Abstract

The use of soil data is essential in geotechnical design, but in a preliminary project phase such data are usually limited to that inferred from field tests, like CPT, SPT or DMT. In previous publications by the authors and co-workers, it was shown how such data can be automatically processed into soil profiles and parameter sets for geotechnical finite element analysis. Another publication demonstrated the automated processing and creation of geological models as an intermediate step to more advanced 3D geotechnical modelling in a BIM / Digital Twin environment, which facilitates the link with other disciplines and stakeholders in a project. The major challenge of connecting layers across multiple 1D boreholes to form 3D soil layers is overcome by using a Machine Learning clustering algorithm. As a next step, the previously introduced Automated Parameter Determination (APD) method (connecting correlations using Graph theory) is applied based on averaged CPT parameters from all contributing layer sections. The result is an automated system that creates a complete 2D or 3D finite element model, including constitutive model parameters, for geotechnical analysis purposes. An automated system may be very efficient when exploring different design alternatives in an early stage of a project. However, it is important to emphasize the role and responsibilities of the geotechnical engineer in the design process, which requires the system to be transparent, verifiable, and adaptable. This paper describes the state-of-the-art of this ongoing research project.

Abstract

The success of numerical analysis relies on several factors, with one crucial aspect being the accurate determination of constitutive model parameters. Extracting these parameters directly from in-situ tests has several advantages, such as costeffectiveness and minimal soil disturbance. However, obtaining soil parameters directly from in-situ tests is not feasible, as empirical correlations are used to interpret them. An ongoing research project aims to create an automated parameter determination (APD) framework using a graph-based approach to determine constitutive model parameters from in-situ tests. The process involves using two spreadsheets as input: the first defines the parameters, while the second specifies the correlations used to compute them. The system then generates connections between the parameters and computes values for each one. The paper discusses the validation of the correlations database used by the system, which includes over 100 correlations for deriving parameters for various soil types. The framework determines parameters based on cone penetration tests (CPT), dilatometer tests (DMT), and in-situ shear wave velocity measurements. The system's output is compared to values interpreted from laboratory tests. To collect data for this validation, a web-based application "Datamap" was employed, which stores and categorizes geotechnical data. The validation process utilized data from the Norwegian GeoTest Sites (NGTS), specifically the NGTS-silt project. The parameters were calculated based on CPT, DMT, and in-situ shear wave velocity measurements. Ongoing research aims to evaluate the accuracy of the derived parameters and expand the system's capabilities to include additional in-situ tests

Abstract

The success of numerical analysis relies on several factors, with one crucial aspect being the accurate determination of constitutive model parameters. Extracting these parameters directly from in-situ tests has several advantages, such as costeffectiveness and minimal soil disturbance. However, obtaining soil parameters directly from in-situ tests is not feasible, as empirical correlations are used to interpret them. An ongoing research project aims to create an automated parameter determination (APD) framework using a graph-based approach to determine constitutive model parameters from in-situ tests. The process involves using two spreadsheets as input: the first defines the parameters, while the second specifies the correlations used to compute them. The system then generates connections between the parameters and computes values for each one. The paper discusses the validation of the correlations database used by the system, which includes over 100 correlations for deriving parameters for various soil types. The framework determines parameters based on cone penetration tests (CPT), dilatometer tests (DMT), and in-situ shear wave velocity measurements. The system's output is compared to values interpreted from laboratory tests. To collect data for this validation, a web-based application "Datamap" was employed, which stores and categorizes geotechnical data. The validation process utilized data from the Norwegian GeoTest Sites (NGTS), specifically the NGTS-silt project. The parameters were calculated based on CPT, DMT, and in-situ shear wave velocity measurements. Ongoing research aims to evaluate the accuracy of the derived parameters and expand the system's capabilities to include additional in-situ tests