Modelling of masonry infills in existing steel moment-resisting frames: Nonlinear force-displacement relationship

Wu, Jing-Ren, Di Sarno, Luigi ORCID: 0000-0001-6244-3251, Freddi, Fabio and D'Aniello, Mario (2022) Modelling of masonry infills in existing steel moment-resisting frames: Nonlinear force-displacement relationship. Engineering Structures, 267. p. 114699.

Text Wu et al 2022_Modelling of Masonry Infills in Existing Steel MRFs Nonlinear Force-Displacement Behaviour - Autors Version.docx - Author Accepted Manuscript Download (39MB)

Abstract

The study described and summarised in this paper was aimed at developing a framework for the definition of force-displacement relationships for single-strut models for masonry infill walls within steel moment-resisting frames. The methodology is based on a genetic algorithm optimisation and can be used for the calibration of force–displacement curves based on databases from either experiments or numerical simulation. A case study is also tested to demonstrate the framework in detail. Due to limited available experimental data on the seismic response of existing steel frames with masonry infills, a set of comprehensive finite element micro-models developed in Abaqus are used to generate a database. The optimal values of the parameters to feed a force–displacement relationship of the single-strut model of the masonry infills are obtained for each micro-model by solving optimisation problems with a genetic algorithm. The optimisation problem involves the minimisation of the discrepancies between the global responses from the database and their corresponding single-strut models through least square minimisation. With the optimal values as the input variables, a generalised quadrilinear model of the masonry strut is obtained through regression analysis and is validated against additional micro-models of infilled steel frames.

Item Type:	Article
Uncontrolled Keywords:	Moment Resisting Frames, Steel Structures, Masonry Infills, Equivalent strut models, Genetic Algorithm
Divisions:	Faculty of Science and Engineering > School of Engineering
Depositing User:	Symplectic Admin
Date Deposited:	19 Aug 2022 09:02
Last Modified:	28 Jul 2023 01:30
DOI:	10.1016/j.engstruct.2022.114699
Related URLs:	Author Publisher
URI:	https://livrepository.liverpool.ac.uk/id/eprint/3161639