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Indexed by:期刊论文

Date of Publication:2019-05-13

Journal:ENGINEERING COMPUTATIONS

Included Journals:SCIE、EI

Volume:36

Issue:4

Page Number:1082-1100

ISSN No.:0264-4401

Key Words:Newton-Raphson method; Nonlinear analysis; Three-point method; Time complexity analysis; Woodbury formula

Abstract:Purpose The purpose of this paper is to make a theoretical comprehensive efficiency evaluation of a nonlinear analysis method based on the Woodbury formula from the efficiency of the solution of linear equations in each incremental step and the selected iterative algorithms. Design/methodology/approach First, this study employs the time complexity theory to quantitatively compare the efficiency of the Woodbury formula and the LDLT factorization method which is a commonly used method to solve linear equations. Moreover, the performance of iterative algorithms also significantly effects the efficiency of the analysis. Thus, the three-point method with a convergence order of eight is employed to solve the equilibrium equations of the nonlinear analysis method based on the Woodbury formula, aiming to improve the iterative performance of the Newton-Raphson (N-R) method. Findings First, the result shows that the asymptotic time complexity of the Woodbury formula is much lower than that of the LDLT factorization method when the number of inelastic degrees of freedom (IDOFs) is much less than that of DOFs, indicating that the Woodbury formula is more efficient for local nonlinear problems. Moreover, the time complexity comparison of the N-R method and the three-point method indicates that the three-point method is more efficient than the N-R method for local nonlinear problems with large-scale structures or a larger ratio of IDOFs number to the DOFs number. Originality/value This study theoretically evaluates the efficiency of nonlinear analysis method based on the Woodbury formula, and quantitatively shows the application condition of the comparative methods. The comparison result provides a theoretical basis for the selection of algorithms for different nonlinear problems.