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タイトル: Manufacturability evaluation for molded parts using fictitious physical models, and its application in topology optimization
著者: Sato, Yuki
Yamada, Takayuki
Izui, Kazuhiro
Nishiwaki, Shinji
著者名の別形: 佐藤, 勇気
山田, 崇恭
泉井, 一浩
西脇, 眞二
キーワード: Manufacturability
Fictitious physical model
Topology optimization
Geometrical constraint
Molding constraint
発行日: Sep-2017
出版者: Springer London
誌名: The International Journal of Advanced Manufacturing Technology
巻: 92
号: 1-4
開始ページ: 1391
終了ページ: 1409
抄録: Manufacturing methods using molds, such as casting and injection molding, are widely used in industries. A basic requirement when using such manufacturing methods is that design engineers must design products so that they incorporate certain geometrical features that allow the mold parts to be removed from the created solid object. In the present study, we propose a manufacturability evaluation method especially adapted for the use of molds. To evaluate the manufacturability, we introduce fictitious physical models that are described by steady-state anisotropic advection-diffusion equations. In these fictitious physical models, material domains have a virtual source term and the advection directions are aligned with the directions along which the mold parts are parted. Void regions, where the values of all fictitious physical fields are high, then represent either undercut geometries that would prevent the mold from being released, or interior voids that cannot be cast. Consequently, manufacturability can be evaluated using these fictitious physical fields. Furthermore, in the present study, we integrate this evaluation method with topology optimization and propose a scheme for imposing a molding constraint within the topology optimization procedure. This newly proposed topology optimization method can consider the position of mold parting lines prior to the detailed optimization procedure. Several numerical examples are provided to demonstrate the validity and effectiveness of the proposed method.
著作権等: The final publication is available at Springer via http://dx.doi.org/10.1007/s00170-017-0218-0.
The full-text file will be made open to the public on 01 September 2018 in accordance with publisher's 'Terms and Conditions for Self-Archiving'
This is not the published version. Please cite only the published version.
この論文は出版社版でありません。引用の際には出版社版をご確認ご利用ください。
URI: http://hdl.handle.net/2433/226740
DOI(出版社版): 10.1007/s00170-017-0218-0
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