An ongoing research project aims to create an automated parameter determination (APD) framework relying on a graph-based approach for determining constitutive model parameters from in-situ tests. The system requires two spreadsheets as inputs. One spreadsheet defines the parameters, while the other spreadsheet specifies the correlations. The system connects parameters and methods by generating paths between them and calculates the value(s) for different parameters. So far, the frame-work focused on determining soil parameters based on the cone penetration test (CPT). This paper focuses on expanding the framework by adding the dilatometer test (DMT). A new database of correlations for the DMT is compiled. The expanded APD framework successfully calculates soil parameters for coarse and fine-grained soils based on CPT as well as DMT data. Validat-ing the output of the system, assessing the accuracy of the derived parameters, and connecting soil parameters to constitutive model parameters are part of ongoing research.@en

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

Performing numerical analysis successfully depends on several factors. One of the most important factors is determining the constitutive model parameters correctly. It is often the case that these parameters are determined based on limited soil data. Using in-situ tests for determining these parameters has several advantages such as minimal disturbance of the soil and lower cost compared to laboratory tests. However, it is not possible to determine soil parameters directly from in-situ tests results. Thus, empirical correlations are required for interpreting soil parameters. Generally, several correlations exist for the same parameter, which will lead to calculating several values for the same parameter. An ongoing research project focuses on formulating an automated parameter determination (APD) framework that uses a graph-based approach to identify constitutive model parameters based on in-situ tests. This is achieved by using two spreadsheets as an input, one for parameters and the other for equations (correlations used to calculate parameters). Based on these two spreadsheets, the system generates paths between the parameters and calculates the value(s) for each individual parameter. So far, the research project focused on determining the parameters for coarse-grained soil based on cone penetration test (CPT) results. Due to the fact that the system was set up in a modular and adaptable way, it is possible to expand the system to accommodate more soil types and in-situ tests. It is the aim of the research project to increase the reliability of the parameters values (required to perform numerical analysis) determined from in-situ tests. This paper focuses on expanding the current framework to determine parameters for fine-grained soil. By using the two spreadsheets as an input, the system successfully calculates the value(s) for fine-grained parameters. Further validation, dealing with several values for each parameter, determining the accuracy of derived parameters and expanding the system to accommodate other in-situ tests and types of soils are part of ongoing research.@en