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Civil-Comp Conferences
ISSN 2753-3239 CCC: 14
PROCEEDINGS OF THE SIXTEENTH INTERNATIONAL CONFERENCE ON COMPUTATIONAL STRUCTURES TECHNOLOGY Edited by: P. Iványi, J. Kruis and B.H.V. Topping
Paper 14.2
Reduced Mesoscale Modelling for Masonry Arch Bridges M.S. El Ashri1,2, S. Grosman3,2, L. Macorini1 and B.A. Izzuddin3
1Department of Civil and Environmental Engineering, Imperial College London, United Kingdom
Full Bibliographic Reference for this paper
M.S. El Ashri, S. Grosman, L. Macorini, B.A. Izzuddin, "Reduced Mesoscale Modelling for Masonry Arch Bridges", in P. Iványi, J. Kruis, B.H.V. Topping, (Editors), "Proceedings of the Sixteenth International Conference on
Computational Structures Technology", Civil-Comp Press, Edinburgh, UK,
Online volume: CCC 14, Paper 14.2, 2026, doi:10.4203/ccc.14.14.2
Keywords: masonry arch bridges, structural assessment, computational efficiency, reduced mesoscale models, material properties calibration, ageing infrastructure.
Abstract
This paper introduces a reduced mesoscale modelling approach for the accurate and efficient assessment of old masonry bridges. As these ageing structures remain a vital part of Europe’s infrastructure, they must be assessed under current traffic loads using models that accurately capture the characteristic 3D response and the anisotropic behaviour arising from the actual masonry bond of the key bridge components. This can be achieved through detailed, high-fidelity 3D masonry models, though these can pose excessive computational demands, thereby constraining their practical application. Typically, more simplified models are used, either employing 3D macroscale isotropic approaches or 2D models that omit 3D effects, potentially leading to inaccurate response predictions. To improve this, the paper utilises mesoscale masonry models with relaxed bond patterns. Numerical results show that bridge models with a calibrated, reduced mesoscale mesh for the masonry parts of the bridge achieve performance comparable to full mesoscale models, capturing essential features of the response to vertical loading while significantly reducing the computational demand.
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