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Sustainable Structural System Selection Using Hybrid Fuzzy Multi-Criteria Decision Model Based on Seismic Performance

Author(s): ORCID

ORCID
Medium: journal article
Language(s): English
Published in: Buildings, , n. 7, v. 14
Page(s): 2107
DOI: 10.3390/buildings14072107
Abstract:

In the rapidly evolving field of sustainable construction, this study aims to address the critical need for advancement in the building industry, focusing on vital indicators like energy efficiency and cost-effectiveness, as well as improving occupant comfort. This research introduces a novel approach to support the choice of suitable structural systems for mass housing projects, with a case study on Iran’s national housing scheme. This methodology involves a four-phase process, beginning with compiling a database from existing studies to outline primary and secondary indicators affecting structural system selection. It utilizes the fuzzy AHP method for criteria prioritization and the fuzzy TOPSIS technique for alternatives (LSF, 3DP, ICF, TRC, and RCCF). The study identified the light steel framing (LSF) system as the optimal choice for Iran’s housing needs based on various criteria. Then, in the final phase, the study evaluates the seismic performance of cold-formed steel (CFS) frames with various sheathing panel types (OSB, DFP, CSP, and GWB) under monotonic loads, examining key seismic parameters across 38 frame setups. The findings reveal that LSF structures can effectively withstand seismic events within the elastic behavior range, suggesting that this construction approach is viable for enhancing mass housing production in Iran’s construction sector.

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
    10795095
  • Published on:
    01/09/2024
  • Last updated on:
    01/09/2024
 
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