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A Parametric HBIM Approach for Preservation of Bai Ethnic Traditional Timber Dwellings in Yunnan, China

Author(s):



ORCID
Medium: journal article
Language(s): English
Published in: Buildings, , n. 7, v. 14
Page(s): 1960
DOI: 10.3390/buildings14071960
Abstract:

This paper proposes a meta-model-based parametric Historic Building Information Modelling (HBIM) approach to preserving and renewing traditional timber dwellings, specifically focusing on traditional Bai ethnic residential architecture. The study integrates traditional architectural principles with contemporary digital construction techniques. Traditional Bai dwellings have complex timber structural and spatial characteristics with various components. Results from the application of HBIM demonstrate improved efficiency in documenting and managing structural information, facilitating the maintenance and preservation of heritage buildings. The study concludes that HBIM, supported by parametric and generative design approaches, offers significant advantages in the digital preservation of architectural heritage. This approach not only ensures the structural integrity and historical accuracy of the models but also provides a scalable solution for managing and preserving traditional dwellings in the face of modernization pressures. This research broadens the scope of parametric design within digital construction theory, particularly concerning ancient timber structures. It offers a crucial framework that can inform both future studies and practical efforts in the preservation of heritage buildings.

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

This creative work has been published under the Creative Commons Attribution 4.0 International (CC-BY 4.0) license which allows copying, and redistribution as well as adaptation of the original work provided appropriate credit is given to the original author and the conditions of the license are met.

  • About this
    data sheet
  • Reference-ID
    10795440
  • Published on:
    01/09/2024
  • Last updated on:
    01/09/2024
 
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