PSI - Issue 55

Isabel Turbay et al. / Procedia Structural Integrity 55 (2024) 168–176 Author name / Structural Integrity Procedia 00 (2019) 000 – 000

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1. Introduction Churches of Popayan (2° 27' 15" N - 76° 36' 33" W) and Cartagena de Indias (10° 23' 59" N - 75° 30' 52" W) (Colombia) and La Antigua (14° 33' 27" N - 90° 44' 00" W) (Guatemala) built between the 16th and 18th centuries and located within the perimeter of their historic centres were studied by the evaluation of an index of global vulnerability (Ortiz et al., 2014; Ortiz et al., 2016, 2018; Ortiz and Ortiz, 2016; Rodríguez et al., 2021). This assessment depends on the conditions of conservation and the environment and allow to classify the building as more or less vulnerable. A statistical study using PCA was employed to locate representative data of the set of variables that influence or affect these churches conservation. The PCA was employed to define the relationship between variables, predict behaviours and set diagnosis evolutions in similar buildings (Moropoulou and Polikreti, 2009). PCA is often applied in cultural heritage with a chemometric approach (Cardinali et al. 2021), in archaeological studies (Busto,2018) to evaluate chronologies. In diagnosis and conservation, Ozga et al. in 2014 identified polluting sources, Moropoulou and Polikreti studied climatic conditions in historical buildings (2009), Mu et al., (2020) implemented PCA in environmental monitoring for the prediction of pathologies, in these cases the dimension of the data is reduced to then build a model. Also, with an important utility in the microclimatic study of Rosenborg Castle, in Denmark with the use of the combination of statistical methods for the subsequent deployment of microclimatic Vulnerability was assessed using the method proposed by Ortiz and Ortiz, 2016; Ortiz et al, (2018), initially using an identification matrix that allows recording and confronting the factors causing impact on a building such as climate (winds, temperature, humidity, dew point, rainfall), soil characteristics (geotechnics, phreatic level), natural phenomena (volcanoes, earthquakes or floods), pollutants or biological agents (gases, particles or xylophagous) and anthropic action (urban dynamics) with the altered variables such as the characteristics of the materials, foundation or structure, the data obtained are then used to create a characterization matrix that synthesizes the action of the alteration agents on the building materials according to the possible alteration indicators that can be generated for the area studied (city, region or country), and then the effects are evaluated for each one, taking into account the alterations observed in the in situ visits and calculating the intensity of the damage; with the data previously obtained, the vulnerability index (VI) is calculated by dividing the total intensity of the disturbance indicators for each building by the sum of the total intensity of the disturbance indicators with the highest frequency, which corresponds to the most unfavourable case. For this study specifically, the method proposed by Ortiz and Ortiz, 2016.; Ortiz et al., (2018) was adapted to the cases studies in Colombia and Guatemala with new variables as seismic vulnerability, traffic, land use, inadequate occupation of public space, cataloguing or level of use. Table 1 shows the four indexes that were studied: vulnerability index (VI), weighted vulnerability index (VIp), intrinsic expanded vulnerability index (VIe2) and global expanded vulnerability index (VIe1). The vulnerability index (VI) in this case has been applied following the model of the RIVUPH and Art-Risk Projects, in Spain, Cuba and Colombia (Ortiz et al., 2014; Ortiz et al., 2016, 2018; Ortiz and Ortiz, 2016; Rodríguez et al., 2021; Turbay et al., 2019). The VIp has been calculated with the weighting obtained from the opinion of experts using the Delphi method with the physical-chemical characteristics, texture, foundation, structure, construction system and alteration of the landscape (Ortiz et al., 2013). The VIe2 has been calculated with the weighted vulnerability index and the opinion of the experts with those variables that are specific to the building, considering the factors that would enhance the vulnerability of the building from the point of view of its intrinsic properties, and that depend on the construction model, as well as its management and maintenance. The VIe1 includes those factors previously developed by Ortiz and Ortiz (2016) and Macías (2012) such as cataloguing, level of use, fire resistance, roof design, state of facilities and constructive simplicity, and new variables due to the conditions of the heritage of Colombia and Guatemala, related to characteristics and dynamics of the historic sensors (Frasca et al., 2022). 2. Material and methods