钢筋混凝土剪力墙非对称恢复力的建模与参数识别

IF 1.9 4区 工程技术 Q3 ENGINEERING, MECHANICAL Advances in Mechanical Engineering Pub Date : 2023-08-01 DOI:10.1177/16878132231192226
Zhou Lina, Senlin Zhang
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引用次数: 1

摘要

在地震波的作用下,钢筋混凝土剪力墙(RC剪力墙)往往表现出强度和刚度退化等滞后特性,以及由于滑移、混凝土的累积损伤、钢筋或钢筋的不均匀腐蚀等因素而产生的夹持效应。磁滞曲线是不对称的。本文在Bouc-Wen-Baber-Noori(BWBN)模型的基础上,引入非对称因子,建立了一个能够描述钢筋混凝土剪力墙滞回特性的非线性恢复力力学模型。特别值得注意的是,该模型中不同加载阶段的滞回能量ε被视为待识别的参数。用于参数识别的常微分方程分为四个部分。将改进的粒子群组织(IPSO)算法用于参数识别,并与遗传算法进行了比较,验证了其优越性。利用钢筋混凝土剪力墙有限元模拟数据验证了该模型的准确性。
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Modeling and parameter identification of asymmetric restoring force of reinforced concrete shear walls
Under the action of the seismic waves, reinforced concrete shear walls (RC shear walls) often exhibit hysteresis characteristics such as strength and stiffness degradation, and pinching effects due to factors such as slippage, cumulative damage of concrete, and non-uniform corrosion of steel bars or reinforcements. The hysteresis curve is asymmetric. In this paper, a nonlinear restoring force mechanical model, based on the Bouc-Wen-Baber-Noori (BWBN) model, that can describe the hysteresis characteristics of the RC shear wall is obtained by introducing the asymmetry factor. Particular attention is the solution of equation that the hysteretic energy ε at different loading stages in this model is regarded as parameters to be identified. The ordinary differential equations for parameter identification are derived into four segments. The improved particle swarm organization (IPSO) algorithm is used for parameters identification, which superiority is verified by comparison to the genetic algorithm. The accuracy of this model is verified by using RC shear wall finite element simulation data.
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来源期刊
Advances in Mechanical Engineering
Advances in Mechanical Engineering 工程技术-机械工程
CiteScore
3.60
自引率
4.80%
发文量
353
审稿时长
6-12 weeks
期刊介绍: Advances in Mechanical Engineering (AIME) is a JCR Ranked, peer-reviewed, open access journal which publishes a wide range of original research and review articles. The journal Editorial Board welcomes manuscripts in both fundamental and applied research areas, and encourages submissions which contribute novel and innovative insights to the field of mechanical engineering
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