Use Case 1 | Foundation models for particle physics detector simulation (CERN)

The use case targets experimental particle physics, specifically focused on particle detection and simulation, emphasizing the intersection of high-performance computing, deep learning, and particle physics research.

Use Case 2 | Nuclear reactor operational safety and efficiency using generative AI (NRG)

The use case focuses on the design, operation, and safety of nuclear reactors. This involves optimizing reactor core configurations and ensuring operational safety through advanced modeling, simulation, and AI-driven automation.

Use Case 3 | AI-Enhanced Criticality Safety Analysis for Nuclear Systems (STUBA)

The use case focuses on enhancing criticality safety analysis in nuclear systems through the application of AI techniques, namely methods for improving the estimation of the Upper Subcritical Limit (USL), as well as predicting and reducing the computational bias in criticality calculations.

Use Case 4 | Debris Bed Formation during Severe Accidents (USTUTT)

The use case aims at accelerating debris bed cooling simulations during severe nuclear accidents while maintaining high accuracy, enabling faster uncertainty and sensitivity analyses.

Use Case 5 | Robust data-driven Models for Weather Forecasting (MF)

The use case targets developing robust and explainable data-driven weather forecasting models that can match physics-based model performance while requiring fewer computing resources and providing transparency in predictions.