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Optimising Plate Thickness in Interlocking Inter-Module Connections for Modular Steel Buildings: A Finite Element and Random Forest Approach

Autor(en): ORCID


ORCID
Medium: Fachartikel
Sprache(n): Englisch
Veröffentlicht in: Buildings, , n. 5, v. 14
Seite(n): 1254
DOI: 10.3390/buildings14051254
Abstrakt:

Interlocking Inter-Module Connections (IMCs) in Modular Steel Buildings (MSBs) have garnered significant interest from researchers. Despite this, the optimisation of plate thicknesses in such structures has yet to be extensively explored in the existing literature. Therefore, this paper focuses on optimising the thickness of interlocking IMCs in MSBs by leveraging established experimental and numerical simulation methodologies. The study developed various numerical models for IMCs with plate thicknesses of 4 mm, 6 mm, 10 mm, and 12 mm, all subjected to compression loading conditions. The novelty of this study lies in its comprehensive parametric analysis, which evaluates the slip prediction model. A random forest regression model, trained using the ‘TreeBagger’ function, was also implemented to predict slip values based on applied force. Sensitivity analysis and comparisons with alternative methods underscored the reliability and applicability of the findings. The results indicate that a plate thickness of 11.03 mm is optimal for interlocking IMCs in MSBs, achieving up to 8.08% in material cost reductions while increasing deformation resistance by up to 50.75%. The ‘TreeBagger’ random forest regression significantly enhanced slip prediction accuracy by up to 7% at higher force levels.

Copyright: © 2024 by the authors; licensee MDPI, Basel, Switzerland.
Lizenz:

Dieses Werk wurde unter der Creative-Commons-Lizenz Namensnennung 4.0 International (CC-BY 4.0) veröffentlicht und darf unter den Lizenzbedinungen vervielfältigt, verbreitet, öffentlich zugänglich gemacht, sowie abgewandelt und bearbeitet werden. Dabei muss der Urheber bzw. Rechteinhaber genannt und die Lizenzbedingungen eingehalten werden.

  • Über diese
    Datenseite
  • Reference-ID
    10787627
  • Veröffentlicht am:
    20.06.2024
  • Geändert am:
    25.01.2025
 
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