Accelerating integrated modeling with surrogate-based optimization: the MAESTRO workflow

TL;DR

The paper presents the MAESTRO workflow, integrating PORTALS with external solvers and surrogate models to efficiently predict plasma profiles for fusion reactor design.

Contribution

It introduces a surrogate-based optimization approach that couples PORTALS with external physics solvers, improving steady-state plasma profile predictions.

Findings

Enhanced surrogate modeling handles discontinuities in transport fluxes.

MAESTRO enables efficient steady-state plasma predictions with full physics models.

Coupling with external solvers improves modeling flexibility and accuracy.

Abstract

This paper introduces the MAESTRO workflow, that enables the coupling of the PORTALS framework [P. Rodriguez-Fernandez et al, Nucl. Fusion 2024] with external solvers for the plasma equilibrium, pedestal physics, divertor constraints and heating. The surrogate-based optimization nature of the transport solver is ideally suited for external coupling, allowing efficient steady-state predictions of plasma profiles with full physics models. Improvements in the surrogate modeling of quasilinear transport models with PORTALS are presented, which enable the efficient handling of discontinuities in the transport fluxes that can arise from numerical issues or physical instabilities with extreme stiffness. The combination of physics-informed methods and advanced numerical techniques allows the MAESTRO workflow to provide accurate and efficient predictions of steady-state plasma profiles, which are critical for fusion reactor design and optimization.