The two main research outputs of the ISLINGTON project are:
1. Development of an Application Programming Interface (API) using a Finite Element Method (FEM) solver for waves-current-soil-object interaction.
2. Generating an experimental dataset for benchmarking of mooring line solvers.
The API developed consists of a coupling between the mooring line solver Moody and the FEM granular soil solver DEM-Engine. Firstly, a study of the numerical implementations of the two models was performed in order to identify the best approach to couple them. Secondly, a first secondment was held at Vigo University to complement the initial literature review with specific training on coupling multi-physics engines. After that, the core API was developed taking into account the following steps:
1. Identifying the mooring system parameters that need to be transferred between the two models: anchor position, cable position, cable internal forces, ground reaction forces and cable properties.
2. Identifying how to represent the mooring system in DEM-Engine: use of existing mesh elements to obtain the contact forces between the mooring system and the granular soil.
3. Building the wrapper to connect Moody and DEM-Engine.
4. Generating sample test cases for verifying compilation errors of the API, code verification and numerical validation.
Once the API development was completed, an experimental campaign was designed in collaboration between the Ocean and Coastal Engineering Research Group of Aalborg University and the Geotechnical Engineering and Offshore Foundations Research Group of Aalborg University. During the experimental campaign, different mooring line configurations over a granular soil bed were tested at the wave flume of the Ocean and Coastal Engineering Laboratory, Aalborg University, Denmark. The experimental campaign resulted on an experimental dataset for benchmarking of mooring line solvers. These data were later used for the experimental validation of the Moody-DEM-Engine API showing good agreement between the experimental data and the numerical simulations. Finally, a second secondment was held at Sigma AB with the objective of improving the API functionalities and sketch the numerical benchmarking of the model. Two publications regarding the API and the experimental dataset are scheduled to be submitted before the end of 2024, while the preliminary results of the API implementation and the experimental dataset have been presented at the RENEW 2024 conference.
