Generalized temperature-dependent material models for compressive strength of masonry using fire tests, statistical methods and artificial intelligence

Daware, Aditya; Naser, M. Z.; Karaki, Ghada

Abstract

Masonry has superior fire resistance properties stemming from its inert characteristics, and slow degradation of mechanical properties. However, once exposed to fire conditions, masonry undergoes a series of physio-chemical changes. Such changes are often described via temperature-dependent material models. Despite calls for standardization of such models, there is a lack in such standardized models. As a result, available temperature-dependent material models vary across various fire codes and standards. In order to bridge this knowledge gap, this paper presents three methodologies, namely, regression-based, probabilistic-based, and the use of artificial neural (ANN) networks, to derive generalized temperature-dependent material models for masonry with a case study on the compressive strength property. Findings from this paper can be adopted to establish updated temperature-dependent material models of fire design and analysis of masonry structures.

• Journal Article Type: Article
• Acceptance Date: Dec 14, 2021
• Online Publication Date: Jan 17, 2022
• Publication Date: 2022-07
• Deposit Date: Apr 24, 2023
• Publicly Available Date: Apr 25, 2023
• Journal: Architecture, Structures and Construction
• Print ISSN: 2730-9886
• Electronic ISSN: 2730-9894
• Publisher: Springer
• Peer Reviewed: Peer Reviewed
• Volume: 2
• Issue: 2
• Pages: 223-229
• DOI: https://doi.org/10.1007/s44150-021-00019-4
• Keywords: Masonry; Fire; Mechanical properties; Material models
• Public URL: https://uwe-repository.worktribe.com/output/10705220
• Publisher URL: https://link.springer.com/article/10.1007/s44150-021-00019-4
• Additional Information: Received: 2 August 2021; Accepted: 14 December 2021; First Online: 17 January 2022; Change Date: 3 February 2022; Change Type: Correction; Change Details: A Correction to this paper has been published:; Change Details: https://doi.org/10.1007/s44150-022-00023-2; : The authors declare no conflict of interest.