Dataset of the paper "An optimised multi-level method for the pushover analysis of historic masonry structures accounting for the actual masonry pattern"

Szabó, Simon ; Funari, Marco Francesco ; D'Altri, Antonio Maria ; de Miranda, Stefano ; Lourenço, Paulo B. (2025) Dataset of the paper "An optimised multi-level method for the pushover analysis of historic masonry structures accounting for the actual masonry pattern". University of Bologna. DOI 10.6092/unibo/amsacta/8407. [Dataset]
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Abstract

This dataset, developed in the framework of the H2020 HOLAHERIS project, contains results data related to an optimised multi-level method to account for the actual masonry pattern in the pushover analysis of historic masonry structures. The method uses (i) a rigid block-based limit analysis to identify realistic failure mechanisms accounting for the actual masonry pattern. Then, (ii) macro-blocks outlining the failure mechanism are identified based on a heuristic search. Finally, (iii) macro-blocks are modelled as homogeneous material interacting via cohesive-frictional interfaces in a finite element environment where base shear-displacement curves can be extracted by means of pushover analyses. Base shear-displacement curves obtained with this optimised multi-level method on five structural benchmarks, as well as the finite element models, are collected herein to provide data for future comparisons.

Abstract
Document type
Dataset
Creators
CreatorsORCIDAffiliationROR
Szabó, SimonUniversity of Minho
Funari, Marco FrancescoUniversity of Surrey
D'Altri, Antonio Maria0000-0002-4932-4554University of Bologna
de Miranda, StefanoUniversity of Bologna
Lourenço, Paulo B.University of Minho
Subjects
DOI
Contributors
Name
ORCID
Type
Affiliation
D'Altri, Antonio Maria
Project leader
University of Bologna
Deposit date
02 Jul 2025 10:40
Last modified
02 Jul 2025 10:40
Related identifier
Related identifier type
Relation type
Code
Project name
HOLAHERIS - A holistic structural analysis method for cultural heritage structures conservation
Funding program
EC - H2020
URI

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