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:2017-04-06
Journal:INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN ENGINEERING
Included Journals:SCIE、EI、Scopus
Volume:110
Issue:1
Page Number:31-56
ISSN No.:0029-5981
Key Words:geometric uncertainties; level set; polynomial chaos; shape sensitivity; robust shape; topology optimization
Abstract:When geometric uncertainties arising from manufacturing errors are comparable with the characteristic length or the product responses are sensitive to such uncertainties, the products of deterministic design cannot perform robustly. This paper presents a new level set-based framework for robust shape and topology optimization against geometric uncertainties. We first propose a stochastic level set perturbation model of uncertain topology/shape to characterize manufacturing errors in conjunction with Karhunen-Loeve (K-L) expansion. We then utilize polynomial chaos expansion to implement the stochastic response analysis. In this context, the mathematical formulation of the considered robust shape and topology optimization problem is developed, and the adjoint-variable shape sensitivity scheme is derived. An advantage of this method is that relatively large shape variations and even topological changes can be accounted for with desired accuracy and efficiency. Numerical examples are given to demonstrate the validity of the present formulation and numerical techniques. In particular, this method is justified by the observations in minimum compliance problems, where slender bars vanish when the manufacturing errors become comparable with the characteristic length of the structures. Copyright (c) 2016 John Wiley & Sons, Ltd.
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
