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A three-dimensional nonlinear reduced-order predictive joint model 被引量:3
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作者 宋亚新 Hartwigsen +1 位作者 LawrenceA.Bergman AlexanderF.Vakakis 《Earthquake Engineering and Engineering Vibration》 SCIE EI CSCD 2003年第1期59-74,共16页
Mechanical joints can have significant effects on the dynamics of assembled structures.However,the lack of efficacious predictive dynamic models tot joints hinders accurate prediction of their dynamic behavior.The goa... Mechanical joints can have significant effects on the dynamics of assembled structures.However,the lack of efficacious predictive dynamic models tot joints hinders accurate prediction of their dynamic behavior.The goal of our work is 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 lwan 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 lwan beam element(3-D AIBE).hupulsive 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 is linear elastic,the parameters of the joint associated with bending in the flame are identified from acceleration responses of the jointed beam structure,using a multi-layer teed-torward neural network(MLFF).Numerieal simulation is then per- formed on the frame structure using the identified parameters.The good agreement between the simulated and experimental impulsive acceleration responses of the frame structure validates the efficacy of the presented 3-D AIBE,and indicates that the model can potentially be applied to more complex structural systems with joint parameters identified from a relatively simple structure. 展开更多
关键词 boiled joints adjusted Iwan beam element (AIBE) nonlinear dynamic analysis parameter identification multi-layer feed-forward neural networks (MLFF)
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