damage severities for both single damage and multiple damage cases. Finally, a physical model of an offshore steel platform was constructed for modal testing and for validating the applicability. Results indicate that the MSED method outperforms the Stubbs index method for structural damage detection.
