Fabrication-Aware Joint Clustering in Freeform Space-Frames

Antiopi Koronaki, Paul Shepherd, Mark Evernden

Research output: Contribution to journalArticlepeer-review

1 Citation (SciVal)


The geometrical variability in the joints of large-scale, doubly-curved space-frame structures can have a substantial impact on the time and cost of their construction. This paper proposes a novel framework to assess the construction complexity of space-frame structures as a factor of the geometrical variability and fabrication of their joints, to promote the informed design of the fabrication process. The k-means algorithm was used to cluster space-frame joints into fabrication batches, providing an overview of the variability distribution. A novel initialisation method was developed that allows the algorithm to adapt to project-specific inputs, substantially improving cluster compactness. Overlaying the clustering results with the properties of different fabrication processes provides an accurate estimation of the construction complexity of alternative fabrication options. The method was applied to a large-scale case study to demonstrate the benefits in practice. Alternative fabrication scenarios were assessed in the early stages of the design development, leading to the informed design of the fabrication process and hence to the efficient construction of large-scale, complex structures.
Original languageEnglish
Article number962
Issue number4
Publication statusPublished - 4 Apr 2023

Bibliographical note

Funding: This study was supported by the EPSRC Centre for Decarbonisation of the Built Environment (dCarb) [Grant Ref: EP/L016869/1].

Data Availability Statement: The data presented in this study are available on request from the corresponding author


  • construction
  • fabrication
  • geometry
  • joints
  • k-means
  • machine learning
  • space-frames

ASJC Scopus subject areas

  • Building and Construction
  • Architecture
  • Civil and Structural Engineering


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