An Unconditionally Stable Integration Method for Structural Nonlinear Dynamic Problems

Chuanguo Jia (), Hongchen Su, Weinan Guo, Yutao Li, Biying Wu and Yingqi Gou
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Chuanguo Jia: Key Laboratory of New Technology for Construction of Cities in Mountain Area, Chongqing University, Chongqing 400045, China
Hongchen Su: School of Civil Engineering, Chongqing University, Chongqing 400045, China
Weinan Guo: School of Civil Engineering, Chongqing University, Chongqing 400045, China
Yutao Li: School of Civil Engineering, Chongqing University, Chongqing 400045, China
Biying Wu: School of Civil Engineering, Chongqing University, Chongqing 400045, China
Yingqi Gou: School of Civil Engineering, Chongqing University, Chongqing 400045, China

Mathematics, 2023, vol. 11, issue 13, 1-19

Abstract: This paper presents an unconditionally stable integration method, which introduces a linearly implicit algorithm featuring an explicit displacement expression. The technique that is being considered integrates one Newton iteration into the mean acceleration method. The stability of the proposed algorithm in solving equations of motion containing nonlinear restoring force and nonlinear damping force is analyzed using the root locus method. The objective of this investigation was to assess the accuracy and consistency of the proposed approach in contrast to the Chang method and the CR method. This is achieved by analyzing the dynamic response of three distinct structures: a three-layer shear structure model outfitted with viscous dampers, a three-layer shear structure model featuring metal dampers, and an eight-story planar frame structure. Empirical evidence indicates that the algorithm in question exhibits a notable degree of precision and robustness when applied to nonlinear dynamic problem-solving.

Keywords: structural nonlinear dynamic problems; linearly implicit algorithm; Newton iteration method; Newmark- ? method; nonlinear dynamic problem-solving (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2023
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