Finite element analysis is the most powerful tool to predict the behavior of a structure in engineering practice. Generally, the initial finite element model must be corrected with experimental data due to its complexity. Thus, it is very necessary to study a finite element model updating method with high precision and high efficiency. To this end, this article presented an improved spectral decomposition flexibility perturbation method for structural finite element model updating. The improvements of the proposed method lie in two aspects. First, using the uniform correction model, the proposed method is more economical in computation than the initial method because the spectral decomposition and reorganization of elemental stiffness matrices can be avoided. Second, using the twice singular-value-truncation method, the proposed method has better performance than the initial method in combating data noise. A beam structure is employed to demonstrate the proposed method for model updating in a noisy environment. It was found that the result obtained by least squares estimate is seriously distorted and the result obtained by the first singular value truncation is also not entirely satisfactory. Only the result obtained by the second singular value truncation is the most stable and accurate. Overall, the improved spectral decomposition flexibility perturbation method is robust and effective in small modification case, large modification case, adjacent modification case, and multiple modifications case. The proposed method may be very useful for structural finite element model updating in the noisy environment.
Parameters of backscattering coefficient models have significant variability in different areas and different periods. In order to break the limitation, a classification algorithm based on spectra dominant factors for Taihu Lake is established. Quasi-analytical algorithm and optical closure are used in this paper to simulate the backscattering coefficient of three types of water in Taihu Lake with the field measurement data respectively. The properties of backscattering coefficient are analyzed synchronously. On this basis, parametric models of backscattering coefficient for three types of water in Taihu Lake are established respectively. Consequently, the differences of the backscattering properties in different time and space are converted into the differences of bio-optical properties of dominant factors in water. So the parametric models of backscattering coefficient are suitable for different parts and different seasons of Taihu Lake.
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