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


Paper Publications

An adaptive refinement approach for topology optimization based on separated density field description

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Indexed by:期刊论文

Date of Publication:2013-02-01

Journal:COMPUTERS & STRUCTURES

Included Journals:SCIE、EI

Volume:117

Page Number:10-22

ISSN No.:0045-7949

Key Words:Topology optimization; Adaptive refinement; Nodal density; Mesh-independent density interpolation; Gray elements; Boundary description quality

Abstract:This paper presents an adaptive density point refinement approach for continuum topology optimization on the basis of an analysis-mesh separated material density field description based on nodal design variables. The Shepard interpolants are used to construct a strictly range-restricted density field over the design domain with the density design variables defined on a density point grid. Since the density points are defined independent of the finite element mesh, it is easy to refine the density point grid without remeshing the finite element model. A refinement criterion is given to identify the gray transitional regions to be adaptively refined in the subsequent optimization iterations. With such a refinement scheme, the topology optimization can start from a relatively coarse density point grid but still yields a desired higher resolution of the structural boundaries in the final design. Because refinements are only performed when and where necessary, this method is able to improve the boundary description quality of the optimal result with much less design variables as compared with the case of global refinement, and therefore can greatly reduce the computational burden involved in the sensitivity analysis and optimization process. Moreover, the percentage of transitional regions in the final solutions can also be reduced. Compared with using a uniformly globally-dense density point arrangement, this approach can achieve similar optimal designs but with much less computational cost. Numerical examples are given to demonstrate the effectiveness and efficiency of the present approach. (C) 2012 Elsevier Ltd. All rights reserved.

Pre One:Mechanics of self-folding of single-layer graphene

Next One:Molecular dynamics study on buckling of single-wall carbon nanotube-based intramolecular junctions and influence factors

Profile

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