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:期刊论文
Date of Publication:2013-12-01
Journal:ACTA MECHANICA SINICA
Included Journals:SCIE、EI、ISTIC、CSCD、Scopus
Volume:29
Issue:6
Page Number:840-850
ISSN No.:0567-7718
Key Words:Topology optimization; Adaptive method; High resolution; Nodal design variable; Penalization factor adaptivity
Abstract:For the purpose of achieving high-resolution optimal solutions this paper proposes a nodal design variable-based adaptive method for topology optimization of continuum structures. The analysis mesh-independent density field, interpolated by the nodal design variables at a given set of density points, is adaptively refined/coarsened according to a criterion regarding the gray-scale measure of local regions. New density points are added into the gray regions and redundant ones are removed from the regions occupied by purely solid/void phases for decreasing the number of design variables. A penalization factor adaptivity technique is employed to prevent premature convergence of the optimization iterations. Such an adaptive scheme not only improves the structural boundary description quality, but also allows for sufficient further topological evolution of the structural layout in higher adaptivity levels and thus essentially enables high-resolution solutions. Moreover, compared with the case with uniformly and finely distributed density points, the proposed adaptive method can achieve a higher numerical efficiency of the optimization process.
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
