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An Intelligent Modeling Method for Protecting and Inheriting the Construction Techniques of Wooden Stilt Buildings

Auteur(s):





Médium: article de revue
Langue(s): anglais
Publié dans: Buildings, , n. 1, v. 15
Page(s): 61
DOI: 10.3390/buildings15010061
Abstrait:

This study examines the digital translation of traditional wooden architectural construction techniques through the application of Building Information Modeling (BIM) methods. The development of a Heritage Building Information Modeling (HBIM) model for these techniques necessitates interdisciplinary integration. Critical steps involve the intelligent incorporation of wooden architectural knowledge into parametric models and the creation of advanced modeling methods capable of translating such models. These aspects are essential for bridging existing gaps and enhancing HBIM applications. By using the Dong drum tower as a case study, this paper presents a parametric model for stilt-style wooden structures, emphasizing the generation rules of construction techniques and the extraction and translation of parameters. A smart automated modeling method was developed and programmed collaboratively using Grasshopper (version 1.0.0007) and Python (version 2.7.12.0). This method facilitates the generation of diverse, customizable drum tower models within 60 s and has successfully created the tallest drum tower model in Guangxi based on actual measurements, validating the method’s reliability and effectiveness. The findings of this study offer digital, automated, and intelligent support for the preservation and transmission of traditional architectural techniques.

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

Cette oeuvre a été publiée sous la license Creative Commons Attribution 4.0 (CC-BY 4.0). Il est autorisé de partager et adapter l'oeuvre tant que l'auteur est crédité et la license est indiquée (avec le lien ci-dessus). Vous devez aussi indiquer si des changements on été fait vis-à-vis de l'original.

  • Informations
    sur cette fiche
  • Reference-ID
    10810619
  • Publié(e) le:
    17.01.2025
  • Modifié(e) le:
    25.01.2025
 
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