InterTwin is an EU-funded project that started on the 1st of September 2022. The project will work with domain experts from different scientific domains in building a technology to support digital twins within scientific research. Digital twins are models for predicting the behaviour and evolution of real-world systems and applications.
InterTwin will focus on employing machine-learning techniques to create and train models that are able to quickly and accurately reflect their physical counterparts in a broad range of scientific domains. The project will develop, deploy and “road harden” a blueprint for supporting digital twins on federated resources. For that purpose, it will support a diverse set of science use-cases, in the domains of radio telescopes (Meerkat), particle physics (CERN/LHC and Lattice-QCD), gravitational waves (Virgo), as well as climate research and environment monitoring (e.g. prediction of flooding and other extreme weather due to climate change). The ultimate goal is to provide a flexible infrastructure that can accommodate the needs of many additional scientific fields.
In the talk, we will present an overview of the interTwin project along with the corresponding Digital Twin Engine (DTE) architecture for federating the different, heterogeneous resources available to the scientific use-cases (storage, HPC, HTC, quantum) when training and exploitation of digital twins within the different scientific domains. The challenges faced when designing the architecture will be described, along with the solutions being developed to address them. interTwin is required to be interoperable with other infrastructures, including EuroHPC-based Destination Earth Initiative (DestinE) and an infrastructure for accessing Copernicus satellite data, C-SCALE. We will also present our strategy for making DTE available within the European Open Science Cloud (EOSC). The details of all such interoperability will also be presented.
|Consider for long presentation||Yes|