A Multiscale Approach for the Seismic Vulnerability Assessment of Historical Centres in Masonry Building Aggregates: Cognitive Approach and Interdisciplinary Perspectives

Cardinali, Vieri; Cristofaro, Maria Teresa; Ferrini, Maurizio; Nudo, Raffaele; Paoletti, Barbara; Tanganelli, Marco

doi:10.1080/15583058.2021.1992536

Cited by 15 publications

(6 citation statements)

References 41 publications

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“…The macro-element approach follows the assumption that masonry panels behave as rigid blocks connected through kinematic chains. Although the more or less refined available procedures, the methodology is a reliable approach to investigate the structural performance of masonry constructions when the structure of historical discontinuities are pointed out [56][57][58][59][60][61]. In this work, the seismic demand was needed on the basis of the geological investigation conducted and the hazard information of the area.…”

Section: Seismic Vulnerability Assessment and Multilevel Evaluationmentioning

confidence: 99%

Knowledge-Based Investigation of Seismic Vulnerability Assessment and Compatible Strengthening Design of an Existing Masonry Building

Cristofaro

Tanganelli

2023

Applied Sciences

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Most existing masonry buildings were built without following code regulations for seismic criteria. Hence, their performance compared to the demands of the current codes, for both seismic and static actions, could be very low. In engineering practice, strengthening interventions can be pursued at different levels, based on qualitative assessments of masonry structures. Firstly, the structures are evaluated through in situ inspections. Then, based on the structural system of the building a strengthening design is proposed. The design can be targeted at guaranteeing a box behavior of structures acting through macro-elements, or at strengthening the in-plane capacity of piers and spandrels. However, lower cognitive levels may drive inaccurate impressions about the capacity of structures, leading to unreliable strengthening solutions. While in some cases the confidence factor could underestimate the effects of the reinforcements, in other cases lower knowledge levels could lead to incorrect reinforcements that do not provide helpful solutions. In this paper, the issues concerning the strengthening design of masonry structures are presented and discussed with regard to an existing building. The construction is a 20th century masonry building used as a nursing home for elderly persons. The study follows a knowledge-based procedure where, after achievement of the highest knowledge level and the proposal of compatible and effective strengthening interventions, the analysis of the potential effects of achieving lower knowledge levels is discussed both in terms of vulnerability computations and in terms of strengthening effectiveness. Regarding vulnerability assessment, a lower knowledge level leads to non-conservative results, with an increase in the estimated capacity of around 80%. Critical evaluation of the different configurations for the case study makes it clear that for the considered masonry building the mortar investigation represented the most important parameter to be investigated. The proposal of strengthening interventions before assessment of this parameter may lead to ineffective improvements resulting in index values lower than 0.60. The study represents the opportunity to assess comparisons in the setting of different investigation strategies and their effect on the definition of the strengthening solutions.

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Section: Seismic Vulnerability Assessment and Multilevel Evaluationmentioning

confidence: 99%

Knowledge-Based Investigation of Seismic Vulnerability Assessment and Compatible Strengthening Design of an Existing Masonry Building

Cristofaro

Tanganelli

2023

Applied Sciences

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“…In recent years, some studies tried to overcome the issues related to the seismic vulnerability assessment of URM aggregates by adopting various approaches, i.e. : holistic approach (Cardinali et al 2021); heuristic approach (e.g. Ferreira et al 2013;Vicente et al 2014;Brando et al 2017;Sandoli et al 2022;Moretic et al 2022), analytical-mechanical approach (Cocco et al 2019;Cima et al 2021;Nale et al 2021; analytical-numerical approach (Ramos and Lourenço 2004;Senaldi et al 2010;Vicente et al 2011;Fagundes et al 2017;Formisano and Massimilla 2019;Bernardini et al 2019;Degli Abbati et al 2019;Valente et al 2019;Greco et al 2020;Grillanda et al 2020;Angiolilli et al 2021;Battaglia et al 2021;Valluzzi et al 2021;Bernardo et al 2022); large-scale approaches based on empirical evaluations obtained from post-earthquake data (Del Gaudio et al 2019;Penna et al 2022a;Sisti et al 2019); as well as hybrid methods (Kappos et al 2006;Maio et al 2015) combining the previous approaches through the individuation of representative building classes.…”

Section: Introductionmentioning

confidence: 99%

Fragility curves of masonry buildings in aggregate accounting for local mechanisms and site effects

Angiolilli

Brunelli

Cattari

2023

Bull Earthquake Eng

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The seismic evaluation of masonry buildings in aggregate, largely diffused within the existing Italian and European building stock, represents a difficult and open task that has not been exhaustively investigated so far. The study proposes a procedure aimed at evaluating the potential impact of the combination of local mechanisms and site-amplification in terms of fragility curves on an existing unreinforced masonry (URM) aggregate which is made of five adjacent structural units mutually interacting with each other during seismic sequences. The case study is inspired by built heritage of the historic centre of Visso struck by the Central Italy 2016/2017 earthquakes. The in-plane (IP) response of URM buildings was simulated through nonlinear dynamic analyses performed on a 3D equivalent frame model of the structure, whereas out-of-plane (OOP) mechanisms were analysed by adopting the rigid-block assumption but assuming, as seismic input, the floor accelerations derived from the post-processing of data derived from the global 3D model. An innovative procedure considering the pounding effect to the global response of the building is also presented. Two soil conditions were assumed with (freefield) and without (bedrock) site amplification. The results showed that site effects strongly affected the seismic vulnerability of the aggregate, also altering the combination between IP and OOP mechanisms. In fact, for bedrock condition, especially for medium–high damage levels, local mechanisms were prevailing with respect to the IP response. Conversely, for freefield condition, IP mainly governed the overall behaviour for all the damage levels, consistently with the field evidence.

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“…The factors characterizing aggregates are so many and so interconnected that it is difficult to unravel it with the classical tools adopted so far to interpret isolated masonry constructions. In recent years, numerous efforts and advances have been made in the literature in this regard, and several methodologies have been proposed for assessing the seismic vulnerability of buildings in aggregate: holistic approach [6]; heuristic approach [7,8,9]; mechanical-analytical approach [10,11]; mechanical-numerical approach [12,13,14,15,16,17,18,19,20]; large-scale approaches based on empirical evaluation obtained from post-earthquake data [4]. Also the experimental campaigns specifically addressed to face this topic are very recent and limited in number [21,22].…”

Section: Introductionmentioning

confidence: 99%

Machine Learning-Based Identification of Vulnerability Factors for Masonry Buildings in Aggregate: The Historical Centre of Casentino Hit by the 2009 L’aquila Earthquake

Pinasco,

Lagomarsino,

Carocci

et al. 2023

Proceedings of the 8th International Conference on Computational Methods in Structural Dynamics and Earthquake Engineering (COM

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Seismic events in Italy and worldwide have highlighted the high vulnerability of unreinforced masonry (URM) structures in small historical centres. A key feature of these settlements is to be mostly composed of buildings in aggregate, i.e., interconnected by a more or less structurally effective connection. The seismic assessment of such buildings is quite debated in the literature and no shared tools procedures are currently available. The difficulty of standardization derives from the fact that structural units can be characterized by multiple features and configurations that determine a vast number of vulnerability factors, whose interdependency is not straightforward to be identified. The paper addresses this issue by combining evidencebased damage data with the potential offered by Machine Learning (ML) technique. Real data are used in combination with state-of-the-art ML algorithms carefully tuned via an advanced statistical procedure for two main purposes. The first one will be able to predict possible URM damages based on the vulnerability factor in both interpolation and extrapolation scenarios. The second purpose of the ML-based techniques will be to predict the most important vulnerability factors in making these predictions, namely to make the ML-based model explainable and informative about the underlying phenomena and not just predictive. The small historic centre of Casentino, hit by the 2009 L'Aquila earthquake, is adopted in the paper as the first test case study. A large amount of data was collected after the earthquake through in-situ surveys made by the Universities of Genova, Catania and Rome. Data include both geometric and structural factors, i.e., the input data supplied to the ML algorithm, as well as the actual seismic damage mechanisms, i.e., the output data expected to be predicted by the ML algorithm. As first application, ML techniques are applied only to data acquired on out-of-plane mechanisms. 1236COMPDYN 2023 9 th ECCOMAS Thematic Conference on Computational Methods in Structural Dynamics and Earthquake Engineering M. Papadrakakis, M. Fragiadakis (eds.

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A Multiscale Approach for the Seismic Vulnerability Assessment of Historical Centres in Masonry Building Aggregates: Cognitive Approach and Interdisciplinary Perspectives

Cited by 15 publications

References 41 publications

Knowledge-Based Investigation of Seismic Vulnerability Assessment and Compatible Strengthening Design of an Existing Masonry Building

Knowledge-Based Investigation of Seismic Vulnerability Assessment and Compatible Strengthening Design of an Existing Masonry Building

Fragility curves of masonry buildings in aggregate accounting for local mechanisms and site effects

Machine Learning-Based Identification of Vulnerability Factors for Masonry Buildings in Aggregate: The Historical Centre of Casentino Hit by the 2009 L’aquila Earthquake

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