• Journal of the Computational Structural Engineering Institute of Korea
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• v.21 no.3
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• pp.281-285
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• 2008

Eigenvalue reduction schemes approximate the lower eigenmodes that represent the global behavior of the structures. In the previous study, we proposed a two-level condensation scheme (TLCS) for the construction of a reduced system. And we have improved previous TLCS with combination of the iterated improved reduced system method (IIRS) to increase accuracy of the higher modes intermediate range. In this study, we apply previous improved TLCS to multi-level sub-structuring scheme. In the first step, the global system is recursively partitioned into a hierarchy of sub-domain. In second step, each uncoupled sub-domain is condensed by the improved TLCS. After assembly process of each reduced sub-eigenvalue problem, eigen-solution is calculated by Lanczos method (ARPACK). Finally, Numerical examples demonstrate performance of proposed method.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.20 no.6
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• pp.731-742
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• 2007

This paper presents a new nonlinear analysis algorithm, that is, adaptive Newton-Raphson iteration method, The presented algorithm is based on the existing Newton-Raphson method, and the concept of it can be summarized as calculating the equivalent load for stiffness(ELS) and adapting this to the initial global stiffness matrix which has already been calculated and saved in initial analysis and finally calculating the correction displacements for the nonlinear analysis, The key characteristics of the proposed algorithm is that it calculates the inverse matrix of the global stiffness matrix only once irresponsive of the number of load steps. The efficiency of the proposed algorithm depends on the ratio of the active Dofs - the Dofs which are directly connected to the members of which the element stiffness are changed - to the total Dofs, and based on this ratio by using the proposed algorithm as a complementary method to the existing algorithm the efficiency of the nonlinear analysis can be improved dramatically.