Following up on previous research on Automated Parameter Determination (APD), in which the soil stratification and numerical model parameters are automatically derived from individual CPTs, this article describes ongoing research in which the geotechnical modelling workflow is further automated in a BIM / Digital Twin environment. Especially in a preliminary project phase, when limited soil data are available, a workflow in which CPT data are used to automatically create a 3D geological model from which 2D or 3D numerical models can be extracted, may be very helpful in exploring different design alternatives. For existing (infrastructural) projects, such an automated system in a Digital Twin environment could also help responsible authorities to check the infrastructure’s safety under changing conditions. In addition to the description of technical solutions used for automatic layer detection and clustering (based on Machine Learning) across different CPTs, the article touches upon the discussion on transparency and accessibility of the automated system in view of the expertise and responsibilities of the operating geotechnical engineer.@en

Rock bolting plays an important role in different geo-engineering applications and its numerical modelling is crucial for the analysis and design of rock structures. Continuum modelling simulation of bolt-reinforced rock masses requires specific techniques to properly model the reinforcement system and its interaction with the rock mass, which often exhibits a nonlinear softening/brittle response. In this context, strain localization might occur, which, in turn, may affect numerical convergence and the quality of results. This paper presents some advanced numerical techniques implemented in PLAXIS to overcome the abovementioned challenges. Firstly, a regularization technique is implemented for an extended version of the Hoek-Brown failure criterion with strain softening. Secondly, the formulation of the structural bolt element interacting with the rock mass is developed. Finally, the robustness and accuracy of these techniques are discussed via a numerical example of a typical underground mining excavation problem.@en

Many constitutive models are nowadays available to simulate the mechanical behaviour of clays under different loading conditions. For geotechnical engineering applications in a soil dynamics context, the PM4Silt model, as proposed by Boulanger & Ziotopoulou (2018), can simulate the cyclic behaviour of low-plasticity silts and clays. Formulated in a bounding surface plasticity framework, this model adapts the capabilities of a previous model suited for sands and non-plastic silts, i.c. PM4Sand, and enables to simulate more clay-like soil behaviour. In this paper, published calibrations for silts with different plasticity properties are employed to simulate the experimental results of monotonic and cyclic undrained DSS test with the purpose to comment on the effect of some key parameters, including the initial stress ratio 𝐾 and the bounding surface parameter . Numerical simulations are performed with the finite element implementation of PM4Silt in PLAXIS. Besides the two original methods to define undrained shear strength (based on 𝑆􀯨 and 𝑆), a third method is proposed here based on the SHANSEP approach. The application of the model in view of the key parameters is demonstrated by means of a practical example. @en

This article describes how efficiency in geotechnical engineering involving finite element (FE) modelling can be improved by automation. An important part of geotechnical FE modelling involves the creation of an underground model and the determination of soil and model parameters. It is explained how Automated Parameter Determination (APD) based on CPT data can be used in conjunction with geological modelling to create the necessary input for a FE model. An example demonstrates the entire workflow. The system is transparent and extendable. It supports the geotechnical engineer in the complex task of parameter determination, while retaining the responsibility at the user. Automation can help reducing the spread in results when different geotechnical engineers analyze the same problem, and hence, it can contribute to the confidence in the use of advanced numerical methods for geotechnical design. @en