Validated and Optimized Strategies for Preserving Historical Heritage Towards Natural and Anthropic Risks: Insights from the DETECT-AGING Project

This paper summarizes simple and practically attractive new methodologies based on validated and optimized strategies for preserving historical heritage towards natural or anthropic risks in order to assist public administrations and stakeholders involved at various levels in the protection of cultural heritage. This represents the outcome of the PRIN 2017 project DETECT-AGING—degradation effects on structural safety of cultural heritage constructions through simulations and health monitoring. Results were built on recent advances in structural performance modelling of historical masonry structures, interpretation of effects of degradation, advanced numerical simulations, and structural health monitoring, with the final aim to go beyond the state of the art in regard to assessing and establishing: (i) degradation effects from the level of materials to the scale of components; (ii) methodologies able to transfer information on mechanical behaviour from a micro-scale to a macro-scale; (iii) the use of ambient vibration measurements to address epistemic modelling uncertainties in historical masonry buildings; (iv) structural health monitoring (SHM) to detect the occurrence of damage and locate/quantify damage; (v) the capability of equivalent frame models (EFMs) to support the SHM of masonry structures in place of more refined 3D finite element models (FEMs); (vi) variations in the structural response that can be monitored by sensor networks as a function of simulated degradation.

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Publication Details

Journal
Buildings
Published
2025-02-22
DOI
https://doi.org/10.3390/buildings15050693
Citations
4
Primary Topic
Structural Health Monitoring Techniques
Type
article
Field-Weighted Citation Impact
3.81
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article

Validated and Optimized Strategies for Preserving Historical Heritage Towards Natural and Anthropic Risks: Insights from the DETECT-AGING Project

Filippo Ubertini, Giorgio Virgulto, Andrea Meoni, Fulvio Parisi et al.
4 citations
Buildings
Structural Health Monitoring Techniques
3.81
article

Validated and Optimized Strategies for Preserving Historical Heritage Towards Natural and Anthropic Risks: Insights from the DETECT-AGING Project

Filippo Ubertini, Giorgio Virgulto, Andrea Meoni, Fulvio Parisi, Daniele Sivori, Laura Ierimonti, Serena Cattari, Nicola Buratti, Sara Alfano, Gian Piero Lignola
article en
4 citations

Abstract

This paper summarizes simple and practically attractive new methodologies based on validated and optimized strategies for preserving historical heritage towards natural or anthropic risks in order to assist public administrations and stakeholders involved at various levels in the protection of cultural heritage. This represents the outcome of the PRIN 2017 project DETECT-AGING—degradation effects on structural safety of cultural heritage constructions through simulations and health monitoring. Results were built on recent advances in structural performance modelling of historical masonry structures, interpretation of effects of degradation, advanced numerical simulations, and structural health monitoring, with the final aim to go beyond the state of the art in regard to assessing and establishing: (i) degradation effects from the level of materials to the scale of components; (ii) methodologies able to transfer information on mechanical behaviour from a micro-scale to a macro-scale; (iii) the use of ambient vibration measurements to address epistemic modelling uncertainties in historical masonry buildings; (iv) structural health monitoring (SHM) to detect the occurrence of damage and locate/quantify damage; (v) the capability of equivalent frame models (EFMs) to support the SHM of masonry structures in place of more refined 3D finite element models (FEMs); (vi) variations in the structural response that can be monitored by sensor networks as a function of simulated degradation.

BuildingsVol. 15(5)
University of Perugia (IT), University of Naples Federico II (IT), University of Genoa (IT), University of Bologna (IT)
Openalex Percentile: Top 8%
Structural Health Monitoring Techniques
3.81
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