Please use this identifier to cite or link to this item: http://hdl.handle.net/11452/21104
Title: Integrated optimal topology design and shape optimization using neural networks
Authors: Uludağ Üniversitesi/Mühendislik Fakültesi/Makine Mühendisliği Bölümü.
Uludağ Üniversitesi/Mühendislik Fakültesi/Endüstri Mühendisliği Bölümü.
0000-0003-1790-6987
0000-0002-8297-0777
Yıldız, Ali Rıza
Öztürk, Nursel
Kaya, Necmettin
Öztürk, Ferruh
F-7426-2011
AAG-9336-2021
R-4929-2018
AAG-9923-2021
Keywords: Topology optimization
Shape optimization
Neural networks
Feature recognition
Homogenization method
Discriminant-analysis
Continuum structures
Structural topology
Components
Geometry
Features
CAD
Computer science
Engineering
Mechanics
Issue Date: Oct-2003
Publisher: Springer-Verlag
Citation: Yıldız, A.R. vd. (2003). “Integrated optimal topology design and shape optimization using neural networks”. Structural and Multidisciplinary Optimization, 25(4), 251-260.
Abstract: In this paper, neural network- and feature-based approaches are introduced to overcome current shortcomings in the automated integration of topology design and shape optimization. The topology optimization results are reconstructed in terms of features, which consist of attributes required for automation and integration in subsequent applications. Features are defined as cost-efficient simple shapes for manufacturing. A neural network-based image-processing technique is presented to match the arbitrarily shaped holes inside the structure with predefined features. The effectiveness of the proposed approach in integrating topology design and shape optimization is demonstrated with several experimental examples.
URI: https://doi.org/10.1007/s00158-003-0300-0
https://link.springer.com/article/10.1007/s00158-003-0300-0
http://hdl.handle.net/11452/21104
ISSN: 1615-147X
Appears in Collections:Web of Science

Files in This Item:
There are no files associated with this item.


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.