Uncertainty Quantification for Multiscale Model of Tritium Breeding Materials

In this talk, we present an approach to modelling materials to support the development of a fusion-relevant tritium breeder module, with a primary focus on lithium-based ceramics.

The model approaches the problem via a multiscale method, sequentially coupling scales until the global macroscopic quantities of interest are computed.
Here, two atomistic levels are considered to resolve the small-scale processes, employing Density Functional Theory (DFT) and classical Molecular Dynamics (MD) for high-fidelity modelling.
The larger scales, which include single-crystal, crystal-amorphous multi-grain and porous systems, are solved via Finite Element Modelling (FEM).
Finally, a global model capable of producing quantities of interest is assembled.

The work describes the application of the model to support an experiment jointly undertaken by Bangor University and the University of Birmingham.
The experiment comprises the preparation of lithium metatitanate samples, the manufacturing of a tritium-breeding module, and the irradiation of Lithium-containing materials under neutron flux at the High Flux Accelerator-Driven Neutron Facility (HF-ADNeF).
The goal of the experiment is to demonstrate a proof of concept for tritium breeding capabilities with this approach, as well as to demonstrate the model-based predictability of such tritium breeding devices, with further goals of material and device testing and optimisation involving simulation-experiment interaction.

The specific focus of the work is on Uncertainty Quantification (UQ) and Sensitivity Analysis (SA) of the material model.
The UQ methods support various sources of uncertainty, aiming for rigorous validation and realistic prediction capabilities of the code.
SA supported both the model and the experimental design, identifying the most important physical factor to be studied via simulation and at the experimental facility.

The UQ approach comprises two main methodological thrusts.
The first is the application of the EasyVVUQ library capabilities to a model based on the FESTIM code.
The other approach is to develop a UQ workflow fully implemented within the MOOSE framework, applying the Stochastic Tools (STM) Module to the TMAP8 code, both of which are implemented within the same simulation framework.