We present a multidisciplinary research aimed at quantifying the conditional probabilities for hazards associated with pyroclastic avalanches at Etna, which combines physical and numerical modeling of granular avalanches and probabilistic analysis. Pyroclastic avalanches are modeled using the depth-averaged model IMEX-SfloW2D, which is able to simulate the transient propagation and emplacement of granular flows generated by the collapse of a prescribed volume of granular material. Preliminary sensitivity analysis allowed us to identify the main controlling parameters of the dynamics, i.e. the total avalanche mass, the initial position of the collapsing granular mass (and the associated terrain morphology), the initial avalanche velocity, and the two rheological parameters which determine the mechanical properties of the flow. While the first two parameters can be considered as scenario parameters in the definition of the hazards, the initial velocity and the rheological parameters need to be calibrated. We therefore adopted a methodology for the statistical calibration of the physical model parameters based on field observations. We used data from the pyroclastic avalanche that occurred on February 10, 2022 at Etna, for which we had an accurate mapping of the deposit and some estimates of the total mass and the initial volume. We then run a preliminary ensemble of numerical simulations, with fixed initial volume and position, to calibrate the other input parameters. Based on the accuracy of the matching of the simulated and observed deposits (measured by the Jaccard Index), we extracted from the simulation ensemble a subsample of equally probable combinations of initial velocities and rheological parameters. We then built an ensemble of model input parameters, with varying (i) avalanche volumes, (ii) initial positions, (iii) velocity, and (iv) rheological coefficients. The initial volume range was chosen within the range of observed pyroclastic avalanches at Etna (i.e., between 0.1 and 3 x 106 m3), using a prescribed probability distribution extracted from the literature data. The initial positions have been chosen on the flanks of the South East Crater of Etna, with homogeneous spatial distribution. The initial velocity and the rheological coefficients were chosen from the subsample created with the calibration. Finally, a semi-automatic procedure (digital workflow) running the Monte Carlo simulation allowed us to produce the first probabilistic map of pyroclastic avalanche invasion at Etna. Such a map, conditional to the occurrence of a pyroclastic avalanche event, can be used to identify the hazardous areas of the volcano and to plan mitigation measures.

Cement-soil mortar is a composite material that provides an efficient and cost-effective solution for a wide range of construction applications. This study analyzes the mechanical properties of cement-soil mortar through experimental investigation and explores the application and parameter calibration of the Concrete Damage Plasticity (CDP) model in the finite element simulation of cement-soil mortar. Additionally, an innovative Initial Defect Generation (IDG) method is proposed to enhance the accuracy in simulation of failure mode. The research findings provide a simulation framework that balances simplicity and accuracy for cement-soil mortar. Uniaxial compressive tests are first conducted on cement-soil mortar specimens with water contents ranging from 40 % to 70 %, and cement-to-soil proportions from 30 % to 300 %. Based on the experimental results, the regression relationships correlating unconfined compressive strength (UCS) with elastic modulus, peak strain and stress-strain curves are established. Then, the simplified equations for calculating CDP model parameters from the UCS of cement-soil mortar are further proposed following damage mechanics. A parameter table summarizing the calculation methods for all relevant CDP parameters is provided to streamline the model calibration process. Simulations incorporating the simplified calibration method and IDG method successfully replicated the stress-strain responses and failure modes observed in uniaxial compressive strength tests of cement-soil specimens with varied strength. The results demonstrate the reliability and broad applicability of this simulation framework in predicting the mechanical performance of cement-soil mortar.