Topology optimisation and reengineering of tubular WAAM joints for hybrid construction

Abstract Compared to conventional subtractive or formative manufacturing techniques, additive manufacturing (AM) offers increased geometric freedom, enhanced structural efficiency and greater automation. Hybrid construction, which combines conventionally produced structural components (e.g. hot‐rolled steel tubes) with additively manufactured parts (e.g. optimised joints), is deemed to be the most practical way to deploy metal AM in construction. This study focuses on developing an optimisation methodology that combines topology optimisation, reengineering and measures to enhance printability. During the topology optimisation phase, the printability of the optimised part is considered by imposing stress and overhang constraints, preventing the formation of overly slender elements and excessive overhang angles. In the reengineering phase, printability is further improved through manual adjustments to satisfy manufacturing constraints. Following its development, this methodology was applied to generate optimised X‐shaped tubular joints, which were subsequently printed by means of wire arc additive manufacturing (WAAM). The structural performance of the printed joints, including the initial stiffness, ultimate load‐bearing capacity, ductility and material efficiency, was assessed through geometrically and materially nonlinear numerical analyses and verified by physical experiments.

Authors

Institutions

Publication Details

Journal
ce/papers
Published
2025-12-01
DOI
https://doi.org/10.1002/cepa.70039
Primary Topic
Topology Optimization in Engineering
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Topology optimisation and reengineering of tubular WAAM joints for hybrid construction

Pinelopi Kyvelou, L. Gardner, Minze Zhang, Xin Meng
ce/papers
Topology Optimization in Engineering
article

Topology optimisation and reengineering of tubular WAAM joints for hybrid construction

Pinelopi Kyvelou, L. Gardner, Minze Zhang, Xin Meng
article en

Abstract

Abstract Compared to conventional subtractive or formative manufacturing techniques, additive manufacturing (AM) offers increased geometric freedom, enhanced structural efficiency and greater automation. Hybrid construction, which combines conventionally produced structural components (e.g. hot‐rolled steel tubes) with additively manufactured parts (e.g. optimised joints), is deemed to be the most practical way to deploy metal AM in construction. This study focuses on developing an optimisation methodology that combines topology optimisation, reengineering and measures to enhance printability. During the topology optimisation phase, the printability of the optimised part is considered by imposing stress and overhang constraints, preventing the formation of overly slender elements and excessive overhang angles. In the reengineering phase, printability is further improved through manual adjustments to satisfy manufacturing constraints. Following its development, this methodology was applied to generate optimised X‐shaped tubular joints, which were subsequently printed by means of wire arc additive manufacturing (WAAM). The structural performance of the printed joints, including the initial stiffness, ultimate load‐bearing capacity, ductility and material efficiency, was assessed through geometrically and materially nonlinear numerical analyses and verified by physical experiments.

ce/papersVol. 8(6)
Imperial College London (GB)
Openalex Percentile: Top 33%
Topology Optimization in Engineering
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.