GMNA-based weighted-metric shape optimisation of DED-Arc tubular nodes
File(s)
Published version
Author(s)
Zhang, Minze
Kyvelou, Pinelopi
Gardner, Leroy
Type
Journal Article
Abstract
Relative to conventional fabrication methods, wire-arc directed energy deposition (DED-Arc) enables the production of geometrically complex steel components with improved structural efficiency. Hybrid construction, combining DED-Arc components with conventionally fabricated components, provides a practical route for the application of DED-Arc in steel structures. This study develops a weighted-metric shape optimisation framework for DED-Arc tubular nodes by integrating particle swarm optimisation with geometrically and materially nonlinear analysis (GMNA), allowing nonlinear structural behaviour to be explicitly considered within the optimisation process. A K-shaped tubular node within a cantilever hybrid truss comprising circular hollow section (CHS) members is investigated. The optimisation minimises node volume subject to a prescribed load-bearing capacity, with a series of capacity-maximisation optimisation processes conducted for verification. The results demonstrate efficient convergence and consistent identification of material-efficient node geometries. A representative optimised node is geometrically reengineered to satisfy manufacturing constraints, fabricated using DED-Arc and tested, confirming its printability and structural performance. The proposed framework provides an effective approach for the capacity-oriented optimisation of DED-Arc structural components.
Date Issued
2026-12-01
Date Acceptance
2026-06-30
Citation
Thin-Walled Structures, 2026, 231, Part A
ISSN
0263-8231
Publisher
Elsevier BV
Journal / Book Title
Thin-Walled Structures
Volume
231, Part A
Copyright Statement
© 2026 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
License URL
Publication Status
Published
Article Number
115351
Date Publish Online
2026-07-02