Progress in FREDA: A Multi-Fidelity Plasma-Engineering Integrated Modeling Platform for Fusion Reactor Design and Assessment

Integrated modeling of fusion reactor design is essential for predicting self-consistent multi-physics loads (thermal, electromagnetic, plasma, neutron, etc.), assessing technical feasibility, quantifying uncertainties, and optimizing design; ultimately it can reduce cost and time to put fusion energy on the grid. The FREDA SciDAC team is building a flexible, component‑based workflow (IPS‑FASTRAN + FERMI) that couples theory‑based plasma transport, boundary physics, and multiphysics engineering to enable iterative, multi‑fidelity design and optimization. A major plasma-engineering gap is predicting heat and particle flux at the wall. FREDA can now map plasma loads to the first wall and divertor using multiple methods. The low fidelity option (similar to HEAT) assumes Eich scaling and maps midplane heat flux from the SOLPS-ITER domain to PFCs. The higher fidelity option uses BOUT++/Hermes-3/Cherab and a newly developed grid mask method to calculate plasma and photon heat flux all the way to wall. A new mesh generation method for SOLPS using AI/ML enables scans in geometry and physical constraints. Parametric CAD representation is generated with a newly developed TRACER tool, and the compact advanced tokamak with a DCLL blanket concept serves as the starting example for FREDA. A subset of engineering analysis workflows was applied, including end‑to‑end coupling of plasma and neutron loads (OpenMC) into thermal analysis (OpenFOAM) to identifying helium flow rates needed to keep temperatures within material limits. Analysis also includes tritium transport in the fluid and solid, and magnet stress (Elmer, Diablo, MFEM) and cooling analysis. This work advances FREDA's goal to provide rapidly iterable, provenance‑tracked pathways from plasma targets to engineering constraints, enabling uncertainty quantification and design trade-off studies that de‑risk FPP concepts and guide meaningful validation experiments.