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This paper presents an assessment of the fragility of a reinforced concrete (RC) element subjected to avalanche loads, and more generally to dynamic pressure fields applied orthogonally to a wall, within a reliability framework. In order to obtain accurate numerical results with supportable computation times, a light and efficient Single-Degree-of-Freedom (SDOF) model describing the mechanical response of the RC element is proposed. The model represents its dynamic mechanical response up to failure. Material non-linearity is taken into account by a moment–curvature approach, which describes the overall bending response. The SDOF model is validated under quasi-static and dynamic loading conditions by comparing its results to alternative approaches based on finite element analysis and the yield line theory. Following this, the deterministic SDOF model is embedded within a reliability framework to evaluate the failure probability as a function of the maximal avalanche pressure reached during the loading. Several reliability methods are implemented and compared, suggesting that non-parametric methods provide significant results at a moderate level of computational burden. The sensitivity to material properties, such as tensile and compressive strengths, steel reinforcement ratio, and wall geometry is investigated. The effect of the avalanche loading rate is also underlined and discussed. Finally, the obtained fragility curves are compared with respect to the few proposals available in the snow avalanche engineering field. This approach is systematic and will prove useful in refining formal and practical risk assessments. It could be applied to other similar natural hazards, which induce dynamic pressure fields onto the element at risk (e.g., mudflows, floods) and where potential inertial effects are expected and for which fragility curves are also lacking.

In snow avalanche long-term forecasting, existing risk-based methods remain difficult to use in a real engineering context. In this work, we expand a quasi analytical decisional model to obtain simple formulae to quantify risk and to perform the optimal design of an avalanche dam in a quick and efficient way. Specifically, the exponential runout model is replaced by the Generalized Pareto distribution (GPD), which has theoretical justifications that promote its use for modelling the different possible runout tail behaviours. Regarding the defence structure/flow interaction, a simple law based on kinetic energy dissipation is compared with a law based on the volume stored upstream of the dam, whose flexibility allows us to cope with various types of snow. We show how a detailed sensitivity study can be conducted, leading to intervals and bounds for risk estimates and optimal design values. Application to a typical case study from the French Alps, highlights potential operational difficulties and how they can be tackled. For instance, the highest sensitivity to the runout tail type and interaction law is found at abscissas of legal importance for hazard zoning (return periods of 10–1000 a), a crucial result for practical purposes.

Snow avalanches are a threat to many kinds of elements (human beings, communication axes, structures, etc.) in mountain regions. For risk evaluation, the vulnerability assessment of civil engineering structures such as buildings and dwellings exposed to avalanches still needs to be improved. This paper presents an approach to determine the fragility curves associated with reinforced concrete (RC) structures loaded by typical avalanche pressures and provides quantitative results for different geometrical configurations. First, several mechanical limit states of the RC wall are defined using classical engineering approaches (Eurocode 2), and the pressure of structure collapse is calculated from the usual yield line theory. Next, the fragility curve is evaluated as a function of avalanche loading using a Monte Carlo approach, and sensitivity studies (Sobol indices) are conducted to estimate the respective weight of the RC wall model inputs. Finally, fragility curves and relevant indicators such a their mean and fragility range are proposed for the different structure boundary conditions analyzed. The influence of the input distributions on the fragility curves is investigated. This shows the wider fragility range and/or the slight shift in the median that has to be considered when a possible slight change in mean/standard deviation/inter-variable correlation and/or the non-Gaussian nature of the input distributions is accounted for.