Zhan Kang
Professor Supervisor of Doctorate Candidates Supervisor of Master's Candidates
Main positions:Deputy Dean, Faculty of Vehicle Engineering and Mechanics
Other Post:Deputy Dean, Faculty of Vehicle Engineering and Mechanics
Gender:Male
Alma Mater:Stuttgart University, Germany
Degree:Doctoral Degree
School/Department:Department of Engineering Mechanics/ State Key Laboratory of Structural Analysis for Industrial Equimpment
Discipline:Engineering Mechanics. Computational Mechanics. Aerospace Mechanics and Engineering. Solid Mechanics
Business Address:https://orcid.org/0000-0001-6652-7831
http://www.ideasdut.com
https://scholar.google.com/citations?user=PwlauJAAAAAJ&hl=zh-CN&oi=ao
https://www.researchgate.net/profile/Zhan_Kang
Contact Information:zhankang#dlut.edu.cn 13190104312
E-Mail:zhankang@dlut.edu.cn
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Indexed by:Journal Papers
Date of Publication:2015-08-01
Journal:SMART MATERIALS AND STRUCTURES
Included Journals:SCIE、EI、Scopus
Volume:24
Issue:8
ISSN No.:0964-1726
Key Words:topology optimization; magneto-rheological fluid; semi-active control; dynamic optimization; frequency-aggregated dynamic compliance
Abstract:This paper investigates topology optimization of the magnetorheological (MR) fluid layer in a sandwich plate for improving the semi-active vibration control performance. Therein, a uniform magnetic field is applied across the MR fluid layer to provide a semi-active damping control effect. In the optimization model, the pseudo-densities describing the MR fluid material distribution are taken as design variables, and an artificial magneto-rheological fluid model (AMRF) with penalization is proposed to suppress intermediate density values. For reducing the vibration level under harmonic excitations, the dynamic compliance under a specific excitation frequency, or the frequency-aggregated dynamic compliance in a given frequency band, is taken as the objective function to be minimized. In this context, the adjoint-variable sensitivity analysis scheme is derived. The effectiveness and efficiency of the proposed method are demonstrated by numerical examples, in which the structural dynamic performance can be remarkably improved through optimization. The influences of several key factors on the optimal designs are also explored. It is shown that the AMRF model is effective in yielding clear boundaries in the final optimal solutions without use of additional regularization techniques.
Dr. Zhan Kang is a Changjiang Scholar Chair Professor of Dalian University of Technology. He graduated from Shanghai Jiaotong University in 1992, received his MEng in mechanics from Dalian University of Technology in 1995 and his Dr. –Ing. degree from Stuttgart University, Germany in 2005. His current research involves issues such as topology optimization, structural optimization under uncertainties, design optimization of smart structures and nanomechanics. Dr. Kang has published over 100 research papers in peer-reviewed international journals and one monograph. He has received 5500 citations and has an H-index of 39 (Google Scholar). Dr. Kang has been granted the Outstanding Youth Fund of Natural Science Foundation of China (NSFC). He has been principal investigator of 8 NSFC projects and a Key Project of Chinese National Programs for Fundamental Research and Development (973 Project). He has also conducted many consultancy projects.
Google Scholar Page: https://scholar.google.com/citations?user=PwlauJAAAAAJ&hl=zh-CN&oi=ao
https://orcid.org/0000-0001-6652-7831
http://www.ideasdut.com