kth.sePublications KTH
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Topology Optimization for Additive Manufacturing – A Numerical Study of Current Design Framework Capabilities and Limitations
KTH, School of Engineering Sciences (SCI), Engineering Mechanics, Vehicle Engineering and Solid Mechanics, Solid Mechanics.ORCID iD: 0000-0001-6375-6292
KTH, School of Engineering Sciences (SCI), Engineering Mechanics, Vehicle Engineering and Solid Mechanics, Solid Mechanics.
KTH, School of Industrial Engineering and Management (ITM), Production Engineering, Manufacturing and Metrology Systems.ORCID iD: 0000-0003-4120-4790
2022 (English)In: Advances in Transdisciplinary Engineering / [ed] A.H.C. Ng et al., IOS Press , 2022, Vol. 21, p. 592-603Conference paper, Published paper (Refereed)
Abstract [en]

Topology optimization (TO) is commonly used to minimize the weight of a structural component subject to a constraint on the maximum equivalent stress. In TO for additive manufacturing (AM), constraints on the build direction as well as the overhang angle are also included in the optimization. However, current design framework generally doesn’t include the residual stresses and distortions that result from the AM process directly into the TO. In this work, it is shown that this limitation can result in components that may fail during the Selective Laser Melting (SLM) due to high stresses and distortion that were not accounted for in the TO. For the studied demonstrative bracket design from Ti-6Al-4V, it is shown that the spatial stress distribution, including both the location and magnitude of the maximum stress, is strongly altered after SLM compared to the stresses used in the TO, even after heat treatment. This work highlights the importance of integrating AM process simulation with residual stress and distortion prediction directly in the TO, which is currently a difficult and computationally inefficient task.

Place, publisher, year, edition, pages
IOS Press , 2022. Vol. 21, p. 592-603
National Category
Applied Mechanics Production Engineering, Human Work Science and Ergonomics Reliability and Maintenance Manufacturing, Surface and Joining Technology
Identifiers
URN: urn:nbn:se:kth:diva-311723DOI: 10.3233/ATDE220177ISI: 001191233200050Scopus ID: 2-s2.0-85132798216OAI: oai:DiVA.org:kth-311723DiVA, id: diva2:1655518
Conference
10th Swedish Production Symposium (SPS2022)
Note

Part of proceedings: ISBN 978-1-64368-268-6

QC 20220506

Available from: 2022-05-02 Created: 2022-05-02 Last updated: 2025-12-05Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full textScopushttps://ebooks.iospress.nl/volumearticle/59336

Authority records

Mansour, RamiGillgren, SaraDadbakhsh, Sasan

Search in DiVA

By author/editor
Mansour, RamiGillgren, SaraDadbakhsh, Sasan
By organisation
Solid MechanicsManufacturing and Metrology Systems
Applied MechanicsProduction Engineering, Human Work Science and ErgonomicsReliability and MaintenanceManufacturing, Surface and Joining Technology

Search outside of DiVA

GoogleGoogle Scholar

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 257 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf