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Three oxynitride glasses from the Y-Si-AI-O-N system and differing in their N/O ratio were studied in the 800-1000 ~ temperature range. Their viscosities were measured using a threepoint bending test through the glass transition domain. For a given temperature, 4.8 wt% N 2 enhances the viscosity by three orders of magnitude in comparison with the corresponding oxide glass. Nitrogen also improves creep resistance. The activation enthalpy for creep, above Tg, is of the same order as those measured for silicon nitride ceramic (--~900 kJ mol -~). The elastic moduli were determined by ultrasonic techniques, from room temperature up to 1200 ~ which allowed calculation of the free activation enthalpy for viscous flow. Owing to the sharp decrease of shear modulus in the glass transition domain, the free activation enthalpy (~500 kJ mo1-1 ) greatly differs from the activation enthalpy usually measured in creep studies.

In this study, a new methodology for the calibration of microscopic parameters for the Cohesive Beam Model (CBM) of discrete element method (DEM) applied to elastic brittle material is presented. This method enables the entry of material mechanical values directly into DEM simulations without any calibration steps. Several DEM simulations of tensile tests with different microscopic parameter values were carried out to generate a database of macroscopic parameter responses. This database was analyzed in order to deduce analytic laws by using non linear least square method. To validate the proposed calibration method, DEM simulations, that use the results of the calibrated microscopic parameters, were carried out. The macroscopic responses were compared to theoretical or experimental values. These validation tests were performed separately for two typical brittle elastic materials, i.e., soda-lime glass and alumina, with different shapes/sizes of discrete domain and various boundary conditions. Results between numerical and experimental values are in good accordance regarding the variability induced by this stochastic approach.