阎琨Yan Kun

(副教授)

 博士生导师  硕士生导师
学位:博士
性别:男
毕业院校:大连理工大学
所在单位:化工学院
电子邮箱:yankun@dlut.edu.cn

论文成果

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An adjoint method of sensitivity analysis for residual vibrations of structures subject to impacts

发表时间:2019-03-11 点击次数:

论文名称:An adjoint method of sensitivity analysis for residual vibrations of structures subject to impacts
论文类型:期刊论文
第一作者:Yan, Kun
通讯作者:Cheng, GD (reprint author), Dalian Univ Technol, Fac Vehicle Engn & Mech, State Key Lab Struct Anal Ind Equipment, Dalian 116023, Peoples R China.
合写作者:Cheng, Gengdong
发表刊物:JOURNAL OF SOUND AND VIBRATION
收录刊物:SCIE、EI
卷号:418
页面范围:15-35
ISSN号:0022-460X
关键字:Lyapunov equation; Residual vibration; Sensitivity analysis; Adjoint method; Impact load
摘要:For structures subject to impact loads, the residual vibration reduction is more and more important as the machines become faster and lighter. An efficient sensitivity analysis of residual vibration with respect to structural or operational parameters is indispensable for using a gradient based optimization algorithm, which reduces the residual vibration in either active or passive way. In this paper, an integrated quadratic performance index is used as the measure of the residual vibration, since it globally measures the residual vibration response and its calculation can be simplified greatly with Lyapunov equation. Several sensitivity analysis approaches for performance index were developed based on the assumption that the initial excitations of residual vibration were given and independent of structural design. Since the resulting excitations by the impact load often depend on structural design, this paper aims to propose a new efficient sensitivity analysis method for residual vibration of structures subject to impacts to consider the dependence. The new method is developed by combining two existing methods and using adjoint variable approach. Three numerical examples are carried out and demonstrate the accuracy of the proposed method. The numerical results show that the dependence of initial excitations on structural design variables may strongly affects the accuracy of sensitivities. (C) 2017 Elsevier Ltd. All rights reserved.
发表时间:2018-03-31