PSI - Issue 78

Sara Mozzon et al. / Procedia Structural Integrity 78 (2026) 646–653

652

0.7 0.8 0.9 1.0

0.7 0.8 0.9 1.0

h hp 1 h hp 2 h hp h hp h hp 1

h hp 1 h hp 2 h hp h hp h hp 1

0. 0. 0. 0.

0. 0. 0. 0.

0.0 0.1 0.2

0.0 0.1 0.2

0.001.002.00 .00 .00 .00 .00

0.001.002.00 .00 .00 .00 .00

0.7 0.8 0.9 1.0

h hp 1 h hp 2 h hp h hp h hp 1

0. 0. 0. 0.

0.0 0.1 0.2

0.001.002.00 .00 .00 .00 .00

Fig. 4: Fragility curves grouped by damage state and obtained for a water flow ( ρ f =1000 kg/m

3 ) and a rectangular-shaped load profile.

Table 3: Logarithmic mean and standard deviation values of the velocities. DS1 [m/s] β [m/s] β [m/s] β 1/5 5.375 0.148 6.620 0.159 7.788 0.212 2/5 2.581 0.218 3.734 0.252 4.565 0.280 3/5 1.611 0.224 2.557 0.242 3.221 0.261 4/5 1.244 0.223 2.039 0.223 2.590 0.232 1 1.138 0.226 1.856 0.204 2.358 0.208 DS2 DS3 h w /h p

5. Conclusions Building on the previously defined taxonomy of structural and non-structural masonry elements, a Monte Carlo simulation was carried out using the analytical model introduced in this study. This approach enabled the evaluation of the OOP capacity of masonry infills and walls while capturing variability in key geometric and mechanical properties. Both epistemic and aleatory uncertainties were incorporated, making the results suitable for territorial scale vulnerability assessments, particularly in contexts where detailed exposure data are lacking. The simulation produced capacity point clouds at selected performance levels − first cracking, moderate damage, and maximum capacity − for each infill class and load profile (rectangular and triangular). Based on these data, surrogate vulnerability models were calibrated to provide direct estimates of panel capacity at each performance level. For each infill type and load configuration, three second-order polynomial equations were developed as functions of five governing parameters: panel height, inverse slenderness, aspect ratio, impacted height ratio, and mean compressive strength. Using these capacity models, incremental demand curves were applied − derived from simplified literature-based hydrostatic and hydrodynamic models. Adopting a methodology analogous to Incremental Dynamic Analysis (IDA),