This study assesses the seismic vulnerability of a masonry building cluster in Casentino, Italy using the FaMIVE analytical approach. The method characterizes the buildings, models the facades, evaluates seismic performance through capacity and fragility curves, and identifies failure mechanisms. Regression analysis found that the number of free corners and level of anchorage most affect vulnerability. Capacity and fragility curves derived with and without restraints show global vulnerability is sensitive to restraint levels. The identified failure mechanisms agreed well with observed damage.

1. Seismic Vulnerability Assessment of a Masonry Building
Cluster in Casentino, Italy
Valentina Putrino*, Professor Dina F. D’Ayala**
* MSc Student, Earthquake Engineering with Disaster Management
** Professor of Structural Engineering, Head of Structure, Department of Civil, Environmental and Geomatic Engineering
Figure 1: 3D view of the damage-characterised masonry building cluster
• Assess the seismic vulnerability of a masonry building cluster located in
Casentino, Italy by using an analytical approach called FaMIVE [1].
• Identify the failure mechanisms of each facade in the building compound and
compare the results with a recent qualitative study conducted on the same
cluster [2].
• Identify the main parameters controlling the extent of vulnerability.
1- Characterisation of the building compound (shown in Figure 1), e.g. structural,
geometrical and mechanical properties.
2- Modelling all facades using the FaMIVE procedure, and obtain the collapse load
factors corresponding to the failure mechanisms of each facade. The collapse
mechanism of each facade is identified based on possible modes listed in Figure 2.
3- Evaluate the seismic performance of the masonry compound to a given scenario,
by developing the capacity curves and performance points of each façade, following
the procedure in Figure 3. Consequently, fragility curves are obtained, for each
damage state.
Figure 3: Flow-chart of FaMIVE procedure
4- Multivariate regression analysis is pursued in order to obtain a mathematical
correlation between the independent variables (listed below) and collapse load
factor (the dependent variable):
• Connection at the edge of the facade (1 side, or 2 sides)
• Anchorages (ties, wall plates, ring beams, one sided or both sided)
• Quoins (one side or both sides)
• Number of free corner of the structural unit (zero, one, two)
• Quality of masonry condition (good, medium, bad)
Failure mechanisms identified for
each facade are shown in Figure 4 in a
plan view. The mechanism found for
each facade is validated using the
actual damage collected from an in-
situ damage survey. An example of
validation is shown in Figure 5 for the
most severely damaged facade.
The building cluster is also analysed for various chronological phases,
presented in Figure 6. The vulnerability of all phases is further investigated
for the condition in which no restraining elements, e.g. ties, are in place. The
average capacity curve of each phase (obtained by calculating the average of
all facades) is presented in Figure 7, with and without restraints. Resultant
fragility curves for phase 6, for both restrain conditions, are shown and
compared in Figure 7.
Figure 4: Failure mechanisms of each facade
Figure 5: Validation of FaMIVE result with the observed damage in facade US4#South
Motivation Masonry Buildings are highly vulnerable in earthquakes.
Assessing the seismic vulnerability is essential!
Research Objectives
Methodology
What analytical method is the best for this aim?
Results & Discussions
Figure 2: Possible modes of damage of a facade
Conclusions References
• The failure mechanisms are found and shown to be in a good agreement with the
on site damage survey.
• Capacity and fragility curves for with and without restraints cases are derived,
showing that the global vulnerability is sensitive to the level of restraints applied.
• Parameters that mostly affect the extent of seismic vulnerability are: i) the level of
anchorage, and ii) the number of free corners present in the building cluster.
Figure 6: Chronological phases of the analysed building cluster
Figure 7: Capacity curves (left) and fragility curves (right) for with and without restraints cases
The importance rate of each
independent variable is presented in
Table 1. The number of free corners is
the most influential factor affecting the
value of the collapse load factor.
A mathematical formulation with a
specific value corresponding to each one
of the parameters involved is also found
as a result of this regression analysis.
Parameter Importance
Connection one edge -
Connection both edges -
Anchorage one side *
Anchorage both side **
Anchorage both side + central **
One lateral quoin -
Two lateral quoins **
Quality of masonry condition **
Number of free corner ***
[1] D. F. D'Ayala. Force and displacement based vulnerability assessment for traditional buildings.
Bulletin of Earthquake Engineering, 3(3):235-265, 2005.
[2] C. F. Carocci. Small centres damaged by 2009 L’Aquila earthquake: on site analyses of historical
masonry aggregates. Bulletin of Earthquake Engineering, 10(1):45-71, 2012.
Table 1: Independent variables