A three－dimensional nonlinear reduced－order predictive joint model

• Published in: Earthquake Engineering and Engineering Vibration Vol. 2; no. 1; pp. 59 - 74
• Main Author: 宋亚新 C.J.Hartwigsen LawrenceA.Bergman AlexanderF.Vakakis
• Format: Journal Article
• Language: English
• Published: Dordrecht Springer Nature B.V 01.06.2003; Department of Aeronautical and Astronautical Engineering University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA%Sandia National Laboratories, Albuquerque, New Mexico, USA%Department of Mechanical and Industrial Engineering, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA; Division of Mechanics, National Technical University of Athens, GR-157 10 Zografos, Athens, Greece
• Subjects: Acceleration; AIBE; Bending; Bolted joints; Computer simulation; Deformation; Dynamic models; Finite element analysis; Finite element method; Frame structures; Mathematical models; MLFF; Model reduction; Modelling; Multilayers; Neural networks; Numerical simulations; Parameter identification; Parameters; Physics; Predictions; Reduced order models; Rotation; Seismic engineering; 参数分析; 多层前馈神经网络; 螺栓联接; 非线性动力学分析; bolted joints; nonlinear dynamic analysis; adjusted Iwan beam element (AIBE); multi-layer feed-forward neural networks (MLFF); parameter identification
• ISSN: 1671-3664; 1993-503X
• DOI: 10.1007/BF02857539

Mechanical joints can have significant effects on the dynamics of assembled structures. However, the lack of efficacious predictive dynamic models for joints hinders accurate prediction of their dynamic behavior. The goal of our workis to develop physics-based, reduced-order, finite element models that are capable of replicating the effects of joints on vi-brating structures. The authors recently developed the so-called two-dimensional adjusted Iwan beam element (2-D AIBE)to simulate the hysteretic behavior of bolted joints in 2-D beam structures. In this paper, 2-D AIBE is extended to three-di-mensional cases by formulating a three-dimensional adjusted Iwan beam element (3-D AIBE). Impulsive loading experi-ments are applied to a jointed frame structure and a beam structure containing the same joint. The frame is subjected to ex-citation out of plane so that the joint is under rotation and single axis bending. By assuming that the rotation in the joint islinear elastic, the parame ters of the joint associated with bending in the frame are identified from acceleration responses ofthe jointed beam structure, using a multi-layer feed-forward neural network (MLFF). Numerical simulation is then per-formed on the frame structure using the identified parameters. The good agreement between the simulated and experiment alimpulsive acceleration responses of the frame structure validates the efficacy of the presented 3-D AIBE, and indicates thatthe model can potentially be applied to more complex structural systems with joint parameters identified from a relativelysimple structure.