System reduction-based approximate reanalysis method for statically indeterminate structures with high-rank modification

TL;DR

This paper introduces a novel approximate reanalysis method for high-rank modifications in statically indeterminate structures, combining system reduction and iterative solutions to enhance computational efficiency.

Contribution

The paper proposes a new reanalysis approach using spectral decomposition and system reduction, improving efficiency for high-rank structural modifications.

Findings

The method shows excellent computational performance for various structures.

It outperforms existing reanalysis methods in efficiency.

Effective for both homogeneous and functionally graded materials.

Abstract

Efficient structural reanalysis for high-rank modification plays an important role in engineering computations which require repeated evaluations of structural responses, such as structural optimization and probabilistic analysis. To improve the efficiency of engineering computations, a novel approximate static reanalysis method based on system reduction and iterative solution is proposed for statically indeterminate structures with high-rank modification. In this approach, a statically indeterminate structure is divided into the basis system and the additional components. Subsequently, the structural equilibrium equations are rewritten as the equation system with the stiffness matrix of the basis system and the pseudo forces derived from the additional elements. With the introduction of spectral decomposition, a reduced equation system with the element forces of the additional elements as the unknowns is established. Then, the approximate solutions of the modified structure can be obtained by solving the reduced equation system through a pre-conditioned iterative solution algorithm. The computational costs of the proposed method and the other two reanalysis methods are compared and numerical examples including static reanalysis and static nonlinear analysis are presented. The results demonstrate that the proposed method has excellent computational performance for both the structures with homogeneous material and structures composed of functionally graded beams. Meanwhile, the superiority of the proposed method indicates that the combination of system reduction and pre-conditioned iterative solution technology is an effective way to develop high-performance reanalysis methods.