PSI - Issue 84

Lorenzo Brezzi et al. / Procedia Structural Integrity 84 (2026) 1159–1166

1166

A key outcome of the study is that the most relevant effect of multiple-source debris-flow scenarios is not a substantial amplification of local peak velocities or impact forces, but rather a marked increase in the spatial extent of the interaction zone along the infrastructure. While peak values of velocity, flow thickness and impact force remain of comparable magnitude in the single- and double-landslide scenarios, the latter produces a significantly wider zone of contact, distributing dynamic actions over a larger portion of the viaduct. From an infrastructure perspective, this result highlights the importance of considering not only maximum local actions, but also their spatial distribution when assessing landslide– viaduct interaction. The adoption of a probabilistic framework based on Monte Carlo simulations proved essential to capture the variability associated with rheological uncertainty and to avoid over-reliance on single deterministic scenarios. In the absence of site-specific calibration data, this approach allows the identification of critical sectors and the estimation of plausible ranges of interaction parameters, providing physically based information to support susceptibility-oriented assessments of existing infrastructure. The proposed framework is not intended to replace detailed structural analyses or design-level verifications. Instead, it offers a conservative and transferable tool to support the preliminary assessment and management of landslide-related hazards for bridges and viaducts exposed to rapid mass movements, particularly in data-scarce mountainous contexts. Future developments may include the explicit modelling of mitigation measures, the coupling with structural response models and the extension to other types of rapid instability phenomena. References Brezzi, L., Bossi, G., Gabrieli, F., Marcato, G., Pastor, M., Cola, S., 2016. A new data assimilation procedure to develop a debris flow run-out model. Landslides 13(5), 1083-1096. https://doi.org/10.1007/s10346-015-0625-y Brezzi, L., Carraro, E., Pasa, D., Teza, G., Cola, S., Galgaro, A., 2021. Post-collapse evolution of a rapid landslide from sequential analysis with FE and SPH-based models. Geosciences 11(9), 364. https://doi.org/10.3390/geosciences11090364 Brezzi, L., …, Galgaro, A., 2021. Propagation analysis and risk assessment of an active complex landslide using a Monte Carlo statistical approach. In: IOP Conference Series: Earth and Environmental Science, 833, 012130. https://doi.org/10.1088/1755-1315/833/1/012130 Cola, S., Brezzi, L., Gabrieli, F., 2019. Calibration of rheological properties of materials involved in flow-like landslides. Rivista Italiana di Geotecnica 1(1/2019), 5-43. Gabrieli, F., …, Simonini, P., 2025. Understanding Landslide-Bridge Interactions through a Comprehensive Analysis of a Global Case Study Database. International Journal of Bridge Engineering, Management and Research 2(2), 214250012-1. https://doi.org/10.70465/ber.v2i2.20 Han, Z., …, Chen, G., 2019. Numerical simulation of debris-flow behavior based on the SPH method incorporating the Herschel-Bulkley Papanastasiou rheology model. Engineering Geology 255, 26-36. https://doi.org/10.1016/j.enggeo.2019.04.013 Kumar, S., Sharma, A., Singh, K., 2024. A Comprehensive Review on Debris Flow Landslide Assessment Using Rapid Mass Movement Simulation (RAMMS). Geotechnical and Geological Engineering 42, 5447–5475. https://doi.org/10.1007/s10706-024-02887-1. Negi, H.S., Kumar, A., Rao, N.N., Thakur, N. K., Shekhar, M. S., Snehmani, 2020. Susceptibility assessment of rainfall induced debris flow zones in Ladakh–Nubra region, Indian Himalaya. Journal of Earth System Science 129, 30. https://doi.org/10.1007/s12040-019-1277-4 Pastor, M., …, Cuomo, S., 2014. Application of a SPH depth-integrated model to landslide run-out analysis. Landslide 11, 793-812. https://doi.org/10.1007/s10346-014-0484-y Scala, A., …, Zampieri, P., 2025. Extreme natural events and bridge collapses: statistical insights in Italy. International Journal of Disaster Risk Reduction, 105880. https://doi.org/10.1016/j.ijdrr.2025.105880 Sosio, R., Crosta, G., B., Hungr, O., 2008. Complete dynamic modeling calibration for the Thurwieser rock avalanche (Italian Central Alps). Engineering Geology 100, 11-26. https://doi.org/10.1016/j.enggeo.2008.02.012 Vagnon, F., Segalini, A., 2016. Debris flow impact estimation on a rigid barrier. Natural Hazards and Earth System Sciences 16, 1691–1697. https://doi.org/10.5194/nhess-16-1691-2016 Van Westen, C., J., Castellanos, E., Kuriakose, S., S., 2008. Spatial data for landslide susceptibility, hazard, and vulnerability assessment: An overview. Engineering Geology 102, 112-131. https://doi.org/10.1016/j.enggeo.2008.03.010 Voellmy, A., 1955. Über die Zerstörungskraft von Lawinen. Bauzeitung 73, 159–165.