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Spatial variability and stochastic finite element model of unreinforced masonry veneer wall system under Out-of-plane loading

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posted on 2025-05-09, 02:37 authored by Imrose B. Muhit, Mark MasiaMark Masia, Mark StewartMark Stewart, Andrea C. Isfeld
Inconsistency in the quality of workmanship, the weather during construction, and materials may result in the high unit-to-unit spatial variability of mechanical properties in the same masonry structure. This paper develops a numerical modelling strategy and focuses on the stochastic assessment of unreinforced masonry (URM) veneer walls with spatially variable wall constituent material properties subjected to out-of-plane loading. 3-D finite element modelling of experimentally tested veneer walls was conducted using a micro-modelling approach combined with the Monte Carlo Simulation technique. Spatial stochastic finite element analysis considered the spatial variability of the properties of the wall components (mortar flexural tensile strength) and compared them with non-spatial analysis. The non-spatial analysis overestimates the wall system failure compared to spatial analysis, and the spatial analysis is considered to more realistically represent the variabilities of the URM veneer wall system. Sensitivity analysis is conducted to check the sensitivity of the veneer system behaviour to variability in the various input parameters. The variability of experimental results obtained in a parallel study are quantified and compared with stochastic finite element analysis (SFEA) results. The SFEA model developed in this study can estimate the behaviour and system peak load reasonably and are considered to be from the similar population as test results. Model errors are also included to assess the efficiency of the SFEA model.

Funding

ARC

DP180102334

History

Journal title

Engineering Structures

Volume

267

Issue

15 September 2022

Article number

114674

Publisher

Elsevier

Language

  • en, English

College/Research Centre

College of Engineering, Science and Environment

School

School of Engineering

Rights statement

© 2022 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).