The installation of monitoring systems on buildings allows analyzing variations in structural parameters over time, creating room for detection of damage. Structural Health Monitoring (SHM) systems have the potential to support pro-active risk management, where structural interventions are planned if specific thresholds related to target performance losses are achieved. DETECT-AGING is a research project of relevant national interest that was funded by the Italian Ministry of University and Research (MUR) through the PRIN 2017 programme. The project started in September 2019 and involves the universities of Bologna, Genova, Napoli Federico II, and Perugia. The main goal of the project is to develop a new analytical-instrumental approach aimed at the quantitative assessment of the effects of aging and material degradation on structural safety of cultural heritage, with special focus on masonry structures. Based on a combined use of structural models and health monitoring systems, indications and operational tools will be provided for the identification and quantification of structural damage, supporting the management of built cultural heritage. To this purpose, a two-storey masonry building, having a single room with a vault at the first floor and a timber roof, was built with the aim of being monitored and progressively and will be damaged during the project. It is equipped with a hybrid SHM system managed by the University of Perugia, which is based on both vibration and strain measurements. The present paper illustrates the main features of the case-study building and presents the results of the experimental program aimed at characterizing the mechanical properties of masonry the materials used. The final part of the paper presents a blind prediction contest based on prediction of modal features of the building in different damaged configurations.

DETECT-AGING blind prediction contest: a benchmark for structural health monitoring of masonry buildings

N. Buratti
Primo
;
G. Virgulto
2022

Abstract

The installation of monitoring systems on buildings allows analyzing variations in structural parameters over time, creating room for detection of damage. Structural Health Monitoring (SHM) systems have the potential to support pro-active risk management, where structural interventions are planned if specific thresholds related to target performance losses are achieved. DETECT-AGING is a research project of relevant national interest that was funded by the Italian Ministry of University and Research (MUR) through the PRIN 2017 programme. The project started in September 2019 and involves the universities of Bologna, Genova, Napoli Federico II, and Perugia. The main goal of the project is to develop a new analytical-instrumental approach aimed at the quantitative assessment of the effects of aging and material degradation on structural safety of cultural heritage, with special focus on masonry structures. Based on a combined use of structural models and health monitoring systems, indications and operational tools will be provided for the identification and quantification of structural damage, supporting the management of built cultural heritage. To this purpose, a two-storey masonry building, having a single room with a vault at the first floor and a timber roof, was built with the aim of being monitored and progressively and will be damaged during the project. It is equipped with a hybrid SHM system managed by the University of Perugia, which is based on both vibration and strain measurements. The present paper illustrates the main features of the case-study building and presents the results of the experimental program aimed at characterizing the mechanical properties of masonry the materials used. The final part of the paper presents a blind prediction contest based on prediction of modal features of the building in different damaged configurations.
2022
Proceedings of the ANIDIS Conference (Torino, Settembre 2022)
2128
2135
N. Buratti, S. Cattari, G. Lignola, A. Meoni, F. Parisi, F. Ubertini, G. Virgulto
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/903958
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