PSI - Issue 44

Giuseppina De Martino et al. / Procedia Structural Integrity 44 (2023) 1816–1823 Giuseppina De Martino et al. / Structural Integrity Procedia 00 (2022) 000–000

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and the horizontal structural types from Sect. 2 of the AeDES form. Table 2 shows the distribution of masonry buildings according to damage states, DS and vulnerability classes. Note that for 2 building it was not possible to define the DS, while for 1 building the vulnerability class was not identified; this due to lack of information in the AeDES form. The table shows that high vulnerability class represents 13% of the dataset of buildings in DS0 and DS1, 17% in DS2, 24% in DS3 and DS4 and 28% in DS5.

Table. 1 Distribution of masonry buildings according to damage states, DS s , and vulnerability classes

Vulnerability

Total

DS0

DS1

DS2

DS3

DS4

DS5

22 29

31 69

16 28 52 96

65 77

21 21 44 86

20 17 34 71

175 241 509

High (A)

Significant (B)

Low (C)

117 168

138 238

124 266

Total 925 Finally, Fig. 8 shows a comparison between the mean damage, μ D , and the standard deviation, σ D , for the three vulnerability classes; they have been computed for each vulnerability class according to [Del Gaudio et al., (2019)] as follows: = ∑ � (1)

4,5

4

3,5

3

2,5

2,5

µ D, µ D ± σ D

2,2

2

1,9

1,5

1

0,5

0

A

B

C

Vulnerability

Fig. 8. Mean damage and relevant standard deviation for vulnerability class.

5. Conclusion In the aftermath of 2017 Ischia earthquake, the damage and usability assessment of buildings was carried out through in-situ surveys. Around 2000 AeDES forms were filled, allowing the collection of information about the building type, dimensions, construction age, intended use, structural type, damage level and usability rating; 1396 forms involved ordinary buildings. The data collected were digitized and geo-referenced using the Erikus-ric platform developed by the Commissarial Structure in the reconstruction process starting. The paper presents and analyses a dataset of 928 masonry residential buildings damaged by the 2017 Ischia earthquake and located in Casamicciola Terme, Forio and Lacco Ameno municipalities. The data related to buildings have been classified based on the construction age, number of stories, average surface area, quality of masonry and horizontal structural type. The main parameters affecting the damage level detected by means of AeDES form have been herein presented and discussed. Then, the damage state, DS, per building has been defined and the dataset was grouped in three classes of vulnerabilities to evaluate the cross-correlations between the building damage and the buildings’ characteristics.