Understanding and properly simulating discontinuity mechanical behaviour is crucial in all rock engineering projects. Several constitutive relationships have been proposed and implemented in numerical codes. This paper discusses the results of a numerical study that exam-ines the influence of adopting different rock discontinuity constitutive models for simulating the behavior of a fractured rock mass. Two constitutive approaches are employed: an enhanced Cou-lomb-based criterion with strain softening and a modified version of the Barton-Bandis model to overcome potential implementation issues. These models have been implemented in PLAXIS and their performance is inspected through numerical analyses of an underground cavity for a specific discontinuity network geometry. The results provide insights into the implications and suitability of adopting different discontinuity constitutive models for assessing the stability of engineering works in fractured rock masses.@en

Thermal and Thermo-Hydro-Mechanical (THM) analysis is at the core of a broad range of geotechnical engineering applications. In this context, an implicit fully coupled formulation has been implemented in the Finite Element software PLAXIS to perform robustly THM analyses. Advanced constitutive models can be easily defined and implemented with the well-known User-Defined Soil Model (UDSM) module. Recently, another module of User-Defined Flow Model (UDFM) has been developed so that users can implement user-defined fluid and heat transfer models (permeability, thermal conductivity functions etc). These improvements allow to perform advanced research analyses in a practical and user-friendly way. In this paper, the aforementioned formulation and functionalities are briefly summarised. Different examples of benchmark numerical analyses of Engineered Barrier Systems (EBS) in radioactive waste disposals as well as geothermal foundation systems are then presented. The obtained numerical results are verified by comparisons with other simulators and/or experimental data.@en